Tree growth algorithm for parameter identification of proton exchange membrane fuel cell models

  1. Hamdy M. Sultan 1
  2. Ahmed S. Menesy 1
  3. Salah Kamel 2
  4. Francisco Jurado 3
  1. 1 Minia University
    info

    Minia University

    Al Minyā, Egipto

    ROR https://ror.org/02hcv4z63

  2. 2 Chongqing University
    info

    Chongqing University

    Chongqing, China

    ROR https://ror.org/023rhb549

  3. 3 Universidad de Jaén
    info

    Universidad de Jaén

    Jaén, España

    ROR https://ror.org/0122p5f64

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Revista:
IJIMAI

ISSN: 1989-1660

Año de publicación: 2020

Volumen: 6

Número: 2

Páginas: 101-111

Tipo: Artículo

DOI: 10.9781/IJIMAI.2020.03.003 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: IJIMAI

Resumen

Demonstrating an accurate mathematical model is a mandatory issue for realistic simulation, optimization and performance evaluation of proton exchange membrane fuel cells (PEMFCs). The main goal of this study is to demonstrate a precise mathematical model of PEMFCs through estimating the optimal values of the unknown parameters of these cells. In this paper, an efficient optimization technique, namely, Tree Growth Algorithm (TGA) is applied for extracting the optimal parameters of different PEMFC stacks. The total of the squared deviations (TSD) between the experimentally measured data and the estimated ones is adopted as the objective function. The effectiveness of the developed parameter identification algorithm is validated through four case studies of commercial PEMFC stacks under various operating conditions. Moreover, comprehensive comparisons with other optimization algorithms under the same study cases are demonstrated. Statistical analysis is presented to evaluate the accuracy and reliability of the developed algorithm in solving the studied optimization problem.

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Fuente de los datos: Dialnet