scholarly journals Research on Braking Force Distribution Strategy of Composite Braking System of Electric Vehicle

2015 ◽  
Author(s):  
Kuiyang Wang ◽  
Liang Zhu ◽  
Shanfeng Wang
Keyword(s):  
Electric Vehicle ◽  
Force Distribution ◽  
Distribution Strategy ◽  
Braking System ◽  
Braking Force

Study on Braking Force Distribution Strategy for a Hydraulic Regenerative Braking System

2014 ◽  
Vol 543-547 ◽  
pp. 1529-1532 ◽  
Author(s):  
Yu Ting Huang ◽  
Liang Chu ◽  
Yi Yang ◽  
Shi Tong Zhang
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Working Condition ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Matlab Simulink ◽  
Distribution Strategy ◽  
Braking System ◽  
Braking Force

This paper is based on a type of hybrid electric vehicles regenerative braking system. The target is to reduce the fuel consumption and improve the energy recovering rate. In this paper,a new braking force distribution strategy that based on two kinds of working condition will be studied. And it will be validated in MATLAB/Simulink and CRUISE.

Intelligent optimization of EV comfort based on a cooperative braking system

2021 ◽  
pp. 095440702110044
Author(s):  
Lingying Zhao ◽  
Min Ye ◽  
Xinxin Xu
Keyword(s):  
System Model ◽  
Regenerative Braking ◽  
Coupling Mechanism ◽  
Intelligent Algorithm ◽  
Distribution Strategy ◽  
Braking System ◽  
Logic Diagram ◽  
Braking Torque ◽  
Braking Force ◽  
The Time Domain

To address the comfort of an electric vehicle, a coupling mechanism between mechanical friction braking and electric regenerative braking was studied. A cooperative braking system model was established, and comprehensive simulations and system optimizations were carried out. The performance of the cooperative braking system was analyzed. The distribution of the braking force was optimized by an intelligent method, and the distribution of a braking force logic diagram based on comfort was proposed. Using an intelligent algorithm, the braking force was distributed between the two braking systems and between the driving and driven axles. The experiment based on comfort was carried out. The results show that comfort after optimization is improved by 76.29% compared with that before optimization by comparing RMS value in the time domain. The reason is that the braking force distribution strategy based on the optimization takes into account the driver’s braking demand, the maximum braking torque of the motor, and the requirements of vehicle comfort, and makes full use of the braking torque of the motor. The error between simulation results and experimental results is 5.13%, which indicates that the braking force’s distribution strategy is feasible.

scholarly journals Research on braking energy recovery strategy of electric vehicle based on ECE regulation and I curve

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041987776 ◽  
Author(s):  
Shengqin Li ◽  
Bo Yu ◽  
Xinyuan Feng
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
State Of Charge ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Battery State Of Charge ◽  
Braking Force ◽  
Braking Control ◽  
Braking Energy Recovery

Electric vehicles can convert the kinetic energy of the vehicle into electric energy for recycling. A reasonable braking force distribution strategy is the key to ensure braking stability and the energy recovery rate. For an electric vehicle, based on the ECE regulation curve and ideal braking force distribution (I curve), the braking force distribution strategy of the front and rear axles is designed to study the braking energy recovery control strategy. The fuzzy control method is adopted while the charging power limit of the battery is considered to correct the regenerative braking torque of the motor, the ratio of the regenerative braking force of the motor to the front axle braking force is designed according to different braking strengths, then the braking force distribution and braking energy recovery control strategies for regenerative braking and friction braking are developed. The simulation model of combined vehicle and energy recovery control strategy is established by Simulink and Cruise software. The braking energy recovery control strategy of this article is verified under different braking conditions and New European Driving Cycle conditions. The results show that the control strategy proposed in this article meets the requirements of braking stability. Under the condition of initial state of charge of 75%, the variation of state of charge of braking control strategy in this article is reduced by 8.22%, and the state of charge of braking strategy based on I curve reduces by 9.12%. The braking force distribution curves of the front and rear axle are in line with the braking characteristics, can effectively recover the braking energy, and improve the battery state of charge. Taking the using range of 95%–5% of battery state of charge as calculation target, the cruising range of vehicle with braking control strategy of this article increases to 136.64 km, which showed that the braking control strategy in this article could increase the cruising range of the electric vehicle.

Research on Electro-Mechanical Braking System Control of EV Based on Maximum Energy Recovery Strategy

2015 ◽  
Vol 740 ◽  
pp. 196-200
Author(s):  
Qing Nian Wang ◽  
Shi Xin Song ◽  
Shao Kun Li ◽  
Wei Chen Zhao ◽  
Feng Xiao
Keyword(s):  
Control Strategy ◽  
Influence Factors ◽  
Maximum Energy ◽  
Regenerative Braking ◽  
Force Distribution ◽  
System Control ◽  
Braking System ◽  
Power Battery ◽  
Braking Force ◽  
The Ideal

With the analysis of influence factors on regenerative braking in electro-mechanical braking system, and considering the power battery charging characteristics, a regenerative braking system control strategy for electric vehicle is researched in this paper. The models of the motor and the whole vehicle are built in AMESim. The control effects and the braking force distribution on front and rear wheels of the control strategy in an FTP-72 driving cycle are simulated and analyzed. The simulation results show that the control strategy could be utilized in the 4WD electric vehicles. The ideal braking force distribution on front and rear wheels and the high amount of recovery energy could be achieved.

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