DocumentCode :
2331027
Title :
Minimization of commutation torque ripple in brushless DC motors with optimized input voltage control
Author :
Ashabani, Mahdi ; Kaviani, A.K. ; Milimonfared, Jafar ; Abdi, Babak
Author_Institution :
Electr. Eng. Dept., Amirkabir Univ. of Technol., Tehran
fYear :
2008
fDate :
11-13 June 2008
Firstpage :
250
Lastpage :
255
Abstract :
This paper presents the method of reducing torque ripple of brushless DC (BLDC) motor. The commutation torque ripple is reduced by control of the DC link voltage during the commutation time. The magnitude of voltage and commutation time is estimated by a neural network and optimized with a new optimization method named particle swarm optimization (PSO) algorithm analysis. The goal of optimization is to minimize the error between the command torque and real torque and doesnpsilat need knowledge of the conduction interval of the three phases. It adaptively adjusts the DC link voltage in commutation duration so that commutation torque ripple is effectively reduced. In this paper, the performance of the proposed brushless DC (BLDC) control is compared with that of conventional BLDC drives without input voltage control.
Keywords :
DC motor drives; brushless DC motors; commutation; electric machine analysis computing; machine control; minimisation; neural nets; particle swarm optimisation; torque control; voltage control; DC link voltage control; brushless DC motors; commutation torque ripple minimization; neural network; optimized input voltage control; particle swarm optimization algorithm analysis; Algorithm design and analysis; Brushless DC motors; Brushless motors; Commutation; DC motors; Neural networks; Optimization methods; Particle swarm optimization; Torque control; Voltage control; BLDC machines; Commutation; Optimized input voltage; Torque ripple;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics, Electrical Drives, Automation and Motion, 2008. SPEEDAM 2008. International Symposium on
Conference_Location :
Ischia
Print_ISBN :
978-1-4244-1663-9
Electronic_ISBN :
978-1-4244-1664-6
Type :
conf
DOI :
10.1109/SPEEDHAM.2008.4581076
Filename :
4581076
Link To Document :
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