Determination of Induction Motor Double-Cage Model Parameters Based on Bacterial Foraging Optimization Algorithm

A newly developed technique, called Bacterial Foraging Optimization (BM) algorithm, is proposed for the parameter determination of induction motor double-cage model from standard manufacture data such as rated output power, starting torque, breakdown torque, full load torque, efficiency and power factor at rated output power Using the squared error between the determined and the manufacture data as the objective function, the parameter determination problem is transferred into an optimization process where the double cage model parameters are determined that minimize the defined objective function The objective function is Iteratively minimized using the BED algorithm The method has been tested with two sample motors The performance of the BEG algorithm is compared with classical parameter determination (CPD) method and other optimization methods including Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Immune Algorithm (IA) Simulation results exhibit the potential of the proposed technique to capture the true values of the machine parameters and the superiority of the results obtained using the BFO over other parameter determination techniques Copyright (C) 2010 Praise Worthy Prize S.r.l. - All rights reserved.