The influence of the battery technology choice on motor optimisation for electric vehicles

Aissam Meddour, Nassim Rizoug, Anthony Babin, Christopher Vagg, Richard Burke

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

Abstract

This paper investigates the impact of battery technology on the electric motor's optimization process for an electric vehicle application. Matlab and Ansys Electronics are used to conduct the simulations. The needed autonomy is estimated for the WLTC driving cycle using a dynamic vehicle model while considering the storage system mass calculated with a connected sizing algorithm. The Motor model is constructed using the finite element soft-ware Ansys electronics. The genetic algorithm will determine its geometrical parameters while considering the new power and torque demands, including the storage system weight. The comparison of the optimization results was carried out for four battery technologies that have promising characteristics for an automotive application. The results discussed active material cost and performances evaluated for the entire selected driving cycle.
Original languageEnglish
Title of host publication2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)
PublisherIEEE
Pages1635-1640
Number of pages6
ISBN (Electronic)978-1-6654-9607-0
ISBN (Print)978-1-6654-9608-7
DOIs
Publication statusPublished - 30 Jun 2022

Publication series

NameInternational Conference on Control, Decision and Information Technologies
PublisherIEEE
ISSN (Print)2576-3547
ISSN (Electronic)2576-3555

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