Title: A Lifecycle-Oriented Digital Twin Framework for Next-Generation Lithium-Ion Battery Systems in Sustainable Electric Mobility Abstract: This paper presents a comprehensive review and forward-looking framework for integrating Digital Twin (DT) technology into the lifecycle management of advanced lithium-ion battery systems for electric vehicles. Focusing on the convergence of Industry 4.0 enablers—including multi-physics simulation, IoT-driven sensor networks, cloud-based big data analytics, and AI-augmented prognostics—the work examines DT applications in electrode microstructure optimization, real-time state estimation, safety monitoring, and predictive health management. By synthesizing current advances in battery prognostics and smart manufacturing, we propose a unified DT architecture that supports closed-loop, cradle-to-grave battery management—from additive manufacturing and in-line defect detection to grid-aware charging, echelon utilization, and end-of-life recycling. The study highlights how DT-enabled cyber-physical systems can accelerate the development of sustainable, safe, and high-performance energy storage solutions critical to the decarbonization of transportation and the resilience of future smart grids.