Pouch Battery Pack Assembly Line

Pouch Battery Pack Assembly Line Process flow

The soft-pack battery assembly line comprises six core processes, achieving full-process closed-loop control through technologies such as machine vision and digital twins.

Cell Preprocessing and Sorting

• Cell Screening: High-precision testing equipment (e.g., HIOKI charge-discharge testers) is used to grade and match cells based on capacity, internal resistance, and voltage, ensuring an intra-group variation of ≤0.5%.
• Tab Processing: Laser cutting machines trim tabs to a precision of ±0.05mm, with plasma cleaning to remove surface oxides, enhancing subsequent welding quality.

Stacking and Module Assembly

• Z-Fold Stacking Technology: Robotic arms stack cells according to preset programs, employing a separator-cell alternating lamination process, increasing energy density by 5-8% compared to wound structures.
• Flexible Fixture Design: Supports dynamic adjustment of cell dimensions (e.g., length 150-300mm, thickness 3-8mm), reducing changeover time to 20 minutes (e.g., Tesscorn solution).

High-Precision Welding Process

• Hybrid Welding Technology: Combines laser welding (tab connection) and ultrasonic welding (busbar integration), controlling the heat-affected zone (HAZ) to within 0.3mm, with a yield rate of 99.7%.
• Real-Time Monitoring System: Infrared thermal imaging detects temperature fluctuations at weld points, automatically compensating energy parameters to avoid cold/overwelding.

Thermal Management and Encapsulation Integration

• Cooling Plate Assembly: A vision positioning system guides the alignment of cooling plates with cells, ensuring a gap of ≤0.1mm and a thermal paste coating thickness precision of ±0.02mm.
• Aluminum-Laminate Film Sealing: Dual-station alternating sealing (top + side), with helium leak detectors ensuring sealing integrity, achieving a leakage rate of ≤1×10⁻⁶ Pa·m³/s.

Final Inspection and Intelligent Control

• EOL Testing: Simulates real-world conditions with 0.5C-3C charge-discharge cycles, using AI algorithms to analyze voltage decay curves and predict battery life (error ±2%).
• Data Traceability: The MES system binds individual cell IDs, enabling real-time retrieval of full lifecycle data (e.g., production batches, test results).