Optimization of a single-phase capacitor induction motor by applying a surrogate field-circuit model

Abstract

Purpose -The purpose of this paper is to present optimization of a single-phase capacitor induction motor with respect to efficiency and starting torque by using surrogate field-circuit model for steady-state. As variables, dimensions of the rotor slots and capacitor capacitance were assumed, whereas outputs were the motor performance characteristics. Searching for a motor design of maximum starting torque or maximum efficiency were objectives of the optimization. To verify design solutions, rated load and locked rotor tests of the optimized motors were performed by computer simulation which confirmed better performance parameters of the optimized motors. Design/methodology/approach -The paper presents optimization procedure of a single-phase capacitor induction motor by applying response surface methodology for surrogate 2D field-circuit model of the motor. For solving the problem a single-objective and bi-objective approach were applied. Findings -The carried out calculations showed that obtained new structures of the capacitor induction motor have better starting properties -the higher ratio of starting to rated torque. It was also obtained the motor construction with higher efficiency and lower stator current at the same time.Originality/value -The main advantage of the formulated optimization procedure was application of the SSO (sequential surrogate optimization) algorithm which exploits a polynomial surrogate model and genetic algorithm to find minimum of the objective functions and also to speed up computations.

Multiparameter Analysis for Efficiency Improvement of Single‐Phase Capacitor Motor

“…Optimization of single-phase capacitor motors has been investigated with triac-based voltage controller or in the drive configuration with Hall sensor [4,5]. 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].…”

Permanently split capacitor motor-study of the design parameters

“…Searching for a motor design of maximum starting torque or maximum efficiency are objectives of the optimization. Some authors propose surrogate circuit-field model that, exploits a polynomial surrogate model and genetic algorithm to find minimum of the objective functions [2]. In addition, variation of the capacitance, as a method for torque increasing, is analyzed [3].…”