This paper examines the problem of predicting the aggregate grid load imposed by battery health-conscious plug-in hybrid electric vehicle (PHEV) charging. The paper begins by generating a set of representative daily PHEV trips using the National Household Travel Survey (NHTS) and a set of federal and real-world drive cycles. Each trip is then used in a multiobjective genetic optimizer, along with a PHEV model and a battery degradation model, to simultaneously minimize PHEV energy cost and battery degradation. The optimization variables include the parameters of the PHEV charge pattern, defined as the timing and rate with which the PHEV receives electricity from the grid. For several weightings of the optimization objectives, total PHEV power demand is predicted by accumulating the charge patterns for individual PHEVs. Two charging scenarios, i.e., charging at home only versus charging at home and work, are examined. Results indicate that the main PHEV peak load occurs early in the morning (between 5.00–6.00a.m.), with approximately 45%–60% of vehicles simultaneously charging from the grid. Moreover, charging at work creates additional peaks in this load pattern.
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ASME 2010 Dynamic Systems and Control Conference
September 12–15, 2010
Cambridge, Massachusetts, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4417-5
PROCEEDINGS PAPER
Battery Health-Conscious Plug-In Hybrid Electric Vehicle Grid Demand Prediction
Saeid Bashash,
Saeid Bashash
University of Michigan, Ann Arbor, MI
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Scott J. Moura,
Scott J. Moura
University of Michigan, Ann Arbor, MI
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Hosam K. Fathy
Hosam K. Fathy
University of Michigan, Ann Arbor, MI
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Saeid Bashash
University of Michigan, Ann Arbor, MI
Scott J. Moura
University of Michigan, Ann Arbor, MI
Hosam K. Fathy
University of Michigan, Ann Arbor, MI
Paper No:
DSCC2010-4197, pp. 489-497; 9 pages
Published Online:
January 25, 2011
Citation
Bashash, S, Moura, SJ, & Fathy, HK. "Battery Health-Conscious Plug-In Hybrid Electric Vehicle Grid Demand Prediction." Proceedings of the ASME 2010 Dynamic Systems and Control Conference. ASME 2010 Dynamic Systems and Control Conference, Volume 1. Cambridge, Massachusetts, USA. September 12–15, 2010. pp. 489-497. ASME. https://doi.org/10.1115/DSCC2010-4197
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