Research On Lateral Control Of Autonomous Vehicle Based On Tire Lateral Stiffness Adaptation

With the development of technology and the application of 5G communication technology,intelligent and networked cars have become an inevitable trend of development.Autonomous vehicles have become the focus of current industry research,and motion control,as one of the core technologies of autonomous vehicles,has become a hot issue for academic research.The motion control of autonomous vehicles mainly includes longitudinal speed control and lateral steering angle control.This thesis will focus on the lateral motion control of autonomous vehicles,and the main contents are as follows.(1)Design tire lateral force observer.Analyze the nonlinear relationship between tire lateral force and tire sideslip angle,and take easily measurable quantities such as vehicle yaw rate and lateral acceleration as inputs to build a tire lateral force observer based on sliding mode observer;Validation of a tire lateral force observer based on the Car Sim/Simulink simulation platform;Designing a tire lateral deflection stiffness adaptive criterion using the observed tire lateral forces for use in the subsequent design of the model predictive control.(2)Lateral control strategy based on model predictive control.Establishing the tracking error model based on the model predictive control theory,applying the designed adaptive criterion of tire lateral deflection stiffness to the tracking error model.Design the objective function and set up constraints to obtain the model predictive controller and adaptive model predictive controller.Simulation experiments are conducted using Car Sim/Simulink to verify the control performance of the two controllers.(3)Lateral control strategy based on active disturbance rejection control.Based on the theory of active disturbance rejection control,controller is established from three aspects: tracking differentiator,extended state observer and nonlinear state error feedback.Simulation experiments based on Car Sim/Simulink are conducted to obtain the optimal combination of parameters of the controller,and comparison experiments are conducted with the traditional PID control algorithm to verify the control performance of the active disturbance rejection control.(4)Real vehicle experiments.Based on the real vehicle experimental platform,real vehicle experiments are conducted,which are divided into four working conditions:double-shifted line condition,circular winding,single-shifted line condition and Ushaped trajectory.By analyzing the vehicle state quantities such as lateral position,heading angle,yaw rate,sideslip angle of the center of mass and lateral acceleration,which can characterize the vehicle trajectory tracking accuracy and vehicle driving stability.It is shown that the controller designed in this paper can also track the target trajectory better in the practical application of the vehicle,and at the same time ensure the stability of the vehicle driving.