Detail publikace

Stator resistance identification of PMSM

VESELÝ, I. POHL, L.

Originální název

Stator resistance identification of PMSM

Anglický název

Stator resistance identification of PMSM

Jazyk

en

Originální abstrakt

The paper describes an online identification of a stator resistance of a permanent magnet synchronous motor. The resistance is identified by two methods. The first one is a frequency analysis based on an injection of a harmonic signal to the control. This method utilizes knowledge of synchronous motor schema in d-q coordinates and it is based on a mutual signals correlation. The second one - Gauss-Newton method utilizes Hammerstein model. In this method a loss function is created from this model, where the motor is divided into a linear dynamics and static nonlinearity. Both algorithms were tested on a real motor through a real time platform D-space.

Anglický abstrakt

The paper describes an online identification of a stator resistance of a permanent magnet synchronous motor. The resistance is identified by two methods. The first one is a frequency analysis based on an injection of a harmonic signal to the control. This method utilizes knowledge of synchronous motor schema in d-q coordinates and it is based on a mutual signals correlation. The second one - Gauss-Newton method utilizes Hammerstein model. In this method a loss function is created from this model, where the motor is divided into a linear dynamics and static nonlinearity. Both algorithms were tested on a real motor through a real time platform D-space.

Dokumenty

BibTex


@inproceedings{BUT128831,
  author="Ivo {Veselý} and Lukáš {Pohl}",
  title="Stator resistance identification of PMSM",
  annote="The paper describes an online identification of a stator resistance of a permanent magnet synchronous motor. The resistance is identified by two methods. The first one is a frequency analysis based on an injection of a harmonic signal to the control. This method utilizes knowledge of synchronous motor schema in d-q coordinates and it is based on a mutual signals correlation. The second one - Gauss-Newton method utilizes Hammerstein model. In this method a loss function is created from this model, where the motor is divided into a linear dynamics and static nonlinearity. Both algorithms were tested on a real motor through a real time platform D-space.",
  booktitle="Proceedings of 14th IFAC INTERNATIONAL CONFERENCE on PROGRAMMABLE DEVICES and EMBEDDED
SYSTEMS PDeS 2016 Preprint",
  chapter="128831",
  doi="10.1016/j.ifacol.2016.12.038",
  howpublished="electronic, physical medium",
  year="2016",
  month="october",
  pages="204--209",
  type="conference paper"
}