Journal
PROCESSES
Volume 9, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/pr9060904
Keywords
PEM fuel cell; fuzzy; neural network; electrical response; flooding; drying
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This paper introduces a fuzzy model to monitor the degree of dehydration or flooding in real-time for a proton exchange membrane of a fuel cell, aiming to optimize its electrical response and achieve autonomous operation. The results show distinct characteristics of the fuel cell voltage evolution in different states, with the application of fuzzy logic being a novel approach towards automated supervision and intelligent control of fuel cells.
In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response, and, consequently, its autonomous operation. By applying load, current, and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits.
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