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Siemens and KIT cooperating on more-efficient production of large-scale batteries
17 January 2013
Working with the Karlsruhe Institute of Technology (KIT), Siemens plans to enhance its automation and control systems technology for the manufacturers of large-scale batteries, leveraging its experience in the production of energy-storage devices.
In a recently signed cooperation agreement, KIT and Siemens agreed to collaborate on an overarching concept for an integrated production-control and monitoring system for the entire production machinery of a battery plant. The aim is to develop a primary control system that will provide online monitoring of all processes via a central computer.
Sometime this year, the system is to be installed in the first production facility for lithium-ion cells of the KIT, where it will highlight the benefits in terms of product quality and reduced costs.
Wind and solar power plants already generate large amounts of electricity. The need to supply this energy as and when required will boost demand for energy-storage devices. These in turn must become cheaper to produce—especially lithium-ion batteries—while offering high quality.
The process used to manufacture such batteries, which can be as large as a shipping container, is still in its infancy, Siemens notes. The chemical processes in the battery cells are complex and highly sensitive. The foil coating of the electrodes, for example, must not deviate from regulation thickness by more than one micrometer across the entire coated surface. This condition must be fulfilled even though manufacturing is carried out at a speed of several tens of meters per minute.
Siemens has great expertise in the areas of automation and drive technology, production-planning, and design software. All of these areas play a role in efforts aimed at making the production of large-scale lithium-ion batteries efficient.
For example, Siemens software creates digital models of planned production facilities. As a result, it is possible to determine the required size of the plant, calculate the maximum potential throughput, and optimize efficiency. These simulation results can then be applied without further modification to real live plants. Similarly, quality-control systems can be directly integrated within fully automated production machinery.
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