The role of ITS in PHEV performance improvement

Author

Gong, Qiuming ; Tulpule, P. ; Marano, V. ; Midlam-Mohler, Shawn ; Rizzoni, G.

Author_Institution

Center for Automotive Res., Ohio State Univ., Columbus, OH, USA

fYear

2011

fDate

June 29 2011-July 1 2011

Firstpage

2119

Lastpage

2124

Abstract

Driving patterns have great impact on fuel economy or power split control decisions of PHEV (Plug-in Hybrid Electric Vehicle) energy management. In this paper, a statistical approach was used to analyze real world velocity profiles to gather traffic information such as average speed, speed limits, segment length, etc. A Markov chain model was developed to make use of such information for generation of random velocity profiles that are representative of real world driving scenarios. The velocity profiles generated using the Markov chain models are used to calculate vehicle fuel economy by means of a validated through the road parallel PHEV model and ECMS (Equivalent Consumption Minimization Strategy) control strategy. The end goal of the research is to find mathematical, statistical or heuristic relationships between road events and the performance of PHEV energy management.

Keywords

Markov processes; energy management systems; fuel economy; hybrid electric vehicles; minimisation; power control; road traffic; road vehicles; statistical analysis; traffic information systems; ECMS control strategy; ITS; Markov chain model; PHEV energy management; PHEV performance improvement; driving pattern; equivalent consumption minimization strategy; heuristic relationship; plug-in hybrid electric vehicle; power split control decision; random velocity profile generation; real world driving scenario; real world velocity profile; road parallel PHEV model; statistical approach; traffic information; vehicle fuel economy; Acceleration; Energy management; Fuel economy; Markov processes; Mathematical model; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2011

Conference_Location

San Francisco, CA

ISSN

0743-1619

Print_ISBN

978-1-4577-0080-4

Type

conf

DOI

10.1109/ACC.2011.5990968

Filename

5990968