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Better Fuel Economy by Optimizing Airflow of the Fuel Cell Hybrid Power Systems Using Fuel Flow-Based Load-Following Control

Author

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  • Nicu Bizon

    (Faculty of Electronics, Communication and Computers, University of Pitesti, 1 Targu din Vale, 110040 Pitesti, Romania
    University Politehnica of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania)

  • Alin Gheorghita Mazare

    (Faculty of Electronics, Communication and Computers, University of Pitesti, 1 Targu din Vale, 110040 Pitesti, Romania)

  • Laurentiu Mihai Ionescu

    (Faculty of Electronics, Communication and Computers, University of Pitesti, 1 Targu din Vale, 110040 Pitesti, Romania)

  • Phatiphat Thounthong

    (Renewable Energy Research Centre (RERC), King Mongkut’s University of Technology North Bangkok, Bangkok 10800, Thailand)

  • Erol Kurt

    (Gazi University, Faculty of Technology, Department of Electrical and Electronics Engineering, 06500 Teknikokullar, Ankara, Turkey)

  • Mihai Oproescu

    (Faculty of Electronics, Communication and Computers, University of Pitesti, 1 Targu din Vale, 110040 Pitesti, Romania)

  • Gheorghe Serban

    (Faculty of Electronics, Communication and Computers, University of Pitesti, 1 Targu din Vale, 110040 Pitesti, Romania)

  • Ioan Lita

    (Faculty of Electronics, Communication and Computers, University of Pitesti, 1 Targu din Vale, 110040 Pitesti, Romania)

Abstract

In this paper, the results of the sensitivity analysis applied to a fuel cell hybrid power system using a fuel economy strategy is analyzed in order to select the best values of the parameters involved in fuel consumption optimization. The fuel economy strategy uses the fuel and air flow rates to efficiently operate the proton-exchange membrane (PEM) fuel cell (FC) system based on the load-following control and the global extremum seeking (GES) algorithm. The load-following control will ensure the charge-sustained mode for the batteries’ stack, improving its lifetime. The optimization function’s optimum, which is defined to improve the fuel economy, will be tracked in real-time by two GES algorithms that will generate the references for the controller of the boost DC-DC converter and air regulator. The optimization function and performance indicators (such as FC net power, FC electrical efficiency, fuel efficiency, and fuel economy) have a multimodal behavior in dithers’ frequency. Furthermore, the optimum in the considered range of frequencies depends on the load level. So, the best value could be selected as the frequency where the optimum is obtained for the most load levels. Considering a dither frequency of 100 Hz selected as the best value, the sensitivity analysis of the fuel economy is further analyzed for different values of the weighting parameter k eff , highlighting the multimodal feature in the parameters for the optimization function and fuel economy as well. A k eff value around of 20 lpm/W seems to give the best fuel economy in the full range of load.

Suggested Citation

  • Nicu Bizon & Alin Gheorghita Mazare & Laurentiu Mihai Ionescu & Phatiphat Thounthong & Erol Kurt & Mihai Oproescu & Gheorghe Serban & Ioan Lita, 2019. "Better Fuel Economy by Optimizing Airflow of the Fuel Cell Hybrid Power Systems Using Fuel Flow-Based Load-Following Control," Energies, MDPI, vol. 12(14), pages 1-17, July.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:14:p:2792-:d:250077
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    References listed on IDEAS

    as
    1. Bizon, Nicu, 2018. "Optimal operation of fuel cell/wind turbine hybrid power system under turbulent wind and variable load," Applied Energy, Elsevier, vol. 212(C), pages 196-209.
    2. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    3. Bizon, Nicu, 2019. "Efficient fuel economy strategies for the Fuel Cell Hybrid Power Systems under variable renewable/load power profile," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    4. Nicu Bizon & Valentin Alexandru Stan & Angel Ciprian Cormos, 2019. "Optimization of the Fuel Cell Renewable Hybrid Power System Using the Control Mode of the Required Load Power on the DC Bus," Energies, MDPI, vol. 12(10), pages 1-15, May.
    5. Bizon, Nicu, 2013. "Energy efficiency for the multiport power converters architectures of series and parallel hybrid power source type used in plug-in/V2G fuel cell vehicles," Applied Energy, Elsevier, vol. 102(C), pages 726-734.
    6. Bizon, Nicu, 2012. "Energy efficiency of multiport power converters used in plug-in/V2G fuel cell vehicles," Applied Energy, Elsevier, vol. 96(C), pages 431-443.
    7. 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.
    8. Bizon, Nicu, 2018. "Effective mitigation of the load pulses by controlling the battery/SMES hybrid energy storage system," Applied Energy, Elsevier, vol. 229(C), pages 459-473.
    9. Bizon, Nicu, 2019. "Fuel saving strategy using real-time switching of the fueling regulators in the proton exchange membrane fuel cell system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    10. Ramos-Paja, Carlos Andrés & Spagnuolo, Giovanni & Petrone, Giovanni & Mamarelis, Emilio, 2014. "A perturbation strategy for fuel consumption minimization in polymer electrolyte membrane fuel cells: Analysis, Design and FPGA implementation," Applied Energy, Elsevier, vol. 119(C), pages 21-32.
    11. Bizon, Nicu, 2016. "Global Maximum Power Point Tracking (GMPPT) of Photovoltaic array using the Extremum Seeking Control (ESC): A review and a new GMPPT ESC scheme," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 524-539.
    12. Bizon, Nicu, 2019. "Real-time optimization strategies of Fuel Cell Hybrid Power Systems based on Load-following control: A new strategy, and a comparative study of topologies and fuel economy obtained," Applied Energy, Elsevier, vol. 241(C), pages 444-460.
    13. Hou, Jun & Song, Ziyou & Park, Hyeongjun & Hofmann, Heath & Sun, Jing, 2018. "Implementation and evaluation of real-time model predictive control for load fluctuations mitigation in all-electric ship propulsion systems," Applied Energy, Elsevier, vol. 230(C), pages 62-77.
    14. Olatomiwa, Lanre & Mekhilef, Saad & Ismail, M.S. & Moghavvemi, M., 2016. "Energy management strategies in hybrid renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 821-835.
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    Cited by:

    1. Phatiphat Thounthong & Pongsiri Mungporn & Serge Pierfederici & Damien Guilbert & Nicu Bizon, 2020. "Adaptive Control of Fuel Cell Converter Based on a New Hamiltonian Energy Function for Stabilizing the DC Bus in DC Microgrid Applications," Mathematics, MDPI, vol. 8(11), pages 1-25, November.
    2. Phatiphat Thounthong & Matheepot Phattanasak & Damien Guilbert & Noureddine Takorabet & Serge Pierfederici & Babak Nahid-Mobarakeh & Nicu Bizon & Poom Kumam, 2020. "Differential Flatness Based-Control Strategy of a Two-Port Bidirectional Supercapacitor Converter for Hydrogen Mobility Applications," Energies, MDPI, vol. 13(11), pages 1-24, June.
    3. Nicu Bizon & Phatiphat Thounthong, 2021. "A Simple and Safe Strategy for Improving the Fuel Economy of a Fuel Cell Vehicle," Mathematics, MDPI, vol. 9(6), pages 1-29, March.

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