The main aim of the present study is to improve the High-Cycle Fatigue (HCF) life of automotive safety components subjected to multi-input random non-proportional loading. A case study was conducted on the automotive knuckle as one of the high-critical mechanical components of the suspension and steering systems. The steering knuckle is subjected to the highest road- and steering-induced random loads that are exerted on several points (i.e., joints of knuckle with lower control arm, steering linkage, and Macpherson strut). Moreover, incorrect adjustment of wheel angles increases the intensity of road loads. In this regard, previous studies have shown that wheel angles affect the service time of this component. In the present study, the authors attempted to present a novel design of wheel alignment to reduce the intensity of 3D stress components, and subsequently, to increase the fatigue life of the steering knuckle. To this end, a Hybrid multibody dynamic, finite element, and data mining techniques was used. Accordingly, different load histories extracted through Multi-Body Dynamics (MBD) analysis of a full vehicle model were applied on various joints of this component. Next, a transient dynamic analysis was performed, and the time histories of 3D stress fields were obtained in the critical zone. The fatigue life of the component was predicted using the Critical Plane Method (CPM) via employing the Rain-flow cycle counting technique and Miner-Palmgren damage accumulation rule. Finally, the results of Taguchi Sensitivity Analysis (TSA) were used to investigate the effect of wheel primary angles, including Camber and Toe, on the fatigue life of the cast iron knuckle. Moreover, Response Surface Method (RSM) was utilized to optimize the wheel alignment, and the cyclic lifetime of the component was compared under the pre- and post-optimization process. The results reveal that knuckle life improves by 33.66% using the optimum settings of wheel alignment.
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