Battery State Estimation Using Impedance Peak Frequency
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Solution Overview
Problem
Existing methods for estimating the state of deterioration in all-solid-state batteries do not adequately consider physical deterioration, such as cracks between active materials and solid-state electrolytes, which affects battery performance.
Innovation Solution
A state estimation method that uses impedance measurements to compute peak frequencies and arc chord lengths before and after a test causing deterioration, establishing a model to relate these parameters to the battery's state, including physical deterioration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If AC impedance method is used to estimate battery state, then measurement can be obtained, but accurate estimation of battery capacity and physical deterioration cannot be achieved
Solution Approach 1:
The patent transforms the impedance spectrum data by identifying peak frequencies in the imaginary component and using these frequency parameters as inputs for machine learning models. This parameter transformation converts raw impedance measurements into meaningful features that correlate with both capacity and physical deterioration states, resolving the inability to accurately detect physical deterioration while maintaining measurement capability.
Solution Approach 2:
The patent introduces machine learning models as intermediary components between the impedance measurements and the final state estimation. These models are trained to recognize patterns in impedance spectra that indicate physical deterioration, acting as a mediator that translates electrical measurements into accurate assessments of both capacity and structural degradation.
2Quantity of substance
If conventional impedance analysis is used, then resistance values can be obtained, but relationship between resistance and battery capacity is not clear
Solution Approach 1:
The patent moves from analyzing simple resistance values to analyzing the frequency domain representation of impedance. By examining the imaginary component of impedance across different frequencies and identifying peak frequencies, the method adds a frequency dimension to the analysis, revealing information about physical deterioration that is not apparent from resistance values alone.
Solution Approach 2:
The patent changes the analytical parameters from resistance values to peak frequencies of the imaginary impedance component. This parameter transformation enables the extraction of information about physical deterioration mechanisms, such as contact resistance changes and structural degradation, that are not reflected in simple resistance measurements.
3Reliability
If existing deterioration estimation methods are applied to all-solid-state batteries, then chemical deterioration can be analyzed, but physical deterioration such as cracks cannot be distinguished
Solution Approach 1:
The patent employs dynamic analysis by examining impedance across a range of frequencies rather than at a single frequency. The frequency-dependent behavior of the imaginary impedance component provides dynamic information about the battery's internal structure, enabling differentiation between chemical and physical deterioration mechanisms through their distinct frequency signatures.
Solution Approach 2:
The patent changes the measurement and analysis parameters to focus on the imaginary component of impedance and its frequency dependence. This parameter change enables the detection of physical deterioration by capturing the dynamic response of the solid-state electrolyte and electrode interfaces, which manifest as characteristic peak frequencies that differ from chemical deterioration patterns.
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
Enables accurate estimation of a rechargeable battery's state, including capacity and physical deterioration, by utilizing a model-based approach that considers the specific characteristics of all-solid-state batteries.
Implementation Method 1
acquiring measurement data and states of a reference rechargeable battery before and after a test that causes deterioration to progress, the measurement data being impedances at respective frequencies that are measured by an impedance method
Data Source
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AI summary
A state estimation device includes a first acquisition section, a derivation section, a second acquisition section, a computation section and an estimation section. The first acquisition section acquires measurement data and states of a reference rechargeable battery before and after a test that causes deterioration to progress. The measurement data is impedances at respective frequencies measured by an impedance method, and the states are found in advance. The derivation section computes peak frequencies before and after the test from arc-shaped curves in graphs plotting the impedances at the respective frequencies represented by the measurement data, and obtains a model representing a relationship between peak frequencies and states. The second acquisition section acquires measurement data of an estimation target rechargeable battery, which is impedances at respective frequencies measured by the impedance method. The computation section computes a peak frequency from an arc-shaped curve in a graph plotting the impedances at the respective frequencies represented by this measurement data. The estimation section uses the model to estimate the state of the estimation target rechargeable battery from the peak frequency of the estimation target rechargeable battery.