Researchers from the Faculty of Mechanical Engineering, Laboratory for Internal Combustion Engines and Electromobility have developed innovative diagnostics methodology for proton exchange membrane fuel cells (PEMFC) enabled by the multi-scale modelling framework.
Simultaneous optimization of efficiency and durability of PEMFCs calls for advanced State-of-X (SoX) diagnostics, where SoX abbreviates State-of-Operation-Conditions – SoOC, State-of-Health – SoH and State-of-Function – SoF. Unlike state-of-the-art SoX methods, which rely on externally measurable electric parameters and, hence, provide limited insight into internal states and parameters of the fuel cell, which consequentially limits their diagnostics capabilities, developed diagnostics approach enables virtual insight into PEMFCs. Therefore, developed diagnostics methodology enables novel SoX functionalities through model-based insight into the internal states of PEMFCs and parameters associated with the rate and efficiency of reactions as well as of transport mechanisms using only measured current and voltage as inputs.
Developed SoX diagnostics methodology namely computes intra-fuel cell states in real-time, which means that it enables real-time virtual sensor functionalities representing innovative SoOC diagnostics and digital twin functionality. Likewise, model-based deciphering of parameters associated with the rate and efficiency of reactions as well as of transport mechanisms opens new SoH diagnostics functionalities, while both support innovative SoF functionalities.
To resolve this challenging task, researchers have developed innovative SoX diagnostics method based on a computationally efficient multi-scale simulation framework for PEMFCs, parameter identification techniques and methods for assessing uniqueness of parameter identification, which is published in International Journal of Hydrogen Energy. Proposed state-of-the-art simulation framework incorporates advanced submodel on spatially resolved dynamics of liquid water and newly added submodel considering the impact of the gas crossover effects on mixed potentials.
Results demonstrate capability of the innovative SoX diagnostics methodology to perform detailed diagnostics of internal states of the PEMFC and to pinpoint degradation-imposed variation of parameters which are interlinked with catalyst activity, membrane losses and gas diffusion layer losses. In addition, developed SoX diagnostics methodology is capable to decipher different component specific contributions to the voltage losses. Therefore, developed methodology opens new horizons in model-based diagnostics of fuel cells and it represents a key enabler for advanced fault detection and isolation methods that will open new perspectives also in the area of fault mitigation strategies.
Authors of the image: Andraž Kravos, Tomaž Katrašnik, and Jon Hauptman