Derived Functions for MATLAB Non-Linear Solvers: An optimal rotor slot and bar design stopgap

Nelson Oyakhilomen Omogbai *

Department of Electrical Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria.
 
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2023, 08(01), 382–390.
Article DOI: 10.30574/wjaets.2023.8.1.0060
Publication history: 
Received on 13 January 2023; revised on 21 February 2023; accepted on 23 February 2023
 
Abstract: 
The most striking difference between the Squirrel cage induction motor (SCIM) and other electric motors lies invariably in the rotor. The major running performance characteristics, together with the entire acceleration performance range, are all influenced, in varying degrees, by the rotor slot and bar design. Therefore, proper dimensioning of the slots and bars is therefore critical to attaining a high performing machine. The preliminary stage of the SCIM design, if well done, facilitates the refinement and optimization stages; serving as a good take-off point for ultimately realizing that final state of the art design. This study therefore attempts to derive relevant design functions that could be fed into the algorithms of various non-linear solvers, one of which is the Genetic Algorithm (GA), to output the rotor slot initial main dimensions for the SCIM; from where proper design refinement/optimization could cheaply evolve. The SCIM design obtained from implementing the derived equations, when compared with the appropriate reference datasheets, showed only minor deviations from the expected performance indices – an outcome deemed satisfactory for a preliminary design attempt. The so obtained initial dimensions may in practice be subjected to the appropriate refinement, depending on the target performance requirement of the motor to be designed.
 
Keywords: 
Objective function; Constraint function; Rotor slot design; Genetic Algorithm; MATLAB; Non-linear solvers.
 
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