Vehicle state and road friction coefficient estimation based on double cubature Kalman filter

Abstract

For the estimation problem of vehicle state and road adhesion coefficient in driving, the estimation algorithm of vehicle state and road adhesion coefficient were studied in this paper based on double cubature Kalman filter. The 3-DOF nonlinear vehicle estimation model with Dugoff tire model was established. The vehicle driving state estimator and tire-road friction coefficient estimator based on double cubature Kalman filter were designed. The estimators contact with each other in the process of estimation and forms a closed loop feedback to estimate the vehicle state and road adhesion coefficient timely and accurately. Selecting the typical working condition, the algorithm was verified by driving simulator experiments in the loop. The results showed that estimation algorithm based on double cubature Kalman filter can more accurately estimate the vehicle state and road adhesion coefficient than estimation algorithm based on extend Kalman filter.