Distributed Battery Modules for Low-Loss Wearable Power Delivery
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Solution Overview
Problem
In wearable electronic devices, batteries are often positioned far from their loads due to space constraints, leading to power loss through electronic connectors, which reduces efficiency and battery life.
Innovation Solution
Implementing a distributed battery architecture with charger battery modules (CBMs) close to electronic components, each equipped with batteries, battery chargers, and microcontrollers, controlled by a central controller that optimizes charging and discharging based on usage patterns and battery type using machine learning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If batteries are positioned far from electronic components due to space constraints, then device layout flexibility is improved, but power transfer efficiency deteriorates
Solution Approach 1:
The patent divides the battery system into multiple distributed battery modules, each positioned close to specific electronic components it serves. This segmentation allows the system to maintain layout flexibility while reducing power transfer distances for each individual module, thereby resolving the contradiction between layout flexibility and power transfer efficiency.
Solution Approach 2:
The patent implements local battery modules with different capacities and characteristics positioned near specific high-power components based on their unique power requirements. This local quality approach ensures that each component receives optimized power delivery, improving overall power transfer efficiency while maintaining device layout flexibility through localized power supply units.
2Loss of energy
If distributed battery modules are implemented close to electronic components, then power transfer efficiency is improved, but device complexity increases
Solution Approach 1:
The patent designs universal battery module interfaces and standardized communication protocols that allow different battery modules to be controlled through a common architecture. This universality reduces the complexity burden of having multiple distributed modules, as they can be managed through standardized methods rather than requiring unique control circuits for each module.
Solution Approach 2:
The patent implements feedback mechanisms where each battery module communicates its status, power delivery, and health information to a central controller, which optimizes the overall power distribution. This feedback system automates the management of distributed modules, reducing the operational complexity and allowing the system to self-optimize power transfer efficiency without manual intervention.
3Duration of action of stationary object
If machine learning optimization is implemented for charging and discharging, then battery life is extended, but computational requirements and device complexity increase
Solution Approach 1:
The patent implements machine learning models that are pre-trained offline to predict optimal charging and discharging strategies based on usage patterns. These pre-computed models are then deployed to the battery control system, allowing the device to execute optimized power management without requiring complex real-time computational resources, thus extending battery life while minimizing additional device complexity.
Data Source
AI summary
The disclosed system may include multiple electronic components and multiple charger battery modules. Each charger battery module may include: at least one battery configured to drive at least one of the electronic components, at least one battery charger configured to charge the battery, and a microcontroller configured to control the charging and discharging of the battery. The system may also include a central controller that may be configured to control the various charger battery modules through each charger battery module's associated microcontroller. Various other methods, systems, and computer-readable media are also disclosed.