Position sensorless extended and unscented Kalman filters with permanent magnet flux linkage and load torque estimation for surface-mounted PMSM

In this paper, novel position sensorless state estimators with improved robustness to permanent magnet (PM) flux linkage variations in permanent magnet synchronous machines (PMSMs) are presented. Unlike state estimators using conventional infinite inertia or electromechanical models, the estimators...

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Bibliographic Details
Published in:Automatika 2024-07, Vol.65 (3), p.1201-1212
Main Author: Horváth, Krisztián
Format: Article
Language:English
Subjects:
Algorithms
Estimators
extended and unscented Kalman filters
Kalman filters
load torque estimation
nonlinear observability
Observability (systems)
Parameter estimation
permanent magnet flux linkage estimation
Permanent magnet synchronous machine
Permanent magnets
Position sensing
position sensorless state estimation
Real time
Sensors
State estimation
Synchronous machines
Synchronous motors
Uncertainty
Velocity
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Summary:In this paper, novel position sensorless state estimators with improved robustness to permanent magnet (PM) flux linkage variations in permanent magnet synchronous machines (PMSMs) are presented. Unlike state estimators using conventional infinite inertia or electromechanical models, the estimators presented here can also estimate the PM flux linkage, so they are not sensitive to its uncertainty. For each models used for state estimation, a detailed observability study is presented. Due to the nonlinear models, extended and unscented Kalman filter algorithms are used for the implementation. To compare the sensitivity of conventional and proposed state estimators to uncertainty in electrical parameters, numerical simulations are carried out. In addition, the computational burden of the estimators is compared by real-time execution.
ISSN:0005-1144
1848-3380
DOI:10.1080/00051144.2024.2354643