Research On Intelligent Vehicle Path Tracking Control Based On Model Predictive Control

The development of intelligent vehicles provides an important solution to traffic congestion and energy crisis for the future human society.With the progress of 5G,vehicle networking and other key technologies,intelligent vehicle path tracking technology has been greatly developed.Intelligent vehicles that could be applied in various occasions have been developed.And higher requirements for the path tracking performance and driving safety at high speed has been put forward.Model predictive control has the ability of model prediction and optimal solution under multiple constraints.It can predict the motion state of the vehicle in a period of time,and work out the trajectory satisfying the driving stability constraints,which embodies extensive application value for the improvement of the path tracking performance and the enhancement of the driving stability of the vehicle.However,it is difficult to improve the vehicle path tracking accuracy,driving stability,driving safety and riding comfort by only improving the algorithm.The application of four-wheel steering technology in intelligent vehicle motion control can directly and effectively improve the path tracking accuracy of vehicle,and improve the turning attitude and driving stability at high speed.This paper studies the path tracking control of front wheel steering and four-wheel steering vehicles in automatic driving,compares the advantages of four-wheel steering path tracking controller in path tracking over the front wheel steering,and explores the stability control strategy of four-wheel steering vehicles,in order to improve the driving stability of intelligent vehicles in high-speed conditions.The main research contents are as follows:1.Vehicle dynamics model and nonlinear tire model are established to analyze the linear range of tire force in different road conditions.Next,the vehicle dynamics model is established by using Car Sim,and the co-simulation platform of Car Sim and Simulink is built,which lays the foundation for the following simulation research.2.The theoretical basis of model predictive control algorithm is introduced in this paper.According to the vehicle dynamics model,the front wheel steering path tracking controller based on linear time-varying model predictive control is designed.The feasibility of the controller is verified by simulation,and the influence of controller parameters on path tracking performance is analyzed.3.The problem of intelligent driving path tracking and the steering characteristics of four-wheel steering vehicle are studied and analyzed.On the basis of the research of front wheel steering path tracking control,a four-wheel steering path tracking controller based on model predictive control is designed,which is simulated and verified from the perspective of snake test and double lane shifting respectively.The simulation results show that the designed four-wheel steering path tracking controller is more effective compared with the front wheel steering,and it has higher path tracking accuracy and better driving attitude.4.This paper extends the research of intelligent driving path tracking control to extreme conditions,studying the vehicle stability control strategy at high speed,analyzing the stability of the vehicle system by using the phase plane method and dividing the stability region.Furthermore,the thesis designs the vehicle state parameters envelope constraint according to the phase plane stability region and the zero sideslip angle control target.The stability control is realized by adding tire slip angle constraint and vehicle state parameters envelope constraint to the MPC path following algorithm.The simulation results show that the proposed method can make the vehicle track the reference path steadily,adapt to various road conditions,and improve the stability of the vehicle.