Xuqian Yan
University of Oldenburg | Siemens Energy
will give a presentation titled
Data-driven state-of-health quantification for industrial
proton exchange membrane (PEM) water electrolyzer fleet
as part of her intended dissertation.
The presentation will take place in a hybrid format:
OFFIS F02, Escherweg 2 and https://meeting.uol.de/b/seb-vqb-mms

Abstract
Proton exchange membrane (PEM) water electrolysis is a hydrogen (H2) generation
technology that uses electricity to split water molecules electrochemically into H2 and oxygen.
The produced H2 can be further used as feedstock for industries or for energy storage.
Due to the high manufacturing cost and short lifetime, PEM water electrolyzers require
rigorous state-of-health monitoring to maximize their operating efficiency and availability.
While voltage is commonly used as a state-of-health indicator, its effectiveness is
compromised in industrial settings due to diverse operating conditions.
This research aims to develop data-driven algorithms to quantify the state-of-health for PEM
electrolyzers. One highlight of this research is the utilization of fleet knowledge to address the
lack of data, which is primarily caused by the limited operation range.
As part of the flagship project H2GIGA, Siemens Energy has provided operational data from
MW-scale industrial PEM electrolyzers with 1 to 3 years of operation history. Two fleet-based
state-of-health quantification algorithms have been developed based on this data and will be
presented in this colloquium.
Supervisor: Prof. Dr. Astrid Nieße