A predictive control of a brushless DC generator is presented in this paper. Starting from the reference value of the electromagnetic torque developed by the generator, in order to satisfy the requirement of the tracking characteristic of the prime-mover, the switching pattern of the AC/DC converter is determined at each sampling period. The inverter commands are determined on the basis of constraints of minimum Joule losses and minimum torque ripple. A simulation study of a conversion system supplying a constant voltage DC grid is carried out in Matlab-Simulink environment. The simulation results of the system controlled by the proposed algorithm are compared to those of the same system achieved by traditional control. The comparison highlights the better performance of the generator by using the proposed control technique instead of the traditional one.

Brushless DC Generator Controlled by Predictive Algorithm

GATTO, GIANLUCA;MARONGIU, IGNAZIO;SERPI, ALESSANDRO
2009-01-01

Abstract

A predictive control of a brushless DC generator is presented in this paper. Starting from the reference value of the electromagnetic torque developed by the generator, in order to satisfy the requirement of the tracking characteristic of the prime-mover, the switching pattern of the AC/DC converter is determined at each sampling period. The inverter commands are determined on the basis of constraints of minimum Joule losses and minimum torque ripple. A simulation study of a conversion system supplying a constant voltage DC grid is carried out in Matlab-Simulink environment. The simulation results of the system controlled by the proposed algorithm are compared to those of the same system achieved by traditional control. The comparison highlights the better performance of the generator by using the proposed control technique instead of the traditional one.
2009
978-1-4244-2544-0
Brushless Machines, Permanent Magnet Generators, Predictive Control, Torque Control
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/109805
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