1903. State estimation based on unscented Kalman filter for semi-active suspension systems

In this paper, a novel approach to estimate vehicle vibration state information in real time is proposed; it is based on unscented Kalman filter (UKF) theory. The UKF is based on the unscented transfer technique which considers high order terms during the measurement and update stage during the estimation. The proposed observer uses easily accessible measurements such as accelerations and suspension deflections to estimate the sprung and unspring mass vertical velocity for the suspension systems of full vehicle under unknown road disturbance. And it is with low sensitivity and robust to the unknown road surfaces. Matlab/Carsim co-simulation experiments are carried out to validate the performance of the estimator under two typical road excitations. The simulation results clearly indicate that the proposed UKF sate observer is precise.