Estimation of the Temperatures in an Asynchronous Machine Using Extended Kalman Filter

In order to monitor the thermal behavior of an
asynchronous machine with squirrel cage rotor, a 9th-order extended
Kalman filter (EKF) algorithm is implemented to estimate the
temperatures of the stator windings, the rotor cage and the stator
core. The state-space equations of EKF are established based on
the electrical, mechanical and the simplified thermal models of an
asynchronous machine. The asynchronous machine with simplified
thermal model in Dymola is compiled as DymolaBlock, a physical
model in MATLAB/Simulink. The coolant air temperature, three-phase
voltages and currents are exported from the physical model and are
processed by EKF estimator as inputs. Compared to the temperatures
exported from the physical model of the machine, three parts of
temperatures can be estimated quite accurately by the EKF estimator.
The online EKF estimator is independent from the machine control
algorithm and can work under any speed and load condition if the
stator current is nonzero current system.




References:
[1] M. O. Sonnaillon, G. Bisheimer, C. D. Angelo, and G. O. Garca, “Online
sensorless induction motor temperature monitoring,” IEEE Transactions
on Energy Conversion, vol. 25, no. 2, pp. 273–280, June 2010.
[2] R. Beguenane and M. E. H. Benbouzid, “Induction motors thermal
monitoring by means of rotor resistance identification,” IEEE
Transactions on Energy Conversion, vol. 14, no. 3, pp. 566–570, Sep
1999.
[3] P. Tavner, Condition monitoring of rotating electrical machines. IET,
2008, vol. 56.
[4] S. Ben Brahim, R. Bouallegue, J. David, T. H. Vuong, and M. David, “A
wireless on-line temperature monitoring system for rotating electrical
machine,” Wireless Personal Communications, pp. 1–21, 2016. (Online).
Available: http://dx.doi.org/10.1007/s11277-016-3808-5
[5] S. B. Brahim, R. Bouallegue, J. David, and T. H. Vuong, “Modelling
and characterization of rotor temperature monitoring system,” in
2016 International Wireless Communications and Mobile Computing
Conference (IWCMC), Sept 2016, pp. 735–740.
[6] G. Welch and G. Bishop, “An introduction to the kalman filter,” Chapel
Hill, NC, USA, Tech. Rep., 1995.
[7] M. Ganchev, B. Kubicek, and H. Kappeler, “Rotor temperature
monitoring system,” in Electrical Machines (ICEM), 2010 XIX
International Conference on, Sept 2010, pp. 1–5.
[8] O. E. E, G. Metin, and B. Seta, “Simultaneous rotor and stator resistance
estimation of squirrel cage induction machine with a single extended
kalman filter,” Turk. J. Elec. Eng. & Comp. Sic., 2010.
[9] Y. Du, T. G. Habetler, and R. G. Harley, “Methods for thermal protection
of medium voltage induction motors - a review,” in 2008 International
Conference on Condition Monitoring and Diagnosis, April 2008, pp.
229–233.
[10] Z. Gao, T. G. Habetler, and R. G. Harley, “An online adaptive stator
winding temperature estimator based on a hybrid thermal model for
induction machines,” in IEEE International Conference on Electric
Machines and Drives, 2005., May 2005, pp. 754–761. [11] Z. Gao, T. G. Habetler, R. G. Harley, and R. S. Colby, “A novel
online rotor temperature estimator for induction machines based on
a cascading motor parameter estimation scheme,” in Diagnostics for
Electric Machines, Power Electronics and Drives, 2005. SDEMPED
2005. 5th IEEE International Symposium on, Sept 2005, pp. 1–6.
[12] C. Kral, T. G. Habetler, R. G. Harley, F. Pirker, G. Pascoli,
H. Oberguggenberger, and C. J. M. Fenz, “Rotor temperature estimation
of squirrel-cage induction motors by means of a combined scheme
of parameter estimation and a thermal equivalent model,” IEEE
Transactions on Industry Applications, vol. 40, no. 4, pp. 1049–1057,
July 2004.
[13] A. Haumer, C. Kral, V. Vukovic, A. David, C. Hettfleisch, and
A. Huzsvar, “A parametrization scheme for high performance thermal
models of electric machines using modelica,” 2012.
[14] D. Zeng, Advances in Computer Science and Engineering. Springer
Publishing Company, Incorporated, 2012.
[15] A. Haumer, C. Kral, H. Kapeller, T. Buml, and J. V. Gragger, “The
advancedmachines library: Loss models for electric machines,” in
Proceedings of the 7th Modelica Conference, 2009, pp. 847–854.
[16] A. H. C. Kral, “Modelica libraries for dc machines, three phase
and polyphase machines,” 4th International Modelica Conference, pp.
549–558, March 2005.
[17] G. Fish, “Dymola-simulink interface,” 2011. (Online). Available:
http://www.claytex.com/blog/dymola-simulink-interface/