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Improved Finite Control-Set Model-Based Direct Power Control of BLDC Motor With Reduced Torque Ripple.

Authors :
de Castro, Allan Gregori
Pereira, William Cesar Andrade
de Almeida, Thales Eugenio Portes
de Oliveira, Carlos Matheus Rodrigues
Roberto Boffino de Almeida Monteiro, Jose
de Oliveira, Azauri Albano
Source :
IEEE Transactions on Industry Applications. Sep2018, Vol. 54 Issue 5, p4476-4484. 9p.
Publication Year :
2018

Abstract

This paper deals with active torque ripple compensation based on direct power control of permanent magnet brushless DC (BLDC) motor drive. The torque undulations caused by the mismatch between stator current and its nonsinusoidal back electromotive force (back EMF) waveforms is a well-known issue on BLDC motor drives. In this paper, to remedy this problem, a simple and comprehensive direct power control based approach is proposed. Instead of using conventional field-oriented control or direct torque control schemes, which are widely used in ac machines with sinusoidal flux distribution, an alternative approach is presented to control the mutual torque production through an active and reactive rotor power control loop. As a result, the proposed approach provides a simple way to reduce torque ripple of a permanent magnet synchronous motor with nonsinusoidal back EMF without requiring rotor orientation or back EMF harmonic content estimation method. In order to synthesize the proper input voltages in the context of torque ripple minimization, high bandwidth controllers are required to cope the torque ripple frequencies. In this sense, the power control loop is implemented based on two-vector finite control-set model-based predictive control approach, which provides fast torque response and good steady-state performance. The validity of the proposed control scheme for low torque ripple BLDC motor drive is verified through experimental results, achieving good steady-state performance while maintaining quick dynamic response. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00939994
Volume :
54
Issue :
5
Database :
Academic Search Index
Journal :
IEEE Transactions on Industry Applications
Publication Type :
Academic Journal
Accession number :
131880517
Full Text :
https://doi.org/10.1109/TIA.2018.2835394