Method of detecting abnormality of storage battery
By calculating the initial constraint deformation and historical data, and using a computer to detect the deformation of the bottom surface and stacking direction of the square battery cell casing, the problem of thermal conductive material peeling and short circuit caused by the deformation of the bottom surface of the casing was solved, and efficient and low-cost anomaly detection was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TOYOTA JIDOSHA KK
- Filing Date
- 2025-12-25
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies require physical sensors to detect instances of thermally conductive material peeling and short circuits caused by deformation of the bottom surface of the casing in batteries with multiple square cell stacks bonded to a platform. This results in larger devices and increased costs.
By calculating the initial constraint deformation and historical data, the deformation of the shell bottom surface and the stacking direction is calculated, and the computer outputs an alarm to detect anomalies, avoiding the use of physical sensors.
This technology enables the detection of deformation anomalies on the bottom surface of the housing and in the stacking direction without the need for physical sensors, thereby improving detection accuracy and reducing device costs.
Smart Images
Figure CN122410342A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to a method for detecting abnormalities in storage batteries, particularly storage batteries in which a stack of multiple square cells is bonded to a platform by means of a thermally conductive material. Background Technology
[0002] Japanese Patent Application Publication No. 2016-027538 discloses a technology for detecting changes in internal pressure and electrode swelling in a sealed secondary battery using a monitoring sensor.
[0003] In a battery where multiple square cells are laminated together and bonded to a platform using a thermally conductive material, one type of anomaly to be detected is the deformation of the bottom surface of the casing, which accompanies the expansion of the cells. This deformation can cause the thermally conductive material to peel off. Furthermore, if the deformation continues, it can lead to a short circuit caused by contact between the casing and the internal electrodes. As a method for detecting such anomalies, a monitoring sensor method, as described in the prior art, can be considered. However, using a monitoring sensor to detect deformation of the bottom surface of the casing results in a larger size and increased cost of the battery storage device. Summary of the Invention
[0004] One embodiment of this disclosure relates to a method for detecting anomalies in a storage battery, the storage battery comprising a stack of multiple square cells bonded to a platform by a thermally conductive material, the method comprising: calculating an initial constraint deformation of a square cell of interest in the stack based on process data obtained in the manufacturing process; calculating a deformation of the bottom surface of the casing of the square cell of interest based on the initial constraint deformation and using historical data; and outputting a first alarm upon receiving a situation where the deformation exceeds a predetermined first threshold.
[0005] According to this disclosure, the amount of deformation of the bottom surface of the prismatic cell casing can be calculated based on data, thus eliminating the need for a physically-based sensor to detect deformation caused by the deformation of the bottom surface of the prismatic cell casing. Attached Figure Description
[0006] The features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which the same reference numerals denote the same elements, wherein,
[0007] Figure 1A This diagram illustrates the structure of a battery with multiple square cells stacked together, and the anomalies caused by the deformation of the square cells.
[0008] Figure 1B This diagram illustrates the structure of a battery with multiple square cells stacked together, and the anomalies caused by the deformation of the square cells.
[0009] Figure 1C This diagram illustrates the structure of a battery with multiple square cells stacked together, and the anomalies caused by the deformation of the square cells.
[0010] Figure 1D This diagram illustrates the structure of a battery with multiple square cells stacked together, and the anomalies caused by the deformation of the square cells.
[0011] Figure 1E This diagram illustrates the structure of a battery with multiple square cells stacked together, and the anomalies caused by the deformation of the square cells.
[0012] Figure 2 This is a diagram illustrating an example of the change in the deformation of the bottom surface of a square battery cell casing caused by repeated charging and discharging.
[0013] Figure 3 A flowchart illustrating a method for detecting anomalies caused by deformation of the bottom surface of a square battery cell casing;
[0014] Figure 4 This is a diagram illustrating an example of the change in the amount of deformation in the stacking direction of a square battery cell caused by repeated charging and discharging.
[0015] Figure 5 A flowchart illustrating a method for detecting anomalies caused by deformation in the stacking direction of square battery cells. Detailed Implementation
[0016] 1. Summary of Battery Malfunctions
[0017] Figure 1A , Figure 1B , Figure 1C , Figure 1D , Figure 1E This diagram illustrates the structure of a battery consisting of multiple square cells stacked together and the anomalies caused by the deformation of the square cells. As an example of a battery used in a pure electric vehicle, battery packs are known to be modularized by stacking multiple square cells and encapsulating multiple modules.
[0018] like Figure 1A As shown, in the modular design, a stack of multiple square cells 10 is embedded between end plates 40 under a constrained and compressed state in the stacking direction. Furthermore, the stack of multiple square cells 10 is bonded to the substrate 30 by a thermally conductive material 20, or more specifically, a thermally conductive adhesive. The substrate 30 may also have a cooling function.
[0019] Even after being embedded between the end plates 40, residual constraint loads remain, causing deformation of each square cell 10. Here, the constraint load remaining on the square cells 10 at the time of manufacture, i.e., the constraint load in the initial state, is referred to as the initial constraint load. The deformation caused by the initial constraint load includes deformation in the height direction of the square cells 10. Figure 1B This shows the cross-sectional shape of the square battery cell 10 in its initial state. In the initial state, the bottom surface 10b of the square battery cell 10's casing deforms downwards due to the initial constraint load.
[0020] The square battery cell 10 gradually expands in the stacking direction through charging and discharging. For example, as... Figure 1C As shown, the expansion of the square battery cell 10 begins with the initial charging. As the square battery cell 10 expands in the stacking direction, the bottom surface 10b of the casing deforms upwards. Furthermore, as... Figure 1D As shown, due to repeated charging and discharging, the degradation intensifies, causing the square battery cell 10 to expand in the stacking direction during charging. This, in turn, increases the amount of deformation in the concave direction, i.e., the inward direction, on the bottom surface 10b of the casing. This deformation of the bottom surface 10b in the upward concave direction results in tensile stress acting between the bottom surface 10b of the casing and the thermally conductive material 20.
[0021] The tensile stress acting between the bottom surface 10b of the housing and the thermally conductive material 20 causes the thermally conductive material 20 to peel off from the bottom surface 10b of the housing. If the deformation of the bottom surface 10b of the housing further develops, a short circuit may occur due to contact between the housing and the internal electrode. That is, the deformation of the bottom surface 10b of the housing caused by repeated charging and discharging may lead to an anomaly such as the thermally conductive material 20 peeling off from the bottom surface 10b of the housing, and further, may lead to an anomaly such as a short circuit caused by contact between the housing and the internal electrode.
[0022] In addition, the deformation caused by the initial constraint load includes deformation in the stacking direction of the square cell 10. The amount of deformation in the stacking direction of the square cell 10 gradually increases as the square cell 10 expands due to repeated charging and discharging. Through this expansion, such as Figure 1E As indicated by the white arrows, the stacked square cells 10 are pressed sequentially from the center toward the end plate 40. The bottom surface 10b of the housing is bonded to the platform 30 by the thermally conductive material 20, so the stress in the shear direction indicated by the black arrows acts between the bottom surface 10b of the housing and the thermally conductive material 20.
[0023] The shear stress acting between the bottom surface 10b of the housing and the thermally conductive material 20 is the cause of the thermally conductive material 20 peeling off from the bottom surface 10b of the housing. That is, the deformation of the stacking direction of the square battery cell 10 caused by repeated charging and discharging may lead to the abnormality of the thermally conductive material 20 peeling off from the bottom surface 10b of the housing.
[0024] 2. Method for detecting abnormalities caused by deformation of the bottom surface of the square battery cell casing
[0025] The deformation of the bottom surface 10b of the square battery cell 10 increases due to repeated charging and discharging. Figure 2 This is a diagram illustrating an example of the change in deformation of the bottom surface 10b of the casing caused by repeated charging and discharging. (See diagram for example.) Figure 2 As shown, the deformation S of the bottom surface of the casing repeatedly increases and decreases with repeated charging and discharging, and gradually increases overall. Furthermore, when the deformation S exceeds a predetermined first threshold Th1, peeling may occur due to stress in the tensile direction of the thermally conductive material 20. And, when the deformation S exceeds a predetermined second threshold Th2, which is larger than the first threshold Th1, a short circuit may occur due to contact between the casing and the internal electrode body. Hereinafter, the first threshold Th1 will be referred to as the thermally conductive material tensile peeling threshold, and the second threshold Th2 will be referred to as the casing short-circuit threshold. The specific values of the thermally conductive material tensile peeling threshold and the casing short-circuit threshold are determined by the battery specifications, and can be determined, for example, through testing or simulation.
[0026] Figure 3 This flowchart illustrates a method for detecting anomalies caused by deformation of the bottom surface 10b of the casing of the square battery cell 10. A key feature of this method is that it does not physically detect the deformation of the bottom surface 10b of the casing of the square battery cell 10 using sensors, but rather calculates the amount of deformation. This method can be executed by a computer.
[0027] The deformation of the bottom surface of the casing of the square cell of interest among the multiple square cells 10 constituting the battery pack is calculated. In this embodiment, the square cell of interest is the thinnest square cell in the battery pack. The thinnest square cell is the square cell whose bottom surface 10b of the casing deforms the most when expansion occurs in the stacking direction, i.e., the square cell most likely to cause tensile peeling and short circuit of the thermally conductive material 20. However, the square cell of interest can be arbitrarily determined. The square cell of interest can be one square cell, multiple square cells, or all of the square cells.
[0028] exist Figure 3In the flowchart shown, steps S11 to S14 are, for example, preparatory processes performed before the battery pack leaves the factory, or before the BEV equipped with the battery pack leaves the factory. In step S11, traceability data of the battery pack that is the object of anomaly detection is obtained. The traceability data includes process data obtained during the battery pack manufacturing process. In step S12, the thinnest square cell is determined based on the traceability data, and its thickness is calculated. In step S13, the initial constraint load of the thinnest square cell is calculated based on its thickness and the traceability data. Then, in step S14, the initial constraint deformation of the thinnest square cell is calculated based on its thickness and the initial constraint load; specifically, the initial value of the deformation of the bottom surface of the casing is calculated. The initial value of the deformation of the bottom surface of the casing calculated in step S14 is stored in the computer's memory.
[0029] exist Figure 3 In the flowchart shown, steps S101 to S108 are processes that are repeatedly performed every time the BEV equipped with the battery pack is operated after it leaves the factory. In step S101, it is determined whether the ignition switch (IG) is on. If the IG is off, the subsequent processes are skipped; if the IG is on, the processes from step S102 onwards are executed.
[0030] In step S102, the estimated expansion amount of the thinnest square cell is obtained. The method for estimating the expansion amount is not limited. It can also be assumed that the expansion amounts of all square cells are approximately equal, and the estimated expansion amount of the average square cells in the entire battery pack is taken as the estimated expansion amount of the thinnest square cell. The expansion amount can be estimated using, for example, a known method such as the method described in Japanese Patent Application Laid-Open No. 2023-11289.
[0031] In step S103, the estimated internal pressure of the thinnest square cell is obtained. The method for estimating the internal pressure is not limited. It can also be assumed that the internal pressures of all square cells are approximately equal, and the estimated internal pressure of the average number of square cells in the entire battery pack is taken as the estimated internal pressure of the thinnest square cell. The estimation of the internal pressure can be performed using known methods, such as those described in Japanese Patent Application Publication No. 2019-118216. Furthermore, the processing in step S103 can be interchanged with the processing in step S102, or they can be performed simultaneously.
[0032] In step S104, the deformation of the bottom surface of the casing of the thinnest square cell is calculated based on the initial value of the casing bottom surface deformation calculated and stored in memory in step S14, the estimated expansion amount obtained in step S102, and the estimated internal pressure obtained in step S103. The estimated expansion amount and estimated internal pressure are used to calculate the change in the casing bottom surface deformation from the initial value. The relationship between the casing bottom surface deformation and the expansion amount and internal pressure is specified by a physical model or mapping.
[0033] In step S105, the deformation amount S of the shell bottom surface obtained in step S104 is compared with the thermally conductive material tensile peeling threshold Th1 to determine whether the deformation amount S of the shell bottom surface has increased to the point of causing tensile peeling of the thermally conductive material 20. If the deformation amount S of the shell bottom surface is below the thermally conductive material tensile peeling threshold Th1, the subsequent processing is skipped. If the deformation amount S of the shell bottom surface exceeds the thermally conductive material tensile peeling threshold Th1, in step S106, diagnostic code 1 is output. Diagnostic code 1 is an alarm notifying of the risk of tensile peeling of the thermally conductive material 20.
[0034] If diagnostic code 1 is output, proceed to step S107. In step S107, the deformation amount S of the housing bottom surface obtained in step S104 is compared with the housing short-circuit threshold Th2 to determine whether the deformation amount S has increased to the point of causing a short circuit. If the deformation amount S is below the housing short-circuit threshold Th2, the subsequent processing is skipped. If the deformation amount S exceeds the housing short-circuit threshold Th2, diagnostic code 2 is output in step S108. Diagnostic code 2 is an alarm indicating the risk of a short circuit. The alarm corresponding to diagnostic code 1 is called the first alarm, and the alarm corresponding to diagnostic code 2 is called the second alarm.
[0035] 3. Method for detecting anomalies caused by deformation in the stacking direction of square battery cells
[0036] The deformation of the square battery cell 10 in the stacking direction increases due to repeated charging and discharging. Figure 4 This is a diagram illustrating an example of the change in deformation along the stacking direction caused by repeated charging and discharging. (See diagram for example.) Figure 4 As shown, the deformation SS in the lamination direction repeatedly increases and decreases with repeated charging and discharging, and gradually increases overall. Furthermore, when the deformation SS in the lamination direction exceeds a predetermined third threshold Th3, delamination caused by stress in the shear direction of the thermally conductive material 20 may occur. Hereinafter, the third threshold Th3 will be referred to as the thermally conductive material shear delamination threshold. The specific value of the thermally conductive material shear delamination threshold is determined by the battery specifications, and can be determined, for example, through testing or simulation.
[0037] Figure 5 This flowchart illustrates a method for detecting anomalies caused by deformation in the stacking direction of the prismatic battery cell 10. A key feature of this method is that it does not physically detect the deformation in the stacking direction of the prismatic battery cell 10 using sensors, but rather calculates the amount of deformation in the stacking direction. This method can be executed by a computer.
[0038] The deformation in the stacking direction of the square cells of interest among the multiple square cells 10 constituting the battery pack is calculated. In this embodiment, the square cell of interest is the square cell closest to the end plate 40 within the module, i.e., the outermost square cell. The outermost square cell is the square cell with the greatest stress in the shear direction when expansion occurs in the stacking direction, i.e., the square cell most likely to cause shear peeling of the thermally conductive material 20. However, the square cell of interest can be arbitrarily determined. The square cell of interest can be one square cell, multiple square cells, or all of the square cells.
[0039] exist Figure 5 In the flowchart shown, steps S21 to S24 are, for example, preparatory processes performed before the battery pack leaves the factory, or before the BEV equipped with the battery pack leaves the factory. In step S21, traceability data for the battery pack that is the object of anomaly detection is obtained. The traceability data includes process data obtained during the battery pack manufacturing process. In step S22, the thickness of each square cell and the thickness of the insulation material between the square cells are calculated based on the traceability data. In step S23, the initial constraint load of the battery pack is calculated based on the traceability data. Then, in step S24, based on the thickness of each square cell and the insulation material, and the initial constraint load, the initial constraint deformation of the outermost square cell is calculated; specifically, the initial value of the deformation in the stacking direction is calculated. The initial value of the deformation in the stacking direction calculated in step S24 is stored in the computer's memory.
[0040] exist Figure 5 In the flowchart shown, steps S201 to S205 are processes that are repeatedly performed every time the BEV equipped with the battery pack is operated after it leaves the factory. In step S201, it is determined whether the IG is on. If the IG is off, the subsequent processing is skipped; if the IG is on, the processing after step S202 is executed.
[0041] In step S202, the estimated expansion amount of the outermost square cell is obtained. The method for estimating the expansion amount is not limited. It can also be regarded that the expansion amount of all square cells is approximately equal, and the estimated expansion amount of the average square cells of the entire battery pack is taken as the estimated expansion amount of the outermost square cell.
[0042] In step S203, based on the initial value of the stacking direction deformation calculated and stored in memory in step S24 and the estimated expansion amount obtained in step S202, the stacking direction deformation of the outermost square cell is calculated. The estimated expansion amount is used to calculate the change in the stacking direction deformation from the initial value. The relationship between the stacking direction deformation and the expansion amount is defined by a physical model or mapping.
[0043] In step S204, the lamination direction deformation amount SS obtained in step S203 is compared with the thermal conductive material shear peeling threshold Th3 to determine whether the lamination direction deformation amount SS has increased to the point of causing shear peeling of the thermal conductive material 20. If the lamination direction deformation amount SS is below the thermal conductive material shear peeling threshold Th3, the subsequent processing is skipped. If the lamination direction deformation amount SS exceeds the thermal conductive material shear peeling threshold Th3, diagnostic code 3 is output in step S205. Diagnostic code 3 is an alarm notifying of the risk of shear peeling of the thermal conductive material 20. The alarm corresponding to diagnostic code 3 is called the third alarm.
[0044] 4. Effects
[0045] According to the method for detecting anomalies caused by deformation of the bottom surface of the casing of the prismatic battery cell according to this embodiment, the amount of deformation of the bottom surface of the casing can be calculated based on data, thus eliminating the need for a physically installed sensor to detect deformation caused by deformation of the bottom surface 10b of the casing of the prismatic battery cell 10. Furthermore, according to the method for detecting anomalies caused by deformation in the stacking direction of the prismatic battery cell according to this embodiment, the amount of deformation in the stacking direction can be calculated based on data, thus eliminating the need for a physically installed sensor to detect deformation caused by deformation in the stacking direction of the prismatic battery cell 10. By having a computer execute the above methods, a first alarm can notify the user of the risk of tensile peeling of the thermally conductive material 20, a second alarm can notify the user of the risk of short circuit, and a third alarm can notify the user of the risk of shear peeling of the thermally conductive material 20.
[0046] The method for detecting anomalies caused by deformation of the bottom surface of the square battery cell casing, as described in this embodiment, and the method for detecting anomalies caused by deformation of the stacking direction of the square battery cell, as described in this embodiment, can be used together as described above, or only one of them can be used. However, by using two methods with different logics together, the detection accuracy of the peeling of the thermally conductive material 20 can be improved.
Claims
1. A method for detecting abnormalities in a storage battery, the storage battery comprising a stack of multiple square cells bonded to a platform by a thermally conductive material, characterized in that, The method for detecting abnormalities in the storage battery includes: The initial constraint deformation of the square cell of interest in the laminate is calculated based on the process data obtained in the manufacturing process. Based on the initial constraint deformation and historical usage data, the deformation of the bottom surface of the casing of the square battery cell of interest is calculated; and Upon receiving a situation where the deformation exceeds a predetermined first threshold, a first alarm is output.
2. The method for detecting abnormalities in a storage battery according to claim 1, characterized in that, Calculating the deformation amount based on the initial constraint deformation amount and the historical data includes: using the initial constraint deformation amount as the initial value of the deformation amount, and calculating the change from the initial value based on the expansion amount and internal pressure of the square cell of interest estimated according to the historical data.
3. The method for detecting abnormalities in a storage battery according to claim 1, characterized in that, The square cell in question is the thinnest square cell in the laminate.
4. The method for detecting abnormalities in a storage battery according to claim 1, characterized in that, The first threshold is set to a value that can cause the thermally conductive material to stretch and peel off from the bottom surface.
5. The method for detecting abnormalities in a storage battery according to any one of claims 1 to 4, characterized in that, The method for detecting abnormalities in the storage battery also includes: A second alarm is output when the deformation exceeds a predetermined second threshold that is greater than the first threshold.
6. The method for detecting abnormalities in a storage battery according to claim 5, characterized in that, The second threshold is set to a value that can generate a short circuit caused by contact between the housing and the internal electrode.