Xjenza Online Vol. 7 Iss. 1 - September 2019
Axial Flux Permanent Magnet Motor Design and Optimisation by Using Artificial Neural Networks
Tuğçe Talay and Kadir Erkan
Tuğçe Talay (firstname.lastname@example.org)
AFPM, ANSYS Maxwell, cogging torque, design optimisation, eciency, NNTOOL
Issue: Xjenza Online Vol. 7 Iss. 1 - September 2019
In this study, the necessary steps for the design of axial ux 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 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 were compared with the results of the artificial neural networks, and optimal working design parameters were found. The most efficient design parameters were submitted to the ANSYS Maxwell 3D design, the cogging torque was subsequently examined and design studies were carried out to reduce the cogging torque.