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Development and Utilization of a Framework for Data-Driven Life Cycle Management of Battery Cells

 
: Singh, Soumya; Weeber, Max; Birke, Kai Peter; Sauer, Alexander

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Fulltext ()

Procedia manufacturing 43 (2020), pp.431-438
ISSN: 2351-9789
Global Conference on Sustainable Manufacturing (GCSM) <17, 2019, Shanghai>
English
Journal Article, Conference Paper, Electronic Publication
Fraunhofer IPA ()
Batterie; Datenanalyse; datengetriebene Produktionsoptimierung; Produktlebenszyklus

Abstract
Advanced battery cells and modules are increasingly used in a variety of applications. Tracking the state of a cell along the product life cycle and in the consecutive life cycles poses a big challenge to the current battery manufacturing industry and OEMs. This is due to diverse types of influencing factors coming from raw materials, manufacturing, usage, product integration and end of life. The goal of this paper is to develop a framework that provides the capacity to survey and assess relevant data at different stages of a battery life cycle. Here we show a data driven framework for data acquisition of relevant product life cycle information. The acquired data is then handled within a data architecture for application of effective data analytics concepts. In our results, we demonstrate how the framework can be implemented for end of life of battery management. The framework focuses on making the information from each life cycle stage available to decision makers for application of possible data analytics concepts. Such organized processing of battery life cycle data can assist in the development of new business models and improvement of existing battery technologies and services.

: http://publica.fraunhofer.de/documents/N-593048.html