Research on Load-Spectrum Construction of Automobile Key Parts Based on Monte Carlo Sampling

Proceedings of the Institution of Mechanical Engineers, Part O:

et al. 2021

To study the influence of random parameter on the reliability of the vehicle front stabilizer bar, the fatigue strength is analyzed according to the random fatigue strength prediction method, then the fatigue limit of the actual parts are estimated, a new fatigue failure model is improved by using the fatigue limit [Formula: see text] of actual parts. Through this model, the stress spectrum collected by real vehicle is introduced, Monte-Carlo simulation method is adopted to analyze the reliability and sensitivities of stabilizer bar under driving conditions. In addition, the influence of each basic random parameter on the failure probability is obtained. The results show that stabilizer bar diameter has a great influence on the failure probability, which provides certain reference for improving the reliability of the front stabilizer bar.

Section: Establishment Of Fatigue Failure Modelmentioning

confidence: 99%

Improved fatigue failure model for reliability analysis of mechanical parts inducing stress spectrum

Proceedings of the Institution of Mechanical Engineers, Part O:

et al. 2021

“…41 Some signals with small load cycles are collected, which will not affect the fatigue life of the axle, the value is far less than the elastic limit of the material. 42 When the train is running, because the track is relatively flat, the load value on the axle is not too large. In order to facilitate analysis, this load signal needs to be removed.…”

Section: Data Processingmentioning

confidence: 99%

Fatigue life prediction of train wheel shaft based on load spectrum characteristics

Luo

Advances in Mechanical Engineering

et al. 2021

Based on the analysis of load spectrum data, the loading sequence and the interaction between loads are considered, a fatigue life prediction model based on load spectrum is proposed. The load spectrum is preprocessed and the probability density function of mean and amplitude are fitted. The running condition of the train is analyzed, the one-dimensional program load spectrum of wheel and axle load is constructed by extrapolating the load spectrum. According to the modified fatigue cumulative damage method, the fatigue life of the axle is predicted with the one-dimensional program load spectrum. The relevant factors that affect the strength of the part are fully considers in the model. It more accurately reflects the objective facts of the component fatigue process. The result has more engineering reference significance and it provides a theoretical basis for the design and manufacture of train axles and ensuring safe operation.

“…The test method helped to extend the service life of the blade safely, and its validity was verified in actual service condition. Wang et al (2018) analyzed interference of random factors in the process of load transfer route, and determined the load spectrum of key parts of the automobile. They provided the technical basis for fatigue life prediction.…”

Section: Introductionmentioning

confidence: 99%

Fatigue life prediction for automobile stabilizer bar

et al. 2019

IJSI

Purpose During the running of automobile, the stabilizer bar is frequently subjected to the impact of complex random loads, which is prone to fatigue failure and accident. In regard to this, the purpose of this paper is to study and discuss fatigue life of automobile stabilizer bar. Design/methodology/approach Durability bench test shows that failure is located at the joint of sleeve and stabilizer bar body. Based on the collection and compilation of micro-strain load spectrum of the stabilizer bar, the strain-life model is studied considering the influence of average stress and maximum stress at failure area. Seven-grade strain-life curves of the stabilizer bar are established. According to the principle of linear damage accumulation, the relationship between fatigue life and damage is discussed, then the fatigue life of stabilizer bar is predicted. Fatigue life evaluation is carried out from three aspects: reliability analysis, static analysis and fatigue life simulation. Findings The results show that the reliability of the test sample is 99.9 percent when the confidence is 90 percent and the durability is 1,073 load spectrum cycles; the ratios of predicted and simulated life to design life are 2.77 and 2.30, respectively. Originality/value Based on the road load characteristics of automobile stabilizer bar, the method of fatigue life prediction and evaluation is discussed, which provides a basis for the design and development of automobile chassis components.