Analysis of Recent Developments in Brushless DC Motors Controlling Techniques
Y. Ramachandra1, M. Akhileshwar2, A. Pandian3, Rajesh Nalli4, K. Subbarao5
1Y.RAMACHANDRA, UG Student, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
2M.AKHILESHWAR, UG Student, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
3A.PANDIAN, Professor, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
4RAJESH NALLI, Research Scholar, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
5K.SUBBARAO, Professor, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram (A.P), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 522-526 | Volume-8 Issue-5, March 2019 | Retrieval Number: D3169028419/19©BEIESP
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Abstract: BLDC motors are the latest option for research people due to their inherent features like high efficiency, constant flux density low maintenance requirements there by it acquire greater reliability. These motors are best suited for many applications, but it needs developments in sensorless control methods to overcome the draw backs of the sensor-based techniques. Within the available control strategies, the flux linkage function-based control strategy is certainly appropriate for BLDC motor even at low-speed range. This paper presents working and behavior of BLDC motor with various controlling techniques with closed loop operation, the function of sensors and its importance, different sensor based and sensorless control techniques were discussed. The modeling of BLDC machine done under MATLAB environment. Closed loop operation of BLDC drive using PI controller helped to analyze the dynamic behavior of drive.
Keyword: Permanent Magnet Brushless DC Motor (PMBLDCM), Hall Sensors, Shaft-Encoders, Zero Crossing Back Electromotive Force (EMF), Flux Linkage Based Sensorless Technique.
Scope of the Article: Pattern Recognition and Analysis