4.7 Article

Study of internal multi-parameter distributions of proton exchange membrane fuel cell with segmented cell device and coupled three-dimensional model

Journal

RENEWABLE ENERGY
Volume 147, Issue -, Pages 650-662

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2019.09.026

Keywords

Proton exchange membrane fuel cell; Segmented cell; 3D multi-physical model; Two-phase flow; Relative humidity distribution; Local current

Funding

  1. National Key R&D Program of China [2018YFB0105600]
  2. Science and Technology Program of Sichuan Province [2019YFG0002, 2017CC0017]
  3. National Natural Science Foundation of China [51707030]
  4. Initiative Scientific Research Program of University of Electronic Science and Technology of China [ZYGX2018KYQD207, ZYGX2018KYQD206]

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Understanding multi-parameter distributions inside the proton exchange membrane fuel cell is critical for the stack design and operation optimization. In this work, in situ measurement and three-dimensional model of internal parameter distributions for fuel cell are studied both experimentally and numerically. A segmented cell device based on printed circuit board with embedded sensors is designed to detect local current, relative humidity and temperature in the single cell simultaneously. Meanwhile, a two-phase flow multi-physical fuel cell model validated by the in situ measurement is built to analyze various internal performances. Quantitative impact of convective gas flow on internal parameter distribution is analyzed to reveal the mechanism of water and heat balance for counter-flow operation. The results show that air flow rate is critical to the parameters distributions including current, relative humidity, reactants concentrations and temperature, but hydrogen flow rate effect is neglected. With parametric sweep modeling, the anode and cathode relative humidity distribution profiles could be respectively described by a linear-approximate piece-wise function, which is helpful to quickly predict and evaluate the internal water content distributions for various fuel cell designs and operations. (C) 2019 Elsevier Ltd. All rights reserved.

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