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Co-Simulation and Analysis on Aerodynamic Noise at the Engine Inlet
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
As the intake noise is a major contributing factor to automotive passenger compartment noise levels, it has received much more attention than before. Because the plastic manifolds could induce and transmit more noise owing to their lighter weight, aerodynamic noise has become a more serious problem in plastic manifolds than in conventional aluminum-made manifolds. Due to the complexity of aerodynamic noise of the intake system, it is difficult to predict the noise precisely, especially for the part whose frequency is higher than 1000 Hz. This paper introduces a new co-simulation method to simulate the aerodynamic noise at the engine inlet. With the coupled simulation between two programs, GT-Power and Fluent, it could simulate the gas flow inside the engine intake system, under the actual running condition of engine. Transient noise source data could be stored for every time step during the coupling process and then should be exported into LMS Virtual.Lab, used as boundary conditions for the calculating of aerodynamic noise at the engine inlet. The coupled simulation results are further corrected to eliminate the effects of cross-sectional area change. A reasonably good agreement was observed between the prediction of the sound pressure level and the actual measurement result at the engine inlet in the frequency range below 2500 Hz, which is better than the one-dimensional calculation data. The source of the intake noise under various frequencies can be identified through the visualization of sound pressure contours of the whole intake system, which can provide guidance for the next optimization design of the intake system structure and arrangement.
CitationQin, M., Gao, W., Liu, L., Zhang, P. et al., "Co-Simulation and Analysis on Aerodynamic Noise at the Engine Inlet," SAE Technical Paper 2018-01-0686, 2018, https://doi.org/10.4271/2018-01-0686.
Data Sets - Support Documents
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