A Multiphysics Dataset Generation Procedure for the Data-Driven Modeling of Traction Electric Motors

A Multiphysics Dataset Generation Procedure for the Data-Driven Modeling of Traction Electric Motors

This paper presents the work done to address two main challenges in the simulation and design of electric machines for traction applications. On one hand, the modeling process is becoming increasingly complex as the demand for higher efficiency, high power density, and low cost pushes the speed and...

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Bibliographic Details
Main Authors: Simone Ferrari, Luigi Solimene, Riccardo Torchio, Costanza Anerdi, Fabio Freschi, Luca Giaccone, Gianmarco Lorenti, Francesco Lucchini, Piergiorgio Alotto, Gianmario Pellegrino, Maurizio Repetto
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Data-driven techniques
machine learning
multi-physics analysis
open-source datasets
traction electric motors
Online Access:https://ieeexplore.ieee.org/document/10937701/
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