1D thermodynamic modeling for a solid oxide fuel cell stack and parametric study for its optimal operating conditions

Gyubin Min, Young Joon Park, Jongsup Hong

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


Solid oxide fuel cell (SOFC) is regarded as one of the promising energy conversion technologies since it enables distributed power supply based on modularity and provides a high efficiency while emitting less CO2 than conventional power systems. In this sense, a number of SOFC systems have been studied actively aiming at high efficiency with various capacity, assisted by thermodynamic system analysis. However, previous SOFC stack models are not appropriate for the thermodynamic system analysis because those models use multi-dimensional simulation tools and require gross computational resources with excessive calculation time. Thus, in this study, an 1D model that employs analytical expressions with design values and properties measured from an in-house-fabricated SOFC for thermo-electrochemistry and resolves spatially a SOFC stack is developed by using C# to investigate its electrochemical and thermal behavior. The model is validated by using experimental data and is used to elucidate the effect of key operating conditions on thermo-electrochemical performance. A parametric study is conducted with respect to various operation variables such as current density, fuel utilization, air utilization, pressure, and steam to carbon ratio in order to estimate optimal SOFC operating conditions. Considering the effect of each parameter on the 1st law efficiency and outlet gas temperature, a performance map is derived as a function of current density, fuel utilization, and air utilization. To gain the efficiency higher than 50% and outlet gas temperature lower than 900℃, it is shown that the combination of a low current density, high fuel utilization, and low air utilization is necessary at an expense of power density and thermal energy. The results obtained in this study enables capturing optimal operating conditions of a SOFC stack without performing costly experiments.

Original languageEnglish
Article number112614
JournalEnergy Conversion and Management
Publication statusPublished - 2020 Apr 1

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology


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