Initial rotor position estimation of salient-pole brushless DC motors by artificial neural network

This paper presents an initial rotor position estimation method for salient-pole brushless DC motors (BLDCMs). An artificial neural network (ANN) is employed as an estimator of BLDCM at standstill. The ANN can express the relationship between the voltage and current of BLDCMs. The initial rotor position can be estimated by using only the current-signals from the ANN. The proposed method has the advantages of measurement noise immunity as well as no sensitivity to machine parameters. Computer simulation results verify the usefulness of the proposed method.

[1]  R. Wu,et al.  A permanent magnet motor drive without a shaft sensor , 1990, Conference Record of the 1990 IEEE Industry Applications Society Annual Meeting.

[2]  Toshihiko Noguchi,et al.  Rotor position estimation method of sensorless PM motor at rest with no sensitivity to armature resistance , 1996, Proceedings of the 1996 IEEE IECON. 22nd International Conference on Industrial Electronics, Control, and Instrumentation.

[3]  B.K. Bose,et al.  Neural network based estimation of feedback signals for a vector controlled induction motor drive , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[4]  Nesimi Ertugrul,et al.  A new algorithm for sensorless operation of permanent magnet motors , 1992, Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting.

[5]  Ronald G. Harley,et al.  Identification and control of induction machines using artificial neural networks , 1993 .

[6]  Nobuyuki Matsui,et al.  Initial Rotor Position Estimation of Sensorless Salient-Pole Brushless DC Motor , 1996 .