Inline evaluation of Li-ion battery electrode porosity using machine learning algorithms - BattPor

Project summary

The background to the BattPor project is the increasing demand for high-performance battery technologies with integrated quality assurance at all stages of production. The focus here is on the calendering process used in the production of Li-ion battery electrodes. In this process step, a certain porosity is set by recompacting the coated and dried electrodes. It is essential to monitor this porosity inline to specifically increase the performance of the battery products. The main objective of the BattPor project is to develop automated optical testing technology with AI-based porosity detection in a continuous roll-to-roll calendaring line. Thus, in the applied M-ERA-NET funded project, the development of this inline testing technology shall be performed on a pre-industrial scale up to a TRL of four. The proposed project serves in the context of battery research and electromobility within the framework of the planned EU-wide energy transition.