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characteristics of the road surface. Both models are hybrid: they combine statistical laws with physical models. With a computing time of a few minutes (very quick compared to full physical models), they provide operational tools for tyre/road noise prediction. Particular fields of interest are road surface optimisation with respect to noise at the laboratory scale, conformity of production of a new surface and acoustic monitoring of roads. They are now implemented as user-friendly stand-alone applications. The presentation will address the principles of the models, their performances and their respective main fields of application. Part 1 will address the philosophy and the principles of the models.

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Considering the relative quietness of electric motors, tyre/road interaction has become the prominent source of noise emission from Electric Vehicles (EVs). This study deals with the potential influence of the road surface on EV noise emission, especially in urban area. A pass-by noise measurement campaign has been carried out on a reference test track, involving six different road surfaces and five electric passenger car models in different vehicle segments. The immunity of sound recordings to background noise was considered with care. The overall and spectral pass-by noise levels have been analysed as a function of the vehicle speed for each couple of road surface and EV model. It was found that the type of EV has few influence on the noise classification of the road surfaces at 50 km/h. However, the noise level difference between the quietest and the loudest road surface depends on the EV model, with an average close to 6 dBA, showing the potential effect of the road surface on noise reduction in the context of growing EV fleet in urban area. The perspective based on an average passenger EV in a future French or European electric fleet is addressed.