An Improved Fuzzy Energy Management Strategy Based-On Particle Swarm Optimal Algorithm for Electric Vehicle

Yadong Wei, Hongwei Ma, Xiaozhong Liao, Tao Huang

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

Abstract

This paper proposes an improved fuzzy energy management strategy based on particle swarm optimal algorithm for electric vehicle with dual-battery storage system. The proposed method adds optimization criterions on the basis of fuzzy rules to maximize the charge-discharge efficiency and achieve optimal power allocation. Simulation results based on Matlab / Simulink illustrated that the improved fuzzy energy management could increase the charge-discharge efficiency and mileage, effectively reduce power output of the main-battery in the case of the low remaining capacity, and extend the lifetime of the main battery to a certain extent.

Original languageEnglish
Title of host publication2016 IEEE Vehicle Power and Propulsion Conference, VPPC 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509035281
DOIs
Publication statusPublished - 19 Dec 2016
Event13th IEEE Vehicle Power and Propulsion Conference, VPPC 2016 - Hangzhou, China
Duration: 17 Oct 201620 Oct 2016

Publication series

Name2016 IEEE Vehicle Power and Propulsion Conference, VPPC 2016 - Proceedings

Conference

Conference13th IEEE Vehicle Power and Propulsion Conference, VPPC 2016
Country/TerritoryChina
CityHangzhou
Period17/10/1620/10/16

Keywords

  • Electric vehicle
  • dual-battery storage system
  • energy management
  • fuzzy control
  • particle swarm optimal algorithm

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