Identification of three phase induction machines equivalent circuits parameters using multi-objective genetic algorithms

The use of multiobjective optimization technique in determining the values of the steady-state equivalent circuit parameters of a three-phase squirrel-cage induction machine is discussed. The identification procedure is based on the steady state phase current versus slip and torque versus slip characteristics. Nonlinearities in the Induction machine such as saturation effects and skin effects are also taken into account. The proposed technique is based on Multiobjective Genetic Algorithms (MOGA). The MOGA is used to minimize the error between the actual data and the data obtained by equivalent circuit. The robustness of the method is shown by identifying parameters of the induction motor in three different cases. The simulation results show that the method successfully estimates the motor parameters.