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Multicriterion optimal electric drive vehicle selection based on lifecycle emission and lifecycle cost
Author(s) -
Ahmadi P.,
Cai X.M.,
Khanna M.
Publication year - 2018
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.3937
Subject(s) - greenhouse gas , automotive engineering , work (physics) , range (aeronautics) , engineering , transport engineering , environmental economics , economics , mechanical engineering , ecology , biology , aerospace engineering
Summary This research paper examines the optimal choice among conventional gasoline vehicles, hybrid electric vehicles (HEVs), plug‐in HEVs (PHEV), and full‐battery EVs taking into account the different characteristics of these vehicles, such as cost, emissions per mile, and vehicle miles to be traveled between refueling and acceleration time. The existing challenges for wide‐spread deployment of EVs are availability of charging infrastructure, higher cost, long time for charging, and lower travel millage compared with conventional vehicles. Statistical data are considered for determining the spatially varying average daily vehicle miles traveled (VMT) across the United States, which, together with charging behavior, can influence the optimal choice among EV with different travel ranges. Two alternative cases for charging are examined: (1) home‐only charging and (2) home plus work charging. The motivation of this work is to select the optimal EV among their types when lifecycle cost and lifecycle emission are considered. The optimization model seeks to minimize total lifecycle cost and emissions for each level of VMT per day. It is found that when lifecycle cost is the sole objective, HEV is usually the best choice, especially for higher VMT levels. When lifecycle greenhouse gas emission is the sole objective, PHEV1 (PHEV with 1 charging station) is the optimal solution over a wide range of VMTs. The outcome of this provides a roadmap for the selection of EVs based on their annual VMT to reduce both lifecycle emission and lifecycle cost.