Coordinated control scheme of path tracking and yaw stability for four-wheel steering and distributed drive autonomous electric vehicles

To simultaneously improve the path tracking accuracy and yaw stability performance for four-wheel steering (4WS) and distributed drive autonomous electric vehicles under different working conditions, a coordinated control scheme is proposed. Firstly, a model error estimator based on Levenberg-Marquardt back propagation (LM-BP) neural network is designed to compensate the vehicle model errors in model predictive control (MPC) caused by model parameterization, simplification, and tire nonlinear characteristics. Secondly, a path tracking controller based on MPC is designed to calculate front-wheel steering angle and rear-wheel steering angle simultaneously. Then, fuzzy sliding mode control (FSMC) is applied to yaw stability control, and the torque distribution is performed according to the load ratio of the front and rear axles. Moreover, the vehicle stability state is divided into multiple levels based on tire force method, and the intervention weight of the yaw stability controller is adjusted according to the stability level, so as to achieve the coordinated control. Finally, the effectiveness of the coordinated control scheme is verified by CarSim&Simulink co-simulation and hardware-in-the-loop (HIL) test. The simulation results illustrate that under the condition of high speed with high road adhesion coefficient and medium-high speed with low road adhesion coefficient, the lateral deviation, sideslip angle, yaw rate are decreased by 24.49%, 81.69%, 74.52% and 32.75%, 55.97%, 65.49% respectively, indicating that the proposed control scheme can effectively improve the vehicle path tracking accuracy while ensure the yaw stability performance.