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• W2898041722 abstract "The expanding market interest on Permanent Magnet Synchronous Motors (PMSM) invoked the emphasis on their efficient control and design optimization. The highperformance control of a motor demands the precise identification of several machine parameters, namely the phase resistance (and dead-time effect curve), d - and q -axis inductances or flux vs. current characteristic and the Permanent Magnet flux-linkage magnitude (PM-flux). In this paper a novel technique for the identification of PM-flux, which does not require the use of a mechanical position or speed sensor is presented. The motor is supposed to be free to move or subject to light load. DC current is imposed (close to nominal amplitude) and the current vector is then rotated by a limited amount, forcing rotor to rotate through the same angle. A mathematical model is developed to estimate the PM-flux using measured voltages and currents within this limited rotor movement. The stator resistance estimation and voltage offset error compensation are also included in this implementation. The method requires the knowledge of angular transition of the rotor to estimate the flux rather than its position. For the Surface Mount-PMSM (SM-PMSM), the initial and final rotor position are determined by the direction of DC current vector, while for the Interior-PMSM (IPMSM), HFI methods could be applied, thus eliminating the need of position sensor in either case. Simulation and experimental results provided on a SM-PMSM confirms the validity of the proposed method. The technique can estimate PM-flux with an error lower than 10%." @default.
• W2898041722 created "2018-10-26" @default.
• W2898041722 creator A5051489234 @default.
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• W2898041722 date "2018-09-01" @default.
• W2898041722 modified "2023-10-18" @default.
• W2898041722 title "Self-Commissioning Identification of Permanent Magnet Flux-Linkage Magnitude in Sensorless Drives for PMSM at Quasi Stand-Still" @default.
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• W2898041722 doi "https://doi.org/10.1109/sled.2018.8486116" @default.
• W2898041722 hasPublicationYear "2018" @default.
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