Influence of translational vehicle dynamics on heavy vehicle noise emission.

Clicks: 203
ID: 41629
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #572 of 637 articles by views in The Science of the total environment

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 637 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Vehicle dynamics can play a significant role in the noise emission from heavy vehicles. In this work, a heavy vehicle noise emission model is presented to study the influence of translational vehicle dynamics on the sound power level emitted by heavy-duty trucks. Vehicle speed and acceleration are calculated using an analytical approximation that describes the tractive and retarding forces acting on a heavy vehicle on grade. Heavy vehicle noise emission associated with rolling noise is defined with reference to the Nordic traffic noise model that takes into account the number of axles for different articulated trucks. An expression for engine noise emission in terms of vehicle speed, weight, engine power, aerodynamic properties and road grade is derived. The individual and combined effects of engine noise and rolling noise for different vehicle mass combinations are examined. The influence of road grade on vehicle kinematics and noise emission is also investigated.
Reference Key
peng2019influencethe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Peng, Jeffrey;Liu, Daipei;Parnell, Jeffrey;Kessissoglou, Nicole;
Journal The Science of the total environment
Year 2019
DOI
S0048-9697(19)32999-7
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.