Paolo Scaltrito
Development of a solid-state battery model to predict the macroscale behavior for automotive applications.
Rel. Ezio Spessa, Daniela Anna Misul, Alessandro Falai, Tiziano Alberto Giuliacci. Politecnico di Torino, Master of science program in Automotive Engineering, 2022
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Abstract
As the vehicle industry grows increasingly devoted to sustainable mobility, hybrid-electric propulsion systems with batteries with enhanced gravimetric energy density and cyclability qualities have drawn a lot of attention. In this setting, the widely established lithium-ion battery technology, despite providing decent performance, has partially attained a certain limit. The battery market is thus exploring new technologies capable of strengthening battery electric vehicle safety and overall life cycle assessment. Under such circumstances, the all-solid-state battery (ASSB) appears to be a valid answer. The current research, with the purpose of establishing the cycle capabilities of ASSB in practical applications, places emphasis on the development of a numerical ageing model based on the open-source coding language, Python.
The model, combining a detailed diffusion mechanism with two significantly simplified temperature-dependent fitting parameters, is targeted at forecasting the development of the solid electrolyte interface (SEI), which is largely assessed as the major cause of battery capacity fading
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