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Application of flower pollination algorithm for enhanced proton exchange membrane fuel cell modelling

机译:花授粉算法在增强质子交换膜燃料电池建模中的应用

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Modelling of Proton Exchange Membrane Fuel Cell (PEMFC) characteristics assumes importance in view of better understanding, analysis and design of high efficient fuel cell systems. Limited by its complexity, strongly coupled behaviour and multivariate characteristics; optimization techniques are attempted to model PEMFC characteristics. Influenced by convergence speed, computational efficiency, level of complexity, dependency on initial solution and ability to locate global optimum; recently evolved Flower Pollination Algorithm is utilized in this work for PEMFC modelling. This method is applied to derive unknown model parameters of fuel cells having different characteristics and rating. Further, to illustrate the superiority of the method, results obtained are compared with some of the recent works. Moreover, to showcase its efficiency; comprehensive comparison is made in terms of model parameter values, sum of squared error, individual absolute error and relative error values. (C) 2019 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译:考虑到对高效燃料电池系统的更好理解,分析和设计,质子交换膜燃料电池(PEMFC)特性的建模非常重要。受其复杂性,强烈耦合的行为和多变量特征的限制;尝试使用最优化技术对PEMFC特性建模。受收敛速度,计算效率,复杂程度,对初始解的依赖性以及确定全局最优能力的影响;在这项工作中,最近发展起来的花卉授粉算法被用于PEMFC建模。该方法适用于推导具有不同特性和等级的燃料电池的未知模型参数。此外,为了说明该方法的优越性,将获得的结果与一些近期的工作进行了比较。此外,展示其效率;根据模型参数值,平方误差总和,单个绝对误差和相对误差值进行了全面比较。 (C)2019氢能出版物有限公司。由Elsevier Ltd.出版。保留所有权利。

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