کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1274367 1497544 2013 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An adaptive RNA genetic algorithm for modeling of proton exchange membrane fuel cells
موضوعات مرتبط
مهندسی و علوم پایه شیمی الکتروشیمی
پیش نمایش صفحه اول مقاله
An adaptive RNA genetic algorithm for modeling of proton exchange membrane fuel cells
چکیده انگلیسی

The accurate mathematical model is the key issue to simulation and design of the fuel cell power systems. Aiming at estimating the proton exchange membrane fuel cell (PEMFC) model parameters, an adaptive RNA genetic algorithm (ARNA-GA) which is inspired by the mechanism of biological RNA is proposed. The ARNA-GA uses the RNA strands to represent the potential solutions and new genetic operators are designed for improving the global searching ability. In order to maintain the population diversity and avoid premature convergence, on the basis of the dissimilarity coefficient, the adaptive genetic strategy that allows the algorithm dynamically select crossover operation or mutation operation to execute is proposed. Numerical experiments have been conducted on some benchmark functions with high dimensions. The results indicate that ARNA-GA has better search capability and a higher quality of solutions. Finally, the proposed approach has been applied for the parameter estimation of PEMFC model and the satisfactory results are reached.

Figure optionsDownload as PowerPoint slideHighlights
► Inspired by biological RNA mechanism, an adaptive RNA-GA is proposed.
► Two mutation operators are designed for improving the global searching ability.
► The adaptive strategy by which genetic operation is executed is presented.
► Numerical results show its superiority over the referenced methods.
► ARNA-GA is demonstrated effectively for parameter estimation of PEMFC model.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Hydrogen Energy - Volume 38, Issue 1, 11 January 2013, Pages 219–228
نویسندگان
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