Identification of a nonlinear PMSM model using symbolic regression and its application to current optimization scenarios

@article{Bramerdorfer2014IdentificationOA,
  title={Identification of a nonlinear PMSM model using symbolic regression and its application to current optimization scenarios},
  author={Gerd Bramerdorfer and Wolfgang Amrhein and Stephan M. Winkler and Michael Affenzeller},
  journal={IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society},
  year={2014},
  pages={628-633}
}
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… CONTINUE READING

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MagOpt - Optimization Tool for Mechatronic Components

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