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Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II
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Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D2: Electrochem: Batteries, Fuel Cells, Capacitors".

Deadline for manuscript submissions: 20 June 2025 | Viewed by 12398

Special Issue Editor

Dr. Orazio Barbera

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Guest Editor
Italian National Research Council (CNR), Department of Engineering, ICT and Technology for Energy and Transport (DIITET), Institute for Advanced Energy Technologies (ITAE), Via Salita S. Lucia Sopra Contesse 5, 98126 Messina, Italy
Interests: low temperature fuel cell stack and batteries; design methodologies; testing protocols and numerical simulations; system integration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Earth’s climate has changed throughout history. Seven cycles of glaciation have taken place in the last 650,000 years, but the current warming trend is of particular significance because it is extremely likely to be the result of using of fossil fuels since the mid-20th century.

In this context, near zero-emission systems based on fuel cell are a potential key factor for the green energy transition.

Therefore, accurate methodologies for fuel cell systems design are becoming increasingly important. Modeling is fundamental for fuel cell and hybrid power system design, where fuel cell is coupled with different power generation devices.

This Special Issue aims to gather research advances in the modeling of fuel-cell-based and hybrid power systems (PV/fuel cell, wind/fuel cell, battery/fuel, and so on). It focuses on the methodologies for mathematical modeling of fuel cell and hybrid systems, by illustrating different approaches to fuel cell technology (PEFC; SOFC, DMFC), system architecture, hybridization level, application (i.e., automotive, stationary, cogeneration, portable), and power management.

The issue will contribute to enrich the background in the field of fuel cell system engineering research, and I am honored to invite you to submit your original work to this Special Issue.

I look forward to receiving your contribution.

Dr. Orazio Barbera
Guest Editor

Manuscript Submission Information

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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. Energies 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 2600 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 power system modeling
  • hybrid power system modeling
  • power system
  • PEFC, SOFC, DMFC
  • automotive
  • portable
  • cogeneration
  • smart grid
  • smart cities
  • mathematical model

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Related Special Issue

Published Papers (7 papers)

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16 pages, 8053 KiB  
Article
A Novel Hydrogen Leak Detection Method for PEM Fuel Cells Using Active Thermography
by Martina Totaro, Dario Santonocito, Giacomo Risitano, Orazio Barbera and Giosuè Giacoppo
Energies 2025, 18(5), 1185; https://doi.org/10.3390/en18051185 - 28 Feb 2025
Viewed by 346
Abstract
Hydrogen leakage in Proton Exchange Membrane (PEM) fuel cells poses critical safety, efficiency, and operational reliability risks. This study introduces an innovative infrared (IR) thermography-based methodology for detecting and quantifying hydrogen leaks towards the outside of PEM fuel cells. The proposed method leverages [...] Read more.
Hydrogen leakage in Proton Exchange Membrane (PEM) fuel cells poses critical safety, efficiency, and operational reliability risks. This study introduces an innovative infrared (IR) thermography-based methodology for detecting and quantifying hydrogen leaks towards the outside of PEM fuel cells. The proposed method leverages the catalytic properties of a membrane electrode assembly (MEA) as an active thermal tracer, facilitating real-time visualisation and assessment of hydrogen leaks. Experimental tests were conducted on a single-cell PEM fuel cell equipped with intact and defective gaskets to evaluate the method’s effectiveness. Results indicate that the active tracer generates distinct thermal signatures proportional to the leakage rate, overcoming the limitations of hydrogen’s low IR emissivity. Comparative analysis with passive tracers and baseline configurations highlights the active tracer-based approach’s superior positional accuracy and sensitivity. Additionally, the method aligns detected thermal anomalies with defect locations, validated through pressure distribution maps. This novel, non-invasive technique offers precise, reliable, and scalable solutions for hydrogen leak detection, making it suitable for dynamic operational environments and industrial applications. The findings significantly advance hydrogen’s safety diagnostics, supporting the broader adoption of hydrogen-based energy systems. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II)
►▼ Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) PEM fuel cell (<b>b</b>) test station.</p> Full article ">Figure 2
<p>The experimental setup: in the foreground, on the tripod, the thermal IR camera, and in the background, the testing station with the single cell mounted on the bench.</p> Full article ">Figure 3
<p>Two pictures of the gasket: (<b>a</b>) intact, (<b>b</b>) with intentional defect.</p> Full article ">Figure 4
<p>Pictures of the used fuel cell (in the centre) with defective gasket: (<b>a</b>) as it is, (<b>b</b>) with passive tracer, (<b>c</b>) with active tracer.</p> Full article ">Figure 5
<p>IR image of the fuel cell with intact gasket: (<b>a</b>) without tracer and (<b>b</b>) with active tracer. Labels (“Environment”, ”Plate”, “Gas mixture”) indicate where the temperature was measured for the graph of <a href="#energies-18-01185-f006" class="html-fig">Figure 6</a>).</p> Full article ">Figure 6
<p>Heating rates of the plate (green) and the environment (red) as the gas mixture temperature increases (blue). The vertical dashed line indicates the insertion of the active tracer in contact with the single cell.</p> Full article ">Figure 7
<p>IR Image with the defective gasket in baseline conditions. No leaks are visible.</p> Full article ">Figure 8
<p>IR image of the thermal gas plume escaping near the defect visible on the passive tracer surface. The label “Leakage” indicates the point where the temperature was measured: (<b>a</b>) with a lower nitrogen flow rate; and (<b>b</b>) with a high nitrogen flow rate.</p> Full article ">Figure 9
<p>Temperature profile of the passive tracer by increasing the nitrogen’s flow rate escaping from the PEM cell. Frame A and Frame B are depicted in <a href="#energies-18-01185-f008" class="html-fig">Figure 8</a>.</p> Full article ">Figure 10
<p>(<b>a</b>) The thermal plume of gas escaping near the defect, displayed on the active tracer, yellow colour corresponds to the highest temperatures, purple colour to the lowest; (<b>b</b>) temperature along the height; (<b>c</b>) temperature along the width of the tracer.</p> Full article ">Figure 11
<p>Correlation between temperature and mass flow increasing, (<b>a</b>) without H<sub>2</sub>–N<sub>2</sub> mixture, (<b>b</b>) with 50 mL/min of H<sub>2</sub> in H<sub>2</sub>–N<sub>2</sub> mixture, (<b>c</b>) with 75 mL/min of H<sub>2</sub> in of H<sub>2</sub>–N<sub>2</sub> mixture.</p> Full article ">Figure 12
<p>Contact pressure distribution of the cell with gasket (<b>a</b>) intact and (<b>b</b>) defective.</p> Full article ">Figure 13
<p>Correlation between (<b>a</b>) the actual position of the leakage evaluated with the sensor arrays and (<b>b</b>) the leakage position revealed from the thermographic image.</p> Full article ">
40 pages, 10424 KiB  
Article
Optimising the Design of a Hybrid Fuel Cell/Battery and Waste Heat Recovery System for Retrofitting Ship Power Generation
by Onur Yuksel, Eduardo Blanco-Davis, Andrew Spiteri, David Hitchmough, Viknash Shagar, Maria Carmela Di Piazza, Marcello Pucci, Nikolaos Tsoulakos, Milad Armin and Jin Wang
Energies 2025, 18(2), 288; https://doi.org/10.3390/en18020288 - 10 Jan 2025
Cited by 1 | Viewed by 897
Abstract
This research aims to assess the integration of different fuel cell (FC) options with battery and waste heat recovery systems through a mathematical modelling process to determine the most feasible retrofit solutions for a marine electricity generation plant. This paper distinguishes itself from [...] Read more.
This research aims to assess the integration of different fuel cell (FC) options with battery and waste heat recovery systems through a mathematical modelling process to determine the most feasible retrofit solutions for a marine electricity generation plant. This paper distinguishes itself from existing literature by incorporating future cost projection scenarios involving variables such as carbon tax, fuel, and equipment prices. It assesses the environmental impact by including upstream emissions integrated with the Energy Efficiency Existing Ship Index (EEXI) and the Carbon Intensity Indicator (CII) calculations. Real-time data have been collected from a Kamsarmax vessel to build a hybrid marine power distribution plant model for simulating six system designs. A Multi-Criteria Decision Making (MCDM) methodology ranks the scenarios depending on environmental benefits, economic performance, and system space requirements. The findings demonstrate that the hybrid configurations, including solid oxide (SOFC) and proton exchange (PEMFC) FCs, achieve a deduction in equivalent CO2 of the plant up to 91.79% and decrease the EEXI and the average CII by 10.24% and 6.53%, respectively. Although SOFC-included configurations show slightly better economic performance and require less fuel capacity, the overall performance of PEMFC designs are ranked higher in MCDM analysis due to the higher power density. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II)
►▼ Show Figures

Figure 1

Figure 1
<p>The methodology flowchart.</p> Full article ">Figure 2
<p>Sample data: Power output distribution of D/Gs.</p> Full article ">Figure 3
<p>The conventional and investigated hybrid design for marine power distribution unit.</p> Full article ">Figure 4
<p>The specific fuel consumption curve of the marine diesel engine.</p> Full article ">Figure 5
<p>The algorithm scheme of the model and EMS (The red, blue, and purple dashed boxes delineate the modelling frameworks for the load sharing of FC, battery, and ICE respectively).</p> Full article ">Figure 6
<p>Usage hour distribution of equipment.</p> Full article ">Figure 7
<p>Fuel consumption distribution of scenarios.</p> Full article ">Figure 8
<p>The operational and upstream (<b>a</b>) CO<sub>2-eq</sub>, (<b>b</b>) CO<sub>2</sub>, (<b>c</b>) N<sub>2</sub>O, and (<b>d</b>) CH<sub>4</sub> emissions of the scenarios.</p> Full article ">Figure 9
<p>The operational and upstream (<b>a</b>) SOx, (<b>b</b>) NOx, (<b>c</b>) PM, and (<b>d</b>) VOC emissions of the scenarios.</p> Full article ">Figure 10
<p>Attained EEXI values of combinations.</p> Full article ">Figure 11
<p>The CII variation of base and zero-carbon cases was attained.</p> Full article ">Figure 12
<p>LCOE of hybrid scenarios considering the economic projection cases and year.</p> Full article ">Figure 13
<p>EPC of hybrid scenarios considering the economic projection cases and year.</p> Full article ">
15 pages, 1956 KiB  
Article
Investigating PEM Fuel Cells as an Alternative Power Source for Electric UAVs: Modeling, Optimization, and Performance Analysis
by Pavel Shuhayeu, Aliaksandr Martsinchyk, Katsiaryna Martsinchyk and Jaroslaw Milewski
Energies 2024, 17(17), 4427; https://doi.org/10.3390/en17174427 - 4 Sep 2024
Cited by 2 | Viewed by 1678
Abstract
Unmanned aerial vehicles (UAVs) have become an integral part of modern life, serving both civilian and military applications across various sectors. However, existing power supply systems, such as batteries, often fail to provide stable, long-duration flights, limiting their applications. Previous studies have primarily [...] Read more.
Unmanned aerial vehicles (UAVs) have become an integral part of modern life, serving both civilian and military applications across various sectors. However, existing power supply systems, such as batteries, often fail to provide stable, long-duration flights, limiting their applications. Previous studies have primarily focused on battery-based power, which offers limited flight endurance due to lower energy densities and higher system mass. Proton exchange membrane (PEM) fuel cells present a promising alternative, providing high power and efficiency without noise, vibrations, or greenhouse gas emissions. Due to hydrogen’s high specific energy, which is substantially higher than that of combustion engines and battery-based alternatives, UAV operational time can be significantly extended. This paper investigates the potential of PEM fuel cells as an alternative power source for electric propulsion in UAVs. This study introduces an adaptive, fully functioning PEM fuel cell model, developed using a reduced-order modeling approach and optimized for UAV applications. This research demonstrates that PEM fuel cells can effectively double the flight endurance of UAVs compared to traditional battery systems, achieving energy densities of around 1700 Wh/kg versus 150–250 Wh/kg for batteries. Despite a slight increase in system mass, fuel cells enable significantly longer UAV operations. The scope of this study encompasses the comparison of battery-based and fuel cell-based propulsion systems in terms of power, mass, and flight endurance. This paper identifies the limitations and optimal applications for fuel cells, providing strong evidence for their use in UAVs where extended flight time and efficiency are critical. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II)
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Figure 1

Figure 1
<p>(<b>a</b>) PEMFC operation principle, (<b>b</b>) reduced order model scheme.</p> Full article ">Figure 2
<p>Investigated UAV A.R.C.H.E.R.</p> Full article ">Figure 3
<p>Scheme of the simulation.</p> Full article ">Figure 4
<p>Simulation results of PEM fuel cell: current-voltage (<b>top</b>) and current-power (<b>bottom</b>) dependency.</p> Full article ">Figure 5
<p>Specific energy of battery vs. fuel cell: (<b>a</b>) gravimetric; (<b>b</b>) volumetric.</p> Full article ">Figure 6
<p>Total mass of the supply system vs. time of operation.</p> Full article ">
12 pages, 1691 KiB  
Article
Biogas-to-Power Systems Based on Solid Oxide Fuel Cells: Thermodynamic Analysis of Stack Integration Strategies
by Arianna Baldinelli, Umberto Desideri, Francesco Fantozzi and Giovanni Cinti
Energies 2024, 17(15), 3614; https://doi.org/10.3390/en17153614 - 23 Jul 2024
Viewed by 859
Abstract
Biogas presents a renewable fuel source with substantial potential for reducing carbon emissions in the energy sector. Exploring this potential in the farming sector is crucial for fostering the development of small-scale distributed biogas facilities, leveraging indigenous resources while enhancing energy efficiency. The [...] Read more.
Biogas presents a renewable fuel source with substantial potential for reducing carbon emissions in the energy sector. Exploring this potential in the farming sector is crucial for fostering the development of small-scale distributed biogas facilities, leveraging indigenous resources while enhancing energy efficiency. The establishment of distributed biogas plants bolsters the proportion of renewable energy in the energy matrix, necessitating efficient power generation technologies. Given their proximity to bio-waste production sites like farms and digesters, optimising combined heat and power generation systems is imperative for energy self-sufficiency. Small-scale biogas facilities demand specific power generation technologies capable of achieving notable efficiencies, ranging from 40% to 55%. This study focuses on employing Solid Oxide Fuel Cells (SOFCs) in biogas-to-power systems and investigates the theoretical operation of SOFCs with fuel mixtures resulting from different biogas lean upgrading pathways. Therefore, starting from ten mixtures including CH4, CO2, H2, H2O, N2, and O2, the study proposes a method to assess their impact on the electrochemical performance, degradation, and energy equilibrium of SOFC units. The model embeds thermodynamic equilibrium, the Nernst potential, and energy balance, enabling a comprehensive comparison across these three analytical domains. The findings underscore the unsuitability of dry biogas and dry biomethane due to the potential risk of carbon deposition. Moreover, mixtures incorporating CO2, with or without H2, present significant thermal balance challenges. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II)
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Figure 1

Figure 1
<p>Bio CHP: conceptual scheme.</p> Full article ">Figure 2
<p>CHO ternary diagram of the analysed compositions (the three axes report molar fractions of each element, and the composition of any point within the triangle sums to 100%). Blue lines mark the carbon deposition zone limits at 700 °C and 800 °C, while the red dashed line highlights the occurrence of Ni oxidation.</p> Full article ">Figure 3
<p>Graphene concentration for the compositions resulting from FACTSage simulations.</p> Full article ">Figure 4
<p>LHV and Nernst voltage of the analysed compositions.</p> Full article ">Figure 5
<p>Thermal balance analysis.</p> Full article ">
21 pages, 4810 KiB  
Article
Assessing Open Circuit Voltage Losses in PEMFCs: A New Methodological Approach
by Francesco Mazzeo, Luca Di Napoli and Massimiliana Carello
Energies 2024, 17(11), 2785; https://doi.org/10.3390/en17112785 - 6 Jun 2024
Cited by 1 | Viewed by 2165
Abstract
Proton-exchange membrane (PEM) fuel cells are increasingly used in the automotive sector. A crucial point for estimating the performance of such systems is open-circuit voltage (OCV) losses, among which the most influential are mixed potential, hydrogen crossover, and internal short circuits. These losses [...] Read more.
Proton-exchange membrane (PEM) fuel cells are increasingly used in the automotive sector. A crucial point for estimating the performance of such systems is open-circuit voltage (OCV) losses, among which the most influential are mixed potential, hydrogen crossover, and internal short circuits. These losses are often overlooked in the modeling of such electrochemical cells, leading to an inaccurate estimation of the real voltage that is calculated starting from the Nernst Equation. An innovative method is presented to estimate the losses based on the division of the membrane into two domains: solid and aqueous. The influence of the macro-parameters (temperature, pressure, and RH) was analyzed for each phenomenon and was linked to the membrane water content. For low levels of PEM hydration, internal short circuits were of the same order of magnitude as hydrogen crossover. The OCV model accuracy was assessed on a commercial stack, used on a vehicle prototype competing in the Shell Eco-Marathon challenge. The data of interest were obtained through laboratory tests and subsequent disassembly of the stack. A PEM thickness of 127 μm was measured corresponding to Nafion 115. For further validation, the model results were compared with data in the literature. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II)
►▼ Show Figures

Figure 1

Figure 1
<p>Fuel Cell Horizon H-500.</p> Full article ">Figure 2
<p>Experimental set-up of the test bench.</p> Full article ">Figure 3
<p>Polarization curve of a single cell of the Horizon H-500.</p> Full article ">Figure 4
<p>From left to right: cathode flow field plate, air filter, cathode gas diffusion layer and catalyst layer, PEM.</p> Full article ">Figure 5
<p>On the <b>left</b>, comparison between hydration by adsorption (<math display="inline"><semantics> <mrow> <msup> <mrow> <mi>λ</mi> </mrow> <mrow> <mi>L</mi> </mrow> </msup> </mrow> </semantics></math>) and by osmosis (<math display="inline"><semantics> <mrow> <msup> <mrow> <mi>λ</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msup> </mrow> </semantics></math>) vs. relative humidity of the PEM at constant temperature of 50 °C. On the <b>right</b>, the sum of the effects (<math display="inline"><semantics> <mrow> <mi>λ</mi> </mrow> </semantics></math>) which gives the total hydration level of the membrane vs. relative humidity of the membrane (RH) for different temperature.</p> Full article ">Figure 6
<p>Solid and aqueous domains vs. hydration number <math display="inline"><semantics> <mrow> <mi>λ</mi> </mrow> </semantics></math> for Horizon H-500.</p> Full article ">Figure 7
<p>Possible hydrogen path through dry and hydrated PEMs [<a href="#B39-energies-17-02785" class="html-bibr">39</a>].</p> Full article ">Figure 8
<p>Membrane electrical resistivity vs. hydration number <math display="inline"><semantics> <mrow> <mi>λ</mi> </mrow> </semantics></math>.</p> Full article ">Figure 9
<p>H<sub>2</sub> crossover current densities vs. temperature at OCV with pressure equal to 3 atm and full wet conditions. In red, the output of the model for the Horizon H-500; in green and purple, the measured values obtained by Zhang et al. [<a href="#B34-energies-17-02785" class="html-bibr">34</a>] for a FC with N112 and N117 PEM, respectively.</p> Full article ">Figure 10
<p>On the <b>left</b>, hydrogen crossover current density in function of hydration number and temperature at hydrogen partial pressure of 1.5 bar. On the <b>right</b>, hydrogen crossover current density in function of hydration number and hydrogen partial pressure at fixed temperature of 50 °C.</p> Full article ">Figure 11
<p>Internal short circuit current density vs. hydration number.</p> Full article ">Figure 12
<p>Comparison between hydrogen crossover current and internal short-circuit current for different membrane water content.</p> Full article ">Figure 13
<p>OCV vs. temperature: Nernst, model, experimental and literature comparison from the work of Zhang et al. [<a href="#B34-energies-17-02785" class="html-bibr">34</a>].</p> Full article ">
30 pages, 12144 KiB  
Article
Steady-State and Transient Operation of Solid Oxide Fuel Cell Systems with Anode Off-Gas Recirculation within a Highly Constrained Operating Range
by Jan Hollmann and Stephan Kabelac
Energies 2023, 16(23), 7827; https://doi.org/10.3390/en16237827 - 28 Nov 2023
Cited by 1 | Viewed by 1999
Abstract
Based on a prototype presented in a prior publication, this research investigates the operational characteristics of a methane-fueled solid oxide fuel cell (SOFC) system with anode off-gas recirculation (AOGR) for electrical energy supply on sea-going vessels. The proposed first-principle system model utilizes a [...] Read more.
Based on a prototype presented in a prior publication, this research investigates the operational characteristics of a methane-fueled solid oxide fuel cell (SOFC) system with anode off-gas recirculation (AOGR) for electrical energy supply on sea-going vessels. The proposed first-principle system model utilizes a spatially segmented SOFC stack and lumped balance of plant components validated on the component level to accurately depict the steady-state and transient operating behavior. Five operational limitations are chosen to highlight permissible operating conditions with regard to stack and pre-reformer degradation. Steady-state operating maps are presented, emphasizing efficient operating conditions at maximum stack fuel utilization and minimal permissible oxygen-to-carbon ratio. Exemplary transient load changes illustrate increasing system control complexity caused by gas flow delays due to the spatially distributed plant layout. Actuation strategies are presented and underline the need for a top-level model predictive system controller to assure a dynamic and efficient operation within the defined constraints. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II)
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Figure 1

Figure 1
<p>Principle schematics of anode off-gas recirculation.</p> Full article ">Figure 2
<p>Overall plant layout, as presented in [<a href="#B7-energies-16-07827" class="html-bibr">7</a>], consisting of one or multiple fuel cell modules (FCMs) and one fuel processing module (FPM). Manipulated system variables are indicated as red arrows.</p> Full article ">Figure 3
<p>Scaled-up intermodal container system consisting of a central fuel processing module (FPM) and twelve fuel cell modules (FCM), arranged in four parallel branches of three modules each.</p> Full article ">Figure 4
<p>SOFC Stack model layout. Left: discretization into control volumes in the flow direction. Right: close-up of one control volume.</p> Full article ">Figure 5
<p>Determination of <math display="inline"><semantics> <mrow> <mi>O</mi> <mo>/</mo> <msub> <mi>C</mi> <mi>min</mi> </msub> </mrow> </semantics></math>. Left: Ternary C/H/O diagram and two exemplary threshold lines at 400 <math display="inline"><semantics> <mrow> <mo>°</mo> <mi mathvariant="normal">C</mi> </mrow> </semantics></math> and 800<math display="inline"><semantics> <mrow> <msup> <mrow/> <mo>∘</mo> </msup> <mi mathvariant="normal">C</mi> </mrow> </semantics></math> for carbon deposition at atmospheric pressure taken from [<a href="#B37-energies-16-07827" class="html-bibr">37</a>] along with corresponding lines of constant <math display="inline"><semantics> <mrow> <mi>O</mi> <mo>/</mo> <mi>C</mi> </mrow> </semantics></math>. Right: deducted <math display="inline"><semantics> <mrow> <mi>O</mi> <mo>/</mo> <msub> <mi>C</mi> <mi>min</mi> </msub> </mrow> </semantics></math> values as a function of temperature (filled squares) and corresponding polynomial fit.</p> Full article ">Figure 6
<p>Concept of stationary operating maps at constant electrical current. Left: Dashed lines of constant <math display="inline"><semantics> <mrow> <mi>F</mi> <msub> <mi>U</mi> <mi>stack</mi> </msub> </mrow> </semantics></math> in 5%-point increments and dotted lines of constant <math display="inline"><semantics> <mrow> <mi>O</mi> <mo>/</mo> <mi>C</mi> </mrow> </semantics></math> in <math display="inline"><semantics> <mrow> <mn>0.1</mn> </mrow> </semantics></math> increments. Right: Exemplary limiting lines and permissible operating range depicted as filled green area.</p> Full article ">Figure 7
<p>The spatial distribution of the electrical current (<b>a</b>), cell temperature (<b>b</b>), and its spatial gradient (<b>c</b>) along the flow coordinate for a set of electrical currents and gas inlet conditions, as given in <a href="#energies-16-07827-t003" class="html-table">Table 3</a>. Cell Voltage and oxygen utilization as a function of the electrical current given in (<b>d</b>).</p> Full article ">Figure 8
<p>Steady-state operating maps of the SOFC system for a set of four electric currents for ‘Begin of Life’ (BoL) (left) and 10,000 h of operation (right). Cell voltage as a function of the electrical system net power (<b>b</b>).</p> Full article ">Figure 9
<p>Transient load reduction simulations by means of four MV ramp-down strategies <math display="inline"><semantics> <mrow> <mo>↘</mo> <mrow> <mi>RD</mi> <mn>1</mn> <mo>−</mo> <mn>4</mn> </mrow> </mrow> </semantics></math> at an identical current ramp rate of 15 <math display="inline"><semantics> <mi mathvariant="normal">A</mi> </semantics></math> min<sup>−1</sup>. Ramp specifications are given in <a href="#energies-16-07827-t005" class="html-table">Table 5</a>. The vertical lines depict the offset ramp start and end times of fuel flow (solid), electrical current (dashed) and blower frequency (dot-dashed).</p> Full article ">Figure 10
<p>Transient load reduction simulations of selected <math display="inline"><semantics> <mrow> <mo>↘</mo> <mrow> <mi>RD</mi> <mn>3</mn> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mo>↘</mo> <mrow> <mi>RD</mi> <mn>4</mn> </mrow> </mrow> </semantics></math> scenarios at three different current ramp rates of 15, 30, and 60 A min<sup>−1</sup>. Ramp specifications are given in <a href="#energies-16-07827-t005" class="html-table">Table 5</a>. The vertical black lines depict the offset ramp start times of fuel flow (solid), electrical current (dashed) and blower frequency (dot-dashed). The coloured solid vertical lines depict the corresponding fuel flow ramp end time.</p> Full article ">Figure 11
<p>Transient load increase simulations started immediately after the load reduction of <a href="#energies-16-07827-f009" class="html-fig">Figure 9</a> at high component temperatures (hot ramp-up) by means of five MV ramp-up strategies <math display="inline"><semantics> <mrow> <mo>↗</mo> <mrow> <mi>HRU</mi> <mn>1</mn> <mo>−</mo> <mn>5</mn> </mrow> </mrow> </semantics></math> at an identical current ramp rate of 15 <math display="inline"><semantics> <mi mathvariant="normal">A</mi> </semantics></math> min<sup>−1</sup>. Ramp specifications are given in <a href="#energies-16-07827-t005" class="html-table">Table 5</a>. The vertical lines depict the offset ramp start and end times of fuel flow (solid), electrical current (dashed) and blower frequency (dot-dashed).</p> Full article ">Figure 12
<p>Transient load increase started from steady-state partial load operating points at lower component temperatures. Selected scenarios starting from <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>R</mi> <mo>=</mo> <mn>70</mn> <mo>%</mo> <mrow/> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>F</mi> <msub> <mi>U</mi> <mi>stack</mi> </msub> <mo>=</mo> <mn>75</mn> <mo>%</mo> <mrow/> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <mo>↗</mo> <mrow> <mi>CRU</mi> <mn>5</mn> </mrow> </mrow> </semantics></math>) and <math display="inline"><semantics> <mrow> <mi>R</mi> <mi>R</mi> <mo>=</mo> <mn>77.5</mn> <mo>%</mo> <mrow/> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>F</mi> <msub> <mi>U</mi> <mi>stack</mi> </msub> <mo>=</mo> <mn>50</mn> <mo>%</mo> <mrow/> </mrow> </semantics></math> (<math display="inline"><semantics> <mrow> <mo>↗</mo> <mrow> <mi>CRU</mi> <mn>6</mn> </mrow> </mrow> </semantics></math>). Ramp specifications are given in <a href="#energies-16-07827-t005" class="html-table">Table 5</a>. The vertical lines depict the offset ramp start and end times of fuel flow (solid) and recirculation ratio (dashed).</p> Full article ">

Review

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24 pages, 2328 KiB  
Review
Review of AEM Electrolysis Research from the Perspective of Developing a Reliable Model
by Rafal Bernat, Jaroslaw Milewski, Olaf Dybinski, Aliaksandr Martsinchyk and Pavel Shuhayeu
Energies 2024, 17(20), 5030; https://doi.org/10.3390/en17205030 - 10 Oct 2024
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Abstract
This review thoroughly examines recent progress, challenges, and future prospects in the field of alkaline exchange membrane (AEM) electrolysis. This emerging technology holds promise for eco-friendly hydrogen production. It blends the benefits of traditional alkaline and proton-exchange membrane technologies, enhancing affordability and operational [...] Read more.
This review thoroughly examines recent progress, challenges, and future prospects in the field of alkaline exchange membrane (AEM) electrolysis. This emerging technology holds promise for eco-friendly hydrogen production. It blends the benefits of traditional alkaline and proton-exchange membrane technologies, enhancing affordability and operational efficiencies by utilizing non-precious metal catalysts and operating at reduced temperatures. This study discusses key developments in materials, electrode design, and performance enhancement techniques. It also highlights the strategic role of AEM electrolysis in meeting global energy transition targets, like achieving Net Zero Emissions by 2050. An in-depth exploration of the operational fundamentals of AEM water electrolysis is provided, noting the technology’s early stage development and the ongoing need for research in membrane-electrode assembly assessment, catalyst efficiency, and electrochemical ammonia production. Moreover, this review compiles results on different cell components, electrolyte types, and experimental approaches, providing insights into operational parameters critical to optimizing AEM performance. The conclusion emphasizes the necessity for continuous research and commercialization efforts to exploit AEM electrolysis’s full potential across diverse industries. Full article
(This article belongs to the Special Issue Fuel Cell-Based and Hybrid Power Generation Systems Modeling, Volume II)
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Figure 1

Figure 1
<p>Types of electrolyzers with LTR indication [<a href="#B1-energies-17-05030" class="html-bibr">1</a>].</p> Full article ">Figure 2
<p>Schematic illustration of a (<b>a</b>) membrane electrolyzer. General reaction pathways for HER and OER in (<b>b</b>) acidic and (<b>c</b>) alkaline solutions [<a href="#B2-energies-17-05030" class="html-bibr">2</a>].</p> Full article ">Figure 3
<p>Volcano plot of exchange current density vs. ΔG<sub>H</sub> for various catalysts [<a href="#B2-energies-17-05030" class="html-bibr">2</a>].</p> Full article ">Figure 4
<p>Polarization curves obtained from AEM water electrolyzer operation at 50 °C using MEAs with 20 wt% and 9 wt% PTFE binders in the anode and cathode, respectively (BC20), across the 10th (<b>a</b>), 50th (<b>b</b>), and 100th cycle (<b>c</b>) under varying cathode feed modes [<a href="#B5-energies-17-05030" class="html-bibr">5</a>].</p> Full article ">Figure 5
<p>Construction of an alkaline water electrolyzer cell [<a href="#B13-energies-17-05030" class="html-bibr">13</a>].</p> Full article ">Figure 6
<p>Schematic of experimental setup for water electrolysis: (1) Electrolytic cell (AEM electrolyzer), (2) Electric heaters for the cell, (3) Tube-in-tube heat exchanger, (4) Dew point meter (wrapped with heat tape), (5) Pre-mixing tank, (6) Flowmeter, (7) Control valve, (8) Circulation pump, (9) Accumulators (liquid–gas separator), (10) Cold traps, (11) Soap film flowmeter, (12) Digital flowmeters, and (13) Gas chromatograph (GC) [<a href="#B12-energies-17-05030" class="html-bibr">12</a>].</p> Full article ">Figure 7
<p>Cell voltage (VCELL) and cell resistance (RCELL) as a function of current density (I) during electrolysis (upwards) using different electrolyte solutions (EL1–EL4) at cell temperature (TCELL) of 50 °C.</p> Full article ">
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