Research On Optimal Control Strategy Of Braking Energy Recovery Of Pure Electric Vehicle Based On Driving Style

As an important energy-saving technology for electric vehicles,brake energy recovery has received extensive attention from researchers.The style of different drivers can directly affect the efficiency of braking energy recovery.Electric vehicles are currently the focus of attention in the industry.This article takes pure electric vehicles as an example,and takes the driving style of drivers in electric vehicles and the energy consumption efficiency of the driving process as the goal,ensuring safety during the driving process as the premise,and studies the braking energy recovery efficiency of electric vehicles based on the driving style optimization.The main content of this article is summarized as follows:(1)A forward model of a pure electric vehicle composed of a driver model and a tire model was constructed to analyze the correlation between driving style and energy consumption during vehicle driving.After comparing and verifying the collected real vehicle road data,the average steering wheel angle and change rate,the average deceleration pedal opening and change rate According to the correlation between energy consumption and the six key characteristic parameters of electric vehicles,such as the average opening and change rate of the accelerator pedal,the impact of behavioral characteristic parameters corresponding to different driving styles under different road conditions on vehicle energy consumption was further studied,laying the foundation for establishing an energy consumption rating model for identifying driving styles.(2)In order to solve the problem that there are many identification parameters in the energy consumption level identification model,the PSO-BP neural network algorithm is selected to optimize the key parameters in the model to achieve the purpose of identifying the energy consumption level corresponding to the handling behavior of drivers with different driving styles.Through experimental verification,it can be concluded that the PSO-BP neural network model can better meet the needs of identifying different driving styles compared to ordinary BP neural network models.(3)Based on the braking energy recovery control strategy of the energy consumption level identification driving style model of the PSO-BP neural network,a complete real vehicle road test scheme was designed,and a real vehicle road test device was established.Three sports drivers and three energy-saving drivers were selected for testing at the prescribed test route site.The results of real vehicle road tests indicate that:1)The optimized control strategy for braking energy recovery designed in this paper can significantly reduce the longitudinal impact generated by vehicle braking,suppress the coupling torque generated by motor braking and mechanical braking during vehicle braking,and thereby enhance the braking experience of the driver during vehicle operation;2)Compared to the control method based on BP neural network identification and SVR support vector machine identification,the control method based on PSO-BP identification is more accurate in energy consumption level identification,resulting in better driving experience and energy saving during braking.For drivers with different driving styles,the vehicle energy saving effect controlled by sports drivers is better,reflecting the effectiveness of the braking optimization control strategy.