The project aims at improving the aging modelling and monitoring of large lithium-ion batteries in the form of pouch cells, by
exploiting additional measurements besides the classical cell voltage, current and surface temperature.  Fiber Bragg grating (FBG)
sensors will be used to record local temperature and strains at the surface of the battery while the so-called battery cell
management unit (CMU) will provide electrochemical impedance spectroscopy (EIS), humidity and gassing measurements.  Battery aging
campaigns will be performed, in which the above measurements will be recorded, and regular performance test will provide capacity and
power fade estimates.  Next, the electrical, electrochemical, mechanical and thermal measurements will be combined in order to model
and predict capacity and power fade.  The most relevant measurements or grouping of measurements will be determined by
dimensionality reduction methods and appropriate black box models will be identified.  The merging of time and frequency domain data will be
performed in two ways. Either a single model will be fitted with both types of data, or estimates determined from each data type
will be merged, and the best option will be retained.  The outcome of the project will include 1) a data base of well documented
multi-physical measurements suitable for battery aging studies, 2) a selection of the most relevant measurements for capacity/power
fade monitoring and 3) a systematic approach for modelling and predicting these phenomena.