Tobias Zeilinger

Method for quality parameter identification and classification in battery cell production quality planning of complex production chains for battery cells

This paper focuses on the identification of quality relevant process parameters in the production of high energy lithium-ion battery cells. Today there is still a high level of uncertainty about the effects of manufacturing processes on the quality of high energy lithium-ion cells - in industry as well as in research. Compared to consumer cells, high energy cells used for automotive applications or grid power supply are subject to much higher quality requirements, especially regarding life time and safety issues as well as different conditions of operation. Consequently, a quality planning approach for the identification of process-product-interactions in the field of high energy lithium-ion cell production is presented. The described methodology is applicable from early design stages to the ramp-up of lithium-ion cell production lines. On the one hand, knowledge about these correlations helps to estimate product quality in dependency of intermediate product properties and process parameters. On the other, required set points for the processes employed in cell manufacturing can be derived. Thus, results of the described methodology contribute to overcome existing challenges for equipment manufacturers, cell manufacturers as well as cell costumers. Therefore, the paper describes and characterizes the entire production chains of hard case cells and pouch cells partially implemented in the High-Energy Battery Cell Production Research Center of the Institute for Machine Tools and Industrial Management (iwb) ([1], [2]). The presented methodology for the identification of process-product-interactions consists of five steps. Step 1 is described in this paper, while step 2 to 5 are outlined. Based on a modified process Failure Mode and Effects Analysis (FMEA) step 1 collects in an unrestrained but oriented way possible failures in cell manufacturing and provides evaluated process-product-interactions. With this information, in step 2 process and material properties are classified employing complexity management methods. Based on the classification, production parameters with significant influence on the product quality features can be selected for the quantification by means of experiments.

Integrated product and process model for production system design and quality assurance for EV battery cells

The megatrend electric mobility induces a significant demand for high energy and high power secondary batteries. Currently lithium-ion technologies are the most promising solution for electrochemical energy storage in hybrid electric vehicles (HEV) and battery electric vehicles (BEV) [1; .Core factors that influence the quality, the performance and the cost of high energy lithium-ion batteries are production technologies, quality measurement techniques and quality management methods [3; . For this reason the Institute for Machine Tools and Industrial Management set up the Research Center for the Production of High-Energy Battery Cells (R-PHEB). In this research center production technologies are investigated according to industrial requirements. Research thrust areas are: first, process and assembly system design; second, quality assurance and management; and third, value chain analysis and design.The mass production of large lithium-ion cells for EV applications is an infant industry; new production technologies are often used in this field [. Hence, the influences of those processes on product properties are not known and the product quality can be evaluated only after the final production step. In order to obtain a resource efficient and economic production of lithium-ion cells, the correlations between the cell performance, the cell quality, the production processes and the assembly system design need to be revealed.This paper focuses on fundamental investigations of the process chain for the production of lithium-ion cells. It introduces a product-and a process-model, both of which specifically match the requirements in the field of battery production. The models can be used individually to describe the product structure or the process chain. Additionally they can be linked via a correlation matrix in order to visualize the dependencies between the requirement specifications of lithium-ion cells and the manufacturing processes (including process alternatives). Both models are based on a layered structure and contain information about battery cell design, battery type and production processes covering all tasks from coating the electrode coils to the start-of-operation of the cells.The product-model, the process-model and the correlation matrix will be implemented in a database, which in the future can be used for the methodical design of assembly systems as well as to investigate the correlations between process parameters and output quality. Furthermore, the database can assist when evaluating established process chains or preparing make-or-buy decisions in the context of battery cell production.