Modeling, Validation, and Operational Variables Optimization of a Solid Oxide Fuel Cell.

Area of Science:

• Electrochemistry
• Thermodynamics
• Energy Conversion

Background:

• Solid oxide fuel cells (SOFCs) are advanced energy conversion devices with high electrical efficiency (>50%) and low pollutant emissions.
• Their applications span stationary power generation, aviation, and hybrid systems for hydrogen and electricity production.

Purpose of the Study:

• To develop and utilize a thermodynamic lumped model for SOFCs to determine voltage-current density characteristics.
• To employ heuristic and deterministic optimization algorithms to identify key operational variables for maximum single-cell power output.
• To provide a detailed analysis of overpotential transport, particularly concentration overpotential, and its calculation.

Main Methods:

• A thermodynamics lumped model was used to simulate SOFC performance.
• Heuristic and deterministic optimization algorithms were applied to find optimal operating parameters.
• The Butler-Volmer equation was solved using an implicit method for enhanced accuracy.
• Physical and chemical phenomena were linked to modeling variables for comprehensive analysis.

Main Results:

• Higher operating pressures and temperatures were found to significantly improve SOFC power output.
• Both heuristic and deterministic optimization algorithms yielded comparable results for maximum power.
• The model successfully estimated key operating variables and assessed parameter influence on performance.

Conclusions:

• The developed SOFC model enables efficient operation within hybrid systems.
• The study provides a method for estimating critical operating variables and understanding parameter impacts.
• Optimized SOFC operation can be achieved through advanced modeling and algorithmic approaches.