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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Veröffentlicht in:IET electric power applications Jg. 12; H. 3; S. 431 - 438
Hauptverfasser: Ruba, Mircea, Jurca, Florin, Czumbil, Levente, Micu, Dan D, Martis, Claudia, Polycarpou, Alexis, Rizzo, Renato
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 01.03.2018
Schlagworte:
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
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
ISSN:1751-8660, 1751-8679, 1751-8679
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Beschreibung
Zusammenfassung: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.
ISSN:1751-8660
1751-8679
1751-8679
DOI:10.1049/iet-epa.2017.0455