Zero-dimensional process simulation model of an anion exchange membrane water electrolyzer system
Publication date
2026-05-13
Document type
Forschungsartikel
Author
Organisational unit
Scopus ID
Publisher
Elsevier
Series or journal
Chemical Engineering Journal
ISSN
Periodical volume
539
Article ID
177238
Peer-reviewed
✅
Part of the university bibliography
✅
Language
English
Keyword
Anion exchange membrane
Electrolyzer
Experimental data analysis
Modeling
Process simulation
Waste heat recovery
Water electrolysis
dtec.bw
Abstract
Clean hydrogen is vital for achieving net-zero emissions and reducing carbon output in society. Anion exchange membrane water electrolysis is gaining momentum in the growing electrolyzer market as a means of producing climate-neutral hydrogen when paired with renewable energy sources. Anion exchange membrane water electrolyzers do not rely on precious metals for electrocatalysts and do not require harsh caustic conditions, making them a safe, scalable, efficient, and potentially affordable method for splitting water. This investigation uses a zero-dimensional numerical model to assess the operation of a market-ready anion exchange membrane water electrolyzer and its capacity to generate clean hydrogen and recover waste heat. A commercial electrolyzer rack with four nominal 2.4 kW<inf>el</inf> electrolyzer modules is used to collect experimental data and examine multiple process parameters during dynamic operation from start to steady-state conditions. These include stack temperature, pressure, hydrogen production rate, cell voltage, and current density. The observed average electrolysis efficiencies at the stack and system levels, based on the lower heating value of hydrogen, reach 68.4% and 61.5%, respectively. The recoverability of the generated waste heat at the stack level is approximately 79.4% at 46 °C, providing approximately 340 W<inf>th</inf> of heating power and about 111 W<inf>th</inf> of exergy heating rate per module. The developed model accurately reproduces the dynamic behavior of electrolyzers, showing strong correlations with experimental data, achieving R<sup>2</sup> values of 0.95 or higher across various time-dependent process parameters, and providing new insights into process simulation for system integration, design, and scaling.
Description
This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).
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Published version
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