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Comparison of full-model and reduced-model EKF based position and speed estimators for sensorless DTC of permanent magnet synchronous machines

机译:基于全模型和简化模型的基于EKF的永磁同步电机无传感器DTC位置和速度估计器的比较

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The aim of this paper is to study the use of the Extended Kalman filer (EKF) for sensorless control of a permanent magnet synchronous motor (PMSM) drive controlled by direct torque control (DTC). The main drawback of DTC is the necessity of short sampling period. The challenge for the EKF is therefore the minimization of its execution time. This is achieved by using so called reduced state space model of the drive with only two state variables, the rotor speed and the rotor position. It is proved by simulations and experiments that the EKF with this reduced model has the same performance as the four-dimensional full state space model at much lower computational cost. The sensorless DTC with the reduced model EKF was found to be equal to DTC with the full model EKF in terms of performance and superior in terms of computational cost. All experiments were carried out on a laboratory prototype of the drive with rated power of 250 W.
机译:本文的目的是研究扩展卡尔曼滤波器(EKF)在由直接转矩控制(DTC)控制的永磁同步电动机(PMSM)驱动器的无传感器控制中的应用。 DTC的主要缺点是必须缩短采样周期。因此,EKF面临的挑战是最大限度地缩短其执行时间。这通过使用仅具有两个状态变量(即转子速度和转子位置)的驱动器的所谓缩减状态空间模型来实现。通过仿真和实验证明,具有这种简化模型的EKF具有与四维全状态空间模型相同的性能,但计算成本却低得多。发现具有简化型号EKF的无传感器DTC在性能方面与具有完整型号EKF的DTC相等,并且在计算成本方面也优越。所有实验均在额定功率为250 W的驱动器的实验室原型上进行。

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