Stability control of distributed drive electric vehicle based on adaptive fuzzy sliding mode

To improve the driving stability of a distributed drive electric vehicle (DDEV), we propose a hierarchical direct yaw moment control strategy. In the upper-level controller, an adaptive fuzzy sliding mode controller (AFSMC) is designed with joint control objectives of sideslip angle and yaw rate. In the conventional controller, the weight coefficients of the joint control objectives are fixed values, which reduces the adaptability of the system. To improve this problem and achieve adaptive adjustment of the weight coefficients of the control objectives with the vehicle motion state, an adaptive fuzzy control-based target weight coefficient controller is designed. In the lower controller, a quadratic programing method is used to assign torque with the optimization objective of minimizing tire attachment utilization. A joint simulation with Carsim and Simulink software was performed to compare and analyze the AFSMC vehicle and the traditional SMC vehicle under the steering wheel turning angle sinusoidal input and double shift line conditions. The results show that AFSMC effectively reduces the magnitude of vehicle sideslip angle, yaw rate, and lateral acceleration, enhances the driving stability of the vehicle, and enables adaptive adjustment of the weight coefficients of the joint control objectives, improving the adaptability of the controller. Finally, the effectiveness of the control strategy is verified by hardware-in-the-loop (HIL) test.