Wheel force measurement for vehicle dynamics control using an intelligent bearing

Abstract

The measurement and estimation of wheel loads is an interesting and complex topic relevant for vehicle dynamics control. Accurate wheel load information allows for more straight-forward, more robust and more efficient control. In this paper a novel model based wheel load reconstruction approach is presented. An Unscented Kalman Filter is used to reconstruct the unknown wheel loads by analysis of the deformation of the bearing outer-ring. The performance of the approach is demonstrated by field tests using an instrumented passenger car. Results show that the proposed approach is well able to reconstruct both tilting and self-aligning moments as well as lateral and vertical wheel forces during various steering maneuvers.