Vehicle mass estimator for adaptive roll stability control

Abstract

Rollover is one of the significant life threatening factors in SUVs (Sports Utility Vehicles). By applying braking or steering, active roll stability controllers help prevent rollover accidents in SUVs. The performance of these controllers is very sensitive to vehicle inertial parameters such as vehicle mass and mass center height. In this paper, a unified estimation method for vehicle mass is proposed considering available driving conditions, where three estimation algorithms are developed based on longitudinal, lateral or vertical vehicle dynamics, respectively. The first algorithm is designed using the longitudinal vehicle dynamics and the recursive least square with the disturbance observer technique for longitudinal traveling case. The second algorithm is designed using the lateral vehicle dynamics where the lateral velocity is estimated with the kinematic vehicle model via the Kalman filter. The third algorithm is designed based on the vertical dynamics and the dual recursive least square algorithm to estimate vehicle sprung mass. Then three algorithms are integrated to extract the vehicle mass during arbitrary vehicle maneuvering. The performance of the proposed vehicle mass estimation method is demonstrated through simulation.