Estimation and performance evaluation of an induction machine using optimization techniques

This paper proposes application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in estimating all the per phase equivalent circuit parameters of an induction machine just with the name plate details and few experimental data. The saturated value of magnetizing reactance (X_m) is predicted from these estimated parameters using an iterative technique. From these estimated values, the steady state performance of the induction machine is predetermined at any operating slip including saturation effect. The comparison between the experimental and calculated values is carried out for different cases which prove the validity of the best.