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A review of DC/DC converter-based electrochemical impedance spectroscopy for fuel cell electric vehicles

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  • Wang, Hanqing
  • Gaillard, Arnaud
  • Hissel, Daniel

Abstract

Considering transport applications, there is worldwide an increasing interest in the use of hydrogen-energy for supplying electric powertrains. In order to extend the fuel cell lifespan and to increase its reliability and efficiency, the following features are essential to a fuel cell stack connected DC/DC boost converter: low input current ripple, high voltage gain ratio, high efficiency, high compactness, and high redundancy. Moreover, in order to assess in real time the state-of-health of the fuel cell stack, on-line Electrochemical Impedance Spectroscopy (EIS) functionality integrated with the fuel cell stack connected DC/DC boost converter is a real promising solution requiring no additional measurement equipment. From these points of view, this paper presents a comparison analysis of high voltage gain DC/DC boost converters for fuel cell electric vehicles applications. In addition, some comments and guidelines regarding integration issues are also provided.

Suggested Citation

  • Wang, Hanqing & Gaillard, Arnaud & Hissel, Daniel, 2019. "A review of DC/DC converter-based electrochemical impedance spectroscopy for fuel cell electric vehicles," Renewable Energy, Elsevier, vol. 141(C), pages 124-138.
    • Handle: RePEc:eee:renene:v:141:y:2019:i:c:p:124-138
    DOI: 10.1016/j.renene.2019.03.130
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    3. Xu, Jiamin & Zhang, Caizhi & Wan, Zhongmin & Chen, Xi & Chan, Siew Hwa & Tu, Zhengkai, 2022. "Progress and perspectives of integrated thermal management systems in PEM fuel cell vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    4. Antony Plait & Pierre Saenger & David Bouquain, 2024. "Fuel Cell System Modeling Dedicated to Performance Estimation in the Automotive Context," Energies, MDPI, vol. 17(15), pages 1-15, August.
    5. Goudarzian, Alireza & Khosravi, Adel & Raeisi, Heidar Ali, 2020. "Analysis of a step-up dc/dc converter with capability of right-half plane zero cancellation," Renewable Energy, Elsevier, vol. 157(C), pages 1156-1170.
    6. Abdelmalek, Samir & Dali, Ali & Bakdi, Azzeddine & Bettayeb, Maamar, 2020. "Design and experimental implementation of a new robust observer-based nonlinear controller for DC-DC buck converters," Energy, Elsevier, vol. 213(C).
    7. Hao, Xinyang & Salhi, Issam & Laghrouche, Salah & Ait Amirat, Youcef & Djerdir, Abdesslem, 2023. "Multiple inputs multi-phase interleaved boost converter for fuel cell systems applications," Renewable Energy, Elsevier, vol. 204(C), pages 521-531.
    8. Aissa Benhammou & Hamza Tedjini & Mohammed Amine Hartani & Rania M. Ghoniem & Ali Alahmer, 2023. "Accurate and Efficient Energy Management System of Fuel Cell/Battery/Supercapacitor/AC and DC Generators Hybrid Electric Vehicles," Sustainability, MDPI, vol. 15(13), pages 1-27, June.
    9. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2019. "Degradation model of proton exchange membrane fuel cell based on a novel hybrid method," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    10. Junxing, Liu & Chagshi, Liu, 2023. "Reliable and precise determination of energy conversion in fuel cells using an integrable energy model," Renewable Energy, Elsevier, vol. 219(P2).
    11. Tiancai Ma & Jiajun Kang & Weikang Lin & Xinru Xu & Yanbo Yang, 2022. "Highly Integrated Online Multi-Channel Electrochemical Impedance Spectroscopy Measurement Device for Fuel Cell Stack," Energies, MDPI, vol. 15(9), pages 1-23, May.
    12. Antonio Guarino & Giovanni Petrone & Walter Zamboni, 2019. "Improving the Performance of a Dual Kalman Filter for the Identification of PEM Fuel Cells in Impedance Spectroscopy Experiments," Energies, MDPI, vol. 12(17), pages 1-18, September.
    13. Vichard, L. & Ravey, A. & Venet, P. & Harel, F. & Pelissier, S. & Hissel, D., 2021. "A method to estimate battery SOH indicators based on vehicle operating data only," Energy, Elsevier, vol. 225(C).
    14. Chen, Kui & Laghrouche, Salah & Djerdir, Abdesslem, 2021. "Prognosis of fuel cell degradation under different applications using wavelet analysis and nonlinear autoregressive exogenous neural network," Renewable Energy, Elsevier, vol. 179(C), pages 802-814.
    15. Ioan-Sorin Sorlei & Nicu Bizon & Phatiphat Thounthong & Mihai Varlam & Elena Carcadea & Mihai Culcer & Mariana Iliescu & Mircea Raceanu, 2021. "Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies," Energies, MDPI, vol. 14(1), pages 1-29, January.

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