Modeling and Simulation of a Hybrid Electric

Propulsion System of a Green Ship

Tiffany Jaster, Andrew Rowe and Zuomin Dong

Dept. of Mechanical Engineering & Inst. for Integrated Energy Systems

University of Victoria

Victoria, BC Canada

zdong@uvic.ca&tjaster@uvic.ca

Abstract—In this work, the hybrid electric propulsion system

of a marine vehicle was modeled in MATLAB Simulink and

SimPowerSystems. Models of each of the propulsion components

were developed and incorporated into a complete system

propulsion model. A rule-based supervisory mode controller was

constructed which specifies the combination of onboard power

sources to be used throughout the mission cycle. The hybrid

electric propulsion and control model was simulated on a

dSPACE hardware-in-the-loop platform. For each simulation,

the energy storage system state of charge, HEV mode, propeller

motor drive speed set point, and hotel load were specified. This

study forms the foundation for further research in ship hybrid

electric propulsion system design and power management.

Keywords—hybrid electric propulsion system; green ship;

modeling; simulation; energy storage system

I. INTRODUCTION

A. General Background

All-electric and hybrid electric ship propulsion has become a leading/emerging area of research, prompting investigation in hybrid propulsion system design, and demonstration of concept vessels. With respect to ship design and operation, minimizing costs associated with fuel consumption and maintenance are key objectives. As well, new and existing ships are being subject to regulatory requirements, specifically regarding emissions and energy efficiency. Hybrid electric propulsion has shown to be a promising approach in addressing these concerns, particularly for smaller scale vessels requiring a high degree of maneuverability.

In this work, a hybrid propulsion system for a 36.6 m research vessel is examined. The proposed ship was designed to conduct slow surveys; operate in environmentally sensitive marine areas; and serve as a ROPOS platform, to name a few. The hybrid propulsion system is beneficial given the varied nature of the tasks. With an all-electric mode available, quiet and emission free operation is possible during low speed cruising/dynamic positioning (DP).

B. Related Work

More recently, there has been a surge of interest in predicting/understanding the shipboard power system response during operation, particularly during load transients. Modeling

and simulation with this focus can be used for power system analysis; fault insertion and system reconfiguration/restoration; fuel consumption and emissions estimation; novel power system evaluation; and control system development.

The study presented by [1] aimed to examine a ship’s power system transient response during prevalent system disturbances, namely the switching of mechanical/electrical loads. Similarly, the all electric ship (AES) model developed by [2] evaluated behavior of the hybrid power system during transients, specifically step changes in the ship drag coefficient and ship service load. The model presented by [3] examined the effect propeller load fluctuations have on the power system, which can impart large electrical transients. Another AES, based on the Visby-class corvette, was modeled with the aim of better understanding the issues arising with voltage stability in a shipboard DC power system [4]. The model created by [5] also investigates DC-link voltage regulation, along with propeller control strategies.

In [6], a dynamic hybrid power system (HPS) model was developed to address real-time power management schemes along with effective power converter control. Two versions of the hybrid system were developed. One model was created for control and optimization development of the HPS for shipboard integrated power systems (IPS) and auxiliary power units. The second model was used as a simulation orientated IPS model; it was used for real-time simulation and analysis of the IPS. A real-time hierarchical controller for normal mode HPS was implemented, as well, a failure mode power management strategy was addressed. Similarly, a ship power system was modeled by [7] with the aim of developing a power management system to handle major power system faults, improve system robustness against blackouts, minimize operational costs, and maintain power system equipment within safe operational limits.

Of the aforementioned ship power system modeling and simulation research, the majority utilized MATLAB Simulink [1][7] as the development environment, in combination with either Fortran [3][5], SimPowerSystems (SPS) [4][6], or other programs [2].

C. Proposed New Approach

To evaluate the design and explore the capability of the proposed hybrid propulsion system, a model based design

978-1-4799-2280-2/14/$31.00 ©2014 IEEE

approach is utilized. The system under investigation is modeled using MATLAB Simulink and SPS. System simulation time is accelerated by executing the model on a dSpace hardware-in-the-loop. Assorted rule-based supervisory control strategies are developed to explore the effective combinational use of the onboard energy sources.

II. HYBRID ELECTRIC PROPULSION SYSTEM DESIGN

The hybrid electric propulsion system is shown in Fig. 1. The onboard power/energy sources include:

150 kW Ballard FCvelocity-HD6 PEM fuel cell (FC)

232 kWh energy storage system (ESS) consisting of 165 Valance U24-12XP battery modules in a configuration of 55 series, 3 parallel strings

three 215 kW marine diesel generators

The system supplies power to a main 460 VAC bus. Both the ESS and FC have dedicated DC/AC converters; the ESS converter is bidirectional and also serves as the shore plug-in charging port. Ship propulsion is provided by two 200 kW azimuthing thrusters, with DP operations supplemented with a 90 kW fixed pitch bow thruster.

Fig. 1. Ship Propulsion System Overview

III. COMPONENT MODELING

Models of the component subsystems and associated emission subsystems (where applicable) are presented in this section. It should be noted that subsystem component equations are not detailed for components represented by an SPS block. In these cases, the block mask parameters are given and the reader is referred to the SPS block documentation for a detailed description.

The ESS is modeled using three parallel connected SPS Battery blocks. The lithium-ion chemistry was selected, and the

block mask was parameterized to reflect a Valance U24-12XP battery (TABLE I. ). The underlying battery mask was modified such that each battery block represents one series string of 55 battery modules. This configuration does not allow battery modules to have different state of charge (SOC) and thus cannot be used for battery bank module balancing simulations. The 5 hour discharge characteristic for the ESS block (single Valance module) is given in Fig. 2, and voltage discharge profiles for various C-rates are given in Fig. 3. The BC Hydro emission factor of 25 tC02e/GWh is used to account for the emissions produced during initial ESS shore side charging [8].

TABLE I. ESS MASK PARAMETERS

Nominal voltage (V) 12.8

Rated capacity/maximum capacity/capacity at nominal voltage (Ah)

110

Fully charged voltage (V) 13.25

Nominal discharge current (A) 22

Internal resistance (ohms) 0.006

Exponential zone [voltage(V), capacity (Ah)] [13 55]

Fig. 2. C/5 Discharge Characteristic for Valance U12-24XP Module

Fig. 3. Voltage Profiles for Valance U12-24XP Module

The SPS FC block was used to model the Ballard FC. Selecting the PEM chemistry, the block was parameterized using HD6 data (TABLE II. ). As 20 kW is consumed internally by auxiliary FC devices, only 130 kW is available to supply the main AC bus. The FC block curves are shown in Fig. 4. The onboard hydrogen storage is capable of providing up to 86.4 kg of hydrogen. As water is the byproduct during FC hydrogen consumption, only the hydrogen production emissions are included in the FC emissions subsystem. The hydrogen source is a recovered by-product from the

manufacture of sodium chlorate, which produces approximately 0.0117 kg of hydrogen per kWh.

TABLE II. FC MASK PARAMETERS

Voltage at 0A and 1A [V_0(V), V_1(V)] [766 763]

Nominal operating point [Inom(A), Vnom(V)] [175 625]

Maximum operating point [Iend(A), Vend(V)] [300 584]

Nominal stack efficiency (%) 55

Operating temperature (Celsius) 70

Nominal air flow rate (lpm) 3450

Nominal supply pressure [fuel(bar), air(bar)] [17 2]

Fig. 4. FC Module Curves

SPS Simplified Synchronous Machine blocks are used to represent the diesel generators, and are parameterized using CAT Marine C9 generator set data (TABLE III. ). The generator control unit employs an automatic voltage regulator to control the field voltage as well as ensures phase synchronization with the bus before connection. No separate engine model is included; instead, the synchronous machine block is driven by a mechanical power request, which represents the engine shaft power. An emissions and fuel consumption model is included in the generator subsystem. The dynamic fuel consumption FCg per unit time of the generator power Pg is calculated using (1), and the dynamic brake specific fuel consumption (BSFC) be,g is given by (2). The static BSFC be,g

s is derived from generator operating data

given in [9]. Lastly, the marine diesel production emission factors were calculated using Total Energy and Emission Analysis for Marine Systems (TEAMS).

TABLE III. SIMPLIFIED SYNCHRONOUS MACHINE MASK PARAMETERS

Nominal power (VA) 269e3

Inertia (kg·m2) 1.89

Damping factor (T(pu)/(pu)) 21

Pairs of poles 2

Internal impedance [R(ohms), L(H)] [0.021 5.5e-4]

FCg = be,g(Pg)Pg

be,g, = be,gs(Pg)+ be,g

s(Pg)(7e-4/3600)(d·Pg/dt)

2

The DC/AC power converters are modeled using the SPS Universal Bridge block with the average-model based VSC option selected. The average voltage reference signals input to the block are generated using PI control. This block was selected as it does not represent harmonics, and can be used with larger sample times without diminishing the average voltage dynamics. The ESS converter is bidirectional and is capable of facilitating a continuous power flow of 354 kVA or 500 A. The FC inverter is limited to 177 kVA or 250A. A transformer is included with each converter as the voltage levels of the DC sources could not be directly converted to 460 VAC. The transformer voltages were selected such that (3) is satisfied.

VDC (2√2·VLL)/√3

The propeller motor drives are represented using SPS AC3 Field-Orientated Control Induction Motor Drive blocks. The block mask was parameterized using information from similarly sized motor data sheets, and the average model detail level was selected. The azimuthing thrusters have an input speed of 1800 rpm, while the maximum rpm of the bow thruster is 1500. The block receives an rpm set point signal and load torque, and outputs shaft rotational speed.

The Kaplan Ka 5-75 propeller in a 19A nozzle was selected to represent the ship’s main podded Z-drives. Similarly, the bow propeller is modeled using the Ka 4-70 series. Using the thrust KT and torque KQ coefficients of the Kaplan series, the thrust T delivered by and torque Q delivered to the thruster are given by (4) and (5), respectively. Both equations are a

function of salt water density w, propeller diameter D, and shaft speed n. The diameter of the azimuthing and bow propellers is 750 mm and 630 mm, respectively. The propeller subsystems receive the shaft rotational speed from the motor drive blocks and return the corresponding torque.

T = KTwD4n

2

Q = KQwD5n

2

The purpose of the power management system is to dispatch the required generation while delivering acceptable fuel economy, minimal emissions, and satisfactory performance all while ensuring safe operations. Energy flows are managed through use of rule-based control strategies. The strategies take into account component operation limitations.

Similar to automotive applications, the ESS is partitioned into operational capacity windows. The useable operational range for the Valance modules is defined to be between 20-90% SOC, with the lowest 10% dedicated to charge sustaining

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The minimum and maximum loading for each of the three generators is 30% and 90% of the rated power, respectively. The minimum loading limit is imposed as a low load maintenance constraint. The maximum limit is derived accounting for blackout prevention; the ship must maintain spinning reserves according to class rules. The details of this derivation can be found in [10]. Using this information, generator operation is managed through predefined generator start/stop tables which are dependent on system power demand. The generator stop power demand is set at 80% of rated power. It should be noted that each online generator carries the same percentage of load – this is a class requirement.

The combinations of the onboard energy sources examined include: ESS only; ESS and FC; ESS and generators; and ESS, FC and generators. The supervisory power management controller selects the mode corresponding to a power source combination to be used. The mode is decided based on system power demand and fuel availability (hydrogen or ESS SOC). Supervisory mode control is illustrated in the flowchart given in Fig. 5.

ESS Only Mode

HEV Mode

FC State:OFF

Measure Pdmd and SOC

Pdmd≤PESS,maxYES YES

Full Hybrid Mode

H2 Available

NO

NO

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YES

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NO

YES

Fig. 5. Supervisory Mode Control

When the ESS only mode cannot provide for the system power demand, an HEV mode or full hybrid mode is entered. Two HEV modes are considered: mild HEV and 30% ESS assist. The first replicates the operation of a mild hybrid vehicle where the ESS provides minimal power to/from the system and is operated in a CS state. The 30% ESS assist HEV mode delays the start of subsequent generators by allowing a significant power contribution by the ESS - up to 30% of rated generator power or 64.5 kW. This additional ESS power is only applied once the maximum generator loading has been reached. When the ESS SOC reaches the mid range of the CS window, the HEV mode automatically switches to CS (mild HEV). The CS mode is designed to apply a constant charge to the ESS when it reaches 23% SOC, and cease this charge when the SOC has reached 28% (sawtooth charging scheme). The start/stop tables for the two HEV modes are given in TABLE IV.

The FC can be in operation during either of the HEV modes (full hybrid functionality). Once the FC has been brought online, it provides power up to its rated maximum with the additional load provided for by the ESS or generators. The FC load is not modified unless the system power demand drops

below the FC maximum rated power; it provides for a base power load.

TABLE IV. GENERATOR START/STOP TABLE

ON

Generator 1 -> 2 Generator 2 -> 3

Mild 30% ESS Assist Mild 30% ESS Assist

193.5 kW 258 kW 387 kW 451.5 kW

OFF

Generator 2 -> 1 Generator 3 -> 2

172 kW 344 kW

IV. SIMULATION RESULTS AND DISCUSSION

The first set of simulations illustrate the operating difference between the two HEV modes. The control strategy has been modified such that the entire simulation is in HEV mode; there is no ESS only operation. The system load profile was designed to operate in the range where the ESS assist would be utilized. Fig. 6 shows the ESS and generator power contributions with the 30% ESS assist HEV mode, while Fig. 7 shows the response of the mild HEV mode. The GHG emissions and diesel fuel consumption over the cycle is given in Fig. 8. Looking at the power contribution figures, it is apparent that the ESS assist HEV mode allows for the generators to be operated in a range of higher efficiency. This translates into reduced fuel consumption and better GHG emissions compared to the case where an additional generator is utilized.

Fig. 6. 30% ESS Assist HEV Mode: Power Contributions

Fig. 7. Mild HEV Mode: Power Contributions

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Two simulations, given in Fig. 9 through Fig. 12, each use the same repeating system load profile as well as have an initial ESS SOC of 90%. For these simulations, no hydrogen is available, and thus no FC operation is possible. One run uses the 30% ESS assist HEV mode, while the other operates as a mild hybrid. The power contributions of the ESS and generators for the 30% ESS assist HEV mode and mild HEV mode are presented in Fig. 9 and Fig. 10, respectively. Fig. 11 shows the ESS SOC for the two HEV modes over the cycle. Lastly, the total GHG emissions and diesel fuel consumption is compared in Fig. 12.

The power contribution figures show minimal difference between using either HEV mode. This is in part due to the load profile. Only between approximately 65-75s is the ESS assist applied in Fig. 9. Accordingly, at lower system power demand, the ESS (with a high SOC) provides for the full system load. The third generator is brought online in each simulation once the SOC reaches the CS range low limit. This scenario of depleting the ESS to its CS window, and operating as a mild hybrid for the remainder of the cycle is typical of a day trip. When the ship returns to port, a shore plug-in power point is available to recharge the ESS.

The GHG emissions and diesel fuel consumed over the cycle can be considered comparable between the two HEV modes, as shown in Fig. 12. In this case, the ESS assist HEV mode provides no measurable benefit. To increase the use of an ESS assist, the behavior of the controller could be modified to allow the assist power to be applied before the maximum generator power allowance is reached, while also ensuring the generator is operating in a range that offers acceptable emissions or fuel consumption.

Fig. 9. 30% ESS Assist HEV Mode: Power Contributions

Fig. 10. Mild HEV Mode: Power Contributions

Fig. 11. ESS SOC

Fig. 12. GHG Emissions and Diesel Fuel Consumption

For the simulations given in Fig. 13 through Fig. 16, full hydrogen tanks are available. Again, the simulations are subject to the same load profile, and have an initial SOC of 90%. The modes of operation during the simulation are ESS and FC, and ESS, FC and generators. Due to the system load profile, the FC is operated at its maximum rated power throughout the simulation. The two simulations diverge once the CS mode is entered. For one run, the CS method is used and the ESS SOC is maintained between 20-30%. The second run simulates a full ESS SOC recharge, at recommended charging current, up to 90% SOC. The power contributions from the various sources for the CS and recharging simulations are presented in Fig. 13 and Fig. 14, respectively. The ESS SOC is compared in Fig. 15, while the total GHG emissions and diesel fuel consumption is compared in Fig. 16.

The ESS full recharge simulation represents a user requested operation – quiet mode. From the start of the simulation, an electric only operation is used until the ESS SOC reaches the CS mid range. At this point, the ship task would be put on hold while the ESS recharges – approximately 93 minutes at the recommended system charging current of

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165A. Once the ESS reaches full capacity, electric only mode can be restored, and the task requiring quiet operation can be resumed.

Fig. 13. Charge Sustaining Mode: Source Power Contributions

Fig. 14. Recharging Mode: Source Power Contributions

Fig. 15. ESS SOC

Fig. 16. GHG Emissions and Diesel Fuel Consumption

The GHG emissions and fuel consumption shown in Fig. 16 show that with recharging at sea, more emissions are produced and fuel consumed, which is expected. To charge the ESS to 90% SOC at port results in 5.2 kg C02e. Over both

simulations, 34.5 kg of H2 is consumed (73.6 kg C02e due to production of this amount).

V. CONCLUSIONS

A complete hybrid propulsion system model was developed in MATLAB Simulink and SPS. Using rule-based control, various combinations of the onboard sources were evaluated for their feasibility of implementation on a ship while adhering to existing class regulations, as well as effectiveness in realizing key objectives. Control strategies were borrowed from industry accepted methods including the calculation of spinning reserves and use of generator start/stop tables. These standard tables were modified to create a 30% ESS assist HEV mode of operation. It was determined that the availability of the additional ESS power does not necessarily guarantee improved emissions or fuel consumption – significant use of the ESS depends on the system load demand. Modification of the control strategy and increase of the ESS assist percentage may improve these results. Regarding the full hybrid simulations, inclusion of the FC allows for an electric only mode at higher power demand; this allows for greater flexibility of operations if a quiet, emission free mode is desired. Overall, better fuel consumption and GHG emissions result using the CS mode over recharging at sea. However, the focus of this simulation was to provide quiet operation rather than optimize the power source management.

ACKNOWLEDGMENT

Financial support from several funding programs including Natural Science and Engineering Research Council of Canada (NSERC), Auto21, Transport Canada, and Natural Resources Canada, as well as technical assistance from members of the UVic Green Vehicle research team are gratefully acknowledged.

REFERENCES

[1] R. Arendt, "Simulation investigations of ship power systems," in Environment and Electrical Engineering (EEEIC), 2011 10th International Conference on, 2011, pp. 1-4.

[2] W. Jiang, R. Fang, J. Khan and R. Dougal, "Performance prediction and dynamic simulation of electric ship hybrid power system," in Electric Ship Technologies Symposium, 2007. ESTS '07. IEEE, 2007, pp. 490-497.

[3] K. Schmitt, "Modeling and simulation of an all electric ship in random seas," 2010.

[4] T. Nord, "Voltage stability in an electric propulsion system for ships," 2006.

[5] J. M. Apsley, A. G. Villasenor, M. Barnes, A. C. Smith, S. Williamson, J. D. Schuddebeurs, P. J. Norman, C. D. Booth, G. M. Burt and J. R. McDonald, "Propulsion drive models for full electric marine propulsion systems," in Electric Machines & Drives Conference, 2007. IEMDC '07. IEEE International, 2007, pp. 118-123.

[6] G. Seenumani, "Real-time power management of hybrid power systems in all electric ship applications," 2010.

[7] D. Radan, “Integrated control of marine electrical power systems,” 2008.

[8] British Columbia: Ministry of Environment. Methodology for Reporting B.C. Public Sector Greenhouse Gas Emissions, Version 1.0. Victoria, BC. February 2011.

[9] Caterpillar, Marine C9 Generator Set Performance Data: PRIME-DM7758-01.

[10] T. Jaster, "Modeling and simulation of a hybrid electric vessel," 2013.

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