Fatigue Reliability Assessment of an Automobile Coil Spring under Random Strain Loads Using Probabilistic Technique

Salvinder Singh Karam Singh,Reza Manouchehrynia,Shahrum Abdullah

doi:10.3390/met10010012

Abstract

This paper presents a mathematical model to estimate strain-life probabilistic modeling based on the fatigue reliability prediction of an automobile coil spring under random strain loads. The proposed technique was determined using a probabilistic method of the Gumbel distribution for strain-life models of automobile suspension systems. Strain signals from different road excitations in experimental tests were measured. The probability density function of the Gumbel distribution was considered to estimate model parameters using maximum likelihood estimation (MLE). The Akaike information criterion (AIC) method was performed to specify which model can estimate the best fit model parameters. Results demonstrated a good agreement between the predicted fatigue lives of the proposed probabilistic model and the measured strain fatigue life models. The root-mean-square errors (RMSE) based on the Coffin–Manson, Morrow, and Smith–Watson–Topper strain-life models were approximately 0.00114, 0.00107, and 0.00509, respectively, indicating a high correlation with the proposed model and experimental data. The results demonstrated that the proposed probabilistic model is effective for the fatigue life prediction of automobile coil springs using strain and stress fatigue life approaches.

Highlights

In recent years, random loadings have become important in predicting mechanical and structural system responses in various engineering fields
This study proposed a framework to explore a mathematical model based on the probabilistic method by using a probabilistic strain-life (ε-N) Gumbel distribution model
The probability density function (PDF) of the Gumbel distribution was considered for the proposed probabilistic mathematical model to estimate parameters by using the maximum likelihood estimation (MLE) method

Summary

Introduction

Random loadings have become important in predicting mechanical and structural system responses in various engineering fields. In this respect, the behavior of automobile suspension systems, coil springs, can be influenced by different road excitation loadings. Reliability assessment has been conducted using experimental, numerical, and analytical approaches alone and in combination [2] This process generally includes fatigue life techniques, which have been evaluated by numerous researchers [3,4,5]. Zhu et al [6,7] established a probabilistic framework based on a numerical approach to measure material and load variations for reliability assessment and fatigue life prediction

Methods

Results

Conclusion