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.