Metamodel-Based Electric Vehicle Powertrain Optimization : A Drive Cycle Approach

被引:0
|
作者
Marchand, Claude [1 ,2 ]
Djami, Mehdi [1 ,2 ,3 ]
Hassan, Maya Hage [2 ]
Krebs, Guillaume [1 ,2 ]
Dessante, Philippe [1 ,2 ]
Belhaj, Lamya [3 ]
机构
[1] Univ Paris Saclay, Centralesupelec, Lab Genie Elect & Elect Paris, CNRS, Gif Sur Yvette, France
[2] Sorbonne Univ, CNRS, Lab Genie Elect & Elect Paris, Paris, France
[3] Stellantis, Ctr Tech Carrieres Sous Poissy, 212 Blvd Pelletier, Carrieres Sous Poissy, France
关键词
electric powertrain; drive cycle; metamodeling; multi-objective optimization; DESIGN;
D O I
10.1109/IEMDC55163.2023.10238941
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Components selection and mutualizing for different segments are needed to improve electric vehicle powertrains and limit costs. This paper proposes a first accelerated approach to model and design the electric vehicle powertrain. The optimization scope includes relevant electric powertrain components such as the inverter, the electrical machine, and the reducer. This methodology applies metamodeling techniques for estimating losses in the machine and analytical models for calculating the inverter and the reducer power losses. The driving cycle is considered through the k-means method to reduce the number of operating points considered. The multi-objective optimization is applied to a case study for the WLTC drive cycle and multiple component combinations to investigate modularity.
引用
收藏
页数:5
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