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Improvement of Position Estimation of PMSMs Using an Iterative Vector Decoupling Algorithm

Author

Listed:
  • Stefano Fabbri

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

  • Klaus Schuhmacher

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

  • Matthias Nienhaus

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

  • Emanuele Grasso

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

Abstract

This paper presents an improvement of sensorless techniques based on anisotropy for the estimation of the electrical angular position of synchronous machines by means of an iterative algorithm. The presented method reduces the effect of the fourth saliency harmonics on the measured signals avoiding the use of an observer or filter, thus, no additional dynamics are introduced on the system. Instead, a static algorithm based on iterative steps is proposed, minimizing the angular position error. The algorithm is presented and applied using the DFC (Direct Flux Control) technique but it is not limited to this choice. The advantages and limitations of this method are presented within this paper. The proof of the algorithm convergence is given. Simulations and experimental tests are performed in order to prove the effectiveness of the proposed algorithm.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:1:p:245-:d:474976
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    References listed on IDEAS

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    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. 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.
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