Distributed Drive Electric Vehicle Hierarchical Control of Yaw Stability Based on Disturbance Observer

This paper addresses the problem of vehicle yaw stability control and proposes a super-twisting sliding mode hierarchical control method based on a disturbance observer. First, the nonlinear vehicle model is linearized, resulting in a linear model that includes a model error disturbance term. This model error, resulting from the linearization process, is estimated and compensated for in real time using the disturbance observer. Then, in the upper layer of the control system, the super-twisting sliding mode is used to determine the additional yaw torque required. In the lower layer, various constraints are thoroughly considered, including slip ratio, driving force, additional yaw moment and actuator limitations. A quadratic programming algorithm is then used to determine the optimal allocation strategy for the four-wheel drive torque to ensure stable vehicle operation. Finally, the effectiveness of the proposed method is validated through a joint simulation of Carsim and MATLAB/Simulink. The results, according to national standards, are presented for different operating conditions, providing a comprehensive evaluation of the driving stability.