Research ArticleA Rule Based Energy Management System ofExperimental BatterySupercapacitor Hybrid EnergyStorage System for Electric Vehicles

Qiao Zhang Weiwen Deng Sumin Zhang and Jian Wu

State Key Laboratory of Automotive Simulation and Control Jilin University Changchun 130022 China

Correspondence should be addressed to Sumin Zhang zhangsuminjlueducn

Received 21 January 2016 Revised 22 May 2016 Accepted 26 May 2016

Academic Editor Ahmed M Massoud

Copyright copy 2016 Qiao Zhang et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

In this paper a simple and efficient rule based energy management system for battery and supercapacitor hybrid energy storagesystem (HESS) used in electric vehicles is presented The objective of the proposed energy management system is to focus onexploiting the supercapacitor characteristics and on increasing the battery lifetime and system efficiency The role of the energymanagement system is to yield battery reference current which is subsequently used by the controller of the DCDC converterFirst a current controller is designed to realize load current distribution between battery and supercapacitor Then a voltagecontroller is designed to ensure the supercapacitor SOC to fluctuatewithin a preset reasonable variation range Finally a commercialexperimental platform is developed to verify the proposed control strategy In addition the energy efficiency and the cost analysisof the hybrid system are carried out based on the experimental results to explore the most cost-effective tradeoff

1 Introduction

Electric vehicles are considered as one of the most promisingtransportation tools for addressing issues faced by automo-tive industry worldwide on energy and environment [1ndash4]Technologies employed for all kinds of electric vehicles arevarious but their performances are largely dependent onthe characteristics of adopted energy storage system (ESS)[5 6] Of all the ESSs battery is one of the most widely usedin kinds of electric vehicles which has been an emergingarea for ensuring a successful application of electric vehiclesHowever battery alone as a power source has yet facedsome challenges for practical engineering application such ashigher energy efficiency smaller voltage drops larger vehicleacceleration or deceleration rates and better uphill climbingperformance Although high power battery can be madeavailable it is very bulky yet cost prohibitive [7 8]

A possible solution to the battery dilemma is to addonboard supercapacitor to form HESS with the purpose thatbattery and supercapacitor function as a complementary rolebased on their individual dynamic characteristics [9 10]

Battery has high energy density and relatively low cost perwatt-hour but low specific power and short lifetime whilesupercapacitor preserves high power density and long cyclelife but relatively low energy density and high cost per watt-hour [11ndash14] Consequently a combination of these two typesof ESSs will yield an equivalent ESS with both high energydensity and high power density where energy is stored in thebattery and power is supplied by the supercapacitor In thisway sudden peak current in battery which can be resulting ina large reduction in lifetime [15 16] can be avoided effectivelyBesides electric vehicle range can also be extended because ofthe high utilization of the regenerative breaking [17]

In order to encourage the development of battery andsupercapacitor HESS mounting research efforts have beendevoted to improving the HESS performance from both lowlevel topology structure [11 18ndash20] and high level energymanagement [21ndash28] In the literature there are a number ofhybridization topology structures where the supercapacitorhas been implemented in combination with battery systemsBased on these topology structures various energy man-agement control strategies for battery and supercapacitor

Hindawi Publishing CorporationJournal of Control Science and EngineeringVolume 2016 Article ID 6828269 17 pageshttpdxdoiorg10115520166828269

2 Journal of Control Science and Engineering

HESS are also developed in the literature These strategiescan be broadly classified into rule based and optimization-based distribution Rule based controllers are referred toas deterministic rule learning network and fuzzy logicalcontroller In [21] an ADVISOR-based battery and super-capacitor HESS was developed the power distribution rulebetween battery and supercapacitor was determined basedon an experiment approach In [22] an integrated rule basedmetaheuristic approachwas presented and simulation resultshave proved the effectiveness of this multilevel EMS fulfillingthe requested performance with better source usage andmuch lower installed capacities In [23] a fuzzy logical con-troller based on particle swarm optimization algorithm waspresented to achieve optimization power flow distributionbetween battery and supercapacitor Reference [24] adoptedthe idea of neural networks and developed an efficient energymanagement system for hybrid electric vehicles with closedform approaches

Optimization-based methods consider local and globaloptimization problems by using past driving cycle infor-mation to determine the power distribution mode amongpower sources Reference [25] formulated an optimizationproblem by concerning the minimization of the magni-tudefluctuation of the current flowing in and out of thebattery and the energy loss of the supercapacitor An MPC(model predictive control) controller for a hybrid battery-supercapacitor power source was proposed and experimen-tally verified in [26] The designed MPC controller enablesthe battery to share the low frequency power componentsand the high frequency power components are allocated tothe supercapacitor In [27] a wavelet transform-based powermanagement strategy was proposed in which load power isdecomposed into different frequency components to the FC(fuel cell) battery and supercapacitor compatible with theirrespective dynamic characteristics Reference [28] adopted afirst-order low-pass filter which was designed for frequencydecomposition along with analysis of components responsesunder real world driving cycles These strategies wouldincrease battery lifetime attributing to effective frequencyseparation consideration

In this paper a rule based energy management systemis developed for a semiactive hybrid system The objectiveof the proposed energy management system is to focus onexploiting the supercapacitor characteristics and increasingthe battery lifetime and system efficiency The main con-tributions of this paper are summarized as follows First asimple but effective rule based energy management system isdeveloped for a semiactive hybrid system The main role ofthe energy management system is to yield battery referencecurrent according to energy levels of the power sources andload demand level Then two classical PI control loops areproposed to adjust the load distribution between battery andsupercapacitor The described energy management systemenables the battery to share low frequency and smooth loadcurrent and the corresponding high frequency and peakcurrent are distributed to the supercapacitor This systemprevents an overstress on the battery while maintaininga good voltage balance of the supercapacitor This is animportant advantage to ensure the vehicle starts a new cycle

if high acceleration is required Second an experimentalplatform of the hybrid system is developed to verify thedescribed energy management system using two standarddrive cycles for an electric vehicle Finally preliminary butsignificant energy efficiency and the cost analysis of thehybrid system are carried out based on the experimentalresults to explore the most cost-effective tradeoff

The rest of this paper is organized as follows Section 2describes the dynamic characteristics of the battery andsupercapacitor Section 3 analyzes the hybrid topology struc-ture Section 4 describes the energy management controlstrategy Section 5 verifies the proposed control strategy basedon a commercial experimental platform Finally the paper isconcluded in Section 6

2 Characteristics of Battery andSupercapacitor as Power Sources

Batteries used in electric vehicle usually have the charac-teristics of high energy density and relatively low powerdensity The latter is a limitation to improve vehicle dynamicperformanceHigh power capability requires the resistance ofthe battery to be low Hence knowledge of the resistance of abattery is critical to the ability to assess its power capabilityIn addition the charging and discharge internal resistances ofbattery are usually different which is dependent on chargingand discharge operating conditions including amplitude andfrequency of charging and discharge of battery For lithium-ion battery the internal resistance could increase when highfrequency loads are exerted The ampere-hour capacity isaffected by the discharging current rate and is modeled by thePeukert equation [13] The charging and discharging internalresistances are nonlinear functions of current and state ofcharge (SOC)

Recently another energy storage device the supercapaci-tor has attractedmuch interest because of its high power den-sity (300Wkgndash5000Wkg) and relatively low energy densityThere are presently commercially available carboncarbonsupercapacitor devices (single cells and modules) from sev-eral companies such as Maxwell Ness EPCOS NipponChemi-Con and Power Systems All these companies marketlarge devices with capacitance of 1000ndash5000 F These devicesare suitable for high power vehicle applications [29]

As described above the difference between battery andsupercapacitor can provide the complementary advantage tomeet power and energy demand From the perspective ofpower characteristics the charging and discharging efficiencyof system is usually considered as the main factor Bycomparison only one-half of the energy at the peak powerfrom the battery is in the form of electrical energy to the loadand the other one-half is dissipated within the battery as heatin the ESR That is to say the efficiency of batteries is around50 For supercapacitor the peak power is usually for a 95efficient discharge in which only 5 of the energy from thedevice is dissipated as heat in the ESR For a correspondinghigh-efficiency discharge batteries would have a much lowerpower capability Furthermore the main drawback of thebatteries is a slow-charging time limited by a chargingcurrent in contrast the supercapacitor may be charged in

Journal of Control Science and Engineering 3

0 50 100 15010

100

1000

10000

Specific energy (Whkg)

Lead-acid Li-ion (HE)

SC (HP)

HP high powerHE high energy

Li-ion (HP)

Spec

ific p

ower

(Wk

g)

Figure 1 Comparison of battery and supercapacitor

a short time depending on a high-charging current (power)available from the main source [30]

Figure 1 shows the comparison of battery and supercapac-itor in terms of power and energy Even though it is true that abattery has the largest energy density (meaning more energyis stored per weight than other technologies) it is importantto consider the availability of that energy This is the tradi-tional advantage of supercapacitor With a time constant ofless than 01 s energy can be taken from a supercapacitorat a very high rate [31] Electrochemical reactions in batteryand double-layer effects in supercapacitor will yield differentacceleration and deceleration transient behaviors of voltageand current which are described as different time constantsin dynamic equivalent circuit models

3 Hybrid Topology Structure

Hybrid energy storage systems are formed in some typicaltopologies in order tomanage the power flowbetween batteryand supercapacitor each of which has its own propertiesIn this section the advantages and disadvantages of fourcommonly used hybrid structures for electric vehicles aredescribed

Figure 2 shows a passive topological structure in whichboth battery and supercapacitor are directly connected inparallel Although it is simple and easy to be realized inHESSthe power distribution is inherently limited by their internalresistance since the voltage of both battery and supercapacitoris the same [25]

Figure 3 shows one of the semiactive topological struc-tures in which the DCDC converter is connected to thevoltage side of the battery and the battery voltage can beboosted up such that the battery pack can be made smallerto reduce its weight and volume Further with this structurethe battery voltage can be controlled more effectively [32]

Figure 4 shows another type of the semiactive topo-logical structures in which the voltage of supercapacitoris controlled by a bidirectional DCDC converter so thatthe supercapacitor can be boosted up to meet the driving

Battery system

Supercapacitorsystem

Load emulator

Cable lineCAN line

Powerdemand

dynamic model

Vehiclelongitudinal

Figure 2 A passive topological structure

Battery system

Supercapacitorsystem

Bidirectional DCDC Load emulator

Controller

Cable lineCAN line

Power demand

Control command

dynamic model

Vehiclelongitudinal

Figure 3 A semiactive topological structure

power demand for electric vehicles Likewise it can also bereduced to a lower level for the purpose of energy recoveryvia regenerative braking This would enable supercapacitorto operate in a wider voltage range and to curb voltagefluctuation and peak current damage to battery Even if itwas not controlled by a bidirectional DCDC converter thebattery would still work in a high effective range [11]

A fully active topological structure is shown in Figure 5In this structure two bidirectional DCDC converters areused such that the hybrid power system is decoupled betweenbattery and supercapacitor Therefore both power sourcescan be controlled via each individual DCDC converterindependentlyThis structure can bemore flexible stable andefficient for voltage control and power distribution between

4 Journal of Control Science and Engineering

Battery system

Supercapacitorsystem

Bidirectional DCDC

Load emulator

Controller

Power demand

Control command

Cable lineCAN line

dynamic model

Vehiclelongitudinal

Figure 4 Another type of semiactive topological structures

Battery system

Supercapacitorsystem

Bidirectional DCDC Load emulator

Power demand

Controlcommand

Cable lineCAN line

Controller

dynamic model

Vehiclelongitudinal

Figure 5 A fully active topological structure

battery and supercapacitor It can also reduce the size andweight of the hybrid energy storage system [19]

As a brief summary the passive hybrid system is simple instructure and more cost-effective but the fully active hybridsystem offers the best performance Therefore a semiactivehybrid system is often a good tradeoff among them in termsof the performance the structure complexity and the cost-effectiveness

4 Energy Management Control Strategy

The presented energy management system control frame inthis research is illustrated in Figure 6

41 Energy Management System The function of energymanagement system is to supply battery reference currentwhich is subsequently used by the controller

The power demand calculation of hybrid system canbe obtained by considering vehicle dynamics and the totalpower demand consisted of rolling resistance power aerody-namic drag power slope resistance power and accelerationresistance power

119875veh = 119875roll + 119875aer + 119875slope + 119875acc (1)

where the rolling resistance power is described as

119875roll =119906veh120578

119872119892119891 cos (120572)3600

(2)

The aerodynamic drag power is described as

119875aer =1

120578

119862aer119860aer76140

1199063

veh (3)

The slope resistance power is described as

119875slope =119906veh120578

119872119892 sin (120572)3600

(4)

The acceleration resistance power is described as

119875acc =119906veh120578

120575119872

3600

119889119906veh119889119905

(5)

The total current demand can be calculated as

119868load =119875veh119880bus

(6)

where 119880bus is the bus voltage 119872 is the vehicle mass 119906vehis the vehicle velocity 119892 is gravity constant 119891 is the rollingresistance coefficient 120572 is the road slope angle 119862aer is theaerodynamic drag coefficient of the vehicle119860aer is the frontalarea of the vehicle and 120578 is the drive efficiency

State of charge (SOC) is traditionally used to indicatethe residual electricity of the battery its definition is usuallywritten by the equation

SOCbat = SOC0minus 119896ch sdot 119896dis sdot int 120576 sdot

119868bat119889119905

119862bat (7)

where SOC0describes the initial value of SOCbat 119896ch and 119896dis

describe the influence coefficients on the current integrationfrom charging current (119868

119871lt 0) and discharging current

(119868119871gt 0) respectively if the battery is charging 119896dis = 1

and if the battery is discharging 119896ch = 1 119862bat describesthe nominal capacity of battery 120576 is the coulomb efficiency(including charging efficiency 120576ch and discharging efficiency120576dis)

Journal of Control Science and Engineering 5

PWMgeneratorController

Energymanagement

system

AVLemulator

Battery DCDC converter Supercapacitor Load

d

Ibat

UscUsc_ref

Iload

SOCbatSOCsc

Ibat_ref

Ibat

Ulbat

Rbat

Ubat

Lbat Cbus

Ibat1

Isc

Csc

Rsc

Ibus

Ubus

Figure 6 Control frame of the HESS

In order to indicate the residual electricity of supercapac-itor the state of charge (SOC) of the supercapacitor is usedto describe a percentage of the rated energy capacity whichdepends on the terminal output voltage and is defined as inthe equation

SOCSC =(119880LSC minus 119880119888min)

(119880119888max minus 119880119888min)

(8)

where 119880LSC is supercapacitor load voltage and 119880119888max and

119880119888min are the maximum and minimum terminal voltage

respectivelyThe proposed energy management system is a rule based

and power-balancing strategy The strategy is realized by aseries of simple control logical rules The main advantageof the proposed strategy is to protect battery from the highdynamics in current demand without overdischarging orovercharging the supercapacitor Consequently both batterylifetime and energy efficiency are increased

The flowchart of DCDC converter control mode strategyis shown in Figure 7 The control mode depends on thesymbol of the load current demandThe positive load currentrepresents the fact that the vehicle is driving In this situationbattery or supercapacitor must supply the requirement driv-ing current to meet vehicle driving demand Therefore theDCDC converter need be switched to buck mode Howeverthe DCDC control mode also depends on the charge anddischarge relationships between battery and supercapacitorEven if the load current is positive the DCDC converter isalso switched to boostmodewhen the supercapacitor chargesbattery In thisway the supercapacitor SOCcan be adjusted tothe expected variation range quickly and thus can ensure theHESS tomeet the load current demandwithout overcharge oroverdischarge of the battery As a result the battery operationcondition can be smoothed greatly and battery lifetime isincreased as well

SC charges battery

Battery charges SC

Buck mode

Yes Yes

No No

Boost modeBuck mode Buck mode Boost mode

lt0gt0

= 0

Sign (Idem)

Current Idem

Vehicle model

Driving cycle

Figure 7 Flowchart of the DCDC converter control mode strategy

The flowchart of driving mode control strategy is shownin Figure 8 This decision-making flowchart considers as thefirst decision a comparison of the real supercapacitor SOCand the preset supercapacitor SOC variation range If the realsupercapacitor SOC is located in the preset supercapacitorSOC variation range then the load current is distributed tosupercapacitor only and the battery will not supply any loadcurrentThe purpose of this arrangement is to protect batteryfrom the frequent charge and discharge process and increasebattery lifetime When the preset supercapacitor SOC vari-ation range is broken the battery is considered to balancethe supercapacitor SOC or share the load current In thissituation if the supercapacitor SOC exceeds its upper limitvalue then the load current is distributed to supercapacitoronly Besides the supercapacitor is charged by the batteryIn this way the supercapacitor SOC can be decreased to the

6 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

gt 0

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = IdemIbat = 0

SOCsc ⩾ SOCsc_max

Isc = IdemIbat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

= Idem times 120578dc= Idem times 120578dc

Isc = Ibatcharge times 120578dc

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

Sign (Idem)

IbatIbat

Figure 8 Flowchart of driving condition control mode

preset variation range quickly and thus guarantee the super-capacitor to work within the reasonable capacity fluctuationrange If the supercapacitor SOCdrops down to its lower limitvalue the battery is considered to share the load current toavoid the large drop of the supercapacitor SOC When thebattery SOC is bigger than its preset minimum value theload current is distributed to battery only At the same timethe supercapacitor is charged by the battery Otherwise thesupercapacitor cannot be charged by the battery It must benoted that the described rules abovemainly include five workmodes for the battery and supercapacitor the battery workonly the supercapacitor work only the battery charges tothe supercapacitor the supercapacitor charges to the batteryand the battery and supercapacitor working together In factwhen the supercapacitor exceeds the preset supercapacitorSOC variation range the load current is distributed to batteryand supercapacitor jointly In this process the charge is alsocarried out simultaneously

The flowchart of idle speed mode control strategy isshown in Figure 9 Generally the SOCof the supercapacitor iscontrolled within a certain reasonable fluctuation rangeThisis to ensure that electric vehicle is able to run even if a highacceleration or deceleration is required without overstressingthe battery Therefore the idle speed mode control strategyis only to ensure the supercapacitor SOC to be controlledwithin preset fluctuation range When the supercapacitorSOC is below the preset lower limit value the supercapacitoris charged by the battery On the contrary the supercapacitoris discharged Otherwise no operation is carried out

The flowchart of braking mode control strategy is shownin Figure 10 Similar to the driving mode control strategy thebattery current is firstly set to zero this is very important toprotect the battery frombig current burst during the transientprocess Then the only decision in this flowchart depends onthe SOC of the supercapacitor and on the preset variationrange When the supercapacitor SOC is below the presetlower limit value then the supercapacitor can absorb thecurrent from the regenerative breaking At the same time thelacking energy is supplied by the battery charge When thesupercapacitor SOC exceeds the preset higher limit value theregenerative breaking current is absorbed by battery At thesame time the part energy is delivered to battery from thesupercapacitor Otherwise the regenerative breaking currentis absorbed by the supercapacitor only

42 Controller The input variable of controller is the batteryreference current and the output variable is the controllercommand In order to realize control objective a classical PIcontroller is adopted in this research In this described config-uration the battery is connected to the DCDC converter butthe supercapacitor is directly connected to the bus withoutDCDC converter The current relations can be written by

119862bus sdot119889119880bus119889119905

= 119868bat1 + 119868SC minus 119868bus (9)

Journal of Control Science and Engineering 7

Yes

Yes

No

No

= 0

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = 0

Ibat = 0SOCsc ⩾ SOCsc_max

Isc = Ibatcharge times 120578dc Ibat = Isccharge times 120578dc

Sign (Idem)

Figure 9 Flowchart of idle speed condition control mode

The equivalentmodel of the DCDC converter connectedto the battery can be described as

119871bat119889119868bat119889119905

+ 119877bat119868bat = 119880119871bat minus 119889 sdot 119880bus (10)

Equation (10) is a nonlinear first-order equation by using theLaplace transform we can obtain that

119868bat (119904) =119880119871bat (119904)

119871bat sdot 119904 + 119877batminus

119889 (119904) 119880bus119871bat sdot 119904 + 119877bat

(11)

The control loop of the battery current is describedin Figure 11 The input is the DCDC converter controlcommand the output is the battery current In order tobalance the hybrid systemwithout overdischarging the super-capacitor a supercapacitor voltage compensation loop hasbeen implemented which is shown in Figure 12

5 Experimental Results and System Analysis

51 Experimental Results In order to validate the proposedenergy management control strategy a commercial exper-imental platform is constructed The whole experimentalplatform mainly includes two parts hardware power systemand software control system which are shown in Figures 13and 14

The supercapacitor pack adopted in this experimentalplatform is the MaxwellBCAP3000 type rated 3000 F 27 Vhaving the parameters given in Table 1 The battery packfor the HESS is ternary lithium battery which is consideredas the next generation battery used in electric vehicle Thespecific parameters of the battery pack are listed in Table 2The presented DCDC is a bidirectional DCDC converterby which both the driving current and the braking currentcan be controlled for the battery pack The main parameters

Table 1 Parameters of the supercapacitor pack

Items SpecificationsNominal voltage 240VNominal capacity 55 FNumber of cells 88Maximum continuous power 30 kW13 sPack mass 45 kg plusmn 5Maximum operating temperature +65∘CMinimum operating temperature minus40∘CMaximum storage temperature +70∘CMinimum storage temperature minus40∘CCommunication type CAN20B J1939Leakage current 53mASafe level IP65Vibration IEC 16750Lifetime 25∘C ge10 yearsInitial 48V module resistance 63mΩShock SAE J2464

of the DCDC converter are listed in Table 3 The ElectricControl Unit (ECU) is a dSPACE-based MicroAutoBox (DS1401) TwoCANcontrollers in theMicroAutoBox are adoptedfor the load current calculation and control algorithm calcu-lation respectively

The experiment was carried out to test the controlstrategy based on two driving cycles that is the USAUrban Dynamometer Driving Schedule (UDDS) and theNew European Driving Cycle (NEDC) Simulation resultsand comparisons between the batteries only power systemand the HESS system for UDDS driving cycle are shown inFigures 15ndash21

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

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Active and Passive Electronic Components

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RotatingMachinery

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

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Volume 2014

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SensorsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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Navigation and Observation

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DistributedSensor Networks

International Journal of

2 Journal of Control Science and Engineering

HESS are also developed in the literature These strategiescan be broadly classified into rule based and optimization-based distribution Rule based controllers are referred toas deterministic rule learning network and fuzzy logicalcontroller In [21] an ADVISOR-based battery and super-capacitor HESS was developed the power distribution rulebetween battery and supercapacitor was determined basedon an experiment approach In [22] an integrated rule basedmetaheuristic approachwas presented and simulation resultshave proved the effectiveness of this multilevel EMS fulfillingthe requested performance with better source usage andmuch lower installed capacities In [23] a fuzzy logical con-troller based on particle swarm optimization algorithm waspresented to achieve optimization power flow distributionbetween battery and supercapacitor Reference [24] adoptedthe idea of neural networks and developed an efficient energymanagement system for hybrid electric vehicles with closedform approaches

Optimization-based methods consider local and globaloptimization problems by using past driving cycle infor-mation to determine the power distribution mode amongpower sources Reference [25] formulated an optimizationproblem by concerning the minimization of the magni-tudefluctuation of the current flowing in and out of thebattery and the energy loss of the supercapacitor An MPC(model predictive control) controller for a hybrid battery-supercapacitor power source was proposed and experimen-tally verified in [26] The designed MPC controller enablesthe battery to share the low frequency power componentsand the high frequency power components are allocated tothe supercapacitor In [27] a wavelet transform-based powermanagement strategy was proposed in which load power isdecomposed into different frequency components to the FC(fuel cell) battery and supercapacitor compatible with theirrespective dynamic characteristics Reference [28] adopted afirst-order low-pass filter which was designed for frequencydecomposition along with analysis of components responsesunder real world driving cycles These strategies wouldincrease battery lifetime attributing to effective frequencyseparation consideration

In this paper a rule based energy management systemis developed for a semiactive hybrid system The objectiveof the proposed energy management system is to focus onexploiting the supercapacitor characteristics and increasingthe battery lifetime and system efficiency The main con-tributions of this paper are summarized as follows First asimple but effective rule based energy management system isdeveloped for a semiactive hybrid system The main role ofthe energy management system is to yield battery referencecurrent according to energy levels of the power sources andload demand level Then two classical PI control loops areproposed to adjust the load distribution between battery andsupercapacitor The described energy management systemenables the battery to share low frequency and smooth loadcurrent and the corresponding high frequency and peakcurrent are distributed to the supercapacitor This systemprevents an overstress on the battery while maintaininga good voltage balance of the supercapacitor This is animportant advantage to ensure the vehicle starts a new cycle

if high acceleration is required Second an experimentalplatform of the hybrid system is developed to verify thedescribed energy management system using two standarddrive cycles for an electric vehicle Finally preliminary butsignificant energy efficiency and the cost analysis of thehybrid system are carried out based on the experimentalresults to explore the most cost-effective tradeoff

The rest of this paper is organized as follows Section 2describes the dynamic characteristics of the battery andsupercapacitor Section 3 analyzes the hybrid topology struc-ture Section 4 describes the energy management controlstrategy Section 5 verifies the proposed control strategy basedon a commercial experimental platform Finally the paper isconcluded in Section 6

2 Characteristics of Battery andSupercapacitor as Power Sources

Batteries used in electric vehicle usually have the charac-teristics of high energy density and relatively low powerdensity The latter is a limitation to improve vehicle dynamicperformanceHigh power capability requires the resistance ofthe battery to be low Hence knowledge of the resistance of abattery is critical to the ability to assess its power capabilityIn addition the charging and discharge internal resistances ofbattery are usually different which is dependent on chargingand discharge operating conditions including amplitude andfrequency of charging and discharge of battery For lithium-ion battery the internal resistance could increase when highfrequency loads are exerted The ampere-hour capacity isaffected by the discharging current rate and is modeled by thePeukert equation [13] The charging and discharging internalresistances are nonlinear functions of current and state ofcharge (SOC)

Recently another energy storage device the supercapaci-tor has attractedmuch interest because of its high power den-sity (300Wkgndash5000Wkg) and relatively low energy densityThere are presently commercially available carboncarbonsupercapacitor devices (single cells and modules) from sev-eral companies such as Maxwell Ness EPCOS NipponChemi-Con and Power Systems All these companies marketlarge devices with capacitance of 1000ndash5000 F These devicesare suitable for high power vehicle applications [29]

As described above the difference between battery andsupercapacitor can provide the complementary advantage tomeet power and energy demand From the perspective ofpower characteristics the charging and discharging efficiencyof system is usually considered as the main factor Bycomparison only one-half of the energy at the peak powerfrom the battery is in the form of electrical energy to the loadand the other one-half is dissipated within the battery as heatin the ESR That is to say the efficiency of batteries is around50 For supercapacitor the peak power is usually for a 95efficient discharge in which only 5 of the energy from thedevice is dissipated as heat in the ESR For a correspondinghigh-efficiency discharge batteries would have a much lowerpower capability Furthermore the main drawback of thebatteries is a slow-charging time limited by a chargingcurrent in contrast the supercapacitor may be charged in

Journal of Control Science and Engineering 3

0 50 100 15010

100

1000

10000

Specific energy (Whkg)

Lead-acid Li-ion (HE)

SC (HP)

HP high powerHE high energy

Li-ion (HP)

Spec

ific p

ower

(Wk

g)

Figure 1 Comparison of battery and supercapacitor

a short time depending on a high-charging current (power)available from the main source [30]

Figure 1 shows the comparison of battery and supercapac-itor in terms of power and energy Even though it is true that abattery has the largest energy density (meaning more energyis stored per weight than other technologies) it is importantto consider the availability of that energy This is the tradi-tional advantage of supercapacitor With a time constant ofless than 01 s energy can be taken from a supercapacitorat a very high rate [31] Electrochemical reactions in batteryand double-layer effects in supercapacitor will yield differentacceleration and deceleration transient behaviors of voltageand current which are described as different time constantsin dynamic equivalent circuit models

3 Hybrid Topology Structure

Hybrid energy storage systems are formed in some typicaltopologies in order tomanage the power flowbetween batteryand supercapacitor each of which has its own propertiesIn this section the advantages and disadvantages of fourcommonly used hybrid structures for electric vehicles aredescribed

Figure 2 shows a passive topological structure in whichboth battery and supercapacitor are directly connected inparallel Although it is simple and easy to be realized inHESSthe power distribution is inherently limited by their internalresistance since the voltage of both battery and supercapacitoris the same [25]

Figure 3 shows one of the semiactive topological struc-tures in which the DCDC converter is connected to thevoltage side of the battery and the battery voltage can beboosted up such that the battery pack can be made smallerto reduce its weight and volume Further with this structurethe battery voltage can be controlled more effectively [32]

Figure 4 shows another type of the semiactive topo-logical structures in which the voltage of supercapacitoris controlled by a bidirectional DCDC converter so thatthe supercapacitor can be boosted up to meet the driving

Battery system

Supercapacitorsystem

Load emulator

Cable lineCAN line

Powerdemand

dynamic model

Vehiclelongitudinal

Figure 2 A passive topological structure

Battery system

Supercapacitorsystem

Bidirectional DCDC Load emulator

Controller

Cable lineCAN line

Power demand

Control command

dynamic model

Vehiclelongitudinal

Figure 3 A semiactive topological structure

power demand for electric vehicles Likewise it can also bereduced to a lower level for the purpose of energy recoveryvia regenerative braking This would enable supercapacitorto operate in a wider voltage range and to curb voltagefluctuation and peak current damage to battery Even if itwas not controlled by a bidirectional DCDC converter thebattery would still work in a high effective range [11]

A fully active topological structure is shown in Figure 5In this structure two bidirectional DCDC converters areused such that the hybrid power system is decoupled betweenbattery and supercapacitor Therefore both power sourcescan be controlled via each individual DCDC converterindependentlyThis structure can bemore flexible stable andefficient for voltage control and power distribution between

4 Journal of Control Science and Engineering

Battery system

Supercapacitorsystem

Bidirectional DCDC

Load emulator

Controller

Power demand

Control command

Cable lineCAN line

dynamic model

Vehiclelongitudinal

Figure 4 Another type of semiactive topological structures

Battery system

Supercapacitorsystem

Bidirectional DCDC Load emulator

Power demand

Controlcommand

Cable lineCAN line

Controller

dynamic model

Vehiclelongitudinal

Figure 5 A fully active topological structure

battery and supercapacitor It can also reduce the size andweight of the hybrid energy storage system [19]

As a brief summary the passive hybrid system is simple instructure and more cost-effective but the fully active hybridsystem offers the best performance Therefore a semiactivehybrid system is often a good tradeoff among them in termsof the performance the structure complexity and the cost-effectiveness

4 Energy Management Control Strategy

The presented energy management system control frame inthis research is illustrated in Figure 6

41 Energy Management System The function of energymanagement system is to supply battery reference currentwhich is subsequently used by the controller

The power demand calculation of hybrid system canbe obtained by considering vehicle dynamics and the totalpower demand consisted of rolling resistance power aerody-namic drag power slope resistance power and accelerationresistance power

119875veh = 119875roll + 119875aer + 119875slope + 119875acc (1)

where the rolling resistance power is described as

119875roll =119906veh120578

119872119892119891 cos (120572)3600

(2)

The aerodynamic drag power is described as

119875aer =1

120578

119862aer119860aer76140

1199063

veh (3)

The slope resistance power is described as

119875slope =119906veh120578

119872119892 sin (120572)3600

(4)

The acceleration resistance power is described as

119875acc =119906veh120578

120575119872

3600

119889119906veh119889119905

(5)

The total current demand can be calculated as

119868load =119875veh119880bus

(6)

where 119880bus is the bus voltage 119872 is the vehicle mass 119906vehis the vehicle velocity 119892 is gravity constant 119891 is the rollingresistance coefficient 120572 is the road slope angle 119862aer is theaerodynamic drag coefficient of the vehicle119860aer is the frontalarea of the vehicle and 120578 is the drive efficiency

State of charge (SOC) is traditionally used to indicatethe residual electricity of the battery its definition is usuallywritten by the equation

SOCbat = SOC0minus 119896ch sdot 119896dis sdot int 120576 sdot

119868bat119889119905

119862bat (7)

where SOC0describes the initial value of SOCbat 119896ch and 119896dis

describe the influence coefficients on the current integrationfrom charging current (119868

119871lt 0) and discharging current

(119868119871gt 0) respectively if the battery is charging 119896dis = 1

and if the battery is discharging 119896ch = 1 119862bat describesthe nominal capacity of battery 120576 is the coulomb efficiency(including charging efficiency 120576ch and discharging efficiency120576dis)

Journal of Control Science and Engineering 5

PWMgeneratorController

Energymanagement

system

AVLemulator

Battery DCDC converter Supercapacitor Load

d

Ibat

UscUsc_ref

Iload

SOCbatSOCsc

Ibat_ref

Ibat

Ulbat

Rbat

Ubat

Lbat Cbus

Ibat1

Isc

Csc

Rsc

Ibus

Ubus

Figure 6 Control frame of the HESS

In order to indicate the residual electricity of supercapac-itor the state of charge (SOC) of the supercapacitor is usedto describe a percentage of the rated energy capacity whichdepends on the terminal output voltage and is defined as inthe equation

SOCSC =(119880LSC minus 119880119888min)

(119880119888max minus 119880119888min)

(8)

where 119880LSC is supercapacitor load voltage and 119880119888max and

119880119888min are the maximum and minimum terminal voltage

respectivelyThe proposed energy management system is a rule based

and power-balancing strategy The strategy is realized by aseries of simple control logical rules The main advantageof the proposed strategy is to protect battery from the highdynamics in current demand without overdischarging orovercharging the supercapacitor Consequently both batterylifetime and energy efficiency are increased

The flowchart of DCDC converter control mode strategyis shown in Figure 7 The control mode depends on thesymbol of the load current demandThe positive load currentrepresents the fact that the vehicle is driving In this situationbattery or supercapacitor must supply the requirement driv-ing current to meet vehicle driving demand Therefore theDCDC converter need be switched to buck mode Howeverthe DCDC control mode also depends on the charge anddischarge relationships between battery and supercapacitorEven if the load current is positive the DCDC converter isalso switched to boostmodewhen the supercapacitor chargesbattery In thisway the supercapacitor SOCcan be adjusted tothe expected variation range quickly and thus can ensure theHESS tomeet the load current demandwithout overcharge oroverdischarge of the battery As a result the battery operationcondition can be smoothed greatly and battery lifetime isincreased as well

SC charges battery

Battery charges SC

Buck mode

Yes Yes

No No

Boost modeBuck mode Buck mode Boost mode

lt0gt0

= 0

Sign (Idem)

Current Idem

Vehicle model

Driving cycle

Figure 7 Flowchart of the DCDC converter control mode strategy

The flowchart of driving mode control strategy is shownin Figure 8 This decision-making flowchart considers as thefirst decision a comparison of the real supercapacitor SOCand the preset supercapacitor SOC variation range If the realsupercapacitor SOC is located in the preset supercapacitorSOC variation range then the load current is distributed tosupercapacitor only and the battery will not supply any loadcurrentThe purpose of this arrangement is to protect batteryfrom the frequent charge and discharge process and increasebattery lifetime When the preset supercapacitor SOC vari-ation range is broken the battery is considered to balancethe supercapacitor SOC or share the load current In thissituation if the supercapacitor SOC exceeds its upper limitvalue then the load current is distributed to supercapacitoronly Besides the supercapacitor is charged by the batteryIn this way the supercapacitor SOC can be decreased to the

6 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

gt 0

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = IdemIbat = 0

SOCsc ⩾ SOCsc_max

Isc = IdemIbat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

= Idem times 120578dc= Idem times 120578dc

Isc = Ibatcharge times 120578dc

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

Sign (Idem)

IbatIbat

Figure 8 Flowchart of driving condition control mode

preset variation range quickly and thus guarantee the super-capacitor to work within the reasonable capacity fluctuationrange If the supercapacitor SOCdrops down to its lower limitvalue the battery is considered to share the load current toavoid the large drop of the supercapacitor SOC When thebattery SOC is bigger than its preset minimum value theload current is distributed to battery only At the same timethe supercapacitor is charged by the battery Otherwise thesupercapacitor cannot be charged by the battery It must benoted that the described rules abovemainly include five workmodes for the battery and supercapacitor the battery workonly the supercapacitor work only the battery charges tothe supercapacitor the supercapacitor charges to the batteryand the battery and supercapacitor working together In factwhen the supercapacitor exceeds the preset supercapacitorSOC variation range the load current is distributed to batteryand supercapacitor jointly In this process the charge is alsocarried out simultaneously

The flowchart of idle speed mode control strategy isshown in Figure 9 Generally the SOCof the supercapacitor iscontrolled within a certain reasonable fluctuation rangeThisis to ensure that electric vehicle is able to run even if a highacceleration or deceleration is required without overstressingthe battery Therefore the idle speed mode control strategyis only to ensure the supercapacitor SOC to be controlledwithin preset fluctuation range When the supercapacitorSOC is below the preset lower limit value the supercapacitoris charged by the battery On the contrary the supercapacitoris discharged Otherwise no operation is carried out

The flowchart of braking mode control strategy is shownin Figure 10 Similar to the driving mode control strategy thebattery current is firstly set to zero this is very important toprotect the battery frombig current burst during the transientprocess Then the only decision in this flowchart depends onthe SOC of the supercapacitor and on the preset variationrange When the supercapacitor SOC is below the presetlower limit value then the supercapacitor can absorb thecurrent from the regenerative breaking At the same time thelacking energy is supplied by the battery charge When thesupercapacitor SOC exceeds the preset higher limit value theregenerative breaking current is absorbed by battery At thesame time the part energy is delivered to battery from thesupercapacitor Otherwise the regenerative breaking currentis absorbed by the supercapacitor only

42 Controller The input variable of controller is the batteryreference current and the output variable is the controllercommand In order to realize control objective a classical PIcontroller is adopted in this research In this described config-uration the battery is connected to the DCDC converter butthe supercapacitor is directly connected to the bus withoutDCDC converter The current relations can be written by

119862bus sdot119889119880bus119889119905

= 119868bat1 + 119868SC minus 119868bus (9)

Journal of Control Science and Engineering 7

Yes

Yes

No

No

= 0

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = 0

Ibat = 0SOCsc ⩾ SOCsc_max

Isc = Ibatcharge times 120578dc Ibat = Isccharge times 120578dc

Sign (Idem)

Figure 9 Flowchart of idle speed condition control mode

The equivalentmodel of the DCDC converter connectedto the battery can be described as

119871bat119889119868bat119889119905

+ 119877bat119868bat = 119880119871bat minus 119889 sdot 119880bus (10)

Equation (10) is a nonlinear first-order equation by using theLaplace transform we can obtain that

119868bat (119904) =119880119871bat (119904)

119871bat sdot 119904 + 119877batminus

119889 (119904) 119880bus119871bat sdot 119904 + 119877bat

(11)

The control loop of the battery current is describedin Figure 11 The input is the DCDC converter controlcommand the output is the battery current In order tobalance the hybrid systemwithout overdischarging the super-capacitor a supercapacitor voltage compensation loop hasbeen implemented which is shown in Figure 12

5 Experimental Results and System Analysis

51 Experimental Results In order to validate the proposedenergy management control strategy a commercial exper-imental platform is constructed The whole experimentalplatform mainly includes two parts hardware power systemand software control system which are shown in Figures 13and 14

The supercapacitor pack adopted in this experimentalplatform is the MaxwellBCAP3000 type rated 3000 F 27 Vhaving the parameters given in Table 1 The battery packfor the HESS is ternary lithium battery which is consideredas the next generation battery used in electric vehicle Thespecific parameters of the battery pack are listed in Table 2The presented DCDC is a bidirectional DCDC converterby which both the driving current and the braking currentcan be controlled for the battery pack The main parameters

Table 1 Parameters of the supercapacitor pack

Items SpecificationsNominal voltage 240VNominal capacity 55 FNumber of cells 88Maximum continuous power 30 kW13 sPack mass 45 kg plusmn 5Maximum operating temperature +65∘CMinimum operating temperature minus40∘CMaximum storage temperature +70∘CMinimum storage temperature minus40∘CCommunication type CAN20B J1939Leakage current 53mASafe level IP65Vibration IEC 16750Lifetime 25∘C ge10 yearsInitial 48V module resistance 63mΩShock SAE J2464

of the DCDC converter are listed in Table 3 The ElectricControl Unit (ECU) is a dSPACE-based MicroAutoBox (DS1401) TwoCANcontrollers in theMicroAutoBox are adoptedfor the load current calculation and control algorithm calcu-lation respectively

The experiment was carried out to test the controlstrategy based on two driving cycles that is the USAUrban Dynamometer Driving Schedule (UDDS) and theNew European Driving Cycle (NEDC) Simulation resultsand comparisons between the batteries only power systemand the HESS system for UDDS driving cycle are shown inFigures 15ndash21

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

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Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

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Volume 2014

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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DistributedSensor Networks

International Journal of

Journal of Control Science and Engineering 3

0 50 100 15010

100

1000

10000

Specific energy (Whkg)

Lead-acid Li-ion (HE)

SC (HP)

HP high powerHE high energy

Li-ion (HP)

Spec

ific p

ower

(Wk

g)

Figure 1 Comparison of battery and supercapacitor

a short time depending on a high-charging current (power)available from the main source [30]

Figure 1 shows the comparison of battery and supercapac-itor in terms of power and energy Even though it is true that abattery has the largest energy density (meaning more energyis stored per weight than other technologies) it is importantto consider the availability of that energy This is the tradi-tional advantage of supercapacitor With a time constant ofless than 01 s energy can be taken from a supercapacitorat a very high rate [31] Electrochemical reactions in batteryand double-layer effects in supercapacitor will yield differentacceleration and deceleration transient behaviors of voltageand current which are described as different time constantsin dynamic equivalent circuit models

3 Hybrid Topology Structure

Hybrid energy storage systems are formed in some typicaltopologies in order tomanage the power flowbetween batteryand supercapacitor each of which has its own propertiesIn this section the advantages and disadvantages of fourcommonly used hybrid structures for electric vehicles aredescribed

Figure 2 shows a passive topological structure in whichboth battery and supercapacitor are directly connected inparallel Although it is simple and easy to be realized inHESSthe power distribution is inherently limited by their internalresistance since the voltage of both battery and supercapacitoris the same [25]

Figure 3 shows one of the semiactive topological struc-tures in which the DCDC converter is connected to thevoltage side of the battery and the battery voltage can beboosted up such that the battery pack can be made smallerto reduce its weight and volume Further with this structurethe battery voltage can be controlled more effectively [32]

Figure 4 shows another type of the semiactive topo-logical structures in which the voltage of supercapacitoris controlled by a bidirectional DCDC converter so thatthe supercapacitor can be boosted up to meet the driving

Battery system

Supercapacitorsystem

Load emulator

Cable lineCAN line

Powerdemand

dynamic model

Vehiclelongitudinal

Figure 2 A passive topological structure

Battery system

Supercapacitorsystem

Bidirectional DCDC Load emulator

Controller

Cable lineCAN line

Power demand

Control command

dynamic model

Vehiclelongitudinal

Figure 3 A semiactive topological structure

power demand for electric vehicles Likewise it can also bereduced to a lower level for the purpose of energy recoveryvia regenerative braking This would enable supercapacitorto operate in a wider voltage range and to curb voltagefluctuation and peak current damage to battery Even if itwas not controlled by a bidirectional DCDC converter thebattery would still work in a high effective range [11]

A fully active topological structure is shown in Figure 5In this structure two bidirectional DCDC converters areused such that the hybrid power system is decoupled betweenbattery and supercapacitor Therefore both power sourcescan be controlled via each individual DCDC converterindependentlyThis structure can bemore flexible stable andefficient for voltage control and power distribution between

4 Journal of Control Science and Engineering

Battery system

Supercapacitorsystem

Bidirectional DCDC

Load emulator

Controller

Power demand

Control command

Cable lineCAN line

dynamic model

Vehiclelongitudinal

Figure 4 Another type of semiactive topological structures

Battery system

Supercapacitorsystem

Bidirectional DCDC Load emulator

Power demand

Controlcommand

Cable lineCAN line

Controller

dynamic model

Vehiclelongitudinal

Figure 5 A fully active topological structure

battery and supercapacitor It can also reduce the size andweight of the hybrid energy storage system [19]

As a brief summary the passive hybrid system is simple instructure and more cost-effective but the fully active hybridsystem offers the best performance Therefore a semiactivehybrid system is often a good tradeoff among them in termsof the performance the structure complexity and the cost-effectiveness

4 Energy Management Control Strategy

The presented energy management system control frame inthis research is illustrated in Figure 6

41 Energy Management System The function of energymanagement system is to supply battery reference currentwhich is subsequently used by the controller

The power demand calculation of hybrid system canbe obtained by considering vehicle dynamics and the totalpower demand consisted of rolling resistance power aerody-namic drag power slope resistance power and accelerationresistance power

119875veh = 119875roll + 119875aer + 119875slope + 119875acc (1)

where the rolling resistance power is described as

119875roll =119906veh120578

119872119892119891 cos (120572)3600

(2)

The aerodynamic drag power is described as

119875aer =1

120578

119862aer119860aer76140

1199063

veh (3)

The slope resistance power is described as

119875slope =119906veh120578

119872119892 sin (120572)3600

(4)

The acceleration resistance power is described as

119875acc =119906veh120578

120575119872

3600

119889119906veh119889119905

(5)

The total current demand can be calculated as

119868load =119875veh119880bus

(6)

where 119880bus is the bus voltage 119872 is the vehicle mass 119906vehis the vehicle velocity 119892 is gravity constant 119891 is the rollingresistance coefficient 120572 is the road slope angle 119862aer is theaerodynamic drag coefficient of the vehicle119860aer is the frontalarea of the vehicle and 120578 is the drive efficiency

State of charge (SOC) is traditionally used to indicatethe residual electricity of the battery its definition is usuallywritten by the equation

SOCbat = SOC0minus 119896ch sdot 119896dis sdot int 120576 sdot

119868bat119889119905

119862bat (7)

where SOC0describes the initial value of SOCbat 119896ch and 119896dis

describe the influence coefficients on the current integrationfrom charging current (119868

119871lt 0) and discharging current

(119868119871gt 0) respectively if the battery is charging 119896dis = 1

and if the battery is discharging 119896ch = 1 119862bat describesthe nominal capacity of battery 120576 is the coulomb efficiency(including charging efficiency 120576ch and discharging efficiency120576dis)

Journal of Control Science and Engineering 5

PWMgeneratorController

Energymanagement

system

AVLemulator

Battery DCDC converter Supercapacitor Load

d

Ibat

UscUsc_ref

Iload

SOCbatSOCsc

Ibat_ref

Ibat

Ulbat

Rbat

Ubat

Lbat Cbus

Ibat1

Isc

Csc

Rsc

Ibus

Ubus

Figure 6 Control frame of the HESS

In order to indicate the residual electricity of supercapac-itor the state of charge (SOC) of the supercapacitor is usedto describe a percentage of the rated energy capacity whichdepends on the terminal output voltage and is defined as inthe equation

SOCSC =(119880LSC minus 119880119888min)

(119880119888max minus 119880119888min)

(8)

where 119880LSC is supercapacitor load voltage and 119880119888max and

119880119888min are the maximum and minimum terminal voltage

respectivelyThe proposed energy management system is a rule based

and power-balancing strategy The strategy is realized by aseries of simple control logical rules The main advantageof the proposed strategy is to protect battery from the highdynamics in current demand without overdischarging orovercharging the supercapacitor Consequently both batterylifetime and energy efficiency are increased

The flowchart of DCDC converter control mode strategyis shown in Figure 7 The control mode depends on thesymbol of the load current demandThe positive load currentrepresents the fact that the vehicle is driving In this situationbattery or supercapacitor must supply the requirement driv-ing current to meet vehicle driving demand Therefore theDCDC converter need be switched to buck mode Howeverthe DCDC control mode also depends on the charge anddischarge relationships between battery and supercapacitorEven if the load current is positive the DCDC converter isalso switched to boostmodewhen the supercapacitor chargesbattery In thisway the supercapacitor SOCcan be adjusted tothe expected variation range quickly and thus can ensure theHESS tomeet the load current demandwithout overcharge oroverdischarge of the battery As a result the battery operationcondition can be smoothed greatly and battery lifetime isincreased as well

SC charges battery

Battery charges SC

Buck mode

Yes Yes

No No

Boost modeBuck mode Buck mode Boost mode

lt0gt0

= 0

Sign (Idem)

Current Idem

Vehicle model

Driving cycle

Figure 7 Flowchart of the DCDC converter control mode strategy

The flowchart of driving mode control strategy is shownin Figure 8 This decision-making flowchart considers as thefirst decision a comparison of the real supercapacitor SOCand the preset supercapacitor SOC variation range If the realsupercapacitor SOC is located in the preset supercapacitorSOC variation range then the load current is distributed tosupercapacitor only and the battery will not supply any loadcurrentThe purpose of this arrangement is to protect batteryfrom the frequent charge and discharge process and increasebattery lifetime When the preset supercapacitor SOC vari-ation range is broken the battery is considered to balancethe supercapacitor SOC or share the load current In thissituation if the supercapacitor SOC exceeds its upper limitvalue then the load current is distributed to supercapacitoronly Besides the supercapacitor is charged by the batteryIn this way the supercapacitor SOC can be decreased to the

6 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

gt 0

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = IdemIbat = 0

SOCsc ⩾ SOCsc_max

Isc = IdemIbat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

= Idem times 120578dc= Idem times 120578dc

Isc = Ibatcharge times 120578dc

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

Sign (Idem)

IbatIbat

Figure 8 Flowchart of driving condition control mode

preset variation range quickly and thus guarantee the super-capacitor to work within the reasonable capacity fluctuationrange If the supercapacitor SOCdrops down to its lower limitvalue the battery is considered to share the load current toavoid the large drop of the supercapacitor SOC When thebattery SOC is bigger than its preset minimum value theload current is distributed to battery only At the same timethe supercapacitor is charged by the battery Otherwise thesupercapacitor cannot be charged by the battery It must benoted that the described rules abovemainly include five workmodes for the battery and supercapacitor the battery workonly the supercapacitor work only the battery charges tothe supercapacitor the supercapacitor charges to the batteryand the battery and supercapacitor working together In factwhen the supercapacitor exceeds the preset supercapacitorSOC variation range the load current is distributed to batteryand supercapacitor jointly In this process the charge is alsocarried out simultaneously

The flowchart of idle speed mode control strategy isshown in Figure 9 Generally the SOCof the supercapacitor iscontrolled within a certain reasonable fluctuation rangeThisis to ensure that electric vehicle is able to run even if a highacceleration or deceleration is required without overstressingthe battery Therefore the idle speed mode control strategyis only to ensure the supercapacitor SOC to be controlledwithin preset fluctuation range When the supercapacitorSOC is below the preset lower limit value the supercapacitoris charged by the battery On the contrary the supercapacitoris discharged Otherwise no operation is carried out

The flowchart of braking mode control strategy is shownin Figure 10 Similar to the driving mode control strategy thebattery current is firstly set to zero this is very important toprotect the battery frombig current burst during the transientprocess Then the only decision in this flowchart depends onthe SOC of the supercapacitor and on the preset variationrange When the supercapacitor SOC is below the presetlower limit value then the supercapacitor can absorb thecurrent from the regenerative breaking At the same time thelacking energy is supplied by the battery charge When thesupercapacitor SOC exceeds the preset higher limit value theregenerative breaking current is absorbed by battery At thesame time the part energy is delivered to battery from thesupercapacitor Otherwise the regenerative breaking currentis absorbed by the supercapacitor only

42 Controller The input variable of controller is the batteryreference current and the output variable is the controllercommand In order to realize control objective a classical PIcontroller is adopted in this research In this described config-uration the battery is connected to the DCDC converter butthe supercapacitor is directly connected to the bus withoutDCDC converter The current relations can be written by

119862bus sdot119889119880bus119889119905

= 119868bat1 + 119868SC minus 119868bus (9)

Journal of Control Science and Engineering 7

Yes

Yes

No

No

= 0

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = 0

Ibat = 0SOCsc ⩾ SOCsc_max

Isc = Ibatcharge times 120578dc Ibat = Isccharge times 120578dc

Sign (Idem)

Figure 9 Flowchart of idle speed condition control mode

The equivalentmodel of the DCDC converter connectedto the battery can be described as

119871bat119889119868bat119889119905

+ 119877bat119868bat = 119880119871bat minus 119889 sdot 119880bus (10)

Equation (10) is a nonlinear first-order equation by using theLaplace transform we can obtain that

119868bat (119904) =119880119871bat (119904)

119871bat sdot 119904 + 119877batminus

119889 (119904) 119880bus119871bat sdot 119904 + 119877bat

(11)

The control loop of the battery current is describedin Figure 11 The input is the DCDC converter controlcommand the output is the battery current In order tobalance the hybrid systemwithout overdischarging the super-capacitor a supercapacitor voltage compensation loop hasbeen implemented which is shown in Figure 12

5 Experimental Results and System Analysis

51 Experimental Results In order to validate the proposedenergy management control strategy a commercial exper-imental platform is constructed The whole experimentalplatform mainly includes two parts hardware power systemand software control system which are shown in Figures 13and 14

The supercapacitor pack adopted in this experimentalplatform is the MaxwellBCAP3000 type rated 3000 F 27 Vhaving the parameters given in Table 1 The battery packfor the HESS is ternary lithium battery which is consideredas the next generation battery used in electric vehicle Thespecific parameters of the battery pack are listed in Table 2The presented DCDC is a bidirectional DCDC converterby which both the driving current and the braking currentcan be controlled for the battery pack The main parameters

Table 1 Parameters of the supercapacitor pack

Items SpecificationsNominal voltage 240VNominal capacity 55 FNumber of cells 88Maximum continuous power 30 kW13 sPack mass 45 kg plusmn 5Maximum operating temperature +65∘CMinimum operating temperature minus40∘CMaximum storage temperature +70∘CMinimum storage temperature minus40∘CCommunication type CAN20B J1939Leakage current 53mASafe level IP65Vibration IEC 16750Lifetime 25∘C ge10 yearsInitial 48V module resistance 63mΩShock SAE J2464

of the DCDC converter are listed in Table 3 The ElectricControl Unit (ECU) is a dSPACE-based MicroAutoBox (DS1401) TwoCANcontrollers in theMicroAutoBox are adoptedfor the load current calculation and control algorithm calcu-lation respectively

The experiment was carried out to test the controlstrategy based on two driving cycles that is the USAUrban Dynamometer Driving Schedule (UDDS) and theNew European Driving Cycle (NEDC) Simulation resultsand comparisons between the batteries only power systemand the HESS system for UDDS driving cycle are shown inFigures 15ndash21

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

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Active and Passive Electronic Components

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RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

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Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

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Electrical and Computer Engineering

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Advances inOptoElectronics

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Volume 2014

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SensorsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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International Journal of

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Navigation and Observation

International Journal of

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DistributedSensor Networks

International Journal of

4 Journal of Control Science and Engineering

Battery system

Supercapacitorsystem

Bidirectional DCDC

Load emulator

Controller

Power demand

Control command

Cable lineCAN line

dynamic model

Vehiclelongitudinal

Figure 4 Another type of semiactive topological structures

Battery system

Supercapacitorsystem

Bidirectional DCDC Load emulator

Power demand

Controlcommand

Cable lineCAN line

Controller

dynamic model

Vehiclelongitudinal

Figure 5 A fully active topological structure

battery and supercapacitor It can also reduce the size andweight of the hybrid energy storage system [19]

As a brief summary the passive hybrid system is simple instructure and more cost-effective but the fully active hybridsystem offers the best performance Therefore a semiactivehybrid system is often a good tradeoff among them in termsof the performance the structure complexity and the cost-effectiveness

4 Energy Management Control Strategy

The presented energy management system control frame inthis research is illustrated in Figure 6

41 Energy Management System The function of energymanagement system is to supply battery reference currentwhich is subsequently used by the controller

The power demand calculation of hybrid system canbe obtained by considering vehicle dynamics and the totalpower demand consisted of rolling resistance power aerody-namic drag power slope resistance power and accelerationresistance power

119875veh = 119875roll + 119875aer + 119875slope + 119875acc (1)

where the rolling resistance power is described as

119875roll =119906veh120578

119872119892119891 cos (120572)3600

(2)

The aerodynamic drag power is described as

119875aer =1

120578

119862aer119860aer76140

1199063

veh (3)

The slope resistance power is described as

119875slope =119906veh120578

119872119892 sin (120572)3600

(4)

The acceleration resistance power is described as

119875acc =119906veh120578

120575119872

3600

119889119906veh119889119905

(5)

The total current demand can be calculated as

119868load =119875veh119880bus

(6)

where 119880bus is the bus voltage 119872 is the vehicle mass 119906vehis the vehicle velocity 119892 is gravity constant 119891 is the rollingresistance coefficient 120572 is the road slope angle 119862aer is theaerodynamic drag coefficient of the vehicle119860aer is the frontalarea of the vehicle and 120578 is the drive efficiency

State of charge (SOC) is traditionally used to indicatethe residual electricity of the battery its definition is usuallywritten by the equation

SOCbat = SOC0minus 119896ch sdot 119896dis sdot int 120576 sdot

119868bat119889119905

119862bat (7)

where SOC0describes the initial value of SOCbat 119896ch and 119896dis

describe the influence coefficients on the current integrationfrom charging current (119868

119871lt 0) and discharging current

(119868119871gt 0) respectively if the battery is charging 119896dis = 1

and if the battery is discharging 119896ch = 1 119862bat describesthe nominal capacity of battery 120576 is the coulomb efficiency(including charging efficiency 120576ch and discharging efficiency120576dis)

Journal of Control Science and Engineering 5

PWMgeneratorController

Energymanagement

system

AVLemulator

Battery DCDC converter Supercapacitor Load

d

Ibat

UscUsc_ref

Iload

SOCbatSOCsc

Ibat_ref

Ibat

Ulbat

Rbat

Ubat

Lbat Cbus

Ibat1

Isc

Csc

Rsc

Ibus

Ubus

Figure 6 Control frame of the HESS

In order to indicate the residual electricity of supercapac-itor the state of charge (SOC) of the supercapacitor is usedto describe a percentage of the rated energy capacity whichdepends on the terminal output voltage and is defined as inthe equation

SOCSC =(119880LSC minus 119880119888min)

(119880119888max minus 119880119888min)

(8)

where 119880LSC is supercapacitor load voltage and 119880119888max and

119880119888min are the maximum and minimum terminal voltage

respectivelyThe proposed energy management system is a rule based

and power-balancing strategy The strategy is realized by aseries of simple control logical rules The main advantageof the proposed strategy is to protect battery from the highdynamics in current demand without overdischarging orovercharging the supercapacitor Consequently both batterylifetime and energy efficiency are increased

The flowchart of DCDC converter control mode strategyis shown in Figure 7 The control mode depends on thesymbol of the load current demandThe positive load currentrepresents the fact that the vehicle is driving In this situationbattery or supercapacitor must supply the requirement driv-ing current to meet vehicle driving demand Therefore theDCDC converter need be switched to buck mode Howeverthe DCDC control mode also depends on the charge anddischarge relationships between battery and supercapacitorEven if the load current is positive the DCDC converter isalso switched to boostmodewhen the supercapacitor chargesbattery In thisway the supercapacitor SOCcan be adjusted tothe expected variation range quickly and thus can ensure theHESS tomeet the load current demandwithout overcharge oroverdischarge of the battery As a result the battery operationcondition can be smoothed greatly and battery lifetime isincreased as well

SC charges battery

Battery charges SC

Buck mode

Yes Yes

No No

Boost modeBuck mode Buck mode Boost mode

lt0gt0

= 0

Sign (Idem)

Current Idem

Vehicle model

Driving cycle

Figure 7 Flowchart of the DCDC converter control mode strategy

The flowchart of driving mode control strategy is shownin Figure 8 This decision-making flowchart considers as thefirst decision a comparison of the real supercapacitor SOCand the preset supercapacitor SOC variation range If the realsupercapacitor SOC is located in the preset supercapacitorSOC variation range then the load current is distributed tosupercapacitor only and the battery will not supply any loadcurrentThe purpose of this arrangement is to protect batteryfrom the frequent charge and discharge process and increasebattery lifetime When the preset supercapacitor SOC vari-ation range is broken the battery is considered to balancethe supercapacitor SOC or share the load current In thissituation if the supercapacitor SOC exceeds its upper limitvalue then the load current is distributed to supercapacitoronly Besides the supercapacitor is charged by the batteryIn this way the supercapacitor SOC can be decreased to the

6 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

gt 0

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = IdemIbat = 0

SOCsc ⩾ SOCsc_max

Isc = IdemIbat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

= Idem times 120578dc= Idem times 120578dc

Isc = Ibatcharge times 120578dc

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

Sign (Idem)

IbatIbat

Figure 8 Flowchart of driving condition control mode

preset variation range quickly and thus guarantee the super-capacitor to work within the reasonable capacity fluctuationrange If the supercapacitor SOCdrops down to its lower limitvalue the battery is considered to share the load current toavoid the large drop of the supercapacitor SOC When thebattery SOC is bigger than its preset minimum value theload current is distributed to battery only At the same timethe supercapacitor is charged by the battery Otherwise thesupercapacitor cannot be charged by the battery It must benoted that the described rules abovemainly include five workmodes for the battery and supercapacitor the battery workonly the supercapacitor work only the battery charges tothe supercapacitor the supercapacitor charges to the batteryand the battery and supercapacitor working together In factwhen the supercapacitor exceeds the preset supercapacitorSOC variation range the load current is distributed to batteryand supercapacitor jointly In this process the charge is alsocarried out simultaneously

The flowchart of idle speed mode control strategy isshown in Figure 9 Generally the SOCof the supercapacitor iscontrolled within a certain reasonable fluctuation rangeThisis to ensure that electric vehicle is able to run even if a highacceleration or deceleration is required without overstressingthe battery Therefore the idle speed mode control strategyis only to ensure the supercapacitor SOC to be controlledwithin preset fluctuation range When the supercapacitorSOC is below the preset lower limit value the supercapacitoris charged by the battery On the contrary the supercapacitoris discharged Otherwise no operation is carried out

The flowchart of braking mode control strategy is shownin Figure 10 Similar to the driving mode control strategy thebattery current is firstly set to zero this is very important toprotect the battery frombig current burst during the transientprocess Then the only decision in this flowchart depends onthe SOC of the supercapacitor and on the preset variationrange When the supercapacitor SOC is below the presetlower limit value then the supercapacitor can absorb thecurrent from the regenerative breaking At the same time thelacking energy is supplied by the battery charge When thesupercapacitor SOC exceeds the preset higher limit value theregenerative breaking current is absorbed by battery At thesame time the part energy is delivered to battery from thesupercapacitor Otherwise the regenerative breaking currentis absorbed by the supercapacitor only

42 Controller The input variable of controller is the batteryreference current and the output variable is the controllercommand In order to realize control objective a classical PIcontroller is adopted in this research In this described config-uration the battery is connected to the DCDC converter butthe supercapacitor is directly connected to the bus withoutDCDC converter The current relations can be written by

119862bus sdot119889119880bus119889119905

= 119868bat1 + 119868SC minus 119868bus (9)

Journal of Control Science and Engineering 7

Yes

Yes

No

No

= 0

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = 0

Ibat = 0SOCsc ⩾ SOCsc_max

Isc = Ibatcharge times 120578dc Ibat = Isccharge times 120578dc

Sign (Idem)

Figure 9 Flowchart of idle speed condition control mode

The equivalentmodel of the DCDC converter connectedto the battery can be described as

119871bat119889119868bat119889119905

+ 119877bat119868bat = 119880119871bat minus 119889 sdot 119880bus (10)

Equation (10) is a nonlinear first-order equation by using theLaplace transform we can obtain that

119868bat (119904) =119880119871bat (119904)

119871bat sdot 119904 + 119877batminus

119889 (119904) 119880bus119871bat sdot 119904 + 119877bat

(11)

The control loop of the battery current is describedin Figure 11 The input is the DCDC converter controlcommand the output is the battery current In order tobalance the hybrid systemwithout overdischarging the super-capacitor a supercapacitor voltage compensation loop hasbeen implemented which is shown in Figure 12

5 Experimental Results and System Analysis

51 Experimental Results In order to validate the proposedenergy management control strategy a commercial exper-imental platform is constructed The whole experimentalplatform mainly includes two parts hardware power systemand software control system which are shown in Figures 13and 14

The supercapacitor pack adopted in this experimentalplatform is the MaxwellBCAP3000 type rated 3000 F 27 Vhaving the parameters given in Table 1 The battery packfor the HESS is ternary lithium battery which is consideredas the next generation battery used in electric vehicle Thespecific parameters of the battery pack are listed in Table 2The presented DCDC is a bidirectional DCDC converterby which both the driving current and the braking currentcan be controlled for the battery pack The main parameters

Table 1 Parameters of the supercapacitor pack

Items SpecificationsNominal voltage 240VNominal capacity 55 FNumber of cells 88Maximum continuous power 30 kW13 sPack mass 45 kg plusmn 5Maximum operating temperature +65∘CMinimum operating temperature minus40∘CMaximum storage temperature +70∘CMinimum storage temperature minus40∘CCommunication type CAN20B J1939Leakage current 53mASafe level IP65Vibration IEC 16750Lifetime 25∘C ge10 yearsInitial 48V module resistance 63mΩShock SAE J2464

of the DCDC converter are listed in Table 3 The ElectricControl Unit (ECU) is a dSPACE-based MicroAutoBox (DS1401) TwoCANcontrollers in theMicroAutoBox are adoptedfor the load current calculation and control algorithm calcu-lation respectively

The experiment was carried out to test the controlstrategy based on two driving cycles that is the USAUrban Dynamometer Driving Schedule (UDDS) and theNew European Driving Cycle (NEDC) Simulation resultsand comparisons between the batteries only power systemand the HESS system for UDDS driving cycle are shown inFigures 15ndash21

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

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International Journal of

Journal of Control Science and Engineering 5

PWMgeneratorController

Energymanagement

system

AVLemulator

Battery DCDC converter Supercapacitor Load

d

Ibat

UscUsc_ref

Iload

SOCbatSOCsc

Ibat_ref

Ibat

Ulbat

Rbat

Ubat

Lbat Cbus

Ibat1

Isc

Csc

Rsc

Ibus

Ubus

Figure 6 Control frame of the HESS

In order to indicate the residual electricity of supercapac-itor the state of charge (SOC) of the supercapacitor is usedto describe a percentage of the rated energy capacity whichdepends on the terminal output voltage and is defined as inthe equation

SOCSC =(119880LSC minus 119880119888min)

(119880119888max minus 119880119888min)

(8)

where 119880LSC is supercapacitor load voltage and 119880119888max and

119880119888min are the maximum and minimum terminal voltage

respectivelyThe proposed energy management system is a rule based

and power-balancing strategy The strategy is realized by aseries of simple control logical rules The main advantageof the proposed strategy is to protect battery from the highdynamics in current demand without overdischarging orovercharging the supercapacitor Consequently both batterylifetime and energy efficiency are increased

The flowchart of DCDC converter control mode strategyis shown in Figure 7 The control mode depends on thesymbol of the load current demandThe positive load currentrepresents the fact that the vehicle is driving In this situationbattery or supercapacitor must supply the requirement driv-ing current to meet vehicle driving demand Therefore theDCDC converter need be switched to buck mode Howeverthe DCDC control mode also depends on the charge anddischarge relationships between battery and supercapacitorEven if the load current is positive the DCDC converter isalso switched to boostmodewhen the supercapacitor chargesbattery In thisway the supercapacitor SOCcan be adjusted tothe expected variation range quickly and thus can ensure theHESS tomeet the load current demandwithout overcharge oroverdischarge of the battery As a result the battery operationcondition can be smoothed greatly and battery lifetime isincreased as well

SC charges battery

Battery charges SC

Buck mode

Yes Yes

No No

Boost modeBuck mode Buck mode Boost mode

lt0gt0

= 0

Sign (Idem)

Current Idem

Vehicle model

Driving cycle

Figure 7 Flowchart of the DCDC converter control mode strategy

The flowchart of driving mode control strategy is shownin Figure 8 This decision-making flowchart considers as thefirst decision a comparison of the real supercapacitor SOCand the preset supercapacitor SOC variation range If the realsupercapacitor SOC is located in the preset supercapacitorSOC variation range then the load current is distributed tosupercapacitor only and the battery will not supply any loadcurrentThe purpose of this arrangement is to protect batteryfrom the frequent charge and discharge process and increasebattery lifetime When the preset supercapacitor SOC vari-ation range is broken the battery is considered to balancethe supercapacitor SOC or share the load current In thissituation if the supercapacitor SOC exceeds its upper limitvalue then the load current is distributed to supercapacitoronly Besides the supercapacitor is charged by the batteryIn this way the supercapacitor SOC can be decreased to the

6 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

gt 0

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = IdemIbat = 0

SOCsc ⩾ SOCsc_max

Isc = IdemIbat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

= Idem times 120578dc= Idem times 120578dc

Isc = Ibatcharge times 120578dc

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

Sign (Idem)

IbatIbat

Figure 8 Flowchart of driving condition control mode

preset variation range quickly and thus guarantee the super-capacitor to work within the reasonable capacity fluctuationrange If the supercapacitor SOCdrops down to its lower limitvalue the battery is considered to share the load current toavoid the large drop of the supercapacitor SOC When thebattery SOC is bigger than its preset minimum value theload current is distributed to battery only At the same timethe supercapacitor is charged by the battery Otherwise thesupercapacitor cannot be charged by the battery It must benoted that the described rules abovemainly include five workmodes for the battery and supercapacitor the battery workonly the supercapacitor work only the battery charges tothe supercapacitor the supercapacitor charges to the batteryand the battery and supercapacitor working together In factwhen the supercapacitor exceeds the preset supercapacitorSOC variation range the load current is distributed to batteryand supercapacitor jointly In this process the charge is alsocarried out simultaneously

The flowchart of idle speed mode control strategy isshown in Figure 9 Generally the SOCof the supercapacitor iscontrolled within a certain reasonable fluctuation rangeThisis to ensure that electric vehicle is able to run even if a highacceleration or deceleration is required without overstressingthe battery Therefore the idle speed mode control strategyis only to ensure the supercapacitor SOC to be controlledwithin preset fluctuation range When the supercapacitorSOC is below the preset lower limit value the supercapacitoris charged by the battery On the contrary the supercapacitoris discharged Otherwise no operation is carried out

The flowchart of braking mode control strategy is shownin Figure 10 Similar to the driving mode control strategy thebattery current is firstly set to zero this is very important toprotect the battery frombig current burst during the transientprocess Then the only decision in this flowchart depends onthe SOC of the supercapacitor and on the preset variationrange When the supercapacitor SOC is below the presetlower limit value then the supercapacitor can absorb thecurrent from the regenerative breaking At the same time thelacking energy is supplied by the battery charge When thesupercapacitor SOC exceeds the preset higher limit value theregenerative breaking current is absorbed by battery At thesame time the part energy is delivered to battery from thesupercapacitor Otherwise the regenerative breaking currentis absorbed by the supercapacitor only

42 Controller The input variable of controller is the batteryreference current and the output variable is the controllercommand In order to realize control objective a classical PIcontroller is adopted in this research In this described config-uration the battery is connected to the DCDC converter butthe supercapacitor is directly connected to the bus withoutDCDC converter The current relations can be written by

119862bus sdot119889119880bus119889119905

= 119868bat1 + 119868SC minus 119868bus (9)

Journal of Control Science and Engineering 7

Yes

Yes

No

No

= 0

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = 0

Ibat = 0SOCsc ⩾ SOCsc_max

Isc = Ibatcharge times 120578dc Ibat = Isccharge times 120578dc

Sign (Idem)

Figure 9 Flowchart of idle speed condition control mode

The equivalentmodel of the DCDC converter connectedto the battery can be described as

119871bat119889119868bat119889119905

+ 119877bat119868bat = 119880119871bat minus 119889 sdot 119880bus (10)

Equation (10) is a nonlinear first-order equation by using theLaplace transform we can obtain that

119868bat (119904) =119880119871bat (119904)

119871bat sdot 119904 + 119877batminus

119889 (119904) 119880bus119871bat sdot 119904 + 119877bat

(11)

The control loop of the battery current is describedin Figure 11 The input is the DCDC converter controlcommand the output is the battery current In order tobalance the hybrid systemwithout overdischarging the super-capacitor a supercapacitor voltage compensation loop hasbeen implemented which is shown in Figure 12

5 Experimental Results and System Analysis

51 Experimental Results In order to validate the proposedenergy management control strategy a commercial exper-imental platform is constructed The whole experimentalplatform mainly includes two parts hardware power systemand software control system which are shown in Figures 13and 14

The supercapacitor pack adopted in this experimentalplatform is the MaxwellBCAP3000 type rated 3000 F 27 Vhaving the parameters given in Table 1 The battery packfor the HESS is ternary lithium battery which is consideredas the next generation battery used in electric vehicle Thespecific parameters of the battery pack are listed in Table 2The presented DCDC is a bidirectional DCDC converterby which both the driving current and the braking currentcan be controlled for the battery pack The main parameters

Table 1 Parameters of the supercapacitor pack

Items SpecificationsNominal voltage 240VNominal capacity 55 FNumber of cells 88Maximum continuous power 30 kW13 sPack mass 45 kg plusmn 5Maximum operating temperature +65∘CMinimum operating temperature minus40∘CMaximum storage temperature +70∘CMinimum storage temperature minus40∘CCommunication type CAN20B J1939Leakage current 53mASafe level IP65Vibration IEC 16750Lifetime 25∘C ge10 yearsInitial 48V module resistance 63mΩShock SAE J2464

of the DCDC converter are listed in Table 3 The ElectricControl Unit (ECU) is a dSPACE-based MicroAutoBox (DS1401) TwoCANcontrollers in theMicroAutoBox are adoptedfor the load current calculation and control algorithm calcu-lation respectively

The experiment was carried out to test the controlstrategy based on two driving cycles that is the USAUrban Dynamometer Driving Schedule (UDDS) and theNew European Driving Cycle (NEDC) Simulation resultsand comparisons between the batteries only power systemand the HESS system for UDDS driving cycle are shown inFigures 15ndash21

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

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RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

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Navigation and Observation

International Journal of

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DistributedSensor Networks

International Journal of

6 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

gt 0

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = IdemIbat = 0

SOCsc ⩾ SOCsc_max

Isc = IdemIbat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

= Idem times 120578dc= Idem times 120578dc

Isc = Ibatcharge times 120578dc

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

Sign (Idem)

IbatIbat

Figure 8 Flowchart of driving condition control mode

preset variation range quickly and thus guarantee the super-capacitor to work within the reasonable capacity fluctuationrange If the supercapacitor SOCdrops down to its lower limitvalue the battery is considered to share the load current toavoid the large drop of the supercapacitor SOC When thebattery SOC is bigger than its preset minimum value theload current is distributed to battery only At the same timethe supercapacitor is charged by the battery Otherwise thesupercapacitor cannot be charged by the battery It must benoted that the described rules abovemainly include five workmodes for the battery and supercapacitor the battery workonly the supercapacitor work only the battery charges tothe supercapacitor the supercapacitor charges to the batteryand the battery and supercapacitor working together In factwhen the supercapacitor exceeds the preset supercapacitorSOC variation range the load current is distributed to batteryand supercapacitor jointly In this process the charge is alsocarried out simultaneously

The flowchart of idle speed mode control strategy isshown in Figure 9 Generally the SOCof the supercapacitor iscontrolled within a certain reasonable fluctuation rangeThisis to ensure that electric vehicle is able to run even if a highacceleration or deceleration is required without overstressingthe battery Therefore the idle speed mode control strategyis only to ensure the supercapacitor SOC to be controlledwithin preset fluctuation range When the supercapacitorSOC is below the preset lower limit value the supercapacitoris charged by the battery On the contrary the supercapacitoris discharged Otherwise no operation is carried out

The flowchart of braking mode control strategy is shownin Figure 10 Similar to the driving mode control strategy thebattery current is firstly set to zero this is very important toprotect the battery frombig current burst during the transientprocess Then the only decision in this flowchart depends onthe SOC of the supercapacitor and on the preset variationrange When the supercapacitor SOC is below the presetlower limit value then the supercapacitor can absorb thecurrent from the regenerative breaking At the same time thelacking energy is supplied by the battery charge When thesupercapacitor SOC exceeds the preset higher limit value theregenerative breaking current is absorbed by battery At thesame time the part energy is delivered to battery from thesupercapacitor Otherwise the regenerative breaking currentis absorbed by the supercapacitor only

42 Controller The input variable of controller is the batteryreference current and the output variable is the controllercommand In order to realize control objective a classical PIcontroller is adopted in this research In this described config-uration the battery is connected to the DCDC converter butthe supercapacitor is directly connected to the bus withoutDCDC converter The current relations can be written by

119862bus sdot119889119880bus119889119905

= 119868bat1 + 119868SC minus 119868bus (9)

Journal of Control Science and Engineering 7

Yes

Yes

No

No

= 0

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = 0

Ibat = 0SOCsc ⩾ SOCsc_max

Isc = Ibatcharge times 120578dc Ibat = Isccharge times 120578dc

Sign (Idem)

Figure 9 Flowchart of idle speed condition control mode

The equivalentmodel of the DCDC converter connectedto the battery can be described as

119871bat119889119868bat119889119905

+ 119877bat119868bat = 119880119871bat minus 119889 sdot 119880bus (10)

Equation (10) is a nonlinear first-order equation by using theLaplace transform we can obtain that

119868bat (119904) =119880119871bat (119904)

119871bat sdot 119904 + 119877batminus

119889 (119904) 119880bus119871bat sdot 119904 + 119877bat

(11)

The control loop of the battery current is describedin Figure 11 The input is the DCDC converter controlcommand the output is the battery current In order tobalance the hybrid systemwithout overdischarging the super-capacitor a supercapacitor voltage compensation loop hasbeen implemented which is shown in Figure 12

5 Experimental Results and System Analysis

51 Experimental Results In order to validate the proposedenergy management control strategy a commercial exper-imental platform is constructed The whole experimentalplatform mainly includes two parts hardware power systemand software control system which are shown in Figures 13and 14

The supercapacitor pack adopted in this experimentalplatform is the MaxwellBCAP3000 type rated 3000 F 27 Vhaving the parameters given in Table 1 The battery packfor the HESS is ternary lithium battery which is consideredas the next generation battery used in electric vehicle Thespecific parameters of the battery pack are listed in Table 2The presented DCDC is a bidirectional DCDC converterby which both the driving current and the braking currentcan be controlled for the battery pack The main parameters

Table 1 Parameters of the supercapacitor pack

Items SpecificationsNominal voltage 240VNominal capacity 55 FNumber of cells 88Maximum continuous power 30 kW13 sPack mass 45 kg plusmn 5Maximum operating temperature +65∘CMinimum operating temperature minus40∘CMaximum storage temperature +70∘CMinimum storage temperature minus40∘CCommunication type CAN20B J1939Leakage current 53mASafe level IP65Vibration IEC 16750Lifetime 25∘C ge10 yearsInitial 48V module resistance 63mΩShock SAE J2464

of the DCDC converter are listed in Table 3 The ElectricControl Unit (ECU) is a dSPACE-based MicroAutoBox (DS1401) TwoCANcontrollers in theMicroAutoBox are adoptedfor the load current calculation and control algorithm calcu-lation respectively

The experiment was carried out to test the controlstrategy based on two driving cycles that is the USAUrban Dynamometer Driving Schedule (UDDS) and theNew European Driving Cycle (NEDC) Simulation resultsand comparisons between the batteries only power systemand the HESS system for UDDS driving cycle are shown inFigures 15ndash21

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Control Science and Engineering 7

Yes

Yes

No

No

= 0

SOCsc_min SOCsc_maxSOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = 0

Ibat = 0SOCsc ⩾ SOCsc_max

Isc = Ibatcharge times 120578dc Ibat = Isccharge times 120578dc

Sign (Idem)

Figure 9 Flowchart of idle speed condition control mode

The equivalentmodel of the DCDC converter connectedto the battery can be described as

119871bat119889119868bat119889119905

+ 119877bat119868bat = 119880119871bat minus 119889 sdot 119880bus (10)

Equation (10) is a nonlinear first-order equation by using theLaplace transform we can obtain that

119868bat (119904) =119880119871bat (119904)

119871bat sdot 119904 + 119877batminus

119889 (119904) 119880bus119871bat sdot 119904 + 119877bat

(11)

The control loop of the battery current is describedin Figure 11 The input is the DCDC converter controlcommand the output is the battery current In order tobalance the hybrid systemwithout overdischarging the super-capacitor a supercapacitor voltage compensation loop hasbeen implemented which is shown in Figure 12

5 Experimental Results and System Analysis

51 Experimental Results In order to validate the proposedenergy management control strategy a commercial exper-imental platform is constructed The whole experimentalplatform mainly includes two parts hardware power systemand software control system which are shown in Figures 13and 14

The supercapacitor pack adopted in this experimentalplatform is the MaxwellBCAP3000 type rated 3000 F 27 Vhaving the parameters given in Table 1 The battery packfor the HESS is ternary lithium battery which is consideredas the next generation battery used in electric vehicle Thespecific parameters of the battery pack are listed in Table 2The presented DCDC is a bidirectional DCDC converterby which both the driving current and the braking currentcan be controlled for the battery pack The main parameters

Table 1 Parameters of the supercapacitor pack

Items SpecificationsNominal voltage 240VNominal capacity 55 FNumber of cells 88Maximum continuous power 30 kW13 sPack mass 45 kg plusmn 5Maximum operating temperature +65∘CMinimum operating temperature minus40∘CMaximum storage temperature +70∘CMinimum storage temperature minus40∘CCommunication type CAN20B J1939Leakage current 53mASafe level IP65Vibration IEC 16750Lifetime 25∘C ge10 yearsInitial 48V module resistance 63mΩShock SAE J2464

of the DCDC converter are listed in Table 3 The ElectricControl Unit (ECU) is a dSPACE-based MicroAutoBox (DS1401) TwoCANcontrollers in theMicroAutoBox are adoptedfor the load current calculation and control algorithm calcu-lation respectively

The experiment was carried out to test the controlstrategy based on two driving cycles that is the USAUrban Dynamometer Driving Schedule (UDDS) and theNew European Driving Cycle (NEDC) Simulation resultsand comparisons between the batteries only power systemand the HESS system for UDDS driving cycle are shown inFigures 15ndash21

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

8 Journal of Control Science and Engineering

Yes

No

Yes

No

Yes

No

lt 0

SOCsc_min SOCsc_max

SOCbat_min SOCbat_max

SOCsc_min ⩽ SOCsc ⩽ SOCsc_max

Isc = Idem

Ibat = 0SOCsc ⩾ SOCsc_max

Ibat = Idem times 120578dc

Ibat = Isccharge times 120578dc

SOCbat ⩾ SOCbat_min

Isc = IdemIsc = Idem times 120578dc

Isc = Ibatcharge times 120578dc

Sign (Idem)

Figure 10 Flowchart of braking condition control mode

PI

PI controller Saturation DCDC converter

ΔIbatIbat_ref

Ibat

+

+minus

Figure 11 Battery current control loop

PI

PI controller Saturation

+minus

Usc_ref

Usc

ΔIbat

Figure 12 Supercapacitor voltage regulation loop

The charging and discharging currents of battery systemare compared in Figure 16 Since the supercapacitor pack canabsorb the regenerative braking energy quickly and supply aburst current demand thus the impact of big charging anddischarging current on the battery pack is avoided It canbe observed that the current of battery system for the HESSis mainly maintained in range from minus20A to 20A whichmeans that depth of discharge (DOD) of the battery packis less than 033 C which is beneficial to extending batterylifetime because the number of cycles to failure increasesexponentially as DOD decreases

Figure 13 Hardware power system

The evolutions of the battery voltage are compared inFigure 17 It can be obviously observed that large voltagedrop of the HESS can be avoided compared to that of thebattery only system namely a good voltage stabilizationperformance can be guaranteed for the battery system It canbe seen that the battery voltage of the HESS is maintainedwithin the range from 279V to 287V and the correspondingvoltage difference is 8V For the battery pack with 72 series

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

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Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Control Science and Engineering 9

Figure 14 Software control system

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

Time (s)

Velo

city

(km

h)

Figure 15 UDDS driving cycle

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 16 Comparison of the battery current curves

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 17 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140088

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 18 Comparison of the battery SOC curves

of battery cells a maximum 011 V voltage drop comparedwith a maximum 028V voltage drop for battery only systemis roughly estimated Therefore it is obvious that the batterysystem is operated in much smaller voltage fluctuation rangeand the potential battery cell balancing problem can beavoided to prevent individual cell voltages drift from time totime which leads to rapid decreases of the total pack capacityor even complete system failure

The comparison of the battery SOC is shown in Figure 18Since the supercapacitor pack absorbs the braking energyactively and efficiently and affords the additional peak powerto meet the vehicle driving power requirement the SOC ofthe battery pack is smoothed which can be better found inFigure 25 By comparison the benefit to electric vehicle rangeextension seems to be limited This is because more braking

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

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Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

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Electrical and Computer Engineering

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Advances inOptoElectronics

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Volume 2014

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SensorsJournal of

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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

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International Journal of

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Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

10 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 19 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 20 Supercapacitor current

0 200 400 600 800 1000 1200 140035

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 21 Supercapacitor SOC

Table 2 Parameters of the battery pack

Items SpecificationsNominal voltage 280VNominal capacity 60AhNumber of cells 74Maximum continuous power 30 kW13 sPack mass 280 kg plusmn 5Maximum charging temperature +45∘CMinimum charging temperature 0∘CMaximum discharging temperature +40∘CMinimum discharging temperature minus20∘CMaximum storage temperature +45∘CMinimum storage temperature minus20∘CLifetime 25∘C ge1500 timesCommunication type CAN20B J1939Charging time 15 hoursInitial 50V module resistance 20mΩShock SAE J2464

Table 3 Parameters of the DCDC converter

Items SpecificationsBoost voltage 200ndash400VBuck voltage 120ndash240VRated power 15 kWMaximum buck current 125AMaximum boost current 75AMaximum operating temperature +60∘CMinimum operating temperature minus20∘CMaximum storage temperature +70∘CMinimum storage temperature minus30∘CCommunication type CAN20B J1939Ripple coefficient le1

energy is absorbed by battery only system These operationsobviously decrease system efficiency and battery lifetime

The current of the supercapacitor pack is described inFigure 20 Because of the fast dynamics and high systemefficiency characteristic of the supercapacitor pack the highfrequency and peak current requirements are distributed tothe supercapacitor packThis can thus protect battery systemfrom the high dynamics in the loads and increase the batterypack lifetime and system efficiency

The SOC of the supercapacitor pack is described inFigure 21 It can be obviously observed that the developedcontrol strategy can successfully maintain supercapacitorSOCwithin suitable variation range and achieve its final value(60 is designed as the final value) Consequently the batterypackrsquos working condition can be greatly optimized benefitingfrom the more frequent and effective participation of thesupercapacitor in the load share operation Besides electricvehicle can be ensured to start a new cycle even if large loadsare required given that the supercapacitor pack has enoughenergy and space to satisfy loads

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Control Science and Engineering 11

0 200 400 600 800 1000 12000

5

10

15

20

25

30

35

Time (s)

Velo

city

(km

h)

Figure 22 NEDC driving cycles

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

Time (s)

Batte

ry cu

rren

t (A

)

Current of battery onlyCurrent of the HESS

Figure 23 Comparison of the battery current curves

Similar simulation was also carried out for the NEDCdriving cycle as shown in Figures 22ndash28 Again in this casethe advantages of the proposed energy management controlstrategy proved to be effective in achieving battery lifetimeand system efficiency

52 Efficiency Analysis of the Hybrid System In this subsec-tion the energy loss is analyzed to evaluate the effectivenessof the DCDC converter used in the HESS Since the energyefficiency has a big relevance with the resistances of thebattery and supercapacitor packs and the efficiency of theDCDC converter thus the resistance test for the batteryand supercapacitor packs and the efficiency of the DCDCconverter test are firstly carried outThe results are plotted inFigures 29ndash31

The energy loss comparisons of two semiactive topolog-ical structures described in Figures 3 and 4 and battery onlysystem for UDDS driving cycle are shown in Figure 32 It can

0 200 400 600 800 1000 1200 1400265

270

275

280

285

290

295

300

Time (s)

Batte

ry v

olta

ge (V

)

Voltage of battery onlyVoltage of the HESS

Figure 24 Comparison of the battery voltage curves

0 200 400 600 800 1000 1200 140087

88

89

90

91

92

93

94

95

Time (s)

Batte

ry S

OC

()

SOC of battery onlySOC of the HESS

Figure 25 Comparison of the battery SOC curves

be observed that the energy loss of the semiactive topologicalstructures described in Figure 4 is about 400 kJ and theenergy loss in the semiactive topological structures describedin Figure 3 is about 250 kJ Therefore the energy efficiencyof the semiactive topological structures described in Figure 3is higher than that of the semiactive topological structuresdescribed in Figure 4This is because the supercapacitor packis adjusted by theDCDC converter to satisfy the load currentfrequently consequently resulting in more energy loss fromthe DCDC converter Therefore the increased range largelydepends on the energy efficiency of the DCDC converterTo clarify the issue for future DCDC converter developmentin the HESS the energy losses of the components in twosemiactive topological structures are described in Figures 33and 34 It can be observed that the energy loss of the HESS is

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

12 Journal of Control Science and Engineering

0 200 400 600 800 1000 1200 14000

02

04

06

08

1

12

14

16

18

2

Time (s)

DC

cont

rol c

omm

and

Figure 26 DCDC converter control command

0 200 400 600 800 1000 1200 1400minus80

minus60

minus40

minus20

0

20

40

60

80

100

Time (s)

Supe

rcap

acito

r cur

rent

(A)

Figure 27 Supercapacitor current

0 200 400 600 800 1000 1200 140025

30

35

40

45

50

55

60

65

70

Time (s)

Supe

rcap

acito

r SO

C

Measured SOCReference SOC

Figure 28 Supercapacitor SOC

20 30 40 50 60 70 80 90 100Battery SOC ()

Resis

tanc

e (Ω

)

Discharge resistanceCharge resistance

0115

012

0125

013

0135

014

0145

015

0155

Figure 29 Chargingdischarging internal resistances of the batterypack

Discharge resistanceCharge resistance

10 20 30 40 50 60 70 80 90 100Supercapacitor SOC ()

Resis

tanc

e (Ω

)

0026

0027

0028

0029

003

0031

0032

0033

0034

0035

Figure 30 Chargingdischarging internal resistances of the super-capacitor pack

mainly from the energy loss of theDCDC converter Besidesthe energy loss of the battery only system is higher thanthe total energy loss of the battery and supercapacitor packin the HESS it is thus suggested that the efficiency of theDCDC converter needs to be increased to one certain limitvalue which can effectively compensate for the energy lossdifference between the HESS and the battery only systemSimilar results can be found in Figures 35ndash37 According tothe experiment results and theoretical analysis based on thedeveloped energy management strategy and the semiactivetopological structure described in Figure 3 the DCDCconverter at least has 97 conversion efficiency to make theHESS energy effective compared to the battery only system

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Control Science and Engineering 13

minus100 minus50 0 50 100Buck mode

Effici

ency

()

70

75

80

85

90

95

Current (A) Boost mode

Low voltage system =

Low voltage system =Low voltage system =

180V230V280V

Figure 31 Efficiency map of the DCDC converter

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0

50

100

150

200

250

300

350

400

Figure 32 Energy loss comparisons of two semiactive topologicalstructures and battery only system for UDDS driving cycle

53 Cost Analysis of the Hybrid System In this section thecost model of hybrid system is establishedThemodel mainlyconsists of battery life cost and system electricity cost

The battery life model is developed in order to analyze theimpact of terrain inaccuracy on battery life Since supercapac-itor has much longer life cycle compared to that of battery itis assumed that the supercapacitor has no degradation duringthe battery lifetime The model on battery capacity dynamicdegradation adopted in this research is a semiempirical lifemodel [33] The model includes four parameters namelytime temperature depth of charge and discharge rate The

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

350

400

Figure 33 Energy loss of the semiactive topological structuredescribed in Figure 4 for UDDS driving cycle

0 200 400 600 800 1000 1200 1400Time (s)

Ener

gy lo

ss (k

J)

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

0

50

100

150

200

250

300

Figure 34 Energy loss of the semiactive topological structuredescribed in Figure 3 for UDDS driving cycle

variations of these parameters will influence battery lifetimedirectly The formula of battery life model is given by

119876loss = 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (12)

where 119876loss is the battery capacity loss which ranges from 0to 1 119861 is the preexponential factor 119864

119886is the activation energy

(Jmolminus1)119877 is the gas constant (J (molminus1 k)minus1)119879 is the batteryabsolute temperature (K) 119860

ℎis the Ah-throughput which is

expressed as 119860ℎ 119911 is the power law factor 119862rate is the battery

discharge rate and 119861 is the compensation factor of 119862rate Theoriginal formula is developed based on LiFePO

4battery test

results For the consideration battery studied in this papera correction coefficient can be considered to predict battery

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

14 Journal of Control Science and Engineering

Supercapacitor + DC with batteryBattery + DC with supercapacitorBattery only

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Time (s)

Ener

gy lo

ss (k

J)

Figure 35 Energy loss comparisons of two semiactive topologicalstructures and battery only system for NEDC driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 36 Energy loss of the semiactive topological structuredescribed in Figure 4 for NEDC driving cycle

lifetime more accurately Then the formula can be rewrittenas

119876loss = 120573 sdot 119861 sdot 119890minus((119864119886+119861sdot119862rate)(119877sdot119879bat)) (119860

ℎ)119911 (13)

where 120573 is the correction coefficient 120573 = 17 times 10minus4 Otherparameters used in this formula are listed in Table 4The Ah-throughput 119860

ℎis defined as

119860ℎ=

1

3600int

119905119891

1199050

1003816100381610038161003816119868bat1003816100381610038161003816 119889119905 (14)

where 1199050is the initial time of a driving cycle and 119905

119891is the final

time of a driving cycle

Time (s)

Ener

gy lo

ss (k

J)

0 200 400 600 800 1000 1200 14000

50

100

150

200

250

Total energy lossDC energy loss

Supercapacitor energy lossBattery energy loss

Figure 37 Energy loss of the semiactive topological structuredescribed in Figure 3 for NEDC driving cycle

Table 4 Parameters of battery life model

Item Value119861 30330119864119886

31700119877 8314119861 3703119911 055

The problem of the battery life is formulated as batterylife cost The cost of energy storage system is assumed to be1600USDkWh for the battery system and 15000USDkWhfor the supercapacitor The electricity cost is assumed tobe 01 USDkWh according to the report of the US EnergyInformation Administration Since it is assumed that thesupercapacitor has no degradation during battery lifetimeonly battery degradation cost is considered in two hybridenergy storage systems with semiactive topology In generalbattery can hardly be used when its capacity is reduced to80 of its initial value Therefore the cost description of thebattery life and the electricity can be given by

Costbatloss (119905)

= 24768

times int

119905

0

1003816100381610038161003816119868bat1003816100381610038161003816

3600119889119905 expminus(

31700 minus 3703119862rate8314119879bat

)

Costele (119905) =01

3600int

119879

0

[119875SC (119905) + 119875bat (119905)]

(15)

Note that the electricity cost can be influenced by theresistance losses for both battery and supercapacitor andefficiency loss for the DCDC converter In this work theresistances of battery and supercapacitor and the efficiencyof DC converter are simplified as a fixed value Thus the total

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Control Science and Engineering 15

Time (s)

Batte

ry li

fe co

st (U

DS)

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

80

90

Figure 38 Comparison of the battery life cost based on UDDSdriving cycle

cost comprising battery life and electricity cost can be writtenas

Cost (119905) = Costlife (119905) + Costele (119905) (16)

The comparison results of the battery life cost and the sys-tem electricity cost based on UDDS driving cycle and NEDCdriving cycle are given in Figures 38ndash41 From Figure 38it has been demonstrated clearly that hybrid system has anabsolute advantage in improving battery life compared withthe battery only systemHowever the systemelectricity cost isincreased because of the energy loss of the supercapacitor andthe DCDC converter By comparison the battery life cost isobviously higher than the systemelectricity costTherefore topursue themaximumbenefit of the hybrid system the batterylife cost should be considered as the main factor in the totalcost In the future when the battery is very cheap the systemelectricity cost may be dominant in the total cost By thenan appropriate balance between the battery life cost and thesystem electricity cost need be considered From Figures 40and 41 similar conclusions can be obtained

6 Conclusion

In this paper a rule based energy management system isdeveloped for the battery and supercapacitor HESS Theobjective of the proposed system is to focus on exploiting thesupercapacitor characteristics and on increasing the batterylifetime and system efficiency Two controllers of the DCDCconverter are designed and integrated to achieve this purposeFirstly a current controller is designed to realize load currentdistribution between battery and supercapacitor Then avoltage controller is designed to ensure the supercapacitorSOC fluctuate within a preset reasonable variation range

Experiment results have shown that the system enablesthe battery to share the low frequency load current which

Battery only systemHybrid system

Time (s)

Elec

tric

ity co

st (U

DS)

0 200 400 600 800 1000 1200 14000

005

01

015

02

025

Figure 39 Comparison of the electricity cost based on UDDSdriving cycle

Battery only systemHybrid system

Time (s)

Batte

ry li

fe co

st (U

DS)

0 200 400 600 800 1000 1200 14000

10

20

30

40

50

60

70

Figure 40 Comparison of the battery life cost based on NEDCdriving cycle

would be very helpful to increase battery lifetime Corre-spondingly the high frequency load current is distributedto the supercapacitor pack Efficiency analysis has revealedthat the semiactive topological structure described in Figure 3has a higher energy efficiency compared with the semiactivetopological structure described in Figure 4 The increasedrange depends on the energy efficiency of the DCDCconverter largely Besides the DCDC converter at least has97 conversion efficiency to make the HESS energy effectivecompared to the battery only system The preliminary costanalysis of hybrid system has demonstrated that hybridsystem can increase battery lifetime obviously comparedwithbattery only system At the same time the analysis alsohighlights that an appropriate balance between the battery life

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

16 Journal of Control Science and Engineering

Battery only systemHybrid system

0 200 400 600 800 1000 1200 14000

001

002

003

004

005

006

007

Time (s)

Elec

tric

ity co

st (U

DS)

Figure 41 Comparison of the electricity cost based on NEDCdriving cycle

cost and the system electricity cost is necessary to pursue themaximum benefit of the hybrid system in the future

Competing Interests

The authors declare that there are no competing interestsregarding the publication of this paper

Acknowledgments

The authors wish to acknowledge the support of NationalScience Foundation of China under Grant U1564211

References

[1] S M Lukic J Cao R C Bansal F Rodriguez and A EmadildquoEnergy storage systems for automotive applicationsrdquo IEEETransactions on Industrial Electronics vol 55 no 6 pp 2258ndash2267 2008

[2] H-W He R Xiong and Y-H Chang ldquoDynamic modelingand simulation on a hybrid power system for electric vehicleapplicationsrdquo Energies vol 3 no 11 pp 1821ndash1830 2010

[3] R F Nelson ldquoPower requirements for batteries in hybridelectric vehiclesrdquo Journal of Power Sources vol 91 no 1 pp 2ndash26 2000

[4] K T Chau and C C Chan ldquoEmerging energy-efficient tech-nologies for hybrid electric vehiclesrdquo Proceedings of the IEEEvol 95 no 4 pp 821ndash835 2007

[5] H Rahimi-Eichi U Ojha F Baronti and M-Y Chow ldquoBatterymanagement system an overview of its application in the smartgrid and electric vehiclesrdquo IEEE Industrial ElectronicsMagazinevol 7 no 2 pp 4ndash16 2013

[6] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles state of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[7] S F Tie and C W Tan ldquoA review of energy sources andenergy management system in electric vehiclesrdquo Renewable andSustainable Energy Reviews vol 20 pp 82ndash102 2013

[8] G Ren G Ma and N Cong ldquoReview of electrical energystorage system for vehicular applicationsrdquo Renewable and Sus-tainable Energy Reviews vol 41 pp 225ndash236 2015

[9] S Pay andY Baghzouz ldquoEffectiveness of battery-supercapacitorcombination in electric vehiclesrdquo in Proceedings of the IEEEBologna PowerTech Conference pp 728ndash733 June 2003

[10] R M Schupbach and J C Balda ldquoThe role of ultracapacitorsin an energy storage unit for vehicle power managementrdquo inProceedings of the IEEEVehicle TechnologyConference pp 3236ndash3240 2003

[11] M Ortuzar J Moreno and J Dixon ldquoUltracapacitor-basedauxiliary energy system for an electric vehicle implementationand evaluationrdquo IEEETransactions on Industrial Electronics vol54 no 4 pp 2147ndash2156 2007

[12] G Guidi T M Undeland and Y Hori ldquoEffectiveness ofsupercapacitors as power-assist in pure EV using a sodium-nickel chloride battery as main energy storagerdquo in Proceedingsof the 24th International Battery Hybrid and Fuel Cell ElectricVehicle Symposium and Exhibition pp 2190ndash2198 May 2009

[13] L Gao R A Dougal and S Liu ldquoPower enhancement of anactively controlled batteryultracapacitor hybridrdquo IEEE Trans-actions on Power Electronics vol 20 no 1 pp 236ndash243 2005

[14] R Carter A Cruden and P J Hall ldquoOptimizing for efficiencyor battery life in a batterysupercapacitor electric vehiclerdquo IEEETransactions on Vehicular Technology vol 61 no 4 pp 1526ndash1533 2012

[15] P Ruetschi ldquoAging mechanisms and service life of lead-acidbatteriesrdquo Journal of Power Sources vol 127 no 1-2 pp 33ndash442004

[16] P Lailler F Zaninotto S Nivet et al ldquoStudy of the softening ofthe positive active-mass in valve-regulated lead-acid batteriesfor electric-vehicle applicationsrdquo Journal of Power Sources vol78 no 1 pp 204ndash213 1999

[17] NOmarMDaowdOHegazy P VD Bossche T Coosemansand J V Mierlo ldquoElectrical double-layer capacitors in hybridtopologiesmdashassessment and evaluation of their performancerdquoEnergies vol 5 no 11 pp 4533ndash4568 2012

[18] F Ju Q Zhang W Deng and J Li ldquoReview of structures andcontrol of battery-supercapacitor hybrid energy storage systemfor electric vehiclesrdquo in Proceedings of the IEEE InternationalConference on Automation Science and Engineering (CASE rsquo14)pp 143ndash148 IEEE Taipei Taiwan August 2014

[19] A Kuperman and I Aharon ldquoBattery-ultracapacitor hybridsfor pulsed current loads a reviewrdquo Renewable and SustainableEnergy Reviews vol 15 no 2 pp 981ndash992 2011

[20] O C Onar and A Khaligh ldquoA novel integrated magnetic struc-ture based DCDC converter for hybrid batteryultracapacitorenergy storage systemsrdquo IEEE Transactions on Smart Grid vol3 no 1 pp 296ndash307 2012

[21] A C Baisden and A Emadi ldquoADVISOR-based model of abattery and an ultra-capacitor energy source for hybrid electricvehiclesrdquo IEEETransactions onVehicular Technology vol 53 no1 pp 199ndash205 2004

[22] J P Trovao P G Pereirinha H M Jorge and C H AntunesldquoA multi-level energy management system for multi-sourceelectric vehiclesmdashan integrated rule-based meta-heuristicapproachrdquo Applied Energy vol 105 pp 304ndash318 2013

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Journal of Control Science and Engineering 17

[23] Z Chenghui S Qingsheng C Naxin and L Wuhua ldquoParticleswarm optimization for energy management fuzzy controllerdesign in dual-source electric vehiclerdquo inProceedings of the IEEE38thAnnual Power Electronics Specialists Conference (PESC rsquo07)pp 1405ndash1410 June 2007

[24] Y Ates O Erdinc M Uzunoglu and B Vural ldquoEnergymanagement of an FCUChybrid vehicular power system usinga combined neural network-wavelet transform based strategyrdquoInternational Journal of Hydrogen Energy vol 35 no 2 pp 774ndash783 2010

[25] M-E Choi S-W Kim and S-W Seo ldquoEnergy managementoptimization in a batterysupercapacitor hybrid energy storagesystemrdquo IEEE Transactions on Smart Grid vol 3 no 1 pp 463ndash472 2012

[26] B Hredzak V G Agelidis and M Jang ldquoA model predic-tive control system for a hybrid battery-ultracapacitor powersourcerdquo IEEE Transactions on Power Electronics vol 29 no 3pp 1469ndash1479 2014

[27] X Zhang C C Mi A Masrur and D Daniszewski ldquoWavelet-transform-based power management of hybrid vehicles withmultiple on-board energy sources including fuel cell batteryand ultracapacitorrdquo Journal of Power Sources vol 185 no 2 pp1533ndash1543 2008

[28] Y Kim T-K Lee and Z Filipi ldquoFrequency domain powerdistribution strategy for series hybrid electric vehiclesrdquo SAEInternational Journal of Alternative Powertrains vol 1 no 1 pp208ndash218 2012

[29] W Gao ldquoPerformance comparison of a fuel cell-battery hybridpowertrain and a fuel cell-ultracapacitor hybrid powertrainrdquoIEEE Transactions on Vehicular Technology vol 54 no 3 pp846ndash855 2005

[30] J P Zheng T R Jow and M S Ding ldquoHybrid power sourcesfor pulsed current applicationsrdquo IEEETransactions onAerospaceand Electronic Systems vol 37 no 1 pp 288ndash292 2001

[31] PThounthong and S Rael ldquoThe benefits of hybridizationrdquo IEEEIndustrial Electronics Magazine vol 6 pp 69ndash76 2008

[32] A Khaligh and Z Li ldquoBattery ultracapacitor fuel cell andhybrid energy storage systems for electric hybrid electric fuelcell and plug-in hybrid electric vehicles State of the artrdquo IEEETransactions on Vehicular Technology vol 59 no 6 pp 2806ndash2814 2010

[33] J Wang P Liu J Hicks-Garner et al ldquoCycle-life model forgraphite-LiFePO

4cellsrdquo Journal of Power Sources vol 196 no

8 pp 3942ndash3948 2011

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of