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Optimized parameter estimation of a PEMFC model based on improved Grass Fibrous Root Optimization Algorithm

  • Haibing Guo
  • , Hai Tao
  • , Sinan Q. Salih
  • , Zaher Mundher Yaseen
  • Jiangsu Ocean University
  • Baoji University of Art and Science
  • University of Anbar
  • Duy Tan University

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

This paper presents a new optimal methodology for parameter identification of a 50 kW polymer membrane fuel cell (PEMFC) based on the economical–functional model. The objective of the study is to optimal estimation of the system parameters such that the minimum total cost has been needed for the stack construction. The total cost here is the sum of the fuel cell stack cost and its auxiliaries by considering air and hydrogen stoichiometric coefficient, system pressure, the current density, and the system temperature. For solving the minimization problem, a newly modified model of the Grass Fibrous Root Optimization Algorithm (MGRA) has been presented. Final results are compared with some several well-known algorithms to indicate the system efficiency and the reliability of the system toward different parameters has been indicated by applying sensitivity analysis.

Original languageEnglish
Pages (from-to)1510-1519
Number of pages10
JournalEnergy Reports
Volume6
DOIs
StatePublished - 1 Nov 2020
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Electrochemically–mechanically​ model
  • Grass Fibrous Root Optimization Algorithm
  • Parameter identification
  • Polymer membrane fuel cell
  • Sensitivity analysis

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