Characterizing One-day Missions of PHEVs Based on Representative Synthetic Driving Cycles

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.