Characterizing one-day missions of PHEVs based on representative synthetic driving cycles

Lee, T.-K. and Baraket, Z. and Gordon, T. and Filipi, Z. (2011) Characterizing one-day missions of PHEVs based on representative synthetic driving cycles. SAE International Journal of Engines, 4 (1). pp. 1088-1101. ISSN 1946-3936

Full content URL: http://dx.doi.org/10.4271/2011-01-0885

Full text not available from this repository.

Item Type:Article
Item Status:Live Archive

Abstract

This paper investigates series plug-in hybrid electric vehicle (PHEV) behavior during one-day with synthesized representative one-day missions. The amounts of electric energy and fuel consumption are predicted to assess the PHEV impact on the grid with respect to the driving distance and different charging scenarios: (1) charging overnight, (2) charging whenever possible. The representative cycles are synthesized using the extracted information from the real-world driving data in Southeast Michigan gathered through the Field Operational Tests (FOT) conducted by the University of Michigan Transportation Research Institute (UMTRI). The real-world driving data include 4,409 trips covering 830 independent days and temporal distributions of departure and arrival times. The sample size is large enough to represent real-world driving. The driving cycle synthesis approach proposed by Lee, and Filipi 2,3 based on a stochastic process and subsequent validation procedure is used to create real-world driving cycles. To cover the entire range of real-world driving distance, ten synthetic cycles are created ranging from 4.78 miles to 40.71 miles following the real-world driving distance distribution. The PHEV behavior over one-day is characterized through a simulation based approach. The PHEV simulation is executed using Matlab simulink based Powertrain System Analysis Toolkit (PSAT) developed by Argonne National Laboratory (ANL) and in-house Matlab codes. The amounts of the electricity and fuel consumptions over one-day are predicted under different driving distances and different charging scenarios. The prediction of the PHEV behavior can be directly linked to the loads on the local distribution network. © 2011 SAE International.

Additional Information:SAE 2011 World Congress and Exhibition
Keywords:Argonne National Laboratory, Arrival time, Driving cycle, Driving distance, Electric energies, Local distribution networks, Matlab code, Matlab-Simulink, Michigan, Operational test, Plug-In Hybrid Electric Vehicle, Power-train systems, Sample sizes, Simulation-based, Stochastic process, Temporal distribution, Transportation research, University of Michigan, Electric vehicles, Fuel consumption, Random processes, Systems analysis, MATLAB
Subjects:H Engineering > H100 General Engineering
H Engineering > H330 Automotive Engineering
Divisions:College of Science > School of Engineering
ID Code:11656
Deposited On:03 Oct 2013 14:32

Repository Staff Only: item control page