Study Of Regenerative Braking Control Strategy For Pure Electric Vehicle

With the global popularity of the automobile,the energy crisis and environmental problems have increased significantly.Under such circumstances,the promotion of new energy vehicles,mainly pure electric vehicles,should be regarded as an effective method to solve the energy consumption and environmental pollution problems.However,the pure electric vehicle industry is limited by the slow development of battery energy storage technology,and the lack of vehicle range has become an obstacle to the popularization of pure electric vehicles.Therefore,braking energy recovery technology realize the recovery of electrical energy from the motor braking have a positive effect on improving the endurance and the energy utilization rate of the vehicle.This paper aims to study the regenerative braking control strategy of the pure electric vehicle,realizing the maximization of energy recovery under the braking safety restriction conditions.First of all,the structure of the braking energy recovery system,the working principle of the energy recovery system and the main factors affecting the energy recovery effect of the pure electric vehicle are analyzed in detail.The distribution mode of mechanical braking force and electromechanical force of the braking energy recovery system is studied.Then,the braking force distribution range of the front and rear axles which can guarantee the braking stability is defined through the analysis of the tire force during braking.Combined with the typical regenerative braking force distribution mode of front and rear shafting,an improved braking force distribution range of front and rear shafting which can take into account both braking safety and energy recovery efficiency is proposed.Secondly,this study analyzed the restriction conditions of the power distribution of the electric mechanism.On the premise of the improved braking force distribution rules of the front and rear shafting,this paper designed three regenerative braking energy recovery control strategies.Firstly,the regenerative braking force distribution strategy of maximizing the front shaft motor is proposed.Secondly,based on the characteristics of nonlinear control of the power distribution of the electric mechanism under the system constraints,this paper propose a multi-input fuzzy control regenerative braking force distribution strategy based on braking intensity Z,battery SOC value and the vehicle speed V.Thirdly,aiming at the fuzzy control defects,this paper also proposed a fuzzy regenerative braking control strategy optimized by a genetic algorithm.Then,this paper used Cruise and Matlab simulation software to conduct joint simulation tests under urban cycle conditions and conventional braking conditions.In NEDC and FTP75 cycles,based on braking allocation strategy based on speed lookup table,the effectiveness of the fuzzy control regenerative braking strategy was verified.Besides,The verification results show that the strategy is feasible.Under city driving cycles and conventional braking conditions,three types of regenerative braking control strategies are simulated and analyzed.The results show that:The first is the recovery effect of fuzzy control regenerative braking strategy after genetic optimization is improved compared with that before optimization,which indicates that the optimization method adopted in this paper achieves the optimization effect and can further improve the amount of energy recovery.Moreover,the maximum regenerative braking control strategy has a slightly higher energy recovery than the fuzzy control regenerative braking strategy before and after optimization,but the gap between the three strategies is small,indicating that the fuzzy control regenerative braking strategy in this paper can effectively use the electric mechanism power.Therefore,through comprehensive analysis,the regenerative braking strategy based on fuzzy control is more able to comprehensively consider the influencing factors of energy recovery.Among the three control strategies,the regenerative braking strategy based on fuzzy control after genetic optimization is more advantageous.