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Implementation of Extended Kalman Filter with Optimized Execution Time for Sensorless Control of a PMSM Using ARM Cortex-M3 Microcontroller
Abstract
This paper addresses the implementation and optimization of an Extended Kalman Filter (EKF) for the Permanent Magnet Synchronous Motor (PMSM) sensorless control using an ARM Cortex-M3 microcontroller. A various optimization levels based on arithmetic calculation reduction was implemented in ARM Cortex-M3 microcontroller. The execution time of EKF estimator was reduced from 260.4 μs to 37.7 μs without loss of accuracy. To further reduce EKF execution time, the separation of a Kalman gain and covariance matrices calculation from prediction and measurement state update, a novel method was proposed, and the performance of it an EKF estimator with separation of a Kalman gain and covariance matrices calculation from prediction and measurement state update was analyzed. Simulation and experiments results validate that the proposed technique could provide the same accuracy with less computation time. A tendency of minimum Kalman gain and covariance matrices calculation frequency from rotor electrical frequency was analyzed and are presented in the paper.
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Authors (3)
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Justas Dilys
- State Research Institute Center for Physical Sciences and Technology, Vilnius, Lithuania
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Voitech Stankevič
- State Research Institute Center for Physical Sciences and Technology, Vilnius, Lithuania
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Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/en14123491
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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ENERGIES
no. 14,
ISSN: 1996-1073 - Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Dilys J., Stankevič V., Łuksza K.: Implementation of Extended Kalman Filter with Optimized Execution Time for Sensorless Control of a PMSM Using ARM Cortex-M3 Microcontroller// ENERGIES -Vol. 14,iss. 12 (2021), s.3491-
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/en14123491
- Verified by:
- Gdańsk University of Technology
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