International Journal of Transportation Engineering and Technology

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Predicting of the Residual Resource of Car Assemblies

Received: 13 February 2019    Accepted: 12 April 2019    Published: 26 October 2019
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Abstract

The research paper introduces a method that can be used for the forecasting the residual life of automobile aggregates (through the example of automobile engines). The results of a test-drive have shown that the proposed method is less labor intensive and has a satisfactory forecast accuracy. In the research the tenets of the reliability theory and mathematical statistics were used as well as information on the post-repair operating time of repaired engines based on the value of the initial main parameter (the gap between the piston and cylinder) for 41 engines. The probability density of this parameter follows the Gauss’ law. In our work we accept the nonlinear change in the mathematical expectation of the main parameter depending on the operating time in the form of a power law. The probability density of the aggregate resource is distributed according to the Weibull law. Adequacy of theoretical information to experimental data was determined by the Fisher criterion. The forecasting of the residual life of the aggregates is relevant when the operating time approaches their limit state. The relative forecast error varies from 0.021 to 0.130, which is quite acceptable for the real-world applications.

DOI 10.11648/j.ijtet.20190504.11
Published in International Journal of Transportation Engineering and Technology (Volume 5, Issue 4, December 2019)
Page(s) 68-73
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Assembly, Reliability, Longevity, Diagnostic Parameter, Residual Resource, Prediction

References
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[3] Bazhenov Yu. V. Prediction of the residual life of electronic engine control systems / Yu.V. Bazhenov, V.P.Kalenov // Bulletin of the Siberian State Automobile and Highway Academy. 2017. – № 2 (54). – Р. 52–59.
[4] Ismagilov R. N. Prediction of the residual life of the bearing according to the vibration level of the mechanism / R. N. Ismagilov, R. R. Gareev, V. U. Yamaliev, A. A. Matsibor // Exposure Oil Gas. – 2015. – № 3 (42). – P. 65–68.
[5] Desnitsky A. A. Problems of predicting the residual resource of safe operation of fire trucks in the EMERCOM of Russia system / A.A. Desnitsky, N.M. Laurent // Modern technologies for civil defense and emergency response vol. 1. – 2016. – № 1 (7). – Р. 110–114.
[6] Kokorev G. D. Methods of selection of diagnosed parameters of cars in the conditions of agricultural production / G. D. Kokorev// Polythematic network electronic scientific journal of the Kuban State Agrarian University. – 2016. – № 117. – Р. 793-806.
[7] Da-shuai W. Research on Service Life Prediction of Diesel Engine /X. Xin-peng, W. Feng-zhong, C. Zhi-qiang, Z. DA-peng // Journal of Software Engineering, 2016. – № 10. – P. 392–399.
[8] Chebotarev M. I. The expert method of factor analysis of the operational reliability of combine harvesters /M. I. Chebotarev, B.F. Tarasenko, Y. A. Shapiro // Polythematic network electronic scientific journal of the Kuban State Agrarian University. – 2018. – № 136. – Р. 71–86.
[9] Richa S. Rana R. Chi-square test and its application in hypothesis testing / S. Richa, R. Rana // Journal of the Practice of Cardiovascular Sciences. – 2015. – № 1 – Р. 69–71.
[10] Gurvich, I. B. Operational reliability of automobile engines / I. B. Gurvich, P. E. Syrkin. - M.: Transport, 1984. - 141 p.
[11] Zhdanovsky, N. S. Reliability and durability of automotive engines / N. S. Zhdanovsky, A. V. Nikolaenko. – M.: Kolos, 1981. - 292 p.
[12] Mikhlin, V. M. Management of reliability of agricultural machinery / V. M. Mikhlin. - M.: Kolos, 1984.— 335 p.
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[14] Ivanov, V. P. Complex diagnosis of the cylinder-piston group of the internal combustion engine // V. P. Ivanov, A. N. Vaskovich, G. A. Uvarov // Bulletin of the PGU: Industry. Applied Sciences - 2015. - № 11. - P. 87–92.
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Author Information
  • Department of Road Transport, State University of Polotzk, Novopolotsk, Republic of Belarus

  • Department of Road Transport, State University of Polotzk, Novopolotsk, Republic of Belarus

  • Department of Road Transport, State University of Polotzk, Novopolotsk, Republic of Belarus

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    Ivanov Vladimir, Vigerina Tatyana, Pilipenko Stanislav. (2019). Predicting of the Residual Resource of Car Assemblies. International Journal of Transportation Engineering and Technology, 5(4), 68-73. https://doi.org/10.11648/j.ijtet.20190504.11

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    ACS Style

    Ivanov Vladimir; Vigerina Tatyana; Pilipenko Stanislav. Predicting of the Residual Resource of Car Assemblies. Int. J. Transp. Eng. Technol. 2019, 5(4), 68-73. doi: 10.11648/j.ijtet.20190504.11

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    AMA Style

    Ivanov Vladimir, Vigerina Tatyana, Pilipenko Stanislav. Predicting of the Residual Resource of Car Assemblies. Int J Transp Eng Technol. 2019;5(4):68-73. doi: 10.11648/j.ijtet.20190504.11

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  • @article{10.11648/j.ijtet.20190504.11,
      author = {Ivanov Vladimir and Vigerina Tatyana and Pilipenko Stanislav},
      title = {Predicting of the Residual Resource of Car Assemblies},
      journal = {International Journal of Transportation Engineering and Technology},
      volume = {5},
      number = {4},
      pages = {68-73},
      doi = {10.11648/j.ijtet.20190504.11},
      url = {https://doi.org/10.11648/j.ijtet.20190504.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijtet.20190504.11},
      abstract = {The research paper introduces a method that can be used for the forecasting the residual life of automobile aggregates (through the example of automobile engines). The results of a test-drive have shown that the proposed method is less labor intensive and has a satisfactory forecast accuracy. In the research the tenets of the reliability theory and mathematical statistics were used as well as information on the post-repair operating time of repaired engines based on the value of the initial main parameter (the gap between the piston and cylinder) for 41 engines. The probability density of this parameter follows the Gauss’ law. In our work we accept the nonlinear change in the mathematical expectation of the main parameter depending on the operating time in the form of a power law. The probability density of the aggregate resource is distributed according to the Weibull law. Adequacy of theoretical information to experimental data was determined by the Fisher criterion. The forecasting of the residual life of the aggregates is relevant when the operating time approaches their limit state. The relative forecast error varies from 0.021 to 0.130, which is quite acceptable for the real-world applications.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Predicting of the Residual Resource of Car Assemblies
    AU  - Ivanov Vladimir
    AU  - Vigerina Tatyana
    AU  - Pilipenko Stanislav
    Y1  - 2019/10/26
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ijtet.20190504.11
    DO  - 10.11648/j.ijtet.20190504.11
    T2  - International Journal of Transportation Engineering and Technology
    JF  - International Journal of Transportation Engineering and Technology
    JO  - International Journal of Transportation Engineering and Technology
    SP  - 68
    EP  - 73
    PB  - Science Publishing Group
    SN  - 2575-1751
    UR  - https://doi.org/10.11648/j.ijtet.20190504.11
    AB  - The research paper introduces a method that can be used for the forecasting the residual life of automobile aggregates (through the example of automobile engines). The results of a test-drive have shown that the proposed method is less labor intensive and has a satisfactory forecast accuracy. In the research the tenets of the reliability theory and mathematical statistics were used as well as information on the post-repair operating time of repaired engines based on the value of the initial main parameter (the gap between the piston and cylinder) for 41 engines. The probability density of this parameter follows the Gauss’ law. In our work we accept the nonlinear change in the mathematical expectation of the main parameter depending on the operating time in the form of a power law. The probability density of the aggregate resource is distributed according to the Weibull law. Adequacy of theoretical information to experimental data was determined by the Fisher criterion. The forecasting of the residual life of the aggregates is relevant when the operating time approaches their limit state. The relative forecast error varies from 0.021 to 0.130, which is quite acceptable for the real-world applications.
    VL  - 5
    IS  - 4
    ER  - 

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