Battery data processing method, device, equipment, storage medium and program product

Abstract

The present application relates to a battery data processing method, apparatus, device, storage medium, and program product. The method comprises: detecting battery data during a battery charging and discharging process to obtain a detection result of the battery data; if the detection result indicates that the battery data includes a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, or at least one of an abnormal data segment, processing the battery data based on the abnormal data to obtain target battery data. Because the abnormal data in the battery data can be detected and processed based on the abnormal data to obtain the target battery data, the quality of the obtained target battery data is improved.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a battery data processing method, apparatus, device, storage medium, and program product. Background Art

[0002] With the widespread use of batteries, users have higher requirements for battery performance, for example, batteries with larger capacity in a smaller size and weight, and longer service life.

[0003] Currently, the initial model is trained using raw battery data, such as the voltage and capacity of a test battery during the charge and discharge phases, to generate a predictive model. Based on the predictive model and design parameters such as the battery's length, width, and anode material, predicted battery data is generated. This predicted battery data can be used to optimize the battery's design parameters, thereby improving battery performance. Therefore, the quality of the battery data required for model training is crucial and impacts the accuracy of the predictive model, and thus battery performance. Therefore, improving the quality of battery data has become a pressing technical issue in this field. Summary of the Invention

[0004] Based on this, it is necessary to provide a battery data processing method, device, equipment, storage medium and program product that can improve the quality of battery data in response to the above technical problems.

[0005] In a first aspect, the present application provides a battery data processing method. The method comprises:

[0006] Detecting battery data during the battery charging and discharging process to obtain a detection result of the battery data;

[0007] When the detection result shows that the battery data includes abnormal data, the battery data is processed according to the abnormal data to obtain target battery data; the abnormal data includes at least one of a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment.

[0008] In this embodiment, battery data during the battery charging and discharging process is detected to obtain a detection result of the battery data. If the detection result shows that the battery data includes at least one of abnormal data selected from a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment, the battery data is processed based on the abnormal data to obtain target battery data. Because the abnormal data in the battery data can be detected and processed based on the abnormal data to obtain the target battery data, the quality of the obtained target battery data is improved.

[0009] In one embodiment, detecting battery data during the battery charging and discharging process to obtain a detection result of the battery data includes:

[0010] The battery data is detected according to the current data corresponding to the battery data during the battery charging and discharging process to obtain a detection result of the battery data.

[0011] In this embodiment, the battery data is detected based on the current data corresponding to the battery data during the battery charging and discharging process to obtain the detection results in the battery data. When the detection result is that the abnormal data in the battery data includes a battery data segment corresponding to the non-constant current data, there is no need to detect the battery data segment corresponding to the constant voltage data, the outlier data points and the outlier data segments, thereby reducing the time cost required for detection.

[0012] In one embodiment, the battery data is detected based on the current data corresponding to the battery data during the battery charging and discharging process to obtain the detection result of the battery data, including:

[0013] Sort the current data according to the magnitude of the current data to obtain target current data;

[0014] Determine the current window according to the length of the target current data and a preset length ratio;

[0015] intercepting target current data based on the current window to obtain a current data segment;

[0016] The battery data is detected according to the current data segment to obtain a detection result of the battery data; the detection result includes whether the battery data includes a battery data segment corresponding to the non-constant current data.

[0017] In this embodiment, the current data is sorted by magnitude to obtain target current data, a current window is determined based on the length of the target current data and a preset length ratio, the target current data is intercepted based on the current window to obtain current data segments, and the battery data is tested based on the current data segments to obtain battery data test results; the test results include whether the battery data includes battery data segments corresponding to non-constant current data. Since the target current data is the data obtained by sorting the current data by magnitude, the two current data located at the two ends of the current data segment are the maximum current data and the minimum current data in the current data segment, which saves the time required to determine the maximum current data and the minimum current data from the current data segment, thereby improving the efficiency of determining the maximum current data and the minimum current data, and thus improving the efficiency of obtaining the test results.

[0018] In one embodiment, the battery data is detected based on the current data segment to obtain a detection result of the battery data; the detection result includes whether the battery data includes a battery data segment corresponding to non-constant current data, including:

[0019] determining a current difference between maximum current data and minimum current data in the current data segment;

[0020] When the current difference is greater than or equal to a preset current difference, performing an iterative operation; the iterative operation includes moving the current window according to a preset moving step size, and intercepting the target current data based on the moved current window to obtain a new current data segment;

[0021] When the current difference corresponding to the new current data segment is greater than or equal to the preset current difference, returning to perform the iterative operation;

[0022] When the current difference corresponding to the new current data segment intercepted last time is greater than or equal to the preset current difference, it is determined that the detection result includes the battery data segment corresponding to the non-constant current data.

[0023] In this embodiment, when the current difference corresponding to the new current data segment is greater than or equal to the preset current difference, the iterative operation is returned to be performed. When the current difference corresponding to the new current data segment obtained in the last interception is greater than or equal to the preset current difference, it is determined that the detection result includes the battery data segment corresponding to the non-constant current data, thereby realizing the determination of the battery data segment corresponding to the non-constant current data.

[0024] In one embodiment, the battery data includes a voltage-to-electricity curve for representing a corresponding relationship between voltage data and electric quantity data, and the method further includes:

[0025] When the abnormal data does not include a battery data segment corresponding to the non-constant current data, obtaining a voltage change trend between a current position point and a position point next to the current position point on the voltage and power curve;

[0026] When the voltage variation trend does not satisfy the monotonicity corresponding to the battery data, obtaining the voltage variation trend of a first preset number of locations after the next location point;

[0027] When the voltage variation trends of the first preset number of positions do not satisfy monotonicity, the battery data segment corresponding to the constant voltage data in the battery data is determined according to the current position and the voltage and power curve segments after the current position.

[0028] In this embodiment, the battery data segment corresponding to the constant voltage data in the battery data is determined based on the voltage change trend of the current position point and the first preset number of position points after the next position point. That is, the battery data segment corresponding to the constant voltage data in the battery data is determined based on the voltage change trend of a sufficient number of position points, thereby improving the accuracy of the determined battery data segment corresponding to the constant voltage data.

[0029] In one embodiment, determining the battery data segment corresponding to the constant voltage data in the battery data based on the current position point and the voltage and power curve segment after the current position point includes:

[0030] The voltage and electricity curve segment at the current position point and after the current position point is used as the first initial data segment corresponding to the constant voltage data;

[0031] A battery data segment corresponding to the constant voltage data in the battery data is determined according to the first initial data segment.

[0032] In this embodiment, by taking the current position point and the voltage and charge curve segment after the current position point as the first initial data segment corresponding to the constant voltage data, the battery data segment corresponding to the constant voltage data in the battery data is determined based on the first initial data segment, thereby realizing the determination of the battery data segment corresponding to the constant voltage data in the battery data.

[0033] In one embodiment, determining the battery data segment corresponding to the constant voltage data in the battery data according to the first initial data segment includes:

[0034] Determine the constant current data segment on the current-time curve; the current-time curve is used to characterize the corresponding relationship between current data and time during the battery charging and discharging process;

[0035] Determining a target position point on the voltage and electricity curve corresponding to the end position point of the constant current data segment;

[0036] The target position point and the voltage and electricity curve segment after the target position point are used as the second initial data segment;

[0037] The union of the first initial data segment and the second initial data segment is used as the battery data segment corresponding to the constant voltage data.

[0038] In this embodiment, by determining the constant current data segment on the current-time curve, determining the target position point corresponding to the end position point of the constant current data segment on the voltage-to-energy curve, using the target position point and the voltage-to-energy curve segment after the target position point as the second initial data segment, and using the union of the first initial data segment and the second initial data segment as the battery data segment corresponding to the constant voltage data. This allows the second initial data segment corresponding to the non-constant current to be determined based on the current-time curve, and then using the union of the second initial data segment and the first initial data segment as the battery data segment corresponding to the constant voltage data. This allows the second initial data segment corresponding to the non-constant current to also be used as the battery data segment corresponding to the constant voltage data, allowing for a more comprehensive and accurate determination of the battery data segment corresponding to the constant voltage data.

[0039] In one embodiment, the battery data includes a voltage-to-electricity curve for representing a corresponding relationship between voltage data and electric quantity data, and the method further includes:

[0040] When the abnormal data does not include a battery data segment corresponding to the non-constant current data, obtaining association information between a current position point and a next position point on the voltage and power curve;

[0041] Identify outlier data points in battery data based on correlation information.

[0042] In this embodiment, by obtaining the correlation information between the current position point and the next position point on the voltage and power curve when the abnormal data does not include the battery data segment corresponding to the non-constant current data, the outlier data points in the battery data are determined based on the correlation information, thereby realizing the detection of the outlier data points in the battery data.

[0043] In one embodiment, the correlation information includes a distance and / or a sampling time interval, and determining an outlier data point in the battery data based on the correlation information includes:

[0044] When the distance is greater than or equal to the preset distance, and / or the sampling time interval is greater than the preset sampling time interval, the next position point is taken as an outlier data point in the battery data.

[0045] In this embodiment, if the distance is greater than or equal to a preset distance and / or the sampling interval is greater than a preset sampling interval, the next location point is identified as an outlier data point in the battery data. Because the distance and / or sampling interval between the current location point and the next location point are directly determined, this method is relatively simple and quick, thereby improving the efficiency of identifying outlier data points.

[0046] In one embodiment, the battery data includes a voltage-to-electricity curve for representing a corresponding relationship between voltage data and electric quantity data, and the method further includes:

[0047] When the abnormal data does not include a battery data segment corresponding to the non-constant current data, obtaining a voltage change trend between a current position point and a position point next to the current position point on the voltage and power curve;

[0048] When the voltage variation trend does not satisfy the monotonicity corresponding to the battery data, an outlier data segment in the battery data is determined based on the voltage variation trends of a second preset number of location points after the next location point.

[0049] In this embodiment, when the abnormal data does not include the battery data segment corresponding to the non-constant current data, the voltage change trend between the current position point and the next position point on the voltage and power curve is obtained. When the voltage change trend does not meet the monotonicity corresponding to the battery data, the outlier data segment in the battery data is determined according to the voltage change trend of the second preset number of position points after the next position point, thereby realizing the detection of the outlier data segment in the battery data, and then processing the battery data based on the outlier data segment to obtain the target battery data, thereby improving the quality of the obtained target battery data.

[0050] In one embodiment, determining an outlier data segment in the battery data based on voltage change trends at a second predetermined number of locations after the next location includes:

[0051] When the voltage variation trend of the second preset number of locations satisfies monotonicity, the voltage and electricity curve segment between the current location and the first location among the second preset number of locations is used as an outlier data segment;

[0052] In the case that there is a voltage change trend that does not satisfy monotonicity among the voltage change trends of the second preset number of position points, the voltage change trends of the second preset number of position points after the last position point that does not satisfy monotonicity are obtained until the voltage change trends of the second preset number of position points obtained most recently satisfy monotonicity, and the voltage and power curve segment between the current position point and the first position point of the second preset number of position points obtained most recently is used as an outlier data segment.

[0053] In this embodiment, the outlier data segment is determined by determining the voltage variation trends of a second preset number of location points, that is, the outlier data segment is determined based on the voltage variation trends of a sufficient number of location points, thereby improving the accuracy of determining the outlier data segment.

[0054] In one embodiment, the battery data includes battery data generated during multiple battery charge and discharge processes, and the target battery data is obtained by processing the battery data according to the abnormal data, including:

[0055] For the battery data generated during each battery charge and discharge process, if the abnormal data corresponding to the battery data does not include a battery data segment corresponding to non-constant current data and includes other abnormal data, the abnormal data in the battery data is removed to obtain the remaining battery data; the other abnormal data includes at least one of a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment;

[0056] Smoothing the remaining battery data to obtain intermediate battery data;

[0057] The missing data in the intermediate battery data are supplemented to obtain the target battery data.

[0058] In this embodiment, by excluding the battery data segment corresponding to the non-constant current data in the abnormal data corresponding to the battery data and including other abnormal data, the abnormal data in the battery data is eliminated to obtain the remaining battery data, the remaining battery data is smoothed to obtain the intermediate battery data, and the missing data in the intermediate battery data is completed to obtain the target battery data, thereby improving the quality of the obtained target battery data.

[0059] In a second aspect, the present application also provides a battery data processing device. The device includes:

[0060] A detection module is used to detect battery data during the battery charging and discharging process and obtain the detection results of the battery data;

[0061] A processing module is used to process the battery data according to the abnormal data to obtain target battery data when the detection result shows that the battery data includes abnormal data; the abnormal data includes at least one of a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment.

[0062] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the above methods when executing the computer program.

[0063] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when executed by a processor.

[0064] In a fifth aspect, the present application further provides a computer program product, comprising a computer program that implements the steps of any of the above methods when executed by a processor.

[0065] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present application. The same reference numerals are used throughout the drawings to represent the same components. In the drawings:

[0067] Figure 1 is a diagram of the internal structure of a computer device in one embodiment;

[0068] Figure 2 This is a flow chart of a battery data processing method provided in an embodiment of the present application;

[0069] Figure 3 This is one of the flowcharts of the abnormal data detection method provided in the embodiment of the present application;

[0070] Figure 4 This is a schematic diagram of a current fluctuating within a small range provided in an embodiment of the present application;

[0071] Figure 5 This is the second flowchart of the abnormal data detection method provided in the embodiment of the present application;

[0072] Figure 6 This is the third flow chart of the abnormal data detection method provided in the embodiment of the present application;

[0073] Figure 7 This is one of the schematic diagrams of the voltage and charge curve of the battery charging process provided in the embodiment of the present application;

[0074] Figure 8 This is the fourth flowchart of the abnormal data detection method provided in the embodiment of the present application;

[0075] Figure 9 This is the fifth flowchart of the abnormal data detection method provided in the embodiment of the present application;

[0076] Figure 10 This is a schematic diagram of a current-time curve and a voltage-capacity curve corresponding to the current-time curve during a battery charging process provided by an embodiment of the present application;

[0077] Figure 11 This is the sixth flowchart of the abnormal data detection method provided in the embodiment of the present application;

[0078] Figure 12 This is the seventh flowchart of the abnormal data detection method provided in the embodiment of the present application;

[0079] Figure 13 This is a second schematic diagram of a voltage and power curve during a battery charging process provided by an embodiment of the present application;

[0080] Figure 14 This is a third schematic diagram of a voltage and power curve during a battery charging process provided in an embodiment of the present application;

[0081] Figure 15 This is a flow chart of a method for acquiring target battery data provided by an embodiment of the present application;

[0082] Figure 16 This is a schematic diagram of the overall flow of a battery data processing method provided in an embodiment of the present application;

[0083] Figure 17 It is a structural diagram of a battery data processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0084] The following embodiments of the technical solution of the present application will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application and are therefore only examples and are not intended to limit the scope of protection of the present application.

[0085] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0086] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0087] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0088] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0089] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0090] In the description of the embodiments of the present application, the technical terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0091] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0092] With the widespread use of batteries, users have higher requirements for battery performance, for example, batteries with larger capacity in a smaller size and weight, and longer service life.

[0093] Currently, the initial model is trained using raw battery data, such as the voltage and capacity of a test battery during the charge and discharge phases, to generate a predictive model. Based on the predictive model and design parameters such as the battery's length, width, and anode material, predicted battery data is obtained. This predicted battery data can be used to optimize the battery's design parameters, thereby improving battery performance. As can be seen, the more accurate the predicted battery data obtained based on the predictive model and battery design parameters, the more accurate the optimization of the design parameters, which in turn improves battery performance. The accuracy of the predicted battery data is affected by the accuracy of the predictive model: the more accurate the predictive model, the more accurate the predicted battery data. Therefore, the quality of the battery data required for model training is crucial, impacting the accuracy of the predictive model and, consequently, the battery's performance.

[0094] However, in practical applications, raw battery data often contains many types of abnormal data due to objective factors such as time, cost, and measurement errors. This introduces biases in model training and limits the accuracy and reliability of modeling. Therefore, improving the quality of battery data has become a pressing technical issue in this field.

[0095] In order to solve the above technical problems, the present invention provides a battery data processing method, which can be applied to Figure 1 The computer device shown may be a terminal. The computer device includes a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal via wired or wireless communication. Wireless communication can be achieved via Wi-Fi, a mobile cellular network, NFC (near-field communication), or other technologies. When executed by the processor, the computer program implements a battery data processing method. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device of the computer device may be a touchscreen covering the display, buttons, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0096] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0097] The present application is described below with reference to an embodiment. In one embodiment, Figure 2 As shown, Figure 2 This is a flow chart of a battery data processing method provided by an embodiment of the present application, in which the method is applied to Figure 1 Taking the computer device in FIG. 1 as an example, the method includes the following steps S201-S202:

[0098] S201 , detecting battery data during the battery charging and discharging process to obtain a detection result of the battery data.

[0099] It should be noted that the battery data in this embodiment may include voltage data and state of charge data corresponding to the voltage data. Alternatively, the battery data may include voltage data and charge data corresponding to the voltage data. The correspondence between the voltage data and charge data may be represented in the form of a curve or in the form of a data table. The battery data may be battery data during the charging process or battery data during the discharging process.

[0100] Since model training expects to obtain battery data corresponding to constant current data, training the model based on battery data corresponding to constant current data can produce a more accurate prediction model. However, battery data during the battery charging and discharging process may not correspond to constant current data. Therefore, it is necessary to detect the battery data to determine whether the battery data corresponds to the battery data segment corresponding to constant current data.

[0101] In one embodiment, whether the battery data corresponds to a battery data segment of constant current data is determined based on the monotonicity of the current charge and discharge process. For example, the battery data during the charging process includes voltage data and power data corresponding to the voltage data. The correspondence between the voltage data and power data is represented by a curve. The curve representing the correspondence between the voltage data and power data can be called a voltage-power curve. The ordinate of the voltage-power curve is voltage, and the abscissa is power. After charging begins, the voltage shows an increasing trend. When the voltage reaches a certain target voltage value, the voltage fluctuation is very small and remains almost constant. That is, the constant voltage stage begins at the point where the voltage reaches the target voltage value.

[0102] Since the voltage and charge curve shows a monotonically increasing trend after the constant current charging starts, the voltage increases as the charging time continues. When the voltage reaches a certain target voltage value, the voltage increase is very small or almost unchanged. Therefore, based on the monotonically increasing characteristics of the voltage and charge curve during the constant current charging process, the curve segment before the voltage reaches the target voltage value can be detected, and the curve segment can be used as the battery data segment corresponding to the constant current data. If the ratio of the length of the curve segment to the total length of the voltage and charge curve is greater than or equal to the preset ratio, it can be determined that the voltage and charge curve is the battery data segment corresponding to the constant current data; if the ratio of the length of the curve segment to the total length of the voltage and charge curve is less than the preset ratio, it can be determined that the voltage and charge curve is the battery data segment corresponding to the non-constant current data, that is, the detection result is that the battery data includes the battery data segment corresponding to the non-constant current data. In this case, the voltage and charge curve can be used as the battery data segment corresponding to the non-constant current data.

[0103] In one embodiment, the battery data can also be detected in combination with the current data corresponding to the battery data during the charging and discharging process to determine whether the battery data is battery data corresponding to constant current data. In this case, if the current data is determined to be constant current data, the battery data can be determined to be a battery data segment corresponding to constant current data, that is, the voltage and power curve is a battery data segment corresponding to constant current data; if the current data is determined to be non-constant current data, the battery data can be determined to be a battery data segment corresponding to non-constant current data, that is, the detection result obtained is that the battery data includes abnormal data, and the abnormal data is a battery data segment corresponding to non-constant current data. In this case, the voltage and power curve can be used as the battery data segment corresponding to non-constant current data.

[0104] In the case where the battery data does not correspond to a battery data segment corresponding to non-constant current data, that is, the voltage and charge curve does not correspond to a battery data segment corresponding to non-constant current data, the battery data can be further subjected to constant voltage data detection, outlier data point detection, and outlier data segment detection. Further performing constant voltage data detection on the battery data can determine whether there is a battery data segment corresponding to constant voltage data in the battery data; further performing outlier data point detection on the battery data can determine whether there are outlier data points in the battery data; and further performing outlier data segment detection on the battery data can determine whether there are outlier data segments in the battery data.

[0105] The battery data detection during the discharge process is similar to the battery data detection during the charging process described above and will not be repeated here. The difference is that during the discharge process, the voltage data shows a monotonically decreasing trend after the discharge begins. After the voltage data drops to a certain level, the voltage approaches 0 and the decrease is very small or almost unchanged.

[0106] S202 : When the detection result shows that the battery data includes abnormal data, the battery data is processed according to the abnormal data to obtain target battery data.

[0107] The abnormal data includes at least one of a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment.

[0108] In order to facilitate a clearer introduction to the embodiments of the present application, the battery data segment corresponding to the non-constant current data is referred to as the first type of abnormal data; the battery data segment corresponding to the constant voltage data is referred to as the second type of abnormal data; the outlier data points in the battery data are referred to as the third type of abnormal data, and the outlier data segment in the battery data is referred to as the fourth type of abnormal data.

[0109] It should be noted that the order in which the first, second, third, and fourth categories of abnormal data are detected is not limited. Therefore, it is possible that all four categories of abnormal data exist, or only some of the four categories of abnormal data exist. All four categories of abnormal data can be detected simultaneously, or one category of abnormal data can be detected first, followed by the next category of abnormal data.

[0110] In one embodiment, the battery data can first be tested for first-category abnormal data. If the abnormal data does not include the first-category abnormal data, the battery data can be tested for constant-voltage data to detect battery data segments corresponding to constant-voltage data within the battery data. Outlier data point detection can also be performed on the battery data to detect outlier data points within the battery data. Outlier data segment detection can also be performed on the battery data to detect outlier data segments within the battery data. That is, if the abnormal data does not include the first-category abnormal data, the battery data may contain at least one of battery data segments corresponding to constant-voltage data, outlier data points, and outlier data segments. If the abnormal data includes the first-category abnormal data, since model training is intended to obtain battery data corresponding to constant-current data, training the model based on battery data corresponding to constant-current data can yield a more accurate prediction model. Therefore, in this embodiment of the present application, battery data segments corresponding to non-constant-current data can be considered unusable data. If the battery data contains battery data segments corresponding to non-constant-current data, the battery data can be subsequently removed. Therefore, subsequent testing for second-category abnormal data, third-category abnormal data, and fourth-category abnormal data can be omitted, thereby improving the efficiency of abnormality detection.

[0111] Processing the battery data according to the abnormal data to obtain the target battery data may include:

[0112] In one possible implementation, when the abnormal data includes the first type of abnormal data, since the model training expects to obtain battery data corresponding to the constant current data, training the model based on the battery data corresponding to the constant current data can obtain a more accurate prediction model. Therefore, in the embodiment of the present application, when the battery data includes the first type of abnormal data, the battery data can be directly regarded as data of no use value and can be eliminated.

[0113] In another possible implementation, when the abnormal data includes at least one of the second, third, and fourth categories of abnormal data, the abnormal data in the battery data may be removed to obtain remaining battery data, the remaining battery data may be smoothed to obtain intermediate battery data, and missing data in the intermediate battery data may be supplemented to obtain target battery data. The missing data may include data missing due to the removal of the abnormal data, or may include data missing due to the removal of the abnormal data and some missing data in the collected battery data itself.

[0114] In another possible implementation, when the abnormal data includes at least one type of abnormal data from among the second type of abnormal data, the third type of abnormal data, and the fourth type of abnormal data, the abnormal data in the battery data can be eliminated to obtain the remaining battery data, and the missing data in the remaining battery data can be completed to obtain the target battery data.

[0115] The following is an exemplary description of a process for processing the battery data to obtain target battery data based on the abnormal data when the detection result shows that the battery data includes abnormal data:

[0116] If the battery data includes battery data generated by 100 battery charge and discharge processes, and the battery data generated by one battery charge and discharge process is represented in the form of a curve, that is, the battery data includes 100 curves, wherein, for the curve corresponding to the first battery charge and discharge process, the curve includes the first type of abnormal data; for the curves corresponding to the 2nd to 80th battery charge and discharge processes, if each of the 79 curves includes at least one type of abnormal data among the second type of abnormal data, the third type of abnormal data, and the fourth type of abnormal data; for the curves corresponding to the 81st to 100th battery charge and discharge processes, the detection results of the 20 curves are that the battery data does not include abnormal data.

[0117] In the above case, the curve corresponding to the first battery charge and discharge process can be directly discarded, and the abnormal data in the 79 curves corresponding to the 2nd to 80th battery charge and discharge processes can be eliminated to obtain the remaining curve segments of each of the 79 curves. Each remaining curve segment is smoothed to obtain an intermediate curve segment, and the missing data in each intermediate curve segment is supplemented to obtain 79 target curves, thereby processing the 80 battery data based on the abnormal data in the 1st to 80th battery data. Since the battery data generated by the first battery charge and discharge process is discarded, the target battery data finally obtained includes 79 target curves obtained after processing the 79 curves generated by the 2nd to 80th battery charge and discharge processes. The 79 target curves and the above-mentioned 20 curves that do not include abnormal data can be used to train the model.

[0118] It can be understood that if 5 curves among the above 100 curves include the first type of abnormal data, and each of the remaining 95 curves contains at least one type of abnormal data among the second type of abnormal data, the third type of abnormal data and the fourth type of abnormal data, then the 5 curves including the first type of abnormal data can be discarded, and the target battery data finally obtained are the 95 target curves obtained after processing the remaining 95 curves.

[0119] In this embodiment, battery data during the battery charging and discharging process is detected to obtain a detection result of the battery data. If the detection result shows that the battery data includes at least one of abnormal data selected from a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment, the battery data is processed based on the abnormal data to obtain target battery data. Because the abnormal data in the battery data can be detected and the battery data is processed based on the abnormal data to obtain the target battery data, the quality of the obtained target battery data is improved.

[0120] In one embodiment, the above-mentioned S201, detecting battery data during the battery charging and discharging process to obtain the detection result of the battery data, can be implemented as follows:

[0121] The battery data is detected according to the current data corresponding to the battery data during the battery charging and discharging process to obtain a detection result of the battery data.

[0122] In order to improve the accuracy and efficiency of the obtained detection results, the battery data may be detected based on the current data corresponding to the battery data during the battery charging and discharging process to obtain the detection results in the battery data.

[0123] For the detection of the first type of abnormal data, the current data can be sorted according to its size to obtain target current data, a current window can be determined based on the length of the target current data and a preset length ratio, the target current data can be intercepted based on the current window to obtain current data segments, and the battery data can be tested based on the current data segments to obtain a battery data detection result; the detection result includes whether the battery data includes a battery data segment corresponding to non-constant current data. Alternatively, a current window can be determined based on the length of the current data and a preset length ratio, the current data can be intercepted based on the current window to obtain current data segments, and the battery data can be tested based on the current data segments to obtain a battery data detection result; the detection result includes whether the battery data includes a battery data segment corresponding to non-constant current data.

[0124] Among them, the battery data is detected according to the current data segment to obtain the detection result of the battery data; the detection result includes whether the battery data includes a battery data segment corresponding to non-constant current data, which may include: when the current difference between the maximum current data and the minimum current data in the current data segment is greater than or equal to the preset current difference, the battery data is used as the battery data segment corresponding to the non-constant current data existing in the battery data; when the current difference is less than the preset current difference, the battery data is used as the battery data segment corresponding to the constant current data.

[0125] For the detection of the second, third and fourth types of abnormal data, when it is determined that there is no battery data segment corresponding to non-constant current data in the battery data, that is, when it is determined based on the current data that the battery data is a battery data segment corresponding to constant current data, the second, third and fourth types of abnormal data can be detected; when the detection result is that the abnormal data in the battery data includes a battery data segment corresponding to non-constant current data, there is no need to detect the second, third and fourth types of abnormal data, thereby improving the efficiency of abnormality detection.

[0126] In this embodiment, the battery data is detected based on the current data corresponding to the battery data during the battery charging and discharging process to obtain the detection results in the battery data. When the detection result is that the abnormal data in the battery data includes a battery data segment corresponding to the non-constant current data, there is no need to detect the battery data segment corresponding to the constant voltage data, the outlier data points and the outlier data segments, thereby reducing the time cost required for detection.

[0127] In one embodiment, Figure 3 As shown, Figure 3 This is one of the flowcharts of the abnormal data detection method provided in the embodiment of the present application. This embodiment relates to a possible implementation method of how to detect battery data based on the current data corresponding to the battery data during the battery charging and discharging process to obtain the battery data detection result. Based on the above embodiment, the method includes the following steps S301-S304:

[0128] S301 , sorting the current data according to the magnitude of the current data to obtain target current data.

[0129] Considering that the constant current data will fluctuate around the fixed current value, it will fluctuate within a small range. Figure 4 As shown, Figure 4This is a schematic diagram of a current fluctuating within a small range provided by an embodiment of the present application. At the same time, since the current data obtained during the charging and discharging process does not provide a standard value for the current, the detection of constant current data is difficult. In order to achieve constant current data detection, this embodiment considers that when the proportion of a certain section of current data concentrated near a certain value reaches a threshold, that is, it is considered that there is a constant current data section in the current data, then it can be determined that the battery data corresponding to the current data is data obtained under constant current conditions. Therefore, in this embodiment, the current data is sorted according to the size of the current data to obtain the target current data, and then the current data is judged to be constant current data based on the length of the target current data and the preset length.

[0130] S302 : Determine a current window according to the length of the target current data and a preset length ratio.

[0131] The current window is determined according to the length of the target current data and the preset length ratio. The product of the length of the target current data and the preset length ratio can be used as a current window. For example, if the target current data is 100 and the preset length ratio is 80%, 80 data can be used as a current window.

[0132] S303 , intercepting target current data based on the current window to obtain current data segments.

[0133] The target current data can be a correspondence between current and time represented in a tabular form, or a correspondence between current and time represented in the form of a current-time curve. Taking the case where the target current data includes a current-time curve as an example, a data segment can be intercepted on the current-time curve based on the current window as a current data segment, and the length of the current data segment is the same as the length of the current window. It should be noted that when intercepting the target current data for the first time, the leftmost end of the current window can be aligned with the leftmost end of the current-time curve before interception. Step S304 can be executed once for each current data segment obtained, or the target current data can be intercepted based on the current window and the moving step to obtain multiple current data segments, and then step S304 is executed based on each current data segment.

[0134] S304 , detecting the battery data according to the current data segment to obtain a detection result of the battery data; the detection result includes whether the battery data includes a battery data segment corresponding to non-constant current data.

[0135] In one embodiment, each time a current data segment is intercepted, the battery data can be detected based on the current data segment. When the detection result is determined based on the current data segment, if the detection result includes a battery data segment corresponding to constant current data, interception can be stopped. When it is determined based on the current data segment that the detection result includes a battery data segment corresponding to non-constant current data, the current window can be moved according to the moving step size, and the target current data can be intercepted based on the moved current window to obtain a new current data segment. When it is determined based on the new current data segment that the battery data is a battery data segment corresponding to non-constant current data, the step of moving the current window according to the moving step size and intercepting the target current data based on the moved current window to obtain a new current data segment is returned to. When the new current data segment is the segment obtained by the last interception and the battery data is determined based on the new current data segment to be a battery data segment corresponding to non-constant current data, it can be determined that the detection result includes a battery data segment corresponding to non-constant current data.

[0136] Exemplarily, the target current data includes 100 data, the current window is 80 data, the moving step is 1, and the current data segment intercepted for the first time includes the 1st-80th data, recorded as current data segment 1. Based on the current data segment 1, when it is determined that the battery data is the battery data segment corresponding to the constant current data, the interception can be stopped, and it can be determined that the detection result includes the battery data segment corresponding to the constant current data.

[0137] It should be noted that if the current difference between the maximum current value and the minimum current value in the current data segment 1 is less than the preset current difference, it means that the current data segment 1 is constant current data. Since the length of the current data segment 1 accounts for a large proportion of the total length of the target current data, the battery data corresponding to the target current data can be regarded as the battery data corresponding to the constant current data, that is, the target current data can be regarded as constant current data first, and then constant voltage data detection can be performed, and the battery data segment corresponding to the non-constant current data can be detected through constant voltage data detection.

[0138] If the battery data is determined to be a battery data segment corresponding to non-constant current data based on current data segment 1, the current window is moved according to the moving step size, and the target battery data is intercepted for a second time based on the moved current window. The second intercepted current data segment includes data from 2nd to 81st, and is recorded as current data segment 2. If the battery data is determined to be a battery data segment corresponding to non-constant current data based on current data segment 2, the current window is moved according to the moving step size, and the target battery data is intercepted for a third time based on the moved current window. The third intercepted current data segment includes data from 3rd to 82nd, and is recorded as current data segment 3. This process of intercepting the target current data is repeated to obtain current data segments. If the battery data is determined to be a battery data segment corresponding to non-constant current data based on the current data segment obtained by the last interception, it can be determined that the detection result includes the battery data segment corresponding to non-constant current data.

[0139] In one embodiment, the target current data may be first intercepted to obtain multiple current data segments based on the current window and the moving step size, and the current difference between the maximum current data and the minimum current data in each current data segment may be determined. If there is at least one current difference value less than a preset current difference value, the detection result may be determined to include a battery data segment corresponding to the battery data being constant current data. If there is no current difference value less than the preset current difference value, the detection result may be determined to include a battery data segment corresponding to the battery data being non-constant current data.

[0140] For example, in conjunction with the above example, if 21 current data segments are obtained by intercepting the target current data, and if at least one current difference value corresponding to the 21 current data segments is less than a preset current difference value, then it can be determined that the detection result includes a battery data segment corresponding to constant current data. If no current difference value corresponding to the 21 current data segments is less than the preset current difference value, then it can be determined that the detection result includes a battery data segment corresponding to non-constant current data.

[0141] In this embodiment, the current data is sorted by magnitude to obtain target current data, a current window is determined based on the length of the target current data and a preset length ratio, the target current data is intercepted based on the current window to obtain current data segments, and the battery data is tested based on the current data segments to obtain battery data test results; the test results include whether the battery data includes battery data segments corresponding to non-constant current data. Since the target current data is the data obtained by sorting the current data by magnitude, the two current data located at the two ends of the current data segment are the maximum current data and the minimum current data in the current data segment, which saves the time required to determine the maximum current data and the minimum current data from the current data segment, thereby improving the efficiency of determining the maximum current data and the minimum current data, and thus improving the efficiency of obtaining the test results.

[0142] In one embodiment, Figure 5 As shown, Figure 5 This is the second flow chart of the abnormal data detection method provided in the embodiment of the present application. This embodiment involves a possible implementation method of how to detect battery data based on current data segments to obtain battery data detection results; the detection results include whether the battery data includes a battery data segment corresponding to non-constant current data. Based on the above embodiment, the method includes the following steps S501-S504:

[0143] S501 , determining a current difference between maximum current data and minimum current data in a current data segment.

[0144] S502 , when the current difference is greater than or equal to a preset current difference, performing an iterative operation; the iterative operation includes moving the current window according to a preset moving step size, and intercepting target current data based on the moved current window to obtain a new current data segment.

[0145] When the current difference is less than the preset current difference, the battery data can be used as the battery data segment corresponding to the constant current data. That is, as long as the current difference corresponding to one current data segment is less than the preset current difference, the battery data can be used as the battery data segment corresponding to the constant current data.

[0146] S503 : When the current difference corresponding to the new current data segment is greater than or equal to the preset current difference, return to perform the iterative operation.

[0147] When the current difference corresponding to the new current data segment is less than the preset current difference, the battery data can be used as the battery data segment corresponding to the constant current data. In combination with the above example, when the battery data is determined to be a battery data segment corresponding to non-constant current data based on current data segment 1, the current window is moved according to the moving step size, and the target battery data is intercepted for the second time based on the moved current window. The second intercepted current data segment, that is, the new current data segment, includes the 2nd to 81st data and is recorded as current data segment 2. When the current difference corresponding to current data segment 2 is less than the preset current difference, the battery data is used as the battery data segment corresponding to the constant current data, and there is no need to perform the iterative operation, thereby shortening the excessive time taken by the interception operation and improving the efficiency of determining the detection result.

[0148] S504 : When the current difference corresponding to the new current data segment intercepted last time is greater than or equal to the preset current difference, determine that the detection result includes a battery data segment corresponding to the battery data being non-constant current data.

[0149] The detection result in this step is that the abnormal data in the battery data includes a battery data segment corresponding to the non-constant current data.

[0150] In this embodiment, when the current difference corresponding to the new current data segment is greater than or equal to the preset current difference, the iterative operation is returned to be performed. When the current difference corresponding to the new current data segment obtained in the last interception is greater than or equal to the preset current difference, it is determined that the detection result includes the battery data segment corresponding to the non-constant current data, thereby realizing the determination of the battery data segment corresponding to the non-constant current data.

[0151] In one embodiment, when the abnormal data in the detection result does not include the first type of abnormal data, that is, when the abnormal data does not include the battery data segment corresponding to the non-constant current data, the second type of abnormal data detection can also be performed on the battery data. In this embodiment, the battery data includes a voltage and power curve for characterizing the corresponding relationship between voltage data and power data, such as Figure 6 As shown, Figure 6 This is the third flow chart of the abnormal data detection method provided in the embodiment of the present application. The method includes the following steps S601-S603:

[0152] S601 , when the abnormal data does not include a battery data segment corresponding to non-constant current data, obtain a voltage change trend between a current point on a voltage and power curve and a point next to the current point.

[0153] For example, Figure 7 As shown, Figure 7 This is one of the schematic diagrams of the voltage and charge curve of the battery charging process provided by the embodiment of the present application. Figure 7 As shown, Figure 7 The battery data in the data includes a voltage and charge curve 71. The battery data corresponding to the voltage and charge curve 71 is not a battery data segment corresponding to non-constant current data. For example, position B1 is the current position, and position B2 is the next position of position B1. Position B1 and position B2 may be adjacent positions, and there may also be a preset number of positions between position B1 and position B2. When position B1 and position B2 are adjacent positions, it is determined whether position B1 and position B2 are strictly monotonic; when there is a preset number of positions between position B1 and position B2, it is determined whether position B1 and position B2 are non-strictly monotonic, that is, in a broad sense, it is determined whether position B1 and position B2 meet monotonicity.

[0154] The voltage difference between the current position and the next position can be calculated to determine whether the voltage change trend meets the monotonicity corresponding to the battery data based on the voltage difference. If the absolute value of the voltage difference is less than a positive preset value, it can be considered that the voltage change trend does not meet the monotonicity and enters the constant voltage stage. Figure 7 As shown, since the voltage at point B2 is equal to the voltage at point B1, the voltage variation trends at points B1 and B2 do not satisfy the monotonicity corresponding to the battery data. The monotonicity corresponding to the battery data during the battery charging process is a monotonically increasing characteristic. As can be seen from voltage and charge curve 71, the voltage variation trends at points before point B1 satisfy the monotonically increasing characteristic.

[0155] S602 : When the voltage variation trend does not satisfy the monotonicity corresponding to the battery data, obtain the voltage variation trend of a first preset number of position points after the next position point.

[0156] When the voltage change trend between the B1 position point and the B2 position point does not satisfy the monotonicity corresponding to the battery data, that is, the voltage change trend between the B1 position point and the B2 position point does not satisfy the monotonically increasing characteristic, the voltage change trend of the first preset number of position points after the B2 position point can be obtained.

[0157] S603 : When the voltage variation trends at the first preset number of locations do not satisfy monotonicity, determine the battery data segment corresponding to the constant voltage data in the battery data according to the current location and the voltage and power curve segments after the current location.

[0158] It can be seen from the voltage-to-capacity curve 71 that the voltage change trend of the first preset number of positions after position B2 does not satisfy the monotonically increasing characteristic, so position B1 and the voltage-to-capacity curve segment after position B1 can be used as the battery data segment corresponding to the constant voltage data.

[0159] In this embodiment, the battery data segment corresponding to the constant voltage data in the battery data is determined based on the voltage change trend of the current position point and the first preset number of position points after the next position point. That is, the battery data segment corresponding to the constant voltage data in the battery data is determined based on the voltage change trend of a sufficient number of position points, thereby improving the accuracy of the determined battery data segment corresponding to the constant voltage data.

[0160] In one embodiment, Figure 8 As shown, Figure 8 This is the fourth flow chart of the abnormal data detection method provided by the embodiment of the present application. This embodiment involves a possible implementation method of how to determine the battery data segment corresponding to the constant voltage data in the battery data based on the current position point and the voltage and power curve segment after the current position point. Based on the above embodiment, the above S603 "determine the battery data segment corresponding to the constant voltage data in the battery data based on the current position point and the voltage and power curve segment after the current position point" includes the following steps S801-S802:

[0161] S801: Use the current position point and the voltage and electricity curve segment after the current position point as the first initial data segment corresponding to the constant voltage data.

[0162] S802 : Determine a battery data segment corresponding to the constant voltage data in the battery data according to the first initial data segment.

[0163] In a possible implementation, the first initial data segment can be used as the battery data segment corresponding to the constant voltage data in the battery data. Figure 7 As shown, the voltage and electricity curve segment at and after the B1 position point can be used as the battery data segment corresponding to the constant voltage data in the battery data.

[0164] In another possible implementation, based on the current data corresponding to the battery data, the second initial data segment corresponding to the constant voltage data can be determined from the voltage and power curve, and the union of the first initial data segment and the second initial data segment can be used as the battery data segment corresponding to the constant voltage data.

[0165] The constant current data segment in the current data can be determined, the end data point in the constant current data segment can be determined, the position point corresponding to the end data point can be determined on the voltage and power curve, and the position point and the voltage and power curve segment after the position point can be used as the second initial data segment, and then the union of the first initial data segment and the second initial data segment can be used as the battery data segment corresponding to the constant voltage data.

[0166] In this embodiment, by taking the current position point and the voltage and charge curve segment after the current position point as the first initial data segment corresponding to the constant voltage data, the battery data segment corresponding to the constant voltage data in the battery data is determined based on the first initial data segment, thereby realizing the determination of the battery data segment corresponding to the constant voltage data in the battery data.

[0167] In one embodiment, Figure 9 As shown, Figure 9 This is the fifth flow chart of the abnormal data detection method provided in the embodiment of the present application. This embodiment involves a possible implementation method of how to determine the battery data segment corresponding to the constant voltage data in the battery data based on the first initial data segment. Based on the above embodiment, the above S802 includes the following steps S901-S904:

[0168] S901, determining a constant current data segment on a current-time curve; the current-time curve is used to represent the corresponding relationship between current data and time during the battery charging and discharging process.

[0169] When charging a battery with a constant charging current, the collected voltage normally increases. After the battery reaches a certain level, the charging current begins to decrease, and the voltage fluctuates very little, remaining nearly constant. This is when the voltage enters the constant voltage phase. The battery discharge process is the opposite of the charging process described above. During discharge, the voltage decreases. After the battery reaches a certain level, the discharge current approaches zero, and the voltage fluctuates very little, remaining nearly constant. This is when the voltage enters the constant voltage phase. Therefore, the charging current can be combined to determine the battery data segment corresponding to the constant voltage data in the battery data.

[0170] like Figure 10 As shown, Figure 10 This is a schematic diagram of a current-time curve and a voltage-capacity curve corresponding to the current-time curve during a battery charging process provided by an embodiment of the present application. Figure 10 Combined Figure 7 The voltage-to-energy curve 71 is introduced as follows. The current-time curve 101 is a curve corresponding to the above-mentioned voltage-to-energy curve 71, that is, voltage data, energy data and current data can be obtained during the battery charging process. The voltage-to-energy curve is determined based on the voltage data and the energy data corresponding to the voltage data, and the current-time curve is determined based on the current data corresponding to the voltage data.

[0171] In one possible implementation, the current difference between two adjacent position points in any current data point group on the current-time curve 101 can be determined. When the absolute value of the current difference is less than or equal to the preset current difference, it is determined that the current corresponding to the current data point group is a constant current. In this way, it can be determined whether the current of each current data point group is a constant current, and the current data segments corresponding to multiple consecutive current data point groups of constant current are used as constant current data segments, wherein one current data point group includes two adjacent position points.

[0172] Exemplarily, if the current corresponding to the first to the 100th current data point group is a constant current, the current data segment corresponding to the first to the 100th current data point group is used as a constant current data segment.

[0173] In another possible implementation, the absolute value of the current difference between two current data points in the current data point group on the current-time curve may be determined. If the absolute value is greater than or equal to a preset value, the absolute value of the two current differences between two current data points in the current data point group immediately preceding the current data point group may be determined until the determined absolute value is less than a preset threshold. The current data point group corresponding to the absolute value less than the preset threshold and the current data segment preceding the current data point group are used as the constant current data segment. The current current data point group includes the current data point corresponding to the current position point and the current data point immediately preceding the current data point.

[0174] For example, if the current position on the voltage-to-charge curve 71 is B1, then the current current data point group on the current-time curve 101 includes the C1 current data point and the C2 current data point. The absolute value of the current difference between the C1 current data point and the C2 current data point is greater than or equal to a preset value, meaning that the current fluctuations between the C1 current data point and the C2 current data point are still large and not constant. Therefore, the absolute value of the current difference between the C2 current data point and the C3 current data point is then determined. The C2 current data point and the C3 current data point constitute the previous current data point group of the current current data point group. As shown in the current-time curve 101, the absolute value of the current difference between the C2 current data point and the C3 current data point is greater than or equal to the preset value, and the currents of the C2 current data point and the C3 current data point exhibit a monotonically decreasing characteristic. Similarly, continue to determine the current difference between the C3 current data point and the current data point before the C3 current data point. Assuming that the absolute value of the current difference between the C10 current data point and the C11 current data point is less than the preset value, it means that the current data segment before the C10 current data point is a constant current current data segment, and the current data segment after the C10 current data point is a non-constant current current data segment, and the current data segment before the C10 current data point is used as a constant current current data segment.

[0175] S902: Determine a target position point on the voltage-to-electricity curve corresponding to the end position point of the constant current data segment.

[0176] Exemplarily, the end position point of the constant current data segment is C10, and the target position point corresponding to C10 on the voltage and power curve is B10.

[0177] S903: Use the target location point and the voltage and electricity curve segment after the target location point as a second initial data segment.

[0178] In combination with the above example, the voltage and electricity curve segment at position B10 and after position B10 may be used as the second initial data segment.

[0179] S904 : Taking the union of the first initial data segment and the second initial data segment as the battery data segment corresponding to the constant voltage data.

[0180] Exemplarily, in combination with the above example, the union of the first initial data segment and the second initial data segment is B10 and the voltage and power curve segment after B10, and B10 and the voltage and power curve segment after B10 serve as the battery data segment corresponding to the constant voltage data.

[0181] In this embodiment, by determining the constant current data segment on the current-time curve, determining the target position point corresponding to the end position point of the constant current data segment on the voltage-to-energy curve, using the target position point and the voltage-to-energy curve segment after the target position point as the second initial data segment, and using the union of the first initial data segment and the second initial data segment as the battery data segment corresponding to the constant voltage data. This allows the second initial data segment corresponding to the non-constant current to be determined based on the current-time curve, and then using the union of the second initial data segment and the first initial data segment as the battery data segment corresponding to the constant voltage data. This allows the second initial data segment corresponding to the non-constant current to also be used as the battery data segment corresponding to the constant voltage data, allowing for a more comprehensive and accurate determination of the battery data segment corresponding to the constant voltage data.

[0182] In one embodiment, when the abnormal data in the detection result does not include the first type of abnormal data, the third type of abnormal data detection can also be performed on the battery data. In this embodiment, the battery data includes a voltage and power curve for characterizing the corresponding relationship between voltage data and power data, such as Figure 11 As shown, Figure 11 This is the sixth flow chart of the abnormal data detection method provided in the embodiment of the present application. The method includes the following steps S1101-S1102:

[0183] S1101 , when the abnormal data does not include a battery data segment corresponding to non-constant current data, obtaining association information between a current position point and a next position point on a voltage and power curve.

[0184] S1102 : Determine outlier data points in the battery data based on the correlation information.

[0185] In a possible implementation, the association information includes the distance between the current location point and the next location point. When the distance is greater than or equal to a preset distance, the outlier data point in the battery data of the next location point can be removed.

[0186] In another possible implementation, the association information includes a sampling time interval between the current location point and the next location point. When the sampling time interval is greater than or equal to a preset sampling time interval, the outlier data point in the battery data of the next location point can be detected.

[0187] In another possible implementation, the associated information includes the distance and sampling time interval between the current position point and the next position point. When the distance is greater than or equal to the preset distance and the sampling time interval is greater than the preset sampling time interval, the next position point is regarded as an outlier data point in the battery data.

[0188] In this embodiment, when the abnormal data does not include the battery data segment corresponding to the non-constant current data, the association information between the current position point and the next position point on the voltage and power curve is obtained, and the outlier data point in the battery data is determined according to the association information.

[0189] In one embodiment, the correlation information includes distance and / or sampling time interval. The above-mentioned S1002 of determining outlier data points in the battery data based on the correlation information can be implemented as follows:

[0190] When the distance is greater than or equal to the preset distance, and / or the sampling time interval is greater than the preset sampling time interval, the next position point is regarded as an outlier data point in the battery data.

[0191] In this embodiment, if the distance is greater than or equal to a preset distance and / or the sampling interval is greater than a preset sampling interval, the next location point is identified as an outlier data point in the battery data. Because the distance and / or sampling interval between the current location point and the next location point are directly determined, this method is relatively simple and quick, thereby improving the efficiency of identifying outlier data points.

[0192] In one embodiment, when the abnormal data does not include the battery data segment corresponding to the non-constant current data, the fourth type of abnormal data detection can also be performed on the battery data. In this embodiment, the fourth type of abnormal data detection is performed. In this embodiment, the battery data includes a voltage and power curve for characterizing the corresponding relationship between voltage data and power data, such as Figure 12 As shown, Figure 12This is the seventh flowchart of the abnormal data detection method provided in the embodiment of the present application. The method includes the following steps S1201-S1202:

[0193] S1201 , when the abnormal data does not include a battery data segment corresponding to non-constant current data, obtain a voltage change trend between a current point and a point next to the current point on a voltage-to-capacity curve.

[0194] The current position point and the next position point on the voltage-to-electricity curve may be two adjacent data points, or may be two data points separated by a preset number of data points.

[0195] S1202 : When the voltage variation trend does not satisfy the monotonicity corresponding to the battery data, determine an outlier data segment in the battery data according to the voltage variation trends of a second preset number of location points after the next location point.

[0196] When the voltage variation trends of the second preset number of location points meet the monotonicity, the voltage and electricity curve segment between the current location point and the first location point of the second preset number of location points is used as the outlier data segment.

[0197] For example, the points in Table 1 include points 1 through 6, with the voltage at point 1 being 5 and the voltage at point 2 being 4. The voltages at each point are shown in Table 1. If the current point is point 1 and the next point is point 2, since the voltage trends at points 1 and 2 do not satisfy the monotonically increasing characteristic, it is necessary to continue determining the voltage trends at a second preset number of points after point 2. For example, if the second preset number is 4, Table 1 shows that the voltage trends at the four points after point 2 satisfy the monotonicity, i.e., the voltage trends at points 3 through 6 satisfy the monotonically increasing characteristic. Therefore, the data segment between points 1 and 3 can be considered an outlier data segment.

[0198]

[0199] Table 1

[0200] In the case that there is a voltage change trend that does not satisfy monotonicity among the voltage change trends of the second preset number of position points, the voltage change trends of the second preset number of position points after the last position point that does not satisfy monotonicity are obtained until the voltage change trends of the second preset number of position points obtained most recently satisfy monotonicity, and the voltage and power curve segment between the current position point and the first position point of the second preset number of position points obtained most recently is used as an outlier data segment.

[0201] For example, the locations in Table 2 include locations 1 to 11, with the voltage at location 1 being 3 and the voltage at location 2 being 4. The voltages of the various locations are shown in Table 1 below. If the current location is location 1 and the next location is location 2, since the voltage change trends at location 1 and location 2 do not satisfy the monotonically increasing characteristic, it is necessary to continue determining the voltage change trends at a second preset number of locations after location 2. Taking the second preset number of 4 as an example, Table 2 shows that the voltage change trends at location 2 and location 3 satisfy the monotonically increasing characteristic, and the voltage change trends at location 3 and location 4 satisfy the monotonically increasing characteristic, but the voltage change trends at location 4 and location 5 do not satisfy the monotonically increasing characteristic. Location 5 is the last location point that does not satisfy the monotonicity corresponding to the battery data. In this case, it is necessary to determine the voltage variation trends at locations 5 and 6. As can be seen from Table 2, the voltage variation trends at locations 5 and 6 satisfy the monotonically increasing characteristic. The voltage variation trends at locations 6 and 7 are then determined. These do not satisfy the monotonically increasing characteristic. The voltage variation trends at a second predetermined number of locations after location 7 are then determined. Since the voltage variation trends at locations 7 and 8, 8 and 9, 9 and 10, and 10 and 11 all satisfy the monotonically increasing characteristic, the battery data between locations 1 and 8 can be considered an outlier data segment. Alternatively, the battery data between locations 2 and 7 can be considered an outlier data segment.

[0202]

[0203] Table 2

[0204] like Figure 13 As shown, Figure 13 This is the second schematic diagram of the voltage and charge curve of the battery charging process provided in the embodiment of the present application. Figure 14 This is the third schematic diagram of the voltage and power curve of the battery charging process provided in the embodiment of the present application. Figure 13 and Figure 14 The data segment selected by the middle rectangular box is the outlier data segment.

[0205] In this embodiment, when the abnormal data does not include the battery data segment corresponding to the non-constant current data, the voltage change trend between the current position point and the next position point on the voltage and power curve is obtained. When the voltage change trend does not meet the monotonicity corresponding to the battery data, the outlier data segment in the battery data is determined according to the voltage change trend of the second preset number of position points after the next position point, thereby realizing the detection of the outlier data segment in the battery data, and then processing the battery data based on the outlier data segment to obtain the target battery data, thereby improving the quality of the obtained target battery data.

[0206] In one embodiment, the step of “determining an outlier data segment in the battery data based on the voltage change trends of a second preset number of locations after the next location” in S1202 can be implemented as follows:

[0207] When the voltage variation trend of the second preset number of locations satisfies monotonicity, the voltage and electricity curve segment between the current location and the first location among the second preset number of locations is used as an outlier data segment;

[0208] In the case that there is a voltage change trend that does not satisfy monotonicity among the voltage change trends of the second preset number of position points, the voltage change trends of the second preset number of position points after the last position point that does not satisfy monotonicity are obtained until the voltage change trends of the second preset number of position points obtained most recently satisfy monotonicity, and the voltage and power curve segment between the current position point and the first position point of the second preset number of position points obtained most recently is used as an outlier data segment.

[0209] In this embodiment, the outlier data segment is determined by determining the voltage variation trends of a second preset number of location points, that is, the outlier data segment is determined based on the voltage variation trends of a sufficient number of location points, thereby improving the accuracy of determining the outlier data segment.

[0210] In one embodiment, Figure 15 As shown, Figure 15 This is a flow chart of a method for acquiring target battery data provided by an embodiment of the present application. This embodiment relates to a possible implementation method of how to process battery data based on abnormal data to obtain target battery data. Based on the above embodiment, the "processing battery data based on abnormal data to obtain target battery data" in S202 above may include the following steps S1501-S1503:

[0211] S1501, for battery data generated during each battery charge and discharge process, if the abnormal data corresponding to the battery data does not include a battery data segment corresponding to non-constant current data and includes other abnormal data, the abnormal data in the battery data is eliminated to obtain remaining battery data; the other abnormal data includes at least one of a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment.

[0212] S1502, smoothing the remaining battery data to obtain intermediate battery data;

[0213] The remaining battery data may be smoothed using a Kalman filter method, a linear smoothing method, a median filter method, or the like to obtain intermediate battery data.

[0214] S1503: Perform data completion processing on the missing data in the intermediate battery data to obtain target battery data.

[0215] Interpolation methods such as B-spline interpolation, K-nearest neighbors (KNN), neighbor value interpolation, and linear interpolation can be used to complete the missing data in the intermediate battery data to obtain the target battery data.

[0216] In this embodiment, by excluding the battery data segment corresponding to the non-constant current data in the abnormal data corresponding to the battery data and including other abnormal data, the abnormal data in the battery data is eliminated to obtain the remaining battery data, the remaining battery data is smoothed to obtain the intermediate battery data, and the missing data in the intermediate battery data is completed to obtain the target battery data, thereby improving the quality of the obtained target battery data.

[0217] Reference Figure 16 , Figure 16It is a schematic diagram of the overall flow of a battery data processing method provided by an embodiment of the present application. The battery data processing method includes two parts: abnormal curve detection and abnormal curve repair. Abnormal curve detection includes extracting voltage data and power data from the test data of the battery charging and discharging process, obtaining a voltage-power curve based on the voltage data and power data, and performing non-constant current data detection on the voltage-power curve based on the current window and current data to determine whether the voltage-power curve is a curve corresponding to non-constant current data; if the voltage-power curve is not a curve corresponding to non-constant current data, constant voltage data detection can be performed on the voltage-power curve to detect the battery data segment corresponding to the constant voltage data in the voltage-power curve; and if the voltage-power curve is not a curve corresponding to non-constant current data, outlier data point detection can also be performed on the voltage-power curve to detect outlier data points in the voltage-power curve; if the voltage-power curve is not a curve corresponding to non-constant current data, outlier data segment detection can also be performed on the voltage-power curve to detect outlier data segments in the voltage-power curve. After abnormal curve detection, normal voltage and electricity curves can be identified from multiple voltage and electricity curves and referred to as normal data. Furthermore, voltage and electricity curves containing abnormal data can be identified and referred to as abnormal voltage and electricity curves. Abnormal voltage and electricity curves are data to be repaired.

[0218] Abnormal curve repair refers to repairing the data to be repaired. For abnormal voltage and power curves that include battery data segments corresponding to non-constant current data, the abnormal voltage and power curves can be directly discarded. For abnormal voltage and power curves that do not include battery data segments corresponding to non-constant current data, abnormal curve repair includes removing the abnormal data in the abnormal voltage and power curves to obtain the remaining battery data, smoothing the remaining battery data to obtain intermediate battery data, and completing the missing data in the intermediate battery data to obtain the target battery data. The target battery data and the normal voltage and power curve are processed data obtained after testing and processing the test data, and can be provided for model training.

[0219] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0220] Based on the same inventive concept, embodiments of the present application also provide a battery data processing device for implementing the aforementioned battery data processing method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more battery data processing device embodiments provided below can be found in the aforementioned limitations of the battery data processing method and will not be further elaborated here.

[0221] In one embodiment, Figure 17 As shown, Figure 17 1700 is a schematic diagram of the structure of a battery data processing device provided in an embodiment of the present application. The device 1700 includes:

[0222] The detection module 1701 is used to detect battery data during the battery charging and discharging process and obtain the detection result of the battery data;

[0223] Processing module 1702 is used to process the battery data according to the abnormal data to obtain target battery data when the detection result shows that the battery data includes abnormal data; the abnormal data includes at least one of a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment.

[0224] In one embodiment, the detection module 1701 is specifically configured to detect the battery data according to current data corresponding to the battery data during the battery charging and discharging process to obtain a detection result of the battery data.

[0225] In one embodiment, the detection module 1701 includes:

[0226] A sorting unit, configured to sort the current data according to the magnitude of the current data to obtain target current data;

[0227] a first determining unit, configured to determine a current window according to a length of target current data and a preset length ratio;

[0228] a cutting unit, configured to cut target current data based on the current window to obtain current data segments;

[0229] The detection unit is used to detect the battery data according to the current data segment to obtain a detection result of the battery data; the detection result includes whether the battery data includes a battery data segment corresponding to the non-constant current data.

[0230] In one embodiment, the detection unit is specifically used to determine the current difference between the maximum current data and the minimum current data in the current data segment; when the current difference is greater than or equal to the preset current difference, perform an iterative operation; the iterative operation includes moving the current window according to a preset moving step, and intercepting the target current data based on the moved current window to obtain a new current data segment; when the current difference corresponding to the new current data segment is greater than or equal to the preset current difference, return to perform the iterative operation; when the current difference corresponding to the new current data segment obtained in the last interception is greater than or equal to the preset current difference, determine that the detection result includes the battery data segment corresponding to the non-constant current data.

[0231] In one embodiment, the battery data includes a voltage-to-electricity curve for characterizing the correspondence between voltage data and electric quantity data. The detection module 1701 is further used to obtain the voltage change trend between the current position point and the next position point on the voltage-to-electricity curve when the abnormal data does not include the battery data segment corresponding to the non-constant current data; when the voltage change trend does not satisfy the monotonicity corresponding to the battery data, obtain the voltage change trend of the first preset number of position points after the next position point; when the voltage change trend of the first preset number of position points does not satisfy the monotonicity, determine the battery data segment corresponding to the constant voltage data in the battery data based on the current position point and the voltage-to-electricity curve segment after the current position point.

[0232] In one embodiment, the detection module 1701 is specifically configured to use the current position point and the voltage and charge curve segment after the current position point as the first initial data segment corresponding to the constant voltage data; and determine the battery data segment corresponding to the constant voltage data in the battery data based on the first initial data segment.

[0233] In one embodiment, the detection module 1701 is specifically used to determine a constant current data segment on a current-time curve; the current-time curve is used to characterize the correspondence between current data and time during the battery charging and discharging process; a target position point corresponding to the end position point of the constant current data segment is determined on the voltage-to-energy curve; the target position point and the voltage-to-energy curve segment after the target position point are used as the second initial data segment; and the union of the first initial data segment and the second initial data segment is used as the battery data segment corresponding to the constant voltage data.

[0234] In one embodiment, the battery data includes a voltage-to-electricity curve for characterizing the correspondence between voltage data and electric quantity data. The detection module 1701 is also used to obtain the correlation information between the current position point and the next position point on the voltage-to-electricity curve when the abnormal data does not include a battery data segment corresponding to non-constant current data; and determine the outlier data points in the battery data based on the correlation information.

[0235] In one embodiment, the associated information includes distance and / or sampling time interval, and the detection module 1701 is specifically used to treat the next position point as an outlier data point in the battery data when the distance is greater than or equal to a preset distance and / or the sampling time interval is greater than a preset sampling time interval.

[0236] In one embodiment, the battery data includes a voltage-to-electricity curve for characterizing the correspondence between voltage data and electric quantity data. The detection module 1701 is also used to obtain the voltage change trend between the current position point and the next position point on the voltage-to-electricity curve when the abnormal data does not include a battery data segment corresponding to non-constant current data; when the voltage change trend does not meet the monotonicity corresponding to the battery data, the outlier data segment in the battery data is determined based on the voltage change trend of a second preset number of position points after the next position point.

[0237] In one embodiment, the detection module 1701 is specifically used to, when the voltage change trend of the second preset number of position points satisfies monotonicity, use the voltage and power curve segment between the current position point and the first position point among the second preset number of position points as an outlier data segment; when there is a voltage change trend that does not satisfy monotonicity among the voltage change trends of the second preset number of position points, obtain the voltage change trend of the second preset number of position points after the last position point that does not satisfy monotonicity, until the voltage change trend of the second preset number of position points obtained most recently satisfies monotonicity, and use the voltage and power curve segment between the current position point and the first position point among the second preset number of position points obtained most recently as an outlier data segment.

[0238] In one embodiment, the battery data includes battery data generated by multiple battery charge and discharge processes. The processing module 1702 is specifically used to eliminate the abnormal data in the battery data generated by each battery charge and discharge process to obtain remaining battery data, if the abnormal data corresponding to the battery data does not include a battery data segment corresponding to non-constant current data and includes other abnormal data; the other abnormal data includes at least one of a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment; smooth the remaining battery data to obtain intermediate battery data; and complete the missing data in the intermediate battery data to obtain target battery data.

[0239] Each module in the battery data processing device described above can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0240] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of any of the above-mentioned method embodiments are implemented. The technical principles and technical effects are similar and will not be repeated here.

[0241] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned method embodiments are implemented. The technical principles and technical effects are similar and will not be repeated here.

[0242] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps of any of the above method embodiments are implemented. The technical principles and technical effects are similar and will not be repeated here.

[0243] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0244] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0245] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0246] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and they should all be included in the scope of the claims and specification of the present application. In particular, as long as there is no structural conflict, the various technical features mentioned in the various embodiments can be combined in any way. The present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

Claims

1. A battery data processing method, characterized in that: The method comprises: Detecting battery data during the battery charging and discharging process to obtain a detection result of the battery data; If the detection result indicates that the battery data includes abnormal data, the battery data is processed according to the abnormal data to obtain target battery data; the abnormal data includes at least one of a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment; and the constant current data is data that fluctuates around a fixed current value. The detecting of battery data during the battery charging and discharging process to obtain the detection result of the battery data includes: detecting the battery data according to current data corresponding to the battery data during charging and discharging of the battery to obtain a detection result of the battery data; The detecting the battery data to obtain a detection result of the battery data according to the current data corresponding to the battery data during the charging and discharging process of the battery includes: sorting the current data according to the magnitude of the current data to obtain target current data; determining a current window according to a length of the target current data and a preset length ratio; intercepting the target current data based on the current window to obtain a current data segment; The battery data is detected according to the current data segment to obtain a detection result of the battery data; the detection result includes whether the battery data includes a battery data segment corresponding to non-constant current data.

2. The method according to claim 1, characterized in that The detecting the battery data according to the current data segment to obtain the detection result of the battery data includes: determining a current difference between maximum current data and minimum current data in the current data segment; When the current difference is greater than or equal to a preset current difference, performing an iterative operation; the iterative operation includes moving the current window according to a preset moving step size, and intercepting the target current data based on the moved current window to obtain a new current data segment; If the current difference value corresponding to the new current data segment is greater than or equal to the preset current difference value, returning to execute the iterative operation; When the current difference corresponding to the new current data segment intercepted last time is greater than or equal to the preset current difference, it is determined that the detection result includes the battery data segment corresponding to the non-constant current data.

3. The method according to claim 1 or 2, characterized in that The battery data includes a voltage-to-electricity curve for characterizing a corresponding relationship between voltage data and electric quantity data. The method further includes: When the abnormal data does not include a battery data segment corresponding to non-constant current data, obtaining a voltage change trend between a current position point and a position point next to the current position point on the voltage and power curve; When the voltage variation trend does not satisfy the monotonicity corresponding to the battery data, obtaining voltage variation trends of a first preset number of locations after the next location point; When the voltage variation trends of the first preset number of position points do not satisfy the monotonicity, the battery data segment corresponding to the constant voltage data in the battery data is determined according to the current position point and the voltage and power curve segment after the current position point.

4. The method according to claim 3, characterized in that The determining, based on the current position point and the voltage and power curve segment after the current position point, a battery data segment corresponding to the constant voltage data in the battery data includes: Using the current position point and the voltage and electricity curve segment after the current position point as the first initial data segment corresponding to the constant voltage data; A battery data segment corresponding to the constant voltage data in the battery data is determined according to the first initial data segment.

5. The method according to claim 4, characterized in that The determining, based on the first initial data segment, a battery data segment corresponding to the constant voltage data in the battery data includes: Determining a constant current data segment on a current-time curve; the current-time curve is used to characterize the corresponding relationship between current data and time during the charging and discharging process of the battery; Determining a target position point on the voltage and electricity curve corresponding to the end position point of the constant current data segment; Using the target location point and the voltage and electricity curve segment after the target location point as a second initial data segment; The union of the first initial data segment and the second initial data segment is used as the battery data segment corresponding to the constant voltage data.

6. The method according to claim 1 or 2, characterized in that The battery data includes a voltage-to-electricity curve for characterizing a corresponding relationship between voltage data and electric quantity data. The method further includes: When the abnormal data does not include a battery data segment corresponding to non-constant current data, obtaining association information between a current position point and a next position point on the voltage and power curve; Outlier data points in the battery data are determined according to the association information.

7. The method according to claim 6, characterized in that The association information includes a distance and / or a sampling time interval, and determining the outlier data point in the battery data according to the association information includes: When the distance is greater than or equal to a preset distance, and / or the sampling time interval is greater than a preset sampling time interval, the next position point is taken as an outlier data point in the battery data.

8. The method according to claim 1 or 2, characterized in that The battery data includes a voltage-to-electricity curve for characterizing a corresponding relationship between voltage data and electric quantity data. The method further includes: When the abnormal data does not include a battery data segment corresponding to non-constant current data, obtaining a voltage change trend between a current point on the voltage and power curve and a point next to the current point; When the voltage variation trend does not satisfy the monotonicity corresponding to the battery data, an outlier data segment in the battery data is determined according to the voltage variation trends of a second preset number of location points after the next location point.

9. The method according to claim 8, characterized in that The determining of the outlier data segment in the battery data according to the voltage change trend of a second preset number of location points after the next location point includes: When the voltage variation trend of the second preset number of points satisfies the monotonicity, the voltage and electricity curve segment between the current point and the first point among the second preset number of points is used as the outlier data segment; In the case that there is a voltage change trend that does not satisfy the monotonicity among the voltage change trends of the second preset number of position points, the voltage change trends of the second preset number of position points after the last position point that does not satisfy the monotonicity are obtained, until the voltage change trend of the second preset number of position points obtained most recently satisfies the monotonicity, and the voltage and power curve segment between the current position point and the first position point of the second preset number of position points obtained most recently is used as the outlier data segment.

10. The method according to claim 1 or 2, characterized in that The battery data includes battery data generated during multiple battery charge and discharge processes, and the processing of the battery data according to the abnormal data to obtain target battery data includes: For the battery data generated during each battery charge and discharge process, if the abnormal data corresponding to the battery data does not include the battery data segment corresponding to the non-constant current data and includes other abnormal data, the abnormal data in the battery data is removed to obtain remaining battery data; the other abnormal data includes at least one of a battery data segment corresponding to the constant voltage data, an outlier data point, and an outlier data segment; Smoothing the remaining battery data to obtain intermediate battery data; The target battery data is obtained by performing data completion processing on the missing data in the intermediate battery data.

11. A battery data processing device, characterized in that: The device comprises: A detection module, configured to detect battery data during the battery charging and discharging process and obtain a detection result of the battery data; a processing module, configured to, if the detection result indicates that the battery data includes abnormal data, process the battery data according to the abnormal data to obtain target battery data; the abnormal data includes at least one of a battery data segment corresponding to non-constant current data, a battery data segment corresponding to constant voltage data, an outlier data point, and an outlier data segment; and constant current data is data that fluctuates around a fixed current value; The detecting of battery data during the battery charging and discharging process to obtain the detection result of the battery data includes: detecting the battery data according to current data corresponding to the battery data during charging and discharging of the battery to obtain a detection result of the battery data; The detecting the battery data to obtain a detection result of the battery data according to the current data corresponding to the battery data during the charging and discharging process of the battery includes: sorting the current data according to the magnitude of the current data to obtain target current data; determining a current window according to a length of the target current data and a preset length ratio; intercepting the target current data based on the current window to obtain a current data segment; The battery data is detected according to the current data segment to obtain a detection result of the battery data; the detection result includes whether the battery data includes a battery data segment corresponding to non-constant current data.

12. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 10 are implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

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