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Speaker performance in Acoustic Vehicle Alerting System (AVAS) plays a crucial role for pedestrian safety. Sound radiation from AVAS speaker has obvious directivity pattern. Considering this feature is critical for accurately simulating the exterior sound field of electrical vehicles. This paper proposes a new process to characterize the sound directivity pattern of AVAS speaker. The first step of the process is to perform an acoustic testing to measure the sound pressure radiated from the speaker at a certain number of microphone locations in a free field environment. Based on the geometry of a virtual speaker, the locations of each microphone and measured sound pressure data, an inverse method, namely the inverse pellicular analysis, is adopted to recover a set of vibration pattern of the virtual speaker surface. The recovered surface vibration pattern can then be incorporated in the full vehicle numerical model as an excitation for simulating the exterior sound field.

Vehicle sound insulation systems, such as front of dash mats or carpet assemblies, etc. play a key role in controlling vehicle interior noise. However, dash and carpet insulators are often designed to have varied thickness in compliance with packaging constraints or to fulfill manufacturing clearance requirements. While it is obvious to NVH engineers that thinned-down areas would significantly affect the insulation performance, design engineers would benefit from a quick tool to flag any design details that may negatively impact the performance. This paper therefore proposes a concept called the performance equivalent thickness for the sound insulation system. The aim is to link acoustic performance of an insulator layer to a geometric measure so that the component performance can be easily monitored and preserved at the design stage.

In recent years several variants of lightweight multi-layered acoustic treatments have been used successfully in vehicles to replace conventional barrier-decoupler interior dash mats. The principle involved is to utilize increased acoustic absorption to offset the decrease in insertion loss from the reduced mass such that equivalent vehicle level performance can be achieved. Typical dual density fibrous constructions consist of a relatively dense cap layer on top of a lofted layer. The density and flow resistivity of these layers are tuned to optimize a balance of insertion loss and absorption performance. Generally these have been found to be very effective with the exception of dash mats with very high insertion loss requirements. This paper describes an alternative treatment which consists of a micro-perforated film top layer and fibrous decoupler layer.

The primary function of damping treatment on a vibrating panel in a vehicle is to reduce vibration levels or radiated sound power by the dissipation of energy. However, in automotive applications the mass effects of damping materials should not be ignored, especially with regard to airborne noise performance. In this paper, a Finite Element-Statistical Energy Analysis (FE-SEA) hybrid analysis is used to evaluate the mass effects of applied damping materials on Sound Transmission Loss (STL). The analysis takes into consideration effects on both the elastic properties and modal mass of the panel. It is shown that while uniformly distributing the mass of the damping material over the panel generally over-estimate the mass effects on STL, an area weighting approach underestimates the effects. Results are confirmed by laboratory testing. A nomogram is generated to show the total effect of the mass of the damping material on STL.

In traditional FE based structure-borne noise analysis, interior trims are normally modeled as lump masses in the FE structure model and acoustic specific impedance of the trim is assigned to the FE acoustics model when necessary. This simplification has proven to be effective and sufficient for low frequency analysis. However, as the frequency goes into the mid-frequency range, the elastic behavior of the trim may impose some effects on the structural and acoustic responses. The approach described in this paper is based on the structural FE and acoustic SEA coupling analysis developed by ESI, aiming to improve the modeling efficiency for a possible quick turnaround in virtual assessments.

The Door system is one of the major paths for vehicle interior noise under a variety of load conditions. In this paper we consider the elements of the door lower (excluding glass) in terms of noise transmission. Passenger car doors are comprised of the outer skin, door cavity, door inner sheet metal, vapor barrier, and interior trim. Statistical Energy Analysis (SEA) models must effectively describe these components in terms of their acoustic properties and capture the dominant behaviors relative to the overall door system. In addition, the models must interface seamlessly with existing vehicle level SEA models. SEA modeling techniques for the door components are discussed with door STL testing and model correlation results.

With Statistical Energy Analysis (SEA) proven to be a powerful tool for airborne noise analysis, the capability of predicting the exterior sound field around a vehicle at high frequencies (the load case in the SEA analysis) is of particular interest to OEMs and suppliers. This paper employs the High Frequency Boundary Element Method (HFBEM) to simulate the scattered exterior sound field distribution due to a monopole source. It is shown that the proposed method is able to efficiently predict the spatial and frequency averaged sound pressure levels reasonably well up to 10 kHz, even at points in the near field of the vehicle body.

In this paper, a model condensation technique is developed to ensure consistent modeling of STL (Sound Transmission Loss) between coarse and detailed SEA model. In the Performance-Based coarse SEA Model, the component level performance (STL and absorption) is assigned to each path, which comes from various ways including detailed analytical SEA model. From the detailed SEA model for the component or even the whole vehicle, the equivalent performance data needs to be condensed and extracted for the coarse model. The condensation theory for equivalent STL is presented in this paper. The extra work needed to apply this technique to detailed SEA model is negligible by using AutoSEA script. An example for condensation of a detailed component model is given at the end. Comparison between the detailed analytical SEA model and the coarse SEA Model is consistent.

The application of Statistical Energy Analysis (SEA) to vehicle development is discussed, with a new technique to implement noise path analysis within a SEA model to enable efficient solution and optimization of acoustic trim. A whole vehicle Performance-Based SEA model is used, in which Sound Transmission Loss (STL) and acoustic absorption coefficient characterize subsystem performance. In such a model, the net contribution from each body panel/path, such as the floor, to a specific interior subsystem, such as the driver's head space, is extremely important for vehicle interior noise development. First, it helps to identify the critical path to root-cause potential problems. Second, it is necessary in order to perform balancing of path contributions. With current software, the power based noise contribution analysis is for direct paths/adjacent subsystems.

The Energy Flow Method (EFM), which is based on a Finite Element Analysis (FEA) model and its modal frequency response solution is presented in this paper. The energy and power for each subsystem are the primary response and excitation parameters as in the Statistical Energy analysis (SEA) method. This gives a broad-brush prediction by averaging over both frequency and spatial domain. This prediction is useful when uncertainties exist in the model. The FEA model is used to capture the geometry detail, which is critical in mid-frequency vibration. As an example, a five-plate system is studied using various methods, including traditional FEA, SEA and EFM. The last one has been implemented in MSC/NASTRAN. A discussion is given to understand the limitation of SEA and FEA application in mid frequency response.