Development of Vehicle Roll Rate Estimator Using Transfer Function Estimation

Abstract

An accurate measurement of the roll angle or roll rate is important in RSC(Roll Stability Control) research. It can be measured directly only with expensive measuring equipment like INS(Inertial Navigation System) or dual-antenna GPS.

Moreover, the estimation approach requires vehicle parameters, including cornering stiffness, spring coefficient, and damping coefficient. This paper proposes a technique to estimate roll rate without vehicle parameter information through transfer function estimation. By using dynamic models, a transfer function is derived to describe the relation between the roll rate and the yaw rate. Driving data for step steer, double lane change, lane change, and sine sweep scenarios are used, and a multi-model estimator is designed to secure estimation performance at various speeds. The proposed method is verified by simulation and real vehicle experiments.