Strain-based fatigue reliability assessment of an automobile’s lower arm for various road load conditions due to limited experimental data

The aim of this paper is to characterise the strain-based fatigue reliability of a lower arm suspension system using strain signals captured from different types of road load conditions. Given the challenges of acquiring comprehensive loading history data and the inherent difficulties in capturing accurate load–time history data through laboratory or fiield-testing, a stochastic modelling approach was developed. Strain loads obtained from strain gauges were stochastically induced to generate random loads, which were then used to assess fatigue reliability based on the experimental data. The fatigue life, ranging from 3.43 x 10<sup>5</sup> - 9.02 x 10<sup>5</sup> cycles per block for highway, rural, and campus roads, was evaluated using the rainfl ow cycle counting technique through the strain life models, i.e. CoffinManson, Morrow, and Smith-Watson-Topper. Furthermore, the reliability of the induced fatigue life data was modelled using a Weibull distribution, resulting in a mean cycle to failure for the lower arm falling within the range of 1.92 x 10<sup>6</sup> to 2.53 x 10<sup>6</sup> cycles per block. Among the various road conditions analyzed, the highway exhibited the highest fatigue life, indicating that it is less prone to failure compared to other road conditions, which can be attributed to the smoother road profile. Hence, the use of stochastically induced random loads is proposed as an effective method for assessing strain-based fatigue reliability in aiding for the prediction of the durability and structural integrity of the lower arm suspension system.