Fuel Cells最新文献_第5页

Experimental Study on Cooling Uniformity and Hotspot Suppression Characteristics of Air-Cooled PEMFC With Fan Configuration 风机配置的风冷PEMFC冷却均匀性及热点抑制特性实验研究

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-10 DOI: 10.1002/fuce.70100

Sanghyun Yun, Jinwon Yun, Jaeyoung Han

{"title":"Experimental Study on Cooling Uniformity and Hotspot Suppression Characteristics of Air-Cooled PEMFC With Fan Configuration","authors":"Sanghyun Yun, Jinwon Yun, Jaeyoung Han","doi":"10.1002/fuce.70100","DOIUrl":"https://doi.org/10.1002/fuce.70100","url":null,"abstract":"<p>Air-cooled polymer electrolyte membrane fuel cells (PEMFCs) offer structural simplicity and advantages in compact system design; however, nonuniform thermal management induced by fan-based cooling can lead to hotspot formation, resulting in increased membrane resistance, performance degradation, and reduced durability. In particular, variations in airflow characteristics caused by different fan configurations directly influence stack temperature distribution and voltage stability, indicating the necessity for systematic experimental and quantitative investigation. Accordingly, this study derives a critical operating temperature based on the temperature–voltage characteristics of an air-cooled PEMFC stack and applies a scheduled PI control strategy targeting experimentally identified hotspot locations using multipoint temperature sensors to enhance thermal stability. Three cooling configurations including single large fan, dual small fans, and quad small fans were experimentally evaluated in terms of stack voltage performance, fan energy consumption, and temperature distribution. Quantitative assessment was conducted using the Cooling Uniformity Index (CUI) and Hotspot Severity Index (HSI). The results demonstrate that the single large fan provides the most stable voltage performance and superior hotspot suppression under high-load conditions, whereas the quad small fans configuration exhibits the highest cooling efficiency in terms of average temperature reduction and fan power consumption. In contrast, the dual small fans configuration does not present any significant advantage in either thermal stability or energy efficiency.</p>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fuce.70100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental Study on Cooling Uniformity and Hotspot Suppression Characteristics of Air-Cooled PEMFC With Fan Configuration 风机配置的风冷PEMFC冷却均匀性及热点抑制特性实验研究

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-10 DOI: 10.1002/fuce.70100

Sanghyun Yun, Jinwon Yun, Jaeyoung Han

{"title":"Experimental Study on Cooling Uniformity and Hotspot Suppression Characteristics of Air-Cooled PEMFC With Fan Configuration","authors":"Sanghyun Yun, Jinwon Yun, Jaeyoung Han","doi":"10.1002/fuce.70100","DOIUrl":"https://doi.org/10.1002/fuce.70100","url":null,"abstract":"<p>Air-cooled polymer electrolyte membrane fuel cells (PEMFCs) offer structural simplicity and advantages in compact system design; however, nonuniform thermal management induced by fan-based cooling can lead to hotspot formation, resulting in increased membrane resistance, performance degradation, and reduced durability. In particular, variations in airflow characteristics caused by different fan configurations directly influence stack temperature distribution and voltage stability, indicating the necessity for systematic experimental and quantitative investigation. Accordingly, this study derives a critical operating temperature based on the temperature–voltage characteristics of an air-cooled PEMFC stack and applies a scheduled PI control strategy targeting experimentally identified hotspot locations using multipoint temperature sensors to enhance thermal stability. Three cooling configurations including single large fan, dual small fans, and quad small fans were experimentally evaluated in terms of stack voltage performance, fan energy consumption, and temperature distribution. Quantitative assessment was conducted using the Cooling Uniformity Index (CUI) and Hotspot Severity Index (HSI). The results demonstrate that the single large fan provides the most stable voltage performance and superior hotspot suppression under high-load conditions, whereas the quad small fans configuration exhibits the highest cooling efficiency in terms of average temperature reduction and fan power consumption. In contrast, the dual small fans configuration does not present any significant advantage in either thermal stability or energy efficiency.</p>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fuce.70100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148238006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Bioelectricity Generation From High-Strength Industrial Wastewaters via Microbial Fuel Cells 利用微生物燃料电池从高强度工业废水中比较生物发电

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-10 DOI: 10.1002/fuce.70120

İdris Biryol, Azize Ayol

{"title":"Comparative Bioelectricity Generation From High-Strength Industrial Wastewaters via Microbial Fuel Cells","authors":"İdris Biryol, Azize Ayol","doi":"10.1002/fuce.70120","DOIUrl":"https://doi.org/10.1002/fuce.70120","url":null,"abstract":"<div>\u0000 \u0000 <p>Microbial fuel cells (MFCs) represent a dual-purpose technology capable of treating high-strength industrial wastewaters while generating renewable electricity. This study compared the performance of dual-chamber MFCs equipped with titanium and graphite electrodes using five industrial effluents: olive mill wastewater, landfill leachate, slaughterhouse wastewater, yeast industry effluent, and municipal wastewater. The results demonstrated that electrode material and substrate type significantly influenced system performance. Graphite-based MFCs consistently outperformed titanium systems, achieving up to 93% chemical oxygen demand (COD) removal and a maximum power density of 30 mW/m<sup>2</sup> with yeast industry effluent. Slaughterhouse wastewater also exhibited strong bioelectrochemical activity, whereas olive mill wastewater and landfill leachate showed limited performance due to inhibitory compounds. Microbial community analysis revealed that Clostridia are key fermentative bacteria, whereas Gammaproteobacteria play a dominant role in extracellular electron transfer. In addition, SEM–EDS analysis indicated that mineral scaling was a critical factor affecting electrode performance, especially in calcium-rich wastewaters. The findings highlight the importance of optimizing electrode materials, substrate selection, and biofilm-electrode interactions for improving MFC efficiency. Overall, the study demonstrates that graphite-based MFC systems have strong potential for integration into industrial wastewater treatment processes, contributing to sustainable resource recovery and decentralized energy production.</p>\u0000 </div>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148238007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Bioelectricity Generation From High-Strength Industrial Wastewaters via Microbial Fuel Cells 利用微生物燃料电池从高强度工业废水中比较生物发电

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-10 DOI: 10.1002/fuce.70120

İdris Biryol, Azize Ayol

{"title":"Comparative Bioelectricity Generation From High-Strength Industrial Wastewaters via Microbial Fuel Cells","authors":"İdris Biryol, Azize Ayol","doi":"10.1002/fuce.70120","DOIUrl":"https://doi.org/10.1002/fuce.70120","url":null,"abstract":"<div>\u0000 \u0000 <p>Microbial fuel cells (MFCs) represent a dual-purpose technology capable of treating high-strength industrial wastewaters while generating renewable electricity. This study compared the performance of dual-chamber MFCs equipped with titanium and graphite electrodes using five industrial effluents: olive mill wastewater, landfill leachate, slaughterhouse wastewater, yeast industry effluent, and municipal wastewater. The results demonstrated that electrode material and substrate type significantly influenced system performance. Graphite-based MFCs consistently outperformed titanium systems, achieving up to 93% chemical oxygen demand (COD) removal and a maximum power density of 30 mW/m<sup>2</sup> with yeast industry effluent. Slaughterhouse wastewater also exhibited strong bioelectrochemical activity, whereas olive mill wastewater and landfill leachate showed limited performance due to inhibitory compounds. Microbial community analysis revealed that Clostridia are key fermentative bacteria, whereas Gammaproteobacteria play a dominant role in extracellular electron transfer. In addition, SEM–EDS analysis indicated that mineral scaling was a critical factor affecting electrode performance, especially in calcium-rich wastewaters. The findings highlight the importance of optimizing electrode materials, substrate selection, and biofilm-electrode interactions for improving MFC efficiency. Overall, the study demonstrates that graphite-based MFC systems have strong potential for integration into industrial wastewater treatment processes, contributing to sustainable resource recovery and decentralized energy production.</p>\u0000 </div>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148238008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Degradation Prediction of Proton-Exchange Membrane Fuel Cell Tested Under Static and Quasi-Dynamic Operating Conditions 静态和准动态工况下质子交换膜燃料电池的降解预测

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-07 DOI: 10.1002/fuce.70116

Matthew Georgio Dekkers, Marcia L. Baptista, Helmut Prendinger

{"title":"Degradation Prediction of Proton-Exchange Membrane Fuel Cell Tested Under Static and Quasi-Dynamic Operating Conditions","authors":"Matthew Georgio Dekkers, Marcia L. Baptista, Helmut Prendinger","doi":"10.1002/fuce.70116","DOIUrl":"https://doi.org/10.1002/fuce.70116","url":null,"abstract":"<p>The viability and extended lifetime of proton-exchange membrane (PEM) fuel cells are essential to enable hydrogen electric aviation. Their reliability, that is, the ability to maintain stable performance over long operational periods under varying environmental and load conditions, is a critical factor for their adoption in aviation systems. Prognostics and Health Management (PHM) is a popular strategy used extensively in aero engines. This data-driven approach is used to estimate the best maintenance times and to prevent utilisation of equipment beyond its end-of-life. Despite being considerably well established in classical aeronautics, PHM is not yet mature for PEM fuel cells. Currently PHM for PEM fuel cells face three technical problems: (1) reliance on multi-sensor datasets that limit applicability when only voltage and current measurements are available, (2) short-term prediction windows of typically below 100 h, and (3) limited linkage between physics models and machine learning models for RUL predictions. This study presents a hybrid long short-term memory (LSTM) and echo state network (ESN) framework to address gaps (1) and (2) under static and quasi-dynamic conditions. Using seasonal and trend decomposition using LOESS (STL), voltage and current are separated into components, enabling medium-term prediction up to 125 h. Existing membrane degradation models are utilised to establish a foundation for future linkage with a machine learning model to improve remaining useful life (RUL) predictions. Our results suggest that the hybrid LSTM–ESN framework enables 125-h degradation predictions using only voltage and current measurements.</p>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fuce.70116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Degradation Prediction of Proton-Exchange Membrane Fuel Cell Tested Under Static and Quasi-Dynamic Operating Conditions 静态和准动态工况下质子交换膜燃料电池的降解预测

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-07 DOI: 10.1002/fuce.70116

Matthew Georgio Dekkers, Marcia L. Baptista, Helmut Prendinger

{"title":"Degradation Prediction of Proton-Exchange Membrane Fuel Cell Tested Under Static and Quasi-Dynamic Operating Conditions","authors":"Matthew Georgio Dekkers, Marcia L. Baptista, Helmut Prendinger","doi":"10.1002/fuce.70116","DOIUrl":"https://doi.org/10.1002/fuce.70116","url":null,"abstract":"<p>The viability and extended lifetime of proton-exchange membrane (PEM) fuel cells are essential to enable hydrogen electric aviation. Their reliability, that is, the ability to maintain stable performance over long operational periods under varying environmental and load conditions, is a critical factor for their adoption in aviation systems. Prognostics and Health Management (PHM) is a popular strategy used extensively in aero engines. This data-driven approach is used to estimate the best maintenance times and to prevent utilisation of equipment beyond its end-of-life. Despite being considerably well established in classical aeronautics, PHM is not yet mature for PEM fuel cells. Currently PHM for PEM fuel cells face three technical problems: (1) reliance on multi-sensor datasets that limit applicability when only voltage and current measurements are available, (2) short-term prediction windows of typically below 100 h, and (3) limited linkage between physics models and machine learning models for RUL predictions. This study presents a hybrid long short-term memory (LSTM) and echo state network (ESN) framework to address gaps (1) and (2) under static and quasi-dynamic conditions. Using seasonal and trend decomposition using LOESS (STL), voltage and current are separated into components, enabling medium-term prediction up to 125 h. Existing membrane degradation models are utilised to establish a foundation for future linkage with a machine learning model to improve remaining useful life (RUL) predictions. Our results suggest that the hybrid LSTM–ESN framework enables 125-h degradation predictions using only voltage and current measurements.</p>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/fuce.70116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring a Solid Acid Fuel Cell for Direct Conversion of Ammonia 探索一种用于氨直接转化的固体酸燃料电池

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-07 DOI: 10.1002/fuce.70119

Den Harvey Balboa, Jason G. Chen, Andrew C. Chien, Denny Y. Kuo, Leo H. Yi

引用次数: 0

Exploring a Solid Acid Fuel Cell for Direct Conversion of Ammonia 探索一种用于氨直接转化的固体酸燃料电池

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-07 DOI: 10.1002/fuce.70119

Den Harvey Balboa, Jason G. Chen, Andrew C. Chien, Denny Y. Kuo, Leo H. Yi

引用次数: 0

Engineering a Low-Cost and Sustainable Electrochemical Cell Using Sericin as a Bio-Electrolyte 利用丝胶蛋白作为生物电解质设计一种低成本、可持续的电化学电池

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-03 DOI: 10.1002/fuce.70117

Prajwal Battampara, Nandhini Dhanavel, Narendra Reddy, Pornanong Aramwit

{"title":"Engineering a Low-Cost and Sustainable Electrochemical Cell Using Sericin as a Bio-Electrolyte","authors":"Prajwal Battampara, Nandhini Dhanavel, Narendra Reddy, Pornanong Aramwit","doi":"10.1002/fuce.70117","DOIUrl":"https://doi.org/10.1002/fuce.70117","url":null,"abstract":"<div>\u0000 \u0000 <p>Sericin, a water-soluble protein derived as a byproduct of silk processing, was investigated as a bio electrolyte in a single chambered cell. As a byproduct of silk processing, sericin is a natural, biodegradable, and sustainable biopolymer. Sericin extracted from <i>Bombyx mori</i> cocoons was dispersed in water at concentrations ranging from 0.5% to 8% and the homogeneous solution was used as an electrolyte with graphite serving as both cathode and anode. The performance of the electrolyte (sericin) in the electrochemical cell (SEC) was evaluated by varying the applied voltage, charging time, and electrolyte concentration. Further, the ability of the electrolyte to store and release electrical energy was studied. Sericin contains both positively and negatively charged amino acids and exhibited a maximum voltage retention of 2.8 V. The performance of the SEC was strongly dependent on the operating parameters, particularly sericin concentration and applied voltage. A sericin concentration of 2% and applied voltage of 15 V for 60 min provided the maximum potential. A maximum discharge time of approximately 7 min was obtained when the SEC was fully charged and connected to a standard LED (forward voltage ∼1.8–2 V, current ∼20 mA). Electrochemical studies confirmed that the performance of the battery was mainly dependent on the sericin concentration, attributed to ionizable amino acid residues that facilitate ionic conduction through hydrogen-bonded networks within the protein matrix. The SEC could be charged and discharged multiple times without loss of potential. In addition, ionic properties of the SEC were investigated using impedance studies, dielectric analysis, and transport number measurements. Sericin-based electrochemical systems show promise as sustainable energy sources for low powered electronics, such as medical devices and personal care devices.</p>\u0000 </div>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Voltage Stability Enhancement in DFIG Systems Through IOT-Based Adaptive Control Using Neural Network Technique 基于物联网的神经网络自适应控制增强DFIG系统电压稳定性

IF 3.1 4区工程技术

Fuel Cells Pub Date : 2026-06-03 DOI: 10.1002/fuce.70112

Angala Parameswari G., Arunsankar G.

{"title":"Voltage Stability Enhancement in DFIG Systems Through IOT-Based Adaptive Control Using Neural Network Technique","authors":"Angala Parameswari G., Arunsankar G.","doi":"10.1002/fuce.70112","DOIUrl":"https://doi.org/10.1002/fuce.70112","url":null,"abstract":"<div>\u0000 \u0000 <p>Doubly fed induction generator (DFIG) systems can enhance voltage stability through Internet of Things (IoT)-based monitoring and control, enabling effective analysis and proactive grid management. However, voltage stability in DFIG systems with IoT can be affected by communication delays that slow control actions, reducing the effectiveness of voltage regulation. This manuscript presents a novel framework for voltage stability enhancement in DFIG systems through IoT-based adaptive control. The proposed method integrates the capabilities of logarithmic differential convolutional neural network (LDCNN) with a reindeer cyclone optimization (RCO) algorithm, forming a model termed LDCNN–RCO. The primary goals of the proposed technique are to maximize efficiency, develop system stability, develop forecasting accuracy, and minimize estimation errors. LDCNN is employed to forecast the dynamic behavior of DFIG-driven wind turbines (WTs) throughout voltage dips, whereas RCO optimizes the distribution of reactive power. The proposed method demonstrates better performance than existing techniques, including Tasmanian devil optimization algorithm with multiresolution sinusoidal neural network (MSNN–TDO), artificial neural network (ANN), and sparrow search algorithm (SSA), as evaluated and compared using the MATLAB platform. The proposed technique achieves a lower torque ripple of 0.13%, response time of 1 ms, and higher accuracy of 99.3%, along with a higher computational efficiency of 97%, indicating superior performance and effectiveness compared to existing methods. The proposed LDCNN–RCO framework significantly enhances voltage stability and control efficiency in DFIG systems, outperforming existing methods in accuracy and response time.</p>\u0000 </div>","PeriodicalId":12566,"journal":{"name":"Fuel Cells","volume":"26 3","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0