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Fatigue Life Prediction of an Automobile Cradle Mount

Journal Article
2013-01-1009
ISSN: 1946-3995, e-ISSN: 1946-4002
Published April 08, 2013 by SAE International in United States
Fatigue Life Prediction of an Automobile Cradle Mount
Sector:
Citation: Zarrin-Ghalami, T., Fatemi, A., and Lee, Y., "Fatigue Life Prediction of an Automobile Cradle Mount," SAE Int. J. Passeng. Cars - Mech. Syst. 6(1):351-359, 2013, https://doi.org/10.4271/2013-01-1009.
Language: English

Abstract:

Elastomers have large reversible elastic deformation, good damping and high energy absorption capabilities. Due to these characteristics along with low cost of manufacturing, elastomeric components are widely used in many industries and applications, including in automobiles. These components are typically subjected to complex multiaxial and variable amplitude cyclic loads during their service life. Therefore, fatigue failure and life prediction are important issues in the design and analyses of these components. Availability of an effective CAE technique to evaluate fatigue damage and to predict fatigue life under complex loading conditions is a valuable tool for such analysis. This paper discusses a general CAE analytical technique for durability analysis and life prediction of elastomeric components. The methodology is then illustrated and verified by using experimental fatigue test results from an automobile cradle mount. The developed methodology involves constitutive behavior and fatigue behavior of the material, finite element analysis of the component, and fatigue damage quantification for life predictions. The commonly used Rainflow cycle counting method and Miner linear cumulative damage rule for metals are also evaluated for their application to variable amplitude loading of elastomeric components. The experiments included axial as well as combined in-phase and out-of-phase axial-torsion constant amplitude and variable amplitude tests. Comparisons of the predictions with experimental results show that the developed methodology correctly predicts the failure location. It also provides reasonably accurate estimates of the fatigue initiation life.