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System Identification of the PEMFCs based on Balanced Manta-Ray Foraging Optimization algorithm

机译:基于平衡式Manta射线觅食优化算法的PEMFC的系统识别

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The present paper proposes a new optimal method for modeling and simulating of a proton exchange membrane fuel cell (PEMFC) system. The main idea is to minimize the Sum of Squared Error (SSE) between the experimental and the estimated output voltages to achieve the maximum agreement between them. To minimize the error value, a modified metaheuristic, called Balanced Manta-Ray Foraging Optimization (BMRFO) algorithm has been designed. The designed algorithm is proposed for resolving the algorithm premature convergence and to improve the algorithm diversity. By performing 30 independent runs for the suggested BMRFO algorithm and comparing it with some other algorithms from the literature, it is observed that the proposed method gives better convergency in speed and accuracy.
机译:本文提出了一种新的最佳方法,用于建模和模拟质子交换膜燃料电池(PEMFC)系统。主要思想是最小化实验和估计的输出电压之间的平方误差(SSE)的总和,以实现它们之间的最大协议。为了最小化误差值,设计了一种被设计的修改的成群质雕刻,称为平衡的Manta-ray觅食优化(BMRFO)算法。建议设计算法用于解决算法过早收敛并改善算法的多样性。通过为建议的BMRFO算法执行30个独立运行,并将其与文献中的一些其他算法进行比较,观察到所提出的方法可以更好地收敛速度和准确性。

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