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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    Title :

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


    Contributors:


    Publication date :

    2014-06-01


    Size :

    527611 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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