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.
OPTIMAL DESIGN OF NEURAL NETWORKS FOR ESTIMATION OF TYRE/ROAD FRICTION
Vehicle System Dynamics ; 29 , sup1 ; 312-321
1998-01-01
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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