How does an automatic EOL tester comprehensively determine whether a lithium battery pack has reached the end-of-life standard using multi-dimensional parameters?

Publish Time: 2025-11-27

In the fields of new energy vehicles, energy storage systems, and consumer electronics, the safety and reliability of lithium battery packs directly affect the performance lifespan of end products and user safety. When a battery pack enters the end of its life cycle or has experienced abnormal use, its health status cannot be accurately determined solely by appearance or a single voltage measurement. Therefore, the automatic EOL tester has emerged—as an integrated solution for the final stage of functional testing of lithium battery packs. It constructs a scientific, efficient, and quantifiable end-of-life determination system by simultaneously collecting multi-dimensional key parameters such as total voltage, internal resistance, protection functions, temperature sensing, and communication protocols, truly achieving "no one who should be scrapped will be missed, and those that can be reused will be accurately screened."

1. Multi-point synchronous electrical performance testing: Building a comprehensive health profile

Traditional manual testing often involves testing each item individually, which is inefficient and prone to missing related faults. The automatic battery decommissioning detector supports multi-channel parallel data acquisition, simultaneously measuring multiple core indicators within seconds:

Total voltage reflects the overall state of charge of the battery pack. If it is significantly lower than the nominal value and cannot be recovered, irreversible capacity decay may have occurred.

AC internal resistance (ACIR) is a key indicator for assessing the degree of aging. An abnormally high internal resistance usually indicates electrolyte drying, SEI film thickening, or tab corrosion.

Overcurrent/overvoltage protection trigger thresholds verify whether the BMS (Battery Management System) can still effectively cut off dangerous operating conditions.

Short-circuit protection response time tests whether the protection circuit can act within milliseconds to prevent thermal runaway under simulated extreme short circuits.

The accuracy of the NTC temperature sensor and the consistency of the ID resistor ensure normal battery pack identification and temperature control logic.

These parameters corroborate each other, forming a comprehensive "electrical-control-thermal" health profile of the battery pack, avoiding misjudgments based on a single indicator.

2. Intelligent Algorithm Integration for Judgment: From "Experience-Based Judgment" to "Data-Driven Decision-Making"

The built-in judgment engine of the detector does not simply set thresholds, but rather establishes a multi-parameter weighted scoring model based on the analysis of a large amount of historical failure data. For example, a battery pack with slightly high internal resistance but intact protection functions and stable voltage may only need to be downgraded for low-power scenarios; while a battery pack with normal voltage but short-circuit protection failure, even if its capacity is sufficient, must be forcibly scrapped—due to its significant safety hazards. The system can flexibly configure scrapping rule bases for different application scenarios to achieve differentiated and refined intelligent decision-making.

3. High-Speed Fully Automated Process: Ensuring Consistency and Efficiency in Judgment

Relying on intelligent fixture automatic switching and robotic loading and unloading integration, the detector can continuously process hundreds of battery packs without human intervention, shortening the testing cycle by more than 50%. The entire process is controlled by the program, including charging and discharging conditions, protection trigger simulation, and data acquisition, completely eliminating human wiring errors or subjective judgment biases. Simultaneously, the system supports seamless integration with the production line MES, achieving "testing and filing simultaneously," significantly improving the reliability and capacity adaptability of batch scrapping screening.

4. Full Lifecycle Data Traceability: Providing Basis for Quality Closed-Loop Management

The test results for each battery group are bound to its unique ID and automatically uploaded to a cloud database, containing a complete data package including original waveforms, protection action timestamps, and internal resistance change curves. This not only meets the traceability requirements of the ISO quality system but also provides objective evidence in case of after-sales disputes. More importantly, the long-term accumulated end-of-life data can feed back into R&D—analyzing high-frequency failure modes, optimizing battery design and BMS strategies, forming a quality closed loop of "detection—feedback—improvement."

The multi-dimensional comprehensive judgment capability of the automatic EOL tester marks a shift from extensive to precise battery retirement management. It no longer relies on vague experience of "whether it can still be used" but uses data as a yardstick and safety as a boundary, achieving a balance between efficiency and rigor. With the large-scale retirement of power batteries approaching, this type of intelligent testing equipment is not only a "gatekeeper" for enterprises to control risks but also a key infrastructure for promoting the cascade utilization and green recycling of batteries—ensuring that the final destination of every battery is clear, safe, and valuable.