Research On Control Method And Strategy Of Electric Vehicle Hub Driving Robot

The driving range test for electric vehicles is one of the mandatory tests for the production of new vehicles as stipulated by national regulations.The electric vehicle driving hub driving robot performs the driving mileage test on the rotating hub,which can alleviate the problems of high cost,long time and high error rate in the driving test of the electric vehicle and the existing mechanical driving robot.The objectivity,repeatability and accuracy of the test data are also greatly improved,which is of great significance for improving the test level of electric vehicles in China and ensuring the progress of research and development of electric vehicles.Based on the electric vehicle driving range test system project,this paper uses the unique structure of electric vehicle structure and control,relies on the self-designed electric vehicle hub driving robot,and uses electric signals to complete the control of the vehicle to improve and improve the electric vehicle.The driving performance of the hub-driving robot and the tracking accuracy of the vehicle speed are aimed at combining the theory and practice,and carry out related research work in the aspects of electric vehicle system modeling,vehicle model parameter identification and control algorithm.The main research contents of this thesis include the following aspects:(1)Research on the modeling of electric vehicle systems.By analyzing the longitudinal dynamics of electric vehicles,this paper establishes the longitudinal dynamics model of electric vehicles whose input is the expected torque output of the motor as the vehicle speed.Since the dynamic model of electric vehicles is versatile and cannot reflect the differences between vehicles,it is difficult to apply to actual vehicle tests.This paper draws on the deficiencies of the traditional electric vehicle dynamics modeling method,studies the electric vehicle control strategy,and establishes the electric vehicle control strategy model whose input is the accelerator pedal opening output as the expected torque of the motor.The longitudinal dynamic model and the control strategy model of the electric vehicle are combined to obtain a general model of the electric vehicle.(2)The parameter identification method of electric vehicle model is studied.In order to match the established general model of the electric vehicle with the actual vehicle,the online parameter identification of the electric vehicle general model was carried out.Firstly,the online parameter identification of the electric vehicle longitudinal dynamics model is carried out by using the least squares method.Then,the electric vehicle control strategy model is polynomially fitted by the least squares method to realize the parameter identification of the electric vehicle control strategy model and based on the real vehicle measurement.The data was verified against the general model of the electric vehicle.The test results show that the vehicle parameter identification using least square method is accurate and effective.(3)Research on the speed control method of electric vehicles.The parameter tuning and optimization methods of PID controller are briefly introduced.In order to accurately follow the set condition of electric vehicle and reduce the "fan" of the accelerator pedal,a PID controller based on particle swarm optimization is designed to realize PID control.Online optimization of the parameters of the device.The performance of the driving robot is evaluated from four aspects: speed tracking accuracy,speed error rate,accelerator pedal repeatability and accelerator pedal smoothness,and compared with human driver driving performance.The experimental results show that the PID control method based on particle swarm optimization can effectively overcome the problems of large speed fluctuation and poor system adaptability in the conventional PID control method.The driving of the electric vehicle hub driving robot can realize the smooth control of the accelerator pedal and repeat the control.High sex,and higher superiority with human drivers,can completely replace the human driver for electric vehicle driving mileage test.