1 option
Fatigue Life Analysis Methods for Rolling Lobe Air Spring South China University of Technology
- Format:
- Book
- Conference/Event
- Author/Creator:
- Yu, Yingjin, author.
- Conference Name:
- WCX SAE World Congress Experience (2024-04-16 : Detroit, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2024
- Summary:
- The fatigue prediction model of an air spring based on the crack initiation method is established in this study. Taking a rolling lobe air spring with an aluminum casing as the studying example, a finite element model for analyzing force versus displacement is developed. The static stiffness and dimensional parameters of limit positions are calculated and analyzed. The influence of different modeling methods of air springs bellow are compared and analyzed. Static stiffness measurement of an air spring is conducted, and the calculation results and the measured results of the static stiffness are compared. It is shown that the relative error of the measured stiffness and calculated stiffness is within 1%. The Abaqus post-processing stage is redeveloped in Python language. The damage parameters including the maximum principal nominal strain, maximum Green-Lagrange strain, and effective stress of air spring bellows are extracted and calculated to find out the critical points, where the maximum amplitude of damage parameters appear. Finally, according to the Miner damage accumulation rule, the fatigue life of an air spring under variable amplitude loads is estimated. The durability of the air spring is carried out. The fatigue life of the air spring predicted by the three models is given and compared with the measured fatigue life. It is concluded that the three proposed models in this paper for fatigue life prediction can be used to estimate the fatigue life for an air spring
- Notes:
- Vendor supplied data
- Publisher Number:
- 2024-01-2259
- Access Restriction:
- Restricted for use by site license
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