Seven-parameter PEMFC model optimization using an battlefield optimization algorithm

Seven-parameter PEMFC model optimization using an battlefield optimization algorithm

Precise modeling of Proton Exchange Membrane Fuel Cells (PEMFCs) requires accurate identification of key parameters, which are often unavailable from manufacturers but crucial for predicting fuel cell performance. The system relies on seven key parameters to determine activation and ohmic and concen...

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Bibliographic Details
Main Authors: Manish Kumar Singla, S.A. Muhammed Ali, Jyoti Gupta, Pradeep Jangir, Arpita, Ramesh Kumar, Reena Jangid, Mohammad Khishe
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Electrochemistry Communications
Subjects:
Machine learning
Optimization
Fuel cell
Parameter estimation
Run time
Friedman ranking test
Online Access:http://www.sciencedirect.com/science/article/pii/S1388248125001730
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Summary:Precise modeling of Proton Exchange Membrane Fuel Cells (PEMFCs) requires accurate identification of key parameters, which are often unavailable from manufacturers but crucial for predicting fuel cell performance. The system relies on seven key parameters to determine activation and ohmic and concentration overpotential values through ξ1, ξ2, ξ3, ξ4, λ, Rc, and β. The Battlefield Optimization Algorithm (BfOA) represents a new optimization method that finds these seven essential PEMFC parameters effectively. Using Sum Squared Error (SSE) to minimize the difference between estimated and actual cell voltages, BfOA outperformed other optimization algorithms in determining parameters for six PEMFC models under varying operating conditions. The optimized parameters enabled accurate prediction of I-V and PV curves, closely matching experimental data. BfOA's efficiency and robustness make it well-.suited for real-time fuel cell modeling. Its effectiveness as a method for precise PEMFC device analysis within electronic component simulators is demonstrated. Future development will explore BfOA's compatibility with other fuel cell technologies, incorporate real-time data capabilities, and implement the algorithm in embedded systems for real-time PEMFC monitoring and control.
ISSN:1388-2481

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