Journal
IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 34, Issue 6, Pages 5880-5892Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2018.2867615
Keywords
Brushless dc (BLdc) motor; commutation signal; fuzzy neural network (FNN); sensorlessmotor; zero-crossing points (ZCPs) detection
Categories
Funding
- National Natural Science Foundation of China [61873020, 61403015]
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Phase-to-neutral voltage or neutral-to-virtual neutral voltage zero-crossing points (ZCPs) detection method is usually used for sensorless brushless dc motor commutation control. Unfortunately, neither of them can be realized in lower speed range. In this paper, a simple commutation point detection method is proposed based on detecting inactive phase terminal to dc-link midpoint voltage. It eliminates the requirement of neutral wire or virtual neutral voltage and provides an amplified version of back electromotive force at the ZCPs which makes the lower speed range detection possible. As the speed increases, commutation point error is enlarged due to the low-pass filter. Utilizing the symmetry of the terminal to midpoint voltage, the phase error can be corrected. However, due to the nonlinear relationship between the detected voltage difference and phase error, it is difficult to regulate the error fast and robustly. Therefore, a novel phase regulator based on fuzzy neural network is proposed in this paper with simple structure and learning ability. The validity of the proposed ZCPs detection method and commutation instant shift correction method are verified through experimental results.
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