IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i12p4256-d835161.html
   My bibliography  Save this article

Methodology for the Estimation of Electrical Power Consumed by Locomotives on Undocumented Railroad Tracks

Author

Listed:
  • Miguel Angel Rodriguez-Cabal

    (Facultad de Ingeniería, Departamento de Mecatrónica y Electromecánica, Instituto Tecnologico Metropolitano, Medellín 050036, Colombia
    These authors contributed equally to this work.)

  • Diego Alejandro Herrera-Jaramillo

    (Facultad de Ingeniería, Departamento de Electrónica y Telecomunicaciones, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia
    These authors contributed equally to this work.)

  • Juan David Bastidas-Rodriguez

    (Facultad de Ingeniería y Arquitectura, Universidad Nacional de Colombia, Manizales 170001, Colombia
    These authors contributed equally to this work.)

  • Juan Pablo Villegas-Ceballos

    (Facultad de Ingeniería, Departamento de Electrónica y Telecomunicaciones, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia
    These authors contributed equally to this work.)

  • Kevin Smit Montes-Villa

    (Facultad de Ingeniería, Departamento de Electrónica y Telecomunicaciones, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia
    These authors contributed equally to this work.)

Abstract

The energy consumption estimation of a locomotive for a particular route is important for the selection of a locomotive technology, the improvement of the energy management system, the evaluation of the locomotive’s potential energy generation, among others. The methodologies reported in the literature usually assume that the information of the railway track is available; however, in some cases, the track information is incomplete, not available, or the route is still in a planning stage. Therefore, this paper proposes a methodology to estimate the energy consumption and the potential energy generation of a locomotive when the railway track information is not available or incomplete. The methodology begins by extracting the main technical information of the locomotive to be analyzed. Then, the route is traced on Google Earth with steps of 100 m and the obtained information is processed to generate the longitude, latitude, elevation, and distance of the points along the route. From such information, it is possible to generate the slope and curvature profiles, while the speed profile can be obtained from the track operator or the regulations of a specific country. With that information, it is possible to estimate the equivalent power of the locomotive at each point of the route to finally calculate the consumed energy. The proposed methodology is validated with two case studies. The first one compares the results with a methodology available in the literature for the same route and locomotive, while the second case shows the applicability of the proposed methodology for a route without information.

Suggested Citation

  • Miguel Angel Rodriguez-Cabal & Diego Alejandro Herrera-Jaramillo & Juan David Bastidas-Rodriguez & Juan Pablo Villegas-Ceballos & Kevin Smit Montes-Villa, 2022. "Methodology for the Estimation of Electrical Power Consumed by Locomotives on Undocumented Railroad Tracks," Energies, MDPI, vol. 15(12), pages 1-23, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4256-:d:835161
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/12/4256/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/12/4256/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Loet Leydesdorff & Olle Persson, 2010. "Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1622-1634, August.
    2. Andrey Andryushchenko & Pavel Kolpahchyan & Alexander Zarifyan Jr., 2018. "Reduction Of Electric Locomotive'S Energy Consumption By Scalable Tractive Power Control," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 13(2), pages 103-110, June.
    3. Cipek, Mihael & Pavković, Danijel & Kljaić, Zdenko & Mlinarić, Tomislav Josip, 2019. "Assessment of battery-hybrid diesel-electric locomotive fuel savings and emission reduction potentials based on a realistic mountainous rail route," Energy, Elsevier, vol. 173(C), pages 1154-1171.
    4. Quintana, Jose J. & Ramos, Alejandro & Diaz, Moises & Nuez, Ignacio, 2021. "Energy efficiency analysis as a function of the working voltages in supercapacitors," Energy, Elsevier, vol. 230(C).
    5. Cipek, Mihael & Pavković, Danijel & Krznar, Matija & Kljaić, Zdenko & Mlinarić, Tomislav Josip, 2021. "Comparative analysis of conventional diesel-electric and hypothetical battery-electric heavy haul locomotive operation in terms of fuel savings and emissions reduction potentials," Energy, Elsevier, vol. 232(C).
    6. Qiwei Lu & Bangbang He & Mingzhe Wu & Zhichun Zhang & Jiantao Luo & Yankui Zhang & Runkai He & Kunyu Wang, 2018. "Establishment and Analysis of Energy Consumption Model of Heavy-Haul Train on Large Long Slope," Energies, MDPI, vol. 11(4), pages 1-20, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Chi & Zeng, Guohong & Wu, Jian & Wei, Shaoyuan & Zhang, Weige & Sun, Bingxiang, 2023. "Integrated optimization of driving strategy and energy management for hybrid diesel multiple units," Energy, Elsevier, vol. 281(C).
    2. Chen, Shuang & Hu, Minghui & Lei, Yanlei & Kong, Linghao, 2023. "Novel hybrid power system and energy management strategy for locomotives," Applied Energy, Elsevier, vol. 348(C).
    3. Jiang Wu, 2013. "Geographical knowledge diffusion and spatial diversity citation rank," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 181-201, January.
    4. Bornmann, Lutz & Leydesdorff, Loet, 2012. "Which are the best performing regions in information science in terms of highly cited papers? Some improvements of our previous mapping approaches," Journal of Informetrics, Elsevier, vol. 6(2), pages 336-345.
    5. Kapetanović, Marko & Núñez, Alfredo & van Oort, Niels & Goverde, Rob M.P., 2021. "Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains," Applied Energy, Elsevier, vol. 294(C).
    6. Matija Krznar & Petar Piljek & Denis Kotarski & Danijel Pavković, 2021. "Modeling, Control System Design and Preliminary Experimental Verification of a Hybrid Power Unit Suitable for Multirotor UAVs," Energies, MDPI, vol. 14(9), pages 1-24, May.
    7. Marina Van Geenhuizen & Pieter Stek, 2015. "Mapping innovation in the global photovoltaic industry: a bibliometric approach to cluster identification and analysis," ERSA conference papers ersa15p697, European Regional Science Association.
    8. Wang, Bin & Wang, Chaohui & Wang, Zhiyu & Ni, Siliang & Yang, Yixin & Tian, Pengyu, 2023. "Adaptive state of energy evaluation for supercapacitor in emergency power system of more-electric aircraft," Energy, Elsevier, vol. 263(PA).
    9. Irena Sajovic & Bojana Boh Podgornik, 2022. "Bibliometric Analysis of Visualizations in Computer Graphics: A Study," SAGE Open, , vol. 12(1), pages 21582440211, January.
    10. Waltman, Ludo & Tijssen, Robert J.W. & Eck, Nees Jan van, 2011. "Globalisation of science in kilometres," Journal of Informetrics, Elsevier, vol. 5(4), pages 574-582.
    11. Mo Chen & Zhuang Xiao & Pengfei Sun & Qingyuan Wang & Bo Jin & Xiaoyun Feng, 2019. "Energy-Efficient Driving Strategies for Multi-Train by Optimization and Update Speed Profiles Considering Transmission Losses of Regenerative Energy," Energies, MDPI, vol. 12(18), pages 1-25, September.
    12. Geraldo J. Pessoa Junior & Thiago M. R. Dias & Thiago H. P. Silva & Alberto H. F. Laender, 2020. "On interdisciplinary collaborations in scientific coauthorship networks: the case of the Brazilian community," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2341-2360, September.
    13. Bornmann, Lutz & Waltman, Ludo, 2011. "The detection of “hot regions” in the geography of science—A visualization approach by using density maps," Journal of Informetrics, Elsevier, vol. 5(4), pages 547-553.
    14. Yunfang Jiang & Luyao Hou & Tiemao Shi & Qinchang Gui, 2017. "A Review of Urban Planning Research for Climate Change," Sustainability, MDPI, vol. 9(12), pages 1-21, December.
    15. Gaston Heimeriks & Ron Boschma, 2014. "The path- and place-dependent nature of scientific knowledge production in biotech 1986–2008," Journal of Economic Geography, Oxford University Press, vol. 14(2), pages 339-364.
    16. Juraj Karlušić & Mihael Cipek & Danijel Pavković & Željko Šitum & Juraj Benić & Marijan Šušnjar, 2020. "Benefit Assessment of Skidder Powertrain Hybridization Utilizing a Novel Cascade Optimization Algorithm," Sustainability, MDPI, vol. 12(24), pages 1-15, December.
    17. Artur Kierzkowski & Szymon Haładyn, 2022. "Method for Reconfiguring Train Schedules Taking into Account the Global Reduction of Railway Energy Consumption," Energies, MDPI, vol. 15(5), pages 1-18, March.
    18. Guangyao Zhang & Yuqi Wang & Weixi Xie & Han Du & Chunlin Jiang & Xianwen Wang, 2021. "The open access usage advantage: a temporal and spatial analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6187-6199, July.
    19. Lu, Kun & Wolfram, Dietmar, 2010. "Geographic characteristics of the growth of informetrics literature 1987–2008," Journal of Informetrics, Elsevier, vol. 4(4), pages 591-601.
    20. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4256-:d:835161. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.