The advancements and research trends in state of charge estimation for lithium-ion batteries over the last two decades: A visualization analysis based on bibliometric data

The accurate forecasting of the state of charge has garnered substantial attention from both the scholastic world and industry due to its inherent ability to optimize the use of lithium-ion batteries, which are the most expensive component in an electric vehicle. This work employs bibliometrics and graphical approaches to examine the advancement and patterns of research on the state of charge estimation. The data was gathered from the core collection of Web of Science database and the Dimension database, which included a total of 3077 publications published between 2004 and 2023. The construction of a knowledge domain graph involved the use of co-citation analysis, co-word analysis, and cluster analysis, facilitated by software tools like CiteSpace and VOSviewer. This paper thoroughly examines the research on state of charge estimate and clearly outlines the progression of State of charge estimation methodologies into three distinct levels: The fundamental level, the development of application opportunities, and future directions including AI integration and real-time predictive models for next-gen technologies, which provides a deep understanding in the progress and expanding possibilities of state of charge estimation. These sources shed light on the depth of literature already reviewed, guiding the direction of future studies. This study is important because it enhances and refines the estimation for state of charge, enabling further progression in the fast-evolving research domain of electric vehicles. Provide a deep understanding of the progress and expanding possibilities of state of charge estimation. • Bibliometric study about the State of Charge estimation of Lithium-ion batteries. • The co-occurrence of keywords was studied for content and gap analyses. • Bibliometric data-based illustrative analysis was used to identify significant contributions. • Identified significant authors in the research area of State of Charge estimation. • Identify significant counties and journals contributing to this research area. • Analysis is provided about the prospects and areas of study for State of Charge estimation.