Battery Residual Value Screening by Coulometry Aging Curves
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Solution Overview
Problem
Current methods for determining the suitability of used lithium-ion batteries for second-life applications in stationary energy storage are imprecise, failing to accurately assess the temporal trend of battery health, leading to inhomogeneous storage systems and premature aging.
Innovation Solution
A method involving high-precision coulometry and temperature control to measure battery load cycles, with calibration and optimization techniques to determine residual value criteria, allowing for precise assessment of battery aging and allocation into homogeneous groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional battery management system information is used to assess battery suitability, then the assessment process is simple, but the measurement precision is insufficient leading to inhomogeneous storage systems
Solution Approach 1:
The patent transforms the assessment from using single-point parameters (residual capacity, internal resistance) to using temporal trend parameters (aging curves, capacity loss rates, derivative values). This parameter transformation enables precise identification of batteries near the knee point while maintaining a manageable assessment process through automated curve analysis.
Solution Approach 2:
The patent performs preliminary aging trend analysis before batteries are deployed into storage systems. By assessing the temporal development trajectory in advance, batteries can be sorted into homogeneous groups based on their predicted aging behavior, preventing future inhomogeneity without requiring complex real-time monitoring systems.
2Loss of time
If only current state measurements are taken, then the measurement process is simple and quick, but the ability to predict future battery behavior is lost
Solution Approach 1:
The patent performs preliminary aging trend analysis by conducting accelerated aging tests and fitting aging curves before deployment. This preliminary action captures the temporal development trajectory early, enabling reliable predictions of future battery behavior without requiring long-term monitoring during actual operation.
Solution Approach 2:
The patent uses feedback from accelerated aging tests and historical data to refine aging curve models. By continuously improving the accuracy of aging predictions through feedback mechanisms, the system achieves high prediction reliability while maintaining quick assessment times through optimized modeling approaches.
3Stability of the object's composition
If batteries with similar current capacity are grouped together, then the initial homogeneity is achieved, but rapid divergence occurs due to undetected aging trends
Solution Approach 1:
The patent performs preliminary sorting based on aging trends rather than just current state. By analyzing aging curves and capacity loss rates before grouping, batteries are initially sorted into homogeneous groups based on their predicted future behavior, not just their current capacity, preventing rapid divergence.
Solution Approach 2:
The patent changes the grouping criterion from static parameters (current capacity) to dynamic parameters (aging rate, capacity loss trajectory, knee point proximity). This parameter change ensures that batteries in the same group have similar aging patterns, maintaining homogeneity over extended periods.
4Measurement precision
If detailed aging analysis is performed on all batteries, then the measurement precision is high, but the productivity of the assessment process decreases
Solution Approach 1:
The patent segments the battery population into different assessment categories based on preliminary screening. Batteries are divided into groups requiring full detailed analysis versus those needing only standard assessment, enabling high-precision analysis only where necessary and maintaining high throughput for the overall process.
Solution Approach 2:
The patent applies partial detailed aging analysis only to batteries that require it (e.g., those near knee point or showing unusual patterns), rather than performing exhaustive analysis on all batteries. This selective approach maintains high precision for critical cases while preserving overall assessment productivity.
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 provides a precise evaluation of battery residual value, reducing the risk of maintenance and failure, enabling the creation of stable and efficient stationary energy storage systems by accurately predicting battery aging behavior.
Implementation Method 1
The test temperature is stabilized for the duration of the test so that any deviations from the test temperature are less than 2 K
Implementation Method 2
a number of battery load cycles are measured using a high-precision coulometry device, with the measurement results comprising a number of current values
Data Source
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AI summary
High-precision coulometry is used to assess the residual value of used batteries, particularly their suitability for second-life applications in stationary energy storage systems. This involves determining the capacity to estimate the current possible energy throughput, the energy efficiency to estimate the required cooling capacity, and the current aging rate to estimate the remaining service life.