Online Parameters Identification for an IPMSM Based on Extended Kalman Filter

This paper introduces an online identification of d-q axis apparent inductance in an interior permanent magnet synchronous machines (IPMSM) using extended Kalman filter (EKF). The primary objective is to achieve accurate tracking of apparent inductances, which are nonlinear and varies under different operating conditions. The apparent inductances are crucial for calculating electromagnetic torque. A nonlinear IPMSM model based on finite element analysis (FEA) is employed for simulations. The effectiveness of the proposed approach is demonstrated through MATLAB/Simulink simulations. To verify the efficiency of real-world application, two machines with different conditions were investigated under various operating scenarios, with the results compared to steady state analysis to ensure the accuracy of the proposed estimation method.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.23919/icems60997.2024.10921339
Primary Topic
Inertial Sensor and Navigation
Type
article
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Online Parameters Identification for an IPMSM Based on Extended Kalman Filter

Sompob Polmai, Supat Kittiratsatcha, Khanaphot Treebubpha
Inertial Sensor and Navigation
article

Online Parameters Identification for an IPMSM Based on Extended Kalman Filter

Sompob Polmai, Supat Kittiratsatcha, Khanaphot Treebubpha
article en

Abstract

This paper introduces an online identification of d-q axis apparent inductance in an interior permanent magnet synchronous machines (IPMSM) using extended Kalman filter (EKF). The primary objective is to achieve accurate tracking of apparent inductances, which are nonlinear and varies under different operating conditions. The apparent inductances are crucial for calculating electromagnetic torque. A nonlinear IPMSM model based on finite element analysis (FEA) is employed for simulations. The effectiveness of the proposed approach is demonstrated through MATLAB/Simulink simulations. To verify the efficiency of real-world application, two machines with different conditions were investigated under various operating scenarios, with the results compared to steady state analysis to ensure the accuracy of the proposed estimation method.

King Mongkut's Institute of Technology Ladkrabang (TH)
Openalex Percentile: Top 53%
Inertial Sensor and Navigation
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