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Extended Solution of a Trimmed Vehicle Finite Element Model in the Mid-Frequency Range
ISSN: 0148-7191, e-ISSN: 2688-3627
To be published on September 30, 2020 by SAE International in United States
Event: 11th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference
The acoustic trim components play an essential role in Noise, Vibration and Harshness (NVH) behavior by reducing both the structure borne and airborne noise transmission while participating to the absorption inside the car and the damping of the structure. Over the past years, the interest for numerical solutions to predict the noise including trim effects in mid frequency range has grown, leading to the development of dedicated CAE tools. Finite Element (FE) models are an established method to analyze NVH problems. FE analysis is a robust and versatile approach that can be used for a large number of applications, like noise prediction inside and outside the vehicle due to different sources or pass-by noise simulation. Typically, results feature high quality correlations. However, future challenges, such as electric motorized vehicles, with changes of the motor noise spectrum, will require an extension of the existing approaches. In this paper, the vibro-acoustic frequency response of an existing MSC Nastran FE model is extended using the Actran Statistical Energy Analysis (SEA) approach, Virtual SEA. In Virtual SEA, the necessary information required to build the SEA system is extracted from the FE models. The fluid-structure Coupling Loss Factors (CLF) are computed through the Statistical modal Energy distribution Analysis (SmEdA) method. This method is a suitable candidate to account for acoustic trim effects based on analytical approach. The case studied consists of a trimmed body car model transfer function calculation. The result of the case study is an extensive correlation study containing measured and simulated transfer functions in low and mid frequency range. Simulation results are derived from two approaches, FE method and Virtual SEA method.