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Impact of Battery Sizing on Stochastic Optimal Power Management in Plug-in Hybrid Electric Vehicles

CSS Publication Number
CSS08-20
Full Publication Date
October 10, 2008
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.

Co-Author(s)
Scott J. Moura
Research Areas
Mobility Systems
Transportation
Keywords
Battery management systems, Cost function, Dynamic programming, Hybrid electric vehicles, Power demand
Publication Type
Conference Proceeding
Digital Object Identifier
DOI:10.1109/ICVES.2008.4640902
Full Citation
Moura, Scott J., Duncan S. Callaway, Hosam K. Fathy, Jeffrey L. Stein. 2008. Impact of Battery Sizing on Stochastic Optimal Power Management in Plug-in Hybrid Electric Vehicles. Proceedings of the International Conference on Vehicular Electronics and Safety, Institute of Electrical and Electronics Engineers (IEEE) Columbus, OH, September 22-24 ,2008. 1-7.