The pursue of the new increasingly intelligent, and heavier state estimation algorithms requires a significant amount of data and computing power, which may challenge their deployment in current BMS solutions. To address that issue, this paper proposes a cloud-based Digital Twin Platform to extend computing power and data storage capacity. This tool aims to contain the integration of models to analyse thermoelectric and ageing aspects of a LIB, based on experimental operation data by comparative analysis. Based on well-known cell-level modelling techniques, a module-level modelling approach is proposed and an experimental validation platform is suggested.
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