IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v18y2026i7p3257-d1907280.html

An AI-Powered Integrated Management Model for a Sustainable Electric Vehicle Charging Infrastructure

Author

Listed:
  • Arianna D’Ulizia

    (Consiglio Nazionale delle Ricerche (CNR)—Istituto di Ricerche sulla Popolazione e le Politiche Sociali (IRPPS), 00185 Rome, Italy)

  • Alessia D’Andrea

    (Consiglio Nazionale delle Ricerche (CNR)—Istituto di Ricerche sulla Popolazione e le Politiche Sociali (IRPPS), 00185 Rome, Italy)

  • Marco Pirrone

    (Consiglio Nazionale delle Ricerche (CNR)—Istituto di Ricerche sulla Popolazione e le Politiche Sociali (IRPPS), 00185 Rome, Italy)

  • Daizhong Su

    (School of Architecture, Design and the Built Environment, Nottingham Trent University, Nottingham NG1 4BU, UK)

Abstract

The rapid increase of electric mobility is challenging the deployment design and operation of electric vehicle charging infrastructure in a scalable, sustainable, operationally reliable, and regulation-compliant manner. Although advances in both digitization and artificial intelligence in recent years have made smarter charging solutions possible, today’s approaches tend to concentrate on individual technical parts without considering holistic views. This paper introduces an AI-driven integrated management model for sustainable EV charging infrastructures, composed of four interconnected layers, namely, Eco-Design, Digital Tools, Risk Management, and Governance. In particular, each layer focuses on specific aspects of functionality, including environmentally friendly design decisions, digital monitoring capabilities, proactive risk reduction, and strategic coordination. Compared with existing approaches that address isolated technical or operational aspects, the proposed model provides an integrated, multi-layer architecture that unifies eco-design, digital intelligence, risk management and governance, offering a more holistic and scalable foundation for sustainable EV charging infrastructures. It represents the conceptual output of a structured integration of existing technologies, design principles and governance needs. Considering that fragmented, solution-specific advances are reduced by including interdependencies between layers, the model allows us to better integrate technical operations, resilience mechanisms and sustainability goals. The model is theoretical and offers a scalable point of reference for researchers, as well as infrastructure operators and politicians.

Suggested Citation

  • Arianna D’Ulizia & Alessia D’Andrea & Marco Pirrone & Daizhong Su, 2026. "An AI-Powered Integrated Management Model for a Sustainable Electric Vehicle Charging Infrastructure," Sustainability, MDPI, vol. 18(7), pages 1-23, March.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:7:p:3257-:d:1907280
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/18/7/3257/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/18/7/3257/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:18:y:2026:i:7:p:3257-:d:1907280. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.