Adaptive Estimator for Vehicle Roll and Road Bank Angles Using Inertial Sensors

Abstract

This paper presents an adaptive approach to simultaneously estimate the angles of vehicle roll and road bank with off-the-shelf vehicle inertial sensors. Measured signals are firstly processed through a kinematic model based adaptive complementary filter, and then fused in a dynamic model based Kalman filter. Adaptive law is designed to suppress the undesired effect caused by transient motion and integral drift. Suspension displacement sensors were installed to accurately measure the reference value of vehicle-body roll angle, and on-vehicle experiments on uneven ground were conducted to evaluate the performance of the proposed method. The effectiveness of the estimator was approved by comparing the estimating results and the reference.