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Optimization of PEMFC model parameters with a modified particle swarm optimization

机译:用改进的粒子群算法优化PEMFC模型参数

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摘要

In this paper, an electrochemical-based proton exchange membrane fuel cell (PEMFC) model suitable for engineering applications is presented. In order to improve the accuracy of this model so that it can reflect the actual PEMFC performance better, its parameters are optimized by means of a modified particle swarm optimization (MPSO). The MPSO is a modified method for the PSO's inertia weight. The proposed inertia weight is calculated according to the distance of the particle's current position from the best solution of the entire swarm. The obtained results of the PEMFC model with optimized parameters agree with experimental data well. Therefore, the MPSO is a helpful and reliable technique for optimizing the model parameters and can be used to solve other complex parameter optimization problems of fuel cell models. Copyright © 2010 John Wiley & Sons, Ltd.
机译:本文提出了一种适用于工程应用的基于电化学的质子交换膜燃料电池(PEMFC)模型。为了提高此模型的准确性,使其可以更好地反映实际的PEMFC性能,通过改进的粒子群优化(MPSO)对其参数进行了优化。 MPSO是PSO惯性权重的一种修改方法。建议的惯性权重是根据粒子当前位置与整个群的最佳解的距离来计算的。通过优化参数得到的PEMFC模型结果与实验数据吻合良好。因此,MPSO是一种用于优化模型参数的有用且可靠的技术,可用于解决燃料电池模型的其他复杂参数优化问题。版权所有©2010 John Wiley&Sons,Ltd.

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