The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 27, 2023

Filed:

Apr. 13, 2018
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Sabrina Kathrin Rechkemmer, Shanghai, CN;

Xiaoyun Zang, Shanghai, CN;

Oliver T. H. Sawodny, Shanghai, CN;

Alexander Boronka, Shanghai, CN;

Assignee:

Robert Bosch GmbH, Stuttgart, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B60L 53/66 (2019.01); B60L 53/64 (2019.01); H02J 7/00 (2006.01);
U.S. Cl.
CPC ...
B60L 53/66 (2019.02); B60L 53/64 (2019.02); B60L 53/665 (2019.02); H02J 7/005 (2020.01); H02J 7/0048 (2020.01); B60L 2250/18 (2013.01); B60L 2250/20 (2013.01); H02J 7/00034 (2020.01); H02J 2310/48 (2020.01);
Abstract

An optimization system includes a processor configured to receive one or more criteria for optimizing use of a power storage device in an application device, to receive data comprising at least one of user input(s), data from a cloud, and data regarding the application device, and to determine a charging/discharging profile for charging or discharging the power storage device from the received data based on the one or more criteria. The optimization system further includes an output configured to output the charging/discharging profile. The processor is configured to receive user feedback regarding the charging/discharging profile, machine learning data, big data, and/or a change regarding the optimization system and/or the application device, and to update the charging/discharging profile based on the received at least one of the user feedback regarding the charging/discharging profile, machine learning data, big data and the change regarding the optimization system and/or the application device.


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