Multi-objective optimization of automotive electrical/energy storage system

Gauthier Fontaine, Omar Hammami

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are strongly emerging as potential solutions to respect the more and more restrictive laws concerning CO2 emissions. In this context, the optimization of the costly Hybrid Energy Storage System (HESS) of HEVs is a key factor in reducing both CO2 emissions and costs of HEVs. In this paper, we propose an approach to optimize the configuration of an HESS architecture using evolutionary multi-objective optimization algorithms. Multiple constraints relaxation was necessary in order to match the objectives of the study. This results in a need for a systems engineering approach to define the scope and consequences of constraints relaxation.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Industrial Technology, ICIT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages339-343
Number of pages5
ISBN (Electronic)9781467380751
DOIs
Publication statusPublished - 19 May 2016
EventIEEE International Conference on Industrial Technology, ICIT 2016 - Taipei, Taiwan, Province of China
Duration: 14 Mar 201617 Mar 2016

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology
Volume2016-May

Conference

ConferenceIEEE International Conference on Industrial Technology, ICIT 2016
Country/TerritoryTaiwan, Province of China
CityTaipei
Period14/03/1617/03/16

Keywords

  • EMOO
  • HESS
  • M&S
  • PHEV
  • System

Fingerprint

Dive into the research topics of 'Multi-objective optimization of automotive electrical/energy storage system'. Together they form a unique fingerprint.

Cite this