A method and system for analyzing current collector material of fast-charging battery based on wavelet denoising

Abstract

The application relates to the technical field of material analysis, and discloses a fast-charging battery current collector material analysis method and system based on wavelet noise reduction, which comprises the following steps: based on the frequency characteristic distribution of an electrochemical test signal, performing multi-scale wavelet decomposition on the electrochemical test signal to obtain wavelet coefficients of the electrochemical test signal; according to the amplitude distribution characteristics of the wavelet coefficients, determining local threshold parameters of the wavelet coefficients, and based on the local threshold parameters, performing soft threshold processing on the wavelet coefficients to obtain denoised wavelet coefficients; performing wavelet reconstruction processing on the denoised wavelet coefficients to obtain a reconstructed electrochemical test signal; according to the reconstructed electrochemical test signal, extracting interface impedance characteristics and charge transport characteristics; and according to the interface impedance characteristics and the charge transport characteristics, evaluating the performance stability of the fast-charging battery current collector material under high-rate charging and discharging conditions; and the application can improve the efficiency of fast-charging battery current collector material analysis.

Description

Technical Field

[0001] This invention relates to the field of materials analysis technology, and more specifically, to a method and system for analyzing the current collector materials of fast-charging batteries based on wavelet denoising. Background Technology

[0002] The performance evaluation of current collector materials in fast-charging batteries under high-rate charge and discharge scenarios heavily relies on the accurate interpretation of electrochemical test signals. Traditional analytical methods directly use raw current and voltage response signals for feature extraction and performance determination, failing to effectively address the issue of signals being susceptible to environmental noise and equipment interference under high-rate operating conditions. This leads to signal distortion and feature shift, failing to accurately reflect the intrinsic characteristics of material interface impedance and charge transport, resulting in insufficient accuracy of the analytical results.

[0003] Existing signal denoising methods mostly employ a globally fixed threshold processing approach, which struggles to adapt to the multi-scale and non-stationary frequency distribution characteristics of electrochemical test signals. During denoising, effective details corresponding to the material's microscopic properties are easily lost, and the methods cannot adaptively match signal variation patterns under different charge-discharge rates. This results in low extraction accuracy of key features such as interface impedance and charge transport, ultimately making it impossible to objectively assess the performance stability of current collector materials under high-rate charge-discharge conditions. This fails to meet the practical needs of fast-charging battery material research and performance optimization. Therefore, how to overcome the instability of fast-charging battery current collector materials has become a pressing technical problem to be solved in the industry. Summary of the Invention

[0004] To address the aforementioned problems in the existing technology, embodiments of the present invention provide a method and system for analyzing current collector materials in fast-charging batteries based on wavelet denoising.

[0005] To achieve the above objectives, this invention provides a method for analyzing current collector materials in fast-charging batteries based on wavelet denoising, comprising: A. Acquire electrochemical test signals of the current collector material of a fast-charging battery at different charge / discharge rates, wherein the electrochemical test signals include current response signals and voltage response signals; B. Based on the frequency characteristic distribution of the electrochemical test signal, perform multi-scale wavelet decomposition on the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal; C. Based on the amplitude distribution characteristics of the wavelet coefficients, determine the local threshold parameters of the wavelet coefficients, and perform soft thresholding on the wavelet coefficients based on the local threshold parameters to obtain the noise-reduced wavelet coefficients of the current collector material of the fast charging battery. D. Perform wavelet reconstruction processing on the denoised wavelet coefficients to obtain the reconstructed electrochemical test signal of the current collector material of the fast charging battery; E. Based on the reconstructed electrochemical test signal, extract the interfacial impedance characteristics and charge transport characteristics of the current collector material of the fast-charging battery. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient. F. Evaluate the performance stability of the fast-charging battery current collector material under high-rate charge and discharge conditions based on the interfacial impedance characteristics and the charge transport characteristics.

[0006] Preferably, the step of acquiring electrochemical test signals of the current collector material of the fast-charging battery at different charge / discharge rates includes current response signals and voltage response signals, comprising: Collect raw electrochemical data streams of current collector materials in fast-charging batteries at different charge / discharge rates; Extract the current response signal segment and voltage response signal segment within the steady-state response period from the original electrochemical data stream; Outlier detection is performed on the current response signal segment and the voltage response signal segment, and linear interpolation is performed on the detected current response signal segment and voltage response signal segment to obtain the current response sequence and voltage response sequence of the current collector material of the fast charging battery; The current response sequence and the voltage response sequence are time-aligned to obtain the electrochemical test signal of the current collector material of the fast-charging battery.

[0007] Preferably, the step of performing multi-scale wavelet decomposition on the electrochemical test signal based on the frequency characteristic distribution of the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal includes: Perform a discrete wavelet transform on the electrochemical test signal with a preset maximum number of decomposition layers to obtain the detail coefficients and approximation coefficients of the decomposition layers in the electrochemical test signal; Calculate the sum of squares and attenuation factor of the decomposition layer; The sum of squares attenuation factor is compared with a preset attenuation threshold to obtain the final number of decomposition layers of the electrochemical test signal; The detail coefficients and approximation coefficients of the final decomposition layer are used as the wavelet coefficients of the electrochemical test signal.

[0008] Preferably, the formula for calculating the sum of squares attenuation factor is as follows: ; in, Indicates the first Sum of squares and attenuation factor of the layer Indicates the first The sum of squares of the layer detail coefficients, Indicates the first The sum of squares of the layer detail coefficients.

[0009] Preferably, the step of determining the local threshold parameter of the wavelet coefficients based on the amplitude distribution characteristics of the wavelet coefficients, and performing soft thresholding on the wavelet coefficients based on the local threshold parameter to obtain the noise-reduced wavelet coefficients of the fast-charging battery current collector material includes: The detailed coefficients are divided into continuous coefficient sub-intervals in chronological order, and the local threshold parameters of the coefficient sub-intervals are determined based on the amplitude distribution of the coefficient sub-intervals. The absolute values ​​of the detail coefficients are compared and analyzed with the local threshold parameters to obtain new detail coefficients for the coefficient sub-intervals: If the absolute value is less than or equal to the local threshold parameter, then the detail coefficient is set to zero. If the absolute value is greater than the local threshold parameter, then the sign of the detail coefficient is retained, and the difference between the absolute value and the local threshold parameter is taken as the new amplitude of the detail coefficient; The new detail coefficients are combined with the approximation coefficients to form the noise-reduced wavelet coefficients of the current collector material of the fast-charging battery.

[0010] Preferably, determining the local threshold parameter of the coefficient sub-interval based on the amplitude distribution of the coefficient sub-interval includes: Extract the absolute values ​​of the detail coefficients within the coefficient sub-interval, and use half of the difference between the maximum and minimum values ​​of the absolute values ​​as the amplitude span reference value of the coefficient sub-interval; Arrange the amplitude span reference values ​​according to the magnitude of the absolute values ​​to obtain the median amplitude of the coefficient sub-interval; The smaller of the amplitude span reference value and the median amplitude is used as the local threshold parameter of the coefficient sub-interval.

[0011] Preferably, the step of performing wavelet reconstruction processing on the denoised wavelet coefficients to obtain the reconstructed electrochemical test signal of the fast-charging battery current collector material includes: Extract the highest-level approximation coefficients and the detail coefficients of the decomposition layer from the denoised wavelet coefficients; The highest-level approximation coefficients are upsampled by a factor of two, and the upsampled approximation coefficient sequence is then low-pass reconstructed to obtain the approximate components of the fast-charging battery current collector material. The detail coefficients of the current highest resolution layer are upsampled by a factor of two, and the upsampled detail coefficient sequence is then subjected to high-pass reconstruction filtering to obtain the detail components of the current collector material of the fast-charging battery. The approximate components and the detailed components are added point by point to obtain the reconstruction approximation coefficients of the current collector material of the fast charging battery; By integrating the reconstruction approximation coefficients of the decomposed layer, the reconstruction electrochemical test signal of the current collector material of the fast-charging battery is obtained.

[0012] Preferably, the step of extracting the interfacial impedance characteristics and charge transport characteristics of the fast-charging battery current collector material based on the reconstructed electrochemical test signal, wherein the interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient, including: The reconstructed current response sequence and the reconstructed voltage response sequence are separated from the reconstructed electrochemical test signal, and the reconstructed current response sequence and the reconstructed voltage response sequence are aligned according to time points to obtain the aligned current response sequence and aligned voltage response sequence of the fast charging battery current collector material; The ratio of the aligned current response sequence to the aligned voltage response sequence is used to obtain the ratio sequence of the current collector material of the fast-charging battery; Extract a continuous subsequence from the ratio sequence after the charging and discharging process enters a stable period, and use the average value of the continuous subsequence as the interface resistance of the current collector material of the fast charging battery; Numerical difference operations are performed on the aligned current response sequence and the aligned voltage response sequence to obtain the voltage change rate sequence and current change rate sequence of the current collector material of the fast charging battery. The ratio of the voltage change rate sequence to the current change rate sequence is used as the dynamic ratio sequence of the fast-charging battery current collector material, and the peak value of the dynamic ratio sequence corresponding to the charging and discharging start period is used as the interface capacitance of the fast-charging battery current collector material. Identify the current abrupt change point corresponding to the start of charging and discharging from the aligned current response sequence, record the current rise rate per unit time after the current abrupt change point, and use the current rise rate as the charge transfer rate of the current collector material of the fast charging battery. The aligned voltage response sequence is segmented and smoothed to obtain the voltage decay trend line of the fast-charging battery current collector material, and the absolute value of the slope of the voltage decay trend line is used as the diffusion coefficient of the fast-charging battery current collector material. The interface resistance and the interface capacitance are integrated into the interface impedance characteristics of the current collector material of the fast-charging battery. By combining the charge transfer rate and the diffusion coefficient, the charge transport characteristics of the current collector material of the fast-charging battery are obtained.

[0013] Preferably, evaluating the performance stability of the fast-charging battery current collector material under high-rate charge-discharge conditions based on the interfacial impedance characteristics and the charge transport characteristics includes: By comparing and analyzing the interface impedance characteristics and the charge transport characteristics, the performance variation trend of the current collector material of the fast-charging battery can be obtained. The interface impedance characteristics and charge transport characteristics are visualized to obtain the performance evaluation spectrum of the fast-charging battery current collector material. Data annotation is performed on the performance evaluation spectrum, and key performance nodes and performance inflection points are marked on the performance evaluation spectrum to obtain the annotated performance evaluation spectrum of the current collector material of the fast charging battery. Under high-rate charge and discharge conditions, the current collector material of the fast-charging battery is evaluated based on the labeled performance evaluation spectrum to obtain the performance stability of the current collector material of the fast-charging battery.

[0014] Furthermore, the present invention also provides a fast-charging battery current collector material analysis system based on wavelet denoising, comprising: The signal acquisition module is used to acquire electrochemical test signals of the current collector material of the fast-charging battery at different charge and discharge rates. The electrochemical test signals include current response signals and voltage response signals. The signal decomposition module is used to perform multi-scale wavelet decomposition on the electrochemical test signal based on the frequency characteristic distribution of the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal. The coefficient processing module is used to determine the local threshold parameters of the wavelet coefficients based on the amplitude distribution characteristics of the wavelet coefficients, and to perform soft thresholding on the wavelet coefficients based on the local threshold parameters to obtain the noise-reduced wavelet coefficients of the current collector material of the fast charging battery. The coefficient reconstruction module is used to perform wavelet reconstruction processing on the noise-reduced wavelet coefficients to obtain the reconstructed electrochemical test signal of the fast-charging battery current collector material. The feature extraction module is used to extract the interfacial impedance characteristics and charge transport characteristics of the current collector material of the fast-charging battery based on the reconstructed electrochemical test signal. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient. The performance evaluation module is used to evaluate the performance stability of the fast-charging battery current collector material under high-rate charge and discharge conditions based on the interface impedance characteristics and the charge transport characteristics.

[0015] The beneficial effects of this invention are as follows: 1. This invention utilizes wavelet noise reduction technology to efficiently process electrochemical test signals of current collector materials in fast-charging batteries. By precisely decomposing and thresholding the signal, it improves signal purity, directly enhancing the overall efficiency of material analysis and making the signal processing process more stable and efficient.

[0016] 2. This invention can quickly extract the core features of interface impedance and charge transport through the reconstructed accurate signal, efficiently complete the performance stability assessment under high-rate charge and discharge conditions, improve the credibility and practicality of the analysis results, and provide reliable support for the performance determination of current collector materials for fast-charging batteries. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for analyzing current collector materials in fast-charging batteries based on wavelet denoising, as described in this invention. Figure 2 This is a schematic diagram illustrating the functional modules of a fast-charging battery current collector material analysis system based on wavelet denoising in this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] This application provides a method for analyzing current collector materials in fast-charging batteries based on wavelet denoising. The execution entity of this method includes, but is not limited to, at least one electronic device configured to execute the method provided in this application, such as a server or a terminal. In other words, the method can be executed by software or hardware installed on a terminal device or server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cluster of cloud servers. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0020] Reference Figure 1 The diagram shown is a flowchart illustrating a method for analyzing current collector materials in fast-charging batteries based on wavelet denoising, according to an embodiment of the present invention. In this embodiment, the method for analyzing current collector materials in fast-charging batteries based on wavelet denoising includes: A. Acquire electrochemical test signals of the current collector material of a fast-charging battery at different charge / discharge rates, wherein the electrochemical test signals include current response signals and voltage response signals; In this embodiment of the invention, the electrochemical test signals of the current collector material of the fast-charging battery at different charge / discharge rates are obtained. These electrochemical test signals include current response signals and voltage response signals, comprising: Collect raw electrochemical data streams of current collector materials in fast-charging batteries at different charge / discharge rates; Extract the current response signal segment and voltage response signal segment within the steady-state response period from the original electrochemical data stream; Outlier detection is performed on the current response signal segment and the voltage response signal segment, and linear interpolation is performed on the detected current response signal segment and voltage response signal segment to obtain the current response sequence and voltage response sequence of the current collector material of the fast charging battery; The current response sequence and the voltage response sequence are time-aligned to obtain the electrochemical test signal of the current collector material of the fast-charging battery.

[0021] Experiments were conducted at different charge / discharge rates in accordance with the testing specifications for current collector materials of fast-charging batteries. All raw electrochemical data generated by the materials during the experiment were continuously collected throughout the process, forming a complete and continuous raw electrochemical data stream.

[0022] Based on the steady-state determination criteria of electrochemical testing, the original electrochemical data stream was checked segment by segment, and the data segments containing only the steady-state response period were accurately located and extracted. The current response signal segment and voltage response signal segment within the steady-state response period were then separated.

[0023] The current response signal segment and voltage response signal segment are traversed point by point. Data points that deviate from the normal data distribution range are identified as outliers and marked. For the marked outlier locations, linear interpolation calculations are performed using the normal data points adjacent to the outlier. The calculated values ​​are used to replace the outliers. After filling in the gaps, a continuous and complete current response sequence and voltage response sequence are formed.

[0024] By checking each data point of the current response sequence and voltage response sequence one by one according to the time axis scale, the time correspondence between the two sequences is adjusted so that the current data and voltage data at the same moment are completely consistent, and finally a time-consistent electrochemical test signal is formed.

[0025] The beneficial effects are that through the complete process of raw data acquisition, steady-state time period interception, outlier detection and linear interpolation filling, and time sequence alignment, pure and time-synchronized electrochemical test signals can be obtained, providing a reliable data foundation for subsequent wavelet denoising and feature extraction, avoiding interference from non-steady-state data, outlier data and time sequence deviations on the analysis results, and improving the accuracy and reliability of fast-charging battery current collector material analysis.

[0026] B. Based on the frequency characteristic distribution of the electrochemical test signal, perform multi-scale wavelet decomposition on the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal; In this embodiment of the invention, the step of performing multi-scale wavelet decomposition on the electrochemical test signal based on the frequency characteristic distribution of the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal includes: Perform a discrete wavelet transform on the electrochemical test signal with a preset maximum number of decomposition layers to obtain the detail coefficients and approximation coefficients of the decomposition layers in the electrochemical test signal; Calculate the sum of squares and attenuation factor of the decomposition layer; The sum of squares attenuation factor is compared with a preset attenuation threshold to obtain the final number of decomposition layers of the electrochemical test signal; The detail coefficients and approximation coefficients of the final decomposition layer are used as the wavelet coefficients of the electrochemical test signal.

[0027] The formula for calculating the sum of squares attenuation factor is as follows: ; in, Indicates the first Sum of squares and attenuation factor of the layer Indicates the first The sum of squares of the layer detail coefficients, Indicates the first The sum of squares of the layer detail coefficients.

[0028] The electrochemical test signal is subjected to discrete wavelet transform sequentially according to the preset maximum decomposition level. Each transform decomposes the signal into detail coefficients and approximation coefficients of the corresponding decomposition level, thus obtaining the detail coefficients and approximation coefficients of all decomposition levels under the preset maximum decomposition level.

[0029] The values ​​of all detail coefficients for each decomposition layer are statistically analyzed layer by layer. Each detail coefficient is squared and then summed to obtain the sum of squares for the corresponding layer. The sum of squares of the current layer is then divided by the sum of squares of the previous layer to obtain the sum of squares attenuation factor of the current decomposition layer.

[0030] The sum of squares of the detail coefficients is obtained by squaring each detail coefficient individually and then summing the results. The sum of squares attenuation factor is obtained by dividing the sum of squares of the detail coefficients by the sum of squares of the detail coefficients. The sum of squares attenuation factor is used to quantitatively reflect the degree of energy change between adjacent detail coefficients during wavelet decomposition. It can provide a direct numerical basis for determining the final decomposition level of the electrochemical test signal. As the number of decomposition levels increases, the sum of squares attenuation factor will gradually decrease. As the number of decomposition levels continues to increase, the rate of decrease in the sum of squares attenuation factor will gradually level off.

[0031] The sum of squares attenuation factor calculated for each layer is compared with the preset attenuation threshold. Decomposition layers with a sum of squares attenuation factor greater than the preset attenuation threshold are retained, while decomposition layers with a sum of squares attenuation factor less than or equal to the preset attenuation threshold are removed. The top layer retained is taken as the final decomposition layer number of the electrochemical test signal.

[0032] Extract all detail coefficients and approximation coefficients corresponding to the final decomposition level, and integrate these coefficients to form wavelet coefficients of the electrochemical test signal.

[0033] The beneficial effects are that by presetting the maximum number of decomposition layers, calculating the sum of squares attenuation factors and comparing with the threshold, the final number of decomposition layers can be determined. This can adapt to the frequency characteristic distribution of electrochemical test signals, avoid the problems of over-decomposition or under-decomposition, accurately obtain wavelet coefficients that can reflect the intrinsic characteristics of the signal, and provide a stable coefficient basis for subsequent threshold processing and signal reconstruction.

[0034] C. Based on the amplitude distribution characteristics of the wavelet coefficients, determine the local threshold parameters of the wavelet coefficients, and perform soft thresholding on the wavelet coefficients based on the local threshold parameters to obtain the noise-reduced wavelet coefficients of the current collector material of the fast charging battery. In this embodiment of the invention, the step of determining the local threshold parameter of the wavelet coefficients based on the amplitude distribution characteristics of the wavelet coefficients, and performing soft thresholding on the wavelet coefficients based on the local threshold parameter to obtain the noise-reduced wavelet coefficients of the fast-charging battery current collector material includes: The detailed coefficients are divided into continuous coefficient sub-intervals in chronological order, and the local threshold parameters of the coefficient sub-intervals are determined based on the amplitude distribution of the coefficient sub-intervals. The absolute values ​​of the detail coefficients are compared and analyzed with the local threshold parameters to obtain new detail coefficients for the coefficient sub-intervals: If the absolute value is less than or equal to the local threshold parameter, then the detail coefficient is set to zero. If the absolute value is greater than the local threshold parameter, then the sign of the detail coefficient is retained, and the difference between the absolute value and the local threshold parameter is taken as the new amplitude of the detail coefficient; The new detail coefficients are combined with the approximation coefficients to form the noise-reduced wavelet coefficients of the current collector material of the fast-charging battery.

[0035] Determining the local threshold parameter of the coefficient sub-interval based on the amplitude distribution of the coefficient sub-interval includes: Extract the absolute values ​​of the detail coefficients within the coefficient sub-interval, and use half of the difference between the maximum and minimum values ​​of the absolute values ​​as the amplitude span reference value of the coefficient sub-interval; Arrange the amplitude span reference values ​​according to the magnitude of the absolute values ​​to obtain the median amplitude of the coefficient sub-interval; The smaller of the amplitude span reference value and the median amplitude is used as the local threshold parameter of the coefficient sub-interval.

[0036] Divide the detail coefficients into continuous and non-overlapping coefficient sub-intervals in chronological order. Extract the absolute values ​​of all detail coefficients in each coefficient sub-interval one by one. Find the maximum and minimum values ​​of the absolute values ​​in the sub-interval. Subtract the minimum value from the maximum value to get the difference. Divide the difference by two to get the amplitude span reference value of the current coefficient sub-interval.

[0037] Arrange the absolute values ​​of all detail coefficients within the same coefficient sub-interval in ascending order, and find the value in the middle position after the arrangement as the median amplitude of that coefficient sub-interval.

[0038] Compare the amplitude span reference value and the median amplitude of the current coefficient sub-interval, and select the smaller value as the local threshold parameter of the current coefficient sub-interval.

[0039] Extract each detail coefficient within the coefficient sub-interval one by one, calculate the absolute value of the detail coefficient, and compare the calculated absolute value with the local threshold parameter of the current coefficient sub-interval.

[0040] When the absolute value of a detail coefficient is less than or equal to the local threshold parameter, the value of that detail coefficient is directly replaced with zero.

[0041] When the absolute value of a detail coefficient is greater than the local threshold parameter, the original sign of the detail coefficient remains unchanged. The difference is obtained by subtracting the local threshold parameter from the absolute value of the detail coefficient, and this difference is used as the new amplitude of the detail coefficient.

[0042] After processing all the detail coefficients, new detail coefficients corresponding to each coefficient sub-interval are obtained. All the new detail coefficients are integrated together and then merged with the approximate coefficients that have not undergone interval division and threshold processing to form the noise-reduced wavelet coefficients of the fast-charging battery current collector material.

[0043] The beneficial effect is that by dividing the coefficient sub-intervals according to time and combining the amplitude distribution to determine the local threshold parameters, and then carrying out targeted soft thresholding, the wavelet coefficients corresponding to noise can be accurately removed while retaining the effective details related to material properties. This improves the targeting and effectiveness of wavelet coefficient denoising and provides a high-quality coefficient foundation for subsequent electrochemical signal reconstruction.

[0044] D. Perform wavelet reconstruction processing on the denoised wavelet coefficients to obtain the reconstructed electrochemical test signal of the current collector material of the fast charging battery; In this embodiment of the invention, the step of performing wavelet reconstruction processing on the denoised wavelet coefficients to obtain the reconstructed electrochemical test signal of the fast-charging battery current collector material includes: Extract the highest-level approximation coefficients and the detail coefficients of the decomposition layer from the denoised wavelet coefficients; The highest-level approximation coefficients are upsampled by a factor of two, and the upsampled approximation coefficient sequence is then low-pass reconstructed to obtain the approximate components of the fast-charging battery current collector material. The detail coefficients of the current highest resolution layer are upsampled by a factor of two, and the upsampled detail coefficient sequence is then subjected to high-pass reconstruction filtering to obtain the detail components of the current collector material of the fast-charging battery. The approximate components and the detailed components are added point by point to obtain the reconstruction approximation coefficients of the current collector material of the fast charging battery; By integrating the reconstruction approximation coefficients of the decomposed layer, the reconstruction electrochemical test signal of the current collector material of the fast-charging battery is obtained.

[0045] The highest-level approximation coefficients and the detail coefficients corresponding to all decomposition layers are separated from the denoised wavelet coefficients.

[0046] A zero value is inserted between every two adjacent data points of the highest-level approximation coefficients to complete the upsampling operation. The upsampled approximation coefficient sequence is then processed point by point through a low-pass reconstruction filter to retain low-frequency components and remove high-frequency interference, thus forming the approximation components of the current collector material for fast-charging batteries.

[0047] A zero value is inserted between every two adjacent data points of the detail coefficients of the current highest decomposition layer to complete the upsampling operation. The upsampled detail coefficient sequence is then processed point by point through a high-pass reconstruction filter to retain high-frequency components and remove low-frequency interference, thus forming the detail components of the current collector material of the fast-charging battery.

[0048] The approximate components and the values ​​at the same position in the detail components are added one by one, and the sum of the sums at each position is combined to form the reconstruction approximation coefficients of the current collector material of the fast charging battery.

[0049] Following the hierarchical order of the decomposition layers, the above upsampling, filtering, and point-by-point addition operations are performed layer by layer. The reconstructed approximation coefficients obtained from all decomposition layers are then sequentially spliced ​​and integrated to finally form the reconstructed electrochemical test signal of the fast-charging battery current collector material.

[0050] The beneficial effect is that through the reconstruction process of hierarchical upsampling, channel filtering and point-by-point superposition, the electrochemical test signal without noise interference can be completely restored based on the wavelet coefficients after noise reduction, preserving the original frequency characteristics and numerical variation law of the signal, and providing accurate and reliable data support for subsequent extraction of interface impedance and charge transport characteristics.

[0051] E. Based on the reconstructed electrochemical test signal, extract the interfacial impedance characteristics and charge transport characteristics of the current collector material of the fast-charging battery. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient. In this embodiment of the invention, the interfacial impedance characteristics and charge transport characteristics of the fast-charging battery current collector material are extracted based on the reconstructed electrochemical test signal. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient, including: The reconstructed current response sequence and the reconstructed voltage response sequence are separated from the reconstructed electrochemical test signal, and the reconstructed current response sequence and the reconstructed voltage response sequence are aligned according to time points to obtain the aligned current response sequence and aligned voltage response sequence of the fast charging battery current collector material; The ratio of the aligned current response sequence to the aligned voltage response sequence is used to obtain the ratio sequence of the current collector material of the fast-charging battery; Extract a continuous subsequence from the ratio sequence after the charging and discharging process enters a stable period, and use the average value of the continuous subsequence as the interface resistance of the current collector material of the fast charging battery; Numerical difference operations are performed on the aligned current response sequence and the aligned voltage response sequence to obtain the voltage change rate sequence and current change rate sequence of the current collector material of the fast charging battery. The ratio of the voltage change rate sequence to the current change rate sequence is used as the dynamic ratio sequence of the fast-charging battery current collector material, and the peak value of the dynamic ratio sequence corresponding to the charging and discharging start period is used as the interface capacitance of the fast-charging battery current collector material. Identify the current abrupt change point corresponding to the start of charging and discharging from the aligned current response sequence, record the current rise rate per unit time after the current abrupt change point, and use the current rise rate as the charge transfer rate of the current collector material of the fast charging battery. The aligned voltage response sequence is segmented and smoothed to obtain the voltage decay trend line of the fast-charging battery current collector material, and the absolute value of the slope of the voltage decay trend line is used as the diffusion coefficient of the fast-charging battery current collector material. The interface resistance and the interface capacitance are integrated into the interface impedance characteristics of the current collector material of the fast-charging battery. By combining the charge transfer rate and the diffusion coefficient, the charge transport characteristics of the current collector material of the fast-charging battery are obtained.

[0052] Independent reconstructed current response sequences and reconstructed voltage response sequences are extracted from the reconstructed electrochemical test signals. Data points of the two sequences are matched one by one according to the same time scale, so that each time point corresponds to unique current and voltage data, forming aligned current response sequences and aligned voltage response sequences.

[0053] The values ​​of each data point in the aligned voltage response sequence are divided by the values ​​of the aligned current response sequence at the same time point, and all the calculation results are arranged in chronological order to form a ratio sequence.

[0054] Locate the period of stable charging and discharging operation in the ratio sequence, extract the continuous data subsequence within this period, add all the values ​​in the continuous subsequence and divide by the total number of data points, and use the average value as the interface resistance of the current collector material of the fast charging battery.

[0055] The difference between the values ​​at adjacent time points in the aligned voltage response sequence is calculated and the change amplitude is recorded to form a voltage change rate sequence. Similarly, the difference between the values ​​at adjacent time points in the aligned current response sequence is calculated and the change amplitude is recorded to form a current change rate sequence.

[0056] Divide the value of each data point in the voltage change rate sequence by the value of the current change rate sequence at the same time point. Arrange all the calculation results in time order to form a dynamic ratio sequence. Find the maximum value corresponding to the start of charging and discharging in the dynamic ratio sequence and use this peak value as the interface capacitance of the current collector material of the fast charging battery.

[0057] Traverse the aligned current response sequence, locate the position where the value changes abruptly at the start of charging and discharging as the current abrupt change point, and count the total change amplitude of the current value within a fixed unit time after the current abrupt change point. This amplitude value is used as the charge transfer rate of the current collector material of the fast charging battery.

[0058] The aligned voltage response sequence is divided into continuous data segments in chronological order. Each segment is smoothed and fitted to eliminate local fluctuations, forming a coherent voltage decay trend line. The slope of the voltage decay trend line is calculated, and the absolute value of the slope is taken as the diffusion coefficient of the current collector material of the fast-charging battery.

[0059] By combining interface resistance and interface capacitance according to their characteristic types, the interface impedance characteristics of the current collector material in fast-charging batteries can be formed.

[0060] By combining the charge transfer rate and diffusion coefficient according to characteristic types, the charge transport characteristics of the current collector material in fast-charging batteries can be formed.

[0061] The beneficial effects are that based on the reconstructed pure electrochemical signal, operations such as time alignment, ratio calculation, difference operation, and smooth fitting are completed. It can accurately extract four core parameters: interface resistance, interface capacitance, charge transfer rate, and diffusion coefficient, and fully construct the interface impedance characteristics and charge transport characteristics, so as to truly reflect the intrinsic electrochemical performance of the current collector material of fast charging battery.

[0062] F. Evaluate the performance stability of the fast-charging battery current collector material under high-rate charge and discharge conditions based on the interfacial impedance characteristics and the charge transport characteristics.

[0063] In this embodiment of the invention, evaluating the performance stability of the fast-charging battery current collector material under high-rate charge-discharge conditions based on the interface impedance characteristics and the charge transport characteristics includes: By comparing and analyzing the interface impedance characteristics and the charge transport characteristics, the performance variation trend of the current collector material of the fast-charging battery can be obtained. The interface impedance characteristics and charge transport characteristics are visualized to obtain the performance evaluation spectrum of the fast-charging battery current collector material. Data annotation is performed on the performance evaluation spectrum, and key performance nodes and performance inflection points are marked on the performance evaluation spectrum to obtain the annotated performance evaluation spectrum of the current collector material of the fast charging battery. Under high-rate charge and discharge conditions, the current collector material of the fast-charging battery is evaluated based on the labeled performance evaluation spectrum to obtain the performance stability of the current collector material of the fast-charging battery.

[0064] By comparing the parameters of the interface impedance characteristics and charge transport characteristics one by one at different charge and discharge rates, both horizontally and vertically, the variation patterns of the parameters with changes in charge and discharge conditions are analyzed, and the performance change trend of the current collector material of fast-charging batteries is formed.

[0065] The parameters of interface impedance and charge transport characteristics are transformed into intuitive graphs and curves, and presented according to unified coordinate and scale rules to form a performance evaluation map of fast-charging battery current collector materials.

[0066] Mark the key performance nodes with abnormal performance values ​​and significant changes at the corresponding positions on the performance evaluation map. At the same time, mark the performance inflection points where the direction of parameter change changes. After marking, the labeled performance evaluation map is obtained.

[0067] By combining the actual operating conditions of high-rate charging and discharging, and comparing the performance change trends, key performance nodes and performance inflection points in the marked performance evaluation chart, the fluctuation range and rationality of material parameters are comprehensively judged, and the performance stability of the current collector material of fast-charging battery is finally determined.

[0068] The beneficial effect is that through a complete process of data comparison and analysis, visualization, key node annotation and comprehensive judgment of the spectrum, the performance stability of fast-charging battery current collector materials under high-rate charge and discharge conditions can be evaluated intuitively, clearly and comprehensively, providing a clear and reliable evaluation basis for material screening and optimization.

[0069] like Figure 2 The diagram shown is a functional block diagram of a fast-charging battery current collector material analysis system based on wavelet denoising, provided in an embodiment of the present invention.

[0070] The wavelet-based noise reduction system for analyzing current collector materials in fast-charging batteries, as described in this invention, can be installed in electronic devices. Depending on the functions implemented, this system may include a signal acquisition module, a signal decomposition module, a coefficient processing module, a coefficient reconstruction module, a feature extraction module, and a performance evaluation module. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0071] In this embodiment, the functions of each module / unit are as follows: The signal acquisition module is used to acquire electrochemical test signals of the current collector material of the fast-charging battery at different charge and discharge rates. The electrochemical test signals include current response signals and voltage response signals. The signal decomposition module is used to perform multi-scale wavelet decomposition on the electrochemical test signal based on the frequency characteristic distribution of the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal. The coefficient processing module is used to determine the local threshold parameters of the wavelet coefficients according to the amplitude distribution characteristics of the wavelet coefficients, and to perform soft thresholding on the wavelet coefficients based on the local threshold parameters to obtain the noise-reduced wavelet coefficients of the current collector material of the fast charging battery. The coefficient reconstruction module is used to perform wavelet reconstruction processing on the noise-reduced wavelet coefficients to obtain the reconstructed electrochemical test signal of the fast-charging battery current collector material. The feature extraction module is used to extract the interfacial impedance characteristics and charge transport characteristics of the current collector material of the fast-charging battery based on the reconstructed electrochemical test signal. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient. The performance evaluation module is used to evaluate the performance stability of the fast-charging battery current collector material under high-rate charge and discharge conditions based on the interface impedance characteristics and the charge transport characteristics.

[0072] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0073] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0074] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0075] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0076] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for analyzing current collector materials in fast-charging batteries based on wavelet denoising, characterized in that, The method includes: A. Acquire electrochemical test signals of the current collector material of a fast-charging battery at different charge / discharge rates, wherein the electrochemical test signals include current response signals and voltage response signals; B. Based on the frequency characteristic distribution of the electrochemical test signal, perform multi-scale wavelet decomposition on the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal; C. Based on the amplitude distribution characteristics of the wavelet coefficients, determine the local threshold parameters of the wavelet coefficients, and perform soft thresholding on the wavelet coefficients based on the local threshold parameters to obtain the noise-reduced wavelet coefficients of the current collector material of the fast charging battery. D. Perform wavelet reconstruction processing on the denoised wavelet coefficients to obtain the reconstructed electrochemical test signal of the current collector material of the fast charging battery; E. Based on the reconstructed electrochemical test signal, extract the interfacial impedance characteristics and charge transport characteristics of the current collector material of the fast-charging battery. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient. F. Evaluate the performance stability of the fast-charging battery current collector material under high-rate charge and discharge conditions based on the interfacial impedance characteristics and the charge transport characteristics.

2. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 1, characterized in that, The method involves acquiring electrochemical test signals of the current collector material of a fast-charging battery at different charge / discharge rates. These electrochemical test signals include current response signals and voltage response signals, comprising: Collect raw electrochemical data streams of current collector materials in fast-charging batteries at different charge / discharge rates; Extract the current response signal segment and voltage response signal segment within the steady-state response period from the original electrochemical data stream; Outlier detection is performed on the current response signal segment and the voltage response signal segment, and linear interpolation is performed on the detected current response signal segment and voltage response signal segment to obtain the current response sequence and voltage response sequence of the current collector material of the fast charging battery; The current response sequence and the voltage response sequence are time-aligned to obtain the electrochemical test signal of the current collector material of the fast-charging battery.

3. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 1, characterized in that, The process of performing multi-scale wavelet decomposition on the electrochemical test signal based on its frequency characteristic distribution to obtain the wavelet coefficients of the electrochemical test signal includes: Perform a discrete wavelet transform on the electrochemical test signal with a preset maximum number of decomposition layers to obtain the detail coefficients and approximation coefficients of the decomposition layers in the electrochemical test signal; Calculate the sum of squares and attenuation factor of the decomposition layer; The sum of squares attenuation factor is compared with a preset attenuation threshold to obtain the final number of decomposition layers of the electrochemical test signal; The detail coefficients and approximation coefficients of the final decomposition layer are used as wavelet coefficients of the electrochemical test signal.

4. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 3, characterized in that, The formula for calculating the sum of squares attenuation factor is as follows: ； in, Indicates the first Sum of squares and attenuation factor of the layer Indicates the first The sum of squares of the layer detail coefficients, Indicates the first The sum of squares of the layer detail coefficients.

5. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 3, characterized in that, The step of determining the local threshold parameters of the wavelet coefficients based on their amplitude distribution characteristics, and then performing soft thresholding on the wavelet coefficients based on these local threshold parameters to obtain the noise-reduced wavelet coefficients of the fast-charging battery current collector material includes: The detailed coefficients are divided into continuous coefficient sub-intervals in chronological order, and the local threshold parameters of the coefficient sub-intervals are determined based on the amplitude distribution of the coefficient sub-intervals. The absolute values ​​of the detail coefficients are compared and analyzed with the local threshold parameters to obtain new detail coefficients for the coefficient sub-intervals: If the absolute value is less than or equal to the local threshold parameter, then the detail coefficient is set to zero. If the absolute value is greater than the local threshold parameter, then the sign of the detail coefficient is retained, and the difference between the absolute value and the local threshold parameter is taken as the new amplitude of the detail coefficient; The new detail coefficients are combined with the approximation coefficients to form the noise-reduced wavelet coefficients of the current collector material of the fast-charging battery.

6. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 5, characterized in that, Determining the local threshold parameter of the coefficient sub-interval based on the amplitude distribution of the coefficient sub-interval includes: Extract the absolute values ​​of the detail coefficients within the coefficient sub-interval, and use half of the difference between the maximum and minimum values ​​of the absolute values ​​as the amplitude span reference value of the coefficient sub-interval; Arrange the amplitude span reference values ​​according to the magnitude of the absolute values ​​to obtain the median amplitude of the coefficient sub-interval; The smaller of the amplitude span reference value and the median amplitude is used as the local threshold parameter of the coefficient sub-interval.

7. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 1, characterized in that, The step of performing wavelet reconstruction processing on the denoised wavelet coefficients to obtain the reconstructed electrochemical test signal of the fast-charging battery current collector material includes: Extract the highest-level approximation coefficients and the detail coefficients of the decomposition layer from the denoised wavelet coefficients; The highest-level approximation coefficients are upsampled by a factor of two, and the upsampled approximation coefficient sequence is then low-pass reconstructed to obtain the approximate components of the fast-charging battery current collector material. The detail coefficients of the current highest resolution layer are upsampled by a factor of two, and the upsampled detail coefficient sequence is then subjected to high-pass reconstruction filtering to obtain the detail components of the current collector material of the fast-charging battery. The approximate components and the detailed components are added point by point to obtain the reconstruction approximation coefficients of the current collector material of the fast charging battery; By integrating the reconstruction approximation coefficients of the decomposed layer, the reconstruction electrochemical test signal of the current collector material of the fast-charging battery is obtained.

8. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 1, characterized in that, Based on the reconstructed electrochemical test signal, the interfacial impedance characteristics and charge transport characteristics of the fast-charging battery current collector material are extracted. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient, including: The reconstructed current response sequence and the reconstructed voltage response sequence are separated from the reconstructed electrochemical test signal, and the reconstructed current response sequence and the reconstructed voltage response sequence are aligned according to time points to obtain the aligned current response sequence and aligned voltage response sequence of the fast charging battery current collector material; The ratio of the aligned current response sequence to the aligned voltage response sequence is used to obtain the ratio sequence of the current collector material of the fast-charging battery; Extract a continuous subsequence from the ratio sequence after the charging and discharging process enters a stable period, and use the average value of the continuous subsequence as the interface resistance of the current collector material of the fast charging battery; Numerical difference operations are performed on the aligned current response sequence and the aligned voltage response sequence to obtain the voltage change rate sequence and current change rate sequence of the current collector material of the fast charging battery. The ratio of the voltage change rate sequence to the current change rate sequence is used as the dynamic ratio sequence of the fast-charging battery current collector material, and the peak value of the dynamic ratio sequence corresponding to the charging and discharging start period is used as the interface capacitance of the fast-charging battery current collector material. Identify the current abrupt change point corresponding to the start of charging and discharging from the aligned current response sequence, record the current rise rate per unit time after the current abrupt change point, and use the current rise rate as the charge transfer rate of the current collector material of the fast charging battery. The aligned voltage response sequence is segmented and smoothed to obtain the voltage decay trend line of the fast-charging battery current collector material, and the absolute value of the slope of the voltage decay trend line is used as the diffusion coefficient of the fast-charging battery current collector material. The interface resistance and the interface capacitance are integrated into the interface impedance characteristics of the current collector material of the fast-charging battery. By combining the charge transfer rate and the diffusion coefficient, the charge transport characteristics of the current collector material of the fast-charging battery are obtained.

9. The method for analyzing current collector materials in fast-charging batteries based on wavelet denoising as described in claim 1, characterized in that, The evaluation of the performance stability of the fast-charging battery current collector material under high-rate charge-discharge conditions based on the interfacial impedance characteristics and the charge transport characteristics includes: By comparing and analyzing the interface impedance characteristics and the charge transport characteristics, the performance variation trend of the current collector material of the fast-charging battery can be obtained. The interface impedance characteristics and charge transport characteristics are visualized to obtain the performance evaluation spectrum of the fast-charging battery current collector material. Data annotation is performed on the performance evaluation spectrum, and key performance nodes and performance inflection points are marked on the performance evaluation spectrum to obtain the annotated performance evaluation spectrum of the fast charging battery current collector material. Under high-rate charge and discharge conditions, the current collector material of the fast-charging battery is evaluated based on the labeled performance evaluation spectrum to obtain the performance stability of the current collector material of the fast-charging battery.

10. A fast-charging battery current collector material analysis system based on wavelet denoising, characterized in that, The system for implementing the wavelet denoising-based fast-charging battery current collector material analysis method of claim 1 includes: The signal acquisition module is used to acquire electrochemical test signals of the current collector material of the fast-charging battery at different charge and discharge rates. The electrochemical test signals include current response signals and voltage response signals. The signal decomposition module is used to perform multi-scale wavelet decomposition on the electrochemical test signal based on the frequency characteristic distribution of the electrochemical test signal to obtain the wavelet coefficients of the electrochemical test signal. The coefficient processing module is used to determine the local threshold parameters of the wavelet coefficients according to the amplitude distribution characteristics of the wavelet coefficients, and to perform soft thresholding on the wavelet coefficients based on the local threshold parameters to obtain the noise-reduced wavelet coefficients of the current collector material of the fast charging battery. The coefficient reconstruction module is used to perform wavelet reconstruction processing on the noise-reduced wavelet coefficients to obtain the reconstructed electrochemical test signal of the fast-charging battery current collector material. The feature extraction module is used to extract the interfacial impedance characteristics and charge transport characteristics of the current collector material of the fast-charging battery based on the reconstructed electrochemical test signal. The interfacial impedance characteristics include interfacial resistance and interfacial capacitance, and the charge transport characteristics include charge transfer rate and diffusion coefficient. The performance evaluation module is used to evaluate the performance stability of the fast-charging battery current collector material under high-rate charge and discharge conditions based on the interface impedance characteristics and the charge transport characteristics.

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