Study On Lateral And Longitudinal Coordinated Control Of Autonomous Electric Formula Racecar

FSAC,the Formula Student Autonomous China is a series of Formula SAE competitions,which aims to conform the development trend of autonoumous vehicles and the cultivation of related talents.Motion control is one of the core issues in the field of autonomous racecar research,and is the basis for other parts to realize functions.This article aims at the Liaoning University of Technology's autonomous electric formula racecar,and study the lateral,longitudinal,and lateral-longitudinal coordinated control methods of the racecar in the unmanned state.The purpose is to design a stable and feasible lateral,longitudinal,and lateral-longitudinal coordinated control system.The paper combines the actual development project of autonomous electric formula racecar of Liaoning University of Technology,and carries out research under the support of the National Natural Science Foundation of China(51675257).The main research contents are as follows:Firstly,the hardware structure and software structure of the autonoumous racecar are set up.Considering that the autonomous racecar is driving at a high speed and requires good real-time control,a three-degree-of-freedom dynamic model of the vehicle is established for the predictive model of model predictive control in the paper,and a tire model and a motor model are also established.According to the basic parameters of the car,Car Sim and MATLAB/ Simulink joint simulation were used to establish a joint simulation model of the autonomous racecar,including the body,tires,steering system,suspension system and braking system,which laid the foundation for the research and verification of control methods.Secondly,research on lateral control strategy.The lateral control of autonomous racecar adopts model predictive control logic,and the prediction model of the car is established based on the three-degree-of-freedom dynamic model.The appropriate objective function is selected,and appropriate constraints are formulated according to the structure and driving conditions of the car,then calculated the front wheel angle.The simulation results show that the model predictive control reduces the lateral displacement deviation and the heading angle deviation of the path tracking by adjusting the output of the front wheel angle,and improves the lateral tracking accuracy and lateral stability of the racecar.Thirdly,the longitudinal control strategy is studied.The longitudinal control adopts fuzzy PI control logic,and calculates the longitudinal driving torque based on the track information and the actual speed to achieve the longitudinal control of the autonomous racecar.The experimental results show that the speed tracking effect is good,and the longitudinal controller design strategy is feasible.Finally,the lateral-longitudinal coordinated strategies are studied.The actual working conditions of the car are analyzed,the lateral controller and the longitudinal controller are combined and the parameters of the control system are optimized,and a coordinated control system for the autonomous racecar is constructed.Simulation experiment results show that after adjusting the lateral and longitudinal control through the coordinated controller,the influence between the lateral and longitudinal movements can be eliminated,and the racecar can track the upper reference path quickly and steadily,which verifies the feasibility of the lateral-longitudinal coordinated controller design.In order to improve the effect of path tracking control of autonomous racecar,this paper designs a lateral controller based on model predictive control,a longitudinal controller based on fuzzy PI adaptive control,and a lateral-longitudinal coordinated controller based on empirical laws.Through simulation experiments,The verification shows that the design of the lateral-longitudinal coordinated controller of the autonomous racecar is feasible.Part of the results were applied to the autonomous racecar of Liaoning University of Technology in 2019 and achieved excellent results.At the same time,it has laid a certain foundation for the research of autonomous vehicles.