Research On Path Tracking And Lateral Stability Control Of Intelligent Vehicle Based On PWA Tire Model

Intelligent vehicle is a high-tech complex of environment perception,information fusion,decision planning and automatic control,which plays an important role in reducing traffic accidents,improving traffic efficiency and increasing economic benefits.Path tracking and lateral stability control,as one of the key parts of intelligent vehicle dynamics control,are of great significance in ensuring vehicle safety.The vehicle dynamics system is a highly uncertain,time-varying and nonlinear complex,and how to improve its control performance effectively is still facing great challenges.As the only part of the vehicle in contact with the ground,how to accurately reflect the tire nonlinear mechanical characteristics under complex driving conditions is the core of intelligent vehicle dynamic control.Although some existing studies have considered the tire nonlinear mechanical characteristics,the tire model form is too complex,leading to greater difficulties in subsequent controller design and low computational efficiency,which cannot meet the high-precision dynamic control requirements of intelligent vehicles under special driving conditions.Therefore,based on the piecewise affine(PWA)identification of the tire nonlinear mechanical characteristics under combined conditions,this paper proposes an intelligent vehicle path tracking and lateral stability optimization control strategy.The main research contents include:Firstly,the PWA modeling of tire longitudinal slip and sideslip characteristics was completed.Based on the high-performance flat tire test bench,the test data reflecting the tire nonlinear mechanical characteristics were accurately obtained,and the nonlinear mapping relationship between the tire longitudinal and lateral forces and their influencing factors was analyzed.On this basis,the PWA identification of tire model was completed through the steps of data clustering,parameter estimation and the hyperplane coefficient matrices calculation.The simulation results were compared with the test data to verify the fitting accuracy of the identified PWA tire model.Secondly,complete the vehicle dynamics modeling and driving state estimation based on the PWA tire model.Based on the PWA model which consider the tire nonlinear longitudinal slip and sideslip characteristics,the seven-degree-of-freedom dynamic modeling of the vehicle was carried out.On this basis,in order to improve the accuracy of vehicle critical state estimation when the statistical characteristics of noise are unknown,an adaptive Square-root Cubature Kalman filter state estimation strategy is designed based on the maximum a posteriori probability criterion combined with the Square-root Cubature Kalman filter algorithm.The effectiveness of the proposed estimation strategy in Sine-Wave and J turn cases was verified by Car Sim-Simulink co-simulation platform.Thirdly,lateral instability analysis and adaptive preview time driver steering control model were completed.The dβ-β phase plane method was used to study the stable region of vehicles at different speeds and road friction coefficients,and the mathematical expression of the stable region was obtained by data fitting.On this basis,the driver steering model control of preview time was designed,and the vehicle instability state and tracking error were taken as the performance indexes.The adaptive driver control model of preview time was optimized by particle swarm optimization algorithm,and the target yaw rate of the vehicle along the reference path was calculated.The actual performance of the adaptive preview time model was verified with the Car Sim-Simulink co-simulation platform.Finally,the path tracking and lateral stability control strategy of intelligent vehicle based on piecewise affine dynamics model are designed.To reduce the tracking error of yaw rate and sideslip angle as control objectives,the real-time front wheel Angle and external yaw moment were calculated,and the upper controller strategy of vehicle dynamics was designed.On this basis,the lower controller aims to meet the external yaw moment and speed tracking requirements.An efficient control method of torque distribution without complicated iterative calculation was designed to ensure that the optimal torque required by four wheels can be calculated effectively.Based on Car Sim-Simulink co-simulation platform,the effectiveness of the designed path tracking and lateral stability control strategy was verified under two cases which are medium speed on wet road and high speed on dry road.