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Electrochemical low-frequency impedance spectroscopy algorith for diagnostics of PEM fuel cell degradation

Ivar J. Halvorsen; Ivan Pivac; Dario Bezmalinovic; Frano Barbir; Federico Zenith

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  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3631187", 
  "container_title": "International Journal Hydrogen Energy", 
  "title": "Electrochemical low-frequency impedance spectroscopy algorith for diagnostics of PEM fuel cell degradation", 
  "issued": {
    "date-parts": [
  "abstract": "<p>In order to estimate fuel-cell degradation status on-line and inexpensively, a diagnostic technique based on relay feedback is developed. The technique can obtain critical parameters within seconds of start-up and is robust to measurement bias.</p>\n\n<p>Electrochemical impedance spectroscopy (EIS) is a popular laboratory technique to perform diagnostics on electrochemical systems such as fuel cells, but its application to real-life fuel-cell systems is difficult because of the size and cost of the apparatus. In this study, we present a more detailed equivalent-circuit model for a PEM fuel cell, able to explain the positive reactance shown at low frequencies.</p>\n\n<p>Some of these characteristics, measured at several stages during an Accelerated Stress Test (AST), progress gradually with catalyst degradation, providing an effective prognostic variable. In order to measure these characteristics, a relay-based feedback excitation algorithm is developed to estimate the low-frequency intercept in the Nyquist plane of the cell impedance without resorting to a full-fledged EIS.</p>\n\n<p>The simulations indicate that the algorithm converges to an estimate within about 5 seconds, and is robust to bias. The algorithm can be run within the standard control system that fuel cells are usually equipped with, with no additional hardware.</p>", 
  "author": [
      "family": "Ivar J. Halvorsen"
      "family": "Ivan Pivac"
      "family": "Dario Bezmalinovic"
      "family": "Frano Barbir"
      "family": "Federico Zenith"
  "volume": "45", 
  "note": "Data published under ODbL.", 
  "type": "dataset", 
  "issue": "2", 
  "id": "3631187"
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