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Identification of Linear Permanent Magnet Synchronous Motor Parameters and Inverter Non-Linearity Effects

Odhano, Shafiq; Tang, Mi; Formentini, Andrea; Zanchetta, Pericle; Bojoi, Radu

Authors

Shafiq Odhano

Mi Tang

Andrea Formentini

Radu Bojoi



Abstract

The paper presents an automatic parameter identification procedure for linear permanent magnet synchronous motors. The electrical parameters of a test machine are estimated by identification tests performed through the inverter. The method employs the available feedback signals that are needed by the control. The stator resistance and machine inductances are estimated through signal injection at standstill. The permanent magnets' flux-linkage identification instead requires carriage movement. Subsequently, the inverter nonlinearity characteristics are identified, again at standstill, through a flux-observer. The proposed self-commissioning process requires only the nameplate data of the machine and no datasheet information of the power electronic devices is needed. The developed techniques can be used both with and without a position sensor. The complete process is automatic and safe to run on its own and requires least intervention from the operator.

Citation

Odhano, S., Tang, M., Formentini, A., Zanchetta, P., & Bojoi, R. (2018). Identification of Linear Permanent Magnet Synchronous Motor Parameters and Inverter Non-Linearity Effects. In Proceedings: International Symposium on Power Electronics, Electrical Drives, Automation and Motion 2018 (26-32). https://doi.org/10.1109/SPEEDAM.2018.8445214

Conference Name 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)
Conference Location Amalfi, Italy
Start Date Jun 20, 2018
End Date Jun 22, 2018
Acceptance Date Mar 8, 2018
Online Publication Date Aug 26, 2018
Publication Date 2018-06
Deposit Date Nov 26, 2018
Publisher Institute of Electrical and Electronics Engineers
Pages 26-32
Book Title Proceedings: International Symposium on Power Electronics, Electrical Drives, Automation and Motion 2018
ISBN 978-1-5386-4942-8
DOI https://doi.org/10.1109/SPEEDAM.2018.8445214
Public URL https://nottingham-repository.worktribe.com/output/1307490
Publisher URL https://ieeexplore.ieee.org/document/8445214