Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer
Attia A. El-Fergany
Renewable Energy, 2018, vol. 119, issue C, 641-648
Abstract:
In the last years, significant attentions have been paid in the state-of-the-literature to have precise current/voltage (I/V) polarization curves of polymer exchange membrane fuel cells (PEMFCs). This article presents a novel application of a very recent heuristic-based on technique, namely Salp Swarm Optimizer (SSO) to define the best values of unknown parameters of PEMFC model. The total of square deviations (TSD) between the actual and calculated results represents the objective function. The TSD is minimized by the proposed SSO-based methodology to insignificant values to ensure the concurrence and consistency between measured and estimated voltage points and subjects to set of constraints. Two test case studies of typical commercial stacked PEMFCs, namely NedStack PS6 and BCS 500-W PEM generator are performed to demonstrate the potential of the proposed procedure under various operating scenarios. Moreover, necessary comparisons to other optimizers under same data and conditions are in order. In addition to this, performance measures are made to evaluate the performance of the SSO. The simulations along with comparisons indicate that the proposed SSO-based on method is successfully used to characterize the PEMFC model precisely.
Keywords: Proton exchange membrane fuel cell (PEMFC) stack; Parameters' extraction; Total of square deviations (TSD); Salp Swarm Optimizer (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148117312557
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:119:y:2018:i:c:p:641-648
DOI: 10.1016/j.renene.2017.12.051
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().