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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Thermodynamically based reduced dimensionality proton exchange membrane fuel cell model for observer based monitoring and control</dc:title><dc:creator>Kravos,	Andraž	(Avtor)
	</dc:creator><dc:creator>Katrašnik,	Tomaž	(Mentor)
	</dc:creator><dc:creator>Hametner,	Christoph	(Komentor)
	</dc:creator><dc:subject>proton exchange membrane fuel cells</dc:subject><dc:subject>thermodynamically consistent models with reduced dimensionality</dc:subject><dc:subject>mechanistic-based liquid water modeling</dc:subject><dc:subject>optimal design of experiments</dc:subject><dc:subject>causal chain of degradation phenomena</dc:subject><dc:subject>coupled performance and degradation</dc:subject><dc:description>This doctoral thesis focuses on modeling and predicting fuel cell performance and degradation. Firstly, a reduced dimensionality model is developed, improving predictability in low current density regions and allowing for efficient determination of fuel cell intrinsic parameters, which can with developed model-based design of experiments methodology be efficiently determined with reduced experimental effort. Furthermore, novel mechanistic-based liquid water model is developed, that addresses critical aspects such as flooding, phase change, and two-phase transport in all fuel cell regions. When applied to the existing and newly developed 1D+1D system-level model, it provides a comprehensive understanding of liquid water dynamics, particularly in channels, catalyst, and gas diffusion layers. With real-time readiness and excellent agreement with experimental data, this model demonstrates its applicability in practical scenarios. Additionally, an integrated modelling framework considers causal chain of intertwined degradation mechanisms, providing comprehensive predictions for fuel cell degradation by addressing membrane aging, catalyst layer degradation, platinum migration, and peroxide formation, this framework enhances the understanding of degradation processes. Lastly developed modelling frameworks is used to develop distributed parameter model-based observer algorithm that makes possible, for the first time, to identify spatially resolved two-phase internal states of the fuel cell based only on adequate voltage and current traces.</dc:description><dc:publisher>[A. Kravos] </dc:publisher><dc:date>2023</dc:date><dc:date>2023-10-14 08:30:24</dc:date><dc:type>Doktorsko delo/naloga</dc:type><dc:identifier>151660</dc:identifier><dc:identifier>UDK: 621.352.6:004.942:532.5(043.3)</dc:identifier><dc:identifier>VisID: 257740</dc:identifier><dc:identifier>COBISS_ID: 168972035</dc:identifier><dc:language>sl</dc:language></metadata>
