Solid oxide fuel cells (SOFCs) are electrochemical devices working at high temperature and producing electricity with high efficiency. An importantopen issue of this promising technology is the characterization of the degradation process. Being a direct observation of degradation phenomena difficult to implement, indirect performance indicators based on voltage measurements are frequently adopted, that are influenced also by the temperature of the furnace containing the cells. The voltage measurements collected during degradation tests on SOFC stacks can be effectively modelled by empirical random-effects regression models. They allow us to describe the variability components present in the measurements, such as the slow decay of voltage over time of each single cell of the stack, the variability of voltage decay among cells, and the fluctuations of voltage due to experimental noise and lack of fit, depending also on the temperature fluctuations. Some advancements are introduced on the available degradation empirical models in order to cope with correlation structure induced by temperature. Point and interval estimates are also derived for some performance measures of interest, for instance the prediction of cell voltage and the reliability function. Finally, the proposed methodology is applied to a real degradation test of a SOFC prototype.

Some advancements on degradation empirical models for reliability evaluation of solid oxide fuel cells

POSTIGLIONE, Fabio
2016-01-01

Abstract

Solid oxide fuel cells (SOFCs) are electrochemical devices working at high temperature and producing electricity with high efficiency. An importantopen issue of this promising technology is the characterization of the degradation process. Being a direct observation of degradation phenomena difficult to implement, indirect performance indicators based on voltage measurements are frequently adopted, that are influenced also by the temperature of the furnace containing the cells. The voltage measurements collected during degradation tests on SOFC stacks can be effectively modelled by empirical random-effects regression models. They allow us to describe the variability components present in the measurements, such as the slow decay of voltage over time of each single cell of the stack, the variability of voltage decay among cells, and the fluctuations of voltage due to experimental noise and lack of fit, depending also on the temperature fluctuations. Some advancements are introduced on the available degradation empirical models in order to cope with correlation structure induced by temperature. Point and interval estimates are also derived for some performance measures of interest, for instance the prediction of cell voltage and the reliability function. Finally, the proposed methodology is applied to a real degradation test of a SOFC prototype.
2016
978-9963-2227-1-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4676532
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