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Advanced Technologies in Hydrogen Fuel Cell
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Advanced Technologies in Hydrogen Fuel Cell

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 7552

Special Issue Editor

Dr. Cong Yin

E-Mail Website
Guest Editor
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 610056, China
Interests: fuel cell; flow battery; multiphysical modeling; in situ measurement

Special Issue Information

Dear Colleagues,

Fuel cells are one of the most promising clean power sources for automobile, unmanned aerial vehicles, portable devices, and stationary power station applications, due to their advantages of high energy efficiency and power density. The commercialization of hydrogen fuel cells has been promoted over the past decade, but it remains a significant challenge to improve their performance, lifetime, and cost. Fundamental research on the system, component, material, and mechanism are strongly required for the advancement of hydrogen fuel cell technologies. Recently, studies concerning the fuel cell system, stack design and modeling, multiphysical mechanisms, and advanced components and materials are attracting more and more interest for researchers all over the world. 

In this Special Issue, cutting-edge investigations regarding advanced technologies in hydrogen fuel cells are invited in the form of submissions including full-length research articles and comprehensive review papers. 

Dr. Cong Yin
Guest Editor

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 system
  • intelligent control
  • design and modeling
  • water and thermal management
  • key component and material
  • performance and durability

Published Papers (5 papers)

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Research

18 pages, 6411 KiB  
Article
Improving a Fuel Cell System’s Thermal Management by Optimizing Thermal Control with the Particle Swarm Optimization Algorithm and an Artificial Neural Network
by Bo Deng, Xuefeng Zhang, Cong Yin, Yuqin Luo and Hao Tang
Appl. Sci. 2023, 13(23), 12895; https://doi.org/10.3390/app132312895 - 1 Dec 2023
Cited by 1 | Viewed by 1061
Abstract
The thermal management of proton exchange membrane fuel cell systems plays a significant role in a stack’s lifetime, performance, and reliability. However, it is challenging to manage the thermal system precisely due to the multiple coupling relationships between the stack’s components, its operating [...] Read more.
The thermal management of proton exchange membrane fuel cell systems plays a significant role in a stack’s lifetime, performance, and reliability. However, it is challenging to manage the thermal system precisely due to the multiple coupling relationships between the stack’s components, its operating environment, and its thermal management system. In addition, temperature hysteresis (temporal inconsistency of temperature with electrochemical reactions and fluid mechanics) imposes more difficulties on thermal control. We aim to develop an effective thermal control model for the fuel cell system to improve the temperature regulation accuracy and response speed and thus achieve highly stable temperature control. A dynamic mechanistic model is first developed based on the physical processes of the stack and its thermal management system. The model is then validated through experiments. Based on this dynamic mechanistic model, a control model is proposed for stack thermal management with the particle swarm optimization algorithm and an artificial neural network. It is applied and compared with the traditional PID algorithm. The simulation results indicate that the regulation time of the coolant inlet temperature as the current changes is reduced by more than 74%, and the overshoot is reduced by more than 50%. Therefore, the control model can enhance the dynamic response capability and temperature control precision under complex operating conditions with constantly changing load current and preset stack temperature, ensuring the temperature’s stability and thus improving the fuel cell system’s reliability and durability. Full article
(This article belongs to the Special Issue Advanced Technologies in Hydrogen Fuel Cell)
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11 pages, 6887 KiB  
Article
Imaging Liquid Water in a Polymer Electrolyte Fuel Cell with High-Energy X-ray Compton Scattering
by Tetsuya Miyazawa, Naruki Tsuji, Daiki Fujioka, Takuma Kaneko, Yuki Mizuno, Yoshiharu Uchimoto, Hideto Imai and Yoshiharu Sakurai
Appl. Sci. 2023, 13(19), 10753; https://doi.org/10.3390/app131910753 - 27 Sep 2023
Cited by 1 | Viewed by 889
Abstract
Compton scattering imaging with intense, high-energy synchrotron X-rays allows us to visualize a light element substance in an operating electrochemical device. In this paper, we report the first experiment of Compton scattering imaging (CSI) on an operating polymer electrolyte fuel cell (PEFC). The [...] Read more.
Compton scattering imaging with intense, high-energy synchrotron X-rays allows us to visualize a light element substance in an operating electrochemical device. In this paper, we report the first experiment of Compton scattering imaging (CSI) on an operating polymer electrolyte fuel cell (PEFC). The novelty of the CSI technique is a non-destructive direct observation of cross-sectional images with a sensitivity to light elements and a capability of simultaneous measurements with fluorescent X-rays of heavy elements. Analyses of the observed images provide the cross-sectional distribution of generated liquid water and its current density dependency. The results show that the amount of generated water increases in the vicinity of the cathode catalyst layer at current densities ranging from 100 to 500 mA/cm2, while it remains constant or slightly decreases from 500 to 900 mA/cm2. In both the gas diffusion layer and the channel, liquid water is observed near the channel and rib interface above 500 mA/cm2, indicating the formation of a liquid water flow path. In addition, simultaneous measurements of fluorescent Pt-Ka X-rays reveal a significant correlation between the generated liquid water and Pt catalysts, using the Pearson correlation coefficient. The result shows that water is dispersed in the catalyst layer without any correlation with the amount of Pt catalysts at low current densities, but water tends to be distributed in the Pt-rich areas at high current densities. This study demonstrates that Compton scattering imaging is one of the unique techniques to characterize the behavior of generated liquid water in an operating PEFC. Full article
(This article belongs to the Special Issue Advanced Technologies in Hydrogen Fuel Cell)
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24 pages, 4081 KiB  
Article
Thermal Management of Fuel Cells Based on Diploid Genetic Algorithm and Fuzzy PID
by Ruikang Zhao, Dongchen Qin, Benhai Chen, Tingting Wang and Hongxia Wu
Appl. Sci. 2023, 13(1), 520; https://doi.org/10.3390/app13010520 - 30 Dec 2022
Cited by 8 | Viewed by 1694
Abstract
The operation of a proton exchange membrane fuel cell (PEMFC) is greatly affected by temperature. Reliable thermal management of fuel cells can improve the life, efficiency, and power output of fuel cells. The model established in this paper is based on the inner [...] Read more.
The operation of a proton exchange membrane fuel cell (PEMFC) is greatly affected by temperature. Reliable thermal management of fuel cells can improve the life, efficiency, and power output of fuel cells. The model established in this paper is based on the inner layer of the fuel cell, and through the analysis of the heat change and material flow between layers, the simulink model can reflect the temperature change of the end plate, the bipolar plate, and the membrane electrode assembly (MEA) plate. In terms of the thermal management control strategy, the deviation and deviation rate between the MEA plate’s temperature and the target temperature are taken as input, and the fuzzy PID (proportional integral differential) controller is used to control the cooling water flow, to achieve a cooling effect. Due to the low efficiency and instability of a haploid genetic algorithm (GA) in solving dynamic optimization problems, a diploid genetic algorithm to optimize the membership function of the controller, and improve the adaptability of the control system, was designed. The simulation results show that compared with the haploid genetic algorithm, the optimal results of 100 iterations of the fuzzy PID control strategy reduce by 27.9%. Compared with the haploid genetic algorithm and fuzzy PID control, the MEA layer temperature, under the control of a diploid genetic algorithm, is reduced by 18% and 28%, respectively, and the minimum temperature difference of the reactor is 2.28 K. Full article
(This article belongs to the Special Issue Advanced Technologies in Hydrogen Fuel Cell)
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15 pages, 4226 KiB  
Article
A Dimension-Reduced Artificial Neural Network Model for the Cell Voltage Consistency Prediction of a Proton Exchange Membrane Fuel Cell Stack
by Jishen Cao, Cong Yin, Yulun Feng, Yanghuai Su, Pengfei Lu and Hao Tang
Appl. Sci. 2022, 12(22), 11602; https://doi.org/10.3390/app122211602 - 15 Nov 2022
Cited by 3 | Viewed by 1396
Abstract
The voltage consistency of hundreds of cells in a proton exchange membrane fuel cell stack significantly influences the stack’s performance and lifetime. Using the physics-based model to estimate the cell voltage consistency is highly challenging due to the massive calculation efforts and the [...] Read more.
The voltage consistency of hundreds of cells in a proton exchange membrane fuel cell stack significantly influences the stack’s performance and lifetime. Using the physics-based model to estimate the cell voltage consistency is highly challenging due to the massive calculation efforts and the complicated fuel cell designs. In this research, an artificial neural network (ANN) model is developed to efficiently predict the cell voltage distribution and the consistency of a commercial-size fuel cell stack. To balance the computation efficiency and accuracy, a dimension-reduced method is proposed with different output-grouping strategies to optimize the ANN structure based on the experiment test of a 100-cell stack. The model’s training time falls nonlinearly from 16 min to 6 s with the output neuron number decreasing from 100 to 5, while the model can still predict the cell voltage distribution trends. With the proposed model, the stack’s cell voltage distributions could be reproduced with significantly lowered computation time, which is beneficial to evaluate the fuel cell status and optimize the control strategies. Full article
(This article belongs to the Special Issue Advanced Technologies in Hydrogen Fuel Cell)
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21 pages, 3487 KiB  
Article
Thermodynamic Analysis of Three Internal Reforming Protonic Ceramic Fuel Cell-Gas Turbine Hybrid Systems
by Sasmoko, Sheng-Wei Lee, Mallikarjun Bhavanari, Widya Wijayanti, I.N.G. Wardana, Ahmad Andi Azhari and Chung-Jen Tseng
Appl. Sci. 2022, 12(21), 11140; https://doi.org/10.3390/app122111140 - 3 Nov 2022
Cited by 2 | Viewed by 1477
Abstract
Protonic ceramic fuel cells (PCFCs) offer direct and efficient conversion of hydrocarbon fuels into electricity. In this study, three internal-reforming (IR)-PCFC/gas turbine (GT) hybrid systems are proposed and analyzed to achieve higher system efficiency. High-quality heat from GT in system 1 and system [...] Read more.
Protonic ceramic fuel cells (PCFCs) offer direct and efficient conversion of hydrocarbon fuels into electricity. In this study, three internal-reforming (IR)-PCFC/gas turbine (GT) hybrid systems are proposed and analyzed to achieve higher system efficiency. High-quality heat from GT in system 1 and system 2 is supplied to anode and cathode preheaters, respectively, whereas in system 3, the heat is simultaneously split into both preheaters. Effects of air flow rate, fuel utilization factor (Uf), and steam to carbon ratio (S/C) are also investigated. It is found that the best system design can be achieved by effectively utilizing GT exhaust heat for both electrode preheaters, as indicated in system 3. The maximum energy system efficiency obtained among the hybrid systems analyzed in this study is 71% with total exergy destruction of 686.7 kW. When fueled by methane, the hybrid system can achieve energy and exergy efficiencies of 71% and 77%, respectively, with 0.85 Uf. On the other hand, propane-fueled systems can achieve energy and exergy efficiencies of 68% and 75%, respectively. As S/C increases from 2 to 7, system efficiency decreases from 71% to 50%. When system 3 is fueled with butane or propane, system efficiency is only 3% lower than that fueled by methane. Full article
(This article belongs to the Special Issue Advanced Technologies in Hydrogen Fuel Cell)
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