Battery safety state detection method, device, apparatus, medium, and product

Abstract

This disclosure provides a method, apparatus, device, medium, and product for detecting the safety status of a battery. The method includes: acquiring charging data of multiple batteries during at least one charging cycle; determining the status indicators of each battery based on the charging data; and detecting the safety status of a target battery by analyzing the outlier degree of its status indicators relative to the status indicators of the multiple batteries. This disclosure solves the problem that detecting the safety status of a battery based on the signal characteristics of a single battery may lead to inaccurate detection results. It improves the accuracy of battery safety status detection by analyzing the outlier degree of the target battery's status indicators among the status indicators of multiple batteries.

Description

Technical Field

[0001] This disclosure relates to the field of battery status detection, and more specifically, to a method, apparatus, equipment, medium, and product for detecting the safety status of a battery. Background Technology

[0002] Lithium-ion batteries, with their significant advantages such as high energy density, long cycle life, and low self-discharge rate, have become dominant in energy storage systems. However, safety issues such as thermal runaway pose a serious threat to the safe operation of energy storage systems. Taking thermal runaway in lithium-ion batteries as an example, once it occurs, the battery releases a huge amount of energy in a short period, causing a rapid rise in battery temperature, which in turn leads to electrolyte decomposition and the generation of large amounts of flammable gases. These flammable gases, when mixed with air, are highly ignitable, causing fires or even explosions, resulting in catastrophic consequences for life, property, and the surrounding environment. Such battery safety issues may even hinder the healthy development of the energy storage industry.

[0003] In related technologies, signals such as voltage, temperature, and current of individual batteries can be collected, and the safety risks of the battery can be identified based on the changing characteristics of these signals. However, due to the complexity of the internal electrochemical reactions during the charging and discharging process of the battery, accurate detection results may not be obtained by using a single observation method. Summary of the Invention

[0004] In view of the problem that detecting the safety status of a battery based on the signal characteristics of a single cell in related technologies may lead to inaccurate detection results, this disclosure proposes a method, apparatus, equipment, medium and product for detecting the safety status of a battery, so as to solve or at least alleviate the above-mentioned problem.

[0005] The first aspect of this disclosure provides a method for detecting the safety status of a battery. The method includes: acquiring charging data of multiple batteries in at least one charging cycle; determining a status index for each battery based on the charging data, wherein the status index is determined based on the internal resistance or voltage of the battery during the charging process; and detecting the safety status of a target battery by analyzing the degree of outlier of the status index of a target battery relative to the status index of the multiple batteries.

[0006] Optionally, the charging data includes battery voltage data and current data, and the status index includes a first index, which characterizes the internal resistance of the battery in a single charging cycle. The step of determining the status index of each battery based on the charging data includes: determining a target time in a single charging cycle of the plurality of batteries where the current change meets a preset condition, wherein the plurality of batteries are connected in series, and the preset condition characterizes the current change exceeding a preset level; and determining the first index of each battery based on the voltage and current data of each battery at a preset time interval from the target time.

[0007] Optionally, the step of detecting the safety status of the target battery by analyzing the outlier degree of the target battery's status indicators relative to the status indicators of the plurality of batteries includes: determining the ratio between the internal resistance of the target battery at a target time and the representative value of the internal resistance of the plurality of batteries at the target time; and determining that the target battery's status is abnormal if the outlier degree of the target battery's internal resistance at the target time relative to the internal resistance of the plurality of batteries at the target time is greater than or equal to a first preset degree and the ratio is greater than or equal to a first preset threshold.

[0008] Optionally, the charging data includes battery voltage data, and the state index includes a second index, which characterizes the dispersion of the battery's off-center voltage across multiple charging cycles. The off-center voltage characterizes the deviation of the battery's voltage from the voltage center of the multiple batteries. The step of determining the state index of each battery based on the charging data includes: for each battery, statistically analyzing the off-center voltage at multiple times in each charging cycle to obtain a statistical value of the off-center voltage in each charging cycle; determining multiple voltage ranges based on the statistical values ​​of the off-center voltage of each battery in each charging cycle; and determining the second index of each battery based on the probability that the statistical value of the off-center voltage of each battery in each charging cycle falls within each voltage range.

[0009] Optionally, the status index further includes a third index, which characterizes the difference in the off-center voltage statistics of the battery in the first and last charging cycles of the plurality of charging cycles, or the rate of change of the off-center voltage statistics of the battery in the plurality of charging cycles. The step of detecting the safety status of the target battery by analyzing the outlier degree of the target battery's status index relative to the status indexes of the plurality of batteries includes: determining a second outlier degree of the target battery's second index relative to the second indexes of the plurality of batteries; and determining that the target battery's status is abnormal in response to the second outlier degree being greater than or equal to a second preset degree and the third index of the target battery meeting a preset index condition.

[0010] Optionally, for each battery, the off-center voltage statistics of the battery in each charging cycle are obtained by: determining the voltage of each of the multiple batteries at multiple moments in the current charging cycle; determining the off-center voltage of the current battery's voltage at that moment relative to the voltage center of the multiple batteries at that moment for each of the multiple moments; and determining the off-center voltage statistics of the current battery in the current charging cycle by statistically analyzing the off-center voltage of the current battery at each moment.

[0011] Optionally, for any given time, the voltage center is determined by: taking the center value of the voltage of the plurality of batteries at that time as the voltage center; or, taking the voltage range formed by the voltages of the plurality of batteries at multiple preset positions at that time as the voltage center.

[0012] Optionally, the status indicators include a first indicator for a single charging cycle and a second indicator for multiple charging cycles. The step of detecting the safety status of the target battery by analyzing the outlier degree of the target battery's status indicators relative to the status indicators of the multiple batteries includes: detecting the safety status of the target battery based on the first indicator to obtain a first detection result; detecting the safety status of the target battery based on the second indicator to obtain a second detection result; and determining a final detection result for the safety status of the target battery based on the first detection result and the second detection result.

[0013] A second aspect of this disclosure provides a battery safety status detection device, the detection device comprising: an acquisition unit configured to acquire charging data of a plurality of batteries in at least one charging cycle; a determination unit configured to determine a status index of each battery based on the charging data, wherein the status index is determined based on the internal resistance or voltage of the battery during charging; and a detection unit configured to detect the safety status of a target battery by analyzing the degree of outlier of the status index of a target battery among the plurality of batteries relative to the status index of the plurality of batteries.

[0014] A third aspect of this disclosure provides an electronic device comprising: a processor; and a memory for storing processor-executable instructions, wherein the processor-executable instructions, when executed by the processor, cause the processor to perform a battery safety status detection method according to this disclosure.

[0015] A fourth aspect of this disclosure provides a computer-readable storage medium that, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform a battery safety state detection method according to this disclosure.

[0016] A fifth aspect of this disclosure provides a computer program product including computer-executable instructions that, when executed by at least one processor, implement a method for detecting battery safety status according to this disclosure.

[0017] According to the battery safety status detection scheme disclosed herein, the status indicators of each battery can be determined based on the charging data of multiple batteries. By analyzing the outlier degree of the target battery's status indicators among the status indicators of multiple batteries, the safety status of the target battery can be detected. In this way, detection bias in the analysis of individual batteries can be avoided, and the accuracy of battery safety status detection can be improved. Attached Figure Description

[0018] These and / or other aspects and advantages of this disclosure will become clearer and more readily understood from the following detailed description of embodiments of this disclosure taken in conjunction with the accompanying drawings.

[0019] Figure 1 This is a schematic flowchart illustrating a method for detecting the safety status of a battery according to an exemplary embodiment of the present disclosure.

[0020] Figure 2 This is a schematic flowchart illustrating the determination of a second indicator in a battery safety status detection method according to an exemplary embodiment of the present disclosure.

[0021] Figure 3This is a schematic diagram illustrating the calculation results of the internal resistance of each cell in the battery pack in a battery safety status detection method according to an exemplary embodiment of the present disclosure.

[0022] Figure 4A This is a schematic diagram illustrating the average off-center voltage of a plurality of batteries in a battery safety status detection method according to an exemplary embodiment of the present disclosure.

[0023] Figure 4B This is a schematic diagram illustrating the coefficients of variation of multiple batteries in a battery safety status detection method according to an exemplary embodiment of the present disclosure.

[0024] Figure 5 This is a schematic diagram illustrating a battery safety status detection device according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0025] The following detailed embodiments are provided to aid the reader in gaining a comprehensive understanding of the methods, apparatus, and / or systems described herein. However, various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but may be changed as will become clear upon understanding this disclosure, except for operations that must occur in a specific order. Furthermore, for clarity and conciseness, descriptions of features known in the art may be omitted.

[0026] As mentioned above, in related technologies, there is a problem that detecting the safety status of a battery based on the signal characteristics of a single cell may lead to inaccurate detection results.

[0027] Specifically, based on different triggering paths of thermal runaway, from the perspectives of internal defects and external abuse, and combined with real-time signals such as cell voltage, cell temperature, and current collected by the Battery Management System (BMS), the risk of battery thermal runaway can be identified by focusing on the extreme values ​​and consistency characteristics of the signals (such as rapid rise in local temperature, abnormal dispersion of cell voltage, etc.).

[0028] However, in related technologies, abnormal cells are identified solely from sources such as abnormal internal resistance or abnormal cell voltage. In this regard, the internal electrochemical reactions during battery charging and discharging are complex, and using a single observation method may lead to false alarms, affecting the practicality of the battery warning system.

[0029] Furthermore, in related technologies, internal short-circuit anomalies in battery cells are mainly identified by calculating the internal temperature or internal short-circuit resistance of the cell based on parameters such as current, voltage, and external temperature. However, the heat generated when a micro-short circuit occurs inside the cell is easily dissipated; therefore, the internal temperature only rises significantly when there is a severe internal short circuit. Moreover, the calculation of the internal short-circuit resistance of a single battery cell is affected by the error of a single signal sampling, leading to inaccurate calculations and making it difficult to accurately detect micro-short circuits within the cell.

[0030] Furthermore, in related technologies, individual cell voltage deviation characteristics (such as the voltage multiple of the central cluster and the voltage entropy value of the off-center position) are calculated based on data from a single charging process. However, deviations in individual cell voltage during a single charge may be due to factors such as differences in State of Charge (SOC) and capacity. Because of the lack of long-term individual cell voltage consistency analysis, this approach struggles to distinguish between random fluctuations and genuine anomalies, posing a risk of false alarms. Here, SOC represents the remaining battery capacity or the ratio of charged capacity to full capacity.

[0031] In view of this, the present disclosure provides a method for detecting battery safety status, a device for detecting battery safety status, an electronic device, a computer-readable storage medium, and a computer program product, which can solve or at least alleviate the above-mentioned problems.

[0032] According to a first aspect of an exemplary embodiment of the present disclosure, a method for detecting the safety status of a battery is provided. This method can be performed by an electronic device, which may be configured or communicatively connected to a battery system such as an electrochemical energy storage system, for monitoring or providing early warning of the status of each battery in the system. The system may, for example, execute corresponding battery safety strategies based on the detection results of the method.

[0033] According to exemplary embodiments of this disclosure, such as Figure 1 As shown, the method for detecting the battery's safety status may include the following steps: In step S110, charging data of multiple batteries in at least one charging cycle can be acquired.

[0034] As an example, the charging data for each battery may include the battery's voltage data and / or current data.

[0035] As an example, a charging cycle can refer to a single continuous charging process. The start and end times of charging, as well as the initial and final battery levels, are not particularly restricted. The amount of charge in different charging cycles can be the same or different. The charging data for each charging cycle can be data for the entire charging process within that cycle, or data for a portion of the charging process (e.g., a charging segment). For example, it can be data within the range of 20% ≤ SOC ≤ 90%, or data within other SOC ranges. Here, SOC represents the remaining battery capacity or the ratio of charged capacity to full capacity (State of Charge).

[0036] In the embodiments of this disclosure, charging data from one charging cycle can be used to identify the battery state on a short time scale; charging data from multiple charging cycles can also be used to identify the battery state on a long time scale. Furthermore, the identification results at different time scales can be compared to obtain the final identification result (which will be described in detail below).

[0037] Furthermore, as an example, the aforementioned multiple batteries can be connected in series. For instance, the detection method according to embodiments of this disclosure can be used to detect each battery in a battery energy storage system comprising multiple batteries to achieve safety detection of the battery energy storage system. Additionally, in embodiments of this disclosure, a single battery cell can be, for example, but not limited to, a cell within a battery pack.

[0038] In step S120, the state indicators of each battery can be determined based on the charging data.

[0039] Here, the state indicators can be determined based on the battery's internal resistance or voltage during charging. As an example, the state indicators may include a first indicator and / or a second indicator, whereby the first indicator characterizes the battery's internal resistance in a single charging cycle, and the second indicator characterizes the dispersion of the battery's off-center voltage across multiple charging cycles, wherein the off-center voltage characterizes the difference in the battery's voltage relative to the voltage centers of multiple batteries.

[0040] Specifically, in the example where the status indicator includes a first indicator, the charging data may include battery voltage data and current data. Step S120 may include: determining a target time in which the current change in a single charging cycle of multiple batteries meets a preset condition; and determining the first indicator of each battery based on the voltage data and current data of each battery at a preset time interval from the target time.

[0041] In this example, multiple batteries are connected in series, and a preset condition characterizes a current change exceeding a preset level. Here, because multiple batteries are connected in series, the current change is the same for all batteries.

[0042] As an example, the preset conditions may include: the change in current at the target time is greater than or equal to a first preset value; the maximum / minimum current value within a first time range determined based on the target time is less than or equal to a second preset value; and the maximum / minimum current value within a second time range determined based on the target time is less than or equal to a third preset value.

[0043] Here, the first, second, and third preset values ​​can be set according to actual needs. For example, the first preset value can be 1 / 3C, and the second and third preset values ​​can both be 1.05. The first time range can be, for example, a preset time period before the target time, and the second time range can be, for example, a preset time period after the target time. The durations of the first and second time ranges can be the same or different.

[0044] For example, a target time t can be selected if the change in current meets at least one of the following preset conditions: the change in current at target time t is ≥ 1 / 3C; the maximum / minimum current value in the first time range [t-5, t) is ≤ 1.05; and the maximum / minimum current value in the second time range (t, t+5) is ≤ 1.05.

[0045] When at least one target time t is determined based on charging data, the voltage and current data of each battery at a preset time interval from the target time can be determined from the charging data. Here, the preset time interval can be determined, for example, based on the boundary between a first time range and a second time range. Taking the above example, the preset time interval can be 5 seconds. Specifically, the voltage list of each individual battery at time t-5 and the voltage list of each individual battery at time t+5 can be recorded to calculate the internal resistance of the individual battery as a first indicator.

[0046] For example, the first metric of each individual cell can be calculated using the following formula (1): (1) in, Indicates the first The internal resistance of each individual cell (as the primary indicator). This indicates a preset time interval (e.g., 5 seconds). Indicates the first The first single cell Voltage at time, Indicates the first The first single cell Voltage at time, Indicates the first The first single cell The change in current at time (i.e., the target time).

[0047] Using the above method, the internal resistance of each cell can be calculated by taking the voltage change of the individual cells before and after the current change as a characteristic value on a short time scale such as a single charging cycle, which helps to detect the battery status more accurately in the future.

[0048] In an example where the status indicator includes a second indicator, the charging data may include battery voltage data, such as... Figure 2 As shown, step S120 may include: In step S210, for each battery, the off-center voltage at multiple times in each charging cycle can be statistically analyzed to obtain the statistical value of the off-center voltage of the battery in each charging cycle.

[0049] As described above, the off-center voltage characterizes the degree of deviation or difference of the voltage of a single cell relative to the voltage center of multiple cells. Here, the voltage center can be represented by the center voltage of each cell, or by the center voltage range of each cell, for example, the range from the lower quartile voltage to the upper quartile voltage as the center voltage range. However, the embodiments of this disclosure are not limited to this. The voltage center is intended to characterize the central position of the voltage distribution of multiple cells, and other voltage parameters or voltage ranges can also be used as the voltage center.

[0050] As an example, for any moment in a charging cycle, the voltage center can be determined in the following ways: by taking the center value of the voltages of multiple batteries at that moment as the voltage center; or, based on the voltages of the multiple batteries at that moment being at multiple preset positions, taking the voltage range formed by the voltages at the multiple preset positions as the voltage center. Here, the preset positions may include, but are not limited to, the lower quartile voltage, the upper quartile voltage, etc.

[0051] Specifically, in one example, the voltage center can be represented by the center voltage of each cell, and the off-center voltage of each individual cell can be represented by the following equation (2): (2) in, Indicates the first Frame (here, a frame can refer to the voltage acquisition time), the first The off-center voltage of a single cell Indicates the first Frame, First The voltage of each individual cell, Indicates the first Frame off-center voltage.

[0052] In another example, the voltage center can be represented by the center voltage range of each cell. The off-center voltage of each individual cell can be represented as the average voltage of the off-center cluster, which can be determined based on the average voltage of the center voltage range and the voltage of the individual cells, for example, by the following equation (3): (3) in, Indicates the first Frame, First The off-center voltage of a single cell Indicates the first Frame, First The voltage of each individual cell, Indicates the first Frame center bit voltage, Indicates the first Frame-level quartile voltage Indicates the first The quartile voltage on the frame, of which, Indicates the center voltage range.

[0053] Although the lower quartile and upper quartile voltages are used as examples to determine the center voltage range, the embodiments of this disclosure are not limited to this, and the center voltage range can also be determined based on other voltage parameters.

[0054] Using the above methods, you can flexibly choose the method for calculating the center voltage and the off-center voltage according to actual needs.

[0055] Based on the above example of determining the off-center voltage, the off-center voltage statistics of each battery in each charging cycle can be obtained in the following way: for multiple moments in the current charging cycle, determine the voltage of each of the multiple batteries; for each of the multiple moments, determine the off-center voltage of the current battery's voltage at that moment relative to the voltage center of the multiple batteries at that moment; by statistically analyzing the off-center voltage of the current battery at each moment, determine the off-center voltage statistics of the current battery in the current charging cycle.

[0056] Specifically, for each of the multiple time points, the off-center voltage of a single battery relative to the voltage center of all batteries at that time point can be determined first. Then, the off-center voltages at each time point can be statistically analyzed to obtain the statistical value of the off-center voltage for that charging cycle. Here, the statistical value of the off-center voltage is, for example, but not limited to, the average value. For example, the statistical value of the off-center voltage can be represented by the following formula (4): (4) in, Indicates the first charge in the current charging cycle. The average deviation of the voltage of each individual cell from the center voltage (as a statistical value of the off-center voltage), where N represents the total number of frames in the current charging cycle. Indicates the first Frame, First The off-center voltage of each individual cell. Here, in an example where the voltage center is represented by the center potential voltage of each cell, It can be determined based on the above equation (2); in the example where the voltage center is represented by the central voltage range of the voltage of each battery, It can be determined based on the above formula (3).

[0057] Using the above method, the voltage deviation of a single cell from the overall voltage of multiple cells can be determined according to the voltage data acquisition time, and the deviation at multiple time points can be statistically analyzed to facilitate a more accurate analysis of whether there are any abnormalities in the state of the target cell.

[0058] Return to reference Figure 2 In step S220, multiple voltage ranges can be determined based on the off-center voltage statistics of each battery in each charging cycle.

[0059] Here, multiple voltage ranges can be determined by dividing the voltage range based on the maximum and minimum values ​​of the off-center voltage statistics of individual cells in each charging cycle.

[0060] For example, the aforementioned multiple charging cycles can be the m charging processes closest to the time of battery safety status detection. By determining the off-center voltage statistics of each individual cell in the m charging cycles, for example, data of 20%≤SOC≤90% can be taken in the last m charging processes.

[0061] Given the eccentricity voltage statistics of each individual cell in each charging cycle, a matrix of eccentricity voltage statistics of each individual cell in m charging cycles can be formed, as shown in equation (5) below: (5) in, Indicates the first In the first charging cycle Statistical values ​​of the off-center voltage of each individual cell. , where n represents the number of individual cells.

[0062] The extreme values ​​in the matrix of the off-center voltage statistics of each individual cell in m charging cycles can be determined, and the range of the corresponding extreme values ​​of the matrix can be obtained. For example, it can be determined by the following formula (6): (6) in, Represents the range of the matrix. This represents the maximum value among the statistical values ​​of the off-center voltage of each individual cell during m charging cycles. This represents the minimum value among the statistical values ​​of the off-center voltage of each individual cell during m charging cycles.

[0063] The aforementioned multiple voltage intervals can be determined by dividing the voltage range according to the maximum and minimum values ​​mentioned above. Here, the voltage interval can also be called a probability interval. Specifically, it can be defined as follows: and As the window extreme value, and dividing the probability interval, the interval form can be expressed as: ,in, It is a parameter that determines the length of the interval. This is the parameter that determines the number of intervals. The probability interval is used to calculate the total number of times the off-center voltage statistical value of a single cell falls into each voltage interval. Here, and All settings can be customized according to actual needs.

[0064] In step S230, the second index of each battery can be determined based on the probability that the off-center voltage statistical value of each battery falls into each voltage range in each charging cycle.

[0065] In this step, it is possible to analyze which range of the above voltage range the off-center voltage statistics of each battery falls into in each charging cycle, thereby determining the probability distribution of the off-center voltage statistics of the battery.

[0066] For example, the first can be determined by the following formula (7). The probability matrix is ​​formed by calculating the probability that the off-center voltage statistical value of each individual cell falls within the above voltage range (or probability range): (7) in, Indicates the first The single cell fell into the first The probability of each voltage range Indicates the first The single cell fell into the first Number of times in each voltage range This represents the sum of the number of times the voltage of each individual cell falls within any voltage range. This indicates the total number of voltage intervals obtained from the division.

[0067] Given the probability that the off-center voltage statistics of each battery fall within each voltage range in each charging cycle, the entropy of the off-center voltage statistics of each battery can be calculated based on this probability. Here, entropy can represent the degree of dispersion of the off-center voltage statistics of the battery across multiple charging cycles.

[0068] For example, the first charge in m charging cycles can be determined by the following formula (8). The entropy of the off-center voltage statistics of an individual cell; (8) in, It represents the first charging cycle in m charging cycles. The entropy of the off-center voltage statistics of a single cell.

[0069] In this example, the entropy of the off-center voltage statistics of each battery can be used as a second indicator to determine whether the battery is in an abnormal state.

[0070] Return to reference Figure 1 In step S130, the safety status of the target battery can be detected by analyzing the degree of outlier of the target battery's state index relative to the state index of the multiple batteries.

[0071] In this step, the target battery can be any single cell from a plurality of batteries. For example, the detection method according to embodiments of the present disclosure can be used to detect each battery in a battery energy storage system comprising multiple batteries as the target battery, thereby achieving safety detection of the battery energy storage system.

[0072] Here, outlier can characterize the degree of deviation of the state index of a single cell from the data set of state indices of the aforementioned multiple cells, and it can be represented by outlier values.

[0073] In an example where the status indicator includes the first indicator, step S130 may include: determining the ratio between the internal resistance of the target battery at the target time and the representative value of the internal resistance of multiple batteries at the target time; and determining that the status of the target battery is abnormal in response to the outlier degree of the internal resistance of the target battery at the target time relative to the internal resistance of multiple batteries at the target time being greater than or equal to a first preset degree and the ratio being greater than or equal to a first preset threshold.

[0074] As an example, it can be determined whether the outlier level is greater than or equal to a first preset level by comparing the internal resistance of the target battery at the target time with the statistical values ​​of the internal resistance of multiple batteries at the target time. Here, the statistical values ​​of the internal resistance of multiple batteries at the target time can be, for example, but not limited to, the mode, average, etc. of the internal resistance.

[0075] As an example, the statistical value of the internal resistance of multiple batteries at the target time can be the upper limit of the interquartile range. For example, it can be determined by the following formula (9): (9) in, This represents the statistical value of the internal resistance of multiple batteries at the target time. This represents the median of the internal resistance of multiple batteries at the target time. This is a preset coefficient, which can represent the interquartile range multiple in a box plot. It can be an empirical value. In the above formula (9), Indicates the interquartile range. , Indicates the upper quartile. This represents the lower quartile.

[0076] Thus, it can be determined whether the internal resistance of the target battery at the target time satisfies the first condition: To determine whether the outlier of the target battery's internal resistance at a target time relative to the internal resistances of multiple batteries at the target time is greater than or equal to a first preset level, in response to satisfying It can be assumed that the outlier degree is greater than or equal to the first preset degree; in response to not satisfying Therefore, the degree of outlier can be considered to be less than the first preset degree.

[0077] As an example, a representative value of the internal resistance of multiple batteries at a target time can be, for example, but not limited to, the median of the internal resistance of multiple batteries at the target time. This means that the first preset threshold can be set according to actual conditions. In this example, the above ratio can be expressed as... This allows us to determine whether the internal resistance of a single cell at the target time satisfies the second condition: However, the aforementioned representative value is not limited to the median; it can also be the average of the internal resistances of multiple batteries at the target time. or minimum value Correspondingly, the second condition can also be or Here, different first preset thresholds can be set for different representative values.

[0078] In the embodiments of this disclosure, the presence of an abnormality in the battery can be determined based on both the first and second conditions mentioned above. On the one hand, an absolute comparison can be made between the internal resistance of a single battery and the statistical value of multiple battery groups. On the other hand, the relative ratio of the internal resistance of a single battery to the statistical value of multiple battery groups can be compared with a preset threshold. In this way, the safety status of the battery can be comprehensively evaluated. Compared with a single evaluation method such as absolute or relative comparison, the battery status can be determined more accurately, and the accuracy of the detection results can be improved.

[0079] In an example where the status indicator includes a second indicator, step S130 may include: determining the mean and standard deviation of the second indicators of the multiple batteries; and determining the degree of outlier of the second indicator of the target battery relative to the second indicators of the multiple batteries based on the second indicator of the target battery, the mean and the standard deviation.

[0080] For example, the degree of outlier can be represented by the coefficient of variation, which can be determined, for example, by the following equation (10): (10) in, Indicates the first The coefficient of variation of an individual cell. Indicates the first The second metric for a single cell (e.g., the target cell) in a single charging cycle. This represents the average of the second metric for all batteries during the corresponding charging cycle. This represents the standard deviation of the second metric for all batteries in the corresponding charging cycle.

[0081] In some cases, the safety status of the target battery can be determined based on the aforementioned coefficient of variation, for example, to determine the first... Coefficient of variation of an individual cell (e.g., the target cell) Does it meet the following requirements: ≥Preset outlier level, responding to satisfy If the outlier level is greater than or equal to a preset threshold, the individual battery cell can be considered to pose a safety risk, such as the risk of thermal runaway; in response to not meeting this threshold... If the pre-defined outlier level is greater than or equal to the threshold, the individual battery cell can be considered to pose no safety risk.

[0082] In some cases, the state indicators may also include a third indicator, which may characterize the difference between the off-center voltage statistics of the battery in the first and last charging cycles of multiple charging cycles, or the rate of change of the off-center voltage statistics of the battery in the multiple charging cycles.

[0083] For example, in the example where the third index characterizes the difference in the eccentricity voltage statistics of the first and last charging cycles, for m charging cycles, the third index can be represented by the following formula (11): (11) in, Indicates the first The difference in the off-center voltage statistics of an individual cell in the first and last charging cycles of multiple charging cycles. Indicates the first The statistical value of the off-center voltage of each individual cell in the first charging cycle (i.e., the first cycle). Indicates the first The off-center voltage statistics of a single cell in the last charging cycle (i.e., the m-th cycle). Here, the off-center voltage statistics can be determined, for example, by the above equation (4).

[0084] In the example where the third index characterizes the rate of change of the off-center voltage statistics over multiple charging cycles, for m charging cycles, the third index can be represented by the following equation (12): (12) in, Indicates the first The rate of change of the off-center voltage statistical value of an individual cell over multiple charging cycles This represents the interval between the first and last charging cycles in a series of charging cycles. For example, it can be the duration between the start of the first charging cycle and the end of the last charging cycle. Here, the off-center voltage statistics can be determined, for example, by the above equation (4).

[0085] In this example, step S130 may include: determining a second outlier degree of a second indicator of the target battery relative to the second indicators of multiple batteries; and determining that the state of the target battery is abnormal in response to the second outlier degree being greater than or equal to a second preset degree and the third indicator of the target battery meeting a preset indicator condition. For example, it may be determined that a micro-short circuit has occurred in the target battery.

[0086] Specifically, the second outlier degree can be expressed, for example, by the coefficient of variation in equation (10) above. This indicates that the second preset level can be, for example, the preset outlier level mentioned above. Here, the second preset level can be set according to actual needs.

[0087] In the example where the third index represents the difference between the eccentric voltage statistics of the first and last charging cycles, the preset index condition can be that the third index is greater than or equal to the second preset value.

[0088] In this example, a second indicator that can respond to the target battery satisfy ≥Second preset level, and the third indicator of the target battery satisfy If the value is ≥ the second preset threshold, the target battery can be considered abnormal; in response to the second indicator of the target battery Not satisfied ≥Second preset level and / or the third indicator of the target battery Not satisfied If the value is greater than or equal to the second preset threshold, the target battery can be considered to be free of abnormalities.

[0089] In the example where the third index characterizes the rate of change of the off-center voltage statistics over multiple charging cycles, the preset index condition can be that the fourth index is less than or equal to the third preset value.

[0090] In this example, a second indicator that can respond to the target battery satisfy ≥Second preset level, and the third indicator of the target battery satisfy If the value is ≥ the third preset threshold, the target battery can be considered abnormal; the second indicator responds to the target battery. Not satisfied ≥Second preset level and / or the third indicator of the target battery Not satisfied If the value is greater than or equal to the third preset threshold, the target battery can be considered to be free of abnormalities.

[0091] Using the above method, the presence of abnormalities in the battery can be determined based on both the second and third indicators. In this way, the safety status of the battery can be comprehensively evaluated based on the second indicator, which is related to the dispersion of the off-center voltage across multiple charging cycles, and the third indicator, which is related to the difference in off-center voltage across different charging cycles. This allows for a more accurate assessment of the battery's condition and improves the accuracy of the test results.

[0092] Furthermore, in embodiments of this disclosure, in examples where the status indicators include a first indicator for a single charging cycle and a second indicator for multiple charging cycles, the final detection result can be determined based on the detection results for both the first and second indicators.

[0093] Specifically, step S130 may include: detecting the safety status of the target battery based on a first indicator to obtain a first detection result; detecting the safety status of the target battery based on a second indicator to obtain a second detection result; and determining the final detection result of detecting the safety status of the target battery based on the first detection result and the second detection result.

[0094] Examples of determining the first and second test results have been described above, so they will not be repeated here.

[0095] As an example, if both the first and second detection results indicate that the target battery is abnormal, the final detection result can be determined to be that the target battery is abnormal; if at least one of the first and second detection results indicates that the target battery is not abnormal, the final detection result can be determined to be that the target battery is not abnormal.

[0096] For example, in the detection of each of multiple batteries, if the abnormal single cell (e.g., battery number) identified in the first detection result is the same as the abnormal single cell (e.g., battery number) identified in the second detection result, it can be considered that the single cell is abnormal, for example, there is a risk of thermal runaway.

[0097] The above method can evaluate the battery from two aspects: the first detection result for a single charging cycle and the second detection result for multiple charging cycles. It takes into account the battery's performance on both short and long time scales, and can detect the battery status more accurately.

[0098] Furthermore, it should be noted that although the calculation methods of each indicator or parameter have been described above with reference to the various expressions, the embodiments of this disclosure are not limited thereto. The above expressions are merely examples of implementing the corresponding operations, and they can be adjusted according to actual needs. For example, variations of the above expressions can be obtained by weighting or adding other calculation items, and these variations can also be used to implement the corresponding operations in the embodiments of this disclosure.

[0099] The battery safety status detection method according to the embodiments of this disclosure can provide safety risk warnings for individual batteries on short-term and / or long-term time scales.

[0100] Specifically, on a short timescale, the moment when the current change in a single charging segment meets a set condition (e.g., the moment when the charging current sudden change exceeds 1 / 3C) can be selected. Simultaneously, individual cell voltage data within a preset time period before and after this moment is collected to form a voltage list. Based on this voltage data, the individual cell voltage difference within the preset time period before and after the current sudden change can be calculated, constructing a voltage difference matrix. Then, the values ​​in this matrix are divided by the current sudden change to obtain the internal resistance value of each cell. In this example, the box plot method and threshold method can be combined to comprehensively judge the calculated internal resistance values, filtering out individual cells with excessively high internal resistance, thereby determining that the individual cell is abnormal.

[0101] On a long-term scale, the off-center voltage statistics of each individual cell can be calculated across multiple charging segments, such as 10 segments, forming a data matrix of off-center voltage statistics for multiple cells. This allows for the determination of the entropy of the off-center voltage statistics for each individual cell, which can then be used to identify anomalous cells whose voltage gradually "outsiders" within that time range. Furthermore, a threshold judgment can be made based on the difference between the off-center voltage statistics of the first and last charges to identify anomalous cells.

[0102] In the detection method of the embodiments of this disclosure, to address the problem that relying solely on the internal temperature or internal resistance of the battery may lead to inaccurate detection results, this method evaluates the micro-short circuit of the battery by detecting the consistency of the individual cell voltage over multiple charging cycles. When a micro-short circuit occurs in a single cell, its individual cell voltage exhibits a continuous decreasing trend over a long period. By calculating the average off-center voltage error during multiple charging processes, the influence of single voltage sampling errors is eliminated, thereby improving detection accuracy.

[0103] To address the issue of potentially inaccurate detection results from a single charging cycle, this method constructs a matrix of differential voltage statistics for multiple individual cells across multiple charging cycles by calculating the off-center voltage statistics of each cell during multiple charging processes. By calculating the entropy of the off-center voltage statistics for each cell and the difference between the off-center voltage statistics for the first and last charging cycles, outlier abnormal cells are identified.

[0104] Furthermore, the embodiments of this disclosure can combine detection results on long and short time scales to obtain the final detection result for a single cell, thereby reducing the probability of false alarms.

[0105] Figure 3 An example of the calculated internal resistance of each cell within the battery pack is shown in the test for the first indicator. Figure 4A An example is shown of the average off-center voltage of multiple batteries in the detection of the second metric. Figure 4B A schematic diagram of the coefficients of variation of multiple batteries in the detection of the second indicator is shown.

[0106] like Figure 3 As shown, taking a 104-cell battery pack as an example, during the current charging process on a short time scale, the internal resistance of each individual cell is calculated. Combining the box plot and threshold method, it is determined that the internal resistance of cell #71 exceeds the upper limit of the box plot and that the internal resistance of this cell exceeds the threshold multiple of the median internal resistance. Therefore, it is determined that cell #71 has an abnormal internal resistance.

[0107] like Figure 4A and Figure 4B As shown, on a long time scale, based on the data of the current charging cycle and the 10 charging cycles before the current moment, the characteristic value difference between the first and last charging cycles of the off-center voltage statistics of cell #71 is 0.021V, and the coefficient of variation is greater than 3, indicating that the cell is abnormal.

[0108] Combination Figure 3 , Figure 4A and Figure 4B The identification results shown on both short and long time scales can indicate that there is a risk of thermal runaway in cell #71, thus enabling early warning of thermal runaway failure risk.

[0109] The battery safety status detection method described above according to exemplary embodiments of the present disclosure proposes to use "off-center voltage statistics" as a feature value for identifying abnormal internal short circuits in individual cells, replacing the thermal runaway identification method based on sudden changes in signals such as individual cell voltage and individual cell temperature, thus providing a basis for constructing early warning systems for safety issues such as thermal runaway risks.

[0110] Furthermore, the battery safety status detection method according to the exemplary embodiments of this disclosure also proposes a "feature value entropy value-change value joint calculation" method, which effectively overcomes the problem of false alarms caused by sample consistency in traditional entropy value analysis method through a two-dimensional data fusion mechanism. This method improves the accuracy of faulty individual cell identification and reduces the probability of false alarms.

[0111] Furthermore, according to the exemplary embodiment of the present disclosure, the battery safety status detection method establishes a thermal runaway risk identification method with long and short time scales. It identifies cells with abnormal internal resistance on a short time scale and abnormal cells with voltage outliers on a long time scale. By combining the abnormal cell identification results on both long and short time scales, the accuracy of early warning is improved.

[0112] Figure 5 A structural block diagram of a battery safety status detection device according to an exemplary embodiment of the present disclosure is shown.

[0113] Reference Figure 5 The battery safety status detection device according to an exemplary embodiment of the present disclosure includes an acquisition unit 510, a determination unit 520, and a detection unit 530.

[0114] The acquisition unit 510 is configured to acquire charging data of multiple batteries in at least one charging cycle.

[0115] The determination unit 520 is configured to determine the state indicators of each battery based on charging data, wherein the state indicators are determined based on the battery’s internal resistance or voltage during the charging process.

[0116] The detection unit 530 is configured to detect the safety status of the target battery by analyzing the degree of outlier of the target battery's state indicators relative to the state indicators of the multiple batteries.

[0117] As an example, the charging data includes battery voltage data and current data, and the status indicators include a first indicator, which characterizes the internal resistance of the battery in a single charging cycle. The determining unit 520 is configured to: determine a target time in which the current change in a single charging cycle of multiple batteries meets a preset condition, wherein the multiple batteries are connected in series, and the preset condition characterizes that the current change exceeds a preset level; and determine the first indicator of each battery based on the voltage data and current data of each battery at a preset time interval from the target time.

[0118] As an example, the detection unit 530 is configured to: determine the ratio between the internal resistance of the target battery at a target time and the representative value of the internal resistance of multiple batteries at the target time; and determine that the state of the target battery is abnormal in response to the outlier degree of the internal resistance of the target battery at the target time relative to the internal resistance of multiple batteries at the target time being greater than or equal to a first preset degree and the ratio being greater than or equal to a first preset threshold.

[0119] As an example, the charging data includes battery voltage data, and the state index includes a second index, which characterizes the dispersion of the battery's off-center voltage in multiple charging cycles. The off-center voltage characterizes the degree of deviation of the battery's voltage from the voltage center of multiple batteries. The determining unit 520 is configured to: for each battery, statistically analyze the off-center voltage of the battery at multiple times in each charging cycle to obtain the statistical value of the off-center voltage of the battery in each charging cycle; determine multiple voltage intervals based on the statistical value of the off-center voltage of each battery in each charging cycle; and determine the second index of each battery according to the probability that the statistical value of the off-center voltage of each battery in each charging cycle falls into each voltage interval.

[0120] As an example, the status index also includes a third index, which characterizes the difference between the off-center voltage statistics of the battery in the first and last charging cycles of multiple charging cycles or the rate of change of the off-center voltage statistics of the battery in multiple charging cycles. The detection unit 530 is configured to: determine the second outlier degree of the second index of the target battery relative to the second index of multiple batteries; and determine that the status of the target battery is abnormal in response to the second outlier degree being greater than or equal to the second preset degree and the third index of the target battery meeting the preset index condition.

[0121] As an example, for each battery, the off-center voltage statistics for each battery in each charging cycle are obtained as follows: for multiple moments in the current charging cycle, the voltage of each of the multiple batteries is determined; for each of the multiple moments, the off-center voltage of the current battery's voltage at that moment is determined relative to the voltage center of the voltages of the multiple batteries at that moment; by statistically analyzing the off-center voltage of the current battery at each moment, the off-center voltage statistics of the current battery in the current charging cycle are determined.

[0122] As an example, for any given moment, the voltage center is determined in the following ways: the center value of the voltage of multiple batteries at that moment is taken as the voltage center; or, based on the voltage of multiple batteries at multiple preset positions at that moment, the voltage range formed by the voltage of the multiple preset positions is taken as the voltage center.

[0123] As an example, the status indicators include a first indicator for a single charging cycle and a second indicator for multiple charging cycles, wherein the detection unit 530 is configured to: detect the safety status of the target battery based on the first indicator to obtain a first detection result; detect the safety status of the target battery based on the second indicator to obtain a second detection result; and determine the final detection result of the safety status detection of the target battery based on the first detection result and the second detection result.

[0124] It should be understood that the specific processing performed by the aforementioned device has been referenced. Figures 1 to 4B The above description has been detailed and will not be repeated here. Furthermore, it should be understood that the various units in the above-described apparatus can be implemented as hardware components and / or software components.

[0125] According to a third aspect of an exemplary embodiment of the present disclosure, an electronic device is provided, the electronic device comprising: a processor; and a memory for storing processor-executable instructions, wherein the processor-executable instructions, when executed by the processor, cause the processor to perform a battery safety state detection method according to an embodiment of the present disclosure.

[0126] The processor can execute instructions or code stored in memory, which can also store data. Instructions and data can also be sent and received over a network via a network interface device, which can employ any known transport protocol.

[0127] Memory can be integrated with the processor; for example, RAM or flash memory can be housed within an integrated circuit microprocessor. Alternatively, memory can comprise a separate device, such as an external disk drive, storage array, or other storage device that can be used by any database system. Memory and processor can be operatively coupled, or can communicate with each other, for example, via I / O ports, network connections, etc., enabling the processor to read files stored in the memory.

[0128] According to a fourth aspect of exemplary embodiments of the present disclosure, a computer-readable storage medium is provided, wherein when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform a battery safety state detection method according to embodiments of the present disclosure.

[0129] Specifically, the battery safety status detection method according to embodiments of the present disclosure can be programmed into a computer program and stored on a computer-readable storage medium. When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is caused to perform the battery safety status detection method according to exemplary embodiments of the present disclosure.

[0130] According to a fifth aspect of an exemplary embodiment of the present disclosure, a computer program product is provided, including computer-executable instructions that, when executed by at least one processor, implement a method for detecting battery safety status according to an embodiment of the present disclosure.

[0131] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

[0132] The specific embodiments of this disclosure have been described in detail above. Although some embodiments have been shown and described, those skilled in the art should understand that modifications and variations can be made to these embodiments without departing from the principles and spirit of this disclosure, which are defined by the claims and their equivalents. Such modifications and variations should also be within the protection scope of the claims of this disclosure.

Claims

1. A method of detecting a safety state of a battery, characterized by, The detection method includes: Acquire charging data for multiple batteries during at least one charging cycle; Based on the charging data, the state indicators of each battery are determined, wherein the state indicators are determined based on the internal resistance or voltage of the battery during the charging process. The safety status of the target battery is detected by analyzing the degree of outlier of the target battery's state indicators relative to the state indicators of the multiple batteries.

2. The detection method according to claim 1, characterized in that, The charging data includes battery voltage and current data, and the status indicators include a first indicator, which characterizes the battery's internal resistance in a single charging cycle. The step of determining the state indicators of each battery based on the charging data includes: Determine the target time when the current change in a single charging cycle of the plurality of batteries meets a preset condition, wherein the plurality of batteries are connected in series, and the preset condition indicates that the current change exceeds a preset level. Based on the voltage and current data of each battery at a preset time interval from the target time, the first index of each battery is determined.

3. The detection method according to claim 2, characterized in that, The step of detecting the safety status of the target battery by analyzing the outlier degree of the target battery's state indicators relative to the state indicators of the multiple batteries includes: Determine the ratio between the internal resistance of the target battery at the target time and the representative value of the internal resistance of the plurality of batteries at the target time; In response to the fact that the outlier degree of the internal resistance of the target battery at the target time relative to the internal resistance of the plurality of batteries at the target time is greater than or equal to a first preset degree, and the ratio is greater than or equal to a first preset threshold, it is determined that the state of the target battery is abnormal.

4. The detection method according to claim 1, characterized in that, The charging data includes battery voltage data, and the state index includes a second index, which characterizes the dispersion of the battery's off-center voltage across multiple charging cycles. The off-center voltage characterizes the degree to which the battery's voltage deviates from the voltage center of the plurality of batteries. The step of determining the state indicators of each battery based on the charging data includes: For each battery, the off-center voltage at multiple times in each charging cycle is statistically analyzed to obtain the statistical value of the off-center voltage of the battery in each charging cycle. Based on the statistical values ​​of the off-center voltage of each battery in each charging cycle, multiple voltage ranges are determined. The second index for each battery is determined based on the probability that the off-center voltage statistics of each battery fall into each voltage range during each charging cycle.

5. The detection method according to claim 4, characterized in that, The status index also includes a third index, which characterizes the difference in the off-center voltage statistics of the battery in the first and last charging cycles of the plurality of charging cycles, or the rate of change of the off-center voltage statistics of the battery in the plurality of charging cycles. The step of detecting the safety status of the target battery by analyzing the outlier degree of the target battery's state indicators relative to the state indicators of the multiple batteries includes: Determine the second outlier degree of the target battery relative to the second indicators of the plurality of batteries; In response to the second outlier degree being greater than or equal to the second preset degree, and the third indicator of the target battery meeting the preset indicator condition, it is determined that the state of the target battery is abnormal.

6. The detection method according to claim 4 or 5, characterized in that, For each battery, the off-center voltage statistics for each charging cycle are obtained as follows: For multiple moments in the current charging cycle, determine the voltage of each of the plurality of batteries; For each of the plurality of time points, determine the off-center voltage of the current battery voltage at that time point relative to the voltage center of the plurality of battery voltages at that time point. By statistically analyzing the off-center voltage of the current battery at various times, the statistical value of the off-center voltage of the current battery in the current charging cycle is determined.

7. The detection method according to claim 6, characterized in that, The voltage center is determined at any given time in the following manner: The center value of the voltage of the plurality of batteries at that moment is taken as the voltage center; or, Based on the voltage of the multiple batteries at a given moment at which they are located at multiple preset positions, the voltage range formed by the voltages at the multiple preset positions is taken as the voltage center.

8. The detection method according to claim 1, characterized in that, The status indicators include a first indicator for a single charging cycle and a second indicator for multiple charging cycles. The step of detecting the safety status of the target battery by analyzing the outlier degree of the target battery's state indicators relative to the state indicators of the multiple batteries includes: Based on the first indicator, the safety status of the target battery is detected to obtain a first detection result; Based on the second indicator, the safety status of the target battery is detected to obtain a second detection result; Based on the first detection result and the second detection result, the final detection result for detecting the safety status of the target battery is determined.

9. A device for detecting the safety status of a battery, characterized in that, The detection device includes: The acquisition unit is configured to acquire charging data of multiple batteries in at least one charging cycle; The determining unit is configured to determine the state indicators of each battery based on the charging data, wherein the state indicators are determined based on the battery’s internal resistance or voltage during the charging process. The detection unit is configured to detect the safety status of the target battery by analyzing the degree of outlier of the target battery's status indicators relative to the status indicators of the plurality of batteries.

10. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store processor-executable instructions. Wherein, when the processor executes the processor, it causes the processor to perform the battery safety state detection method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is able to perform the battery safety state detection method according to any one of claims 1 to 8.

12. A computer program product comprising computer-executable instructions, characterized in that, When the computer-executable instructions are executed by at least one processor, they implement the battery safety status detection method according to any one of claims 1 to 8.

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