Intelligent sampling of battery cells for in-depth quality evaluation and analysis
Patent Information
- Application Number
- EP2023833272
- Authority / Receiving Office
- EP · EP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-11-22
- Filing Date
- 2023-11-23
- Publication Date
- 2025-10-01
AI Technical Summary
Current methods for detecting defects in battery cells are inefficient, as they often require costly and time-consuming processes like X-ray scans and teardowns, and are unable to detect operational defects such as lithium plating and electrolyte degradation, leading to potential catastrophic failures.
A two-stage acoustic signal-based system is deployed on battery cell manufacturing lines, using a first scanner for rapid anomaly detection and a second scanner for high-resolution confirmation, allowing for intelligent selection of defective cells for in-depth analysis, reducing waste and resource allocation.
This approach effectively identifies defective cells with high confidence, minimizing unnecessary in-depth analysis of defect-free cells and preventing defective cells from entering the market, thereby enhancing manufacturing efficiency and quality control.
Smart Images

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