Comparison of optimal supervisory control strategies for a series plug-in hybrid electric vehicle powertrain

Rakesh Patil, Zoran Filipi, Hosam Fathy

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

9 Scopus citations

Abstract

This paper uses dynamic programming to compare the optimal fuel and electricity costs associated with two supervisory control strategies from the plug-in hybrid electric vehicle (PHEV) literature. One strategy blends fuel and electricity for propulsion throughout the useful range of battery state of charge (SOC), while the second strategy switches from all-electric to blended operation at a predefined SOC threshold. Both strategies are optimized for a series PHEV powertrain using deterministic dynamic programming (DDP) to ensure a fair comparison. The DDP algorithm is implemented in a novel manner using a backward-looking powertrain model instead of forward-looking models used in previous research. The paper's primary conclusion is that there is no significant difference in the performance of the two control strategies for the series PHEV considered. This result contrasts sharply with previous results for parallel and power-split PHEVs, and is examined for different relative fuel and electricity prices and trip lengths.

Original languageEnglish (US)
Title of host publicationASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011
Pages757-764
Number of pages8
DOIs
StatePublished - 2011
EventASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011 - Arlington, VA, United States
Duration: Oct 31 2011Nov 2 2011

Publication series

NameASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011
Volume1

Other

OtherASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, DSCC 2011
Country/TerritoryUnited States
CityArlington, VA
Period10/31/1111/2/11

All Science Journal Classification (ASJC) codes

  • Fluid Flow and Transfer Processes
  • Control and Systems Engineering

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