Research on Stability Control of Distributed Driven Electric Vehicles Based on SVD-ACKF State Estimator

Vehicle stability control is a key technology to ensure the safe driving of vehicles. A yaw stability control strategy based on SVD-ACKF (SVD-adaptive cubature Kalman filter) state estimation was proposed for distributed drive electric vehicles. Firstly, an SVD-ACKF state estimator was built by improving the CKF filtering algorithm to enhance the robustness of the estimator and the estimation accuracy of the algorithm. Secondly, a twolayer structure was used for yaw stability control. The upper layer uses the constructed sliding mode (SMC) controller to calculate the desired yaw moment required for stable vehicle driving. The lower layer based on the tire load rate as the optimization target reasonably distributes the desired torque. Finally, a joint simulation platform was built with Simulink/Carsim software for simulation verification. The results show that under two different working conditions, the yaw stability control strategy based on SVD-ACKF state estimation improves the control effect of the vehicle yaw rate by $\mathbf{2 5. 4 \%}$ and $\mathbf{2 0. 8 \%}$, respectively, and improves the control effect of the sideslip angle by $8.9 \%$ and $22.4 \%$, respectively. It enables the vehicle to have good path tracking ability, improves the yaw stability and active safety of distributed drive electric vehicles.