Piecewise Affine Magnetic Modeling of Permanent-Magnet Synchronous Machines for Virtual-Flux Control

Bernard Steyaert (), Ethan Swint, W. Wesley Pennington and Matthias Preindl ()
Additional contact information
Bernard Steyaert: Department of Electrical Engineering, Columbia University, New York, NY 10027, USA
Ethan Swint: Tau Motors, Inc.; Redwood City, CA 94063, USA
W. Wesley Pennington: Tau Motors, Inc.; Redwood City, CA 94063, USA
Matthias Preindl: Department of Electrical Engineering, Columbia University, New York, NY 10027, USA

Energies, 2022, vol. 15, issue 19, 1-14

Abstract: Accurate flux linkage magnetic models are essential for virtual-flux controllers in PMSMs. Flux linkage exhibits saturation and cross-saturation at high currents, introducing nonlinearities into the machine model. Virtual-flux controllers regulate the flux of a machine by using field-oriented control, such as model predictive control. In this study, a methodology for creating a piecewise affine flux linkage magnetic model is proposed which locally linearizes the inductance and flux offset of the machine. This method keeps the magnetic model and thus the state-space model of the system linear while capturing the saturation effects, enabling robust controls and efficient operation. The model is created using FEA-simulated data points and verified with experimental datapoints. An algorithm to optimize the model in MTPA and derated operation is presented with an average flux error less than 1 % and maximum error less than 3 % using only 40 points. This represents a ≈ 1–3% and ≈5–8% reduction in the average and maximum flux errors compared with a regularly gridded model, respectively.

Keywords: flux estimation; motor parameters; piecewise linear techniques; permanent-magnet synchronous machines (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/19/7259/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/19/7259/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:19:p:7259-:d:932431

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().