Backward Extended Kalman Filter to Estimate and Adaptively Control a PMSM in Saturation Conditions

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This article describes the use of a combined extended Kalman filter, which is calculated using backward Euler discretization and a bivariate polynomial for the estimation of saturated nonlinear augmented states Ld and Lq. The benefit is the further processing of inductance in the control of a permanent magnetic synchronous machine. Backward Euler discretization is proposed in an extended Kalman filter structure to obtain stability for long sampling times, which are due to the complexity of software to be implemented in the microcontroller. Hardware in the loop (HIL), as an emulator, is used for validation of the functionality of the presented estimation method in the saturation region under the influence of both cross-coupling effects and spatial harmonics as well as under the influence of temperature variation in superposition. Measured results using HIL to validate the proposed algorithm and a discussion of the algorithm's advantages and disadvantages are included.
Original languageEnglish
JournalIeee Journal of Emerging and Selected Topics in Industrial Electronics
Volume5
Issue number2
Pages (from-to)462-474
Number of pages13
ISSN2687-9735
DOIs
Publication statusPublished - 01.04.2024

    Research areas

  • Bivariate polynomial, extended Kalman filter (EKF), hardware in the loop (HIL) validation, Parameter estimation, permanent magnetic synchronous machine (PMSM)
  • Engineering

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