Accurate, efficient and reliable parameter extraction of PEM fuel cells using shuffled multi-simplexes search algorithm
•A shuffled multi-simplexes search (SMS) is proposed for parameter extraction of PEMFC.•SMS merges the strengths of three concepts to accomplish strong global convergence.•The performance of SMS is tested by the reported V-I datasets of four PEMFC stacks.•The results of SMS are compared with those o...
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Veröffentlicht in: | Energy conversion and management 2020-02, Vol.206, p.112501, Article 112501 |
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Sprache: | eng |
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Zusammenfassung: | •A shuffled multi-simplexes search (SMS) is proposed for parameter extraction of PEMFC.•SMS merges the strengths of three concepts to accomplish strong global convergence.•The performance of SMS is tested by the reported V-I datasets of four PEMFC stacks.•The results of SMS are compared with those of reported state-of-the-art algorithms.•SMS exhibits better accuracy, convergence speed and reliability than other algorithms.
Parameter extraction is significant for simulation analysis, evaluation, optimal control and fault detection of proton exchange membrane fuel cell (PEMFC) system. Although various techniques have been developed for parameter extraction of PEMFC, it is still challenging to quickly obtain accurate and reliable results. In this paper, a shuffled multi-simplexes search (SMS) algorithm, merging the strengths of three concepts: (a) periodic shuffling multiple simplexes for an effective global exploration, (b) monitoring and revitalization of degenerate simplex to maintain the population diversity for preventing premature convergence and (c) modified simplex search algorithm to conduct a robust and powerful local exploitation, is proposed to fast and accurate extract the model parameter of PEMFC. To be objective and reproducible, the reported experimental V–I datasets of four PEMFC stacks are chosen for testing the parameter extraction performance of proposed SMS algorithm and comparing it with some state-of-the-art algorithms. The comparison results indicate that for all the four test cases, the proposed SMS consistently gets the optimal results among all compared algorithms and exhibits faster convergence speed, lesser computational CPU time (less than 0.3 s for 5000 function evaluations to converge), preferable accuracy and higher statistical robustness (the smallest standard deviation is 1.90E−16) than other algorithms. Due to these superiorities, the proposed SMS is quite promising and envisaged to be an accurate, efficient and reliable alternative for solving the parameter extraction problem of PEMFC model. |
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ISSN: | 0196-8904 1879-2227 |
DOI: | 10.1016/j.enconman.2020.112501 |