Electromagnetic Design Optimization of a PMSG Using a Deep Neural Network Approach

This digest presents the design optimization of a permanent magnet synchronous generator (PMSG) based on machine learning. A deep neural network (DNN) was developed using 3D FE data of a PMSG. The DNN is based on the nonlinear Rectified Linear Unit (ReLU). The resulting DNN was later used to construct the PMSG objective function which was then minimized. Numerical results are given.