基于路面附着系数估计的汽车横摆力矩控制OA

To address the issue of poor vehicle driving stability on roads with varying friction coefficients and the difficulty in estimating them quickly and accurately,a direct yaw moment control(DYC)method that incorporates road friction coefficient estimation was proposed.This approach aims to enhance the control performance of the yaw moment.A seven-degree-of-freedom vehicle dynamics model was established based on Dugoff tire model,and a road friction coefficient estimator was designed according to the unscented Kalman filter(UKF)algorithm.A model predictive control(MPC)algorithm was adopted to calculate the additional yaw moment,thereby improving the vehicle's driving stability on roads with different friction coefficients.To validate the effectiveness of the proposed control strategy,simulation tests under various road friction conditions were designed using a Carsim and Simulink co-simulation platform.The results demonstrate that under the sine-steering maneuver on a split-friction road,the peak errors of the sideslip angle and yaw rate are controlled within 0.001 75 rad and 0.007 85 rad/s,respectively.Compared with(proportional-integral derivative,PID)and linear quadratic requlator(LQR)controls,the peak values are reduced by 14.2%and 8.2%,respectively,effectively overcoming the control challenges posed by sudden changes in road friction.