Designing electric vehicle incentives to meet emission reduction targets

Electric vehicles are expected to reduce transportation emissions. The authors design and allocate rebates and charging infrastructure investments to induce electric vehicle adoption and achieve emission reduction targets. A nonlinear mixed-integer mathematical model is proposed to optimize the investment allocation over a planning horizon. Logistic functions describe the vehicle demand driven by capital and ownership costs and network externalities. A simulated annealing algorithm is used to solve the nonlinear programming problem that is applied using data representative of the United States market. The authors' analysis indicates that rebates should be provided earlier than chargers due to neighborhood effects of electric vehicle adoption and the minimization of expenditure; availability of home charging influences consumers choice and the drivers electrified travel distance; rebates are more effective for modest drivers while charging stations should be prioritized for frequent drivers; network externalities should be further investigated because of their impact on electric vehicle demand.

• Record URL:
  https://doi.org/10.1016/j.trd.2022.103320
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1361920922001481
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • © 2022 Yen-Chu Wu et al. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Wu, Yen-Chu
  • Kontou, Eleftheria
  • 0000-0003-1367-4226
• Publication Date: 2022-6

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 103320
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 107
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Electric vehicle charging; Electric vehicles; Incentives; Optimization; Pollutants
• Subject Areas: Environment; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01849260
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 23 2022 9:16AM