[其它]Modeling a PEMFC by a support vector machine

Abstract &c;@u?:@S  
This paper reports a modeling study of proton exchange membrane fuel cell (PEMFC) performance by using a support vector machine (SVM). ?fO 2&)r  
A PEMFC is a nonlinear, multi-variable system that is hard to model by conventional methods. As regards the SVM, it has a superior capability for \tL9`RKpg  
generalization, and this capability is independent on the dimensionality of the input data. These two merits combine to make it a powerful tool to m(~5X0  
predict how a PEMFC will behave under different operating conditions. Herein a SVM model of a PEMFC system is built, optimized and tested. `S&(J2KV  
First, the model is determined with selected experimental data, and then it is used to predict PEMFC performance. It is shown that the model can *hJ&7w ~  
make the prediction in 10 ms with the squared correlation coefficient as high as 99.7%. Therefore, the proposed black-box SVM PEMFC model 'g3!SdaLF  
applies to the simulation, real-time control and monitoring of a fuel cell’s performance. hqEnD  
© 2006 Elsevier B.V. All rights reserved. jt({@;sU[<  
Keywords: Fuel c .. 8|:bis~wm  
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