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Autocorrelation standard deviation and root mean square frequency analysis of polymer electrolyte membrane fuel cell to monitor for hydrogen and air undersupply
- Autocorrelation standard deviation and root mean square frequency analysis of polymer electrolyte membrane fuel cell to monitor for hydrogen and air undersupply
- Kim, Joo Gon; Mukherjee, Santanu; Bates, Alex; Zickel, Benjamin; Park, Sam; Son, Byung Rak; Choi, Jae Sung; Kwon, Osung; Lee, Dong Ha; Chung, Hyun-Youl
- DGIST Authors
- Son, Byung Rak; Lee, Dong Ha
- Issue Date
- Journal of Power Sources, 300, 164-174
- Article Type
- Autocorrelation; Electrolytes; Energy Conversion; Energy Conversion Devices; Frequency Variation; Fuel Cell Performance; Fuel Cells; Health Monitoring; Hydrogen Supply; Hydrogen Supply Capacity; Membrane Electrode Assemblies; Membranes; PEMFC; Polyelectrolytes; Proton-Exchange Membrane Fuel Cells (PEMFC); RMSF; Starvation Conditions; Statistics
- Proton exchange membrane fuel cells are a promising energy conversion device which can help to solve urgent environmental and economic problems. Among the various types of fuel cells, the air breathing proton exchange membrane fuel cell, which minimizes the balance of plant, has drawn a lot of attention due to its superior energy density. In this study a compact, air breathing, proton exchange membrane fuel cell based on Nafion and a Pt/C membrane electrode assembly was designed. The fuel cell was tested using a Scribner Associates 850e fuel cell test station. Specifically, the hydrogen fuel and oxygen starvation of the fuel cell were accurately and systematically tested and analyzed using a frequency analysis method which can analyze the input and output frequency. The analysis of the frequency variation under a fuel starvation condition was done using RMSF (root mean square frequency) and ACSD (autocorrelation standard deviation). The study reveals two significant results: first, the fuel starvations show entirely different phenomenon in both RMSF and ACSD and second, the results of the Autocorrelation show clearer results for fuel starvation detection than the results with RMSF. © 2015 Elsevier B.V. All rights reserved.
- ELSEVIER SCIENCE BV
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