A novel neural network based current injection technique for torque ripple reduction in BLDCM

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.