4.7 Article

Lifetime prediction of a polymer electrolyte membrane fuel cell via an accelerated startup-shutdown cycle test

Journal

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
Volume 37, Issue 12, Pages 9775-9781

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2012.03.104

Keywords

Accelerated degradation test (ADT); Lifetime prediction; Membrane electrode assembly (MEA); Nonparametric regression; Polymer electrolyte membrane fuel cell (PEMFC)

Funding

  1. PEFC
  2. Samsung Advanced Institute of Technology (SAIT)
  3. Samsung Electronics
  4. NRF
  5. MEST [2011-0016598]
  6. Korea Institute of Energy Technology Evaluation and Planning (KETEP)
  7. Korean Ministry of Knowledge Economy [2011T100200280]
  8. Korea Evaluation Institute of Industrial Technology (KEIT) [20113010030060] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  9. Ministry of Public Safety & Security (MPSS), Republic of Korea [2012KIAT-MOT-KIAT] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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To expand commercial applications of polymer electrolyte membrane fuel cells (PEMFCs), the evaluation time for their durability must be shortened. This article provides a straightforward accelerated degradation testing (ADT) procedure for PEMFC for easy and quick implementation of the procedure. The ADT procedure includes statistical modeling of degradation patterns of membrane electrode assemblies (MEAs) in PEMFCs under startup-shutdown cycling conditions. For this purpose, we propose a nonparametric degradation model to describe the nonlinear performance degradation paths of PEMFC MEAs. The analysis results indicate that the nonparametric approach provides more accurate estimates of the observed degradation data than other parametric approaches. Based on the nonparametric degradation model, we suggest a method to predict failure-times under normal operating conditions by estimating the time-scale factor under accelerated operating conditions. Copyright (C) 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

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