TY - JOUR
T1 - Urban public charging infrastructure planning for electric vehicles
T2 - A continuum approximation approach
AU - An, Yichan
AU - Chow, Joseph Y.J.
AU - Woo, Soomin
AU - Lee, Jinwoo
N1 - Publisher Copyright:
© 2025 The Authors
PY - 2025/4
Y1 - 2025/4
N2 - Effective planning of electric vehicle charging infrastructure is crucial for enhancing charging network serviceability, which leads to greater electric vehicle adoption and ultimately contributes to mitigating environmental impact and achieving sustainability. In this study, we propose a novel continuum approximation approach to optimally plan urban public fast charging infrastructure considering spatial heterogeneity. We analytically estimate waiting and travel times to charge with queueing theory and evaluate serviceability over a planning region with spatial heterogeneity. The analytical model determines serviceability with planning factors, including station density and chargers per station; operational factors, such as station assignment rules; and exogenous factors, including charging demand, roadway network, and traffic conditions. We formulate an optimization problem to maximize serviceability and validate our framework in New York City, demonstrating improvements over current infrastructure. Furthermore, we investigate existing issues and provide guidance for future development, offering valuable insights for policymakers in developing efficient urban charging networks.
AB - Effective planning of electric vehicle charging infrastructure is crucial for enhancing charging network serviceability, which leads to greater electric vehicle adoption and ultimately contributes to mitigating environmental impact and achieving sustainability. In this study, we propose a novel continuum approximation approach to optimally plan urban public fast charging infrastructure considering spatial heterogeneity. We analytically estimate waiting and travel times to charge with queueing theory and evaluate serviceability over a planning region with spatial heterogeneity. The analytical model determines serviceability with planning factors, including station density and chargers per station; operational factors, such as station assignment rules; and exogenous factors, including charging demand, roadway network, and traffic conditions. We formulate an optimization problem to maximize serviceability and validate our framework in New York City, demonstrating improvements over current infrastructure. Furthermore, we investigate existing issues and provide guidance for future development, offering valuable insights for policymakers in developing efficient urban charging networks.
KW - Case study
KW - Continuum approximation
KW - Electric vehicles
KW - Public charging infrastructure
KW - Serviceability
KW - Spatial heterogeneity
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U2 - 10.1016/j.trd.2025.104605
DO - 10.1016/j.trd.2025.104605
M3 - Article
AN - SCOPUS:85218420811
SN - 1361-9209
VL - 141
JO - Transportation Research Part D: Transport and Environment
JF - Transportation Research Part D: Transport and Environment
M1 - 104605
ER -