Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor

Transverse flux motors (TFMs) are being investigated to be used in vehicle traction applications due to their high torque density. In this paper, a two-phase axial-gap transverse flux motor is designed for an electric scooter, proposing a novel analytical design method. First, the dimensioning equat...

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Main Authors: Víctor Ballestín-Bernad, Jesús Sergio Artal-Sevil, José Antonio Domínguez-Navarro
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/12/3666
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author Víctor Ballestín-Bernad
Jesús Sergio Artal-Sevil
José Antonio Domínguez-Navarro
author_facet Víctor Ballestín-Bernad
Jesús Sergio Artal-Sevil
José Antonio Domínguez-Navarro
author_sort Víctor Ballestín-Bernad
collection DOAJ
description Transverse flux motors (TFMs) are being investigated to be used in vehicle traction applications due to their high torque density. In this paper, a two-phase axial-gap transverse flux motor is designed for an electric scooter, proposing a novel analytical design method. First, the dimensioning equations of the motor are obtained based on the vehicle requirements, and the stationary dq model is calculated. Then, the motor is optimized using a multiobjective genetic algorithm, and finally a 3D-FEM verification is made. Both the motor structure and the design method aim to have a low complexity, in order to favor the sizing and manufacturing processes through a low computation time and simple core shapes. This approach has not yet been explored in axial-gap TFMs.
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spelling doaj.art-379e2b3b7f174a8bb07960521fafb0c42023-11-22T00:54:04ZengMDPI AGEnergies1996-10732021-06-011412366610.3390/en14123666Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux MotorVíctor Ballestín-Bernad0Jesús Sergio Artal-Sevil1José Antonio Domínguez-Navarro2Department of Electrical Engineering, School of Engineering and Architecture, University of Zaragoza, C/María de Luna, 50018 Zaragoza, SpainDepartment of Electrical Engineering, School of Engineering and Architecture, University of Zaragoza, C/María de Luna, 50018 Zaragoza, SpainDepartment of Electrical Engineering, School of Engineering and Architecture, University of Zaragoza, C/María de Luna, 50018 Zaragoza, SpainTransverse flux motors (TFMs) are being investigated to be used in vehicle traction applications due to their high torque density. In this paper, a two-phase axial-gap transverse flux motor is designed for an electric scooter, proposing a novel analytical design method. First, the dimensioning equations of the motor are obtained based on the vehicle requirements, and the stationary dq model is calculated. Then, the motor is optimized using a multiobjective genetic algorithm, and finally a 3D-FEM verification is made. Both the motor structure and the design method aim to have a low complexity, in order to favor the sizing and manufacturing processes through a low computation time and simple core shapes. This approach has not yet been explored in axial-gap TFMs.https://www.mdpi.com/1996-1073/14/12/3666transverse flux motorvehicle tractionanalytical designmultiobjective genetic algorithmfinite element method
spellingShingle Víctor Ballestín-Bernad
Jesús Sergio Artal-Sevil
José Antonio Domínguez-Navarro
Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor
Energies
transverse flux motor
vehicle traction
analytical design
multiobjective genetic algorithm
finite element method
title Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor
title_full Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor
title_fullStr Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor
title_full_unstemmed Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor
title_short Analytical Optimal Design of a Two-Phase Axial-Gap Transverse Flux Motor
title_sort analytical optimal design of a two phase axial gap transverse flux motor
topic transverse flux motor
vehicle traction
analytical design
multiobjective genetic algorithm
finite element method
url https://www.mdpi.com/1996-1073/14/12/3666
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