Fretting Analysis of an Engine Bearing Cap Using Computer Simulation

Event
SAE 2016 World Congress and Exhibition
Authors Abstract
Content
The independent bearing cap is a cylinder block bearing structure that has high mass reduction effects. In general, this structure has low fastening stiffness compared to the rudder block structure. Furthermore, when using combination of different materials small sliding occurs at the mating surface, and fretting fatigue sometimes occurs at lower area than the material strength limit. Fretting fatigue was previously predicted using CAE, but there were issues with establishing a correlation with the actual engine under complex conditions, and the judgment criteria were not clear, so accurate prediction was a challenge. This paper reports on a new CAE-based prediction method to predict the fretting damage occurring on the bearing cap mating surface in an aluminum material cylinder block. First of all, condition a fretting fatigue test was performed with test pieces, and identification of CAE was performed for the strain and sliding amount. In addition, the fatigue life results obtained by the test-piece test were used to construct a fretting fatigue limit line for the strain and sliding amount of the CAE results. Next, identification was performed with an excitation rig test that simulates an actual engine operating condition, and the CAE boundary conditions were determined. The strength predicted by CAE and the fretting result by the excitation rig test were correlated well. It showed the validity of the newly constructed CAE method. Finally, fretting damage under the actual engine durability test was also predicted, and the results were confirmed to also exhibit good correlation.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-1083
Pages
7
Citation
Sato, K., Hamakawa, T., Yamasaki, T., Ishihara, Y. et al., "Fretting Analysis of an Engine Bearing Cap Using Computer Simulation," Engines 9(3):1847-1853, 2016, https://doi.org/10.4271/2016-01-1083.
Additional Details
Publisher
Published
Apr 5, 2016
Product Code
2016-01-1083
Content Type
Journal Article
Language
English