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Erschienen in: Electrical Engineering 2/2022

18.08.2021 | Original Paper

IM to IPM design transformation using neural network and DoE approach considering the efficiency and range extension of an electric vehicle

verfasst von: Uğur Demir

Erschienen in: Electrical Engineering | Ausgabe 2/2022

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Abstract

This paper is regarding to the design transformation methodology from induction motor (IM) to interior permanent magnet motor (IPM) to increase the efficiency of the traction motor and extend the range of the electric vehicle. Furthermore, the rotor structure of IPM is tried to be optimized without changing the stator and winding structure of the IM from the previous study to meet the vehicle requirements and maximize the motor efficiency in order to design the rotor structure of the IPM. Firstly, the design parameters, the vehicle requirements, and constraints are determined for the reference IM model. Secondly, the appropriate rotor geometry is chosen by considering the advantages and disadvantages of different rotor geometries for IPM. Then, the design parameters for the rotor are determined and investigated by using Taguchi's design of experiment (DoE) method considering the importance and priorities of the rotor design parameters of IPM. Thirdly, a neural network (NN) to predict better design parameters is trained to operate with the data of DoE according to the prioritization and normalization of framework. Finally, the reference IM and the predicted IPM models are evaluated in terms of the acceleration, the slope climbing, the driving performance (ECE R15), and battery consumption characteristics.

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Metadaten
Titel
IM to IPM design transformation using neural network and DoE approach considering the efficiency and range extension of an electric vehicle
verfasst von
Uğur Demir
Publikationsdatum
18.08.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
Electrical Engineering / Ausgabe 2/2022
Print ISSN: 0948-7921
Elektronische ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-021-01378-3

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