基于粒子群优化的电动汽车再生制动模糊控制

Regenerative braking system for EV with fuzzy control based on particle swarm optimization

针对某型电动汽车制动能量回收系统,文章设计了控制再生制动力分配的模糊控制器。为提高制动能量回收的效率,保证车辆制动稳定性,提出在模糊控制的基础上,应用粒子群算法对模糊控制器的模糊规则进行优化。对不同初始速度与不同电池荷电状态下的一般制动工况进行仿真分析。仿真结果表明,基于粒子群优化的模糊控制器,在ECE法规的前提下,回收的制动能量相对于优化前有明显改善。

Aiming at a regenerative braking system of electric vehicle （EV） ,the regenerative braking force distribution fuzzy controller is designed .Taking braking energy regeneration efficiency and braking stability as design targets ,the particle swarm optimization（PSO） algorithm is used to optimize the rules of fuzzy controller based on the fuzzy control .The simulations are conducted under normal braking conditions with different initial speed and different initial state of capacity （SOC） of battery .The results show that the regenerative braking energy is obviously improved by the fuzzy controller based on particle swarm optimization under the constraint of ECE regulation .