Modeling MCSRM with artificial neural network

In this study, modeling MCSRM (mutually couple switched reluctance machine) which is produced through modifications in wrap around structure of SRM with feed forward back propagation ANN (artificial neural network) is performed. Data obtained from angle, current, flux and torque components obtained through FEM analysis of MCSRM has been used in ANN training. In the course of literature research, no use of ANN in MCSRM modeling is detected and it is seen that algorithms consisting of analytical methods are preferred It is established that, in modeling studies which are based on such algorithms, the structure consists of thousands of loops and that these loops extend time needed for simulation; besides, it is seen that installation of loops in modeling become rather difficult. The data obtained from dynamic analysis of the model are compared with the data obtained from motor tests in the literature and it is witnessed that the model produces similar torques in similar voltage and current forms.