Dynamic Parameter Identification of Induction Motors using Intelligent Search Techniques

T. Kulworawanichpong, K.-L. Areerak, K.-N. Areerak, P. Pao-la-or, D. Puangdownreong, and S. Sujitjor (Thailand)


Parameter identification, genetic algorithm, intelligentsearch, induction motors.


This paper describes an intelligent approach to estimate dynamic parameters of induction motors. Due to the complication of space phasor equations describing dynamic behaviours of induction motors, the parameters can be roughly estimated through conventional tests (no load, locked-rotor and retardation tests). These tests are based on the steady-state analysis. Therefore, they may cause inaccurate estimation, especially when transient characteristics are seriously required. In this paper, some efficient intelligent search techniques, which are i) Genetic Algorithm (GA) and ii) Adaptive Tabu Search (ATS), are employed to demonstrate this intelligent identification. In comparison with the conventional parameter tests, the effectiveness of the proposed scheme is confirmed.

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