Title :
Tire force estimation for a passenger vehicle with the Unscented Kalman Filter
Author :
Hamann, Hendrik F. ; Hedrick, J. Karl ; Rhode, Stephan ; Gauterin, Frank
Author_Institution :
Karlsruhe Inst. of Technol., Karlsruhe, Germany
Abstract :
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.
Keywords :
Kalman filters; bicycles; estimation theory; friction; nonlinear filters; road vehicles; stability; tyres; CarSim reference model; UKF; bicycle model; combined slip maneuvers; passenger vehicle; random walk tire force model; stability properties; standard vehicle sensors; tire force estimation; tire-road friction; unscented Kalman filter; Estimation; Force; Noise; Sensors; Tires; Vehicles; Wheels;
Conference_Titel :
Intelligent Vehicles Symposium Proceedings, 2014 IEEE
Conference_Location :
Dearborn, MI
DOI :
10.1109/IVS.2014.6856391