Research On Motion Control Of Distributed Intelligent Electric Vehicle Under Extreme Conditions

In order to solve the problems of road jam,traffic accidents and environmental contamination caused by the popularization of vehicles,the electrification and intelligence of vehicles have become crucial growing tendency.Distributed drive,as one of the mainstream drive forms of electric vehicles,has excellent performance and good compatibility with automobile intelligent systems.At present,the research of smart car motion control mostly focuses on the design of the controller under normal working conditions,but the control performance under extreme and complex working conditions still needs to be improved.Therefore,this thesis conducts research on the motion control of intelligent distributed drive electric vehicles under extreme conditions.First,the trajectory tracking controller is designed,and the yaw stability controller is additionally designed by using the advantages of four-wheel independent driving,forming a vehicle control system that integrates trajectory tracking ability and stability.Offline simulation and real-time verification under extreme conditions show that the controller has good effectiveness and real-time performance.The main research content of the paper is:(1)According to the kinetic properties of distributed drive electric automobile,a seven DOF automobile kinetic model,a wheel model,a tyre model,and a motor model are built.Then,based on the national standard test conditions,the model is compared and simulated,which verifies that the model has good validity and accuracy.(2)Aiming at the problem of trajectory tracking and control of smart cars,horizontal and vertical controllers are designed respectively.Firstly,the multiple restraint LTV-MPC tactic is adapted to the lateral controller.On account of the automobile model and the nonlinear tyre model,a theoretical model for control under extreme conditions is proposed.Based on this model,the predictive equation is constructed,and the constrained optimization question is devised and resolved.And then apply PSO to optimize the choice of MPC controller arguments.In addition,the longitudinal controller is designed ground on the PI approach,and the required longitudinal force is calculated.Finally,a great track pursual effect of the smart vehicle under extreme conditions is realized.(3)Aiming at the problem of vehicle instability under extreme conditions,a yaw stability hierarchical controller is designed,including the top yaw moment control module and the bottom torque optimization distribution module.First,a sliding mode controller is drafted to compute the needed yaw torque ground on the differences of the control variate,and a VUFSMC approach is arranged to further the controller and shorten the flutter of the SMC system.Then,on the basis of the longitudinal force demand by the automobile and the attached yaw torque,a torque optimal distribution controller based on the minimum tire attachment utilization is designed to solve the longitudinal force of each wheel and convert it into the motor torque.It effectively ensures that the vehicle has good driving ability and yaw stability under extreme conditions.(4)A double closed-loop hierarchical controller is designed and its performance is verified.Firstly,the offline simulation is performed under the double-line shifting conditions with different attachment conditions.The consequences indicate that the control arithmetic has great trajectory pursual ability and stability.Then use d SPACE rapid control prototype and Car Sim virtual vehicle system to design a real-time verification platform to verify performance under extreme conditions.By comparing the effects of offline simulation and real-time verification,it proves that the control arithmetic has great reliability and actual time property,thus verifying that the design content of this paper can significantly improve the performance of motion control under extreme conditions.