DocumentCode
3034121
Title
Impact of battery sizing on stochastic optimal power management in plug-in hybrid electric vehicles
Author
Moura, Scott J. ; Callaway, Duncan S. ; Fathy, Hosam K. ; Stein, Jeffrey L.
Author_Institution
Dept. of Mech. Eng., Univ. of Michigan, Ann Arbor, MI
fYear
2008
fDate
22-24 Sept. 2008
Firstpage
96
Lastpage
102
Abstract
This paper examines the impact of battery sizing on the performance and efficiency of power management algorithms in plug-in hybrid electric vehicles (PHEVs). Existing studies examine this impact for power management algorithms derived using either rule-based or deterministic dynamic programming methods. This paper extends the above investigations to power management algorithms optimized using stochastic dynamic programming (SDP). The paper treats both PHEV trip duration and PHEV power demand over the course of a given trip as stochastic. Furthermore, the paper examines two power management optimization objectives: one emphasizing fuel consumption only, and one that emphasizes the total cost of the blended use of fuel and electricity. The paper shows that blending provides significant benefits for small batteries, but this effect diminishes with increasing battery size.
Keywords
dynamic programming; hybrid electric vehicles; stochastic programming; battery sizing; deterministic dynamic programming methods; plug-in hybrid electric vehicles; stochastic dynamic programming; stochastic optimal power management; Battery management systems; Cost function; Drives; Dynamic programming; Energy management; Fuels; Hybrid electric vehicles; Power demand; Size control; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Vehicular Electronics and Safety, 2008. ICVES 2008. IEEE International Conference on
Conference_Location
Columbus, OH
Print_ISBN
978-1-4244-2359-0
Electronic_ISBN
978-1-4244-2360-6
Type
conf
DOI
10.1109/ICVES.2008.4640902
Filename
4640902
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