基于Q学习算法的再生制动能量回收控制策略

Regenerative Braking Energy Recovery Control Strategy Based on Q Learning Algorithm

针对前轴驱动混合动力汽车再生制动过程中电液制动力矩分配问题,提出基于Q学习算法的再生制动能量回收控制策略。文章以制动能量回收效率最大为优化目标,通过Q学习算法优化得到制动力矩分配系数,从而对前后轮机械摩擦制动力和再生制动力进行分配。并基于MATLAB/Simulink软件进行仿真验证,结果表明:与理想制动力分配策略相比,制动能量回收效率提升了6.5%。提出的控制策略能够在保证制动安全的前提下,进一步提高了制动能量回收效率,对于制动能量回收的研究具有重要意义。

Aiming at the problem of electro-hydraulic braking torque distribution in the regenerative braking process of front axle drive hybrid electric vehicles,regenerative braking energy recovery control strategy based on Q learning algorithm is proposed.This paper takes the maximum braking energy recovery efficiency as the optimization goal.By the Q learning algorithm,the braking torque distribution coefficients are obtained,thus the mechanical friction braking force and regenerative braking force are distributed.Based on MATLAB/Simulink software,the simulation model is established.The results show that compared with the ideal braking force distribution strategy,the braking energy recovery efficiency is increased by 6.5%,The proposed control strategy can further improve the efficiency of braking energy recovery under the premise of ensuring braking safety,which is of great significance to the research of braking energy recovery.