Electric Vehicle Fleet and Charging Infrastructure Planning

• 成果类型: Article
• 署名作者: Varma, Sushil Mahavir; Castro, Francisco; Maguluri, Siva Theja
• 署名单位: University System of Georgia; Georgia Institute of Technology; University of California System; University of California Los Angeles
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2024.08524
• 发表日期: 2026
• 关键词: Electric vehicles; capacity planning; spatial operations; asymptotic analysis

摘要

We study electric vehicle (EV) fleet and charging infrastructure planning in a spatial setting. For a centrally managed fleet that serves customer requests arriving continuously at a rate lambda throughout the day, we determine the minimum number of vehicles and chargers for a target service level along with matching and charging policies. Whereas non-EV systems require extra Theta(lambda 2/3) vehicles because of pickup times, EV systems differ. Charging increases nominal capacity, enabling pickup time reductions and allowing for an extra fleet requirement of only Theta(lambda nu) for nu is an element of (1/2, 2/3], depending on charging infrastructure and battery pack sizes. We propose the power-of-d dispatching policy, which achieves this performance by selecting the closest vehicle with the highest battery level from d options. We extend our results to accommodate time-varying demand patterns and discuss conditions for transitioning between EV and non-EV capacity planning. Simulations verify our scaling results, insights, and policy effectiveness. Whereas long-range, fast-charging fleets resemble non-EV systems, short-range, low-cost fleets can still perform competitively, underscoring the need for EV-aware management policies.