LAPSE:2023.19054
Published Article
LAPSE:2023.19054
Regression Model-Based Flux Observer for IPMSM Sensorless Control with Wide Speed Range
Jongwon Choi
March 9, 2023
Abstract
A new linear regression form is derived for a flux observer and a position observer is designed. In general, the observability of the permanent-magnet synchronous motor is lost at zero speed. In this work, the proposed regressor vector contains current derivative terms in both directions (dq-axis), and it gives the chance for the model-based flux observer to operate at zero speed. When an excitation signal is injected into d and q axes with the proposed flux observer, it helps to satisfy the persistent excitation condition in the low-speed range. Therefore, the sensorless performance of the model-based is improved greatly, even at zero speed. However, it appears with a disturbance term, which depends on the derivative of the d-axis current. Thus, the disturbance does not vanish when an excitation signal is injected. In this work, the disturbance term is also taken care of in constructing an observer. It results in an observer which allows signal injection. Thus, high frequency signal can be injected in the low speed region and turned off when it is unnecessary as the speed increases. This model-based approach utilizes the signal injection directly without recurring to a separate high frequency model. In other words, it provides a seamless transition without switching to the other algorithm. The validity is demonstrated by simulation and experimental results under various load conditions near zero speed.
Keywords
active flux, gradient algorithm, IPMSM, linear regression form, nonlinear observer, persistence of excitation, sensorless algorithm, signal injection
Suggested Citation
Choi J. Regression Model-Based Flux Observer for IPMSM Sensorless Control with Wide Speed Range. (2023). LAPSE:2023.19054
Author Affiliations
Choi J: Department of Electrical and Electronic Engineering, Hannam University, Daejeon 34430, Korea
Journal Name
Energies
Volume
14
Issue
19
First Page
6249
Year
2021
Publication Date
2021-10-01
ISSN
1996-1073
Version Comments
Original Submission
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PII: en14196249, Publication Type: Journal Article
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LAPSE:2023.19054
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