PROCÉDURE EFFICACE D'ESTIMATION DES PARAMÈTRES À L'AIDE DE L'ALGORITHME D'OPTIMISATION DU TOURNESOL POUR UN MOTEUR À INDUCTION SIXPHASÉ
Mots-clés :
Péage d'optimisation des essaims de particules, Machines synchrones à aimants permanents, Circuit équivalent des machines synchrones à aimants permanents, Estimation des paramètres en ligneRésumé
La précision de l'étude des performances des moteurs à induction à six phases (SPIM) dépend de l'estimation précise des paramètres du moteur. Cet article examine l'évaluation des performances des SPIM parmi plusieurs algorithmes d'optimisation utilisant l'optimisation des paramètres. Les algorithmes compétitifs sont les algorithmes d'évolution différentielle (DE), d'algorithme génétique (GA), d'algorithme d'optimisation de Jaya (JOA), d'optimisation d'essaim de particules (PSO) et d'optimisation de tournesol (SFO). L'estimation des paramètres est extraite des courbes de performance basées sur les données du fabricant. Les vérifications en laboratoire sont effectuées sur un SPIM modifié à partir d'un moteur à induction triphasé. Il montre également que l'utilisation de SFO donne une convergence entre les paramètres mesurés et estimés avec de petites erreurs et une réponse rapide par rapport à de nombreux algorithmes d'optimisation. L'analyse statistique des résultats montre l'efficacité de l'algorithme SFO proposé par rapport à d'autres méthodes à différentes valeurs d'itérations.
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