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Optimal Study on the TL of Automotive Door Sealing System Based on the Interior Speech Intelligibility Tongji University

SAE Technical Papers (1906-current) Available online

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Format:
Conference/Event
Author/Creator:
Deng, Deng, author.
Contributor:
Shao, Jianwang
Wu, Xian
Zhao, Meng
Zheng, Songlin
Conference Name:
WCX World Congress Experience (2018-04-10 : Detroit, Michigan, United States)
Language:
English
Physical Description:
1 online resource
Place of Publication:
Warrendale, PA SAE International 2018
Summary:
AbstractWind noise becomes the foremost noise source when a car runs at high speeds. High frequency characteristics of wind noise source and effective performance of seal rubbers for insulating leakage noise make research on the Transmission Loss (TL) of automotive door sealing systems significant. The improvement of TL of automotive door sealing system could effectively decrease the interior noise due to wind noise for vehicles at high speeds. In this study, compression simulation of seal rubbers for an automotive door is performed through a Finite Element (FE) tool firstly. Compressed geometries of the seal rubbers are obtained. Then, based on the final compressed geometries and pre-stress modes of the automotive door seal rubbers, the TL of the whole door sealing system is acquired by hybrid Finite Element - Statistic Energy Analysis (FE-SEA) method. The fluctuating surface pressure on a car body was captured by a Computational Fluid Dynamics (CFD) tool. The wind noise source is obtained by the Corcos model and the Boundary Element Method (BEM). A full vehicle SEA model is built to predict the interior sound pressure level. The TL of the automotive door sealing system is included in the full vehicle SEA model. After the SPL in the car is obtained by SEA simulation, the Articulation Index (AI) is calculated. Finally, the TL of the automotive door sealing system is optimized by orthogonal design of experiment based on AI. This integrated approach can be used to optimize TLs of automotive door sealing systems
Notes:
Vendor supplied data
Publisher Number:
2018-01-0672
Access Restriction:
Restricted for use by site license

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