Method, device, equipment, storage medium and program product for detecting lithium plating of battery

Abstract

The present application relates to a method, device, equipment, storage medium and program product for detecting lithium plating of a battery. The method includes: determining a capacity loss step of a target battery according to charge and discharge test data of the target battery, and determining an accumulated capacity loss value of the target battery within a plurality of detection cycles according to the capacity loss step and the charge and discharge test data, and then determining the lithium plating state of the target battery according to the accumulated capacity loss value of the target battery within the plurality of detection cycles. Wherein, the capacity loss step includes at least one data cycle of the charge and discharge test data. In the above method, the capacity loss step includes at least one data cycle, which increases the cycle span for measuring the battery capacity loss, enables the battery capacity loss to be accumulated, and the value becomes larger, making it easier to detect and determine whether lithium plating occurs, and improving the sensitivity of lithium plating detection.

Description

Technical Field

[0001] This application relates to the technical field of battery detection, and particularly to a method, device, equipment, storage medium and program product for detecting lithium plating of a battery. Background Art

[0002] Lithium plating of a battery refers to the phenomenon that metallic lithium is deposited on the anode surface of a lithium-ion battery during long-term charge and discharge in a low-temperature environment. The entire process of lithium plating of a battery is irreversible. If this continues for a long time, it will not only damage the battery, but also pose a safety risk to the battery.

[0003] In the traditional technology, the average voltage change caused by lithium plating of a battery is usually used to determine whether lithium plating has occurred in the battery.

[0004] However, the sensitivity of the lithium plating detection method in the traditional technology is poor. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a method, device, equipment, storage medium and program product for detecting lithium plating of a battery, which can improve the sensitivity of lithium plating detection.

[0006] In a first aspect, an embodiment of the present application provides a method for detecting lithium plating of a battery, the method comprising:

[0007] Determining a capacity loss step of a target battery according to charge and discharge test data of the target battery; the capacity loss step includes at least one data cycle period of the charge and discharge test data;

[0008] Determining an accumulated capacity loss value of the target battery within a plurality of detection periods according to the capacity loss step and the charge and discharge test data; the duration of the detection period is equal to the capacity loss step;

[0009] Determining the lithium plating state of the target battery according to the accumulated capacity loss value of the target battery within a plurality of detection periods.

[0010] In an embodiment of the present application, by determining the capacity loss step of the target battery according to the charge and discharge test data of the target battery, and determining the accumulated capacity loss value of the target battery within a plurality of detection periods according to the capacity loss step and the charge and discharge test data, and then determining the lithium plating state of the target battery according to the accumulated capacity loss value of the target battery within a plurality of detection periods. Among them, the capacity loss step includes at least one data cycle period of the charge and discharge test data, and the duration of the detection period is equal to the capacity loss step. In this method, the capacity loss step includes at least one data cycle period, which increases the cycle span for measuring the battery capacity loss, enables the battery capacity loss to be accumulated, the value becomes larger, and it is easier to detect and determine whether lithium plating has occurred, thereby improving the sensitivity of lithium plating detection.

[0011] In one embodiment, determining the capacity loss step of the target battery according to the charge-discharge test data of the target battery includes:

[0012] Obtaining the data cycle period of the charge-discharge test data according to the charge-discharge test data of the target battery;

[0013] Determining the capacity loss step according to the data cycle period and the preset configuration strategy.

[0014] In the embodiment of the present application, by obtaining the data cycle period of the charge-discharge test data of the target battery and the preset configuration strategy, corresponding capacity loss steps are configured for different data cycle periods, improving the matching degree of the determined capacity loss step with the charge-discharge test data with different periodic characteristics, and further improving the accuracy of lithium plating detection.

[0015] In one embodiment, obtaining the data cycle period of the charge-discharge test data according to the charge-discharge test data of the target battery includes:

[0016] Classifying the charge-discharge test data to obtain first charge-discharge test data and second charge-discharge test data; wherein, the first charge-discharge test data and the second charge-discharge test data respectively represent the charge-discharge test data obtained under different charge-discharge test methods;

[0017] Determining the data cycle period of the charge-discharge test data according to the first charge-discharge test data and the second charge-discharge test data.

[0018] In the embodiment of the present application, by classifying the charge-discharge test data, first charge-discharge test data and second charge-discharge test data obtained under different charge-discharge test methods are obtained, and then the data cycle period of the charge-discharge test data is determined according to the first charge-discharge test data and the second charge-discharge test data. This method divides the charge-discharge test data into two types of charge-discharge test data through classification processing, prepares data for subsequent determination of the data cycle period, so as to more efficiently determine the data cycle period and improve the efficiency of lithium plating detection.

[0019] In one embodiment, classifying the charge-discharge test data to obtain first charge-discharge test data and second charge-discharge test data includes:

[0020] Performing linear fitting processing on the charge-discharge test data to obtain a first fitting line and a second fitting line;

[0021] Determining the midline between the first fitting line and the second fitting line;

[0022] Take the charge-discharge test data on one side of the midline as the first charge-discharge test data, and take the charge-discharge test data on the other side of the midline as the second charge-discharge test data.

[0023] In the embodiments of the present application, by performing linear fitting processing on the charge-discharge test data, a first fitting line and a second fitting line are obtained, and then the midline between the first fitting line and the second fitting line is determined, so as to take the charge-discharge test data on both sides of the midline as the first charge-discharge test data and the second charge-discharge test data respectively. In this method, the charge-discharge test data is divided into the first charge-discharge test data and the second charge-discharge test data by means of linear fitting processing. The processing process is simple and easy to be implemented by computer equipment, which improves the processing efficiency and the classification accuracy at the same time.

[0024] In one of the embodiments, determining the data cycle period of the charge-discharge test data according to the first charge-discharge test data and the second charge-discharge test data includes:

[0025] Determine the first data volume according to the first charge-discharge test data, and determine the second data volume according to the second charge-discharge test data;

[0026] Obtain the data volume ratio of the first data volume and the second data volume;

[0027] Determine the sum of the numerator and the denominator in the data volume ratio as the data cycle period.

[0028] In the embodiments of the present application, by respectively counting the data volumes of the first charge-discharge test data and the second charge-discharge test data, and taking the sum of the numerator and the denominator in the data volume ratio corresponding to the obtained first data volume and the second data volume as the data cycle period. In this method, the data cycle period is obtained quickly and accurately based on the data statistics method, which provides a data basis for subsequent lithium plating detection and improves the efficiency and accuracy of lithium plating detection.

[0029] In one of the embodiments, the preset configuration strategy includes a preset period threshold. Determining the capacity loss step length according to the data cycle period and the preset configuration strategy includes:

[0030] Obtain the comparison result between the data cycle period and the period threshold;

[0031] Determine the cumulative coefficient according to the comparison result;

[0032] Determine the capacity loss step length according to the cumulative coefficient and the data cycle period.

[0033] In the embodiments of the present application, by obtaining the comparison result between the data cycle period and the period threshold, the cumulative coefficient is determined according to the comparison result, and then the capacity loss step size is determined from the cumulative coefficient and the data cycle period. In this method, through comparison, segmented configuration for different data cycle periods is achieved, simplifying the configuration strategy, reducing the time consumed for determining the capacity loss step size, and improving the overall detection efficiency.

[0034] In one of the embodiments, determining the capacity loss step size from the cumulative coefficient and the data cycle period includes:

[0035] Obtaining the product of the cumulative coefficient and the data cycle period as the capacity loss step size.

[0036] In the embodiments of the present application, by calculating the product of the cumulative coefficient and the data cycle period as the capacity loss step size. In this method, the calculation method for determining the capacity loss step size is simple and direct, which helps to improve the efficiency of lithium plating detection.

[0037] In one of the embodiments, the charge-discharge test data includes the battery charge capacity and the battery discharge capacity;

[0038] Determining the cumulative capacity loss value of the target battery in multiple detection periods according to the capacity loss step size and the charge-discharge test data includes:

[0039] Obtaining the average battery charge capacity and the average battery discharge capacity of each detection period according to the capacity loss step size;

[0040] Obtaining the cumulative capacity loss value of the target battery in multiple detection periods according to the ratio between the average battery charge capacity and the average battery discharge capacity in each detection period.

[0041] In the embodiments of the present application, by obtaining the average battery charge capacity and the average battery discharge capacity of each detection period according to the capacity loss step size, and obtaining the cumulative capacity loss value of the target battery in multiple detection periods according to the ratio between the average battery charge capacity and the average battery discharge capacity in each detection period. In this method, the way of calculating the average value does not require calculating the cumulative capacity loss value for each battery charge capacity and battery discharge capacity, reducing the calculation amount and thus improving the test efficiency.

[0042] In one of the embodiments, determining the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery in multiple detection periods includes:

[0043] Determining a first capacity loss value curve according to the cumulative capacity loss value of the target battery in multiple detection periods;

[0044] If there is a first target point on the first capacity loss value curve whose slope is greater than a preset slope threshold, it is determined that lithium plating occurs in the target battery during the target test cycle corresponding to the cumulative capacity loss value at the first target point.

[0045] In the embodiments of the present application, by determining the first capacity loss value curve based on the cumulative capacity loss values of the target battery in multiple detection cycles, and when there is a first target point on the first capacity loss value curve whose slope is greater than a preset slope threshold, it is determined that lithium plating occurs in the target battery during the target test cycle corresponding to the cumulative capacity loss value at the first target point. In this method, the slope can directly represent the change amount of the cumulative capacity loss value and is helpful for the implementation of computer programs. Therefore, the accurate determination of the target test cycle in which the target battery undergoes lithium plating is achieved, improving the detection efficiency while ensuring the accuracy of the detection.

[0046] In one of the embodiments, the charge-discharge test data includes the battery charging capacity and the battery discharging capacity;

[0047] Determining the cumulative capacity loss value of the target battery in multiple detection cycles according to the capacity loss step and the charge-discharge test data includes:

[0048] Determining the cumulative capacity loss value of the target battery in multiple detection cycles according to the battery charging capacity at the nth test timing and the battery discharging capacity at the (n + x)th test timing; where n is the test timing and x is the capacity loss step.

[0049] In the embodiments of the present application, the cumulative capacity loss value of the target battery in multiple detection cycles is determined according to the battery charging capacity at the nth test timing and the battery discharging capacity at the (n + x)th test timing. Where n is the test timing and x is the capacity loss step. In this method, the battery charging capacity and the battery discharging capacity with a cycle span are used to determine the cumulative capacity loss value, realizing the accumulation of the battery capacity loss and improving the sensitivity of lithium plating detection.

[0050] In one of the embodiments, determining the lithium plating state of the target battery according to the cumulative capacity loss values of the target battery in multiple detection cycles includes:

[0051] According to the data arrangement timing in each detection cycle, the cumulative capacity loss values located at the same data arrangement timing are divided into the same group to obtain multiple reference cycle groups of the target battery;

[0052] Determining the lithium plating state of the target battery according to the cumulative capacity loss values in multiple reference cycle groups of the target battery.

[0053] In the embodiments of the present application, by arranging the data in each detection period in chronological order, the cumulative capacity loss values at the same data arrangement chronological order are divided into the same group, obtaining multiple reference period groups of the target battery, and then determining the lithium plating state of the target battery according to the cumulative capacity loss values in the multiple reference period groups of the target battery. In this method, for each detection period, the charge-discharge test data at the same data arrangement chronological order have the same data characteristics, and the corresponding cumulative capacity loss values also have the same data characteristics. After grouping, the cumulative capacity loss values with the same data characteristics within the group are used to determine the lithium plating state of the target battery, which can effectively improve the accuracy and reliability of lithium plating detection.

[0054] In one of the embodiments, determining the lithium plating state of the target battery according to the cumulative capacity loss values in the multiple reference period groups of the target battery includes:

[0055] According to the multiple cumulative capacity loss values in each reference period group, determine the second capacity loss value curve corresponding to each reference period group;

[0056] According to the second capacity loss value curves corresponding to each reference period group, obtain the target second capacity loss value curve with the largest slope;

[0057] Determine the lithium plating state of the target battery according to the target second capacity loss value curve and a preset slope threshold.

[0058] In the embodiments of the present application, by determining the second capacity loss value curve corresponding to each reference period group according to the multiple cumulative capacity loss values in each reference period group, and then obtaining the target second capacity loss value curve with the largest slope therefrom, to determine the lithium plating state of the target battery according to the target second capacity loss value curve and a preset slope threshold. In this method, the slope can directly represent the change amount of the cumulative capacity loss value. The probability of lithium plating occurring at the test time sequence corresponding to the target second capacity loss value curve with the largest slope is relatively large. Subsequently, determining the lithium plating state of the target battery based on this target second capacity loss value curve not only reduces the data calculation amount, but also improves the accuracy of lithium plating state determination.

[0059] In one of the embodiments, determining the lithium plating state of the target battery according to the target second capacity loss value curve and a preset slope threshold includes:

[0060] If there is a second target point on the second capacity loss value curve whose slope is greater than the preset slope threshold, it is determined that the target battery has lithium plating during the target test time sequence corresponding to the cumulative capacity loss value of the second target point.

[0061] In the embodiments of the present application, if there is a second target point on the two-capacity loss value curve whose slope is greater than the preset slope threshold, it is determined that the target battery experiences lithium plating during the target test time sequence corresponding to the cumulative capacity loss value at the second target point. In this method, the slope can directly represent the change amount of the cumulative capacity loss value and is helpful for the implementation of computer programs. Therefore, the accurate determination of the target test cycle for the target battery to experience lithium plating is achieved, improving the detection efficiency while ensuring the accuracy of the detection.

[0062] In one of the embodiments, the above method further includes:

[0063] Judging whether the charge-discharge test data of the target battery is data with periodic characteristics;

[0064] If so, execute the step of determining the capacity loss step length of the target battery.

[0065] In the embodiments of the present application, by judging whether the charge-discharge test data of the target battery is data with periodic characteristics, in the case of determining that the charge-discharge test data of the target battery has periodic characteristics, the subsequent step of determining the capacity loss step length of the target battery is executed. In the above method, the charge-discharge test data of the target battery is pre-judged for periodic characteristics, and the lithium plating determination is performed based on the charge-discharge test data with periodic characteristics, improving the accuracy of the lithium plating determination.

[0066] In one of the embodiments, the above method further includes:

[0067] If the charge-discharge test data is data with periodic characteristics, judge whether there is a breakpoint in the charge-discharge test data of the target battery;

[0068] If there is a breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step length of the target battery according to any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint;

[0069] If there is no breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step length of the target battery according to the charge-discharge test data.

[0070] In an embodiment of the present application, when the charge-discharge test data has periodic characteristics, it is further determined whether there is a breakpoint in the charge-discharge test data of the target battery. Among them, if there is a breakpoint, the step of determining the capacity loss step length of the target battery is performed on any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint; if there is no breakpoint, the step of determining the capacity loss step length of the target battery is performed according to the charge-discharge test data. In this method, judging whether there is a breakpoint in the charge-discharge test data with periodic characteristics provides a data basis for subsequent detection, eliminates data interference, and improves the accuracy of lithium deposition detection.

[0071] In a second aspect, an embodiment of the present application further provides a detection device for lithium deposition in a battery. The device includes:

[0072] A step length determination module, configured to determine the capacity loss step length of the target battery according to the charge-discharge test data of the target battery; the capacity loss step length includes at least one data cycle of the charge-discharge test data;

[0073] A loss determination module, configured to determine the cumulative capacity loss value of the target battery within multiple detection cycles according to the capacity loss step length and the charge-discharge test data; the duration of the detection cycle is equal to the capacity loss step length;

[0074] A state determination module, configured to determine the lithium deposition state of the target battery according to the cumulative capacity loss value of the target battery within multiple detection cycles.

[0075] In a third aspect, an embodiment of the present application further provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps in the detection method for lithium deposition in a battery provided in any one of the embodiments in the first aspect above.

[0076] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps in the detection method for lithium deposition in a battery provided in any one of the embodiments in the first aspect above.

[0077] In a fifth aspect, an embodiment of the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the steps in the detection method for lithium deposition in a battery provided in any one of the embodiments in the first aspect above.

[0078] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically given below. Description of the Drawings

[0079] Figure 1 Internal structure diagram of a computer device in an embodiment;

[0080] Figure 2 Flow schematic diagram of a method for detecting lithium plating in a battery in an embodiment;

[0081] Figure 3 Schematic diagram of discharge test data and test timing in an embodiment;

[0082] Figure 4 Flow schematic diagram of determining the capacity loss step size in an embodiment;

[0083] Figure 5 Flow schematic diagram of determining the data cycle period in an embodiment;

[0084] Figure 6 Flow schematic diagram of determining the data cycle period in another embodiment;

[0085] Figure 7 Flow schematic diagram of obtaining the first charge-discharge test data and the second charge-discharge test data in an embodiment;

[0086] Figure 8 Schematic diagram of battery discharge capacity and test timing in an embodiment;

[0087] Figure 9 Flow schematic diagram of determining the capacity loss step size in another embodiment;

[0088] Figure 10 Flow schematic diagram of determining the cumulative capacity loss value in an embodiment;

[0089] Figure 11 Flow schematic diagram of determining the lithium plating state of the target battery in an embodiment;

[0090] Figure 12 Flow schematic diagram of determining the lithium plating state of the target battery in another embodiment;

[0091] Figure 13 Flow schematic diagram of determining the lithium plating state of the target battery in another embodiment;

[0092] Figure 14 Schematic diagram of the cumulative capacity loss value Cn / Dn+x and test timing in an embodiment;

[0093] Figure 15 Schematic diagram of the cumulative capacity loss value Cn / Dn+x and test timing in another embodiment;

[0094] Figure 16 Schematic flowchart for determining whether charge-discharge test data has periodic characteristics in one embodiment;

[0095] Figure 17 Schematic flowchart for determining whether there are breakpoints in charge-discharge test data in one embodiment;

[0096] Figure 18 Schematic diagram of the distribution of charge-discharge test data in one embodiment;

[0097] Figure 19 Structural block diagram of a lithium plating detection device for a battery in one embodiment. Detailed implementation manners

[0098] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0099] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field 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 term "including" and any of its variations in the specification and claims of this application and the above accompanying drawings description are intended to cover non-exclusive inclusion.

[0100] Referring to "embodiment" herein means that a specific feature, structure or characteristic described in conjunction with the embodiment can be included in at least one embodiment of this application. The phrase appears at various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0101] In the description of the embodiments of this application, the term "and / or" is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In the description of the embodiments of this application, the term "plurality" refers to two or more (including two), unless otherwise specifically limited.

[0102] In recent years, batteries have been widely used in various electronic devices, covering many fields such as communication, transportation, aerospace, etc. Taking lithium-ion batteries as an example, with the continuous expansion of the application scope of lithium-ion batteries, the safety of battery use has become the focus of people's attention. Lithium plating in batteries refers to the phenomenon that metallic lithium is deposited on the anode surface of lithium-ion batteries during long-term charge and discharge in a low-temperature environment. The whole process of lithium plating in batteries is irreversible. In the long run, it will not only damage the battery but also pose a safety risk to the battery.

[0103] To detect whether lithium plating occurs in a battery, people usually use the average voltage change caused by lithium plating in the battery to determine whether lithium plating occurs in the battery. However, through long-term experiments, the applicant found that only when the battery undergoes severe lithium plating will it cause a change in the average voltage. The method of using the average voltage change caused by lithium plating in the battery to determine whether lithium plating occurs in the battery in traditional technologies has certain limitations, with limited application value, and it is unable to detect lithium plating in the battery in a timely manner at the initial stage of lithium plating when slight lithium plating occurs. Therefore, the detection sensitivity is low.

[0104] In order to detect lithium plating in the battery in a timely manner when slight lithium plating occurs and improve the detection sensitivity, through in-depth research, the applicant found that the cyclic capacity loss comes from power loss and irreversible capacity loss. Power loss exists during both charge and discharge, mainly due to the thickening of the solid electrolyte interface (SEI) on the surfaces of the positive and negative electrode materials. The irreversible capacity loss mainly comes from the loss of active lithium, including lithium plating and side reactions. Lithium plating occurs at the end of charging. During discharge, due to factors such as detachment from conductive contact, the deposited lithium cannot participate in the discharge 100%, causing a part of the lithium to be consumed, resulting in a decrease in the discharge capacity. Obviously, lithium plating will cause the discharge capacity of the battery to be lower than the charge capacity. Side reactions are related to the state of charge (SOC) and exist during both charge and discharge. In short, among the main factors causing battery capacity loss, lithium plating is related to the charge and discharge directions. Therefore, it is possible to judge whether lithium plating occurs based on the charge capacity and discharge capacity of the same cycle or the charge capacity and discharge capacity of different cycles. Based on this, the applicant designed a detection method for lithium plating in batteries. By increasing the cycle span for measuring the battery capacity loss, the battery capacity loss can be accumulated, the value becomes larger, and it is easier to detect and determine whether lithium plating occurs, thereby achieving the technical effect of improving the sensitivity of lithium plating detection.

[0105] In one embodiment, a detection method for lithium plating in a battery is provided. This method is applied to Figure 1Take the computing device as an example for illustration. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for detecting lithium plating in a battery.

[0106] Those skilled in the art can understand that Figure 1 the structure shown in

[0107] In one embodiment, the embodiment of the present application provides a method for detecting lithium plating in a battery, as shown in Figure 2 and the embodiment includes the following steps:

[0108] S210. Determine the capacity loss step of the target battery according to the charge-discharge test data of the target battery.

[0109] Among them, the capacity loss step includes at least one data cycle period of the charge-discharge test data and is a time unit for measuring the battery capacity loss. For example, if the capacity loss step includes one data cycle period, that is, the capacity loss step = the data cycle period, this capacity loss step is used to measure the battery capacity loss generated by the target battery within one data cycle period.

[0110] The type of the target battery in the embodiment of the present application is not limited, and it can be a lithium-ion battery or other types of batteries. Taking the lithium-ion battery for charge-discharge test as an example, the corresponding charge-discharge test data obtained is data with periodic characteristics, which can be specifically obtained during the process of charge-discharge testing of the target battery. Each charge-discharge test includes one charge and one discharge, and one charge-discharge test corresponds to one test timing. For example, the charge-discharge test data of the target battery is obtained by performing 5 charge-discharge tests on the target battery, that is, the data obtained by performing the 1st test, the 2nd test, the 3rd test, the 4th test, and the 5th test respectively; among them, 1-5 are the test timings.

[0111] Optionally, the above charge-discharge test data may include charge data obtained during the charging process and / or discharge data obtained during the discharging process. For example, the battery charging capacity and / or the battery discharging capacity.

[0112] Optionally, after obtaining the charge-discharge test data of the target battery, the computer device may determine the capacity loss step of the target battery based on the periodic characteristics of the charge-discharge test data.

[0113] Each data cycle includes multiple sets of charge-discharge test data. Between different data cycles, the data characteristics at the same time sequence are consistent. For example, the charge-discharge test data of the target battery includes 2 data cycles, and each data cycle includes 3 sets of charge-discharge test data. Then, the data characteristics of the charge-discharge test data at the first time sequence in the first cycle are consistent with the data characteristics of the charge-discharge test data at the first time sequence in the second cycle; the data at the second time sequence in the first cycle is consistent with the data at the second time sequence in the second cycle; the data at the third time sequence in the first cycle is consistent with the data at the third time sequence in the second cycle. Based on this, to ensure the consistency of data characteristics and improve the accuracy of detection, the above capacity loss step x is an integer multiple of the data cycle T, that is, x = N * T, N ∈ N + .

[0114] S220. Determine the cumulative capacity loss value of the target battery in multiple detection periods according to the capacity loss step and the charge-discharge test data.

[0115] Among them, the duration of each detection period is equal to the capacity loss step. As Figure 3 shown, taking the charge-discharge test data of the target battery including 40 sets of charge-discharge test data (one set of data is obtained for each charge-discharge test), the data cycle is 5, and the capacity loss step is 1 times the data cycle, that is, 5 for example, every 5 charge-discharge tests is a test period.

[0116] It should be noted that during the battery test, capacity loss will occur, that is, the battery charging capacity (Charge) decreases as the number of tests increases, or the battery discharging capacity (Discharge) decreases as the number of tests increases, or the capacity difference between the battery charging capacity and the battery discharging capacity increases as the number of tests increases.

[0117] Under normal circumstances, lithium plating in the battery is the main cause of battery capacity loss. Based on this, optionally, the computer device can determine the cumulative capacity loss value according to the change in the battery charging capacity C. For example, obtaining the ratio / difference between the battery charging capacity Cn obtained from the nth charge-discharge test and the battery charging capacity Cn+x obtained from the (n + x)th charge-discharge test as the cumulative capacity loss value, the cumulative capacity loss value within each test cycle can be obtained.

[0118] Optionally, the computer device can also determine the cumulative capacity loss value according to the change in the battery discharge capacity D. For example, obtaining the ratio / difference between the battery discharge capacity Dn obtained from the nth charge-discharge test and the battery discharge capacity Dn+x obtained from the (n + x)th charge-discharge test as the cumulative capacity loss value, the cumulative capacity loss value within each test cycle can be obtained.

[0119] Optionally, the computer device can also determine the cumulative capacity loss value according to the change of the battery discharge capacity D relative to the battery charging capacity C. For example, obtaining the ratio / difference between the battery charging capacity Cn obtained from the nth charge-discharge test and the battery discharge capacity Dn+x obtained from the (n + x)th charge-discharge test as the cumulative capacity loss value, the cumulative capacity loss value within each test cycle can be obtained.

[0120] S230. Determine the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery in multiple detection cycles.

[0121] Optionally, after obtaining the cumulative capacity loss values of the target battery in multiple detection cycles, that is, obtaining multiple cumulative capacity loss values, the computer device can compare each cumulative capacity loss value with a preset loss threshold and determine the lithium plating state of the target battery according to the comparison result. Among them, if the cumulative capacity loss value is greater than the preset loss threshold, it is determined that the target battery has lithium plating during the charge-discharge test when obtaining this preset loss threshold; otherwise, if the cumulative capacity loss value is not greater than the preset loss threshold, it is determined that the target battery does not have lithium plating during the charge-discharge test when obtaining this preset loss threshold.

[0122] Optionally, the above preset loss threshold can include multiple ones to correspond to different degrees of lithium plating. For example, the preset loss threshold includes a first threshold and a second threshold, and the second threshold is greater than the first threshold. Among them, if the cumulative capacity loss value is less than the first threshold, it is determined that the target battery does not have lithium plating during the charge-discharge test when obtaining this preset loss threshold; if the cumulative capacity loss value is greater than the first threshold and less than the second threshold, it is determined that the target battery has slight lithium plating during the charge-discharge test when obtaining this preset loss threshold; if the cumulative capacity loss value is greater than the second threshold, it is determined that the target battery has severe lithium plating during the charge-discharge test when obtaining this preset loss threshold.

[0123] In an embodiment of the present application, the computer device determines the capacity loss step of the target battery according to the charge-discharge test data of the target battery, and determines the cumulative capacity loss value of the target battery within multiple detection cycles according to the capacity loss step and the charge-discharge test data. Then, the lithium plating state of the target battery is determined according to the cumulative capacity loss value of the target battery within multiple detection cycles. Among them, the capacity loss step includes at least one data cycle of the charge-discharge test data. In this method, the capacity loss step includes at least one data cycle, which increases the cycle span for measuring the battery capacity loss, enables the battery capacity loss to be accumulated, and the value becomes larger, making it easier to detect and determine whether lithium plating occurs, and improving the sensitivity of lithium plating detection.

[0124] The capacity loss step can be determined according to the data cycle of the charge-discharge test data. Based on this, in one embodiment, as Figure 4 shown, the above S210, determining the capacity loss step of the target battery according to the charge-discharge test data of the target battery, includes:

[0125] S410, obtaining the data cycle of the charge-discharge test data according to the charge-discharge test data of the target battery.

[0126] Optionally, the computer device can use the data feature analysis method to determine the periodic characteristics of the charge-discharge test data of the target battery, and then obtain the data cycle of the charge-discharge test data. Among them, the data feature analysis method can be Fourier transform. The computer device can also use various methods such as linear fitting and data classification to obtain the data cycle of the charge-discharge test data.

[0127] S420, determining the capacity loss step according to the data cycle and the preset configuration strategy.

[0128] Among them, the preset configuration strategy is used to represent the corresponding relationship between the data cycle and the capacity loss step. Each data cycle has a corresponding capacity loss step.

[0129] Optionally, after obtaining the data cycle of the charge-discharge test data, the computer device determines the capacity loss step corresponding to the currently obtained data cycle according to the preset configuration strategy.

[0130] In an embodiment of the present application, by obtaining the data cycle of the charge-discharge test data of the target battery and the preset configuration strategy, corresponding capacity loss steps are configured for different data cycles, improving the matching degree of the determined capacity loss step with the charge-discharge test data with different periodic characteristics, and further improving the accuracy of lithium plating detection.

[0131] The periodic characteristics of charge-discharge test data are related to the charge-discharge test method. One charge-discharge test method corresponds to charge-discharge test data with one data characteristic, and multiple charge-discharge test methods correspond to charge-discharge test data with multiple data characteristics. In the case where at least two charge-discharge test methods are alternated, charge-discharge test data with alternating data characteristics is correspondingly formed, that is, charge-discharge test data with periodic characteristics. Therefore, the charge-discharge test data can be classified based on different data characteristics to determine the data cycle period according to the classification result. In one embodiment, as Figure 5 shown, S410 above, obtaining the data cycle period of the charge-discharge test data according to the charge-discharge test data of the target battery, includes:

[0132] S510, performing classification processing on the charge-discharge test data to obtain first charge-discharge test data and second charge-discharge test data.

[0133] Among them, the first charge-discharge test data and the second charge-discharge test data respectively represent charge-discharge test data obtained under different charge-discharge methods.

[0134] Optionally, for the charge-discharge test data obtained by alternating two charge-discharge test methods, after classification processing, the first charge-discharge test data and the second charge-discharge test data are correspondingly obtained. Among them, the above classification processing can be methods such as clustering and linear fitting.

[0135] S520, determining the data cycle period of the charge-discharge test data according to the first charge-discharge test data and the second charge-discharge test data.

[0136] Optionally, the computer device can respectively count the data amounts of the first charge-discharge test data and the second charge-discharge test data to determine the data cycle period of the charge-discharge test data according to their respective data amounts.

[0137] In the embodiments of the present application, by performing classification processing on the charge-discharge test data, the first charge-discharge test data and the second charge-discharge test data obtained under different charge-discharge test methods are obtained, and then the data cycle period of the charge-discharge test data is determined according to the first charge-discharge test data and the second charge-discharge test data. This method divides the charge-discharge test data into two types of charge-discharge test data through classification processing, prepares data for subsequent determination of the data cycle period, so as to more efficiently determine the data cycle period and improve the efficiency of lithium plating detection.

[0138] In an optional embodiment, a realizable manner is provided for determining the data cycle period of the charge-discharge test data according to the first charge-discharge test data and the second charge-discharge test data, as Figure 6 shown, the above S520 includes the following steps:

[0139] S610. Determine the first data volume based on the first charge-discharge test data and determine the second data volume based on the charge-discharge test data.

[0140] Specifically, after classifying the first charge-discharge test data and the second charge-discharge test data in the charge-discharge test data, the computer device further counts the data volume of the first charge-discharge test data as the first data volume and counts the data volume of the second charge-discharge test data as the second data volume.

[0141] The first data volume represents the quantization value of the first charge-discharge test data. Similarly, the second data volume represents the quantization value of the second charge-discharge test data. And the quantization value is not limited to the value quantized from dimensions such as quantity, storage capacity, data length, etc.

[0142] For example, taking 200 groups of charge-discharge test data as an example, it is statistically obtained that the first charge-discharge test data includes 160 groups of data, the first data volume is 160, the second charge-discharge test data includes 40 groups of data, and the second data volume is 40.

[0143] For another example, preset some corresponding relationships between data lengths and quantization values. Based on this corresponding relationship, first obtain the data length of the first charge-discharge test data, and then look up its corresponding quantization value in the corresponding relationship according to the data length of the first charge-discharge test data, and take the found quantization value as the first data volume of the first charge-discharge test data. Similarly, the data length of the second charge-discharge test data can also be obtained, and then look up its corresponding quantization value in the corresponding relationship according to the data length of the second charge-discharge test data, and take the found quantization value as the second data volume of the second charge-discharge test data.

[0144] S620. Obtain the data volume ratio of the first data volume and the second data volume.

[0145] After obtaining the first data volume of the first charge-discharge test data and the second data volume of the second charge-discharge test data, calculate the ratio between the first data volume and the second data volume, which is the required data volume ratio.

[0146] S630. Determine the data cycle period by summing the numerator and denominator in the data volume ratio.

[0147] Specifically, the computer device determines the sum of the numerator and denominator in the data volume ratio as the data cycle period according to the data volume ratio of the first data volume and the second data volume.

[0148] Continuing with the above example, the data volume ratio = first data volume / second data volume = 160 / 40 = 4 / 1, then the data cycle period = 1 + 4 = 5.

[0149] In the embodiments of the present application, the computer device classifies the charge-discharge test data using data features, obtaining the first charge-discharge test data and the second charge-discharge test data corresponding to different charge-discharge test methods. Then, based on the first charge-discharge test data and the second charge-discharge test data, the data cycle period of the charge-discharge test data is determined. Specifically, the data cycle period can be determined according to the data volume ratio between the first charge-discharge test data and the second charge-discharge test data. Through the above data classification and data statistics methods, the data cycle period can be obtained quickly and accurately, providing a data basis for subsequent lithium deposition detection and correspondingly improving the efficiency and accuracy of lithium deposition detection.

[0150] To improve the accuracy of classification, a linear fitting method can be used to classify the charge-discharge test data. Therefore, in one of the embodiments, the process of classifying the charge-discharge test data to obtain the first charge-discharge test data and the second charge-discharge test data is described as follows. Figure 7 As shown, the above S510 includes the following steps:

[0151] S710. Perform linear fitting processing on the charge-discharge test data to obtain the first fitting line and the second fitting line.

[0152] Among them, since the charge-discharge test data is obtained by alternately performing two charge-discharge test methods, correspondingly, the computer device performs linear fitting processing on the charge-discharge test data, and thus obtains two fitting lines, namely the first fitting line and the second fitting line. As shown in Figure 8 Taking the charge-discharge test data obtained by alternately performing fast charge and slow charge on the target battery as an example, Figure 8 only the battery discharge capacity (Discharge) in the charge-discharge test data is shown. After linear fitting processing, the first fitting line S1 and the second fitting line S2 are obtained, corresponding to the charge-discharge test methods of the fast charge mode and the slow charge mode respectively.

[0153] S720. Determine the midline between the first fitting line and the second fitting line.

[0154] Specifically, after obtaining the first fitting line and the second fitting line, the computer device can use a geometric algorithm to determine the midline between the first fitting line and the second fitting line. For example, obtain multiple intermediate points between the first fitting line and the second fitting line, then perform linear fitting on the multiple intermediate points, and use the obtained fitting line as the midline between the first fitting line and the second fitting line. As shown in Figure 8 The fitting line S is the midline between the first fitting line S1 and the second fitting line S2.

[0155] S730. Take the charge-discharge test data on one side of the midline as the first charge-discharge test data, and take the charge-discharge test data on the other side of the midline as the second charge-discharge test data.

[0156] As can be seen from Figure 8 , not all data points fall on the fitting line. Therefore, in order to classify all charge-discharge test data into the corresponding classes, the computer can use the obtained midline as the segmentation reference, take the charge-discharge test data on one side of the midline as the first charge-discharge test data, and take the charge-discharge test data on the other side of the midline as the second charge-discharge test data. As Figure 8 shown, the charge-discharge test data located below and to the left of the midline S is the first charge-discharge test data, and the charge-discharge test data located above and to the right of the midline S is the second charge-discharge test data.

[0157] In the embodiment of the present application, the computer device divides the charge-discharge test data into the first charge-discharge test data and the second charge-discharge test data by means of linear fitting processing. The processing process is simple and easy to be implemented by the computer device, which improves the processing efficiency and the classification accuracy at the same time.

[0158] To simplify the configuration strategy, the above preset configuration strategy includes a preset cycle threshold, and the computer device can implement segmented configuration based on the size relationship between the data cycle period and the cycle threshold. Based on this, an embodiment is provided for the above process of determining the capacity loss step size according to the data cycle period and the preset configuration strategy. The above S420 includes the following steps:

[0159] S910. Obtain the comparison result between the data cycle period and the cycle threshold.

[0160] Optionally, the computer device compares the size between the data cycle period and the cycle threshold to obtain the comparison result. Among them, when a cycle threshold is preset, the comparison result is that the data cycle period is greater than / equal to the cycle threshold, or the data cycle period is less than the cycle threshold.

[0161] S920. Determine the cumulative coefficient according to the comparison result.

[0162] Among them, the cumulative coefficient is used to represent the multiple relationship between the data cycle period and the capacity loss step size.

[0163] Optionally, when a preset cycle threshold is set, if the comparison result is that the data cycle period is greater than or equal to the cycle threshold, the accumulation coefficient is the first coefficient; if the comparison result is that the data cycle period is less than the cycle threshold, the accumulation coefficient is the second coefficient; where the second coefficient is greater than the first coefficient. For example, the cycle threshold T0 = 5, if the data cycle period T ≥ T0, the accumulation coefficient is the first coefficient X1 = 1; if the data cycle period T < T0, the accumulation coefficient is the second coefficient X2 ≥ 2.

[0164] S930. Determine the capacity loss step size according to the accumulation coefficient and the data cycle period.

[0165] Specifically, the computer device obtains the product between the determined accumulation coefficient X and the data cycle period T, and uses this product as the capacity loss step size x. Optionally, x = X * T; where, if T ≥ T0, X = 1; if T < T0, X ≥ 2.

[0166] In the embodiments of this application, the computer device determines the accumulation coefficient according to the comparison result between the data cycle period and the cycle threshold, so as to determine the capacity loss step size according to the accumulation coefficient and the data cycle period. Specifically, it is to obtain the product between the accumulation coefficient and the data cycle period as the capacity loss step size. Through the comparison method, the segmented configuration for different data cycle periods is realized, the configuration strategy is simplified, the time consumption for determining the capacity loss step size is reduced, and the overall detection efficiency is improved.

[0167] When the charge-discharge test data includes the battery charge capacity and the corresponding battery discharge capacity in each data cycle period, the cumulative capacity loss value can be determined according to the change of the battery discharge capacity relative to the battery charge capacity. In one of the embodiments, to reduce the calculation amount, the cumulative capacity loss value can be determined according to the average value of the battery charge capacity and the average value of the battery discharge capacity in each test cycle. As Figure 10 shown, the above S220. Determine the cumulative capacity loss value of the target battery in multiple detection cycles according to the capacity loss step size and the charge-discharge test data, including:

[0168] S1010. Obtain the average value of the battery charge capacity and the average value of the battery discharge capacity in each detection cycle according to the capacity loss step size.

[0169] Specifically, the computer device determines the detection cycles included in the charge-discharge test data according to the capacity loss step size, and obtains the average value of the battery charge capacity and the average value of the battery discharge capacity in each detection cycle. As Figure 3As shown, the 1st to 5th tests correspond to the 1st detection cycle, the 6th to 10th tests correspond to the 2nd detection cycle... the 36th to 40th tests correspond to the 8th detection cycle. The computer device then calculates the average values of the battery charging capacity within the 1st to 8th detection cycles respectively, and correspondingly obtains 8 average values of the battery charging capacity C1' to C8'. At the same time, it calculates the average values of the battery discharging capacity within the 1st to 8th detection cycles respectively, and correspondingly obtains 8 average values of the battery discharging capacity D1' to D8'.

[0170] S1020. Obtain multiple cumulative capacity loss values of the target battery according to the ratio between the average value of the battery charging capacity and the average value of the battery discharging capacity within each detection cycle.

[0171] Optionally, after determining the average value of the battery charging capacity and the battery discharging capacity within each detection cycle, the computer device can calculate the ratio of the average value of the battery charging capacity to the battery discharging capacity within each detection cycle as the cumulative capacity loss value, and then obtain multiple cumulative capacity loss values of the target battery, each detection cycle corresponding to one. Continuing the above example, for the 1st detection cycle, the cumulative capacity loss value C1' / D1' is obtained; for the 2nd detection cycle, the cumulative capacity loss value C2' / D2' is obtained;......; for the 8th detection cycle, the cumulative capacity loss value C8' / D8' is obtained. The computer device obtains 8 cumulative capacity loss values based on 40 sets of charge-discharge test data.

[0172] In the embodiment of the present application, the computer device obtains the average value of the battery charging capacity and the average value of the battery discharging capacity of each detection cycle according to the capacity loss step size, and then determines the cumulative capacity loss value within multiple detection cycles according to the ratio between the average value of the battery charging capacity and the average value of the battery discharging capacity within each detection cycle. In this method, the way of calculating the average value does not need to calculate the cumulative capacity loss value for each battery charging capacity and battery discharging capacity, reducing the calculation amount and thus improving the test efficiency.

[0173] To improve the accuracy of lithium plating detection, the lithium plating state can be determined according to the change amount of the cumulative capacity loss value, and the change amount can be characterized by the slope. Therefore, in one embodiment, as Figure 11 shown, the above S230. Determine the lithium plating state of the target battery according to multiple cumulative capacity loss values, including:

[0174] S1110. Determine the first capacity loss value curve according to the cumulative capacity loss values of the target battery within multiple detection cycles.

[0175] Optionally, the computer device performs linear fitting on the cumulative capacity loss values of the aforementioned obtained target battery within multiple detection cycles, that is, multiple cumulative capacity loss values, to obtain the first capacity loss value curve. Continuing with the above example, the computer device performs linear fitting on the 8 obtained cumulative capacity loss values, that is, obtains the fitting line determined by these 8 cumulative capacity loss values, which is the first capacity loss value curve.

[0176] S1120. If there is a first target point on the first capacity loss value curve whose slope is greater than the preset slope threshold, then it is determined that lithium plating occurs in the target test cycle corresponding to the cumulative capacity loss value of the target battery at the first target point.

[0177] Among them, each point included on the first capacity loss value curve corresponds to a cumulative capacity loss value.

[0178] Specifically, after obtaining the first capacity loss value curve, the computer device further obtains the slope of each point on the first capacity loss value curve and compares it with the preset slope threshold, so as to determine, from all the points included on the first capacity loss value curve, the first target point whose slope is greater than the preset slope threshold, and determine the test cycle corresponding to the cumulative capacity loss value of this first target point as the target test cycle, and then determine that lithium plating occurs in the target battery during this target test cycle. Continuing with the above example, if the slope of the point corresponding to the cumulative capacity loss value C2' / D2' on the first capacity loss value curve obtained by the computer device is greater than the preset slope threshold, then it is determined that the second test cycle corresponding to the capacity loss value C2' / D2' is the target test cycle, and it is determined that lithium plating occurs in the target battery during this second test cycle.

[0179] Optionally, after determining that lithium plating occurs in the target battery during the target test cycle, the computer device can further determine the target test timing when lithium plating occurs according to the charge-discharge test data during the target test cycle.

[0180] Optionally, the computer device can determine the ratio / difference between the battery charging capacity and the battery discharging capacity at each test timing within the target test cycle, and determine the target test timing when lithium plating occurs in the target battery according to this ratio / difference. Among them, when the above ratio is the ratio obtained by dividing the battery charging capacity by the battery discharging capacity, that is, C / D, or the above difference is the difference obtained by subtracting the battery discharging capacity from the battery charging capacity, that is, C - D, then the test timing corresponding to the maximum ratio / difference is determined as the target test timing when lithium plating occurs in the target battery; on the contrary, when the above ratio is the ratio obtained by dividing the battery discharging capacity by the battery charging capacity, that is, D / C, or the above difference is the difference obtained by subtracting the battery charging capacity from the battery discharging capacity, that is, D - C, then the test timing corresponding to the minimum ratio / difference is determined as the target test timing when lithium plating occurs in the target battery.

[0181] In an embodiment of the present application, the computer device determines a first capacity loss value curve based on the cumulative capacity loss value of the target battery within multiple detection cycles, and when there is a first target point on the first capacity loss value curve whose slope is greater than a preset slope threshold, it determines that lithium plating occurs in the target battery during the target test cycle corresponding to the cumulative capacity loss value of the first target point. The slope can directly represent the change amount of the cumulative capacity loss value and is helpful for the implementation of computer programs. Therefore, the accurate determination of the target test cycle in which lithium plating occurs in the target battery is achieved, improving the detection efficiency while ensuring the accuracy of detection.

[0182] To accurately locate the target test timing when lithium plating occurs in the target battery, it is necessary to determine the cumulative capacity loss value based on the charge-discharge test data at each test timing (i.e., obtained from each charge-discharge test). In one embodiment, the above S220, determining the cumulative capacity loss value of the target battery within multiple detection cycles according to the capacity loss step and the charge-discharge test data, includes:

[0183] Determine multiple cumulative capacity loss values of the target battery based on the battery charge capacity at the nth test timing and the battery discharge capacity at the (n + x)th test timing.

[0184] Where, n is the test timing, and x is the capacity loss step.

[0185] Optionally, the charge-discharge test data of the target battery includes the battery charge capacity and the battery discharge capacity. The computer device can directly obtain the battery charge capacity at the nth test timing and the battery discharge capacity at the (n + x)th test timing as the cumulative capacity loss value, that is, Cn / Dn + x, and thus obtain multiple cumulative capacity loss values of the target battery. For Figure 3 example, it includes 40 sets of charge-discharge test data, that is, 40 charge-discharge tests are performed, the capacity loss step x = 5. According to the calculation method of Cn / Dn + x, the cumulative capacity loss value C1 / D1 + 5 corresponding to the first test, the cumulative capacity loss value C2 / D2 + 5 corresponding to the second test,..., the cumulative capacity loss value C35 / D35 + 5 corresponding to the 35th test are obtained, that is, 35 cumulative capacity loss values of the target battery are obtained.

[0186] In an embodiment of the present application, the computer device determines the cumulative capacity loss value of the target battery within multiple detection cycles based on the battery charge capacity at the nth test timing and the battery discharge capacity at the (n + x)th test timing. Where, n is the test timing, and x is the capacity loss step. In this method, the battery charge capacity and the battery discharge capacity with a cycle span are used to determine the cumulative capacity loss value, achieving the accumulation of the battery capacity loss and improving the sensitivity of lithium plating detection.

[0187] To improve the accuracy of lithium plating detection, the lithium plating state can be determined according to the change amount of the cumulative capacity loss value of the same data arrangement timing in each detection cycle. Based on this, as Figure 12 shown, the above S230 determines the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery in multiple detection cycles, including:

[0188] S1210. According to the data arrangement timing in each detection cycle, the cumulative capacity loss values located at the same data arrangement timing are divided into the same group to obtain multiple reference cycle groups of the target battery.

[0189] Taking Figure 3 as an example, the cumulative capacity loss value C1 / D6 at the first position in the first detection cycle, the cumulative capacity loss value C6 / D11 at the first position in the second detection cycle, the cumulative capacity loss value C11 / D16 at the first position in the third detection cycle, and so on are divided into a group as the first reference cycle group; the cumulative capacity loss value C2 / D7 at the second position in the first detection cycle, the cumulative capacity loss value C7 / D12 at the second position in the second detection cycle, the cumulative capacity loss value C12 / D17 at the second position in the third detection cycle, and so on are divided into a group as the second reference cycle group;... until, the cumulative capacity loss value C5 / D10 at the last position in the first detection cycle, the cumulative capacity loss value C10 / D15 at the last position in the second detection cycle, the cumulative capacity loss value C15 / D20 at the second position in the third detection cycle, and so on are divided into a group as the fifth reference cycle group. For the charge-discharge test data with a data cycle of 5, 5 groups of reference cycle groups are correspondingly obtained.

[0190] S1220. Determine the lithium plating state of the target battery according to the cumulative capacity loss values in multiple reference cycle groups of the target battery.

[0191] Optionally, the computer device can select at least one group of reference cycle groups from multiple reference cycle groups of the target battery and determine the lithium plating state of the target battery based on the cumulative capacity loss values in this reference cycle group.

[0192] In the embodiment of the present application, the computer device divides the cumulative capacity loss values located at the same data arrangement timing into the same group according to the data arrangement timing in each detection cycle to obtain multiple reference cycle groups of the target battery, and then determines the lithium plating state of the target battery according to the cumulative capacity loss values in multiple reference cycle groups of the target battery. In this method, for each detection cycle, the charge-discharge test data under the same data arrangement timing have the same data characteristics, and the corresponding cumulative capacity loss values also have the same data characteristics. After grouping, the cumulative capacity loss values with the same data characteristics within the group are used to determine the lithium plating state of the target battery, which can effectively improve the accuracy and reliability of lithium plating detection.

[0193] In an optional embodiment, as Figure 13 shown, the above S1220, determining the lithium plating state of the target battery according to the cumulative capacity loss values within multiple reference cycle groups of the target battery, includes

[0194] S1310. According to the multiple cumulative capacity loss values within each reference cycle group, determine the second capacity loss value curve corresponding to each reference cycle group.

[0195] Optionally, the computer device obtains the cumulative capacity loss values within each group of reference cycle groups and performs linear fitting to obtain the second capacity loss value curve corresponding to each group of reference cycle groups. For 5 groups of reference cycle groups, 5 corresponding second capacity loss value curves are fitted. For reference, see Figure 14 , Figure 14 in which only 3 second capacity loss value curves (C / D+5—1, C / D+5—4, C / D+5—5) are shown, which are respectively obtained by fitting the cumulative capacity loss values at the 1st time sequence, the 4th time sequence, and the 5th time sequence in each reference cycle group.

[0196] S1320. According to the second capacity loss value curves corresponding to each reference cycle group, obtain the target second capacity loss value curve with the largest slope.

[0197] Optionally, the computer device obtains the slopes of the second capacity loss value curves corresponding to each reference cycle group, and determines the second capacity loss value curve with the largest slope through comparison, that is, the target second capacity loss value curve. Taking Figure 14 the three second capacity loss value curves shown in as an example, it is determined that the slope of the second capacity loss value curve C / D+5—5 is the largest, so the second capacity loss value curve C / D+5—5 is determined as the target second capacity loss value curve.

[0198] Optionally, the slope of the second capacity loss value curve can be determined based on the sum of the slopes of all points on the curve; among them, the larger the sum of the slopes, the larger the slope of the determined second capacity loss value curve; conversely, the smaller the sum of the slopes, the smaller the slope of the determined second capacity loss value curve. The computer device can also determine it according to the slope difference between the maximum slope and the minimum slope of the points on the curve; among them, the larger the slope difference, the larger the slope of the determined second capacity loss value curve; conversely, the smaller the slope difference, the smaller the slope of the determined second capacity loss value curve. Optionally, the slope of the second capacity loss value curve can also be determined based on the average value, median, and mode of the slopes of all points on the curve.

[0199] S1330. Determine the lithium plating state of the target battery according to the target second capacity loss value curve and the preset slope threshold.

[0200] Among them, the points included in the second capacity loss value curve correspond to a cumulative capacity loss value respectively.

[0201] Specifically, after determining the target second capacity loss value curve, the computer device further obtains the slope of each point on the target second capacity loss value curve and compares it with a preset slope threshold, so as to determine, from all the points included in the target second capacity loss value curve, a second target point whose slope is greater than the preset slope threshold. The test timing corresponding to the cumulative capacity loss value of the second target point is determined as the target test timing, and it is determined that lithium plating occurs in the target battery during the target test timing. As Figure 15 shown, the test timing corresponding to the cumulative capacity loss value marked by the arrow is the test timing when lithium plating occurs. For example, lithium plating occurs in the target battery during the 155th test.

[0202] In the embodiment of the present application, the computer device determines the second capacity loss value curve corresponding to each reference cycle group according to multiple cumulative capacity loss values in each reference cycle group, and then obtains the target second capacity loss value curve with the largest slope therefrom, so as to determine the lithium plating state of the target battery according to the target second capacity loss value curve and the preset slope threshold. In this method, the slope can directly represent the change amount of the cumulative capacity loss value. The possibility of lithium plating occurring at the test timing corresponding to the target second capacity loss value curve with the largest slope is relatively high. Subsequently, determining the lithium plating state of the target battery based on the target second capacity loss value curve not only reduces the data calculation amount, but also improves the accuracy of the lithium plating state determination. Moreover, the slope can directly represent the change amount of the cumulative capacity loss value, which is helpful for the implementation of computer programs. Therefore, the accurate determination of the target test cycle when lithium plating occurs in the target battery is realized, and the detection efficiency is improved while ensuring the detection accuracy.

[0203] As described above, the charge and discharge test data of the target battery are data with periodic characteristics. Therefore, in one embodiment, as Figure 16 shown, the above method further includes:

[0204] S1610. Determine whether the charge and discharge test data of the target battery are data with periodic characteristics.

[0205] Among them, the data with periodic characteristics are the data that continuously cycle according to a certain rule.

[0206] Optionally, the computer device can perform data analysis on the obtained charge and discharge test data of the target battery to determine whether the charge and discharge test data show regular cycling. Among them, if so, it is determined that the charge and discharge test data of the target battery have periodic characteristics; on the contrary, if not, it is determined that the charge and discharge test data of the target battery do not have periodic characteristics.

[0207] S1620. If so, execute the step of determining the capacity loss step of the target battery.

[0208] Specifically, when the computer device determines that the charge-discharge test data of the target battery has periodic characteristics, it continues to execute the above S210, that is, the step of determining the capacity loss step of the target battery.

[0209] On the contrary, when the computer device determines that the charge-discharge test data of the target battery does not have periodic characteristics, other methods can be used to determine the lithium plating state of the target battery. For example, for each test, obtain the ratio C / D of the battery charge capacity to the battery discharge capacity, compare the size of C / D with the threshold, and when C / D is greater than the threshold, determine that lithium plating occurs in the test corresponding to the obtained C / D; otherwise, no lithium plating occurs.

[0210] In the embodiments of the present application, the computer device determines whether the charge-discharge test data of the target battery is data with periodic characteristics, so as to execute the subsequent step of determining the capacity loss step of the target battery when it is determined that the charge-discharge test data of the target battery is data with periodic characteristics. In the above method, whether the charge-discharge test data of the target battery has periodic characteristics is pre-determined, so as to determine lithium plating based on the charge-discharge test data with periodic characteristics, improving the accuracy of lithium plating determination.

[0211] During the charge-discharge test of the target battery, test interruptions caused by various reasons exist, resulting in breakpoints in the obtained charge-discharge test data. To eliminate the influence of breakpoints on lithium plating detection, in one embodiment, as Figure 17 shown, the above method further includes:

[0212] S1710. If the charge-discharge test data is data with periodic characteristics, determine whether there are breakpoints in the charge-discharge test data of the target battery.

[0213] Among them, a breakpoint is a point that divides the charge-discharge test data into multiple segments. As Figure 18 shown, the circled points are breakpoints, and the two breakpoints in the figure divide the charge-discharge test data into three groups.

[0214] Optionally, when it is determined that the charge-discharge test data is data with periodic characteristics, the computer device further determines whether there are points with discontinuous change trends and exceeding the change threshold in the charge-discharge test data, and determines the discontinuous points as breakpoints. The identification of breakpoints in the charge-discharge test data can also be determined by other data analysis methods, such as data classification, feature analysis, trend comparison, etc. In the embodiments of the present application, the method for identifying breakpoints is not specifically limited.

[0215] S1720. If there is a breakpoint in the charge-discharge test data, then perform the step of determining the capacity loss step of the target battery on any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint.

[0216] Among them, the breakpoint divides the charge-discharge test data of the target battery into multiple segments. For example, if there is one breakpoint, the charge-discharge test data is divided into two segments; if there are two breakpoints, the charge-discharge test data is divided into three segments (as Figure 18 shown by taking the battery discharge capacity as an example).

[0217] Optionally, when there is a breakpoint in the charge-discharge test data, the computer device randomly selects one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint to perform the above S210, that is, the step of determining the capacity loss step of the target battery. It is also possible to sequentially perform the above S210 for each segment obtained by division.

[0218] S1730. If there is no breakpoint in the charge-discharge test data, then perform the step of determining the capacity loss step of the target battery according to the charge-discharge test data.

[0219] Optionally, when there is no breakpoint in the charge-discharge test data, the computer device directly takes the charge-discharge test data of the target battery to perform the above S210, that is, the step of determining the capacity loss step of the target battery.

[0220] In the embodiments of this application, when the charge-discharge test data of the computer device is data with periodic characteristics, it is further determined whether there is a breakpoint in the charge-discharge test data of the target battery. Among them, if there is one, perform the step of determining the capacity loss step of the target battery on any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint; if not, perform the step of determining the capacity loss step of the target battery according to the charge-discharge test data. In this method, judging whether there is a breakpoint in the charge-discharge test data with periodic characteristics provides a data basis for subsequent detection, eliminates data interference, and improves the accuracy of lithium deposition detection.

[0221] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0222] In one embodiment, as Figure 19 shown, a detection device for lithium plating of a battery is provided, including: a step length determination module 1901, a loss determination module 1902, and a state determination module 1903; wherein,

[0223] The step length determination module 1901 is configured to determine the capacity loss step length of the target battery according to the charge and discharge test data of the target battery; the capacity loss step length includes at least one data cycle period of the charge and discharge test data;

[0224] The loss determination module 1902 is configured to determine the cumulative capacity loss value of the target battery within multiple detection periods according to the capacity loss step length and the charge and discharge test data; the duration of the detection period is equal to the capacity loss step length;

[0225] The state determination module 1903 is configured to determine the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery within multiple detection periods.

[0226] In one of the embodiments, the step length determination module 1901 is specifically configured to:

[0227] Obtain the data cycle period of the charge and discharge test data according to the charge and discharge test data of the target battery; determine the capacity loss step length according to the data cycle period and the preset configuration strategy.

[0228] In one of the embodiments, the step length determination module 1901 is specifically configured to:

[0229] Classify the charge and discharge test data to obtain first charge and discharge test data and second charge and discharge test data; wherein, the first charge and discharge test data and the second charge and discharge test data respectively represent the charge and discharge test data obtained under different charge and discharge test methods; determine the data cycle period of the charge and discharge test data according to the first charge and discharge test data and the second charge and discharge test data.

[0230] In one embodiment, the step determination module 1901 is specifically configured to:

[0231] Perform linear fitting on the charge-discharge test data to obtain a first fitting line and a second fitting line; determine the midline between the first fitting line and the second fitting line; use the charge-discharge test data on one side of the midline as the first charge-discharge test data, and use the charge-discharge test data on the other side of the midline as the second charge-discharge test data.

[0232] In one embodiment, the step determination module 1901 is specifically configured to:

[0233] Determine a first data volume according to the first charge-discharge test data, and determine a second data volume according to the second charge-discharge test data; obtain the data volume ratio of the first data volume and the second data volume; determine the sum of the numerator and denominator in the data volume ratio as the data cycle period.

[0234] In one embodiment, the preset configuration strategy includes a preset cycle threshold, and the step determination module 1901 is specifically configured to:

[0235] Obtain the comparison result between the data cycle period and the cycle threshold; determine the cumulative coefficient according to the comparison result; determine the capacity loss step according to the cumulative coefficient and the data cycle period.

[0236] In one embodiment, the step determination module 1901 is specifically configured to:

[0237] Obtain the product of the cumulative coefficient and the data cycle period as the capacity loss step.

[0238] In one embodiment, the charge-discharge test data includes the battery charge capacity and the battery discharge capacity; the loss determination module 1802 is specifically configured to:

[0239] Obtain the average battery charge capacity and the average battery discharge capacity of each detection period according to the capacity loss step; obtain the cumulative capacity loss value of the target battery in multiple detection periods according to the ratio between the average battery charge capacity and the average battery discharge capacity in each detection period.

[0240] In one embodiment, the state determination module 1903 is specifically configured to:

[0241] Determine a first capacity loss value curve according to the cumulative capacity loss value of the target battery in multiple detection periods; if there is a first target point on the first capacity loss value curve with a slope greater than the preset slope threshold, determine that the target battery has lithium plating during the target test period corresponding to the cumulative capacity loss value of the first target point.

[0242] In one embodiment, the charge-discharge test data includes the battery charging capacity and the battery discharging capacity; the loss determination module 1902 is specifically configured to:

[0243] Determine the cumulative capacity loss value of the target battery within multiple detection cycles according to the battery charging capacity at the nth test timing and the battery discharging capacity at the (n + x)th test timing; where n is the test timing and x is the capacity loss step size.

[0244] In one embodiment, the state determination module 1903 is specifically configured to:

[0245] According to the data arrangement timing within each detection cycle, divide the cumulative capacity loss values located at the same data arrangement timing into the same group to obtain multiple reference cycle groups of the target battery; determine the lithium plating state of the target battery according to the cumulative capacity loss values within the multiple reference cycle groups of the target battery.

[0246] In one embodiment, the state determination module 1903 is specifically configured to:

[0247] Determine the second capacity loss value curve corresponding to each reference cycle group according to the multiple cumulative capacity loss values within each reference cycle group; obtain the target second capacity loss value curve with the largest slope according to the second capacity loss value curves corresponding to each reference cycle group; determine the lithium plating state of the target battery according to the target second capacity loss value curve and the preset slope threshold.

[0248] In one embodiment, the state determination module 1903 is specifically configured to:

[0249] If there is a second target point on the second capacity loss value curve whose slope is greater than the preset slope threshold, determine that the target battery undergoes lithium plating within the target test timing corresponding to the cumulative capacity loss value of the second target point.

[0250] In one embodiment, the above device further includes a data preparation module, which is specifically configured to:

[0251] Judge whether the charge-discharge test data of the target battery is data with periodic characteristics; if so, execute the step of determining the capacity loss step size of the target battery.

[0252] In one embodiment, the above data preparation module is further used for:

[0253] If the charge-discharge test data is data with periodic characteristics, determine whether there is a breakpoint in the charge-discharge test data of the target battery; if there is a breakpoint in the charge-discharge test data, perform the step of determining the capacity loss step of the target battery for any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint; if there is no breakpoint in the charge-discharge test data, perform the step of determining the capacity loss step of the target battery according to the charge-discharge test data.

[0254] Each module in the above lithium plating detection device of the battery can be implemented in whole or in part by software, hardware and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0255] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0256] According to the charge-discharge test data of the target battery, determine the capacity loss step of the target battery; the capacity loss step includes at least one data cycle of the charge-discharge test data; according to the capacity loss step and the charge-discharge test data, determine the cumulative capacity loss value of the target battery in multiple detection cycles; the duration of the detection cycle is equal to the capacity loss step; determine the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery in multiple detection cycles.

[0257] In one of the embodiments, when the processor executes the computer program, the following steps are further implemented:

[0258] According to the charge-discharge test data of the target battery, obtain the data cycle of the charge-discharge test data; according to the data cycle and the preset configuration strategy, determine the capacity loss step.

[0259] In one of the embodiments, when the processor executes the computer program, the following steps are further implemented:

[0260] Classify the charge-discharge test data to obtain the first charge-discharge test data and the second charge-discharge test data; wherein, the first charge-discharge test data and the second charge-discharge test data respectively represent the charge-discharge test data obtained under different charge-discharge test methods; according to the first charge-discharge test data and the second charge-discharge test data, determine the data cycle of the charge-discharge test data.

[0261] In one of the embodiments, when the processor executes the computer program, the following steps are further implemented:

[0262] Perform linear fitting on the charge-discharge test data to obtain a first fitting line and a second fitting line; determine the midline between the first fitting line and the second fitting line; use the charge-discharge test data on one side of the midline as the first charge-discharge test data, and use the charge-discharge test data on the other side of the midline as the second charge-discharge test data.

[0263] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0264] Determine a first data volume according to the first charge-discharge test data, and determine a second data volume according to the second charge-discharge test data; obtain the data volume ratio of the first data volume and the second data volume; determine the sum of the numerator and denominator in the data volume ratio as the data cycle period.

[0265] In one embodiment, the preset configuration strategy includes a preset cycle threshold. When the processor executes the computer program, the following steps are further implemented:

[0266] Obtain the comparison result between the data cycle period and the cycle threshold; determine the cumulative coefficient according to the comparison result; determine the capacity loss step size according to the cumulative coefficient and the data cycle period.

[0267] In one embodiment, when the processor executes the computer program, the following steps are further implemented: <U+ <U+

[0268] Obtain the product of the cumulative coefficient and the data cycle period as the capacity loss step size.

[0269] In one embodiment, the charge-discharge test data includes the battery charge capacity and the battery discharge capacity. When the processor executes the computer program, the following steps are further implemented:

[0270] Obtain the average battery charge capacity and the average battery discharge capacity of each detection period according to the capacity loss step size; obtain the cumulative capacity loss value of the target battery in multiple detection periods according to the ratio between the average battery charge capacity and the average battery discharge capacity in each detection period.

[0271] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0272] Determine a first capacity loss value curve according to the cumulative capacity loss value of the target battery in multiple detection periods; if there is a first target point on the first capacity loss value curve with a slope greater than the preset slope threshold, determine that the target battery has lithium plating during the target test period corresponding to the cumulative capacity loss value of the first target point.

[0273] In one embodiment, the charge-discharge test data includes the battery charge capacity and the battery discharge capacity. When the processor executes the computer program, the following steps are further implemented:

[0274] Determine the cumulative capacity loss value of the target battery within multiple detection cycles based on the battery charging capacity at the nth test timing and the battery discharging capacity at the (n + x)th test timing; where n is the test timing and x is the capacity loss step size.

[0275] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0276] Arrange the cumulative capacity loss values at the same data arrangement timing into the same group according to the data arrangement timing within each detection cycle, to obtain multiple reference cycle groups of the target battery; determine the lithium plating state of the target battery based on the cumulative capacity loss values within the multiple reference cycle groups of the target battery.

[0277] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0278] Determine the second capacity loss value curve corresponding to each reference cycle group according to the multiple cumulative capacity loss values within each reference cycle group; obtain the target second capacity loss value curve with the largest slope according to the second capacity loss value curves corresponding to each reference cycle group; determine the lithium plating state of the target battery based on the target second capacity loss value curve and the preset slope threshold.

[0279] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0280] If there is a second target point on the second capacity loss value curve whose slope is greater than the preset slope threshold, determine that lithium plating occurs in the target test timing where the cumulative capacity loss value corresponding to the second target point of the target battery is located.

[0281] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0282] Judge whether the charge-discharge test data of the target battery is data with periodic characteristics; if so, execute the step of determining the capacity loss step size of the target battery.

[0283] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0284] If the charge-discharge test data is data with periodic characteristics, judge whether there is a breakpoint in the charge-discharge test data of the target battery; if there is a breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step size of the target battery according to any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint; if there is no breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step size of the target battery according to the charge-discharge test data.

[0285] 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 following steps are implemented:

[0286] According to the charge-discharge test data of the target battery, determine the capacity loss step of the target battery; the capacity loss step includes at least one data cycle period of the charge-discharge test data; according to the capacity loss step and the charge-discharge test data, determine the cumulative capacity loss value of the target battery within multiple detection periods; the duration of the detection period is equal to the capacity loss step; determine the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery within multiple detection periods.

[0287] In one of the embodiments, when the computer program is executed by a processor, the following steps are further implemented:

[0288] According to the charge-discharge test data of the target battery, obtain the data cycle period of the charge-discharge test data; according to the data cycle period and the preset configuration strategy, determine the capacity loss step.

[0289] In one of the embodiments, when the computer program is executed by a processor, the following steps are further implemented:

[0290] Classify the charge-discharge test data to obtain first charge-discharge test data and second charge-discharge test data; wherein, the first charge-discharge test data and the second charge-discharge test data respectively represent the charge-discharge test data obtained under different charge-discharge test methods; according to the first charge-discharge test data and the second charge-discharge test data, determine the data cycle period of the charge-discharge test data.

[0291] In one of the embodiments, when the computer program is executed by a processor, the following steps are further implemented:

[0292] Perform linear fitting processing on the charge-discharge test data to obtain a first fitting line and a second fitting line; determine the midline between the first fitting line and the second fitting line; use the charge-discharge test data on one side of the midline as the first charge-discharge test data, and use the charge-discharge test data on the other side of the midline as the second charge-discharge test data.

[0293] In one of the embodiments, when the computer program is executed by a processor, the following steps are further implemented:

[0294] Determine a first data volume according to the first charge-discharge test data, and determine a second data volume according to the second charge-discharge test data; obtain the data volume ratio of the first data volume and the second data volume; determine the sum of the numerator and the denominator in the data volume ratio as the data cycle period.

[0295] In one embodiment, the preset configuration policy includes a preset cycle threshold, and when the computer program is executed by a processor, the following steps are further implemented:

[0296] Obtain the comparison result between the data cycle period and the cycle threshold; determine the accumulation coefficient according to the comparison result; determine the capacity loss step size according to the accumulation coefficient and the data cycle period.

[0297] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0298] Obtain the product of the accumulation coefficient and the data cycle period as the capacity loss step size.

[0299] In one embodiment, the charge-discharge test data includes the battery charge capacity and the battery discharge capacity; when the computer program is executed by a processor, the following steps are further implemented:

[0300] Obtain the average value of the battery charge capacity and the average value of the battery discharge capacity for each detection cycle according to the capacity loss step size; obtain the cumulative capacity loss value of the target battery in multiple detection cycles according to the ratio between the average value of the battery charge capacity and the average value of the battery discharge capacity in each detection cycle.

[0301] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0302] Determine the first capacity loss value curve according to the cumulative capacity loss value of the target battery in multiple detection cycles; if there is a first target point on the first capacity loss value curve whose slope is greater than the preset slope threshold, determine that the target battery has lithium plating during the target test cycle corresponding to the cumulative capacity loss value of the first target point.

[0303] In one embodiment, the charge-discharge test data includes the battery charge capacity and the battery discharge capacity; when the computer program is executed by a processor, the following steps are further implemented:

[0304] Determine the cumulative capacity loss value of the target battery in multiple detection cycles according to the battery charge capacity at the nth test time sequence and the battery discharge capacity at the (n + x)th test time sequence; where n is the test time sequence and x is the capacity loss step size.

[0305] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0306] Arrange the cumulative capacity loss values located at the same data arrangement time sequence into the same group according to the data arrangement time sequence in each detection cycle, and obtain multiple reference cycle groups of the target battery; determine the lithium plating state of the target battery according to the cumulative capacity loss values in multiple reference cycle groups of the target battery.

[0307] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0308] According to multiple cumulative capacity loss values within each reference cycle group, determine a second capacity loss value curve corresponding to each reference cycle group; according to the second capacity loss value curves corresponding to each reference cycle group, obtain a target second capacity loss value curve with the largest slope; determine the lithium plating state of the target battery according to the target second capacity loss value curve and a preset slope threshold.

[0309] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0310] If there is a second target point on the second capacity loss value curve whose slope is greater than the preset slope threshold, determine that the target battery has lithium plating during the target test time sequence corresponding to the cumulative capacity loss value of the second target point.

[0311] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0312] Judge whether the charge-discharge test data of the target battery is data with periodic characteristics; if so, execute the step of determining the capacity loss step length of the target battery.

[0313] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0314] If the charge-discharge test data is data with periodic characteristics, judge whether there is a breakpoint in the charge-discharge test data of the target battery; if there is a breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step length of the target battery according to any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint; if there is no breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step length of the target battery according to the charge-discharge test data.

[0315] In one embodiment, a computer program product is provided, including a computer program, which when executed by a processor, implements the following steps:

[0316] According to the charge-discharge test data of the target battery, determine the capacity loss step length of the target battery; the capacity loss step length includes at least one data cycle period of the charge-discharge test data; according to the capacity loss step length and the charge-discharge test data, determine the cumulative capacity loss value of the target battery within multiple detection cycles; the duration of the detection cycle is equal to the capacity loss step length; determine the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery within multiple detection cycles.

[0317] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0318] Obtain the data cycle period of the charge-discharge test data according to the charge-discharge test data of the target battery; determine the capacity loss step according to the data cycle period and the preset configuration strategy.

[0319] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0320] Classify the charge-discharge test data to obtain the first charge-discharge test data and the second charge-discharge test data; wherein, the first charge-discharge test data and the second charge-discharge test data respectively represent the charge-discharge test data obtained under different charge-discharge test methods; determine the data cycle period of the charge-discharge test data according to the first charge-discharge test data and the second charge-discharge test data.

[0321] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0322] Perform linear fitting processing on the charge-discharge test data to obtain the first fitting line and the second fitting line; determine the midline between the first fitting line and the second fitting line; use the charge-discharge test data on one side of the midline as the first charge-discharge test data, and use the charge-discharge test data on the other side of the midline as the second charge-discharge test data.

[0323] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0324] Determine the first data volume according to the first charge-discharge test data, and determine the second data volume according to the second charge-discharge test data; obtain the data volume ratio of the first data volume and the second data volume; determine the sum of the numerator and denominator in the data volume ratio as the data cycle period.

[0325] In one embodiment, the preset configuration strategy includes a preset period threshold. When the computer program is executed by the processor, the following steps are further implemented:

[0326] Obtain the comparison result between the data cycle period and the period threshold; determine the cumulative coefficient according to the comparison result; determine the capacity loss step according to the cumulative coefficient and the data cycle period.

[0327] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0328] Obtain the product of the cumulative coefficient and the data cycle period as the capacity loss step.

[0329] In one embodiment, the charge-discharge test data includes the battery charging capacity and the battery discharging capacity. When the computer program is executed by the processor, the following steps are further implemented:

[0330] Obtain the average battery charging capacity and the average battery discharging capacity for each detection period according to the capacity loss step size; obtain the cumulative capacity loss value of the target battery over multiple detection periods based on the ratio between the average battery charging capacity and the average battery discharging capacity within each detection period.

[0331] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0332] Determine the first capacity loss value curve based on the cumulative capacity loss value of the target battery over multiple detection periods; if there is a first target point on the first capacity loss value curve with a slope greater than the preset slope threshold, determine that the target battery experiences lithium plating during the target test period corresponding to the cumulative capacity loss value of the first target point.

[0333] In one embodiment, the charge-discharge test data includes the battery charging capacity and the battery discharging capacity; when the computer program is executed by the processor, the following steps are further implemented:

[0334] Determine the cumulative capacity loss value of the target battery over multiple detection periods based on the battery charging capacity at the nth test timing and the battery discharging capacity at the (n + x)th test timing; where n is the test timing and x is the capacity loss step size.

[0335] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0336] Arrange the cumulative capacity loss values at the same data arrangement timing into the same group according to the data arrangement timing within each detection period, obtaining multiple reference period groups of the target battery; determine the lithium plating state of the target battery based on the cumulative capacity loss values within the multiple reference period groups of the target battery.

[0337] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0338] Determine the second capacity loss value curve corresponding to each reference period group based on the multiple cumulative capacity loss values within each reference period group; obtain the target second capacity loss value curve with the maximum slope based on the second capacity loss value curves corresponding to each reference period group; determine the lithium plating state of the target battery based on the target second capacity loss value curve and the preset slope threshold.

[0339] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0340] If there is a second target point on the second capacity loss value curve with a slope greater than the preset slope threshold, determine that the target battery experiences lithium plating during the target test timing corresponding to the cumulative capacity loss value of the second target point.

[0341] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0342] Determine whether the charge-discharge test data of the target battery is data with periodic characteristics; if so, execute the step of determining the capacity loss step of the target battery.

[0343] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0344] If the charge-discharge test data is data with periodic characteristics, determine whether there is a breakpoint in the charge-discharge test data of the target battery; if there is a breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step of the target battery according to any one of the multiple segments of charge-discharge test data obtained by dividing according to the breakpoint; if there is no breakpoint in the charge-discharge test data, execute the step of determining the capacity loss step of the target battery according to the charge-discharge test data.

[0345] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing 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 embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAMs), magnetoresistive random access memories (MRAMs), ferroelectric random access memories (FRAMs), phase change memories (PCMs), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0346] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered as the scope described in this specification.

[0347] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for detecting lithium deposition in a battery, characterized in that: The method comprises: Determining a capacity loss step length of the target battery according to charge and discharge test data of the target battery; wherein the capacity loss step length includes at least one data cycle period of the charge and discharge test data; Determining a cumulative capacity loss value of the target battery over a plurality of detection cycles according to the capacity loss step and the charge and discharge test data; wherein the duration of the detection cycle is equal to the capacity loss step; The lithium plating state of the target battery is determined according to the accumulated capacity loss value of the target battery in multiple detection cycles.

2. The method according to claim 1, characterized in that The determining the capacity loss step length of the target battery according to the charge and discharge test data of the target battery includes: Obtaining a data cycle period of the charge and discharge test data according to the charge and discharge test data of the target battery; The capacity loss step is determined according to the data cycle period and a preset configuration strategy.

3. The method according to claim 2, characterized in that The step of obtaining a data cycle period of the charge and discharge test data according to the charge and discharge test data of the target battery includes: Classifying and processing the charge-discharge test data to obtain first charge-discharge test data and second charge-discharge test data; wherein the first charge-discharge test data and the second charge-discharge test data respectively represent charge-discharge test data obtained under different charge-discharge test modes; A data cycle period of the charge and discharge test data is determined according to the first charge and discharge test data and the second charge and discharge test data.

4. The method according to claim 3, characterized in that The classifying and processing the charge-discharge test data to obtain first charge-discharge test data and second charge-discharge test data includes: Performing linear fitting processing on the charge and discharge test data to obtain a first fitting line and a second fitting line; determining a midline between the first fitted line and the second fitted line; The charge and discharge test data on one side of the center line is used as the first charge and discharge test data, and the charge and discharge test data on the other side of the center line is used as the second charge and discharge test data.

5. The method according to claim 3, characterized in that The step of determining a data cycle period of the charge-discharge test data according to the first charge-discharge test data and the second charge-discharge test data includes: determining a first data volume according to the first charge-discharge test data, and determining a second data volume according to the second charge-discharge test data; Obtaining a data volume ratio between the first data volume and the second data volume; The sum of the numerator and the denominator in the data volume ratio is determined as the data cycle period.

6. The method according to any one of claims 2 to 5, characterized in that The preset configuration strategy includes a preset cycle threshold, and determining the capacity loss step size according to the data cycle and the preset configuration strategy includes: Obtaining a comparison result between the data cycle period and the cycle threshold; determining a cumulative coefficient according to the comparison result; The capacity loss step length is determined according to the accumulation coefficient and the data cycle period.

7. The method according to claim 6, characterized in that The determining the capacity loss step size according to the accumulation coefficient and the data cycle period includes: The product of the accumulation coefficient and the data cycle period is obtained as the capacity loss step length.

8. The method according to any one of claims 1 to 5, characterized in that The charge and discharge test data includes battery charge capacity and battery discharge capacity; The step of determining the cumulative capacity loss value of the target battery over multiple detection cycles based on the capacity loss step and the charge and discharge test data includes: Obtaining, according to the capacity loss step, an average value of the battery charging capacity and an average value of the battery discharging capacity in each detection cycle; The cumulative capacity loss value of the target battery in multiple detection cycles is obtained according to the ratio between the average value of the battery charging capacity and the average value of the battery discharging capacity in each detection cycle.

9. The method according to claim 8, characterized in that The determining the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery in multiple detection cycles includes: Determining a first capacity loss value curve according to the accumulated capacity loss value of the target battery over multiple detection cycles; If there is a first target point on the first capacity loss value curve whose slope is greater than a preset slope threshold, it is determined that lithium plating occurs in the target battery within the target test cycle where the cumulative capacity loss value corresponding to the first target point is located.

10. The method according to any one of claims 1 to 5, characterized in that The charge and discharge test data includes battery charge capacity and battery discharge capacity; The step of determining the cumulative capacity loss value of the target battery over multiple detection cycles based on the capacity loss step and the charge and discharge test data includes: The cumulative capacity loss value of the target battery in multiple detection cycles is determined based on the battery charging capacity at the nth test sequence and the battery discharging capacity at the n+xth test sequence; wherein n is the test sequence and x is the capacity loss step.

11. The method according to claim 10, characterized in that The determining the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery in multiple detection cycles includes: According to the data arrangement time sequence in each detection cycle, the accumulated capacity loss values in the same data arrangement time sequence are divided into the same group to obtain multiple reference cycle groups of the target battery; The lithium plating state of the target battery is determined according to the accumulated capacity loss values of the target battery in a plurality of reference cycle groups.

12. The method according to claim 11, characterized in that The determining the lithium plating state of the target battery according to the accumulated capacity loss values in the plurality of reference cycle groups of the target battery includes: Determining a second capacity loss value curve corresponding to each reference cycle group according to a plurality of accumulated capacity loss values in each reference cycle group; Obtaining a target second capacity loss value curve with a maximum slope according to the second capacity loss value curve corresponding to each reference cycle group; The lithium plating state of the target battery is determined according to the target second capacity loss value curve and a preset slope threshold.

13. The method according to claim 12, characterized in that The determining the lithium plating state of the target battery according to the target second capacity loss value curve and a preset slope threshold comprises: If there is a second target point on the second capacity loss value curve with a slope greater than a preset slope threshold, it is determined that lithium plating occurs in the target battery within the target test time sequence where the cumulative capacity loss value corresponding to the second target point is located.

14. The method according to any one of claims 1 to 5, characterized in that The method further comprises: Determining whether the charge and discharge test data of the target battery is data with periodic characteristics; If yes, the step of determining the capacity loss step of the target battery is performed.

15. The method according to any one of claims 1 to 5, characterized in that The method further comprises: If the charge and discharge test data is data with periodic characteristics, determining whether there is a breakpoint in the charge and discharge test data of the target battery; If there is a breakpoint in the charge-discharge test data, obtaining any one of the multiple charge-discharge test data segments obtained by dividing the data by the breakpoint and executing the step of determining the capacity loss step of the target battery; If no breakpoint exists in the charge and discharge test data, the step of determining the capacity loss step length of the target battery is performed according to the charge and discharge test data.

16. A battery lithium deposition detection device, characterized in that: The device comprises: a step length determination module, configured to determine a capacity loss step length of the target battery based on charge and discharge test data of the target battery; the capacity loss step length includes at least one data cycle period of the charge and discharge test data; a loss determination module, configured to determine a cumulative capacity loss value of a target battery over a plurality of detection cycles based on the capacity loss step length and the charge and discharge test data; wherein the duration of the detection cycle is equal to the capacity loss step length; A state determination module is used to determine the lithium plating state of the target battery according to the cumulative capacity loss value of the target battery in multiple detection cycles.

17. 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 15 are implemented.

18. 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 15 are implemented.

19. 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 15 are implemented.

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