Vehicle Dynamics Estimation Using Kalman Filters

Abstract

Abstract This paper deals with the application of stochastic state estimators in vehicle dynamics control. It is often unrealistic to assume that all vehicle states and the disturbances acting on it can be measured. System states that cannot be measured directly, can be estimated by a Kalman Filter. The idea of the Kalman filter is to implement a model of the real system in an on-board computer in parallel with the system itself. This paper will give 3 examples of this principle applied to automotive systems.