Contribution
Assessing Tyre-Road Noise: Insights from Texture Analysis and Acoustic Characterisation
* Presenting author
Abstract:
The mFUND research project Tyre Road Noise (TyRoN) aims to identify and quantify innovative measures to reduce tyre-road noise (TRN) emissions, which are becoming increasingly dominant in electric vehicles. To this end, a comprehensive database of factors influencing TRN under real traffic conditions is being developed. Predictive models, powered by artificial intelligence techniques, seek to bridge the gap between physical models and real-world conditions for more accurate and reliable noise mitigation strategies.In an initial measurement campaign, extensive data were collected on 15 sections of German highways and motorways, which were temporarily closed for this purpose. These data include detailed macro- and micro texture parameters, friction values, and acoustic properties for model development.This paper analyses and compares these parameters across various pavement types. Macro- and micro textures were examined using Fourier Transform (FFT) and Power Spectral Density (PSD) analysis to identify their frequency components. Additionally, the road surface was acoustically characterized, analysing sound propagation and attenuation. Advanced methods were used to explore correlations between these parameters and TRN emissions.The findings enhance understanding of critical factors and provide a robust foundation for further investigations under real conditions, ultimately supporting the development of more effective noise reduction measures.