Toshiba had 65 patents in batteries during Q2 2024. Toshiba Corp’s patents in Q2 2024 involve a system that uses machine learning to classify electric vehicle consumption in a power distribution network, allowing for more efficient power generation. Another patent focuses on an electrode material for batteries containing a niobium-titanium composite oxide with specific ratios and additional elements for improved performance. GlobalData’s report on Toshiba gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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Toshiba had no grants in batteries as a theme in Q2 2024.

Recent Patents

Application: Premises electric vehicle charge detection (Patent ID: US20240149736A1)

The patent filed by Toshiba Corp. describes a system that utilizes machine learning to classify premises based on electric vehicle charging behavior. The system accesses consumption data from a premises in a power distribution network, applies a machine-learning model to classify the premises as either not charging an electric vehicle, charging with a level 1 charger, or charging with a level 2 charger. This classification is then used to control power generation in the network. The machine-learning model is trained using ground-truth data from multiple premises and can be updated with additional consumption data.

Additionally, the system normalizes consumption data, uses time-domain data for analysis, and can generate forecasts of future electric vehicle charging operations. The classification of premises is represented using a one-hot encoding of a SoftMax function, allowing for a comprehensive understanding of electric vehicle charging behavior across the network. The patent also covers a non-transitory, computer-readable medium and a computer-implemented method for implementing the described system, providing a detailed framework for utilizing machine learning in power distribution networks to optimize electric vehicle charging operations.

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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.