Analysis of Influence Factors on Braking Energy Recovery of Pure Electric Vehicle

2014 ◽  
Vol 494-495 ◽  
pp. 214-218
Author(s):  
Jian Wei Cai ◽  
Liang Chu ◽  
Wen Ruo Wei ◽  
Yong Sheng Zhang ◽  
Wen Hui Li
Keyword(s):  
Electric Vehicle ◽  
Energy Recovery ◽  
Control Strategies ◽  
Influence Factors ◽  
Regenerative Braking ◽  
Braking System ◽  
Vehicle Mass ◽  
Braking Control ◽  
Braking Energy Recovery ◽  
Main Influence

Based on the analysis the theoretical of regenerative braking and energy flow of the pure electric vehicle, the main influence factors of braking energy recovery were obtained. Ignoring the energy loss and the efficiency of system components as well as the response delay of the hydraulic braking system, two different regenerative braking control strategies were established without regard to the braking force distribution restrictions of the relevant brake laws. The simulation model was built on MATLAB/Simulink platform to analysis the effect of control strategies, vehicle mass and driving cycle for pure electric vehicle braking energy recovery. It was guidance for the development of pure electric vehicle braking energy recovery control strategy.

scholarly journals Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jiankun Peng ◽  
Hongwen He ◽  
Wei Liu ◽  
Hongqiang Guo
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Control Strategies ◽  
Hierarchical Control ◽  
Regenerative Braking ◽  
Recovery Efficiency ◽  
Braking System ◽  
Braking Torque ◽  
Braking Energy Recovery

This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved.

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.

Study on Regenerative Braking Control Algorithm

2014 ◽  
Vol 898 ◽  
pp. 873-877 ◽  
Author(s):  
Jian Wei Cai ◽  
Liang Chu ◽  
Zi Cheng Fu ◽  
Yan Bo Wang ◽  
Wen Hui Li
Keyword(s):  
Energy Recovery ◽  
Control Strategies ◽  
Regenerative Braking ◽  
Brake Pedal ◽  
Hydraulic Unit ◽  
Recovery System ◽  
Braking Control ◽  
Vehicle Test ◽  
Pedal Feel ◽  
Braking Energy Recovery

Based on the traditional hydraulic unit of ESC, Jilin University developed a braking energy recovery system of uniaxial decoupled. A first-order hysteresis filtering method with filtering time factor adaptively corrected was used to calculate driver's braking demand based on pressure of the master cylinder. A series of fixed partition coefficient control strategy was developed, coordinated control of electrical regenerative braking and hydraulic braking was carried out. Vehicle test was carried out. Vehicle test results show that the brake pedal travel simulator and the braking control strategies can improve the energy recovery, and ensure that the brake pedal feel is consistent with the traditional vehicle.

Analysis of Hydraulic Regenerative Braking System for Electric Vehicle

2012 ◽  
Vol 490-495 ◽  
pp. 195-202 ◽  
Author(s):  
Xiao Bing Ning ◽  
Yao Ting Xu ◽  
Qiu Cheng Wang ◽  
Jue Jiang Chen
Keyword(s):  
Electric Vehicle ◽  
Pid Control ◽  
Energy Recovery ◽  
Dynamic Performance ◽  
Regenerative Braking ◽  
Energy Recovery System ◽  
Braking System ◽  
Recovery System ◽  
Driving Range ◽  
Braking Energy Recovery

In order to increase the regenerative braking energy recovery and the dynamic performance of vehicle start and acceleration in the stage of brake, the hydraulic braking energy recovery system was used with the storage battery braking energy recovery system after comparing kinds of regenerative braking recovery plan and energy storage method. The system was used to do simulation and analysis in vehicle dynamic performance and energy recovery efficiency under the PID control and ECE-15 cycle. The system simulation and analysis results show that using hydraulic regenerative braking system in pure electric vehicle can significantly improve the ability of vehicle’s start-acceleration and the increase in vehicle driving range of around 28%.

Modeling and Simulation of Electro-Hydraulic Compound Regenerative Braking Control Strategy for Electric Vehicle

2014 ◽  
Vol 701-702 ◽  
pp. 733-738
Author(s):  
Chen Lu Kong ◽  
Mao Song Wan ◽  
Ning Chen ◽  
Li Ya Lv ◽  
Bing Lin Li
Keyword(s):  
Control Strategy ◽  
Energy Recovery ◽  
Simulation Software ◽  
Regenerative Braking ◽  
Dynamic Distribution ◽  
Braking System ◽  
Braking Control ◽  
Friction Braking System ◽  
Braking Energy Recovery ◽  
Better Than

This paper mainly discusses the dynamic distribution of regenerative braking system and conventional friction braking system of EV.In order to meet the requirements of vehicle braking stability and recycle the braking energy whenever possible, the paper proposes a control strategy which based on ECE regulation and I curve.Then the proposed control strategy is embedded into the simulation software ADVISOR.The result shows that the control strategy of regenerative braking the paper presented is better than ADVISOR’s own on braking energy recovery, and is especially suitable for frequent braking city conditions.

Research of Electric Vehicle Regenerative Braking Control Strategy Based on EHB System

2013 ◽  
Vol 724-725 ◽  
pp. 1436-1439
Author(s):  
Hong Yu Zheng ◽  
Rong He ◽  
Chang Fu Zong
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Rear Axle ◽  
Regenerative Braking ◽  
Distribution Method ◽  
Braking Force ◽  
Braking Control ◽  
Recovery Simulation ◽  
Braking Energy Recovery

In accordance with ECE-R-13 braking regulations limit line, a regenerative braking control strategy is proposed to improve the braking energy recovery. Based on a Electric Vehicle, the braking distribution method makes the front and rear axle braking force arbitrarily distributed which is more effective to improve the rate of energy recovery. Simulation results show that this braking force distribution method focuses on making the braking force distribute to the drive shaft to a maximum extent and can decrease the vehicle fuel consumption.

scholarly journals Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2202
Author(s):  
Cong Geng ◽  
Dawen Ning ◽  
Linfu Guo ◽  
Qicheng Xue ◽  
Shujian Mei
Keyword(s):  
Control Strategy ◽  
Energy Recovery ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Front Axle ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Braking Force ◽  
Braking Control ◽  
Braking Energy Recovery

This paper proposes a double layered multi parameters braking energy recovery control strategy for Hybrid Electric Vehicle, which can combine the mechanical brake system with the motor brake system in the braking process to achieve higher energy utilization efficiency and at the same time ensure that the vehicle has sufficient braking performance and safety performance. The first layer of the control strategy proposed in this paper aims to improve the braking force distribution coefficient of the front axle. On the basis of following the principle of braking force distribution, the braking force of the front axle and the rear axle is reasonably distributed according to the braking strength. The second layer is to obtain the proportional coefficient of regenerative braking, considering the influence of vehicle speed, braking strength, and power battery state of charge (SOC) on the front axle mechanical braking force and motor braking force distribution, and a three-input single-output fuzzy controller is designed to realize the coordinated control of mechanical braking force and motor braking force of the front axle. Finally, the AMESim and Matlab/Simulink co-simulation model was built; the braking energy recovery control strategy proposed in this paper was simulated and analyzed based on standard cycle conditions (the NEDC and WLTC), and the simulation results were compared with regenerative braking control strategies A and B. The research results show that the braking energy recovery rate of the proposed control strategy is respectively 2.42%, 18.08% and 2.56%, 16.91% higher than that of the control strategies A and B, which significantly improves the energy recovery efficiency of the vehicle.

scholarly journals An Optimal Slip Ratio-Based Revised Regenerative Braking Control Strategy of Range-Extended Electric Vehicle

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1526
Author(s):  
Hanwu Liu ◽  
Yulong Lei ◽  
Yao Fu ◽  
Xingzhong Li
Keyword(s):  
Service Life ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Regenerative Braking ◽  
Improve Energy Efficiency ◽  
Capacity Loss ◽  
Battery Capacity ◽  
Braking Control ◽  
Braking Energy Recovery

The energy recovered with regenerative braking system can greatly improve energy efficiency of range-extended electric vehicle (R-EEV). Nevertheless, maximizing braking energy recovery while maintaining braking performance remains a challenging issue, and it is also difficult to reduce the adverse effects of regenerative current on battery capacity loss rate (Qloss,%) to extend its service life. To solve this problem, a revised regenerative braking control strategy (RRBCS) with the rate and shape of regenerative braking current considerations is proposed. Firstly, the initial regenerative braking control strategy (IRBCS) is researched in this paper. Then, the battery capacity loss model is established by using battery capacity test results. Eventually, RRBCS is obtained based on IRBCS to optimize and modify the allocation logic of braking work-point. The simulation results show that compared with IRBCS, the regenerative braking energy is slightly reduced by 16.6% and Qloss,% is reduced by 79.2%. It means that the RRBCS can reduce Qloss,% at the expense of small braking energy recovery loss. As expected, RRBCS has a positive effect on prolonging the battery service life while ensuring braking safety while maximizing recovery energy. This result can be used to develop regenerative braking control system to improve comprehensive performance levels.

Optimization of Regenerative Braking Control Strategy for Pure Electric Vehicle

2017 ◽  
Vol 872 ◽  
pp. 331-336 ◽  
Author(s):  
Zhi Jun Guo ◽  
Dong Dong Yue ◽  
Jing Bo Wu
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Pso Algorithm ◽  
Regenerative Braking ◽  
Recovery Efficiency ◽  
Constraint Optimization ◽  
Vehicle Model ◽  
Braking Torque ◽  
Braking Control

The regenerative braking strategy for precursor pure electric vehicle was studied in this paper. Firstly, a constraint optimization model was established for the braking force distribution, in which both braking stability and recovery efficiency of braking energy were taken into account. Secondly, Particle Swarm Optimization (PSO) algorithm was applied to optimize the multi key parameters in the model. Finally, the optimized braking torque of the motor was obtained at different speed, different braking strength and different battery charge state. A vehicle model was built to validate the optimized results through simulation. The results showed that, compared with the original control strategy, the optimized control strategy not only could increase the braking stability effectively, but also improve the energy recovery efficiency in a certain extent.

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