A battery local reaction abnormality detection method based on magnetic field change direction difference

Abstract

A method for detecting local anomalies in battery reactions based on differences in the direction of magnetic field changes belongs to the field of battery testing technology. This method acquires spatial distribution images of the magnetic fields of a standard reference battery and a target battery under test, extracts the gradient direction vector fields of local magnetic field changes in the X and Y directions, and constructs a consistency map of the angles between these direction vector fields. This allows for the identification of reorganization or perturbation phenomena of the reaction path in the target battery within a local spatial region. This method does not rely on global mean or template libraries but instead makes point-by-point judgments based on the similarity of spatial directional structures, possessing advantages such as strong physical interpretability, clear anomaly localization, and high adaptability. By utilizing the distribution of directional structural differences, the distribution of local anomaly features can be visualized and analyzed, and combined with spatial morphology, it can be used to infer the type of perturbation and potential mechanisms. This invention is applicable to multiple application scenarios such as battery consistency assessment, process defect identification, electrode aging tracking, and cell structure design optimization.

Description

Technical Field

[0001] This invention belongs to the field of battery testing technology, specifically relating to a method for detecting local abnormal reactions in batteries based on differences in the direction of magnetic field changes. Background Technology

[0002] Lithium-ion batteries are now widely used in consumer electronics, new energy vehicles, and energy storage systems, and their performance, safety, and consistency are of great concern. During charging and discharging, batteries inevitably exhibit non-uniform reaction behavior, especially under conditions of material inconsistency, complex structural design, or localized stress and thermal disturbance. This can easily lead to spatial heterogeneity phenomena such as enhanced local reactions, polarization accumulation, and hot spot formation. These non-uniform behaviors may cause battery performance fluctuations in the short term, and in the long term, may induce localized failures or even thermal runaway. The ability to identify and control these non-uniform reactions has become a core issue in the selection and design optimization of high-quality batteries.

[0003] Current battery status assessments primarily rely on monitoring single-point or global parameters such as overall voltage, current, and temperature, which struggles to capture the dynamic evolution of localized reactions within the battery. Indicators such as voltage plateaus, internal resistance changes, and electrochemical impedance spectroscopy (EIS), while indirectly reflecting certain performance trends, lack the ability to resolve non-uniform spatial distributions, making them unsuitable for early anomaly identification or operational adjustment capability assessment. Furthermore, some spatial resolution methods, such as X-ray, thermal imaging, or neutron imaging, suffer from limitations such as high cost, low throughput, or inability to be integrated into mass production processes. Therefore, a novel method for detecting localized anomalies is urgently needed, combining spatial resolution, dynamic response sensitivity, and engineering feasibility to support cell optimization design, in-situ detection, and fault tracing. Summary of the Invention

[0004] To overcome the shortcomings of the prior art, this invention provides a method for detecting local anomalies in battery reactions based on differences in the direction of magnetic field changes. This method, based on non-invasive magnetic field detection, constructs a direction vector field of magnetic field changes and compares it with a standard reference battery. This enables spatial localization and visual judgment of reaction path anomalies caused by internal current density redistribution. It overcomes the problems of traditional methods, such as reliance on global amplitude, lack of spatial direction resolution, and insensitivity to weak local disturbances. This significantly improves the ability to distinguish structural anomalies within the battery and has stronger physical interpretability and versatility.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for detecting localized abnormal reactions in batteries based on differences in the direction of magnetic field changes includes the following steps:

[0007] Step 1: Under constant current conditions, acquire magnetic field distribution data of the standard reference battery and the target battery under test at different times during operation. , and Based on the initial reference state Calculate the change in magnetic field distribution at each time point. Furthermore, the vector magnitude of the change in magnetic field distribution is calculated. This is used to map the spatial dynamic changes of non-uniform reactions within the battery electrode plane, where , 1 represents the standard reference battery, 2 represents the target battery to be tested, the xy direction is the direction of the battery's length and width plane, and the z direction is the direction of the battery's thickness perpendicular to the length and width plane;

[0008] Step 2: Measure the vector magnitude of the magnetic field distribution change of the standard reference battery and the target battery under test. exist and Directional derivatives are calculated in each direction to construct the direction vector fields of the standard reference cell and the target cell under test. and The direction vector field is used to represent the local trend of the direction of magnetic field change;

[0009] Step 3: For each spatial location point The cosine difference of the angle between the direction vectors of the standard reference battery and the target battery under test is calculated, and the directional structural difference distribution is constructed:

[0010] Its numerical range is 0-2;

[0011] Step 4: Based on the distribution of directional structural differences The location and morphology of the medium- and high-value areas are used to determine whether the target battery under test has local abnormal reactions and its spatial distribution characteristics: (1) If at a certain moment This indicates that the directions of current change in the two batteries at that point are completely consistent, and there is no abnormality; (2) If at a certain moment This indicates that the difference in the direction of current change between the two batteries at this point is less than 90°, that is, there is a slight abnormal reaction; (3) if at a certain moment This indicates that the difference in the direction of current change between the two batteries at this point is greater than or equal to 90°, indicating a strong abnormal reaction; (4) If at a certain moment This indicates that the current change direction of the two batteries at that point is reversed by 180°, which is very likely to cause severe local degradation or failure.

[0012] Step 5: Plot the distribution of directional structural differences based on different test time points. The evolution trend of current change path of the target battery under test relative to the standard reference battery during operation is analyzed.

[0013] Furthermore, in step two, the method for calculating the magnitude of the magnetic field distribution change vector is as follows:

[0014] .

[0015] Furthermore, in step two, the derivative calculation is implemented using a two-dimensional Sobel convolution operator, which has advantages in direction enhancement and noise suppression. Specifically, the following convolution kernel is used:

[0016] ,

[0017] The directional derivatives obtained after the convolution operation are as follows:

[0018] ,

[0019] Furthermore, the standard reference battery and the target battery under test construct a direction vector field. and Constructed using the following normalization formula:

[0020]

[0021] Preferably, the battery includes a stacked battery or a wound battery.

[0022] Preferably, the magnetic field measurement device for magnetic field distribution data includes an array-type magnetic sensing device or a scanning magnetic sensing device.

[0023] Compared with the prior art, the beneficial effects of the present invention are:

[0024] 1. This invention is based on the changes in magnetic field distribution at different time points during battery operation, calculating its gradient direction structure in the spatial plane, which can reflect the directional change trend caused by the redistribution of internal current density. This method has high sensitivity to changes in the reaction path caused by factors such as local electrode stress and degradation. Compared with traditional methods that rely on magnetic field strength values ​​or statistical analysis, this invention does not depend on the absolute amplitude, making it more suitable for evaluating the lateral consistency between different types and structures of battery cells and screening for local anomalies, possessing good versatility and adaptability.

[0025] 2. This invention constructs a directional structural difference distribution based on the cosine difference of the included angle, which can intuitively present the changes in the reaction path between the target battery under test and the standard reference battery in spatial distribution, enabling accurate identification and visual positioning of abnormal areas. This method can not only effectively distinguish between normal and abnormal batteries, but also further differentiate the types of abnormalities, such as path disturbances triggered by local factors, reaction imbalances caused by degradation, and local reaction anomalies caused by structure. It provides spatial data support and image evidence for fault tracing, structural optimization, and automatic screening, and is applicable to cell condition assessment and quality grading under various operating conditions. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating the overall process of the detection method described in this invention.

[0027] Figure 2 The magnitude of the vector of magnetic field distribution change Schematic diagram;

[0028] Figure 3 A schematic diagram of the direction vector fields of the standard reference battery and the target battery under test;

[0029] Figure 4 A schematic diagram showing the structural differences between the standard reference battery and the target battery under test.

[0030] Figure 5 A schematic diagram illustrating the structural differences between reference batteries and locally squeezed batteries under different testing time standards.

[0031] Figure 6 This diagram illustrates the structural differences between reference batteries and decaying batteries at different test time standards. Detailed Implementation

[0032] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only some embodiments of the invention, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0033] Example 1

[0034] This embodiment provides a method for detecting localized abnormal reactions in batteries based on differences in the direction of magnetic field changes, such as... Figure 1 As shown, the method includes the following specific steps:

[0035] Step 1: Under constant current conditions, acquire magnetic field distribution data of the standard reference battery and the target battery under test at different times during operation. , and Based on the initial reference state Calculate the vector of magnetic field distribution change at each time point. Furthermore, the vector magnitude of the change in magnetic field distribution is calculated. This is used to map the spatial dynamic changes of non-uniform reactions within the battery electrode plane, where , 1 represents the standard reference battery, 2 represents the target battery to be tested, the xy direction is the direction of the battery's length and width plane, and the z direction is the direction of the battery's thickness perpendicular to the length and width plane;

[0036] In this embodiment, four 5Ah wound pouch cells are used as examples for testing. Cell 1 serves as the standard reference cell, cell 2 is a normal cell of the same type under test, cell 3 is a cell of the same type under test with partial compression, and cell 4 is a cell of the same type under test with degradation. According to the testing method in step one, the test plane is a plane 5mm above the cell surface, the test area is 65mm*70mm, and the test interval is 5mm. Under 1C constant current conditions, the magnetic field distribution data at different times during cell operation are collected. , and Measurements were performed based on the initial reference state. Calculate the change in magnetic field distribution at each time point. Furthermore, the vector magnitude of the change in magnetic field distribution is calculated. This is used to map the spatial dynamic changes of non-uniform reactions within the battery electrode plane, where , Refers to batteries 1, 2, 3, and 4, and the vector magnitude of the change in magnetic field distribution. like Figure 2 As shown;

[0037] Step 2: Measure the vector magnitude of the magnetic field distribution change of the standard reference battery and the target battery under test. exist and Directional derivatives are calculated in each direction to construct the direction vector fields of the standard reference cell and the target cell under test. and The direction vector field is used to represent the local trend of the direction of magnetic field change;

[0038] In this embodiment, the vector magnitude of the magnetic field distribution change of the standard reference battery 1 and the target test batteries 2, 3, and 4 is... exist and Directional derivatives are calculated in each direction to construct the direction vector fields of the standard reference cell and the target cell under test. , , and ,like Figure 3 As shown, the direction vector field is used to represent the local trend of the direction of magnetic field change.

[0039] Step 3: For each spatial location point The cosine difference of the angle between the direction vectors of the standard reference battery and the target battery under test is calculated, and the directional structural difference distribution is constructed:

[0040] Its numerical range is 0-2;

[0041] In this embodiment, the standard reference battery 1 and the target batteries 2, 3, and 4 are calculated at each spatial location point. The cosine difference of the angle between direction vectors is used to construct the directional structure difference distribution, and the result is as follows: Figure 4 As shown, Figure 4 (a) is a schematic diagram of the local extrusion site of battery 3. Figure 4 (b)-(d) are schematic diagrams showing the differences in directional structure between battery 1 and batteries 2, 3 and 4, respectively;

[0042] Step 4: Based on the distribution of directional structural differences The location and morphology of the medium- and high-value areas are used to determine whether the target battery under test has local abnormal reactions and its spatial distribution characteristics: (1) If at a certain moment This indicates that the directions of current change in the two batteries at that point are completely consistent, and there is no abnormality; (2) If at a certain moment This indicates that the difference in the direction of current change between the two batteries at this point is less than 90°, that is, there is a slight abnormal reaction; (3) if at a certain moment This indicates that the difference in the direction of current change between the two batteries at this point is greater than or equal to 90°, indicating a strong abnormal reaction; (4) If at a certain moment This indicates that the current change direction of the two batteries at that point is reversed by 180°, which is very likely to cause severe local degradation or failure.

[0043] In this embodiment, by Figure 4 (b) It can be seen that the standard reference battery 1 and the normal battery 2 are... For 1e -7 The magnitude indicates that battery 1 and battery 2 are highly consistent, with no difference in internal reaction changes; Figure 4 (c) It can be seen that battery 3 shows a significant reversal of current change direction at the local compression site, with an angle greater than 90°. This indicates that, due to compression, the current change in this area does not propagate into the battery like in battery 1, but rather propagates towards the electrode tab; Figure 4(d) It can be seen that after the degradation of battery 4, the current change at the bottom reverses and points to the center of the battery, indicating that there may be uneven degradation inside the battery, which leads to a change in the internal reaction equilibrium path.

[0044] Step 5: Plot the distribution of directional structural differences based on different test time points. The evolution trend of the current change path of the target battery under test relative to the standard reference battery during operation was analyzed.

[0045] In this embodiment, the directional structural differences between the standard reference battery and the partially squeezed battery 3 at different test time points are analyzed. Perform drawing, such as Figure 5 As shown, as the reaction proceeds during operation, the main affected area of ​​battery 3 is concentrated at the site of compression, but more bright areas appear inside, indicating that the impact of compression on the battery accumulates over time and affects more areas; as Figure 6 As shown, battery 4 exhibits a large-area directional change in the reaction redistribution path relative to the standard reference battery at the start of discharge, and there is no uniform change pattern. This indicates that degradation leads to more significant non-uniformity of reaction activity within the battery plane. As discharge progresses, the orientation of the battery body tends to be consistent. This is because the reaction redistribution mainly diffuses from the tabs into the battery interior. The overall trend of change is not changed due to structural influences throughout the discharge process, but this difference is further transferred to the bottom region of the battery.

[0046] The detection method of this invention does not rely on global averages or template libraries, but instead performs point-by-point judgments based on spatial structural similarity. It boasts advantages such as strong physical interpretability, clear anomaly localization, and high adaptability, making it suitable for consistency comparison and anomaly screening between cells of different structures and states. It also offers the advantages of being non-destructive and spatiotemporally resolvable. Especially in practical applications such as battery production consistency assessment, local degradation / fault identification, and structural design optimization, it demonstrates excellent engineering adaptability and widespread application value.

[0047] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for detecting localized abnormal reactions in batteries based on differences in the direction of magnetic field changes, characterized in that, Includes the following steps: Step 1: Under constant current conditions, acquire magnetic field distribution data of the standard reference battery and the target battery under test at different times during operation. , and Based on the initial reference state Calculate the change in magnetic field distribution at each time point. Furthermore, the vector magnitude of the change in magnetic field distribution is calculated. This is used to map the spatial dynamic changes of non-uniform reactions within the battery electrode plane, where , 1 represents the standard reference battery, 2 represents the target battery to be tested, the xy direction is the direction of the battery's length and width plane, and the z direction is the direction of the battery's thickness perpendicular to the length and width plane; Step 2: Measure the vector magnitude of the magnetic field distribution change of the standard reference battery and the target battery under test. exist and Directional derivatives are calculated in each direction to construct the direction vector fields of the standard reference cell and the target cell under test. and The direction vector field is used to represent the local trend of the direction of magnetic field change; Step 3: For each spatial location point The cosine difference of the angle between the direction vectors of the standard reference battery and the target battery under test is calculated, and the directional structural difference distribution is constructed: Its numerical range is 0-2; Step 4: Based on the distribution of directional structural differences The location and morphology of the medium and high value areas are used to determine whether the target battery under test has local reaction anomalies and its spatial distribution characteristics: (1) If at a certain moment This indicates that the directions of current change in the two batteries at that point are completely consistent, and there is no abnormality; (2) If at a certain moment This indicates that the difference in the direction of current change between the two batteries at this point is less than 90°, that is, there is a slight abnormal reaction; (3) if at a certain moment This indicates that the difference in the direction of current change between the two batteries at this point is greater than or equal to 90°, indicating a strong abnormal reaction; (4) If at a certain moment This indicates that the current change direction of the two batteries at that point is reversed by 180°, which is very likely to cause severe local degradation or failure. Step 5: Plot the distribution of directional structural differences based on different test time points. The evolution trend of current change path of the target battery under test relative to the standard reference battery during operation is analyzed.

2. The method according to claim 1, characterized in that: In step two, the method for calculating the magnitude of the magnetic field distribution change vector is as follows: 。 3. The method according to claim 1, characterized in that: In step two, the derivative calculation is achieved through a two-dimensional Sobel convolution operator, which has the advantages of direction enhancement and noise suppression. Specifically, the following convolution kernel is used: ， The directional derivatives obtained after the convolution operation are as follows: ， 。 4. The method according to claim 1, characterized in that: The standard reference battery and the target battery under test construct a direction vector field. and Constructed using the following normalization formula: 。 5. The method according to claim 1, characterized in that: The battery includes stacked batteries or wound batteries.

6. The method according to claim 1, characterized in that: Magnetic field measurement devices for magnetic field distribution data include array-type magnetic sensing devices or scanning magnetic sensing devices.

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