Work

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

Year: 2023

Type: conference-paper

Abstract: 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.

Source: IEEE International Electric Machines & Drives Conference (IEMDC)

DOI: 10.1109/iemdc55163.2023.10238941

Authors: Claude Marchand, Mehdi Djami, Maya Hage Hassan, Guillaume Krebs, Philippe Dessante, Lamya Belhaj

Institutions: Centre National de la Recherche Scientifique, Laboratoire de Génie Électrique et Électronique de Paris, CentraleSupélec

Language: English

Topic: Electric and Hybrid Vehicle Technologies

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: green

Funder: Association Nationale de la Recherche et de la Technologie