When, Where, Who, and What: A 4 W analysis of digital twin-enabled optimization in EV energy storage systems

The integration of digital twin technology into electric vehicles, particularly in optimizing energy storage systems, is pivotal for advancing sustainable transportation and achieving critical global sustainability targets. This paper provides a comprehensive overview and thematic analysis focused on the nexus of digital twin and electric vehicle energy storage systems optimization. Utilizing a structured 4Ws framework (When, Where, Who, and What) and a technology-readiness perspective, we systematically analyzed 184 scholarly articles retrieved from the Scopus database, supplemented by a policy impact assessment using the Overton policy database. Our findings reveal exponential growth in scholarly attention from 2021 onwards, driven by significant contributions from China and the United States, with notable institutional leadership from organizations such as the Beijing Institute of Technology. Thematic insights identify “digital twins”, “machine learning”, “artificial intelligence”, and “lithium-ion battery” as the dominant research areas, underscored by their frequent appearance in the literature. Analysis shows 43 % of studies at technology-readiness levels 4–6 (prototypes, hardware-in-the-loop) and 25 % at levels 7–9 (commercial fleets, grid integration), indicating progress toward scalability. Despite strong academic developments, the analysis indicates limited integration of digital twin-enabled energy storage systems optimization research into policy frameworks, pointing to significant opportunities for enhancing research-policy engagement. This study presents clear theoretical, methodological, and practical implications, highlights key challenges associated with digital twin-enabled optimization of energy storage systems, and provides valuable insights for researchers, industry stakeholders, and policymakers aiming to leverage digital twin technologies for sustainable electric mobility. Furthermore, based on the findings, we provide future research directions that can facilitate innovation and inform policy development in this field.