| Identification and analysis based on genetic algorithm for proton exchange membrane fuel cell stack |
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| 引用本文： | 李曦 曹广益 朱新坚 卫东. Identification and analysis based on genetic algorithm for proton exchange membrane fuel cell stack[J]. 中南工业大学学报(英文版), 2006, 13(4): 428-431. DOI: 10.1007/s11771-006-0062-0 |
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| 作者姓名： | 李曦 曹广益 朱新坚 卫东 |
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| 作者单位： | [1]Department of Control Science and Engineering,Huazhong University of Science and Technolgy, Wuhan 430074, China [2]Department of Automation, Shanghai Jiaotong University, Shanghai 200030, China |
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| 基金项目： | 高比容电子铝箔的研究开发与应用项目 |
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| 摘 要： | The temperature of proton exchange membrane fuel cell stack and the stoichiometric oxygen in cathode have relationship with the performance and life span of fuel cells closely. The thermal coefficients were taken as important factors affecting the temperature distribution of fuel cells and components. According to the experimental analysis, when the stoichiometric oxygen in cathode is greater than or equal to 1.8, the stack voltage loss is the least. A novel genetic algorithm was developed to identify and optimize the variables in dynamic thermal model of proton exchange membrane fuel cell stack, making the outputs of temperature model approximate to the actual temperature, and ensuring that the maximal error is less than 1℃. At the same time, the optimum region of stoichiometric oxygen is obtained, which is in the range of 1.8 -2.2 and accords with the experimental analysis results. The simulation and experimental results show the effectiveness of the proposed algorithm.
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| 关 键 词： | 质子交换膜燃料电池 遗传算法 温度 导热率 |
| 文章编号： | 1005-9784（2006）04-0423-04 |
| 收稿时间： | 2005-10-25 |
| 修稿时间： | 2005-12-05 |
Identification and analysis based on genetic algorithm for proton exchange membrane fuel cell stack |
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| Li Xi , Cao Guang-yi , Zhu Xin-jian and Wei Dong. Identification and analysis based on genetic algorithm for proton exchange membrane fuel cell stack[J]. Journal of Central South University of Technology, 2006, 13(4): 428-431. DOI: 10.1007/s11771-006-0062-0 |
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| Authors: | Li Xi Cao Guang-yi Zhu Xin-jian Wei Dong |
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| Affiliation: | (1) Department of Control Science and Engineering, Huazhong University of Science and Technology, 430074 Wuhan, China;(2) Department of Automation, Shanghai Jiaotong University, 200030 Shanghai, China |
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| Abstract: | The temperature of proton exchange membrane fuel cell stack and the stoichiometric oxygen in cathode have relationship with the performance and life span of fuel cells closely. The thermal coefficients were taken as important factors affecting the temperature distribution of fuel cells and components. According to the experimental analysis, when the stoichiometric oxygen in cathode is greater than or equal to 1.8, the stack voltage loss is the least. A novel genetic algorithm was developed to identify and optimize the variables in dynamic thermal model of proton exchange membrane fuel cell stack, making the outputs of temperature model approximate to the actual temperature, and ensuring that the maximal error is less than 1 °C. At the same time, the optimum region of stoichiometric oxygen is obtained, which is in the range of 1.8–2.2 and accords with the experimental analysis results. The simulation and experimental results show the effectiveness of the proposed algorithm. Foundation item: Project (2003AA517020) supported by the National High-Technology Research Plan of China |
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| Keywords: | proton exchange membrane fuel cell genetic algorithm temperature thermal coefficient stoichiometric oxygen |
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