A FEM-Based Comparative Study of the Effect of Rotor Bar Designs on the Performance of Squirrel Cage Induction Motors

Cemil Ocak ()
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Cemil Ocak: Department of Electrical and Electronics Engineering, Faculty of Technology, Gazi University, Ankara 06560, Turkey

Energies, 2023, vol. 16, issue 16, 1-17

Abstract: Induction motors (IM) are the most frequently used type of motor in the industry. The number of rotor slots, bar geometry, and conductivity of bar material have a strong impact on the torque profile and efficiency characteristics of induction motors. This study focused on investigating the effect of different rotor bar designs on motor performance by the finite element method (FEM). The IMs have been designed using the same stator core, winding, and core lengths. The total rotor bar cross-section areas are also fixed throughout all designs. In addition to the change in the number of rotor bars and geometry, the effect of copper and aluminum bar materials on motor performance was also investigated, both for single and double-layered squirrel-cage structures. The results of the study indicate that the starting torque of the motor in a 36/30-slot aluminum single-cage structure was obtained as 96.26 Nm, while the starting torque of a 36/46-slot aluminum double-cage structure was found to be 115.34 Nm. It is also found that the starting torque of the initial design can be increased by up to 19.82% by changing only the rotor bar numbers and material with the same stator and rotor size. The efficiency of the motors was determined as 86.6% for both designs. In addition to efficiency, the output torque ripple has been decreased to 2.63, which equals a 67.32% decrease in the ripple of the initial design. The improved design has an approximately 8 °C lower T 2 due to better cooling performance as a result of a higher number of rotor slots.

Keywords: induction motor; squirrel cage; slot number; starting torque; bar material (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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