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Fuel Cell Hybrid Locomotive with Modified Fuzzy Logic Based Energy Management System

Author

Listed:
  • Hamed Jafari Kaleybar

    (Department of Energy, Politecnico di Milano, 20156 Milan, Italy)

  • Morris Brenna

    (Department of Energy, Politecnico di Milano, 20156 Milan, Italy)

  • Huan Li

    (Department of Energy, Politecnico di Milano, 20156 Milan, Italy)

  • Dario Zaninelli

    (Department of Energy, Politecnico di Milano, 20156 Milan, Italy)

Abstract

As one of the most environmentally friendly energy sources today, fuel cells have become the focus of research in countries around the world, especially in the electric transportation field. This paper mainly studies the modeling of fuel cell hybrid locomotives (FCHL) including fuel cells, batteries, motors, and energy management systems. To increase the operating efficiency and improve the performance of FCHL, a modified fuzzy logic-based energy management system (MFL-EMS) is proposed and compared with the traditional power flow energy management system (PF-EMS). Meanwhile, a modified fuel cell hybrid power system model for locomotives is proposed, taking into account the traction motor features that, compared with a simplified controlled source load, can directly reflect the status of the locomotive running speed and the output power of the traction motor load. The proposed system parameters and configurations are determined by combining the characteristics of power and energy density, response characteristics, and charging/discharging characteristics of fuel cells and batteries. The precise simulation results revealed that adopting the proposed MFL-EMS in comparison to the traditional PF-EMS, reduced the hydrogen consumption by 2.943%. Comparing the battery output voltage, it is confirmed that with MFL-EMS it tends to be steeper than the one with PF-EMS, showing the proposed strategy’s robustness. Overall, the obtained results revealed an improved performance in terms of power distribution as well as SOC, which means less hydrogen consumption and therefore a more economical solution.

Suggested Citation

  • Hamed Jafari Kaleybar & Morris Brenna & Huan Li & Dario Zaninelli, 2022. "Fuel Cell Hybrid Locomotive with Modified Fuzzy Logic Based Energy Management System," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8336-:d:857845
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    References listed on IDEAS

    as
    1. Song, Ke & Wang, Xiaodi & Li, Feiqiang & Sorrentino, Marco & Zheng, Bailin, 2020. "Pontryagin’s minimum principle-based real-time energy management strategy for fuel cell hybrid electric vehicle considering both fuel economy and power source durability," Energy, Elsevier, vol. 205(C).
    2. Simone Barcellona & Luigi Piegari, 2017. "Lithium Ion Battery Models and Parameter Identification Techniques," Energies, MDPI, vol. 10(12), pages 1-24, December.
    3. Débora B. S. Oliveira & Luna L. Glória & Rodrigo A. S. Kraemer & Alisson C. Silva & Douglas P. Dias & Alice C. Oliveira & Marcos A. I. Martins & Mathias A. Ludwig & Victor F. Gruner & Lenon Schmitz & , 2022. "Mixed-Integer Linear Programming Model to Assess Lithium-Ion Battery Degradation Cost," Energies, MDPI, vol. 15(9), pages 1-18, April.
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    Citations

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    Cited by:

    1. 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).
    2. Zhaowen Liang & Kai Liu & Jinjin Huang & Enfei Zhou & Chao Wang & Hui Wang & Qiong Huang & Zhenpo Wang, 2022. "Powertrain Design and Energy Management Strategy Optimization for a Fuel Cell Electric Intercity Coach in an Extremely Cold Mountain Area," Sustainability, MDPI, vol. 14(18), pages 1-16, September.
    3. Mehrshad Kolahchian Tabrizi & Tarcisio Cerri & Davide Bonalumi & Tommaso Lucchini & Morris Brenna, 2024. "Retrofit of Diesel Engines with H 2 for Potential Decarbonization of Non-Electrified Railways: Assessment with Lifecycle Analysis and Advanced Numerical Modeling," Energies, MDPI, vol. 17(5), pages 1-13, February.
    4. Mubashir Rasool & Muhammad Adil Khan & Runmin Zou, 2023. "A Comprehensive Analysis of Online and Offline Energy Management Approaches for Optimal Performance of Fuel Cell Hybrid Electric Vehicles," Energies, MDPI, vol. 16(8), pages 1-33, April.
    5. Andrea Di Martino & Seyed Mahdi Miraftabzadeh & Michela Longo, 2022. "Strategies for the Modelisation of Electric Vehicle Energy Consumption: A Review," Energies, MDPI, vol. 15(21), pages 1-20, October.

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