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A model of a tractor cab was built using Statistical Energy Analysis (SEA) best practices. In this paper, it is shown how this model was correlated using p/Q transfer functions measured in the lab with a volume velocity source. After correlation, the model was excited using acoustic loads measured during tractor operation. It was found that the data predicted by the model is in good agreement with the data measured inside the cabin during this test. It was concluded that SEA can be used as an engineering tool to predict the behavior under many different conditions and can be used to guide the development process.

The excitation of structural modes of vehicle roofs due to structure-borne excitations from the road and powertrain can generate boom and noise issues inside the passenger cabin. The use of elastomeric foams between the roof bows and roof panel can provide significant damping to the roof and reduce the vibration. If computer-aided engineering (CAE) can be used to predict the effect of elastomeric foams accurately on vibration and noise, then it would be possible to optimize the properties and placement of foam materials on the roof to attenuate vibration. The properties of the different foam materials were characterized in laboratory tests and then applied to a flat test panel and a vehicle body-in-white. This paper presents the results of an investigation into the testing and CAE analysis of the vibration and radiated sound power of flat steel panels and the roof from the BIW of an SUV with anti-flutter foam and Terophon® high damping foam (HDF) materials.

Porous materials have been applied increasingly for absorbing noise energy and improving the acoustic performance. Different models have been proposed to predict the performance of these materials, and much progress has been achieved. However, most of the foregoing researches have been conducted on a single layer of porous material. In real application, porous materials are usually combined with other kinds of materials to compose a multilayered noise control treatment. This paper investigates the acoustic performance of such treatments with a combination of porous and non-porous media. Results from numerical simulation are compared to experimental measurements. Transfer matrix method is adopted to simulate the insertion loss and absorption associated with three samples of a noise control treatment product, which has two porous layers bonded by an impervious screen.

Sound propagation through noise control treatment is governed by fluid, mechanical and geometric properties of the materials. The knowledge of material properties is important to improve the acoustical performance of the resulting noise control products. A method based on optimization together with genetic algorithm is used to estimate material properties of multi-layered treatments. Unlike previous inverse characterization approaches based on normal incidence performance metrics measured using standing wave impedance tubes, the current approach is based on random incidence performance metrics. Specially, the insertion loss ‘measured’ from two room transmission loss suite is utilized. To validate the applicability of the proposed method, numerically synthesized insertion loss computed from known material properties are used. In order to properly represent the ‘measured’ values, noise is added to the numerically synthesized insertion loss values.

Finite element analysis (FEA) is commonly used in the automotive industry to predict low frequency NVH behavior (<150 Hz) of structures. Also, statistical energy analysis (SEA) framework is used to predict high frequency (>400 Hz) noise transmission from the source space to the receiver space. A comprehensive approach addressing the entire spectrum (>20 Hz) by taking into account structure-borne and air-borne paths is not commonplace. In the works leading up to this paper a hybrid methodology was employed to predict structure-borne and air-borne transfer functions up to 1000 Hz by combining FEA and SEA. The dash panel was represented by FE structural subsystems and the noise control treatments (NCTs) and the pass-throughs were characterized via testing to limit uncertainty in modeling. The rest of the structure and the fluid spaces were characterized as SEA subsystems.