Nonlinear Identification of a PEM Fuel Cell Humidifier Using Wavelet Networks
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.
KeywordsFuel Cell Multivariate Adaptive Regression Spline Fuel Cell System Polymer Electrolyte Membrane Fuel Cell Wavelet Network
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