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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This book presents a broad explanation on the effect of performance of an open-loop and closed loop control of a Brushless Direct Current (BLDC) Motor drive supplied from a two-level voltage source inverter (VSI) working on 120-degree mode of conduction, simulated in MATLAB based software for both No-load and load condition. BLDC motors are superior to other motors because of the high reliability, good efficiency, high power concentration, simplicity of control and mainly the brushless operation. It is found that by tuning the value of rotor position the variation in torque can be minimized. Different performance parameters for no-load and load condition of the BLDC motor like phase voltages and currents, speed, electromagnetic torque, direct-axis, quadrature-axis current and rotor position etc. are determined in MATLAB environment. This book focuses on exploring and estimating the efficiency of a continuous brushless DC motor (PMBLDC) drive, controlled by a current controller with various combinations of Classical Controllers as Proportional Integral, Genetic Algorithm based PI, Proportional Integral Derivative Controller. Typical PWM operated control strategy is applied in the conventional two-level voltage source inverter (VSI) fed permanent magnet (BLDC) motor to minimize the torque ripple. As the inner current loop should be ahead in procedure associated with the external speed loop, thus PI controllers are mostly chosen as a current controller. These controller gains are enhanced by means of two optimization methods of Particle swarm optimization and Genetic algorithm to get a better response by eliminating steady-state error, maximum peak overshoot and decreasing the rising time, peak time, of the projected Brushless Direct Control motor drive.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This book presents a broad explanation on the effect of performance of an open-loop and closed loop control of a Brushless Direct Current (BLDC) Motor drive supplied from a two-level voltage source inverter (VSI) working on 120-degree mode of conduction, simulated in MATLAB based software for both No-load and load condition. BLDC motors are superior to other motors because of the high reliability, good efficiency, high power concentration, simplicity of control and mainly the brushless operation. It is found that by tuning the value of rotor position the variation in torque can be minimized. Different performance parameters for no-load and load condition of the BLDC motor like phase voltages and currents, speed, electromagnetic torque, direct-axis, quadrature-axis current and rotor position etc. are determined in MATLAB environment. This book focuses on exploring and estimating the efficiency of a continuous brushless DC motor (PMBLDC) drive, controlled by a current controller with various combinations of Classical Controllers as Proportional Integral, Genetic Algorithm based PI, Proportional Integral Derivative Controller. Typical PWM operated control strategy is applied in the conventional two-level voltage source inverter (VSI) fed permanent magnet (BLDC) motor to minimize the torque ripple. As the inner current loop should be ahead in procedure associated with the external speed loop, thus PI controllers are mostly chosen as a current controller. These controller gains are enhanced by means of two optimization methods of Particle swarm optimization and Genetic algorithm to get a better response by eliminating steady-state error, maximum peak overshoot and decreasing the rising time, peak time, of the projected Brushless Direct Control motor drive.