This title appears in the Scientific Report :
2019
Please use the identifier:
http://dx.doi.org/10.1016/j.apenergy.2018.10.026 in citations.
Modeling polymer electrolyte fuel cells: A high precision analysis
Modeling polymer electrolyte fuel cells: A high precision analysis
In this paper, a computational model is used to study the distributions of several key parameters and the performance of a fuel cell with an active area of 200 . The results reveal that the model is capable of predicting the overall behavior in good agreement with experimental data and with superior...
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Personal Name(s): | Zhang, Shidong (Corresponding author) |
---|---|
Reimer, Uwe / Beale, Steven / Lehnert, Werner / Stolten, Detlef | |
Contributing Institute: |
JARA - HPC; JARA-HPC Technoökonomische Systemanalyse; IEK-3 |
Published in: | Applied energy, 233-234 (2019) S. 1094 - 1103 |
Imprint: |
Amsterdam [u.a.]
Elsevier Science
2019
|
DOI: |
10.1016/j.apenergy.2018.10.026 |
Document Type: |
Journal Article |
Research Program: |
Flexible Simulation of Fuel Cells with OpenFOAM Fuel Cells |
Publikationsportal JuSER |
In this paper, a computational model is used to study the distributions of several key parameters and the performance of a fuel cell with an active area of 200 . The results reveal that the model is capable of predicting the overall behavior in good agreement with experimental data and with superior resolution. Polarization curves are compared and cell voltage prediction deviations are within of experimental values. The predicted current density distribution is very close to both the experimentally measured results and a volume-average approach based on rate equations. Local variations of current density, oxygen, and water mole fraction change significantly from under-rib regions to under-channel regions. The serpentine type flow path leads to greater pressure gradients, but is beneficial to gas bypassing through the gas diffusion layers. This type of flow path helps to redistribute the species and current density distributions. Never before has it been possible to construct computational models capable of predicting fine-scale details in local current density; details which were not captured neither by previous models nor by present-day experiments. |