Advanced modeling and parameter estimation of PEM fuel cells using the g-function and self-adaptive differential evolution algorithm
Martin Ćalasan, Snežana Vujošević, Mihailo Micev, Shady H E Abdel Aleem, Brian Azzopardi · 2025
Read Advanced modeling and parameter estimation of PEM fuel cells using the g-function and self-adaptive differential evolution algorithm by Martin Ćalasan, Snežana Vujošević, Mihailo Micev, Shady H E Abdel Aleem, Brian Azzopardi (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12722225.txt.
Description
Martin Ćalasan and four co-authors present a 2025 study on modeling fuel cells that run on a proton exchange membrane. These cells are efficient and flexible, serving uses from small devices to power grids. Good models of their voltage and current behavior matter, above all for control systems, which need current written as a function of voltage.
The team builds its model on a math function first used for solar cells, chosen because it stays stable where the classic function fails. They pair it with a self-tuning search method to fit the model settings. Tests on three real fuel cell systems, from three makers, showed steady gains over rival methods in error scores. A sensitivity check then weighed how each setting moves the fit.
Catalog record
| CREATOR | Martin Ćalasan, Snežana Vujošević, Mihailo Micev, Shady H E Abdel Aleem, Brian Azzopardi |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 77 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |