Lithium ion battery cell production quality control based on AI machine learning

Penetration of Li-ion battery technologies has been restrained by the high production cost and safety concern. Effective and efficient production of high-quality battery cells is crucial not only to enable the wide-adoption of the battery technologies, but also to ensure the longevity of the battery cells and protect the safety of the users. To enable high-quality battery cell production and facilitate efficient screening process, it is crucial to assess the battery cell’s quality at the end of the production. Direct current internal resistance (DCIR) is one of the most important metrics for assessing whether the battery cell is within the desirable quality or not due to the strong correlation between the battery cell DCIR and its states, i.e., state of health, power performance, etc. Here, we have proposed a battery cell quality control method based on DCIR through AI machine learning. We have used the proposed method to quickly and reliably assess more than 10,000 production battery line cells whether they satisfied the high-quality requirement or not. It is expected this proposed method based on AI machine learning can efficiently screen high-quality battery cells and thus greatly decrease the battery cell manufacturing cost, and further enhance the penetration of Li-ion battery technologies.