Battery Charging Rate Throttling via Power Cable Data Exchange
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Solution Overview
Problem
In high-availability computing device environments, the limited power source often results in batteries being charged at an equal rate, which may not be desirable in scenarios requiring prioritized charging for devices with varying battery states.
Innovation Solution
A system and method where a group charging policy is stored in each computing device, allowing it to throttle its power draw rate based on its own and other connected devices' battery status data, enabling prioritized charging through communication via a power cable and charging cradle with additional contacts for data exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If batteries are charged at maximum rate in default configuration, then charging speed is improved, but power source limitations cause unequal charging rates among multiple devices
Solution Approach 1:
The system dynamically adjusts the charging rate of each device based on real-time battery status data and group charging policies. Computing devices monitor their own battery levels and the battery levels of other devices, then automatically throttle their power draw rates to implement prioritized charging strategies, transforming the static equal-rate charging into a dynamic adaptive system.
Solution Approach 2:
The system implements feedback mechanisms where computing devices continuously exchange battery status data with each other. Each device receives battery status information from other devices connected to the same power source, uses this feedback to determine appropriate charging rates according to group policies, and adjusts its power consumption accordingly, creating a closed-loop control system.
2Ease of operation
If limited power source current is equally divided among computing devices, then charging simplicity is maintained, but charging efficiency is reduced due to inability to prioritize devices with varying battery states
Solution Approach 1:
Computing devices autonomously manage their own charging rates without requiring external control. Each device independently monitors battery status data from itself and other devices, applies group charging policies locally, and self-adjusts its power draw rate. This self-service approach maintains operational simplicity while enabling efficient prioritized charging, as devices automatically negotiate and coordinate their charging behavior.
Solution Approach 2:
The system changes the operating parameters of charging by allowing devices to dynamically adjust their power draw rates based on battery status conditions. Instead of maintaining a fixed equal division of power, the system enables parameter variation where each device's charging rate becomes a variable that can be adjusted according to real-time battery levels and group charging policies, thereby improving overall charging efficiency.
Data Source
AI summary
A method and system for charging a battery is provided. A group charging policy specifying a conditional charging behavior for charging a battery of a computing device is stored in a memory of the computing device. The computing device is coupled to a power source. Battery status data is received, via a communications interface of the device, for each of at least one other computing device coupled to the power source. A power draw rate for charging the battery of the computing device is throttled according to the group charging policy and the battery status data of the computing device and the at least one other computing device.