A Study of Reducing Analysis Time on Minimizing Detent Torque in Linear Motors Using Surrogate Model

The detent torque of a linear motor is an irregular torque fluctuation caused by the interaction between the magnets and the core, which can degrade the performance and efficiency of the system. This study presents a method that utilizes a neural network-based surrogate model to minimize the detent torque of a linear motor. To analyze the skew, which has a significant impact on detent torque, a 3D analysis is deemed appropriate, and the use of surrogate model will greatly contribute to reducing computational costs. The method using surrogate model has been shown to contribute to the reduction of detent torque and analysis time in linear motors.