FBS Decoupling at Suspension Level for Road Noise Applications

底盘 汽车工业 解耦(概率) 计算机科学 噪音(视频) 触摸屏 组分(热力学) 工程类 模拟 汽车工程 控制工程 人工智能 机械工程 计算机硬件 物理 图像(数学) 热力学 航空航天工程
作者
Domenico Minervini,SangYoung Park,Tom Dirickx,Theo Geluk
出处
期刊:SAE International Journal of Advances and Current Practices in Mobility 卷期号:05 (2): 937-951 被引量:5
标识
DOI:10.4271/2022-01-0978
摘要

<div class="section abstract"><div class="htmlview paragraph">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.</div><div class="htmlview paragraph">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.</div><div class="htmlview paragraph">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.</div></div>
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