4.7 Article

Optimal design and allocation of electrified vehicles and dedicated charging infrastructure for minimum life cycle greenhouse gas emissions and cost

Journal

ENERGY POLICY
Volume 51, Issue -, Pages 524-534

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.enpol.2012.08.061

Keywords

Electric vehicles; Plug-in hybrid electric vehicles; Hybrid electric vehicles

Funding

  1. National Science Foundation from the Foundation's Material Use, Science, Engineering and Society program [0628084]
  2. CAREER program [0747911]
  3. Graduate Research Fellowship program [0750271]
  4. Ford Motor Company
  5. Toyota Motors of America
  6. Steinbrenner Graduate Fellowship
  7. Div Of Chem, Bioeng, Env, & Transp Sys
  8. Directorate For Engineering [0628084] Funding Source: National Science Foundation
  9. Div Of Civil, Mechanical, & Manufact Inn
  10. Directorate For Engineering [0747911] Funding Source: National Science Foundation

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Electrified vehicles can reduce greenhouse gas (GHG) emissions by shifting energy demand from gasoline to electricity. GHG reduction potential depends on vehicle design, adoption, driving and charging patterns, charging infrastructure, and electricity generation mix. We construct an optimization model to study these factors by determining optimal design of conventional vehicles, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs) with optimal allocation of vehicle designs and dedicated workplace charging infrastructure in the fleet for minimum life cycle cost or GHG emissions over a range of scenarios. We focus on vehicles with similar body size and acceleration to a Toyota Prius under government 5-cycle driving conditions. We find that under the current US grid mix, PHEVs offer only small GHG emissions reductions compared to HEVs, and workplace charging is insignificant. With grid decarbonization, PHEVs and BEVs offer substantial GHG emissions reductions, and workplace charging provides additional benefits. HEVs are optimal or near-optimal for minimum cost in most scenarios. High gas prices and low vehicle and battery costs are the major drivers for PHEVs and BEVs to enter and dominate the cost-optimal fleet. Carbon prices have little effect. Cost and range restrictions limit penetration of BEVs. (C) 2012 Elsevier Ltd. All rights reserved.

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