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Tradeoffs between battery energy capacity and stochastic optimal power management in plug-in hybrid electric vehicles

CSS Publication Number
CSS09-33
Full Publication Date
November 13, 2009
Abstract

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.

Co-Author(s)
Scott J. Moura
Research Areas
Mobility Systems
Transportation
Energy Systems
Keywords

Plug-in hybrid electric vehicles, Lithium ion batteries, Power management, Stochastic dynamic programming, Optimal control, Battery sizing

Publication Type
Journal Article
Digital Object Identifier
https://doi.org/10.1016/j.jpowsour.2009.11.026
Full Citation

Moura, S. J., Callaway, D. S., Fathy, H. K., & Stein, J. L. (2009). Tradeoffs between battery energy capacity and stochastic optimal power management in plug-in hybrid electric vehicles. Journal of Power Sources, 195(9), 2979–2988. https://doi.org/10.1016/j.jpowsour.2009.11.026. CSS09-33.