The advancements and research trends in state of health estimation for lithium-ion batteries over the last two decades: A bibliometric examination of prospective trends

The precise prediction of the state of health has attracted significant interest from academia and business because of its potential to heighten the use of lithium-ion storage, the most costly component in electric vehicles. This study utilizes bibliometrics and visual techniques to examine the advancements and patterns in state of health estimation studies. The data was gathered from the Web of Science Core Collection, OpenAlex, and the Dimension AI database, comprising a total of 2155 papers published between 2005 and 2024. The creation of a knowledge domain graph utilized co-citation analysis, co-word analysis, and cluster analysis, supported by software tools such as CiteSpace, VOSviewer, and R Studio. The study delineated and synthesized the progression of research focal points in the domain, employing clusters identified by CiteSpace from the gathered data, and categorizing them into five principal tiers. Deliver a comprehensive insight into the advancements and increasing potential of state of health estimate. They furthermore function as a beacon for forthcoming research endeavors. This scholarly endeavor is essential for enhancing and refining the assessment of the state of health, facilitating significant advancements in the dynamic domain of electric car research. • Keyword co-occurrence evaluated for content analysis and gap detection in literature. • Using cross-database bibliometrics an illustrative analysis for SoH is presented. • Identification of authors, countries, and journals, in Li-ion battery SoH assessment. • Clear analysis outlines prospects and areas for Li-ion battery SoH approximation.