Modelling of fuel composition influences on solid oxide fuel cell performance by artificial neural network

• Autorzy: Milewski J. , Świrski K. , Santarelli M. , Leone P.
• Języki publikacji: EN

Abstrakty

EN

There are many mathematical models of the singular solid oxide fuel cell (SOFC). SOFC performance modelling is related to the multiphysic processes taking places on the fuel cell surfaces. Heat transfer together with electrochemical reactions, mass and charge transport are conducted inside the cell. There are many parameters which impact the cell working conditions, e.g. electrolyte material, electrolyte thickness, cell temperature, inlet and outlet gas compositions at anode and cathode, anode and cathode porosities ect. The Artificial neural Network (ANN) can be applied to stimulate an object.s behaviour without an algorithmic solution merely by utilizing available experimental data. The ANN is used for modelling singular cell behaviour. The optimal network architecture is shown and commented. The error back-propagation algorithm was used for an ANN training procedure.

Słowa kluczowe

EN

artificial neural network; mathematical modelling; solid oxide fuel cell

PL

modelowanie matematyczne; sztuczne sieci neuronowe

• Wydawca: Wydawnictwo Instytutu Maszyn Przepływowych PAN ; Komitet Termodynamiki i Spalania PAN
• Czasopismo: Archives of Thermodynamics
• Rocznik: 2009
• Tom: Vol. 30, no. 4
• Strony: 13--24
• Opis fizyczny: Biblior. 11 poz.,Rys., tab., wykr., wz.,

Twórcy

autor

Milewski J.

autor

Świrski K.

autor

Santarelli M.

autor

Leone P.

• Institute if Heat Engineering, Warsaw University if Technology, ul. Nowowiejska 21/25, 00-665 Warsaw, Poland,

Bibliografia

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