The benefits of electromechanical braking (EMB) systems are short response time, high braking efficiency, ease of assembly and easy integration with other electronic control systems. Therefore, a model of an EMB system is developed based on which the braking stability, braking efficiency, and the regenerative braking energy recovery in electric vehicles are investigated. Electric vehicles can effectively increase their driving range by using a rational regenerative braking control strategy. Firstly, a fuzzy regenerative braking control strategy is developed for comparison, and an optimized regenerative braking control strategy is designed based on the NSGA-II algorithm. The technique for order preference by similarity to ideal solution (TOPSIS) is used to comprehensively evaluate the Pareto optimal solution set and to select an optimal solution for the optimization problem. Secondly, a Takagi-Sugeno fuzzy neural network is trained with the optimized discrete data, and then the braking force distribution controller is obtained. Simulink and AVL CRUISE are used to simulate the control strategy. The simulation results for variable intensity braking conditions and cyclic conditions NEDC, FTP75, and CLTC-P show that the optimized control strategy outperforms the fuzzy control strategy in braking stability and braking energy recovery.
Research on Design Optimization and Simulation of Regenerative Braking Control Strategy for Pure Electric Vehicle Based on EMB Systems
2023-01-01
Transactions of FAMENA ; ISSN 1333-1124 (Print) ; ISSN 1849-1391 (Online) ; Volume 47 ; Issue 4 (online first)
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC: | 629 |
Regenerative braking control system based on pure electric vehicle
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