Numéro |
Sci. Tech. Energ. Transition
Volume 79, 2024
Power Components For Electric Vehicles
|
|
---|---|---|
Numéro d'article | 2 | |
Nombre de pages | 9 | |
DOI | https://doi.org/10.2516/stet/2023041 | |
Publié en ligne | 9 janvier 2024 |
Review Article
Optimal drive cycle current supply of a wound field automotive electrical machine using surrogate models
1
SATIE Laboratory, Stellantis and Paris Saclay University, Carrières-sous-Poissy, France
2
SATIE Laboratory, CY Cergy Paris University, Cergy, France
3
LMSSC, Cnam, HESAM University, Paris, France
4
Stellantis, Carrières-sous-Poissy, France
5
SATIE, Paris Saclay University, Gif-sur-Yvette, France
* Corresponding author: rebecca.mazloum@stellantis.com
Received:
15
September
2023
Accepted:
15
December
2023
Surrogate models have become a widely used solution for reducing computation times along design processes. In this work, a Gaussian Process surrogate model is built and used to predict the performance and losses of a wound field electrical machine in a fast manner. This approach is relevant, especially for drive cycle calculations that rapidly generate rising computation costs if they are computed using physical models, especially finite elements analysis. We present in detail the established method and a comparison of the obtained results with finite elements results. In addition, a detailed analysis of the optimized current supply is presented, and the advantages of variable excitation current are highlighted.
Key words: Drive cycle / Electrical machine / Excitation current / Gaussian process / Metamodeling
© The Author(s), published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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