Abstract
Humidification is a key factor influencing the performance of a Proton Exchange Membrane (PEM) Fuel Cell system. It is important to obtain an accurate temperature model of the humidifier to achieve the optimal humidity by means of some control strategy. Analysis shows that humidification process is nonlinear. To avoid the curse-of-dimensionality problem, a class of wavelet networks proposed by Billings was employed for the identification in this work. An efficient model term selection approach was applied to solve the high dimensional problem. The model was identified based on the experimental data acquired from our test bench. The one-step-ahead predictions and the five-step-ahead predictions were compared with the real measurements respectively. It shows that the identified model can effectively describe the real system.
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© 2006 Springer-Verlag Berlin Heidelberg
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Deng, XR. (2006). Nonlinear Identification of a PEM Fuel Cell Humidifier Using Wavelet Networks. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_156
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DOI: https://doi.org/10.1007/11760191_156
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
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