| Intelligent electric vehicle trajectory tracking is a key step in the execution of unmanned vehicles.It is closely related to the driving safety of intelligent vehicles.It has a vital contribution to improving the driving performance of unmanned vehicles and providing passengers with a better driving experience..However,there are still some key issues that need to be solved urgently in the research of trajectory tracking related technologies.To meet people’s high requirements for the comprehensive performance of unmanned vehicles,we need to continuously improve and improve the level of trajectory tracking related technologies.In previous studies,trajectory tracking algorithms are usually designed for conventional working conditions using kinematics models or purely side-sliding dynamics models.However,when vehicles are driving in the real world,they will inevitably encounter extremes such as high speed,low attachment,and emergency obstacle avoidance.Under working conditions,the vehicle and tires are in a state of strong side-longitudinal-vertical coupling,which improves the trajectory tracking control performance of smart vehicles under extreme working conditions,which is of great significance to improve the safety of the vehicle.IEV vehicles have more control freedom and provide an ideal platform for vehicle control research under extreme conditions.Therefore,this paper selects IEV vehicles as the platform for research.Under extreme conditions,the tire has a high degree of lateral,longitudinal and vertical coupling,which brings new challenges to the vehicle control system.Therefore,this article fully considers the high coupling characteristics of tires in the vehicle control system under extreme conditions,and aims to design a It is used in the trajectory tracking controller under extreme conditions.In this paper,the research on trajectory tracking control under extreme working conditions is arranged as follows:(1)Four-wheel drive electric vehicle vehicle modeling: Based on the CarSim and Simulink/Matlab co-simulation platform,a four-wheel hub motor-driven vehicle cosimulation model was established,and the drive system in CarSim was modified and built in Simulink UniTire tire model and motor model under compound conditions.Finally,the accuracy of the co-simulation model and the actual vehicle test data is compared and verified,which proves that the established co-simulation model is in good agreement with the actual vehicle test data and can be used for algorithm simulation test.(2)Vehicle stability analysis and instability boundary description: Based on the nonlinear four-wheel and seven-degree-of-freedom vehicle dynamics model and UniTire tire model,this chapter studies the vehicle’s mass center slip angle-yaw rate phase plane,and uses the design of the envelope boundary.Methods Based on the saddle point of the phase plane,the boundary of the stable area and the unstable area in the phase plane is designed.The influence of longitudinal vehicle speed,road adhesion coefficient and front wheel angle on the position of the saddle point is studied,and the saddle point position equation is proposed to design the envelope.The boundary equation provides stability boundary constraints for vehicle trajectory tracking under extreme conditions.(3)Intelligent electric vehicle trajectory tracking control under extreme conditions:Based on the control-oriented UniTire coupled tire model,a trajectory tracking controller that integrates the vehicle’s "side,vertical and vertical" coupling characteristics is designed.1)The control-oriented UniTire coupled tire model is used to more accurately describe the coupling and nonlinear characteristics of tires under extreme conditions.The lateral and longitudinal coupling characteristics of the tire are concentrated in the effective cornering stiffness,and only used with the effective cornering The stiffness-related formula can describe the tire coupling more accurately,which greatly simplifies the complexity of introducing the coupled tire model into the controller.2)Based on the UniTire model under extreme conditions and the sevendegree-of-freedom vehicle model,a vehicle state space model is established to improve the prediction accuracy of the vehicle state.Based on this,a model predictive controller is designed.3)In order to improve the adaptability of the trajectory tracking controller to different driving conditions,a weight distribution scheme based on trajectory tracking and stability is proposed.If the vehicle is in a stable state,the primary control objective will be focused on trajectory tracking;if the vehicle is in a critical instability state,the primary control objective will be focused on stability.This effectively improves the trajectory tracking control ability of the four-wheel hub motor-driven electric vehicle under extreme working conditions.(4)Simulation verification of the trajectory tracking controller: In order to verify the trajectory tracking performance of the vehicle under extreme conditions,the effectiveness of the algorithm is verified through simulation experiments under highspeed double-line shifting conditions.The simulation test results show that the use of the tire model under compound conditions is beneficial to improve the trajectory tracking control effect of the controller compared with the controller with a fixed cornering stiffness(traditional controller);it can be based on the state of the vehicle.Stable or unstable,to allocate different four-wheel torques,which greatly improves the overall performance of the vehicle under extreme conditions,and takes into account trajectory tracking and stability;it is more conducive to more reasonable under extreme conditions The four-wheel torque distribution,which can track the trajectory more accurately under the same condition control effect. |
