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In electrified automobiles, wind noise significantly contributes to the overall noise inside the cabin. In particular, underbody airflow is a dominant noise source at low frequencies (less than 500 Hz). However, the wind noise transmission mechanism through a battery electric vehicle (BEV) underbody is complex because the BEV has a battery under the floor panel. Although various types of underbody structures exist for BEVs, in this study, the focus was on an underbody structure with two surfaces as inputs of wind noise sources: the outer surface exposed to the external underbody flow, such as undercover and suspension, and the floor panel, located above the undercover and battery. In this study, aero-vibro-acoustic simulations were performed to clarify the transmission mechanism of the BEV underbody wind noise. The external flow and acoustic fields were simulated using computational fluid dynamics.

During the last decade, fuel economy mandates (CAFE regulations) have driven engine downsizing and down-speeding trends. More recently, downsized turbos are percolating down to heavier SUVs and trucks. Larger/heavier vehicles require high torque engines to provide attractive dynamic performance. While higher torque requirements can be satisfied with new innovations like the variable compression engine, larger and more upscale vehicles also need to deliver higher quietness requirements. For this, the vibration control system for combustion induced forces with high torque engines become very important. To address both dynamic performance and quietness requirements, active engine mounts have been previously adopted, however challenges for light-weighting, downsizing, and costs have still persisted.

Interior noise caused by exterior air flow, or wind noise, is one of the noise-and-vibration phenomena for which a systematic simulation method has been desired for enabling their prediction. One of the main difficulties in simulating wind noise is that, unlike most other noises from the engine or road input, wind noise has not one but two different types of sources, namely, convective and acoustic ones. Therefore, in order to synthesize the interior sound pressure level (SPL), the body sensitivities (interior SPL/outer source level) for both types of sources have to be considered. In particular, sensitivity to the convective input has not been well understood, and hence it has not been determined. Moreover, the high-frequency nature of wind noise (e.g., the main energy range extends up to 4000 Hz) has limited the effective application of CAE for determining body sensitivities, for example, from the side window glass to the occupants’ ears.

Recently, urgent needs have arisen for improving the fuel economy of passenger cars. To improve the fuel comsumption, it is necessary to develop a technology that can improve fuel efficiency and weight-saving. This paper describes the development of a soundproof package to balance weight-saving with performance of acoustic isolation used to reduce engine noise. First, we developed a hybrid statistical energy analysis (HSEA) model to evaluate the performance. Second, by using the HSEA model, we (1) analyzed the power flow and dominant path from noise source to interior cavity, (2) extracted efficient sections such as dash, dash penetration parts, and floor so as to improve the performance. Using the above process, we developed a soundproof package that improves the performance without increasing the weight. As a result, we balanced weight-saving with performance of acoustic isolation using the HSEA model.

This paper describes the design measures taken to develop the noise and vibration performance of a new rear suspension and a new drivetrain system for rear-wheel-drive vehicles. The new rear suspension is designed to solve trade-off issues between road noise and handling performance. Despite higher drive torque, booming noise is greatly reduced by the new rear suspension and drivetrain without increasing the vehicle weight or sacrificing fuel economy.

The accuracy of the vibro-acoustic coupled system model for the low frequency range depends on how accurately modal characteristics are represented at the input, output, and the structure-acoustic coupling surface. This study focus on extracting the detailed acoustic mode shapes on the coupling surface for the improvement of the model accuracy. In order to extract the acoustic mode shapes on the coupling surface from an experimental test, the applied method is initially evaluated by FE model results. As the next step, the same procedure in the previous step is applied to the test data of an actual vehicle for the purpose of extracting the detailed acoustic mode shapes at the coupling surface of the body structure and cabin interior acoustic field.