A Novel Model Parameter Estimation of an Induction Motor using Genetic Algorithm

J. Treetrong, J.K. Sinha, F. Gu, and A. Ball (UK)


Induction Motors, Parameter Estimation, Genetic Algorithm


This paper presents a new model of induction motor parameter estimation using genetic algorithm. The model is arranged from flux linkage models and torque model of a squirrel-cage induction motor. Genetic algorithm (GA) is applies as a key technique to estimates motor parameters: stator and rotor resistance, stator and rotor reactance and magnetizing reactance. Stator voltage, current and rotor speed are used as measured data. The proposed GA method is applied to search the parameters by comparing between the estimated data and measured data. The model is evaluated with different motor sizes and different noises in simulation test. The proposed method has further been validated on the experimental data of an induction motor under normal operating condition at full load. The results show that the proposed method can estimate effectively the motor parameters with reliability.

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