An Assessment of Predictive Control Strategies for Lateral Stability Control of 4-Wheels Drive Electrical Vehicle

Distributed electric drive vehicles offer convenience and maneuverability, but distributing torque to all four wheels to ensure stability under various driving conditions can be a challenge. This paper presents a novel control strategy for torque vector control using both linear and nonlinear model predictive control (MPC) as an optimal way to generate additional yaw moment, which improves handling stability while also maintaining accuracy in trajectory tracking. This strategy combines handling, lateral stability, and ride comfort. The MPC and nonlinear MPC controllers are designed to follow reference values and improve handling and lateral stability by calculating the total required torque while minimizing tracking errors in sideslip and yaw angle. The torque for each wheel is then determined based on yaw moment and longitudinal force using low-level torque vector synthesis. The optimized control sequence is then sent to the actuator. Simulations in different road conditions for pathfollowing scenarios were conducted in MATLAB/Simulink, and the proposed nonlinear MPC method was found to be superior to the ordinary MPC-based direct yaw method.