Ageing of electrocatalytic materials is one of the key challenges in sustaining the long-term performance and effectiveness of fuel cells. Experimental approaches of catalytic degradation characterization are often time consuming and require extensive laboratory work. This thesis presents development of innovative rotating disc electrode model for use in virtual sensors for detecting the ageing of catalytic material is presented. The presented model builds upon physically and electrochemically consistent description of processes in RDE, using an analytically supported description of the current field, simplified transport equations, and thermodynamically consistent electrochemical kinetics, it enables reliable separation between kinetic and diffusion contributions of the electrochemical response. The model was validated on experimental data using global optimization algorithm. Furthermore, the possibility of simplifying the model was examined based on an analysis of the Fisher information matrix, with the aim of determining parameter sensitivity and identifiability. The results show that virtual sensor predicts the evolution of polarization curve during catalytic degradation very accurately, as the R-squared value is always greater than 0,99, which enables reliable tracking of performance and aging indicators such as mass activity loss. The model provides a flexible and computationally efficient alternative to experimental characterization as well as opens up the possibility of monitoring catalyst aging within fuel cell in real time.
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