Application of neural networks for estimation of tyre/road forces

Abstract

The behaviour of the tyre plays an important role in the vehicle handling. Thus for the analysis of vehicles and road safety, it is necessary to take into account the forces and moments generated at contact match. An accurate tyre model that estimates these forces and moments it is highly essential for the studies of vehicle dynamics and control. Much of the tyre models neglect the coupling of the forces in different directions. They describe the tyre-forces generated at the pure-slip conditions of braking, driving or cornering. Nevertheless, a steering maneuver during braking, generally, decreases the braking stiffness, the longitudinal peak force, and its corresponding slip value. A model for the interaction between the slip in both directions is therefore inevitable for more advanced vehicle simulations. In this work, a recursive lazy learning method based on neural networks is proposed in order to model the tyre force generation at combined slip. Experimental results obtained after training show that the neural model learns to model the tyre behaviour without difficulty. Copyright © 2010 by ASME.