View source for 18077615. APPARATUS FOR PREDICTING BATTERY LIFESPAN AND METHOD PREDICTING BATTERY LIFESPAN simplified abstract (Kia Corporation)

=APPARATUS FOR PREDICTING BATTERY LIFESPAN AND METHOD PREDICTING BATTERY LIFESPAN=


==Organization Name==

[[:Category:Kia Corporation|Kia Corporation]]


[[Category:Kia Corporation]]

==Inventor(s)==

[[:Category:Jaekyung Oh of Yongin-Si (KR)|Jaekyung Oh of Yongin-Si (KR)]][[Category:Jaekyung Oh of Yongin-Si (KR)]]

[[:Category:Chulkyu Lee of Anyang-Si (KR)|Chulkyu Lee of Anyang-Si (KR)]][[Category:Chulkyu Lee of Anyang-Si (KR)]]

[[:Category:Ju Seok Kim of Suwon-Si (KR)|Ju Seok Kim of Suwon-Si (KR)]][[Category:Ju Seok Kim of Suwon-Si (KR)]]

[[:Category:Hee Yeon Ryu of Yongin-Si (KR)|Hee Yeon Ryu of Yongin-Si (KR)]][[Category:Hee Yeon Ryu of Yongin-Si (KR)]]

[[:Category:Bohyun Lee of Incheon (KR)|Bohyun Lee of Incheon (KR)]][[Category:Bohyun Lee of Incheon (KR)]]

[[:Category:Kyeongeun Cho of Seoul (KR)|Kyeongeun Cho of Seoul (KR)]][[Category:Kyeongeun Cho of Seoul (KR)]]

[[:Category:Hangsoon Jung of Seoul (KR)|Hangsoon Jung of Seoul (KR)]][[Category:Hangsoon Jung of Seoul (KR)]]

[[:Category:Seongyoon Kim of Incheon (KR)|Seongyoon Kim of Incheon (KR)]][[Category:Seongyoon Kim of Incheon (KR)]]

[[:Category:Jung-Il Choi of Goyang-Si (KR)|Jung-Il Choi of Goyang-Si (KR)]][[Category:Jung-Il Choi of Goyang-Si (KR)]]

==APPARATUS FOR PREDICTING BATTERY LIFESPAN AND METHOD PREDICTING BATTERY LIFESPAN - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18077615 titled 'APPARATUS FOR PREDICTING BATTERY LIFESPAN AND METHOD PREDICTING BATTERY LIFESPAN

==Simplified Explanation==

The patent application describes a vehicle system that includes a display, a battery, a battery sensor, and a processor. The processor uses a battery lifespan model to predict the lifespan value of the battery and displays an indication of the battery's lifespan on the display.

* The vehicle system includes a display, battery, battery sensor, and processor.
* The battery sensor collects battery data, which is used by the processor.
* The processor uses a battery lifespan model to predict the lifespan value of the battery.
* The predicted lifespan value is then displayed on the display.

==Potential Applications==
* Electric vehicles: This technology can be applied to electric vehicles to provide users with information about the lifespan of their vehicle's battery.
* Consumer electronics: This technology can be used in devices like smartphones or laptops to inform users about the health of their device's battery.

==Problems Solved==
* Lack of battery lifespan information: This technology solves the problem of not having accurate information about the lifespan of a battery in a vehicle or electronic device.
* Battery management: By providing users with information about the battery's lifespan, this technology helps in managing and maintaining the battery more effectively.

==Benefits==
* User awareness: Users can make informed decisions about their vehicle or device based on the predicted lifespan value of the battery.
* Optimal battery usage: By knowing the lifespan value, users can optimize their battery usage and plan for replacements or maintenance in advance.
* Improved battery management: This technology helps in improving battery management by providing accurate information about the battery's lifespan.


==Original Abstract Submitted==

A vehicle may include a display; a battery; a battery sensor configured to acquire battery data of the battery; and a processor configured to acquire an output of a battery lifespan model associated with the battery data, predict a lifespan value of the battery based on the output of the battery lifespan model, and display an indication associated with the lifespan value of the battery on the display. The battery lifespan model may include a cell lifespan model associated with a basic lifespan model trained using first battery cell data collected in a first operating environment. The cell lifespan model may use second battery cell data collected in a second operating environment, and a pack lifespan model may be trained using battery pack data collected in the first operating environment.



[[Category:G06N3/0442]]
[[Category:H01M10/42]]
[[Category:G06N3/08]]