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Analysis by synthesis of engine sounds for the design of dynamic auditory feedback of electric vehicles

Authors :
Dupré, Théophile
Denjean, Sébastien
Aramaki, Mitsuko
Kronland-Martinet, Richard
Perception, Représentations, Image, Son, Musique (PRISM)
Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)
Stellantis - PSA Centre Technique de Vélizy
Source :
Acta Acustica, Acta Acustica, 2023, 7, pp.36. ⟨10.1051/aacus/2023031⟩
Publication Year :
2023
Publisher :
HAL CCSD, 2023.

Abstract

In traditional combustion engine vehicles, the sound of the engine plays an important role in enhancing the driver’s experience of the vehicle’s dynamics, and contributes to both comfort and safety. However, with the development of quieter electric vehicles, drivers no longer receive this important auditory feedback, and this can lead to a less satisfying acoustic environment in the vehicle cabin. To address this issue, sonification strategies have been developed for electric vehicles to provide similar auditory feedback to the driver, but feedback from users has suggested that the sounds produced by these strategies do not blend seamlessly with the other sounds in the vehicle cabin. This study focuses on identifying the key acoustic parameters that create a sense of cohesion between the synthetic sounds and the vehicle’s natural soundscape, based on the characteristics of traditional combustion engine vehicles. Through analyzing the time and frequency of the noises produced by combustion engine vehicles, the presence of micro-modulations in both frequency and amplitude was identified, as well as resonances caused by the transfer of sound between the engine and the cabin. These parameters were incorporated into a synthesis model for the sonification of electric vehicle dynamics, based on the Shepard-Risset illusion. A perceptual test was conducted, and the results showed that the inclusion of resonances in the synthesized sounds significantly enhanced their naturalness, while micro-modulations had no significant impact.

Details

Language :
English
ISSN :
26814617
Database :
OpenAIRE
Journal :
Acta Acustica, Acta Acustica, 2023, 7, pp.36. ⟨10.1051/aacus/2023031⟩
Accession number :
edsair.od......3430..2cb419374a15204761831c756f85e2de