Siemens Aktiengesellschaft

Siemens Energy Global Gmbh & Co. Kg

Frank Steinbacher

Günter Schmid

Manfred Baldauf

Arno Arzberger

Marc Christian Weber

Clemens Otte

Thomas A Runkler

Alexander Michael Gigler

Christian Reller

Sascha Schulte

Jonas Witt

Gunnar Stoelben

Thomas Runkler

Various embodiments include a method for analyzing an electrode layer for a battery storage device in an electrode layer production facility. The method may include: acquiring an image comprising two pixels of the electrode layer, wherein a first pixel represents a first location of the electrode layer and a second pixel represents a second location of the electrode layer, wherein the first location and the second location are disposed adjacent to each other; determining a first value for a material property of the electrode layer at the first location based on the first pixel; determining a second value for the material property of the electrode layer at the second location based on the second pixel; comparing the first value and the second value and determining a comparison value; and determining characteristic properties of the electrode layer based on the comparison value.

Method for analyzing an electrode layer of a battery storage device, method for producing a battery storage device, and production unit

Method and apparatus for industrial scale production of a suspension for a battery, wherein an input material is processed via ball milling in a rotating chamber of a device that is effected as a continuous process with a continuously controlled addition of the input material and with a continuously controlled delivery of the processed output material, where state parameters of the input material and process parameters of the manufacturing installation are acquired as first parameters during production of the suspension, results of laboratory analyses about the state or quality of the manufactured suspension are acquired as second parameters in a learning phase during production, the first and the second parameters are used in the learning phase for training a model for predicting the state or quality via machine learning, and where the device is open-loop or closed-loop controlled outside the learning phase via the first parameters and the trained model.

Method and arrangement for industrial scale production of a suspension for a battery

Various embodiments include a method for producing a quality test system executing a quality test model with a filter mask and a quality model to determine a quality feature of a battery cell. The system has an electrochemical impedance spectroscopic unit for capturing test data relating to the battery within a frequency range. The method includes: creating the model; and producing the system. Creating the model includes: capturing spectroscopic learning data; creating the filter mask using a first machine learning method with analysis data from part of the frequency range by consulting the filter mask and creating the model using a second machine learning method. The first and the second learning method are coupled based on the learning data. The first machine learning method creates a filter mask determining the analysis data such that the second machine learning method creates a quality model optimized with respect to maximizing the quality.

Production of a quality test system

Growing community of inventors

Eckental, Germany

Frank Steinbacher