Control Framework for Stability and Comfort in Distributed Drive Electric Vehicles

In this study, we propose a novel control framework aimed at improving the stability and comfort of distributed drive electric vehicles (DDEVs). Leveraging the classical two degrees of freedom (2DOF) vehicle model, we compute the desired yaw rate and lateral deviation angle, which serve as reference signals for the model predictive control (MPC) controller. To objectively quantify and describe ride comfort, we establish a comfort domain boundary integrated into the MPC controller. Subsequently, we calculate total additional yaw moments using constrained MPC and allocate torque based on a tire load optimization approach. Finally, we validate the effectiveness of our control framework through a co-simulation experiment involving CarSim and Matlab/Simulink. Our results demonstrate that the proposed framework significantly enhances both vehicle stability and comfort.