  The correct assessment of battery states is essential to maximize battery
pack performances while ensuring reliable and safe operation. This work
introduces EIS2MOD, a novel modelling framework for Li-ion cells based on
Distribution of Relaxation Time (DRT). A physically based Electric Circuit
Model (ECM) is developed starting from Electrochemical Impedance Spectroscopy
(EIS) and Open Circuit Voltage (OCV) measurements. DRT is applied to deconvolve
the electrochemical phenomena from the EIS. The presented methodology is based
on: i) DRT calculation from EIS, ii) DRT analysis for ECM configuration and
iii) 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 (-10{\deg}C to 35{\deg}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% 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.
