Module-Level Modelling Approach for a Cloudbased Digital Twin Platform for Li-Ion Batteries

Abstract

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.

A Digital Twin Framework for Simulating Distributed Energy Resources in Distribution Grids

“…DT technology, serving as a virtual representation of a physical lithium ion battery (LIB), can play a crucial role in battery production operations [25], engine-based power plants [26], and battery energy storage systems (BESSs) [27], showcasing its versatility and applicability in diverse industrial contexts. For instance, DT technology is used to optimize real-time disassembly strategies for end-of-life LIBs [28], production and value chain efficiency [29], and management systems [30]. DTs have also been employed to predict future battery behavior [31], the partial discharge voltage curve [32], the maximum available capacity of LIBs in EVs [33], the remaining useful cycle life [34], and the capacity decay and safety hazards in LIBs [35].…”