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A new EKF-based algorithm for flux estimation in induction machines

机译:一种基于EKF的感应电机磁通估计新算法

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摘要

A reduced-order algorithm for estimating the rotor flux components of induction motors with schemes such as field-oriented control is described. The algorithm is based on the extended Kalman filter (EKF) theory and estimates the desired quantities online using only measurements of the stator voltages and currents and the rotor speed. The online adaptation of the inverse rotor time constant makes it possible to obtain very accurate estimates of rotor flux components, in spite of temperature and magnetic saturation effects. The algorithm order reduction decreases the computational complexity and makes the proposed estimator superior to others based on EKF theory.
机译:描述了一种使用诸如磁场定向控制等方案估算感应电动机的转子磁通分量的降阶算法。该算法基于扩展卡尔曼滤波器(EKF)理论,仅使用定子电压和电流以及转子速度的测量值在线估算所需量。尽管存在温度和磁饱和效应,但通过逆转子时间常数的在线匹配,可以获得非常精确的转子磁通分量估算值。该算法的降阶降低了计算复杂度,并使基于EKF理论的估计器优于其他估计器。

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