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Load spectrum for automotive wheels hub based on mixed probability distribution model

In actual engineering, the actual road test or indoor bench test is usually used to collect the data of the road load of the parts to acquire the fatigue life estimation of the auto parts. This paper proposes a method for load spectrum construction based on the mixed distribution probability model using the data of the road load spectrum collected in the test site. Pau Ta criteria outlier elimination and wavelet signal denoising are applied to analyze the original road load spectrum data. Then the maximum likelihood estimation method is used to estimate the generalized Pareto distribution parameters of all excesses. The Pareto distribution is also employed to extrapolate the load spectrum. Through the characteristic analysis of the load spectrum, the one-dimensional and two-dimensional program load spectrum of the hub is established based on the mixed probability distribution model, which provides a theoretical basis for the life prediction of the hub. In addition, the research results of this paper provide inspirations for the fatigue life prediction and fatigue durability bench test of automotive parts subjected to the complexity and variability of random loads.