In this paper, an analytical procedure for prediction of shell radiated noise of air induction systems (AIS) due to engine acoustic excitation, without a prototype and physical measurement, is presented. A set of modeling and simulation techniques are introduced to address the challenges to the analytical radiated noise prediction of AIS products. A filter seal model is developed to simulate the unique nonlinear stiffness and damping properties of air cleaner boxes. A finite element model (FEM) of the AIS assembly is established by incorporating the AIS structure, the proposed filter seal model and its acoustic cavity model. The coupled acoustic-structural FEM of the AIS assembly is then employed to compute the velocity frequency response of the AIS structure with respect to the air-borne acoustic excitations. A boundary element model (BEM) is in turn employed to process the structural vibration results to predict the shell radiated noise in terms of sound pressure levels and their distributions. Verifications of filter seal models in air cleaner boxes are first demonstrated through CAE and test correlation, in terms of the point mobility results for AIS assemblies. Examples of analytical radiated noise prediction of AIS products are illustrated for applications of the proposed procedure, along with the filter seal modeling and coupled acoustic-structural simulation techniques. The benefits of the analytical radiated noise prediction for NVH performance evaluation and AIS product development are demonstrated as well.
Radiated Noise Prediction of Air Induction Systems Using Filter Seal Modeling and Coupled Acoustic-Structural Simulation Techniques
Sae Technical Papers
SAE World Congress & Exhibition ; 2007
2007-04-16
Conference paper
English
Acoustic Modeling and Radiated Noise Prediction for Plastic Air-Intake Manifolds
SAE Technical Papers | 2003
|Acoustic modeling and radiated noise prediction for plastic air-intake manifolds
Automotive engineering | 2003
|Engine radiated noise prediction modeling using noise source decomposition and regression analysis
Automotive engineering | 2005
|