A robust method to estimate tire forces for a passenger vehicle with the Unscented Kalman Filter (UKF) is provided. Only standard vehicle sensors were used and no a priori knowledge of tire and road properties was required. The estimator uses the bicycle model and a random walk tire force model. The tire force estimates were compared to a CarSim reference model for combined slip maneuvers. The results showed a good overall tracking performance of the estimator. In addition, the UKF-estimator demonstrated a high convergence rate and good stability properties. The performed robustness studies showed that the estimator performs well even in the presence of disturbances such as changes in tire-road friction. This method enables a cost-effective and robust implementation for future real time vehicle applications.
Tire force estimation for a passenger vehicle with the Unscented Kalman Filter
2014-06-01
527611 byte
Conference paper
Electronic Resource
English
TIRE FORCE ESTIMATION FOR A PASSENGER VEHICLE WITH THE UNSCENTED KALMAN FILTER
British Library Conference Proceedings | 2014
|Unscented Kalman filter for vehicle state estimation
Online Contents | 2011
|Unscented Kalman filter for vehicle state estimation
Automotive engineering | 2011
|Unscented Kalman filter for vehicle state estimation
Taylor & Francis Verlag | 2011
|Vehicle State Information Estimation with the Unscented Kalman Filter
Tema Archive | 2014
|