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The correct assessment of battery states is essential to maximize battery pack performances while ensuring reliable and safe operation. This article introduces EIS2MOD, a novel modeling framework for li-ion cells based on distribution of relaxation time. A physically-based electric circuit model is developed starting from electrochemical impedance spectroscopy and open-circuit voltage measurements. Distribution of relaxation time (DRT) is applied to deconvolve the electrochemical phenomena from the EIS. The presented methodology is based on: DRT calculation from EIS; DRT analysis for ECM configuration; and model parameters extraction and fitting. The proposed framework is applied to large format li-ion pouch cells, which are tested over the whole state of charge (SoC) range and a wide temperature range (&#x2212;10 &#x00B0;C to 35 &#x00B0;C). Different current profiles have been tested to validate the model, showing its high accuracy in reproducing the battery cell behavior (e.g., RMSE on the battery terminals voltage lower than 1.50&#x0025; for driving cycle simulations at variable temperature and SoC). An additional advantage of EIS2MOD is its light computational load thus offering an attractive framework for battery management system implementation.

EIS2MOD: A DRT-Based Modeling Framework for Li-Ion Cells