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

2009-01-2203

05/19/2009

Event
SAE 2009 Noise and Vibration Conference and Exhibition
Authors Abstract
Content
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 windnoise 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 windnoise 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 windnoise 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.
Meta TagsDetails
DOI
https://doi.org/10.4271/2009-01-2203
Pages
8
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, https://doi.org/10.4271/2009-01-2203.
Additional Details
Publisher
Published
May 19, 2009
Product Code
2009-01-2203
Content Type
Technical Paper
Language
English