Development of multiple linear regression-based models for fatigue life evaluation of automotive coil springs. (1st March 2019)

• Record Type: Journal Article
• Authors: Kong, Y.S.; Abdullah, S.; Schramm, D.; Omar, M.Z.; Haris, S.M.
• Is Part Of: Mechanical systems and signal processing. Volume 118(2019)
• Page Start: 675
• Page End: 695
• Publication Date: 2019-03-01
• Subjects: Spring durability -- Fatigue life predictions -- Quarter car model -- Multiple linear regression -- Data mining; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2018.09.007
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: MLR-based models are developed to predict fatigue life of automotive coil springs. Fatigue life is a function of the vertical vibrations and natural frequencies. Three types of strain-life models are chosen for fatigue analysis. All models fulfil linearity, normality, and homoscedasticity assumptions. All models have high R 2 values of more than 80%. 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.