Statistical tyre/road noise modelling based on continuous 3D texture data

Abstract

In this article, statistical modelling approaches for tyre/road noise levels (according to the CPX method) based on continuous 3D texture measurements are presented. The main focus is to estimate if viable correlations of interpretable 3D texture parameters with frequency-dependent CPX levels can be found. Therefore, a set of descriptive 3D texture parameters is introduced. Two different modelling approaches, focussing on linearity in order to gain interpretability, are shown. First, a linear model is calculated based on the first principal components of the texture parameters, and second, a random forest regression approach is performed on the direct texture parameters. As a principal component analysis of the CPX measurement data reveals three highly correlated frequency ranges, both approaches are calculated independently for low, mid and high frequency bands. Both models show good performance in the low and mid frequency range, whereas the accuracy in the high frequency range declines. Due to the focus on linearity, both approaches result in comparable statistical benchmark parameters.