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GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses

Acetta, Angelo and Alonge, Francesco and Cirrincione, Maurizio and D'Ippolito, Filippo and Pucci , Marcello and Sferlazza, Antonino (2020) GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses. IEEE Open Journal of Industry Applications, 1 . pp. 135-147. ISSN 2644-1241

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    Abstract

    This paper, starting from recent papers in the scientific literature dealing with Induction Motor (IM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; particularly it takes into account the dependence of the magnetic saturation by the stator leakage inductance, as a further effect of the load. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a FEA of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up.

    Item Type: Journal Article
    Subjects: T Technology > TA Engineering (General). Civil engineering (General)
    T Technology > TK Electrical engineering. Electronics Nuclear engineering
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
    Depositing User: Fulori Nainoca - Waqairagata
    Date Deposited: 10 Dec 2020 12:30
    Last Modified: 10 Dec 2020 12:30
    URI: http://repository.usp.ac.fj/id/eprint/12484
    UNSPECIFIED

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