Particle Swarm Optimization Algorithm for Regenerative Braking Fuzzy Control of Electric Vehicle

Abstract

Improving raking energy regeneration efficiency is a vital problem of electric vehicle. Particle swarm optimization is introduced for regenerative braking fore distribution fuzzy controller, using membership functions and rules of fuzzy controller as optimization object and using limit of input as constraint condition. In this article, based on the front and rear braking force distribution strategy, a traditional fuzzy controller is designed. Then we show how to use particle swarm optimization algorithm to optimize it. Compared to the traditional one, we carry on some simulations in ADVISOR software. The results show that, the braking torque is improved and the braking energy regeneration efficiency raises by 7.19 percent, which indicates the validity of the proposed fuzzy controller.