Application of similarity theory in modeling the output characteristics of proton exchange membrane fuel cellShow others and affiliations
2021 (English)In: International journal of hydrogen energy, ISSN 0360-3199, E-ISSN 1879-3487, Vol. 46, no 74, p. 36940-36953Article in journal (Refereed) Published
Abstract [en]
Proton Exchange Membrane Fuel Cell (PEMFC) has attracted widespread interest. In the present work, similarity analysis is adopted for a three-dimensional single-phase isothermal model of PEMFC to derive similarity criteria. Seven kinds of input criteria (Pi(1) similar to Pi(7)) are obtained, relevant to the fluid flow, pressure drop, flow resistance in a porous medium, activity loss, diffusion mass transfer, convective mass transfer and ohmic loss in PEMFC respectively. Dimensionless voltage and dimensionless current density are defined as two output criteria. Numerical verifications show that if the seven criteria keep their individual values with their components vary in a wide range, the dimensionless polarization curves keep the same with a deviation about 1%, showing the validity and feasibility of the present analysis. From the effect on the dimensionless polarization curve, sensibility analysis shows that the seven criteria can be divided into three categories: strong (Pi(4) and Pi(7), -94.9% similar to +349.2%), mild to minor (Pi(5) and Pi(6), -4.5% similar to +5.0%), and negligible (Pi(1), Pi(2) and Pi(3), -1.2% similar to +1.1%). The similarity analysis approach can greatly save computation time in modeling the output characteristics of PEMFC. (C) 2021 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.
Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD , 2021. Vol. 46, no 74, p. 36940-36953
Keywords [en]
Proton exchange membrane fuel cell, Similarity analysis, Dimensionless polarization curve, Sensibility analysis
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-56308DOI: 10.1016/j.ijhydene.2021.08.205ISI: 000707714900013Scopus ID: 2-s2.0-85116456171OAI: oai:DiVA.org:mdh-56308DiVA, id: diva2:1606755
2021-10-282021-10-282021-11-05Bibliographically approved