The reuse of lithium-ion batteries from electric vehicles is emerging as an essential component of sustainability efforts in the automotive industry. As electric cars become more prevalent, the potential for conserving resources through upcycling used batteries has grown significantly. However, the process has not yet become mainstream due to technical and economic challenges. The QuaLiProM research project aims to address these barriers and improve the viability of battery reuse.
Funded by Germany’s Federal Ministry of Education and Research (BMBF), the QuaLiProM project brings together experts from the Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM, the Friedrich-Alexander University Erlangen-Nuremberg, and Industrial Dynamics.
The interdisciplinary team is focusing on questions related to the efficient and safe reuse of batteries from electric vehicles, investigating the technical and economic hurdles involved. “The scientific goal of QuaLiProM is to determine the residual capacity and service life of used lithium-ion batteries in a non-destructive, fast, and safe manner,” the project states, emphasizing the importance of a reliable and economically viable second use for the batteries.
Lithium-ion batteries experience a gradual loss of storage capacity over time, which directly affects their performance. The state of health (SoH) of a battery—an indicator of its age-related degradation—is a crucial factor in assessing its performance and remaining lifespan. Traditionally, SoH has been evaluated through methods such as capacity tests, electrochemical impedance spectroscopy, and lifetime tests.
The QuaLiProM project, however, introduces quantum magnetometry, a technique already utilized in battery research. This method offers a faster, more precise means of determining the health status of battery cells. By analyzing the magnetization of the cells, quantum sensors can detect defects, impurities, and the battery’s state of charge.
The project also aims to combine quantum magnetometry with artificial intelligence (AI) to develop a high-speed measurement system for classifying cells based on their health. In this process, lithium-ion cells undergo forced degradation through cyclic aging tests. The cells, which are deliberately aged to defined states, are then analyzed using quantum magnetics. Quantum sensors measure the magnetic field of each cell with high precision by observing the spin of a specific defect in a diamond. These measurements generate magnetic field mappings, which provide valuable insights into potential anomalies within the cells.
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The non-destructive nature of this method eliminates the need for lengthy charging and discharging cycles, making it suitable for use not only in cell production but also in recycling and upcycling processes. One of the key goals of the project is to transition the methodology from laboratory-level testing to industrial-scale applications. The AI-based analysis of magnetic field mappings will use deep learning methods to identify features that correlate with the aging state of the cells, enabling the classification of cells as healthy, degraded, or defective.
This process will allow for the identification of degraded cells that, while no longer suitable for use in electric vehicles, can still be repurposed for secondary applications. By developing strategies for upcycling and exploring new second-life uses in less demanding fields, QuaLiProM aims to support sustainable battery usage and promote resource efficiency in the industry.
Source: ifam.fraunhofer.de
