IP Library › Granted Patent US 12,580,406
Granted Patent B2
US 12,580,406 · App. 17/933,712 · Granted Mar 17, 2026

Optimizing battery charging with synchronized context data

Inventors: Gina B Lu (San Francisco, CA); Kartik R Venkatraman (San Francisco, CA); Aaron Cotter (San Francisco, CA); Alexander D Palmer (San Jose, CA)
Assignee: Apple Inc.
H02J7/0071G06F1/263H02J7/0047
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Quick Facts
Patent No.
US 12,580,406
App. No.
17/933,712
Granted
Mar 17, 2026
Kind
B2
Abstract

An electronic device can include a power system including a battery and a processor programmed to: receive synchronized context data from one or more other devices associated with a user of the device, determine, at least in part based on the synchronized context data, one or more battery charging intervals, and operate the power system to charge the battery from the external power source during the identified one or more battery charging intervals. The processor can be programmed to determine the one or more battery charging intervals using a machine learning model. The synchronized context data can provide indication of the user's location. If the synchronized context data indicates that the user is at a different location than the device, the one or more battery charging intervals determined based at least in part on an expected time for the user to return to the location of the device.

Claims (36)

1 . An electronic device comprising:

a power system including a battery; and

a processor programmed to:

detect connection of an external power source to the electronic device;

determine an estimated disconnection time at which the external power source is expected to be disconnected from the electronic device based at least in part on one or more contexts synchronized from one or more other devices associated with a user of the electronic device;

identify one or more desired battery charging intervals prior to the estimated disconnection time; and

operate the power system to charge the battery from the external power source during the identified one or more desired battery charging intervals.

2 . The electronic device of claim 1 wherein the processor is programmed to determine an estimated disconnection time using a machine learning model.

3 . The electronic device of claim 1 wherein the one or more contexts synchronized from one or more other devices associated with the user of the electronic device provides indication of the user's location.

4 . The electronic device of claim 3 wherein if the one or more contexts synchronized from one or more other devices associated with the user of the electronic device indicates that the user is at a different location than the electronic device, the estimated disconnection time is determined based at least in part on an expected time for the user to return to the location of the electronic device.

5 . The electronic device of claim 4 wherein the one or more desired battery charging intervals are selected to reduce time that the battery spends at full charge.

6 . The electronic device of claim 1 wherein the processor is further programmed to operate the power system to charge the battery from the external power source during the identified one or more desired battery charging intervals by regulating a rate of battery charging to reduce time that the battery spends at full charge.

7 . The electronic device of claim 1 further comprising a display, wherein the processor is further programmed to communicate information about the one or more desired battery charging intervals to a user via the display.

8 . The electronic device of claim 1 further comprising an input device, wherein the processor is further programmed to receive user input regarding charging via the input device.

9 . A method of operating an electronic device, the method performed by a processor of the electronic device and comprising:

detecting connection of an external power source to the electronic device;

determining an estimated disconnection time at which the external power source is expected to be disconnected from the electronic device based at least in part on one or more contexts synchronized from one or more other devices associated with a user of the electronic device;

identifying one or more desired battery charging intervals prior to the estimated disconnection time; and

operating the electronic device to charge a battery of the electronic device from the external power source during the identified one or more desired battery charging intervals.

10 . The method of claim 9 wherein determining an estimated disconnection time further comprises using a machine learning model.

11 . The method of claim 9 wherein the one or more contexts synchronized from one or more other devices associated with the user of the electronic device provides indication of the user's location.

12 . The method of claim 11 wherein if the one or more contexts synchronized from one or more other devices associated with the user of the electronic device indicates that the user is at a different location than the electronic device, the estimated disconnection time is determined based at least in part on an expected time for the user to return to the location of the electronic device.

13 . The method of claim 12 wherein the one or more desired battery charging intervals are selected to reduce time that the battery spends at full charge.

14 . The method of claim 9 further comprising regulating a rate of battery charging to reduce time that the battery spends at full charge.

15 . The method of claim 9 further comprising communicating information about the one or more desired battery charging intervals to a user via a display of the electronic device.

16 . The method of claim 15 further comprising receiving user input regarding charging via an input of the electronic device.

17 . An electronic device comprising:

a power system including a battery; and

a processor programmed to:

receive one or more contexts synchronized from one or more other devices associated with a user of the electronic device;

determine, at least in part based on the one or more contexts synchronized from one or more other devices associated with the user of the electronic device, one or more battery charging intervals; and

operate the power system to charge the battery from an external power source during the determined one or more battery charging intervals.

18 . The electronic device of claim 17 wherein the processor is programmed to determine the one or more battery charging intervals using a machine learning model.

19 . The electronic device of claim 17 wherein the one or more contexts synchronized from one or more other devices associated with the user of the electronic device provides indication of the user's location, and if the one or more contexts synchronized from one or more other devices associated with the user of the electronic device indicates that the user is at a different location than the electronic device, the one or more battery charging intervals determined based at least in part on an expected time for the user to return to the location of the electronic device.

20 . The electronic device of claim 19 wherein the one or more battery charging intervals are selected to reduce time that the battery spends at full charge.

21 . The electronic device of claim 17 wherein the processor is further programmed to operate the power system to charge the battery during the one or more battery charging intervals by regulating a rate of battery charging to reduce time that the battery spends at full charge.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 19, 2023
From: LU, GINA B; VENKATRAMAN, KARTIK R; COTTER, AARON; PALMER, ALEXANDER D
To: APPLE INC.
Reel/Frame 062426/0982 →
Continuity (2)
Provisional Application 63374665 · Sep 6, 2022
Related Publication 20240097470A1 · Mar 21, 2024
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