Journal
JOURNAL OF POWER SOURCES
Volume 195, Issue 9, Pages 2979-2988Publisher
ELSEVIER
DOI: 10.1016/j.jpowsour.2009.11.026
Keywords
Plug-in hybrid electric vehicles; Lithium ion batteries; Power management; Stochastic dynamic programming; Optimal control; Battery sizing
Funding
- National Science Foundation
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Recent results in plug-in hybrid electric vehicle (PHEV) power management research suggest that battery energy capacity requirements may be reduced through proper power management algorithm design. Specifically, algorithms which blend fuel and electricity during the charge depletion phase using smaller batteries may perform equally to algorithms that apply electric-only operation during charge depletion using larger batteries. The implication of this result is that blended power management algorithms may reduce battery energy capacity requirements, thereby lowering the acquisition costs of PHEVs. This article seeks to quantify the tradeoffs between power management algorithm design and battery energy capacity, in a systematic and rigorous manner. Namely, we (1) construct dynamic PHEV models with scalable battery energy capacities, (2) optimize power management using stochastic control theory, and (3) develop simulation methods to statistically quantify the performance tradeoffs. The degree to which blending enables smaller battery energy capacities is evaluated as a function of both daily driving distance and energy (fuel and electricity) pricing. (c) 2009 Elsevier B.V. All rights reserved.
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