Equivalent Circuit Models for Lithium-Ion Batteries: A Comprehensive Review

Equivalent circuit models (ECMs), owing to their simple structure, high computational efficiency, and ease of embedded implementation, have become the most practically applicable modeling approach in lithium-ion battery management systems (BMSs). This paper provides a systematic review of the research progress in lithium-ion battery ECMs along the main line of model construction, parameter identification, and state estimation. First, the topological characteristics, mathematical representations, and application scenarios of the Rint, Thevenin, partnership for a new generation of vehicles (PNGV), dual-polarization, high-order RC, Randles, and fractional-order models are summarized and compared, thereby revealing the inherent trade-off among model accuracy, complexity, and real-time performance. Second, open-circuit voltage–state of charge (OCV–SOC) calibration, offline/online parameter identification, and ECM-based state of charge (SOC) estimation methods are reviewed, with particular emphasis on the advantages and limitations of least squares, recursive least squares, Kalman filtering, particle filtering, sliding-mode observers, and model–data fusion methods. Furthermore, based on model validation and comparative performance results, it is shown that simple models possess high real-time capability but limited dynamic characterization ability; the first-order RC model achieves a more favorable balance between accuracy and complexity; and although high-order models can improve dynamic fitting and state estimation accuracy, they also increase parameter dimensionality and implementation cost. Finally, the key issues faced in this field are distilled, including insufficient adaptability under full operating conditions and across the full lifecycle, inadequate multi-physics coupled modeling, limited integration depth between physical constraints and data-driven methods, and the lack of a unified standardized validation framework. Future research is expected to further advance toward adaptive variable-structure modeling, multi-physics coupling, intelligent hybrid modeling, and unified benchmark testing. This review can provide a systematic reference for ECM design, parameterization method selection, and the development of BMS state estimation strategies for lithium-ion batteries.