The continuously growing demand for electrical energy storage devices for mobile and stationary applications is accompanied by high demands on the manufacturing processes. In particular, the high complexity along the process chain poses major challenges for the planning of lithium-ion battery cell production. The existing interactions of the individual sub-processes are also difficult to take into account. Fluctuations within individual sub-processes thus have a direct impact on subsequent processes and thus on the cell properties. It is therefore essential to consider the process chain in its entirety in order to optimize production, improve product quality and reduce waste.
Start 01.10.2020 End 30.09.2023
Funding source: BMBF
The aim in ViPro is to take into account the interactions of the sub-processes and to influence subsequent processes accordingly in order to view and optimize the process chain in its entirety. For this purpose, a virtual production system is established that can be controlled by means of a cross-process production control system. This enables optimization approaches to be tested in virtual space in a realistic and low-risk manner. The results can then be transferred to the real processes. Furthermore, it is necessary to link the sub-processes by means of uniform interfaces. The tested approaches can then be finally transferred to the linked sub-processes and enable production while taking interactions into account. These goals result in different work contents, which are worked on in the context of the project in co-operation with three other institutes.
First of all, a virtual production system is being set up that models the process steps of coating, assembly, electrolyte filling and formation. The basis for this is formed by uniform interfaces for data transmission and a model standard. Furthermore, a standard for communication and interfaces between the machines is being developed. This will also make it possible to read out data that can then be stored in a database. With the help of the central database system, process data can be accessed from any location. This also makes it possible to link battery production sub-processes across different locations. The last work area of the project relates to an operations control system that enables cross-process production control. To this end, a cross-process production control system is being developed that uses machine learning methods to identify cause-effect relationships and to select optimal process parameters that take into account intermediate product properties and interactions. The cross-process control system is validated using the developed models. The operations control system then links the cross-process control with data acquisition and process visualization and monitoring.
Within the framework of ViPro, the IWF is particularly involved in the development of the operations control system, which also includes the human-machine interface (sustainable production and life cycle engineering). The cross-process production control system coupled with the operations control system is also being developed at the IWF. In addition, knowledge about the process of electrolyte filling is contributed here to achieve the goal (production technologies and process automation). This will make a significant contribution to increasing the quality of the battery cells and reducing production waste by quantifying the interactions and the associated adjustment of the process parameters via the control system and the operations control system.