Polymer electrolyte fuel cell modeling - A comparison of two models with different levels of complexity

Research output: Contribution to journalArticle


title = "Polymer electrolyte fuel cell modeling - A comparison of two models with different levels of complexity",
abstract = "The modeling of fuel cells requires the coupling of fluid transport with electro-chemical reactions. There are two approaches commonly used. Firstly, the electrodes can be treated as two planes, where the potential gradient can be considered as being locally one-dimensional. In this case a two dimensional current density distribution is obtained. Secondly, the two electrode layers can be spatially resolved and the protonic and electronic potentials obtained by solving a pair of coupled Poisson equations. The latter approach requires much higher computational resources, because a higher spatial resolution is required and a large set of model parameters is required. On the other hand, much more detailed local information can be obtained by this method. The motivation for this study was to compare the results quantitively with detailed experimental data for a high temperature polymer electrolyte fuel cell with a geometric area of 200 cm2. Both model approaches show very good agreement with measured local current density distributions. The second model is able to provide a deeper insight into the current density variation through the membrane and catalyst layers and reveals points with local extremes. The present results are specific for high temperature polymer electrolyte fuel cells but the conclusions may readily be applied to the modeling of other high temperature fuel cell types.",
keywords = "Computational fluid dynamics, Current density, Fuel cell, Mathematical modeling",
author = "S. Zhang and Beale, {S. B.} and U. Reimer and M. Andersson and W. Lehnert",
year = "2020",
month = jul,
day = "31",
doi = "10.1016/j.ijhydene.2020.05.060",
language = "English",
volume = "45",
pages = "19761--19777",
journal = "International Journal of Hydrogen Energy",
issn = "1879-3487",
publisher = "Elsevier",
number = "38",