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<p>The accessibility of public electric vehicle charging stations (EVCS) is a critical factor in the widespread adoption of electric vehicles (EVs). Optimizing their spatial distribution to achieve equitable service coverage has become a vital task for promoting sustainable urban development. Taking the central urban area of Chengdu as a case study, this research evaluates the accessibility of public EVCS for residents within 1 km and 3 km service radii using an opportunity-based accessibility assessment method, incorporating inter-community competition effects and internal demand. This study employs spatial autocorrelation analysis to investigate the spatial clustering patterns of public EVCS accessibility and its relationship with community characteristics from a multi-scale perspective. The spatial equity of EVCS distribution was assessed, thereby providing a scientific foundation for optimizing infrastructure layouts. Key findings include: (1) Both EVCS and communities exhibit distinct central clustering in spatial distribution; (2) Compared to the inner-core areas, the outer-core areas face more severe imbalances in EVCS resource allocation; (3) The spatial autocorrelation between community characteristics (housing price, households, year built) and EVCS accessibility varies significantly across spatial scales and service ranges.</p>

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A multi-scale perspective on the accessibility of public electric vehicle charging stations and community equity disparities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月23日

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  • Congcong Wang,
  • Yang Gu,
  • Jiangwei Shen

摘要

The accessibility of public electric vehicle charging stations (EVCS) is a critical factor in the widespread adoption of electric vehicles (EVs). Optimizing their spatial distribution to achieve equitable service coverage has become a vital task for promoting sustainable urban development. Taking the central urban area of Chengdu as a case study, this research evaluates the accessibility of public EVCS for residents within 1 km and 3 km service radii using an opportunity-based accessibility assessment method, incorporating inter-community competition effects and internal demand. This study employs spatial autocorrelation analysis to investigate the spatial clustering patterns of public EVCS accessibility and its relationship with community characteristics from a multi-scale perspective. The spatial equity of EVCS distribution was assessed, thereby providing a scientific foundation for optimizing infrastructure layouts. Key findings include: (1) Both EVCS and communities exhibit distinct central clustering in spatial distribution; (2) Compared to the inner-core areas, the outer-core areas face more severe imbalances in EVCS resource allocation; (3) The spatial autocorrelation between community characteristics (housing price, households, year built) and EVCS accessibility varies significantly across spatial scales and service ranges.