Pareto Efficient Policy for Supervisory Power Management Control

In this paper the author addresses the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). The author models HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and shows that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.

• Record URL:
  https://doi.org/10.1109/ITSC.2015.457
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9781467365956
• Supplemental Notes:
  • Abstract reprinted with permission of IEEE.
• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  3 Park Avenue, 17th Floor
  New York, NY  United States  10016-5997
• Authors:
  • Malikopoulos, Andreas
• Conference:
  • 18th International IEEE Conference on Intelligent Transportation Systems (ITSC)
  • Location: Canary Islands , Spain
  • Date: 2015-9-15 to 2015-9-18
• Publication Date: 2015

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 2843-2848
• Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

• TRT Terms: Electric vehicles; Hybrid vehicles; Markov chains; Optimization
• Uncontrolled Terms: Pareto optimum; Power management
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01599790
• Record Type: Publication
• ISBN: 9781467365956
• Files: TRIS
• Created Date: May 2 2016 3:22PM