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| Home > Publications database > Dynamic Degradation Modeling in PEM-Electrolysis. Utilizing Surrogate Models for Quantifying and Forecasting the State-of-health of a PEM-Electrolytic Cell. |
| Home > Publications database > Dynamic Degradation Modeling in PEM-Electrolysis. Utilizing Surrogate Models for Quantifying and Forecasting the State-of-health of a PEM-Electrolytic Cell. |
| Talk (non-conference) (Other) | FZJ-2024-05923 |
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2024
Abstract: Addressing, understanding and furthermore predicting ongoing degradation phenomena during the operation and thereby the current state-of-health is crucial for improving the overall performance and reliability of PEM electrolytic cells (PEMECs) in large-scale hydrogen production. This first progress presentation of my PhD formulates a framework for developing a dynamic surrogate model in 1D and 2D which will assist in quantifying and also forecasting this state-of-health of a PEMEC in operation. Challenges are the development of a suitable dynamic physics-based model on the macroscale cell level, the embedding of existing degradation submodels, and the setup of an efficient workflow for the data curation to finally train and test the dynamic surrogate model.
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