An Energy Management System for a Battery Ultracapacitor Hybrid Electric Vehicle Varsha A. Shah, Sanjay G. Karndhar, Ranjan Maheshwari, Prasanta Kundu, Hardik Desai

S V National Institute of Technology, Surat – 395007 Email: vas@eed.svnit.ac.in, karndhar@gmail.com, pk@eed.svnit.ac.in;

Abstract- In this paper, a simple and efficient power split rule based energy management algorithm is designed for optimal sharing of energy between different energy sources in parallel HEV. This algorithm is simulated in MATLAB for Indian driving cycle (urban drive cycle) and Indian express highway drive cycle. The results indicate that the split of power can allow the engine to operate at its best efficiency and the life of battery can also be improved significantly with the introduction of ultracapacitor by maintaining the battery state of charge (SOC) within desired limits.

Keywords- Hybrid electric vehicle (HEV), Ultracapacitor, Battery, Indian Driving Cycle, Energy Management Algorithm (EMA), Battery state of charge (SOC), Electrical vehicles (EV).

List of symbols: FTR = Total tractive force Fla = Linear acceleration force, FgxT = Gravitational force acting on the vehicle on non-horizontal roads Froll = Rolling resistance force FAD = Aerodynamic drag force PBATT = Power supplied by battery PBATTmax = Maximum power limit of battery PUC = Power supplied by ultracapacitor PUCmax = Maximum power limit of ultracapacitor PICE = Power supplied by IC engine PMOTOR = Power supplied by motor PICEon = Minimum power level at which ICE turns on P(ICE+MOTOR)on = Minimum power level at which both ICE and motor are turned on PICEmax = Maximum power limit of IC engine SOCBATTmax = Maximum allowable SOC of battery SOCBATTmin = Minimum allowable SOC of battery SOCUCmax = Maximum allowable SOC of ultracapacitor (100%) SOCUCmin = Minimum allowable SOC of ultracapacitor Pcharging = Charging power Pb = Brake power

I. INTRODUCTION

Conventional vehicles offer many advantages like long drive range, good performance and easy refueling; hence they are dominating the vehicle market. However conventional vehicles have limitations such as air pollution and inefficient usages of fossil fuel. Necessity of the hour is fuel efficient and low emission vehicle without sacrificing the performance,

reliability and safety of the vehicle. Pollution problem can be minimized by using zero emission electrical vehicles (EV) at the cost of limited drive range [1,2]. To overcome limited range of EV and low efficiency of engine, a new concept named as Hybrid Electric Vehicle (HEV) has been suggested in the field of vehicle technology. HEVs are the best tradeoff between EV & conventional vehicle. HEVs [1,3] have advantages of high performance, long drive range, low emission, high fuel efficiency and capacity to accept regenerative power during braking and allow the use of a downsized internal combustion engine (ICE) compared to conventional vehicle.

Electrical motor is powered by Hybrid Energy Storage system. This hybrid storage device [3,4] has three main characteristics (1) high energy density for driving range (under urban drive condition) (2) high power density for acceleration (starting of HEV) (3) capacity to absorb power during regenerative braking. During acceleration, electric motor requires high current, during normal operation it requires average current & during braking, it generates high current [5]. If electric motor is driven by only battery as driving source, then battery has to deal with power peaks during either acceleration or braking. But battery cannot supply/ absorb such peak power in a short time as battery is high energy but low power density device. Ultra capacitor is low energy density, high power density and long life device. Its operating voltage is in the range of 2.3V to 2.5V [2,4] and offers very high capacitance in terms of thousand of farads. By connecting both the storage devices (battery and ultracapacitor) in parallel a complete Electric Energy Source is built up with high power and energy density which enhances the life of battery and overall performance of HEV.

The energy management algorithm [5] determines the operating mode such as motor only, power assist, engine only and regenerative braking and controls the amount of energy flow among the components of HEV to optimize energy consumption.

Considerable efforts have been made to address various control algorithms to control energy flow through multiple energy sources. Results based on rule based energy split algorithm [6,7] show that both the sources are operated at maximum efficiency. In static optimization [8] method, the power split problem is tackled in terms of optimal control using statistical data of vehicle power demands for known drive

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cycle. But it may not yield optimal power split for any arbitrary drive cycles. As an alternative, a fuzzy logic based energy management [5,9,10] has been proposed. A comparative approach & results show that fuzzy based method is more flexible but requires more design variables. Another approach is based on predictive control [11] for electric vehicle & shows that current drawn from battery is less compared to only DC - link voltage control method. Power split algorithm [12] is based on structured and modular approach with the fuzzy inference engine to regulate the SOC of ultracapacitor in relation with vehicle speed. Power split algorithm based on dynamic optimization will be more accurate under transient condition but due to their preview nature & having more computation requirement they are not implemented but can be used as benchmark based on which intelligent control techniques can be improved or compared against intelligent control techniques such as sliding mode control, Neural Network Control, genetic algorithm. Feed forward simulation method has been suggested by [7,13-19] different authors for power split between engine & electric motor as well as between Hybrid Energy Storage System i.e. ultra capacitor & battery system.

In this paper simplified power split rule based control strategy is proposed. The vehicle has to be operated in charge sustaining mode and energy management algorithm is based on prior knowledge of driving pattern. EMA will select appropriate energy source based on the power demand of the vehicle as well as the SOC levels of the electrical energy sources. Power flow through battery and ultracapacitor can be controlled based on their SOC levels.

II. OBJECTIVE OF HEV MODELING

The objective of this paper is to develop optimum energy and power management technique for parallel HEV having ICE, BLDC Motor, converter and Hybrid Energy storage device (ultra capacitor + Battery) as its components. The structure of the vehicle is simulated as a single rigid body equipped with four wheels. The vehicle mass is assumed to be concentrated in a single point and vehicle dynamics are given by the following force balance equation.

FTR = Fla + FgxT + Froll + FAD…………………….(1) The whole HEV system is simulated in MATLAB. Simple control mechanism is developed to improve performance of ICE as well as maximise utilization of electric power supplied by battery and ultracapacitor under different operating conditions like acceleration, regenerative braking, cruise speed and normal operation for city drive (urban) cycle & highway drive cycle. In this paper, following parallel HEV topology has been modeled and simulated. The data of HEV is shown in Table 1.

Fig. 1. Parallel HEV Configuration [2,3]

III. ENERGY MANAGEMENT ALGORITHM

The algorithm for energy management is rule based. It is developed on the basis of efficiency maps of different drivetrain components and simple engineering logic.

Table 1.

HEV Specification

Vehicle Weight (Curb+Passengers):1500 kg, Frontal area : 2.25 sq. mt.

Engine

Rated power : 20 kW, Max. Torque :690 Nm @ 2500 rpm, Max Speed : 5000rpm, Speed at max. power : 4500 rpm

Motor 27.5 kW BLDC, Max. power:40 kW Max. Torque : 108 Nm, Max. Speed : 10,000 rpm

Battery 220 V, 400 Ah VRLA Ultracapacitor 96 V, 167 F

The input to the HEV model is the drive cycle which is a profile of velocity versus time. The drive cycle is a representation of the speed desired by the driver at different instants. By the knowledge of the current vehicle speed and the desired vehicle speed, the power required by the vehicle (Prequired) is calculated. Depending on the value of Prequired, the energy management algorithm comes into picture and decides whether this power has to be supplied by motor, ICE or a combination of both. At each instant, the energy management system checks the value of power demanded by HEV and the SOC and current levels of battery and ultracapacitor. It is ensured that the SOCs and the currents of the battery and ultracapacitor are within their maximum and minimum limits.

Two power lines indicating PICEon and P(ICE+MOTOR)on are drawn on the engine efficiency map. The engine always operates in the high efficiency region located between these two limits. If power demanded Prequired is less than PICEon, motor supplies the power. If Prequired is between PICEon and P(ICE+MOTOR)on, the engine alone supplies the power. If Prequired is greater than P(ICE+MOTOR)on, the engine delivers the power P(ICE+MOTOR)on which is the maximum power that it can efficiently generate and the remaining power is supplied by the motor. If Prequired exceeds the sum of P(ICE+MOTOR)on and

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PMOTORmax, the motor supplies its maximum power PMOTORmax and the rest of the power is supplied by the IC engine, though it operates beyond the high efficiency region.

Thus depending on the energy source supplying power to the vehicle, there are three modes of operation : (i) motor only (motoring mode), (ii) ICE only and (iii) ICE and motor

1. Motoring or motor only mode (urban drive cycle) In this mode, only motor supplies power to the vehicle.

If ( SOCBATT > SOCBATTmin and SOCUC > SOCUCmin ) and Prequired ≤ PICEon PICE = 0, PMOTOR = Prequired………………(2) a. Acceleration mode (starting, gradient climbing and high speed operation)

At start, it is assumed that battery and ultracapacitor are fully charged from previous operations. From standstill to final steady speed, only motor supplies the power to HEV where the major portion of the power comes from the ultracapacitor through bidirectional DC DC buck boost converter operating in boost mode. The DC DC converter offers the flexibility of selecting the energy storage devices of different voltage rating with respect to common DC bus at which load is connected. As soon as the acceleration is over, vehicle demands average power which is supplied by battery only.

The following equations describe the power sharing between the battery and the ultracapacitor. For PMOTOR ≥ 0 (Pulse power operation) If PMOTOR < PUCmax

PBATT = 0, PUC = PMOTOR,…………..…….(3) If PMOTOR ≥ PUCmax,

PUC = PUCmax, PBATT = PMOTOR - PUCmax......(4) For PMOTOR ≥ 0 (Normal operation) PMOTOR = PBatt,…………………………...(5) b. Charging mode (ultracapacitor charging through battery)

Except for regenerative braking, this mode occurs whenever following condition is satisfied SOCBATT >SOCBATTmin & SOCUC < SOCUCmax

During this battery power delivering mode, charging of ultracapacitor through battery depends on following conditions: If SOCUC > 80 %

Ultracapacitor is not charged If 50% ≤ SOCUC ≤ 80% Battery charges the ultracapacitor at a slower rate If SOCUC < 50% Battery charges the ultracapacitor at a faster rate The rate of charging of ultracapacitor is controlled by the bidirectional DC DC buck boost converter operating in the buck mode. Upper bound on SOCUC is kept at nearly 80% to accept charge from possible regenerative braking. The battery will charge the ultracapacitor only if its own SOC is greater than 80%.

2. ICE only mode (Highway drive cycle) a. ICE powering vehicle only

In this mode, only ICE supplies power to the vehicle. If SOCBATT >SOCBATTmin & SOCUC > SOCUCmin and PICEon < Prequired ≤ P(ICE+MOTOR)on

PICE = Prequired, PMOTOR = 0……………….(6)

b. ICE powering vehicle and charging battery In this mode, power demand of vehicle is less so the ICE

drives the vehicle and charges the battery. ICE generates the charging power Pcharging to charge the battery through the motor working in generating mode. ICE charges the battery within the most efficient region. If the SOC of ultracapacitor goes below its minimum desired level but the SOC of battery is above its minimum acceptable level, the battery will charge the ultracapacitor upto its maximum value by operating the bidirectional DC DC converter in the buck mode which means that if SOC of battery goes below SOCBATTmin, it indicates that the engine has to charge battery. Once the controller enters into battery charging mode, it will come out of it, only after battery SOC reaches upper limit. If SOCBATT < SOCBATTmin and Prequired + Pcharging ≤ PICEmax

PICE = Prequired + Pcharging,………………...(7) PMOTOR = - Pcharging………………………(8)

In charging mode, the engine has to supply the power (Prequired + Pcharging) which even if less than PICEon requires the engine to be turned on to avoid deep discharge of battery. If SOCBATT < SOCBATTmin and Prequired + Pcharging < PICEon

PICE = Prequired + Pcharging,……………….(9) PMOTOR = - Pcharging…………………….(10)

3. ICE and Motor mode In this mode, power required by vehicle is more than the

power that can be efficiently supplied by engine. So motor supplies the excess power to assist the engine. If P(ICE+MOTOR)on< Prequired ≤ P(ICE+MOTOR)on + PMOTORmax and SOCBATT ≥ SOCBATTmin PICE = P(ICE+MOTOR)on ……………….....(11) PMOTOR = Prequired - P(ICE+MOTOR)on ……(12) If P(ICE+MOTOR)on< Prequired ≤ P(ICE+MOTOR)on + PMOTORmax and SOCBATT < SOCBATTmin PICE = Prequired…………………………(13) If Prequired > P(ICE+MOTOR)on + PMOTORmax and SOCBATT ≥ SOCBATTmin PICE = Prequired - PMOTORmax……………(14) PMOTOR = PMOTORmax…………………..(15) If Prequired > P(ICE+MOTOR)on + PMOTORmax and SOCBATT < SOCBATTmin PICE = Prequired,………………………...(16) since the battery SOC should not cross its lower limit.

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4. Regenerative Braking mode Whenever brakes are applied or the vehicle declines through

a gradient, the motor operates as a generator and the regenerative braking energy is used to charge ultracapacitor and battery. In case of brakes applied to retard the vehicle, if the braking power required exceeds the retarding power provided by the regenerative braking, mechanical brakes are applied. If SOC of ultracapacitor is less than its upper limit, the regeneration energy is used to charge the ultracapacitor but if the ultracapacitor is fully charged, same is used to charge the battery. In case both are fully charged, regenerative energy is dissipated in brake resistors. If Prequired ≥ PMOTORmin PICE = 0, PMOTOR = Prequired, Pb = 0,…….(17) If Prequired < PMOTORmin PICE = 0, PMOTOR = PMOTORmin, ……..…(18) Pb = Prequired - PMOTORmin……………....(19) If PMOTOR < 0 : motor acts as a generator If SOCUC < SOCUCmin & SOCBATT > SOCBATTmin PMOTOR = PUC……………………….…(20) If SOCUC > SOCUCmin & SOCBATT < SOCBATTmin PMOTOR = PBATT………………………..(21)

IV. SIMULATION RESULTS

In this paper, the HEV model prepared has been simulated for Indian driving cycle [13] (urban driving cycle) and Indian express highway driving cycle. The system is simulated as per the developed energy management algorithm and the results show that the system is operating efficiently.

Fig. 2 shows the complete model of parallel HEV simulated in MATLAB. Fig. 3 shows the performance of the HEV based on the developed rule based algorithm for Indian Driving Cycle (urban drive cycle). The total power demanded by the vehicle is supplied by motor only through either ultracapacitor or battery and ICE is not supplying any power. The results show that the SOCs of battery and ultracapacitor are maintained within desired levels under all conditions. Peak power is supplied / absorbed by ultracapacitor while the average power is supplied by battery. Fig. 4 shows the performance of HEV for highway driving cycle. The vehicle starts with the help of electric motor and the engine takes over when the vehicle reaches its final cruising velocity. During initial acceleration part, the accelerating power is supplied by ultracapacitor while the steady average power is supplied by battery. During cruising, power is supplied solely by IC engine and the braking is implemented through mechanical brake.

Fig. 2. HEV Simulation

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Fig. 3. Battery and ultracapacitor performance results for simulation of parallel HEV for Indian Driving Cycle [20] (Urban Driving Cycle)

V. CONCLUSION

Optimal energy flows from different energy sources are obtained with the help of simple rule based energy management algorithm with known drive cycle. It can be concluded that

1. Since ICE is relieved of supplying the peak power during acceleration, it can be downsized.

2. In urban drive cycle, ICE is in shut off mode (not started) and the battery ultracapacitor hybrid energy storage system propels the vehicle. The transient part of the vehicle load demand is supplied by ultracapacitor only which relieves the battery of supplying peak power. So battery supplies only the average power under urban drive cycle. Thus inclusion of

ultracapacitor leads to reduced battery size and increased battery life due to battery SOC being maintained within desired limits. And as the ICE is in shut off mode in urban drive cycle, emissions are reduced.

Fig. 4. ICE, Battery and ultracapacitor performance results for simulation of parallel HEV for Indian Express Highway Driving Cycle

In highway drive cycle, as the ICE is not used for starting and acceleration of vehicle, ICE is shut off during that period which leads to reduced emissions.

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An efficient control strategy for managing the energy and power flow in a hybrid electric vehicle succeeds in using the optimally suited energy source for the given load demand and thus achieves the best possible utilization of all the energy sources without compromising the vehicle performance.

ACKNOWLEDGEMENT

The authors acknowledge the support of SVNIT, Surat,

INDIA for this work.

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