Optimal Values of Unknown Parameters of Polymer Electrolyte Membrane Fuel Cells Using Improved Chaotic Electromagnetic Field Optimization

Hamdy M. Sultan, Ahmed S. Menesy, Salah Kamel, Rania A. Turky, H. M. Hasanien, Ahmed Al-Durra

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In this article, the improved chaotic electromagnetic field optimization (ICEFO) algorithm is adopted to generate the optimal values of unknown parameters of fuel cells (FCs). The mathematical model of polymer electrolyte membrane FC (PEMFC) considers nonlinear and complex optimization problems with different control variables. The sum of squared error between the measured and computed stack voltages is considered as the main objective function. The performance of the ICEFO algorithm is tested on three PEMFC stacks. Moreover, sensitivity and statistical measures are presented to confirm the reliability and accuracy of ICEFO. In addition, the effect of changing the cell temperature and reactants pressures is studied for more validation of ICEFO. Furthermore, the results obtained by ICEFO are competitive compared with other optimization methods. These results confirm the effectiveness of ICEFO in solving the optimization problem of PEMFC parameter estimation. Finally, based on the optimization results a Simulink model for PEMFC is developed to examine the dynamic performance of the PEMFCs.

Original languageBritish English
Pages (from-to)6669-6687
Number of pages19
JournalIEEE Transactions on Industry Applications
Volume57
Issue number6
DOIs
StatePublished - 2021

Keywords

  • Chaotic maps
  • dynamic performance
  • improved chaotic electromagnetic field optimization (ICEFO)
  • parameter estimation
  • polymer electrolyte membrane fuel cell (PEMFC)
  • statistical analysis

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