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Title: How uncertain is the future of electric vehicle market: Results from Monte Carlo simulations using a nested logit model

Plug-in electric vehicles (PEVs) are widely regarded as an important component of the technology portfolio designed to accomplish policy goals in sustainability and energy security. However, the market acceptance of PEVs in the future remains largely uncertain from today's perspective. By integrating a consumer choice model based on nested multinomial logit and Monte Carlo simulation, this study analyzes the uncertainty of PEV market penetration using Monte Carlo simulation. Results suggest that the future market for PEVs is highly uncertain and there is a substantial risk of low penetration in the early and midterm market. Top factors contributing to market share variability are price sensitivities, energy cost, range limitation, and charging availability. The results also illustrate the potential effect of public policies in promoting PEVs through investment in battery technology and infrastructure deployment. Here, continued improvement of battery technologies and deployment of charging infrastructure alone do not necessarily reduce the spread of market share distributions, but may shift distributions toward right, i.e., increase the probability of having great market success.
 [1] ;  [2] ;  [1] ;  [2]
  1. National Transportation Research Center, Knoxville, TN (United States)
  2. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
International Journal of Sustainable Transportation
Additional Journal Information:
Journal Volume: 11; Journal Issue: 4; Journal ID: ISSN 1556-8318
Taylor & Francis
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). National Transportation Research Center (NTRC)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Country of Publication:
United States
33 ADVANCED PROPULSION SYSTEMS; 97 MATHEMATICS AND COMPUTING; charging infrastructure; consumer choice; electric vehicles; energy transition; market penetration; Monte Carlo simulation
OSTI Identifier: