Enhanced hunger games search algorithm that incorporates the marine predator optimization algorithm for optimal extraction of parameters in PEM fuel cells

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 6, 2025

Abstract This article introduces a novel optimization approach to improve the parameter estimation of proton exchange membrane fuel cells (PEMFCs), which are critical for diverse applications but challenging model due their nonlinear behavior. The proposed method, HGS-MPA, enhances Hunger Games Search (HGS) algorithm by integrating Marine Predator Algorithm (MPA) operators, significantly boosting its exploitation capabilities and convergence rate. effectiveness HGS-MPA was validated on three commercial PEMFC datasets: 250-W stack, BCS 500-W, NedStack PS6, using Sum Squared Error (SSE) as performance metric. Experimental results highlight that achieves minimum fitness values 0.33770, 1.31620, 0.01174 respective datasets, outperforming other state-of-the-art algorithms. These findings underscore method’s potential accurate estimation, offering enhanced reliability.

Language: Английский

---

A cooperative strategy-based differential evolution algorithm for robust PEM fuel cell parameter estimation

Ionics, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 2, 2024

Language: Английский

---

Parameters optimization of PEMFC model based on gazelle optimization algorithm

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 87, P. 214 - 226

Published: Sept. 7, 2024

Language: Английский

---

A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 11, 2025

Electrochemical energy conversion technologies include proton exchange membrane fuel cells (PEMFCs) where interchange is an alternative to diesel distributed generation, and PEMFCs are considered as a promising backup power source tool regulate consumption. Some of the major benefits these especially in system applications low emission carbon, fast load following capability, no noise high start-up reliability. It challenging find best PEMFC parameters because model complex problem nonlinear; not all optimization algorithms can solve this problem. This paper presents new approach that applies QUasi-Affine TRansformation Evolution algorithm with adaptation Matrix Selection operation (QUATRE-EMS) determine optimal values uncertain stack references. The objective function defined sum squared errors actual predicted voltage data. effectiveness proposed QUATRE-EMS also checked through statistical analysis variant compared other variants DE which recently state-of-the-art literature such LSHADE, MadDE, CS-DE, LPalmDE, EDEV, jSO, SHADE, ISDE, JADE. Results show reduces SSE significantly, average 0.078492, 15% less than performing existing algorithms. achieved lowest absolute error, relative error mean bias among different references, accuracy improved by up 20%. was computationally more efficient, cutting runtime half methods. results findings confirm practicability for improving BCS500W, NedStackPS6, SR12, H12, HORIZON, Standard 250W

Language: Английский

---

Optimizing proton exchange membrane fuel cell parameters using adaptive cluster division differential evolution

Ionics, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

---