Automated optical detection of particles and defects on a Li-Ion-cell surface using a single-point analysis

Electric mobility is of crucial importance for a sustainable future of individual mobility. Challenges in energy storage with batteries have been identified as a major barrier of a broader electrification of cars. Expensive raw materials, a high scrap rate in production of cells and the lack of a not fully automated process chain lead to high costs of electric cars. Within this paper a new approach, named Single-Point-Analysis, is presented to setup inline quality assurance in the production of cell foils using optical measurement techniques. The filtering algorithm observes the inter-point distance of each single point in the range of interest. Furthermore a mean distance for each single measurement point is calculated by considering the distances to its direct neighbors. The main focus is the detection of particles and defects like scratches on the cell surface. It is demonstrated that the developed analysis is able to clearly identify these typical failures of cells.