Evolution of Intelligent Battery Management System for Enhanced Safety and Performance in Lithium-Ion Electric Vehicles

This review comprehensively examined the evolution of Intelligent Battery Management Systems for lithium-ion electric vehicles by synthesizing recent developments reported between 2020 and 2026. The findings demonstrate that Battery Management Systems have progressed from conventional protection and monitoring devices to intelligent, AI-driven platforms capable of predictive diagnostics, adaptive decision-making, and real-time battery optimization. The integration of Artificial Intelligence, Machine Learning, Digital Twin technology, cloud computing, wireless communication, and edge computing has substantially improved the accuracy of battery state estimation, fault detection, charging optimization, and thermal management. These technological advancements have enhanced battery safety, increased operational efficiency, prolonged battery lifespan, and supported the reliable deployment of electric vehicles under diverse operating conditions. The systematic analysis further revealed that AI-based SOC and SOH estimation, predictive maintenance, cloud-connected battery analytics, and digital twin-enabled battery monitoring represent the most rapidly growing research areas within the field of Intelligent Battery Management Systems. Nevertheless, important research challenges remain, including computational complexity, cybersecurity vulnerabilities, limited real-world datasets, interoperability issues, and the need for transparent and explainable AI models for safety-critical automotive applications. Overcoming these challenges will require interdisciplinary collaboration among battery scientists, data scientists, automotive manufacturers, and control engineers. Future Intelligent Battery Management Systems are expected to incorporate autonomous learning, cloud-edge collaborative intelligence, federated learning, explainable artificial intelligence, and digital twin ecosystems to support next-generation lithium-ion and solid-state battery technologies. Overall, Intelligent Battery Management Systems will play a pivotal role in enhancing the safety, performance, sustainability, and commercial viability of future electric vehicles while contributing significantly to the global transition toward low-carbon and intelligent transportation systems.

1.      Ghalkhani, M., & Habibi, S. (2023). Review of the Li-ion battery, thermal management, and AI-based battery management system for EV application. Energies, 16(1), 185. https://doi.org/10.3390/en16010185 2.      Lipu, M. S. H., Miah, S., Jamal, T., Rahman, T., Ansari, S., Rahman, S., Ashique, R. H., Shihavuddin, A. S. M., & Shakib, M. N. (2023). Artificial intelligence approaches for advanced battery management systems in electric vehicle applications: A statistical analysis towards future research opportunities. Vehicles, 6(1), 22–70. https://doi.org/10.3390/vehicles6010002 3.      Niri, M. F., Aslansefat, K., Haghi, S., Hashemian, M., Daub, R., & Marco, J. (2023). A review of the applications of explainable machine learning for lithium-ion batteries: From production to state and performance estimation. Energies, 16(17), 6360. https://doi.org/10.3390/en16176360 4.      Tran, M. K., Panchal, S., Khang, T. D., Panchal, K., Fraser, R., & Fowler, M. (2022). Concept review of a cloud-based smart battery management system for lithium-ion batteries: Feasibility, logistics, and functionality. Batteries, 8(3), 19. https://doi.org/10.3390/batteries8030019 5.      García, E., Quiles, E., & Correcher, A. (2023). Distributed intelligent battery management system using a real-world cloud computing system. Sensors, 23(7), 3417. https://doi.org/10.3390/s23073417 6.      Ghazali, A. K., Aziz, N. A. A., Hassan, M. K., et al. (2025). Advanced algorithms in battery management systems for electric vehicles: A comprehensive review. Symmetry, 17(3), 321. https://doi.org/10.3390/sym17030321 7.      Kurkin, A., et al. (2025). Battery management system for electric vehicles. World Electric Vehicle Journal, 16(8), 451. https://doi.org/10.3390/wevj16080451 8.      Gómez Díaz, K. Y., et al. (2025). Thermal management systems for lithium-ion batteries used in electric vehicles: A review. World Electric Vehicle Journal, 16(7), 346. https://doi.org/10.3390/wevj16070346