Development of multiple linear regression-based models for fatigue life evaluation of automotive coil springs

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

Research output: Contribution to journalArticle

Abstract

This paper discusses the establishment of multiple linear regression (MLR)-based spring durability models for predicting the fatigue life of automotive coil springs based on the vertical vibrations of the vehicle and natural frequencies of the vehicle suspension system. These models were developed in order to simplify the design and development process of vehicle suspension systems, which is both time-intensive and cost-intensive. The simulated force-time histories were processed to obtain the fatigue life of the automotive coil spring based on the strain-life models whereas the acceleration-time histories were weighted according to the ISO-2631-1:1997 standard to determine the vertical vibrations of the vehicle. MLR was used to establish the spring durability models and the goodness of fit, linearity, normality, and homoscedasticity of the models were assessed. The highest coefficient of determination at 0.8820 was obtained for the Morrow MLR-based spring durability model, with the mean square error of 0.5855. The models were validated by comparing the fatigue life values predicted by the models with those predicted from strain measurements. The results show a good agreement between the predicted and experimental values, indicating the suitability of these models in predicting the fatigue life of automotive coil springs.

LanguageEnglish
Pages675-695
Number of pages21
JournalMechanical Systems and Signal Processing
Volume118
DOIs
Publication statusPublished - 1 Mar 2019

Fingerprint

Linear regression
Fatigue of materials
Vehicle suspensions
Durability
Strain measurement
Mean square error
Vibrations (mechanical)
Natural frequencies

Keywords

  • Data mining
  • Fatigue life predictions
  • Multiple linear regression
  • Quarter car model
  • Spring durability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications

Cite this

Development of multiple linear regression-based models for fatigue life evaluation of automotive coil springs. / Kong, Y. S.; Abdullah, Shahrum; Schramm, D.; Omar, M. Z.; Mohamed Haris, Sallehuddin.

In: Mechanical Systems and Signal Processing, Vol. 118, 01.03.2019, p. 675-695.

Research output: Contribution to journalArticle

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