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001038430 037__ $$aFZJ-2025-01426
001038430 041__ $$aEnglish
001038430 1001_ $$0P:(DE-Juel1)201275$$aAbdollahi, Farideh$$b0
001038430 1112_ $$aHelmholtz AI Conference 2024$$cDusseldorf$$d2024-06-12 - 2024-06-14$$wGermany
001038430 245__ $$aAutonomous Data Analytics for Enhanced Performance and Lifetime Prediction in PEM Fuel Cells and Water Electrolyzers
001038430 260__ $$c2024
001038430 3367_ $$033$$2EndNote$$aConference Paper
001038430 3367_ $$2BibTeX$$aINPROCEEDINGS
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001038430 520__ $$aLongevity is a crucial aspect in evaluating the economic viability of polymer electrolyte fuel cells (PEFCs) in a sustainable energy economy. Making reliable predictions on the performance and lifetime of PEFCs remains challenging due to the complex interplay of processes involved in their operation, including those that drive degradation. The prospects of forecasting PEFC performance with physical models hinges on their completeness in terms of processes accounted for and data available for parameterization. Data-driven models, on the other hand, typically lack the mechanical insight necessary for a deep understanding of degradation causes. We, therefore, pursue the development of a hybrid modeling approach that combines the capabilities of physical models with the agility of data-driven techniques. The aim of this approach is to evaluate the effectiveness of physical models in forecasting performance and to assess their ability for making reliable predictions about performance degradation and lifetime. The combined approach is anticipated to surpass separate physical and data-based models in terms of accuracy, robustness, and interpretability, providing a reliable foundation for identifying maintenance needs and extending the lifespan of PEFCs.
001038430 536__ $$0G:(DE-HGF)POF4-1231$$a1231 - Electrochemistry for Hydrogen (POF4-123)$$cPOF4-123$$fPOF IV$$x0
001038430 65027 $$0V:(DE-MLZ)SciArea-180$$2V:(DE-HGF)$$aMaterials Science$$x0
001038430 7001_ $$0P:(DE-Juel1)181057$$aMalek, Kourosh$$b1
001038430 7001_ $$0P:(DE-Juel1)178966$$aKadyk, Thomas$$b2
001038430 7001_ $$0P:(DE-Juel1)178034$$aEikerling, Michael$$b3$$eCorresponding author
001038430 909CO $$ooai:juser.fz-juelich.de:1038430$$pVDB
001038430 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)201275$$aForschungszentrum Jülich$$b0$$kFZJ
001038430 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)181057$$aForschungszentrum Jülich$$b1$$kFZJ
001038430 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178966$$aForschungszentrum Jülich$$b2$$kFZJ
001038430 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)178034$$aForschungszentrum Jülich$$b3$$kFZJ
001038430 9131_ $$0G:(DE-HGF)POF4-123$$1G:(DE-HGF)POF4-120$$2G:(DE-HGF)POF4-100$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-1231$$aDE-HGF$$bForschungsbereich Energie$$lMaterialien und Technologien für die Energiewende (MTET)$$vChemische Energieträger$$x0
001038430 9141_ $$y2024
001038430 920__ $$lyes
001038430 9201_ $$0I:(DE-Juel1)IET-3-20190226$$kIET-3$$lIET-3$$x0
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