Battery Current Limiting Module for Portable Computing Devices
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Solution Overview
Problem
Portable computing devices face challenges in managing battery capacity to optimize functionality without increasing the risk of brownout, as the trend towards smaller form factors and stagnant battery technology density limits the ability to accommodate additional functionality without sacrificing user experience.
Innovation Solution
A battery current limiting module that dynamically adjusts battery capacity safety margins using request/grant and reactive loop methodologies, periodically polling the battery to determine active demand and authorizing or denying requests based on available power consumption levels to maintain an optimal current margin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a larger battery capacity is included to support additional functionality, then the battery capacity increases, but the device form factor increases
Solution Approach 1:
The patent implements dynamic battery capacity management by continuously monitoring system state and adjusting the available battery capacity allocation in real-time. The system dynamically determines which components can be powered and at what levels based on current battery state, allowing the effective battery capacity to adapt to changing system requirements without physical expansion.
Solution Approach 2:
The system changes the operational parameters of battery capacity allocation by adjusting power distribution to different components based on system state. It modifies parameters such as component power levels, operational modes, and priority allocations to optimize the use of fixed battery capacity, effectively increasing usable capacity through parameter optimization rather than physical expansion.
2Reliability
If a fixed safety margin of battery capacity is maintained to prevent brownout, then system reliability improves, but the available functionality for the user decreases
Solution Approach 1:
The system replaces fixed safety margins with dynamic capacity management that continuously adjusts the reserve capacity based on real-time system state, component priorities, and battery conditions. This allows the safety margin to be minimized when possible while maintaining reliability, and expanded only when necessary based on actual system needs rather than predetermined fixed values.
Solution Approach 2:
The patent changes the parameter of safety margin from a fixed value to a dynamically adjustable parameter. The system monitors multiple factors including battery state of charge, component power requirements, thermal conditions, and system priorities to continuously optimize the safety margin parameter, allowing maximum functionality while maintaining adequate protection against brownout.
3Adaptability or versatility
If battery capacity safety margin is narrowed to maximize functionality, then user experience improves, but the risk of brownout or system crash increases
Solution Approach 1:
The system implements continuous feedback loops that monitor battery state, component power consumption, and system operational status. Based on this feedback, the dynamic capacity management algorithm adjusts power allocation and safety margins in real-time, allowing the system to operate closer to capacity limits while maintaining stability through active monitoring and adjustment rather than passive fixed margins.
Solution Approach 2:
The patent makes the safety margin dynamic by continuously adjusting it based on real-time system conditions. When system state indicates low risk (stable power consumption, adequate battery state), the safety margin is narrowed to maximize functionality. When conditions indicate potential risk (rapid discharge, thermal issues, high-power demands), the margin is automatically expanded to prevent brownout, creating a responsive adaptive system.
Data Source
AI summary
Various embodiments of methods and systems for managing battery capacity in a portable computing device (“PCD”) are disclosed. One such method includes leveraging a request/grant algorithm that receives a request from an offline component to come online. If battery capacity is available to accommodate the offline component, the request is granted. If battery capacity is not available to accommodate the offline component, the request is authorized at a reduced power level or capacity is created by reducing power to online components. Another method polls a battery to monitor demand on its capacity by active components. Offline components likely to come online concurrently with the active components are identified and ranked based on power consumption. A target current margin is adjusted based on the highest power consumption associated with an identified block of offline components.