DocumentCode :
3566081
Title :
Identification of a nonlinear PMSM model using symbolic regression and its application to current optimization scenarios
Author :
Bramerdorfer, Gerd ; Amrhein, Wolfgang ; Winkler, Stephan M. ; Affenzeller, Michael
Author_Institution :
Inst. for Electr. Drives & Power Electron., Johannes Kepler Univ. Linz, Linz, Austria
fYear :
2014
Firstpage :
628
Lastpage :
633
Abstract :
This article presents the nonlinear modeling of the torque of brushless PMSMs by using symbolic regression. It is still popular to characterize the operational behavior of electrical machines by employing linear models. However, nowadays most PMSMs are highly utilized and thus a linear motor model does not give an adequate accuracy for subsequently derived analyses, e.g., for the calculation of the maximum torque per ampere (MTPA) trajectory. This article focuses on modeling PMSMs by nonlinear white-box models derived by symbolic regression methods. An optimized algebraic equation for modeling the machine behavior is derived using genetic programming. By using a Fourier series representation of the motor torque a simple to handle model with high accuracy can be derived. A case study is provided for a given motor design and the motor model obtained is used for deriving the MTPA-trajectory for sinusoidal phase currents. The model is further applied for determining optimized phase current waveforms ensuring zero torque ripple.
Keywords :
Fourier series; brushless machines; linear motors; optimisation; permanent magnet machines; regression analysis; synchronous machines; torque motors; Fourier series representation; MTPA trajectory; algebraic equation; brushless PMSM torque; current optimization scenarios; electrical machines; genetic programming; linear motor; maximum torque per ampere trajectory; motor torque; nonlinear PMSM model; nonlinear white box models; sinusoidal phase currents; symbolic regression; Brushless motors; Mathematical model; Optimization; Permanent magnet motors; Rotors; Stators; Torque; Brushless machines; MTPA; cogging torque; symbolic regression; torque ripple;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2014 - 40th Annual Conference of the IEEE
Type :
conf
DOI :
10.1109/IECON.2014.7048566
Filename :
7048566
Link To Document :
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