CN-121978563-A - Battery EIS measurement method based on internal short circuit sensitive frequency band optimization

CN121978563ACN 121978563 ACN121978563 ACN 121978563ACN-121978563-A

Abstract

The invention relates to the technical field of battery measurement, and discloses a battery EIS measurement method based on internal short-circuit sensitive frequency band optimization, which is used for solving the problem that a real sensitive frequency band can change when battery measurement is carried out, and comprises the steps of obtaining sensitive frequency band influence parameters of batteries corresponding to each internal short-circuit sensitive frequency band, calculating according to the sensitive frequency band influence parameters to obtain frequency band influence indexes, and judging whether the internal short-circuit sensitive frequency band needs to be adjusted according to the frequency band influence index, if so, adjusting the starting frequency and the ending frequency of the internal short-circuit sensitive frequency band according to the frequency band influence index to obtain an adjusted internal short-circuit sensitive frequency band, traversing all the internal short-circuit sensitive frequency bands in the internal short-circuit sensitive frequency band set to obtain an adjusted internal short-circuit sensitive frequency band set, and effectively improving the accuracy of internal short-circuit judgment.

Inventors

LI YUNPENG
WANG ZHAO
YU WEIFENG
YU XUEYING
HAN JUNWEN
CHEN YIBIN
XI ZHEN

Assignees

广东汽车检测中心有限公司
中南大学

Dates

Publication Date: 20260505
Application Date: 20251217

Claims (10)

1. The battery EIS measurement method based on the internal short circuit sensitive frequency band optimization is characterized by comprising the following steps of; Step 1, respectively constructing a normal state sample and a plurality of different internal short circuit resistance samples aiming at a battery of a target model, and executing a conventional electrochemical impedance spectrum test to obtain impedance data corresponding to a normal state and impedance data corresponding to different internal short circuit states; Step 2, according to preset test frequency, respectively obtaining impedance data corresponding to a normal state and impedance values under each test frequency of impedance data corresponding to an internal short-circuit state for each different internal short-circuit state, calculating relative deviation values of the impedance data corresponding to the normal state and the internal short-circuit state for the same test frequency point, obtaining relative deviation values of all test frequency points, obtaining internal short-circuit sensitive frequency bands according to the relative deviation values of all test frequency points, and summarizing the internal short-circuit sensitive frequency bands of each different internal short-circuit state to obtain an internal short-circuit sensitive frequency band set; Step 3, acquiring sensitive frequency band influence parameters of a battery corresponding to each internal short-circuit sensitive frequency band, wherein the sensitive frequency band influence parameters comprise a battery shell surface temperature measurement value, a battery shell outer surface variable measurement value and a battery core compression structure compression force measurement value, calculating according to the sensitive frequency band influence parameters to obtain a frequency band influence index, and judging whether the internal short-circuit sensitive frequency band needs to be adjusted according to the frequency band influence index; Step 4, if the internal short-circuit sensitive frequency band is judged to need to be adjusted, adjusting the initial frequency and the termination frequency of the internal short-circuit sensitive frequency band according to the frequency band influence index to obtain an adjusted internal short-circuit sensitive frequency band, traversing all internal short-circuit sensitive frequency bands in the internal short-circuit sensitive frequency band set, and obtaining an adjusted internal short-circuit sensitive frequency band set; Step 5, obtaining the representative sensitivity of each internal short-circuit sensitive frequency band in the adjusted internal short-circuit sensitive frequency band set, and constructing and obtaining a frequency weighting function according to the representative sensitivity of the internal short-circuit sensitive frequency band; step 6, obtaining the minimum frequency and the maximum frequency of the adjusted internal short-circuit sensitive frequency band set, determining the clock frequency and the sequence length of the pseudo-random binary sequence according to the minimum frequency and the maximum frequency, and generating a pseudo-random excitation signal through the pseudo-random binary sequence; Step 7, optimizing and adjusting the pseudo-random excitation signal according to the frequency weighting function to obtain an optimized pseudo-random excitation signal; Step 8, applying small-amplitude current disturbance to the battery by adopting the optimized pseudo-random excitation signal, collecting a response signal of the battery, carrying out frequency domain analysis on the optimized pseudo-random excitation signal and the response signal, and calculating complex impedance of each test frequency point; and 9, calculating the difference value between the complex impedance of each frequency point and the reference impedance corresponding to the normal state to obtain the impedance difference value of each frequency point, and judging whether the current battery has an internal short circuit or not according to the impedance difference value of each frequency point.
2. The method for measuring the EIS of the battery based on the optimization of the internal short-circuit sensitive frequency band of claim 1, wherein the step of obtaining the internal short-circuit sensitive frequency band is as follows: for the same frequency point, acquiring the impedance value of the normal state and the impedance value of the internal short circuit state, calculating the absolute difference value between the impedance value of the internal short circuit state and the impedance value of the normal state, dividing the absolute value of the impedance value of the normal state by the absolute value of the impedance value of the normal state to obtain the relative deviation value of the frequency point, and recording the relative deviation value as the sensitivity of the frequency point; Acquiring the sensitivity of all frequency points, comparing the sensitivity with a sensitivity threshold, screening out all frequency points which are larger than or equal to the sensitivity threshold, and classifying the frequency points with adjacent frequency differences smaller than a preset frequency interval into the same frequency point set; And for each frequency point set, acquiring the minimum frequency and the maximum frequency in the frequency point set, and forming an internal short-circuit sensitive frequency band by the minimum frequency and the maximum frequency.
3. The battery EIS measurement method based on internal short-circuit sensitive frequency band optimization according to claim 1, wherein the step of obtaining the frequency band influence index is: Obtaining a measured value of the surface temperature of the battery shell, and calculating to obtain a surface thermal disturbance coefficient according to the measured value of the surface temperature of the battery shell; Obtaining a battery shell outer surface variable measurement value, and calculating according to the battery shell outer surface variable measurement value to obtain an electrode respiratory coupling coefficient; Obtaining a compression force measurement value of the cell compression structure, and calculating to obtain a compression force offset coefficient according to the compression force measurement value of the cell compression structure; And carrying out normalization processing on the surface thermal disturbance coefficient, the electrode respiratory coupling coefficient and the compression force offset coefficient, and calculating to obtain a frequency band influence index according to the normalized surface thermal disturbance coefficient, the normalized electrode respiratory coupling coefficient and the normalized compression force offset coefficient.
4. The battery EIS measurement method based on internal short-circuit sensitive frequency band optimization according to claim 3, wherein the surface thermal disturbance coefficient obtaining step is as follows: acquiring temperature measurement values of a plurality of temperature sampling points on the outer surface of the battery shell, wherein the temperature measurement values comprise surface temperatures of the surface of the battery shell at different spatial positions at the same sampling moment to form a surface temperature matrix; for any two adjacent temperature sampling points in the surface temperature matrix, calculating the absolute value of the temperature difference, and carrying out cumulative summation on the absolute values of the temperature differences of all the adjacent temperature sampling points to obtain the total amount of the space temperature difference at the current moment; dividing the total space temperature difference by the number of temperature sampling points to obtain a dynamic thermal gradient value at the current moment; In a preset time window, dynamic thermal gradient values at all sampling moments are obtained, the maximum value and the minimum value of the dynamic thermal gradient values in the preset time window are selected, and difference value calculation is carried out on the maximum value and the minimum value to obtain thermal disturbance amplitude; and carrying out average value calculation on the dynamic thermal gradient values at all sampling moments in a preset time window to obtain an average dynamic thermal gradient value, and dividing the thermal disturbance amplitude by the average dynamic thermal gradient value to obtain a surface thermal disturbance coefficient.
5. The method for measuring the EIS of the battery based on the optimization of the internal short-circuit sensitive frequency band according to claim 3, wherein the step of obtaining the respiratory coupling coefficient of the electrode is as follows: in a preset time window, obtaining deformation measurement values of a plurality of deformation measurement points distributed on the outer surface of the battery shell at each sampling moment to form a deformation measurement matrix; For the deformation measurement matrix, at each sampling moment, carrying out arithmetic average on deformation measurement values of all measurement points at the sampling moment to obtain an equivalent deformation value at the sampling moment; obtaining equivalent deformation values at all sampling moments in a preset time window, respectively selecting the maximum value and the minimum value of the equivalent deformation values in the time window, and performing difference value calculation on the maximum value and the minimum value to obtain the breathing amplitude of the battery; performing average value calculation on equivalent deformation values at all sampling moments in a preset time window to obtain a reference deformation; Dividing the respiration amplitude of the battery by the reference deformation quantity to obtain the respiration coupling coefficient of the electrode.
6. The method for measuring the EIS of the battery based on the optimization of the internal short-circuit sensitive frequency band according to claim 3, wherein the step of obtaining the compression force offset coefficient is as follows: acquiring a compaction force measurement value of a plurality of compaction force measurement points distributed in a cell compaction structure at each sampling time in a preset time window to form a compaction force measurement matrix; Average calculation is carried out on the compression force measured values of all sampling moments and all compression force measuring points in the compression force measuring matrix, so as to obtain a compression force steady-state reference value; For each compression force measurement value in the compression force measurement matrix, calculating the absolute value of the difference between the measurement value and the compression force steady-state reference value, and dividing the total number of the compression force measurement values by the total number of all the absolute values of the difference after accumulation and summation to obtain the compression force disturbance quantity; Dividing the compacting force disturbance quantity by a compacting force steady-state reference value to obtain a compacting force offset coefficient.
7. The method for measuring the EIS of the battery based on the optimization of the internal short-circuit sensitive frequency band of claim 1, wherein the step of judging whether the internal short-circuit sensitive frequency band needs to be adjusted according to the frequency band influence index is as follows: And comparing the frequency band influence index with a frequency band influence threshold, if the frequency band influence index is larger than or equal to the frequency band influence threshold, judging that the internal short circuit sensitive frequency band needs to be adjusted, and if the frequency band influence index is smaller than the frequency band influence threshold, judging that the internal short circuit sensitive frequency band does not need to be adjusted.
8. The method for measuring the EIS of the battery based on the optimization of the internal short-circuit sensitive frequency band of claim 7, wherein the step of acquiring the adjusted internal short-circuit sensitive frequency band set is as follows: for each sensitive frequency band in the internal short-circuit sensitive frequency band set, respectively acquiring the initial frequency and the termination frequency of the sensitive frequency band, recording the initial frequency and the initial termination frequency, and simultaneously acquiring the frequency band influence index and the corresponding frequency band influence threshold value of the sensitive frequency band; For each internal short circuit sensitive frequency band, dividing the frequency band influence index by a frequency band influence threshold value to obtain an adjustment coefficient; when the frequency band influence index is greater than or equal to the frequency band influence threshold, acquiring a preset frequency step length, subtracting the product of the adjustment coefficient and the preset frequency step length from the initial frequency to obtain an actual initial frequency; When the frequency band influence index is smaller than the frequency band influence threshold, adding 1 to the initial starting frequency to subtract the product of the adjustment coefficient and the preset frequency step length to obtain the actual starting frequency; When the initial frequency adjustment direction is different from the final frequency adjustment direction, namely the actual initial frequency is greater than or equal to the actual final frequency in the expansion or contraction process, marking the sensitive frequency band as an invalid frequency band and removing the invalid frequency band from the sensitive frequency band set; and recombining the adjusted initial frequency and the termination frequency of all the sensitive frequency bands according to the original frequency band sequence to obtain an adjusted internal short-circuit sensitive frequency band set.
9. The method for measuring the EIS of the battery based on the internal short-circuit sensitive frequency band optimization of claim 1, wherein the step of obtaining the frequency weighting function is as follows: normalizing the representative sensitivity of each internal short-circuit sensitive frequency band to obtain normalized representative sensitivity of each internal short-circuit sensitive frequency band, calculating the reciprocal of each normalized representative sensitivity, and adding the normalized representative sensitivity and the corresponding reciprocal to obtain a segmentation weighting coefficient of the internal short-circuit sensitive frequency band; For each test frequency point in the test frequency range, judging whether the test frequency point falls into the frequency range of any internal short-circuit sensitive frequency band, if so, setting the weight of the test frequency point as a segmentation weighting coefficient corresponding to the internal short-circuit sensitive frequency band, and if not, setting the weight of the test frequency point as the minimum value in all segmentation weighting coefficients; the method comprises the steps of respectively obtaining a frequency value and a corresponding weight of each test frequency point, forming a frequency-weight mapping pair by the test frequency point and the weight thereof, and arranging all the mapping pairs according to the increasing sequence of the frequency values; The frequency weighting function covering the test frequency range is constructed with all the "frequency-weight" mapping pairs arranged as inputs.
10. The method for measuring the EIS of the battery based on the optimization of the internal short-circuit sensitive frequency band of claim 1, wherein the step of judging whether the internal short circuit exists in the current battery according to the impedance difference value of each frequency point is as follows: Comparing the impedance difference value of each frequency point with an impedance threshold value, screening to obtain frequency points with the impedance difference value being greater than or equal to the impedance threshold value, marking the frequency points as internal short circuit frequency points, judging that the current battery has internal short circuits if the internal short circuit frequency points are greater than or equal to the frequency point number threshold value, and judging that the current battery has no internal short circuits if the internal short circuit frequency points are smaller than the frequency point number threshold value.

Description

Battery EIS measurement method based on internal short circuit sensitive frequency band optimization Technical Field The invention relates to the technical field of battery measurement, in particular to a battery EIS measurement method based on internal short circuit sensitive frequency band optimization. Background Along with the wide application of the high specific energy density battery in an energy storage system, an electric automobile and portable equipment, the accurate evaluation of the internal safety state of the battery becomes an important link for guaranteeing the stable operation of the system. Among them, a slight internal short circuit is a potential risk of being hidden and possibly evolving into a serious safety accident, and its early recognition ability directly affects the safety management level of the battery. Electrochemical Impedance Spectroscopy (EIS), which reflects the electrochemical reaction kinetics and transmission behavior of a battery, is widely used to study the internal state of a battery, and is one of the important means for identifying internal anomalies. Existing EIS tests typically apply an excitation signal over a wide frequency range, identifying possible internal short-circuit characteristics by calculating complex impedance at different frequencies and analyzing their trend of variation. In order to improve the sensitivity of detection, the industry generally adopts a "sensitive frequency band identification" manner, i.e. a specific frequency interval with obvious influence on internal short circuit is selected, and the impedance change of the frequency range is focused in the subsequent diagnosis process. The common method is that the impedance difference between the normal state and the abnormal state is obtained under a single working condition, a plurality of frequency points sensitive to internal short circuits are obtained through threshold value screening, and then a sensitive frequency band is constructed based on the frequency points for subsequent abnormal recognition. However, the above technology has at least the following technical problems: However, in practical application, the battery may undergo various state changes during operation, and there are differences in impedance behaviors under different operation conditions, so that the sensitive frequency band obtained by the original method may not be stable during practical detection. When the sensitive frequency band cannot truly reflect the impedance sensitivity in the current test state, the accuracy of the internal short circuit judgment based on the frequency band can be reduced, and the early recognition capability of slight abnormality is affected. Disclosure of Invention In order to overcome the defects in the prior art, the invention provides a battery EIS measurement method based on internal short circuit sensitive frequency band optimization, which aims to solve the problems in the background art. In order to achieve the above purpose, the present invention provides the following technical solutions: A battery EIS measurement method based on internal short circuit sensitive frequency band optimization comprises the following steps of 1, respectively constructing a normal state sample and a plurality of different internal short circuit resistance value samples for a target type battery, executing a conventional electrochemical impedance spectrum test, obtaining impedance data corresponding to the normal state and impedance data corresponding to different internal short circuit states, 2, respectively obtaining impedance values under each test frequency of the impedance data corresponding to the normal state and the impedance data corresponding to the internal short circuit state according to preset test frequencies, calculating relative offset values of the impedance values and the impedance values of the impedance data corresponding to the internal short circuit states, obtaining relative offset values of all test frequency points, obtaining an internal short circuit sensitive frequency band according to the relative offset values of all test frequency points, summarizing internal short circuit sensitive frequency bands in different internal short circuit states to obtain an internal short circuit sensitive frequency band set, 3, obtaining sensitive frequency band influence parameters of the battery corresponding to each internal short circuit sensitive frequency band, wherein the sensitive frequency band influence parameters comprise a battery shell surface temperature measurement value, a battery shell surface variable measurement value and a battery core pressing structure pressing force measurement value, calculating a frequency band influence index according to the preset test frequency, judging whether the frequency band influence index is needed to be regulated according to the sensitive frequency band influence index, and judging whether the internal short circuit frequency band