Electrochemical impedance spectroscopy (EIS), a conventional and alternating-current-(AC)-based technique for impedance measurement, is commonly used in battery diagnosis. However, it requires expensive equipment and demanding operating conditions and is complex and model-dependent in data analysis. Recently, novel direct current (DC) analytics have emerged as an alternative to EIS. They are simple yet powerful, being capable of revealing impedance information that traditionally could only be obtained through EIS and determining Li-ion diffusion coefficient. Besides, a complete EIS spectrum can be predicted based on constant current charging curves in the support of machine learning methods. This work highlights the similarities and discrepancies between DC techniques and EIS in the electrochemical analysis of Li-ion batteries. Looking ahead, DC techniques may be a promising substitute for EIS in future battery diagnosis, requiring simplified equipment while offering a deep understanding of battery impedance and its underlying electrochemical processes.
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