Parameter sensitivity analysis of a physico-chemical lithium-ion battery model with combined discharge voltage and electrochemical impedance data

Physico-chemical battery models are capable of better simulation lithium-ion cell behaviour due to their more physically descriptive modelling approach using many physical parameters. Accuracy simulations highly depend on the correct identification However, large parameter estimation uncertainties and model complexities increase parameterization difficulties. Therefore, pre-analysis sensitivities outputs can greatly help determining best conditions techniques for identifying parameters with accuracy. This work demonstrates a next step in improving accuracy by combined sensitivity analysis both discharge voltage EIS data. A commercially available NMC-graphite based is modelled 26 analysed sensitivity. For voltage, capacity-related non-capacity-related clearly show different patterns at C-rates depth regions. Moreover, non-dimensional spectra states introduced impedance-based accurate observed matching frequency bands truly affected kinetics. The ranked demonstrate ability identify insensitive impedance measurements, which would number identifiable physico-chemical model.