Automatic Tuning of Extended Kalman Filter in Synchronous Reluctance Motor Drives with a Master-Slave Configuration
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in: IEEE Open Journal of Power Electronics, 2025.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Automatic Tuning of Extended Kalman Filter in Synchronous Reluctance Motor Drives with a Master-Slave Configuration
AU - Rigon, Saverio
AU - Haus, Benedikt
AU - Mercorelli, Paolo
AU - Zigliotto, Mauro
N1 - Publisher Copyright: © 2025 IEEE. All rights reserved.
PY - 2025
Y1 - 2025
N2 - A substantial reduction in the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRM). As low-cost motors, SynRMs are commonly employed in sensorless AC drives. Sensorless algorithms based on the Extended Kalman Filter (EKF) offer several advantages, but they require a time-consuming trial-and-error tuning procedure. This paper proposes the automatic tuning of the EKF through a second Kalman Filter (KF) in a masterslave (MS) configuration. The two KFs work concurrently: the first estimates the required quantities for machine control, and the second updates the process noise statistics of the first KF. The second KF is much easier to tune, requiring only one non-critical parameter. Experimental results confirm the validity of this approach.
AB - A substantial reduction in the human environmental footprint can be achieved through the use of more efficient motors, such as synchronous reluctance motors (SynRM). As low-cost motors, SynRMs are commonly employed in sensorless AC drives. Sensorless algorithms based on the Extended Kalman Filter (EKF) offer several advantages, but they require a time-consuming trial-and-error tuning procedure. This paper proposes the automatic tuning of the EKF through a second Kalman Filter (KF) in a masterslave (MS) configuration. The two KFs work concurrently: the first estimates the required quantities for machine control, and the second updates the process noise statistics of the first KF. The second KF is much easier to tune, requiring only one non-critical parameter. Experimental results confirm the validity of this approach.
KW - AC machines
KW - Adaptive Kalman Filter
KW - Kalman Filter
KW - Master-Slave Kalman Filter
KW - Sensorless
KW - Synchronous Reluctance Motor (SynRM)
UR - http://www.scopus.com/inward/record.url?scp=85219473750&partnerID=8YFLogxK
U2 - 10.1109/OJPEL.2025.3546752
DO - 10.1109/OJPEL.2025.3546752
M3 - Journal articles
AN - SCOPUS:85219473750
JO - IEEE Open Journal of Power Electronics
JF - IEEE Open Journal of Power Electronics
SN - 2644-1314
ER -