A CFD/SEA Approach for Prediction of Vehicle Interior Noise due to Wind Noise

Paper #:
  • 2009-01-2203

Published:
  • 2009-05-19
DOI:
  • 10.4271/2009-01-2203
Citation:
Moron, P., Powell, R., Freed, D., Perot, F. et al., "A CFD/SEA Approach for Prediction of Vehicle Interior Noise due to Wind Noise," SAE Technical Paper 2009-01-2203, 2009, doi:10.4271/2009-01-2203.
Pages:
8
Abstract:
For most car manufacturers, aerodynamic noise is becoming the dominant high-frequency noise source (≻ 500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain mainly an experimental art implying high-cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the development of a reliable numerical prediction capability. The goal of this paper is to present a computational approach developed to predict the greenhouse wind noise contribution to the interior noise heard by the vehicle passengers. This method is based on coupling an unsteady Computational Fluid Dynamics (CFD) solver for the wind noise excitation to a Statistical Energy Analysis (SEA) solver for the structural acoustic behavior. The basic strategy is to convert the time-domain pressure signals generated by CFD everywhere on the panels into structural power inputs, which in turn are used as input to an SEA model leading to the noise inside the cabin. This approach quantifies the wind noise contribution coming from different panels (e.g., side windows, windshield) at various locations inside the vehicle (driver and passenger headspace). In this paper the key technical and numerical aspects of the approach are presented, and interior noise predictions corresponding to real automotive cases are compared to experimental measurements. As examples of the usage, a vehicle exterior shape design study and an acoustic package optimization study are presented.
Access
Now
SAE MOBILUS Subscriber? You may already have access.
Buy
Select
Price
List
Download
$26.00
Mail
$26.00
Members save up to 38% off list price.
Share
HTML for Linking to Page
Page URL

Related Items

Technical Paper / Journal Article
2003-10-19
Training / Education
2016-03-10
Training / Education
2011-04-12
Training / Education
2012-08-27