On split-mu roads, vehicles tend to deviate initially. Traditional vehicles use differentials to adjust driving force, causing power loss. In contrast, corner modular vehicles integrate the executive components of drive-brake-rotation-suspension, allowing for independent control of driving torque and tire rotation angle for each wheel, which makes it possible to optimize vehicular driving performance and directional stability. This paper proposes a Joint control framework for corner modular vehicles starting on split-mu roads. First, the active steering system (ASS) controller is developed by using model predictive control (MPC) ensures directional stability via the front-wheel steering angle proportional feedforward and yaw rate proportional feedback. An acceleration slip regulation (ASR) controller is then developed, utilizing radial basis function neural network adaptive PID (RBFPID) to control wheel torque. Simulation and driver-in-the-loop experiments on various split-mu road conditions demonstrate that joint control reduces low-adhesion wheel slip ratio from 0.9 to around 0.1 within 2 s, increases longitudinal speed by 67%, stabilizes yaw rate to 0 within 5 s, and significantly minimizes lateral deviation, effectively balancing driving performance and directional stability.
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