[1]韩闯,吴莉莉.质子交换膜燃料电池建模与控制研究进展[J].郑州大学学报(工学版),2015,36(06):61.[doi:10.3969/j.issn.1671－6833.2015. 06.012]
　Han Chuang,Wu Lili.Review on Modeling and Control of Proton Exchange Membrane Fuel Cell[J].Journal of Zhengzhou University (Engineering Science),2015,36(06):61.[doi:10.3969/j.issn.1671－6833.2015. 06.012]
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质子交换膜燃料电池建模与控制研究进展()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
36
期数:
2015年06期
页码:
61
栏目:
出版日期:
2015-12-25

文章信息/Info

Title:
Review on Modeling and Control of Proton Exchange Membrane Fuel Cell
作者:
韩闯; 吴莉莉
郑州大学电气工程学院，河南郑州450001
Author(s):
Han Chuang;  Wu Lili
School of Electric Engineering，Zhengzhou University，Zhengzhou 450001，China
关键词:
质子交换膜燃料电池; 建模; 智能控制
Keywords:
Proton exchange membrane fuel cell; Modeling; Intelligent control
DOI:
10.3969/j.issn.1671－6833.2015. 06.012
文献标志码:
A
摘要:
针对质子交换膜燃料电池的建模与控制问题，概述了基于极化曲线和参数维度的经验模型和机理模型，分析了基于电化学反应、温度、压力等因素的电化学稳态模型和动态模型，介绍了基于神经网络辨识、群集智能算法和支持向量机等的智能方法模型，对质子交换膜燃料电池的现有智能控制策略进行了总结，最后指出:利用群集智能算法同时优化质子交换膜燃料电池的模型参数和环境参数将是建模的一个发展方向，预测广义Hamilton理论等也可被尝试用于质子交换膜燃料电池建模的研究中，同时融合新算法的智能控制策略将成为质子交换膜燃料电池控制的研究趋势．
Abstract:
For the modeling and control of proton exchange membrane fuel cells, the empirical model and mechanism model based on polarization curve and parameter dimension are summarized, the electrochemical steady-state model and dynamic model based on electrochemical reaction, temperature, pressure and other factors are analyzed, and the intelligent method model based on neural network identification, swarm intelligence algorithm and support vector machine is introduced.The existing intelligent control strategies of proton exchange membrane fuel cells are summarized. Finally, it is pointed out that it will be a development direction of modeling to optimize the model parameters and environmental parameters of proton exchange membrane fuel cells by using swarm intelligence algorithm. The generalized Hamilton theory can also be tried to be used in the modeling of proton exchange membrane fuel cells.At the same time, the intelligent control strategy combining the new algorithm will become the research trend of proton exchange membrane fuel cell control.

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