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Optimal power management of plug-in HEV with intelligent transportation system

  • University of Wisconsin-Milwaukee
  • University of Wisconsin-Milwaukee

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

83 Scopus citations

Abstract

Hybrid electric vehicles (HEV) have demonstrated their capability of improving the fuel economy and emission. The plug-in HEV (PHEV), utilizing more battery power, has become a more attractive upgrade of HEV. The charge-depletion mode is more appropriate for the power management of PHEV, i.e. the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the destination of the trip. In the past, the trip information has been considered as future information for vehicle operation and thus unavailable a priori. This situation can be changed by the current advancement of Intelligent Transportation Systems (ITS) based on the use of on-board Geographical Information Systems (GIS), Global Positioning Systems (GPS) and advanced traffic flow modeling techniques. In this paper, a new approach of optimal power management of PHEV in the charge-depletion mode is proposed with driving cycle modeling based on the historic traffic information. A dynamic programming (DP) algorithm is applied to reinforce the charge-depletion control such that the SOC drops to a specific terminal value at the final time of the cycle. The vehicle model was based on a hybrid SUV. Only fuel consumption is considered for the current stage of study. Simulation results showed significant improvement in fuel economy compared with rule-based power management. Furthermore, simulations on several driving cycles using the proposed method showed much better consistency in fuel economy compared to the rule-based control.

Original languageEnglish
Title of host publication2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM - Zurich, Switzerland
Duration: 4 Sep 20077 Sep 2007

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM

Conference

Conference2007 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
Country/TerritorySwitzerland
CityZurich
Period4/09/077/09/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Dynamic programming
  • Intelligent transportation system
  • Plug-in hybrid electric vehicles
  • Power management

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