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Processes
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Representative Model and Flow Characteristics of Fuel Cells
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Representative Model and Flow Characteristics of Fuel Cells

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (10 July 2021) | Viewed by 16525

Special Issue Editors

Prof. Dr. Yong-Song Chen

E-Mail Website
Guest Editor
Department of Mechanical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan
Interests: redox flow battery; fuel cell; electrochemistry
Special Issues, Collections and Topics in MDPI journals
Dr. Amornchai Arpornwichanop

E-Mail Website
Guest Editor
Center of Excellence in Process and Energy Systems Engineering, Department of Chemical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
Interests: hydrogen and fuel cell technology; renewable energy; biorefinergy process; process design, synthesis and optimization

Special Issue Information

Dear Colleagues,

Fuel cells (FCs) play an important role in the development of green energy, and have drawn much attention during the past decade. They have been widely employed as power sources for electric vehicles, unmanned aerial vehicles, underwater vehicles, and other power generation systems. Recently, FC research has focused on cost reduction and durability improvement to enhance FC commercialization. The cost and performance of FCs are influenced by many factors, including materials of key components, structures of membrane electrode assemblies, manufacturing processes, and operating conditions. How these factors influence the electrochemical reaction within the FC is an interesting and essential topic for the development of FCs.

This special Issue aims to showcase recent progress and breakthroughs in the cost reduction and performance improvement of FCs, including both high- and low-temperature FCs. For this special Issue, we welcome and encourage contributions covering representative models or experimental studies that can capture flow characteristics, catalytic activity, gas management, energy efficiency, and degradation mechanisms.

Prof. Dr. Yong-Song Chen
Dr. Amornchai Arpornwichanop
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fuel cell
  • durability
  • cost reduction
  • membrane electrode assembly
  • gas management
  • energy efficiency
  • degradation

Published Papers (4 papers)

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Research

28 pages, 12735 KiB  
Article
Fault Detection and Isolation for a Cooling System of Fuel Cell via Model-based Analysis
by Jaesu Han, Sangseok Yu and Jaeyoung Han
Processes 2020, 8(9), 1115; https://doi.org/10.3390/pr8091115 - 8 Sep 2020
Cited by 2 | Viewed by 3835
Abstract
The development of fuel cell electric vehicles in recent years has led to increased interest in the use of fuel cells as sources of renewable energy. To achieve successful commercialization of fuel cell vehicles, it will be necessary to guarantee the safety, reliability, [...] Read more.
The development of fuel cell electric vehicles in recent years has led to increased interest in the use of fuel cells as sources of renewable energy. To achieve successful commercialization of fuel cell vehicles, it will be necessary to guarantee the safety, reliability, and lifetime of fuel cell systems by predictive fault detection and isolation (FDI). In this study, the parity equation, an observer, and a Kalman filter are employed together to compare the characteristics of FDI, focusing on the sensors of the thermal management system. Residuals corresponding to the difference between temperature outputs of linear models under driving cycles and nonlinear temperature outputs are used to isolate faults. Then, assessment of three model-based sensor FDI schemes is used to isolate sensor faults using the Cumulative Sum Control Chart (CUSUM) method. Generated residuals are evaluated by CUSUM to detect the presence of a sensor fault. As a result, isolated sensor faults are assessed. Full article
(This article belongs to the Special Issue Representative Model and Flow Characteristics of Fuel Cells)
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14 pages, 3463 KiB  
Article
Performance Prediction Model of Solid Oxide Fuel Cell System Based on Neural Network Autoregressive with External Input Method
by Shan-Jen Cheng and Jing-Kai Lin
Processes 2020, 8(7), 828; https://doi.org/10.3390/pr8070828 - 13 Jul 2020
Cited by 7 | Viewed by 2348
Abstract
An accurate performance prediction model for the solid oxide fuel cell (SOFC) system not only contributes to the realization of the operating condition but also plays a role in long-term prediction performance. Accordingly, a research study has been developed to suitably deal with [...] Read more.
An accurate performance prediction model for the solid oxide fuel cell (SOFC) system not only contributes to the realization of the operating condition but also plays a role in long-term prediction performance. Accordingly, a research study has been developed to suitably deal with the time-series model and accurately build the performance prediction model of SOFC system based on neural network autoregressive with external input (NNARX) method. The architecture regressor parameters of the NNARX model were efficiently determined using the Taguchi orthogonal array (OA) method for optimal sets. The identified and evaluated optimal parameter levels were used to conduct an analysis of variance (ANOVA) to prove correctness. Moreover, a series of statistics criteria and multi-step prediction were also employed for investigating the uncertainty of the predicted model and solve the overfitting and under fitting problems; further. These criteria were also used to determine the performance of the proposed model architecture. The predicted results of the current study indicated that the developed optimal model level parameters consistently had the least statistics errors and reduced workload of the trial-and-error processes. Full article
(This article belongs to the Special Issue Representative Model and Flow Characteristics of Fuel Cells)
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16 pages, 10532 KiB  
Article
Experimental Analysis of the Performance and Load Cycling of a Polymer Electrolyte Membrane Fuel Cell
by Andrea Ramírez-Cruzado, Blanca Ramírez-Peña, Rosario Vélez-García, Alfredo Iranzo and José Guerra
Processes 2020, 8(5), 608; https://doi.org/10.3390/pr8050608 - 20 May 2020
Cited by 7 | Viewed by 4767
Abstract
In this work, a comprehensive experimental analysis on the performance of a 50 cm2 polymer electrolyte membrane (PEM) fuel cell is presented, including experimental results for a dedicated load cycling test. The harmonized testing protocols defined by the Joint Research Centre (JRC) [...] Read more.
In this work, a comprehensive experimental analysis on the performance of a 50 cm2 polymer electrolyte membrane (PEM) fuel cell is presented, including experimental results for a dedicated load cycling test. The harmonized testing protocols defined by the Joint Research Centre (JRC) of the European Commission for automotive applications were followed. With respect to a reference conditions representative of automotive applications, the impact of variations in the cell temperature, reactants pressure, and cathode stoichiometry was analyzed. The results showed that a higher temperature resulted in an increase in cell performance. A higher operating pressure also resulted in higher cell voltages. Higher cathode stoichiometry values negatively affected the cell performance, as relatively dry air was supplied, thus promoting the dry-out of the cell. However, a too low stoichiometry caused a sudden drop in the cell voltage at higher current densities, and also caused significant cell voltage oscillations. No significant cell degradation was observed after the load cycling tests. Full article
(This article belongs to the Special Issue Representative Model and Flow Characteristics of Fuel Cells)
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22 pages, 5203 KiB  
Article
Designing Hydrogen and Oxygen Flow Rate Control on a Solid Oxide Fuel Cell Simulator Using the Fuzzy Logic Control Method
by Darjat, Sulistyo, Aris Triwiyatno, Sudjadi and Andra Kurniahadi
Processes 2020, 8(2), 154; https://doi.org/10.3390/pr8020154 - 25 Jan 2020
Cited by 11 | Viewed by 4976
Abstract
A solid oxide fuel cell (SOFC) is an electrochemical cell that converts chemical energy into electrical energy by oxidizing fuel. SOFC has high efficiency and cleans oxidation residues. Research has shown the importance of SOFC control. Voltage output control is needed because of [...] Read more.
A solid oxide fuel cell (SOFC) is an electrochemical cell that converts chemical energy into electrical energy by oxidizing fuel. SOFC has high efficiency and cleans oxidation residues. Research has shown the importance of SOFC control. Voltage output control is needed because of nonlinearity, slow dynamics, and proper SOFC operating restrictions. This study aims to design an SOFC simulator with output voltage control to optimize the flow rate of fuel (hydrogen) and air (oxygen). This SOFC simulator is designed based on a microcontroller model. The controller is designed using the fuzzy logic method. Tests show that the output voltage can approach the set point with an average of 340.6 volts. The pressure difference (∆Pressure) between the two gases averaged 4428 Pa, and the fuel/gas flow rate was in the range of 0.7 mol/s. The controller can correct both the output voltage of the SOFC simulator and the difference in gas pressure under 8106 Pa (0.08 atm). Full article
(This article belongs to the Special Issue Representative Model and Flow Characteristics of Fuel Cells)
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