Microscopic series plug-in hybrid electric vehicle energy consumption model: Model development and validation

Plug-in hybrid electric vehicles (PHEVs) significantly improve vehicle fuel efficiency compared to conventional internal combustion engine vehicles (ICEVs) and also eliminate the “range anxiety” associated with battery-only electric vehicles (BEVs). This paper develops a simple PHEV energy consumption model that can be used in a real-time in-vehicle and smartphone eco-driving application, an eco-routing navigation system, and/or a microscopic traffic simulation software. The majority of PHEV studies have centered on the evaluation of energy consumption to analyze vehicle control strategies or the behavior of the battery system assuming an average constant value for the regenerative braking energy efficiency or regenerative braking factors that are principally dependent on the vehicle’s average speed. The proposed series PHEV energy consumption model estimates a PHEV’s instantaneous energy consumption using second-by-second vehicle speed, acceleration, and roadway grade data as input variables accounting for the regenerative braking efficiency using instantaneous vehicle parameters. The model developed in this study computes the vehicle’s energy consumption producing an average error of 4% relative to independently collected field data. Results show that PHEVs can recover a higher amount of energy in urban driving when compared to high speed highway driving. Finally, it is important to highlight the fact that this model is flexible and general and thus can model different PHEVs as there is no need for efficiency maps for the electric motor or the internal combustion engine.

• Record URL:
  • https://doi.org/10.1016/j.trd.2018.04.022
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1361920917306843
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • © 2018 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Fiori, Chiara
  • Ahn, Kyoungho
  • Rakha, Hesham A
• Publication Date: 2018-8

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 175-185
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 63
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Energy consumption; Microscopic traffic flow; Plug-in hybrid vehicles; Pollutants; Regenerative braking; Traffic simulation; Validation
• Subject Areas: Energy; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01680503
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 17 2018 10:32AM