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.


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    Titel :

    Tire force estimation for a passenger vehicle with the Unscented Kalman Filter


    Beteiligte:
    Hamann, Harry (Autor:in) / Hedrick, J. Karl (Autor:in) / Rhode, Stephan (Autor:in) / Gauterin, Frank (Autor:in)


    Erscheinungsdatum :

    01.06.2014


    Format / Umfang :

    527611 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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    Hamann, H. / Hedrick, J. / Rhode, S. et al. | British Library Conference Proceedings | 2014


    Tire Force Estimation for a Passenger Vehicle with the Unscented Kalman Filter

    Hamann, H. / Hedrick, J.K. / Rhode, S. et al. | DataCite | 2014


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