Browse Publications Technical Papers 2019-01-1511

Extensive Correlation Study of Acoustic Trim Packages in Trimmed Body Modeling of an Automotive Vehicle 2019-01-1511

In the automotive sector, the structure borne noise generated by the engine and road-tire interactions is a major source of noise inside the passenger cavity. In order to increase the global acoustic comfort, predictive simulation models must be available in the design phase. The acoustic trims have a major impact on the noise level inside the car cavity. Although several publications for this kind of simulations can be found, an extensive correlation study with measurement is needed, in order to validate the modeling approaches. In this article, a detailed correlation study for a complete car is performed. The acoustic trim package of the measured car includes all acoustic trims, such as carpet, headliner, seats and firewall covers. The simulation methodology relies on the influence of the acoustic trim package on the car structure and acoustic cavities. The challenge lies in the definition of an efficient and accurate framework for acoustic trimmed bodies. Two different approaches to achieve this objective are reviewed. In the first approach, the acoustic trim package is modeled as a set of porous and solid layers represented by finite elements in physical coordinate system. The acoustic trim models update the modal fluid / structure model of the car body and car cavity. The second approach uses impedance surfaces to apply the acoustic absorption of the trimmed body on the car cavity side. It uses a Virtual Kundt’s tube. Both approaches are solved as state of the art modal analysis. The result of the correlation study provides acceleration and Sound Pressure Level (SPL) results for different configurations and excitations, introducing the Root Mean Squared Deviation (RMSD). The expected difference between the two approaches is obtained. The first approach results in higher correlation accuracy than the second approach, while the second approach has advantages in computational time.


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