An Adaptive MPC-based Motion Stability Control Strategy for Four In-Wheel Motor-Actuated Electric Vehicles.

The article focuses on developing an adaptive model predictive control (MPC)-based motion stability control strategy for four in-wheel motor-actuated electric vehicles (EVs). It introduces a comprehensive control framework that simultaneously addresses longitudinal, lateral, and vertical vehicle stability by integrating a nonlinear MPC slip ratio adjustment torque controller, a fuzzy logic-based adaptive weighting factor to balance speed tracking and vertical stability, and a motion adjustment torque controller based on PID algorithms. Simulation experiments conducted on a Modelica/Simulink co-simulation platform under acceleration/braking and ISO double lane change scenarios demonstrate that the proposed control scheme improves vehicle speed tracking accuracy, reduces energy consumption, and enhances multi-dimensional motion stability compared to baseline and conventional PID-MPC methods. This approach offers a validated solution to the 62nd IEEE CDC benchmark challenge, emphasizing improved drivability and passenger comfort in four in-wheel motor electric vehicles.