Revolutionizing batteries based on digital twin through AI-simulation synergy for design, manufacturing, operation, and recycling

Optimizing lithium-ion batteries (LIBs) is pivotal for advancing sustainable energy solutions, particularly for portable electronics, electric vehicles and renewable energy storage systems. This review explores state-of-the-art strategies that integrate advanced digital simulations with comprehensive lifecycle management, assisted by artificial intelligence (AI), to overcome critical challenges in battery performance, safety, and durability. Our approach combines computational materials science with multi-scale modeling, bridging atomic-scale phenomena to system-level dynamics. This synergy provides new insights into materials behavior and electrochemical processes. Physics-based simulation techniques and AI-driven optimization technologies underpin these methods, enabling them to achieve accurate predictions and drive the design of next-generation batteries. Furthermore, the integration of cloud-based battery management systems (BMS) with edge computing facilitates real-time monitoring, predictive diagnostics, and proactive control, while the adoption of the “Battery Passport” concept enhances lifecycle traceability, promoting recycling and reuse. Collectively, these strategies establish a robust framework centered on standardization, modularization, and digitization, driving innovation across design, manufacturing, maintenance and recycling processes. This industry-academia-research collaborative battery large model has not only accelerated the industrialization of next-generation battery technologies but also provided strong support for the sustainable development of the sector. This review underscores the transformative potential of these integrated approaches, laying the groundwork for future breakthroughs in energy technologies and advancing global sustainability goals.