In previous publications [1,2] it was shown that the tyre can be used as a sensor to estimate the tyre-to-road friction coefficient. In the estimation procedure, Neural Networks were used to describe the lyre and wheel suspension behaviour. In this paper the problem of selecting the optimal network architecture for the estimation problem is addressed. A general network architecture is discussed from which a particular network is derived by optimization using a Genetic Algorithm. Results on experimental data are shown.


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    Titel :

    OPTIMAL DESIGN OF NEURAL NETWORKS FOR ESTIMATION OF TYRE/ROAD FRICTION


    Beteiligte:
    Pasterkamp, W.R. (Autor:in) / Pacejka, H.B. (Autor:in)

    Erschienen in:

    Vehicle System Dynamics ; 29 , sup1 ; 312-321


    Erscheinungsdatum :

    1998-01-01


    Format / Umfang :

    10 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Optimal Design of Neural Networks for Estimation of Tyre/Road Friction

    Pasterkamp, W. R. / Pacejka, H. B. / International Association for Vehicle System Dynamics | British Library Conference Proceedings | 1998


    Optimal design of neural networks for estimation of tyre/road friction

    Pasterkamp,W.R. / Pacejka,H.B. / Delft Univ.of Technology,NL | Kraftfahrwesen | 1998



    Design of tyre force excitation for tyre–road friction estimation

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