Multi-Energy X-Ray Sorting for Early Li-Ion Battery Detection
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Solution Overview
Problem
Lithium-ion batteries (LIBs) pose a significant fire hazard in recycling plants due to mechanical damage during processing, and existing detection methods, such as thermographic cameras and manual sorting, are inadequate for early identification in complex material flows.
Innovation Solution
A sorting device employing multi-energy X-ray technology and AI algorithms to detect lithium-ion batteries by analyzing density, atomic number, and structural information in real-time, allowing for early recognition and separation of LIBs in recycling processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If thermographic cameras are used to detect temperature rises, then fire detection capability is provided, but detection rate for high material thicknesses is problematic and system cost is high (up to 5 million euros)
Solution Approach 1:
The patent replaces thermographic cameras (optical/thermal detection) with an X-ray detection system. The X-ray system penetrates material flows and detects lithium-ion batteries through radiography, providing reliable detection regardless of material thickness. This substitution resolves the contradiction by enabling accurate detection through dense materials that block thermal infrared radiation.
Solution Approach 2:
The patent changes the detection parameter from temperature (thermal energy) to X-ray attenuation (radiation absorption). By measuring the attenuation of X-rays through different materials, the system can identify lithium-ion batteries based on their unique radiological properties, achieving reliable detection through thick material layers where thermal detection fails.
2Reliability
If manual sorting is used at the end of conveyor belts, then some LIBs can be removed, but it is much too late to react to ignited or igniting LIBs and labor intensive
Solution Approach 1:
The patent implements preliminary detection and identification of lithium-ion batteries at the beginning of the material flow processing, before any mechanical damage or ignition can occur. The X-ray system detects LIBs in advance, allowing the system to react immediately when batteries are identified, rather than waiting for manual sorting at the end of the conveyor belt where ignition may have already occurred.
3Measurement precision
If multi-energy X-ray system is used to detect LIBs in material flows, then detection accuracy is improved, but system complexity and cost increase
Solution Approach 1:
The patent employs a multi-energy X-ray system that performs multiple functions: it detects the presence of lithium-ion batteries, determines their position in the material flow, and provides information about their size and shape. This multi-functionality achieves high detection accuracy while managing system complexity by consolidating multiple detection tasks into a single integrated system rather than requiring separate specialized systems for each function.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system significantly reduces fire hazards by accurately identifying LIBs at the beginning of the recycling process, avoiding costly fire detection and extinguishing systems, and ensuring high detection quality with lower operational costs.
Implementation Method 1
a single or multi-energy X-ray system configured to radiograph the material flow by using at least one energy or at least two different energies and to detect radiographs based on the radiography
Data Source
AI summary
Sorting device (10), comprising: conveying means (12) for conveying a material flow (14) through the sorting device (10); a multi-energy X-ray system (20) configured to radiograph the material flow (14) by using at least two different energies and to detect radiographs based on the radiography, wherein each radiograph includes, per area, first information regarding a density and/or an atomic number as well as second structural information; a processor (28) configured to detect one or several areas comprising a component to be recycled (16) or a battery, in particular a lithium-ion battery, or a battery cell, in particular a lithium-ion battery cell, in a respective one of the radiographs using an AI algorithm; wherein detecting takes place based on a first feature (M1) derived from first information and a second feature (M2) derived from the second structural information.