Battery Cell Selection for Known Future Load
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Solution Overview
Problem
Consumer electronic devices face challenges in optimizing battery performance due to the exponential growth in electronic system performance outpacing linear improvements in battery technology, often requiring trade-offs between characteristics like charging speed and storage capacity.
Innovation Solution
The method involves selecting and adaptively controlling multiple battery cells within a computing device based on discharge and charge profile data, current and future power requirements, and user-defined goals, using a switching element to optimize battery usage for efficiency, longevity, cost, recharging opportunities, and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If new battery chemistries are developed to improve charging speed, then charging performance is improved, but storage capacity is reduced
Solution Approach 1:
The battery system is divided into multiple individual battery cells (first battery cell, second battery cell, etc.) that can be independently controlled. This segmentation allows the system to selectively charge or discharge specific cells based on their individual characteristics and the current power requirements, enabling optimization of both charging speed and storage capacity utilization across the battery pack.
Solution Approach 2:
The battery management system dynamically selects which battery cells to charge or discharge based on real-time conditions including current power requirements, known future power requirements, and individual cell characteristics. This dynamic control allows the system to adapt to changing conditions and optimize performance without being constrained by fixed charging/discharging patterns.
2Power
If battery cells are used to meet current power requirements, then immediate power needs are satisfied, but future power availability may be compromised
Solution Approach 1:
The system performs preliminary actions by charging selected battery cells in advance when power is available, based on known future power requirements. The operating system provides information about upcoming high-power tasks, and the battery management system proactively charges specific cells before these tasks occur, ensuring power availability when needed while extending overall battery life.
Solution Approach 2:
The battery management system continuously monitors discharge profile data and charge profile data from each battery cell, comparing actual performance against expected performance. This feedback mechanism allows the system to adjust charging/discharging strategies in real-time, optimizing the balance between meeting current power demands and preserving battery life for future use.
Data Source
AI summary
Methods for optimizing battery use for a known future load are described. In an embodiment, one or more battery cells are selected from a set of battery cells to provide power to a computing-based device. The battery cells are selected based on discharge profile data for each battery cell and both the current power requirement and a known future power requirement of the computing-based device. The known future power requirement is calculated based on information available to the operating system running on the computing-based device. In some examples, one or more battery cells may also be selected for charging when a power source is available and these cells may be selected based on charge profile data and the known future power requirement. The selection of the battery cells may also be made in order to satisfy a battery optimization goal, which may be defined by a user.