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Developed Coyote Optimization Algorithm and its application to optimal parameters estimation of PEMFC model

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Veröffentlicht in: Energy reports 6(2020) vom: Nov., Seite 1106-1117
Personen und Körperschaften: Yuan, Zhi (VerfasserIn), Wang, Weiqing (VerfasserIn), Wang, Haiyun (VerfasserIn), Yildizbasi, Abdullah (VerfasserIn)
Titel: Developed Coyote Optimization Algorithm and its application to optimal parameters estimation of PEMFC model/ Zhi Yuan, Weiqing Wang, Haiyun Wang, Abdullah Yildizbasi
Format: E-Book-Kapitel
Sprache: Englisch
veröffentlicht:
2020
Gesamtaufnahme: : Energy reports, 6(2020) vom: Nov., Seite 1106-1117
, volume:6
Schlagwörter:
Quelle: Verbunddaten SWB
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Zusammenfassung: In this paper, a new approach has been introduced for optimal parameter estimation of a proton exchange membrane fuel cell (PEMFC) model. The main purpose is to minimize the total error between the empirical data and the proposed method by optimal parameter selection of the model. The methodology is based on using a newly introduced developed version of the Coyote Optimization Algorithm (DCOA) for determining the value of the unknown parameters in the model. Two different PEMFC models including 2 kW Nexa FC and 6kW NedSstack PS6 FC are adopted for validation and the results are compared with the empirical data and some well-known methods including conventional COA, Seagull Optimization Algorithm, and (N + λ) - ES algorithm to show the proposed method's superiority toward the literature methods. The final results declared a satisfying agreement between the proposed DCOA and the empirical data. The results also declared the excellence of the presented method toward the other compared methods.
ISSN: 2352-4847
DOI: 10.1016/j.egyr.2020.04.032
Zugang: Open Access