A method and apparatus for determining battery failure

Abstract

The application provides a battery fault determination method and device. The method comprises: obtaining temperature data corresponding to multiple time points in a battery thermal runaway test process, extracting waveform features from a temperature change curve of the temperature data according to the temperature change curve; determining abnormal features in the battery thermal runaway test process according to the waveform features; determining a battery fault corresponding to the abnormal features; wherein the battery fault is an internal fault of a battery cell or a fault between two adjacent battery cells; and performing fault removal processing on the battery according to the battery fault. The application can quickly identify the internal fault type of the battery during the battery thermal runaway process and perform processing to effectively suppress the spread of thermal runaway in the battery pack, thereby improving the safety of the battery.

Description

Technical Field

[0001] This application relates to the field of battery technology, and more specifically, to a method and apparatus for determining battery faults. Background Technology

[0002] Lithium-ion batteries, as a clean and efficient energy source, are widely used in production and daily life; however, their safety is a major concern. The essence of lithium-ion battery safety incidents is thermal runaway. Thermal runaway in a single cell can trigger the spread of thermal runaway throughout the entire battery system, leading to serious accidents.

[0003] Currently, in the monitoring process of battery thermal runaway testing, the determination of whether the battery has thermal runaway is often made by real-time collection of voltage, temperature, smoke concentration, etc. However, this method can only be used to alarm when thermal runaway occurs, and cannot effectively suppress the spread of thermal runaway within the battery pack after thermal runaway has occurred. The actual safety control effect is limited and cannot improve the safety of the battery. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method and apparatus for determining battery faults, which can quickly identify the type of internal fault that occurs in the battery during the thermal runaway process and handle it to effectively suppress the spread of thermal runaway in the battery pack and improve battery safety.

[0005] In a first aspect, embodiments of this application provide a method for determining battery faults, the method comprising:

[0006] During the battery thermal runaway test, temperature data were acquired at multiple time points.

[0007] Based on the temperature change curve of the temperature data, waveform features are extracted from the temperature change curve;

[0008] Based on the waveform characteristics, determine the abnormal features during the battery thermal runaway test process;

[0009] Identify the battery fault corresponding to the abnormal characteristics; wherein the battery fault is a fault inside the cell or a fault between two adjacent cells;

[0010] Based on the battery fault, perform fault clearing procedures on the battery.

[0011] In one optional embodiment of this application, the abnormal features include a first abnormal feature and / or a second abnormal feature. The step of determining the abnormal features during the battery thermal runaway test based on the waveform features includes:

[0012] If the waveform feature includes a first target waveform in which the amplitude change exceeds the first amplitude range and the direction of the first target waveform is bidirectional, then the first target waveform and the bidirectional direction are determined as the first abnormal feature in the battery thermal runaway test process.

[0013] If the waveform feature includes a second target waveform in which the amplitude changes within the second amplitude range and the direction of the second target waveform is unidirectional, then the second target waveform and the unidirectional direction are determined as the second abnormal feature in the battery thermal runaway test process.

[0014] In one optional embodiment of this application, the step of determining the battery fault corresponding to the abnormal feature includes:

[0015] If the detected abnormal feature is the first abnormal feature, then the battery fault is determined to be an internal fault of the battery cell.

[0016] If the detected abnormal feature is the second abnormal feature, then the battery fault is determined to be a fault between two adjacent cells.

[0017] In one optional embodiment of this application, the step of clearing the battery fault according to the battery fault includes:

[0018] If the battery fault is an internal fault of the battery cell, the fault clearing method includes one of the following: increasing the spacing between the battery cell tabs and other structures in the battery pack, or changing the battery cell packaging process;

[0019] If the battery fault is a fault between two adjacent cells, the fault clearing method includes one of the following: changing the cell arrangement, changing the cell interconnection method, adding heat insulation material or heat dissipation device between two adjacent cells.

[0020] In one optional embodiment of this application, the step of extracting waveform features from the temperature change curve based on the temperature data includes:

[0021] The temperature data is filtered to obtain normal temperature datasets and abnormal temperature datasets;

[0022] A first temperature change curve is determined based on the normal temperature dataset, and a second temperature change curve is determined based on the abnormal temperature dataset.

[0023] Based on the first temperature change curve, waveform features are extracted from the second temperature change curve.

[0024] In one optional embodiment of this application, the step of filtering the temperature data to obtain a normal temperature dataset and an abnormal temperature dataset includes:

[0025] The first temperature data with a temperature change rate not greater than the target temperature change rate threshold is selected from the temperature data to obtain the normal temperature dataset;

[0026] The abnormal temperature dataset is obtained by filtering out the second temperature data whose temperature change rate is greater than the target temperature change rate threshold from the temperature data.

[0027] In one optional embodiment of this application, the target temperature change rate threshold is determined through the following steps:

[0028] Obtain a first temperature range and a first preset temperature change rate corresponding to the first temperature range, and a second temperature range and a second preset temperature change rate corresponding to the second temperature range; wherein any temperature value in the second temperature range is greater than any temperature value in the first temperature range;

[0029] If the temperature data obtained at the current time point belongs to the first temperature range, then the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the first preset temperature change rate.

[0030] If the temperature data obtained at the current time point belongs to the second temperature range, then the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the second preset temperature change rate.

[0031] In one optional embodiment of this application, the step of acquiring temperature data at multiple time points during a battery thermal runaway test includes:

[0032] Place the thermocouple at the target location on the battery;

[0033] During the battery thermal runaway test, the thermoelectric potential corresponding to multiple time points collected by the thermocouple at the target location is obtained;

[0034] Based on the functional relationship between thermoelectric potential and temperature, temperature data corresponding to multiple time points are determined.

[0035] In one optional embodiment of this application, the target location includes at least one of the following: the middle region of the battery cell, the battery cell tab, the center point of the heating film, the perforation location, the positive electrode copper busbar, the middle region of the battery casing, the screw hole, and the battery heat dissipation surface.

[0036] Secondly, embodiments of this application provide a battery fault determination device, the device comprising:

[0037] The data acquisition module is used to acquire temperature data at multiple time points during battery thermal runaway testing.

[0038] The feature extraction module is used to extract waveform features from the temperature change curve of the temperature data.

[0039] An anomaly determination module is used to determine the abnormal characteristics during the battery thermal runaway test based on the waveform characteristics.

[0040] The fault determination module is used to determine the battery fault corresponding to the abnormal characteristics; wherein the battery fault is a fault inside the cell or a fault between two adjacent cells;

[0041] The fault clearing module is used to clear the battery fault based on the battery fault.

[0042] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the battery fault determination method described above are performed.

[0043] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the battery fault determination method described above.

[0044] This application provides a method and apparatus for determining battery faults. The method includes: acquiring temperature data at multiple time points during a battery thermal runaway test; extracting waveform features from the temperature change curves based on the temperature data; determining abnormal features during the battery thermal runaway test based on the waveform features; determining the battery fault corresponding to the abnormal features; wherein the battery fault is an internal fault of the battery cell or a fault between two adjacent battery cells; and performing fault clearing processing on the battery based on the battery fault. This application can quickly identify and process battery faults based on the waveform features of the temperature change curve during battery thermal runaway, thereby effectively suppressing the spread of thermal runaway within the battery pack and improving battery safety.

[0045] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0046] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a schematic diagram of the temperature change curves during battery thermal runaway detected in existing technologies;

[0048] Figure 2 A flowchart illustrating a method for determining battery faults provided in an embodiment of this application;

[0049] Figure 3 This is a schematic diagram of curves showing different preset temperature change rates during battery thermal runaway, provided in an embodiment of this application.

[0050] Figure 4 A schematic diagram of a first temperature change curve and a second temperature change curve provided for embodiments of this application;

[0051] Figure 5 A schematic diagram of a battery fault determination device provided in an embodiment of this application;

[0052] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0054] In existing technologies, thermocouples are commonly used to measure battery temperature during thermal runaway testing. Type K thermocouples are frequently chosen for testing due to their lower cost and more stable performance. A Type K thermocouple consists of two metal wires: a nickel-chromium positive electrode and a nickel-silicon negative electrode, with a measurement range of 0℃ to 1300℃. The nickel-chromium (positive electrode) and nickel-silicon (negative electrode) are combined into a closed loop. One junction serves as the working junction (hot junction), absorbing thermal radiation and generating a temperature rise, while the other junction serves as the reference junction (cold junction), maintaining a constant temperature. Specifically, based on the thermoelectric effect, the temperature difference between the working and reference junctions generates a thermoelectric potential in the loop. When the reference junction temperature is fixed, EAB(T, T0) = EAB(T) - EAB(T0) = f(T). By measuring the thermoelectric potential difference, the temperature of the working junction can be measured.

[0055] Currently, in the monitoring process of battery thermal runaway testing, the determination of whether the battery has thermal runaway is often made by real-time collection of voltage, temperature, smoke concentration, etc. However, this method can only be used to alarm when thermal runaway occurs, and cannot effectively suppress the spread of thermal runaway within the battery pack after thermal runaway has occurred. The actual safety control effect is limited and cannot improve the safety of the battery.

[0056] Based on this, embodiments of this application provide a method and apparatus for determining battery faults, which can quickly identify the type of internal fault occurring in the battery during thermal runaway and process it to effectively suppress the spread of thermal runaway within the battery pack and improve battery safety.

[0057] Please see Figure 2 , Figure 2 This is a flowchart illustrating a method for determining battery faults provided in an embodiment of this application. Figure 2 As shown in the embodiments of this application, the method includes:

[0058] S201. During the battery thermal runaway test, acquire temperature data at multiple time points;

[0059] S202. Based on the temperature change curve of the temperature data, extract the waveform features from the temperature change curve;

[0060] S203. Determine the abnormal characteristics during the battery thermal runaway test based on the waveform characteristics;

[0061] S204. Determine the battery fault corresponding to the abnormal characteristics; wherein, the battery fault is a fault inside the cell or a fault between two adjacent cells.

[0062] S205. Based on the battery fault, perform fault clearing procedures on the battery.

[0063] This application embodiment acquires temperature data at multiple time points during battery thermal runaway testing. Based on the temperature change curves, waveform features are extracted. Abnormal characteristics during the battery thermal runaway test are determined based on these waveform features. The corresponding battery faults are identified, including internal cell faults or faults between two adjacent cells. Based on the battery faults, fault clearing procedures are performed. This application can quickly identify and address battery faults based on the waveform features of the temperature change curve during battery thermal runaway, effectively suppressing the spread of thermal runaway within the battery pack and improving battery safety.

[0064] The following is a detailed explanation of steps S201 to S205:

[0065] In step S201, during the battery thermal runaway test, temperature data corresponding to multiple time points are acquired.

[0066] In this embodiment, the temperature of the battery is measured using a thermocouple to obtain temperature data at multiple time points. The process of measuring the battery temperature using a thermocouple is described above and will not be repeated here.

[0067] In one optional embodiment, during the battery thermal runaway test, the temperature data measured by the thermocouple will be different due to the different positions of the thermocouple on the battery. Therefore, this application can obtain different temperature data corresponding to multiple time points according to the different positions of the thermocouple on the battery.

[0068] Specifically, step S201 includes:

[0069] Step 2011: Place the thermocouple at the target position on the battery.

[0070] Here, the target location includes at least one of the following: the middle area of ​​the battery cell, the battery cell tab, the center point of the heating film, the perforation location, the positive copper busbar, the middle area of ​​the battery casing, the screw hole, and the battery heat dissipation surface.

[0071] Step 2012: During the battery thermal runaway test, acquire the thermoelectric potential corresponding to multiple time points collected by the thermocouple at the target location.

[0072] Here, when there is a temperature difference between the working end and the reference end of the thermocouple, a thermoelectric electromotive force is generated between them, thus forming a current of a certain magnitude in the circuit. This phenomenon is called the thermoelectric effect.

[0073] Step 2013: Based on the functional relationship between thermoelectric potential and temperature, determine the temperature data corresponding to multiple time points.

[0074] Here, each time point corresponds to a thermoelectric potential, and the temperature data corresponding to multiple time points can be determined based on the functional relationship between the thermoelectric potential and temperature.

[0075] By measuring temperature data at different locations on the battery, thermal runaway monitoring can be performed on different parts of the battery in a targeted manner, thereby providing early warning of potential faults and resolving them in a timely manner, which can reduce the failure rate of the battery during actual use.

[0076] In the relevant solutions, it was found during the monitoring of battery thermal runaway testing that the temperature change curve waveform plotted from the temperature data measured by thermocouples often has superimposed interference waveforms. These interference waveforms form a large number of false temperature points, which seriously interfere with the temperature changes during battery thermal runaway. This makes it impossible for users to accurately obtain the temperature changes during battery thermal runaway, and thus makes it difficult to pay attention to the time when the positive and negative short circuits occur during battery thermal runaway, as well as the arcing and arcing that occur during the heat propagation process between cells.

[0077] While existing technologies propose several measures to prevent interference with thermocouples, filtering out interference waveforms superimposed on the temperature change curves plotted from thermocouple-measured temperature data—such as shielding (shielding the thermocouple's compensating wires within a grounded metal shield to prevent electromagnetic interference and high-voltage electric field interference); isolation (suspending the thermocouple (using insulating material to separate the thermocouple from its support) to prevent high-temperature leakage interference); and grounding (introducing interference to the ground during measurement cycles to ensure instrument accuracy), and grounding the thermocouple's measuring terminals (effectively preventing high-temperature leakage interference), these shielding, isolation, and grounding methods are suitable for large electrical products or boilers where wiring space is unrestricted. They are impractical for applications like battery packs, where space is limited and electrical insulation from the outside is required. Furthermore, the temperature change curves plotted from thermocouple-measured temperature data often lack any discernible pattern. Figure 1 As shown, this prevents users from analyzing the causes of battery thermal runaway based on temperature change curves, and consequently prevents users from improving the cell arrangement, interconnection, cell isolation and insulation methods, and the setting and optimization of heating films within the battery pack by analyzing data from battery thermal runaway.

[0078] Based on this, step S202 specifically includes:

[0079] Step 2021: Filter the temperature data to obtain normal temperature datasets and abnormal temperature datasets.

[0080] In this embodiment, the temperature data includes a normal temperature dataset and an abnormal temperature dataset. The normal temperature dataset represents a set of temperature data that changes according to the temperature rise pattern during battery thermal runaway. For example, the relationship between the thermoelectric potential generated by a commonly used K-type thermocouple under temperature influence and temperature is a linear or approximately linear single-valued function. Since the heat from thermal runaway originates from the chemical reaction heat of the electrolyte, separator, and tab materials, as well as the Joule heat generated by the internal current, the temperature rise rate of the cells in a battery pack with a large heat capacity increases at different stages during thermal runaway, but the cell temperature changes continuously without abrupt changes.

[0081] Anomaly temperature datasets represent temperature data sets that deviate from the expected temperature rise pattern during battery thermal runaway, instead exhibiting abrupt temperature changes. The primary factor causing these abrupt temperature changes is thermocouple electromagnetic interference. For example, the spatial electromagnetic field generated by the short-circuit current between the positive and negative terminals of the battery cell induces a voltage on the thermocouple leads. Similarly, the spatial electromagnetic field generated by arcing or flashover within the battery pack also induces a voltage on the thermocouple leads. These induced voltages lead to abrupt temperature changes during battery thermal runaway, resulting in the abnormal temperature data.

[0082] In related solutions, battery thermal runaway is a process of increasing temperature. Common filtering methods include sampling the battery temperature N times consecutively per unit time, removing the maximum and minimum values, and averaging the remaining data. However, this method distorts the details of the temperature change curve. To address these issues, this application's embodiment filters normal temperature data and abnormal temperature data caused by electromagnetic interference by setting a range for the rate of temperature change at each time point during thermocouple testing. Specifically, it filters out normal temperature datasets whose rate of temperature change meets the range, and uses the data remaining after filtering out normal temperature datasets as the abnormal temperature dataset.

[0083] In one optional embodiment, step 2021 specifically includes:

[0084] Step 20211: Select the first temperature data from the temperature data whose temperature change rate is not greater than the target temperature change rate threshold to obtain the normal temperature dataset;

[0085] Step 20212: Filter out the second temperature data from the temperature data whose temperature change rate is greater than the target temperature change rate threshold to obtain the abnormal temperature dataset.

[0086] Here, step 20212 can also be: filter out the normal temperature dataset from the temperature data and use it as the abnormal temperature dataset.

[0087] The target temperature change rate threshold is determined through the following steps:

[0088] (1) Obtain a first temperature range and a first preset temperature change rate corresponding to the first temperature range, and a second temperature range and a second preset temperature change rate corresponding to the second temperature range; wherein any temperature value in the second temperature range is greater than any temperature value in the first temperature range.

[0089] Here, any temperature value in the second temperature range is greater than any temperature value in the first temperature range. Since the rate of temperature increase increases at different stages during the battery thermal runaway process, and the temperature increases over time, it can be concluded that the rate of change of the first preset temperature is less than the rate of change of the second preset temperature.

[0090] (2) If the temperature data obtained at the current time point belongs to the first temperature range, the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the first preset temperature change rate.

[0091] Specifically, the first preset temperature change rate is set to ΔT1, and the temperature data acquired at the previous time point is Ta. n-1 The temperature data obtained at the current time point is Ta. n The threshold for the rate of change of the target temperature at the current time point is Tc. If the temperature data Ta acquired at the current time point is detected... n If it falls within the first temperature range, then Tc = Ta n-1 +ΔT1×t, where t represents the time interval and n is a positive integer. Determine Ta n The magnitude relationship between Tc and Ta, if Ta is detected n If it is greater than Tc, then Ta n This is abnormal temperature data; if Ta is detected... n If Ta is less than or equal to Tc, then Ta n These are normal temperature data.

[0092] (3) If the temperature data obtained at the current time point belongs to the second temperature range, the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the second preset temperature change rate.

[0093] Specifically, the second preset temperature change rate is set to ΔT2, and the temperature data acquired at the previous time point is Ta. n-1 ', The temperature data obtained at the current time point is Ta. n ', The threshold for the rate of change of the target temperature at the current time point is Tc', If the temperature data Ta acquired at the current time point is detected... n If ' belongs to the second temperature range, then Tc = Tan-1 '+ΔT2×t, where t represents the time interval and n is a positive integer. Determine Ta n The relationship between ' and Tc', if Ta is detected n If ' is greater than Tc', then Ta n ' represents abnormal temperature data; if Ta is detected... n If 'less than or equal to Tc', then Ta n ' represents normal temperature data.

[0094] In real-world battery thermal runaway scenarios, assuming the battery is charged at a preset target current rate during thermal runaway, the first and second temperature ranges will differ depending on the preset target current rate. Figure 3 In this calculation, the first temperature range is the temperature range between temperature T1 and temperature T2, and the second temperature range is the range greater than temperature T2. For example, when the preset target multiplier is 1°C, T1 is approximately 26°C and T2 is approximately 84°C; when the preset target multiplier is 2°C, T1 is approximately 26°C and T2 is approximately 95°C; when the preset target multiplier is 3°C, T1 is approximately 26°C and T2 is approximately 101°C; and when the preset target multiplier is 4°C, T1 is approximately 26°C and T2 is approximately 103°C. At any of the above preset target multipliers, the curve pointed to by A represents the third preset temperature change rate of less than 0.01°C / s, the curve pointed to by B represents the first preset temperature change rate of 0.15°C / s, and the curve pointed to by C represents the second preset temperature change rate of 10°C / s. When calculating the target temperature change rate threshold corresponding to the current time point, ΔT1 is 0.15°C / s, ΔT2 is 10°C / s, and t is 1 second.

[0095] Step 2022: Determine the first temperature change curve based on the normal temperature dataset, and determine the second temperature change curve based on the abnormal temperature dataset.

[0096] Here, according to step 2022, normal temperature dataset and abnormal temperature dataset will be obtained. On a graph with time on the horizontal axis and temperature on the vertical axis, the first temperature change curve of normal temperature data and the second temperature change curve of abnormal temperature data will be plotted over time.

[0097] When plotting the first temperature change curve, for certain time points where normal temperature data is unavailable, the first temperature change curve can be fitted by combining the corresponding normal temperature data from the preceding and following time points. This makes the first temperature change curve more accurate when used as a reference curve. However, for the second temperature change curve, since the data on the second temperature change curve represents temperature data affected by electromagnetic interference, it is necessary to plot the second temperature change curve based on the actual measured abnormal temperature data.

[0098] For example, such as Figure 4 As shown, the first temperature change curve and the second temperature change curve are plotted on the same time axis with lines of different thicknesses, where 401 represents the first temperature change curve and 402 represents the second temperature change curve.

[0099] Step 2023: Referencing the first temperature change curve, extract waveform features from the second temperature change curve.

[0100] Here, the first temperature change curve is used as a reference curve, and the second temperature change curve is compared with the first temperature change curve. Specifically, the temperature data on the first temperature change curve and the temperature data on the second temperature change curve at the same time point can be compared.

[0101] In one optional embodiment, abnormal features can be analyzed from waveform characteristics. Specifically, the abnormal features include a first abnormal feature and / or a second abnormal feature. The first abnormal feature can be represented using waveform characteristics corresponding to a short circuit inside the battery, and the second abnormal feature can be represented using waveform characteristics corresponding to arcing, flashover, or sparking inside the battery.

[0102] In step S203, abnormal characteristics during the battery thermal runaway test are determined based on waveform features. Specifically, when the abnormal characteristics include a first abnormal characteristic and / or a second abnormal characteristic, step S203 includes:

[0103] Step 2031: If the waveform features include a first target waveform whose amplitude changes beyond the first amplitude range and whose direction is bidirectional, then the first target waveform and the bidirectional direction are determined as the first abnormal feature in the battery thermal runaway test process.

[0104] Step 2032: If the waveform features include a second target waveform in which the amplitude changes within the second amplitude range and the direction of the second target waveform is unidirectional, then the second target waveform and the unidirectional direction are determined as the second abnormal feature in the battery thermal runaway test process.

[0105] In steps 2031 and 2032, the amplitude and direction of the oscillation waveform in the second temperature change curve are analyzed using the first temperature change curve as a reference curve.

[0106] In this embodiment, the oscillation waveform is mainly distinguished by amplitude and direction. One type is a first target waveform whose amplitude changes beyond a first amplitude range, and the other type is a second target waveform whose amplitude changes within a second amplitude range. For example, Figure 4As shown, the second temperature change curve indicated by 4021 has upward and downward peak waveforms, and the second temperature change curve indicated by 4022 has an upward peak waveform. The amplitude of the peak waveform of the second temperature change curve indicated by 4021 is greater than the amplitude of the peak waveform of the second temperature change curve indicated by 4022.

[0107] Among them, the waveforms of the three faults, namely sparking, arcing, and flashover, are all oscillating waveforms. Because the current formed by the breakdown of the air medium due to sparking, arcing, or flashover increases and then decreases, it will show oscillating changes on the second temperature change curve.

[0108] In this way, because the larger the change in short-circuit current of the battery cell, the greater its energy, the induced voltage generated by the electromagnetic field on the thermocouple leads exhibits an oscillating waveform, thus appearing on the second temperature change curve. The voltage waveform generated by internal arcing or flashover is even narrower and more complex, and because its energy is relatively smaller, the induced voltage generated by its electromagnetic field on the thermocouple leads also exhibits an oscillating waveform, thus also appearing on the second temperature change curve. Since the amplitude of the oscillating waveform caused by the battery cell short circuit is much larger than that caused by arcing, arcing, or flashover, the amplitude of the oscillating waveform caused by the battery cell short circuit on the second temperature change curve is much larger than that caused by arcing, arcing, or flashover. Furthermore, the oscillating waveform caused by the battery cell short circuit includes both upward and downward waveform directions, while the oscillating waveform caused by arcing, arcing, or flashover only includes one waveform direction. For example, the amplitude of the oscillating waveform caused by the battery cell short circuit is about 2 to 3 orders of magnitude larger than that caused by arcing, arcing, or flashover.

[0109] For example, such as Figure 4 As shown, 4021 indicates that the second temperature change curve has upward and downward peak waveforms. From this peak waveform, the first abnormal feature can be extracted, such as the first target waveform whose amplitude changes exceed the first amplitude range and the bidirectional direction of the first target waveform; 4022 indicates that the second temperature change curve has upward peak waveforms. From this peak waveform, the second abnormal feature can be extracted, such as the second target waveform whose amplitude changes within the second amplitude range and the unidirectional direction of the second target waveform.

[0110] Step S204, the step of determining the battery fault corresponding to the abnormal characteristics, specifically includes:

[0111] Step 2041: If the detected abnormal feature is the first abnormal feature, then the battery fault is determined to be an internal fault of the battery cell.

[0112] For example, internal cell faults mainly include short-circuit faults. Because the short-circuit current between the positive and negative electrodes of the cell varies greatly (up to several hundred amperes), and this short-circuit current increases and then decreases again, the second temperature change curve will include a large-amplitude oscillating waveform, with amplitudes ranging from over 800°C to below 0°C. This far exceeds the maximum temperature for thermal runaway in lithium batteries (around 600°C).

[0113] Step 2042: If the detected abnormal feature is the second abnormal feature, then the battery fault is determined to be a fault between two adjacent cells.

[0114] For example, faults between two adjacent cells include arcing, flashover, and short circuit. For a short circuit between the positive and negative terminals of a cell, the current from arcing, flashover, or short circuit within the battery pack is much smaller, resulting in much less electromagnetic energy. The second temperature change curve will include oscillating waveforms with relatively small amplitudes, approximately 2 to 3 orders of magnitude. For example, the waveform is typically a series of small-amplitude sawtooth patterns, but the waveform shape is affected by the time axis of the temperature curve.

[0115] As can be seen from steps 2041 and 2042, the first and second abnormal features can be analyzed from the waveform features extracted from the second temperature change curve. Furthermore, by using the characteristics of the obtained abnormal features, the faults that occur in the battery can be quickly identified. This is of great significance for improving the arrangement and interconnection of cells in the battery pack, the isolation and insulation methods between cells, and the setting and optimization of the heating film.

[0116] Furthermore, if multiple cells within the battery pack experience short circuits at roughly the same time, the release of heat energy from thermal runaway can be very intense, potentially leading to battery casing rupture and violent ejection of high-temperature gaseous electrolyte and reactants. This application's embodiments also allow for the extraction of the short-circuit fault occurrence time from the battery pack's temperature test data using a second temperature curve, referencing a first temperature curve. This enables targeted improvements to the cell arrangement, interconnection methods, cell isolation and insulation methods, and the placement and optimization of the heating film within the battery pack to avoid the aforementioned problems.

[0117] By comparing the timing of short circuits, the order of thermal propagation between cells can be deduced. Based on this, it's possible to determine how to optimize thermal propagation isolation measures and adopt more effective pressure relief designs to disperse the energy release order of each cell within the battery pack during thermal runaway. This reduces the severity of thermal runaway energy release, prevents casing rupture, reduces the intensity of high-temperature gas-liquid ejection, and mitigates external damage.

[0118] In step S205, the step of clearing the battery fault according to the battery fault includes:

[0119] If the battery fault is internal to the cell, the fault clearing methods include one of the following: increasing the spacing between the cell tabs and other structures in the battery pack, or changing the cell packaging process.

[0120] If the battery fault is between two adjacent cells, the fault clearing methods include one of the following: changing the cell arrangement, changing the cell interconnection method, adding heat insulation material or heat dissipation device between two adjacent cells.

[0121] For example, when monitoring thermal runaway of the cell tabs, if a potential fault is detected at the cell tabs, the spacing between the cell tabs and other structures in the battery pack can be increased; when monitoring thermal runaway of the middle area of ​​the cell, if a potential fault is detected in the middle area of ​​the cell, structures such as insulating partitions can be added to the middle area of ​​the cell; if a potential fault is detected in the middle area of ​​the battery casing, the cell packaging process can be improved to prevent battery leakage.

[0122] Specifically, the main measures for improving the battery pack are thermal isolation, such as: a battery pack with internal double-row cells connected in series can be changed into two external single-row cell battery packs connected in series; heat insulation materials or heat dissipation devices are added between the cells in the battery pack; and explosion-proof vent valves with larger flow rates are used.

[0123] Furthermore, in normal thermal runaway tests, phenomena such as arcing, flashover, and sparking between cells occur after a short circuit. If these phenomena occur before a short circuit, and it is confirmed that they are not interference introduced by the experiment, it can be determined that there is an insulation problem inside the battery pack.

[0124] The aforementioned methods are significant for improving the cell arrangement and interconnection within the battery pack, the cell isolation and insulation methods, and the setting and optimization of the heating film, and also have a certain degree of universality. By promptly addressing faulty batteries, the spread of thermal runaway within the battery pack can be effectively suppressed, thereby improving battery safety.

[0125] The battery fault determination method provided in this application can quickly identify and process battery faults based on the waveform characteristics of temperature change curves during battery thermal runaway, effectively suppressing the spread of thermal runaway within the battery pack and improving battery safety. Furthermore, by dividing temperature data into abnormal and normal datasets and plotting different temperature change curves for each, the waveform characteristics of the two temperature change curves can be compared. Using the first temperature change curve as a benchmark, abnormal characteristics are determined based on waveform features and direction, thereby identifying the battery fault type. The entire data processing process is simple and facilitates rapid identification of internal battery fault types during thermal runaway. This method is significant for improving cell arrangement, interconnection methods, cell isolation and insulation methods, and the setting and optimization of heating films within battery packs, and also possesses a certain degree of versatility.

[0126] Furthermore, the embodiments of this application are applicable not only to the analysis of temperature data obtained by thermocouples in battery packs that have experienced thermal runaway, but also to the analysis of temperature data obtained by thermocouples in battery packs that have not experienced thermal runaway. Specifically, for batteries that have not experienced thermal runaway, the method provided in the embodiments of this application may reveal instances of arcing, flashover, or other disturbances that occurred inside the battery pack during battery operation, indicating a serious problem of deteriorated insulation within the battery pack. This deterioration in internal insulation may be related to cell damage and leakage, a decrease in the quality of the battery casing, or rainwater infiltration into the power cord. By analyzing the temperature data within the battery pack, products with safety risks can be identified and preventative measures can be taken.

[0127] Based on the same inventive concept, this application also provides a battery fault determination device corresponding to the battery fault determination method. Since the principle of the device in this application is similar to the battery fault determination method described above in this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0128] Please see Figure 5 , Figure 5 This is a schematic diagram of a battery fault determination device provided in an embodiment of this application. Figure 5 As shown, the device 500 includes:

[0129] The data acquisition module 501 is used to acquire temperature data at multiple time points during the battery thermal runaway test.

[0130] The feature extraction module 502 is used to extract waveform features from the temperature change curve based on the temperature data.

[0131] The anomaly determination module 503 is used to determine the abnormal characteristics during the battery thermal runaway test based on waveform characteristics.

[0132] The fault determination module 504 is used to determine the battery fault corresponding to the abnormal characteristics; wherein, the battery fault is a fault inside the cell or a fault between two adjacent cells.

[0133] The fault clearing module 505 is used to clear the battery faults based on the battery faults.

[0134] In an optional embodiment, the anomaly features include a first anomaly feature and / or a second anomaly feature, and the anomaly determination module 503 is specifically used for:

[0135] If the waveform features include a first target waveform whose amplitude changes exceed the first amplitude range and the direction of the first target waveform is bidirectional, then the first target waveform and the bidirectional direction are determined as the first abnormal feature in the battery thermal runaway test process.

[0136] If the waveform features include a second target waveform in which the amplitude changes within the second amplitude range and the direction of the second target waveform is unidirectional, then the second target waveform and the unidirectional direction are determined as the second abnormal feature in the battery thermal runaway test process.

[0137] In an optional embodiment, the fault determination module 504 is used to:

[0138] If the detected abnormal feature is the first abnormal feature, then the battery fault is determined to be an internal fault of the battery cell.

[0139] If the detected abnormal feature is the second abnormal feature, then the battery fault is determined to be a fault between two adjacent cells.

[0140] In an optional embodiment, the fault clearing module 505 is specifically used for:

[0141] If the battery fault is internal to the cell, the fault clearing methods include one of the following: increasing the spacing between the cell tabs and other structures in the battery pack, or changing the cell packaging process.

[0142] If the battery fault is between two adjacent cells, the fault clearing methods include one of the following: changing the cell arrangement, changing the cell interconnection method, adding heat insulation material or heat dissipation device between two adjacent cells.

[0143] In an optional embodiment, the feature extraction module 502 is specifically used for:

[0144] The temperature data is filtered to obtain normal temperature datasets and abnormal temperature datasets;

[0145] A first temperature change curve is determined based on a normal temperature dataset, and a second temperature change curve is determined based on an abnormal temperature dataset.

[0146] Based on the first temperature change curve, waveform features are extracted from the second temperature change curve.

[0147] In an optional embodiment, the feature extraction module 502 is further configured to:

[0148] The normal temperature dataset is obtained by filtering out the first temperature data whose temperature change rate is not greater than the target temperature change rate threshold from the temperature data.

[0149] The abnormal temperature dataset is obtained by filtering out the second temperature data whose temperature change rate is greater than the target temperature change rate threshold from the temperature data.

[0150] In an optional embodiment, the feature extraction module 502 is further configured to determine the target temperature change rate threshold through the following steps:

[0151] Obtain a first temperature range and a first preset temperature change rate corresponding to the first temperature range, as well as a second temperature range and a second preset temperature change rate corresponding to the second temperature range; wherein any temperature value in the second temperature range is greater than any temperature value in the first temperature range.

[0152] If the temperature data obtained at the current time point belongs to the first temperature range, then the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the first preset temperature change rate.

[0153] If the temperature data obtained at the current time point belongs to the second temperature range, then the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the second preset temperature change rate.

[0154] In one optional embodiment, the data acquisition module 501 is specifically used for:

[0155] Place the thermocouple at the target location on the battery;

[0156] During the battery thermal runaway test, the thermoelectric potential corresponding to multiple time points collected by the thermocouple at the target location is obtained;

[0157] Based on the functional relationship between thermoelectric potential and temperature, temperature data corresponding to multiple time points are determined.

[0158] In one optional embodiment, the target location includes at least one of the following: the middle region of the battery cell, the battery cell tab, the center point of the heating film, the perforation location, the positive electrode copper busbar, the middle region of the battery casing, the screw hole, and the battery heat dissipation surface.

[0159] The battery fault determination device provided in this application can quickly identify and process battery faults based on the waveform characteristics of temperature change curves during battery thermal runaway, effectively suppressing the spread of thermal runaway within the battery pack and improving battery safety. Furthermore, by dividing temperature data into abnormal and normal datasets and plotting different temperature change curves for each, the device can compare the waveform characteristics of the two temperature change curves. Using the first temperature change curve as a benchmark, abnormal characteristics are determined based on waveform features and direction, thereby identifying the battery fault type. The entire data processing process is simple and facilitates rapid identification of internal battery fault types during thermal runaway. This is significant for improving cell arrangement, interconnection methods, cell isolation and insulation methods, and the setting and optimization of heating films within the battery pack, and also has a certain degree of versatility.

[0160] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 6 As shown, the electronic device 600 includes a processor 601, a memory 602, and a bus 603.

[0161] The memory 602 stores machine-readable instructions executable by the processor 601. When the electronic device 600 is running, the processor 601 communicates with the memory 602 via the bus 603. When the machine-readable instructions are executed by the processor 601, they can perform the operations described above. Figure 2 The steps of the battery fault determination method in the illustrated method embodiment can be found in the method embodiment for specific implementation, and will not be repeated here.

[0162] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 2 The steps of the battery fault determination method in the illustrated method embodiment can be found in the method embodiment for specific implementation, and will not be repeated here.

[0163] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0164] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0165] The units described as separate components may or may not be physically separate. The components shown as units 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0166] In addition, the functional units in the various embodiments of this application 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.

[0167] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0168] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The scope of protection of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining battery faults, characterized in that, The method includes: During the battery thermal runaway test, temperature data were acquired at multiple time points. The temperature data is filtered to obtain a normal temperature dataset and an abnormal temperature dataset; a first temperature change curve is determined based on the normal temperature dataset, and a second temperature change curve is determined based on the abnormal temperature dataset; waveform features are extracted from the second temperature change curve with reference to the first temperature change curve. Based on the waveform characteristics, determine the abnormal features during the battery thermal runaway test process; Identify the battery fault corresponding to the abnormal characteristics; wherein the battery fault is a fault inside the cell or a fault between two adjacent cells; Based on the battery fault, perform fault clearing procedures on the battery.

2. The method according to claim 1, characterized in that, The abnormal features include a first abnormal feature and / or a second abnormal feature. The steps for determining the abnormal features during the battery thermal runaway test based on the waveform features include: If the waveform feature includes a first target waveform in which the amplitude change exceeds the first amplitude range and the direction of the first target waveform is bidirectional, then the first target waveform and the bidirectional direction are determined as the first abnormal feature in the battery thermal runaway test process. If the waveform feature includes a second target waveform in which the amplitude changes within the second amplitude range and the direction of the second target waveform is unidirectional, then the second target waveform and the unidirectional direction are determined as the second abnormal feature in the battery thermal runaway test process.

3. The method according to claim 2, characterized in that, The steps for determining the battery fault corresponding to the abnormal characteristics include: If the detected abnormal feature is the first abnormal feature, then the battery fault is determined to be an internal fault of the battery cell. If the detected abnormal feature is the second abnormal feature, then the battery fault is determined to be a fault between two adjacent cells.

4. The method according to claim 1, characterized in that, The steps for clearing the battery fault according to the aforementioned battery fault include: If the battery fault is an internal fault of the battery cell, the fault clearing method includes one of the following: increasing the spacing between the battery cell tabs and other structures in the battery pack, or changing the battery cell packaging process; If the battery fault is a fault between two adjacent cells, the fault clearing method includes one of the following: changing the cell arrangement, changing the cell interconnection method, adding heat insulation material or heat dissipation device between two adjacent cells.

5. The method according to claim 1, characterized in that, The steps of filtering the temperature data to obtain normal temperature datasets and abnormal temperature datasets include: The first temperature data with a temperature change rate not greater than the target temperature change rate threshold is selected from the temperature data to obtain the normal temperature dataset; The abnormal temperature dataset is obtained by filtering out the second temperature data whose temperature change rate is greater than the target temperature change rate threshold from the temperature data.

6. The method according to claim 5, characterized in that, The target temperature change rate threshold is determined using the following steps: Obtain a first temperature range and a first preset temperature change rate corresponding to the first temperature range, and a second temperature range and a second preset temperature change rate corresponding to the second temperature range; wherein any temperature value in the second temperature range is greater than any temperature value in the first temperature range; If the temperature data obtained at the current time point belongs to the first temperature range, then the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the first preset temperature change rate. If the temperature data obtained at the current time point belongs to the second temperature range, then the target temperature change rate threshold corresponding to the current time point is determined based on the temperature data obtained at the previous time point and the second preset temperature change rate.

7. The method according to claim 1, characterized in that, The steps for acquiring temperature data at multiple time points during battery thermal runaway testing include: Place the thermocouple at the target location on the battery; During the battery thermal runaway test, the thermoelectric potential corresponding to multiple time points collected by the thermocouple at the target location is obtained; Based on the functional relationship between thermoelectric potential and temperature, temperature data corresponding to multiple time points are determined.

8. The method according to claim 7, characterized in that, The target location includes at least one of the following: the middle area of ​​the battery cell, the battery cell tab, the center point of the heating film, the perforation location, the positive electrode copper busbar, the middle area of ​​the battery casing, the screw hole, and the battery heat dissipation surface.

9. A device for determining battery faults, characterized in that, The device includes: The data acquisition module is used to acquire temperature data at multiple time points during battery thermal runaway testing. The feature extraction module is used to filter the temperature data to obtain a normal temperature dataset and an abnormal temperature dataset; determine a first temperature change curve based on the normal temperature dataset, and determine a second temperature change curve based on the abnormal temperature dataset; and extract waveform features from the second temperature change curve with reference to the first temperature change curve. An anomaly determination module is used to determine the abnormal characteristics during the battery thermal runaway test based on the waveform characteristics. The fault determination module is used to determine the battery fault corresponding to the abnormal characteristics; wherein the battery fault is a fault inside the cell or a fault between two adjacent cells; The fault clearing module is used to clear the battery faults according to the battery faults.

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