Position estimation at zero speed for PMSM using probabilistic neural network

K. Urbanski
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引用次数: 6

Abstract

The paper presents a method for estimating the shaft position of a synchronous motor with permanent magnets (PMSM) for the zero and very low speed range. The method is based on the analysis of the high frequency currents, which are induced by the additional test voltage in a stationary coordinate system associated with the stator. Although this method involves the identification of currents hodograph, the method does not need to calculate the current ellipse position. Presented method involves a comparison of obtained shape to the reference pattern using probabilistic neural network (PNN). The method can achieve satisfactory accuracy in a case the high asymmetry of the inductance, as well as in the case of small values of the inductance asymmetry ratio, also in the case of a high level of noise.
基于概率神经网络的永磁同步电机零转速位置估计
本文提出了一种估算永磁同步电动机在零速和极低速范围内轴位的方法。该方法基于对附加测试电压在与定子相关的静止坐标系中产生的高频电流的分析。该方法虽然涉及到电流轨迹的识别,但不需要计算电流椭圆的位置。该方法利用概率神经网络(PNN)将得到的形状与参考图案进行比较。该方法在电感不对称度高、电感不对称比值小、噪声水平高的情况下均能取得满意的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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