Siemens had 32 patents in batteries during Q2 2024. Siemens AG filed patents in Q2 2024 for methods involving analyzing electrode paste and layers in battery cells using AI, as well as for changing the electrical state of charge in energy storage devices by setting target values, determining actual values, extrapolating state of charge, and adjusting the charging process based on deviations. GlobalData’s report on Siemens gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Siemens had no grants in batteries as a theme in Q2 2024.
Recent Patents
Application: Methods for analyzing an electrode layer of a battery cell using a ki engine, training a ki engine, producing a battery storage device, and production units (Patent ID: US20240133819A1)
The patent filed by Siemens AG describes a method for analyzing an electrode paste and/or an electrode layer for a battery cell. The method involves measuring properties of the electrode paste and/or layer using a measuring facility, generating measurement data, and determining a quality value using an AI engine based on the measurement data. The quality value can measure factors such as degree of mixing, relief value, porosity, and crack value of the electrode layer. Additional properties can be measured using a second measuring facility, and the AI engine can be trained to analyze the electrode layer using deep-learning methods.
Furthermore, the method can be used in the production of a battery storage device by measuring properties of the electrode layer paste and/or layer, generating measurement data, and utilizing production conditions such as temperatures, solvent content, degree of mixing, and application rate of the electrode layer paste. The AI engine can be trained to evaluate the electrode layer and assign quality classes to different locations based on the measurement data. Overall, the patent outlines a comprehensive method for analyzing and producing battery cells with the help of advanced AI technology and measurement facilities.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
