Speed sensorless flux and position control of induction machines based on pulse injection and multiple saliency extraction

Similar to other sensorless control methods based on signal injection, the resulting signal of the transient voltage excitation is influenced, for example, by the slotting saliency, the anisotropy saliency, as well as by the saturation based saliency and its load and flux dependencies. A separation algorithm to extract the slotting saliency and saturation saliency from the resulting signal is presented. It includes an artificial neural network (ANN) to identify, compensate disturbing influences and interactions of the saliencies. The slotting saliency component is used for calculating the rotor position in combination with the current model (rotor-equation). The saturation saliency component is first corrected using an ANN to get the estimated reference flux angle and then combined with a stabilized voltage model (stator-equation) for flux position calculation. This allows a calculation of the flux- and rotor position especially around zero fundamental frequency. The approach given in this paper attempts to combine both methods to provide an excellent performance of the sensorless control scheme in the whole frequency range. The transient signal is used to stabilize the voltage model what results in smooth output with the advantage that the dynamic performance is not reduced. At low frequencies it is assisted by the current model which provides additional stability.

[1]  Robert D. Lorenz,et al.  Measuring, modeling and decoupling of saturation-induced saliencies in carrier signal injection-based sensorless AC drives , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[2]  T.M. Wolbank,et al.  Adaptive Flux model for commissioning of signal injection based zero speed sensorless flux control of induction machines , 2007, 2007 7th International Conference on Power Electronics and Drive Systems.

[3]  H. Hauser,et al.  Interaction of induction machines fundamental wave design and asymmetries in the transient electrical behavior caused by saturation , 2003, IECON'03. 29th Annual Conference of the IEEE Industrial Electronics Society (IEEE Cat. No.03CH37468).

[4]  P. Garcia,et al.  Saliency tracking-based, sensorless control of AC machines using structured neural networks , 2005, Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005..

[5]  M. Schroedl,et al.  Sensorless control of AC machines at low speed and standstill based on the "INFORM" method , 1996, IAS '96. Conference Record of the 1996 IEEE Industry Applications Conference Thirty-First IAS Annual Meeting.

[6]  Robert D. Lorenz,et al.  Transducerless position and velocity estimation in induction and salient AC machines , 1994, Proceedings of 1994 IEEE Industry Applications Society Annual Meeting.

[7]  Qiang Gao,et al.  Sensorless Position and Speed Control of Induction Motors Using High-Frequency Injection and Without Offline Precommissioning , 2007, IEEE Transactions on Industrial Electronics.

[8]  T.M. Wolbank,et al.  Tracking inherent saliencies of standard induction machines for zero speed sensorless control using different signal processing methods , 2008, 2008 IEEE Power Electronics Specialists Conference.

[9]  Joachim Holtz,et al.  Methods for Speed Sensorless Control of AC Drives , 1996 .

[10]  T. Fagernes Nestli,et al.  Evaluation and comparison of predictor models for rotor flux calculation in induction motors , 1994, Proceedings of 1994 Power Electronics Specialist Conference - PESC'94.

[11]  Jung-Ik Ha,et al.  Physical understanding of high frequency injection method to sensorless drives of an induction machine , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[12]  T. M. Wolbank,et al.  Evaluation of the influence of design and operation of standard induction motors on sensorless control schemes utilising saliencies in the transient electrical behaviour , 2000, 2000 IEEE 31st Annual Power Electronics Specialists Conference. Conference Proceedings (Cat. No.00CH37018).

[13]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[14]  Alfio Consoli,et al.  Low-frequency signal-demodulation-based sensorless technique for induction motor drives at low speed , 2006, IEEE Transactions on Industrial Electronics.

[15]  G.M. Asher,et al.  Sensorless position detection for vector controlled induction motor drives using an asymmetric outer-section cage , 1996, IAS '96. Conference Record of the 1996 IEEE Industry Applications Conference Thirty-First IAS Annual Meeting.