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

Issue title: Selected papers from the International Symposium on Electromagnetic Fields in Mechatronics, Electrical and Electronic Engineering ISEF 2019

Guest editors: Paolo Di Barba, Maria Evelina Mognaschi and Sławomir Wiak

Article type: Research Article

Authors: Nobahari, Amin^a | Vahedi, Abolfazl^a; | Takorabet, Noureddine^b

Affiliations: [a] School of Electrical and Electronics Engineering, Iran University of Science and Technology, Tehran, Iran | [b] Groupe de Recherche en Energie Electrique de Nancy, Université de Lorraine, Nancy, France

Correspondence: [*] Corresponding author: Abolfazl Vahedi, School of Electrical and Electronics Engineering, Iran University of Science and Technology, Tehran, Iran. E-mail: [email protected]

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.

Keywords: Permanent magnet motors, design optimization, permanent magnet shaping, ANN model, torque profile, electric motorcycle

DOI: 10.3233/JAE-209512

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 64, no. S1, pp. S155-S166, 2020