Synchronous reluctance machine geometry optimisation through a genetic algorithm based technique

In this study, the design optimisation of a synchronous reluctance machine for light electric vehicles is proposed, to increase efficiency and reduce torque ripples. The existing machine was structurally optimised, using dedicated genetic algorithms, replacing only the rotor and keeping the stator a...

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Vydáno v:IET electric power applications Ročník 12; číslo 3; s. 431 - 438
Hlavní autoři: Ruba, Mircea, Jurca, Florin, Czumbil, Levente, Micu, Dan D, Martis, Claudia, Polycarpou, Alexis, Rizzo, Renato
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 01.03.2018
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ISSN:1751-8660, 1751-8679, 1751-8679
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Abstract In this study, the design optimisation of a synchronous reluctance machine for light electric vehicles is proposed, to increase efficiency and reduce torque ripples. The existing machine was structurally optimised, using dedicated genetic algorithms, replacing only the rotor and keeping the stator and it's winding untouched. Starting from the original design of the rotor implemented in Flux2D, a finite element analysis software, and the genetic algorithm optimisation implemented in Matlab, a complex co-simulation was accomplished to obtain a rotor architecture that increases the machine's performances and decreases the torque ripples. By this, performing rotor skewing is not needed any more, hence the torque loss due to it was cancelled. The optimised rotor design increases the machine performances by higher mean torque, no skewing, <8% torque ripples, higher efficiency and better inductance characteristics. Comparative results obtained both in simulations and experimental measurements prove positive outcomes of the optimisation process.
AbstractList In this study, the design optimisation of a synchronous reluctance machine for light electric vehicles is proposed, to increase efficiency and reduce torque ripples. The existing machine was structurally optimised, using dedicated genetic algorithms, replacing only the rotor and keeping the stator and it's winding untouched. Starting from the original design of the rotor implemented in Flux2D, a finite element analysis software, and the genetic algorithm optimisation implemented in Matlab, a complex co‐simulation was accomplished to obtain a rotor architecture that increases the machine's performances and decreases the torque ripples. By this, performing rotor skewing is not needed any more, hence the torque loss due to it was cancelled. The optimised rotor design increases the machine performances by higher mean torque, no skewing, <8% torque ripples, higher efficiency and better inductance characteristics. Comparative results obtained both in simulations and experimental measurements prove positive outcomes of the optimisation process.
Author Micu, Dan D
Czumbil, Levente
Rizzo, Renato
Martis, Claudia
Jurca, Florin
Ruba, Mircea
Polycarpou, Alexis
Author_xml – sequence: 1
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  surname: Ruba
  fullname: Ruba, Mircea
  organization: 1Department of Electrical Machines and Drives, Technical University Cluj-Napoca, Str. George Baritiu, nr. 26-28, Cluj Napoca, Romania
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  givenname: Florin
  surname: Jurca
  fullname: Jurca, Florin
  organization: 1Department of Electrical Machines and Drives, Technical University Cluj-Napoca, Str. George Baritiu, nr. 26-28, Cluj Napoca, Romania
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  givenname: Levente
  surname: Czumbil
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  organization: 2Deptartment of Electrotechnics and Measurements, Technical University of Cluj-Napoca, Str. George Baritiu, nr. 26-28, Cluj Napoca, Romania
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  givenname: Dan D
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  organization: 3Department of Electrical Engineering, Federick University, Nicosia, 1036, Cyprus
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  givenname: Renato
  surname: Rizzo
  fullname: Rizzo, Renato
  email: renato.rizzo@unina.it
  organization: 4Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21-80125 Naples, Italy
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Issue 3
Keywords rotors
synchronous reluctance machine geometry optimisation
machine performances
electric vehicles
genetic algorithm-based technique
torque loss
Flux2D
genetic algorithms
design optimisation
dedicated genetic algorithms
light electric vehicles
stators
mean torque
inductance characteristics
rotor architecture
rotor skewing
reluctance machines
optimised rotor design
complex co-simulation
torque ripple reduction
stator
finite element analysis software
optimisation process
Matlab
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Snippet In this study, the design optimisation of a synchronous reluctance machine for light electric vehicles is proposed, to increase efficiency and reduce torque...
SourceID crossref
wiley
iet
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Publisher
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SubjectTerms complex co‐simulation
dedicated genetic algorithms
design optimisation
electric vehicles
finite element analysis software
Flux2D
genetic algorithms
genetic algorithm‐based technique
inductance characteristics
light electric vehicles
machine performances
Matlab
mean torque
optimisation process
optimised rotor design
reluctance machines
Research Article
rotor architecture
rotor skewing
rotors
stator
stators
synchronous reluctance machine geometry optimisation
torque loss
torque ripple reduction
Title Synchronous reluctance machine geometry optimisation through a genetic algorithm based technique
URI http://digital-library.theiet.org/content/journals/10.1049/iet-epa.2017.0455
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Volume 12
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