Bi-object Energy Consumption Minimization Strategy for HEVs

Yen Hsiang Huang, Nan Chyuan Tsai, Hsin Lin Chiu, Yu Chi Chen, Chia Cheng Kuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The proposed BOECMS (Bi-Object Equivalent Consumption Minimization Strategy) possesses three key features: being real-time, causal and capable of fulfilling two objects, namely, (i) minimized fuel consumption, and (ii) the battery SOC (State Of Charge) steadily retained within a relatively narrow range. A HEV (Hybrid Electric Vehicle) model and its corresponding power split strategy are developed and verified by using the vehicle simulator ADVISOR (ADvanced VehIcle SimulatOR) and Simulink at design stage. According to the computer simulation results, the degree of the improvement of fuel economy is up to 40.39 % in terms of 'MANHATTAN' drive cycle in comparison to the conventional pure ICE (Internal Combustion Engine) vehicles. Moreover, the experimental results by HIL (Hardware-In-the-Loop) are pretty close to the computer simulations undertaken by Simulink. This implies that the proposed energy management strategy, BOECMS, can be potentially applied to the real-world driving in the future.

Original languageEnglish
Title of host publication2018 5th International Conference on Electric Power and Energy Conversion Systems, EPECS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538664575
DOIs
Publication statusPublished - 2018 Aug 21
Event5th International Conference on Electric Power and Energy Conversion Systems, EPECS 2018 - Kitakyushu, Japan
Duration: 2018 Apr 232018 Apr 25

Publication series

Name2018 5th International Conference on Electric Power and Energy Conversion Systems, EPECS 2018

Other

Other5th International Conference on Electric Power and Energy Conversion Systems, EPECS 2018
CountryJapan
CityKitakyushu
Period18-04-2318-04-25

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

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