Vehicle Wireless Charger Predictive Battery Scheduling
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Solution Overview
Problem
Existing battery charging methods lack efficiency and intelligence in managing battery charging based on usage patterns, leading to unnecessary energy consumption and potential battery drain during critical usage times.
Innovation Solution
A charging strategy that utilizes calendric patterns of device usage to predict future power needs, optimizing charging times and levels to ensure battery readiness while minimizing energy consumption and extending battery life, by communicating between the battery charger and device to develop a customized charging plan based on usage habits and rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous charging is performed to ensure battery readiness, then battery availability is improved, but energy consumption increases
Solution Approach 1:
The system performs charging in advance based on predicted usage patterns. The charger determines a charging schedule that proactively charges the battery before power is needed, rather than waiting for the battery to deplete. This preliminary action ensures battery availability while avoiding continuous or unnecessary charging operations that would waste energy.
Solution Approach 2:
The system uses feedback from usage patterns to dynamically adjust charging behavior. The charger monitors how the device is used and feeds this information back into the charging schedule determination, allowing the system to optimize charging timing and duration based on actual consumption patterns, thereby balancing reliability with energy efficiency.
2Use of energy by moving object
If charging is performed based on fixed schedules, then energy consumption is reduced, but battery readiness for unpredictable usage deteriorates
Solution Approach 1:
The charging schedule is dynamic rather than fixed. The system continuously adapts the charging schedule based on observed usage patterns and predictions of future power needs. This dynamic approach allows the system to maintain energy efficiency while ensuring the battery is ready for unpredictable usage demands by adjusting charging timing and duration in real-time.
Solution Approach 2:
The system serves itself by automatically learning and adapting to usage patterns without external intervention. The charger monitors its own charging effectiveness and the device's usage patterns, then self-adjusts the charging schedule to optimize both energy consumption and battery readiness, making the system responsive to unpredictable usage while maintaining efficiency.
3Productivity
If standard charging methods are used, then device complexity is minimized, but charging efficiency and battery life management deteriorate
Solution Approach 1:
The system introduces a charging schedule determination component as an intermediary between the charger and the battery. This intermediary analyzes usage patterns, predicts power needs, and determines optimal charging schedules, thereby improving charging efficiency and battery life management while keeping the overall system architecture manageable through clear separation of concerns.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach ensures the battery is adequately charged for predicted usage while reducing energy waste and extending battery life by aligning charging with usage patterns and optimizing energy consumption.
Implementation Method 1
The battery charger (10) wirelessly provides electrical power (20) to the mobile device (12)
Data Source
AI summary
Methods, systems, and products describe a car, truck, or other vehicle that charges a battery in a mobile device. The vehicle wirelessly inductively charges the battery based on historical usage.