The production of lithium-ion battery cells (LIBs) for electric vehicles requires a considerable amount of energy and raw materials. Due to the increasing added value along the production chain, it is essential to recognise deviations in the intermediate products as early as possible using 100% inline measurement processes. For this reason, LIBs are inspected during cell assembly using plain radiography to qualitatively check their internal geometry. For safety-critical features, such as the anode-cathode-overhang (AC-overhang) in the composite, measuring methods are required that are not fulfilled by plain radiography. The use of computer tomography (CT) offers a solution for this demand. However, to realise a 100% CT inspection, the scan time of conventional systems and the number of applications along the cell assembly must be reduced. This research presents an approach to overcome this limitation in the form of a cross-process X-ray inspection strategy based on a technical and economic analysis of the cell assembly. To reduce scan time and the number of X-ray applications, multiple internal features are measured in a single CT scan prior to electrolyte filling. An initial feasibility assessment of this inspection position is being investigated using a state-of-the-art metal-jet tube and photon counting detector. This provides an inspection time of 1 s, enabling detailed inspection to be combined in a time-efficient process. However, moving the CT inspection downstream would contradict the key objective of early defect detection. To overcome these challenges, an upstream vision system was developed. This vision system detects outliers immediately after the stacking process by detecting the position of the external feature separator in the electrode separator composite (ESC) without X-rays and at a much lower cost than CT. This approach aligns with the primary objective of early defect detection in the production chain through the cross-process inspection strategy.

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Cross-Process X-ray Inspection Strategy in Battery Cell Assembly

  • Steffen Masuch,
  • Sophie Gräfnitz,
  • Klaus Dröder

摘要

The production of lithium-ion battery cells (LIBs) for electric vehicles requires a considerable amount of energy and raw materials. Due to the increasing added value along the production chain, it is essential to recognise deviations in the intermediate products as early as possible using 100% inline measurement processes. For this reason, LIBs are inspected during cell assembly using plain radiography to qualitatively check their internal geometry. For safety-critical features, such as the anode-cathode-overhang (AC-overhang) in the composite, measuring methods are required that are not fulfilled by plain radiography. The use of computer tomography (CT) offers a solution for this demand. However, to realise a 100% CT inspection, the scan time of conventional systems and the number of applications along the cell assembly must be reduced. This research presents an approach to overcome this limitation in the form of a cross-process X-ray inspection strategy based on a technical and economic analysis of the cell assembly. To reduce scan time and the number of X-ray applications, multiple internal features are measured in a single CT scan prior to electrolyte filling. An initial feasibility assessment of this inspection position is being investigated using a state-of-the-art metal-jet tube and photon counting detector. This provides an inspection time of 1 s, enabling detailed inspection to be combined in a time-efficient process. However, moving the CT inspection downstream would contradict the key objective of early defect detection. To overcome these challenges, an upstream vision system was developed. This vision system detects outliers immediately after the stacking process by detecting the position of the external feature separator in the electrode separator composite (ESC) without X-rays and at a much lower cost than CT. This approach aligns with the primary objective of early defect detection in the production chain through the cross-process inspection strategy.