Parameter Identification of Inverter-Fed Induction Motors: A Review

Jing Tang,Yongheng Yang,Jie Chen,Zhigang Liu,Frede Blaabjerg,Lijun Diao

doi:10.3390/en11092194

Abstract

Induction motor parameters are essential for high-performance control. However, motor parameters vary because of winding temperature rise, skin effect, and flux saturation. Mismatched parameters will consequently lead to motor performance degradation. To provide accurate motor parameters, in this paper, a comprehensive review of offline and online identification methods is presented. In the implementation of offline identification, either a DC voltage or single-phase AC voltage signal is injected to keep the induction motor standstill, and the corresponding identification algorithms are discussed in the paper. Moreover, the online parameter identification methods are illustrated, including the recursive least square, model reference adaptive system, DC and high-frequency AC voltage injection, and observer-based techniques, etc. Simulations on selected identification techniques applied to an example induction motor are presented to demonstrate their performance and exemplify the parameter identification methods.

Highlights

Induction motors (IMs) are widely used in practical industrial applications due to the low cost, high robustness, and high reliability [1]
With the discussion and consideration, the aim of this paper is to provide a detailed and comprehensive review of the offline and online parameter identification methods for IM systems
The methods based on the recursive least square, model reference adaptive system, and DC injection are commonly used and implemented

Summary

Introduction

Induction motors (IMs) are widely used in practical industrial applications due to the low cost, high robustness, and high reliability [1]. No matter which method is used, the drive performance highly depends on motor parameters. In the IFOC method, the rotor flux position is calculated by adding the measured rotor angular frequency from a speed sensor and the computed slip angular frequency from the torque command. The rotor flux orientation of the IFOC heavily depends on the slip frequency, which is relative to the rotor resistance and rotor inductance. The stator resistance is essential for the flux estimation, especially in low-frequency applications.

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Conclusion