Parameters estimation of double-cage induction motors using a hybrid metaheuristic algorithm

In this paper, a hybrid metaheuristic algorithm, named the hybrid Phasor Particle Swarm Optimization and Gravitational Search Algorithm (PPSOGSA), is proposed for estimating parameters of double-cage induction motors. The parameters are obtained by minimizing the objective function related to the error between the calculated and manufacturer data. The performances of the proposed algorithm are analyzed and evaluated using the motors of different powers. Compared to the original PSOGSA and other algorithms applied in solving the parameter estimation problem, it is found that the proposed algorithm has better performances.