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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.

Analyzing low frequency brake noise (< 300Hz) has been challenging due to the difficulty associated with calculating dynamic friction behavior and its multiple structure-borne noise transfer paths. In theory, it is possible to simulate sound pressure level inside the cabin by calculating a transfer function between friction excitation, which is on the interface between rotor and pads, and cabin acoustic response, and by multiplying dynamic friction force at the rotor-pad interface to that transfer function. However, calculating the dynamic friction forces when brake noise occurs has been one of the most challenging research topics in the brake community. This paper describes a novel concept to simulate sound pressure level inside the cabin without knowing the dynamic friction forces at the rotor-pad interface in advance.

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 dash mat is one of the most important acoustic components in the vehicle for both powertrain noise and road noise attenuation. To optimize acoustic performance and mass requirements in the advanced development stage, analytical modeling is essential. The development of a detailed Statistical Energy Analysis (SEA) model of a dash mat is discussed in this paper. Modeling techniques and correlation with test are presented for two different production dash mat designs, a barrier-decoupler conventional system and a dual layer dissipative system without a mass barrier. The material properties and thickness distribution are used in the SEA model together with the geometry information of the dash panel. With the SEA model suitably correlated, trade-off studies are conducted to investigate the relationship between mass reduction of the barrier and change in decoupler thickness. The effects of air gaps are also considered in both modeling and testing.

This paper presents a pioneer work and first time application of Multi Objective Robust Optimization to analytically improve Idle Shake Performance. The method is developed to obtain a robust design with multiple objectives under consideration along with managing material property variation. It was a Robust Optimization on top of Multi Objective Genetic Algorithm, Robu-MOGA. The design variables in the study included the nominal values and tolerances of Sound Transmission Loss property, and interior material Absorption property. The analytical objective was not only to minimize the peak airborne noise at each specified frequency, but also to reduce the total cost and the total mass of the materials. In the study, AutoSEA (statistical energy analysis) from ESI Software, Inc. was used as the solver. AutoSEA was integrated with iSIGHT from Engineous Software, Inc.

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 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.

Damping treatments are widely used in passenger vehicles, but the knowledge of damping treatments is often fragmentary in the industry. In this study, vibro-acoustics behavior of a set of vehicle floor and dash panels with various types of damping treatments was investigated. Sound transmission loss, sound radiation efficiency as well as damping loss factor were measured. The damping treatments ranged from laminated steel construction (thin viscoelastic layer) and doubler plate construction (thick viscoelastic layer) to less structural “bake-on” damping and self-adhesive aluminum foil-backed damping treatments. In addition, the bare vehicle panels were tested as a baseline and the fully carpeted floor panel was tested as a reference. The test data were then examined together with analytical modeling of some of the test configurations. As expected, the study found that damping treatments add more than damping. They also add mass and change body panel stiffness.