• DocumentCode
    181543
  • 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
  • fYear
    2014
  • fDate
    8-11 June 2014
  • Firstpage
    814
  • Lastpage
    819
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium Proceedings, 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/IVS.2014.6856391
  • Filename
    6856391