Designing Data Ecosystems for Circular Supply Chains: Implementing Data Spaces for EV Battery Lifecycle

Bachelor or Master thesis

Background

Industries relying on linear economic models deplete natural resources and generate significant waste, contributing to pressing environmental challenges. The Circular Economy (CE) provides a sustainable alternative by promoting practices like repair, remanufacturing, and recycling. However, achieving these circular principles across supply chains requires effective collaboration and robust data ecosystems.
Transitioning to a CE model faces both economic and technical challenges, particularly the lack of transparent and secure data sharing among diverse stakeholders. Data spaces offer a promising solution by enabling controlled, interoperable environments where information can be shared securely, while respecting data sovereignty and privacy. For CE applications like the disassembly and remanufacturing of electric vehicle batteries, these data spaces are essential to facilitate decision-making and optimize resource recovery across complex supply chains.
Within the ZirkulEA project, we focus on building robust data ecosystems to support CE practices. This thesis will contribute to ZirkulEA by designing and implementing a data space within the Asset Administration Shell (AAS) framework. The data space will be tailored to support specific use cases in EV battery disassembly and remanufacturing, enabling seamless data and information sharing among stakeholders. This environment will help stakeholders track components, improve decision-making, and ensure that materials are reused effectively—ultimately reducing environmental impact and fostering sustainable development.

Research Goal

The objective of this thesis is to implement a use case as part of the publicly funded research project ZirkulEA project, specifically focusing on EV battery disassembly and remanufacturing, within a Data Space. The goal is to create a prototype that mimics the data and information sharing needed for decision-making among various stakeholders in a controlled, practical environment, utilizing digital twins for lifecycle management.

Your main tasks will include:
  • Identifying and defining the data sharing requirements and integration steps needed for implementing the EV battery disassembly and remanufacturing use case within a data space.
  • Developing a prototype to simulate the data flow and sharing mechanisms required for decision-making in these processes. This includes configuring the data space to support secure, role-based access and lifecycle management of EV battery components.
  • Building and testing the prototype within the data space to demonstrate how stakeholders can access and share data for informed decision-making during disassembly and remanufacturing.
This thesis offers the opportunity to contribute directly to the development of sustainable data practices in the automotive industry, supporting circular economy objectives.

Your Profile

  • You are passionate about data sharing, data ecosystems, and circular economy applications.
  • You are motivated to tackle real-world challenges in a self-organized and goal-oriented manner.
  • You bring analytical and technical skills to implement a data-sharing solution within a data space environment.
  • You have some programming skills or are eager to learn them.
  • You have very good English skills, as the thesis will be written in English.

Details

  • Start: Immediately
  •  Language: English

We offer you a challenging research topic, close supervision, and the opportunity to develop practical as well as theoretical skills. If you are interested, please send a current transcript of records, a short CV, and a brief motivation (2-3 sentences) to Ann-Sophie Finner. (ann-sophie.finner∂kit.edu).

 

Prüfer:
Prof. Dr. Orestis Terzidis, Institutsleiter des EnTechnon, Email: orestis terzidis∂kit edu