Optimal disc brake design for reducing squeal instability using slip-dependent complex eigenvalue analysis
- Authors
- Yoon, Jungro; Park, Joosang; Min, Seungjae
- Issue Date
- Sep-2022
- Publisher
- Academic Press
- Keywords
- Squeal instability; Friction-induced vibration; Complex eigenvalue analysis; Surrogate modeling; Model-based design
- Citation
- Mechanical Systems and Signal Processing, v.177, pp.1 - 21
- Indexed
- SCIE
SCOPUS
- Journal Title
- Mechanical Systems and Signal Processing
- Volume
- 177
- Start Page
- 1
- End Page
- 21
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/185414
- DOI
- 10.1016/j.ymssp.2022.109240
- ISSN
- 0888-3270
- Abstract
- This paper proposes an improved disc brake system optimization method for squeal instability reduction using slip-dependent eigenvalue results. Although complex eigenvalue analysis is widely used for minimizing brake squeal instability, conventional optimization approaches still have the limitation of not being able to reflect slip rate-varying squeal instability characteristics. While relative angular velocity between the pad and disc declines due to braking, disc brake system instability gradually increases up to a specific peak velocity point and decreases until the vehicle stops, which means a maximum instability point exists during the braking process. Therefore, instability optimization should target the prevention of a maximum value during a braking scenario. The proposed optimization formulation is conducted considering maximum instability during full braking. To obtain braking time profiles, a model-based design method is employed and utilized instead of full finite element transient dynamic analysis to reduce computational cost. Kriging surrogate modeling is also used for solving the optimization problem and better express the multi-variable squeal problem. The proposed optimal design method produces minimal squeal instability during the full vehicle braking time range. The effectiveness of the proposed disc brake optimal design is demonstrated via acceleration power value comparison of the structure acceleration with that derived by conventional optimization approach.
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