Regenerative Braking Control Strategy to Improve Braking Energy Recovery of Pure Electric Bus

Author(s):  
Yu Jiang ◽  
Yanping Zheng ◽  
Yang Guo ◽  
Ming Cong
2019 ◽  
Vol 103 (1) ◽  
pp. 003685041987776 ◽  
Author(s):  
Shengqin Li ◽  
Bo Yu ◽  
Xinyuan Feng

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.


2012 ◽  
Vol 490-495 ◽  
pp. 1783-1787
Author(s):  
Guan Feng Li ◽  
Hong Xia Wang

In order to improve the recovery of braking energy in electric vehicles, a braking force distribution control strategy is proposed which the braking force proportion of the front and rear wheels are distributed according to the brake strength, by analyzing the vehicle braking mechanics and related braking regulation, and combining with the motor output characteristics. A simulation is carried out with SIMULINK/ADVISOR, the results show that, comparing with ADVISOR braking force distribution control strategy, the control strategy not only meets braking stability well,but also there are obvious advantages in energy consumption per 100 kilometers,the rate of braking energy recovery and utilization.


2014 ◽  
Vol 701-702 ◽  
pp. 733-738
Author(s):  
Chen Lu Kong ◽  
Mao Song Wan ◽  
Ning Chen ◽  
Li Ya Lv ◽  
Bing Lin Li

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.


2013 ◽  
Vol 724-725 ◽  
pp. 1436-1439
Author(s):  
Hong Yu Zheng ◽  
Rong He ◽  
Chang Fu Zong

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.


Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2202
Author(s):  
Cong Geng ◽  
Dawen Ning ◽  
Linfu Guo ◽  
Qicheng Xue ◽  
Shujian Mei

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.


Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1526
Author(s):  
Hanwu Liu ◽  
Yulong Lei ◽  
Yao Fu ◽  
Xingzhong Li

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.


2013 ◽  
Vol 278-280 ◽  
pp. 360-364
Author(s):  
Jun Wang ◽  
Jian Huang ◽  
Zhi Quan Qi

In order to improve braking stability and energy recovery ability of electric buses, a new-type electronic-controlled pneumatic regenerative braking system for electric buses was designed. The regenerative braking system controls pneumatic braking force of front and rear wheels by high-speed solenoid valves, which could coordinate mechanical and regenerative braking force effectively. A simulation model of electric bus braking process was established, as well as regenerative braking control strategy. Simulink and AMESim joint simulation analysis of braking process of electric bus was run. The results show that energy recovery of the new-type regenerative braking system is effective and braking control strategy is reasonable.


2017 ◽  
Vol 872 ◽  
pp. 331-336 ◽  
Author(s):  
Zhi Jun Guo ◽  
Dong Dong Yue ◽  
Jing Bo Wu

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.


2020 ◽  
Vol 10 (5) ◽  
pp. 1789 ◽  
Author(s):  
Hanwu Liu ◽  
Yulong Lei ◽  
Yao Fu ◽  
Xingzhong Li

Currently, the researches on the regenerative braking system (RBS) of the range-extended electric vehicle (R-EEV) are inadequate, especially on the comparison and analysis of the multi-objective optimization (MOO) problem. Actually, the results of the MOO problem should be mutually independent and balanced. With the aim of guaranteeing comprehensive regenerative braking performance (CRBP), a revised regenerative braking control strategy (RRBCS) is introduced, and a method of the MOO algorithm for RRBCS is proposed to balance the braking performance (BP), regenerative braking loss efficiency (RBLE), and battery capacity loss rate (BCLR). Firstly, the models of the main components related to the RBS of the R-EEV for the calculation of optimization objectives are built in MATLAB/Simulink and AVL/Cruise. The BP, RBLE, and BCLR are selected as the optimization objectives. The non-dominated sorting genetic algorithm (NSGA-II) is applied in RRBCS to solve the MOO problem, and a group of the non-inferior Pareto solution sets are obtained. The simulation results show a clear conflict that three optimization objectives cannot be optimal at the same time. Then, we evaluate the performance of the proposed method by taking the individual with the optimal CRBP as the final optimal solution. The comparation among BP, RBLE, BCLR, and CRBP before and after optimization are analyzed and discussed. The results illustrate that characteristic parameters of RRBCS is crucial to optimization objectives. After parameters optimization, regenerative braking torque works early to increase braking energy recovery on low tire-road adhesion condition, and to reduce the battery capacity loss rate at the expense of small braking energy recovery on the medium tire-road adhesion condition. In addition, the results of the sensitivity analysis show that after parameter optimization, RRBCS is proved to perform better road adaptability regarding the distribution of solutions. These results thoroughly validate the proposed approach for multi-objective optimization of RRBCS and have a strong directive to optimize the control strategy parameters of RBS.


2014 ◽  
Vol 898 ◽  
pp. 873-877 ◽  
Author(s):  
Jian Wei Cai ◽  
Liang Chu ◽  
Zi Cheng Fu ◽  
Yan Bo Wang ◽  
Wen Hui Li

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.


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