Abstract
Road traffic noise affects the quality of life of many citizens. In particular, the noise emitted by electric vehicles is mainly caused by tyre-road contact. There are many conflicts of interest between the performance characteristics of tyres and road surfaces. Therefore, more accurate prediction models are needed to exploit the potential for reducing tyre-road noise emissions during development. To this end, the TyreRoadNoise project team is developing a physics- and data-based tyre-road noise prediction model over a three-year period. A multi-manufacturer fleet of vehicles will collect extensive data on tyre-road noise emissions and their influencing parameters using simple measurement methods. AI methods will be used to estimate relevant parameters and correlations, which will be validated by measurements in controlled environments. The model should make it possible to extrapolate emissions on other routes from appropriate measurements on a specific road and to derive mitigation measures. Data and models will be made publicly available for future use. This article identifies the research needs, gives a brief overview of the project and describes the tyre-road noise measurement techniques used. Interested parties are invited to discuss and participate in the project.
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