Introducing a New Hybrid Method to Reduce BLDC Motor Torque Ripple, Based on Predictive Control and Quasi Z-Source Converter

The commutation torque ripple adversely affects the performance of the six-phase inverter of the BLDC motor with trapezoidal back EMF and creates vibration and noise for industrial applications. In this paper, the motor model is obtained in non-commutation times and during the commutation period, and according to that, a suitable method to reduce the torque ripple, by equalizing the slope of the current disconnected from the motor and the slope of the current connected to the motor during commutation, is presented. At low speeds, torque ripple is reduced using predictive pulse width modulation technique. With this method, the duty cycle of the switch involved in the commutation is predicted and applied to the switch during the commutation intervals. At high speeds, this reduction is done using quasi z-source converter and selector circuit. The quasi z-source converter and the selector circuit increase the input voltage of the inverter during commutation intervals and increase its value to four times the back EMF voltage of the motor, thus reducing the torque ripple at high speeds. The theoretical and analytical results are verified using the simulations performed in the PLECS software

Estimation of Electrical Parameters of the Induction Machine Steady State Model Using Nameplate Data and Hunger Game Search Algorithm

In this paper, the Hunger Games Search (HGS) optimization algorithm is used to estimate the electrical parameters of the induction machine steady state model. Induction machine nameplate data is used as input to the proposed algorithm. The performance of the proposed method is confirmed by comparing the output characteristics obtained by estimating the motor parameters including torque, current and power factor in the steady state model of the induction machine with the values provided by the manufacturer. In addition, by evaluating and comparing the results of the proposed method with the results of previous research, it is shown that the proposed algorithm is a very effective and accurate method for the acceptable estimation of induction machine parameters