Hardware-in-the-loop simulation of regenerative braking for a hybrid electric vehicle

855 Hardware-in-the-loop simulation of regenerative braking for a hybrid electric vehicle HYeoand HKim* School of Mechanical Engineering, Sungkyunkwan University, Suwon, South Korea Abstract: A regenerative braking algorithm and a hydraulic module are proposed for a parallel hybrid electric vehicle ( HEV ) equipped with a continuous variable transmission (CVT). The regenerative algorithm is developed by considering the battery state of charge, vehicle velocity and motor capacity. The hydraulic module consists of a reducing valve and a power unit to supply the front wheel brake pressure according to the control algorithm. In addition, a stroke simulator is designed to provide a similar pedal operation feeling. In order to evaluate the performance of the regenerative braking algorithm and the hydraulic module, a hardware-in-the-loop simulation ( HILS) is performed. In the HILS system, the brake system consists of four wheel brakes and the hydraulic module. Dynamic characteristics of the HEV are simulated using an HEV simulator. In the HEV simulator, each element of the HEV powertrain such as internal combustion engine, motor, battery and CVT is modelled using MATLAB SIMULINK. In the HILS, a driver operates the brake pedal with his or her foot while the vehicle speed is displayed on the monitor in real time. It is found from the HILS that the regenerative braking algorithm and the hydraulic module suggested in this paper provide a satisfactory braking performance in tracking the driving schedule and maintaining the battery state of charge. Keywords: hybrid electric vehicle, regenerative braking, stroke simulator, continuously variable transmission NOTATION A B F i I J K t M N P r R t T V W front wheel cylinder area battery power force speed ratio current inertia torque constant vehicle mass nal reduction gear ratio pressure brake e ective radius tyre radius torque velocity weight factor The MS was received on 19 April 2002 and was accepted after revision for publication on 22 August 2002. * Corresponding author: School of Mechanical Engineering, Sungkyunkwan University, 300 Chunchun-dong, Suwon, 440-746, South Korea. hskim@me.skku.ac.kr b(i) g m v coe cient e ciency friction coe cient rotational speed 1 INTRODUCTION In regenerative braking, kinetic and potential energy of the vehicle is stored in an energy storing device instead of being dissipated as heat by the friction braking system and the stored energy is recycled to drive the vehicle. In a hybrid electric vehicle (HEV ), the energy recuperation takes place by transforming the mechanical energy into electric energy via a generator. The electric energy stored in the energy storing device such as battery or supercapacitor is used to propel the vehicle via a motor. Recovering the kinetic and potential energy of the vehicle is an e ective approach to improve the vehicle e ciency, especially for the vehicles in heavy stopand-go tra c. Studies in the past showed that an HEV s range for in-city driving can be extended between 14 and 40 per cent by using regenerative braking [1]. Generally, the regenerative braking system works

856 H YEO AND H KIM together with the conventional friction brake for the following reasons: ( 1) the regenerative braking torque is not large enough to cover the required braking torque; (2) the regenerative braking cannot be used for many reasons such as a high state of charge (SOC ) or high temperature of the battery to increase the battery life. In these cases, the conventional friction braking system works to supply the required braking torque. Therefore, in order to apply regenerative braking, a control algorithm on how to distribute the braking torque into the regenerative torque and the mechanical friction torque is required with respect to the battery SOC, motor speed, etc. It is also important to provide a brake feeling that is similar to that of the conventional brake during the regenerative braking. As for regenerative braking, few investigations have been reported. The e ectiveness of regenerative braking was investigated for the electric vehicle ( EV ) and HEV by Gao et al. [2]. They suggested a parallel braking system which has a structure such that the regenerative braking and mechanical braking share the braking force of the front axle with a xed relationship. As for the regenerative braking of the EV, Wyczalk [3] suggested a mathematical formulation of the regenerative braking energy by considering the charging and discharging e ciencies and showed that a signi cant improvement in the regenerative braking could be achieved by adopting a continuously variable transmission (CVT). A regenerative braking algorithm was proposed for the EV from the viewpoint of stability by considering proportioning the braking force to the front and the rear wheel [4]. In Toyota s Prius, an electronically controlled regenerative braking system is introduced for a parallel HEV using a 30 kw motor [5]. The hydraulic module in the brake system consists of an ingeniously designed master cylinder, and a stroke simulator to absorb the brake oil ow. Panagiotidis et al. [6] suggested a regenerative braking model for a parallel HEV using ADVISOR. This model computes the wheel pressure, based on a look-up table yielding the distribution of braking forces between the front and rear wheel and the generator. However, the literature reveals little detail of the modelling of the regenerative braking system or the e ect on the HEV powertrain. In this paper, a regenerative braking control algorithm is presented for a parallel HEV equipped with a CVT and a hydraulic module designed to implement the proposed control algorithm. Performance of the regenerative braking system is investigated by hardware-in-theloop simulation (HILS) using the four wheel brakes and the hydraulic module. For the HEV regenerative braking simulator, dynamic models of the HEV powertrain are derived and used as the software part of the simulator. Fig. 1 Schematic diagram of parallel HEV motor by a single shaft. One clutch is used between the electric motor and the CVT transmission. The transmission, a metal belt CVT, is used to maintain the engine operation on the minimum fuel consumption region independent of the vehicle speed. The HEV used in this study is front-wheel drive. In the HEV in Fig. 1, the front-wheel braking is performed by the regenerative braking ( REGEN ) plus the mechanical friction braking; meanwhile, the rear wheel is purely under friction braking. In order to provide an appropriate REGEN for a given driving condition, a control algorithm is required to determine the magnitude of the regenerative torque with respect to the battery SOG, motor speed, etc. corresponding to the driver s demand. Figure 2 shows the motor characteristic curve used in this study. Negative torque means the regenerative torque that the motor is able to generate. If the required motor torque is a, frontwheel braking can be achieved only by the REGEN since a is smaller than the available motor torque. When a braking torque c which is larger than the available motor torque is demanded, the conventional friction brake has to be operated together with regenerative braking to supply the missing torque, d. When the brake pedal is applied, the ideal motor torque is obtained from Fig. 2. Next, the REGEN torque from the electric motor is determined by considering the battery SOC and the vehicle velocity. These factors are included by a weight factor. In Fig. 3a, the weight factor for the battery SOC is shown. In this study, a weight factor of 1 is used in charging the battery for 2 REGENERATIVE BRAKING ALGORITHM Figure 1 shows a schematic diagram of the parallel HEV used in this study. The engine is connected to the electric Fig. 2 Motor torque characteristics

SIMULATION OF REGENERATIVE BRAKING FOR A HYBRID ELECTRIC VEHICLE 857 torque by Fig. 3 Weight factor for regenerative braking: (a) battery SOC; (b) regenerative torque versus velocity SOC =0 80 per cent to increase the SOC level. For SOC =80 90 per cent, the weight factor decreases linearly. This protects the battery from overcharging that may a ect the battery life. In addition, the magnitude of the REGEN torque varies depending on the vehicle velocity (Fig. 3b). Below V 1, no REGEN torque is generated. From V 1 to V 2, the REGEN torque increases in proportion to the vehicle velocity. In this study, no REGEN torque is applied below V 1, in other words at low speed for the following reasons: (1) the regeneration energy is not large and (2) the comfort could deteriorate. For a velocity above V 2, the maximum motor torque available is applied to obtain as much regeneration energy as possible. Therefore the actual REGEN torque given by the electric motor is obtained as T REG =W 1 W 2 T m (1) where W 1 and W 2 are the weight factors and T m is the electric motor torque determined from Fig. 2. The REGEN torque applied to the front wheel T R is represented as T R =int REG (2) where i is the CVT speed ratio, N is the nal reduction gear ratio and T REG is the regenerative torque provided by the motor. When the REGEN and the friction braking work together, the hydraulic pressure in the front wheel cylinder should be reduced corresponding to the regenerative P= T REG Am 2r (3) where m is the friction coe cient, A is the front-wheel cylinder area and r is the e ective radius. Therefore, the hydraulic pressure P F which needs to be supplied to the front wheel is given by P F =P m P (4) where P m is the master cylinder pressure. Therefore, the total braking torque T F at the front wheel is represented as T F =T R +T f (5) where T is the torque provided by conventional friction braking. f In regenerative braking, the magnitude of the REGEN torque depends on the motor capacity. This may cause a problem when the motor torque capacity is relatively large. For instance, when the motor capacity is large, the REGEN torque may be higher than the demanded braking torque, which results in more velocity reduction than expected. Therefore, the REGEN algorithm needs to be modi ed by considering the motor torque capacity as described below. The driver s demand is estimated from the brake pedal position. The REGEN torque can be determined from the vehicle velocity (Fig. 3b) and the current battery SOC in Fig. 3a. If the demanded braking torque is less than the REGEN torque, the magnitude of the REGEN torque is limited so as not to exceed the demanded braking torque. Where the demanded braking torque is larger than the REGEN torque, the friction braking works together with the REGEN. In Fig. 4, an algorithm to determine the magnitude of the regenerative torque is shown. If the available regenerative torque T is less than the required front braking R torque T, the di erence torque T T should be provided by the friction braking. Thus, at the front wheel, F F R the hydraulic pressure needs to be supplied to generate the friction braking. The front-wheel pressure which is reduced by an amount P is applied. If T is larger than R T, front-wheel braking is achieved only by the REGEN F without mechanical friction braking, which results in zero front-wheel pressure. Braking forces acting on the front and rear wheels are required to be proportional to their corresponding normal load. In order to obtain the maximum braking stability of the vehicle, the distribution of the braking forces on the front and rear wheels should be considered. However, in this study, an ideal distribution of the braking forces is not considered. Instead, here the focus is on how to distribute the front-wheel braking torque on the REGEN and mechanical friction braking by assuming that the braking forces are evenly distributed on the front and rear wheels.

858 H YEO AND H KIM wheel pressure by reducing the master cylinder pressure by the amount P from equations (3) and ( 4). The accumulator pressure is controlled to maintain the pressure between 100 and 120 bar. When the accumulator pressure exceeds the upper limit, the motor turns o and vice versa. This motor on o operation keeps the motor from wasting unnecessary power. In the REGEN process, the oil ow from the master cylinder to the front-wheel cylinder is blocked since the front-wheel pressure is supplied through the reducing valve from the REGEN hydraulic module. This causes an unfamiliar brake pedal feeling for the driver compared with that of the conventional brake system without REGEN. In order to provide a similar pedal feeling, a device to consume the oil ow that is blocked is required. In this study, a stroke simulator is designed as shown in Fig. 6a. Two springs with di erent spring constants are used to simulate the front-wheel cylinder characteristics on the basis of the ow analysis of the brake system used in this study. Figure 6b shows the simulation results of the input ow to the front-wheel cylinder when braking is carried out from 80 to 0 km/h during a period of 5 s. It is noted from Fig. 6 that the stroke simulator designed in this study shows similar ow characteristics to the front-wheel cylinder, which guarantees a similar pedal feeling. Fig. 4 Flowchart for regenerative braking 3 REGENERATIVE BRAKING HYDRAULIC MODULE In order to implement the REGEN algorithm described previously, the REGEN system has to have the following capabilities: (a) measure the master cylinder pressure which is directly related to the driver s demand; (b) calculate the regenerative torque; (c) calculate the available motor torque by considering the battery SOC, motor speed and CVT ratio; (d) provide similar brake pedal feeling to the conventional brake system when the REGEN is used. Figure 5 shows a schematic diagram of the REGEN hydraulic module which is developed in this study to meet the above design speci cations. The REGEN system in Fig. 5 consists of a booster, a master cylinder, a stroke simulator, a reducing valve and a hydraulic power unit. A vacuum booster operated by the engine is used since the engine used in this study is always running in the drive mode. The reducing valve controls the front-wheel pressure according to the REGEN algorithm from the brake control unit (BCU ). When the REGEN works, the reducing valve supplies the front- 4 HILS FOR HEV REGENERATIVE BRAKING The HEV regenerative braking simulator shown in Fig. 7 consists of a hardware part, software part and input/ output (I/O) part. The hardware part is composed of conventional brake system, BCU, brake pedal, digital signal processor, host computer and the REGEN hydraulic module developed in this study. The software part is composed of the HEV dynamic model and driving schedule. A/D and D/A converters for data communication between the hardware and software parts are in the I/O part. 4.1 Hardware part Figure 8 shows the hardware which includes the four wheel calipers, master cylinder, booster, pressure sensor and hydraulic module. The brake pedal is actuated by the operator. The brake pedal force is boosted by the vacuum pump. The rear-wheel cylinder pressure is generated from the master cylinder depending on the brake pedal force. The front-wheel cylinder pressure is supplied from the reducing valve by the BCU signal. A pressure sensor is used to measure the master cylinder pressure, and this signal is transmitted to the HEV simulator to calculate the demanded braking torque. A DS1103 controller board is used as a signal processor; the DSP board has a 400 MHz main processor, 2 Mbyte local SRAM,

SIMULATION OF REGENERATIVE BRAKING FOR A HYBRID ELECTRIC VEHICLE 859 Fig. 5 Regenerative braking system 4.2.1 Vehicle dynamics The state equation of the HEV velocity when the engine and the motor work together is presented as g g i(n/r )(T +T T ) T D t e m LOSS dv dt = F F g g [N2i(di/dt)J/R2]V L b T D t M+(J /R2)+g g (in/r )2J w t T D t (6) where T e is the engine torque, T m is the motor torque, F L is the road load, F b is the brake force, R t is the tyre radius, M is the vehicle mass, g T is the CVT e ciency, g D the is nal reduction gear e ciency and J is the equivalent inertia of the engine and clutch. 4.2.2 Engine Since the engine and the motor are connected, the state equation of the engine is expressed as (J e +J m ) dv e dt =T e +T m T loss T net (7) Fig. 6 Stroke simulator: (a) simulator; (b) ow characteristics 32 Mbyte global DRAM. The HILS is performed in real time by linking the hardware signals to the HEV simulator through the DSP. 4.2 Software part The software part of the HEV REGEN simulator is mainly composed of the vehicle dynamic model and the experimental conditions. Dynamic modelling of the HEV powertrain is explained in this section. where J e and J m are the engine and the motor inertias respectively. v e is the engine speed, T loss is the auxiliary device loss and T net is the CVT input torque. 4.2.3 Motor The motor is used for tractive e ort when the battery is discharged and is used as a generator when the battery is charged, in other words in the regenerative braking mode. When the motor is used for tractive e ort, the motor torque T m is represented as T m =K t I (8) where K t is the motor torque constant, and I is the

860 H YEO AND H KIM Fig. 7 HEV regenerative braking simulator using HILS current. The motor torque transmitted to the wheel can be obtained including the motor e ciency. 4.2.4 Battery The battery SOC is represented as follows: SOC=SOC B c t (9) 0 3600B F where SOC is the battery initial SOC (per cent), B is 0 c the consumed power (kw ), B is the full charge power F (kw) and t is the sampling time. In the charging or discharging process, the inner resistance of the battery changes depending on the battery SOC. This resistance change is considered as an e ciency map. The e ciency map used in this study is shown in Fig. 9. 4.2.5 CVT The CVT shift dynamics plays an integral role in the vehicle response. In addition, the CVT shift dynamics a ects the engine performance on the optimal operation line (OOL). In this study, the following CVT shift dynamics suggested by Ide et al. [7] are used: di dt =b(i)v p (F p F* p ) (10) where b(i) is a constant which is a function of the CVT ratio i, v p is the primary pulley speed, F p is the primary thrust and F* p is the primary thrust at steady state. The CVT ratio needs to be controlled to keep the engine operation point on the OOL for the best fuel economy. The desired CVT ratio i d is de ned as i d = R t v d NV (11) where v d is the desired engine speed which can be obtained as the point where the OOL and the throttle valve opening curve cross each other [8]. The HEV powertrain is modelled using MATLAB

SIMULATION OF REGENERATIVE BRAKING FOR A HYBRID ELECTRIC VEHICLE 861 Fig. 9 Battery e ciency map Fig. 8 Hardware part of HILS SIMULINK. In Fig. 10, the MATLAB model of the HEV powertrain is shown. 4.3 HILS procedure Figure 11 shows a block diagram of the HILS. For a given driving mode, the driver operates the drive pedal to follow the target velocity. The driver pedal operation is modelled by the PID controller in the HEV simulator. From the drive pedal opening A p, and the power map that is constructed from the vehicle test, the vehicle power is determined. For the required vehicle power, the motor power and the engine power are obtained from the operating strategy of the HEV. Since the operating strategy of the HEV is out of the scope of this study, the details are omitted. Once the engine and the motor power are given, the engine and the motor torque can be determined from the optimal engine speed. The optimal engine speed can be obtained from the OOL and Fig. 10 MATLAB model of HEV powertrain

862 H YEO AND H KIM Fig. 11 Block diagram of HILS the iso-power curve of the engine. The wheel torque transmitted through the CVT and the nal reduction gear drives the vehicle. The braking is achieved by the driver s brake pedal operation. In the HILS, the driver operates the brake pedal by watching the vehicle velocity displayed on the monitor in real time. In braking, the driver s demand is estimated from the rear-wheel pressure measured by the pressure sensor and is transformed into the braking force in the HEV simulator. The vehicle velocity is reduced corresponding to the braking force in the simulator. In the case of regenerative braking, the REGEN torque is calculated in the BCU according to the owchart in Fig. 4. The REGEN torque is transformed into the front-wheel braking torque by considering the CVT ratio. The front-wheel pressure is supplied from the reducing valve by reducing the master cylinder pressure by an amount P which is equivalent to the REGEN torque. During the HILS, the vehicle velocity is displayed on the monitor in real time. 5 RESULTS AND DISCUSSION In the HILS, the controllability of the pressurizing system of the hydraulic module and the REGEN algorithm developed in this study is tested instead of testing the actual braking performance. So, the wheels are not loaded or turning. The braking performance is tested by the simulator using the dynamic models of the HEV powertrain. In Table 1, vehicle data used in the HILS are shown. In the HILS, 10 and 30 kw motors are used to evaluate the REGEN algorithm suggested in this study. In Fig. 12, results of the HILS are shown for the 10 kw motor. The actual vehicle velocity (Fig. 12a) follows the target velocity closely. The velocity di erence in the deceleration region is due to the human error in the brake pedal operation. The motor torque shows a positive value when the motor is used to drive the vehicle and shows a negative value when it is used as a generator.

SIMULATION OF REGENERATIVE BRAKING FOR A HYBRID ELECTRIC VEHICLE 863 Table 1 Vehicle data Engine Stroke volume 1600 cm3 Maximum torque 140 N m Motor 10 kw motor torque at 0 r/min 50 N m 30 kw motor torque at 0 r/min 150 N m CVT nal reduction gear CVT gear ratio range 0.455 2.47 Final reduction gear ratio 5.763 Car body Vehicle mass 1380 kg Front projected area 1.964 m2 Drag coe cient 0.346 Tyre radius 0.279 m vided by the 10 kw motor is relatively small. It is seen from Fig. 12d that the rear-wheel pressure still exists after the vehicle stops. This is because the driver pushes the brake pedal for a few seconds after the vehicle stops completely. The front-wheel pressure becomes zero as soon as the vehicle stops since the front-wheel pressure is controlled by the BCU. The CVT ratio ( Fig. 12e) upshifts as the vehicle velocity increases and downshifts during the deceleration. In Fig. 13, results of the HILS for the 30 kw motor are shown. In this simulation, the REGEN algorithm is evaluated for various motor capacities. The HILS are performed using REGEN algorithm I with consideration of the motor capacity adjustment and algorithm II without the motor capacity adjustment. In the HILS without consideration of the motor capacity, it is assumed that the motor REGEN torque increases in proportion to the motor capacity. In the rst deceleration, the vehicle given by algorithm II decreases more than the target velocity ( Fig. 13a) since the motor REGEN torque is larger than the required braking torque (Fig. 13b). The motor REGEN torque given by algorithm II is generated showing a limit torque that is one-half of the maximum torque for the 30 kw motor. When a large motor REGEN Fig. 12 HILS results for 10 kw motor The REGEN motor torque is limited to 25 N m since the REGEN torque is limited to one-half of the maximum motor torque in this study. The battery SOC (Fig. 12c) decreases when the motor is used to propel the vehicle and increases when the motor is used as a generator. The front-wheel pressure ( Fig. 12d) is reduced compared with the rear-wheel pressure by the amount of the REGEN torque. The pressure di erence between the rear- and the front-wheel pressure P has a relatively small value, 3 5 bar, because the REGEN torque pro- Fig. 13 HILS results for 30 kw motor: algorithm I, with motor capacity adjustment; algorithm II, without motor capacity adjustment

864 H YEO AND H KIM torque is applied, mechanical friction braking does not occur, so the front- and the rear-wheel cylinder pressures do not build up (Fig. 13e) When the vehicle velocity decreases below the velocity V 1 where the REGEN starts (Fig. 3b), the REGEN is not used and friction braking works at both the front and the rear wheels. In the case when algorithm I is used, a motor REGEN torque that is equivalent to the required braking torque is generated at the front wheel (Fig. 13b). At the rear wheel, mechanical friction braking works to supply the required braking torque, so the rear-wheel pressure builds up. When the vehicle velocity drops below V 1, the REGEN stops and friction braking is applied. The vehicle velocity given by algorithm I follows the target velocity more closely since the REGEN torque is adjusted by consideration of the motor capacity. Since a larger REGEN torque is generated by algorithm II, the battery SOC given by algorithm II shows a higher value than that of the algorithm I. In the second deceleration, since the required braking torque is larger than the REGEN torque, friction braking and regenerative braking work together. Therefore, the maximum available REGEN torque is generated for both algorithms ( Fig. 13b). It is seen that only a small pressure is applied at the front wheel while the REGEN is working (Figs 13d and e). As soon as the vehicle velocity decreases below V 1, the brake pressure builds up to supply friction braking at both the front and the rear wheel. From the HILS results in Figs 12 and 13, it is found that the REGEN algorithm and the hydraulic module developed in the study provide a satisfactory braking performance while increasing the battery SOC during the regeneration. 6 CONCLUSION A regenerative braking algorithm and a hydraulic module are proposed for a parallel HEV. The regenerative algorithm is developed by considering the battery SOC, vehicle velocity and motor capacity. The hydraulic module consists of a reducing valve and a power unit to supply the front-wheel brake pressure according to the control algorithm. In addition, a stroke simulator is designed to provide a similar pedal operation feeling with the conventional brake system. In order to evaluate the performance of the regenerative braking algorithm and the hydraulic module, HILS is performed. In the HILS, the hardware of the brake system, which consists of four wheel brakes and the hydraulic module, is used. Dynamic characteristics of the HEV are simulated using a HEV simulator. In the HEV simulator, each element of the HEV powertrain such as internal combustion engine, motor, battery and CVT is modelled using MATLAB SIMULINK. In the HILS, a driver operates the brake pedal with his or her foot while the vehicle speed is displayed on the monitor in real time. It is found from the HILS that the regenerative braking algorithm and the hydraulic module suggested in this paper provide a satisfactory braking performance in following the driving schedule while increasing the battery SOC during the regeneration. REFERENCES 1 LaPlante, J., Anderson, C. J. annd Auld, J. Development of a hybrid electric vehicle for the US Marine Corps. SAE paper 951905, 1995. 2 Gao, Y., Chen, L. and Ehsani, M. Investigation of the e ectiveness of regenerative braking for EV and HEV. SAE paper 1999-01-2910, 1999. 3 Wyczalk, F. A. Regenerative braking concepts for electric vehicle a primer. SAE paper 920648, 1992. 4 Bailey, K. E. and Cikanek, S. R. Comparison of energy recovery capability of electric vehicle braking systems. In International Symposium on Advanced Vehicle Control, 1996. 5 Toyota, Prius Manual, 1997. 6 Panagiotidis, M., Delagrammatikas, G. and Assanis, D. Development and use of a regenerative braking model for a parallel hybrid electric vehicle. SAE paper 2000-01-0995, 2000. 7 Ide, T., Uchitama, H. and Kataoka, R. Experimental investigation on shift speed characteristics of a metal V-belt CVT. In Proceedings of International Conference on Continuously Variable Power Transmission, 1996. 8 Kim, H. S. and Kim, T. C. Low level control of metal belt CVT considering shift dynamics and ratio valve on o characteristics. KSME Int. J., 2000, 14, 645 654.