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Sequence-Separation Complex-Vector Observer in Sensorless PMSM Drives for BEMF Trajectory Optimization
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AI
DOI：10.1109/TIE.2022.3196354.png)
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摘要
En 中文
The back electromotive force (BEMF) based position estimation is attractive for sensorless permanent magnet synchronous motor (PMSM) drives. However, it shows weak robustness against the low-frequency disturbance induced by the practical nonideal conditions. This results in the trajectory deviation of the estimated BEMF, causing apparent position-estimation error. To address this problem, this article proposed a sequence-separation complex-vector observer to optimize the trajectory of the estimated BEMF. First, a sequence-separation structure is designed to remove the response of the equivalent negative-sequence disturbance at the operation frequency. On this basis, the speed-adaptive disturbance compensation law is added to the observer to force the center of the estimated BEMF converging to the original point. Compared with the conventional method, the studied BEMF observer can ensure the accurate position estimation by optimizing the trajectory of the estimated BEMF. Finally, the studied algorithm is experimentally verified on a 2.2 kW ARM-based PMSM platform.
Keyword:
Observers
Phase locked loops
Frequency estimation
Estimation error
Mathematical models
Time-frequency analysis
Robustness
BEMF trajectory optimization
sensorless permanent magnet synchronous drives
sequence-separation complex-vector observer
sequence-separation structure
speed-adaptive compensation law
期刊
IF:
7.2
论文数:
1.8W
被引数:
9.8W