Research On Trajectory Tracking Control Of Autonomous Vehicles Considering Tire Cornering Characteristic Parameters

Autonomous driving has become a current research hotspot in the automotive industry due to its advantages of improving traffic efficiency and relieving traffic pressure.Autonomous vehicles can effectively complete trajectory tracking based on vehicle status information.However,the strong nonlinearity of tires largely increases the difficulty of trajectory tracking control,making it difficult to balance the accuracy and stability of trajectory tracking of autonomous vehicles under low adhesion roads.In order to improve the tracking accuracy and driving stability of autonomous vehicles under complex conditions,this paper conducts research on the state and parameter estimation of tire cornering characteristics,autonomous steering system control and trajectory tracking and lateral stability coordination.Firstly,an autonomous steering system dynamics model with steering motor and pinion gear characteristics is constructed.To analyze effect of the change in tire-road friction coefficient on the performance of the autonomous steering system,a tire cornering stiffness coefficient is introduced and an equivalent stiffness model is developed to characterize the equivalent torque to the pinion gear from the self-aligning torque.A three-degree-of-freedom vehicle model with the introduction of tire cornering stiffness coefficients is developed as a nominal model for the upper-level controller of trajectory tracking,taking into account the influence of tire cornering stiffness uncertainty on the trajectory tracking control.The joint CarSim-MATLAB/Simulink simulation verifies the validity of the proposed model.Secondly,a vehicle state and parameter estimation strategy driven by data and model is proposed.By analyzing the influence of tire cornering characteristics on vehicle motion control,a tire-road friction coefficient estimation strategy based on BiLSTM(Bi-directional Long Short Term Memory)is designed.Accordingly,by constructing fuzzy rules between the tire-road friction coefficient,the tire side slip angle and the tire cornering stiffness coefficient,a tire cornering stiffness coefficient recognition system is established.A tire lateral force observer based on sliding mode observers is designed,and a tire side slip angle observer is designed in conjunction with a seven-degree-of-freedom vehicle model.The simulation results show that the tire cornering stiffness adaptive estimation strategy can meet the requirements of different driving conditions,and the tire-road friction coefficient estimation strategy and the tire lateral force and tire side slip angle observer have high accuracy.Thirdly,a hierarchical control strategy for trajectory tracking for autonomous vehicles considering the tire cornering characteristics is designed.A trajectory tracking upper-level controller based on model predictive control algorithm is proposed considering tire cornering stiffness uncertainty.In order to eliminate the disturbance caused by the uncertainty in tire cornering stiffness to the autonomous steering system,a trajectory tracking lower-level controller is designed based on sliding mode control algorithm combined with the equivalent stiffness model.Based on the analysis of the stability properties such as the yaw rate and side slip angle,the dynamic characteristic of the tire side slip angle of front axle tire is taken into account and an addition yawmoment controller is designed.Furthermore,an additional yaw-moment distribution controller is designed to coordinate and distribute the additional yaw-moment,thereby controlling the output torque of the in-wheel motor for lateral stability control.The simulation results show that the proposed control strategy can effectively improve the accuracy and driving stability of trajectory tracking of autonomous vehicles under complex conditions.Finally,a semi-physical HiL(Hardware-in-Loop)testbed for autonomous vehicles is built to validate the effectiveness of the proposed strategy.In order to build the dualmotor autonomous steering system bench,the requirements of the dual-motor autonomous steering system were analyzed,and the key components and mechanical structure of the system were identified.Deployment of the controlled model,strategy model and engineering files to complete the construction of the semi-physical HiL test platform.The test results show that the comprehensive strategy proposed in this paper,which combines the vehicle state and parameters estimation strategy and the trajectory tracking and lateral stability control strategy for autonomous vehicles,is able to effectively improve the accuracy and driving stability of trajectory tracking under complex working conditions,with a maximum improvement of 25.5% in tracking accuracy and a maximum reduction of 18.9% and 14.0% in yaw rate and lateral acceleration,respectively.