Spatial Association of Public Electric Vehicle Charging Stations and Urban Public Facilities: A Comparative Study of Historic and New Development Districts in Suzhou

Against the global imperative to address climate change and accelerate energy transitions, the rapid growth of the electric vehicle (EV) industry has turned public charging infrastructure into a key foundation of urban operations, driven by carbon peaking and carbon neutrality goals. However, effective supply depends not only on scale but on deep association with urban functional spaces. This study compares Gusu District (a historic preservation district) and Industrial Park District (a new development district) in Suzhou. The goal is to reveal how public electric vehicle charging stations (EVCSes) associate with functional spaces under different urban development models. The study employs Standard Deviational Ellipse (SDE), Kernel Density Estimation (KDE), Bivariate Spatial Autocorrelation, and Coupling Coordination Degree (CCD) models to compare layout patterns, clustering features and functional association. The research findings are as follows: (1) The EVCS layout in Gusu District shows strong dependence on roads and administrative boundaries, while EVCSes in Industrial Park District show clear planning intervention, less constrained by its administrative boundary. (2) KDE analysis confirms that Gusu District has continuous clustering centered on the ancient city, but Industrial Park District shows a multi-center layout. (3) Bivariate Spatial Autocorrelation reveals different priorities in facility allocation. In Gusu District, spatial association is mainly driven by high-mobility nodes, while in Industrial Park District, EVCSes are more deeply embedded in social services and daily life scenarios. (4) CCD analysis reveals that the coordination in Gusu District forms a monocentric, spatially continuous gradient centered on the ancient city, whereas in Industrial Park District it displays a polycentric but fragmented pattern, with high coordination areas confined to planned cores. This comparative study reveals the EVCS spatial layout, which is shaped by both administrative boundaries and policy constraints, and the heterogeneity in spatial association between two districts. It provides scientific evidence and decision support for different spatial governance and facility optimization in various types of urban areas.