A Hierarchical Digital Twin Adoption Framework for the Electric Mobility Ecosystem: Enablers, Challenges and Opportunities

The growing interest in green and sustainable transportation motivates large scale adoption of electric vehicles (EVs). Accurate modeling of the energy demands and traffic flows of the growing volumes of EVs is essential to enable optimal infrastructure sizing, operation and resource allocation, particularly as EVs couple the operation of the ground transportation networks (TNs) with that of the power distribution networks (PDNs). This encourages the utilization of digital twin (DT) technologies to model the electric (e-) mobility ecosystem, by utilizing high-fidelity data-driven simulations to build virtual replicas of the different assets and processes in the physical world. Nonetheless, owing to the inherent complexities and inter-dependencies between TNs and PDNs in the e-mobility ecosystem, e- mobility DT solutions are currently at the forefront of research and development activities with limited practical implementation. However, they are gaining an increasing popularity due to their ability to integrate and synchronize the physical and virtual worlds in real-time, thereby enabling precise analytics, real-time monitoring, performance optimization and decision making. Accordingly, this paper reviews state-of-the-art literature on the realization of DTs within the hierarchy of components, assets and systems that form an integrated e-mobility ecosystem, and highlights their advantages over existing traditional simulation platforms, as well as the different challenges and opportunities associated with the adoption of this transformative technology in the e-mobility domain. Potential future research directions are also discussed, leading the development of intelligent DTs of the EV charging infrastructure within coupled TNs and PDNs to enable a more interconnected electric transportation landscape.