Title: A genetic-fuzzy control method for regenerative braking in electric vehicle

Authors: Zhiqiang Liu; Shan Lu; Rong-hua Du

Addresses: School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China ' School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China ' School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China

Abstract: In order to improve the recovery ratio of the regenerative braking energy in electric vehicles, the influence factors on braking energy feedback in electric vehicles were analysed. Then, a parallel braking force distribution model was established, and a fuzzy controller on braking force distribution was designed, in which the inputs were vehicle speed, braking strength, battery SOC, and output was regenerative braking ratio. On the other hand, the implementation of genetic algorithm in optimisation process was studied. Furthermore, the genetic algorithm was used to optimise the fuzzy control rules, and new fuzzy distribution rules of electro-hydraulic braking force were obtained. The experimental results showed that the recoverable energy ratio was increased by 2.7% with the comparison of the optimised distribution rules and the original rules. So, the genetic-fuzzy control method is effective for regenerative braking in electric vehicles.

Keywords: electric vehicle; braking force distribution; fuzzy control; genetic algorithm.

DOI: 10.1504/IJCSM.2020.106699

International Journal of Computing Science and Mathematics, 2020 Vol.11 No.3, pp.263 - 277

Received: 09 Oct 2017
Accepted: 03 Nov 2017
Published online: 20 Apr 2020 *

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