DocumentCode :
2729728
Title :
Statistical analysis of PHEV fleet data
Author :
Gong, Qiuming ; Midlam-Mohler, Shawn ; Marano, Vincenzo ; Rizzoni, Giorgio ; Guezennec, Yann
Author_Institution :
Center for Automotive Res., Ohio State Univ., Columbus, OH, USA
fYear :
2010
fDate :
1-3 Sept. 2010
Firstpage :
1
Lastpage :
6
Abstract :
The added load that a PHEV (Plug-in Hybrid Electric Vehicle) fleet imposes on the existing electrical grid is of great concern to the electric utility industry. In this paper, analysis was done for a PHEV fleet which consists of 6 PHEVs that were instrumented using data loggers for a period of approximately one year. Systematic analysis using a clustering approach was carried out for the real world velocity profiles. A driving pattern recognition algorithm was developed based on the clustering of the results and Markov-chain model was used for the stochastic velocity generation for different driving patterns. The work of this paper is a part of a larger project in which a mass simulation of a neighborhood of PHEVs will be conducted based on statistical representations of key factors such as vehicle usage patterns, vehicle characteristics, and market penetration of PHEVs.
Keywords :
Markov processes; electricity supply industry; hybrid electric vehicles; power grids; statistical analysis; Markov-chain model; PHEV; clustering approach; electric utility industry; electrical grid; fleet data; pattern recognition algorithm; statistical analysis; stochastic velocity generation; Acceleration; Markov processes; Measurement; Road transportation; System-on-a-chip; Vehicles; PHEV; fleet study; grid interaction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicle Power and Propulsion Conference (VPPC), 2010 IEEE
Conference_Location :
Lille
Print_ISBN :
978-1-4244-8220-7
Type :
conf
DOI :
10.1109/VPPC.2010.5729224
Filename :
5729224
Link To Document :
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