Road Bank Estimation Based on Curve Adaptive Strong Tracking Kalman Filter

Abstract:

The road bank angle directly affects the lateral dynamics of the vehicle. Bank angle has become one of the key parameters of the intelligent vehicle stability control system. However， not only the coupling problem between road bank and vehicle roll， but the difficulty of getting lateral force makes the accurate estimation of bank angle a challenging problem. Therefore， an extension fusion road bank estimation algorithm based on the acceleration sensor was proposed in this paper. First， a lateral acceleration sensor model and the roll dynamics model were proposed， and the curve adaptive strong tracking Kalman filter （CASTKF） was used to estimate the road bank. Then， a direct estimation method based on the lateral acceleration sensor was proposed to prevent the wrong estimation after the loss of observability of the system. Next， the extension algorithm was used to fuse the estimated values of the two methods. Finally， hardware-in-loop tests （HIL） were conducted to verify the effectiveness of the proposed algorithm under various working conditions and the results revealed the accuracy and robustness of the CASTKF algorithm.

Key words:intelligent vehicle;road bank estimation;extension fusion;strong tracking Kalman filter;adaptive filter