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

2002 ◽  
Vol 216 (11) ◽  
pp. 855-864 ◽  
Author(s):  
H Yeo ◽  
H Kim
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Continuous Variable ◽  
State Of Charge ◽  
Regenerative Braking ◽  
Vehicle Speed ◽  
Hardware In The Loop ◽  
Battery State Of Charge ◽  
Hybrid Electric

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.

scholarly journals Battery state of charge management strategies for a real-time controller of a Plug-in Hybrid Electric Vehicle

2018 ◽  
Vol 148 ◽  
pp. 258-265 ◽  
Author(s):  
Gabriele Caramia ◽  
Nicolò Cavina ◽  
Michele Caggiano ◽  
Stefano Patassa ◽  
Davide Moro
Keyword(s):  
Real Time ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Management Strategies ◽  
State Of Charge ◽  
Battery State Of Charge ◽  
Charge Management ◽  
Hybrid Electric

Regenerative Braking Potential and Energy Simulations for a Plug-In Hybrid Electric Vehicle Under Real Driving Conditions

2009 ◽  
Author(s):  
L. A. S. B. Martins ◽  
J. M. O. Brito ◽  
A. M. D. Rocha ◽  
J. J. G. Martins
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Regenerative Braking ◽  
Driving Cycles ◽  
Energy Flows ◽  
Hybrid Electric ◽  
Series Type ◽  
Energy Simulations ◽  
Electric Traction

There are several possible configurations and technologies for the powertrains of electric and hybrid vehicles, but most of them will include advanced energy storage systems comprising batteries and ultra-capacitors. Thus, it will be of capital importance to evaluate the power and energy involved in braking and the fraction that has the possibility of being regenerated. The Series type Plug-in Hybrid Electric Vehicle (S-PHEV), with electric traction and a small Internal Combustion Engine ICE) powering a generator, is likely to become a configuration winner. The first part of this work describes the model used for the quantification of the energy flows of a vehicle, following a particular route. Normalised driving-cycles used in Europe and USA and real routes and traffic conditions were tested. The results show that, in severe urban driving-cycles, the braking energy can represent more than 70% of the required useful motor-energy. This figure is reduced to 40% in suburban routes and to a much lower 18% on motorway conditions. The second part of the work consists on the integration of the main energy components of an S-PHEV into the mathematical model. Their performance and capacity characteristics are described and some simulation results presented. In the case of suburban driving, 90% of the electrical motor-energy is supplied by the battery and ultra-capacitors and 10% by the auxiliary ICE generator, while on motorway these we got 65% and 35%, respectively. The simulations also indicate an electric consumption of 120 W.h/km for a small 1 ton car on a suburban route. This value increases by 11% in the absence of ultra-capacitors and a further 28% without regenerative braking.

Introducing predictive Best-Mode controller for minimizing hybrid electric vehicle fuel consumption

2021 ◽  
pp. 095440622110000
Author(s):  
M Khademnahvi ◽  
B Mashadi
Keyword(s):  
Dynamic Programming ◽  
Energy Consumption ◽  
Real Time ◽  
Prediction Accuracy ◽  
Hybrid Electric Vehicle ◽  
State Of Charge ◽  
Lower Sensitivity ◽  
Vehicle Speed ◽  
Battery State Of Charge ◽  
Hybrid Electric

In this paper, a real-time predictive control strategy is developed to control the energy consumption of hybrid electric vehicles with lower sensitivity to prediction accuracy. A predictive Best-Mode concept is introduced based on the future speed predictions, by which the trend of battery state of charge is estimated. The estimated battery state of charge is used to better management of the battery charge mode. The optimum work zones of the components are then selected according to the best battery charging mode and the vehicle speed and power demand. This controller is less sensitive to the prediction accuracy and enables the system to work at the near-optimal points. The results show that the predictive Best-Mode controller is capable of minimizing the energy consumption in real-time applications, very close to the results of the offline dynamic programming with a 2% error margin. The predictive Best-Mode strategy's performance is better than the finite-horizon dynamic programming, except for accurate prediction with a longer than 20-sec prediction horizon.

Development of a Novel Torque Management Strategy for Parallel Hybrid Electric Vehicle

2013 ◽  
Vol 278-280 ◽  
pp. 1729-1736 ◽  
Author(s):  
Xian Wu Gong ◽  
Chuang Gao ◽  
Pei Wang
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Management Strategy ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
The State ◽  
State Of Charge ◽  
Parallel Hybrid Electric Vehicle ◽  
Parallel Hybrid ◽  
Hybrid Electric

In this paper, a torque management strategy for parallel hybrid electric vehicle(PHEV) is developed. The proposed strategy is responsible for vehicle's torque distribution during driving，between the Internal Combustion Engine(ICE) and the electric motor(EM) by Fuzzy Logic Control(FLC). This has been investigated through two main aspects. The first is the optimum torque split between the ICE and the EM. The second is sustaining the State of Charge(SOC) of the battery.These goals have been accomplished by developing two fuzzy logic(FL) controllers. The FL controllers are designed based on the state of charge of the battery, the ICE speed, the vehicle's requested torque and the ICE target torque. The strategy is validated by ADVISOR2002 simulation model based on the software Matlab/Simulink. The performance of the vehicle have been analyzed throughout a combined driving cycle that represents the normal and the worst operating conditions.Compared to the electric assistant control strategy(EACS), The simulation results show that the proposed torque management strategy is effective to control the engine's operating points within the highest efficiency as well as sustain the SOC of the battery. Thereby, improving the efficiency of the ICE and the EM, enhancing the battery’s life, reducing fuel consumption and decreasing emission.

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