The OOR (out-of-roundness) wheel is one of the main excitation sources causing vehicle vibration. However, the OOR wheel is random, which indicates that the vehicle vibration obtained with a deterministic OOR wheel cannot comprehensively express dynamic performances. To this end, a probability analysis framework is proposed in this paper. First, the probability model of the OOR wheel is derived; Second, the equation of the vehicle system dynamics is modelled; Then, the direct probability integral method is developed to obtain the PDF (probability density function) of vehicle random vibration; Finally, the statistics characterized random vibration characteristics of the vehicle are calculated. The effectiveness of the proposed framework is verified with a case study. The results show that the PDF of vehicle random vibration excited by the Gaussian distribution OOR wheel excitation exhibits a right-skew shape, which significantly affects the dynamic performance. Compared to the Monte Carlo simulation, the proposed framework has higher computational efficiency for the same accuracy to analyze vehicle random vibration.


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    Titel :

    An Efficient Probability Analysis Framework to Obtain Vehicle Random Vibration Considering the Randomness of Out-of-Roundness Wheels


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Huang, Wei (Herausgeber:in) / Ahmadian, Mehdi (Herausgeber:in) / Wang, Tengfei (Autor:in) / Zhou, Jinsong (Autor:in) / Sun, Wenjing (Autor:in) / Li, Guoshun (Autor:in)

    Kongress:

    The IAVSD International Symposium on Dynamics of Vehicles on Roads and Tracks ; 2023 ; Ottawa, ON, Canada August 21, 2023 - August 25, 2023



    Erscheinungsdatum :

    01.11.2024


    Format / Umfang :

    6 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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