Lagging battery determination system

Abstract

The present application provides a system for determining lagging batteries, relating to the field of power supply technology, and capable of improving the accuracy of determining lagging batteries. The system comprises: multiple batteries, a collection device, and an algorithm analysis device; the collection device is configured to obtain battery information of the multiple batteries during a target time period and transmit the battery information of the multiple batteries during the target time period to the algorithm analysis device; the algorithm analysis device is configured to receive the battery information of the multiple batteries during the target time period, and determine, based on the battery information of the multiple batteries during the target time period, a first battery bank, a second battery bank, and a third battery bank, and determine that batteries included in each of the first battery bank, the second battery bank, and the third battery bank are lagging batteries. Embodiments of the present application are used in the process of determining lagging batteries.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a system for determining a lagging battery. Background Art

[0002] Battery packs, as highly reliable power sources, are widely used in power supply systems across various industries. However, after a period of use, lagging cells may appear in the pack. During the discharge process, the terminal voltage of lagging cells drops rapidly. When the terminal voltage of any cell in the pack drops below a threshold, the entire pack stops discharging its capacity. Therefore, lagging cells can affect the battery's capacity release, thereby shortening the battery's service life. Therefore, identifying lagging cells in a battery pack is crucial for maintaining the pack.

[0003] Currently, the primary method for identifying lagging cells in a battery pack is voltage measurement. This involves measuring the battery voltage with a multimeter and identifying it as a lagging cell if the voltage is less than a preset threshold. However, the accuracy of identifying lagging cells based on voltage measurement is poor. Summary of the Invention

[0004] The present application provides a lagging battery determination system, which can improve the accuracy of lagging battery determination.

[0005] To achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a lagging battery determination system, which includes: multiple batteries, a collection device, and an algorithm analysis device; the collection device is used to obtain battery information of the multiple batteries in a target time period and send the battery information of the multiple batteries in the target time period to the algorithm analysis device; the battery information includes: internal resistance, voltage, and pole temperature; the algorithm analysis device is used to receive the battery information of the multiple batteries in the target time period, and determine a first battery library, a second battery library, and a third battery library based on the battery information of the multiple batteries in the target time period, and determine that the batteries included in the first battery library, the second battery library, and the third battery library are lagging batteries; wherein the first battery library includes batteries whose internal resistance abnormality number is greater than or equal to a first preset threshold in the target time period; the second battery library includes batteries whose voltage abnormality number is greater than or equal to a second preset threshold in the target time period; and the third battery library includes batteries whose pole temperature differs from the average pole temperature of the multiple batteries by a degree greater than or equal to a third preset threshold.

[0007] In one possible implementation, the algorithm analysis device includes: a data storage module, a data analysis module, and a result determination module; the data storage module is used to receive and store battery information of multiple batteries in a target time period, and send the battery information of multiple batteries in the target time period to the data analysis module; the data analysis module is used to receive the battery information of multiple batteries in the target time period, determine the first battery library, the second battery library, and the third battery library according to the battery information of the multiple batteries in the target time period, and send the first battery library, the second battery library, and the third battery library to the result determination module; the result determination module is used to receive the first battery library, the second battery library, and the third battery library, and determine that the batteries included in the first battery library, the second battery library, and the third battery library are backward batteries.

[0008] In one possible implementation, the target time period includes: multiple first moments, multiple second moments, a third moment, and a fourth moment; the battery information includes: internal resistance at multiple first moments, voltage at multiple second moments, pole temperature at the third moment, and pole temperature at the fourth moment; the first moment is the moment when the battery is in a charging state; the second moment is the moment when the battery is in a discharging state; the third moment is the moment when the battery starts discharging; and the fourth moment is the moment when the battery ends discharging.

[0009] In one possible implementation, the data analysis module is specifically used to perform the following operations on the internal resistance of multiple batteries at each first moment to obtain the first battery at each first moment; determine the average value of the internal resistance of multiple batteries at the target first moment as the target average internal resistance; the target first moment is any first moment among the multiple first moments; determine the battery with abnormal internal resistance at the target first moment based on the internal resistance of multiple batteries at the target first moment and the target average internal resistance; the data analysis module is specifically used to determine the number of times each battery is marked as a battery with abnormal internal resistance based on the battery with abnormal internal resistance at each first moment, and determine that the battery is a battery in the first battery library when the number of times it is marked as a battery with abnormal internal resistance is greater than or equal to a first preset threshold.

[0010] In one possible implementation, the data analysis module is specifically used to perform the following operations on the internal resistance of each battery at the target first moment: determining a battery with abnormal internal resistance at the target first moment; determining the difference between the internal resistance of the target battery at the target first moment and the target average internal resistance, and the ratio of the internal resistance to the target average internal resistance is the first difference value of the target battery at the target first moment; the target battery is any one of a plurality of batteries; when the first difference value is greater than or equal to a fourth preset threshold value, marking the target battery as a battery with abnormal internal resistance.

[0011] In one possible implementation, the data analysis module is specifically used to determine that the sum of the voltages of multiple batteries at a preset second moment is a first voltage; the preset second moment is the moment with the earliest time sorting among the multiple second moments; the data analysis module is specifically used to determine the voltage-abnormal battery at each second moment based on the voltages of the multiple batteries at each second moment among the multiple second moments and the first voltage; the data analysis module is specifically used to determine the number of times each battery is marked as a voltage-abnormal battery based on the voltage-abnormal battery at each second moment; when the number of times the battery is marked as a voltage-abnormal battery is greater than or equal to a second preset threshold, the data analysis module is specifically used to determine that the battery is a battery in the second battery library.

[0012] In one possible implementation, the data analysis module is specifically used to perform the following operations: perform the following operations on the voltages of multiple batteries at each second moment to obtain batteries with abnormal voltages at each second moment; determine that the difference between the voltages of multiple batteries at the target second moment and the voltages of multiple batteries at the preset second moment is the voltage drop of the multiple batteries at the target second moment; the target second moment is any second moment among the multiple second moments; determine that the sum of the voltage drops of the multiple batteries, and the difference between the sum and the first voltage is the second voltage; perform the following operations on the voltage of each battery at the target second moment to determine batteries with abnormal voltages at the target second moment; determine the difference between the voltage drop of the target battery and the second voltage, and the ratio to the second voltage is the second difference value of the target battery; when the second difference value is greater than or equal to the fifth preset threshold, mark the target battery as a battery with abnormal voltage.

[0013] In one possible implementation, when the second difference value is greater than or equal to a fifth preset threshold, the data analysis module is specifically used to: determine a target second difference value of the target battery; the target second difference value is the second difference value of the target battery at the last sampling moment; the last sampling moment is the second moment with the latest time order among multiple second moments; when the target second difference value is greater than or equal to a sixth preset threshold, the data analysis module is specifically used to mark the target battery as a battery with abnormal voltage.

[0014] In one possible implementation, the data analysis module is specifically used to determine that the average value of the pole temperatures of multiple batteries at a third moment is the first pole temperature, and to determine that the average value of the pole temperatures of multiple batteries at a fourth moment is the second pole temperature; the data analysis module is specifically used to determine the difference between the pole temperature of the target battery at the third moment and the first pole temperature, and the ratio of the difference between the pole temperature of the target battery at the fourth moment and the second pole temperature is the third difference value of the target battery; when the third difference value is greater than or equal to the third preset threshold value, the data analysis module is specifically used to determine that the target battery is a battery in a third battery library.

[0015] In one possible implementation, the acquisition device includes: an online sampling module and a monitoring module; the online acquisition module includes multiple battery acquisition modules; the battery acquisition module is used to collect battery information of multiple batteries in a preset time period, and send the battery information of multiple batteries in the preset time period to the monitoring module; the time length of the preset time period is greater than the time length of the target time period; the monitoring module is used to receive the battery information of multiple batteries in the preset time period, filter out the battery information of multiple batteries in the target time period from the battery information of multiple batteries in the preset time period, and send the battery information of multiple batteries in the target time period to the algorithm analysis device.

[0016] The above technical solution brings at least the following beneficial effects: the acquisition device can first obtain battery information (i.e., internal resistance, voltage, and pole temperature) of multiple batteries in the target time period, and send the above-obtained battery information to the algorithm analysis device. The algorithm analysis device is used to receive the battery information of multiple batteries in the target time period, and determine the first battery library, the second battery library, and the third battery library based on the battery information of the multiple batteries in the target time period, and determine that the batteries included in the first battery library, the second battery library, and the third battery library are lagging batteries. In this way, the algorithm analysis device determines the lagging batteries based on the three dimensions of internal resistance, voltage, and pole temperature. The lagging batteries determined in this way are batteries with a large number of abnormalities in the three parameters of internal resistance, voltage, and pole temperature, thereby ensuring the accuracy of the lagging batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A structural diagram of a lagging battery determination system provided in an embodiment of the present application;

[0018] Figure 2 A structural diagram of a lagging battery determination system provided in an embodiment of the present application;

[0019] Figure 3 A structural diagram of another lagging battery determination system provided in an embodiment of the present application;

[0020] Figure 4 A structural diagram of an algorithm analysis device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The following describes in detail the lagging battery determination system provided by the embodiments of the present application with reference to the accompanying drawings.

[0022] The term "and / or" in this article is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0023] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0024] Furthermore, the terms "including," "having," and any variations thereof, as used in the description of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to the process, method, product, or apparatus.

[0025] It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being more preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0026] In the description of the present application, unless otherwise specified, “plurality” means two or more.

[0027] Battery packs, as highly reliable power sources, are widely used in power supply systems across various industries. However, after a period of use, lagging cells may appear in the pack. During the discharge process, the terminal voltage of lagging cells drops rapidly. When the terminal voltage of any cell in the pack drops below a threshold, the entire pack stops discharging its capacity. Therefore, lagging cells can affect the battery's capacity release, thereby shortening the battery's service life. Therefore, identifying lagging cells in a battery pack is crucial for maintaining the pack.

[0028] Currently, the primary method for identifying lagging cells in a battery pack is voltage measurement. This involves measuring the battery voltage with a multimeter and identifying it as a lagging cell if the voltage is less than a preset threshold. However, the accuracy of identifying lagging cells based on voltage measurement is poor.

[0029] In order to solve the problems existing in the above-mentioned prior art, the embodiment of the present application proposes a lagging battery determination system, which can improve the accuracy of determining lagging batteries. Figure 1 As shown, the lagging battery determination system 10 includes: multiple batteries 101 , a collection device 102 , and an algorithm analysis device 103 .

[0030] The collecting device 102 is used to obtain battery information of the multiple batteries 101 in the target time period, and send the battery information of the multiple batteries 101 in the target time period to the algorithm analyzing device 103.

[0031] The battery information includes internal resistance, voltage, and terminal temperature.

[0032] The algorithm analysis device 103 is used to receive battery information of multiple batteries 101 in a target time period, determine a first battery library, a second battery library, and a third battery library based on the battery information of the multiple batteries 101 in the target time period, and determine that the batteries 101 included in the first battery library, the second battery library, and the third battery library are lagging batteries.

[0033] The first battery pool includes batteries 101 whose internal resistance abnormality frequency is greater than or equal to a first preset threshold value during the target time period. The second battery pool includes batteries 101 whose voltage abnormality frequency is greater than or equal to a second preset threshold value during the target time period. The third battery pool includes batteries 101 whose terminal temperature differs from the average terminal temperature of multiple batteries 101 by greater than or equal to a third preset threshold value.

[0034] In one possible implementation, the target time period includes: multiple first moments, multiple second moments, a third moment, and a fourth moment. The battery information includes: internal resistance at multiple first moments, voltage at multiple second moments, electrode temperature at the third moment, and electrode temperature at the fourth moment. The first moment is when the battery 101 is in a charging state. The second moment is when the battery 101 is in a discharging state. The third moment is when the battery 101 starts discharging. The fourth moment is when the battery 101 ends discharging.

[0035] In combination with the above implementation, the voltages at multiple second moments can be displayed in a matrix format. For example, taking the multiple second moments including i+1 second moments as an example, the voltages at the i+1 second moments can be: Here, t is used to represent a time, and u is used to represent the voltage of the battery 101 .

[0036] Optionally, the charging state may include at least one of the following: a floating charge state and an equalizing charge state. The above is only an exemplary description of the charging state, and the charging state may include other charging states, which is not limited in this application.

[0037] In some examples, the battery 101 may be a valve-regulated sealed lead-acid battery or a high-rate valve-regulated sealed lead-acid battery. The above are only two exemplary descriptions of the battery 101. The battery 101 may also be other batteries, and this application does not impose any limitation on this.

[0038] Optionally, the algorithm analysis device 103 may determine that the batteries 101 included in both the first battery bank and the second battery bank are secondary lagging batteries.

[0039] Alternatively, the algorithm analysis device 103 may select the batteries 101 included in both the first battery bank and the third battery bank, and the batteries 101 included in both the second battery bank and the third battery bank as the warning lagging batteries.

[0040] Alternatively, the algorithm analysis device 103 may select the batteries 101 in the first battery bank, the batteries 101 in the second battery bank, and the batteries 101 in the third battery bank as lagging batteries to be noted.

[0041] It is understandable that Figure 1 Compared to the existing verification discharge method (i.e., performing verification discharge on each battery 101 in the battery pack using a preset load to determine the capacity of each battery 101, and determining that the battery 101 is a lagging battery when the capacity of the battery 101 is lower than a preset capacity threshold), the lagging battery determination system 10 provided by the present application does not need to be limited to scenarios with spare batteries 101, nor does it require operation and maintenance personnel to go to the site for inspection, thereby enabling the lagging battery determination device to conveniently and quickly determine lagging batteries.

[0042] In one possible implementation, the algorithm analysis device 103 is installed in a monitoring terminal. The monitoring terminal may include at least one of the following: a local terminal and a remote terminal. The monitoring terminal has functions such as parameter setting and modification, communication management, manual internal resistance test operation, viewing lagging battery determination results, supporting the operation of the lagging battery determination software algorithm analysis platform, and data transmission.

[0043] In some examples, the battery may also be a storage battery. The algorithm analysis device may be used to deploy an algorithm analysis platform.

[0044] The above technical solution brings at least the following beneficial effects: the acquisition device 102 can first obtain the battery information (i.e., internal resistance, voltage, and pole temperature) of multiple batteries 101 in the target time period, and send the above-obtained battery information to the algorithm analysis device 103. The algorithm analysis device 103 is used to receive the battery information of multiple batteries 101 in the target time period, and determine the first battery library, the second battery library, and the third battery library based on the battery information of the multiple batteries 101 in the target time period, and determine that the batteries 101 included in the first battery library, the second battery library, and the third battery library are lagging batteries. In this way, the algorithm analysis device 103 determines the lagging batteries based on the three dimensions of internal resistance, voltage, and pole temperature. The lagging batteries determined in this way are batteries 101 with a large number of abnormalities in the three parameters of internal resistance, voltage, and pole temperature, thereby ensuring the accuracy of the lagging batteries.

[0045] In an optional embodiment, as Figure 2 As shown, the algorithm analysis device 103 may include: a data storage module 1031 , a data analysis module 1032 , and a result determination module 1033 .

[0046] The data storage module 1031 is configured to receive and store battery information of the plurality of batteries 101 in a target time period, and send the battery information of the plurality of batteries 101 in the target time period to the data analysis module 1032 .

[0047] The data analysis module 1032 is used to receive battery information of multiple batteries 101 in a target time period, determine the first battery library, the second battery library, and the third battery library based on the battery information of the multiple batteries 101 in the target time period, and send the first battery library, the second battery library, and the third battery library to the result determination module 1033.

[0048] The result determination module 1033 is configured to receive the first battery library, the second battery library, and the third battery library, and determine that the batteries 101 included in the first battery library, the second battery library, and the third battery library are outdated batteries.

[0049] In an optional embodiment, the implementation process of the data analysis module 1032 determining the first battery bank based on the battery information of the plurality of batteries 101 in the target time period is described below:

[0050] The data analysis module 1032 is specifically configured to perform the following operations on the internal resistance of the plurality of batteries 101 at each first moment to obtain the first battery 101 at each first moment.

[0051] The average internal resistance of the plurality of batteries 101 at a target first moment is determined as a target average internal resistance. The target first moment is any first moment among the plurality of first moments. Based on the internal resistances of the plurality of batteries 101 at the target first moment and the target average internal resistance, a battery 101 having an abnormal internal resistance at the target first moment is determined.

[0052] The data analysis module 1032 is specifically used to determine the number of times each battery 101 is marked as a battery 101 with abnormal internal resistance based on the battery 101 with abnormal internal resistance at each first moment, and to determine that the battery 101 is a battery 101 in the first battery library when the number of times the battery 101 is marked as a battery 101 with abnormal internal resistance is greater than or equal to a first preset threshold.

[0053] Optionally, each of the two closest first moments may be 15 minutes apart. Exemplarily, the multiple first moments may include: January 1, 20XX -3:00, January 1, 20XX -3:15, January 1, 20XX -3:30, January 1, 20XX -3:45, and January 1, 20XX -4:00.

[0054] For example, taking the above-mentioned internal resistances of the plurality of batteries 101 at the target first moment as 90 milliohms, 92 milliohms, 95 milliohms, 98 milliohms, and 120 milliohms, respectively, the target average internal resistance is 99 milliohms.

[0055] For example, the abnormal internal resistance batteries 101 at the first moment #1 are batteries 101#1, 101#2, and 101#3; the abnormal internal resistance batteries 101 at the first moment #2 are batteries 101#2, 101#3, and 101#4; and the abnormal internal resistance batteries 101 at the first moment #3 are batteries 101#2, 101#3, and 101#5. The data analysis module 1032 can determine that the abnormal internal resistance batteries 101 at the first moment #1 are batteries 101#2, 101#3, and 101#5. At a certain moment (i.e., the first moment #1, the first moment #2, and the first moment #3), battery 101#1 is marked as a battery 101 with abnormal internal resistance 1 time, battery 101#2 is marked as a battery 101 with abnormal internal resistance 3 times, battery 101#3 is marked as a battery 101 with abnormal internal resistance 3 times, battery 101#4 is marked as a battery 101 with abnormal internal resistance 1 time, and battery 101#5 is marked as a battery 101 with abnormal internal resistance 1 time.

[0056] As an optional implementation method, the data analysis module 1032 is also used to determine the first preset threshold value of the determination device, and its implementation process can be: the data analysis module 1032 can sort the above-mentioned multiple batteries 101 in descending order based on the number of times they are marked as internal resistance abnormalities to obtain a first sequence, and from the above-mentioned first sequence, the number of times the Nth battery 101 is marked as an internal resistance abnormality battery 101 is the first preset threshold value.

[0057] Optionally, the data analysis module 1032 may determine N based on the number of batteries 101 and a preset ratio. For example, if the number of batteries 101 is 24 and the preset ratio is 10%, the data analysis module 1032 may determine N to be 3. For another example, if the number of batteries 101 is 30 and the preset ratio is 10%, the data analysis module 1032 may determine N to be 3. The above preset ratio may be set by the data analysis module 1032 based on actual circumstances, and this application does not impose any limitations on this.

[0058] Optionally, the battery 101 in the first battery bank can be based on the above Figure 3 The method shown is dynamically refreshed. If the data analysis module 1032 determines that the batteries 101 in the first battery library include: battery 101#6 and battery 101#7 based on the battery information in time period #1, and the data analysis module 1032 determines that the batteries 101 in the first battery library include: battery 101#6 and battery 101#8 based on the battery information in time period #2 (time period #2 is later than time period #1), then if the above-mentioned battery 101#7 is not eliminated, the first battery library can include battery 101#6, battery 101#7, and battery 101#8. If the above-mentioned battery 101#7 is eliminated, the first battery library can include battery 101#6 and battery 101#8.

[0059] The above technical solution provides at least the following beneficial effects: the data analysis module 1032 can first determine the average internal resistance of the multiple batteries 101 at any first moment as the average internal resistance, and then determine the battery 101 with abnormal internal resistance at the first moment based on the internal resistance of the multiple batteries 101 at the first moment and the average internal resistance, until the battery 101 with abnormal internal resistance is determined for each of the first batteries 101 at the multiple first moments. The data analysis module 1032 determines the number of times each battery 101 has been marked as a battery 101 with abnormal internal resistance based on the abnormal internal resistance of each first battery 101, and if the number is greater than or equal to a first preset threshold, determines that the battery 101 is a battery 101 in the first battery pool. In this way, the data analysis module 1032 of the present application determines the batteries 101 in the first battery pool based on the internal resistances of the batteries 101 at multiple first moments, rather than simply determining the batteries 101 in the first battery pool based on the internal resistances of the batteries 101 at a single moment, thereby improving the accuracy of determining the first battery pool.

[0060] In an optional embodiment, the data analysis module 1032 determines the battery 101 with abnormal internal resistance at the target first moment based on the internal resistance of the plurality of batteries 101 at the target first moment and the target average internal resistance.

[0061] The data analysis module 1032 is specifically configured to perform the following operations on the internal resistance of each battery 101 at the target first moment, to determine the battery 101 with abnormal internal resistance at the target first moment.

[0062] A difference between the internal resistance of a target battery 101 at a target first moment and a target average internal resistance is determined, and a ratio of the difference to the target average internal resistance is defined as a first difference value of the target battery 101 at the target first moment. The target battery 101 is any one of the multiple batteries 101. If the first difference value is greater than or equal to a fourth preset threshold, the target battery 101 is marked as a battery 101 with abnormal internal resistance.

[0063] Optionally, the first target moment may be understood by referring to the description of the corresponding position above, which will not be repeated here.

[0064] In a possible implementation, the first difference value may satisfy the following formula 1:

[0065]

[0066] Among them, s j is the first difference value of the target battery 101 at the target first moment. j is the internal resistance of the target battery 101 at the target first moment. is the target average internal resistance.

[0067] Optionally, the fourth preset threshold may be set by the data analysis module 1032 according to actual conditions. For example, the data analysis module 1032 sets the fourth preset threshold to 30%, and this application does not impose any limitation on this.

[0068] Optionally, the acquisition module can also be used to obtain the temperature of the environment in which the battery 101 is located at the target moment. However, the internal resistance of the battery 101 will change with the change of the ambient temperature. For example, when the ambient temperature of the battery 101 is in the range of -10 degrees Celsius (°C) to -30°C, the internal resistance of the battery 101 will undergo a large mutation. Therefore, if the temperature of the battery 101 environment at the target moment is not in the range of -10 degrees Celsius (°C) to -30°C, the data analysis module 1032 will mark the target battery 101 as a battery 101 with abnormal internal resistance. If the temperature of the battery 101 environment at the target moment is in the range of -10 degrees Celsius (°C) to -30°C, the data analysis module 1032 will not mark the target battery 101 as a battery 101 with abnormal internal resistance.

[0069] The above technical solution brings at least the following beneficial effects: the data analysis module 1032 first determines the difference between the internal resistance of the target battery 101 (i.e., any one battery 101 among the multiple batteries 101) at the target first moment and the target average internal resistance, and the ratio of the internal resistance to the target average internal resistance is the first difference value of the target battery 101 at the target first moment, and when the above first difference value is greater than or equal to the fourth preset threshold, the target battery 101 is marked as an abnormal internal resistance battery 101, until each battery 101 among the above multiple batteries 101 is determined, and the abnormal internal resistance battery 101 at the target first moment is obtained, which provides a data basis for the subsequent data analysis module 1032 to determine the number of times each battery 101 is marked as an abnormal internal resistance battery 101 based on the abnormal internal resistance battery 101 at the first moment.

[0070] In an optional embodiment, the implementation process of the data analysis module 1032 determining the second battery bank based on the battery information of the plurality of batteries 101 in the target time period is described below:

[0071] The data analysis module 1032 is specifically configured to determine that the sum of the voltages of the plurality of batteries 101 at a preset second moment is the first voltage. The preset second moment is the earliest moment in the plurality of second moments.

[0072] The data analysis module 1032 is specifically configured to determine a battery 101 with abnormal voltage at each second moment according to the voltages of the plurality of batteries 101 at each second moment among the plurality of second moments and the first voltage.

[0073] The data analysis module 1032 is specifically configured to determine the number of times each battery 101 is marked as a battery 101 with abnormal voltage based on the battery 101 with abnormal voltage at each second moment.

[0074] When the number of times the battery 101 is marked as having abnormal voltage is greater than or equal to the second preset threshold, the data analysis module 1032 is specifically configured to determine that the battery 101 is a battery 101 in the second battery bank.

[0075] In a possible implementation, the first voltage may satisfy the following formula 2:

[0076]

[0077] Wherein, U0 is the first voltage. 0,j is the voltage of the j-th battery 101 at the preset second moment. J is a positive integer.

[0078] Optionally, each of the two closest second moments may be 10 seconds apart. Exemplarily, the multiple first moments may include: January 1, 20XX -3:00:10, January 1, 20XX -3:00:20, January 1, 20XX -3:00:30, January 1, 20XX -3:00:40, and January 1, 20XX -3:00:50.

[0079] Optionally, the batteries 101 in the second battery bank can also be dynamically refreshed. The implementation process of the data analysis module 1032 dynamically refreshing the batteries 101 in the second battery bank can be referred to the implementation process of the data analysis module 1032 dynamically refreshing the batteries 101 in the second battery bank, which will not be repeated here.

[0080] The above technical solution brings at least the following beneficial effects: the data analysis module 1032 can first determine that the sum of the voltages of multiple batteries 101 at a preset second moment is the first voltage, and then determine the voltage-abnormal battery 101 at each second moment based on the voltages of the multiple batteries 101 and the first voltage. The data analysis module 1032 determines the number of times each battery 101 is marked as a voltage-abnormal battery 101 based on the voltage-abnormal battery 101 at each second moment, and if the number of times the battery 101 is marked as a voltage-abnormal battery 101 is greater than or equal to a second preset threshold, the battery 101 is determined to be a battery 101 in the second battery pool. In this way, the data analysis module 1032 of the present application determines the battery 101 in the second battery pool based on the voltages of the battery 101 at multiple second moments, rather than determining the battery 101 in the second battery pool based solely on the battery voltage at a single moment, thereby improving the accuracy of determining the second battery pool.

[0081] In an optional embodiment, the data analysis module 1032 determines the abnormal voltage battery 101 at each second moment according to the voltage of the plurality of batteries 101 and the first voltage at each second moment in the plurality of second moments.

[0082] The data analysis module 1032 is specifically configured to perform the following operations:

[0083] The following operation is performed on the voltages of the plurality of batteries 101 at each second moment, to obtain the battery 101 with abnormal voltage at each second moment.

[0084] The difference between the voltages of the multiple batteries 101 at the target second time and the voltages of the multiple batteries 101 at the preset second time is determined as a voltage drop of the multiple batteries 101 at the target second time. The target second time is any second time from the multiple second times. The difference between the sum of the voltage drops of the multiple batteries 101 and the first voltage is determined as a second voltage.

[0085] The following operation is performed on the voltage of each battery 101 at the target second time, and the battery 101 with abnormal voltage at the target second time is determined.

[0086] The difference between the voltage drop of the target battery 101 and the second voltage is determined, and the ratio of the voltage drop to the second voltage is a second difference value of the target battery 101 .

[0087] When the second difference value is greater than or equal to the fifth preset threshold, the target battery 101 is marked as a battery 101 with abnormal voltage.

[0088] In one example, the voltage of the battery 101 described in this application may be the terminal voltage of the battery 101 .

[0089] In one possible implementation, the voltage drop of the battery 101 may satisfy the following formula 3:

[0090] ΔU i,j =|u i,j -u 0,j | Formula 3

[0091] Among them, ΔU i,j is the voltage drop of the jth battery 101 among the multiple batteries 101 at the target second moment. i,j is the voltage of the jth battery 101 among the multiple batteries 101 at the target second moment. 0,j is the voltage of the j-th battery 101 among the multiple batteries 101 at the preset second moment.

[0092] In a possible implementation, the second voltage may satisfy the following formula 4:

[0093]

[0094] Among them, ΔU i is the second voltage.

[0095] In a possible implementation, the second difference value may satisfy the following formula 5:

[0096]

[0097] Among them, K i,j is the second difference value of the j-th battery 101 among the plurality of batteries 101 at the target second time.

[0098] In an optional implementation, the data analysis module 1032 may determine the fifth preset threshold value by: the data analysis module 1032 determines the fifth preset threshold value as the largest second difference value among the second difference values ​​of the plurality of batteries 101. Because the largest second difference value among the second difference values ​​of the plurality of batteries 101 is different at different second moments in time, the fifth preset threshold value is different at different second moments in time.

[0099] Optionally, the data analysis module 1032 can also be used to determine the second difference value of the target battery 101 at the last second moment among the above-mentioned multiple second moments. When the second difference value is greater than or equal to the sixth preset threshold, the target battery 101 is determined to be an abnormal battery 101.

[0100] The above technical solution provides at least the following beneficial effects: the data analysis module 1032 first determines the difference between the voltage of the plurality of batteries 101 at the target second moment and the voltage of the plurality of batteries 101 at the preset second moment as the voltage drop of the plurality of batteries 101 at the target second moment, and determines the sum of the voltage drops of the plurality of batteries 101, the difference between which and the first voltage is the second voltage. Next, the data analysis module 1032 determines the difference between the voltage drop of the target battery 101 and the second voltage, the ratio of which to the second voltage is the second difference value of the target battery 101, and if the second difference value is greater than or equal to a fifth preset threshold, marks the target battery 101 as a voltage-abnormal battery 101. This process continues until each of the plurality of batteries 101 is identified, obtaining the voltage-abnormal battery 101 at the target second moment. This provides a data basis for the subsequent data analysis module 1032 to determine the number of times each battery 101 is marked as a voltage-abnormal battery 101 based on the voltage-abnormal battery 101 at the second moment.

[0101] In an optional embodiment, the implementation process of the data analysis module 1032 marking the target battery 101 as a battery 101 with abnormal voltage when the second difference value is greater than or equal to the fifth preset threshold is described below:

[0102] If the second difference value is greater than or equal to the fifth preset threshold, the data analysis module 1032 is specifically configured to determine a target second difference value of the target battery 101. The target second difference value is the second difference value of the target battery 101 at the last sampling moment. The last sampling moment is the second moment with the latest time sequence among the multiple second moments.

[0103] When the target second difference value is greater than or equal to the sixth preset threshold, the data analysis module 1032 is specifically configured to mark the target battery 101 as a battery 101 with abnormal voltage.

[0104] It is understandable that because the voltage of battery 101 may change suddenly as the discharge time increases, the probability of a sudden change in the voltage of battery 101 is relatively high at the last sampling moment among the multiple second moments. For this reason, before the data analysis module 1032 determines that the target battery 101 is a battery 101 with abnormal voltage, determining whether the target second difference value of the target battery 101 is greater than or equal to the sixth preset threshold can effectively improve the accuracy of determining the battery 101 with abnormal voltage.

[0105] The above technical solution brings at least the following beneficial effects: when the second difference value is greater than or equal to the fifth preset threshold, the data analysis module 1032 first determines the target second difference value of the target battery 101, and when the target second difference value is greater than or equal to the sixth preset threshold, the target battery 101 is marked as a voltage-abnormal battery 101. In this way, in the process of determining the voltage-abnormal battery 101, the influence of the discharge time on the voltage is taken into consideration, thereby effectively improving the accuracy of determining the voltage-abnormal battery 101.

[0106] In an optional embodiment, the data analysis module 1032 determines the implementation process of the third battery bank according to the battery information of the plurality of batteries 101 in the target time period.

[0107] The data analysis module 1032 is specifically configured to determine an average value of the pole temperatures of the plurality of batteries 101 at the third moment as a first pole temperature, and to determine an average value of the pole temperatures of the plurality of batteries 101 at the fourth moment as a second pole temperature.

[0108] The data analysis module 1032 is specifically used to determine the ratio of the difference between the pole temperature of the target battery 101 at the third moment and the first pole temperature to the difference between the pole temperature of the target battery 101 at the fourth moment and the second pole temperature as the third difference value of the target battery 101.

[0109] When the third difference value is greater than or equal to the third preset threshold, the data analysis module 1032 is specifically configured to determine that the target battery 101 is the battery 101 in the third battery bank.

[0110] For example, if the electrode temperatures of the plurality of batteries 101 at the third moment are 18° C., 19° C., 20° C., 21° C., and 22° C., respectively, the first electrode temperature is 20° C. If the electrode temperatures of the plurality of batteries 101 at the third moment are 28° C., 29° C., 30° C., 31° C., and 32° C., respectively, the second electrode temperature is 30° C.

[0111] In a possible implementation, the third difference value may satisfy the following formula 6:

[0112]

[0113] Where, ΔT j is the third difference value of the target battery 101. 1,j T is the terminal temperature of the target battery 101 at the third moment. 2,j is the terminal temperature of the target battery 101 at the fourth moment. is the first pole temperature. is the second pole temperature.

[0114] Optionally, the batteries 101 in the third battery bank can also be dynamically refreshed. The implementation process of the data analysis module 1032 dynamically refreshing the batteries 101 in the third battery bank can be referred to the implementation process of the data analysis module 1032 dynamically refreshing the batteries 101 in the third battery bank, which will not be repeated here.

[0115] The above technical solution provides at least the following beneficial effects: the data analysis module 1032 can determine the average of the electrode temperatures of the multiple batteries 101 at the third moment as the first electrode temperature, and determine the average of the electrode temperatures of the multiple batteries 101 at the fourth moment as the second electrode temperature. Next, the data analysis module 1032 determines the ratio of the difference between the electrode temperature of the target battery 101 at the third moment and the first electrode temperature to the difference between the electrode temperature of the target battery 101 at the fourth moment and the second electrode temperature as a third difference value for the target battery 101. If the third difference value is greater than or equal to a third preset threshold, the target battery 101 is determined to be a battery 101 in the third battery bank. Thus, the data analysis module 1032 of the present application determines the batteries 101 in the third battery bank based on the electrode temperatures of the multiple batteries 101 at the first moment, rather than simply determining the batteries 101 in the third battery bank based on the battery electrode temperature at a single moment, thereby improving the accuracy of determining the third battery bank.

[0116] In an optional embodiment, as Figure 3 As shown, the acquisition device 102 may include: an online sampling module 1021 and a monitoring module 1022 .

[0117] The online acquisition module may include multiple battery acquisition modules 10211, each of which corresponds to one or more batteries 101. The battery acquisition module 10211 is configured to acquire battery information from the battery 101 within a preset time period and transmit the battery information to the monitoring module 1022. The preset time period is longer than the target time period.

[0118] The above-mentioned monitoring module 1022 is used to receive battery information of multiple batteries 101 in a preset time period, and filter out battery information of multiple batteries 101 in a target time period from the battery information of multiple batteries 101 in the preset time period, and send the battery information of multiple batteries 101 in the target time period to the algorithm analysis device 103.

[0119] Optionally, the battery acquisition module 10211 may also acquire terminal voltages and terminal currents of the plurality of battery packs. The terminal currents of the plurality of battery packs may be used to determine the current state of the battery.

[0120] Optionally, the lagging battery determination system 10 can use an independent power supply to power the above-mentioned battery collection module. In this case, the lagging battery determination system 10 can set the working power supply for the above-mentioned battery collection module to a working power supply with an output voltage of 48 volts, or a working power supply with an input voltage of 220 volts, or a working power supply with an output voltage of 240 volts.

[0121] Alternatively, the lagging battery determination system 10 may use a non-independent power supply method to power the battery acquisition module. In this case, the lagging battery determination system 10 may set the working power supply for the battery acquisition module to a 2V working power supply or a 12V working power supply.

[0122] It should be noted that the above-mentioned battery acquisition module 10211 also has short-circuit protection function (to avoid the problem of battery short circuit caused by failure of the battery acquisition module), leakage current detection function, reverse connection protection function, overvoltage protection function, overcurrent protection function, overtemperature protection function and other functions, and can also store at least two battery charge and discharge records.

[0123] It should be noted that the monitoring module 1022 can display, store, and query the battery information collected by the battery collection module. For example, the memory of the monitoring module 1022 can store battery information collected by the battery collection module 10211 for seven consecutive days, ensuring that this battery information is not lost after a power outage. The monitoring module 1022 can also have an AI interface and use this AI interface to collect parameters such as AC and DC load bus voltage, load current, and power.

[0124] Optionally, the monitoring module 1022 can be connected to at least one battery collection module 10211. For example, one monitoring module 1022 can be connected to the battery collection modules 10211 of two to four battery packs 9 (for example, the battery pack includes 120 batteries 101). The monitoring module 1022 can be connected to at least one monitoring terminal. For example, one monitoring module 1022 can be connected to two monitoring terminals. The data transmitted by the monitoring module 1022 to the monitoring terminal can be transmitted using two data transmission methods: wired transmission and wireless transmission. Specifically, the monitoring module 1022 transmits data to the monitoring terminal via the RJ45 interface and the 4G module.

[0125] Optionally, the lagging battery determination system 10 may be applied to a scenario where, within a target time period, multiple batteries are in both a charging state (eg, a floating charge state, an equalizing charge state) and a discharging state.

[0126] The above technical solution brings at least the following beneficial effects: a battery collection module is used to collect battery information of multiple batteries in a preset time period, and send the battery information of multiple batteries in the preset time period to the monitoring module; the time length of the preset time period is greater than the time length of the target time period; the monitoring module is used to receive the battery information of multiple batteries in the preset time period, filter out the battery information of multiple batteries in the target time period from the battery information of multiple batteries in the preset time period, and send the battery information of multiple batteries in the target time period to the algorithm analysis device, so as to avoid the monitoring terminal receiving more redundant battery information and reduce the transmission burden.

[0127] The embodiments disclosed in this application can divide the algorithm analysis device 103 into functional modules. For example, each functional module can be divided into corresponding functional modules, or two or more functions can be integrated into one processing module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiments disclosed in this application is schematic and is only a logical functional division. In actual implementation, other division methods may be used.

[0128] Figure 4This is a structural diagram of an algorithm analysis device 103 provided in an embodiment of the present application. Figure 4 As shown, the algorithm analysis device 103 includes: at least one processor 401, a communication line 402, and at least one communication interface 404, and may also include a memory 403. The processor 401, the memory 403 and the communication interface 404 may be connected via the communication line 402.

[0129] The processor 401 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application, such as one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).

[0130] The communication link 402 may include a path for transmitting information between the aforementioned components.

[0131] The memory 403 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including a compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to include or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0132] The communication interface 404 is used to communicate with other devices or communication networks and can use any transceiver-like device, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0133] In one possible design, memory 403 can exist independently of processor 401, that is, memory 403 can be a memory external to processor 401. In this case, memory 403 can be connected to processor 401 via communication line 402 to store execution instructions or application code, and be controlled by processor 401 to implement the software upgrade method provided in the following embodiments of this application. In another possible design, memory 403 can also be integrated with processor 401, that is, memory 403 can be an internal memory of processor 401, for example, memory 403 is a high-speed cache that can be used to temporarily store some data and instruction information.

[0134] As an implementation method, the processor 401 may include one or more CPUs, such as Figure 1 As another implementation, the algorithm analysis device 103 may include multiple processors, such as Figure 4 As another implementation, the algorithm analysis device 103 may further include an output device 405 and an input device 406.

[0135] Optionally, the algorithm analysis device 403 can be applied to access network equipment, equipment rooms (eg, convergence rooms, core rooms, etc.), data centers, and other equipment.

[0136] It should be pointed out that Figure 4 The structure shown in does not constitute a limitation on the algorithm analysis device 103, except Figure 4 In addition to the components shown, the algorithm analysis device 103 may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0137] Through the description of the above embodiments, those skilled in the art will clearly understand that for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0138] Among them, the computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0139] The above are only specific embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or replacements within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A lagging battery determination system, characterized in that: The lagging battery determination system includes: a plurality of batteries, a collection device, and an algorithm analysis device; The acquisition device is used to obtain battery information of multiple batteries in a target time period and send the battery information of the multiple batteries in the target time period to the algorithm analysis device; the battery information includes: internal resistance, voltage, and terminal temperature; The algorithm analysis device is configured to receive battery information of the plurality of batteries during a target time period, determine a first battery bank, a second battery bank, and a third battery bank based on the battery information of the plurality of batteries during the target time period, and determine that batteries included in the first battery bank, the second battery bank, and the third battery bank are lagging batteries; The first battery pool includes batteries whose internal resistance abnormality frequency is greater than or equal to a first preset threshold value during the target time period; the second battery pool includes batteries whose voltage abnormality frequency is greater than or equal to a second preset threshold value during the target time period; and the third battery pool includes batteries whose battery pole temperature differs from the average pole temperature of the plurality of batteries by a degree greater than or equal to a third preset threshold value. The algorithm analysis device includes: a data storage module, a data analysis module, and a result determination module; The data storage module is configured to receive and store battery information of the plurality of batteries in a target time period, and send the battery information of the plurality of batteries in the target time period to the data analysis module; The data analysis module is configured to receive battery information of the plurality of batteries in a target time period, determine a first battery library, a second battery library, and a third battery library based on the battery information of the plurality of batteries in the target time period, and send the first battery library, the second battery library, and the third battery library to the result determination module; The result determination module is configured to receive the first battery library, the second battery library, and the third battery library, and determine that batteries included in the first battery library, the second battery library, and the third battery library are outdated batteries; The acquisition device includes: an online sampling module and a monitoring module; the online sampling module includes multiple battery acquisition modules; The battery collection module is configured to collect battery information of the multiple batteries in a preset time period and send the battery information of the multiple batteries in the preset time period to the monitoring module; the length of the preset time period is greater than the length of the target time period; The monitoring module is used to receive battery information of the multiple batteries in the preset time period, filter out battery information of the multiple batteries in the target time period from the battery information of the multiple batteries in the preset time period, and send the battery information of the multiple batteries in the target time period to the algorithm analysis device.

2. The system according to claim 1, wherein: The target time period includes: multiple first moments, multiple second moments, a third moment, and a fourth moment; the battery information includes: internal resistance at the multiple first moments, voltage at the multiple second moments, pole temperature at the third moment, and pole temperature at the fourth moment; the first moment is the moment when the battery is in a charging state; the second moment is the moment when the battery is in a discharging state; the third moment is the moment when the battery starts discharging; and the fourth moment is the moment when the battery ends discharging.

3. The system according to claim 2, characterized in that The data analysis module is specifically configured to perform the following operations on the internal resistance of the plurality of batteries at each first moment to obtain the first battery at each first moment; Determining an average value of the internal resistances of the plurality of batteries at a target first moment as a target average internal resistance; the target first moment being any first moment among the plurality of first moments; determining a battery with an abnormal internal resistance at the target first moment based on the internal resistances of the plurality of batteries at the target first moment and the target average internal resistance; The data analysis module is specifically used to determine the number of times each battery is marked as a battery with abnormal internal resistance based on the battery with abnormal internal resistance at each first moment, and determine that the battery is a battery in the first battery library when the number of times the battery is marked as a battery with abnormal internal resistance is greater than or equal to the first preset threshold.

4. The system according to claim 3, characterized in that The data analysis module is specifically configured to perform the following operations on the internal resistance of each battery at the target first moment to determine the battery with abnormal internal resistance at the target first moment; Determine a difference between the internal resistance of the target battery at the target first moment and the target average internal resistance, and a ratio of the difference to the target average internal resistance is a first difference value of the target battery at the target first moment; The target battery is any one of the multiple batteries; When the first difference value is greater than or equal to a fourth preset threshold, the target battery is marked as the battery with abnormal internal resistance.

5. The system according to claim 2, wherein: The data analysis module is specifically configured to determine that the sum of the voltages of the plurality of batteries at a preset second moment is the first voltage; the preset second moment is the earliest moment in the plurality of second moments; The data analysis module is specifically configured to determine a battery with abnormal voltage at each of the plurality of second moments according to the voltages of the plurality of batteries at each of the plurality of second moments and the first voltage; The data analysis module is specifically configured to determine, based on the battery with abnormal voltage at each second moment, the number of times each battery is marked as the battery with abnormal voltage; When the number of times the battery is marked as having abnormal voltage is greater than or equal to the second preset threshold, the data analysis module is specifically configured to determine that the battery is a battery in the second battery bank.

6. The system according to claim 5, characterized in that The data analysis module is specifically configured to perform the following operations: Performing the following operations on the voltages of the plurality of batteries at each second moment to obtain the battery with abnormal voltage at each second moment; Determine a difference between the voltages of the plurality of batteries at the target second moment and the voltages of the plurality of batteries at the preset second moment as a voltage drop of the plurality of batteries at the target second moment; The target second time is any one of the plurality of second time points; determining a second voltage as a difference between a sum of voltage drops of the plurality of batteries and the first voltage; performing the following operation on the voltage of each battery at the target second moment to determine a battery with abnormal voltage at the target second moment; Determine a difference between a voltage drop of a target battery and the second voltage, wherein a ratio of the voltage drop to the second voltage is a second difference value of the target battery; When the second difference value is greater than or equal to a fifth preset threshold, the target battery is marked as the battery with abnormal voltage.

7. The system according to claim 6, characterized in that When the second difference value is greater than or equal to the fifth preset threshold, the data analysis module is specifically configured to: determine a target second difference value of the target battery; the target second difference value is the second difference value of the target battery at the last sampling moment; the last sampling moment is the second moment with the latest time order among the multiple second moments; When the target second difference value is greater than or equal to a sixth preset threshold, the data analysis module is specifically configured to mark the target battery as the battery with abnormal voltage.

8. The system according to claim 2, wherein: The data analysis module is specifically configured to determine that an average value of the pole temperatures of the plurality of batteries at the third moment is a first pole temperature, and to determine that an average value of the pole temperatures of the plurality of batteries at the fourth moment is a second pole temperature; The data analysis module is specifically configured to determine a ratio of a difference between a pole temperature of the target battery at the third moment and the first pole temperature to a difference between a pole temperature of the target battery at the fourth moment and the second pole temperature as a third difference value of the target battery; When the third difference value is greater than or equal to the third preset threshold, the data analysis module is specifically configured to determine that the target battery is a battery in the third battery bank.

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