Battery Time Estimation via Cumulative Capacity Data
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Solution Overview
Problem
Current methods for estimating battery time in rechargeable batteries are inaccurate as they do not consider historical usage patterns, leading to unexpected battery depletion and potential loss of work due to incorrect power capacity readings.
Innovation Solution
A method that acquires and processes cumulative data on battery capacity over time to provide a more accurate estimate of available battery time by tracking the time duration for each decrement level, allowing for real-time power capacity assessments and task completion predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If battery time is estimated based on new battery capacity specifications, then the estimation is simple and quick, but the accuracy deteriorates significantly as the battery ages
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and recording battery capacity at different charge levels before the user needs to estimate battery time. Historical data is collected in advance during normal battery operation, building a database of capacity-time relationships that will be used for accurate future predictions without requiring complex real-time calculations.
Solution Approach 2:
The system implements feedback by using actual measured battery capacity data from previous operations to refine and improve future battery time estimates. The monitored historical data serves as feedback that updates the estimation model, allowing the system to adapt to battery aging and provide increasingly accurate predictions as the battery lifecycle progresses.
2Reliability
If historical battery usage data is collected and processed, then battery time estimation accuracy improves, but the complexity of data management increases
Solution Approach 1:
The battery monitoring system performs self-service by automatically collecting, storing, and processing its own operational data without requiring external intervention. The system monitors its own capacity degradation patterns and uses this self-generated data to improve its estimation accuracy, eliminating the need for manual data collection or external analysis while maintaining high reliability.
3Ease of operation
If battery capacity is displayed as a percentage of maximum capacity, then the display is simple and intuitive, but it fails to account for battery aging and capacity degradation
Solution Approach 1:
The system introduces dynamics by transitioning from a static percentage-based capacity display to a dynamic estimation that adapts to actual battery conditions. The battery time estimation continuously updates based on monitored capacity degradation, providing realistic predictions about actual available power while maintaining user-friendly presentation through the estimated time display.
Data Source
AI summary
A method is disclosed for providing information related to the power capacity of a rechargeable battery at a specified time, wherein the battery is disposed to supply power to a laptop computer or other electronic device. The method comprises the step of acquiring a set of cumulative data that represents the capacity of the battery at different times when the battery is being used to supply power to the device. The method further comprises selectively processing the set of data, to provide an estimate of the battery time that is available at the specified time. The estimate is then used to determine whether or not the battery has sufficient power capacity to complete a particular task subsequent to the specified time.