Position and Speed Estimation Algorithm for Permanent Magnet Synchronous Machines Considering Nonlinear Magnetic Effects

Brodatzki, Matthias; Richter, Jan; Kolb, Johannes; Braun, Michael

doi:10.23919/icpe2019-ecceasia42246.2019.8796980

Cited by 3 publications

(2 citation statements)

References 15 publications

(19 reference statements)

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“…In recent years, an approach using numerical optimization to estimate the rotor position and speed of a PMSM has gained interest [5], [6], [7], [8]. When applying numerical optimization, the stator voltage equation of the PMSM is evaluated.…”

Section: Introductionmentioning

confidence: 99%

“…Compared to the state of the art, the simple description of the transfer function leads to advantages during commissioning. In the majority of the publications, the design of the parameters of the SSC and the speed control is not described [2], [3], [5], [6], [7], [8], [9], [10], [11]. While the publication [13] gives rules for the parametrization of the position estimation, speed control is not addressed.…”

Section: Introductionmentioning

confidence: 99%

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Analytical Design of Self-Sensing Control for PMSM Using Quasi-Direct Calculation

Himker

Mertens

2023

IEEE Open J. Ind. Applicat.

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The analytical description and parameterization of a self-sensing control (SSC) for an electrical machine is an important step toward easier commissioning of these systems. In this article, the advantages of high bandwidth position estimation via numerical optimization and the filtering characteristics of a phaselocked loop are combined in the quasi-direct (QD) calculation. The QD calculation uses two parameters for estimation. With the help of the maximum possible acceleration of the drive train, an interdependency between these two parameters is derived. The remaining degree of freedom is used to tune the dynamics of the estimation. Using the transfer function of the estimator, which is derived analytically, the parameters of the speed control are selected, and a specified phase-margin is implemented. With the help of the analytical parameterization, no empirical or numerical tuning needs to be done, which is unique for SSC. All results are experimentally validated.

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Section: Introductionmentioning

confidence: 99%