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Modeling and Simulation of an Energy Management

System for Plug-in Hybrid Electric VehiclesSalisa Abdul Rahman1,2, Nong Zhang1and Jianguo Zhu11School of Electrical, Mechanical and Mechatronic Systems,

University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia.2Department of Physical Sciences, Faculty of Science and Technology,

Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu Darul Iman.

[email protected]

Abstract- This paper presents modeling, control strategy andsimulation results of an energy management strategy (EMS) for aspecific Plug-in Hybrid Electric Vehicle (PHEV). A good controlstrategy is required among components, such as the EnergyStorage System, an Electric Motor, a Power Control Unit, and anInternal Combustion Engine in order to ensure that the vehicleachieve an improvement in energy efficiency, reduction inemissions, fuel use, weight and cost. In this work, firstly, througha power flow analysis, the vehicle components are sized to meet

the expected power and energy requirements of a typical 5-passenger car. Then, the model is tested numerically in theMATLAB/SIMULINK environment using the Highway FuelEconomy Test drive cycle with the proposed EMS. The accuracyof the model is verified by a comparison between the simulationresults from a specific PHEV code and Advanced Vehicle

Simulator (ADVISOR) Hybrid Electric Vehicle (HEV) model.The simulation results of the two different HEV models arecompared and the pros and cons discussed.

I. INTRODUCTIONFigure 1 shows a block diagram of the proposed Plug-in

Hybrid Electric Vehicle (PHEV) configuration, consists of an

Energy Storage System (ESS), a Power Control Unit (PCU),

an Electric Motor (EM) and an Internal Combustion Engine

(ICE) [1,2]. A proposed Energy Management Strategy (EMS)

is applied to the PHEV code to ensure the vehicle achieve the

target driving performance without sacrificing the optimum

operating condition.

II. ADVISORAdvanced Vehicle Simulator (ADVISOR) is a software

based on MATLAB/SIMULINK, originally developed by the

U. S. Department of Energy (DOE) and the National

Renewable Energy Laboratory (NREL), to simulate and

analyze light and heavy vehicles, including hybrid and fuel

cell vehicles [3]. It allows the user to perform rapid analysis ofthe performance, emissions and fuel economy of conventional,

electric and hybrid vehicles.

ADVISOR was initially developed as an analysis tool,

rather than a detailed design tool. Its components are created

as a quasi-stated model, and therefore, it cannot be used to

perform dynamic analysis. ADVISOR utilizes a backward

looking vehicle simulation architecture, in which the required

and desired vehicle speeds are used as the inputs to determine

the required drivetrain torque, speed and power [4].

Figures 2, 3 and 4 show the ADVISOR screens of input,

simulation setup and results, respectively. The ADVISOR

model has been validates and used as a benchmark of

reference model. The ADVISOR model vehicle contains two

separate EMs which are used as the motor and generator,respectively, and no Ultracapacitor in the ESS. The proposed

PHEV, however, has only one EM which functions as either a

motor or generator at a time, specified by the special energy

management scheme, and an Ultracapacitor bank for fast

charging and discharging during the regenerative braking and

fast acceleration.

To simulate the proposed PHEV, we have derived a model

and compiled a PHEV code. This code is verified by

comparing the simulation results of the ADVISOR model

HEV.

Figure 1. Block diagram of PHEV configuration

III. VEHICLE MODELINGThe vehicle type selected is an average 5-passenger sedan,

which is the majority of the vehicles on road. Table 1 lists the

parameters of a typical vehicle of this type [5]. In the

simulation, the air density is chosen as 1.18 kg/m3, and the

gravitational acceleration 9.81 m/s2.

EM

Wheel

Gear Reduction

PCU

ICE

ESS

Wheel

2008 Australasian Universities Power Engineering Conference (AUPEC'08) Paper P-274 Page 1

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Figure 2. ADVISOR vehicle input screen

Figure 3. ADVISOR simulation setup screen

Figure 4. ADVISOR results screen

TABLE IPARAMETERS OF AN AVERAGE 5-PASSENGER SEDAN

Name Value Units

Aerodynamic drag coefficient 0.29 -

Coefficient of rolling resistance 0.01 -

Frontal area 2.52 m2

Wheel radius 0.291 m

Vehicle mass 1255 kg

The development of the vehicle models begins with

calculations of vehicle energy and power requirements for

typical driving conditions based on the parameters and target

specifications of the vehicle. The size and capacity of each

vehicle component are then determined through a power flow

analysis accordingly to meet these requirements. Combining

the constitutive equations of all components, we obtain a

mathematical model of the vehicle. The vehicle performance

for a given EMS and driving cycle is simulated in the

MATLAB/SIMULINK environment. Figure 5 illustrates the

overall structure of the PHEV model inMATLAB/SIMULINK [6-8].

Figure 5. Overall structure of the PHEV model in MATLAB/SIMULINK

IV. ENERGY MANAGEMENT STRATEGYThe EMS is responsible for deciding in which mode that the

vehicle is operating. Figure 6 shows various operation modes

of the proposed EMS to control the distribution of power

amongst the components, which are mechanical braking,

regenerative braking, motor only, engine recharge, engine and

motor assist and engine only mode according to the vehicle

power demand in acceleration and deceleration and the ESS

SOC level [911].

V. SIMULATION RESULTSA standard U.S. EPA (Environmental Protection Agency)

drive cycle for highway driving is simulated by ADVISOR

and the PHEV code. Figure 7 illustrates the time history of the

HWFET drive cycle.


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Figure 11. ESS voltage in HWFET cycle (Blue: PHEV, Red: ADVISOR)

Figure 13 illustrates the State-Of-Charge (SOC) of the ESS

system for the HWFET drive cycle. The overall trends of the

energy consumption and generation of the two models match

reasonably well. However, there is some discrepancy between

the ESS SOC results of the PHEV and ADVISOR codes. This

is because the PHEV code has a better EMS and can capture

more regenerative braking energy.

The EM speed, torque and power of the PHEV and

ADVISOR codes for the HWFET drive cycle are included in

Figures 14, 15 and 16. As shown in the simulation results,

when the vehicle accelerates, the required Motor/Generator

torque increases quickly, and when the vehicle reaches the

relatively stable highway velocity level, a much smaller torque

is required o overcome the resistance and air drag to the

vehicle. The average power demand from the Motor/Generatoris 8 kW at the highway velocity level and the peak power

demand is 24 kW during the acceleration. The speed, torque

and power results from the two codes match reasonably well.

However, the PHEV code exhibits lower torque and input

power than the ADVISOR code.

Figure 17 and 18 depict the wheel speed and torque

requirement for the HWFET drive cycle simulated by two

codes. The maximum wheel torque, 600Nm, occurs when the

vehicle is accelerating from standstill to the highway speed.

The required torque then reduces since the HWFET drive

cycle only consists of mild accelerations and decelerations.

The overall results and trends match very closely. However, it

is noted that there are several differences between the

magnitudes of the wheel torque. It can be attributed to

difference between the two strategies.

Figure 12. ESS output power in HWFET cycle (Blue: PHEV, Red: ADVISOR)

Figure 13. ESS SOC in HWFET drive cycle (Blue: PHEV, Red: ADVISOR)

Figure 14. EM speed in HWFET drive cycle (Blue: PHEV, Red: ADVISOR)


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Figure 15. EM torque in HWFET drive cycle (Blue: PHEV, Red: ADVISOR)

Figure 16. EM input power in HWFET cycle (Blue: PHEV, Red: ADVISOR)

Figure 17 and 18 depict the wheel speed and torque

requirement for the HWFET drive cycle for two codes. The

maximum wheel torque, 600Nm, occurs when the vehicle is

accelerating from standstill to the highway speed. The

required torque then reduces since the HWFET drive cycle

only consists of mild accelerations and decelerations. The

overall results and trends match very closely. However, it is

noted that there are several differences between the

magnitudes of the wheel torque. It can be attributed to

difference between the two strategies.

Figure 19 plots the acquired and required speeds of the

HWFET drive cycle. It can be seen that acquired and required

speeds agree reasonably well. The PHEV code followed the

required drive cycle speed very well for the standard drive

cycle used to simulate highway driving.

Figure 17. Wheel speed in HWFET cycle (Blue: PHEV, Red: ADVISOR)

Figure 18. Wheel torque in HWFET cycle (Blue: PHEV, Red: ADVISOR)

Figure 19. HWFET cycle (Green: required speed, Magenta: acquired speed)


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VI. CONCLUSIONThe results of the vehicle subsystems in terms of ESS

current, voltage, output power and SOC, Motor/Generator

speed and torque, vehicle speed and force and wheel speed

and torque are within reasonable and expected range of actual

typical behavior of these subsystems. The components of the

vehicle subsystems are correctly sized as the vehicle is

capable of achieving performance to a target velocity. Incombination with previous discussion, it can be concluded that

results of the PHEV code are correct

ACKNOWLEDGEMENT

This research is part of the work performed by the Centre of

Intelligent Mechatronic Systems, University of Technology,

Sydney, Australia.REFERENCES

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[3] B. K. Wipke, ADVISOR 2.1: A User-friendly Advanced PowertrainSimulation using a Combined Backward/forward Approach, IEEETransactions on Vehicular Technology, vol. 48, 1999, pp 1751-1761.

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