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Fuzzy Logic-Based State-of-Health Determination of PEM Fuel Cells

Proton exchange membrane (PEM) fuel cells are being rapidly developed as the primary power source for advanced electric vehicles. The monitoring and control of these fuel cells is very important to ensure long life and reliable performance of these devices. In this paper we present a novel technique, based on the combination of impedance measurements, current-voltage measurements, and fuzzy logic data analysis, for the prediction of the state-of-health (SOH) of PEM fuel cells. Galvanostatic electrochemical impedance spectroscopy (EIS) measurements were made on four different 5W H-Power PEM fuel cell stacks over a frequency range of 0.1Hz to 1 kHz at both opencircuit and with a small 10mA loading of the fuel cell stack. Also, the current-voltage characteristics of the stacks were measured over a range of 0-1A. The measurements were made under simulated conditions of flooding of the air channels, followed by purging of the channels with dry air; and under simulated conditions of membrane dryout, followed by membrane rehumidification. Following membrane dryout, the magnitude of the impedance of the fuel cell stack was seen to increase. As the membrane became steadily rehumidified, the impedance magnitude was seen to correspondingly decrease. Flooding of the air channels resulted in very little change in the impedance of the fuel cell stacks but significant changes in the current-voltage characteristics of the stack were observed under this simulated failure condition. The data from two of the fuel cell stacks were used to develop a fuzzy logic model to predict the SOH of the fuel cell stacks and data from the other two fuel cells were used to test the model. It was found that the fuzzy logic model was able to predict the SOH of the fuel cells under all failure modes, almost 90% of the time. This is an excellent result, particularly when the sample size that was used for developing the fuzzy logic model was so small.