Multi-objective optimization for energy management of fuel cell hybrid electric vehicles

Hao Liu, Jian Chen*, Chengshuai Wu, Hao Chen

*Corresponding author for this work

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

Abstract

Energy management strategies (EMSs) are crucial for enhancing the economy and durability of fuel cell hybrid electric vehicles (FCHEVs), However, most existing EMSs are only concerned with economy and ignore the durability, especially the durability of the energy sources. In this paper, based on an improved FCHEV powertrain model, an equivalent cost function considering both economy and durability is developed, and then a fuzzy logic based EMS is designend to realize the energy distribution between fuel cell and battery. After that, based on three different driving cycles, the teaching learning based optimization (TLBO) is introduced to solve the parameters optimization problem of the fuzzy logic based multiobjective EMS. Test results show that the TLBO algorithm has faster convergence rate and better optimization results than the existing genetic algorithm approach.

Original languageEnglish
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6303-6308
Number of pages6
ISBN (Print)9781538654286
DOIs
StatePublished - 9 Aug 2018
Externally publishedYes
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: 27 Jun 201829 Jun 2018

Publication series

NameProceedings of the American Control Conference
Volume2018-June
ISSN (Print)0743-1619

Conference

Conference2018 Annual American Control Conference, ACC 2018
Country/TerritoryUnited States
CityMilwauke
Period27/06/1829/06/18

Keywords

  • Energy management strategy
  • fuel cell hybrid electric vehicles
  • multi-objective optimization
  • teaching learning based optimization

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