Cited by Single-Cell Analysis of Proton Exchange Membrane Fuel Cell (PEMFC) for Portable Power Generator in Rural Area: Thermodynamic Approach of Temperature Dependency

An Accurate Parameter Estimation Method of the Voltage Model for Proton Exchange Membrane Fuel Cells DOI

Jian Mei,

Xuan Meng,

Xingwang Tang

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(12), P. 2917 - 2917

Published: June 13, 2024

Accurate and reliable mathematical modeling is essential for the optimal control performance analysis of polymer electrolyte membrane fuel cell (PEMFC) systems, which are mainly implemented based on accurate parameter estimation. In this paper, a multi-strategy tuna swarm optimization (MS-TSO) proposed to estimate parameters PEMFC voltage models compare them with other optimizers such as differential evolution, whale approach, salp algorithm, particle optimization, Harris hawk slime mould algorithm. optimizing routine, unidentified factors PEMFCs used decision variables, optimized minimize sum square errors between estimated measured data. The examined three datasets including BCS500W, NedStackPS6 harizon500W well set experimental data using Greenlight G20 platform 25 cm2 single at 353 K. It confirmed that MS-TSO gives better in terms convergence speed accuracy than competing algorithms. Furthermore, results achieved by compared reported approaches literature. advantages ascertaining optimum various have been comprehensively demonstrated.

Language: Английский

Citations

Robust parameter estimation of proton exchange membrane fuel cell using Huber loss statistical function DOI

Bahaa Saad,

Ragab A. El‐Sehiemy, Hany M. Hasanien

et al.

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 323, P. 119231 - 119231

Published: Nov. 11, 2024

Language: Английский

Citations

An efficient framework for proton exchange membrane fuel cell parameter estimation using numerous MH algorithms DOI

Asmita Ajay Rathod, Pankaj Sharma, Arun Choudhary

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 216, P. 115603 - 115603

Published: April 8, 2025

Language: Английский

Citations

Enhancing the analytical modeling of proton-exchange membrane fuel cells for optimal parameter extraction with the Ali Baba and the forty thieves algorithm DOI

Lazhar Linoubli,

Salah Hajji,

Ramzi Ben Messaoud

et al.

Journal of the Taiwan Institute of Chemical Engineers, Journal Year: 2025, Volume and Issue: 172, P. 106093 - 106093

Published: March 23, 2025

Language: Английский

Citations

Prediction of venous clinical severity score in yoga practitioners and non-practitioners using discriminant analysis and metaheuristic algorithms DOI

Fengcai Wang,

Wang Yan Fei

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127272 - 127272

Published: March 1, 2025

Language: Английский

Citations

Ensemble of deep learning models with Walrus Optimization Algorithm for accurate botnet recognition and classification DOI

Ashwathy Anda Chacko,

E. Bijolin Edwin, M. Roshni Thanka

et al.

Iran Journal of Computer Science, Journal Year: 2025, Volume and Issue: unknown

Published: April 11, 2025

Language: Английский

Citations

Enhanced global optimization using quadratically interpolated hybrid pathfinder algorithm DOI

Oluwatayomi Rereloluwa Adegboye,

Afi Kekeli Feda,

Abosede Omowumi Tibetan

et al.

Cluster Computing, Journal Year: 2025, Volume and Issue: 28(5)

Published: April 28, 2025

Language: Английский

Citations

Optimal Parameter Extraction of PEM Fuel Cell Using a Hybrid Weighted Mean of Vectors and Nelder-Mead Simplex Method DOI

Rahul Khajuria, Mahipal Bukya, Ravita Lamba

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 121346 - 121367

Published: Jan. 1, 2024

Language: Английский

Citations

Novel reinforcement learning technique based parameter estimation for proton exchange membrane fuel cell model DOI

Nermin M. Salem, Mohamed A. M. Shaheen, Hany M. Hasanien

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 11, 2024

Proton Exchange Membrane Fuel Cells (PEMFCs) offer a clean and sustainable alternative to traditional engines. PEMFCs play vital role in progressing hydrogen-based energy solutions. Accurate modeling of PEMFC performance is essential for enhancing their efficiency. This paper introduces novel reinforcement learning (RL) approach estimating parameters, addressing the challenges complex nonlinear dynamics PEMFCs. The proposed RL method minimizes sum squared errors between measured simulated voltages provides an adaptive self-improving RL-based Estimation that learns continuously from system feedback. demonstrates superior accuracy compared with metaheuristic techniques. It has been validated through theoretical experimental comparisons tested on commercial PEMFCs, including Temasek 1 kW, 6 kW Nedstack PS6, Horizon H-12 12 W. dataset used this study comes data. research contributes precise improving efficiency, developing wider adoption

Language: Английский

Citations

Enhancement of the Commandable Areas of a Modular DC–DC Converter With Anti-Windup Synthesis in Fuel Cell Systems DOI

Mohammad Afkar, Roghayeh Gavagsaz‐Ghoachani, Wiset Saksiri

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 95673 - 95683

Published: Jan. 1, 2024

This study investigates the commandability in a DC-DC converter for fuel cell applications. In this modular system, each module is established on three-level converter. The operation areas of studied terms have already been investigated. paper, manner to increase commandable area suggested. An anti-windup scheme used enhance stability under duty-cycle saturation. indirect sliding-mode controller utilized balance DC voltages and control currents with dynamical properties regardless operating settings. Simulations experiments consistent theoretical are conducted confirm suggested scheme.

Language: Английский

Citations