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Interest and Applicability of Meta-Heuristic Algorithms in the Electrical Parameter Identification of Multiphase Machines

 

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Opened Access Interest and Applicability of Meta-Heuristic Algorithms in the Electrical Parameter Identification of Multiphase Machines
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Autor: Gutiérrez-Reina, Daniel
Barrero, Federico
Riveros, José
González-Prieto, Ignacio
Toral, S. L.
Durán, Mario J.
Departamento: Universidad de Sevilla. Departamento de Ingeniería Electrónica
Fecha: 2019-01
Publicado en: Energies, 12 (2)
Tipo de documento: Artículo
Resumen: Multiphase machines are complex multi-variable electro-mechanical systems that are receiving special attention from industry due to their better fault tolerance and power-per-phase splitting characteristics compared with conventional three-phase machines. Their utility and interest are restricted to the definition of high-performance controllers, which strongly depends on the knowledge of the electrical parameters used in the multiphase machine model. This work presents the proof-of-concept of a new method based on particle swarm optimization and standstill time-domain tests. This proposed method is tested to estimate the electrical parameters of a five-phase induction machine. A reduction of the estimation error higher than 2.5% is obtained compared with gradient-based approaches.
Cita: Gutiérrez-Reina, D., Barrero, F., Riveros, J., González-Prieto, I., Toral, S.L. y Durán, M.J. (2019). Interest and Applicability of Meta-Heuristic Algorithms in the Electrical Parameter Identification of Multiphase Machines. Energies, 12 (2)
Tamaño: 3.109Mb
Formato: PDF

URI: https://hdl.handle.net/11441/85925

DOI: 10.3390/en12020314

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