Theoretical and experimental background for artificial neural network modeling of alpha type Stirling engine

Abstract

This article presents a theoretical background for an artificial neural network (ANN) model of the alpha type Stirling engine where thermodynamic dependencies, connected with equations of motion for the piston-crankshaft system with three degrees of freedom were taken into account. Because of the highly nonlinear description of Stirling engine dynamics, the ANN was employed, that modelled output power of Stirling engine as a function of the input power, molar mass, load current, pressure obtained by gas combustion and working parameters of the engine. The ANN model was tested on experimental data, gathered at the laboratory stand, in different working conditions. The proposed ANN model provides good results for both training and testing data-sets.