KIT Looks to Optimize Large Scale Production of Li-Ion Batteries with Automatic Error Detection

July 16, 2021 by Ahmad Ezzeddine

The Karlsruhe Institute of Technology is using automatic error detection to produce high-quality lithium-ion batteries. The process is implemented at the AQua Battery Competence Cluster.

The battery manufacturing industry in Germany is probably going to be among the best in the world. The research activities are being held at the AQua battery research cluster in cooperation with the Federal Ministry of Education and Research “Battery research factory”. New approaches toward quality assurance and analytics in production are being developed at KIT.  The research aims to produce low prices, powerful, durable, and safe batteries.

With new methods from AQua, the quality of the electrode coating can be checked automatically. Image courtesy of Irina Westermann and the Karlsruhe Institute of Technology (KIT)

The researchers have to make sure that manufacturing is at the lowest cost with the best quality. Therefore, they have to start by looking at each production step. This reveals each error at each step. After the detection of errors, they should be optimized and automated to ensure a high-quality product at the end of the process. “In production, every step has to be flawless. All steps are designed to work together, and any error can affect the later performance of the cells,” says Professor Helmut Ehrenberg from the Institute for Applied Materials (IAM-ESS) of KIT, who coordinates the research.

What is Automatic Error Detection?

The scientists in the AQua projects work, according to the principle of Failure Mode and Effects Analysis (FMEA).  FMEA is a method used to evaluate the possibilities for failures, reasons for failure, and failure impacts on a process. FMEA reviews the steps in the process, failure modes, failure causes, and failure effects. These are then applied directly in the production process. With automatic error detection, any piece that might be defected is rejected by the machine after being inspected.  “This also allows us to draw conclusions about the causes of errors and we can eliminate process disruptions at an early stage and avoid further costs due to rejects,” explains Dr. Lea de Biasi, one of the researchers in the project.

Manufacture of a stack of electrodes in the laboratory. Semi-automated production lines ensure flexible manufacturing.  Image courtesy of Karlsruhe Institute of Technology (KIT).

The Upcoming Li-Ion Batteries

Li-Ion batteries could have malfunctioned during manufacturing and operation. Those malfunctions are internal, such as solid electrolyte interface formation, overcharge, and over-discharge, or external such as sensor faults and cooling system faults. Those faults might have hazardous effects, for example, battery combustion or explosion. With automatic error detection the probability to avoid those faults increases.

The Data Infrastructure

Collecting data is crucial to speed up the research transfer. Therefore, a new research platform is complemented by an accompanying project that is being coordinated at KIT by Dr. Micheal Selzer. “With the data infrastructure, we provide sustainable access to this research data and the analysis tools.”