IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i4p3531-d1071399.html
   My bibliography  Save this article

Noise Emission Models of Electric Vehicles Considering Speed, Acceleration, and Motion State

Author

Listed:
  • Ziqin Lan

    (National Environmental Protection Engineering and Technology Center for Road Traffic Noise Control, Beijing 100088, China
    Research Institute of Highway Ministry of Transport, Beijing 100088, China
    School of Automobile and Transportation Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

  • Minmin Yuan

    (National Environmental Protection Engineering and Technology Center for Road Traffic Noise Control, Beijing 100088, China
    Research Institute of Highway Ministry of Transport, Beijing 100088, China)

  • Shegang Shao

    (National Environmental Protection Engineering and Technology Center for Road Traffic Noise Control, Beijing 100088, China
    Research Institute of Highway Ministry of Transport, Beijing 100088, China)

  • Feng Li

    (School of Automobile and Transportation Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China)

Abstract

Electric vehicles, known for their low-noise emission, are popular and widespread in metropolises in China, and they provide an opportunity for a reduction in environmental noise from vehicles. To understand the noise from electric vehicles better, this study develops noise emission models considering speed, acceleration, and motion state. The model construction is based on the data collected from a pass-by noise measurement experiment in Guangzhou, China. The models describe a linear relationship between the noise level, the logarithm of speed, and the acceleration for multiple motion states (i.e., the constant-speed state, the acceleration state, and the deceleration state). From the spectrum analysis, the low-frequency noise is barely affected by the speed and acceleration, but the noise at a certain frequency is most sensitive to them. Compared to other models, the proposed ones have the highest accuracy and the greatest ability for extrapolation and generalization.

Suggested Citation

  • Ziqin Lan & Minmin Yuan & Shegang Shao & Feng Li, 2023. "Noise Emission Models of Electric Vehicles Considering Speed, Acceleration, and Motion State," IJERPH, MDPI, vol. 20(4), pages 1-15, February.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:3531-:d:1071399
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/4/3531/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/4/3531/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gábor Horváth & Attila Bai & Sándor Szegedi & István Lázár & Csongor Máthé & László Huzsvai & Máté Zakar & Zoltán Gabnai & Tamás Tóth, 2023. "A Comprehensive Review of the Distinctive Tendencies of the Diffusion of E-Mobility in Central Europe," Energies, MDPI, vol. 16(14), pages 1-29, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:3531-:d:1071399. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.