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2 Power Electronics and Drives

2 2018

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Introduction to the Special Section on State and Parameter Estimation Methods for Sensorless Drives

Barut M., Hinkkanen M., Orlowska-Kowalska T.

Power Electronics and Drives

2018

Vol. 3 (38), No. 1

111-113

This short article constitutes an introductory part of the Special Section (SS) on State and Parameter Estimation Methods in Sensorless Drives. In the current issue of the journal, the first part of this section is published. Accepted articles are focussed mainly on estimation of the state variables and parameters for vector-controlled induction motor (IM) drives, using different concepts, such as different types of Kalman filters (KFs) and model reference adaptive systems (MRASs). The KF was also proposed for brushless DC motor (BLDC). Also, neural networks (NNs) have been proposed for mechanical state variables’ estimation of the drive system with elastic couplings.

Extended Kalman filter based speed-sensorless load torque and inertia estimations with observability analysis for induction motors

Zerdali E., Barut M.

Power Electronics and Drives

2018

Vol. 3 (38), No. 1

115--127

This paper aims to introduce a novel extended Kalman filter (EKF) based estimator including observability analysis to the literature associated with the high performance speed-sensorless control of induction motors (IMs). The proposed estimator simultaneously performs the estimations of stator stationary axis components of stator currents and rotor fluxes, rotor mechanical speed, load torque including the viscous friction term, and reciprocal of total inertia by using measured stator phase currents and voltages. The inertia estimation is done since it varies with the load coupled to the shaft and affects the performance of speed estimation especially when the rotor speed changes. In this context, the estimations of all mechanical state and parameters besides flux estimation required for high performance control methods are performed together. The performance of the proposed estimator is tested by simulation and real-time experiments under challenging variations in load torque and velocity references; and in both transient and steady states, the quite satisfactory estimation performance is achieved.