This paper considers a method for estimating vehicle handling dynamic states in real-time, using a reduced sensor set; the information is essential for vehicle handling stability control and is also valuable in chassis design evaluation. An extended (nonlinear) Kalman filter is designed to estimate the rapidly varying handling state vector. This employs a low order (4 DOF) handling model which is augmented to include adaptive states (cornering stiffnesses) to compensate for tyre force nonlinearities. The adaptation is driven by steer-induced variations in the longitudinal vehicle acceleration. The observer is compared with an equivalent linear, model-invariant Kalman filter. Both filters are designed and tested against data from a high order source model which simulates six degrees of freedom for the vehicle body, and employs a combined-slip Pacejka tyre model. A performance comparison is presented, which shows promising results for the extended filter, given a sensor set comprising three accelerometers only. The study also presents an insight into the effect of correlated error sources in this application, and it concludes with a discussion of the new observer's practical viability.


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    Titel :

    An Extended Adaptive Kalman Filter for Real-time State Estimation of Vehicle Handling Dynamics


    Beteiligte:
    Best, M.C. (Autor:in) / Gordon, T.J. (Autor:in) / Dixon, P.J. (Autor:in)

    Erschienen in:

    Vehicle System Dynamics ; 34 , 1 ; 57-75


    Erscheinungsdatum :

    01.07.2000




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    An extended adaptive Kalman filter for real-time state estimation of vehicle handling dynamics

    Best,M.C. / Gordon,T.J. / Dixon,P.J. et al. | Kraftfahrwesen | 2000



    Real-time State Estimation of Vehicle Handling Dynamics Using an Adaptive Kalman Filter

    Best, M. / Gordon, T. / Society of Automotive Engineers of Japan | British Library Conference Proceedings | 1998