Research on Variable Current Regenerative Braking Control Strategy Based on Radial Basis Function Neural Network Tuning PID Control

Abstract

Nowadays, regenerative braking is one of the most prevalent and important technology applied in EV (electric vehicle). It can extend the driving range of EV by transforming part of kinetic energy into electric energy during the braking process of EV. The research object of this paper is one certain EV with the hybrid electric power which includes lithium ion battery and ultra-capacitor. This paper establishes the circuit mathematical model of RBS (regenerative braking system) and analyzes the system comprehensively. Based on that, this paper designs a braking force distribution method between the front-axle and rear-axle. Under the premise of braking safety, this paper puts forward a variable current regenerative braking control strategy based on RBF (radial basis function) neural network tuning PID control with the aim of maximum energy recovery. In order to prove the validity of the model and the control strategy, this paper contrasts the variable current regenerative braking control strategy with the traditional constant current braking control strategy by bench test and simulation under NEDC driving cycle. The result shows that the variable current regenerative braking control strategy is effective, improving the energy recovery efficiency, extending the driving range of EV.