Battery Runtime Management via Adaptive Power Scaling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Portable Information Handling Systems (IHSs) face challenges in managing battery runtime effectively when using undersized AC adapters, which can lead to slow battery depletion and reduced runtime due to the inability to simultaneously charge the battery at maximum rate while operating in performance mode.
Innovation Solution
The system employs historical context data and machine learning models to adaptively optimize battery runtime by identifying locations and contexts, adjusting power consumption settings such as reducing CPU clock speed, placing components in standby, or shutting down applications, to match the DC runtime achievable with an undersized AC adapter to that of a nominally-sized adapter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If the IHS operates in performance mode with an undersized AC adapter, then the processor can achieve higher computational power, but the battery charge depletes slowly and runtime is reduced
Solution Approach 1:
The system performs preliminary actions by detecting the AC adapter's power capacity before full performance mode activation. The processor determines whether the adapter is undersized based on negotiated power delivery parameters, and proactively adjusts power consumption settings to prevent battery depletion during charging operations.
Solution Approach 2:
The system dynamically adjusts processor power consumption based on real-time conditions. The processor can switch between performance mode and power-saving modes depending on the AC adapter's capabilities, creating a dynamic power management system that adapts to changing power availability rather than operating in a fixed state.
2Adaptability or versatility
If the IHS uses an undersized AC adapter for charging, then the system can operate with limited power infrastructure, but the battery cannot be charged at maximum rate while in performance mode
Solution Approach 1:
The system changes operational parameters based on the AC adapter's power delivery capabilities. The processor monitors power negotiation parameters and adjusts its power consumption profile to match the adapter's maximum output, ensuring optimal charging rates within the constraints of the available power infrastructure.
Solution Approach 2:
The system applies partial action by operating the processor at reduced power levels when connected to undersized adapters. Rather than attempting to draw maximum power that the adapter cannot supply, the system deliberately limits power consumption to match available capacity, accepting partial performance in exchange for successful charging operation.
3Duration of action of moving object
If the IHS reduces power consumption to extend battery runtime, then the DC runtime is extended, but the performance of the system is reduced
Solution Approach 1:
The system implements dynamic power management where processor performance and power consumption are adjusted in real-time based on operational context. The processor can transition between high-performance states and low-power states, allowing the system to optimize the balance between runtime extension and performance maintenance based on current workload requirements and power availability.
Data Source
AI summary
Embodiments of systems and methods for managing battery runtime based upon power source activity are described. In some embodiments, a method may include determining, based at least in part upon location and context information, that a battery of an Information Handling System (IHS) is expected to be charged by a given alternating current (AC) adapter; and modifying one or more IHS settings to reduce a power consumption of the IHS in response to the determination.