Stability control of in-wheel motor driven vehicle based on extension pattern recognition

According to the characteristics that the torque of each wheel of the in-wheel motor driven vehicle is independent and controllable, the stability control of in-wheel motor driven vehicle based on extension pattern recognition method is proposed in this paper. The dynamic model of the vehicle is established by Matlab/Simulink and Carsim. Taking two-degree-of-freedom (2-DOF) vehicle model as reference model, the vehicle yaw rate and the sideslip angle as the control objectives. The differences between the actual values and the reference values of the yaw rate and the actual sideslip angle are used to define the vehicle stability status. The vehicle stability status is divided into four stability control patterns, which are the no control pattern, the yaw rate control pattern, the yaw rate and sideslip angle joint control pattern, and the sideslip angle control pattern, respectively. The extension pattern recognition algorithm is used to determine the vehicle control pattern. The fuzzy controllers of yaw rate and sideslip angle are designed to obtain the additional yaw moment. Besides, the optimal torque distribution method is proposed by taking the lowest total energy loss of four motors as the objective function. The feasibility and effectiveness of the proposed control strategy are verified by Matlab/Simulink and Carsim joint simulation platform and hardware-in-the-loop (HIL) test.