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The use of induction machine spatial saliencies for sensorless vector control in the proximity of zero electrical frequency has been extensively researched over the last few decades. A robust technique to extract machine saliencies is called voltage step excitation, and it computes a saliency phasor out of phase current derivatives resulting from specific voltage steps generated by the inverter switching. Within the saliency phasor, all machine saliencies appear superposed. For some machine constructions, multiple saliencies are present, containing information about the spatial, magnetic and geometric state of the machine. Due to its direct relation with the rotor angle and its high accuracy, rotor slotting saliency is often chosen as the sensorless control signal. In order to exclusively access rotor slotting, saliency separation needs to be carried out, with the goal of eliminating all non-control saliencies from the saliency phasor. In this research, feedforward harmonic compensation based on look-up tables (LUTs) is chosen. The idea is to estimate each saliency in relation to amplitude and phase shift once, store such information in a torque-dependent LUT and use it for feedforward compensation. Yet, several saliencies are linked to the rotor position and, thus, the stored phase shift in the LUT is fixed to a defined rotor position at which the saliency estimation was performed. For the feedforward compensation to work during each sensorless start-up, an initial rotor slot detection must be carried out. This paper presents a technique to estimate initial rotor angle based only on the inherent characteristics of the induction machine multi-saliencies and an iterative feedforward compensation process that requires no extra resources and only a few PWM (Pulse Width Modulation) periods to achieve initial slot rotor angle. Experimental results measured at two different test benches prove the high accuracy of the method.
Wydawca
Czasopismo
Rocznik
Tom
Strony
301--313
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
- Institute of Energy Systems and Electrical Drives, Technische Universität Wien, Vienna, Austria
autor
- Rolling Stock Platform/Components Division, ALSTOM Transport Austria GmbH, Vienna, Austria
autor
- Institute of Energy Systems and Electrical Drives, Technische Universität Wien, Vienna, Austria
Bibliografia
- Caruana, C., Asher, G. M., Bradley, K. J. and Woolfson M. S. (2003). Flux Position Estimation in Cage Induction Machines Using Synchronous Injection and Kalman Filtering. IEEE Transactions on Industry Applications, 39(5), pp. 1372–1378.
- Chen, Z., Zhang, Z., Kennel, R. and Luo, G. (2015). Hybrid sensorless control for SPMSM with multiple saliencies. In: 41st Annual Conference of the IEEE Industrial Electronics Society, Yokohama, 9–12 November 2015.
- Degner, M. W. and Lorenz, R. D (1997). Using Multiple Saliencies for the Estimation of Flux, Position, and Velocity in AC Machines. In: Proceedings of IEEE IAS Annual Meeting, New Orleans, 5–9 October 1997.
- Diaz-Reigosa, D., Briz, F., Blanco-Charro, C, Di-Gioia, A., Garcia, P. and Guerrero, J. M. (2013). Sensorless control of doubly fed induction generators based on rotor high-frequency signal injection. IEEE Transactions on Industry Applications, 49(6), pp. 2593–2601.
- Fahrner, W., Vogelsberger, M. A. and Wolbank, T. (2018). A new technique to identify induction machine rotor parameters during dynamic operation and low speed. In: IEEE 18th International Power Electronics and Motion Control Conference, Budapest, 26–30 August 2018.
- Gao, Q., Asher, G. M., Sumner, M. and Makys, P. (2007). Position Estimation of AC Machines over a Wide Frequency Range Based on Space Vector PWM Excitation. IEEE Transactions on Industry Application, 43(4), pp. 1001–1011.
- Holtz, J. and Pan. H. (2002). Elimination of saturation effects in sensorless position controlled induction motors. In: Proceedings of IEEE Industry Applications Annual Meeting, Pittsburg, 13–18 October.
- Jang, J.-H., Ha, J.-I., Ohto, M., Ide, K. and Sul S. K. (2004). Analysis of Permanent-Magnet Machine for Sensorless Control Based on Highfrequency Signal Injection. IEEE Transactions on Industry Applications, 40(6), pp. 1595–1604.
- Landsmann, P., Paulus, D. and Kennel, R. (2013). Silent and parameter independent hybrid sensorless control for SPMSM based on current oversampling. In: IEEE International Symposium on Sensorless Control for Electrical Drives and Predictive Control of Electrical Drives and Power Electronics, Munich, 17–19 October 2013.
- Lin, T. C. and Zhu, Z. Q. (2015). Sensorless Operation Capability of Surfacemounted Permanent-Magnet Machine based on High-Frequency Signal Injection Methods. IEEE Transactions on Industry Applications, 51(3), pp. 2161–2171.
- Makyš, P., Asher, G. M., Sumner, M., Gao, Q. and Vittek. J. (2006). A Low Memory Disturbance Elimination Method for Sensorless Control of Induction Motor Drive using Test Vector Injection. In: Proceedings of the Annual Conference of the IEEE Industrial Electronics Society, Paris, 6–1 November 2006.
- Rodriguez-Montero, E., Vogelsberger, M. A. and Wolbank, T. (2019). Robust Signal Offset Identification for Sensorless Control of Induction Machines at Rated Load using One-Active Modulating Pulse Excitation. In: IEEE Energy Conversion Congress and Expo, Baltimore, 29 September–3 October 2019.
- Rodriguez-Montero, E., Vogelsberger, M. A. and Wolbank, T (2021). Sensorless identification of the initial rotor slot position using one active inverter state excitation in induction machines. In: Proceedings of the 19th International Power Electronics and Motion Control Conference PEMC, Gliwice, 25–29 April 2021.
- Teske, N., Asher, G., Bradley, K. and Sumner, M. (2000). Sensorless position estimation for symmetric cage induction motor under loaded conditions. In: Conference Record of the 2000 IEEE Industry Applications Conference, Rome, 8–12 October 2000.
- Teske, N., Asher, G., Bradley, K. and Summer, M. (2001). Analysis and suppression of inverter clamping saliency in sensorless position controlled induction machine drives. In: Conference Record of the 2001 IEEE Industry Applications Conference, Chicago, 30 September–3 October 2001.
- Wolbank, T. M. and Metwally, M. K. (2008). Saliency tracking-based sensorless control of induction machines using artificial neural networks. In: 12th International Middle-East Power System Conference, Aswan, 12–15 March 2008.
- Yoon, Y.-D. and Sul, S.-K. (2014). Sensorless Control for Induction Machines Based on Square-Wave Voltage Injection. IEEE Transactions on Power Electronics, 29(7), pp. 3637–3645.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-d6fe2d9e-0c84-464e-8757-0b11da3bbf2a