Research On Distribution Method Of Regenerative Brake For Electric Vehicle Based On Fuzzy Neural Network

With the continuous growth of car ownership,the problems of energy consumption and environmental pollution have become increasingly prominent.As a new energy vehicle,electric vehicles have shown great development potential in the fields of reducing energy consumption and reducing emissions,and have attracted the enthusiasm of many automotive research institutions and development manufacturers worldwide.The cruising range of electric vehicles is a key factor to characterize its performance.Regenerative braking energy recovery is an important means of environmental protection and energy saving for electric vehicles.Designing a reasonable and effective braking force distribution strategy for electric vehicles is a key task for achieving regenerative braking systems to maximize energy recovery and meet the safety performance requirements of electric vehicles.The main content of this article is as follows:Firstly,aiming at the structure of the electric vehicle regenerative braking system,a model of key components was built in the Simulink environment.For the motor braking part,it focuses on analyzing the typical working principle of the motor and battery to complete the system model construction and reasonable parameter matching.For the hydraulic braking part,it focuses on the dynamic mechanism of the solenoid valve,brake wheel cylinder and brake disc And complete the model building.Secondly,according to the requirements of the regenerative braking energy recovery system on the safety and energy saving of the whole vehicle,the perspectives of front and rear axle braking torque distribution and regenerative braking and hydraulic braking torque distribution are analyzed.Considering the ideal braking conditions and the requirements of the vehicle safety regulations ECE,determine the braking force distribution coefficient of the front and rear axles under normal driving conditions.Considering that the regenerative braking performance is affected by driving speed,braking strength and battery SOC,a fuzzy controller is designed to control the above factors to complete the regenerative braking torque distribution.Then optimize the fuzzy process of fuzzy control,complete the design of the self-tuning algorithm of the membership function parameters,and then obtain the fuzzy neural network controller to complete the optimization of regenerative braking force distribution.Thirdly,to verify the effectiveness of the regenerative braking force distribution controller,offline simulation and hardware-in-the-loop simulation are used.Set up an offline simulation model in Simulink,select typical braking conditions and standard driving cycle conditions to verify the effectiveness of the braking force distribution strategy designed in this paper for regenerative braking energy recovery;build a hardware-in-the-loop test system,and integrate the control strategy and model Loaded into the system to further verify the control effect under cyclic conditions.The test results show that the fuzzy neural network controller established after optimization is superior in braking energy recovery.