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Analysis and Exploitation of the Star-Point Voltage of Synchronous Machines for Sensorless Operation

Author

Listed:
  • Emanuele Grasso

    (Laboratory of Actuation Technology, Saarland University, 66123 Saarbrücken, Germany)

  • Riccardo Mandriota

    (Laboratory of Actuation Technology, Saarland University, 66123 Saarbrücken, Germany)

  • Niklas König

    (Laboratory of Actuation Technology, Saarland University, 66123 Saarbrücken, Germany)

  • Matthias Nienhaus

    (Laboratory of Actuation Technology, Saarland University, 66123 Saarbrücken, Germany)

Abstract

In the field of sensorless drive of synchronous machines (SMs), many techniques have been proposed that can be applied successfully in most applications. Nevertheless, these techniques rely on the measurement of the phase currents to extract the rotor position information. In the particular case of low-power machines, the application of such techniques is challenging due to the limited bandwidth of the available current sensors. An alternative is offered by those techniques that exploit the star-point voltage rather than phase currents. This work aims at providing a model of the dynamic behavior of the star-point voltage and presenting a technique for extracting the rotor electrical position needed for sensorless operation of SMs. Two different circuitries for measuring the star-point voltage are also presented and then compared. The presented mathematical analysis and the measurement methods are validated both numerically and experimentally on a test machine.

Suggested Citation

  • Emanuele Grasso & Riccardo Mandriota & Niklas König & Matthias Nienhaus, 2019. "Analysis and Exploitation of the Star-Point Voltage of Synchronous Machines for Sensorless Operation," Energies, MDPI, vol. 12(24), pages 1-21, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4729-:d:296839
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    Citations

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    Cited by:

    1. Emanuele Grasso & Marco Palmieri & Riccardo Mandriota & Francesco Cupertino & Matthias Nienhaus & Stephan Kleen, 2020. "Analysis and Application of the Direct Flux Control Sensorless Technique to Low-Power PMSMs," Energies, MDPI, vol. 13(6), pages 1-27, March.
    2. Stefano Fabbri & Klaus Schuhmacher & Matthias Nienhaus & Emanuele Grasso, 2021. "Improvement of Position Estimation of PMSMs Using an Iterative Vector Decoupling Algorithm," Energies, MDPI, vol. 14(1), pages 1-23, January.
    3. Romain Brasse & Jonah Vennemann & Niklas König & Matthias Nienhaus & Emanuele Grasso, 2022. "Design and Implementation of a Driving Strategy for Star-Connected Active Magnetic Bearings with Application to Sensorless Driving," Energies, MDPI, vol. 16(1), pages 1-18, December.

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