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The statistical energy analysis (SEA) is widely used to support the development of the sound package of cars. This paper will present the preparation of a model designed to investigate the sound package of the new Audi A3 and associated correlation against measurements. Special care was given during the creation of the model on the representation of the structure to enable the analysis of structure borne energy flow on top of the classical airborne analysis usually done with SEA. The sound package was also detailed in the model to allow further optimization and analysis of its performance. Two real life load cases will be presented to validate the model with measurements. First, the dominating powertrain and a second load case with dominating rolling noise. An analysis of the contribution of the different source components and a way to diagnose the weak paths of the vehicle will be presented. The focus of this investigation is the application of optimally adjusted treatment.

During the design phase of a vehicle, it is important to have a simulation tool, which allows to make multiple runs and check the sensitivity of the acoustic response to several trim configurations with a quick turnover time. The Statistical Energy Analysis (SEA) is widely used to investigate such problems for airborne excitation. For structure-borne excitation, classical methods based on a simplistic modeling of the trim using 1D oscillators and non-structural mass are not accurate enough to capture the actual behavior of the trim. On the other hand, a detailed Finite Element-Poroelastic Element Method (FE-PEM) modeling strategy of the trim may be time consuming. Besides the large number of degrees of freedom required to accurately model dissipative materials (e.g. poroelastic), a FE-based approach also needs a preprocessing phase where each layer of the trims must be carefully meshed.

The need for the industry to simulate and optimize the acoustic trim parts has increased during the last decade. There are many approaches to integrate the effect of an acoustic trim in a finite element model. These approaches can be very simple and empirical like the classical non-structural mass (NSM) combined to a high acoustic damping value in the receiver cavity to much more detailed and complex approach like the Poro-Elastic Materials (PEM) method using the Biot parameters. The objective of this paper is to identify which approach is the most appropriate in given situations. This article will first make a review of the theory behind the different methods (NSM, Impedances, Transfer Matrix Method, PEM). Each of them will be investigated for the different typical trim families used in the automotive industry: absorber, spring/mass, spring/mass/absorber.

The need in the automotive industry to understand the physical behavior of trims used in a vehicle is high. The PEM (poro-elastic method) was developed to permit an explicit representation of the trims in the FEM full vehicle models and to give tools to diagnose the effect of the trims and test design changes (porous material property, geometry, etc.,). During the last decade, the evolution of software and hardware has allowed the creation of models with highly detailed trim description (porous material using Biot parameters, plastic trims, etc.,). These models can provide good correlation up to 400Hz compared to measurements in contrast to classical NSM (Non Structural Mass) methodology which shows limitations.

Since the last decade, the automotive industry has expressed the need to better understand how the different trim parts interact together in a complete car up to 400 Hz for structureborne excitations. Classical FE methods in which the acoustic trim is represented as non-structural masses (NSM) and high damping or surface absorbers on the acoustic cavity can only be used at lower frequencies and do not provide insights into the interactions of the acoustic trims with the structure and the acoustic volume. It was demonstrated in several papers that modelling the acoustic components using the poroelastic finite element method (PEM) can yield accurate vibro-acoustic response such as transmission loss of a car component [1,2,3]. The increase of performance of today's computers and the further optimization of commercial simulation codes allow computations on full vehicle level [4,5,6] with adequate accuracy and computation times, which is essential for a car OEM.