Hindawi Publishing CorporationThe Scientific World JournalVolume 2013 Article ID 815280 13 pageshttpdxdoiorg1011552013815280

Research ArticlePSO Based PI Controller Design for a Solar Charger System

Her-Terng Yau1 Chih-Jer Lin2 and Qin-Cheng Liang1

1 Department of Electrical Engineering National Chin-Yi University of Technology Taichung 41170 Taiwan2Graduate Institute of Automation and Technology National Taipei University of Technology Taipei 10608 Taiwan

Correspondence should be addressed to Her-Terng Yau pan1012ms52hinetnet

Received 2 March 2013 Accepted 11 April 2013

Academic Editors C-F Juang and J Zhang

Copyright copy 2013 Her-Terng Yau 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

Due to global energy crisis and severe environmental pollution the photovoltaic (PV) systemhas become one of themost importantrenewable energy sources Many previous studies on solar charger integrated system only focus on load charge control or switchingMaximum Power Point Tracking (MPPT) and charge control modes This study used two-stage system which allows the overallportable solar energy charging system to implement MPPT and optimal charge control of Li-ion battery simultaneously First thisstudy designs a DCDC boost converter of solar power generation which uses variable step size incremental conductance method(VSINC) to enable the solar cell to track the maximum power point at any time The voltage was exported from the DCDC boostconverter to the DCDC buck converter so that the voltage dropped to proper voltage for charging the batteryThe charging systemuses constant currentconstant voltage (CCCV) method to charge the lithium battery In order to obtain the optimum PI chargecontroller parameters this study used intelligent algorithm to determine the optimum parameters According to the simulationand experimental results the control parameters resulted from PSO have better performance than genetic algorithms (GAs)

1 Introduction

Effective utilization of solar energy is an important researchsubject of photovoltaic (PV) system at present and using theelectric energy generated by solar cell is the key The electricenergy generated by solar cell is very likely to be influencedby environmental factors such as irradiance conditions solarangle temperature variation and instability of output poweror shadow which would result in power loss of solar cell [1]

Therefore there must be an electric energy controllerwith good robustness and stability to ensure the effectiveutilization of solar energy in order for the overall solarpower supply system to generate maximum electric energyefficiently and maintain the balanced and stable control ofsystem [2]

Recharging of secondary battery efficiently is very impor-tant The chargers only charged batteries in the past and thecharging method and efficiency were not designed well sothat the excessive charging time or frequency often damagedbatteries and reduced the lifetime In order to improve the lifeor charging effect of secondary battery there must be a good

charge control design for battery so that the battery life can beprolonged and the charge efficiency can be increased [3ndash5]

Many studies of the charger of PV system use single-buckconverter to discuss the overall MPPT and charge controlsystem [6] The defect in using single-buck converter tocontrol the overall system is that one converter only controlsone system in order to achieve the MPPT of solar energyand to control the lithium battery charging there must be aswitchingmechanism to identify the control method selectedby the systemThis single-buck converter system is unable toimplement MPPT and charge control simultaneously Whenthis single-stage design is applied to MPPT the lithiumbattery load has not controlled the voltage and current andthe battery life may be reduced

This study designed a portable solar energy lithiumbattery charger on the principle of two-stage system Thefirst stage uses a DCDC boost converter which adopts thevariable step size incremental conductance (VSINC) methodto control the solar power system working at the maximumpower point [7ndash9] The second stage uses a DCDC buckconverter [10] which controls the charging system by battery

2 The Scientific World Journal

voltage and current feedback for the lithium battery so asto make the system attain constant voltage current andvoltage charge The PI controller based on optimal algorithmis designed to achieve the charge control of second stage[11 12] This two-stage system can achieve simultaneousMPPT of solar energy and lithium charge control The two-stage design not only controls the two-stage system but alsothere is a control system when the battery is being chargedthus prolonging the charge cycle of lithium battery Thisstudy used Simulink and Simpower of MATLAB simulationsoftware for simulation analysis of system In terms ofportable hardware the embedded PIC18F8720 microcontrolchip developed byMicrochipwas used to compose theMPPTalgorithm and battery charge controller The experimentalresults were compared with simulation result to prove theeffect of the proposed control theory

2 Solar Cell Characteristics

Solar cell is mainly made of PV wafers converts the lightenergy of solar irradiation into voltage and current directlyfor load and conducts electricity without electrolytic effectThe electric energy is obtained from the PN interface ofsemiconductor directly therefore the solar cell is also knownas PV cell [1 2]

Themathematical model of solar cells in series or parallelconnection can be simply expressed as

119868PV = 119868ph minus 119868sat (exp119902

119861119896119879119881PV minus 1) (1)

where 119868PV is output current of solar cell (A) 119881PV is outputvoltage of solar cell (V) 119868sat is reverse saturation current ofsolar cell 119868ph is current output of solar cell 119902 is quantity ofelectronic charge 119896 is boltzmann constant 119861 is ideal factor ofsolar cell and 119879 is solar cell surface temperature

The power-voltage and current-voltage curves of mathe-matical model corresponding to solar cell in different illumi-nations are shown in Figures 1 and 2

3 Maximum Power Point System Design

In application the MPPT algorithm is between the solar celland DCDC boost converter The solar cell output uses theduty cycle of direct control power converter to reduce thecomplexity of system [13]The process of MPPT algorithm ofthis modified VSINC method is shown in Figure 3 The stepsize of MPPT algorithm of traditional incremental conduc-tance is fixed If large step size control is adopted the solarcell can track themaximumpower point rapidly but the largestep size tracking can cause much oscillation in relativelysteady state This result will reduce the output efficiencyOn the contrary it tracks the maximum power point slowlyand the oscillation is very small in steady state Thereforethe step size fixed incremental conductance method mustmake choices between transient and steady state This studyused VSINC [14] which can track the maximum powerpoint rapidly in transient The steady-state oscillation is verysmall so that the tracking time can be shortened and it has

excellent efficiency as comparedwith traditional incrementalconductance method

The duty cycle of converter is modulated automaticallyIn the system of duty cycle of solar cell output power directcontrol converter119881(119905) and 119868(119905) are the voltage and current ofsolar cell output at time 119905 and119863(119905) and step are the variationof duty cycle and step size The design of variable step sizereduces the problems of slow tracking of small step size andlarge steady-state oscillation of large step size of traditionalincremental conductance method expressed as the followingequation [14]

119863(119905) = 119863 (119905 minus 1) plusmn step (2)

where step is the variable step size variation of duty cyclevariation and this variation can be expressed as

step = 119870 times

10038161003816100381610038161003816100381610038161003816

119889119875

119889119881

10038161003816100381610038161003816100381610038161003816

(3)

|119889119875||119889119881| is identification factor of step change of VSINCand the differentials of 119875 and 119881 are determined from thepower-voltage output characteristic curve of solar cell Thestep size is identified and119870 is the scaling factor of duty cycleTherefore (2) can be changed to the following equation

119863 (119905) = 119863 (119905 minus 1) plusmn 119870 times

10038161003816100381610038161003816100381610038161003816

119889119875

119889119881

10038161003816100381610038161003816100381610038161003816

= 119863 (119905 minus 1) plusmn 119870 times

10038161003816100381610038161003816100381610038161003816

119875 (119905) minus 119875 (119905 minus 1)

119881 (119905) minus 119881 (119905 minus 1)

10038161003816100381610038161003816100381610038161003816

(4)

Here the performance of MPPT depends on the scalingfactor 119870 and the tuning of this parameter depends on thesystemefficiencyTheoperation process of the algorithmusedin this paper is described below as follows

(1) The step size uses Δ119863max as initial tracking conditionso that the system tracks the maximum power pointrapidly

(2) The variable step size scaling condition of this Δ119863maxis evaluated in steady state here |119889119875||119889119881| is in theminimum value of maximum power point

(3) The variable step size feeds back update condition toensure the convergence here the variable step sizevariation must meet the following condition [14]

Δ119863max (119905) + 119870 times

10038161003816100381610038161003816100381610038161003816

119889119875

119889119881

10038161003816100381610038161003816100381610038161003816

lt Δ119863max (119905 minus 1) (5)

so the condition of scaling factor is

119870 ltΔ119863max (119905 minus 1)

[|119889119875119889119881| + Δ119863max (119905)] (6)

The solar energy MPPT controller in this paper can beimplemented by a DCDC boost converter and the system isshown in Figure 4 The MPPT controller is the VSINC

The Scientific World Journal 3

765432100

02

04

06

08

1

119868 PV

(A)

119881PV (V)

1kWm2

08 kWm2

06 kWm2

04 kWm2

Figure 1 Current-voltage characteristic curve diagram of solar cellunder varying irradiance

4

35

25

2

15

1

05

00 1 2 3 4 5 6 7

3

119875PV

(W)

119881PV (V)

1kWm2

08 kWm206 kWm2

04 kWm2

Figure 2 Power-voltage curve diagram of solar cell under varyingirradiance

4 Design of Charging System

The constant currentconstant voltage method is the mostpractical at present The charging process of this method isconsisted of two stages First the lithium battery is chargedwith constant current so as to shorten the charging timeWhen the battery voltage reaches the required set valueit is charged with constant voltage The charging currentdecreases gradually as the time extends and the charger is cutoff until the charging current decreases to about 0 [15ndash17]

The charging method used in this study connects aDCDC buck converter to the preceding stage output sothat the voltage and current of preceding stage maximum

power control the constant currentconstant voltage charge-upmethod for lithium batteryThe constant currentconstantvoltage architecture is that the fed back output voltage uses aPI controller to control the duty cycle for charging Since thePI controller can suppress high-frequency noise to improvethe system or eliminate steady-state error the battery outputachieves stable constant currentconstant voltage control

Take constant voltage as an example the charging systemuses state space averagingmethod to analyze the PI controllerand DCDC buck converter This method can linearize thenonlinear system equation of DCDC buck converter so as toestablish the transfer function of integrated charging systemFigure 5 shows the linearized closed loop control system ofcharging system

Figure 6 shows the on-off equivalent circuit of DCDCbuck converter and the input and output transfer functionsare deduced from this system

119866 (119904) =119900(119904)

(119904)=

119904119862 + 1

119871119862 (1199042 + (1119877119862) 119904 + (1119871119862)) (7)

Equation (7) can be expressed as

119866 (119904) =119900(119904)

(119904)=

119904119862 + 1

119871119862119877 (1199042 + (1119877119862) 119904 + (1119871119862))times 119881119894 (8)

where 119894119900is the output current

The transfer function of DCDC buck converter (7) iscombined with PI controller to deduce the loop circuittransfer function 119879(119904) of overall constant voltage chargingsystem

119879 (119904) =V119900(119904)

V119903(119904)

=119875119868 (119904) 119866 (119904)

1 + 119875119868 (119904) 119866 (119904)

=119896119875

1198711199042

+ (119896119875

119871119862+119896119868

119871) 119904 +

119896119868

119871119862

times (1199043

+ (1

119877119862+119896119875

119871) 1199042

+(119896119875

119871119862+119896119868

119871+

1

119871119862) +

119896119868

119871119862)

minus1

(9)

This transfer function 119879(119904) is substituted in the RLC parame-ter value of this system to obtain

119879 (119904) = 11988611198961198751199042

+ (5 times 107

119896119875+ 1198861119896119868) 119904 + 5 times 10

7

119896119868

times (1199043

+ (5 times 107

+ 1198861119896119875) 1199042

+ (5 times 107

119896119875+ 1198861119896119868+ 5 times 10

7

) 119904 + 5 times 107

119896119868)minus1

(10)

where 1198861= 250000

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (10)

119860 (119904) = 1199043

+ (5 times 107

+ 1198861119896119901) 1199042

+ (5 times 107

119896119901+ 1198861119896119894+ 5 times 10

7

) 119904 + 5 times 107

119896119868

(11)

4 The Scientific World Journal

Return

Start

Sample

No

Yes

Yes

Yes

Yes

Yes

No

No

No

No

Update 119881(119896 minus 1) = 119881(119896) 119868(119870 minus 1) = 119868(119896)

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1) 119863(119896) = 119863(119896 minus 1)

119889119868119889119881 gt minus119868119881 119889119868 gt 0

119889119868119889119881 = minus119868119881 119889119868 = 0

119889119881 = 0

119889119881 = 119881(119896) minus 119881(119896 minus 1) 119889119868 = 119868(119896) minus 119868(119896 minus 1)

119889119875 = 119881(119896) lowast 119868(119896) minus 119881(119896 minus 1) lowast 119868(119896 minus 1)

119881(119896) 119868(119896)

Figure 3 Flow chart of VSINC

PVpanel

DCDCboost

converterLoad

Duty cycle

MPPTcontroller

Figure 4 MPPT control system of solar cell

controller+

minus

DCDCbuck converter

PI (119904)PI119903(119904)

119903(119904)

119900(119904)

119900(119904)

(119904)

119866(119904) =119900(119904)

(119904)

Figure 5 Linearized closed loop control system

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896119868are greater than zero the poles

of this system are in the left half plane of s planemeaning thatthe PI controller can control the stability of this system

The transfer function of DCDC buck converter (12)is combined with PI controller to deduce the loop circuittransfer function 119879(119904) of overall constant-current chargingsystem

119879 (119904) =119900(119904)

119903(119904)

=119875119868 (119904) 119866 (119904)

1 + 119875119868 (119904) 119866 (119904)

=119896119875119881119894

1198711198771199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877) 119904 +

119896119868119881119894

119871119862119877

= (1199043

+ (1

119862119877+119896119875119881119894

119871119877) 1199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877+

1

119871119862) 119904 +

119896119868119881119894

119871119862119877)

minus1

(12)

where 119881119894is the input voltage of DCDC buck converter this

transfer function T(s) is substituted in the RLC parametervalue of this system to obtain

119879 (119904) =

11988621198961198751199042

+ (108

119896119875+ 1198862119896119868) 119904 + 10

8

119896119868

1199043 + (108 + 1198862119896119875) 1199042 + (108119896

119875+ 1198862119896119868+ 108) + 108119896

119868

(13)

where 1198862= 500000

The Scientific World Journal 5

119881119894

1198941198711198782 = 1 119871

1198782 = 0

119862

119868119900 119877+

minus

119881119900

Figure 6 DCDC buck converter

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (13)

119860 (119904) = 1199043

+ (108

+ 1198862119896119875) 1199042

+ (108

119896119875+ 1198862119896119868+ 108

) + 108

119896119868

(14)

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896

119868are greater than 0 the poles

of this system are in the left half plane of s plane meaningthat the PI controller can control the stability of this system

The PI controller used in the second-stage chargingsystem certainly can make the system achieve steady-stateresponse under its control this study focused on selecting the119896119875and 119896119868values of PI controller to make the charging system

implementing optimal constant voltage and constant cur-rentconstant voltage charge Therefore this study used theGenetic Algorithm (GA) and Particle Swarm Optimization(PSO) of optimization algorithm to search for and compare119896119875and 119896119868values [18ndash21]The system structure block is shown

in Figure 7

5 Simulation Result of Portable Solar EnergyCharging System

This study used Simulink of MATLAB simulation softwareto construct the mathematical model of overall systemincluding the boost converter of the first stage and the buckconverter of the second stage The duty cycle control inputof the first stage boost converter uses MPPT algorithm forinput voltage stabilization and output boost control of theboost converter connected to the solar cell The duty cyclecontrol input of the second-stage buck converter uses batteryfed back current and voltage for charge control so that thelithium battery can be charged stably Figure 8 shows theoverall simulation system of this study

51 MPPT Simulation Result The MPPT algorithm simu-lation in this study compares the VSINC method with thegeneral incremental conductance method (large step sizeand small step size) simulated in standard test conditions(1 KWm2 AM 15 25∘C) and varying irradiance condition(1 KWm2 and 800Wm2) The tracked maximum power ofthe solar cell used in this study is 35W when the irradianceis 1 KWm2 and the tracked maximum power is 27W whenthe irradiance is 800Wm2

Figure 9 compares the voltage current and power offixed step size incremental conductance method when the

controller

Optimizationalgorithm

DCDCbuck converter

119881119861

119881119903 119881119890+

minus

Li-ion battery

119880(119905)PI

Figure 7 Optimization algorithm system of DCDC buck con-verter

irradiance is changed from 800Wm2 to 1 KWm2 and to800Wm2 with that of the VSINC method As seen theVSINC method used in this study has better efficiencythan the traditional fixed step size incremental conductancemethod The maximum power point tracking time is muchshorter when the PV system is started up and the maximumpower point can be tracked faster than traditional fixed stepsize incremental conductance method when the irradiance ischangedAccording to the comparison of voltage and currentwhether the irradiance is increased or decreased the steady-state oscillation of trackingmaximum power of PV system bythe VSINC method is less than that by traditional fixed stepsize incremental conductance method

52 Simulation Result of Charge Control This charging sys-tem uses GA and PSO to search for 119896

119875and 119896

119868values of the

PI controller in the charging system and then uses constantvoltage and constant currentconstant voltage method tosimulate the charging systemThe lithium battery used in thispaper is 37 V 3000mAH and the battery saturation voltageis 42 V

The simulation system uses optimization evolutionmethod to find the 119896

119875and 119896119868values of feedback PI controller

and then they are substituted in the system for comparisonThe fitness function IAE design of this study will takeabsolute value integral from input-output error and uses themaximum value of each calculation process as the adaptivevalue This fitness function is expressed as follows

IAE = int

infin

0

|119890 (119905)| 119889119905 (15)

where 119890(119905) is the current under ideal control subtracting errorvalues of feedback output voltage and output current valuesfrom voltage

The algorithm adjusts the PI controller according to thefitness function of (15) so as to converge the steady-stateerror to 0 The voltage and current of the second-stagecharging system can be controlled stably and the systemimplements constant voltage and constant currentconstantvoltage charge

This study used a feedback voltage charging system tocontrol the constant voltage charge for saturation voltage42 V of lithium battery and used feedback current to controlthe constant current at 1 A to charge the batteryThe constant

6 The Scientific World Journal

To workspace4

To workspace2

To workspace3

119879 119879

119866

119866

Clock

Clock

Subsystem1

Clock1

Time

To workspace6 Boost

119875

To workspace1

119881

Buck

119881

119863

119889

To workspace7

119868

To workspace5

119875(I)

119868(I)

119881(I)

119863(I)

+minus

To workspace

119881119900(119868) 119881119900

119881119900

119889119881119900

119894119871

1198891199091

1199092

To workspace8

To workspace9

1198811199002

119894119871

1198632

pi control

119904119905

119881119903

Figure 8 Solar charger simulation system

voltage charge-up method and constant currentconstantvoltage charge-up method were discussed and comparedFigure 10 is the IAE convergence curve diagram of optimiza-tion algorithm for constant voltage charge As seen the GAcan search for the optimal solution rapidly and althoughthe convergence rate of PSO is lower than that of GA theconvergence value of PSOrsquos optimal solution is better thanGA

Figure 11 shows the simulation result of constant voltagecharge using PI controller The 119896

119875and 119896

119868values of PI

controller are adjusted by GA and PSO respectively As seenwhetherwe use PSOorGA the adjusted 119896

119875and 119896119868values of PI

controller can stabilize the power supplied from the first-stageconverter so as to supply electric energy soundly to charge thesecond-stage charging system effectively Moreover the PSOadjusted PI controller is better than GA the PSO adjustedconstant voltage PI controller can use the electric energygenerated by the first-stage PV system effectively and chargesthe battery faster than the GA adjusted constant voltage PIcontroller

Figure 12 shows the IAE convergence curve of optimiza-tion algorithm for constant currentconstant voltage chargeAs seen in constant-current charge the convergence rate ofGA is similar to that of PSO In this constant-current statethe convergence value of PSO is better than that of GA

Figure 13 shows the simulation result of constant cur-rentconstant voltage charge using PI controllerThe constantcurrentconstant voltage charge in this study switches thebattery to constant-current charge to obtain 418 V chargingvoltage and then switches to constant voltage charge Thecharging system uses GA and PSO to adjust the 119896

119875and 119896119868val-

ues of PI controller respectively In constant currentconstantvoltage charging whether we use PSO or GA the 119896

119875and 119896

119868

values of the adjusted PI controller canmake the second-stagecharging system charge effectively

The GA adjusted PI controller has not implementedconstant-current charge of system effectively so that thecharging time is prolonged whereas the PSO adjusted PIcontroller can implement accurate constant-current chargeof the secondary charging system In addition in the second-stage constant voltage charge any optimization algorithm cancharge the battery with 42 V constant voltage

The constant voltage charge is compared with constantcurrentconstant voltage charge according to the simulationresult Both the constant voltage charge and the constantcurrentconstant voltage charge can use preceding stage solarenergy output electric energy to charge battery effectivelyhowever the defect in constant voltage charge is that theinternal impedance of battery decreases gradually whenthe battery is charged up to a certain voltage so that thecharging current decreases gradually and the charging timeis prolonged relativelyThe constant currentconstant voltagecharge has solved this problem the constant-current chargeis implemented first so that the full charge time of battery isshortened Finally the constant voltage charge is used so thatthe battery will not be overcharged

6 Experimental Result of Portable SolarEnergy Charging System

For the implementation of controller this study used themicrocontrol chip PIC18F8720 developed by MicroChip tocomplete the overall portable design Figure 14(a) showsthe overall portable solar energy lithium battery chargingmodule Figure 14(b) shows the two-stage DCDC converterand lithium battery used in this paper Figure 14(c) shows themicrocontrol chip PIC18F8720 used in this paper

The MPPT of portable charging module and batterycharging system in this study are processed by PIC18F8720The program calculation process is shown in Figure 15

The Scientific World Journal 7

Irradiation step change

1k to 800Wm2 04 s800 to 1 kWm2 02 s

465V 485V 465V

6

5

4

3

2

1

00 005 01 015 02 025 03 035 04 045 05

119879 (s)

VSINCINC step = 0005INC step = 001

5251

54948

021 023 025 027

4746454443

041 043 045 047

119881PV

(V)

(a)

Irradiation step change

075

07

065

06

055

05

045

040 005 01 015 02 025 03 035 04 045 05

058A058A

072A

VSINCINC step = 0005INC step = 001

119879 (s)

07207

068066064

021 023 025 027

06106

059058

041 043 045 047

119868 PV

(A)

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(b)

Irradiation step change

35W27W

27W

VSINCINC step = 0005INC step = 001

119879 (s)

4

35

3

25

15

1

05

00

005 01 015 02 025 03 035 04 045 05

2

021 023 025 027

27227

268266264262

041 043 045 047

119875PV

(W)

35345

34335

33

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(c)

Figure 9 Comparison of best power point (a) voltage (b) current and (c) power in changed irradiance condition (800Wm2-1 KWm2-800Wm2)

As shown in the flow chart the AD buffer PWM enableand interrupt enable must be set at the beginning The ADbuffer keeps reading external signal which is the voltage andcurrent generated by the solar cell and the voltage and currentof lithium battery First the voltage and current values ofsolar cell generate PWM signal through MPPT algorithmto the DCDC boost converter The MPPT algorithm keepsidentifying whether the solar cell has tracked maximumpower point In addition the voltage and current valuesof lithium battery generate PWM signal via charge controlmethod to the DCDC buck converter The charge control

keeps identifyingwhether the battery has been charged under42 V stable voltage

61 Experimental Result of MPPT The experimental resultof MPPT algorithm is compared with simulation result Theresults of different methods are simulated in standard testconditions (1 KWm2 AM 15 25∘C) and changed irradiancecondition (1 KWm2 and 800Wm2)

The portable charging module in this study was inde-pendent PV system power supply and the precondition was

8 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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Submit your manuscripts athttpwwwhindawicom

VLSI Design

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Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Chemical EngineeringInternational Journal of Antennas and

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DistributedSensor Networks

International Journal of

2 The Scientific World Journal

voltage and current feedback for the lithium battery so asto make the system attain constant voltage current andvoltage charge The PI controller based on optimal algorithmis designed to achieve the charge control of second stage[11 12] This two-stage system can achieve simultaneousMPPT of solar energy and lithium charge control The two-stage design not only controls the two-stage system but alsothere is a control system when the battery is being chargedthus prolonging the charge cycle of lithium battery Thisstudy used Simulink and Simpower of MATLAB simulationsoftware for simulation analysis of system In terms ofportable hardware the embedded PIC18F8720 microcontrolchip developed byMicrochipwas used to compose theMPPTalgorithm and battery charge controller The experimentalresults were compared with simulation result to prove theeffect of the proposed control theory

2 Solar Cell Characteristics

Solar cell is mainly made of PV wafers converts the lightenergy of solar irradiation into voltage and current directlyfor load and conducts electricity without electrolytic effectThe electric energy is obtained from the PN interface ofsemiconductor directly therefore the solar cell is also knownas PV cell [1 2]

Themathematical model of solar cells in series or parallelconnection can be simply expressed as

119868PV = 119868ph minus 119868sat (exp119902

119861119896119879119881PV minus 1) (1)

where 119868PV is output current of solar cell (A) 119881PV is outputvoltage of solar cell (V) 119868sat is reverse saturation current ofsolar cell 119868ph is current output of solar cell 119902 is quantity ofelectronic charge 119896 is boltzmann constant 119861 is ideal factor ofsolar cell and 119879 is solar cell surface temperature

The power-voltage and current-voltage curves of mathe-matical model corresponding to solar cell in different illumi-nations are shown in Figures 1 and 2

3 Maximum Power Point System Design

In application the MPPT algorithm is between the solar celland DCDC boost converter The solar cell output uses theduty cycle of direct control power converter to reduce thecomplexity of system [13]The process of MPPT algorithm ofthis modified VSINC method is shown in Figure 3 The stepsize of MPPT algorithm of traditional incremental conduc-tance is fixed If large step size control is adopted the solarcell can track themaximumpower point rapidly but the largestep size tracking can cause much oscillation in relativelysteady state This result will reduce the output efficiencyOn the contrary it tracks the maximum power point slowlyand the oscillation is very small in steady state Thereforethe step size fixed incremental conductance method mustmake choices between transient and steady state This studyused VSINC [14] which can track the maximum powerpoint rapidly in transient The steady-state oscillation is verysmall so that the tracking time can be shortened and it has

excellent efficiency as comparedwith traditional incrementalconductance method

The duty cycle of converter is modulated automaticallyIn the system of duty cycle of solar cell output power directcontrol converter119881(119905) and 119868(119905) are the voltage and current ofsolar cell output at time 119905 and119863(119905) and step are the variationof duty cycle and step size The design of variable step sizereduces the problems of slow tracking of small step size andlarge steady-state oscillation of large step size of traditionalincremental conductance method expressed as the followingequation [14]

119863(119905) = 119863 (119905 minus 1) plusmn step (2)

where step is the variable step size variation of duty cyclevariation and this variation can be expressed as

step = 119870 times

10038161003816100381610038161003816100381610038161003816

119889119875

119889119881

10038161003816100381610038161003816100381610038161003816

(3)

|119889119875||119889119881| is identification factor of step change of VSINCand the differentials of 119875 and 119881 are determined from thepower-voltage output characteristic curve of solar cell Thestep size is identified and119870 is the scaling factor of duty cycleTherefore (2) can be changed to the following equation

119863 (119905) = 119863 (119905 minus 1) plusmn 119870 times

10038161003816100381610038161003816100381610038161003816

119889119875

119889119881

10038161003816100381610038161003816100381610038161003816

= 119863 (119905 minus 1) plusmn 119870 times

10038161003816100381610038161003816100381610038161003816

119875 (119905) minus 119875 (119905 minus 1)

119881 (119905) minus 119881 (119905 minus 1)

10038161003816100381610038161003816100381610038161003816

(4)

Here the performance of MPPT depends on the scalingfactor 119870 and the tuning of this parameter depends on thesystemefficiencyTheoperation process of the algorithmusedin this paper is described below as follows

(1) The step size uses Δ119863max as initial tracking conditionso that the system tracks the maximum power pointrapidly

(2) The variable step size scaling condition of this Δ119863maxis evaluated in steady state here |119889119875||119889119881| is in theminimum value of maximum power point

(3) The variable step size feeds back update condition toensure the convergence here the variable step sizevariation must meet the following condition [14]

Δ119863max (119905) + 119870 times

10038161003816100381610038161003816100381610038161003816

119889119875

119889119881

10038161003816100381610038161003816100381610038161003816

lt Δ119863max (119905 minus 1) (5)

so the condition of scaling factor is

119870 ltΔ119863max (119905 minus 1)

[|119889119875119889119881| + Δ119863max (119905)] (6)

The solar energy MPPT controller in this paper can beimplemented by a DCDC boost converter and the system isshown in Figure 4 The MPPT controller is the VSINC

The Scientific World Journal 3

765432100

02

04

06

08

1

119868 PV

(A)

119881PV (V)

1kWm2

08 kWm2

06 kWm2

04 kWm2

Figure 1 Current-voltage characteristic curve diagram of solar cellunder varying irradiance

4

35

25

2

15

1

05

00 1 2 3 4 5 6 7

3

119875PV

(W)

119881PV (V)

1kWm2

08 kWm206 kWm2

04 kWm2

Figure 2 Power-voltage curve diagram of solar cell under varyingirradiance

4 Design of Charging System

The constant currentconstant voltage method is the mostpractical at present The charging process of this method isconsisted of two stages First the lithium battery is chargedwith constant current so as to shorten the charging timeWhen the battery voltage reaches the required set valueit is charged with constant voltage The charging currentdecreases gradually as the time extends and the charger is cutoff until the charging current decreases to about 0 [15ndash17]

The charging method used in this study connects aDCDC buck converter to the preceding stage output sothat the voltage and current of preceding stage maximum

power control the constant currentconstant voltage charge-upmethod for lithium batteryThe constant currentconstantvoltage architecture is that the fed back output voltage uses aPI controller to control the duty cycle for charging Since thePI controller can suppress high-frequency noise to improvethe system or eliminate steady-state error the battery outputachieves stable constant currentconstant voltage control

Take constant voltage as an example the charging systemuses state space averagingmethod to analyze the PI controllerand DCDC buck converter This method can linearize thenonlinear system equation of DCDC buck converter so as toestablish the transfer function of integrated charging systemFigure 5 shows the linearized closed loop control system ofcharging system

Figure 6 shows the on-off equivalent circuit of DCDCbuck converter and the input and output transfer functionsare deduced from this system

119866 (119904) =119900(119904)

(119904)=

119904119862 + 1

119871119862 (1199042 + (1119877119862) 119904 + (1119871119862)) (7)

Equation (7) can be expressed as

119866 (119904) =119900(119904)

(119904)=

119904119862 + 1

119871119862119877 (1199042 + (1119877119862) 119904 + (1119871119862))times 119881119894 (8)

where 119894119900is the output current

The transfer function of DCDC buck converter (7) iscombined with PI controller to deduce the loop circuittransfer function 119879(119904) of overall constant voltage chargingsystem

119879 (119904) =V119900(119904)

V119903(119904)

=119875119868 (119904) 119866 (119904)

1 + 119875119868 (119904) 119866 (119904)

=119896119875

1198711199042

+ (119896119875

119871119862+119896119868

119871) 119904 +

119896119868

119871119862

times (1199043

+ (1

119877119862+119896119875

119871) 1199042

+(119896119875

119871119862+119896119868

119871+

1

119871119862) +

119896119868

119871119862)

minus1

(9)

This transfer function 119879(119904) is substituted in the RLC parame-ter value of this system to obtain

119879 (119904) = 11988611198961198751199042

+ (5 times 107

119896119875+ 1198861119896119868) 119904 + 5 times 10

7

119896119868

times (1199043

+ (5 times 107

+ 1198861119896119875) 1199042

+ (5 times 107

119896119875+ 1198861119896119868+ 5 times 10

7

) 119904 + 5 times 107

119896119868)minus1

(10)

where 1198861= 250000

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (10)

119860 (119904) = 1199043

+ (5 times 107

+ 1198861119896119901) 1199042

+ (5 times 107

119896119901+ 1198861119896119894+ 5 times 10

7

) 119904 + 5 times 107

119896119868

(11)

4 The Scientific World Journal

Return

Start

Sample

No

Yes

Yes

Yes

Yes

Yes

No

No

No

No

Update 119881(119896 minus 1) = 119881(119896) 119868(119870 minus 1) = 119868(119896)

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1) 119863(119896) = 119863(119896 minus 1)

119889119868119889119881 gt minus119868119881 119889119868 gt 0

119889119868119889119881 = minus119868119881 119889119868 = 0

119889119881 = 0

119889119881 = 119881(119896) minus 119881(119896 minus 1) 119889119868 = 119868(119896) minus 119868(119896 minus 1)

119889119875 = 119881(119896) lowast 119868(119896) minus 119881(119896 minus 1) lowast 119868(119896 minus 1)

119881(119896) 119868(119896)

Figure 3 Flow chart of VSINC

PVpanel

DCDCboost

converterLoad

Duty cycle

MPPTcontroller

Figure 4 MPPT control system of solar cell

controller+

minus

DCDCbuck converter

PI (119904)PI119903(119904)

119903(119904)

119900(119904)

119900(119904)

(119904)

119866(119904) =119900(119904)

(119904)

Figure 5 Linearized closed loop control system

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896119868are greater than zero the poles

of this system are in the left half plane of s planemeaning thatthe PI controller can control the stability of this system

The transfer function of DCDC buck converter (12)is combined with PI controller to deduce the loop circuittransfer function 119879(119904) of overall constant-current chargingsystem

119879 (119904) =119900(119904)

119903(119904)

=119875119868 (119904) 119866 (119904)

1 + 119875119868 (119904) 119866 (119904)

=119896119875119881119894

1198711198771199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877) 119904 +

119896119868119881119894

119871119862119877

= (1199043

+ (1

119862119877+119896119875119881119894

119871119877) 1199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877+

1

119871119862) 119904 +

119896119868119881119894

119871119862119877)

minus1

(12)

where 119881119894is the input voltage of DCDC buck converter this

transfer function T(s) is substituted in the RLC parametervalue of this system to obtain

119879 (119904) =

11988621198961198751199042

+ (108

119896119875+ 1198862119896119868) 119904 + 10

8

119896119868

1199043 + (108 + 1198862119896119875) 1199042 + (108119896

119875+ 1198862119896119868+ 108) + 108119896

119868

(13)

where 1198862= 500000

The Scientific World Journal 5

119881119894

1198941198711198782 = 1 119871

1198782 = 0

119862

119868119900 119877+

minus

119881119900

Figure 6 DCDC buck converter

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (13)

119860 (119904) = 1199043

+ (108

+ 1198862119896119875) 1199042

+ (108

119896119875+ 1198862119896119868+ 108

) + 108

119896119868

(14)

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896

119868are greater than 0 the poles

of this system are in the left half plane of s plane meaningthat the PI controller can control the stability of this system

The PI controller used in the second-stage chargingsystem certainly can make the system achieve steady-stateresponse under its control this study focused on selecting the119896119875and 119896119868values of PI controller to make the charging system

implementing optimal constant voltage and constant cur-rentconstant voltage charge Therefore this study used theGenetic Algorithm (GA) and Particle Swarm Optimization(PSO) of optimization algorithm to search for and compare119896119875and 119896119868values [18ndash21]The system structure block is shown

in Figure 7

5 Simulation Result of Portable Solar EnergyCharging System

This study used Simulink of MATLAB simulation softwareto construct the mathematical model of overall systemincluding the boost converter of the first stage and the buckconverter of the second stage The duty cycle control inputof the first stage boost converter uses MPPT algorithm forinput voltage stabilization and output boost control of theboost converter connected to the solar cell The duty cyclecontrol input of the second-stage buck converter uses batteryfed back current and voltage for charge control so that thelithium battery can be charged stably Figure 8 shows theoverall simulation system of this study

51 MPPT Simulation Result The MPPT algorithm simu-lation in this study compares the VSINC method with thegeneral incremental conductance method (large step sizeand small step size) simulated in standard test conditions(1 KWm2 AM 15 25∘C) and varying irradiance condition(1 KWm2 and 800Wm2) The tracked maximum power ofthe solar cell used in this study is 35W when the irradianceis 1 KWm2 and the tracked maximum power is 27W whenthe irradiance is 800Wm2

Figure 9 compares the voltage current and power offixed step size incremental conductance method when the

controller

Optimizationalgorithm

DCDCbuck converter

119881119861

119881119903 119881119890+

minus

Li-ion battery

119880(119905)PI

Figure 7 Optimization algorithm system of DCDC buck con-verter

irradiance is changed from 800Wm2 to 1 KWm2 and to800Wm2 with that of the VSINC method As seen theVSINC method used in this study has better efficiencythan the traditional fixed step size incremental conductancemethod The maximum power point tracking time is muchshorter when the PV system is started up and the maximumpower point can be tracked faster than traditional fixed stepsize incremental conductance method when the irradiance ischangedAccording to the comparison of voltage and currentwhether the irradiance is increased or decreased the steady-state oscillation of trackingmaximum power of PV system bythe VSINC method is less than that by traditional fixed stepsize incremental conductance method

52 Simulation Result of Charge Control This charging sys-tem uses GA and PSO to search for 119896

119875and 119896

119868values of the

PI controller in the charging system and then uses constantvoltage and constant currentconstant voltage method tosimulate the charging systemThe lithium battery used in thispaper is 37 V 3000mAH and the battery saturation voltageis 42 V

The simulation system uses optimization evolutionmethod to find the 119896

119875and 119896119868values of feedback PI controller

and then they are substituted in the system for comparisonThe fitness function IAE design of this study will takeabsolute value integral from input-output error and uses themaximum value of each calculation process as the adaptivevalue This fitness function is expressed as follows

IAE = int

infin

0

|119890 (119905)| 119889119905 (15)

where 119890(119905) is the current under ideal control subtracting errorvalues of feedback output voltage and output current valuesfrom voltage

The algorithm adjusts the PI controller according to thefitness function of (15) so as to converge the steady-stateerror to 0 The voltage and current of the second-stagecharging system can be controlled stably and the systemimplements constant voltage and constant currentconstantvoltage charge

This study used a feedback voltage charging system tocontrol the constant voltage charge for saturation voltage42 V of lithium battery and used feedback current to controlthe constant current at 1 A to charge the batteryThe constant

6 The Scientific World Journal

To workspace4

To workspace2

To workspace3

119879 119879

119866

119866

Clock

Clock

Subsystem1

Clock1

Time

To workspace6 Boost

119875

To workspace1

119881

Buck

119881

119863

119889

To workspace7

119868

To workspace5

119875(I)

119868(I)

119881(I)

119863(I)

+minus

To workspace

119881119900(119868) 119881119900

119881119900

119889119881119900

119894119871

1198891199091

1199092

To workspace8

To workspace9

1198811199002

119894119871

1198632

pi control

119904119905

119881119903

Figure 8 Solar charger simulation system

voltage charge-up method and constant currentconstantvoltage charge-up method were discussed and comparedFigure 10 is the IAE convergence curve diagram of optimiza-tion algorithm for constant voltage charge As seen the GAcan search for the optimal solution rapidly and althoughthe convergence rate of PSO is lower than that of GA theconvergence value of PSOrsquos optimal solution is better thanGA

Figure 11 shows the simulation result of constant voltagecharge using PI controller The 119896

119875and 119896

119868values of PI

controller are adjusted by GA and PSO respectively As seenwhetherwe use PSOorGA the adjusted 119896

119875and 119896119868values of PI

controller can stabilize the power supplied from the first-stageconverter so as to supply electric energy soundly to charge thesecond-stage charging system effectively Moreover the PSOadjusted PI controller is better than GA the PSO adjustedconstant voltage PI controller can use the electric energygenerated by the first-stage PV system effectively and chargesthe battery faster than the GA adjusted constant voltage PIcontroller

Figure 12 shows the IAE convergence curve of optimiza-tion algorithm for constant currentconstant voltage chargeAs seen in constant-current charge the convergence rate ofGA is similar to that of PSO In this constant-current statethe convergence value of PSO is better than that of GA

Figure 13 shows the simulation result of constant cur-rentconstant voltage charge using PI controllerThe constantcurrentconstant voltage charge in this study switches thebattery to constant-current charge to obtain 418 V chargingvoltage and then switches to constant voltage charge Thecharging system uses GA and PSO to adjust the 119896

119875and 119896119868val-

ues of PI controller respectively In constant currentconstantvoltage charging whether we use PSO or GA the 119896

119875and 119896

119868

values of the adjusted PI controller canmake the second-stagecharging system charge effectively

The GA adjusted PI controller has not implementedconstant-current charge of system effectively so that thecharging time is prolonged whereas the PSO adjusted PIcontroller can implement accurate constant-current chargeof the secondary charging system In addition in the second-stage constant voltage charge any optimization algorithm cancharge the battery with 42 V constant voltage

The constant voltage charge is compared with constantcurrentconstant voltage charge according to the simulationresult Both the constant voltage charge and the constantcurrentconstant voltage charge can use preceding stage solarenergy output electric energy to charge battery effectivelyhowever the defect in constant voltage charge is that theinternal impedance of battery decreases gradually whenthe battery is charged up to a certain voltage so that thecharging current decreases gradually and the charging timeis prolonged relativelyThe constant currentconstant voltagecharge has solved this problem the constant-current chargeis implemented first so that the full charge time of battery isshortened Finally the constant voltage charge is used so thatthe battery will not be overcharged

6 Experimental Result of Portable SolarEnergy Charging System

For the implementation of controller this study used themicrocontrol chip PIC18F8720 developed by MicroChip tocomplete the overall portable design Figure 14(a) showsthe overall portable solar energy lithium battery chargingmodule Figure 14(b) shows the two-stage DCDC converterand lithium battery used in this paper Figure 14(c) shows themicrocontrol chip PIC18F8720 used in this paper

The MPPT of portable charging module and batterycharging system in this study are processed by PIC18F8720The program calculation process is shown in Figure 15

The Scientific World Journal 7

Irradiation step change

1k to 800Wm2 04 s800 to 1 kWm2 02 s

465V 485V 465V

6

5

4

3

2

1

00 005 01 015 02 025 03 035 04 045 05

119879 (s)

VSINCINC step = 0005INC step = 001

5251

54948

021 023 025 027

4746454443

041 043 045 047

119881PV

(V)

(a)

Irradiation step change

075

07

065

06

055

05

045

040 005 01 015 02 025 03 035 04 045 05

058A058A

072A

VSINCINC step = 0005INC step = 001

119879 (s)

07207

068066064

021 023 025 027

06106

059058

041 043 045 047

119868 PV

(A)

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(b)

Irradiation step change

35W27W

27W

VSINCINC step = 0005INC step = 001

119879 (s)

4

35

3

25

15

1

05

00

005 01 015 02 025 03 035 04 045 05

2

021 023 025 027

27227

268266264262

041 043 045 047

119875PV

(W)

35345

34335

33

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(c)

Figure 9 Comparison of best power point (a) voltage (b) current and (c) power in changed irradiance condition (800Wm2-1 KWm2-800Wm2)

As shown in the flow chart the AD buffer PWM enableand interrupt enable must be set at the beginning The ADbuffer keeps reading external signal which is the voltage andcurrent generated by the solar cell and the voltage and currentof lithium battery First the voltage and current values ofsolar cell generate PWM signal through MPPT algorithmto the DCDC boost converter The MPPT algorithm keepsidentifying whether the solar cell has tracked maximumpower point In addition the voltage and current valuesof lithium battery generate PWM signal via charge controlmethod to the DCDC buck converter The charge control

keeps identifyingwhether the battery has been charged under42 V stable voltage

61 Experimental Result of MPPT The experimental resultof MPPT algorithm is compared with simulation result Theresults of different methods are simulated in standard testconditions (1 KWm2 AM 15 25∘C) and changed irradiancecondition (1 KWm2 and 800Wm2)

The portable charging module in this study was inde-pendent PV system power supply and the precondition was

8 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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Active and Passive Electronic Components

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RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Submit your manuscripts athttpwwwhindawicom

VLSI Design

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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

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Advances inOptoElectronics

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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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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

International Journal of

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DistributedSensor Networks

International Journal of

The Scientific World Journal 3

765432100

02

04

06

08

1

119868 PV

(A)

119881PV (V)

1kWm2

08 kWm2

06 kWm2

04 kWm2

Figure 1 Current-voltage characteristic curve diagram of solar cellunder varying irradiance

4

35

25

2

15

1

05

00 1 2 3 4 5 6 7

3

119875PV

(W)

119881PV (V)

1kWm2

08 kWm206 kWm2

04 kWm2

Figure 2 Power-voltage curve diagram of solar cell under varyingirradiance

4 Design of Charging System

The constant currentconstant voltage method is the mostpractical at present The charging process of this method isconsisted of two stages First the lithium battery is chargedwith constant current so as to shorten the charging timeWhen the battery voltage reaches the required set valueit is charged with constant voltage The charging currentdecreases gradually as the time extends and the charger is cutoff until the charging current decreases to about 0 [15ndash17]

The charging method used in this study connects aDCDC buck converter to the preceding stage output sothat the voltage and current of preceding stage maximum

power control the constant currentconstant voltage charge-upmethod for lithium batteryThe constant currentconstantvoltage architecture is that the fed back output voltage uses aPI controller to control the duty cycle for charging Since thePI controller can suppress high-frequency noise to improvethe system or eliminate steady-state error the battery outputachieves stable constant currentconstant voltage control

Take constant voltage as an example the charging systemuses state space averagingmethod to analyze the PI controllerand DCDC buck converter This method can linearize thenonlinear system equation of DCDC buck converter so as toestablish the transfer function of integrated charging systemFigure 5 shows the linearized closed loop control system ofcharging system

Figure 6 shows the on-off equivalent circuit of DCDCbuck converter and the input and output transfer functionsare deduced from this system

119866 (119904) =119900(119904)

(119904)=

119904119862 + 1

119871119862 (1199042 + (1119877119862) 119904 + (1119871119862)) (7)

Equation (7) can be expressed as

119866 (119904) =119900(119904)

(119904)=

119904119862 + 1

119871119862119877 (1199042 + (1119877119862) 119904 + (1119871119862))times 119881119894 (8)

where 119894119900is the output current

The transfer function of DCDC buck converter (7) iscombined with PI controller to deduce the loop circuittransfer function 119879(119904) of overall constant voltage chargingsystem

119879 (119904) =V119900(119904)

V119903(119904)

=119875119868 (119904) 119866 (119904)

1 + 119875119868 (119904) 119866 (119904)

=119896119875

1198711199042

+ (119896119875

119871119862+119896119868

119871) 119904 +

119896119868

119871119862

times (1199043

+ (1

119877119862+119896119875

119871) 1199042

+(119896119875

119871119862+119896119868

119871+

1

119871119862) +

119896119868

119871119862)

minus1

(9)

This transfer function 119879(119904) is substituted in the RLC parame-ter value of this system to obtain

119879 (119904) = 11988611198961198751199042

+ (5 times 107

119896119875+ 1198861119896119868) 119904 + 5 times 10

7

119896119868

times (1199043

+ (5 times 107

+ 1198861119896119875) 1199042

+ (5 times 107

119896119875+ 1198861119896119868+ 5 times 10

7

) 119904 + 5 times 107

119896119868)minus1

(10)

where 1198861= 250000

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (10)

119860 (119904) = 1199043

+ (5 times 107

+ 1198861119896119901) 1199042

+ (5 times 107

119896119901+ 1198861119896119894+ 5 times 10

7

) 119904 + 5 times 107

119896119868

(11)

4 The Scientific World Journal

Return

Start

Sample

No

Yes

Yes

Yes

Yes

Yes

No

No

No

No

Update 119881(119896 minus 1) = 119881(119896) 119868(119870 minus 1) = 119868(119896)

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1) 119863(119896) = 119863(119896 minus 1)

119889119868119889119881 gt minus119868119881 119889119868 gt 0

119889119868119889119881 = minus119868119881 119889119868 = 0

119889119881 = 0

119889119881 = 119881(119896) minus 119881(119896 minus 1) 119889119868 = 119868(119896) minus 119868(119896 minus 1)

119889119875 = 119881(119896) lowast 119868(119896) minus 119881(119896 minus 1) lowast 119868(119896 minus 1)

119881(119896) 119868(119896)

Figure 3 Flow chart of VSINC

PVpanel

DCDCboost

converterLoad

Duty cycle

MPPTcontroller

Figure 4 MPPT control system of solar cell

controller+

minus

DCDCbuck converter

PI (119904)PI119903(119904)

119903(119904)

119900(119904)

119900(119904)

(119904)

119866(119904) =119900(119904)

(119904)

Figure 5 Linearized closed loop control system

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896119868are greater than zero the poles

of this system are in the left half plane of s planemeaning thatthe PI controller can control the stability of this system

The transfer function of DCDC buck converter (12)is combined with PI controller to deduce the loop circuittransfer function 119879(119904) of overall constant-current chargingsystem

119879 (119904) =119900(119904)

119903(119904)

=119875119868 (119904) 119866 (119904)

1 + 119875119868 (119904) 119866 (119904)

=119896119875119881119894

1198711198771199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877) 119904 +

119896119868119881119894

119871119862119877

= (1199043

+ (1

119862119877+119896119875119881119894

119871119877) 1199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877+

1

119871119862) 119904 +

119896119868119881119894

119871119862119877)

minus1

(12)

where 119881119894is the input voltage of DCDC buck converter this

transfer function T(s) is substituted in the RLC parametervalue of this system to obtain

119879 (119904) =

11988621198961198751199042

+ (108

119896119875+ 1198862119896119868) 119904 + 10

8

119896119868

1199043 + (108 + 1198862119896119875) 1199042 + (108119896

119875+ 1198862119896119868+ 108) + 108119896

119868

(13)

where 1198862= 500000

The Scientific World Journal 5

119881119894

1198941198711198782 = 1 119871

1198782 = 0

119862

119868119900 119877+

minus

119881119900

Figure 6 DCDC buck converter

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (13)

119860 (119904) = 1199043

+ (108

+ 1198862119896119875) 1199042

+ (108

119896119875+ 1198862119896119868+ 108

) + 108

119896119868

(14)

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896

119868are greater than 0 the poles

of this system are in the left half plane of s plane meaningthat the PI controller can control the stability of this system

The PI controller used in the second-stage chargingsystem certainly can make the system achieve steady-stateresponse under its control this study focused on selecting the119896119875and 119896119868values of PI controller to make the charging system

implementing optimal constant voltage and constant cur-rentconstant voltage charge Therefore this study used theGenetic Algorithm (GA) and Particle Swarm Optimization(PSO) of optimization algorithm to search for and compare119896119875and 119896119868values [18ndash21]The system structure block is shown

in Figure 7

5 Simulation Result of Portable Solar EnergyCharging System

This study used Simulink of MATLAB simulation softwareto construct the mathematical model of overall systemincluding the boost converter of the first stage and the buckconverter of the second stage The duty cycle control inputof the first stage boost converter uses MPPT algorithm forinput voltage stabilization and output boost control of theboost converter connected to the solar cell The duty cyclecontrol input of the second-stage buck converter uses batteryfed back current and voltage for charge control so that thelithium battery can be charged stably Figure 8 shows theoverall simulation system of this study

51 MPPT Simulation Result The MPPT algorithm simu-lation in this study compares the VSINC method with thegeneral incremental conductance method (large step sizeand small step size) simulated in standard test conditions(1 KWm2 AM 15 25∘C) and varying irradiance condition(1 KWm2 and 800Wm2) The tracked maximum power ofthe solar cell used in this study is 35W when the irradianceis 1 KWm2 and the tracked maximum power is 27W whenthe irradiance is 800Wm2

Figure 9 compares the voltage current and power offixed step size incremental conductance method when the

controller

Optimizationalgorithm

DCDCbuck converter

119881119861

119881119903 119881119890+

minus

Li-ion battery

119880(119905)PI

Figure 7 Optimization algorithm system of DCDC buck con-verter

irradiance is changed from 800Wm2 to 1 KWm2 and to800Wm2 with that of the VSINC method As seen theVSINC method used in this study has better efficiencythan the traditional fixed step size incremental conductancemethod The maximum power point tracking time is muchshorter when the PV system is started up and the maximumpower point can be tracked faster than traditional fixed stepsize incremental conductance method when the irradiance ischangedAccording to the comparison of voltage and currentwhether the irradiance is increased or decreased the steady-state oscillation of trackingmaximum power of PV system bythe VSINC method is less than that by traditional fixed stepsize incremental conductance method

52 Simulation Result of Charge Control This charging sys-tem uses GA and PSO to search for 119896

119875and 119896

119868values of the

PI controller in the charging system and then uses constantvoltage and constant currentconstant voltage method tosimulate the charging systemThe lithium battery used in thispaper is 37 V 3000mAH and the battery saturation voltageis 42 V

The simulation system uses optimization evolutionmethod to find the 119896

119875and 119896119868values of feedback PI controller

and then they are substituted in the system for comparisonThe fitness function IAE design of this study will takeabsolute value integral from input-output error and uses themaximum value of each calculation process as the adaptivevalue This fitness function is expressed as follows

IAE = int

infin

0

|119890 (119905)| 119889119905 (15)

where 119890(119905) is the current under ideal control subtracting errorvalues of feedback output voltage and output current valuesfrom voltage

The algorithm adjusts the PI controller according to thefitness function of (15) so as to converge the steady-stateerror to 0 The voltage and current of the second-stagecharging system can be controlled stably and the systemimplements constant voltage and constant currentconstantvoltage charge

This study used a feedback voltage charging system tocontrol the constant voltage charge for saturation voltage42 V of lithium battery and used feedback current to controlthe constant current at 1 A to charge the batteryThe constant

6 The Scientific World Journal

To workspace4

To workspace2

To workspace3

119879 119879

119866

119866

Clock

Clock

Subsystem1

Clock1

Time

To workspace6 Boost

119875

To workspace1

119881

Buck

119881

119863

119889

To workspace7

119868

To workspace5

119875(I)

119868(I)

119881(I)

119863(I)

+minus

To workspace

119881119900(119868) 119881119900

119881119900

119889119881119900

119894119871

1198891199091

1199092

To workspace8

To workspace9

1198811199002

119894119871

1198632

pi control

119904119905

119881119903

Figure 8 Solar charger simulation system

voltage charge-up method and constant currentconstantvoltage charge-up method were discussed and comparedFigure 10 is the IAE convergence curve diagram of optimiza-tion algorithm for constant voltage charge As seen the GAcan search for the optimal solution rapidly and althoughthe convergence rate of PSO is lower than that of GA theconvergence value of PSOrsquos optimal solution is better thanGA

Figure 11 shows the simulation result of constant voltagecharge using PI controller The 119896

119875and 119896

119868values of PI

controller are adjusted by GA and PSO respectively As seenwhetherwe use PSOorGA the adjusted 119896

119875and 119896119868values of PI

controller can stabilize the power supplied from the first-stageconverter so as to supply electric energy soundly to charge thesecond-stage charging system effectively Moreover the PSOadjusted PI controller is better than GA the PSO adjustedconstant voltage PI controller can use the electric energygenerated by the first-stage PV system effectively and chargesthe battery faster than the GA adjusted constant voltage PIcontroller

Figure 12 shows the IAE convergence curve of optimiza-tion algorithm for constant currentconstant voltage chargeAs seen in constant-current charge the convergence rate ofGA is similar to that of PSO In this constant-current statethe convergence value of PSO is better than that of GA

Figure 13 shows the simulation result of constant cur-rentconstant voltage charge using PI controllerThe constantcurrentconstant voltage charge in this study switches thebattery to constant-current charge to obtain 418 V chargingvoltage and then switches to constant voltage charge Thecharging system uses GA and PSO to adjust the 119896

119875and 119896119868val-

ues of PI controller respectively In constant currentconstantvoltage charging whether we use PSO or GA the 119896

119875and 119896

119868

values of the adjusted PI controller canmake the second-stagecharging system charge effectively

The GA adjusted PI controller has not implementedconstant-current charge of system effectively so that thecharging time is prolonged whereas the PSO adjusted PIcontroller can implement accurate constant-current chargeof the secondary charging system In addition in the second-stage constant voltage charge any optimization algorithm cancharge the battery with 42 V constant voltage

The constant voltage charge is compared with constantcurrentconstant voltage charge according to the simulationresult Both the constant voltage charge and the constantcurrentconstant voltage charge can use preceding stage solarenergy output electric energy to charge battery effectivelyhowever the defect in constant voltage charge is that theinternal impedance of battery decreases gradually whenthe battery is charged up to a certain voltage so that thecharging current decreases gradually and the charging timeis prolonged relativelyThe constant currentconstant voltagecharge has solved this problem the constant-current chargeis implemented first so that the full charge time of battery isshortened Finally the constant voltage charge is used so thatthe battery will not be overcharged

6 Experimental Result of Portable SolarEnergy Charging System

For the implementation of controller this study used themicrocontrol chip PIC18F8720 developed by MicroChip tocomplete the overall portable design Figure 14(a) showsthe overall portable solar energy lithium battery chargingmodule Figure 14(b) shows the two-stage DCDC converterand lithium battery used in this paper Figure 14(c) shows themicrocontrol chip PIC18F8720 used in this paper

The MPPT of portable charging module and batterycharging system in this study are processed by PIC18F8720The program calculation process is shown in Figure 15

The Scientific World Journal 7

Irradiation step change

1k to 800Wm2 04 s800 to 1 kWm2 02 s

465V 485V 465V

6

5

4

3

2

1

00 005 01 015 02 025 03 035 04 045 05

119879 (s)

VSINCINC step = 0005INC step = 001

5251

54948

021 023 025 027

4746454443

041 043 045 047

119881PV

(V)

(a)

Irradiation step change

075

07

065

06

055

05

045

040 005 01 015 02 025 03 035 04 045 05

058A058A

072A

VSINCINC step = 0005INC step = 001

119879 (s)

07207

068066064

021 023 025 027

06106

059058

041 043 045 047

119868 PV

(A)

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(b)

Irradiation step change

35W27W

27W

VSINCINC step = 0005INC step = 001

119879 (s)

4

35

3

25

15

1

05

00

005 01 015 02 025 03 035 04 045 05

2

021 023 025 027

27227

268266264262

041 043 045 047

119875PV

(W)

35345

34335

33

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(c)

Figure 9 Comparison of best power point (a) voltage (b) current and (c) power in changed irradiance condition (800Wm2-1 KWm2-800Wm2)

As shown in the flow chart the AD buffer PWM enableand interrupt enable must be set at the beginning The ADbuffer keeps reading external signal which is the voltage andcurrent generated by the solar cell and the voltage and currentof lithium battery First the voltage and current values ofsolar cell generate PWM signal through MPPT algorithmto the DCDC boost converter The MPPT algorithm keepsidentifying whether the solar cell has tracked maximumpower point In addition the voltage and current valuesof lithium battery generate PWM signal via charge controlmethod to the DCDC buck converter The charge control

keeps identifyingwhether the battery has been charged under42 V stable voltage

61 Experimental Result of MPPT The experimental resultof MPPT algorithm is compared with simulation result Theresults of different methods are simulated in standard testconditions (1 KWm2 AM 15 25∘C) and changed irradiancecondition (1 KWm2 and 800Wm2)

The portable charging module in this study was inde-pendent PV system power supply and the precondition was

8 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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DistributedSensor Networks

International Journal of

4 The Scientific World Journal

Return

Start

Sample

No

Yes

Yes

Yes

Yes

Yes

No

No

No

No

Update 119881(119896 minus 1) = 119881(119896) 119868(119870 minus 1) = 119868(119896)

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)minus step

119863(119896) = 119863(119896 minus 1)+ step

119863(119896) = 119863(119896 minus 1) 119863(119896) = 119863(119896 minus 1)

119889119868119889119881 gt minus119868119881 119889119868 gt 0

119889119868119889119881 = minus119868119881 119889119868 = 0

119889119881 = 0

119889119881 = 119881(119896) minus 119881(119896 minus 1) 119889119868 = 119868(119896) minus 119868(119896 minus 1)

119889119875 = 119881(119896) lowast 119868(119896) minus 119881(119896 minus 1) lowast 119868(119896 minus 1)

119881(119896) 119868(119896)

Figure 3 Flow chart of VSINC

PVpanel

DCDCboost

converterLoad

Duty cycle

MPPTcontroller

Figure 4 MPPT control system of solar cell

controller+

minus

DCDCbuck converter

PI (119904)PI119903(119904)

119903(119904)

119900(119904)

119900(119904)

(119904)

119866(119904) =119900(119904)

(119904)

Figure 5 Linearized closed loop control system

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896119868are greater than zero the poles

of this system are in the left half plane of s planemeaning thatthe PI controller can control the stability of this system

The transfer function of DCDC buck converter (12)is combined with PI controller to deduce the loop circuittransfer function 119879(119904) of overall constant-current chargingsystem

119879 (119904) =119900(119904)

119903(119904)

=119875119868 (119904) 119866 (119904)

1 + 119875119868 (119904) 119866 (119904)

=119896119875119881119894

1198711198771199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877) 119904 +

119896119868119881119894

119871119862119877

= (1199043

+ (1

119862119877+119896119875119881119894

119871119877) 1199042

+ (119896119875119881119894

119871119862119877+119896119868119881119894

119871119877+

1

119871119862) 119904 +

119896119868119881119894

119871119862119877)

minus1

(12)

where 119881119894is the input voltage of DCDC buck converter this

transfer function T(s) is substituted in the RLC parametervalue of this system to obtain

119879 (119904) =

11988621198961198751199042

+ (108

119896119875+ 1198862119896119868) 119904 + 10

8

119896119868

1199043 + (108 + 1198862119896119875) 1199042 + (108119896

119875+ 1198862119896119868+ 108) + 108119896

119868

(13)

where 1198862= 500000

The Scientific World Journal 5

119881119894

1198941198711198782 = 1 119871

1198782 = 0

119862

119868119900 119877+

minus

119881119900

Figure 6 DCDC buck converter

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (13)

119860 (119904) = 1199043

+ (108

+ 1198862119896119875) 1199042

+ (108

119896119875+ 1198862119896119868+ 108

) + 108

119896119868

(14)

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896

119868are greater than 0 the poles

of this system are in the left half plane of s plane meaningthat the PI controller can control the stability of this system

The PI controller used in the second-stage chargingsystem certainly can make the system achieve steady-stateresponse under its control this study focused on selecting the119896119875and 119896119868values of PI controller to make the charging system

implementing optimal constant voltage and constant cur-rentconstant voltage charge Therefore this study used theGenetic Algorithm (GA) and Particle Swarm Optimization(PSO) of optimization algorithm to search for and compare119896119875and 119896119868values [18ndash21]The system structure block is shown

in Figure 7

5 Simulation Result of Portable Solar EnergyCharging System

This study used Simulink of MATLAB simulation softwareto construct the mathematical model of overall systemincluding the boost converter of the first stage and the buckconverter of the second stage The duty cycle control inputof the first stage boost converter uses MPPT algorithm forinput voltage stabilization and output boost control of theboost converter connected to the solar cell The duty cyclecontrol input of the second-stage buck converter uses batteryfed back current and voltage for charge control so that thelithium battery can be charged stably Figure 8 shows theoverall simulation system of this study

51 MPPT Simulation Result The MPPT algorithm simu-lation in this study compares the VSINC method with thegeneral incremental conductance method (large step sizeand small step size) simulated in standard test conditions(1 KWm2 AM 15 25∘C) and varying irradiance condition(1 KWm2 and 800Wm2) The tracked maximum power ofthe solar cell used in this study is 35W when the irradianceis 1 KWm2 and the tracked maximum power is 27W whenthe irradiance is 800Wm2

Figure 9 compares the voltage current and power offixed step size incremental conductance method when the

controller

Optimizationalgorithm

DCDCbuck converter

119881119861

119881119903 119881119890+

minus

Li-ion battery

119880(119905)PI

Figure 7 Optimization algorithm system of DCDC buck con-verter

irradiance is changed from 800Wm2 to 1 KWm2 and to800Wm2 with that of the VSINC method As seen theVSINC method used in this study has better efficiencythan the traditional fixed step size incremental conductancemethod The maximum power point tracking time is muchshorter when the PV system is started up and the maximumpower point can be tracked faster than traditional fixed stepsize incremental conductance method when the irradiance ischangedAccording to the comparison of voltage and currentwhether the irradiance is increased or decreased the steady-state oscillation of trackingmaximum power of PV system bythe VSINC method is less than that by traditional fixed stepsize incremental conductance method

52 Simulation Result of Charge Control This charging sys-tem uses GA and PSO to search for 119896

119875and 119896

119868values of the

PI controller in the charging system and then uses constantvoltage and constant currentconstant voltage method tosimulate the charging systemThe lithium battery used in thispaper is 37 V 3000mAH and the battery saturation voltageis 42 V

The simulation system uses optimization evolutionmethod to find the 119896

119875and 119896119868values of feedback PI controller

and then they are substituted in the system for comparisonThe fitness function IAE design of this study will takeabsolute value integral from input-output error and uses themaximum value of each calculation process as the adaptivevalue This fitness function is expressed as follows

IAE = int

infin

0

|119890 (119905)| 119889119905 (15)

where 119890(119905) is the current under ideal control subtracting errorvalues of feedback output voltage and output current valuesfrom voltage

The algorithm adjusts the PI controller according to thefitness function of (15) so as to converge the steady-stateerror to 0 The voltage and current of the second-stagecharging system can be controlled stably and the systemimplements constant voltage and constant currentconstantvoltage charge

This study used a feedback voltage charging system tocontrol the constant voltage charge for saturation voltage42 V of lithium battery and used feedback current to controlthe constant current at 1 A to charge the batteryThe constant

6 The Scientific World Journal

To workspace4

To workspace2

To workspace3

119879 119879

119866

119866

Clock

Clock

Subsystem1

Clock1

Time

To workspace6 Boost

119875

To workspace1

119881

Buck

119881

119863

119889

To workspace7

119868

To workspace5

119875(I)

119868(I)

119881(I)

119863(I)

+minus

To workspace

119881119900(119868) 119881119900

119881119900

119889119881119900

119894119871

1198891199091

1199092

To workspace8

To workspace9

1198811199002

119894119871

1198632

pi control

119904119905

119881119903

Figure 8 Solar charger simulation system

voltage charge-up method and constant currentconstantvoltage charge-up method were discussed and comparedFigure 10 is the IAE convergence curve diagram of optimiza-tion algorithm for constant voltage charge As seen the GAcan search for the optimal solution rapidly and althoughthe convergence rate of PSO is lower than that of GA theconvergence value of PSOrsquos optimal solution is better thanGA

Figure 11 shows the simulation result of constant voltagecharge using PI controller The 119896

119875and 119896

119868values of PI

controller are adjusted by GA and PSO respectively As seenwhetherwe use PSOorGA the adjusted 119896

119875and 119896119868values of PI

controller can stabilize the power supplied from the first-stageconverter so as to supply electric energy soundly to charge thesecond-stage charging system effectively Moreover the PSOadjusted PI controller is better than GA the PSO adjustedconstant voltage PI controller can use the electric energygenerated by the first-stage PV system effectively and chargesthe battery faster than the GA adjusted constant voltage PIcontroller

Figure 12 shows the IAE convergence curve of optimiza-tion algorithm for constant currentconstant voltage chargeAs seen in constant-current charge the convergence rate ofGA is similar to that of PSO In this constant-current statethe convergence value of PSO is better than that of GA

Figure 13 shows the simulation result of constant cur-rentconstant voltage charge using PI controllerThe constantcurrentconstant voltage charge in this study switches thebattery to constant-current charge to obtain 418 V chargingvoltage and then switches to constant voltage charge Thecharging system uses GA and PSO to adjust the 119896

119875and 119896119868val-

ues of PI controller respectively In constant currentconstantvoltage charging whether we use PSO or GA the 119896

119875and 119896

119868

values of the adjusted PI controller canmake the second-stagecharging system charge effectively

The GA adjusted PI controller has not implementedconstant-current charge of system effectively so that thecharging time is prolonged whereas the PSO adjusted PIcontroller can implement accurate constant-current chargeof the secondary charging system In addition in the second-stage constant voltage charge any optimization algorithm cancharge the battery with 42 V constant voltage

The constant voltage charge is compared with constantcurrentconstant voltage charge according to the simulationresult Both the constant voltage charge and the constantcurrentconstant voltage charge can use preceding stage solarenergy output electric energy to charge battery effectivelyhowever the defect in constant voltage charge is that theinternal impedance of battery decreases gradually whenthe battery is charged up to a certain voltage so that thecharging current decreases gradually and the charging timeis prolonged relativelyThe constant currentconstant voltagecharge has solved this problem the constant-current chargeis implemented first so that the full charge time of battery isshortened Finally the constant voltage charge is used so thatthe battery will not be overcharged

6 Experimental Result of Portable SolarEnergy Charging System

For the implementation of controller this study used themicrocontrol chip PIC18F8720 developed by MicroChip tocomplete the overall portable design Figure 14(a) showsthe overall portable solar energy lithium battery chargingmodule Figure 14(b) shows the two-stage DCDC converterand lithium battery used in this paper Figure 14(c) shows themicrocontrol chip PIC18F8720 used in this paper

The MPPT of portable charging module and batterycharging system in this study are processed by PIC18F8720The program calculation process is shown in Figure 15

The Scientific World Journal 7

Irradiation step change

1k to 800Wm2 04 s800 to 1 kWm2 02 s

465V 485V 465V

6

5

4

3

2

1

00 005 01 015 02 025 03 035 04 045 05

119879 (s)

VSINCINC step = 0005INC step = 001

5251

54948

021 023 025 027

4746454443

041 043 045 047

119881PV

(V)

(a)

Irradiation step change

075

07

065

06

055

05

045

040 005 01 015 02 025 03 035 04 045 05

058A058A

072A

VSINCINC step = 0005INC step = 001

119879 (s)

07207

068066064

021 023 025 027

06106

059058

041 043 045 047

119868 PV

(A)

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(b)

Irradiation step change

35W27W

27W

VSINCINC step = 0005INC step = 001

119879 (s)

4

35

3

25

15

1

05

00

005 01 015 02 025 03 035 04 045 05

2

021 023 025 027

27227

268266264262

041 043 045 047

119875PV

(W)

35345

34335

33

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(c)

Figure 9 Comparison of best power point (a) voltage (b) current and (c) power in changed irradiance condition (800Wm2-1 KWm2-800Wm2)

As shown in the flow chart the AD buffer PWM enableand interrupt enable must be set at the beginning The ADbuffer keeps reading external signal which is the voltage andcurrent generated by the solar cell and the voltage and currentof lithium battery First the voltage and current values ofsolar cell generate PWM signal through MPPT algorithmto the DCDC boost converter The MPPT algorithm keepsidentifying whether the solar cell has tracked maximumpower point In addition the voltage and current valuesof lithium battery generate PWM signal via charge controlmethod to the DCDC buck converter The charge control

keeps identifyingwhether the battery has been charged under42 V stable voltage

61 Experimental Result of MPPT The experimental resultof MPPT algorithm is compared with simulation result Theresults of different methods are simulated in standard testconditions (1 KWm2 AM 15 25∘C) and changed irradiancecondition (1 KWm2 and 800Wm2)

The portable charging module in this study was inde-pendent PV system power supply and the precondition was

8 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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International Journal of

The Scientific World Journal 5

119881119894

1198941198711198782 = 1 119871

1198782 = 0

119862

119868119900 119877+

minus

119881119900

Figure 6 DCDC buck converter

This system is loop circuit transfer function where 119860(119904)is the characteristic equation as (13)

119860 (119904) = 1199043

+ (108

+ 1198862119896119875) 1199042

+ (108

119896119875+ 1198862119896119868+ 108

) + 108

119896119868

(14)

The result of the characteristic equation calculated byRouth table is that if 119896

119875and 119896

119868are greater than 0 the poles

of this system are in the left half plane of s plane meaningthat the PI controller can control the stability of this system

The PI controller used in the second-stage chargingsystem certainly can make the system achieve steady-stateresponse under its control this study focused on selecting the119896119875and 119896119868values of PI controller to make the charging system

implementing optimal constant voltage and constant cur-rentconstant voltage charge Therefore this study used theGenetic Algorithm (GA) and Particle Swarm Optimization(PSO) of optimization algorithm to search for and compare119896119875and 119896119868values [18ndash21]The system structure block is shown

in Figure 7

5 Simulation Result of Portable Solar EnergyCharging System

This study used Simulink of MATLAB simulation softwareto construct the mathematical model of overall systemincluding the boost converter of the first stage and the buckconverter of the second stage The duty cycle control inputof the first stage boost converter uses MPPT algorithm forinput voltage stabilization and output boost control of theboost converter connected to the solar cell The duty cyclecontrol input of the second-stage buck converter uses batteryfed back current and voltage for charge control so that thelithium battery can be charged stably Figure 8 shows theoverall simulation system of this study

51 MPPT Simulation Result The MPPT algorithm simu-lation in this study compares the VSINC method with thegeneral incremental conductance method (large step sizeand small step size) simulated in standard test conditions(1 KWm2 AM 15 25∘C) and varying irradiance condition(1 KWm2 and 800Wm2) The tracked maximum power ofthe solar cell used in this study is 35W when the irradianceis 1 KWm2 and the tracked maximum power is 27W whenthe irradiance is 800Wm2

Figure 9 compares the voltage current and power offixed step size incremental conductance method when the

controller

Optimizationalgorithm

DCDCbuck converter

119881119861

119881119903 119881119890+

minus

Li-ion battery

119880(119905)PI

Figure 7 Optimization algorithm system of DCDC buck con-verter

irradiance is changed from 800Wm2 to 1 KWm2 and to800Wm2 with that of the VSINC method As seen theVSINC method used in this study has better efficiencythan the traditional fixed step size incremental conductancemethod The maximum power point tracking time is muchshorter when the PV system is started up and the maximumpower point can be tracked faster than traditional fixed stepsize incremental conductance method when the irradiance ischangedAccording to the comparison of voltage and currentwhether the irradiance is increased or decreased the steady-state oscillation of trackingmaximum power of PV system bythe VSINC method is less than that by traditional fixed stepsize incremental conductance method

52 Simulation Result of Charge Control This charging sys-tem uses GA and PSO to search for 119896

119875and 119896

119868values of the

PI controller in the charging system and then uses constantvoltage and constant currentconstant voltage method tosimulate the charging systemThe lithium battery used in thispaper is 37 V 3000mAH and the battery saturation voltageis 42 V

The simulation system uses optimization evolutionmethod to find the 119896

119875and 119896119868values of feedback PI controller

and then they are substituted in the system for comparisonThe fitness function IAE design of this study will takeabsolute value integral from input-output error and uses themaximum value of each calculation process as the adaptivevalue This fitness function is expressed as follows

IAE = int

infin

0

|119890 (119905)| 119889119905 (15)

where 119890(119905) is the current under ideal control subtracting errorvalues of feedback output voltage and output current valuesfrom voltage

The algorithm adjusts the PI controller according to thefitness function of (15) so as to converge the steady-stateerror to 0 The voltage and current of the second-stagecharging system can be controlled stably and the systemimplements constant voltage and constant currentconstantvoltage charge

This study used a feedback voltage charging system tocontrol the constant voltage charge for saturation voltage42 V of lithium battery and used feedback current to controlthe constant current at 1 A to charge the batteryThe constant

6 The Scientific World Journal

To workspace4

To workspace2

To workspace3

119879 119879

119866

119866

Clock

Clock

Subsystem1

Clock1

Time

To workspace6 Boost

119875

To workspace1

119881

Buck

119881

119863

119889

To workspace7

119868

To workspace5

119875(I)

119868(I)

119881(I)

119863(I)

+minus

To workspace

119881119900(119868) 119881119900

119881119900

119889119881119900

119894119871

1198891199091

1199092

To workspace8

To workspace9

1198811199002

119894119871

1198632

pi control

119904119905

119881119903

Figure 8 Solar charger simulation system

voltage charge-up method and constant currentconstantvoltage charge-up method were discussed and comparedFigure 10 is the IAE convergence curve diagram of optimiza-tion algorithm for constant voltage charge As seen the GAcan search for the optimal solution rapidly and althoughthe convergence rate of PSO is lower than that of GA theconvergence value of PSOrsquos optimal solution is better thanGA

Figure 11 shows the simulation result of constant voltagecharge using PI controller The 119896

119875and 119896

119868values of PI

controller are adjusted by GA and PSO respectively As seenwhetherwe use PSOorGA the adjusted 119896

119875and 119896119868values of PI

controller can stabilize the power supplied from the first-stageconverter so as to supply electric energy soundly to charge thesecond-stage charging system effectively Moreover the PSOadjusted PI controller is better than GA the PSO adjustedconstant voltage PI controller can use the electric energygenerated by the first-stage PV system effectively and chargesthe battery faster than the GA adjusted constant voltage PIcontroller

Figure 12 shows the IAE convergence curve of optimiza-tion algorithm for constant currentconstant voltage chargeAs seen in constant-current charge the convergence rate ofGA is similar to that of PSO In this constant-current statethe convergence value of PSO is better than that of GA

Figure 13 shows the simulation result of constant cur-rentconstant voltage charge using PI controllerThe constantcurrentconstant voltage charge in this study switches thebattery to constant-current charge to obtain 418 V chargingvoltage and then switches to constant voltage charge Thecharging system uses GA and PSO to adjust the 119896

119875and 119896119868val-

ues of PI controller respectively In constant currentconstantvoltage charging whether we use PSO or GA the 119896

119875and 119896

119868

values of the adjusted PI controller canmake the second-stagecharging system charge effectively

The GA adjusted PI controller has not implementedconstant-current charge of system effectively so that thecharging time is prolonged whereas the PSO adjusted PIcontroller can implement accurate constant-current chargeof the secondary charging system In addition in the second-stage constant voltage charge any optimization algorithm cancharge the battery with 42 V constant voltage

The constant voltage charge is compared with constantcurrentconstant voltage charge according to the simulationresult Both the constant voltage charge and the constantcurrentconstant voltage charge can use preceding stage solarenergy output electric energy to charge battery effectivelyhowever the defect in constant voltage charge is that theinternal impedance of battery decreases gradually whenthe battery is charged up to a certain voltage so that thecharging current decreases gradually and the charging timeis prolonged relativelyThe constant currentconstant voltagecharge has solved this problem the constant-current chargeis implemented first so that the full charge time of battery isshortened Finally the constant voltage charge is used so thatthe battery will not be overcharged

6 Experimental Result of Portable SolarEnergy Charging System

For the implementation of controller this study used themicrocontrol chip PIC18F8720 developed by MicroChip tocomplete the overall portable design Figure 14(a) showsthe overall portable solar energy lithium battery chargingmodule Figure 14(b) shows the two-stage DCDC converterand lithium battery used in this paper Figure 14(c) shows themicrocontrol chip PIC18F8720 used in this paper

The MPPT of portable charging module and batterycharging system in this study are processed by PIC18F8720The program calculation process is shown in Figure 15

The Scientific World Journal 7

Irradiation step change

1k to 800Wm2 04 s800 to 1 kWm2 02 s

465V 485V 465V

6

5

4

3

2

1

00 005 01 015 02 025 03 035 04 045 05

119879 (s)

VSINCINC step = 0005INC step = 001

5251

54948

021 023 025 027

4746454443

041 043 045 047

119881PV

(V)

(a)

Irradiation step change

075

07

065

06

055

05

045

040 005 01 015 02 025 03 035 04 045 05

058A058A

072A

VSINCINC step = 0005INC step = 001

119879 (s)

07207

068066064

021 023 025 027

06106

059058

041 043 045 047

119868 PV

(A)

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(b)

Irradiation step change

35W27W

27W

VSINCINC step = 0005INC step = 001

119879 (s)

4

35

3

25

15

1

05

00

005 01 015 02 025 03 035 04 045 05

2

021 023 025 027

27227

268266264262

041 043 045 047

119875PV

(W)

35345

34335

33

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(c)

Figure 9 Comparison of best power point (a) voltage (b) current and (c) power in changed irradiance condition (800Wm2-1 KWm2-800Wm2)

As shown in the flow chart the AD buffer PWM enableand interrupt enable must be set at the beginning The ADbuffer keeps reading external signal which is the voltage andcurrent generated by the solar cell and the voltage and currentof lithium battery First the voltage and current values ofsolar cell generate PWM signal through MPPT algorithmto the DCDC boost converter The MPPT algorithm keepsidentifying whether the solar cell has tracked maximumpower point In addition the voltage and current valuesof lithium battery generate PWM signal via charge controlmethod to the DCDC buck converter The charge control

keeps identifyingwhether the battery has been charged under42 V stable voltage

61 Experimental Result of MPPT The experimental resultof MPPT algorithm is compared with simulation result Theresults of different methods are simulated in standard testconditions (1 KWm2 AM 15 25∘C) and changed irradiancecondition (1 KWm2 and 800Wm2)

The portable charging module in this study was inde-pendent PV system power supply and the precondition was

8 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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VLSI Design

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Shock and Vibration

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Acoustics and VibrationAdvances in

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Advances inOptoElectronics

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Navigation and Observation

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DistributedSensor Networks

International Journal of

6 The Scientific World Journal

To workspace4

To workspace2

To workspace3

119879 119879

119866

119866

Clock

Clock

Subsystem1

Clock1

Time

To workspace6 Boost

119875

To workspace1

119881

Buck

119881

119863

119889

To workspace7

119868

To workspace5

119875(I)

119868(I)

119881(I)

119863(I)

+minus

To workspace

119881119900(119868) 119881119900

119881119900

119889119881119900

119894119871

1198891199091

1199092

To workspace8

To workspace9

1198811199002

119894119871

1198632

pi control

119904119905

119881119903

Figure 8 Solar charger simulation system

voltage charge-up method and constant currentconstantvoltage charge-up method were discussed and comparedFigure 10 is the IAE convergence curve diagram of optimiza-tion algorithm for constant voltage charge As seen the GAcan search for the optimal solution rapidly and althoughthe convergence rate of PSO is lower than that of GA theconvergence value of PSOrsquos optimal solution is better thanGA

Figure 11 shows the simulation result of constant voltagecharge using PI controller The 119896

119875and 119896

119868values of PI

controller are adjusted by GA and PSO respectively As seenwhetherwe use PSOorGA the adjusted 119896

119875and 119896119868values of PI

controller can stabilize the power supplied from the first-stageconverter so as to supply electric energy soundly to charge thesecond-stage charging system effectively Moreover the PSOadjusted PI controller is better than GA the PSO adjustedconstant voltage PI controller can use the electric energygenerated by the first-stage PV system effectively and chargesthe battery faster than the GA adjusted constant voltage PIcontroller

Figure 12 shows the IAE convergence curve of optimiza-tion algorithm for constant currentconstant voltage chargeAs seen in constant-current charge the convergence rate ofGA is similar to that of PSO In this constant-current statethe convergence value of PSO is better than that of GA

Figure 13 shows the simulation result of constant cur-rentconstant voltage charge using PI controllerThe constantcurrentconstant voltage charge in this study switches thebattery to constant-current charge to obtain 418 V chargingvoltage and then switches to constant voltage charge Thecharging system uses GA and PSO to adjust the 119896

119875and 119896119868val-

ues of PI controller respectively In constant currentconstantvoltage charging whether we use PSO or GA the 119896

119875and 119896

119868

values of the adjusted PI controller canmake the second-stagecharging system charge effectively

The GA adjusted PI controller has not implementedconstant-current charge of system effectively so that thecharging time is prolonged whereas the PSO adjusted PIcontroller can implement accurate constant-current chargeof the secondary charging system In addition in the second-stage constant voltage charge any optimization algorithm cancharge the battery with 42 V constant voltage

The constant voltage charge is compared with constantcurrentconstant voltage charge according to the simulationresult Both the constant voltage charge and the constantcurrentconstant voltage charge can use preceding stage solarenergy output electric energy to charge battery effectivelyhowever the defect in constant voltage charge is that theinternal impedance of battery decreases gradually whenthe battery is charged up to a certain voltage so that thecharging current decreases gradually and the charging timeis prolonged relativelyThe constant currentconstant voltagecharge has solved this problem the constant-current chargeis implemented first so that the full charge time of battery isshortened Finally the constant voltage charge is used so thatthe battery will not be overcharged

6 Experimental Result of Portable SolarEnergy Charging System

For the implementation of controller this study used themicrocontrol chip PIC18F8720 developed by MicroChip tocomplete the overall portable design Figure 14(a) showsthe overall portable solar energy lithium battery chargingmodule Figure 14(b) shows the two-stage DCDC converterand lithium battery used in this paper Figure 14(c) shows themicrocontrol chip PIC18F8720 used in this paper

The MPPT of portable charging module and batterycharging system in this study are processed by PIC18F8720The program calculation process is shown in Figure 15

The Scientific World Journal 7

Irradiation step change

1k to 800Wm2 04 s800 to 1 kWm2 02 s

465V 485V 465V

6

5

4

3

2

1

00 005 01 015 02 025 03 035 04 045 05

119879 (s)

VSINCINC step = 0005INC step = 001

5251

54948

021 023 025 027

4746454443

041 043 045 047

119881PV

(V)

(a)

Irradiation step change

075

07

065

06

055

05

045

040 005 01 015 02 025 03 035 04 045 05

058A058A

072A

VSINCINC step = 0005INC step = 001

119879 (s)

07207

068066064

021 023 025 027

06106

059058

041 043 045 047

119868 PV

(A)

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(b)

Irradiation step change

35W27W

27W

VSINCINC step = 0005INC step = 001

119879 (s)

4

35

3

25

15

1

05

00

005 01 015 02 025 03 035 04 045 05

2

021 023 025 027

27227

268266264262

041 043 045 047

119875PV

(W)

35345

34335

33

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(c)

Figure 9 Comparison of best power point (a) voltage (b) current and (c) power in changed irradiance condition (800Wm2-1 KWm2-800Wm2)

As shown in the flow chart the AD buffer PWM enableand interrupt enable must be set at the beginning The ADbuffer keeps reading external signal which is the voltage andcurrent generated by the solar cell and the voltage and currentof lithium battery First the voltage and current values ofsolar cell generate PWM signal through MPPT algorithmto the DCDC boost converter The MPPT algorithm keepsidentifying whether the solar cell has tracked maximumpower point In addition the voltage and current valuesof lithium battery generate PWM signal via charge controlmethod to the DCDC buck converter The charge control

keeps identifyingwhether the battery has been charged under42 V stable voltage

61 Experimental Result of MPPT The experimental resultof MPPT algorithm is compared with simulation result Theresults of different methods are simulated in standard testconditions (1 KWm2 AM 15 25∘C) and changed irradiancecondition (1 KWm2 and 800Wm2)

The portable charging module in this study was inde-pendent PV system power supply and the precondition was

8 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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DistributedSensor Networks

International Journal of

The Scientific World Journal 7

Irradiation step change

1k to 800Wm2 04 s800 to 1 kWm2 02 s

465V 485V 465V

6

5

4

3

2

1

00 005 01 015 02 025 03 035 04 045 05

119879 (s)

VSINCINC step = 0005INC step = 001

5251

54948

021 023 025 027

4746454443

041 043 045 047

119881PV

(V)

(a)

Irradiation step change

075

07

065

06

055

05

045

040 005 01 015 02 025 03 035 04 045 05

058A058A

072A

VSINCINC step = 0005INC step = 001

119879 (s)

07207

068066064

021 023 025 027

06106

059058

041 043 045 047

119868 PV

(A)

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(b)

Irradiation step change

35W27W

27W

VSINCINC step = 0005INC step = 001

119879 (s)

4

35

3

25

15

1

05

00

005 01 015 02 025 03 035 04 045 05

2

021 023 025 027

27227

268266264262

041 043 045 047

119875PV

(W)

35345

34335

33

1k to 800Wm2 04 s800 to 1 kWm2 02 s

(c)

Figure 9 Comparison of best power point (a) voltage (b) current and (c) power in changed irradiance condition (800Wm2-1 KWm2-800Wm2)

As shown in the flow chart the AD buffer PWM enableand interrupt enable must be set at the beginning The ADbuffer keeps reading external signal which is the voltage andcurrent generated by the solar cell and the voltage and currentof lithium battery First the voltage and current values ofsolar cell generate PWM signal through MPPT algorithmto the DCDC boost converter The MPPT algorithm keepsidentifying whether the solar cell has tracked maximumpower point In addition the voltage and current valuesof lithium battery generate PWM signal via charge controlmethod to the DCDC buck converter The charge control

keeps identifyingwhether the battery has been charged under42 V stable voltage

61 Experimental Result of MPPT The experimental resultof MPPT algorithm is compared with simulation result Theresults of different methods are simulated in standard testconditions (1 KWm2 AM 15 25∘C) and changed irradiancecondition (1 KWm2 and 800Wm2)

The portable charging module in this study was inde-pendent PV system power supply and the precondition was

8 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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 The Scientific World Journal

012

01

008

006

004

002

00 10 20 30 40 50 60 70 80 90 100

PSOGA

Fitn

ess v

alue

Generation

Figure 10 IAE curve diagram of GA and PSO

15

2

25

3

35

4

45

0 05 1 15 2 25 3 35 40

05

1

15

2

25

3

35

PSOGA

119881119861

(V)

119868 119861(A

)

119881119861119868119861

119881119861119868119861

119879 (h)

Figure 11 Constant voltage charge using optimization algorithm

that the input voltage must be high enough to drive themicrocontroller and the driver of DCDC converter Thustwo solar cells of the specifications used in this study wereconnected in series for experiment The solar cells connectedin series could double the voltage and maintain the currentIn this series connection the maximum power point voltagegenerated by solar energy was 97 V the current was 072Aand the power was 698Wwhen the irradiance was 1 KWm2Themaximum power point voltage generated by solar energywas 9V the current was 066A and the power was 6Wwhenthe irradiance was 800Wm2

Figures 16 and 17 show the experimental results of voltagecurrent and power of VSINC when the illumination ischanged As seen the VSINC can make the system trackthe maximum power when the illumination is changed

PSOGA

100806040200Generation

Fitn

ess v

alue

35

345

34

335

33

325

32

315

31

Figure 12 IAE curve diagram of GA and PSO

45

4

35

25

3

10 051

15

15

2

25002040608112141618

2

2

GA PSO119881119861119868119861

119881119861119868119861

119881119861

(V)

119868 119861(A

)

119879 (h)

Figure 13 Constant voltage charge using optimization algorithm

However according to the comparison between incrementalconductance methods of step 0005 and step 001 large stepsize incremental conductance results in very large oscillationof tracking maximum power This oscillation causes slightpower loss of the systemWhen the step is changed the incre-mental conductance method still cannot track the maximumpower pointThe trackedmaximum power is 56Wwhen theirradiance is 800Wm2 and the tracked maximum power is66W when the irradiance is 1 KWm2

Figure 18 shows the experimental result of VSINC usedin this paper The yellow line in Figure 18(a) is the maximumpower point voltage and the blue line is maximum powerpoint current As seen the VSINC method used in thisstudy can implement the tracking efficiency completely inmicrocontroller so that the PV system obtains maximumefficiency It can also track the maximum power point whenthe illumination is changed The system tracked maximum

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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

The Scientific World Journal 9

(a) (b)

(c)

Figure 14 (a) hardware facility (b) charging circuit and (c) control chip of portable system

power is 6W when the irradiance is 800Wm2 and thetracked maximum power is 698W when the irradiance is1 KWm2

According to this experimental result as comparedwith general incremental conductance method the VSINCmethod has the advantages of large step size and small stepsize implementing rapid tracking of maximum power pointand minimum range of oscillation in simulation analysis andtracking the maximum power point in different irradianceconditions effectively Thus the PV system can exert max-imum service efficiency for load The VSINC method usedin this study also can track the maximum power in differentilluminations rapidly and has small steady-state oscillation

The experimental results of maximum power are com-pared in Table 1 As seen for fixed step size incrementalconductance method whether it is small step size (step size0005) or large step size (step size 001) the solar cell is unableto supply electric energy for the load effectively The trackedmaximum power point is 66W when the step size is 0005the steady-state error of maximum power is 0062W and theefficiency of this result is 936 the trackedmaximum powerpoint is 66Wwhen the step size is 001 the steady-state errorofmaximumpower is 0132W and the efficiency of this resultis 927 The VSINC method can improve the steady-stateerror greatly and track themaximumpower pointTheoverallefficiency is 983 so that the solar cell can supply electricenergy for the load effectively

Table 1 Comparison of efficiency of MPPT algorithm

Maximumpowerpoint

Trackedmaximumpowerpoint

Averagesteady-state

errorEfficiency

Incrementalconductancemethod(Step size is 0005)

698W 66W 0062W 936

Incrementalconductancemethod(Step size is 001)

698W 66W 0132W 927

VSINC 698W 698W 00578W 991

62 Experimental Result of the Charging System The optimalcharge control design proposed in this study was validatedby battery charge experiment and compared with simulationanalysis result In the standard test conditions the electricenergy generated by the first-stage PV system MPPT passedthrough the second-stage buck converter before chargingthe lithium battery The parameter value of PI controllerof microcontroller was substituted in computer simulated

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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

10 The Scientific World Journal

Start

Set AD registerSet PWM

Set discontinue

AD converse

MPPTalgorithm

PWM

DCDCboost converter

Solar cell

No

Yes

PWM

DCDCbuck converter

Li-ionbattery

Yes

No

End

119875 = 119875max

119881119861 = 42V

Chargingsystem

119881o and 119868o119881PV and 119868PV

119881119900 and 119868119900

119881PV and 119868PV

Figure 15 Program flow chart

optimization algorithm to search for PI value The computersimulation revealed that the 119896

119875and 119896119868values searched by PSO

are better than the search results of GA thus this study usedthe 119896119875and 119896119868values searched by PSO for experiment directly

to shorten charging time

621 Constant Voltage Charge Figure 19 shows the exper-iment of battery charging voltage and current of constantvoltage charge As seen the second-stage DCDC buckconverter used in this study can use the PI controller ofmicrocontroller to charge the battery under constant voltageand the charging time is about 3 h

622 Constant CurrentConstant Voltage Charge Figure 20shows the experiment of battery charging voltage and cur-rent by constant currentconstant voltage charge When thebattery voltage is 418 V the constant current is switched

to constant voltage charge The second-stage DCDC buckconverter can use the PI controller of microcontroller toimplement constant currentconstant voltage charge of bat-tery and the charging time is about 2 h

The experiments of constant voltage and constant cur-rentconstant voltage charge can validate the simulationresultsThese twomethods can use the first-stage solar energyeffectively The regulation of feedback PI controller of thesecond-stage system stabilizes the output electric energy ofthe first-stage MPPT system and attains the effect of constantvoltage current and charge The charging time of constantcurrentconstant voltage ismuch shorter than that of constantvoltage charge

7 Conclusions

This study found that the proposed microcontroller 18F8720of the portable solar cell charging module can make the first-stage DCDC boost converter track the maximum powerpoint of solar cell and supply electric energy for the second-stage DCDC buck converter so as to increase the efficiencyof charging module The main contributions of this study arelisted as follows

(1) This study proved that in the first-stage MPPT theVSINC method can track the maximum power pointfaster than the fixed step size incremental conduc-tance method and can track the maximum powerpoint promptly when the solar irradiance is changed

(2) The computer simulation proved that in the second-stage battery charge PI controller design the PSOalgorithm can search for the optimum controller gainvalue faster than GA algorithm and its IAE value issmallerThis result means that the search efficiency ofPSO algorithm is better than that of GA

(3) According to the simulation results the constantcurrentconstant voltage charge can charge batteryfaster than simple constant voltage charge underoptimal PI control and the full charge time of batteryis shorter

(4) The experimental results proved that the two-stagesystem integrated with MPPT and battery chargeproposed in this study can remedy the defects inthe switchover control system using single-buck con-verter and control the MPPT of solar energy andbattery charge simultaneously This can ensure thatthe first-stage boost converter of system enables thesystem to track the maximum power point rapidlyby the VSINC method so as to stabilize the voltageIn the second-stage PI controlled charge the gainvalue obtained by PSO algorithm enables the constantcurrentconstant voltage charge to charge faster thansimple constant voltage charge and the overall charg-ing system can implement constant voltage chargeeffectively

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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

The Scientific World Journal 11

(a) (b)

Figure 16 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 0005)

(a) (b)

Figure 17 Experimental results of incremental conductance method (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2) (step size is 001)

(a) (b)

Figure 18 Experimental result of VSINC (a) voltage current (b) power when irradiance is changed (800Wm2-1 KWm2-800Wm2)

12 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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 The Scientific World Journal

45

4

35

3

25

20 2000 4000 6000 8000 10000

002040608112141618222

119881119861

(V)

119881119861119868119861

119879 (s)

119868 119861(A

)Figure 19 Constant voltage charge

0 1000 2000 3000 4000 5000 6000 7000002040608112141618222

119881119861

(V)

119881119861

119868119861

45

4

35

3

25

2

119868 119861(A

)

Figure 20 Constant currentconstant voltage charge

Acknowledgment

The authors would like to thank the National Science Councilof Taiwan Taiwan for financially supporting this researchunder Contracts nos NSC 100-2221-E-027-015 and NSC-2628-E-167-002-MY3 Professor Lin and Mr Liang are coau-thors in the paper They help to set up the experimentalinstructions for this paper and also help in the analysis of thesimulation and experimental results

References

[1] R Gules J D P Pacheco H L Hey and J Imhoff ldquoAmaximumpower point tracking system with parallel connection forPV stand-alone applicationsrdquo IEEE Transactions on IndustrialElectronics vol 55 no 7 pp 2674ndash2683 2008

[2] J M Kwon B H Kwon and K H Nam ldquoGrid-connected pho-tovoltaic multistring PCS with PV current variation reduction

controlrdquo IEEE Transactions on Industrial Electronics vol 56 no11 pp 4381ndash4388 2009

[3] A Pandey N Dasgupta and A K Mukerjee ldquoA simple single-sensorMPPT solutionrdquo IEEE Transactions on Power Electronicsvol 22 no 2 pp 698ndash700 2007

[4] I Hong B Kang and S Park ldquoDesign and implementation ofintelligent energy distribution management with photovoltaicsystemrdquo IEEE Transactions on Consumer Electronics vol 58 no2 pp 340ndash346 2012

[5] C H Lin C Y Hsieh and K H Chen ldquoA li-ion battery chargerwith smooth control circuit and built-in resistance compensatorfor achieving stable and fast chargingrdquo IEEE Transactions onCircuits and Systems I vol 57 no 2 pp 506ndash517 2010

[6] E Koutroulis and K Kalaitzakis ldquoNovel battery charging regu-lation system for photovoltaic applicationsrdquo IEE ProceedingsmdashElectric Power Applications vol 151 no 2 pp 191ndash197 2004

[7] T S Mundra and A Kumar ldquoMicro power battery state-of-charge monitorrdquo IEEE Transactions on Consumer Electronicsvol 54 no 2 pp 623ndash630 2008

[8] C Yao X Ruan X Wang and C K Tse ldquoIsolated buck-boostDCDC converters suitable for wide input-voltage rangerdquo IEEETransactions on Power Electronics vol 26 no 9 pp 2599ndash26132011

[9] Q Mei M Shan L Liu and J M Guerrero ldquoA novel improvedvariable step-size incremental-resistanceMPPTmethod for PVsystemsrdquo IEEETransactions on Industrial Electronics vol 58 no6 pp 2427ndash2434 2011

[10] J P Rodrigues S A Mussa M L Heldwein and A J PerinldquoThree-level ZVS active clamping PWM for the DC-DC buckconverterrdquo IEEE Transactions on Power Electronics vol 24 no10 pp 2249ndash2258 2009

[11] C N Ko Y P Chang and C J Wu ldquoA PSO method with non-linear time-varying evolution for optimal design of harmonicfiltersrdquo IEEE Transactions on Power Systems vol 24 no 1 pp437ndash444 2009

[12] L Z Liu F X Wu and W J Zhang ldquoInference of biological s-sytem using the separable estimation method and the geneticalgorithmrdquo IEEEACM Transactions on Computational Biologyand Bioinformatics vol 9 no 4 pp 955ndash965 2012

[13] N FemiaDGranozio G Petrone G Spagnuolo andMVitellildquoPredictive amp adaptive MPPT perturb and observe methodrdquoIEEE Transactions on Aerospace and Electronic Systems vol 43no 3 pp 934ndash950 2007

[14] A Pandey N Dasgupta and A K Mukerjee ldquoDesign issues inimplementing MPPT for improved tracking and dynamic per-formancerdquo in Proceedings of the 32nd IEEE Annual Conferenceon Industrial Electronics (IECON rsquo06) pp 4387ndash4391 November2006

[15] K M Tsang andW L Chan ldquoCurrent sensorless quick chargerfor lithium-ion batteriesrdquo Energy Conversion and Managementvol 52 no 3 pp 1593ndash1595 2011

[16] A A H Hussein and I Batarseh ldquoA review of chargingalgorithms for nickel and lithium battery chargersrdquo IEEETransactions on Vehicular Technology vol 60 no 3 pp 830ndash838 2011

[17] B Y Chen and Y S Lai ldquoNew digital-controlled techniquefor battery charger with constant current and voltage controlwithout current feedbackrdquo IEEE Transactions on ConsumerElectronics vol 59 no 3 pp 1545ndash1553 2012

[18] S Kwong and C W Chau ldquoAnalysis of parallel geneticalgorithms on HMM based speech recognition systemrdquo IEEE

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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

The Scientific World Journal 13

Transactions on Consumer Electronics vol 43 no 4 pp 1229ndash1233 1997

[19] J C Chen ldquoPartial transmit sequences for PAPR reduction ofOFDM signals with stochastic optimization techniquesrdquo IEEETransactions on Consumer Electronics vol 56 no 3 pp 1229ndash1234 2010

[20] B Liu LWang and Y H Jin ldquoAn effective PSO-basedmemeticalgorithm for flow shop schedulingrdquo IEEE Transactions onSystems Man and Cybernetics B vol 37 no 1 pp 18ndash27 2007

[21] X Chen and Y Li ldquoA modified PSO structure resulting inhigh exploration ability with convergence guaranteedrdquo IEEETransactions on Systems Man and Cybernetics B vol 37 no 5pp 1271ndash1289 2007

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