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Prediction of Eigenfrequencies and Eigenmodes of Seatbelt Retractors in the Vehicle Environment, Supporting an Acoustically Optimal Retractor Integration by CAE
Technical Paper
2018-01-1543
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
From an acoustical point of view, the integration of seatbelt retractors in a vehicle is a real challenge that has to be met early in the vehicle development process. The buzz and rattle noise of seat belt retractors is a weak yet disturbing interior noise. Street irregularities excite the wheels and this excitation is transferred via the car body to the mounting location of the retractor. Ultimately, the inertia sensor of the locking mechanism is also excited. This excitation can be amplified by structural resonances and generate a characteristic impact noise. The objective of this paper is to describe a simulation method for an early development phase that predicts the noise-relevant low frequency local modes and consequently the contact of the retractor with the mounting panel of the car body via the finite element method. Based on a round robin simulation study (1 OEM, 2 TIER1 suppliers, 1 research institute), different simulation approaches among the different companies were compared with each other and validated by experimental measurements. Partial divergences between the approaches were the subject of a detailed parametric study where the nonlinear contact definition, sub-model size and the influence of manufacturing tolerances were investigated. Based on these investigations, a robust approach with an acceptable prediction quality suitable for use in a process could be derived. This approach analyzes countermeasures such as dimples with regard to an improved robustness of the mounting situation and to increased lowest associated eigenfrequency.
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Citation
Schaffner, T., Girstmair, J., Neumann, J., Witfeld, E. et al., "Prediction of Eigenfrequencies and Eigenmodes of Seatbelt Retractors in the Vehicle Environment, Supporting an Acoustically Optimal Retractor Integration by CAE," SAE Technical Paper 2018-01-1543, 2018, https://doi.org/10.4271/2018-01-1543.Data Sets - Support Documents
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References
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