This paper proposes a hierarchical control strategy to enhance the lateral stability of distributed drive electric vehicles. In the upper layer, the extended kalman filter (EKF) is employed for real-time estimation of critical vehicle states, including the sideslip angle and yaw rate. In the intermediate layer, a direct yaw-moment control (DYC) system based on integral terminal sliding mode control (ITSMC) is designed, which utilizes the deviation between the EKF-estimated states and their desired values to calculate the required additional yaw moment for stability compensation. In the lower layer, an optimal control–based torque allocation strategy is adopted to distribute the driving torque among the four in-wheel motors. Unlike many existing direct yaw moment control strategies that assume ideal state availability or suffer from control chattering and limited wheel-level realizability, this study explicitly addresses the coupled problem of state estimation uncertainty, robust yaw-moment generation, and practical torque realization under nonlinear tire dynamics. Simulation results demonstrate that the proposed EKF-based state estimation achieves high accuracy, while the ITSMC-DYC controller significantly improves lateral stability, trajectory tracking capability, and driving safety. Furthermore, hardware-in-the-loop (HIL) tests validate the effectiveness of the hierarchical control strategy under realistic scenarios, confirming its potential for practical applications.
Wang et al. (Thu,) studied this question.
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