scholarly journals Multi-Objective Optimization Study of Regenerative Braking Control Strategy for Range-Extended Electric Vehicle

2020 ◽  
Vol 10 (5) ◽  
pp. 1789 ◽  
Author(s):  
Hanwu Liu ◽  
Yulong Lei ◽  
Yao Fu ◽  
Xingzhong Li
Keyword(s):  
Control Strategy ◽  
Regenerative Braking ◽  
Multi Objective Optimization ◽  
Braking Performance ◽  
Multi Objective ◽  
Capacity Loss ◽  
Battery Capacity ◽  
Braking Control ◽  
Braking Energy Recovery ◽  
Adhesion Condition

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.

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.

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 Strategy for EV Based on the Vehicle Braking Mechanics

2012 ◽  
Vol 490-495 ◽  
pp. 1783-1787
Author(s):  
Guan Feng Li ◽  
Hong Xia Wang
Keyword(s):  
Energy Consumption ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Energy Recovery ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Braking Force ◽  
Braking Control ◽  
Output Characteristics ◽  
Braking Energy Recovery

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.

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.

Study on Regenerative Braking Control Strategy

2012 ◽  
Vol 588-589 ◽  
pp. 1484-1489
Author(s):  
Tian Li Wang ◽  
Chang Hong Chen ◽  
Qing Jie Zhao ◽  
Ying Xiao Yu
Keyword(s):  
Control Strategy ◽  
Control Strategies ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Braking Force ◽  
Braking Control ◽  
Distribution State ◽  
Avl Cruise ◽  
Braking Energy Recovery ◽  
The Ideal

Based on the analysis about the front and rear braking force distribution curve and the motor anti-drag braking characteristic, the Regenerative Braking Control Strategy which can maintain the capacity of the motor braking energy recovery and make the front and rear braking force distribution closer to the ideal distribution state is proposed. Create a control model. It is simulated by AVL-cruise. The results show that the new control strategies can improve the utilization of ground adhesion coefficient and braking stability.

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.

Simulation of a Regenerative Braking System Producing Controlled Braking Force

2011 ◽  
Vol 383-390 ◽  
pp. 5729-5737
Author(s):  
Jiang Hong ◽  
De Wang Zhang ◽  
Guang Pin Wang ◽  
Ni Sui
Keyword(s):  
Electric Vehicles ◽  
Control Strategy ◽  
Operating Mode ◽  
Regenerative Braking ◽  
Super Capacitor ◽  
Braking System ◽  
Driving Range ◽  
Braking Force ◽  
Braking Control ◽  
Braking Energy Recovery

The pure electric vehicles (PEV) research is mainly focus on regenerative braking. How to improve the efficiency of battery power utilization and increase vehicles’ driving range is a crucial problem. Based on the analysis of braking feeling, super capacitor characteristics and the efficiency of regenerative braking energy recovery, the control strategy of regenerative braking system is firstly established, which has two objective functions. One is to control the regenerative braking force. The other is to improve the recovery efficiency of regenerative braking energy. Then, the main operating mode of regenerative braking system is presented. On this basis, regenerative braking controller that is based on DC-DC controller is designed and implemented in simulink software. The results show that the regenerative braking control strategy can effectively control the regenerative braking force during braking and increase driving range of electric vehicles

Concentrated Driving Electric Passenger Vehicle Braking Control Strategy Optimization

2013 ◽  
Vol 339 ◽  
pp. 183-189
Author(s):  
Jun Zhi Zhang ◽  
Hui Zhou ◽  
Cheng Lin ◽  
Peng Liu
Keyword(s):  
Control Strategy ◽  
Brake System ◽  
Regenerative Braking ◽  
Passenger Vehicle ◽  
Braking Performance ◽  
Electric Bus ◽  
Braking Control ◽  
And Performance

Regarding the centralized driving electric bus as the research object, the influence of Regenerative braking for vehicle braking performance is analyzed, and the original brake system was optimized, a braking control strategy, which does not reduce the vehicle braking safety and performance on the conditions of recovering braking energy as much as possible.

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