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Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells

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Optimal parameter identification of solid oxide fuel cell using modified fire Hawk algorithm.

Rahul Khajuria¹, Mahipal Bukya², Ravita Lamba³

¹Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, India.

Scientific Reports

|September 28, 2024

Summary

This summary is machine-generated.

A modified fire hawk algorithm (MFHA) accurately identifies solid oxide fuel cell (SOFC) model parameters. This approach enhances SOFC energy system design by providing precise parameter estimation for robust performance.

Keywords:

Modified fire Hawk algorithm Parameter identification Polarization curves Solid oxide fuel cell Statistical analysis

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Area of Science:

Energy Systems Engineering
Computational Science
Electrochemistry

Background:

Accurate mathematical models are crucial for designing robust energy systems incorporating solid oxide fuel cells (SOFCs).
Identifying unknown parameters in SOFC models is essential for reliable performance prediction and system optimization.
Existing methods may lack the efficiency or accuracy required for complex SOFC parameter estimation.

Purpose of the Study:

To propose and evaluate a modified fire hawk algorithm (MFHA) for accurately determining unknown parameters of SOFC mathematical models.
To assess the performance of MFHA in estimating parameters for both a commercial cylindrical SOFC and a 5 kW dynamic stack.
To compare MFHA's effectiveness against the original fire hawk algorithm (FHA) and other established algorithms.

Main Methods:

Development of a modified fire hawk algorithm (MFHA) tailored for SOFC parameter identification.
Application of MFHA to a Siemens cylindrical SOFC model across four different temperatures (1073 K to 1273 K).
Implementation of MFHA for parameter estimation in a 96-cell, 5 kW dynamic SOFC stack under various pressures and temperatures.

Main Results:

MFHA achieved very low sum of squared errors (SSE) for the cylindrical cell, with minimum SSE values as low as 1.03E-05.
For the 5 kW stack, MFHA yielded SSE values in the range of 1.18E-03 to 6.00E-02 across different temperatures and pressures.
MFHA demonstrated superior or comparable performance to existing algorithms in both case studies.

Conclusions:

The modified fire hawk algorithm (MFHA) is a highly accurate and efficient method for identifying unknown parameters in solid oxide fuel cell mathematical models.
MFHA's successful application to diverse SOFC configurations highlights its robustness and potential for improving SOFC energy system design.
The proposed MFHA offers a valuable tool for researchers and engineers working on SOFC modeling and optimization.