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 |
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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: | 09 Dec 2020 23:30 |
Last Modified: | 09 Dec 2020 23:30 |
URI: | https://repository.usp.ac.fj/id/eprint/12484 |
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