Periodic Reporting for period 1 - AUTOMATED BATTERY UPCYCLING (Automated Lithium-Ion battery upcycling process using robotics and computer vision to deliver sustainable energy storage at scale)
Reporting period: 2023-03-01 to 2023-11-30
The European Union (EU) aims to achieve zero emissions by 2050. However, the transition to renewable energy sources is causing issues with battery storage availability. The required storage capacity is expected to increase from 0.7 TWh in 2019 to 10.5 TWh by 2030, which could account for up to 248% of the global lithium reserves. Recycling and reusing batteries is crucial, but current practices result in over 80% of still-usable battery storage being wasted. Moreover, it is worth noting that 88% of battery recycling is outsourced to Asia.
However, Circu Li-ion has developed a sustainable approach to battery upcycling and recycling. The company facilitates the automated processing of used battery packs and provides dependable analytics on each battery cell. Circu Li-ion refurbishes cells for re-use and prepares end-of-life cells for recycling. The technology can recover more than 80% of cells that would otherwise be recycled, double the battery lifetime, reduce production emissions by 80%, and increase recycling efficiency.
The project aims to enhance our ability to analyze, diagnose, and repurpose cells through an in-house pilot program. This requires further development of computer vision algorithms, quality control measures, predictive maintenance systems, and monitoring systems. Furthermore, it is necessary to develop hardware for safety systems, battery categorization, and sorting systems.
However, Circu Li-ion has developed a sustainable approach to battery upcycling and recycling. The company facilitates the automated processing of used battery packs and provides dependable analytics on each battery cell. Circu Li-ion refurbishes cells for re-use and prepares end-of-life cells for recycling. The technology can recover more than 80% of cells that would otherwise be recycled, double the battery lifetime, reduce production emissions by 80%, and increase recycling efficiency.
The project aims to enhance our ability to analyze, diagnose, and repurpose cells through an in-house pilot program. This requires further development of computer vision algorithms, quality control measures, predictive maintenance systems, and monitoring systems. Furthermore, it is necessary to develop hardware for safety systems, battery categorization, and sorting systems.
The project aims to a significant advancement in lithium-ion battery recycling technologies.
WP1 focused on the analytical and diagnostic aspects of the project, developing sophisticated methods for assessing the quality and potential for reuse of used lithium-ion cells. The main achievements in WP1 include the implementation of advanced computer vision and AI for battery cell analysis, improved surface quality control, and the development of predictive maintenance techniques for better battery lifecycle management. Furthermore, WP1 has produced innovative software solutions for real-time analytics and diagnostics within the upcycling plant.
WP4 focused on developing and enhancing the project's core technologies, with a specific emphasis on automating and optimizing lithium-ion battery upcycling processes. WP4 achieved significant progress in automating and using computer vision for battery sorting and diagnostics, improving processing methods to increase recovery rates of valuable battery materials, and reducing waste and carbon footprint through optimized recycling processes.
The goal of WP4 and WP1 is to increase sustainability by improving recycling efficiency, which will reduce the environmental impact of battery disposal. Additionally, the improved recycling processes are expected to lower costs and create new economic opportunities within the battery recycling sector. The project's advancements in AI and automation are expected to set new standards in battery recycling technology.
To maintain the project's momentum and maximize its impact, ongoing research, better market access, and regulatory support are essential. This includes continued innovation in technologies and processes, strategies for integrating the project's outcomes into the existing recycling and manufacturing industries, and the development of supportive regulatory frameworks to promote the widespread adoption of these technologies.
WP1 focused on the analytical and diagnostic aspects of the project, developing sophisticated methods for assessing the quality and potential for reuse of used lithium-ion cells. The main achievements in WP1 include the implementation of advanced computer vision and AI for battery cell analysis, improved surface quality control, and the development of predictive maintenance techniques for better battery lifecycle management. Furthermore, WP1 has produced innovative software solutions for real-time analytics and diagnostics within the upcycling plant.
WP4 focused on developing and enhancing the project's core technologies, with a specific emphasis on automating and optimizing lithium-ion battery upcycling processes. WP4 achieved significant progress in automating and using computer vision for battery sorting and diagnostics, improving processing methods to increase recovery rates of valuable battery materials, and reducing waste and carbon footprint through optimized recycling processes.
The goal of WP4 and WP1 is to increase sustainability by improving recycling efficiency, which will reduce the environmental impact of battery disposal. Additionally, the improved recycling processes are expected to lower costs and create new economic opportunities within the battery recycling sector. The project's advancements in AI and automation are expected to set new standards in battery recycling technology.
To maintain the project's momentum and maximize its impact, ongoing research, better market access, and regulatory support are essential. This includes continued innovation in technologies and processes, strategies for integrating the project's outcomes into the existing recycling and manufacturing industries, and the development of supportive regulatory frameworks to promote the widespread adoption of these technologies.
The Battery Disassembly Line (BDL) has the ability to automatically disassemble battery packs of various assemblies and brands. The focus of the results was on reducing processing time and increasing throughput for known battery packs, while also defining the value of extracted cells. The BDL has been split into four separate machines to enhance modularity. Each machine is intended to be CE Marked for overall system integration. This will provide us with the flexibility to address throughput constraints as they mature.
Additional research is required to comprehend the diversity of battery packs available in the market. Currently, we have processed 80 different battery packs, which ensures that the BDL is capable of handling a wide range of scenarios. Moreover, the integration of vision system algorithms is critical. Ongoing research and development efforts aim to refine these algorithms for evaluation as a feedback loop in the robot's real-time process.
The potential impacts include improved market reach and a new customer base due to the BDL's enhanced modularity and adaptability. Compliance with CE Marking and the modular design make integration into existing systems easier, which is attractive for many industries seeking solutions, such as OEMs, recyclers, and aftersales.
The project demonstrates promising results in the disassembly of batteries for various assemblies and the assessment of cell state of health (SOH). Further research and development efforts are necessary to address the constantly evolving landscape of battery technologies and designs.
Additional research is required to comprehend the diversity of battery packs available in the market. Currently, we have processed 80 different battery packs, which ensures that the BDL is capable of handling a wide range of scenarios. Moreover, the integration of vision system algorithms is critical. Ongoing research and development efforts aim to refine these algorithms for evaluation as a feedback loop in the robot's real-time process.
The potential impacts include improved market reach and a new customer base due to the BDL's enhanced modularity and adaptability. Compliance with CE Marking and the modular design make integration into existing systems easier, which is attractive for many industries seeking solutions, such as OEMs, recyclers, and aftersales.
The project demonstrates promising results in the disassembly of batteries for various assemblies and the assessment of cell state of health (SOH). Further research and development efforts are necessary to address the constantly evolving landscape of battery technologies and designs.