Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells

Proton Exchange Membrane Fuel Cells play a key role in sustainable power systems by delivering both superior energy conversion efficiency and eco-friendly operation. The complex multivariate structure together with nonlinear behavior of these systems makes it parameter estimation a challenging task,...

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Main Authors: Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Results in Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025026404
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author Mohammad Aljaidi
Pradeep Jangir
Arpita
Sunilkumar P. Agrawal
Sundaram B. Pandya
Anil Parmar
G. Gulothungan
Ali Fayez Alkoradees
Mohammad Khishe
Reena Jangid
author_facet Mohammad Aljaidi
Pradeep Jangir
Arpita
Sunilkumar P. Agrawal
Sundaram B. Pandya
Anil Parmar
G. Gulothungan
Ali Fayez Alkoradees
Mohammad Khishe
Reena Jangid
author_sort Mohammad Aljaidi
collection DOAJ
description Proton Exchange Membrane Fuel Cells play a key role in sustainable power systems by delivering both superior energy conversion efficiency and eco-friendly operation. The complex multivariate structure together with nonlinear behavior of these systems makes it parameter estimation a challenging task, which negatively affects operational reliability and system lifespan. This research presents Polar Lights Optimization (PLO), a noval aurora-inspired method developed to address the current optimization challenges. PLO combines auroral gyration motion for local exploitation with oval walking dynamics for global exploration, ensuring a balanced search process. PLO undergoes performance testing against nine established optimization techniques including GSA, DE, PSO, MFO, ACOR, MVO, WOA, SCA, and JAYA through six PEMFC models which include BCS 500 W, Nedstack 600 W PS6, SR-12 W, Horizon H-12, Ballard Mark V, and STD 250 W Stack. The proposed algorithm consistently outperforms its competitors, achieving the lowest Sum of Squared Errors (SSE) and fastest convergence rates. The PLO algorithm generates SSE results of 0.025493 for BCS 500 W and 0.275211 for Nedstack 600 W PS6 and 0.283774 for STD 250 W Stack while keeping AE at 0.259293 and RE% at 1.185075 for the STD 250 W Stack. The algorithm completes 50 iterations in every test scenario and achieves the top Friedman Ranking score of 1. The experimental data shows that PLO application improves PEMFC system predictive accuracy and operational reliability and energy output performance.
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spelling doaj-art-e7d0d98872be4d34b707a70c003002192025-08-20T03:44:36ZengElsevierResults in Engineering2590-12302025-09-012710657110.1016/j.rineng.2025.106571Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cellsMohammad Aljaidi0Pradeep Jangir1 Arpita2Sunilkumar P. Agrawal3Sundaram B. Pandya4Anil Parmar5G. Gulothungan6Ali Fayez Alkoradees7Mohammad Khishe8Reena Jangid9Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa 13110, Jordan; Corresponding authors.Jadara University Research Center, Jadara University, PO Box 733, Irbid, Jordan; Applied Science Research Center, Applied Science Private University, Amman 11937, Jordan; Research and Innovation Cell, Bahra University, Distt. Solan, HP, Waknaghat, IndiaDepartment of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai 602105, IndiaDepartment of Electrical Engineering, Government Engineering College, Gandhinagar, Gujarat 382028, IndiaDepartment of Electrical Engineering, Shri K.J. Polytechnic, Bharuch 392 001, IndiaDepartment of Electrical Engineering, Shri K.J. Polytechnic, Bharuch 392 001, IndiaDepartment of Electronics and Communication Engineering, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, Chengalpattu, Tamilnadu 603203, India; Corresponding authors.Unit of Scientific Research, Applied College, Qassim University, Saudi Arabia; Corresponding authors.Department of Electrical Engineering, Imam Khomeini Naval Science University of Nowshahr, Nowshahr, Iran; Corresponding author at: Department of Electrical Engineering, Imam Khomeini Naval Science University of Nowshahr, Nowshahr, Iran.Department of CSE, Graphic Era Hill University, Dehradun 248002, India; Department of CSE, Graphic Era Deemed to be University, Dehradun, Uttarakhand 248002, India; Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab 140401, India; Rayat Bahra Institute of Engineering and Nano Technology, Hoshiarpur, Punjab, IndiaProton Exchange Membrane Fuel Cells play a key role in sustainable power systems by delivering both superior energy conversion efficiency and eco-friendly operation. The complex multivariate structure together with nonlinear behavior of these systems makes it parameter estimation a challenging task, which negatively affects operational reliability and system lifespan. This research presents Polar Lights Optimization (PLO), a noval aurora-inspired method developed to address the current optimization challenges. PLO combines auroral gyration motion for local exploitation with oval walking dynamics for global exploration, ensuring a balanced search process. PLO undergoes performance testing against nine established optimization techniques including GSA, DE, PSO, MFO, ACOR, MVO, WOA, SCA, and JAYA through six PEMFC models which include BCS 500 W, Nedstack 600 W PS6, SR-12 W, Horizon H-12, Ballard Mark V, and STD 250 W Stack. The proposed algorithm consistently outperforms its competitors, achieving the lowest Sum of Squared Errors (SSE) and fastest convergence rates. The PLO algorithm generates SSE results of 0.025493 for BCS 500 W and 0.275211 for Nedstack 600 W PS6 and 0.283774 for STD 250 W Stack while keeping AE at 0.259293 and RE% at 1.185075 for the STD 250 W Stack. The algorithm completes 50 iterations in every test scenario and achieves the top Friedman Ranking score of 1. The experimental data shows that PLO application improves PEMFC system predictive accuracy and operational reliability and energy output performance.http://www.sciencedirect.com/science/article/pii/S2590123025026404Metaheuristic optimizationParameter estimationPolar Lights Optimization (PLO)Proton Exchange Membrane Fuel Cells (PEMFCs)Sum of Squared Errors (SSE)
spellingShingle Mohammad Aljaidi
Pradeep Jangir
Arpita
Sunilkumar P. Agrawal
Sundaram B. Pandya
Anil Parmar
G. Gulothungan
Ali Fayez Alkoradees
Mohammad Khishe
Reena Jangid
Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells
Results in Engineering
Metaheuristic optimization
Parameter estimation
Polar Lights Optimization (PLO)
Proton Exchange Membrane Fuel Cells (PEMFCs)
Sum of Squared Errors (SSE)
title Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells
title_full Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells
title_fullStr Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells
title_full_unstemmed Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells
title_short Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells
title_sort polar lights optimizer a novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells
topic Metaheuristic optimization
Parameter estimation
Polar Lights Optimization (PLO)
Proton Exchange Membrane Fuel Cells (PEMFCs)
Sum of Squared Errors (SSE)
url http://www.sciencedirect.com/science/article/pii/S2590123025026404
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