@ARTICLE{Rolek_Jarosław_An_2018, author={Rolek, Jarosław and Utrata, Grzegorz}, volume={vol. 67}, number={No 2}, journal={Archives of Electrical Engineering}, howpublished={online}, year={2018}, publisher={Polish Academy of Sciences}, abstract={The paper presents an identification procedure of electromagnetic parameters for an induction motor equivalent circuit including rotor deep bar effect. The presented proce- dure employs information obtained from measurement realised under the load curve test, described in the standard PN-EN 60034-28: 2013. In the article, the selected impedance frequency characteristics of the tested induction machines derived from measurement have been compared with the corresponding characteristics calculated with the use of the adopted equivalent circuit with electromagnetic parameters determined according to the presented procedure. Furthermore, the characteristics computed on the basis of the classical machine T-type equivalent circuit, whose electromagnetic parameters had been identified in line with the chosen methodologies reported in the standards PN-EN 60034-28: 2013 and IEEE Std 112TM-2004, have been included in the comparative analysis as well. Additional verification of correctness of identified electromagnetic parameters has been realised through comparison of the steady-state power factor-slip and torque-slip characteristics determined experimentally and through the machine operation simulations carried out with the use of the considered equivalent circuits. The studies concerning induction motors with two types of rotor construction – a conventional single cage rotor and a solid rotor manufactured from magnetic material – have been presented in the paper.}, type={Artykuły / Articles}, title={An identification procedure of electromagnetic parameters for an induction motor equivalent circuit including rotor deep bar effect}, URL={http://so.czasopisma.pan.pl/Content/104084/PDF/AEE-67-2-art04.pdf}, doi={10.24425/119640}, keywords={induction motors, equivalent circuits, parameter identification, frequency-domain analysis, genetic algorithms}, }