Correlation of Uniaxial and Multiaxial Fatigue Models for Automobile Spring Life Assessment

Y. S. Kong, S. Abdullah, D. Schramm, M. Z. Omar, S. M. Haris

Research output: Contribution to journalArticle

Abstract

This paper presents a regression analysis of uniaxial and multiaxial fatigue life for automobile coil spring under various road excitations. Coil spring is a suspension component with complex geometry and shear loading which is applied during operating conditions. Hence, uniaxial strain measurement for durability assessment of coil spring is insufficient because the loadings are non-proportional. Rosette strain signals of coil spring under five different road conditions were obtained and used as input to uniaxial strain-life and multiaxial critical plane models to predict the spring fatigue life. During the multiaxial fatigue analysis, the strain biaxiality ratio of range 0.3 to 0.5 indicates the loadings as out-of-phase. Through a simple linear regression method, a linear regression model between uniaxial and multiaxial fatigue life were obtained with coefficient of determination value as high as 0.8696. This model provides significant contribution through correlating uniaxial to multiaxial fatigue life. Hence, uniaxial fatigue life predictions could be approximated to multiaxial for more conservative analysis through the application of generated linear models.

Original languageEnglish
JournalExperimental Techniques
DOIs
Publication statusAccepted/In press - 1 Jan 2019

Fingerprint

Automobile springs
Fatigue of materials
Linear regression
Suspensions (components)
Strain measurement
Regression analysis
Automobiles
Durability
Geometry

Keywords

  • Coil spring
  • Critical plane
  • Linear regression
  • Multiaxial fatigue
  • Uniaxial fatigue

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering

Cite this

Correlation of Uniaxial and Multiaxial Fatigue Models for Automobile Spring Life Assessment. / Kong, Y. S.; Abdullah, S.; Schramm, D.; Omar, M. Z.; Haris, S. M.

In: Experimental Techniques, 01.01.2019.

Research output: Contribution to journalArticle

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