Brief description
As part of the FOOD research project, a new approach to optimizing the forming process in battery cell production is to be developed and tested. This involves using measurement data from the forming process, which to date has only been used to control and regulate the process. Forming data will be evaluated using new battery diagnostics methods to be developed. Instead of comparing individual measuring points with threshold values, model-based and AI-based approaches as well as methods derived from laboratory analysis are used. In this project, the results of the battery diagnostic procedures are transferred to a database whose data records are evaluated using ML methods.
Based on the evaluation methodology, three digital production modules are being developed and tested in this project:
1. “Optimization of the forming protocol”
2. “Improved cell grading”
3. “Reduction of end-of-line tests”