Precision control of a sensorless PM BLDC motor using PLL control algorithm
This paper presents particular methods for deployment of precision control of a sensorless permanent magnet brushless DC (PM BLDC) motor using PLL control algorithm. Firstly, we utilizes the third harmonic of the motor internal voltages to determine the commutation instants of the PM BLDC motor for sensorless control. The waveform of the motor internal voltages (or back emf) contains fundamental and higher-order frequency harmonics. Therefore, the third harmonic component is extracted from the stator phase voltage. The resulting third harmonic signal maintains a constant phase relationship with the rotor flux at any motor speed and load condition. And is practically free of noise that can be introduced by the inverter switching, making this a robust sensing method. As a result, the method described here is not sensitive to filtering delays, allowing the motor to achieve a good performance over a wide speed range. For conventional 6-pulse control using the Hall-IC alone, this sensor misalignment would pose problems such as excessive torque ripple, noise, and inefficiency. Therefore, to implement the third harmonic sensing methods and speed control algorithm in this paper, the principle of the Johnson counter is used and it can estimate the same Hall-ICs signal with a non-difference phase resulting from the signals of the Johnson counter. Also, to precise control of a sensorless PM BLDC motor, we applied the position signal of phase lock loop (PLL) control algorithm and the remainder scheme in this paper, thus one can operate PM BLDC motor in high performance. Also, a simple starting method and speed estimation approach are proposed. Simulation an experimental results are provided, to demonstrate the validity of the precision control of a sensorless PM BLDC motor using PLL control algorithm.
KeywordsPM BLDC motor Sensorless PLL control algorithm Precision control Johnson counter
This study was conducted by research funds from Gwangju University in 2017.
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