| Nonlinear modeling of PEMFC based on neural networks identification |
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| 作者姓名： | 孙涛 曹广益 朱新坚 |
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| 作者单位： | Fuel Cell Institute，Department of Automation，Shanghai Jiaotong University，Shanghai 200030，China，Fuel Cell Institute，Department of Automation，Shanghai Jiaotong University，Shanghai 200030，China，Fuel Cell Institute，Department of Automation，Shanghai Jiaotong University，Shanghai 200030，China |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | INTRODUCTION With worldwide increase of air pollution and the environmental consciousness of governments, people have to look for new resources to mitigate the energy crisis and improve the present environmental status (Ferng et al., 2004; Rowe and Li, 2001). Fuel cells are highly efficient and environmentally clean electrical generators (Mann et al., 2000) that convert the chemical energy of a gaseous fuel directly into elec-tricity energy and play an important role in solving the prob…
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| 关 键 词： | 非线性模型 PEMFC 神经网络 LMBP算法 |
Nonlinear modeling of PEMFC based on neural networks identification |
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| Sun Tao,Cao Guang-yi,Zhu Xin-jian.Nonlinear modeling of PEMFC based on neural networks identification[J].Journal of Zhejiang University Science,2005,6(5):365-370. |
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| Authors: | Sun Tao Cao Guang-yi Zhu Xin-jian |
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| Institution: | (1) Fuel Cell Institute, Department of Automation, Shanghai Jiaotong University, 200030 Shanghai, China |
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| Abstract: | The proton exchange membrane generation technology is highly efficient and clean, and is considered as the most hopeful "green" power technology. The operating principles of proton exchange membrane fuel cell (PEMFC) system involve thermodynamics, electrochemistry, hydrodynamics and mass transfer theory, which comprise a complex nonlinear system, for which it is difficult to establish a mathematical model. This paper first simply analyzes the necessity of the PEMFC generation technology, then introduces the generating principle from four aspects: electrode, single cell, stack, system; and then uses the approach and self-study ability of artificial neural network to build the model of nonlinear system, and adapts the Levenberg-Marquardt BP (LMBP) to build the electric characteristic model of PEMFC. The model uses experimental data as training specimens, on the condition the system is provided enough hydrogen. Considering the flow velocity of air (or oxygen) and the cell operational temperature as inputs, the cell voltage and current density as the outputs and establishing the electric characteristic model of PEMFC according to the different cell temperatures. The voltage-current output curves of model has some guidance effect for improving the cell performance, and provide basic data for optimizing cell performance that have practical significance. |
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| Keywords: | Proton exchange membrane fuel cell Nonlinear system modeling LMBP algorithm |
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