{"id":12066,"date":"2021-04-01T10:00:00","date_gmt":"2021-04-01T10:00:00","guid":{"rendered":"https:\/\/zbt.de\/projects\/degrad-el3\/"},"modified":"2025-08-19T12:59:24","modified_gmt":"2025-08-19T12:59:24","slug":"degrad-el3","status":"publish","type":"project","link":"https:\/\/zbt.de\/en\/projects\/degrad-el3\/","title":{"rendered":"Degrad-EL3 - Identification of degradation mechanisms in PEMEL, AEL and HTEL electrolysers"},"content":{"rendered":"
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Degrad-EL3 – Identification of degradation mechanisms in PEMEL, AEL and HTEL electrolysers<\/h2>\n

As part of \u2018DEGRAD-EL3-Q\u2019, Fraunhofer IPA is investigating the use of quantum computing methods for the lifetime analysis of electrolysers. The project is part of the H2Giga flagship project, which aims to advance the industrial manufacturing process of electrolysers. The project is investigating various methods of quantum machine learning, including the use of quantum neural networks to solve differential equations. Research is also being conducted into how quantum computing can be used to simulate chemical processes in the context of electrolyser degradation.<\/p>\n

Hydrogen will be one of the main energy sources for the energy transition. For example, hydrogen can be used directly as a fuel for fuel cell vehicles. The chemical element can also be used as a raw material for the production of synthetic fuel, which is needed for the existing fleet of over 60 million vehicles in Germany. Producing the necessary quantities requires high-performance electrolysers in the gigawatt range, which then supply the required hydrogen in a correspondingly smaller power class directly at filling stations. However, the electrolysers must have a long service life in order to be economical.<\/p>\n

As part of the \u2018DEGRAD-EL3-Q\u2019 project, the quantum computing team at Fraunhofer IPA is building on expertise gained from various quantum computing projects, including the use of the \u2018IBM Q System One quantum computer\u2019 installed in an IBM Germany data centre in Ehningen (near Stuttgart).<\/p>\n

On the one hand, the DEGRAD-EL3-Q project aims to investigate the benefits of quantum computers in terms of technology, application scenarios and algorithms relating to the degradation of electrolysers. On the other hand, working with the quantum computer serves to build expertise and increase competitive advantages for industry and science. To this end, the quantum computing team at Fraunhofer IPA is also focusing on methodological development work to improve existing algorithms used in the fields of quantum machine learning and quantum simulation. Quantum computers promise a significant advantage over classical computers, particularly in the field of quantum simulations, i.e. the calculation of atomic and\/or molecular properties. This can be understood intuitively when one considers the fact that quantum computers are themselves quantum systems and thus inherently reflect the underlying physics of quantum mechanics.<\/p>\n

In the DEGRAD-EL3-Q project, Fraunhofer IPA is investigating the extent to which degradation analyses of electrolysers can be usefully supplemented by quantum computing methods and the extent to which quantum computers offer significant advantages over classical computer technologies. The research work is based on three thematic pillars. An important aspect here is modelling and life cycle analysis using advanced machine learning methods. The quantum computing activities focus on the areas of quantum machine learning and quantum simulations, with a constant eye on methodological development work. The service life test data required for modelling is generated and provided by the project partners.<\/p>\n

\u2018DEGRAD-EL3-Q\u2019 is part of the joint project \u2018DEGRAD-EL3 \u2013 Identification of degradation mechanisms & development of methods for predicting the service life of AEL, PEMEL and HTEL\u2019, which in turn is embedded in the H2Giga flagship project. Funding comes from the Federal Ministry of Education and Research and is coordinated by the project management agency J\u00fclich. The aim of the H2Giga lead project is to advance the industrial series production of electrolysers on a gigawatt scale \u2013 and to do so in a technology-neutral manner. Established electrolyser manufacturers, suppliers from various technology sectors, including many small and medium-sized enterprises, as well as various research institutions and universities are pooling their knowledge of electrolyser technologies and working together to advance them.<\/p>\n

Funding code<\/strong>: 03HY110D<\/p>\n

Project duration<\/strong>:
\n01.04.2021 – 31.03.2025<\/p>\n

Project volume<\/strong>:
\n1.5 million<\/p>\n

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Project partners<\/strong>:<\/p>\n

DECHEMA-Forschungsinstitut (DFI)
\nDeutsches Zentrum f\u00fcr Luft- und Raumfahrt (DLR)
\nEurop\u00e4isches Institut f\u00fcr Energieforschung (EIFER)
\nZentrum f\u00fcr BrennstoffzellenTechnik (ZBT)<\/p>\n

Source:
\nhttps:\/\/www.ipa.fraunhofer.de\/de\/referenzprojekte\/Degrad-EL3-Q.html<\/a><\/p>\n

further Information:
\nhttps:\/\/www.wasserstoff-leitprojekte.de\/leitprojekte\/h2giga\/projekte<\/a><\/p>\n<\/div>\n<\/section>\n\n\n

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pAST-EL – Predictive AST Protocols for Alkaline Electrolysis<\/h4>\n

As part of the pAST-EL project, ZBT and DLR are developing predictive stress tests and machine learning models to detect degradation more quickly, predict service life more reliably, and optimise operating strategies for electrolysers.<\/p>\n <\/div>\n

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grELjet<\/h4>\n

As part of the grELjet project, ZBT is collaborating with Fraunhofer ENAS to develop spatially resolved, optimised catalyst layers designed to reduce the iridium requirements of PEM electrolysers and increase their efficiency.<\/p>\n <\/div>\n

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NH3-HRS<\/h4>\n

The NH3-HRS project is developing a compact system that converts ammonia directly into high-purity hydrogen at hydrogen refueling stations.<\/p>\n <\/div>\n

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H2B \u2013 Is Hydrogen the Right Solution for Energy-Intensive SMEs?<\/h4>\n

New Interreg Project H2B Provides Entrepreneurs with Clarity on Hydrogen as an Energy Solution.<\/p>\n <\/div>\n

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