Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs

This paper investigates the modeling of brushless permanent-magnet synchronous machines (PMSMs). The focus is on deriving an automatable process for obtaining dynamic motor models that take nonlinear effects, such as saturation, into account. The modeling is based on finite element (FE) simulations...

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Veröffentlicht in:	IEEE transactions on industrial electronics (1982) 2014-11, Vol.61 (11), p.6454-6462
Hauptverfasser:	Bramerdorfer, Gerd, Winkler, Stephan M., Kommenda, Michael, Weidenholzer, Guenther, Silber, Siegfried, Kronberger, Gabriel, Affenzeller, Michael, Amrhein, Wolfgang
Format:	Artikel
Sprache:	eng
Schlagworte:	Analytical models artifical neural network Brushless machine cogging torque field-oriented control Finite element analysis genetic programming Iron modeling Neural networks permanent magnet Permanent magnet motors random forests Rotors Stators symbolic regression Torque torque ripple Vectors
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