A genetic-fuzzy control method for regenerative braking in electric vehicle. (4th April 2020)

• Record Type: Journal Article
• Authors: Liu, Zhiqiang; Lu, Shan; Du, Rong-hua
• Is Part Of: International journal of computing science and mathematics. Volume 11:Number 3(2020)
• Page Start: 263
• Page End: 277
• Publication Date: 2020-04-04
• Subjects: electric vehicle -- braking force distribution -- fuzzy control -- genetic algorithm; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

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.