Publication

Abstract : Cyber-physical systems in the e-transportation era have emerged as an advancement in the Electric Vehicle (EV) industry. Batteries are a prominent research product of EVs, driving progress towards the saturation of Industrial Revolution 5.0 by enhancing their efficiency, performance, and safety criteria. The current study provides a detailed survey on the implementation of Digital Twin Technology (DTT), a cyber-physical system in EV batteries. Battery Digital Twins (BDTs), which couple a physical battery with a continuously updated virtual counterpart, are widely proposed for this purpose; however, existing reviews rarely evaluates the level of BDT. This review addresses one central question: the extension of BDT implementations that satisfy the defining requirements of a digital twin while delivering the three functions on which predictive maintenance depends, namely thermal safety, state estimation and Remaining Useful Life (RUL) prediction. The review contributes an operational BDT definition and maturity classification, a reproducible evidence base and a research agenda prioritizing field-data validation, uncertainty-aware RUL prediction, bidirectional synchronization, interoperability and cybersecurity, with implications for researchers, battery manufacturers, fleet operators and digital-twin developers, thereby contributing to Sustainable Development Goal 7 (SDG-7).