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Prediction and Optimization of Blocked Force Changes of a Suspension System Using Bush Stiffness Injection Method

刚度 悬挂(拓扑) 控制理论(社会学) 材料科学 计算机科学 结构工程 工程类 数学 人工智能 纯数学 控制(管理) 同伦
作者
Munhwan Cho,David P. Song,Myoungok Lee,Jongwon Lee,Steven W. B. Klaassen,Ron Reichart,D. de Klerk,Eunyeong Kim,Yeon June Kang
出处
期刊:SAE technical paper series 卷期号:1 被引量:5
标识
DOI:10.4271/2022-01-0956
摘要

<div class="section abstract"><div class="htmlview paragraph">Automotive OEMs have introduced a new development paradigm, modular architecture development, to improve diversity quality and production efficiency. It needs solid fundamentals of system-based performance evaluation and development for each system level and single component level. When it comes to NVH development, it is challenging to realize the modular concept because noise and vibration should be transferred through various transfer path consisting of many parts and systems, which interact with each other. It is challenging for a single system of interest to be evaluated independently of the adjacent parts and environments. In this study, a new system-based development process for a vehicle suspension was investigated by applying blocked force theory and FRF-based dynamic substructuring. The objective is to determine the better dynamic stiffness distribution of many bushes installed in a suspension system in the frequency range corresponding to road noise. The suspension force rig test methodology isolated the entire suspension system from the interaction with body structures. The blocked force outputs are measured directly on the suspension force rig. Dynamic substructuring is conducted to derive the transfer characteristics from tire wheel centers to multiple force outputs. Bush stiffness injection (BSI) method is developed through the dynamic substructuring of the system, by which suspension system-level blocked force differences by changes in multiple bush stiffnesses can be predicted without any actual bush-changing works. The BSI method enables a sensitivity analysis for each change in bush dynamic stiffness and an optimization study to determine the best combination of multiple bush dynamic stiffnesses.</div></div>
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