Voltage measurement method, computer device, vehicle, and storage medium

Abstract

Disclosed in embodiments of the present application are a voltage measurement method, a computer device, a vehicle, and a storage medium. The method comprises: acquiring a data group of a target object in at least one time interval, the data group comprising the voltage of each battery cell comprised in at least one battery pack of the target object; on the basis of the voltage, comprised in a data group in any time interval, of each battery cell comprised in any battery pack, obtaining the voltage of any battery pack in the any time interval; clustering the voltage of the at least one battery pack in the any time interval on the basis of a clustering algorithm to obtain a plurality of battery pack voltage clusters in the any time interval; determining suspected voltage outlier clusters and voltage outlier clusters from among the plurality of battery pack voltage clusters in the at least one time interval; and on the basis of the number of the suspected voltage outlier clusters and the number of the voltage outlier clusters, determining whether a battery pack voltage outlier is present in the target object. According to the embodiments of the present application, the voltages of battery packs can be effectively measured, thereby ensuring the efficient and safe operation of the battery system.

Description

Voltage detection method, computer equipment, vehicle and storage medium

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on February 19, 2024, with application number 202410187788.5 and invention name “A voltage detection method, device, vehicle and storage medium”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of battery technology, and in particular to a voltage detection method, computer equipment, vehicle, and storage medium. Background Art

[0003] With the rapid development of the new energy industry, batteries, as a core component of new energy, are gradually attracting attention from consumers. Although energy storage batteries offer many advantages such as large capacity, high energy density, and long service life, their complex internal structure and production process can lead to low or high voltage within the battery pack (BC) during use, resulting in problems such as abnormal battery capacity and, in severe cases, even the risk of internal short circuits. A battery pack voltage outlier refers to a significant difference or abnormality in the voltage of certain cells or individual cells in the battery pack compared to other cells.

[0004] Summary of the Invention

[0005] The embodiments of the present application provide a voltage detection method, computer equipment, vehicle, and storage medium, which can effectively detect the voltage of a battery pack and ensure the efficient and safe operation of the battery system.

[0006] In some embodiments of the present application, an embodiment of the present application provides a voltage detection method, the method comprising:

[0007] Acquire a data set of at least one time interval of a target object; the data set includes the voltage of each battery cell included in at least one battery pack of the target object;

[0008] Obtaining the voltage of any battery pack in any time interval according to the voltage of each cell included in any battery pack included in the data group in any time interval;

[0009] Clustering the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval;

[0010] determining a suspected voltage outlier cluster and a voltage outlier cluster from a plurality of battery pack voltage clusters in at least one time interval;

[0011] Whether the target object has battery pack voltage outliers is determined based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters.

[0012] In some embodiments of the present application, an embodiment of the present application provides a voltage detection device, which includes:

[0013] An acquisition unit, configured to acquire a data set of at least one time interval of a target object; the data set includes the voltage of each battery cell included in at least one battery pack of the target object;

[0014] a processing unit, configured to obtain the voltage of any battery pack in any time interval based on the voltage of each cell included in any battery pack included in the data group in any time interval;

[0015] The processing unit is further configured to cluster the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of battery pack voltage clusters in any time interval;

[0016] a determining unit, configured to determine a suspected voltage outlier cluster and a voltage outlier cluster from a plurality of battery pack voltage clusters in at least one time interval;

[0017] The determining unit is further configured to determine whether the target object has battery pack voltage outliers based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters.

[0018] In some embodiments of the present application, the determination unit determines the voltage outlier cluster in the following manner:

[0019] Obtaining a first voltage mean value of voltages included in a currently traversed suspected voltage outlier cluster, and a second voltage mean value of each other suspected voltage outlier cluster in at least one time interval except the currently traversed suspected voltage outlier cluster;

[0020] A voltage outlier cluster is determined based on the first voltage mean and each second voltage mean until the traversal ends.

[0021] In some embodiments of the present application, the determining unit determines a voltage outlier cluster based on the first voltage mean and each second voltage mean until the traversal ends, including:

[0022] If the absolute values ​​of the differences between the second voltage mean values ​​and the first voltage mean values ​​are all greater than the first preset voltage threshold, the currently traversed suspected voltage outlier cluster is determined as a voltage outlier cluster until the traversal is completed.

[0023] In some embodiments of the present application, the determining unit determines whether the target object has a battery pack voltage outlier based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters, including:

[0024] If the ratio of the number of voltage outlier clusters to the number of suspected voltage outlier clusters is greater than a first preset ratio threshold, or if the difference between the number of voltage outlier clusters and the number of other suspected voltage outlier clusters in the suspected voltage outlier clusters other than the voltage outlier cluster is greater than a preset number threshold, it is determined that a battery pack voltage outlier exists in the target object.

[0025] In some embodiments of the present application, the acquiring unit is further configured to include:

[0026] Obtaining object data of a target object; the object data of the target object includes voltages of respective cells contained in at least one battery pack of the target object within a historical time period;

[0027] The object data of the target object is divided to obtain a data group of at least one time interval of the target object.

[0028] In some embodiments of the present application, the object data further includes: the state of charge of each battery cell included in at least one battery pack in the target object during a historical time period;

[0029] The processing unit divides the object data of the target object to obtain a data group of at least one time interval of the target object, including: obtaining the voltage of each battery cell included in at least one battery pack at any time point from the object data;

[0030] Obtaining a target voltage at any time point from at least one voltage at any time point; the target voltage is higher than other voltages in the at least one voltage;

[0031] Obtain the target state of charge of the battery cell corresponding to the target voltage at any time point;

[0032] determining target object data based on the target voltage and the target state of charge;

[0033] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0034] In some embodiments of the present application, the determining unit determines the target object data based on the target voltage and the target state of charge, including:

[0035] If the target voltage is greater than a second preset voltage threshold, and the target state of charge is greater than a second preset ratio threshold, the object data at any time point in the object data is determined as the target object data.

[0036] In some embodiments of the present application, the object data further includes: the current of any battery cell included in at least one battery pack in the target object during a historical time period;

[0037] The processing unit divides the object data of the target object to obtain a data group of at least one time interval of the target object, including: obtaining the current of any battery cell at any time point and the current of any battery cell at k adjacent time points at any time point from the object data; k is a positive integer;

[0038] Determine target object data based on the current at any time point and the currents at k adjacent time points;

[0039] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0040] In some embodiments of the present application, the determining unit determines the target object data based on the current at any time point and the currents at k adjacent time points, including:

[0041] If the current at any time point is less than a first preset current threshold, and the difference between the maximum current and the minimum current among the currents at k adjacent time points and the current at any time point is less than a second preset current threshold, the object data at any time point in the object data is determined as the target object data.

[0042] In some embodiments of the present application, the processing unit clusters the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval, including:

[0043] Clustering the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of candidate battery pack voltage clusters;

[0044] If the number of the plurality of candidate battery pack voltage clusters is greater than a preset value, clustering the plurality of candidate battery pack voltage clusters based on a clustering algorithm to obtain a plurality of clustered candidate battery pack voltage clusters;

[0045] If the number of the plurality of clustered candidate battery pack voltage clusters is greater than a preset value, the plurality of clustered candidate battery pack voltage clusters are used as a plurality of candidate battery pack voltage clusters, and a clustering algorithm is triggered to cluster the plurality of candidate battery pack voltage clusters to obtain a plurality of clustered candidate battery pack voltage clusters, until the number of the plurality of clustered candidate battery pack voltage clusters obtained is equal to the preset value;

[0046] A plurality of clustered candidate battery pack voltage clusters, the number of which is equal to a preset value, is determined as a plurality of battery pack voltage clusters in any time interval.

[0047] In some embodiments of the present application, an embodiment of the present application provides a computer device, wherein the computer device includes a memory, a communication interface, and a processor, wherein the memory, the communication interface, and the processor are interconnected; the memory stores a computer program, and the processor calls the computer program stored in the memory to implement the above-mentioned voltage detection method.

[0048] In some embodiments of the present application, an embodiment of the present application provides a vehicle, wherein the vehicle includes a vehicle body and a processor, and the processor is used to execute the above-mentioned voltage detection method.

[0049] In some embodiments of the present application, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned voltage detection method is implemented.

[0050] In some embodiments of the present application, the embodiments of the present application provide a computer program product, which includes a computer program stored in a computer storage medium; a processor of a computer device reads the computer program from the computer storage medium, and the processor executes the computer program, so that the computer device performs the above-mentioned voltage detection method.

[0051] In an embodiment of the present application, a data set of at least one time interval of a target object is obtained; the data set includes the voltages of each cell contained in at least one battery pack of the target object; the voltage of any battery pack in any time interval is obtained based on the voltages of each cell contained in any battery pack contained in the data set of any time interval; the voltage of at least one battery pack in any time interval is clustered based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval; suspected voltage outlier clusters and voltage outlier clusters are determined from the multiple battery pack voltage clusters in at least one time interval; and whether the target object has battery pack voltage outliers is determined based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters. After detecting the suspected voltage outlier clusters of the battery pack, the voltage outlier cluster is determined to effectively detect the battery pack voltage outliers, which can effectively detect the battery pack voltage and ensure the efficient and safe operation of the battery system. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0053] FIG1 is a schematic diagram of the architecture of a voltage detection system provided in an embodiment of the present application;

[0054] FIG2 is a flow chart of a voltage detection method provided in an embodiment of the present application;

[0055] FIG3 is a schematic diagram of a flow chart of a clustering algorithm provided in an embodiment of the present application;

[0056] FIG4 is a flow chart of another voltage detection method provided in an embodiment of the present application;

[0057] FIG5 is a schematic structural diagram of a voltage detection device provided in an embodiment of the present application;

[0058] FIG6 is a schematic structural diagram of a computer device provided in an embodiment of the present application. Specific embodiments

[0059] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0060] It should be noted that, in this document, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0061] It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this document, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the term "if" as used herein may be interpreted as "when," "when," or "in response to a determination." Furthermore, as used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms "comprising" and "including" indicate the presence of the described features, steps, operations, elements, components, items, types, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, types, and / or groups. The terms "or," "and / or," "including at least one of the following," etc., used herein, may be interpreted as inclusive, or mean any one or any combination. For example, “comprising at least one of the following: A, B, C” means “any of the following: A; B; C; A and B; A and C; B and C; A and B and C”; and for another example, “A, B or C” or “A, B and / or C” means “any of the following: A; B; C; A and B; A and C; B and C; A and B and C”. An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some manner.

[0062] It should be understood that, although the various steps in the flowchart in the embodiment of the present application are shown in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless clearly stated herein, the execution of these steps is not strictly limited in order, and they can be performed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and their execution order is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0063] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to the determination" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0064] Please refer to Figure 1, which is a schematic diagram of the architecture of a voltage detection system provided in an embodiment of the present application. The target object may refer to a vehicle equipped with a battery or a photovoltaic system equipped with an energy storage battery.

[0065] Exemplarily, a data group of at least one time interval of a target object is obtained; the data group includes the voltages of individual cells contained in at least one battery pack of the target object; the voltage of any battery pack in any time interval is obtained based on the voltages of individual cells contained in any battery pack contained in the data group of any time interval; the voltage of at least one battery pack in any time interval is clustered based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval; suspected voltage outlier clusters and voltage outlier clusters are determined from the multiple battery pack voltage clusters of at least one time interval; and whether the target object has battery pack voltage outliers based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters.

[0066] Optionally, after the target object collects the original data of the target object and uploads it to the cloud server, the processor can obtain the original data of the target object from the cloud, sort the original data by time, and obtain the object data of the target object.

[0067] Please refer to FIG. 2 , which is a flow chart of a voltage detection method provided in an embodiment of the present application. The voltage detection method shown in FIG. 2 includes but is not limited to steps S201 to S205 , wherein:

[0068] S201: Acquire a data set of at least one time interval of a target object.

[0069] In this embodiment, the target object may refer to a vehicle equipped with a battery or a photovoltaic system equipped with an energy storage battery. For example, the target object is a target vehicle. After the vehicle collects vehicle data, it is uploaded to a cloud server or a local server, and the central processing unit (CPU) obtains a data group of at least one time interval of the target object.

[0070] In some embodiments of the present application, the method further comprises:

[0071] Obtaining object data of a target object; the object data of the target object includes voltages of respective cells contained in at least one battery pack of the target object within a historical time period;

[0072] The object data of the target object is divided to obtain a data group of at least one time interval of the target object.

[0073] In this embodiment, the CPU divides the vehicle data to obtain a data group of at least one time interval of the target vehicle.

[0074] In one implementation, the object data further includes: the state of charge of each battery cell included in at least one battery pack in the target object during a historical time period;

[0075] Dividing the object data of the target object to obtain a data group of at least one time interval of the target object includes: obtaining the voltage of each battery cell included in at least one battery pack at any time point from the object data;

[0076] Obtaining a target voltage at any time point from at least one voltage at any time point; the target voltage is higher than other voltages in the at least one voltage;

[0077] Obtain the target state of charge of the battery cell corresponding to the target voltage at any time point;

[0078] determining target object data based on the target voltage and the target state of charge;

[0079] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0080] In this embodiment, the voltage of each battery cell contained in at least one battery pack in the vehicle data at any time point is obtained, and the target voltage at any time point is obtained from at least one voltage at any time point, the target voltage is higher than other voltages in the at least one voltage, that is, the highest voltage, and the state of charge (SOC) of the battery cell corresponding to the highest voltage is obtained, where the state of charge refers to the percentage of the amount of electricity stored in the battery relative to the total capacity, and the target vehicle data is determined based on the highest voltage and the state of charge of the highest voltage; the time-continuous target vehicle data in the vehicle data is determined as a data group of a time interval to obtain a data group of at least one time interval.

[0081] In one implementation, determining target object data based on the target voltage and the target state of charge includes:

[0082] If the target voltage is greater than a second preset voltage threshold, and the target state of charge is greater than a second preset ratio threshold, the object data at any time point in the object data is determined as the target object data.

[0083] In this embodiment, if the maximum voltage is greater than a second preset voltage threshold, for example, the second preset voltage threshold is 3V, if the maximum voltage is greater than 3V, and the state of charge of the battery cell corresponding to the maximum voltage is greater than a second preset ratio threshold, for example, the second preset ratio threshold is sixty percent, if the state of charge of the battery cell corresponding to the maximum voltage is greater than sixty percent, then the vehicle data at any time point in the vehicle data is determined as the target vehicle data.

[0084] In one implementation, the object data further includes: the current of any battery cell included in at least one battery pack in the target object during a historical time period;

[0085] Dividing the object data of the target object to obtain a data group of at least one time interval of the target object includes: obtaining the current of any battery cell at any time point and the current of any battery cell at k adjacent time points at any time point from the object data, where k is a positive integer;

[0086] Determine target object data based on the current at any time point and the currents at k adjacent time points;

[0087] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0088] In this embodiment, the current of any battery cell at any time point and the current of any battery cell at k adjacent time points are obtained from vehicle data; k is a positive integer; the k time points can be the k time points before the any time point, the k time points after the any time point, or a total of k time points before and after the any time point. Target object data is determined based on the current at any time point and the currents at the k adjacent time points; and the temporally continuous target object data in the object data are determined as a data group for a time interval, thereby obtaining a data group for at least one time interval.

[0089] In one implementation, determining target object data based on the current at any time point and the currents at k adjacent time points includes:

[0090] If the current at any time point is less than a first preset current threshold, and the difference between the maximum current and the minimum current among the currents at k adjacent time points and the current at any time point is less than a second preset current threshold, the object data at any time point in the object data is determined as the target object data.

[0091] In this embodiment, if the current at any time point is less than a first preset current threshold, and the difference between the current at k adjacent time points and the maximum and minimum currents at any time point is less than a second preset current threshold, then the vehicle data at any time point in the vehicle data is determined as target vehicle data. For example, if the value of k is 4, the first preset current threshold is 0.2 amperes, and the second preset current threshold is 1 ampere, then the current at any time point and the four adjacent time points is obtained. If the current at any time point is less than 0.2 amperes, and the difference between the maximum and minimum currents at any time point and the four adjacent time points is less than 1 ampere, then the vehicle data at any time point in the vehicle data is determined as target vehicle data.

[0092] Alternatively, the original vehicle data of the target vehicle can be obtained from the cloud big data platform and preprocessed to obtain the vehicle data. For example, preprocessing can include deleting illegal data caused by software and hardware sampling failures on the target vehicle, cloud communication failures, and parsing errors; reordering the data based on the data time, and retaining only one frame of data with the same data time. After preprocessing the original vehicle data, the vehicle data is obtained.

[0093] S202 , obtaining the voltage of any battery pack in any time interval according to the voltage of each cell included in any battery pack included in the data group in any time interval.

[0094] In this embodiment, the voltage of the battery pack corresponding to each battery cell is determined by the voltage of each battery cell. For example, the battery pack includes a first battery cell, a second battery cell and a third battery cell, and the voltage of the first battery cell is 2V, the voltage of the second battery cell is 3V, and the voltage of the third battery cell is 3V. Then the voltage of the battery pack is obtained by adding the battery cell voltages, that is, 9V.

[0095] S203 , clustering the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of battery pack voltage clusters in any time interval.

[0096] In this embodiment, the voltage of at least one battery pack in any time interval is clustered using a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval.

[0097] In one implementation, clustering the voltage of at least one battery pack in any time interval is performed based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval, including:

[0098] Clustering the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of candidate battery pack voltage clusters;

[0099] If the number of the plurality of candidate battery pack voltage clusters is greater than a preset value, clustering the plurality of candidate battery pack voltage clusters based on a clustering algorithm to obtain a plurality of clustered candidate battery pack voltage clusters;

[0100] If the number of the plurality of clustered candidate battery pack voltage clusters is greater than a preset value, the plurality of clustered candidate battery pack voltage clusters are used as a plurality of candidate battery pack voltage clusters, and a clustering algorithm is triggered to cluster the plurality of candidate battery pack voltage clusters to obtain a plurality of clustered candidate battery pack voltage clusters, until the number of the plurality of clustered candidate battery pack voltage clusters obtained is equal to the preset value;

[0101] A plurality of clustered candidate battery pack voltage clusters, the number of which is equal to a preset value, is determined as a plurality of battery pack voltage clusters in any time interval.

[0102] In this embodiment, please refer to FIG3 , which is a flow chart of a clustering algorithm provided in an embodiment of the present application.

[0103] S301, input an independent cluster.

[0104] Enter the individual battery pack voltage data within the vehicle data segment as a separate cluster.

[0105] S302: Calculate the inter-cluster distance.

[0106] The inter-cluster distance is calculated based on the voltage data characteristics of a single battery pack and the task requirements. Optional clustering algorithms include Single Linkage (selecting the distance between the two points with the shortest distance in the two clusters as the inter-cluster distance), Complete Linkage (selecting the distance between the two points with the farthest distance in the two clusters as the inter-cluster distance), Average Linkage (taking the average of the distances between all pairs of points in the two clusters as the inter-cluster distance), or Ward Linkage (Ward Linkage, when merging two clusters, minimizing the increase in the variance within the cluster after the merger) to calculate the inter-cluster distance.

[0107] S303, clusters corresponding to the shortest inter-cluster distances are aggregated.

[0108] All battery pack voltage data in the cluster with the shortest inter-cluster distance are aggregated to form a new cluster, thereby obtaining multiple candidate battery pack voltage clusters.

[0109] S304: Determine whether the clustering result meets the requirements.

[0110] Analyze whether the current clustering result meets the requirements, that is, the number N of clusters obtained by the final clustering. The value of N is not fixed and is generally 2 or 3. For example, if the value of N is 2 and the number of clusters obtained by the final clustering is 2, the requirement is met and the clustering algorithm is stopped. If the number of clusters obtained by the final clustering is greater than 2, the requirement is not met and the above step S302 is performed to calculate the inter-cluster distance. If the number of candidate battery pack voltage clusters after the multiple clustering is greater than the preset number 2, the candidate battery pack voltage clusters after the multiple clustering are regarded as multiple candidate battery pack voltage clusters and the inter-cluster distance is continued to be calculated for clustering until the number of candidate battery pack voltage clusters after the multiple clustering is equal to the preset number 2.

[0111] S305: Output the clusters after clustering.

[0112] After clustering is completed, N preset battery pack voltage clusters in any time interval are obtained.

[0113] S204 : Determine suspected voltage outlier clusters and voltage outlier clusters from a plurality of battery pack voltage clusters in at least one time interval.

[0114] In one implementation, a method for determining a voltage outlier cluster includes:

[0115] Obtaining a first voltage mean value of voltages included in a currently traversed suspected voltage outlier cluster, and a second voltage mean value of each other suspected voltage outlier cluster in at least one time interval except the currently traversed suspected voltage outlier cluster;

[0116] A voltage outlier cluster is determined based on the first voltage mean and each second voltage mean until the traversal ends.

[0117] In this embodiment, after clustering is completed, N preset battery pack voltage clusters are obtained. Among the N battery pack voltage clusters, the cluster with the least number of battery pack voltage data is determined as a suspected outlier cluster. The suspected voltage outlier clusters of at least one time interval are traversed, and the first voltage mean value of the voltages included in the currently traversed suspected voltage outlier cluster and the second voltage mean values ​​of each suspected voltage outlier cluster other than the currently traversed suspected voltage outlier cluster in the suspected voltage outlier cluster of at least one time interval are obtained. The voltage outlier cluster is determined based on the first voltage mean value and each second voltage mean value until the traversal is completed.

[0118] In one implementation, determining a voltage outlier cluster based on the first voltage mean and each second voltage mean until the traversal is completed includes:

[0119] If the absolute values ​​of the differences between the second voltage mean values ​​and the first voltage mean values ​​are all greater than the first preset voltage threshold, the currently traversed suspected voltage outlier cluster is determined as a voltage outlier cluster until the traversal is completed.

[0120] In this embodiment, for example, if the first preset voltage threshold is 0.5V, the first voltage mean of the currently traversed suspected voltage outlier cluster is 4V, and the second voltage means are 5V, 5.2V, and 5.3V, then the absolute value of the difference between the second voltage means and the first voltage mean is 1V, 1.2V, and 1.3V, and the absolute value of the difference between the second voltage means and the first voltage mean is greater than the first preset voltage threshold, then the currently traversed suspected voltage outlier cluster is determined to be a voltage outlier cluster, and this continues until the traversal ends. When the voltage data for each time interval BC has been obtained, only the number of clusters N at the time of clustering completion, which is an external parameter, needs to be input into the clustering algorithm to obtain the information of the suspected voltage outlier cluster. There is no need to design a detection threshold based on the historical data of the detected battery, the battery production process, the battery model, and other information. Therefore, this method is highly adaptive.

[0121] S205 : Determine whether there is a battery pack voltage outlier in the target object based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters.

[0122] In one implementation, determining whether a target object has a battery pack voltage outlier based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters includes:

[0123] If the ratio of the number of voltage outlier clusters to the number of suspected voltage outlier clusters is greater than a first preset ratio threshold, or if the difference between the number of voltage outlier clusters and the number of other suspected voltage outlier clusters in the suspected voltage outlier clusters other than the voltage outlier cluster is greater than a preset number threshold, it is determined that a battery pack voltage outlier exists in the target object.

[0124] In this embodiment, the target object may refer to a vehicle equipped with a battery or a photovoltaic system equipped with an energy storage battery. For example, the target object is a target vehicle, and the number of determined voltage outlier clusters and the number of suspected voltage outlier clusters are obtained. For example, if the first preset ratio threshold is 50%, the number of voltage outlier clusters is 6, the number of suspected voltage outlier clusters is 10, and the ratio of voltage outlier clusters to suspected voltage outlier clusters is 60%, and 60% is greater than 50%, then it is determined that the target vehicle has a battery pack voltage outlier; or if the preset number threshold is 10, the number of voltage outlier clusters is 20, the number of suspected voltage outlier clusters is 5, and the difference between the number of voltage outlier clusters and the number of suspected voltage outlier clusters is 15, and the difference 15 is greater than the preset number 10, then it is determined that the target vehicle has a battery pack voltage outlier. By adjusting the first preset ratio threshold or the preset number threshold, the width of the detection window can be adjusted, and the detection standard can be specifically adjusted for the key focus object.

[0125] In an embodiment of the present application, a data set of at least one time interval of a target object is obtained; the data set includes the voltages of each cell contained in at least one battery pack of the target object; the voltage of any battery pack in any time interval is obtained based on the voltages of each cell contained in any battery pack contained in the data set of any time interval; the voltage of at least one battery pack in any time interval is clustered based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval; suspected voltage outlier clusters and voltage outlier clusters are determined from the multiple battery pack voltage clusters in at least one time interval; and whether the target object has battery pack voltage outliers is determined based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters. After detecting the suspected voltage outlier clusters of the battery pack, the voltage outlier cluster is determined, which can effectively detect the battery pack voltage and ensure the efficient and safe operation of the battery system.

[0126] Please refer to FIG4 , which is a flowchart of another voltage detection method provided by an embodiment of the present application. The voltage detection method shown in FIG4 includes but is not limited to steps S401 to S406 , wherein:

[0127] S401, determining the charge and discharge status of the target object.

[0128] In this embodiment, the target object may refer to a vehicle equipped with a battery or a photovoltaic system equipped with an energy storage battery. For example, the target object is a target vehicle, and the charging and discharging status of the vehicle is first determined based on the vehicle data obtained from the cloud.

[0129] Alternatively, the current data can be used to determine the vehicle's charge and discharge status; for example, a positive current typically indicates charging, while a negative current indicates discharging. Zero current typically indicates the battery is at rest, meaning it is not being charged or discharged.

[0130] Optionally, the charge and discharge status of the vehicle is determined by voltage data; for example, a higher voltage may indicate charging, and a lower voltage may indicate discharging.

[0131] Optionally, the state of charge (SOC) is used to determine the vehicle's charge and discharge status. SOC refers to the ratio of the battery's current stored charge to its total capacity, usually expressed as a percentage. If the SOC value increases, it is charging, and if it decreases, it is discharging.

[0132] Alternatively, the charge and discharge status of the vehicle can be determined by the vehicle operating conditions; for example, if the vehicle is driving and the battery current is positive, the battery is likely to be in a discharging state. If the vehicle is stopped and the current is positive, the battery is likely to be in a charging state.

[0133] Optionally, the vehicle's charging and discharging status can be comprehensively judged based on current, voltage, state of charge and vehicle operating conditions.

[0134] S402 : Divide the object data of the target object based on the charge and discharge state of the target object to obtain a data group of at least one time interval.

[0135] In this embodiment, optionally, if the target vehicle is in a charging state, the vehicle data of the target vehicle is divided based on a division method during charging to obtain a data group of at least one time interval.

[0136] In one implementation, the object data further includes: the state of charge of each battery cell included in at least one battery pack in the target object during a historical time period;

[0137] Dividing the object data of the target object to obtain a data group of at least one time interval of the target object includes: obtaining the voltage of each battery cell included in at least one battery pack at any time point from the object data;

[0138] Obtaining a target voltage at any time point from at least one voltage at any time point; the target voltage is higher than other voltages in the at least one voltage;

[0139] Obtain the target state of charge of the battery cell corresponding to the target voltage at any time point;

[0140] determining target object data based on the target voltage and the target state of charge;

[0141] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0142] In this embodiment, if the target vehicle is in a charging state, the voltage of each battery cell contained in at least one battery pack at any time point is obtained in the vehicle sequence data, and the target voltage at any time point is obtained from at least one voltage at any time point. The target voltage is higher than other voltages in the at least one voltage, that is, the highest voltage. The SOC of the battery cell corresponding to the highest voltage is obtained, and the target vehicle data is determined based on the highest voltage and the SOC of the highest voltage; the time-continuous target vehicle data in the vehicle data is determined as a data group of a time interval to obtain a data group of at least one time interval.

[0143] In one implementation, determining target object data based on the target voltage and the target state of charge includes:

[0144] If the target voltage is greater than a second preset voltage threshold, and the target state of charge is greater than a second preset ratio threshold, the object data at any time point in the object data is determined as the target object data.

[0145] In this embodiment, if the maximum voltage is greater than a second preset voltage threshold, for example, the second preset voltage threshold is 3V, if the maximum voltage is greater than 3V, and the SOC of the battery cell corresponding to the maximum voltage is greater than a second preset ratio threshold, for example, the second preset ratio threshold is 60%, if the state of charge of the battery cell corresponding to the maximum voltage is greater than 60%, then the vehicle data at any time point in the vehicle data is determined as the target vehicle data, and the time-continuous target vehicle data in the vehicle data is determined as a data group of a time interval to obtain a data group of at least one time interval and the data group is a high-state charging segment. Intercepting the high-state charging segment as a data group can eliminate the adverse effects of the voltage characteristics of the lithium iron phosphate battery on the voltage of the individual cell (IC), wherein the voltage characteristics of the lithium iron phosphate battery refer to the existence of a plateau period in the lithium iron phosphate battery during the charging process. During the plateau period, the voltage difference of the IC with a large SOC difference is not obvious, and cluster analysis cannot be performed. In contrast, during the high-state-of-charge phase, the IC voltage is significantly affected by the SOC, making it easier to detect IC voltage changes caused by cell problems. Since resistance increases during the high-SOC phase, even small resistance differences can significantly impact the voltage. The purpose of intercepting the high-state-of-charge point is to minimize the negative impact of the lithium iron phosphate battery's voltage characteristics on the IC voltage.

[0146] Optionally, if the target vehicle is in a discharging state, the vehicle data of the target vehicle is divided based on a division method during discharge to obtain a data group of at least one time interval.

[0147] In one implementation, the object data further includes: the current of any battery cell included in at least one battery pack in the target object during a historical time period;

[0148] Dividing the object data of the target object to obtain a data group of at least one time interval of the target object includes: obtaining the current of any battery cell at any time point and the current of any battery cell at k adjacent time points at any time point from the object data, where k is a positive integer;

[0149] Determine target object data based on the current at any time point and the currents at k adjacent time points;

[0150] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0151] In this embodiment, if the target vehicle is in a discharging state, the current of any battery cell at any time point and the current of any battery cell at k adjacent time points are obtained from the vehicle data sequence; k is a positive integer; the k time points can be the k time points before the any time point, the k time points after the any time point, or the k time points before and after the any time point. Based on the current at any time point and the current at the k adjacent time points, the target vehicle data is determined; the temporally continuous target vehicle data in the vehicle data is determined as a data group for a time interval, thereby obtaining a data group for at least one time interval.

[0152] In one implementation, determining target object data based on the current at any time point and the currents at k adjacent time points includes:

[0153] If the current at any time point is less than a first preset current threshold, and the difference between the maximum current and the minimum current among the currents at k adjacent time points and the current at any time point is less than a second preset current threshold, the object data at any time point in the object data is determined as the target object data.

[0154] In this embodiment, if the current at any time point is less than a first preset current threshold, and the difference between the current at k adjacent time points and the maximum and minimum currents at any time point is less than a second preset current threshold, then the vehicle data at any time point in the vehicle data is determined as target vehicle data. For example, if the value of k is 4, the first preset current threshold is 0.2 amperes, and the second preset current threshold is 1 ampere, then the current at any time point and the four adjacent time points is obtained. If the current at any time point is less than 0.2 amperes, and the difference between the maximum and minimum currents at any time point and the four adjacent time points is less than 1 ampere, then the vehicle data at any time point in the vehicle data is determined as target vehicle data.

[0155] S403 , obtaining the voltage of any battery pack in any time interval according to the voltage of each cell included in any battery pack included in the data group in any time interval.

[0156] For the specific steps of this embodiment, please refer to the above step S202, and this step will not be repeated.

[0157] S404 , clustering the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of battery pack voltage clusters in any time interval.

[0158] For the specific steps of this embodiment, please refer to the above step S203, and this step will not be repeated.

[0159] S405 : Determine suspected voltage outlier clusters and voltage outlier clusters from a plurality of battery pack voltage clusters in at least one time interval.

[0160] For the specific steps of this embodiment, please refer to the above step S204, and this step will not be repeated.

[0161] S406 : Determine whether there is a battery pack voltage outlier in the target object based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters.

[0162] For the specific steps of this embodiment, please refer to the above step S205, and this step will not be repeated.

[0163] In an embodiment of the present application, the charge and discharge state of a target object is determined. Based on the charge and discharge state of the target object, the object data of the target object is divided to obtain a data group of at least one time interval. The voltage of any battery pack in any time interval is obtained based on the voltage of each cell contained in any battery pack contained in the data group of any time interval. The voltage of at least one battery pack in any time interval is clustered based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval. From the multiple battery pack voltage clusters in at least one time interval, suspected voltage outlier clusters and voltage outlier clusters are determined. Based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters, it is determined whether the target object has battery pack voltage outliers. By determining the charge and discharge state of the target object, and then obtaining the BC voltage data of the high-state charging segment and the steady-state discharge segment respectively, the data of the charging segment and the discharge segment can be covered, thereby achieving all-weather detection of the battery cells. After detecting the suspected voltage outlier cluster of the battery pack, the voltage outlier cluster is determined, which can effectively detect the battery pack voltage and ensure the efficient and safe operation of the battery system.

[0164] An embodiment of the present application further provides a computer storage medium, in which program instructions are stored. When the program instructions are executed, they are used to implement the corresponding methods described in the above embodiments.

[0165] Referring again to FIG. 5 , FIG. 5 is a schematic structural diagram of a voltage detection device provided in an embodiment of the present application.

[0166] In one implementation of the voltage detection device of the embodiment of the present application, the voltage detection device includes the following structure:

[0167] An acquisition unit 501 is configured to acquire a data set of at least one time interval of a target object; the data set includes the voltage of each cell included in at least one battery pack of the target object;

[0168] The processing unit 502 is configured to obtain the voltage of any battery pack in any time interval based on the voltage of each cell included in any battery pack included in the data group in any time interval;

[0169] The processing unit 502 is further configured to cluster the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of battery pack voltage clusters in any time interval;

[0170] a determining unit 503 , configured to determine a suspected voltage outlier cluster and a voltage outlier cluster from a plurality of battery pack voltage clusters in at least one time interval;

[0171] The determining unit 503 is further configured to determine whether the target object has a battery pack voltage outlier according to the number of suspected voltage outlier clusters and the number of voltage outlier clusters.

[0172] In some embodiments of the present application, in one embodiment, the determination unit 503 determines the voltage outlier cluster in the following manner:

[0173] Obtaining a first voltage mean value of voltages included in a currently traversed suspected voltage outlier cluster, and a second voltage mean value of each other suspected voltage outlier cluster in at least one time interval except the currently traversed suspected voltage outlier cluster;

[0174] A voltage outlier cluster is determined based on the first voltage mean and each second voltage mean until the traversal ends.

[0175] In some embodiments of the present application, the determining unit 503 determines a voltage outlier cluster based on the first voltage mean and each second voltage mean until the traversal is completed, including:

[0176] If the absolute values ​​of the differences between the second voltage mean values ​​and the first voltage mean values ​​are all greater than the first preset voltage threshold, the currently traversed suspected voltage outlier cluster is determined as a voltage outlier cluster until the traversal is completed.

[0177] In some embodiments of the present application, the determining unit 503 determines whether the target object has a battery voltage outlier based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters, including:

[0178] If the ratio of the number of voltage outlier clusters to the number of suspected voltage outlier clusters is greater than a first preset ratio threshold, or the difference between the number of voltage outlier clusters and the number of other suspected voltage outlier clusters in the suspected voltage outlier clusters other than the voltage outlier cluster is greater than a preset number threshold, it is determined that the target vehicle has a battery pack voltage outlier.

[0179] In some embodiments of the present application, the acquiring unit 501 is further configured to include:

[0180] Obtaining object data of a target object; the object data of the target object includes voltages of respective cells contained in at least one battery pack of the target object within a historical time period;

[0181] The object data of the target object is divided to obtain a data group of at least one time interval of the target object.

[0182] In some embodiments of the present application, the object data further includes: the state of charge of each battery cell included in at least one battery pack in the target object during a historical time period;

[0183] The processing unit 502 divides the object data of the target object to obtain a data group of at least one time interval of the target object, including: obtaining the voltage of each battery cell included in at least one battery pack at any time point from the object data;

[0184] Obtaining a target voltage at any time point from at least one voltage at any time point; the target voltage is higher than other voltages in the at least one voltage;

[0185] Obtain the target state of charge of the battery cell corresponding to the target voltage at any time point;

[0186] determining target object data based on the target voltage and the target state of charge;

[0187] Determine the time-continuous target object data in the object data as a data group of a time interval to obtain a data group of at least one time interval. In one embodiment, the determination unit 503 determines the target object data based on the target voltage and the target state of charge, including:

[0188] If the target voltage is greater than a second preset voltage threshold, and the target state of charge is greater than a second preset ratio threshold, the object data at any time point in the object data is determined as the target object data.

[0189] In some embodiments of the present application, the object data further includes: the current of any battery cell included in at least one battery pack in the target object during a historical time period;

[0190] The processing unit 502 divides the object data of the target object to obtain a data group of at least one time interval of the target object, including: obtaining the current of any battery cell at any time point and the current of any battery cell at k adjacent time points at any time point from the object data; k is a positive integer;

[0191] Determine target object data based on the current at any time point and the currents at k adjacent time points;

[0192] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0193] In some embodiments of the present application, the determining unit 503 determines the target object data based on the current at any time point and the currents at k adjacent time points, including:

[0194] If the current at any time point is less than a first preset current threshold, and the difference between the maximum current and the minimum current among the currents at k adjacent time points and the current at any time point is less than a second preset current threshold, the object data at any time point in the object data is determined as the target object data.

[0195] In some embodiments of the present application, the processing unit 502 clusters the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval, including:

[0196] Clustering the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of candidate battery pack voltage clusters;

[0197] If the number of the plurality of candidate battery pack voltage clusters is greater than a preset value, clustering the plurality of candidate battery pack voltage clusters based on a clustering algorithm to obtain a plurality of clustered candidate battery pack voltage clusters;

[0198] If the number of the plurality of clustered candidate battery pack voltage clusters is greater than a preset value, the plurality of clustered candidate battery pack voltage clusters are used as a plurality of candidate battery pack voltage clusters, and a clustering algorithm is triggered to cluster the plurality of candidate battery pack voltage clusters to obtain a plurality of clustered candidate battery pack voltage clusters, until the number of the plurality of clustered candidate battery pack voltage clusters obtained is equal to the preset value;

[0199] A plurality of clustered candidate battery pack voltage clusters, the number of which is equal to a preset value, is determined as a plurality of battery pack voltage clusters in any time interval.

[0200] In an embodiment of the present application, the acquisition unit 501 acquires a data group of at least one time interval of the target object; the data group includes the voltage of each cell contained in at least one battery pack of the target object; the processing unit 502 obtains the voltage of any battery pack in any time interval based on the voltage of each cell contained in any battery pack contained in the data group of any time interval; the processing unit 502 clusters the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval; the determination unit 503 determines suspected voltage outlier clusters and voltage outlier clusters from the multiple battery pack voltage clusters in at least one time interval; the determination unit 503 determines whether there is a battery pack voltage outlier in the target object based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters. After detecting the suspected voltage outlier cluster of the battery pack, the voltage outlier cluster is determined, which can effectively detect the battery pack voltage and ensure the efficient and safe operation of the battery system.

[0201] Referring again to FIG. 6 , FIG. 6 is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. The computer device in an embodiment of the present application includes a power supply module and other structures. The computer device can run on a cloud server or a local server and includes a processor 601, a memory 602, and a communication interface 603. The processor 601, the memory 602, and the communication interface 603 can exchange data, and the processor 601 implements the corresponding voltage detection method.

[0202] The memory 602 may include volatile memory, such as random-access memory (RAM); the memory 602 may also include non-volatile memory, such as flash memory, solid-state drive (SSD), etc.; the memory 602 may also include a combination of the above types of memory.

[0203] The processor 601 may be a central processing unit (CPU). The processor 601 may also be a combination of a central processing unit (CPU) and a graphics processing unit (GPU). In a computer device, multiple CPUs and GPUs may be included as needed to perform corresponding voltage detection. In one embodiment, the memory 602 is used to store program instructions. The processor 601 may call program instructions to implement the various methods described above in the embodiments of the present application.

[0204] In some embodiments of the present application, the processor 601 of the computer device calls the program instructions stored in the memory 602 to obtain a data group of at least one time interval of the target object; the data group includes the voltage of each battery cell contained in at least one battery pack of the target object; based on the voltage of each battery cell contained in any battery pack contained in the data group of any time interval, the voltage of any battery pack in any time interval is obtained; based on the clustering algorithm, the voltage of at least one battery pack in any time interval is clustered to obtain multiple battery pack voltage clusters in any time interval; from the multiple battery pack voltage clusters of at least one time interval, suspected voltage outlier clusters and voltage outlier clusters are determined; based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters, it is determined whether the target object has battery pack voltage outliers.

[0205] In some embodiments of the present application, the processor 601 may perform the following operations to determine the voltage outlier cluster:

[0206] Obtaining a first voltage mean value of voltages included in a currently traversed suspected voltage outlier cluster, and a second voltage mean value of each other suspected voltage outlier cluster in at least one time interval except the currently traversed suspected voltage outlier cluster;

[0207] A voltage outlier cluster is determined based on the first voltage mean and each second voltage mean until the traversal ends.

[0208] In some embodiments of the present application, the processor 601 determines a voltage outlier cluster based on the first voltage mean and each second voltage mean until the traversal is completed, and may perform the following operations:

[0209] If the absolute values ​​of the differences between the second voltage mean values ​​and the first voltage mean values ​​are all greater than the first preset voltage threshold, the currently traversed suspected voltage outlier cluster is determined as a voltage outlier cluster until the traversal is completed.

[0210] In some embodiments of the present application, the processor 601 determines whether a battery pack voltage outlier exists in the target object based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters, and may perform the following operations:

[0211] If the ratio of the number of voltage outlier clusters to the number of suspected voltage outlier clusters is greater than a first preset ratio threshold, or if the difference between the number of voltage outlier clusters and the number of other suspected voltage outlier clusters in the suspected voltage outlier clusters other than the voltage outlier cluster is greater than a preset number threshold, it is determined that a battery pack voltage outlier exists in the target object.

[0212] In some embodiments of the present application, the processor 601 may further perform the following operations:

[0213] Obtaining object data of a target object; the object data of the target object includes voltages of respective cells contained in at least one battery pack of the target object within a historical time period;

[0214] The object data of the target object is divided to obtain a data group of at least one time interval of the target object.

[0215] In some embodiments of the present application, the object data further includes: the state of charge of each battery cell included in at least one battery pack in the target object during a historical time period;

[0216] The processor 601 divides the object data of the target object to obtain a data group of at least one time interval of the target object, and may perform the following operations:

[0217] Obtaining, from the object data, the voltage of each battery cell included in at least one battery pack at any time point;

[0218] Obtaining a target voltage at any time point from at least one voltage at any time point; the target voltage is higher than other voltages in the at least one voltage;

[0219] Obtain the target state of charge of the battery cell corresponding to the target voltage at any time point;

[0220] determining target object data based on the target voltage and the target state of charge;

[0221] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0222] In some embodiments of the present application, the processor 601 determines target object data based on the target voltage and the target state of charge, and may perform the following operations:

[0223] If the target voltage is greater than a second preset voltage threshold, and the target state of charge is greater than a second preset ratio threshold, the object data at any time point in the object data is determined as the target object data.

[0224] In some embodiments of the present application, the object data further includes: the current of any battery cell included in at least one battery pack in the target object during a historical time period;

[0225] The processor 601 divides the object data of the target object to obtain a data group of at least one time interval of the target object, and may perform the following operations:

[0226] Obtain the current of any cell at any time point and the current of any cell at k adjacent time points at any time point from the object data; k is a positive integer;

[0227] Determine target object data based on the current at any time point and the currents at k adjacent time points;

[0228] The time-continuous target object data in the object data are determined as a data group of a time interval to obtain a data group of at least one time interval.

[0229] In some embodiments of the present application, the target object data is determined based on the current at any time point and the currents at k adjacent time points. The following operations may be performed:

[0230] If the current at any time point is less than a first preset current threshold, and the difference between the maximum current and the minimum current among the currents at k adjacent time points and the current at any time point is less than a second preset current threshold, the object data at any time point in the object data is determined as the target object data.

[0231] In some embodiments of the present application, the processor 601 clusters the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain multiple battery pack voltage clusters in any time interval, and may perform the following operations:

[0232] Clustering the voltage of at least one battery pack in any time interval based on a clustering algorithm to obtain a plurality of candidate battery pack voltage clusters;

[0233] If the number of the plurality of candidate battery pack voltage clusters is greater than a preset value, clustering the plurality of candidate battery pack voltage clusters based on a clustering algorithm to obtain a plurality of clustered candidate battery pack voltage clusters;

[0234] If the number of the plurality of clustered candidate battery pack voltage clusters is greater than a preset value, the plurality of clustered candidate battery pack voltage clusters are used as a plurality of candidate battery pack voltage clusters, and a clustering algorithm is triggered to cluster the plurality of candidate battery pack voltage clusters to obtain a plurality of clustered candidate battery pack voltage clusters, until the number of the plurality of clustered candidate battery pack voltage clusters obtained is equal to the preset value;

[0235] A plurality of clustered candidate battery pack voltage clusters, the number of which is equal to a preset value, is determined as a plurality of battery pack voltage clusters in any time interval.

[0236] In an embodiment of the present application, the processor 601 obtains a data set of at least one time interval of a target object; the data set includes the voltage of each cell contained in at least one battery pack of the target object; based on the voltage of each cell contained in any battery pack contained in the data set of any time interval, the voltage of any battery pack in any time interval is obtained; based on the clustering algorithm, the voltage of at least one battery pack in any time interval is clustered to obtain multiple battery pack voltage clusters in any time interval; from the multiple battery pack voltage clusters in at least one time interval, suspected voltage outlier clusters and voltage outlier clusters are determined; based on the number of suspected voltage outlier clusters and the number of voltage outlier clusters, it is determined whether the target object has battery pack voltage outliers. After detecting the suspected voltage outlier cluster of the battery pack, the voltage outlier cluster is determined, which can effectively detect the battery pack voltage and ensure the efficient and safe operation of the battery system.

[0237] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM (Read-Only Memory), random access memory (RAM), magnetic disks, or optical disks.

[0238] The above disclosure is only part of the embodiments of the present application, and it is certainly not intended to limit the scope of the rights of the present application. Ordinary technicians in this field can understand that all or part of the processes of the above embodiments and equivalent changes made in accordance with the claims of the present application are still within the scope covered by the present application.

Claims

1. A voltage detection method, wherein: include: Acquire a data set of at least one time interval of a target object; the data set includes the voltage of each battery cell included in at least one battery pack of the target object; Obtaining the voltage of any battery pack in any time interval according to the voltage of each cell included in any battery pack included in the data group in any time interval; Clustering the voltage of the at least one battery pack in the any time interval based on a clustering algorithm to obtain a plurality of battery pack voltage clusters in the any time interval; determining a suspected voltage outlier cluster and a voltage outlier cluster from the plurality of battery pack voltage clusters in the at least one time interval; It is determined whether a battery pack voltage outlier exists in the target object according to the number of the suspected voltage outlier clusters and the number of the voltage outlier clusters.

2. The method according to claim 1, wherein The voltage outlier cluster is determined by: Obtaining a first voltage mean value of voltages included in the currently traversed suspected voltage outlier cluster, and a second voltage mean value of each of the other suspected voltage outlier clusters in the at least one time interval except the currently traversed suspected voltage outlier cluster; A voltage outlier cluster is determined based on the first voltage mean value and each of the second voltage mean values ​​until the traversal ends.

3. The method according to claim 2, wherein: The determining of a voltage outlier cluster based on the first voltage mean and each of the second voltage means until the traversal is completed includes: If the absolute value of the difference between each second voltage mean and the first voltage mean is greater than a first preset voltage threshold, the currently traversed suspected voltage outlier cluster is determined as a voltage outlier cluster until the traversal is completed.

4. The method according to claim 1, wherein The determining whether the target object has a battery pack voltage outlier according to the number of the suspected voltage outlier clusters and the number of the voltage outlier clusters includes: If the ratio of the number of the voltage outlier clusters to the number of the suspected voltage outlier clusters is greater than a first preset ratio threshold, or the difference between the number of the voltage outlier clusters and the number of other suspected voltage outlier clusters in the suspected voltage outlier clusters except the voltage outlier cluster is greater than a preset number threshold, it is determined that the target object has a battery pack voltage outlier.

5. The method according to claim 1, wherein The method further comprises: Acquire object data of the target object; the object data of the target object includes the voltage of each battery cell included in at least one battery pack of the target object within a historical time period; The object data of the target object is divided to obtain a data group of at least one time interval of the target object.

6. The method according to claim 5, wherein: The object data further includes: the state of charge of each battery cell included in at least one battery pack in the target object during the historical time period; The dividing the object data of the target object to obtain a data group of at least one time interval of the target object includes: obtaining the voltage of each battery cell included in the at least one battery pack at any time point from the object data; Obtaining a target voltage at any time point from at least one voltage at any time point; wherein the target voltage is higher than other voltages in the at least one voltage; Obtaining a target state of charge of the battery cell corresponding to the target voltage at any time point; determining target object data based on the target voltage and the target state of charge; The time-continuous target object data in the object data are determined as a data group of a time interval to obtain the data group of the at least one time interval.

7. The method according to claim 6, wherein: The determining target object data based on the target voltage and the target state of charge includes: If the target voltage is greater than a second preset voltage threshold, and the target state of charge is greater than a second preset ratio threshold, the object data at any time point in the object data is determined as target object data.

8. The method according to claim 5, wherein The object data further includes: the current of any battery cell included in at least one battery pack in the target object during the historical time period; Dividing the object data of the target object to obtain a data group of at least one time interval of the target object includes: obtaining, from the object data, the current of any battery cell at any time point, and the current of any battery cell at k adjacent time points at the time point; k is a positive integer; determining target object data based on the current at any one time point and the currents at the k adjacent time points; The time-continuous target object data in the object data are determined as a data group of a time interval to obtain the data group of the at least one time interval.

9. The method according to claim 8, wherein The determining target object data based on the current at any one time point and the currents at the k adjacent time points includes: If the current at any time point is less than a first preset current threshold, and the difference between the maximum current and the minimum current among the currents at the k adjacent time points and the current at any time point is less than a second preset current threshold, the object data at any time point in the object data is determined as the target object data.

10. The method according to claim 1, wherein The clustering of the voltage of the at least one battery pack in the any time interval based on a clustering algorithm to obtain a plurality of battery pack voltage clusters in the any time interval includes: Clustering the voltage of the at least one battery pack in the any time interval based on a clustering algorithm to obtain a plurality of candidate battery pack voltage clusters; If the number of the plurality of candidate battery pack voltage clusters is greater than a preset value, clustering the plurality of candidate battery pack voltage clusters based on the clustering algorithm to obtain a plurality of clustered candidate battery pack voltage clusters; If the number of the plurality of clustered candidate battery pack voltage clusters is greater than the preset value, the plurality of clustered candidate battery pack voltage clusters are used as a plurality of candidate battery pack voltage clusters, and the clustering algorithm based on the plurality of clustered candidate battery pack voltage clusters is triggered to execute. clustering the plurality of candidate battery pack voltage clusters to obtain a plurality of clustered candidate battery pack voltage clusters, until the number of the plurality of clustered candidate battery pack voltage clusters obtained is equal to the preset value; A plurality of clustered candidate battery pack voltage clusters, the number of which is equal to the preset value, is determined as the plurality of battery pack voltage clusters in the any one time interval.

11. A computer device, wherein: The computer device includes a memory, a communication interface, and a processor, wherein the memory, the communication interface, and the processor are interconnected; the memory stores a computer program, and the processor calls the computer program stored in the memory to implement the voltage detection method according to any one of claims 1 to 10.

12. A vehicle, wherein: The vehicle includes a vehicle body and a processor, and the processor is used to execute the voltage detection method according to any one of claims 1 to 10.

13. A computer-readable storage medium, wherein: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the voltage detection method according to any one of claims 1 to 10 is implemented.

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