Battery performance judgment method and device and computer readable storage medium

Abstract

The invention provides a battery performance judgment method and device and a computer readable storage medium, and relates to the field of battery management. The battery performance judgment method comprises the following steps: determining a to-be-detected group consisting of n target batteries including a to-be-detected target battery; for a to-be-detected group formed by n target batteries of the target type of batteries, constructing an individual performance curve of each target battery; taking the time parameter of the to-be-detected target battery in the to-be-detected group as the time parameter of other target batteries except the to-be-detected target battery in the to-be-detected group, and determining the target performance parameter of each target battery in the to-be-detected group on the individual performance curve of other target batteries; and based on the target performance parameter of each target battery in the to-be-detected group, determining whether the target performance of the to-be-detected target battery is qualified. According to the battery performance judgment method, the situation that battery defects are difficult to detect or missed due to time differences of storage, transportation and the like of a large number of batteries is avoided to a great extent.

Description

Technical Field

[0001] The present application relates to the field of battery management, and in particular, to a battery performance determination method, device and computer-readable storage medium. Background Art

[0002] Batteries are widely used in consumer electronics, electric vehicles and energy storage systems. As a key component for energy storage and supply, the performance of batteries directly affects the operating efficiency and stability of terminal equipment. In order to ensure the efficient, reliable and safe operation of batteries, the performance parameters of batteries must be accurately monitored and analyzed.

[0003] At present, after the battery is produced, the relevant performance parameters are measured many times to determine whether a certain performance of the battery meets the requirements. However, the time from the completion of battery production to the battery leaving the warehouse is uncertain, and the time for long-distance transportation is difficult to accurately estimate. When the current quantitative statistical method is used to screen batteries that do not meet the performance requirements, it is easy to cause problems such as over-screening and missed screening during the screening process. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a battery performance judgment method, device and computer-readable storage medium. The battery performance judgment method establishes a performance and parameter model by evaluating the performance of multiple target batteries including the target battery to be detected, and determines whether the performance of the target battery to be detected meets the requirements, thereby greatly avoiding the situation where battery defects of a large number of batteries are difficult to detect or missed due to differences in storage, transportation, etc.

[0005] In a first aspect, an embodiment of the present application provides a battery performance judgment method, which includes: determining a group to be detected consisting of n target batteries including a target battery to be detected; for the group to be detected consisting of n target batteries of a target type of battery, constructing an individual performance curve for each target battery; wherein the individual performance curve characterizes the relationship between the target performance of the target battery and time; based on the time parameters of the target battery to be detected in the group to be detected, on the individual performance curves of other target batteries, determining the target performance parameters of each target battery in the group to be detected; based on the target performance parameters of each target battery in the group to be detected, judging whether the target performance of the target battery to be detected is qualified.

[0006] Optionally, in the embodiment of the present application, based on the time parameter of the target battery to be detected in the group to be detected, on the individual performance curves of other target batteries, the target performance parameter of each target battery in the group to be detected is determined, including: based on the T of the target battery to be detected tm , on the individual performance curves of other target batteries, determine the updated target performance parameters S of other target batteriesnm '; Among them, T tm is the mth target performance parameter S of the target battery to be tested tm The acquisition time is t∈[1,n].

[0007] In the above implementation process, the battery performance judgment method provided by the embodiment of the present application constructs an individual performance curve for each target battery, analyzes and determines in detail the target performance parameters of the target battery to be detected and other batteries in its group, thereby achieving accurate judgment of the performance of the target battery to be detected. The battery performance judgment method provided by the embodiment of the present application can effectively solve the problems of over-screening and missed screening caused by the difficulty of setting thresholds in traditional methods, improve the overall yield rate, and ensure the performance consistency and quality level of battery products. At the same time, by unifying the time parameters, the evaluation is made more accurate and consistent, further improving the reliability and accuracy of battery performance detection.

[0008] Optionally, in an embodiment of the present application, the time parameter includes the acquisition time; for a group to be detected consisting of n target batteries of the target type of battery, constructing an individual performance curve of each target battery, including: determining a basic performance curve of the target type of battery with respect to the target performance based on a sample battery of the target type of battery; according to (S nm , T nm ), the basic performance curve is fitted to obtain the individual performance curve of each target battery; where S nm is the mth target performance parameter of the nth target battery, T nm For S nm The collection time, n and m are positive integers.

[0009] In the above implementation process, the battery performance judgment method provided by the embodiment of the present application can accurately construct the individual performance curve of each target battery. The basic performance curve provides a reliable benchmark, and by fitting the actual measured parameter data, the performance characteristics of each battery can be refined. It can adapt to changes in different batches and usage conditions, and improve the accuracy of battery performance judgment.

[0010] Optionally, in the embodiment of the present application, the target performance parameter includes an open circuit voltage; according to the (S nm , T nm ), fitting the basic performance curve, including: according to each target battery in the group to be tested (V n1 , T n1 )、(V n2 , T n2 ) and (V n3 , T n3), fit the basic performance curve; where V n1 is the first open circuit voltage of the nth target battery, V n2 is the second open circuit voltage of the nth target battery, V n3 is the third open circuit voltage of the nth target battery; T n1 V n1 The acquisition time, T n2 V n2 The sampling time, T n3 V n3 The collection time.

[0011] In the above implementation process, the battery performance judgment method provided in the embodiment of the present application, after obtaining the basic performance curve, measures the open circuit voltage of a large number of target batteries at different times, and then fits the basic curve; it can capture the subtle differences in battery performance over time, and can accurately reflect the individual performance changes of each target battery, thereby improving the judgment accuracy and reliability of the actual performance of the target battery.

[0012] Optionally, in the embodiment of the present application, based on the T tm , on the individual performance curves of other target batteries, determine the updated target performance parameters S of other target batteries nm ', including: based on T t2 , on the individual performance curves of other target batteries, an updated second open circuit voltage V of other target batteries is obtained n2 '; Based on T t3 , on the individual performance curves of other target batteries, an updated third open circuit voltage V of other target batteries is obtained n3 '.

[0013] In the above implementation process, the battery performance judgment method provided by the embodiment of the present application can align the open circuit voltage parameters of all target batteries in the group to be tested to the same time point by determining the updated open circuit voltage on the individual performance curve of each target battery based on a unified time reference, thereby realizing a standardized evaluation of battery performance. This not only improves the feasibility and accuracy of battery performance comparison, but also enhances the fairness of the screening process, ensuring the reliability and accuracy of the performance judgment of the target battery to be tested.

[0014] Optionally, in the embodiment of the present application, the target performance includes a self-discharge rate; based on the target performance parameter of each target battery in the group to be detected, judging whether the target performance of the target battery to be detected is qualified includes: determining the target performance of the target battery to be detected according to the second open circuit voltage V t2 , the third open circuit voltage V of the target battery to be detected t3 and the T of the target battery to be tested t2 With Tt3 The target self-discharge rate of the target battery to be detected is calculated according to the time interval between the updated second open circuit voltages V n2 ', the updated third open circuit voltage V of other target batteries n3 ' and the T of the target battery to be tested t2 With T t3 The time interval between the two targets is used to calculate other self-discharge rates of other target batteries; based on the target self-discharge rate and other self-discharge rates, it is determined whether the self-discharge rate of the target battery to be tested is qualified.

[0015] In the above implementation process, by calculating the self-discharge rate of the target battery and other batteries under a unified time reference, and judging whether the self-discharge rate of the target battery is qualified based on these calculation results, the problem of difficulty in setting the self-discharge rate threshold due to uncertain storage and transportation time can be overcome. The ability to accurately compare the performance changes of batteries within the same time interval avoids the phenomenon of missed screening or misscreening caused by relying solely on traditional experience, thereby improving the accuracy and reliability of the screening process.

[0016] Optionally, in an embodiment of the present application, based on the target self-discharge rate and other self-discharge rates, it is determined whether the self-discharge rate of the target battery to be detected is qualified, including: performing outlier detection on other data points consisting of the updated third open-circuit voltage and other self-discharge rates of other target batteries, and target data points consisting of the third open-circuit voltage and target self-discharge rate of the target battery to be detected; determining whether the target data point is an outlier; if the target data point is an outlier, determining that the target battery to be detected is a battery with an abnormal self-discharge rate.

[0017] In the above implementation process, the battery performance judgment method provided by the embodiment of the present application can accurately identify batteries with significantly abnormal self-discharge rates by performing outlier detection on the data points of other target batteries and the data points of the target battery to be detected, thereby avoiding the problem of difficulty in setting traditional empirical thresholds caused by uncertain storage and transportation time, significantly improving the accuracy and reliability of battery screening, ensuring that only those truly abnormal batteries are excluded, and reducing the phenomenon of misscreening and missed screening.

[0018] Optionally, in an embodiment of the present application, determining a group to be tested consisting of n target batteries including a target battery to be tested includes: taking n as a window, sliding a preset interval in the direction of a newly produced target battery to determine the group to be tested; wherein the target batteries are arranged in order of production.

[0019] In the above implementation process, the battery performance judgment method provided in the embodiment of the present application is particularly suitable for the operation mode under the continuous production line environment. There is no need to stack batteries on a large scale for testing. With its high efficiency and accuracy, it can play an important role in the battery manufacturing process.

[0020] In a second aspect, an embodiment of the present application provides a battery performance judgment device, which includes: a module for determining a group to be detected, a performance curve construction module and a performance detection module; the module for determining the group to be detected is used to determine a group to be detected consisting of n target batteries including a target battery to be detected; the performance curve construction module is used to construct an individual performance curve of each target battery in the group to be detected consisting of n target batteries of a target type of battery; wherein the individual performance curve characterizes the relationship between the target performance of the target battery and time; the performance detection module is used to determine the target performance parameters of each target battery in the group to be detected on the individual performance curves of other target batteries based on the time parameters of the target battery to be detected in the group to be detected; and based on the target performance parameters of each target battery in the group to be detected, determine whether the target performance of the target battery to be detected is qualified.

[0021] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores program instructions, and when the processor reads and runs the program instructions, it executes the steps in any implementation of the above-mentioned battery performance judgment method.

[0022] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer program instructions are stored in the computer-readable storage medium. When the computer program instructions are read and executed by a processor, the steps in any implementation of the above-mentioned battery performance judgment method are executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 A flow chart of battery performance determination provided in an embodiment of the present application;

[0025] Figure 2 A flowchart for constructing an individual performance curve provided in an embodiment of the present application;

[0026] Figure 3 A schematic diagram of a basic curve provided in an embodiment of the present application;

[0027] Figure 4 A schematic diagram of multiple individual function curves of batteries provided in an embodiment of the present application;

[0028] Figure 5An updated open circuit voltage determination schematic diagram provided in an embodiment of the present application;

[0029] Figure 6 A self-discharge rate determination flow chart provided in an embodiment of the present application;

[0030] Figure 7 A flowchart of a judgment example provided in an embodiment of the present application;

[0031] Figure 8 A schematic diagram of outliers provided in an embodiment of the present application;

[0032] Fig. 9 A schematic diagram of a module of a battery performance determination device provided in an embodiment of the present application;

[0033] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings in the embodiments of the present application. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram may represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of boxes in the block diagram and / or the flowchart, can be implemented by a dedicated hardware-based system that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part.

[0035] Faced with global carbon emission challenges, increasing environmental pollution and energy security issues, countries around the world are making every effort to promote the rapid development of the new energy industry, among which battery technology and industry, as a key link, are particularly valued. Batteries have important applications in consumer electronics, electric vehicles and various energy storage systems. As a key component for energy storage and supply, the performance of batteries directly affects the operating efficiency and stability of terminal equipment. In order to ensure the efficient, reliable and safe operation of batteries, the performance parameters of batteries must be accurately monitored and analyzed.

[0036] At present, the traditional method measures the self-discharge rate once or more after the battery is produced. That is, after the battery is produced, the self-discharge rate of the battery is measured once or more, and a threshold of the self-discharge rate is set according to experience or standards to determine whether the battery is qualified. The inventors have found that in this process, since the time from the completion of battery production to the battery being shipped out of the warehouse is uncertain, and the time for long-distance transportation is difficult to accurately estimate, when using traditional quantitative statistical methods for battery screening, it is very difficult to set the threshold, which can easily lead to problems of over-screening and missed screening in the screening process.

[0037] Based on this, the present application proposes a battery performance judgment method, device and computer-readable storage medium. The battery performance judgment method evaluates the performance of multiple target batteries including the target battery to be detected, establishes a model about performance and parameters, and determines whether the performance of the target battery to be detected meets the requirements, which greatly avoids the situation where battery defects of a large number of batteries are difficult to detect or missed due to differences in storage, transportation and other time.

[0038] Please see Figure 1 , Figure 1 The present invention provides a battery performance judgment flow chart of the embodiment of the present invention; the present invention provides a battery performance judgment method, device and computer readable storage medium, the battery performance judgment method can be Fig. 9 electronic devices to perform.

[0039] The battery performance determination method comprises the following steps:

[0040] Step S100: determining a to-be-detected group consisting of n target batteries including the to-be-detected target battery.

[0041] In the above step S100, a group to be detected is first determined, and the group to be detected is composed of n target batteries. It should be noted that the group to be detected needs to cover the target batteries to be detected.

[0042] For example, if there are 10,000 batteries, and n is 1,000, that is, there are 1,000 target batteries in each group to be tested. In addition, there are many ways to select the group to be tested; assuming that the target battery to be tested is the 3,000th battery, then the 2,001st to 3,000th batteries can be taken as the group to be tested; or, the 3,000th to 3,999th batteries can be taken as the group to be tested; or, the 2,501st to 3,500th batteries can be taken as the group to be tested; or, starting from the 100th, at intervals of 3, the 100th, 103rd, 106th, and other target number batteries can be taken as the group to be tested. Of course, there are many other ways to determine the group to be tested, as long as the target battery to be tested is included.

[0043] Step S200: constructing an individual performance curve of each target battery in a to-be-tested group consisting of n target batteries of a target type.

[0044] In the above step S200, for the determined group to be processed, it is necessary to construct an individual performance curve of each target battery in the group to be detected. For example, assuming that n is 1000, there are 1000 target batteries in each group to be detected; then, it is necessary to construct an individual performance curve of each target battery in the 1000 target batteries.

[0045] It is important to understand that even for batteries produced in the same batch, each battery will have certain differences in performance (self-discharge rate, internal resistance, capacity, charge and discharge efficiency, etc.) due to manufacturing process, material consistency, storage time, storage conditions, etc. Constructing an individual performance curve for each battery can accurately understand the performance characteristics of each battery, and then accurately judge the performance of the target battery to be tested.

[0046] Step S300: Based on the time parameters of the target battery to be detected in the group to be detected, the target performance parameters of each target battery in the group to be detected are determined on the individual performance curves of other target batteries.

[0047] In the above step S300, after establishing the individual performance curve of each target battery in the group to be detected, the target performance parameters of the target battery to be detected can be determined from the individual performance curve of the target battery to be detected. Further, the time parameters of the target battery to be detected are used as the time parameters of other target batteries in the group to be detected, so as to determine the target performance parameters of other target batteries in the group to be detected from the individual performance curves of other target batteries.

[0048] Among them, the target performance parameter is a parameter that can reflect (or reflect through calculation) the target performance of the target battery. The target performance can be self-discharge rate, internal resistance, capacity, charge and discharge efficiency, etc. Correspondingly, the target performance parameter corresponding to the self-discharge rate can be voltage change (ΔV) or capacity loss (ΔQ), and the target performance parameter corresponding to the internal resistance can be AC ​​internal resistance (ACIR) or DC internal resistance (DCIR), etc., which can provide important data support for the evaluation and optimization of battery performance.

[0049] In an optional embodiment, in step S300, the time parameter of the target battery to be detected in the group to be detected is used as the time parameter of other target batteries in the group to be detected except the target battery to be detected, and the target performance parameter of each target battery in the group to be detected is determined on the individual performance curves of the other target batteries. This can be achieved in the following way: based on the T of the target battery to be detected tm , on the individual performance curves of other target batteries, determine the updated target performance parameters S of other target batteries nm '; Among them, T tm is the mth target performance parameter S of the target battery to be tested tm Acquisition time, t∈[1,n].

[0050] For example, there are 10,000 batteries, if n is 1,000; assuming that the target battery to be tested is the 3,000th battery, take the 2,001st to 3,000th batteries as the group to be tested. The time parameters of the target battery to be tested are used as the time parameters of other target batteries in the group to be tested, that is, the acquisition time of the target performance parameters of the 3,000th battery is used as the acquisition time of the target performance parameters of the 2,001st to 2,999th batteries.

[0051] In detail, assuming that you want to determine the self-discharge rate of the 3000th battery, you need to measure the parameters of the 3000th battery at different time points, such as the open circuit voltage. Assume that the open circuit voltages at three time points are measured, namely the open circuit voltage at the first time point, the open circuit voltage at the second time point, and the open circuit voltage at the third time point; the time parameters in the above process are the open circuit voltage collection time at the first time point, the open circuit voltage collection time at the second time point, and the open circuit voltage collection time at the third time point. The open circuit voltage collection time is used as the open circuit voltage collection time for the other 999 target batteries, and the target performance parameters of each other target battery in the group to be tested are determined on the individual performance curves of the other target batteries.

[0052] Step S400: Based on the target performance parameters of each target battery in the group to be tested, determining whether the target performance of the target battery to be tested is qualified.

[0053] In the above step S400, it is determined whether the target performance of the target battery to be detected is qualified according to the target performance parameters of each target battery obtained. For example, if the self-discharge rate of the target battery to be detected is evaluated, then the self-discharge rates of all target batteries in a group to be detected are obtained, and based on the self-discharge rates of all target batteries, it is determined whether the self-discharge rate of the target battery to be detected is qualified.

[0054] pass Figure 1 It can be seen that the battery performance judgment method provided in the embodiment of the present application constructs an individual performance curve for each target battery, analyzes and determines in detail the target performance parameters of the target battery to be detected and other batteries in its group, thereby achieving accurate judgment of the performance of the target battery to be detected. The battery performance judgment method provided in the embodiment of the present application can effectively solve the problems of over-screening and missed screening caused by the difficulty of setting thresholds in traditional methods, improve the overall yield rate, and ensure the performance consistency and quality level of battery products. At the same time, by unifying the time parameters, the evaluation is made more accurate and consistent, further improving the reliability and accuracy of battery performance detection.

[0055] Please see Figure 2 , Figure 2 A flowchart for constructing an individual performance curve provided in an embodiment of the present application; in an optional implementation of an embodiment of the present application, the time parameter includes an acquisition time; step S200 is for a group to be detected consisting of n target batteries of a target type of battery, and constructing an individual performance curve for each target battery can be achieved by the following steps:

[0056] Step S210: Based on sample batteries of the target type of battery, determine a basic performance curve of the target type of battery with respect to the target performance.

[0057] In the above step S210, a basic curve of the target type battery with respect to the target performance is determined based on the sample battery of the target type battery. The sample batteries are tested to measure the changes of their target performance parameters (such as self-discharge rate, internal resistance, capacity, charge and discharge efficiency, etc.) at different time points, and a basic curve with respect to the target performance is constructed.

[0058] The number of sample batteries is variable, for example, 10. To determine the number of sample batteries, a smaller number of sample batteries need to be determined to determine the approximate trend of the basic curve of the target performance.

[0059] For example, 10 battery samples are selected from the battery production line. After the battery is formed, it is placed in a constant temperature environment of 25°C for 12 hours. In the next 90 days, the open circuit voltage of each battery is measured every 24 hours, thus forming 900 data points; please refer to Figure 3 , Figure 3A schematic diagram of a basic curve provided in an embodiment of the present application; each battery has one data point per day, the horizontal axis represents the number of days, and the vertical axis represents the open circuit voltage. Figure 3 In the process, the least square method is used to fit these 900 data points to obtain a curve that fits the original data points and has the largest determination coefficient, which is used as the benchmark function curve of the open circuit voltage of this model battery over time.

[0060] Step S220: Based on the (S nm , T nm ), the basic performance curve is fitted to obtain the individual performance curve of each target battery.

[0061] Among them, S nm is the mth target performance parameter of the nth target battery, T nm For S nm The collection time, n and m are positive integers.

[0062] In the above step S220, the performance parameters of each target battery in the detection group are collected, specifically, the target performance parameters (S nm ) and its acquisition time (T nm ), where n is the battery number and m is the parameter number.

[0063] Use the collected data points to compare and fit with the basic performance curve. Through fitting, the basic performance curve can be adjusted to more accurately reflect the individual performance of each target battery. Among them, the fitting process may involve the use of statistical methods (linear regression), curve fitting algorithms (polynomial fitting, exponential fitting, etc.) or machine learning techniques (neural network algorithms, support vector regression, etc.) to ensure that the individual performance curves obtained reflect the true performance of each target battery as accurately as possible.

[0064] pass Figure 2 It can be seen that the battery performance judgment method provided in the embodiment of the present application can accurately construct the individual performance curve of each target battery. The basic performance curve provides a reliable benchmark, and by fitting the actual measured parameter data, the performance characteristics of each battery can be refined. It can adapt to changes in different batches and usage conditions, and improve the accuracy of battery performance judgment.

[0065] In an optional embodiment, the target performance parameter includes an open circuit voltage. In order to detect the self-discharge rate of the battery, it is necessary to measure the open circuit voltage of the battery.

[0066] In step S220, according to the (S nm , T nm), the basic performance curve can be fitted by the following method: according to the (V n1 , T n1 )、(V n2 , T n2 ) and (V n3 , T n3 ), and fit the basic performance curve.

[0067] Among them, V n1 is the first open circuit voltage of the nth target battery, V n2 is the second open circuit voltage of the nth target battery, V n3 is the third open circuit voltage of the nth target battery; T n1 V n1 The acquisition time, T n2 V n2 The acquisition time, T n3 V n3 The collection time.

[0068] The self-discharge rate of a battery refers to the rate at which the battery naturally loses its charge due to internal chemical reactions when not in use. The self-discharge rate is one of the important indicators for measuring the energy storage performance of a battery, and directly affects the storage life and availability of the battery.

[0069] For self-discharge rate measurement, the battery can be fully charged and then disconnected from the circuit, the open circuit voltage of the battery can be measured regularly, the voltage change over time can be recorded, and the self-discharge rate can be estimated by the rate at which the voltage drops. Alternatively, the battery can be fully charged and stored for a period of time, and then its remaining capacity can be measured; the capacity loss ratio during storage can be calculated to obtain the self-discharge rate. Alternatively, a precision instrument can be used to directly measure the self-discharge current of the battery, and the self-discharge rate can be calculated by current and time. In the embodiment of the present application, the self-discharge rate of the battery is calculated by measuring the open circuit voltage of the battery at different times.

[0070] In the above implementation process, in order to study the open circuit voltage, according to the (S nm , T nm ), and fit the obtained basic performance curve.

[0071] Assume that the voltage of each target battery is measured three times, and the voltage corresponding to these three measurements is the first open circuit voltage V in this embodiment of the application. n1 , the second open circuit voltage V n2 and the third open circuit voltage V n3For example, there are 10,000 batteries, if n is 1000; assuming that the target battery to be tested is the 3000th battery, take the 2001st to 3000th batteries as the group to be tested. Then, for the 2001th battery, its first open circuit voltage, second open circuit voltage and third open circuit voltage are V (2001)1 、V (2001)2 、V (2001)3 , the corresponding first open circuit voltage V (2001) The acquisition time is T (2001)1 , The second open circuit voltage acquisition time The open circuit voltage acquisition time T (2001)2 The third open circuit voltage acquisition time is T (2001)3 Then, there are three sets of data for each battery, namely three open circuit voltages and corresponding acquisition times.

[0072] It should be noted that the first open circuit voltage is generally the temperature of the normal temperature environment after the battery is formed; for example, after the battery is left in a constant temperature environment of 25°C for 12 hours after formation, its first open circuit voltage is recorded. The second open circuit voltage is generally recorded when the battery completes all production tests and is put into storage. The third open circuit voltage is generally measured again after the battery leaves the warehouse and before the battery is put into use.

[0073] Further, for each target battery, based on the data point (V n1 , T n1 )、(V n2 , T n2 )、(V n3 , T n3 ) three sets of data, through the nonlinear least squares fitting method, construct an individual function curve of the open circuit voltage changing with time for each battery; please refer to Figure 4 , Figure 4 A schematic diagram of multiple individual battery function curves provided in an embodiment of the present application; Figure 4 In the figure, the vertical axis is the open circuit voltage (v), the horizontal axis is the acquisition time (days), and the functions of different colors represent non-universal target batteries; Figure 4 It can be seen that the acquisition time of the third open circuit voltage of different batteries may vary greatly. The reason is that the time when different batteries are put into use is different.

[0074] It can be seen that the battery performance judgment method provided in the embodiment of the present application, after obtaining the basic performance curve, measures the open circuit voltage of a large number of target batteries at different times, and then fits the basic curve; it can capture the subtle differences in battery performance over time, and can accurately reflect the individual performance changes of each target battery, thereby improving the judgment accuracy and reliability of the actual performance of the target battery.

[0075] In an optional embodiment, based on the T tm , on the individual performance curves of other target batteries, determine the updated target performance parameters S of other target batteries nm ', can be achieved by:

[0076] Based on T t2 , on the individual performance curves of other target batteries, an updated second open circuit voltage V of other target batteries is obtained n2 '; Based on T t3 , on the individual performance curves of other target batteries, an updated third open circuit voltage V of other target batteries is obtained n3 '.

[0077] Please refer to Figure 5 , Figure 5 The schematic diagram for determining the open circuit voltage provided in the embodiment of the present application is updated; assuming that T t2 For the 9th day, T t3 is the 58th day; Figure 5 As shown, the updated second open circuit voltage V on the individual function curve of each battery is determined with the 9th day and the 58th day as the horizontal coordinates. n2 '( Figure 5 The blue dashed line in the middle) and the updated third open circuit voltage V n3 '( Figure 5 The red dotted line in the middle). Then the time for re-determining the open circuit voltage of all batteries is the 9th day and the 58th day, so that the corresponding open circuit voltages of all target batteries in the group to be tested are determined to the same time reference.

[0078] pass Figure 5 It can be seen that the battery performance judgment method provided in the embodiment of the present application can align the open circuit voltage parameters of all target batteries in the group to be tested to the same time point by determining the updated open circuit voltage on the individual performance curve of each target battery based on a unified time reference, thereby realizing a standardized evaluation of battery performance. This not only improves the feasibility and accuracy of battery performance comparison, but also enhances the fairness of the screening process, ensuring the reliability and accuracy of the performance judgment of the target battery to be tested.

[0079] Please see Figure 6 , Figure 6 A self-discharge rate determination flow chart provided in an embodiment of the present application; in an optional embodiment, the above step S400 determines whether the target performance of the target battery to be detected is qualified based on the target performance parameters of each target battery in the group to be detected, which can be achieved by the following steps:

[0080] Step S410: According to the second open circuit voltage V of the target battery to be detectedt2 , the third open circuit voltage V of the target battery to be detected t3 and the T of the target battery to be tested t2 With T t3 The target self-discharge rate of the target battery to be detected is calculated based on the time interval between the two.

[0081] Step S420: Update the second open circuit voltage V of other target batteries n2 ', the updated third open circuit voltage V of other target batteries n3 ' and the T of the target battery to be tested t2 With T t3 The time interval between the two targets is used to calculate other self-discharge rates of other target batteries.

[0082] Step S430: Based on the target self-discharge rate and other self-discharge rates, determine whether the self-discharge rate of the target battery to be tested is qualified.

[0083] In the above steps S410 to S430, for the target battery, the self-discharge rate of the target battery is The self-discharge rate of other batteries is Furthermore, based on k t and k n Determine k t Is the self-discharge rate qualified?

[0084] pass Figure 6 It can be seen that by calculating the self-discharge rate of the target battery and other batteries under a unified time base, and judging whether the self-discharge rate of the target battery is qualified based on these calculation results, the problem of difficulty in setting the self-discharge rate threshold due to uncertain storage and transportation time can be overcome. The ability to accurately compare the performance changes of batteries within the same time interval avoids the phenomenon of missed screening or misscreening caused by relying solely on traditional experience, thereby improving the accuracy and reliability of the screening process.

[0085] Please see Figure 7 , Figure 7 A flowchart of a judgment example provided in an embodiment of the present application; in an optional implementation of an embodiment of the present application, the above step S430 judges whether the self-discharge rate of the target battery to be detected is qualified based on the target self-discharge rate and other self-discharge rates, which can be achieved by the following steps:

[0086] Step S431: outlier detection is performed using other data points consisting of the updated third open circuit voltages and other self-discharge rates of other target batteries and target data points consisting of the third open circuit voltage and target self-discharge rate of the target battery to be detected.

[0087] In the above step S431, the updated third open circuit voltage (Vn3 ') and self-discharge rate (k n ) as other data points, the third open circuit voltage (V t3 ) and self-discharge rate (k t ) as the target data point.

[0088] Further, these data points are analyzed using statistical methods (such as box plots, Z-score, DBSCAN, etc.) to find out which data points deviate significantly from the overall data distribution. Outliers are points that are significantly different from other data points in a given data set, usually representing anomalies or extreme values.

[0089] Step S432: Determine whether the target data point is an outlier.

[0090] Step S433: If the target data point is an outlier, the target battery to be detected is determined to be a battery with an abnormal self-discharge rate.

[0091] In the above steps S432-S433, it is determined whether the target data point is an outlier. Figure 8 , Figure 8 A schematic diagram of outliers provided in an embodiment of the present application; Figure 8 In the figure, the horizontal axis is the open circuit voltage, the vertical axis is the self-discharge rate, the blue points are outliers, and the black points are non-outliers; the batteries can be screened through machine learning, such as using algorithms such as isolation forest, K-means clustering or local outlier factor to identify outliers in the data; the batteries corresponding to the outliers are considered to be potential defective batteries, while non-outlier batteries are judged to be normal. Therefore, if the data point corresponding to the target battery to be tested (target data point) falls into the outlier area, it can be concluded that the battery is defective; conversely, if the target data points are distributed in the normal area, the battery quality is judged to be qualified.

[0092] Assume the following data points: Other target battery data points (V n3 ', k n ): (3.9V, 0.02 / day), (4.0V, 0.015 / day), (3.95V, 0.018 / day), (4.1V, 0.02 / day)...; target battery data points to be tested (V t3 , k t ): (3.7V, 0.05 / day); In the data set, the self-discharge rate of the target battery to be tested (0.05 / day) is significantly higher than the self-discharge rate data distribution range of other batteries (0.015-0.02 / day). Through outlier detection, it is found that the self-discharge rate of the target battery to be tested is inconsistent with most data points, and the self-discharge rate of the target battery is marked as an outlier.

[0093] pass Figure 7 It can be seen that the battery performance judgment method provided by the embodiment of the present application can accurately identify batteries with significantly abnormal self-discharge rates by performing outlier detection on the data points of other target batteries and the data points of the target battery to be detected, thereby avoiding the problem of difficulty in setting traditional empirical thresholds caused by uncertain storage and transportation time, significantly improving the accuracy and reliability of battery screening, ensuring that only those truly abnormal batteries are excluded, and reducing the phenomenon of misscreening and missed screening.

[0094] In an optional embodiment, the mean μ and standard deviation σ of other target battery self-discharge rates may also be calculated, and the mean and standard deviation may be used to construct an evaluation criterion. For example, a reasonable threshold range may be set based on the mean, and μ±2σ may usually be used as the judgment criterion.

[0095] If k t In the range of μ±2σ, if k t If k is within the range of μ±2σ, the self-discharge rate of the target battery to be tested is considered qualified. t If it is not within the range of μ±2σ, the self-discharge rate of the target battery to be tested is considered abnormal.

[0096] In an optional embodiment, the determination of the to-be-detected group consisting of n target batteries including the to-be-detected target battery in the above step S100 may be implemented in the following manner:

[0097] With n as the window, slide the preset interval towards the newly produced target batteries to determine the group to be tested; wherein the target batteries are arranged in the order of production.

[0098] In the above implementation process, a window of size n is first selected and slid toward the newly produced batteries at a certain preset interval. Arranged in the production order, each sliding window will cover the new batteries and some of the batteries that have been tested.

[0099] For example, assume that there are 10,000 batteries on the production line, the window size n is 1,000, and the preset interval is 500. For example, the initial window position: the 1st to 1,000th battery, the group 1 to be tested: the 1st to 1,000th battery. The window slides 500 batteries, the window position: the 501st to 1,500th battery, the group 2 to be tested: the 501st to 1,500th battery. The window slides another 500 batteries, the window position: the 1,001st to 2,000th battery, the group 3 to be tested: the 1,001st to 2,000th battery. And so on, the window slides 500 batteries each time until all the produced batteries are covered.

[0100] Commonly, in actual operation, 1 is often used as the preset interval, for example, initial window position: 1st to 1000th battery, group 1 to be tested: 1st to 1000th battery. The window slides 1 battery, the window position: 2nd to 1001st battery, group 2 to be tested: 2nd to 1001st battery. The window slides 1 battery again, the window position: 3rd to 1002nd battery, group 3 to be tested: 3rd to 1002nd battery.

[0101] It can be seen that the battery performance judgment method provided in the embodiment of the present application is particularly suitable for the operation mode under the continuous production line environment. There is no need to stack batteries on a large scale for testing. With its efficient and accurate characteristics, it can play an important role in the battery manufacturing process.

[0102] In an optional embodiment, for non-assembly line production methods, the battery performance judgment method provided in the embodiment of the present application is also applicable, and a step-by-step moving window selection strategy is not adopted. Whenever a certain number of batteries is reached, these batteries are used for screening. That is to say, the data of the 1st to nth batteries are used to judge the 1st to nth batteries, and then the data of the n+1th to 2n+1th batteries are used to judge the n+1th to 2n+1th batteries, and so on.

[0103] Please see Fig. 9 , Fig. 9 This is a module diagram of a battery performance judgment device provided in an embodiment of the present application; the present application also provides a battery performance judgment device, the battery performance judgment device 100 includes a module 110 for determining a group to be detected, a performance curve construction module 120 and a performance detection module 130.

[0104] The to-be-detected group determining module 110 is used to determine a to-be-detected group consisting of n target batteries including the to-be-detected target battery.

[0105] The performance curve construction module 120 is used to construct an individual performance curve of each target battery in a to-be-tested group consisting of n target batteries of a target type of battery; wherein the individual performance curve represents the relationship between the target performance of the target battery and time.

[0106] The performance detection module 130 is used to determine the target performance parameters of each target battery in the group to be detected based on the time parameters of the target battery to be detected in the group to be detected and on the individual performance curves of other target batteries; based on the target performance parameters of each target battery in the group to be detected, determine whether the target performance of the target battery to be detected is qualified.

[0107] In an optional embodiment, the time parameter includes the acquisition time; in the process of constructing the individual performance curve of each target battery in the group to be detected consisting of n target batteries of the target type, the performance curve construction module 120 is used to: determine the basic performance curve of the target type battery with respect to the target performance based on the sample battery of the target type battery; according to the (S nm , T nm ), the basic performance curve is fitted to obtain the individual performance curve of each target battery; where S nm is the mth target performance parameter of the nth target battery, T nm For S nm The collection time, n and m are positive integers.

[0108] In an optional embodiment, in the process of determining the target performance parameter of each target battery in the group to be detected based on the time parameter of the target battery to be detected in the group to be detected and on the individual performance curves of other target batteries, the performance detection module 130 is used to: tm , on the individual performance curves of other target batteries, determine the updated target performance parameters S of other target batteries nm '; Among them, T tm is the mth target performance parameter S of the target battery to be tested tm The acquisition time is t∈[1,n].

[0109] In an optional embodiment, the target performance parameter includes an open circuit voltage; according to the (S nm , T nm ), in the process of fitting the basic performance curve, the performance curve building module 120 is used to: according to the (V n1 , T n1 )、(V n2 , T n2 ) and (V n3 , T n3 ), fit the basic performance curve; where V n1 is the first open circuit voltage of the nth target battery, V n2 is the second open circuit voltage of the nth target battery, V n3 is the third open circuit voltage of the nth target battery; T n1 V n1 The acquisition time, T n2 V n2 The sampling time, T n3 V n3 The collection time.

[0110] In an optional embodiment, based on the T of the target battery to be detected tm , on the individual performance curves of other target batteries, determine the updated target performance parameters S of other target batteries nm ', the performance detection module 130 is used to: based on T t2 , on the individual performance curves of other target batteries, an updated second open circuit voltage V of other target batteries is obtained n2 '; Based on T t3 , on the individual performance curves of other target batteries, an updated third open circuit voltage V of other target batteries is obtained n3 '.

[0111] In an optional embodiment, the target performance includes a self-discharge rate; in the process of judging whether the target performance of the target battery to be detected is qualified based on the target performance parameter of each target battery in the group to be detected, the performance detection module 130 is used to: t2 , the third open circuit voltage V of the target battery to be detected t3 and the T of the target battery to be tested t2 With T t3 The target self-discharge rate of the target battery to be detected is calculated according to the time interval between the updated second open circuit voltages V n2 ', the updated third open circuit voltage V of other target batteries n3 ' and the T of the target battery to be tested t2 With T t3 The time interval between the two targets is used to calculate other self-discharge rates of other target batteries; based on the target self-discharge rate and other self-discharge rates, it is determined whether the self-discharge rate of the target battery to be tested is qualified.

[0112] In an optional embodiment, in the process of judging whether the self-discharge rate of the target battery to be detected is qualified based on the target self-discharge rate and other self-discharge rates, the performance detection module 130 is used to: perform outlier detection using other data points consisting of the updated third open-circuit voltage and other self-discharge rates of other target batteries, and target data points consisting of the third open-circuit voltage and target self-discharge rate of the target battery to be detected; judge whether the target data point is an outlier; if the target data point is an outlier, determine that the target battery to be detected is a battery with an abnormal self-discharge rate.

[0113] In an optional embodiment, in the process of determining a group to be inspected consisting of n target batteries including a target battery to be inspected, the module 110 for determining the group to be inspected is used to: use n as a window and slide a preset interval in the direction of the newly produced target battery to determine the group to be inspected; wherein the target batteries are arranged in the order of production.

[0114] See also Fig.10 , Fig.10 The electronic device 200 provided in the embodiment of the present application includes: a processor 201 and a memory 202, wherein the memory 202 stores machine-readable instructions executable by the processor 201, and when the machine-readable instructions are executed by the processor 201, the above method is executed.

[0115] Based on the same inventive concept, an embodiment of the present application also provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are read and executed by a processor, the steps in any implementation of the above-mentioned battery performance judgment method are executed.

[0116] The computer-readable storage medium may be a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or any other medium that can store program code.

[0117] In this article, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0118] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining battery performance, characterized in that: The battery performance judgment method comprises: Determine a to-be-detected group consisting of n target batteries including the to-be-detected target battery; For a group to be tested consisting of n target batteries of a target type of battery, construct an individual performance curve for each target battery; wherein the individual performance curve represents the relationship between the target performance of the target battery and time; Based on the time parameters of the target batteries to be detected in the group to be detected, on the individual performance curves of other target batteries, determining the target performance parameters of each of the target batteries in the group to be detected; Based on the target performance parameter of each of the target batteries in the group to be tested, it is determined whether the target performance of the target battery to be tested is qualified.

2. The method according to claim 1, characterized in that in, The time parameter includes the acquisition time; the individual performance curve of each target battery is constructed for the group to be detected consisting of n target batteries of the target type, including: Determining a basic performance curve of the target type battery with respect to the target performance based on a sample battery of the target type battery; According to the (S nm , T nm ), fitting the basic performance curve to obtain the individual performance curve of each target battery; wherein S nm is the mth target performance parameter of the nth target battery, T nm For the S nm The collection time, n and m are positive integers.

3. The method according to claim 2, characterized in that The step of determining the target performance parameter of each target battery in the group to be detected based on the time parameter of the target battery to be detected in the group to be detected on the individual performance curves of the other target batteries includes: Based on the T of the target battery to be detected tm , on the individual performance curves of the other target batteries, determine the updated target performance parameters S of the other target batteries nm '; Among them, T tm is the mth target performance parameter S of the target battery to be tested tm The acquisition time is t∈[1,n].

4. The method according to claim 3, characterized in that in, The target performance parameter includes an open circuit voltage; the (S nm , T nm ), fitting the basic performance curve, including: According to the (V n1 , T n1 )、(V n2 , T n2 ) and (V n3 , T n3 ), fitting the basic performance curve; Among them, V n1 is the first open circuit voltage of the nth target battery, V n2 is the second open circuit voltage of the nth target battery, V n3 is the third open circuit voltage of the nth target battery; T n1 For the V n1 The acquisition time, T n2 For the V n2 The sampling time, T n3 For the V n3 The collection time.

5. The method according to claim 4, characterized in that The T of the target battery to be detected tm , on the individual performance curves of the other target batteries, determine the updated target performance parameters S of the other target batteries nm ',include: Based on T t2 , on the individual performance curves of the other target batteries, an updated second open circuit voltage V of the other target batteries is obtained n2 '; Based on T t3 , on the individual performance curves of the other target batteries, an updated third open circuit voltage V of the other target batteries is obtained n3 '.

6. The method according to claim 5, characterized in that in, The target performance includes a self-discharge rate; and judging whether the target performance of the target battery to be tested is qualified based on the target performance parameter of each target battery in the group to be tested includes: According to the second open circuit voltage V of the target battery to be detected t2 , the third open circuit voltage V of the target battery to be detected t3 and the T of the target battery to be detected t2 With T t3 The time interval between the two, calculating the target self-discharge rate of the target battery to be detected; According to the updated second open circuit voltage V of the other target battery n2 ', the updated third open circuit voltage V of the other target battery n3 ' and the T of the target battery to be detected t2 With T t3 The time interval between the other target batteries is used to calculate other self-discharge rates of the other target batteries; Based on the target self-discharge rate and other self-discharge rates, it is determined whether the self-discharge rate of the target battery to be tested is qualified.

7. The method according to claim 6, characterized in that The step of judging whether the self-discharge rate of the target battery to be detected is qualified based on the target self-discharge rate and other self-discharge rates includes: Perform outlier detection using other data points consisting of the updated third open circuit voltage and the other self-discharge rate of the other target battery and target data points consisting of the third open circuit voltage and the target self-discharge rate of the target battery to be detected; Determine whether the target data point is an outlier; If the target data point is an outlier, the target battery to be detected is determined to be a battery with an abnormal self-discharge rate.

8. The method according to claim 1, characterized in that: The step of determining a group to be detected consisting of n target batteries including the target battery to be detected comprises: Taking n as a window, slide a preset interval in the direction of the newly produced target batteries to determine the group to be tested; wherein the target batteries are arranged in the order of production.

9. A battery performance judgment device, characterized in that: The battery performance judgment device comprises: a to-be-detected group determination module, a performance curve construction module and a performance detection module; The to-be-detected group determination module is used to determine a to-be-detected group consisting of n target batteries including the to-be-detected target battery; The performance curve building module is used to build an individual performance curve of each target battery in a to-be-tested group consisting of n target batteries of a target type of battery; wherein the individual performance curve represents the relationship between the target performance of the target battery and time; The performance detection module is used to determine the target performance parameters of each target battery in the group to be detected on the individual performance curves of the other target batteries based on the time parameters of the target battery to be detected in the group to be detected; and to judge whether the target performance of the target battery to be detected is qualified based on the target performance parameters of each target battery in the group to be detected.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the steps in the method according to any one of claims 1 to 8 are executed.

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