Static sensor assisted rotor temperature estimation of permanent magnet machine for the low‐speed servo applications

Abstract

A permanent magnet synchronous machine (PMSM) temperature estimation method fusing the classic lumped‐parameter thermal network (LPTN) and the stator sensor temperature information is investigated. With respect to the industrial servo applications, it is important to monitor the rotor magnet temperature to extend the machine thermal utilisation. A simple LPTN is developed and the quadratic programming is applied to identify the model parameters. The research work shows that the rotor temperature is sensitive to the rotor speed even at low speeds, and this simple estimation network can provide an accurate estimation. The winding sensor information can further improve the performance. A compound mechanism is built, by which the winding temperature estimation error is used as feedback to suppress the model‐based temperature estimation error accumulation. The estimation performance is compared with a regular constant LPTN‐based method. Experimental results based on a PMSM are presented to validate the proposed method.

Research on cogging torque reduction method for permanent magnet synchronous motor accounting for the magnetic pole edge effect

“…Due to their high power density, high efficiency, and good dynamic performance, permanent magnet synchronous motors (PMSMs) are widely used in industrial fields such as robots and numerically-controlled machine tools [1,2]. However, the cogging torque caused by the variation of air-gap permeance due to the stator slots will lead to motor vibration and noise, which will also affect control accuracy.…”