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ANN-based optimization approach devoted to the sizing of arbitrary rotor pole geometries of permanent magnet motors for electric motorcycle

Abstract : Various design approaches have been studied for performance improvement of permanent magnet motors, especially for electric vehicles application. This paper deals with an effective concept that is based on adopting non-traditional geometries for permanent magnet poles. The study focuses on a general methodology for optimal sizing of the rotor poles’ pre-defined geometrical parameters considering certain objectives. For this purpose, the artificial neural network is employed for creating an accurate and simple model to be used in a multi-objective optimization procedure. An interior crescent-shaped permanent magnet motor for an electric motorcycle is studied as a typical case study to prove the performance of the proposed method. Finite element models are developed to create the required dataset for the modeling stage as well as to verify the results.
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https://hal.univ-lorraine.fr/hal-03260394
Contributor : Bernard Davat <>
Submitted on : Monday, June 14, 2021 - 8:45:35 PM
Last modification on : Thursday, June 17, 2021 - 1:57:54 PM

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Amin Nobahari, Abolfazl Vahedi, Noureddine Takorabet. ANN-based optimization approach devoted to the sizing of arbitrary rotor pole geometries of permanent magnet motors for electric motorcycle. International Journal of Applied Electromagnetics and Mechanics, IOS Press 2020, 64, pp.S155-S166. ⟨10.3233/JAE-209512⟩. ⟨hal-03260394⟩

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