Title Interest and applicability of meta-heuristic algorithms in the electrical parameter identification of multiphase machines †
Authors GUTIÉRREZ REINA, DANIEL, Barrero F., Riveros J., Gonzalez-Prieto I., Toral S.L., Duran M.J., GUTIÉRREZ REINA, DANIEL
External publication No
Means Energies
Scope Article
Nature Científica
JCR Quartile 3
SJR Quartile 1
JCR Impact 2.70200
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060549873&doi=10.3390%2fen12020314&partnerID=40&md5=4ef6f1e97c7bff8d229cf9f177552801
Publication date 01/01/2019
ISI 000459743700115
Scopus Id 2-s2.0-85060549873
DOI 10.3390/en12020314
Abstract 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. © 2019 by the authors.
Keywords Electric network parameters; Fault tolerance; Heuristic algorithms; Particle swarm optimization (PSO); Time domain analysis; Electrical parameter; Electromechanical systems; Five phase induction machi
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