Digital Twin Technologies for Battery Systems: Advancements, Applications, and Future Directions

Authors

• Seyed Saeed Madani, Institut National de la Recherche Scientifique
• Yasmin Shabeer, University of Waterloo
• Michael Fowler, University of Waterloo
• Satyam Panchal, University of Waterloo
• Carlos Ziebert, Karlsruhe Institute of Technology
• Hicham Chaoui, Old Dominion UniversityFollow
• François Allard, Institut National de la Recherche Scientifique

Document Type

Article

Publication Date

2026

DOI

10.3389/fbael.2026.1764210

Publication Title

Frontiers in Batteries and Electrochemistry

Volume

5

Pages

1764210

Abstract

The relationships among deep learning, edge computing, artificial intelligence (AI), and the most recent advancements in digital twin (DT) technology for battery energy storage systems are discussed in this paper. The study highlights the need for improved cloud-edge coordination, AI model development, and stronger cybersecurity features by demonstrating real-world applications of digital twin technology in electric vehicles (EVs), aircraft, and grid storage. It also described DT-based structures for fault detection, real-time monitoring, and optimization through standardization and battery management system (BMS) fusion. Because DT-based solutions for distributed energy resources (DERs) offer improved energy management systems, various studies have been conducted on them. Better predictive maintenance results, greater operational resilience, and longer system lifespan are facilitated by the strategic digital transformation advancements of adaptive modeling, federated learning, and mixed-reality applications.

Rights

© 2026 Madani, Shabeer, Fowler, Panchal, Ziebert, Chaoui and Allard. 

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Original Publication Citation

Madani, S. S., Shabeer, Y., Fowler, M., Panchal, S., Ziebert, C., Chaoui, H., & Allard, F. (2026). Digital twin technologies for battery systems: Advancements, applications, and future directions. Frontiers in Batteries and Electrochemistry, 5, Article 1764210. https://doi.org/10.3389/fbael.2026.1764210

Repository Citation

Madani, Seyed Saeed; Shabeer, Yasmin; Fowler, Michael; Panchal, Satyam; Ziebert, Carlos; Chaoui, Hicham; and Allard, François, "Digital Twin Technologies for Battery Systems: Advancements, Applications, and Future Directions" (2026). Electrical & Computer Engineering Faculty Publications. 593.
https://digitalcommons.odu.edu/ece_fac_pubs/593

ORCID

0000-0001-8728-3653 (Chaoui)