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Communication dans un congrès

Hybrid interior point method and genetic algorithm for parameter estimation of three-phase induction motor

Abstract : This paper suggests a new technique based on a genetic algorithm and interior point method to determine the parameters of a three-phase induction machine. We will base our study on the manufacturer data in the nameplate of the machine, mainly the voltage input frequency, starting current and torque, the maximum torque, nominal current and torque, and the machine power factor. An identification method based on the steady-state equivalent circuit of the induction machine is used to estimate the machine parameters from the manufacturer data. The used machine parameters are mainly the resistance and the leakage reactance of both stator and rotor also the Magnetizing reactance. We will construct a fitness function quantifying the difference between the manufacturer data and their estimated values. Finally the machine parameters are obtained by solving a minimization problem with the proposed fitness function. The genetic algorithms will be employed to obtain an initial feasible solution of the minimizing problem, then the interior point method will be used to ameliorate the solution. The accuracy of the proposed hybrid algorithm will be shown in the simulation results.
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Communication dans un congrès
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https://hal-u-picardie.archives-ouvertes.fr/hal-03850008
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Soumis le : samedi 12 novembre 2022 - 16:20:38
Dernière modification le : dimanche 13 novembre 2022 - 03:06:35

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Sami Labdai, Larbi Chrifi-Alaoui, Laurent Delahoche, Bruno Marhic, Pascal Bussy. Hybrid interior point method and genetic algorithm for parameter estimation of three-phase induction motor. 2021 9th International Renewable and Sustainable Energy Conference (IRSEC), Nov 2021, Morocco, Morocco. pp.1-7, ⟨10.1109/IRSEC53969.2021.9741191⟩. ⟨hal-03850008⟩

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