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On-line Water Contents Diagnosis of PEMFC Based on Measurements

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Abstract

The polymer electrolyte membrane fuel cell has been widely studied in many fields and is being commercialized through various applications such as automobiles or distributed power generation. However, there are some fuel-cell operation stability and durability issues yet to be solved. One such problem is how to monitor the hydration condition within a fuel cell quickly and precisely for fault detection during operation. This study presents a method for monitoring the water management status in the fuel cell on-line. The relationship between equivalent circuit elements, voltage and current is described mathematically, and based on this equation, the equivalent circuit elements are estimated on-line through the voltage and current values measured in the experiment. The experiment is performed in three pre-defined states: normal, dry-out, and flooding. The parameter values of the equivalent circuit estimated by the least square method show different behaviors for each state, and it is confirmed that it is possible to implement fault isolation related to water management of a polymer electrolyte membrane fuel cell through parameter estimation, showing different behaviors in each state.

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Abbreviations

PEMFC:

Polymer electrolyte membrane fuel cell

ARX model:

Autoregressive with exogenous model

FDI:

Fault diagnosis and isolation

\({\text{C}}_{dl}\) :

Double-layer capacitance

E:

Electromotive force

\({\text{R}}_{\text{a}}\) :

Activation resistance (polarization resistance)

\({\text{R}}_{\text{m}}\) :

Membrane resistance (ohmic resistance)

\({\text{V}}_{\text{a}}\) :

Voltage drop by parallel circuit of activation resistance and double-layer capacitance

\({\text{V}}_{\text{m}}\) :

Voltage drop by membrane resistance

\({\text{V}}_{\text{fc}}\) :

Output voltage of fuel-cell stack

\({\text{q}}^{ - 1}\) :

Backward shift operator

\({{\varphi }}\) :

Known parameter vector

\({{\theta }}\) :

Unknown parameter vector

\(\widehat{\theta }\) :

\({{\theta }}\) estimated by least square method

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Authors and Affiliations

  1. School of Mechanical Engineering, Korea University of Technology and Education, Cheonan-si, Chungcheongnam-do, 31253, Republic of Korea

    Donghoon Shin & Seungryeol Yoo

  2. School of Electronic Engineering, Kangnam University, Yongin-si, Geonggi-do, 16979, Republic of Korea

    Young-Hyun Lee

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Correspondence to Seungryeol Yoo.

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Shin, D., Yoo, S. & Lee, YH. On-line Water Contents Diagnosis of PEMFC Based on Measurements. Int. J. of Precis. Eng. and Manuf.-Green Tech. 7, 1085–1093 (2020). https://doi.org/10.1007/s40684-020-00232-4

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