Induction Motor parameters identification using Genetic Algorithms for varying flux levels

This paper describes a novel approach for identifying induction motor electrical parameters in function of flux levels based on experimental transient measurements from a vector controlled induction motor (I.M.) drive and using an off line genetic algorithm (GA) routine with a linear machine model. The evaluation of the electrical motor parameters is achieved by minimizing the error between experimental and simulation model responses. An accurate and fast estimation of the electrical motor parameters is performed by running a number of optimizations using experimental tests taken under different operating conditions (flux level). Results are verified through a comparison of speed, torque and line current responses between the experimental IM drive and a Matlab - Simulink model.