Title :
A novel neural network based current injection technique for torque ripple reduction in BLDCM
Author :
Vandhana, J. ; Sreekumar, T. ; Benny, A.
Author_Institution :
Electr. & Electron. Dept., Amal Jyothi Coll. of Eng., Kottayam, India
Abstract :
Neural Networks have made their mark in various fields of endeavor through their superior learning skills. In this paper, a Neural Network (NN) based reference model of a Brushless Direct Current Motor (BLDCM) has been developed in MATLAB/Simulink. During careful scrutiny, it was observed that the electromagnetic torque varies with the magnitude of the phase currents for motor operation between commutations and during commutation. Thus, constant torque production involves phase currents as the vital correction parameter. A novel torque control scheme through phase current control has been proposed in this work. The NNBLDCM has been employed to nullify the deviations in phase current waveforms at loaded condition of a real BLDCM through Neural Network based Current Injection Technique (NNCIT). The simulation results prove that the new technique improves the constant torque characteristic which, in turn, leads to an increase in the reliability of the BLDCM.
Keywords :
brushless DC motors; electric current control; machine control; neurocontrollers; torque control; BLDCM; NNCIT; brushless direct current motor; current injection technique; electromagnetic torque; neural network; phase current control; phase current waveform; torque control; torque ripple reduction; Artificial neural networks; Brushless DC motors; Load modeling; Mathematical model; Software packages; Torque; Brushless Direct Current Motor (BLDCM); MATLAB/Simulink; Neural Network(NN); Phase currents; Torque;
Conference_Titel :
Computing, Communications and Networking Technologies (ICCCNT),2013 Fourth International Conference on
Conference_Location :
Tiruchengode
Print_ISBN :
978-1-4799-3925-1
DOI :
10.1109/ICCCNT.2013.6726736