In this study, the necessary steps for the design of axial flow permanent magnet motors are shown. The design and analysis of the engine were carried out based on ANSYS Maxwell program. The design parameters of the ANSYS For design optimization, variable ranges were assigned, and the performance values were examined and the artificial neural network model was established based on these data. Artificial neural networks established based on neuron structure of the human brain, artificial neural networks can be modeled and learned. Artificial neural networks are first trained using existing data and then tested with data not used during training. Although the training process takes time, after this training they have quick decision make mechanism. Maxwell program and the artificial neural network system were established in MATLAB, and the most efficient design parameters were found with the trained neural network. The results of the Maxwell program and the results of the artificial neural networks are compared, and optimal working design parameters are found. The most efficient design parameters were submitted to the ANSYS Maxwell 3D design, and the cogging torque was examined and design studies were carried out to reduce the cogging torque by doing modifications on rotors side.
Anahtar Kelimeler: AFPM, ANSYS Maxwell, Cogging torque, Design optimisation, Efficiency, NNTOOL
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