A comprehensive review of the lithium-ion battery state of health prognosis methods combining aging mechanism analysis

In the field of new energy vehicles, lithium-ion batteries have become an inescapable energy storage device. However, they still face significant challenges in practical use due to their complex reaction processes. Among them, aging-induced performance loss and even thermal runaway can cause serious hazards, so accurate state of health (SOH) estimation and timely maintenance are crucial. Since the aging of battery performance is affected by various factors and can be quantified in SOH assessment, this paper presents a comprehensive review of current SOH prediction techniques by systematically introducing the aging mechanism of batteries, focusing on data-driven methods, evaluating the implementation details, advantages and disadvantages of these methods in terms of model types and data set types, and giving a brief comment. Finally, we summarize the current state of development and provide an outlook on the future trends of SOH estimation methods by combining the advantages of cross-disciplinary approaches.