Sun, T., Koc, M. and Wang, J.B. orcid.org/0000-0003-4870-3744 (2018) MTPA control of IPMSM drives based on virtual signal injection considering machine parameter variations. IEEE Transactions on Industrial Electronics, 65 (8). pp. 6089-6098. ISSN 0278-0046
Abstract
Due to parameter variations with stator currents, the derivatives of machine parameters with respect to current angle or d-axis current are not zero. However, these derivative terms are ignored by most of mathematical model based efficiency optimized control schemes. Therefore, even though the accurate machine parameters are known, these control schemes cannot calculate the accurate efficiency optimized operation points. In this paper, the influence of these derivative terms on maximum torque per ampere (MTPA) control is analyzed and a method to take into account these derivative terms for MTPA operation is proposed based on the recently reported virtual signal injection control (VSIC) method for interior permanent magnet synchronous machine (IPMSM) drives. The proposed control method is demonstrated by both simulations and experiments under various operating conditions on prototype IPMSM drive systems.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Interior permanent magnet synchronous machine (IPMSM) drives; maximum torque per ampere (MTPA); parameter variation; virtual signal injection control (VSIC) |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Jan 2018 14:10 |
Last Modified: | 14 Aug 2020 15:08 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/TIE.2017.2784409 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:126176 |