Energy management of hybrid vehicles using artificial intelligence

Hao Ran Chi, Kwok Tai Chui, Kim Fung Tsang, Henry Shu Hung Chung

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

5 Citations (Scopus)

Abstract

High depletion of diesel and petroleum gas in vehicles has wreaked havoc on environment and human beings. In the light of better fuel economy and lower pollution, more people will adopt hybrid electric vehicles. To improve the energy efficiency of fuel-cell based hybrid electric vehicles and thus improving the performance of fuel reduction, a feasibility study of optimization of energy efficiency has been discussed using fuzzy logic controller. On the other hand, energy has precedence to be generated by battery over fuel as battery produces less pollutants and carbon dioxide. Based on various percentage battery capacity and fuel tank capacity, thirty two (9) scenarios have been investigated. The average reduction of fuel consumption by fuzzy logic controller is 21.1% with 464 tons carbon dioxide reduction and 3.3 million Hong Kong dollars saving provided one million of hybrid electric vehicles travel for 28 kilometers. This can relieve the greenhouse effect and increase the popularity of people from replacing conventional vehicles with hybrid electric vehicles.

Original languageEnglish
Title of host publication2013 IEEE 2nd Global Conference on Consumer Electronics, GCCE 2013
Pages65-67
Number of pages3
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 IEEE 2nd Global Conference on Consumer Electronics, GCCE 2013 - Tokyo, Japan
Duration: 1 Oct 20134 Oct 2013

Publication series

Name2013 IEEE 2nd Global Conference on Consumer Electronics, GCCE 2013

Conference

Conference2013 IEEE 2nd Global Conference on Consumer Electronics, GCCE 2013
Country/TerritoryJapan
CityTokyo
Period1/10/134/10/13

Keywords

  • Artificial Intelligence (AI)
  • Energy Management
  • Fuzzy Logic (FL))
  • Hybrid Electric Vehicle (HEV)

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