Case study on noise identification of an electric vehicle using psychoacoustic metrics

被引：0

作者：

Guimaraes, G. P. ^{[1
]}

Schmidt, M. ^{[2
]}

Bartel, T. ^{[2
]}

Matthias, M. ^{[2
]}

机构：

[1] Fed Univ Ouro Preto UFOP, Dept Mech Engn, Campus Morro Cruzeiro, Ouro Preto, MG, Brazil

[2] Fraunhofer Inst Struct Durabil & Syst Reliabil LB, Smart Struct Div, Bartningstr 47, D-64289 Darmstadt, Germany

来源：

PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2020) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2020) | 2020年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

The electrification of vehicles brings new challenges to noise control, as higher frequency components and a lack of masking noise (originally from the combustion engine). This work focus on the experimental identification of electric vehicle (BMWi3) noise and on perception analysis. The measurements are made during a run-up manoeuvre and psychoacoustic analysis (based on loudness and sharpness) is performed afterwards. As results, strong tonal high-frequency noise arises related to the electrical motor orders and harmonic components (fan effect) from the power electronics, not only around the switching frequency but also around its multiples. By extracting (bandpass filter) and filtering (removing) orders and bands, it is possible to rank the components regarding its annoyance. Such results can contribute to the development of packaging of the noise sources, based on new materials (as metamaterials) and active solutions (as smart structures), as well as a combination of both (active metamaterials).

引用

页码：3303 / 3317

页数：15

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