Autocorrelation standard deviation and root mean square frequency analysis of polymer electrolyte membrane fuel cell to monitor for hydrogen and air undersupply
| Autor: | Dong-Ha Lee, Jae Sung Choi, Byungrak Son, Santanu Mukherjee, Sam Park, Osung Kwon, Benjamin Zickel, Joo Gon Kim, Hyun-Youl Chung, Alex Bates |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Materials science
Renewable Energy Sustainability and the Environment Membrane electrode assembly Analytical chemistry Energy Engineering and Power Technology Proton exchange membrane fuel cell Mechanics Electrolyte Standard deviation Root mean square chemistry.chemical_compound chemistry Hydrogen fuel Nafion Energy transformation Electrical and Electronic Engineering Physical and Theoretical Chemistry |
| Zdroj: | Journal of Power Sources. 300:164-174 |
| ISSN: | 0378-7753 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect