Systematic literature review of urban charging infrastructure planning over time

Abstract

The transition from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs) is imperative to achieve the goal of reducing transport-related greenhouse gas emissions by 90 % in 2050. As urbanization intensifies, vehicle miles in urban environments increase and cities already consume 75 % of global energy, there is a pressing need for efficient charging infrastructure (CI) placement tailored to urban environments. Accordingly, this paper conducts a systematic literature review to outline prevailing research and derive requirements for a future CI model adaptable to urban environments. Analysis of N = 57 studies underscores the necessity for agent-based demand models to capture the intricate behaviors of EV drivers, which are currently underrepresented due to their data-heavy nature (n = 28 flow-based; n = 18 node-based). Furthermore, with a projected surge of 800 % in CI installations in Europe by 2030, strategic placement according to demand and urban-specific requirements is paramount. Still, multi-periodicity considerations are largely absent in current literature (n = 50). Geometric segmentation is presented as a solution to mitigate partial coverage issues. Ultimately, agent-based models, coupled with geometric segmentation, emerge as pivotal requirements for future CI models in urban environments, facilitating the transition to EVs, aligning with emission reduction targets, ensuring resource efficiency, and fostering urban sustainability.