Usage-Based Battery Charging Curves for Variable Duty Cycles
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Solution Overview
Problem
Existing battery charging systems struggle to efficiently charge energy storage devices based on variable and unscheduled usage patterns, leading to inefficiencies, increased degradation, and downtime.
Innovation Solution
Battery charging systems that utilize usage information to predict available charging periods, determine a target state of charge, and adjust charging curves to optimize charging, thereby reducing power consumption, noise, and extending the lifespan of energy storage devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If battery charging is performed continuously or at fixed schedules, then the battery may be available when needed, but energy consumption increases and battery lifespan decreases
Solution Approach 1:
The system performs preliminary actions by predicting future usage periods and scheduling charging operations in advance during optimal time windows. The controller analyzes historical usage data to forecast when the battery will be needed, then proactively charges the battery during predicted idle periods before actual usage occurs, ensuring availability while avoiding continuous charging.
Solution Approach 2:
The charging schedule is made dynamic rather than static. The system continuously monitors actual usage patterns and adjusts future charging schedules in real-time based on deviations from predicted patterns. This dynamic adaptation allows the system to optimize energy consumption while maintaining reliability despite variable usage conditions.
2Loss of time
If fast charging is applied to quickly charge the battery, then charging time is reduced, but battery degradation increases
Solution Approach 1:
The system performs preliminary charging actions during extended idle periods before actual usage is needed. By anticipating future usage requirements and charging the battery in advance during periods when time is less critical, the system can use moderate charging rates that preserve battery lifespan while still ensuring the battery is fully charged when actually needed.
Solution Approach 2:
The charging rate parameter is dynamically adjusted based on the remaining time until predicted usage. When the battery is charged well in advance of needed usage, lower charging rates are applied to minimize degradation. As the predicted usage time approaches, the system may increase charging rates appropriately, optimizing the balance between charging speed and battery health preservation.
3Reliability
If charging is performed during all idle periods, then battery availability improves, but noise from charging operations increases
Solution Approach 1:
The system performs preliminary charging during predicted idle periods when the battery will not be needed for usage. By concentrating charging operations during these predetermined windows, the system ensures the battery is ready for future usage while avoiding charging during periods when operational constraints (such as noise sensitivity) may be present.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor actual usage patterns and adjust future charging schedules accordingly. If noise-sensitive periods are identified through usage pattern analysis, the controller adapts the charging schedule to avoid these periods, dynamically optimizing the balance between battery availability and noise generation based on real-world operational conditions.
4Adaptability or versatility
If usage patterns are variable and unscheduled, then operational flexibility is maintained, but charging optimization becomes difficult
Solution Approach 1:
The system performs preliminary analysis of historical usage data to predict future usage patterns. By proactively forecasting when the battery will be needed based on past patterns, the system can optimize charging schedules in advance without requiring real-time complex decision-making, thus managing complexity while maintaining adaptability to variable usage.
Solution Approach 2:
The system uses feedback from actual usage patterns to continuously refine and update predictions. By monitoring deviations between predicted and actual usage, the controller adapts future predictions and charging schedules accordingly. This feedback mechanism allows the system to maintain operational flexibility for variable usage patterns while managing complexity through data-driven adaptation rather than complex real-time control.
Data Source
Figure 1A
Figure 1B
Figure 2A~2B
AI summary
A battery charging system comprises power conversion circuitry configured to convert input power to charging power; communications circuitry configured to access usage information from a management system of an energy storage device, the usage information comprising a plurality of charging periods and a plurality of discharging periods of the energy storage device; and control circuitry configured to: predict an available charging period based on the usage information; determine a target state of charge of the energy storage device based on the usage information; determine a charging curve configured to charge the energy storage device to the target state of charge by an end time of the available charging period; and control the power conversion circuitry to charge the energy storage device using the charging curve.