Reliability modelling of equipment engaged in the production (electrolysers) and usage of hydrogen

This project aims to improve reliability and reduce degradation in equipment engaged in the production (electrolysers) and usage of hydrogen. Highly reliable and long-lasting systems are essential for the successful uptake and deployment of novel technologies. The release of an unreliable product can undermine the success of an otherwise promising technology. Despite electrolysers and users of hydrogen forming a technology cornerstone of a green hydrogen economy, there is very little research on their reliability at both the cell and system level.
This project will use advanced reliability techniques to establish reliability and degradation models equipment engaged in the production (electrolysers) and usage of hydrogen. These models will be used to examine the reliability of these systems, establishing key routes to failure and preventative action required to mitigate risk and reduce downtime.
The research will also establish new methodologies for assessing reliability, utilising the hybridisation of deterministic physics-based models with stochastic coloured petri nets. These will be augmented with machine learning methods to give capability for predicting lifetime in different applications. Models will be validated at the cell level through experiments and at the system level through data sharing and literature data. Novel experimental strategies for degrading cell/system performance to enable accurate reliability prediction will be investigated. This experimental framework will be transferable across applications yielding a 'system level' capability across platforms.
Deliverables
-Production of open-source experimental degradation dataset of equipment, engaged in the production (electrolysers) and usage of hydrogen at lab scale.
-Open-source reliability model equipment engaged in the production (electrolysers) and usage of hydrogen