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Digital archive of theses discussed at the University of Pisa

 

Thesis etd-01102014-102320


Thesis type
Tesi di dottorato di ricerca
Author
BERTEI, ANTONIO
email address
antonio.bertei@for.unipi.it
URN
etd-01102014-102320
Thesis title
Mathematical Modeling of Solid Oxide Fuel Cells
Academic discipline
ING-IND/25
Course of study
INGEGNERIA
Supervisors
tutor Prof. Nicolella, Cristiano
commissario Prof. Peppley, Brant
commissario Prof. Canu, Paolo
Keywords
  • electrochemistry
  • multi-scale modeling
  • packing algorithm
  • porous media
  • SOFC
Graduation session start date
10/02/2014
Availability
Full
Summary
In this thesis, an integrated microstructural–electrochemical modeling framework for Solid Oxide Fuel Cells (SOFCs) is presented. At the microscale, the model numerically reconstructs the microstructure of the electrodes, which are random porous composite media wherein the electrochemical reactions occur. The effective properties of the electrodes are evaluated in the reconstructed microstructures and used, as input parameters, in physically–based electrochemical models, consisting of mass and charge balances written in continuum approach, which describe the transport and reaction phenomena at the mesoscale within the cell. Therefore, the strong coupling between microstructural characteristics and electrochemical processes can be conveniently taken into account by the integrated model.
The presented modeling framework represents a tool to fulfill a from–powder–to–power approach: it is able to reproduce and predict the SOFC macroscopic response, such as the current–voltage relationship, knowing only the powder characteristics and the operating conditions, which are the same measurable and controllable parameters available in reality. As a consequence, empirical, fitted or adjustable parameters are not required, feature which makes the model fully predictive and widely applicable in a broad range of conditions and fuel cell configurations as an interpretative tool of experimental data and as a design tool to optimize the system performance.
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