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Other literature type . 2023
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Presentation . 2023
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Presentation . 2023
License: CC BY
Data sources: Datacite
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Classifying Error States of PEMFCs by Current Mapping and Cell Voltage Monitoring

Authors: Nissen, Jens; Schrievers, Max; Schwämmlein, Jan Nicolas; Hölzle, Markus;

Classifying Error States of PEMFCs by Current Mapping and Cell Voltage Monitoring

Abstract

Error states in PEMFC stacks typically cause distortions of the local current distribution and the cell voltage. Measuring those properties can be used for identification of those error states, e.g., membrane dry-out, channel blockage, reactant media contamination, local starvation, gross starvation, overall stack starvation and pinholes. Two techniques for online diagnosis are introduced, measuring the current density distribution by a printed circuit board, and measuring the local cell voltage by a multipoint cell voltage monitoring. A non-invasive experimental setup is proposed for both techniques to gain reliable measurement data. The relationship of the cell voltage distribution over the stack and the current density distribution within the cells is discussed and used to discriminate different error states. Experimental measurement data of those techniques is shown for several common error states. Finally, a categorization of error states is proposed, based on their characteristic patterns of disturbed local current density and cell voltage.

Keywords

CVM pattern, cell voltage redistribution, current density distribution, multipoint cell voltage monitoring, current density redistribution, non-equipotential bipolar plates, automotive fuel cell, error states

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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