Battery Power Management Using Adaptive Performance Shifting
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Solution Overview
Problem
Existing power management settings for computing systems are static and do not adapt to changing battery capacity or user profiles, leading to unpredictable battery life and performance.
Innovation Solution
A hardware and/or software solution that monitors the remaining battery capacity and adjusts system performance settings dynamically, shifting from high performance to energy efficiency and back based on battery usage rates, to maintain predictable battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If power management settings are tuned to meet a battery life target, then battery life is improved, but processor performance is limited
Solution Approach 1:
The power management system dynamically adjusts processor performance settings based on real-time battery state-of-charge levels. When battery charge is high, the system allows higher processor performance; when battery charge drops, the system reduces performance to extend battery life. This dynamic adjustment resolves the contradiction by making performance adaptable rather than statically limited.
Solution Approach 2:
The system changes operational parameters (processor frequency, voltage, and performance profiles) based on battery state-of-charge thresholds. Different parameter sets are applied at different charge levels, allowing the system to optimize between performance and battery life by adjusting parameters rather than maintaining fixed settings.
2Device complexity
If power management settings are static, then system simplicity is maintained, but battery life becomes unpredictable as battery ages
Solution Approach 1:
The system implements feedback by continuously monitoring battery state-of-charge levels and adjusting power management settings accordingly. The monitor tracks battery charge and provides information to the power management system, which then adapts processor performance settings. This feedback loop ensures predictable battery life even as the battery degrades over time.
Solution Approach 2:
The power management system automatically adjusts settings based on battery state without requiring user intervention or complex configuration. The system serves itself by monitoring its own battery status and making appropriate performance adjustments, maintaining simplicity while improving reliability.
3Duration of action of moving object
If processor performance is limited to meet battery life target, then battery life is improved, but system performance becomes worse when usage is lighter than assumed workload
Solution Approach 1:
The system dynamically scales processor performance based on actual battery charge levels rather than assuming a fixed workload. When battery charge is higher than expected, the system can provide enhanced performance for light usage scenarios. When charge is low, it reduces performance to extend battery life, making the system adaptable to actual conditions rather than predetermined assumptions.
Data Source
AI summary
A hardware and/or software (e.g., a controller and/or firmware or software) that monitors a remaining capacity of a battery and adjusts a continuum of system performance settings ranging from best performance to best energy efficiency. The controller starts with best performance setting (at the expense of energy efficiency), and then the controller gradually shifts toward energy efficiency setting (at the expense of performance) when a battery usage exceeds a pre-defined drain rate (e.g., there is a deficit in the battery remaining capacity until the next charge). The controller reverts from energy efficiency setting towards high performance setting when the battery drain rate or discharge rate slows down (e.g., there is a surplus in the battery remaining capacity until the next charge).