Improved Scalable Analytical Model for Predicting SPM Motor Performance Considering Magnet Shape and Magnetization Pattern

This article develops the improved scalable analytical model (iSAM) for predicting the performance of the surface-mounted permanent-magnet (SPM) motor with the arbitrary magnet shape and magnetization direction. It extends the ability of the conventional analytical models. The database of the analytical model can store the electromagnetic information for the SPM motors, which enriches the scaling laws for electrical machines. As for the magnets with arbitrary shapes, they are divided into finite rectangles or fan-shaped segments based on their magnetization directions, which are then replaced by equivalent magnet currents along the magnet surfaces. Then, based on the iSAM, the air-gap field of the SPM motor can be obtained considering the iron nonlinearity. This method is beneficial for accelerating the optimization process aimed at reducing torque ripple in servo motor applications. The finite-element method (FEM) for eccentric magnetic pole servo motors is executed to verify the effectiveness of the proposed method. Additionally, a prototype with parallel magnetized PM is tested to demonstrate the accuracy of the iSAM. The proposed method is particularly useful for the modeling techniques and fault diagnosis of electrical machines.