TITLE:
A Neural Network Approach to Predicting Car Tyre Micro-Scale and Macro-Scale Behaviour
AUTHORS:
Xiaoguang Yang, Mohammad Behroozi, Oluremi A. Olatunbosun
KEYWORDS:
Design Parameters; Finite Element Modelling; Neural Network; Tyre Configuration
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.6 No.1,
February
14,
2014
ABSTRACT: Finite Element (FE) analysis has become the
favoured tool in the tyre industry for virtual development of tyres because of
the ability to represent the detailed lay-up of the tyre
carcass. However, application of FE analysis in tyre design and development is
still very time-consuming and
expensive. Here, the application of various Artificial Neural Network (ANN)
architectures to predicting tyre performance is assessed to select the most
effective and efficient architecture, to allow extensive parametric studies to
be carried out inexpensively and to
optimise tyre design before a much more expensive full FE analysis is used to
confirm the predicted performance.