Researchers from the University of Vaasa in Finland have proposed a novel approach to enhance the sustainability of electric vehicle (EV) batteries by utilizing digital twin technology. This method aims to optimize the disassembly processes of EV batteries, facilitating their remanufacturing or recycling, which are critical for a circular economy. The study was published in the journal “Resources, Conservation & Recycling.”
The researchers highlight that manufacturers often do not adequately support the end-of-life processes of products, such as EV batteries, by not sharing relevant data. This lack of information can hinder efficient disassembly, remanufacturing, or recycling, ultimately impacting sustainability efforts. To address this challenge, the team proposes the use of digital twin technology, which creates a virtual replica of a physical product to simulate and optimize various processes.
The proposed approach leverages the concept of product-process-resource asset networks (PAN), which models the relationships between products, production resources, manufacturing processes, and specific production operations. The researchers introduce a Bi-Flow Product-Process-Resource Asset Network (Bi-PAN) representation, extending the PAN paradigm to cover both the manufacturing and the remanufacturing/recycling phases. This comprehensive model enables the digital twin to provide valuable insights and optimize disassembly processes for various types of EV batteries.
By utilizing product digital twins, the researchers demonstrate that the challenges associated with the disassembly of EV batteries can be solved more flexibly and efficiently. This optimization can lead to reduced ecological impact and enhanced sustainability in the energy sector, particularly in the management of EV batteries. The practical applications of this research include improved decision-making for manufacturers and recyclers, better resource utilization, and more effective circular economy strategies.
In summary, the study presents a promising approach to optimize the end-of-life processes of EV batteries using digital twin technology and Bi-PAN representation. This method can significantly contribute to the sustainability and environmental conservation efforts within the energy industry.
This article is based on research available at arXiv.