The use of AI methods for evaluating condition dependent dynamic models of vehicle brake squeal

  • Authors:

  • Simon Feraday;Chris Harris;Kihong Shin;Mike Brennan;Malcolm Lindsay

  • Affiliations:

  • -;-;-;-;-

  • Venue:
  • IEA/AIE '00 Proceedings of the 13th international conference on Industrial and engineering applications of artificial intelligence and expert systems: Intelligent problem solving: methodologies and approaches
  • Year:
  • 2000

Quantified Score

Hi-index 0.00

Visualization

Abstract

A neurofuzzy modelling technique is used to predict the differential equation coefficients of brake noise time histories as functions of braking test conditions. These are then related to the 3rd order differential equations governing a candidate mathematical model of brake squeal using a second neurofuzzy model. This determines whether similar or sensible parametric changes in the model are required to mirror the dynamic effects of changes in experimental condition parameters. An assessment of the efficacy of the candidate model is then made based on this analysis. The results of different candidate models could be likewise compared to determine which is most realistic.