Research on Lateral Stability Control Strategy for Distributed Drive Electric Vehicles

This study aims to improve the lateral stability of Distributed Drive Electric Vehicles (DDEV) under complex driving conditions by adopting a hierarchical lateral stability control architecture. The upper level is the torque decision layer. A sliding mode controller with an additional yaw moment, optimized using the particle swarm optimization algorithm, is designed with the vehicle dynamics model as the reference framework.Ideal reference values for the yaw angular velocity and the center-of-mass side slip angle are determined based on the maximum road adhesion limit.The lower-level torque distribution layer employs a controller designed with the objective of minimizing the tire load factor, taking into account both the motor output limit and road adhesion constraints. Based on this framework, a quadratic programming-based four-wheel torque optimal distribution strategy is developed to achieve precise allocation of the additional yaw torque. The proposed control algorithm is validated through simulations on the combined CarSim and MATLAB/Simulink platform, under various road adhesion conditions and across two typical driving scenarios: dual lane-changing and serpentine driving. The results demonstrate that, when compared to the standalone SMC and the no-control baseline, the designed direct yaw moment controller and torque distribution algorithm exhibit high stability and outperform the SMC across all adhesion conditions. Furthermore, experimental validation of the lateral stability control algorithm is conducted on a HIL test platform. By comparing the tracking performance of the actual controlled values of yaw rate and center-of-mass sideslip angle against their ideal reference values, the control accuracy, real-time performance, and robustness of the controller are verified.