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Title: Socially optimal replacement of conventional with electric vehicles for the US household fleet

Abstract

In this study, a framework is proposed for minimizing the societal cost of replacing gas-powered household passenger cars with battery electric ones (BEVs). The societal cost consists of operational costs of heterogeneous driving patterns' cars, the government investments for charging deployment, and monetized environmental externalities. The optimization framework determines the timeframe needed for conventional vehicles to be replaced with BEVs. It also determines the BEVs driving range during the planning timeframe, as well as the density of public chargers deployed on a linear transportation network over time. We leverage datasets that represent U.S. household driving patterns, as well as the automobile and the energy markets, to apply the model. Results indicate that it takes 8 years for 80% of our conventional vehicle sample to be replaced with electric vehicles, under the base case scenario. The socially optimal all-electric driving range is 204 miles, with chargers placed every 172 miles on a linear corridor. All of the public chargers should be deployed at the beginning of the planning horizon to achieve greater savings over the years. Sensitivity analysis reveals that the timeframe for the socially optimal conversion of 80% of the sample varies from 6 to 12 years. The optimal decisionmore » variables are sensitive to battery pack and vehicle body cost, gasoline cost, the discount rate, and conventional vehicles' fuel economy. In conclusion, faster conventional vehicle replacement is achieved when the gasoline cost increases, electricity cost decreases, and battery packs become cheaper over the years.« less

Authors:
ORCiD logo [1];  [2]; ORCiD logo [3];  [4]
  1. Univ. of Florida, Gainesville, FL (United States). Dept. of Civil and Coastal Engineering; National Renewable Energy Lab. (NREL), Golden, CO (United States). Transportation and Hydrogen Systems Center
  2. Univ. of Florida, Gainesville, FL (United States). Dept. of Civil and Coastal Engineering; Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Civil and Environmental Engineering
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
  4. Tsinghua Univ., Beijing (China). Dept. of Industrial Engineering
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Vehicle Technologies Office
OSTI Identifier:
1658021
Alternate Identifier(s):
OSTI ID: 1371525
Report Number(s):
NREL/JA-5400-68298
Journal ID: ISSN 1556-8318
Grant/Contract Number:  
AC05-00OR22725; AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of Sustainable Transportation
Additional Journal Information:
Journal Volume: 11; Journal Issue: 10; Journal ID: ISSN 1556-8318
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; 33 ADVANCED PROPULSION SYSTEMS; vehicle replacement; battery electric vehicles (BEVs); internal combustion engine vehicles (ICEVs); charging density; all-electric driving range; 30 DIRECT ENERGY CONVERSION

Citation Formats

Kontou, Eleftheria, Yin, Yafeng, Lin, Zhenhong, and He, Fang. Socially optimal replacement of conventional with electric vehicles for the US household fleet. United States: N. p., 2017. Web. https://doi.org/10.1080/15568318.2017.1313341.
Kontou, Eleftheria, Yin, Yafeng, Lin, Zhenhong, & He, Fang. Socially optimal replacement of conventional with electric vehicles for the US household fleet. United States. https://doi.org/10.1080/15568318.2017.1313341
Kontou, Eleftheria, Yin, Yafeng, Lin, Zhenhong, and He, Fang. Wed . "Socially optimal replacement of conventional with electric vehicles for the US household fleet". United States. https://doi.org/10.1080/15568318.2017.1313341. https://www.osti.gov/servlets/purl/1658021.
@article{osti_1658021,
title = {Socially optimal replacement of conventional with electric vehicles for the US household fleet},
author = {Kontou, Eleftheria and Yin, Yafeng and Lin, Zhenhong and He, Fang},
abstractNote = {In this study, a framework is proposed for minimizing the societal cost of replacing gas-powered household passenger cars with battery electric ones (BEVs). The societal cost consists of operational costs of heterogeneous driving patterns' cars, the government investments for charging deployment, and monetized environmental externalities. The optimization framework determines the timeframe needed for conventional vehicles to be replaced with BEVs. It also determines the BEVs driving range during the planning timeframe, as well as the density of public chargers deployed on a linear transportation network over time. We leverage datasets that represent U.S. household driving patterns, as well as the automobile and the energy markets, to apply the model. Results indicate that it takes 8 years for 80% of our conventional vehicle sample to be replaced with electric vehicles, under the base case scenario. The socially optimal all-electric driving range is 204 miles, with chargers placed every 172 miles on a linear corridor. All of the public chargers should be deployed at the beginning of the planning horizon to achieve greater savings over the years. Sensitivity analysis reveals that the timeframe for the socially optimal conversion of 80% of the sample varies from 6 to 12 years. The optimal decision variables are sensitive to battery pack and vehicle body cost, gasoline cost, the discount rate, and conventional vehicles' fuel economy. In conclusion, faster conventional vehicle replacement is achieved when the gasoline cost increases, electricity cost decreases, and battery packs become cheaper over the years.},
doi = {10.1080/15568318.2017.1313341},
journal = {International Journal of Sustainable Transportation},
number = 10,
volume = 11,
place = {United States},
year = {2017},
month = {4}
}

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