Battery Charging Rate Control via User Activity Profiles
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Solution Overview
Problem
Rechargeable batteries face challenges in optimizing charging rates to balance daily usage needs and battery lifespan, as existing methods do not adapt to individual user lifestyles or account for device utilization patterns, particularly for devices like battery-powered vehicles.
Innovation Solution
A method that creates a user activity profile based on device and peripheral device interactions to estimate charging time and capacity needs, selecting optimal charge rates between fast and slow charging profiles to ensure sufficient battery capacity while extending battery lifespan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fast charging is used to quickly replenish battery capacity, then charging speed is improved, but battery lifespan deteriorates
Solution Approach 1:
The system dynamically adjusts charging rates based on real-time analysis of user activity patterns, device usage, and environmental context. The charging profile transitions from static to dynamic, allowing the system to optimize between fast and slow charging based on predicted user needs and battery health considerations.
Solution Approach 2:
The system continuously monitors user behavior patterns, device usage, and charging history to create activity profiles. This feedback loop enables the system to learn and adapt to individual user preferences, automatically adjusting charging rates to balance speed and battery lifespan without user intervention.
2Reliability
If slow charging is used to extend battery lifespan, then battery durability is improved, but charging capacity insufficient for daily use
Solution Approach 1:
The system performs preliminary analysis of user activity patterns and device usage to predict future charging needs. By proactively adjusting charging rates based on predicted requirements rather than reactive responses, the system ensures sufficient charge capacity is accumulated while maintaining battery health.
Solution Approach 2:
The charging rate dynamically adapts between slow and fast modes based on real-time assessment of user needs and battery status, allowing the system to optimize both battery lifespan and charge capacity accumulation according to actual usage patterns.
3Ease of operation
If fixed charging rate is used to simplify charging process, then ease of operation is improved, but adaptability to user needs deteriorates
Solution Approach 1:
The system autonomously determines optimal charging rates by analyzing user activity patterns, device usage, and environmental factors without requiring user input or manual selection. The self-service approach enables the system to adapt to individual user needs automatically while maintaining operational simplicity.
Solution Approach 2:
Through continuous monitoring of user behavior and device usage patterns, the system builds activity profiles that enable automatic adaptation of charging rates. This feedback mechanism allows the system to become increasingly tailored to individual users over time without adding operational complexity.
Data Source
AI summary
In an approach for selecting a battery charging rate, a processor, responsive to an electronic device with a rechargeable battery being connected to a battery charging device, identifies a current battery status of the rechargeable battery. A processor determines a disconnect time of the battery charging device. A processor determines a charge level required. A processor determines a charging profile based on the current battery status, the disconnect time of battery charging device, and the charge level required. A processor sends the charging profile to the battery charging device.