Engineering tools for interior tyre tread pattern noise

Abstract

The regular tyre tread pattern design process is often based upon experience and experimental evaluations and may take about 2 years. The use of engineering tooling could improve and speed up this process. The research objective is therefore to develop experimental and simulation tooling by which interior tyre tread pattern noise can be predicted, analysed and optimized. The physics of tyre-road noise is explained in a comprehensive manner as a thorough understanding of the physics is needed to evaluate, measure, analyse or optimize tyres with respect to noise. The first engineering tool developed is an instrumented vehicle with dedicated measurement and processing technologies, enabling quantification of the terminology used in subjective evaluations of tyre-road noise. The three most important tyre tread pattern noise characteristics are: level, tonalness and modulation/drumming. They can be quantified, respectively, by the Sound Pressure Level, the so-called order spectrum and the (bandpass filtered) sound pressure variation during one tyre revolution. While rolling on smooth roads, the tyre tread pattern geometry in the tyre-road contact is considered to be the main origin of contact pressure variations, resulting in vibrations and noise. The second engineering tool is a simulation procedure of this source. In the new source modelling approach, the averaged tread pattern height in contact is calculated. The model predicts (R2 = 0.76) the correct trends of the three tyre tread pattern noise characteristics, by using the trend of their geometrical cause. The model can be used to reduce exterior as well as interior tyre tread pattern noise. From these tyre tread pattern noise characteristics dedicated Sound Quality Metrics are defined: for level the Standard Deviation (STD), for tonalness the Order Prominence (OP) and for modulation the Multi-Order Modulation (MOM). They correspond very well (respectively R2=0.96, 0.60 and 0.80) with the human perception of the noise characteristics. An increase in each of the metrics results in a worse subjective perception of the tyre tread pattern noise. The metrics are applicable for measured and simulated sounds. In the third engineering tool the three metrics are combined to model the human percpetion of tyre tread patternn noise. The human perception model is obtained through a linear regression of these tyre related Sound Quality Metrics on the subjective rating of simulated sounds. The output of the model is called the Sound Quality Preference Index (SQPI) predicting the human perception of tyre tread pattern sounds correctly (R2=0.94). The coupled source - human perception model can be used to speed up and improve the current tyre tread patter design process.