Communications - Scientific letters of the University of Zilina X:X | DOI: 10.26552/com.C.2026.045

Modelling and Optimization of Hydrogen Fuel Systems in Railway Vehicles Using Data Analysis and Machine Learning

Oleksandra Shepel1, Ján Dižo ORCID...2, *, Miroslav Blatnický ORCID...2, Martin Bučko ORCID...2
1 Independent researcher, Vilnius, Lithuania
2 University of Zilina, Faculty of Mechanical Engineering, Department of Trasport and Handling Machines, Zilina, Slovakia

Hydrogen fuel cell systems offer a zero-emission alternative to diesel-powered trains, combining high energy density with the potential for renewable energy integration. A hybrid data-driven modelling and optimization approach of improving the efficiency, reliability, and cost-effectiveness of hydrogen fuel systems for rail applications is developed in this research. Using operational and thermodynamic data from simulated and experimental sources, a predictive model of fuel cell performance based on non-linear regression and machine learning methods was developed. Results indicate that the data-driven model predicts system efficiency with a mean absolute error (MAE) of 1.9%, while the optimization framework reduces fuel consumption by up to 12.4% compared to reference operation strategies. The study proves the value of machine learning in optimizing hydrogen energy systems.

Keywords: hydrogen railway transport, environmental optimization, machine learning, fuel cell system, sustainability
Grants and funding:

This publication was realized with support of Operational Program Integrated Infrastructure 2014 - 2020 of the project: Concept, safety and related industrial research for the replacement of diesel traction by hydrogen fuel cell traction in the railway vehicles series 861 (code ITMS2014+: 313011BVC2), co-financed by the European Regional Development Fund. This publication was also supported by the Cultural and Educational Grant Agency of the Ministry of Education of the Slovak Republic in the project KEGA 028ZU-4/2026: Integration of advanced modelling methods and simulation computations into university education of future specialists in vehicles' design.

Conflicts of interest:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Received: May 12, 2026; Accepted: July 7, 2026; Prepublished online: August 20, 2026 

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    References

    1. ALI, Y., MEHMOOD, B., HUZAIFA, M., YASIR, U., KHAN, A.U. Development of a new hybrid multi criteria decision-making method for a car selection scenario. Facta Universitatis Series Mechanical Engineering [online]. 2020, 18(3), p. 357-373 [accessed 2026-04-13]. ISSN 2335-0164. Available from: https://doi.org/10.22190/FUME200305031A Go to original source...
    2. AL-LAMI, A., TOROK, A. Economic growth and transport emissions: testing the environmental Kuznets Curve in Austria and the Netherlands. Transportation Research Procedia [online]. 2026, 93, p. 71-76 [accessed 2026-04-17]. ISSN 2352-1465. Available from: https://doi.org/10.1016/j.trpro.2025.11.011 Go to original source...
    3. FOMIN, O., LOVSKA, A., PISTEK, V., KUCERA, P. Research of stability of containers in the combined trains during transportation by railroad ferry. MM Science Journal [online]. 2020, 2020, p. 3728-3773 [accessed 2026-05-02]. ISSN 1805-0476. Available from: https://doi.org/10.17973/MMSJ.2020_03_2019043 Go to original source...
    4. GERLICI, J., LOVSKA, A., PAVLIUCHENKOV, M. Study of the dynamics and strength of the detachable module for long cargoes under asymmetric loading diagrams. Applied Sciences [online]. 2024, 14(8), 3211 [accessed 2026-03-13]. ISSN 2076-3417. Available from: https://doi.org/10.3390/app14083211 Go to original source...
    5. FOMIN, O., LOVSKA, A., KUCERA, P., PISTEK, V. Substantiation of improvements for the bearing structure of an open car to provide a higher security during rail/sea transportation. Journal of Marine Science and Engineering [online]. 2021, 9(8), 873 [accessed 2026-05-02]. ISSN 2077-1312. Available from: https://doi.org/10.3390/jmse9080873 Go to original source...
    6. PANCHENKO, S., GERLICI, J., VATULIA, G., LOVSKA, A., RYBIN, A., KRAVCHENKO, O. Strength assessment of an improved design of a tank container under operating conditions. Communications - Scientific Letters of the University of Zilina [online]. 2023, 25(3), p. B186-B193 [accessed 2026-03-13]. ISSN 1335-4205, eISSN 2585-7878. Available from: https://doi.org/10.26552/com.C.2023.047. Go to original source...
    7. FOMIN, O., GERLICI, J., LOVSKA, A., KRAVCHENKO, K., PROKOPENKO, P., FOMINA, A., HAUSER, V. Durability determination of the bearing structure of an open freight wagon body made of round pipes during its transportation on the railway ferry. Communications - Scientific Letters of the University of Zilina [online]. 2019, 21(1), p. 28-34 [accessed 2026-04-07]. ISSN 1335-4205, eISSN 2585-7878. Available from: https://doi.org/10.26552/com.c.2019.1.28-34 Go to original source...
    8. BAJOR, I., TOROK, A., ROZIC, T., NOVACKO, L. The EU logistics sector. Periodica Polytechnica Transportation Engineering [online]. 2024, 52(3), p. 229-234 [accessed 2026-04-15]. ISSN 1587-3811. Available from: https://doi.org/10.3311/PPtr.23694 Go to original source...
    9. FISCHER, S., HERMAN, B., SYSYN, M., KURHAN, D., KOCSIS SZURKE, S. Quantitative analysis and optimization of energy efficiency in electric multiple units. Facta Universitatis, Series: Mechanical Engineering [online]. 2025, 23(2), p. 351-375 [accessed 2026-04-14]. ISSN 2335-0164. Available from: https://doi.org/10.22190/FUME241103001F Go to original source...
    10. MAN, D.-W., ZHANG, Y., TANG, L.-P., XU, Q.-H., CHEN, D., JIANG, B.-D., HAN, T.-T., XU, T., LI, J.-B. Nonlinear dynamical characteristics of hybrid tri-stable piezoelectric energy harvester based on rotational motion. Facta Universitatis, Series: Mechanical Engineering [online]. 2024, 22(2), p. 257-273 [accessed 2026-04-13]. ISSN 2335-0164. Available from: https://doi.org/10.22190/FUME240118033M Go to original source...
    11. MIKUSOVA, M., TOROK, A., BRIDA, P. Technological and economical context of renewable and non-renewable energy in electric mobility in Slovakia and Hungary. In: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics ICCCI 2018: proceedings [online] [accessed 2026-04-29]. 2018. ISBN 978-3-319-98445-2, eISBN 978-3-319-98446-9, p. 429-436. Available from: https://doi.org/10.1007/978-3-319-98446-9_40 Go to original source...
    12. TOROK, A., ZOLDY, M. Energetic and economical investigation of greenhouse gas emission of Hungarian road transport sector. Pollack Periodica [online]. 2010, 5(3), p. 123-132 [accessed 2026-03-02]. ISSN 1788-3911. Available from: https://doi.org/10.1556/pollack.5.2010.3.10 Go to original source...
    13. BAJEC, P., PIVTORAK, H., SVADLENKA, L., VRBA, R. Analyzing the characteristics of potential last-mile crowdshippers: insights from survey data in Slovenia, Ukraine, and the Czech Republic. Transportation Research Procedia [online]. 2025, 83, p. 1-10 [accessed 2026-04-28]. ISSN 2352-1465. Available from: https://doi.org/10.1016/j.trpro.2025.02.003 Go to original source...
    14. FICZERE, P. The role of artificial intelligence in the development of rail transport. Cognitive Sustainability [online]. 2023, 2(4), p. 1-5 [accessed 2026-05-04]. ISSN 2939-5240. Available from: https://doi.org/10.55343/CogSust.81 Go to original source...
    15. KURHAN, M., FISCHER, S., TIUTKIN, O., KURHAN, D., HMELEVSKA, N. Development of high-speed railway network in Europe: a case study of Ukraine. Periodica Polytechnica Transportation Engineering [online]. 2024, 52(2), p. 151-158 [accessed 2026-04-16]. ISSN 1587-3811. Available from: https://doi.org/10.3311/PPtr.23464 Go to original source...
    16. ŁUCZYSZYN, K. Sustainable transport - development and goals. Cognitive Sustainability [online]. 2024, 3(1), p. 1-6 [accessed 2026-04-17]. ISSN 2939-5240. Available from: https://doi.org/10.55343/CogSust.92 Go to original source...
    17. GOOLAK, S., GOROBCHENKO, O., HOLUB, H., KULBOVSKIY, I., PETRYCHENKO, O. Traction drive control system for railway electric rolling stock based on the application of power factor as an optimization criterion, Problems of the Regional Energetics / Problemele Energeticii Regionale [online]. 2025, 3(67), p. 1-12 [accessed 2026-07-02]. ISSN 1857-0070. Available from: https://doi.org/10.52254/1857-0070.2025.3-67.01. Go to original source...
    18. GOOLAK, S., KYRUCHENKO, M. Thermal model of the output traction converter of an electric locomotive with induction motors, Problems of the Regional Energetics / Problemele Energeticii Regionale [online]. 2022, 3(55), p. 1-16 [accessed 2026-06-30]. ISSN 1857-0070. Available from: http://doi.org/10.52254/1857-0070.2022.3-55.01 Go to original source...
    19. GOOLAK, S., TKACHENKO, V., KYRYCHENKO, M., KOZLOV, S. Hybrid reactive power compensator with adaptation of the operation of the control system to the parameters of the mains voltage, Problemele Energeticii Regionale [online]. 2023, 57(1), p. 1-16 [accessed 2026-06-30]. ISSN 1875-0070. Available from: https://doi.org/10.52254/1857-0070.2023.1-57.01 Go to original source...
    20. LUKOSEVICIUS, V., GOOLAK, S., DEREHUZ, I., NEDUZHA, L., KERSYS, A., DZERKELIS, V. Conceptual basis of adaptation of a field-oriented control system for traction induction motors to the operating parameters of a locomotive, Energies [online]. 2026, 19(2), 298 [accessed 2026-07-04]. ISSN 1996-1073. Available from: https://doi.org/10.3390/en19020298 Go to original source...
    21. FISCHER, S., KOCSIS SZURKE, S. Detection process of energy loss in electric railway vehicles, Facta Universitatis, Series: Mechanical Engineering [online]. 2023, 21(1), p. 81-99 [accessed 2026-04-10]. ISSN 2335-0164. Available from: https://doi.org/10.22190/FUME221104046F Go to original source...
    22. SZURKE, S. K., KOVACS, G., SYSYN, M., LIU, J., FISCHER, S. Numerical optimization of battery heat management of electric vehicles. Journal of Applied and Computational Mechanics [online]. 2023, 9(4), p. 1076-1092 [accessed 2026-04-05]. ISSN 2383-4536. Available from: https://doi.org/10.22055/jacm.2023.43703.4119 Go to original source...
    23. JABBAR, M. Y., AHMED, S. Y., KHAFAJI, S. O. W. A scoping review of the thermoelectric generator systems designs (heat exchangers and coolers) with locations of application to recover energy from internal combustion engines. Journal of Applied and Computational Mechanics [online]. 2024, 10(3), p. 547-583 [accessed 2026-05-02]. ISSN 2383-4536. Available from: https://doi.org/10.22055/jacm.2024.45491.4376 Go to original source...
    24. TOROK, A. Theoretical estimation of the environmental impact of biofuel mixtures. Transport [online]. 2009, 24(1), p. 26-29 [accessed 2026-04-20]. ISSN 1648-3480. Available from: https://doi.org/10.3846/1648-4142.2009.24.26-29 Go to original source...
    25. KONDOR, P. Limitations of using hydrogen as a sustainable fuel in gas turbines. Cognitive Sustainability [online]. 2026, 5(1), p. 1-6 [accessed 2026-05-02]. ISSN 2939-5240. Available from: https://doi.org/10.55343/Cogsust.21702 Go to original source...
    26. AZIM, R. M., TORII, S. Exploring the potential of ammonia and hydrogen as alternative fuels for transportation. Open Engineering [online]. 2024, 14(1), 20240024 [accessed 2026-04-03]. ISSN 2391-5439. Available from: https://doi.org/10.1515/eng-2024-0024 Go to original source...
    27. MALEK, A., TACCANI, R., KASPAREK, D., HUNICZ, J. Optimization of energy management in a city bus powered by the hydrogen fuel cells. Communications - Scientific Letters of the University of Zilina [online]. 2021, 23(4), p. E56-E67 [accessed 2026-04-10]. ISSN 1335-4205, eISSN 2585-7878. Available from: https://doi.org/10.26552/com.C.2021.4.E56-E67. Go to original source...
    28. MEILUS, L., MASKELIUNAITE, L., SIVILEVICIUS, H. Economical comparison of passenger rail traction rolling stock alternatives. Lecture Notes in Intelligent Transportation and Infrastructure [online]. 2025, Part F230, p. 423-435 [accessed 2026-04-17]. ISSN 2523-3459. Available from: https://doi.org/10.1007/978-3-031-85390-6_39. Go to original source...
    29. FABRI, G., OMETTO, A., LI, H, D'OVIDIO, G. Redesign of a non-electrified urban railway line with hydrogen-fuelled trains. Lecture Notes in Civil Engineering [online]. 2024, 526 LNCE, p. 640-648 [accessed 2026-05-02]. ISSN 2366-2565. Available from: https://doi.org/1007/978-981-97-4355-1_62.
    30. FISCHER, T., REINOLD, S., LICHTEBERG, M., SAHBA, M.-A. Farewell diesel: on the way to climate neutrality using alternative drives and fuels in rail passenger service and rail transport. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit [online]. 2023, 238(3), p. 284-291 [accessed 2026-05-03]. ISSN 2041-3017. Available from: https://doi.org/10.1177/09544097231174487. Go to original source...
    31. DE ABREU, V. H. S., DA ROS HOLLANDA, D. L., PROENCA, L. F. C., BAHIENSE, L., SANTOS, A. S. A systematic review on renewable hydrogen application in the land transportation sector. Energy, Environment, and Sustainability [online]. 2024, Part F2419, p. 9-31. [accessed 2026-04-16]. ISSN 2522-8374. Available from: https://doi.org/10.1007/978-981-97-0515-3_2. Go to original source...
    32. RAHIM MARJANI, S., MOTAMAN, S., VARASTEH, H., YANG, Z., CLEMENTSON, J. Assessing hydrogen as an alternative fuel for rail transport - a case study. Scientific Reports [online]. 2025, 15(1), 6449 [accessed 2026-04-11]. ISSN 2045-2322. Available from: https://doi.org/10.1038/s41598-025-90887-3. Go to original source...
    33. WALLINGTON, T. J., WOODY, M., LEWIS, G. M., KEOLEIAN, G. A., ADLER, E. J., MARTINS, J. R. R. A., COLLETTE, M. D. Hydrogen as a sustainable transportation fuel. Renewable and Sustainable Energy Reviews [online]. 2025, 217, 115725 [accessed 2026-04-02]. ISSN 1879-0690. Available from: https://doi.org/10.1016/j.rser.2025.115725, 115725. Go to original source...
    34. WIESER, S., BRUNNER, L., BOHM, M., SOTO, M., RODRIGUEZ, E. J. Development, application and optimization of hydrogen refuelling processes for railway vehicles. International Journal of Hydrogen Energy [online]. 2025, 124, p. 331-344 [accessed 2026-03-29]. ISSN 0360-3199. Available from: https://doi.org/10.1016/j.ijhydene.2025.04.040 Go to original source...
    35. EMRAN, A., GARG, S., MERTES, S., GAUTAM, A., SCHMIDT, M., WICK, M., WALTERS, M., WAGH, S., SHARMA, V. Fuel cell electric metro train concept - zero emission rail transport solution for Indian cities. SAE International Journal of Advances and Current Practices in Mobility [online]. 2024, 6(6), 197403 [accessed 2026-05-03]. Available from: https://doi.org/10.4271/2024-26-0179. Go to original source...
    36. NQODI, A., MOSETLHE, T. C., YUSUF, A. Advances in hydrogen-powered trains: a brief report. Energies [online]. 2023, 16(18), 6715 [accessed 2026-03-23]. ISSN 1996-1073. Available from: https://doi.org/10.3390/en16186715, no. 18, 6715. Go to original source...
    37. XU, Z., ZHAO, N., YAN, Y., GAO, S., HILLMANSEN, S. Electric-thermal collaborative system and control for hydrogen-fuel cell passenger trains in the UK's winter. Energy Conversion and Management [online]. 2025, 328, 119629 [accessed 2026-04-09]. ISSN 1879-2227. Available from: https://doi.org/10.1016/j.enconman.2025.119629 Go to original source...
    38. TANCZOS, K. Adapting the ITF's transport policy with a focus on the EU's strategy of sustainable mobility. Periodica Polytechnica Transportation Engineering [online]. 2025, 53(2), p. 222-225 [accessed 2026-04-29]. ISSN 1587-3811. Available from: https://doi.org/10.3311/PPtr.39780 Go to original source...
    39. Alstom. Coradia iLint hydrogen train performance report. Alstom Mobility. 2020.
    40. Siemens Mireo Plus [online]. Available from: https://www.mobility.siemens.com/global/en/portfolio/rolling-stock/commuter-and-regional-trains/mireo/mireo-plus.html
    41. Stadler Flirt H2 [online]. Available from: https://www.stadlerrail.com/en/solutions/rolling-stock/mainline-flirt-h2
    42. ZOS Vrutky Inc. [online]. Available from: https://www.zos-vrutky.sk/
    43. KANCHAN, M., MANIYERI, R., POWAR, O. S. Numerical analysis of two side-by-side flexible filaments in shear flow and orbit class prediction using immersed boundary method and machine learning techniques. Journal of Applied and Computational Mechanics [online]. 2026, 12(1), p. 238-254 [accessed 2026-03-17]. ISSN 2383-4536. Available from: https://doi.org/10.22055/jacm.2025.48275.5112 Go to original source...
    44. NWACHUKWU, U., AIKHUELE, D. O., SOROOSHIAN, S. Dynamic concept drift detection using an integrated machine learning model with error-based Page-Hinkley test for enhanced predictive accuracy in adhesive manufacturing process. Open Engineering [online]. 2026, 16(1), 20250158 [accessed 2026-02-28]. ISSN 2391-5439. Available from: https://doi.org/10.1515/eng-2025-0158 Go to original source...
    45. PUKRUSHPAN, J. T., STEFANOPOULOU, A. G., PENG, H. Control of fuel cell power systems: principles, modelling, analysis and feedback design. 1. ed. London, UK: Springer, 2004. ISBN 978-1-4471-3792-4. Go to original source...
    46. OU, S., ACHENIE, L. E. K. Artificial neural network modelling of PEM fuel cell. Journal of Fuel Cell Science and Technology [online]. 2005, 2(4), p. 1-24 [accessed 2026-05-01]. ISSN 1551-6989. Available from: https://doi.org/10.1115/1.2039951 Go to original source...
    47. LIM, H. S., KANG, B., AHN, M., KIM, M. S. Optimizing hydrogen utilization in fuel cell hybrid vehicles: modelling fuel cell systems and managing energy between batteries and fuel cells. International Journal of Hydrogen Energy [online]. 2025, 99, p. 819-835 [accessed 2025-04-20]. ISSN 1879-3487. Available from: https://doi.org/10.1016/j.ijhydene.2024.12.150 Go to original source...
    48. MARJANI, S., MOTAMAN, S., VARASTEH, H., YANG, Z., CLEMENTSON, J. Assessing hydrogen as an alternative fuel for rail transport - a case study. Scientific Reports [online]. 2025, 15, 6449 [accessed 2026-05-02]. ISSN 2045-2322. Available from: https://doi.org/10.1038/s41598-025-90887-3 Go to original source...
    49. NQODI, A., MOSETLHE, T., YUSUFF, A. Advances in hydrogen-powered trains: a brief report. Energies [online]. 2023, 16(18), 6715 [accessed 2026-02-27]. ISSN 1996-1073. Available from: https://doi.org/10.3390/en16186715 Go to original source...
    50. ZBIKOWSKI, M., TEODORCZYK, A. Machine learning for internal combustion engine optimization with hydrogen-blended fuels: a literature review. Energies [online]. 2025, 18(6), 1391 [accessed 2026-04-02]. ISSN 1996-1073. Available from: https://doi.org/10.3390/en18061391 Go to original source...
    51. BAI, F. J. J. S. A Machine learning approach for carbon di oxide and other emissions characteristics prediction in a low carbon biofuel-hydrogen dual fuel engine. Fuel [online]. 2023, 341, 127578 [accessed 2026-02-16]. ISSN 1873-7153. Available from: https://doi.org/10.2139/ssrn.4231208 Go to original source...
    52. SIM, L. C., YEO, W. H., PURBOLAKSONO, J., SAW, L. H., TEY, J. Y., LEE, J.V., YEW, M. C. Thermomechanical stresses of multilayered wellbore structure of underground hydrogen storage - a simplified solution based on recursive algorithm. Journal of Applied and Computational Mechanics [online]. 2022, 8(4), p. 1287-1298 [accessed 2026-02-18]. ISSN 2383-4536. Available from: https://doi.org/10.22055/jacm.2022.39453.3411 Go to original source...
    53. DU, X., GAO, S., YANG, G. Machine learning applications in gray, blue, and green hydrogen production: a comprehensive review. Gases [online]. 2025, 5(2), 9 [accessed 2026-04-20]. ISSN 2673-5628. Available from: https://doi.org/10.3390/gases5020009 Go to original source...
    54. IQBAL, S., AFTAB, K., JANNAT, F., BAIG, M., KALSOOM, U. A bibliographic analysis of optimization of hydrogen production via electrochemical method using machine learning. Fuel [online]. 2024, 372, 132126 [accessed 2026-04-22]. ISSN 1873-7153. Available from: https://doi.org/10.1016/j.fuel.2024.132126 Go to original source...
    55. LEE, J., HONG, S., CHO, H., LYU, B., KIM, M., KIM, J., MOON, I. Machine learning-based energy optimization for on-site SMR hydrogen production. Energy Conversion and Management [online]. 2021, 244, 114438 [accessed 2026-04-23]. ISSN 0196-8904. Available from: https://doi.org/10.1016/j.enconman.2021.114438 Go to original source...
    56. SALEHMIN, M., KIONG, T., MOHAMED, H., UMAR, D., YU, K., ONG, H., NOMANBHAY, S., LIM, S. Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: beyond algorithm development. Journal of Energy Chemistry [online]. 2024, 99, p. 223-252 [accessed 2026-04-24]. ISSN 2096-885X. Available from: https://doi.org/10.1016/j.jechem.2024.07.045 Go to original source...
    57. SETHI, H., AHMAD, I., KHAN, M., QAZI, A., AYUB, A., ZULKEFAL, M., SHUTAYWI, M. Applications of computer intelligence in hydrogen production. ACS Omega [online]. 2025, 10(31), p. 33982-33998 [accessed 2026-04-24]. ISSN 2470-1343. Available from: https://doi.org/10.1021/acsomega.5c01602 Go to original source...
    58. URHAN, B., ERDOGMUS, A., DOKUZ, A., GOKCEK, M. Predicting green hydrogen production using electrolyzers driven by photovoltaic panels and wind turbines based on machine learning techniques: A pathway to on-site hydrogen refuelling stations. International Journal of Hydrogen Energy [online]. 2025, 101, p. 1421-1438 [accessed 2026-04-20]. ISSN 1879-3487. Available from: https://doi.org/10.1016/j.ijhydene.2025.01.017 Go to original source...
    59. BEKMYRZA, K., KUTERBEKOV, K., KABYSHEV, A., KUBENOVA, M., BARATOVA, A., AIDARBEKOV, N., VINCESLAS, F. Integrating machine learning and IoT in hydrogen production, storage, and distribution for a decarbonized transport future. International Journal of Low-Carbon Technologies [online]. 2025, 20, p. 1554-1570 [accessed 2026-04-21]. ISSN 1748-1325. Available from: https://doi.org/10.1093/ijlct/ctaf103 Go to original source...

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