Using Of Neural Network Controller And Fuzzy PID Control To Improve Electric Vehicle Stability Based On A14-DOF Model

Abstract

Vehicle safety and control are attracting increased attention among researchers to improve the stability and maneuverability of the electric vehicles EVs. This paper describes the design and implementation for a control system that aims to enhance lateral stability and vehicle handling based on a 14-DOF full vehicle model and using two control methods, which are fuzzy PID control theory and neural network controller. When the control system has been created using the two controllers, the vehicle’s performance is examined at two completely different front steering angles, which are a lane change maneuver and a step steering. Also, this paper aims to compare the performance of the vehicle when using the fuzzy PID controller and the neural network controller. The performance and output analysis of the control systems implemented have shown the efficiency of the controllers proposed. The yaw rate for the vehicle, which indicates the lateral stability and handling has been improved satisfactorily in comparison with the uncontrolled case of the vehicle.