Fatigue life prediction of parabolic leaf spring under various road conditions

Y. S. Kong, Mohd. Zaidi Omar, L. B. Chua, Shahrum Abdullah

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Parabolic leaf spring experiences repeated cyclic loading during operating condition. Fatigue life assessment of the parabolic leaf spring is a significant aspect during the component design stage. This paper serves to simulate the fatigue life of a parabolic leaf spring design under variable amplitude loading (VAL). VALs carry the road signal that provokes fatigue failure on leaf spring. In order to seek for comprehensive leaf spring fatigue assessment, VALs signal were gathered through measurements from various road conditions such as highway, curve mountain road and rough rural area road. Subsequently, fatigue life of particular leaf spring design was predicted using finite element (FE) stress-strain model together with VALs signal as load input. For more conservative way, Morrow and Smith Watson Topper (SWT) mean stress correction methods were also applied. The results indicate that fatigue life of leaf spring is lowest during rough road mission, followed by curve mountain road and smooth highway road respectively. Additional design modification to prolong the fatigue life of the parabolic leaf spring is compulsory. The road VALs has provided even more realistic fatigue life estimation of parabolic leaf spring design when compared to traditional controlled laboratory method.

Original languageEnglish
Pages (from-to)92-103
Number of pages12
JournalEngineering Failure Analysis
Volume46
DOIs
Publication statusPublished - 2014

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Leaf springs
Fatigue of materials
Loads (forces)

Keywords

  • Fatigue life
  • Finite element
  • Parabolic leaf spring
  • Variable amplitude

ASJC Scopus subject areas

  • Materials Science(all)
  • Engineering(all)

Cite this

Fatigue life prediction of parabolic leaf spring under various road conditions. / Kong, Y. S.; Omar, Mohd. Zaidi; Chua, L. B.; Abdullah, Shahrum.

In: Engineering Failure Analysis, Vol. 46, 2014, p. 92-103.

Research output: Contribution to journalArticle

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