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Mathematical Analysis of the Reliability of Modern Trolleybuses and Electric Buses

Author

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  • Boris V. Malozyomov

    (Department of Electrotechnical Complexes, Novosibirsk State Technical University, 630073 Novosibirsk, Russia)

  • Nikita V. Martyushev

    (Department of Materials Science, Tomsk Polytechnic University, 634050 Tomsk, Russia)

  • Vladimir Yu. Konyukhov

    (Department of Automation and Control, Irkutsk National Research Technical University, 664074 Irkutsk, Russia)

  • Tatiana A. Oparina

    (Department of Automation and Control, Irkutsk National Research Technical University, 664074 Irkutsk, Russia)

  • Nikolay A. Zagorodnii

    (Department of Operation and Organization of Vehicle Traffic, Belgorod State Technological University Named after V.G. Shukhov, 308012 Belgorod, Russia)

  • Egor A. Efremenkov

    (Department of Mechanical Engineering, Tomsk Polytechnic University, 634050 Tomsk, Russia)

  • Mengxu Qi

    (Department of Mechanical Engineering, Tomsk Polytechnic University, 634050 Tomsk, Russia)

Abstract

The rhythmic and stable operation of trolleybuses and autonomous trolleybuses or urban electric buses, depends to a large extent on the reliability of the equipment installed on the trolleybus. The actual operational reliability of trolleybus electrical equipment (EE) depends on its technical condition. Under the influence of external factors and specific operating modes, the technical condition of the equipment is continuously deteriorating, reliability indicators are decreasing, and the number of failures is increasing. Using the mathematical theory of reliability, probability theory and mathematical statistics, numerical methods of solving nonlinear and transcendental equations, this article defines the conditions of diagnostics depending on the intensity of failures and the given probability of failure-free operation of the equipment. Additionally, the inverse problem of determining the current reliability of electrical engineering systems depends on the terms of diagnostics and the intensity of failures being solved. As a result of the processing of statistical information on failures it is established that for the electrical equipment of a trolleybus, after a number of repair measures, the maximum density of failures occurs at a lower mileage, and the probability of failure-free operation can vary depending on the degree of wear of the equipment, i.e., on the number of previous failures. It is theoretically substantiated and experimentally confirmed that the reliability of trolleybus electrical equipment changes according to the exponential law of distribution of a random variable. It has been established that the real averaged diagnostic terms regulated by instructions are not optimal in most cases and differ several times from those defined in this paper. The dependence of switching equipment run-in on time has been clarified, which served as a prerequisite for specifying the inter-repair period for various types of trolleybus electrical equipment. A method of adjustment of the inter-repair time for the electrical equipment of trolleybuses is proposed.

Suggested Citation

  • Boris V. Malozyomov & Nikita V. Martyushev & Vladimir Yu. Konyukhov & Tatiana A. Oparina & Nikolay A. Zagorodnii & Egor A. Efremenkov & Mengxu Qi, 2023. "Mathematical Analysis of the Reliability of Modern Trolleybuses and Electric Buses," Mathematics, MDPI, vol. 11(15), pages 1-25, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:15:p:3260-:d:1201838
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    References listed on IDEAS

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    1. Nikita V. Martyushev & Boris V. Malozyomov & Svetlana N. Sorokova & Egor A. Efremenkov & Mengxu Qi, 2023. "Mathematical Modeling of the State of the Battery of Cargo Electric Vehicles," Mathematics, MDPI, vol. 11(3), pages 1-19, January.
    2. Nickolay I. Shchurov & Sergey I. Dedov & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergey N. Andriashin, 2021. "Degradation of Lithium-Ion Batteries in an Electric Transport Complex," Energies, MDPI, vol. 14(23), pages 1-33, December.
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    4. Chakrabarti, Sandip, 2015. "The demand for reliable transit service: New evidence using stop level data from the Los Angeles Metro bus system," Journal of Transport Geography, Elsevier, vol. 48(C), pages 154-164.
    5. Nikita V. Martyushev & Boris V. Malozyomov & Svetlana N. Sorokova & Egor A. Efremenkov & Mengxu Qi, 2023. "Mathematical Modeling the Performance of an Electric Vehicle Considering Various Driving Cycles," Mathematics, MDPI, vol. 11(11), pages 1-26, June.
    6. Boris V. Malozyomov & Nikita V. Martyushev & Vladislav V. Kukartsev & Vadim S. Tynchenko & Vladimir V. Bukhtoyarov & Xiaogang Wu & Yadviga A. Tyncheko & Viktor A. Kukartsev, 2023. "Overview of Methods for Enhanced Oil Recovery from Conventional and Unconventional Reservoirs," Energies, MDPI, vol. 16(13), pages 1-48, June.
    7. Boris V. Malozyomov & Nikita V. Martyushev & Svetlana N. Sorokova & Egor A. Efremenkov & Mengxu Qi, 2023. "Mathematical Modeling of Mechanical Forces and Power Balance in Electromechanical Energy Converter," Mathematics, MDPI, vol. 11(10), pages 1-11, May.
    8. Yeong Yoo & Yousef Al-Shawesh & Alain Tchagang, 2021. "Coordinated Control Strategy and Validation of Vehicle-to-Grid for Frequency Control," Energies, MDPI, vol. 14(9), pages 1-23, April.
    9. Jianfeng Li & Dongxiao Niu & Ming Wu & Yongli Wang & Fang Li & Huanran Dong, 2018. "Research on Battery Energy Storage as Backup Power in the Operation Optimization of a Regional Integrated Energy System," Energies, MDPI, vol. 11(11), pages 1-20, November.
    10. Nickolay I. Shchurov & Sergey V. Myatezh & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergei I. Dedov, 2021. "Determination of Inactive Powers in a Single-Phase AC Network," Energies, MDPI, vol. 14(16), pages 1-13, August.
    11. Boris V. Malozyomov & Vladimir Ivanovich Golik & Vladimir Brigida & Vladislav V. Kukartsev & Yadviga A. Tynchenko & Andrey A. Boyko & Sergey V. Tynchenko, 2023. "Substantiation of Drilling Parameters for Undermined Drainage Boreholes for Increasing Methane Production from Unconventional Coal-Gas Collectors," Energies, MDPI, vol. 16(11), pages 1-16, May.
    12. Nikita V. Martyushev & Boris V. Malozyomov & Ilham H. Khalikov & Viktor Alekseevich Kukartsev & Vladislav Viktorovich Kukartsev & Vadim Sergeevich Tynchenko & Yadviga Aleksandrovna Tynchenko & Mengxu , 2023. "Review of Methods for Improving the Energy Efficiency of Electrified Ground Transport by Optimizing Battery Consumption," Energies, MDPI, vol. 16(2), pages 1-39, January.
    13. Madina E. Isametova & Rollan Nussipali & Nikita V. Martyushev & Boris V. Malozyomov & Egor A. Efremenkov & Aysen Isametov, 2022. "Mathematical Modeling of the Reliability of Polymer Composite Materials," Mathematics, MDPI, vol. 10(21), pages 1-19, October.
    14. Ryosuke Kataoka & Kazuhiko Ogimoto & Yumiko Iwafune, 2021. "Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility," Energies, MDPI, vol. 14(22), pages 1-21, November.
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    2. Wendi Xu & Xianpeng Wang & Qingxin Guo & Xiangman Song & Ren Zhao & Guodong Zhao & Dakuo He & Te Xu & Ming Zhang & Yang Yang, 2023. "Decomposition Is All You Need: Single-Objective to Multi-Objective Optimization towards Artificial General Intelligence," Mathematics, MDPI, vol. 11(20), pages 1-11, October.
    3. Boris V. Malozyomov & Nikita V. Martyushev & Svetlana N. Sorokova & Egor A. Efremenkov & Denis V. Valuev & Mengxu Qi, 2024. "Analysis of a Predictive Mathematical Model of Weather Changes Based on Neural Networks," Mathematics, MDPI, vol. 12(3), pages 1-17, February.
    4. Boris V. Malozyomov & Nikita V. Martyushev & Svetlana N. Sorokova & Egor A. Efremenkov & Denis V. Valuev & Mengxu Qi, 2024. "Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks," Mathematics, MDPI, vol. 12(4), pages 1-32, February.

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