A study of the dependence of the 3-phase cage motor maximum torque on the centroid of the rotor bar section

Nelson Oyakhilomen Omogbai *

Department of Electrical Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria.
 
Research Article
Global Journal of Engineering and Technology Advances, 2023, 14(01), 097–106.
Article DOI: 10.30574/gjeta.2023.14.1.0019
Publication history: 
Received on 13 December 2022; revised on 26 January 2023; accepted on 28 January 2023
 
Abstract: 
The paper investigates the relative influence of the centroid of the three-phase squirrel cage induction motor rotor bar cross section, on the breakdown (maximum) torque of the machine. The influence of the angle of taper, the top width and the radial depth of the bar section, as established design variables, were also investigated so as to properly situate the degree of influence of the centroid, in comparison; as far as the maximum torque is concerned. The machines were investigated in their steady state operating mode using the equivalent circuit method. The machine learning capabilities of the Least Square Support Vector Machine (LSSVM) was deployed to extract by prediction, information about the likely dependencies between the randomized block of the geometric variables and the maximum torque, and the captured information was stored using the Root Mean Square Error (RMSE) of predictions. The validated results show that the rotor leakage reactance – a part determinant of the maximum torque; tends to show some significant sensitivity to a design change in the centroid of the transverse section of the rotor bar.
 
Keywords: 
Centroid; Maximum torque; LSSVM; RMSE; Rotor leakage reactance; Machine learning
 
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