Vehicle Yaw Stability Model Predictive Control Strategy for Dynamic and Multi-Objective Requirements

Vehicle yaw stability control (YSC) can actively adjust the working state of the chassis actuator to generate a certain additional yaw moment for the vehicle, which effectively helps the vehicle maintain good driving quality under strong transient conditions such as high-speed turning and continuous lane change. However, the traditional YSC pursues too much driving stability after activation, ignoring the difference of multi-objective requirements of yaw maneuverability, actuator energy consumption and other requirements in different vehicle stability states, resulting in the decline of vehicle driving quality. Therefore, a vehicle yaw stability model predictive control strategy for dynamic and multi-objective requirements is proposed in this paper. Firstly, the unstable characteristics of vehicle motion are analyzed, and the nonlinear two-degree-of-freedom vehicle dynamics models are established respectively. Secondly, the vehicle yaw stability control strategy is designed: The two-line method is used to extract the boundary of $\beta -\dot{\beta }$ phase portrait. On this basis, the geometric distance quantization method is applied to establish the dynamic mapping relationship between the multi-objective requirements of driving stability, yaw maneuverability, actuator energy consumption and the weight of YSC cost function in different vehicle stability states. The model predictive theory and rule-based single wheel differential braking technology are applied to achieve vehicle stability control. Finally, a joint simulation platform is built based on vehicle dynamics simulation software CarSim and MATLAB/Simulink for testing and verification. The simulation results show that the YSC designed in this paper can adaptively adjust the controller output according to the dynamic multi-objective requirements in different vehicle stability states, and effectively improve the driving quality of the vehicle under strong transient conditions.