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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A5: Hydrogen Energy".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 17837

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Dr. Ahmad Baroutaji

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Faculty of Engineering and Physical Science, Aston University, Aston Triangle, Birmingham B4 7ET, UK
Interests: additive manufacturing; engineering design and manufacturing; crashworthiness, fuel cell technology
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Dear Colleagues,

Fuel cells are devices that generate electricity through an electrochemical reaction with only heat and water as by-products. Nowadays, fuel cell devices are receiving increased attention as clean energy sources for various practical applications—from small electronic devices to vehicles. Effective design and development of the various components of a fuel cell require an in-depth understanding of the influence of different design variables on the performance of these components. Fuel cell operation involves simultaneous and multiphysics complex processes, and due to the highly reactive, compact nature of the fuel cell, it is challenging to conduct in-situ measurements of critical parameters, such as temperature, pressure and potential gradients, or species concentration. Various computational and modelling techniques, which allow systematic simulation, design, and optimization of fuel cell systems, are valuable tools that provide insight into the phenomena occurring within the cell, reducing the development cycles, and enabling to build the next generation of fuel cells.

Thus, this Special Issue focuses on the recent developments and applications of modelling, simulation, and optimisation tools for the design and development of different types of fuel cell devices.

Dr. Ahmad Baroutaji
Guest Editor

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Keywords

CFD
Matlab
modelling
simulations
optimisation
PEM
SOFC
DMFC
fuel cell

Published Papers (7 papers)

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Research

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12 pages, 4640 KiB

Open AccessArticle

Performance Investigation on Mono-Block-Layer Build Type Solid Oxide Fuel Cells with a Vertical Rib Design

by Siyu Lu, Man Zhang, Jie Wu and Wei Kong

Energies 2022, 15(3), 979; https://doi.org/10.3390/en15030979 - 28 Jan 2022

Cited by 1 | Viewed by 1910

Abstract

Compared with planar-type solid oxide fuel cells (SOFCs), mono-block-layer build (MOLB)-type SOFCs have additional three-phase boundaries per unit volume, and their performance is severely limited by their longer current path. To resolve this issue, a vertical rib design, which was evaluated using a numerical method, was proposed. Compared with the conventional design, the power density for the vertical rib design increased by 12.32%. This is because the vertical rib design provides another short path for current, which not only reduces the ohmic loss in the cathode, but also decreases the ohmic polarization caused by the contact resistance. However, the vertical rib design hinders the transport of oxygen in the cathode and increases the concentration loss. Therefore, the vertical rib size design is crucial. Based on the influence of the vertical rib width, the vertical rib widths on the cathode and anode sides of 0.7 and 1 mm are recommended for different contact resistances, respectively. Full article

(This article belongs to the Special Issue Hydrogen and Fuel Cell Technology, Modelling and Simulation)

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16 pages, 816 KiB

Open AccessArticle

A Self-Validating Method via the Unification of Multiple Models for Consistent Parameter Identification in PEM Fuel Cells

by Luis Blanco-Cocom, Salvador Botello-Rionda, Luis Carlos Ordoñez and Sergio Ivvan Valdez

Energies 2022, 15(3), 885; https://doi.org/10.3390/en15030885 - 26 Jan 2022

Cited by 5 | Viewed by 2154

Abstract

Mathematical models are used for simulating the electrochemical phenomena of proton-exchange-membrane (PEM) fuel cells. They differ in the scale, modeling variables, precision in specific features, and the required parameters. Often, the input parameters are not measurable and need to be estimated by minimizing the error between the model output and experimental data; however, the estimated parameters could differ from one model to another, hence provoking uncertainty about the correct values and the model’s suitability for simulating the real phenomenon. To address these issues, we introduced a self-validating methodology using three different mathematical models: The first set of parameters was estimated with a semi-empirical (SE) model; then, it was used for computing several points of the polarization curve (PC). The SE parameters and points were used to estimate a second set of parameters and to compute a single point of the PC with a macro-homogeneous (MH) model. The parameters and concentration profiles from the MH solution were used to estimate the last set of parameters with the reaction–convection–diffusion (SP-RCD) model, increasing the detail of the simulation. The SP-RCD parameters were returned to the MH model to recover the complete PC. The proposed methodology requires a few data points to consistently recover the same PC from the three models through estimating parameters in one model and validating them in the others. As output, the method provides complete information about several variables and the physical properties of the catalysts. In addition to the consistent simulation, the numerical results are consistent with those reported in the literature, thus validating the proposed method. Full article

(This article belongs to the Special Issue Hydrogen and Fuel Cell Technology, Modelling and Simulation)

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15 pages, 4499 KiB

Open AccessArticle

A Double-Bridge Channel Shape of a Membraneless Microfluidic Fuel Cell

by Ji-Hyun Oh, Muhammad Tanveer and Kwang-Yong Kim

Energies 2021, 14(21), 6973; https://doi.org/10.3390/en14216973 - 24 Oct 2021

Cited by 3 | Viewed by 1723

Abstract

A double-bridge shape is proposed as a novel flow channel cross-sectional shape of a membraneless microfluidic fuel cell, and its electrochemical performance was analyzed with a numerical model. A membraneless microfluidic fuel cell (MMFC) is a micro/nano-scale fuel cell with better economic and commercial viability with the elimination of the polymer electrolyte membrane. The numerical model involves the Navier–Stokes, Butler–Volmer, and mass transport equations. The results from the numerical model were validated with the experimental results for a single-bridge channel. The proposed MMFC with double-bridge flow channel shape performed better in comparison to the single-bridge channel shape. A parametric study for the double-bridge channel was performed using three sub-channel widths with the fixed total channel width and the bridge height. The performance of the MMFC varied most significantly with the variation in the width of the inner channel among the sub-channel widths, and the power density increased with this channel width because of the reduced width of the mixing layer in the inner channel. The bridge height significantly affected the performance, and at a bridge height at 90% of the channel height, a higher peak power density of 171%was achieved compared to the reference channel. Full article

(This article belongs to the Special Issue Hydrogen and Fuel Cell Technology, Modelling and Simulation)

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17 pages, 3335 KiB

Open AccessArticle

Data-Driven Prognostics of the SOFC System Based on Dynamic Neural Network Models

by Shan-Jen Cheng, Wen-Ken Li, Te-Jen Chang and Chang-Hung Hsu

Energies 2021, 14(18), 5841; https://doi.org/10.3390/en14185841 - 15 Sep 2021

Cited by 5 | Viewed by 1750

Abstract

Prognostics technology is important for the sustainability of solid oxide fuel cell (SOFC) system commercialization, i.e., through failure prevention, reliability assessment, and the remaining useful life (RUL) estimation. To solve SOFC system issues, data-driven prognostics methods based on the dynamic neural network (DNN), one of non-linear models, were investigated in this study. Based on DNN model types, the neural network autoregressive (NNARX) model with external inputs, the neural network autoregressive moving average (NNARMAX) model with external inputs, and the neural network output error (NNOE) were utilized to predict the degradation trend and estimate the RUL. First, the degradation trend prediction was executed to evaluate the correctness of the proposed DNN model structures in the first learning phase. Then, the RUL was estimated on the basis of the degradation trend of the NN models in the second inference phase. The comparison test results show the prediction accuracy of the NNARX model is higher and the RUL estimation can be given within a smaller relative error than the NNARMAX and NNOE models. The evaluation criteria of the root mean square error and mean absolute error of the NNARX model are the smallest among these three models. Therefore, the proposed NNARX model can effectively and precisely provide degradation trend prediction and RUL estimation of the SOFC system. Full article

(This article belongs to the Special Issue Hydrogen and Fuel Cell Technology, Modelling and Simulation)

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15 pages, 2707 KiB

Open AccessArticle

Research on Online Diagnosis Method of Fuel Cell Centrifugal Air Compressor Surge Fault

by Su Zhou, Jie Jin and Yuehua Wei

Energies 2021, 14(11), 3071; https://doi.org/10.3390/en14113071 - 25 May 2021

Cited by 3 | Viewed by 2055

Abstract

Stable operation of fuel cell air compressions is constrained by rotating surge in low flowrate conditions. In this paper, a diagnosis criterion based on wavelet transform to solve the surge fault is proposed. First of all, the Fourier transform was used to analyze the spectral characteristics of the outlet flowrate. Before wavelet transform was used, the data are standardized. This step eliminated the influence of the flowrate’s absolute value. Then, the wavelet coefficients under characteristic frequencies were extracted. Finally, the diagnosis criterion’s threshold, which indicates the surge occurrence, was defined from the perspective of safety margin. The criterion threshold alerted a surge only 1 s after it occurred. The analysis results show that the criterion meets with the expectation, and it can be used for the control of anti-surge valve. Full article

(This article belongs to the Special Issue Hydrogen and Fuel Cell Technology, Modelling and Simulation)

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18 pages, 6516 KiB

Open AccessArticle

Adaptive Fuzzy PID Based on Granular Function for Proton Exchange Membrane Fuel Cell Oxygen Excess Ratio Control

by Xiao Tang, Chunsheng Wang, Yukun Hu, Zijian Liu and Feiliang Li

Energies 2021, 14(4), 1140; https://doi.org/10.3390/en14041140 - 21 Feb 2021

Cited by 16 | Viewed by 2021

Abstract

An effective oxygen excess ratio control strategy for a proton exchange membrane fuel cell (PEMFC) can avoid oxygen starvation and optimize system performance. In this paper, a fuzzy PID control strategy based on granular function (GFPID) was proposed. Meanwhile, a proton exchange membrane fuel cell dynamic model was established on the MATLAB/Simulink platform, including the stack model system and the auxiliary system. In order to avoid oxygen starvation due to the transient variation of load current and optimize the parasitic power of the auxiliary system and the stack voltage, the purpose of optimizing the overall operating condition of the system was finally achieved. Adaptive fuzzy PID (AFPID) control has the technical bottleneck limitation of fuzzy rules explosion. GFPID eliminates fuzzification and defuzzification to solve this phenomenon. The number of fuzzy rules does not affect the precision of GFPID control, which is only related to the fuzzy granular points in the fitted granular response function. The granular function replaces the conventional fuzzy controller to realize the online adjustment of PID parameters. Compared with the conventional PID and AFPID control, the feasibility and superiority of the algorithm based on particle function are verified. Full article

(This article belongs to the Special Issue Hydrogen and Fuel Cell Technology, Modelling and Simulation)

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Review

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33 pages, 67295 KiB

Open AccessReview

Flow Configurations of Membraneless Microfluidic Fuel Cells: A Review

by Muhammad Tanveer and Kwang-Yong Kim

Energies 2021, 14(12), 3381; https://doi.org/10.3390/en14123381 - 8 Jun 2021

Cited by 10 | Viewed by 4140

Abstract

Membraneless microfluidic fuel cells (MMFCs) are being studied extensively as an alternative to batteries and conventional membrane fuel cells because of their simple functioning and lower manufacturing cost. MMFCs use the laminar flow of reactant species (fuel and oxidant) to eliminate the electrolyte membrane, which has conventionally been used to isolate anodic and cathodic half-cell reactions. This review article summarizes the MMFCs with six major categories of flow configurations that have been reported from 2002 to 2020. The discussion highlights the critical factors that affect and limit the performance of MMFCs. Since MMFCs are diffusion-limited, most of this review focuses on how different flow configurations act to reduce or modify diffusive mixing and depletion zones to enhance the power density output. Research opportunities are also pointed out, and the challenges in MMFCs are suggested to improve cell performance and make them practical in the near future. Full article

(This article belongs to the Special Issue Hydrogen and Fuel Cell Technology, Modelling and Simulation)

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