Consistency determination method for battery and related products

Abstract

This application provides a method for determining battery consistency and related products. The method includes: determining the voltage difference corresponding to each frame of data, where the voltage difference is the difference between the highest and lowest cell voltages in each frame of data; determining a battery SOC range based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC values ​​in each frame of data, where the voltage difference corresponding to the battery SOC range is greater than a set threshold; and determining the difference between the upper limit and the lower limit of the battery SOC range as the battery SOC deviation, which is used to measure the battery's consistency. This application can reduce the computational load of calculating the SOC deviation.

Description

Technical Field

[0001] This application relates to the field of battery technology, specifically to a method for determining the consistency of batteries and related products. Background Technology

[0002] The rise and widespread adoption of electric vehicles have made lithium-ion battery packs a core component of vehicle power systems, and lithium iron phosphate (LFP) batteries have become the choice of many battery manufacturers due to their excellent safety performance. However, due to the inherent electrochemical properties of LFP batteries, their state of charge (SOC)-open circuit voltage (OCV) curve exhibits a plateau region. This makes it very difficult to accurately estimate the state of charge of individual cells, and this characteristic often leads to inconsistency issues. To more effectively manage and maintain battery systems, it is necessary to detect cell inconsistencies promptly.

[0003] Currently, the main method for detecting cell consistency issues is the problem caused by cell SOC deviation. This typically involves finding the voltage inflection point on the SOC-OCV curve and calculating the difference in state of charge (SOC) at each cell's inflection point to determine the battery's SOC deviation. However, current methods for calculating SOC deviation require calculating the SOC of each cell at its inflection point, resulting in a large computational load. Summary of the Invention

[0004] This application provides a method for determining battery consistency and related products, which can reduce the amount of calculation required to determine SOC deviation.

[0005] A first aspect of this application provides a method for determining the consistency of a battery, the battery comprising at least two cells, the method comprising:

[0006] Determine the voltage difference corresponding to each frame of data, wherein the voltage difference is the difference between the highest cell voltage and the lowest cell voltage in each frame of data;

[0007] Based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, a battery SOC interval is determined, wherein the voltage difference corresponding to the battery SOC interval is greater than a set threshold.

[0008] The difference between the upper limit and the lower limit of the battery's SOC range is defined as the SOC deviation of the battery, which is used to measure the consistency of the battery.

[0009] Optionally, each frame of data is any preprocessed frame of data from the battery within a set time period.

[0010] Optionally, the set time period includes at least one of a discharge period, an AC charging period, and a DC charging period.

[0011] Optionally, the preprocessing includes at least one of the following: sorting by time, removing null values, removing duplicate data, removing invalid values, removing outliers from sampling, and removing data that does not conform to the algorithm's operating conditions.

[0012] Optionally, after determining the voltage difference corresponding to each frame of data, the method further includes:

[0013] The voltage difference corresponding to each frame of data is filtered to obtain the processed voltage difference corresponding to each frame of data.

[0014] The step of determining a battery SOC range based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, wherein the voltage difference corresponding to the battery SOC range is greater than a set threshold, includes:

[0015] Based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, a battery SOC range is determined, wherein the processed voltage difference corresponding to the battery SOC range is greater than a set threshold.

[0016] Optionally, the step of filtering the voltage difference corresponding to each frame of data to obtain the processed voltage difference corresponding to each frame of data includes:

[0017] Determine the set of reliable voltage differences among the voltage differences corresponding to each frame of data within the specified time period;

[0018] Based on the set of reliable voltage differences, a polynomial fitting is performed to obtain the fitted voltage difference corresponding to each frame of data within the set time period.

[0019] The fitted voltage difference corresponding to each frame of data within the set time period is filtered to obtain the processed voltage difference corresponding to each frame of data.

[0020] Optionally, determining the set of reliable voltage differences among the voltage differences corresponding to each frame of data within the set time period includes:

[0021] Based on the correspondence between the voltage difference corresponding to each frame of data and the sampling time point corresponding to each frame of data, a first curve is obtained showing the change of the voltage difference corresponding to each frame of data with time within the set time period.

[0022] The first curve segment in the first curve with a voltage difference greater than a first threshold is determined, the lower envelope region in the first curve segment is determined, and the N smallest voltage differences in the lower envelope region are determined as the set of reliable voltage differences in the voltage differences corresponding to each frame of data within the set time period, where N is an integer greater than or equal to 2.

[0023] Optionally, determining the battery SOC range based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data includes:

[0024] Based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, a second curve is obtained showing the change of the processed voltage difference with the battery SOC value within the set time period.

[0025] Identify the second curve segment in the second curve where the processed voltage difference is greater than a set threshold, and determine the battery SOC range corresponding to the second curve segment.

[0026] Optionally, obtaining a second curve of the processed voltage difference versus battery SOC value within the set time period based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data includes:

[0027] Based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, the minimum of at least two processed voltage differences corresponding to the same battery SOC value is determined as the processed voltage difference corresponding to the same battery SOC value.

[0028] Based on the processed voltage difference corresponding to each different battery SOC value, a second curve is obtained showing the change of the processed voltage difference with the battery SOC value within the set time period.

[0029] Optionally, after obtaining the SOC deviation of the battery, the method further includes:

[0030] The SOC deviation of the battery is uploaded to the cloud server.

[0031] Optionally, the set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region, and the set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the second platform region, and the set threshold is less than the absolute value of the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region and the lower limit of the voltage fluctuation range of the second platform region, wherein the first platform region and the second platform region are two adjacent platform regions in the SOC-OCV curve of the battery.

[0032] Optionally, the SOC-OCV curve of the battery includes a small plateau region, a first large plateau region, and a second large plateau region. The SOC value of the first large plateau region is greater than the SOC value of the small plateau region and less than the SOC value of the second large plateau region. The first plateau region is one of the first large plateau region and the second large plateau region, and the second plateau region is the other of the first large plateau region and the second large plateau region.

[0033] A second aspect of this application provides a battery consistency determination apparatus, the battery comprising at least two cells, the apparatus comprising:

[0034] A determining unit is used to determine the voltage difference corresponding to each frame of data, wherein the voltage difference is the difference between the highest cell voltage and the lowest cell voltage in each frame of data;

[0035] The determining unit is further configured to determine a battery SOC range based on the voltage difference corresponding to each frame of data and the correspondence between the battery SOC in each frame of data, wherein the voltage difference corresponding to the battery SOC range is greater than a set threshold.

[0036] The determining unit is further configured to determine the difference between the upper limit of the battery SOC range and the lower limit of the battery SOC range as the SOC deviation of the battery, and the SOC deviation of the battery is used to measure the consistency of the battery.

[0037] A third aspect of this application provides a server, the server including a first communication module and a processing module, the first communication module being used to communicate with the power equipment where the battery is located to receive the data frame by frame, and the processing module being used to execute the step instructions as in the first aspect of this application.

[0038] Optionally, when the SOC deviation is greater than a preset warning threshold, the processing module is further configured to send a warning signal to the power equipment through the first communication module.

[0039] A fourth aspect of this application provides an electrical power device, the electrical power device including a battery and a second communication module, the second communication module being used to send each frame of data from the battery to a server, so that the server executes the step instructions as described in the first aspect of this application based on the each frame of data.

[0040] A fifth aspect of this application provides an electrical power device, the electrical power device including a battery and a processing component, the processing component being configured to execute step instructions as described in the first aspect of this application based on each frame of data from the battery.

[0041] Optionally, the power equipment includes a warning component, and the processing component is further configured to trigger the warning component to issue a warning message and / or send a warning prompt message to a third-party device when the SOC deviation is greater than a preset warning threshold.

[0042] A sixth aspect of this application provides an electronic device including a processor and a memory, the memory being used to store a computer program, the computer program including program instructions, and the processor being configured to invoke the program instructions to execute the step instructions as described in the first aspect of this application.

[0043] A seventh aspect of this application provides a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the first aspect of this application.

[0044] An eighth aspect of this application provides a computer program product, wherein the computer program product includes a computer program operable to cause a computer to perform some or all of the steps described in the first aspect of this application. The computer program product may be a software installation package.

[0045] A ninth aspect of this application provides a processor configured to invoke program instructions to execute the step instructions as described in the first aspect of this application. The processor may include any one of a chip, an integrated circuit, a microcontroller unit (MCU), or a computer terminal.

[0046] In this embodiment, the voltage difference corresponding to each frame of data is determined. The voltage difference is the difference between the highest and lowest cell voltages in each frame of data. Based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, a battery SOC range is determined. The voltage difference corresponding to the battery SOC range is greater than a set threshold. The difference between the upper limit and the lower limit of the battery SOC range is determined as the battery SOC deviation, which is used to measure the consistency of the battery. In this embodiment, the battery SOC range is determined based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. The difference between the upper limit and the lower limit of the battery SOC range is determined as the battery SOC deviation. In determining the battery SOC deviation, only the battery SOC value is used, without calculating the SOC value of each cell, which reduces the computational load for determining the SOC deviation and thus quickly determines the battery consistency. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the SOC-OCV curve of a lithium iron phosphate battery provided in an embodiment of this application;

[0049] Figure 2 This is a flowchart illustrating a battery consistency determination method provided in an embodiment of this application;

[0050] Figure 3 This is a schematic diagram illustrating the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, as provided in an embodiment of this application.

[0051] Figure 4 This is a flowchart illustrating another method for determining battery consistency provided in an embodiment of this application;

[0052] Figure 5 This is a schematic diagram of a first curve showing the change of voltage difference over time, provided in an embodiment of this application.

[0053] Figure 6 This is a schematic diagram of a second curve showing the change of voltage difference with battery SOC value, provided in an embodiment of this application;

[0054] Figure 7 This is a schematic flowchart illustrating a battery consistency determination method provided in an embodiment of this application.

[0055] Figure 8 A schematic diagram of a battery consistency determination device provided in an embodiment of this application;

[0056] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0057] Figure 10 This is a schematic diagram of the structure of a server provided in an embodiment of this application;

[0058] Figure 11 This is a schematic diagram of the structure of an electrical energy device provided in an embodiment of this application. Detailed Implementation

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0061] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0062] In electric vehicles, to accurately obtain the State of Charge (SOC) of a battery cell, the SOC-Open Circuit Voltage (OCV) curve is typically used. This involves sampling the open circuit voltage of the battery cell and then determining the SOC based on the OCV-SOC mapping relationship within the SOC-OCV curve. The SOC-OCV curve can also be simply referred to as the OCV curve.

[0063] Lithium iron phosphate (LiFePO4, LFP) batteries exhibit a plateau region in their State of Charge (SOC)-Oriented Volume (OCV) curve due to their inherent electrochemical properties. This makes it extremely difficult to accurately estimate the state of charge (SOC) of individual cells, frequently leading to inconsistency issues. To more effectively manage and maintain battery systems, timely detection of cell inconsistencies is crucial. Currently, the primary method for detecting cell inconsistencies is based on SOC deviation. This typically involves identifying the voltage inflection point on the SOC-OCV curve and calculating the difference in SOC deviation for each cell at that point. However, current methods for calculating SOC deviation require calculating the SOC of each cell at the inflection point, resulting in a computationally intensive process.

[0064] The SOC deviation calculation algorithm of this application embodiment determines the battery SOC range based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. The difference between the upper limit and the lower limit of the battery SOC range is the SOC deviation of the battery. Only the battery SOC value is needed, without calculating the SOC value of each cell, which can reduce the amount of calculation to determine the SOC deviation and thus quickly determine the consistency of the battery.

[0065] Please see Figure 1 , Figure 1 This is a schematic diagram of the SOC-OCV curve of a lithium iron phosphate battery provided in an embodiment of this application. Figure 1 As shown, the horizontal axis represents the State of Charge (SOC) value, and the vertical axis represents the Open Circuit Voltage (OCV) value. From... Figure 1 As can be seen, once the open-circuit voltage of the battery cell is obtained, the corresponding SOC value can be obtained from the SOC-OCV curve.

[0066] Depend on Figure 1 The SOC-OCV curve of lithium iron phosphate (LFP) batteries shows that the SOC-OCV curve is non-linear, exhibiting a small plateau region and two large plateau regions. If the cell in its highest state of charge (i.e., state of charge) and the cell in its lowest state of charge are simultaneously located within the same plateau region, the voltage difference obtained from the voltage of the cell in its highest and lowest states will be very small. However, as the electric device discharges or charges, the cells in their highest and lowest states will successively pass through two large plateau regions (e.g., ...). Figure 1 The inflection points of the large platform areas 1 and 2 shown (e.g.) Figure 1 In the inflection point 2), when calculating the change in SOC of the battery under the conditions of high-state cells at a high voltage platform and low-state cells at a low voltage platform, the consistency gap of the cells can be calculated. Figure 1 It contains two inflection points: inflection point 1 and inflection point 2. Inflection point 1 is the inflection point with a lower state of charge, and inflection point 2 is the inflection point with a higher state of charge.

[0067] The electric device can be a device powered by electricity. For example, the electric device can include any of the following: a vehicle, an aircraft, a ship, or an energy storage cabinet.

[0068] It should be noted that, Figure 1 This is just one possible example of a SOC-OCV curve. A SOC-OCV curve can also use OCV as the x-axis and SOC value as the y-axis.

[0069] Please see Figure 2 , Figure 2 This is a flowchart illustrating a battery consistency determination method provided in an embodiment of this application. Figure 2As shown, the method for determining the consistency of this battery includes the following steps.

[0070] 201. The electronic device determines the voltage difference corresponding to each frame of data, which is the difference between the highest cell voltage and the lowest cell voltage in each frame of data.

[0071] Electronic devices can be any device with computing and communication capabilities. For example, an electronic device can be a cloud server. An electronic device can be a cloud server used to calculate battery SOC deviation.

[0072] In this embodiment, the voltage difference is equal to the highest cell voltage minus the lowest cell voltage in each frame of data.

[0073] Each frame of data represents the state data of the battery sampled within each sampling period. The battery may include at least two cells, and the battery state data may include: the voltage of the at least two cells, the cell number of the at least two cells, the battery SOC, and other data. For example, if the sampling period is 30 seconds, each frame of data includes the voltage of at least two cells, the cell number of at least two cells, the battery SOC, and other data sampled within those 30 seconds. Frame data may exist in the form of data frames, or in any form capable of carrying battery state data, such as data sequences; this application embodiment does not impose any limitations.

[0074] Each frame of data can include the highest cell voltage, the lowest cell voltage, and the battery's state of charge (SOC). The battery can consist of at least two cells connected in series. The highest cell voltage in each frame is the voltage of the cell with the highest voltage sampled from all the cells in the battery during the sampling period of that frame (e.g., a sampling period of 30 seconds). The lowest cell voltage in each frame is the voltage of the cell with the lowest voltage sampled from all the cells in the battery during the sampling period of that frame.

[0075] For example, a battery may include 120 cells, and each frame of data may include the voltage of the cell with the highest voltage sampled among the 120 cells within the sampling period corresponding to that frame of data (highest cell voltage), the voltage of the cell with the lowest voltage sampled (lowest cell voltage), and the battery SOC.

[0076] It's important to note that battery SOC and cell SOC are different. Battery SOC refers to the overall SOC of the battery, while cell SOC refers to the SOC of the individual cell.

[0077] Each frame of data may also include the cell number of the cell with the highest voltage and the cell number of the cell with the lowest voltage among multiple cells.

[0078] Optionally, each frame of data is any preprocessed frame of data from the battery within a set time period.

[0079] In this embodiment of the application, each frame of data in step 201 is preprocessed frame data.

[0080] The electronic device can acquire all the raw frame data uploaded by the same vehicle during a set time period, process each raw frame data uploaded by the same vehicle during the set time period, and obtain each frame data in step 201.

[0081] For example, with a set time period of 72 hours, the same vehicle can periodically sample the raw state data of its battery according to a set sampling period, and report the raw state data of the battery to the electronic device in the form of raw frame data. The set sampling period can be preset and can be any value between 1 and 100 seconds. For example, it can be set to 30 seconds. Then, within the set time period of 72 hours, a total of 8640 (72*60*2) raw frame data reported by the same vehicle can be received. The raw state data of the battery may include: the raw voltage of at least two cells of the battery, the raw cell number of the at least two cells, the raw state of charge (SOC) of the battery, etc.

[0082] Optionally, the set time period includes at least one of a discharge period, an AC charging period, and a DC charging period.

[0083] Optionally, the set time period includes at least one of a discharge period and an AC charging period.

[0084] This application embodiment can calculate the battery's SOC deviation based on frame data reported by the battery during the discharge period, and can also calculate the battery's SOC deviation based on frame data reported by the battery during the AC charging phase. Furthermore, it can calculate the battery's SOC deviation based on frame data reported by the battery during both the discharge and AC charging phases. The battery consistency determination method of this application embodiment can be used under both discharge and AC charging conditions.

[0085] The embodiments of this application can be applied to predict inflection points and calculate SOC deviations during discharge or AC charging periods. Since each vehicle has a discharge period, ensuring a sufficient number of frame data points, the battery consistency determination method of this application embodiment can accurately calculate the SOC deviation for all vehicles.

[0086] The set time period can include data on the battery's SOC value within a set SOC range during both the discharge and AC charging periods. This set SOC value range can be preset. Figure 1The SOC value range can be set to 50%–90%. On one hand, within this SOC value range, data occurs frequently, providing sufficient data to calculate the SOC deviation, allowing the electronic device to quickly obtain the calculated SOC deviation. On the other hand, within this SOC value range, there is only one frequently occurring inflection point (e.g., ...). Figure 1 Inflection point 2 shown will not be affected by another inflection point (such as...) when calculating SOC deviation. Figure 1 The interference at inflection point 1 is shown, and compared to the shorter duration of the small plateau region near inflection point 1, the SOC value range is near inflection point 2. The duration of large plateau regions 1 and 2 is relatively longer, resulting in a larger amount of data within this SOC value range. Therefore, the data reliability is relatively higher, and the accuracy of the SOC deviation calculated based on the data within this SOC value range is relatively higher. This allows for a faster and more accurate calculation of the SOC deviation.

[0087] When a battery is charging, once the cell with the highest voltage is fully charged, all other cells will stop charging (including the cell with the lowest voltage). Therefore, the state of charge (SOC) of the cell with the lowest voltage at this point may be above 90%, but not 100%. Data above 90% is unreliable. There will be a significant voltage difference.

[0088] Furthermore, 50% to 90% is a very frequent data point. In actual charging and discharging conditions, this occurs... Figure 1 The probability of encountering inflection point 1 is lower than the probability of encountering inflection point 2, so we select a data segment that includes the high-probability inflection point 2.

[0089] Optionally, the preprocessing includes at least one of the following: sorting by time, removing null values, removing duplicate data, removing invalid values, removing outliers from sampling, and removing data that does not conform to the algorithm's operating conditions.

[0090] Sort by time: Each raw data frame uploaded by the same vehicle contains the sampling time point of that raw data frame. They can be sorted chronologically according to their sampling time points.

[0091] Remove null values: Some fields in the original data frame may be empty. For example, if the value of the field corresponding to the battery SOC is "None" or "empty", it means that the original data frame contains null values, and the original data frame containing null values ​​can be removed.

[0092] Remove duplicate data: If the same data appears twice or more in the original data frame, the duplicate data will be removed, and only one data will be kept.

[0093] Remove invalid values: Invalid values ​​are data that clearly contradicts the facts. For example, the highest cell voltage is 2.4V, and the lowest cell voltage is 3.2V. Invalid original data frames can be removed.

[0094] Remove outliers: Outliers are values ​​that are outside the range of the parameters. For example, if the SOC value ranges from 0 to 100%, and the SOC value in the reported raw data frame is -10, then it is an outlier and the raw data frame containing the outlier can be removed.

[0095] Remove data that does not conform to the algorithm's operating conditions: For example, if the consistency determination method for batteries in this application embodiment is not applicable during the DC charging period, the data during the DC charging period can be removed.

[0096] In this embodiment of the application, the original data frame can be preprocessed to obtain frame data.

[0097] 202. The electronic device determines the battery SOC range based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. The voltage difference corresponding to the battery SOC range is greater than a set threshold.

[0098] In this embodiment, each frame of data contains a battery SOC value, and each frame of data corresponds to a voltage difference. A correspondence between the voltage difference and the battery SOC value in each frame of data can be established. This correspondence can include a set of relational pairs, each pair containing a voltage difference and a corresponding battery SOC value. This set of relational pairs can be stored in the memory of an electronic device (e.g., non-volatile memory). A target set of relational pairs with voltage differences greater than a set threshold can be determined from this set of relational pairs, and the range of SOC values ​​in the target set of relational pairs is defined as the battery SOC range.

[0099] For example, given 10,000 frames of data within a set time period, a correspondence can be established between the voltage difference and the battery SOC value in each frame. For instance, within a battery SOC range of 50% to 90%, the voltage differences corresponding to different battery SOC values ​​can be obtained, and the SOC interval corresponding to voltage differences exceeding a set threshold can be determined.

[0100] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, as provided in an embodiment of this application. Figure 3As shown, the horizontal axis represents the battery's State of Charge (SOC) value, and the vertical axis represents the voltage difference. This allows us to determine the SOC range corresponding to voltage differences exceeding a set threshold. For example... Figure 3 As shown, the lower limit of the SOC interval is SOC1, and the upper limit of the SOC interval is SOC2.

[0101] 203. The difference between the upper limit and the lower limit of the battery SOC range determined by the electronic device is the battery SOC deviation, which is used to measure the battery's consistency.

[0102] In this embodiment of the application, the lower limit of the SOC range can be understood as the point at which the highest voltage cell in the battery reaches its inflection point (e.g., ...). Figure 1 The SOC value of the battery at the inflection point 2) between the two points (e.g., it can be denoted as SOC1). The upper limit of the SOC range can be understood as the value at which the lowest voltage cell in the battery passes through the inflection point (e.g., ...). Figure 1 The SOC value of the battery at the inflection point 2) between the two points (for example, it can be denoted as SOC2). Subtracting SOC1 from SOC2 gives the SOC deviation of the battery.

[0103] In this embodiment of the application, the absolute value of the upper limit of the battery SOC range and the lower limit of the battery SOC range can be used as the SOC deviation of the battery.

[0104] The State of Charge (SOC) deviation of a battery is used to measure its consistency, and it is an important standard for evaluating the consistency of a battery. Generally speaking, the smaller the SOC deviation, the better the consistency of the battery; the larger the SOC deviation, the worse the consistency of the battery.

[0105] In this embodiment, the battery SOC range is determined based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. The difference between the upper limit and the lower limit of the battery SOC range is the SOC deviation of the battery. In the process of determining the battery SOC deviation, only the battery SOC value is used, and there is no need to calculate the SOC value of each cell. This can reduce the amount of calculation required to determine the SOC deviation, thereby quickly determining the consistency of the battery.

[0106] Please see Figure 4 , Figure 4 This is a flowchart illustrating another method for determining battery consistency provided in an embodiment of this application. Figure 4 As shown, the method for determining the consistency of this battery includes the following steps.

[0107] 401. The electronic device determines the voltage difference corresponding to each frame of data, which is the difference between the highest cell voltage and the lowest cell voltage in each frame of data.

[0108] 402. The electronic device filters the voltage difference corresponding to each frame of data to obtain the processed voltage difference corresponding to each frame of data.

[0109] In this embodiment, since the highest and lowest cell voltages in each frame of data are sampled within the same sampling period, the sampling time of each cell voltage will vary within this sampling period (e.g., the sampling period can be set to 30 seconds). If the battery discharges rapidly (e.g., when an electric vehicle is climbing a hill) or charges rapidly (e.g., when an electric vehicle is braking suddenly) within this sampling period, and if the difference in the sampling time of the cell voltage is large (if the sampling period is 30 seconds, the largest difference is 30 seconds), then the voltage difference between the highest and lowest cell voltages in each frame of data will deviate from the actual voltage difference.

[0110] The embodiments of this application can obtain the processed voltage difference value corresponding to each frame of data by filtering the voltage difference value corresponding to the frame data, so that the processed voltage difference value corresponding to each frame of data can be closer to the real voltage difference value, thereby improving the calculation accuracy of SOC deviation.

[0111] Optionally, step 402 may specifically include the following steps:

[0112] (11) The electronic device determines the set of reliable voltage differences in the voltage differences corresponding to each frame of data within the set time period;

[0113] (12) The electronic device performs polynomial fitting based on the set of reliable voltage differences to obtain the fitted voltage difference corresponding to each frame of data within the set time period;

[0114] (13) The electronic device performs filtering processing on the fitted voltage difference corresponding to each frame of data within the set time period to obtain the processed voltage difference corresponding to each frame of data.

[0115] In this embodiment, the electronic device can determine a set of reliable voltage difference values ​​among the voltage difference values ​​corresponding to each frame of data within a set time period. Since the sampling time of each battery cell may differ, the voltage difference between the highest and lowest battery cell voltages in each frame of data will deviate from the true voltage difference. A set of reliable voltage difference values ​​can be found among the voltage difference values ​​corresponding to each frame of data within the set time period. Polynomial fitting can be performed based on the set of reliable voltage difference values ​​to obtain the fitted voltage difference value corresponding to each frame of data within the set time period. The fitted voltage difference value corresponding to each frame of data within the set time period is then filtered to obtain the processed voltage difference value corresponding to each frame of data.

[0116] For example, within a certain sampling period, cell 1 and cell 2 represent the cell with the highest voltage and the cell with the lowest voltage, respectively. The voltages of these two cells may not have been sampled at the same time. At the inflection point, there exists a minimum value theory: if the sampling times of the cell with the highest voltage and the cell with the lowest voltage are not the same, then the voltage difference calculated based on the voltages of the two cells will likely be larger than the actual voltage difference. Based on this minimum value theory, embodiments of this application can increase the reliability of the reliable voltage difference set by selecting the smaller voltage difference among the voltage differences in the inflection point region corresponding to each frame of data within a set time period.

[0117] The minimum value theory can be illustrated with an example. Please refer to Table 1, which is a table showing the actual voltage difference and the sampled calculated voltage difference for three battery cells provided in an embodiment of this application.

[0118] Table 1

[0119]

[0120] The voltage difference calculated by sampling is the difference between the voltage of the cell with the highest voltage and the voltage of the cell with the lowest voltage among the three cells. The first, second, and third sampling time points are three possible sampling time points within the sampling period, and these three sampling time points are not identical. As shown in Table 1, the probability of the difference being less than 2 is 7 / 27, which is relatively low, while the probability of the difference being greater than 2 is 11 / 27, which is relatively high. The probability that the voltage difference calculated by sampling is greater than the actual voltage difference is greater than the probability that the voltage difference calculated by sampling is less than the actual voltage difference. Table 1 is only an example. In actual battery products, the number of cells in a battery is much greater than 3, making the probability that the voltage difference calculated by sampling is greater than the actual voltage difference much greater than the probability that the voltage difference calculated by sampling is less than the actual voltage difference.

[0121] The electronic device can perform polynomial fitting based on the set of reliable voltage differences to obtain the fitted voltage difference corresponding to each frame of data within the set time period. In the set of reliable voltage differences, each reliable voltage difference corresponds to a frame of data, and each frame of data carries a sampling time point to indicate the sampling time of that frame of data. The sampling time of that frame of data can be a point in time within the sampling period of that frame of data. Each reliable voltage difference in the set of reliable voltage differences corresponds to a sampling time point, and each reliable voltage difference and its corresponding sampling time point can form a set of reliable data points.

[0122] This application embodiment can employ polynomial regression to perform polynomial fitting. For example, the polynomial can be set as F(t) = at. n +bt n-1 +…+C. Here, n is the number of terms in the polynomial, and a, b, and c are the parameters to be fitted. t represents time, which can be the sampling time point of each frame of data. F(t) is the fitted polynomial, representing the fitted voltage difference at different time points. F(t) can be a fitted curve with time on the horizontal axis and the fitted voltage difference on the vertical axis. The goal is to minimize the loss of F(t) by allowing this polynomial curve to pass through all the reliable data points in the reliable data point set. It should be noted that the number of reliable data points in the reliable data point set must be greater than n to obtain a fitted polynomial curve.

[0123] The electronic device can filter the fitted voltage difference corresponding to each frame of data within the set time period to obtain the processed voltage difference corresponding to each frame of data. After obtaining the fitted polynomial curve, the fitted voltage difference corresponding to each time point can be obtained according to the fitted polynomial curve, thereby obtaining the fitted voltage difference corresponding to each frame of data within the set time period.

[0124] Because of the minimum value theory at the inflection point, if the sampling times of the cell with the highest voltage and the cell with the lowest voltage are not the same, the voltage difference calculated based on the voltages of the cells with the highest and lowest voltages will likely be larger than the actual voltage difference. However, there is also a small probability that the voltage difference calculated based on the voltages of the cells with the highest and lowest voltages may be smaller than the actual voltage difference. This results in a small number of outliers in the set of reliable voltage differences. To avoid the influence of these outliers, the electronic device can filter the fitted voltage difference corresponding to each frame of data within the set time period to obtain the processed voltage difference corresponding to each frame of data, thereby making the processed voltage difference corresponding to each frame of data closer to the actual voltage difference. For example, a filtering algorithm can be used to filter the fitted voltage difference corresponding to each frame of data within the set time period to remove noise (i.e., remove outliers from the fitted voltage difference) to obtain the processed voltage difference corresponding to each frame of data. For example, this filtering algorithm can be the Butterworth low-pass filter algorithm. The filtering algorithm can use a finite impulse response (FIR) filter, a digital filter that involves convolution in the time domain, allowing for direct filtering in the time domain. The algorithm can also convert time-domain data to the frequency domain for low-pass filtering.

[0125] Optionally, step (11) may specifically include the following steps:

[0126] (111) The electronic device obtains a first curve of the voltage difference corresponding to each frame of data changing with time within the set time period based on the correspondence between the voltage difference corresponding to each frame of data and the sampling time point corresponding to each frame of data.

[0127] (112) The electronic device determines the first curve segment in the first curve whose voltage difference is greater than the first threshold, determines the lower envelope region in the first curve segment, and determines the N smallest voltage differences in the lower envelope region as the set of reliable voltage differences in the voltage differences corresponding to each frame of data within the set time period, where N is an integer greater than or equal to 2.

[0128] Steps (111) and (112) are methods for determining the set of reliable voltage differences.

[0129] Based on the aforementioned minimum value theory, at the inflection point, if the sampling times of the cell with the highest voltage and the cell with the lowest voltage are not the same, then the voltage difference calculated based on the voltages of the cells with the highest and lowest voltages will likely be larger than the actual voltage difference. Since the voltage difference at the inflection point is large, a first curve segment with a large voltage difference can be selected using a first threshold. The lower envelope region within this first curve segment can then be determined, and the N smallest voltage differences within this lower envelope region can be identified as the set of reliable voltage differences for each frame of data within a set time period.

[0130] Optionally, the first curve does not represent the actual curve, but rather the correspondence between the voltage difference of each frame of data within a set time period and the time point.

[0131] The lower envelope region in the first curve segment refers to the adjacent downward trend region and upward trend region within the first curve segment. The downward trend region is the area where the decline exceeds a second threshold, and the upward trend region is the area where the increase exceeds the second threshold. The second threshold can be preset. The lower envelope region includes adjacent downward trend regions and upward trend regions.

[0132] The first threshold can be preset. The first threshold is greater than the difference between the upper and lower limits of the voltage fluctuation range of the first plateau region, and also greater than the difference between the upper and lower limits of the voltage fluctuation range of the second plateau region, and less than the absolute value of the difference between the upper and lower limits of the voltage fluctuation range of the first and second plateau regions. The first and second plateau regions are two adjacent plateau regions in the SOC-OCV curve of the battery, and the upper limit of the voltage fluctuation range of the first plateau region is less than the lower limit of the voltage fluctuation range of the second plateau region. For example, the first plateau region could be... Figure 1 In the SOC-OCV curve, the large plateau region 1 and the second plateau region can be... Figure 1 The SOC-OCV curve shows a large plateau region 2. For example, in the first plateau region, if the cell voltage fluctuates between 3.295 and 3.305V, and in the second plateau region, if the cell voltage fluctuates between 3.345 and 3.355V, then the first threshold can be set to a value greater than 10mV and less than 40mV. For example, the first threshold can be set to 25mV.

[0133] Please see Figure 5 , Figure 5 This is a schematic diagram of a first curve showing the change of voltage difference over time, provided in an embodiment of this application. For example... Figure 5 The first curve shown represents the change in voltage difference over time for each frame of data within a set time period. The horizontal axis represents time, and the vertical axis represents voltage difference. This first curve shows the voltage difference varying within the range of 0–50 mV over time. It should be noted that this first curve is based on multiple frames of data and is composed of multiple discrete data points. The horizontal axis representing time is a discrete value, corresponding to the sampling time of each frame of data. The vertical axis representing voltage difference is also a discrete value. Figure 5 The bolded curve in the image represents the first curve segment where the voltage difference exceeds the first threshold. Figure 5 Taking 25mV as an example, the first threshold is used. From the first curve segment, it can be seen that there is a lower envelope region where the voltage difference is relatively small. The N smallest voltage differences among all discrete data points in the lower envelope region can be determined as the set of reliable voltage differences. Here, N can be greater than the number of terms in the polynomial fitting.

[0134] 403. The electronic device determines the battery SOC range based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. The processed voltage difference corresponding to the battery SOC range is greater than a set threshold.

[0135] In this embodiment of the application, each frame of data contains a battery SOC value, and each frame of data corresponds to a processed voltage difference. A correspondence between the processed voltage difference and the battery SOC value in each frame of data can be established. This correspondence can include a set of relation pairs, each pair containing a processed voltage difference and a corresponding battery SOC value. This set of relation pairs can be stored in the memory of the electronic device (e.g., non-volatile memory). A target set of relation pairs with processed voltage differences greater than a set threshold can be determined from this set of relation pairs, and the range of SOC values ​​in the target set of relation pairs is defined as the battery SOC range.

[0136] Optionally, step 403 may specifically include the following steps:

[0137] (21) The electronic device obtains a second curve of the change of the processed voltage difference with the battery SOC value within the set time period based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data.

[0138] (22) The electronic device determines the second curve segment in the second curve whose processed voltage difference is greater than a set threshold, and determines the battery SOC range corresponding to the second curve segment.

[0139] In this embodiment, there is a one-to-one correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. Based on this correspondence, a second curve can be obtained showing the change of the processed voltage difference with the battery SOC value within a set time period.

[0140] Optionally, the second curve is not limited to being represented in the form of a real curve; it can also be the correspondence or functional relationship between the processed voltage difference and the battery SOC value within a set time period.

[0141] Please see Figure 6 , Figure 6 This is a schematic diagram of a second curve showing the change of voltage difference with battery SOC value, provided in an embodiment of this application. Figure 6 The second curve shown represents the change in voltage difference as a function of the battery's State of Charge (SOC) over a set time period. The horizontal axis represents the battery's SOC, and the vertical axis represents the voltage difference. This second curve shows that the voltage difference varies within the range of 0–50 mV as the battery's SOC changes. It should be noted that this second curve is based on multi-frame data and consists of multiple discrete data points. The time value on the horizontal axis of the second curve is a discrete value, representing the SOC value of each frame. The voltage difference value on the vertical axis is also a discrete value. Figure 6 The bolded curve in the image represents the second curve segment where the voltage difference exceeds a set threshold. Figure 6 The set threshold is 25mV as an example. The second curve segment shows the SOC range corresponding to voltage differences exceeding the set threshold.

[0142] Optionally, step (21) may specifically include the following steps:

[0143] (211) The electronic device determines the minimum value among at least two processed voltage differences corresponding to the same battery SOC value as the processed voltage difference corresponding to the same battery SOC value based on the correspondence between the processed voltage difference value corresponding to each frame of data and the battery SOC value in each frame of data.

[0144] (212) The electronic device obtains a second curve of the change of the processed voltage difference with the battery SOC value within the set time period based on the processed voltage difference corresponding to each different battery SOC value C.

[0145] In this embodiment, since there are many frames of data within a set time period, there may be two or more frames with the same battery SOC value (for example, during discharge, when the vehicle is stopped at a traffic light, the battery SOC value hardly changes, and several consecutive frames may have the same battery SOC value). Therefore, in generating the second curve, only one voltage difference value needs to be taken for the same battery SOC value. In this embodiment, the minimum of at least two processed voltage differences corresponding to the same battery SOC value is determined as the processed voltage difference value corresponding to that same battery SOC value. Selecting the value with the smallest voltage difference, based on the aforementioned minimum value theory, allows the processed voltage difference value corresponding to the same battery SOC value to have a higher probability of approximating the true voltage difference value. This improves the accuracy of the second curve showing the change of voltage difference with the battery SOC value, and consequently improves the accuracy of the calculated battery SOC deviation.

[0146] Optionally, the set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region, and the set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the second platform region, and the set threshold is less than the absolute value of the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region and the second platform region. The first platform region and the second platform region are two adjacent platform regions in the SOC-OCV curve of the battery, and the upper limit of the voltage fluctuation range of the first platform region is less than the lower limit of the voltage fluctuation range of the second platform region. For example, the first platform region can be... Figure 1In the SOC-OCV curve, the large plateau region 1 and the second plateau region can be... Figure 1 The SOC-OCV curve shows a large plateau region 2. For example, in the first plateau region, if the cell voltage fluctuates between 3.295 and 3.305V, and in the second plateau region, if the cell voltage fluctuates between 3.345 and 3.355V, then the threshold value can be set to a value greater than 10mV and less than 40mV. For example, the threshold value can be set to 25mV.

[0147] The threshold value can be the same as the first threshold value, or it can be a different value.

[0148] Optionally, the SOC-OCV curve of the battery includes a small plateau region, a first large plateau region, and a second large plateau region. The SOC value of the first large plateau region is greater than the SOC value of the small plateau region and less than the SOC value of the second large plateau region. The first plateau region is one of the first large plateau region and the second large plateau region, and the second plateau region is the other of the first large plateau region and the second large plateau region. For example, the first large plateau region may be... Figure 1 In the SOC-OCV curve, the first large plateau region can be... Figure 1 The large plateau region 2 in the SOC-OCV curve.

[0149] 404. The difference between the upper limit and the lower limit of the battery SOC range determined by the electronic device is the battery SOC deviation, which is used to measure the battery's consistency.

[0150] The specific implementation of steps 401 and 404 can be found in steps 201 and 203 above, and will not be repeated here.

[0151] Optionally, after performing step 404, the following step (31) may also be performed.

[0152] (31) The electronic device uploads the SOC deviation of the battery to the cloud server.

[0153] In this embodiment, the SOC deviation calculated by the electronic device can be uploaded in real time to a cloud server for analyzing battery consistency, serving as a data foundation for subsequent development. This includes studying the trend of cell consistency changes and determining if there are other potential problems with the cells, such as excessively rapid changes in consistency. Other characteristics (such as the lowest and highest cell percentages during a given period) can also be uploaded simultaneously as criteria to increase the reliability of battery consistency.

[0154] Electronic devices can be cloud servers that calculate battery SOC deviation. These cloud servers can then upload the calculated SOC deviation to a cloud server that analyzes battery consistency. The cloud server for calculating battery SOC deviation and the cloud server for analyzing battery consistency can be different servers.

[0155] Please see Figure 7 , Figure 7 This is a schematic flowchart illustrating a battery consistency determination method provided in an embodiment of this application. Figure 7 As shown, the method for determining the consistency of this battery includes the following steps.

[0156] 701, the cloud server filters out the battery status sequence information of the target vehicle within the target time period.

[0157] There can be multiple battery state sequence information, which can correspond to the original data frames mentioned above.

[0158] Battery status sequence information can include: vehicle status data, maximum and minimum cell voltage, current, temperature, battery SOC value, maximum and minimum number of cells, etc. Vehicles can upload this data, tagged with the sampling time, to a cloud server for subsequent processing.

[0159] 702. The cloud server preprocesses the battery status sequence information by sorting it by time, removing null values, duplicate data, invalid values, outliers, and high current conditions.

[0160] This includes preprocessing the data uploaded by vehicles every 24 hours, such as sorting by time, removing null values, removing duplicate data, removing invalid values, removing outliers, and deleting data that is not applicable to the algorithm.

[0161] The preprocessed data is then input into the algorithm. The algorithm primarily processes the battery's SOC value and the highest cell voltage (V). max Minimum cell voltage V min The values ​​of the highest cell number Nmax and the lowest cell number Nmin are filtered and analyzed.

[0162] 703. The cloud server obtains the voltage difference based on the difference between the highest and lowest cell voltages. It then segments the data according to the operating conditions to obtain different charging and discharging data. The lower envelope of the voltage difference is calculated for the discharging data, and polynomial regression and Butterworth filtering are performed on the discharging data.

[0163] Among them, the highest cell voltage V can be max Minimum cell voltage V min Take the difference, V diff =V max -V minThe V obtained here diff This represents the voltage difference between the cell with the highest electrical state and the cell with the lowest electrical state.

[0164] Because the discharge section voltage is unstable, the sampled cell voltage will fluctuate, requiring the cell voltage difference V to be measured. diff Filtering is performed to remove small sampling errors and different voltage transient responses caused by large currents. First, the lower envelope of the voltage difference is obtained. Then, polynomial regression is performed on the lower envelope value and interpolation is used to obtain V. env (i.e., the fitted voltage difference mentioned above), and then use a Butterworth low-pass filter to apply V env Filtering out noise yields a smooth pressure difference value V. env At this point, the voltage difference between 50% and 90% of the battery's SOC value can be used to judge consistency (above 90% SOC there is a very high voltage difference, below 50% SOC there will be the influence of a low inflection point, so data in the 50% to 90% SOC range is selected).

[0165] 704. The cloud server groups the charging and discharging data according to the SOC and calculates the minimum value of the voltage difference. It then calculates the SOC interval where the continuous voltage difference is greater than a set threshold, obtains the SOC deviation of the battery, and statistically analyzes the highest and lowest cell numbers in the data corresponding to the SOC interval.

[0166] In this embodiment of the application, the data of the entire battery pack with a SOC of 50% to 90% are grouped with an integer SOC (for example, the SOC can be divided into 41 groups: 50%, 51%, 52%, ..., 90%) as the exponent. The grouping function is to find the minimum value, and the original variable of time (number of data frames) is changed to SOC as the variable, so as to obtain the minimum pressure difference corresponding to each integer SOC value.

[0167] Among them, setting the threshold can be done through Figure 1 Determined, by Figure 1 It is evident that when lithium iron phosphate batteries are at two different large plateaus, the voltage difference exceeds 25mV; therefore, the voltage difference threshold is designed to be 25mV. If the cell at its highest electrical state and the cell at its lowest electrical state are simultaneously on the same plateau, the voltage difference will be determined by V... max -V min The obtained V diff It will be very small. As the vehicle charges and discharges or charges, the cells with the highest voltage state and the cells with the lowest voltage state will pass through the inflection point 2 between the large platform 1 and the large platform 2 in sequence. Record the SOC1 of the cell with the highest voltage passing through the inflection point and the SOC2 of the cell with the lowest voltage passing through the inflection point. |SOC2-SOC1| is the consistency deviation of the cells.

[0168] 705. The cloud server uploads the battery's SOC deviation, the minimum cell percentage, and the maximum cell percentage to the cloud.

[0169] The calculated SOC deviation of the battery can be uploaded to the cloud server in real time, serving as the data foundation for subsequent development. This includes studying the trend of changes in cell consistency to determine if there are other potential problems with the cells, such as excessively rapid changes in consistency. Simultaneously, other characteristics (such as the lowest and highest cell percentages during a given period) are also uploaded as criteria to increase the reliability of consistency.

[0170] The lowest cell percentage refers to the proportion of each cell in the data corresponding to that SOC range that has the lowest voltage. The highest cell percentage refers to the proportion of each cell in the data corresponding to that SOC range that has the highest voltage.

[0171] The technical problem that this application's embodiments can solve is that the method for calculating the state of charge (SOC) deviation of a battery cell relies too heavily on data from specific charging stages. When specific data is missing, or when specific data is only recently available, traditional algorithms may fail or fail to obtain real-time SOC deviation of the battery cell. When data quality is poor, such as insufficient synchronization rate, traditional solutions use data from the AC charging stage and cannot use data from the discharging stage.

[0172] The algorithm in this application embodiment is applicable to different vehicle operating conditions. The algorithm not only uses data including AC charging segment to calculate the battery's state of charge deviation, but also uses data including discharging segment to calculate the battery's state of charge deviation, thus calculating the battery's state of charge deviation more timely.

[0173] This application embodiment can determine the state of charge (SOC) deviation of a battery and, based on the SOC deviation, determine whether there are other consistency issues (such as abnormal internal resistance and leakage). This application embodiment can calculate the SOC deviation of a vehicle's battery on a cloud server, continuously track the battery consistency status, and provide a foundation for trend algorithms.

[0174] The above describes the solutions of the embodiments of this application from the perspective of the method execution process. It is understood that, in order to achieve the above functions, the electronic device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments provided herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0175] This application embodiment can divide the electronic device into functional units according to the above method example. For example, each function can be divided into a separate functional unit, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0176] Please see Figure 8 , Figure 8 This is a schematic diagram of a battery consistency determination device provided in an embodiment of this application. The battery includes at least two cells, and the battery consistency determination device 800 may include a determination unit 801, wherein:

[0177] The determining unit 801 is used to determine the voltage difference value corresponding to each frame of data, wherein the voltage difference value is the difference between the highest cell voltage and the lowest cell voltage in each frame of data;

[0178] The determining unit 801 is further configured to determine a battery SOC range based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, wherein the voltage difference corresponding to the battery SOC range is greater than a set threshold.

[0179] The determining unit 801 is further configured to determine the difference between the upper limit of the battery SOC range and the lower limit of the battery SOC range, thereby obtaining the SOC deviation of the battery. The SOC deviation of the battery is used to measure the consistency of the battery.

[0180] Optionally, each frame of data is any preprocessed frame of data from the battery within a set time period.

[0181] Optionally, the set time period includes at least one of a discharge period, an AC charging period, and a DC charging period.

[0182] Optionally, the preprocessing includes at least one of the following: sorting by time, removing null values, removing duplicate data, removing invalid values, removing outliers from sampling, and removing data that does not conform to the algorithm's operating conditions.

[0183] Optionally, the battery consistency determination device 800 may further include a filtering unit 802;

[0184] The filtering unit 802 is used to filter the voltage difference corresponding to each frame of data to obtain the processed voltage difference corresponding to each frame of data.

[0185] The determining unit 801 determines the battery SOC interval based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, wherein the voltage difference corresponding to the battery SOC interval is greater than a set threshold. This includes: determining the battery SOC interval based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, wherein the processed voltage difference corresponding to the battery SOC interval is greater than a set threshold.

[0186] Optionally, the filtering unit 802 performs filtering processing on the voltage difference corresponding to each frame of data to obtain the processed voltage difference corresponding to each frame of data, including: determining a set of reliable voltage difference values ​​among the voltage difference values ​​corresponding to each frame of data within the set time period; performing polynomial fitting based on the set of reliable voltage difference values ​​to obtain the fitted voltage difference value corresponding to each frame of data within the set time period; and performing filtering processing on the fitted voltage difference value corresponding to each frame of data within the set time period to obtain the processed voltage difference value corresponding to each frame of data.

[0187] Optionally, the filtering unit 802 determines a set of reliable voltage differences among the voltage differences corresponding to each frame of data within the set time period, including: obtaining a first curve of the voltage difference changing with time for each frame of data within the set time period based on the correspondence between the voltage difference corresponding to each frame of data and the sampling time point corresponding to each frame of data; determining a first curve segment in the first curve where the voltage difference is greater than a first threshold; determining a lower envelope region in the first curve segment; and determining the N smallest voltage differences in the lower envelope region as a set of reliable voltage differences among the voltage differences corresponding to each frame of data within the set time period, where N is an integer greater than or equal to 2.

[0188] Optionally, the determining unit 801 determines the battery SOC range based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, including: obtaining a second curve of the processed voltage difference changing with the battery SOC value within the set time period based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data; determining a second curve segment in the second curve where the processed voltage difference is greater than a set threshold, and determining the battery SOC range corresponding to the second curve segment.

[0189] Optionally, the determining unit 801 obtains a second curve of the processed voltage difference changing with the battery SOC value within the set time period based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. This includes: determining the minimum of at least two processed voltage differences corresponding to the same battery SOC value as the processed voltage difference corresponding to the same battery SOC value based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data; and obtaining a second curve of the processed voltage difference changing with the battery SOC value within the set time period based on the processed voltage difference corresponding to each different battery SOC value.

[0190] Optionally, the battery consistency determination device 800 may further include a upload unit 803;

[0191] The uploading unit 803 is used to upload the SOC deviation of the battery to the cloud server.

[0192] Optionally, the set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region, and the set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the second platform region, and the set threshold is less than the absolute value of the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region and the lower limit of the voltage fluctuation range of the second platform region, wherein the first platform region and the second platform region are two adjacent platform regions in the SOC-OCV curve of the battery.

[0193] Optionally, the SOC-OCV curve of the battery includes a small plateau region, a first large plateau region, and a second large plateau region. The SOC value of the first large plateau region is greater than the SOC value of the small plateau region and less than the SOC value of the second large plateau region. The first plateau region is one of the first large plateau region and the second large plateau region, and the second plateau region is the other of the first large plateau region and the second large plateau region.

[0194] In this embodiment, the determining unit 801 and the filtering unit 802 can be processors in an electronic device. The uploading unit 803 can be a communication module in an electronic device.

[0195] In this embodiment, the battery SOC range is determined based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. The difference between the upper limit and the lower limit of the battery SOC range is the battery SOC deviation. In the process of determining the battery SOC deviation, only the battery SOC value is used, and there is no need to calculate the SOC value of each cell. This can reduce the amount of calculation required to determine the SOC deviation, thereby quickly determining the consistency of the battery.

[0196] Please see Figure 9 , Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 9 As shown, the electronic device 900 includes a processor 901 and a memory 902, which are interconnected via a communication bus 903. The communication bus 903 can be a peripheral component interconnect (PCI) bus, an extended industry standard architecture (EISA) bus, or a controller area network (CAN) bus, etc. The communication bus 903 can be divided into an address bus, a data bus, and a control bus, etc. For ease of illustration, Figure 9 The code uses only a single thick line to represent a bus, but this does not indicate that there is only one bus or one type of bus. Memory 902 stores computer programs, which include program instructions. Processor 901 is configured to call these program instructions, which include instructions for execution. Figures 2-7 It includes some or all of the steps in the methods.

[0197] The processor 901 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of programs in the above scheme.

[0198] The memory 902 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory may exist independently and be connected to the processor via a bus. The memory may also be integrated with the processor.

[0199] The electronic device 900 may also include a communication module 904, which can upload the battery's SOC deviation to a cloud server. The communication module 904 can also receive raw data frames uploaded by the vehicle.

[0200] In this embodiment, the battery SOC range is determined based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data. The difference between the upper limit and the lower limit of the battery SOC range is the SOC deviation of the battery. In the process of determining the battery SOC deviation, only the battery SOC value is used, and there is no need to calculate the SOC value of each cell. This can reduce the amount of calculation required to determine the SOC deviation, thereby quickly determining the consistency of the battery.

[0201] Please see Figure 10 , Figure 10 This is a schematic diagram of the structure of a server provided in an embodiment of this application, such as... Figure 10 As shown, the server 1000 includes a first communication module 1001 and a processing module 1002. The first communication module 1001 is used to communicate with the power equipment where the battery is located to receive each frame of data. The processing module 1002 is used to execute some or all of the steps of any of the battery consistency determination methods described in the above method embodiments.

[0202] The processing module 1002 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the above battery consistency determination method.

[0203] Optionally, when the SOC deviation is greater than a preset warning threshold, the processing module 1002 is further configured to send a warning signal to the power equipment through the first communication module 1001.

[0204] Please see Figure 11 , Figure 11 This is a schematic diagram of the structure of an electrical energy device provided in an embodiment of this application, such as... Figure 11 As shown, the power device 1100 includes a battery 1101 and a processing component 1102. The processing component 1102 is used to perform some or all of the steps of any of the battery consistency determination methods described in the above method embodiments based on each frame of data from the battery 1101.

[0205] The processing component 1102 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the consistency determination method of the above batteries.

[0206] Optionally, the power equipment includes a warning component 1103, and the processing component 1102 is further configured to trigger the warning component 1103 to issue a warning message and / or send a warning prompt message to a third-party device when the SOC deviation is greater than a preset warning threshold.

[0207] This application also provides a computer-readable storage medium storing a computer program for electronic data interchange that causes a computer to perform some or all of the steps of any of the battery consistency determination methods described in the above method embodiments.

[0208] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0209] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0210] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0211] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0212] Furthermore, the functional units in the various embodiments of the application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0213] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0214] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: a flash drive, a read-only memory, a random access memory, a magnetic disk, or an optical disk, etc.

[0215] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for determining the consistency of a battery, the battery comprising at least two cells, characterized in that, The method is used in discharge conditions and / or AC charging conditions, and the method includes: Determine the voltage difference corresponding to each frame of data, wherein the voltage difference is the difference between the highest cell voltage and the lowest cell voltage in each frame of data; Based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, a battery SOC interval is determined, wherein the voltage difference corresponding to the battery SOC interval is greater than a set threshold. The difference between the upper limit and the lower limit of the battery's SOC range is defined as the SOC deviation of the battery, which is used to measure the consistency of the battery.

2. The method according to claim 1, characterized in that, Each frame of data is any preprocessed frame of data from the battery within a set time period.

3. The method according to claim 2, characterized in that, The set time period includes at least one of a discharge time period, an AC charging time period, and a DC charging time period.

4. The method according to claim 2, characterized in that, The preprocessing includes at least one of the following: sorting by time, removing null values, removing duplicate data, removing invalid values, removing outliers from sampling, and removing data that does not conform to the algorithm's operating conditions.

5. The method according to any one of claims 2 to 4, characterized in that, After determining the voltage difference corresponding to each frame of data, the method further includes: The voltage difference corresponding to each frame of data is filtered to obtain the processed voltage difference corresponding to each frame of data. The step of determining a battery SOC range based on the correspondence between the voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, wherein the voltage difference corresponding to the battery SOC range is greater than a set threshold, includes: Based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, a battery SOC range is determined, wherein the processed voltage difference corresponding to the battery SOC range is greater than a set threshold.

6. The method according to claim 5, characterized in that, The step of filtering the voltage difference corresponding to each frame of data to obtain the processed voltage difference corresponding to each frame of data includes: Determine the set of reliable voltage differences among the voltage differences corresponding to each frame of data within the specified time period; Based on the set of reliable voltage differences, a polynomial fitting is performed to obtain the fitted voltage difference corresponding to each frame of data within the set time period. The fitted voltage difference corresponding to each frame of data within the set time period is filtered to obtain the processed voltage difference corresponding to each frame of data.

7. The method according to claim 6, characterized in that, The step of determining the set of reliable voltage difference values ​​among the voltage difference values ​​corresponding to each frame of data within the set time period includes: Based on the correspondence between the voltage difference corresponding to each frame of data and the sampling time point corresponding to each frame of data, a first curve is obtained showing the change of the voltage difference corresponding to each frame of data with time within the set time period. The first curve segment in the first curve with a voltage difference greater than a first threshold is determined, the lower envelope region in the first curve segment is determined, and the N smallest voltage differences in the lower envelope region are determined as the set of reliable voltage differences in the voltage differences corresponding to each frame of data within the set time period, where N is an integer greater than or equal to 2.

8. The method according to claim 5, characterized in that, The determination of the battery SOC range based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data includes: Based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, a second curve is obtained showing the change of the processed voltage difference with the battery SOC value within the set time period. Identify the second curve segment in the second curve where the processed voltage difference is greater than a set threshold, and determine the battery SOC range corresponding to the second curve segment.

9. The method according to claim 8, characterized in that, The process of obtaining a second curve of the processed voltage difference versus the battery SOC value within a set time period based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data includes: Based on the correspondence between the processed voltage difference corresponding to each frame of data and the battery SOC value in each frame of data, the minimum of at least two processed voltage differences corresponding to the same battery SOC value is determined as the processed voltage difference corresponding to the same battery SOC value. Based on the processed voltage difference corresponding to each different battery SOC value, a second curve is obtained showing the change of the processed voltage difference with the battery SOC value within the set time period.

10. The method according to any one of claims 1-4 and 6-9, characterized in that, The method further includes: The SOC deviation of the battery is uploaded to the cloud server.

11. The method according to any one of claims 1-4 and 6-9, characterized in that, The set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region, and the set threshold is greater than the difference between the upper limit and the lower limit of the voltage fluctuation range of the second platform region, and the set threshold is less than the absolute value of the difference between the upper limit and the lower limit of the voltage fluctuation range of the first platform region and the lower limit of the voltage fluctuation range of the second platform region, wherein the first platform region and the second platform region are two adjacent platform regions in the SOC-OCV curve of the battery.

12. The method according to claim 11, characterized in that, The SOC-OCV curve of the battery includes a small plateau region, a first large plateau region, and a second large plateau region. The SOC value of the first large plateau region is greater than the SOC value of the small plateau region and less than the SOC value of the second large plateau region. The first plateau region is one of the first large plateau region and the second large plateau region, and the second plateau region is the other of the first large plateau region and the second large plateau region.

13. A server, characterized in that, The server includes a first communication module and a processing module. The first communication module is used to communicate with the power equipment where the battery is located to receive the data frame. The processing module is used to execute the method according to any one of claims 1 to 12.

14. The server according to claim 13, characterized in that, When the SOC deviation exceeds a preset warning threshold, the processing module is also used to send a warning signal to the power equipment through the first communication module.

15. An electrical energy device, characterized in that, The power device includes a battery and a second communication module, the second communication module being used to send each frame of data from the battery to a server, so that the server executes the method according to any one of claims 1 to 12 based on the each frame of data.

16. An electrical energy device, characterized in that, The power device includes a battery and a processing component, the processing component being configured to execute the method according to any one of claims 1 to 12 based on each frame of data from the battery.

17. The device according to claim 16, characterized in that, The electrical equipment includes a warning component, and the processing component is further configured to trigger the warning component to issue a warning message and / or send a warning prompt message to a third-party device when the SOC deviation is greater than a preset warning threshold.

18. An electronic device, characterized in that, The device includes a processor and a memory, the memory being used to store a computer program, the computer program including program instructions, and the processor being configured to invoke the program instructions to perform the method as described in any one of claims 1 to 12.

19. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1 to 12.

20. A computer program product, characterized in that, The computer program product includes a computer program operable to cause a computer to perform the method as described in any one of claims 1 to 12.

21. A processor, characterized in that, The processor is configured to invoke program instructions to perform the method as described in any one of claims 1 to 12.

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