Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms DOI Creative Commons

M. Arunadevi,

B. Karthikeyan,

A Shrihari

et al.

Energy Exploration & Exploitation, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 30, 2024

Among various fuel cells (FCs), Polymer exchange membrane FC (PEMFC) plays a vital role in the transportation era because they operate at moderate temperatures, have quick start-up, are highly efficient, scalable size, high energy density etc. With degree of accuracy, machine learning algorithms (MLAs) can be applied to solve nonlinear problems FCs, including performance prediction, service life and fault diagnostics. In addition carrying out optimization operational parameters design, MLAs when paired with techniques may effectively accurately accomplish variety goals. The main objective this study is explain significance PEMFC research describe prediction operating which maximized. This paper structured influence different process such as system temperature, supply pressure, air flow rate on output voltage FC. It clearly observed that temperature has significant percentage contribution 96.92% current 86.22% compared other parameters. Different modelled explore results proved gradient boosting regression provides better predictions decision tree regressor, support vector random forest regression.

Language: Английский

Waste-to-energy poly-generation scheme for hydrogen/freshwater/power/oxygen/heating capacity production; optimized by regression machine learning algorithms DOI
Qiuli Li,

Yuchi Leng,

Azher M. Abed

et al.

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: 187, P. 876 - 891

Published: May 3, 2024

Language: Английский

Citations

7
Numerical analysis of bubble behavior in proton exchange membrane water electrolyzer flow field with serpentine channel DOI
Duy Khang Dang, Biao Zhou

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 88, P. 688 - 701

Published: Sept. 23, 2024

Language: Английский

Citations

4
Acidic oxygen evolution reaction via lattice oxygen oxidation mechanism: progress and challenges DOI Open Access

Yuhua Xie,

Fang Luo, Zehui Yang

et al.

Energy Materials, Journal Year: 2025, Volume and Issue: 5(3)

Published: Jan. 15, 2025

The lattice oxygen mechanism (LOM) plays a critical role in the acidic evolution reaction (OER) as it provides more efficient catalytic pathway compared to conventional adsorption (AEM). LOM effectively lowers energy threshold of and accelerates rate by exciting atoms catalyst directly participate OER process. In recent years, with increase in-depth understanding LOM, researchers have developed variety iridium (Ir) ruthenium (Ru)-based catalysts, well non-precious metal oxide optimized their performance through different strategies. However, still faces many challenges practical applications, including long-term stability precise modulation active sites, application efficiency real electrolysis systems. Here, we review OER, analyze its difference traditional AEM new (OPM) mechanism, discuss experimental theoretical validation methods pathway, prospect future development electrocatalyst design conversion, aiming provide fresh perspectives strategies for solving current challenges.

Language: Английский

Citations

0
Nonlinear modeling and control of hydrogen generating system DOI
Kaushal Singh,

George Benny,

N. Sivakumaran

et al.

International Journal of Green Energy, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: Feb. 3, 2025

Language: Английский

Citations

0
Simulation study of flow fields characterization and structure optimization on U-bend section flow channel DOI
Zhi Zhang, Shen Xu, Bo Huang

et al.

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 111, P. 581 - 591

Published: Feb. 26, 2025

Language: Английский

Citations

0
Advanced microstructure characterization and microstructural evolution of porous cermet electrodes in solid oxide cells: a comprehensive review DOI Creative Commons
Wenyue Yang, Zehua Pan, Zhenjun Jiao

et al.

Energy Reviews, Journal Year: 2024, Volume and Issue: 4(1), P. 100104 - 100104

Published: Aug. 10, 2024

Solid oxide cells (SOCs), capable of interconverting electrical and chemical energy, have emerged as one the key technologies for future multi-energy complementary grid. However, commercialization SOCs is hindered by poor long-term stability, attributed in large-part to microstructural evolution electrodes, which results loss active reaction sites, blockage gas transport pathways, degradation mechanical properties. Owing recently developed three-dimensional (3D) microstructure reconstruction techniques, SOC electrodes can now be investigated quantitatively. This review highlights insights gained from studies porous cermet during operation redox cycling, corresponding effects on electrochemical performance, with particular attention investigations using 3D technologies. The influencing parameters possible strategies mitigate evolution-induced are also summarized. challenges opportunities development stable electrode microstructures analyzed, prospects commercial application provided.

Language: Английский

Citations

3
Enhancing Heat Removal and H2O Retention in Passive Air-Cooled Polymer Electrolyte Membrane Fuel Cells by Altering Flow Field Geometry DOI Open Access
Ali M. Mohsen, Ali Basem

Sustainability, Journal Year: 2024, Volume and Issue: 16(11), P. 4666 - 4666

Published: May 30, 2024

This numerical study presents six three-dimensional (3D) cathode flow field designs for a passive air-cooled polymer electrolyte membrane (PEM) fuel cell to enhance heat removal and H2O retention. The data collected are evaluated in terms of water content, average temperature, current flux density. proposed straight baseline channel (Design 1), converging 2), diverging 3), with cylindrical pin fins 4), trapezium cross-section 5), semi-circle 6). lowest temperature value 56.67 °C was obtained Design 2, while noticeable retention improvement 6.5% achieved 5) compared the channel. However, density shows reduction 0.1% 1.2%. Nevertheless, those values relatively small durability due reduction. Although modifications resulted only minor improvements, ongoing advancements technology have potential make our energy landscape more sustainable. These can help reduce emissions, increase efficiency, integrate renewable sources, security, support transition hydrogen-based economy.

Language: Английский

Citations

2
Investigation of oxygen transport in porous transport layer with different porosity gradient configurations using phase field method DOI
S. J. Zhao, Peng Li,

Siyuan Huang

et al.

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 96, P. 1087 - 1100

Published: Nov. 29, 2024

Language: Английский

Citations

2
A review of gas-liquid flow characteristics of anode porous transport layer in proton exchange membrane electrolysis cell DOI
Xiaolei Zhang, Jing Wang,

Gulizhaina Habudula

et al.

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 100, P. 1010 - 1029

Published: Dec. 28, 2024

Language: Английский

Citations

2
Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms DOI Creative Commons

M. Arunadevi,

B. Karthikeyan,

A Shrihari

et al.

Energy Exploration & Exploitation, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 30, 2024

Among various fuel cells (FCs), Polymer exchange membrane FC (PEMFC) plays a vital role in the transportation era because they operate at moderate temperatures, have quick start-up, are highly efficient, scalable size, high energy density etc. With degree of accuracy, machine learning algorithms (MLAs) can be applied to solve nonlinear problems FCs, including performance prediction, service life and fault diagnostics. In addition carrying out optimization operational parameters design, MLAs when paired with techniques may effectively accurately accomplish variety goals. The main objective this study is explain significance PEMFC research describe prediction operating which maximized. This paper structured influence different process such as system temperature, supply pressure, air flow rate on output voltage FC. It clearly observed that temperature has significant percentage contribution 96.92% current 86.22% compared other parameters. Different modelled explore results proved gradient boosting regression provides better predictions decision tree regressor, support vector random forest regression.

Language: Английский

Citations

1