Enhancing Robust Driver Assistance Control in Distributed Drive Electric Vehicles through Integrated AFS and DYC Technology

The implementation of direct yaw moment control (DYC) in distributed drive electric vehicles brings greater potential for enhancing vehicle maneuverability and stability performance. Therefore, this paper introduces a robust framework for driver assistance control by integrating the active front-wheel steering (AFS) system and DYC, aiming to improve the overall performance. First, the driver steering behavior is modeled and incorporated into the path-tracking system of the distributed drive electric vehicle (DDEV). This integration facilitates a comprehensive consideration of the driver characteristics during the controller design. Moreover, the uncertain model parameters are represented using a reduced number of polytopic vertices. Through field tests, the integrated control scheme showcases its superiority in improving the vehicle's lateral motion capability. Subsequently, to effectively balance the optimization objectives concerning path-tracking accuracy, stability performance, and control efforts, a robust control paradigm is systematically constructed by adjusting the weight coefficients. The optimal assistance inputs for AFS/DYC are derived by solving the linear matrix inequalities (LMIs), ensuring the system's robustness against disturbances. The robust invariant set is further employed to satisfy the system constraints. Finally, a hardware-in-the-loop test platform is developed. Comparative results demonstrate the capacity of the proposed method to enhance human-machine co-driving performance.