The present work of thesis focuses on reversible Solid Oxide Cell (rSOC) modelling through a multiscale approach aiming at performance prediction, considering both the reference initial state and the degradation phenomena. All obtained results have been presented in the framework of two research projects, HERMES (High Efficiency Reversible technologies in fully renewable Multi-Energy System) receiving funds as Project of National Interest and AD ASTRA (HArnessing Degradation mechanisms to prescribe Accelerated Stress Tests for the Realization of SOC lifetime prediction Algorithms) under European Horizon 2020 – Research and Innovation Framework program. Depending on the system scale and the requested phenomenological level, both a lumped-parameter and a higher-level model were developed to forecast the global cell behaviour and the local variations of main physicochemical features on the cell plane respectively. Following a physical based approach, a compromise was reached among a rigorous formulation, effective outcomes and reduced computational efforts, making proposed simulation codes competitive with commercially available tools. Models were applied and validated on several samples, starting from button cell scale until short stack one, referring to two state-of-the-art planar configurations: fuel electrode and electrolyte supported cells. Potentialities and application examples of developed simulation tools were discussed within several case studies, focusing on design, optimization and control of rSOC operation. Careful analysis was devoted, above all, to evaluate degradation effects on global performance, proposing the modelling activity as a key point to reach a better knowledge of occurring phenomena, overcoming experimental constraints.
|Titolo della tesi:||Solid Oxide Cell Modelling|
|Data di discussione:||16-mag-2022|
|Appare nelle tipologie:||Tesi di dottorato|