Optimization of an experimental unsymmetrical-unbalanced two-phase induction motor using the HGAPSO hybrid technique and the finite element method for increasing efficiency and reducing torque ripple

Abstract

Abstract:Two-phase induction motors make an important contribution to social welfare. Accordingly, enhanced quality in such motors would benefit society. This study was done to test this type of motor to determine a nonlinear optimal point in the form of a multiobjective function between ripple of the torque and motor efficiency with consideration of a weighted coefficient in an unbalanced-unsymmetrical two-phase induction motor. Tests demonstrated that minimizing total harmonic distortion could reduce torque ripple. The optimal point was determined using optimization algorithms, and a hybrid of genetic and particle swarm optimization algorithms simultaneously in order to increase efficiency and to

Multiparameter Analysis for Efficiency Improvement of Single‐Phase Capacitor Motor

“…Over the years, different optimization algorithms have been employed for the optimization of the single-phase motors such as particle swarm optimization, surrogate filed-circuit model, or genetic algorithms applied in single-or multiobjective optimization models [6][7][8][9]. Hybrid algorithm consisting of the particle swarm optimization and the genetic algorithms was applied in determining the optimal operating point of the two-phase motors regarding the increased efficiency and reduced torque ripple [10]. The last one presents the optimal motor operating point after optimization has been done and efficiency factor has been calculated by FEM.…”