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FBS Decoupling at Suspension Level for Road Noise Applications

Journal Article
2022-01-0978
ISSN: 2641-9637, e-ISSN: 2641-9645
Published June 15, 2022 by SAE International in United States
FBS Decoupling at Suspension Level for Road Noise Applications
Sector:
Citation: Minervini, D., Park, S., Dirickx, T., and Geluk, T., "FBS Decoupling at Suspension Level for Road Noise Applications," SAE Int. J. Adv. & Curr. Prac. in Mobility 5(2):937-951, 2023, https://doi.org/10.4271/2022-01-0978.
Language: English

Abstract:

With the electrification trend in the automotive industry, the main contributors to in-vehicle noise profile are represented by drivetrain, road and wind noise. To tackle the problem in an early stage, the industry is developing advanced techniques guaranteeing modularity and independent description of each contributor.
Component-based Transfer Path Analysis (C-TPA) allows individual characterization of substructures that can be assembled into a virtual vehicle assembly, allowing the manufacturers to switch between different designs, to handle the increased number of vehicle variants and increasing complexity of products. A major challenge in this methodology is to describe the subsystem in its realistic operational boundary conditions and preload. Moreover, to measure such component, it should be free at the connection interfaces, which logically creates significant difficulties to create the required conditions during the test campaign. A solution for this challenge can be Frequency-based Substructuring (FBS) decoupling, a technique aiming to characterize the vibrational behavior of an unknown component by subtracting the supporting structure from the complete assembly.
In this paper, FBS decoupling is applied to an experimental dataset of a suspension, subframe and damper when coupled with a test rig. The objective is to characterize its dynamics including preload and stick-slip phenomena. Four different variations of the classical formulation, using both interface and non-interface degrees of freedom, are used to identify the correct target. Moreover, an optimization process is exploited to refine the level of accuracy. Results are validated by direct comparison with measured in-vehicle cabin noise.