Co-simulation Of UM And Simlink For Magnetorheological Control Of High-speed Vehicle Suspension System

With the increase in the operating speed of high-speed trains and the further improvement of the high-speed railway network,the difference in the service environment of trains has increased,and the reliability of long-term stable and safe operation of trains needs to be solved urgently.As one of the key components of the high-speed bogie,the suspension system has an important influence on improving the safety and stability of the vehicle system.Therefore,the development of high-speed vehicle suspension system control research has important theoretical significance and engineering practical value.This paper takes the secondary vertical shock absorber as the control object,and studies the influence of semi-active control methods on vehicle running quality based on magnetorheological technology.The main work is as follows:Establish the Bouc-Wen model of magnetorheological damper,introduce fuzzy PID and RBF neural network control methods,establish magnetorheological fuzzy PID controller and magnetorheological RBF neural network controller respectively,and embed them in the vehicle dynamics model to establish Vehicle coupling model.The magnetorheological fuzzy PID controller determines the fuzzy control rules and membership functions according to the amplitude and direction of the car body bogie disturbance.The vertical speed difference and acceleration difference between the car body and the bogie are used as model input variables,and the semi-active The damping force of the suspension system is used as the output variable.The magnetorheological RBF neural network controller determines the output weight,node center and node base width parameters of the RBF neural network controller based on the gradient descent method.It takes the vertical speed difference between the car body and the bogie as input,and sets three hidden parameters.The containing layer,the output is the current value of the magnetorheological damper.The influence of magnetorheological fuzzy PID controller on vehicle dynamics under seven speed conditions is analyzed on the vehicle model based on the magnetorheological fuzzy PID controller and the magnetorheological RBF neural network controller.The results show that for high-speed vehicles with magnetorheological fuzzy PID control,the wheel-rail vertical force and wheel axle lateral force are reduced.Compared with the passive suspension vehicle,the overall performance of the vehicle is improved,and the safety and comfort of the vehicle operation are improved.The high-speed vehicle controlled by the magnetorheological RBF neural network has a significant reduction in the wheel-rail vertical force during high-speed operation,and the magnetorheological RBF neural network control can effectively inhibit the vertical speed and acceleration of the vehicle body.The magnetorheological fuzzy PID control effect is better,which can effectively improve the dynamic performance of the vehicle system and realize the optimized control of the suspension system of high-speed vehicles.