Black box dynamic modelling of proton exchange membrane fuel cells with artificial neural networks

• Autorzy: Kapica J.
• Języki publikacji: EN

Abstrakty

EN

The fuel cells are energy sources which can play an important role in transition of the energy sector into broader use of renewable energy. Numerical modelling provides an easy way to investigate properties of the objects modelled. There are various ways to model dynamic behaviour of the PEM fuel cells including methods using artificial neural networks. There are no clear rules of how a neural network should be configured: how many neurons in the hidden layer and which training algorithm should be used. In a time series modelling task additional parameters including sampling frequency, learning data set duration and number of past data points used for training need to be determined. The paper presents results of research on the influence of various model parameters on the PEM fuel cell modelling accuracy.

Słowa kluczowe

EN

PEM fuel cells; neural network model; dynamic behaviour; black box

• Wydawca: Polish Academy of Sciences, Branch in Lublin
• Czasopismo: ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
• Rocznik: 2016
• Tom: Vol. 5, No 4
• Strony: 85--89
• Opis fizyczny: Bibliogr. 31 poz., rys., tab., wykr., wz.

Twórcy

autor

Kapica J.

• Department of Electrical Engineering and Measurement Systems, University of Life Sciences in Lublin

Bibliografia

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).