A Comprehensive Review of Artificial Intelligence-Driven Battery Management and Emerging Battery Technologies for Electric Vehicles
Abstract
The rapid adoption of electric vehicles (EVs) has intensified the demand for advanced battery technologies capable of delivering higher energy density, improved safety, faster charging, and longer operational life. This review provides a comprehensive assessment of the evolution of EV battery technologies, covering conventional batteries, lithium-ion batteries, and emerging next-generation chemistries, including solid-state, lithium–sulfur, sodium-ion, and lithium–air batteries. Key battery performance characteristics, such as energy density, power density, efficiency, cycle life, charging and discharging behavior, and degradation mechanisms, are critically discussed to highlight their influence on battery performance and lifespan. The review further examines the application of artificial intelligence (AI) in battery management systems, emphasizing machine learning, deep learning, reinforcement learning, and hybrid AI techniques for improving battery state estimation, fault diagnosis, predictive maintenance, thermal management, and charging optimization. The roles of State of Charge (SOC), State of Health (SOH), and Remaining Useful Life (RUL) estimation in enhancing battery reliability and operational safety are also reviewed. In addition, current research gaps related to battery degradation, fast charging, thermal management, recycling, and explainable AI are found, together with future research trends involving digital twins, smart charging, Vehicle-to-Grid (V2G) integration, and sustainable battery technologies. The review concludes that the integration of next-generation battery chemistries with AI-driven battery management systems offers significant potential to improve battery efficiency, extend service life, enhance safety, and accelerate the widespread adoption of electric vehicles while supporting the global transition toward sustainable and intelligent transportation systems.