Singh, SoumyaWeeber, MaxBirke, Kai Peter2023-08-102023-08-1020212313-01051858246601http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-134265http://elib.uni-stuttgart.de/handle/11682/13426http://dx.doi.org/10.18419/opus-13407The concept of Digital Twin (DT) is widely explored in literature for different application fields because it promises to reduce design time, enable design and operation optimization, improve after-sales services and reduce overall expenses. While the perceived benefits strongly encourage the use of DT, in the battery industry a consistent implementation approach and quantitative assessment of adapting a battery DT is missing. This paper is a part of an ongoing study that investigates the DT functionalities and quantifies the DT-attributes across the life cycles phases of a battery system. The critical question is whether battery DT is a practical and realistic solution to meeting the growing challenges of the battery industry, such as degradation evaluation, usage optimization, manufacturing inconsistencies or second-life application possibility. Within the scope of this paper, a consistent approach of DT implementation for battery cells is presented, and the main functions of the approach are tested on a Doyle-Fuller-Newman model. In essence, a battery DT can offer improved representation, performance estimation, and behavioral predictions based on real-world data along with the integration of battery life cycle attributes. Hence, this paper identifies the efforts for implementing a battery DT and provides the quantification attribute for future academic or industrial research.eninfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/621.3article2021-12-01