Logical battery partitions
View Patent ↗A logical battery partitioning approach is disclosed. In one embodiment, a power management system in a portable computing device having a plurality of subsystems can include: (i) a battery coupled to a plurality of subsystems; (ii) a first battery variable provided to a first subsystem to indicate a characteristic of a first logical battery partition; and (iii) a second battery variable provided to a second subsystem to indicate a characteristic of a second logical battery partition. A battery variable can include an accessibility control, or a percent of battery power available, for example.
1. A power management system in a portable computing device, the power management system comprising:
a battery having a plurality of logical battery partitions, each logical battery partition providing power to at least one of a plurality of applications of the portable computing device;
a first battery variable to indicate a first characteristic of a first logical battery partition of the plurality of logical partitions, the first characteristic indicating an amount of power available to a first application of the plurality of applications;
a second battery variable to indicate a second characteristic of a second logical battery partition of the plurality of logical partitions, the second characteristic indicating an amount of power available to a second application of the plurality of applications; and
a power management system to adjust the amount of power available to each of the first and second application based upon a first and second priority assigned to the first and second applications, respectively.
2. The power management system of claim 1 , wherein the power management system is configured to adjust the amount of power available to the first application based upon a predetermined setting.
3. The power management system of claim 2 , wherein the predetermined setting is set by the portable computing device based upon an attribute of the first application obtained by the portable computing device via a machine learning technique.
4. The power management system of claim 2 , wherein the predetermined setting is set by a user of the portable computing device.
5. The power management system of claim 1 , wherein the first battery variable relates to an item selected from the group consisting of: a charge control, a discharge control, a percentage of remaining battery power, and an accessibility control.
6. The power management system of claim 1 , wherein the battery includes a capacitor.
7. The power management system of claim 1 , wherein the first priority is set by the portable computing device based upon an attribute of the first application obtained by the portable computing device via a machine learning technique.
8. A method performed within a power management system of a portable computing device, the method comprising:
assigning a plurality of logical battery partitions within a battery;
assigning each logical battery partition to provide power to at least one of a plurality of applications of the portable computing device;
receiving a first priority of a first application of the plurality of applications;
receiving a second priority of a second application of the plurality of applications; and
adjusting the amount of power available to each of the first and second application based upon the first and second priority assigned to the first and second applications, respectively.
9. The method of claim 8 , further comprising:
Adjusting the amount of power available to the first application based upon a predetermined setting.
10. The method of claim 9 , wherein the predetermined setting is set by the portable computing device based upon an attribute of the first application obtained by the portable computing device via a machine learning technique.
11. The method of claim 9 , wherein the predetermined setting is set by a user of the portable computing device.
12. The method of claim 8 , further comprising:
Storing a first battery variable indicating to a value selected from the group consisting of: a charge control, a discharge control, a percentage of remaining battery power, and an accessibility control.
13. The method of claim 8 , wherein the battery includes a capacitor.
14. The method of claim 8 , wherein the first priority is set by the portable computing device based upon an attribute of the first application obtained by the portable computing device via a machine learning technique.