As a high efficiency hydrogen-to-power device,proton exchange membrane fuel cell(PEMFC)attracts much attention,especially for the automotive applications.Real-time prediction of output voltage and area specific resist...As a high efficiency hydrogen-to-power device,proton exchange membrane fuel cell(PEMFC)attracts much attention,especially for the automotive applications.Real-time prediction of output voltage and area specific resistance(ASR)via the on-board model is critical to monitor the health state of the automotive PEMFC stack.In this study,we use a transient PEMFC system model for dynamic process simulation of PEMFC to generate the dataset,and a long short-term memory(LSTM)deep learning model is developed to predict the dynamic per-formance of PEMFC.The results show that the developed LSTM deep learning model has much better perfor-mance than other models.A sensitivity analysis on the input features is performed,and three insensitive features are removed,that could slightly improve the prediction accuracy and significantly reduce the data volume.The neural structure,sequence duration,and sampling frequency are optimized.We find that the optimal sequence data duration for predicting ASR is 5 s or 20 s,and that for predicting output voltage is 40 s.The sampling frequency can be reduced from 10 Hz to 0.5 Hz and 0.25 Hz,which slightly affects the prediction accuracy,but obviously reduces the data volume and computation amount.展开更多
The catalyst layers(CLs) electrode is the key component of the membrane electrode assembly(MEA) in proton exchange membrane fuel cells(PEMFCs). Conventional electrodes for PEMFCs are composed of carbon-supported, iono...The catalyst layers(CLs) electrode is the key component of the membrane electrode assembly(MEA) in proton exchange membrane fuel cells(PEMFCs). Conventional electrodes for PEMFCs are composed of carbon-supported, ionomer, and Pt nanoparticles, all immersed together and sprayed with a micron-level thickness of CLs. They have a performance trade-off where increasing the Pt loading leads to higher performance of abundant triple-phase boundary areas but increases the electrode cost. Major challenges must be overcome before realizing its wide commercialization. Literature research revealed that it is impossible to achieve performance and durability targets with only high-performance catalysts, so the controllable design of CLs architecture in MEAs for PEMFCs must now be the top priority to meet industry goals. From this perspective, a 3D ordered electrode circumvents this issue with a support-free architecture and ultrathin thickness while reducing noble metal Pt loadings. Herein, we discuss the motivation in-depth and summarize the necessary CLs structural features for designing ultralow Pt loading electrodes. Critical issues that remain in progress for 3D ordered CLs must be studied and characterized. Furthermore, approaches for 3D ordered CLs architecture electrode development, involving material design, structure optimization, preparation technology, and characterization techniques, are summarized and are expected to be next-generation CLs for PEMFCs. Finally, the review concludes with perspectives on possible research directions of CL architecture to address the significant challenges in the future.展开更多
To investigate the influences of co-flowand counter-flowmodes of reactant flowarrangement on a proton exchange membrane fuel cell(PEMFC)during start-up,unsteady physical and mathematical models fully coupling the flow...To investigate the influences of co-flowand counter-flowmodes of reactant flowarrangement on a proton exchange membrane fuel cell(PEMFC)during start-up,unsteady physical and mathematical models fully coupling the flow,heat,and electrochemical reactions in a PEMFC are established.The continuity equation and momentum equation are solved by handling pressure-velocity coupling using the SIMPLE algorithm.The electrochemical reaction rates in the catalyst layers(CLs)of the cathode and anode are calculated using the Butler-Volmer equation.The multiphase mixture model describes the multiphase transport process of gas mixtures and liquid water in the fuel cell.After validation,the influences of co-flow and counter-flow modes on the PEMFC performance are investigated,including the evolution of the current density,flow field,temperature field,and reactant concentration field during start-up,as well as the steady distribution of the current density,reactant concentration,andmembrane water content when the start-up stabilizes.Co-flow and counter-flow modes influence the current density distribution and temperature distribution.On the one hand,the co-flow mode accelerates the start-up process of the PEMFC and leads to a more evenly distributed current density than the counter-flow mode.On the other hand,the temperature difference between the inlet and outlet sections of the cell is up to 10.1℃ under the co-flow mode,much larger than the 5.0℃ observed in the counter-flow mode.Accordingly,the counter-flowmode results in a more evenly distributed temperature and a lower maximum temperature than the co-flow case.Therefore,in the flow field design of a PEMFC,the reactant flow arrangements can be considered to weigh between better heat management and higher current density distribution of the cell.展开更多
The electrical and thermal performances of a simulated 60 kW Proton Exchange Membrane Fuel Cell (PEMFC) cogeneration system are first analyzed and then strategies to make the system operation stable and efficient are ...The electrical and thermal performances of a simulated 60 kW Proton Exchange Membrane Fuel Cell (PEMFC) cogeneration system are first analyzed and then strategies to make the system operation stable and efficient are developed. The system configuration is described first, and then the power response and coordination strategy are presented on the basis of the electricity model. Two different thermal models are used to estimate the thermal performance of this cogeneration system, and heat management is discussed. Based on these system designs, the 60 kW PEMFC cogeneration system is analyzed in detail. The analysis results will be useful for further study and development of the system.展开更多
基金This research is supported by the National Natural Science Founda-tion of China(No.52176196)the National Key Research and Devel-opment Program of China(No.2022YFE0103100)+1 种基金the China Postdoctoral Science Foundation(No.2021TQ0235)the Hong Kong Scholars Program(No.XJ2021033).
文摘As a high efficiency hydrogen-to-power device,proton exchange membrane fuel cell(PEMFC)attracts much attention,especially for the automotive applications.Real-time prediction of output voltage and area specific resistance(ASR)via the on-board model is critical to monitor the health state of the automotive PEMFC stack.In this study,we use a transient PEMFC system model for dynamic process simulation of PEMFC to generate the dataset,and a long short-term memory(LSTM)deep learning model is developed to predict the dynamic per-formance of PEMFC.The results show that the developed LSTM deep learning model has much better perfor-mance than other models.A sensitivity analysis on the input features is performed,and three insensitive features are removed,that could slightly improve the prediction accuracy and significantly reduce the data volume.The neural structure,sequence duration,and sampling frequency are optimized.We find that the optimal sequence data duration for predicting ASR is 5 s or 20 s,and that for predicting output voltage is 40 s.The sampling frequency can be reduced from 10 Hz to 0.5 Hz and 0.25 Hz,which slightly affects the prediction accuracy,but obviously reduces the data volume and computation amount.
基金funded by the Natural Science Foundation of Shandong Province, China (ZR2023MB049)the China Postdoctoral Science Foundation (2020M670483)the Science Foundation of Weifang University (2023BS11)。
文摘The catalyst layers(CLs) electrode is the key component of the membrane electrode assembly(MEA) in proton exchange membrane fuel cells(PEMFCs). Conventional electrodes for PEMFCs are composed of carbon-supported, ionomer, and Pt nanoparticles, all immersed together and sprayed with a micron-level thickness of CLs. They have a performance trade-off where increasing the Pt loading leads to higher performance of abundant triple-phase boundary areas but increases the electrode cost. Major challenges must be overcome before realizing its wide commercialization. Literature research revealed that it is impossible to achieve performance and durability targets with only high-performance catalysts, so the controllable design of CLs architecture in MEAs for PEMFCs must now be the top priority to meet industry goals. From this perspective, a 3D ordered electrode circumvents this issue with a support-free architecture and ultrathin thickness while reducing noble metal Pt loadings. Herein, we discuss the motivation in-depth and summarize the necessary CLs structural features for designing ultralow Pt loading electrodes. Critical issues that remain in progress for 3D ordered CLs must be studied and characterized. Furthermore, approaches for 3D ordered CLs architecture electrode development, involving material design, structure optimization, preparation technology, and characterization techniques, are summarized and are expected to be next-generation CLs for PEMFCs. Finally, the review concludes with perspectives on possible research directions of CL architecture to address the significant challenges in the future.
基金supported by the Projects of Talents Recruitment of Guangdong University of Petrochemical Technology(No.2018rc14)Maoming City Science and Technology Plan Project(Nos.210427094551264 and 220415004552411).
文摘To investigate the influences of co-flowand counter-flowmodes of reactant flowarrangement on a proton exchange membrane fuel cell(PEMFC)during start-up,unsteady physical and mathematical models fully coupling the flow,heat,and electrochemical reactions in a PEMFC are established.The continuity equation and momentum equation are solved by handling pressure-velocity coupling using the SIMPLE algorithm.The electrochemical reaction rates in the catalyst layers(CLs)of the cathode and anode are calculated using the Butler-Volmer equation.The multiphase mixture model describes the multiphase transport process of gas mixtures and liquid water in the fuel cell.After validation,the influences of co-flow and counter-flow modes on the PEMFC performance are investigated,including the evolution of the current density,flow field,temperature field,and reactant concentration field during start-up,as well as the steady distribution of the current density,reactant concentration,andmembrane water content when the start-up stabilizes.Co-flow and counter-flow modes influence the current density distribution and temperature distribution.On the one hand,the co-flow mode accelerates the start-up process of the PEMFC and leads to a more evenly distributed current density than the counter-flow mode.On the other hand,the temperature difference between the inlet and outlet sections of the cell is up to 10.1℃ under the co-flow mode,much larger than the 5.0℃ observed in the counter-flow mode.Accordingly,the counter-flowmode results in a more evenly distributed temperature and a lower maximum temperature than the co-flow case.Therefore,in the flow field design of a PEMFC,the reactant flow arrangements can be considered to weigh between better heat management and higher current density distribution of the cell.
基金Project (No. 2002AA517020) supported by the Hi-Tech Researchand Development Program (863) of China
文摘The electrical and thermal performances of a simulated 60 kW Proton Exchange Membrane Fuel Cell (PEMFC) cogeneration system are first analyzed and then strategies to make the system operation stable and efficient are developed. The system configuration is described first, and then the power response and coordination strategy are presented on the basis of the electricity model. Two different thermal models are used to estimate the thermal performance of this cogeneration system, and heat management is discussed. Based on these system designs, the 60 kW PEMFC cogeneration system is analyzed in detail. The analysis results will be useful for further study and development of the system.
