Genetic algorithm in torque optimisation of permanently split capacitor motor

Paper investigates permanently split capacitor motor of type FMR-35/6, with respect to torque optimization. For this purpose, mathematical model of the motor is derived with the output torque as an objective function for optimization. Motor mathematical model is applied in program developed in the C++ language, which performs the optimization using Genetic Algorithm (GA). Several input design parameters of the motor are varied simultaneously in the GA program. The program gives the best set of varied parameters for which the torque is increased, and consequently a new optimized model of the motor is obtained. Output torque of the optimized motor is increased at rated operating point as well as during motor start. Matlab/Simulink models are designed for obtaining the transient characteristics of the currents, speed and torque. The results from the Simulink models are compared with the results from the mathematical models of the motor-basic and optimized, in order accuracy of the both mathematical models to be verified. Finally, magnetic flux density and its distribution in the cross-section of the motor models are determined for different operating regimes by using Finite Element Method (FEM).