An in-phase filter-based flux observation strategy for sensorless control of PMSMs.

ISA Trans

School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. Electronic address:

Published: December 2024

AI Article Synopsis

  • - The paper highlights the challenges of detecting rotor flux in permanent magnet synchronous machines (PMSMs) due to interference from DC components and harmonics in traditional methods.
  • - It introduces an in-phase filter (IPF) approach, utilizing a double second-order generalized integrator (DSOGI) for precise electrical frequency and a phase angle compensation transfer function (PACTF) for signal adjustment.
  • - Through experiments, the IPF strategy demonstrates improved accuracy in observing rotor flux, speed, and position, showing superior performance compared to existing methods, particularly a 5% improvement over cascade second-order generalized integral techniques.

Article Abstract

Due to the complexity of determining the initial rotor flux and detecting errors, conventional rotor flux observation methods are easily affected by direct current (DC) components and harmonics. To address this issue, this paper proposes an in-phase filter (IPF)-based rotor flux observation strategy for sensorless control of permanent magnet synchronous machines (PMSMs). The core components of the IPF consist of a double second-order generalized integrator (DSOGI) and a phase angle compensation transfer function (PACTF). The DSOGI provides a accurate electrical angular frequency, while the PACTF implements a phase correction to the v signals. By employing IPF structure, accurate observations for rotor flux, electronic speed, and rotor position are achieved, which can be effectively used in the sensorless control of PMSMs, eliminating the need for magnitude and phase compensations. Finally, the proposed observation strategy is applied to an experimental bench of a PMSM, and its effectiveness is illustrated by experimental results. From experimental results, it can be concluded that the IPF is significantly better than the LPF, and 5% more accurate than the observer based on cascade second-order generalized integral(CSOGI) overall.

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http://dx.doi.org/10.1016/j.isatra.2024.09.030DOI Listing

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