| 基于BP神经网络的燃料电池发动机温度模型 |
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| 引用本文： | 欧阳广彬,侯永平,金柳凯,周伟烈.基于BP神经网络的燃料电池发动机温度模型[J].佳木斯工学院学报,2010(6):813-815. |
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| 作者姓名： | 欧阳广彬 侯永平 金柳凯 周伟烈 |
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| 作者单位： | [1]同济大学新能源汽车工程中心,上海201804 [2]上海燃料电池汽车动力系统有限公司,上海201804 |
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| 摘 要： | 燃料电池堆的热特性对燃料电池整体性能和寿命有重要影响,电堆温度特性具有不确定性和非线性,本文利用BP神经网络建立了电堆温度模型,并通过实测数据分析了神经网络模型的特性,研究结果表明,神经网络可以用于电堆温度模型的建立,为质子交换膜燃料电池电堆的建模与控制提供了一条可供参考的途径.
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| 关 键 词： | 质子交换膜燃料电池 神经网络 温度 |
Temperature Modeling of PEMFC Based on BP Neural Networks |
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| Authors: | OUYANG Guang-bin HOU Yong-ping JIN Liu-kai ZHOU Wei-lie |
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| Affiliation: | 1.Clean Energy Automotive Engineering Center,Tongji University,Shanghai 201804,China;2.Shanghai Fuel Cell Vehicle Powertrain Co.Ltd.,Shanghai 201804,China) |
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| Abstract: | The thermal properties of a fuel cell stack have great influence on its integral behaviors and lifespan.The temperature characteristic of fuel cell stack is uncertain and nonlinear.The thesis built a model of the stack temperature with BP neural network and analyses the properties of the BP network with test data.The results showed that neural network can be used for modeling of the stack temperature.The approach is referencable for the modeling and control of PEMFC stack. |
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| Keywords: | proton exchange membrane fuel cell neural network temperature |
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