Masters Theses

Keywords and Phrases

Electric Vehicle; Load Profile; NHTS; Opportunity Charging; Plug-in Hybrid; Vehicle-to-grid

Abstract

"This thesis focuses on the load profile analysis of the plug-in hybrid electric vehicles (PHEV), examining two different scenarios. In the first scenario, the battery of a PHEV is charged at the final arrival time, and the arrival time analysis has a minute accuracy. In the second scenario, opportunity charging, which refers to the stop-time between two trips, is used for charging the battery of the vehicle. However, if the stop-time between two trips is less than 30 minutes, the duration is not counted as an opportunity charging and it is filtered. The results of the two scenarios are compared, and through this comparison, it is revealed that the opportunity charging scenario has a more flat profile. The improvement not only shows the positive features of the opportunity charging in terms of using more electrical power instead of traditional petroleum-based fuel, but also creates more opportunity for the power grid to use renewable energy resources instead of traditional fossil fuels. These two significant features, present opportunity charging as a strong solution for the negative environmental effects of petroleum vehicles in urban areas, and even in a world-scale view. The data pool is collected from the national household travel survey (NHTS) database, which is a major reference for transportation studies. The analyses are done for the years 2001 and 2009, and the resulting data file includes the data of about 43000 different vehicles"--Abstract, page iv.

Advisor(s)

Ferdowsi, Mehdi

Committee Member(s)

Shamsi, Pourya
Modares, Hamidreza

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2017

Pagination

xi, 30 pages

Note about bibliography

Includes bibliographical references (page 29).

Rights

© 2017 Reza Kazem Sharif Sharifi

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 11099

Electronic OCLC #

992441019

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