Multi-Level Coordinated Yaw Stability Control Based on Sliding Mode Predictive Control for Distributed Drive Electric Vehicles Under Extreme Conditions

It is an undeniable fact that the instant sideslip of the vehicle in case of high-speed obstacle avoidance will cause vehicles to lose stability. Current yaw moment control methods for distributed drive electric vehicles (DDEVs) does not fully consider the relationship between the vehicle instability degree and the optimal yaw moment control center, which greatly restricts the attitude correction ability of the four-wheel drive torque. To solve this problem, this article proposes a novel multi-level coordinated yaw stability control method based on robust sliding mode predictive control (SMPC) for DDEVs to improve the maneuverability and lateral stability. Firstly, a novel multi-scale vehicle dynamic model of yaw motion is constructed with the consideration that the vehicle instability center is time-varying under various sideslip conditions. Then, an online sliding mode prediction model of dynamics nonlinear system of DDEVs is established according to the local modeling method based on justintime learning. In addition, the linear time-varying model predictive control algorithm (LTV-MPC) with less predictive horizon is used to obtain the optimal sliding mode control law. Besides, an adaptive weighted soft switching function based on data driven hierarchical predictive proportional-integral-derivative (PID) control is put forward to determine the optimal weight value of the three yaw moment control modes in real time. Finally, the simulation and experimental results have verified that the proposed control method has strong vehicle attitude correction ability which can improve the trajectory tracking accuracy and the handling stability for DDEVs under extreme conditions.