Environmental noise from alerting signals (AVAS) of electric vehicles: comparison with noise prediction models at urban speeds - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Environmental noise from alerting signals (AVAS) of electric vehicles: comparison with noise prediction models at urban speeds

Résumé

In the context of climate change and harmful impact of fossil fuels, electric vehicles (EVs) represent a strongly growing share of the light vehicle fleet, especially in urban areas. With their low propulsion noise, they offer a solution for reducing road traffic noise at urban speeds. In return, the arrival of an EV may be poorly detected audibly by a vulnerable user in a lively soundscape. Consequently, regulations require EVs to be equipped with an alerting signal (AVAS) below 20 km/h, with minimum sound level and some frequency characteristics. The study focuses on EV noise contribution from an environmental point of view when the AVAS is in operation. Based on experiments up to 30 km/h, it evaluates sound emission with several AVAS signals at EVs pass-by, considering laterality, global and frequency impact on acoustic indicators. While the modelling of EVs in national or European noise prediction methods is still an open subject, the results obtained on the tested vehicles with and without AVAS are compared with existing models for conventional vehicles (CNOSSOS-FR, NMPB) in the very low speed range that is becoming common in cities. The objective is to explore the relevance of an EV-specific model when AVAS is active.

Dates et versions

hal-04487359 , version 1 (03-03-2024)

Identifiants

Citer

Marie-Agnès Pallas, Maria Capatina, Adrien Le Bellec, Simon Bianchetti, Julien Cesbron. Environmental noise from alerting signals (AVAS) of electric vehicles: comparison with noise prediction models at urban speeds. 10th Convention of the European Acoustics Association Forum Acusticum 2023, Sep 2023, Turin, France. pp.751-757, ⟨10.61782/fa.2023.0613⟩. ⟨hal-04487359⟩

Collections

CEREMA UNIV-EIFFEL
23 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More