NDLI: A Sensor Fault Detection and Isolation Method in Interior Permanent-Magnet Synchronous Motor Drives Based on an Extended Kalman Filter

Content Provider	IEEE Xplore Digital Library
Author	Foo, G.H.B. Xinan Zhang Vilathgamuwa, D.M.
Copyright Year	1982
Abstract	Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.
Sponsorship	IEEE Industrial Electronics Society
Starting Page	3485
Ending Page	3495
Page Count	11
File Size	2369435
File Format	PDF
ISSN	02780046
Volume Number	60
Issue Number	8
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Stators Indexes Observers Synchronous motors Fault detection Voltage measurement stator current observer Current sensor phase identification extended Kalman filter (EKF) interior permanent-magnet synchronous motor (IPMSM) sensor fault detection sensor fault diagnosis sensor fault tolerant sensorless control
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications

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