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Impact of Powertrain Components Size and Degradation Level on the Energy Management of a Hybrid Industrial Self-Guided Vehicle

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  • Amin Ghobadpour

    (Hydrogen Research Institute, Université du Québec à Trois-Rivières, Trois-Rivières, QC G9A 5H7, Canada)

  • Ali Amamou

    (Hydrogen Research Institute, Université du Québec à Trois-Rivières, Trois-Rivières, QC G9A 5H7, Canada)

  • Sousso Kelouwani

    (Hydrogen Research Institute, Université du Québec à Trois-Rivières, Trois-Rivières, QC G9A 5H7, Canada)

  • Nadjet Zioui

    (Hydrogen Research Institute, Université du Québec à Trois-Rivières, Trois-Rivières, QC G9A 5H7, Canada)

  • Lotfi Zeghmi

    (Hydrogen Research Institute, Université du Québec à Trois-Rivières, Trois-Rivières, QC G9A 5H7, Canada)

Abstract

This paper deals with the design of an energy management strategy (EMS) for an industrial hybrid self-guided vehicle (SGV), considering the size of a fuel cell (FC) stack and degradation of a battery pack. In this context, first, a realistic energy model of the SGV was proposed and validated, based on experiments. This model provided a basis for individual components analysis, estimating energy requirements, component sizing, and testing various EMSs, prior to practical implementation. Second, the performance of the developed FC/battery SGV powertrain was validated under three EMS modes. Each mode was studied by considering four different FC sizes and three battery degradation levels. The final results showed that a small FC as a range extender is recommended, to reduce system cost. It is also important to maintain the FC in its high efficiency zones with a minimum ON/OFF cycle, leading to efficiency and lifetime enhancement of FC system. Battery SOC have to be kept at a high level during SGV operation, to support the FC during SGV acceleration. In order to improve the SGV’s overall autonomy, it is also important to minimize the stop and go and rotational SGV motion with appropriate acceleration and deceleration rate.

Suggested Citation

  • Amin Ghobadpour & Ali Amamou & Sousso Kelouwani & Nadjet Zioui & Lotfi Zeghmi, 2020. "Impact of Powertrain Components Size and Degradation Level on the Energy Management of a Hybrid Industrial Self-Guided Vehicle," Energies, MDPI, vol. 13(19), pages 1-20, September.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5041-:d:418998
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    References listed on IDEAS

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    1. Hannan, M.A. & Azidin, F.A. & Mohamed, A., 2014. "Hybrid electric vehicles and their challenges: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 135-150.
    2. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    3. Ettihir, K. & Boulon, L. & Agbossou, K., 2016. "Optimization-based energy management strategy for a fuel cell/battery hybrid power system," Applied Energy, Elsevier, vol. 163(C), pages 142-153.
    4. Eriksson, E.L.V. & Gray, E.MacA., 2017. "Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems – A critical review," Applied Energy, Elsevier, vol. 202(C), pages 348-364.
    5. Amamou, A. & Kandidayeni, M. & Boulon, L. & Kelouwani, S., 2018. "Real time adaptive efficient cold start strategy for proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 216(C), pages 21-30.
    6. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
    7. Torres, J.L. & Gonzalez, R. & Gimenez, A. & Lopez, J., 2014. "Energy management strategy for plug-in hybrid electric vehicles. A comparative study," Applied Energy, Elsevier, vol. 113(C), pages 816-824.
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    Cited by:

    1. Andreas J. Hanschek & Yann E. Bouvier & Erwin Jesacher & Petar J. Grbović, 2022. "Analysis and Comparison of Power Distribution System Topologies for Low-Voltage DC–DC Automated Guided Vehicle Applications," Energies, MDPI, vol. 15(6), pages 1-23, March.
    2. João Pedro F. Trovão & Minh Cao Ta, 2022. "Electric Vehicle Efficient Power and Propulsion Systems," Energies, MDPI, vol. 15(11), pages 1-4, May.
    3. Massinissa Graba & Sousso Kelouwani & Lotfi Zeghmi & Ali Amamou & Kodjo Agbossou & Mohammad Mohammadpour, 2020. "Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context," Sustainability, MDPI, vol. 12(20), pages 1-21, October.
    4. Chiara Dall’Armi & Davide Pivetta & Rodolfo Taccani, 2021. "Health-Conscious Optimization of Long-Term Operation for Hybrid PEMFC Ship Propulsion Systems," Energies, MDPI, vol. 14(13), pages 1-20, June.

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