Open AccessA Mathematical Model toward Real-Time Monitoring of Automotive PEM Fuel Cells
Author(s) -
Alireza Goshtasbi,
Benjamin L. Pence,
Jixin Chen,
Michael A. DeBolt,
Chunmei Wang,
James Waldecker,
Shinichi Hirano,
Tulga Ersal
Publication year - 2020
Publication title -
journal of the electrochemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.258
H-Index - 271
eISSN - 1945-7111
pISSN - 0013-4651
DOI - 10.1149/1945-7111/ab6dd1
Subject(s) - proton exchange membrane fuel cell , decoupling (probability) , automotive industry , computer science , range (aeronautics) , automotive engineering , fuel cells , cathode , electrolyte , simulation , engineering , electrode , control engineering , chemistry , electrical engineering , aerospace engineering , chemical engineering
A computationally efficient model toward real-time monitoring of automotive polymer electrolyte membrane (PEM) fuel cell stacks is developed. Computational efficiency is achieved by spatio-temporal decoupling of the problem, developing a new reduced-order model for water balance across the membrane electrode assembly (MEA), and defining a new variable for cathode catalyst utilization that captures the trade-off between proton and mass transport limitations without additional computational cost. Together, these considerations result in the model calculations to be carried out more than an order of magnitude faster than real time. Moreover, a new iterative scheme allows for simulation of counter-flow operation and makes the model flexible for different flow configurations. The proposed model is validated with a wide range of experimental performance measurements from two different fuel cells. Finally, simulation case studies are presented to demonstrate the prediction capabilities of the model.