Method and apparatus for calculating battery internal consistency, method and apparatus for calculating battery evaluation value, and electronic device

Abstract

Embodiments of the present application provide a method and apparatus for calculating battery internal consistency, a method and apparatus for calculating a battery evaluation value, and an electronic device. The method for calculating battery internal consistency comprises: on the basis of a data set of a battery, calculating Cronbach's alpha related to the battery internal consistency to obtain the battery internal consistency, wherein the battery internal consistency is used for representing the capability of keeping the temperature difference variation and / or the voltage difference variation in the battery in a preset interval. In the present application, the battery internal consistency is obtained by calculating Cronbach's alpha, so that the performance of the battery can be comprehensively evaluated; in addition, the battery internal consistency can be accurately calculated by using a small amount of data, improving the calculation efficiency.

Description

Method and device for calculating internal consistency and evaluation value of battery and electronic device TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of batteries, and in particular to a method and device for calculating internal consistency and evaluation value of a battery and an electronic device. BACKGROUND

[0002] With the increasing application of power batteries in electric vehicles, power station energy storage and other aspects, the management of batteries is also increasingly valued. In order to effectively manage the battery, it is necessary to evaluate the battery through certain evaluation indexes.

[0003] At present, the evaluation index of the battery usually includes the state of health (SOH) of the battery. The state of health is used to represent the ability of the current battery to store electrical energy relative to a new battery.

[0004] In the prior art, the following method can be used to calculate the state of health of the battery.

[0005] Method 1: determining the state of health of the battery according to the discharge cut-off voltage and the charge cut-off voltage of the single battery cell in the battery;

[0006] Method 2: calibrating the state of charge-open circuit voltage (SOC-OCV) characteristic of the battery using a constant current charging method, a constant current discharging method or other methods (for example, patent document 1: WO2021 / 166465A1), based on the SOC-OCV characteristic, and using the charge data of the battery, calculating the state of health of the battery by ampere-hour integration. The state of charge SOC can represent the current power of the battery.

[0007] It should be noted that the above introduction to the technical background is only for the convenience of clearly and completely describing the technical solutions of the present application, and for the understanding of those skilled in the art, and cannot be considered as the prior art known by those skilled in the art only because these solutions are described in the background section of the present application. SUMMARY

[0008] The present inventors have found that the existing evaluation method for the battery has some limitations, for example: the current evaluation index for the battery mainly uses the state of health index, and lacks other dimension evaluation indexes, which leads to insufficient comprehensive evaluation of the state of the battery after use; in addition, the existing evaluation method is mostly based on actual physical testing, which is time-consuming and affects the normal use of the battery.

[0009] To solve at least one of the above technical problems or other similar problems, embodiments of the present application provide a method and device for calculating battery internal consistency and an electronic device. In the method for calculating battery internal consistency, the battery internal consistency is obtained by calculating a Cohnbach coefficient, so that the performance of the battery can be comprehensively evaluated. In addition, the battery internal consistency can be accurately calculated using a small amount of data, and the calculation efficiency is improved.

[0010] According to an aspect of embodiments of the present application, a method for calculating battery internal consistency is provided, the method comprising:

[0011] The battery internal consistency is obtained by calculating a Cohnbach coefficient related to the battery internal consistency based on a data set of the battery, wherein the battery internal consistency is used to represent the ability of the temperature difference change and / or the voltage difference change in the battery to remain within a preset interval.

[0012] According to another aspect of embodiments of the present application, a device for calculating battery internal consistency is provided, the device comprising:

[0013] The consistency calculation unit obtains the battery internal consistency by calculating a Cohnbach coefficient related to the battery internal consistency based on a data set of the battery, wherein the battery internal consistency is used to represent the ability of the temperature difference change and / or the voltage difference change in the battery to remain within a preset interval.

[0014] According to another aspect of embodiments of the present application, a method for calculating battery evaluation value is provided, the method comprising:

[0015] The evaluation value of the battery is obtained by calculating the product of the score of the battery in at least three evaluation dimensions and the weight of each of the at least three evaluation dimensions based on a data set of the battery, wherein the at least three evaluation dimensions include health, safety and stability,

[0016] The health represents the ability of the battery to store electric quantity,

[0017] The safety represents the ability of the battery to avoid thermal runaway during use,

[0018] The stability represents the ability of the battery to maintain stable operation.

[0019] According to another aspect of embodiments of the present application, a device for calculating battery evaluation value is provided, the device comprising:

[0020] The first calculation device obtains the evaluation value of the battery by calculating the product of the score of the battery in at least three evaluation dimensions and the weight of each of the at least three evaluation dimensions based on a data set of the battery,

[0021] The at least three evaluation dimensions include health, safety, and stability.

[0022] The health represents the capability of the battery to store power,

[0023] The safety represents the capability of the battery to avoid thermal runaway during use,

[0024] The stability represents the capability of the battery to maintain stable operation.

[0025] According to another aspect of the embodiments of the present application, an electronic device is provided, including a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program to implement the method for calculating the battery evaluation value or the method for calculating the battery internal consistency as described above.

[0026] One of the beneficial effects of the embodiments of the present application is that, in the method for calculating the battery internal consistency, the battery internal consistency is obtained by calculating the Colognebach coefficient, so that the performance of the battery can be comprehensively evaluated, and in addition, the battery internal consistency can be accurately calculated using a small amount of data, thereby improving the calculation efficiency.

[0027] Specific implementations of the embodiments of the present application are disclosed in detail in the following description and accompanying drawings, indicating the ways in which the principles of the embodiments of the present application can be employed. It should be understood that the embodiments of the present application are not limited in scope by the number of embodiments described, since the scope of embodiments of the present application is defined by the appended claims. Numerous modifications and adaptations will occur to those skilled in the art, without departing from the spirit and true scope of the embodiments of the present application, as set forth in the following claims. BRIEF DESCRIPTION OF DRAWINGS

[0028] The accompanying drawings, which are included to provide a further understanding of the embodiments of the present application, constitute a part of the specification and illustrate the embodiments of the present application by way of example, and together with the text of the specification, serve to explain the principles of the present application. It is obvious that the accompanying drawings of the following description are only some embodiments of the present application, and other embodiments can be obtained by those skilled in the art without creative labor based on these drawings. In the drawings:

[0029] FIG. 1 is a schematic diagram of a method for calculating a battery evaluation value according to an embodiment of the present application;

[0030] FIG. 2 is a schematic diagram of operation 101;

[0031] FIG. 3 is a schematic diagram of a method for calculating temperature difference consistency result data;

[0032] FIG. 4 is a schematic diagram of a method for calculating pressure difference consistency result data;

[0033] FIG. 5 is a schematic diagram of an apparatus for calculating a battery evaluation value according to an embodiment of the present application;

[0034] FIG. 6 is a schematic diagram of an apparatus for calculating battery internal consistency according to an embodiment of the present application;

[0035] FIG. 7 is a schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] The foregoing and other features of the present application will become apparent to those skilled in the art upon consideration of the following description of specific embodiments of the present application, which are not intended to be limiting. Various modifications to these embodiments can be made by those skilled in the art without departing from the spirit and scope of the application, which are defined solely by the appended claims.

[0037] In the present application, the terms "first", "second", and the like are used to distinguish different elements from one another, but do not indicate spatial arrangement or temporal order, and the elements should not be limited by these terms. The term "and / or" includes any one and all combinations of the associated listed terms. The terms "comprise", "include", "have", and the like are meant to be interpreted inclusively, not exclusively, and thus the listed elements are not intended to be the only elements that can be present in the composition, article, or method.

[0038] In the present application, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. The term "said" is understood to mean "one or more" unless the context clearly dictates otherwise. The term "according to" is understood to mean "based at least in part on", and the term "based on" is understood to mean "based at least in part on" unless the context clearly dictates otherwise.

[0039] Features described and / or illustrated with respect to one implementation can be used in one or more other implementations in the same or similar manner, in combination with or in place of features in other implementations, or in the same or similar manner. The term "comprise / comprising" is used herein to mean that the named element is included, but not that other elements are excluded.

[0040] Embodiments of the first aspect

[0041] The embodiments of the present application provide a method for calculating battery internal consistency, which can be used to calculate battery internal consistency.

[0042] A battery can be assembled from battery cells. According to different processes, there are two forms: one form is to assemble battery cells into a module first, and then assemble the module into a battery pack; another form is to directly assemble battery cells into a battery pack, so as to reduce the structural parts inside the battery and improve the power carrying capacity of the battery pack under the same volume. Due to the inconsistent aging degrees of different battery cells or modules during use of the battery (especially power battery), the voltage difference between the battery cells or modules increases, which causes problems such as capacity decline or inability to run of the whole battery.

[0043] Generally, a battery will be tested for consistency when it is shipped, that is, the maximum voltage and minimum voltage difference of different battery cells or modules inside the battery cannot be too large. With use of the battery, the state of different battery cells or modules inside the battery can change, thereby affecting the consistency between different battery cells or modules inside the battery and the stability of the battery.

[0044] In the present application, the consistency inside the battery is calculated by data, which can evaluate the stable operation ability of the battery, so that the stability of the battery can be measured, thereby facilitating comparison or judgment. In addition, it also provides a reference for secondary use, sale or recycling of the battery.

[0045] In the present application, the consistency inside the battery is used to represent the ability that the temperature difference change and / or voltage difference change of the internal of the battery are kept within a preset interval. The consistency inside the battery includes at least one of the following sub-indicators: temperature difference consistency, voltage difference consistency. The temperature difference consistency represents the ability that the temperature difference change of the internal (i.e., multiple battery cells) of the battery is kept within a preset interval; the voltage difference consistency represents the ability that the voltage difference change of the internal (i.e., multiple battery cells) of the battery is kept within a preset interval.

[0046] The consistency inside the battery can be one indicator of the stability of the battery. The stability can represent the ability of the battery to keep stable operation. The stability can be used as one dimension for calculating the battery evaluation value. In some examples, the stability of the battery can take the internal consistency as an indicator; in addition, the stability of the battery can take the internal consistency as an indicator, and the fault tolerance as another indicator. The fault tolerance is used to represent the tolerance ability of the battery to faults, and the fault tolerance includes at least one of the following sub-indicators: obstacle-free rate, maximum fault signal ratio.

[0047] In the present application, the calculated consistency inside the battery can be further used to calculate the stability of the battery, and then the calculated stability is used to calculate the battery evaluation value.

[0048] For ease of illustration, the method for calculating the battery evaluation value of the present application is first described.

[0049] FIG. 1 is a schematic diagram of a method for calculating a battery evaluation value according to an embodiment of the present application. As shown in FIG. 1, the method comprises:

[0050] In operation 101, a product of a score of the battery in at least three evaluation dimensions and a weight of each of the at least three evaluation dimensions is calculated based on a data set (U) of the battery, to obtain an evaluation value of the battery, the at least three evaluation dimensions comprising health, safety and stability.

[0051] In the present application, the battery can be a rechargeable battery (e.g., a lithium ion battery, etc.) formed by a plurality of battery cells connected in parallel and / or in series.

[0052] According to an embodiment of the present application, in the method for calculating the battery evaluation value, the evaluation value of the battery is calculated based on the scores of the at least three evaluation dimensions, so that the performance of the battery can be comprehensively evaluated, and the data of the battery can be fully mined to improve the evaluation efficiency.

[0053] In some examples of the present application, the at least three evaluation dimensions can be three evaluation dimensions, such as health, safety and stability. In other examples, the at least three evaluation dimensions can be four evaluation dimensions, such as health, safety, stability and usage habit, and the fourth evaluation dimension can also be another evaluation dimension other than usage habit. In yet other examples, the at least three evaluation dimensions can be five or more evaluation dimensions, such as health, safety, stability, usage habit and other evaluation dimensions.

[0054] In the following description of the present application, the at least three evaluation dimensions will be taken as an example of four evaluation dimensions of health, safety, stability and usage habit.

[0055] In some embodiments of the present application:

[0056] The health can represent the ability of the battery to store electric quantity, for example, a ratio of a current capacity of the battery to an originally designed capacity;

[0057] The safety can represent a quality of a system (e.g., a battery system) to perform the function of the system under the condition of acceptable minimum accident loss, and in terms of the battery, the safety can represent the ability of the battery to avoid thermal runaway during use, and in some examples, the type of alarm signal of the battery and / or the frequency of occurrence of the alarm signal can be used to represent the safety, for example, the safety can be evaluated by evaluating the frequency and severity (e.g., the severity is related to the type of alarm signal) of the internal dangerous signal of the battery;

[0058] The stability can refer to the ability of the system to return to or maintain the original state after being disturbed, or the ability of the state to at least remain within a certain range. In the aspect of the battery, the stability is used to represent the ability of the battery to maintain stable operation, for example, the stability can be evaluated by at least one of the parameters such as the consistency of the voltage difference change of the battery pack internal battery cells or modules, the consistency of the temperature difference change, and the tolerance ability to faults.

[0059] The usage habit can be used to evaluate the good or bad degree of the consumer's behavior of using the battery, for example, from the aspects of charging behavior and / or discharging behavior.

[0060] In operation 101, the score of each evaluation dimension can be a percentage value, which can be divided into corresponding intervals, and each interval can correspond to a state of the battery.

[0061] For example, the plurality of intervals can be 5 intervals, and the score can be divided into 5 levels:

[0062] The score is greater than or equal to 90, indicating that the state of the battery is very good;

[0063] 90> score ≥ 80, indicating that the state of the battery is better;

[0064] 80> score ≥ 70, indicating that the state of the battery is general;

[0065] 70> score ≥ 60, indicating that the state of the battery is worse;

[0066] 60> score, indicating that the state of the battery is very poor.

[0067] In addition, the present application is not limited thereto, and the score of each evaluation dimension can also be in other numerical forms, for example, a value less than 1.

[0068] In operation 101, the product of the score of each of the at least three evaluation dimensions and the weight of the evaluation dimension can be calculated, and the evaluation value of the battery can be calculated. In some examples, the scores of the evaluation dimensions can be weighted and summed using the weights to obtain the evaluation value of the battery. For example, the weighted sum is performed using the following formula (1). F=A*α1+B*α2+C*α3+D*α4 (1)

[0069] Wherein, F represents the evaluation value of the battery; A represents the score of the health degree; B represents the score of the safety; C represents the score of the stability; D represents the score of the usage habit; α1 represents the weight of the health degree; α2 represents the weight of the safety; α3 represents the weight of the stability; α4 represents the weight of the usage habit.

[0070] The weight of each evaluation dimension α1, α2, α3, α4 used in operation 102 can be a fixed value or a value adjusted according to the use scenario. In addition, the weight of each evaluation dimension α1, α2, α3, α4 can be pre-set and stored, or set through a predetermined step before operation 101.

[0071] As shown in FIG. 1, the method of calculating the battery evaluation value further includes:

[0072] Operation 102 determines the weight of each of the at least three evaluation dimensions based on the importance score of each evaluation dimension, wherein the importance score reflects the relative importance of each evaluation dimension.

[0073] In some embodiments of the present application, operation 102 can include operation 1021, operation 1022 and operation 1023 as follows.

[0074] Operation 1021 constructs an importance score matrix based on the importance score of each evaluation dimension, wherein in the importance score matrix, the importance scores of different columns in the same row represent the importance score of the evaluation dimension corresponding to the row with respect to the evaluation dimensions corresponding to each column.

[0075] For example, the importance score matrix can be as shown in Table 1 below. Wherein the total score represents the sum of the importance scores in a column of the importance score matrix.

[0076] Table 1

[0077] In the present application, if the importance score of one evaluation dimension with respect to another evaluation dimension is greater than 1, it means that the importance of the one evaluation dimension is higher than that of the other evaluation dimension; otherwise, if the importance score of one evaluation dimension with respect to another evaluation dimension is less than 1, it means that the importance of the one evaluation dimension is lower than that of the other evaluation dimension.

[0078] For example, in Table 1, the number in the second column of the row corresponding to health degree is 3, which means that the importance score of safety with respect to health degree is 3; otherwise, the number in the first column of the row corresponding to safety is 1 / 3, which means that the importance score of health degree with respect to safety is 1 / 3.

[0079] Operation 1022 divides each importance score in the importance score matrix by the sum of the importance scores in the column where the importance score is located, to obtain the standardized score corresponding to each importance score.

[0080] For example, after operation 1022, the importance score matrix can be as shown in Table 2 below, wherein each number represents a standardized score.

[0081] Table 2

[0082] Operation 1023 averages the normalized scores in the same row as the weight of the evaluation dimension corresponding to the row.

[0083] For example, in operation 1022, for the health row in Table 2, the average of the 4 normalized scores of the row is calculated as (0.608+0.675+0.549+0.321) / 4=0.54, which is the weight of health.

[0084] The importance score matrix after operation 1023 can be shown in Table 3 below, where Table 3 adds a column of average (weight) to Table 2, indicating the weight of the evaluation dimension corresponding to the row.

[0085] Table 3

[0086] In the example shown in Table 3, the weights of the evaluation dimensions of health, safety, stability, and usage habit, i.e. α1, α2, α3, and α4, are 0.54, 0.27, 0.155, and 0.035, respectively. Thus, the above formula (1) can be specifically written as formula (2) as follows. F=A*0.54+B*0.27+C*0.155+D*0.035 (2)

[0087] In operation 102, the importance score can be a fixed value or a value adjusted based on the scenario. In some examples, the importance score of each evaluation dimension can be adjusted for different scenarios or customer needs, thereby adjusting the weights. For example, when the method of calculating the battery evaluation value is applied to the insurance industry, more weight is given to usage habit. Therefore, the importance scores of each evaluation dimension can be adjusted, and Table 1 can be adjusted to the form of Table 1a, and Table 3 can be adjusted to the form of Table 3a.

[0088] Table 1a

[0089] Table 3a

[0090] As shown in Table 3a, the weight of usage habit is increased.

[0091] In operation 101 of the present application, each evaluation dimension can have at least one index, each index can have a corresponding weight; each index has at least one sub-index, and each sub-index has a corresponding weight. In some examples, for an evaluation dimension, the sum of the weights of all indexes of the evaluation dimension is equal to the weight of the evaluation dimension; for an index, the sum of the weights of all sub- indexes of the index is equal to the weight of the index.

[0092] In some embodiments of the present application, the logical relationship between the evaluation dimensions, indexes, and sub- indexes can be represented by a logic tree or other forms.

[0093] Table 4 is an example of a logic tree, and the present application is not limited thereto. The logic tree for representing the logical relationship between the evaluation dimensions, indexes, and sub- indexes can also have other forms.

[0094] Table 4

[0095] In at least one embodiment of the present application, the meanings of the indexes of the health, safety, and usage habit evaluation dimensions in Table 4, and the sub- indexes included in each index, can refer to related technologies.

[0096] In at least one embodiment of the present application, stability includes at least one of the following indexes: internal consistency (for example, No. C-1 in Table 4), fault tolerance (for example, No. C-2 in Table 4).

[0097] Internal consistency is used to represent the ability of the temperature difference change and / or voltage difference change in the battery (for example, the battery can be the battery cell) to remain within a preset interval. For example, internal consistency includes at least one of the following sub- indexes: temperature difference consistency (for example, No. C-1-1 in Table 4), pressure difference consistency (for example, No. C-1-2 in Table 4). Wherein, the temperature difference consistency can represent the ability of the temperature difference change of the battery to remain within a preset interval, and the pressure difference consistency can represent the ability of the voltage difference change of the battery to remain within a preset interval.

[0098] The fault tolerance is used to represent the tolerance of the battery to faults. For example, the fault tolerance includes at least one of the following sub-indices: the barrier-free rate (for example, number C-2-1 in Table 4), the maximum fault signal ratio (for example, number C-2-2 in Table 4). Wherein, the barrier-free rate can be the ratio of the total number of fault-free signals of the battery to the total number of fault state signals of the battery during the use of the battery by the electrical appliance (for example, an electric vehicle). For example: during the use of the battery, the sensor collects data to generate a fault state signal corresponding to the collected data, wherein the collected data includes, for example, the current, the total voltage, the highest battery cell voltage, the lowest battery cell voltage and the like. Each item of data has one of two states (i.e., a fault state or a fault-free state), so the fault state signal corresponding to each item of collected data also has one of two states (i.e., a fault state or a fault-free state); the "total number of fault-free signals" refers to the total number of fault state signals in a certain period of time (for example, 6 months) in the state of "fault-free state", and the "total number of fault state signals" refers to the total number of fault state signals in the certain period of time (including "fault-free state" fault state signals and "fault state" fault state signals).

[0099] The maximum fault signal ratio can be the maximum value of the ratio of the total number of fault signals (i.e., the fault state signal in the state of "fault state") to the total number of fault state signals per day during the use of the battery by the electrical appliance (for example, an electric vehicle) in a certain period of time (for example, 6 months).

[0100] In Table 4, the weight of the sub-index is recorded as Info only (only as information), which indicates that the weight of the sub-index is 0, and the score of the sub-index can not be calculated; the weight of the sub-index is recorded as Separate (independent), which indicates that the weight of the sub-index is 0, or the score of the sub-index is considered as 0.

[0101] In the present application, the weight of each index of each evaluation dimension can be obtained according to the importance score of each index of the evaluation dimension, wherein the importance score of the index can represent the relative importance of the index relative to each index of the evaluation dimension. In some examples, a method similar to operation 102 can be used to calculate the weight of each index of a certain evaluation dimension. For example, the stability has two indexes, namely, the internal consistency (numbered C-1) and the fault tolerance (numbered C-2), and the weights of the internal consistency and the fault tolerance can be calculated based on the importance scores corresponding to the internal consistency and the fault tolerance as 0.12 and 0.035.

[0102] In the present application, the weight of each sub-indicator of each indicator can be obtained according to the importance score of each sub-indicator of the indicator, wherein the importance score of a sub-indicator can represent the relative importance of the sub-indicator relative to each sub-indicator of the indicator. In some examples, a method similar to operation 102 can be used to calculate the weight of each sub-indicator of a certain indicator. For example, C-1 internal consistency has two sub-indicators, namely temperature difference consistency (numbered C-1-1) and pressure difference consistency (numbered C-1-2), and the weights of temperature difference consistency and pressure difference consistency can be calculated based on the importance scores corresponding to temperature difference consistency and pressure difference consistency, which are 0.06 and 0.06.

[0103] In the present application, the importance score of each indicator and the importance score of each sub-indicator can be a fixed value or can vary according to the scene.

[0104] Next, operation 101 is further described based on the logical relationship between the aforementioned evaluation dimensions, indicators, and sub-indicators.

[0105] FIG. 2 is a schematic diagram of operation 101. As shown in FIG. 2, operation 101 includes:

[0106] Operation 201, for each evaluation dimension, calculating the score of each sub-indicator of the evaluation dimension; and

[0107] Operation 202, calculating the product of the score of each sub-indicator of the evaluation dimension and the corresponding weight according to the score of each sub-indicator of the evaluation dimension and the corresponding weight of each sub-indicator.

[0108] Operation 201 can include operation 2011 and operation 2012 as follows:

[0109] Operation 2011, for each sub-indicator, calculating the result data of the sub-indicator based on the data set of the battery;

[0110] Operation 2012, converting the result data into the corresponding score of the sub-indicator based on the mapping relationship between the result data of the sub-indicator and the score.

[0111] In operation 2011, the data set of the battery can be the data of the battery in a certain time period obtained based on a certain standard. The data of the battery can be the data of the battery obtained based on the operating state of the electrical equipment in the case that the battery is installed in the electrical equipment. The electrical equipment can be, for example, an electric vehicle or an energy storage device, etc.

[0112] Next, the data set of the battery is described taking the electrical equipment as an electric vehicle. For example, the data set of the battery can be obtained by the following steps:

[0113] Step 1, obtaining the running data of the i-th electric vehicle in a predetermined time period (e.g., more than 6 consecutive months) according to the first standard (e.g., GB / T32960);

[0114] Step 2, screening the set U of battery-related data (i.e., the data set of the battery) specified by the first standard (e.g., GB / T32960) from the data obtained in Step 1, since the set U corresponds to the i-th electric vehicle, the set U can also be denoted as Ui, i.e., the data set of the battery Ui.

[0115] The battery-related data items include static data items and dynamic data items.

[0116] The static data items include at least one of the following data items:

[0117] Model, vehicle manufacturer, vehicle model name, vehicle model year, vehicle manufacturing date, vehicle name, battery model, cell manufacturer, battery assembler, battery positive electrode material, rated capacity (kWh), rated capacity (Ah), rated voltage (v), series-parallel connection number, battery manufacturing date.

[0118] The dynamic data items include at least one of the following data items:

[0119] Time, vehicle state, charging state, running mode, vehicle speed, cumulative mileage, total voltage, total current, state of charge (SOC), direct current-direct current (DC-DC) state, gear, insulation resistance, general alarm symbol, maximum alarm level, maximum temperature value, maximum temperature probe serial number, minimum temperature value, minimum temperature probe serial number, maximum battery cell voltage, maximum voltage battery cell code, minimum battery cell voltage, minimum voltage battery cell code.

[0120] In operation 2011, the result data of each sub-indicator for each evaluation dimension can be calculated based on the data set of the battery Ui.

[0121] In some embodiments of operation 2011, the result data of the sub-indicator can be calculated based on the formula corresponding to the sub-indicator.

[0122] For example, for the sub-indicator D-1-1 of low-charge rate in Table 4, the charging state data and the SOC data at the same time in the data set Ui can be counted, if the i-th electric vehicle is in the charging state and the initial SOC is less than 15%, it is considered as a low-charge, the total number is L; if the charging state of the i-th electric vehicle continuously shows charging until the charging is completed, it is considered as a complete charging behavior, the total number is M; then the result data of the low-charge rate can be calculated by formula (3).

[0123] Result data of low charge rate = L / M*100% (3)

[0124] In addition, in some other embodiments of operation 2011, the result data of the sub-index can also be calculated in other ways, for example, the result data of the temperature difference consistency and / or the voltage difference consistency can be calculated based on the Cronbach coefficient, and the specific calculation method will be described in detail in the subsequent content of the specification.

[0125] In operation 2012, the result data of the sub-index is converted into the score of the sub-index based on the mapping relationship between the result data of the sub-index and the score, for example, the score can be a percentage score (i.e., the lowest is 0 points, and the highest is 100 points).

[0126] For example, the result data of the sub-index can be divided into 5 intervals, and each interval can correspond to different states of the battery (e.g., very good, better, general, worse, very bad, etc.). In addition, the end points of each interval for different sub-indices can be the same or different. In addition, 5 intervals are only an example, and the number of intervals can also be other numbers, for example, 2, 3, 4, or more than 6, etc.

[0127] In some embodiments of operation 2012, the mapping relationship between the result data of the sub-index and the score can be realized by a score conversion equation. For example, the score conversion equation can be in the form of equation (4).

[0128] The meanings of the parameters in equation (4) are as follows:

[0129] X: the result data of the sub-index (i.e., the result data of the sub-index calculated by operation 2011), for example, the result data of the sub-index A-1-1 remaining capacity is 85%, then X = 85%;

[0130] The interval value of the result data, for example, the interval value of the better result of the sub-index A-1-1 remaining capacity is 10%, i.e., 95%-85%;

[0131] K: the limit value of the interval of the result data (i.e., the result data corresponding to the end point of each interval), for example, for the sub-index A-1-1 remaining capacity, K1, K2, K3, K4 are 95%, 85%, 75%, 65% respectively;

[0132] Gi: the score of the sub-index.

[0133] In one example, if the result data X of the sub-index A-1-1 remaining capacity of the i th electric vehicle is 87.5%, which meets K1>X≥K2, then the score Gi of the sub-index A-1-1 remaining capacity is [(87.5%-85%) / 10%]*10+80=82.5.

[0134] In the present application, the parameters in the mapping relationship between the result data and the score of the sub-index (for example, K1, K2, and the like in the above description) can be fixed values; or, these parameters can also be adjustable values, for example, at least one of these parameters can be adjusted based on the use scenario or the needs of the customer.

[0135] Table 5 is one example of the limit values of each interval of the result data of the sub-index, in which, A n , B n , C n , D n , and Δ SOH represent the result data, corresponding to X in formula (4).

[0136] Table 5

[0137] After obtaining the scores of the sub-indices through operation 2012, in operation 202, the scores of the sub-indices of a certain evaluation dimension are multiplied by the weights corresponding to the sub-indices, and the results of the multiplication are added to obtain the product of the score and the weight of the evaluation dimension.

[0138] For example, referring to Table 4, for the evaluation dimension of stability, the weight of the evaluation dimension is 0.155, and the sub-indices are C-1-1 temperature difference consistency, C-1-2 pressure difference consistency, C-2-1 barrier-free rate, and C-2-2 maximum fault signal ratio, and the weights of the sub-indices are 0.06, 0.06, 0.02, and 0.015 respectively, if the scores of the sub-indices are G i1 , G i2 , G i3 , and G i4 respectively, then in the above formula (2), C*0.155=G i1 *0.06+G i2 *0.06+G i3 *0.02+G i4 *0.015.

[0139] Similarly, the values of the other terms in formula (2) can be calculated, that is, A*0.54, B*0.27, and D*0.035, and thus the evaluation value F of the battery can be obtained.

[0140] In the present application, as shown in FIG. 1, the method further comprises:​

[0141] Operation 103, output information related to the evaluation value of the battery.

[0142] For example, in operation 103, the output information can include the evaluation value F. In addition, the output information can also include at least one of the following information: the score of each evaluation dimension, the weight of each evaluation dimension, the index or sub-index of each evaluation dimension, the weight of each index or sub-index, and the score of each index or sub-index.

[0143] Thus, the information related to the evaluation value of the battery can be provided to the user. For example, the information related to the evaluation value of the battery can be in the form of graphics and / or text.

[0144] In the present application, as shown in FIG. 1, the method further comprises:

[0145] Operation 104, adjusting at least one of the following information:

[0146] The output information, the importance score, and the parameter in the mapping relationship between the result data and the score of the sub-index.

[0147] In the present application, the output information is, for example, the information related to the evaluation value of the battery output in operation 103. The importance score is, for example, the importance score used for calculating the weight of the evaluation dimension or the weight of the sub-index. The parameter in the mapping relationship between the result data and the score of the sub-index can be a parameter used for adjusting the mapping relationship, for example, the parameter K in equation (4), and so on.

[0148] The above information can be adjusted according to the application scenario of the evaluation value of the battery, or based on the result of analyzing the data of the battery.

[0149] For example, taking the B-2-2 pressure difference overrate as an example, the data of the battery can be analyzed by the following steps to determine whether the related information needs to be adjusted:

[0150] Obtaining the battery data set Ui of the ith vehicle;

[0151] Based on the data set Ui, calculating the result data of the B-2-2 pressure difference overrate of each time period (for example, using the method shown in operation 2011 described above);

[0152] Arranging the result data of the B-2-2 pressure difference overrate of each time period from small to large, and calculating the median and the average of the result data;

[0153] If the average is less than the median, decreasing the value of K and / or the average value and the median value are close (e.g., the difference between the average value and the median value is less than a preset threshold), the K value is not adjusted the average value and the median value are close (e.g., the difference between the average value and the median value is less than a preset threshold), the K value is not adjusted

[0154] In operation 104 of the present application, the software for calculating the battery evaluation value can be adjusted (e.g., the software has a module that can be edited), so as to adjust the corresponding information; or, by adjusting the register or memory for storing information or parameters or the circuit for setting information, so as to adjust the corresponding information.

[0155] Next, the method for calculating the internal consistency of the battery in the embodiments of the present application is described. The method for calculating the internal consistency of the battery can be implemented alone, or the method for calculating the internal consistency of the battery can be implemented as part of the above-mentioned operation 2011.

[0156] As one of the indicators of stability, the internal consistency can include the following sub-indicators: C-1-1 temperature difference consistency, and / or C-1-2 pressure difference consistency.

[0157] In the embodiments of the present application, the method for calculating the internal consistency of the battery can include: based on the data set of the battery, calculating the Cronbach's alpha related to the internal consistency of the battery to obtain the internal consistency of the battery. Wherein, the Cronbach's alpha related to the internal consistency includes: the Cronbach's alpha related to the temperature difference consistency, and / or the Cronbach's alpha related to the pressure difference consistency.

[0158] FIG. 3 is a schematic diagram of a method for calculating the result data of the temperature difference consistency. As shown in FIG. 3, the method for calculating the result data of the temperature difference consistency includes:

[0159] Operation 301: extracting a plurality of groups of temperature difference data from the data set of the battery;

[0160] Operation 302: calculating the covariance between each group of temperature difference data to obtain the covariance matrix of the plurality of groups of temperature difference data;

[0161] Operation 303: calculating the Cronbach's alpha based on the covariance matrix; and

[0162] Operation 304: calculating the result data of the temperature difference consistency based on the Cronbach's alpha.

[0163] Wherein, the Cronbach's alpha calculated in operation 303 is the Cronbach's alpha related to the temperature difference consistency.

[0164] In operation 301, the data set of the battery is, for example, the aforementioned set Ui. Operation 301 can include the following sub-steps:

[0165] 3011. Divide the data representing the temperature of the battery in the set Ui into multiple segments according to a predetermined time interval (for example, one day, or several hours);

[0166] 3012. Subtract the minimum temperature Tmin from the maximum temperature Tmax of each segment to calculate the temperature difference AT, i.e., AT = Tmax - Tmin, whereby each segment corresponds to an AT, thereby obtaining multiple ATs;

[0167] 3013. Remove invalid data from the multiple ATs, for example, AT is invalid data when AT ≤ 0;

[0168] 3014. Arrange the ATs of each week (or several days) into a group according to the time sequence, denoted as Qj (where j is a natural number, representing the jth group), wherein the number of Qj can be greater than a predetermined value, for example, the number of Qj is greater than or equal to 24 groups;

[0169] 3015. Take the number of ATs in the group Qj with the least amount of data as a reference, delete (for example, randomly delete) the ATs that are continuous and the same in each group Qj (at least one AT is retained), so that the number of ATs in each group Qj is equal, thereby obtaining multiple groups of temperature difference data.

[0170] In operation 302, the covariance between each group of temperature difference data is calculated to obtain a covariance matrix of the multiple groups of temperature difference data.

[0171] For example, the temperature difference data in the first group Q1 temperature difference data is (3, 5, 6, 7, 1), and the temperature difference data in the second group Q2 temperature difference data is (8, 6, 9, 2, 3). The covariance Cov(Q1, Q2) between the first group Q1 and the second group Q2 can be calculated by the following equations (5), (6), (7), (8). E(Q1) = (3 + 5 + 6 + 7 + 1) / 5 = 4.1 (5) E(Q2) = (8 + 6 + 9 + 2 + 3) / 5 = 5.6 (6) E(Q1Q2) = (3 * 8 + 5 * 6 + 6 * 9 + 7 * 2 + 1 * 3) / 5 = 25 (7) Cov(Q1, Q2) = E(Q1Q2) - E(Q1)E(Q2) = 25 - 24.64 = 0.36 (8)

[0172] The above illustrates the calculation method of the covariance between two groups of temperature difference data through an example. For multiple groups of data, the covariance between two groups of data in the multiple groups of data can be calculated respectively, thereby constructing a covariance matrix.

[0173] Table 6 is a schematic diagram of a covariance matrix, showing the case of constructing a covariance matrix for 4 groups of data. For a plurality of groups (greater than or equal to 24 groups) of temperature difference data obtained in operation 3104, the number of rows and the number of columns of the covariance matrix are equal to the number of groups of temperature difference data obtained in operation 3104.

[0174] Table 6

[0175] In operation 303, based on the covariance matrix of Table 6, the Cronbach's alpha can be calculated by the following equations (9), (10), (11).

[0176] In equation (11), N represents the number of groups of data used to construct the covariance matrix, and in the corresponding example of Table 6, N = 4.

[0177] In operation 304, the Cronbach's alpha can be multiplied by 100 to convert it to a percentage value as the result data of temperature difference consistency. As shown in the following equation (12). 0.839*100 = 83.9 (12)

[0178] In addition, in the present application, if the Cronbach's alpha does not need to be converted, operation 304 can also not be performed, that is, the Cronbach's alpha is directly taken as the result data of temperature difference consistency.

[0179] In the present application, based on the Cronbach's alpha to calculate the result data of temperature difference consistency, the temperature difference consistency can be accurately evaluated in the case of limited data amount, thereby improving the calculation efficiency and shortening the calculation time.

[0180] In operation 2011 of the present application, the result data of pressure difference consistency can be calculated based on the Cronbach's alpha.

[0181] FIG. 4 is a schematic diagram of a method for calculating the result data of pressure difference consistency. As shown in FIG. 4, the method for calculating the result data of pressure difference consistency comprises:

[0182] Operation 401, extracting a plurality of groups of voltage difference data from a data set of a battery;

[0183] Operation 402, calculating the covariance between each group of voltage difference data to obtain a covariance matrix of the plurality of groups of voltage difference data;

[0184] Operation 403, calculating the Cronbach's alpha based on the covariance matrix; and

[0185] Operation 404, calculating the result data of the voltage difference consistency based on the Cronbach's alpha.

[0186] In operation 403, the calculated Colòmbia coefficient is the Colòmbia coefficient related to the consistency of the pressure difference.

[0187] In operation 401, the data set of the battery is, for example, the aforementioned set Ui. Operation 401 can include the following sub-steps:

[0188] 4011, extract the voltage data of the battery during the charging process from the set Ui, wherein the charging current is negative for a continuous period (for example, more than 2 minutes) and then suddenly becomes positive, as one data of the charging process, and one complete charging process can include multiple data;

[0189] 4012, for each data of the charging process, subtract the maximum voltage Vmax in the data from the minimum voltage Vmin to calculate the voltage difference AV, that is, AV=(Vmax-Vmin)*1000, in millivolts, and keep two decimal places; thus, each complete charging process can include multiple voltage differences, and the multiple voltage differences are arranged in chronological order to form a set of data, that is, each complete charging process corresponds to a set of voltage difference data, denoted as Qi (i is a natural number, indicating the i-th set of data), wherein the number of Qi can be greater than a predetermined value, for example, the number of Qi is greater than or equal to 60 sets;

[0190] 4013, filter the sets of voltage difference data, remove the data sets with △SOC≤60%, and keep the remaining data sets, for example, the number of remaining data sets is greater than or equal to 48 sets;

[0191] 4014, in the remaining data sets, take the number of AV in the set Qi with the least amount of data as a reference, delete (for example, randomly delete) the AV continuous same data in each set Qi (at least keep one AV), so that the number of AV in each set Qi is equal, thereby obtaining multiple sets of voltage difference data.

[0192] In operation 402, the covariance between each set of voltage difference data is calculated to obtain the covariance matrix of the multiple sets of voltage difference data. For the description of covariance and covariance matrix, reference can be made to the description of operation 302 above.

[0193] The method of calculating the Colòmbia coefficient in operation 403 can also refer to the description of operation 303.

[0194] In operation 404, the Colòmbia coefficient calculated in operation 403 can be multiplied by 100 to convert it into a percentage value as the result data of the consistency of the voltage difference. As shown in formula (12) above.

[0195] In addition, in the present application, if the Cramér-Rao coefficient does not need to be converted, operation 404 can also not be performed, that is, the Cramér-Rao coefficient calculated in operation 403 is directly taken as the result data of the voltage difference consistency.

[0196] In the present application, based on the result data of the voltage difference consistency calculated by the Cramér-Rao coefficient, the voltage difference consistency can be accurately evaluated in the case of limited data amount, thereby improving the calculation efficiency and shortening the calculation time.

[0197] The above only describes the steps or processes related to the present application, but the present application is not limited thereto. The method for calculating the battery evaluation value can also include other steps or processes, and the specific content of these steps or processes can be referred to the prior art. In addition, the above only exemplarily describes the embodiments of the present application by taking some operations used in the method for calculating the battery evaluation value as examples, but the present application is not limited to these structures, and these operations can also be appropriately modified, and the implementation manners of these modifications should be included in the scope of the embodiments of the present application.

[0198] The above embodiments only exemplarily describe the embodiments of the present application, but the present application is not limited thereto, and can also be appropriately modified on the basis of the above embodiments. For example, the above embodiments can be used alone or one or more of the above embodiments can be combined.

[0199] According to the embodiments of the first aspect of the present application, the battery internal consistency is obtained by calculating the Cramér-Rao coefficient, so that the performance of the battery can be comprehensively evaluated; in addition, the battery internal consistency can be accurately calculated using a small amount of data, thereby improving the calculation efficiency; in addition, the battery can be evaluated according to more dimensions, so that the evaluation result more comprehensively reflects the state of the battery; in addition, the present application can complete the evaluation using a small amount of data (for example, using data of about 6 months), which fully mines the value of the existing data and improves the efficiency of the battery performance evaluation. In contrast, in the current detection process of electric vehicles, the actual charge and discharge test is used to evaluate the health degree of the power battery, which takes at least 4 hours.

[0200] Embodiments of the second aspect

[0201] The embodiments of the present application provide a device for calculating a battery evaluation value, which corresponds to the method for calculating a battery evaluation value of the embodiments of the first aspect. The embodiments of the second aspect are the same as the embodiments of the first aspect, and will not be described again.

[0202] FIG. 5 is a schematic diagram of a device for calculating a battery evaluation value according to an embodiment of the present application. As shown in FIG. 5, the device 500 includes:

[0203] The first computing device 501 calculates a product of scores of the battery in at least three evaluation dimensions and respective weights of the at least three evaluation dimensions, to obtain an evaluation value of the battery, based on the data set (U) of the battery, the at least three evaluation dimensions including health (A), safety (B) and stability (C).

[0204] In some embodiments, the health represents the ability of the battery to store electric quantity, the safety represents the ability of the battery to avoid thermal runaway during use, and the stability represents the ability of the battery to keep stable operation.

[0205] As shown in FIG. 5, the device 500 further includes:

[0206] The second computing device 502 determines respective weights of the at least three evaluation dimensions based on importance scores of the respective evaluation dimensions, wherein the importance scores reflect relative importance degrees of the respective evaluation dimensions.

[0207] As shown in FIG. 5, the device 500 further includes:

[0208] The output device 503 outputs information related to the evaluation value of the battery.

[0209] As shown in FIG. 5, the device 500 further includes:

[0210] The adjusting device 504 is configured to adjust at least one of the following information:

[0211] The output information, the importance scores, and the mapping relationship between the result data and the scores of the sub-indicators.

[0212] The descriptions of the respective devices of the device 500 for calculating the evaluation value of the battery can refer to the descriptions of the related steps in the embodiments of the first aspect.

[0213] The embodiments of the present application further provide a device for calculating internal consistency of a battery, corresponding to the method for calculating internal consistency of a battery in the embodiments of the first aspect.

[0214] FIG. 6 is a schematic diagram of the device for calculating internal consistency of a battery according to an embodiment of the present application. As shown in FIG. 6, the device 600 for calculating internal consistency of a battery includes:

[0215] The consistency calculating unit 601 obtains the internal consistency of the battery by calculating a Cronbach's coefficient related to the internal consistency of the battery, based on a data set of the battery.

[0216] The descriptions of the device 600 for calculating internal consistency of a battery can refer to the descriptions of the related steps in the embodiments of the first aspect.

[0217] It is worth noting that the above only illustrates the components or modules related to the present application, but the present application is not limited thereto. The device for calculating the battery evaluation value or the device for calculating the battery internal consistency can also include other components or modules, and the specific content of these components or modules can be referred to related technologies.

[0218] For simplicity, only the connection relationship or signal path between the components or modules is exemplarily shown in FIG. 6, but those skilled in the art should understand that various related technologies such as bus connection can be used. The above components or modules can be implemented by hardware facilities such as processors, memories, etc.; the embodiments of the present application are not limited thereto.

[0219] The above embodiments only exemplarily illustrate the embodiments of the present application, but the present application is not limited thereto, and appropriate modifications can be made on the basis of the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0220] Embodiments of the third aspect

[0221] The embodiments of the present application provide an electronic device including the device for calculating the battery evaluation value 500 or the device for calculating the battery internal consistency 600 as described in the embodiments of the second aspect, the content of which is incorporated herein. The electronic device can be, for example, a computer, a server, a workstation, a laptop computer, a smartphone, etc.; but the embodiments of the present application are not limited thereto.

[0222] FIG. 7 is a schematic diagram of an electronic device according to an embodiment of the present application. As shown in FIG. 7, the electronic device 700 can include a processor (such as a central processing unit CPU) 710 and a memory 720; the memory 720 is coupled to the central processor 710. The memory 720 can store various data; in addition, it also stores a program 721 for information processing, and executes the program 721 under the control of the processor 710.

[0223] In some embodiments, the functions of the device for calculating the battery evaluation value 500 or the device for calculating the battery internal consistency 600 are integrated into the processor 710 for implementation. The processor 710 is configured to implement the method for calculating the battery evaluation value or the method for calculating the battery internal consistency as described in the embodiments of the first aspect.

[0224] In some embodiments, the device 500 for calculating the battery evaluation value or the device 600 for calculating the battery internal consistency is configured separately from the processor 710, for example, the device 500 for calculating the battery evaluation value or the device 600 for calculating the battery internal consistency can be configured as a chip connected to the processor 710, and the functions of calculating the battery evaluation value or calculating the battery internal consistency are realized through the control of the processor 710.

[0225] For example, the processor 710 is configured to control to realize the method for calculating the battery evaluation value or the method for calculating the battery internal consistency according to the embodiments of the first aspect.

[0226] In addition, as shown in FIG. 7, the electronic device 700 can further include an input / output (I / O) device 730, a display 740, and the like; wherein the functions of the above-mentioned components are similar to those of the prior art, and will not be described here. It is worth noting that the electronic device 700 does not necessarily include all the components shown in FIG. 7; in addition, the electronic device 700 can also include components not shown in FIG. 7, which can be referred to related technologies.

[0227] The embodiments of the present application also provide a computer readable program, wherein when the program is executed in an electronic device, the program causes a computer to execute the method for calculating the battery evaluation value or the method for calculating the battery internal consistency according to the embodiments of the first aspect in the electronic device.

[0228] The embodiments of the present application also provide a storage medium storing a computer readable program, wherein the computer readable program causes a computer to execute the method for calculating the battery evaluation value or the method for calculating the battery internal consistency according to the embodiments of the first aspect in an electronic device.

[0229] The above devices and methods of the present application can be realized by hardware, or by a combination of hardware and software. The present application relates to a computer readable program which, when executed by a logic component, can cause the logic component to realize the above-mentioned devices or components, or to realize the above-mentioned various methods or steps. The present application also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, etc.

[0230] The methods / apparatuses described in combination with the embodiments of the present application can be directly embodied as hardware, software modules executed by a processor, or a combination of the two. For example, one or more of the functional block diagrams shown in the figures and / or a combination of one or more of the functional block diagrams can correspond to each software module of the computer program flow, or to each hardware module. These software modules can correspond to each step shown in the figures, respectively. These hardware modules can be realized by, for example, fixing the software modules with a field programmable gate array (FPGA).

[0231] The software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. The storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC. The software module can be stored in a memory location that can be accessed by a processor in a mobile terminal, or in a memory location that can be loaded into the mobile terminal using a storage card, for example. For example, if the device (e.g., mobile terminal) uses a MEGA-SIM card or a flash memory device with a large capacity, the software module can be stored in the MEGA-SIM card or the flash memory device.

[0232] One or more of the functional blocks described in the figures, and / or one or more combinations of the functional blocks, can be implemented as a general- purpose processor, a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any appropriate combination of the foregoing, for performing the functions described herein. One or more of the functional blocks described in the figures, and / or one or more combinations of the functional blocks, can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0233] The application has been described above with the attachment of specific implementations. However, it should be apparent to those skilled in the art that the description is illustrative only and not in a limitation of the scope of the application. Those skilled in the art can make various changes and modifications to the application in light of its teachings without departing from the scope and spirit of the application.

Claims

1. A method for calculating internal consistency of a battery, the method comprising: obtaining the internal consistency of the battery by calculating a Cronbach's coefficient related to the internal consistency of the battery based on a data set of the battery, wherein the internal consistency of the battery is used to represent an ability of the battery to keep temperature difference and / or voltage difference within a preset interval.

2. The method of claim 1, wherein the internal consistency comprises at least one of the following sub-indicators: temperature difference consistency, voltage difference consistency, wherein calculating the Cronbach's coefficient related to the internal consistency comprises: calculating a Cronbach's coefficient related to the temperature difference consistency, and / or calculating a Cronbach's coefficient related to the voltage difference consistency.

3. The method of claim 2, wherein calculating the Cronbach's coefficient related to the temperature difference consistency comprises: extracting a plurality of groups of temperature difference data from the data set of the battery; calculating a covariance between each group of temperature difference data to obtain a covariance matrix of the plurality of groups of temperature difference data; and calculating a Cronbach's coefficient based on the covariance matrix as the Cronbach's coefficient related to the temperature difference consistency.

4. The method of claim 2, wherein calculating the Cronbach's coefficient related to the voltage difference consistency comprises: extracting a plurality of groups of voltage difference data from the data set of the battery; calculating a covariance between each group of voltage difference data to obtain a covariance matrix of the plurality of groups of voltage difference data; and calculating a Cronbach's coefficient based on the covariance matrix as the Cronbach's coefficient related to the voltage difference consistency.

5. The method of claim 1, further comprising: obtaining an evaluation value of the battery by calculating a product of scores of the battery in at least three evaluation dimensions and respective weights of the at least three evaluation dimensions based on the data set of the battery, wherein the at least three evaluation dimensions comprise health, safety and stability, wherein the health represents an ability of the battery to store electric quantity, the safety represents an ability of the battery to avoid thermal runaway during use, and the stability represents an ability of the battery to keep stable operation, wherein the stability comprises internal consistency as an indicator, and the internal consistency is calculated by the method for calculating internal consistency of a battery according to any one of claims 1 to 4.

6. The method of claim 5, wherein the method further comprises: determining the respective weights of the at least three evaluation dimensions based on importance scores of each evaluation dimension in the at least three evaluation dimensions, wherein the importance scores reflect relative importance degrees of the evaluation dimensions.

7. The method of claim 6, wherein determining the respective weights of the at least three evaluation dimensions comprises: constructing an importance score matrix based on the importance scores of the evaluation dimensions, wherein different columns of the same row in the importance score matrix represent importance scores of an evaluation dimension corresponding to the row with respect to evaluation dimensions corresponding to the columns; dividing each importance score in the importance score matrix by a sum of importance scores in the column where the importance score is located to obtain a standardized score corresponding to the importance score; and ​ 3. The method of claim 2, wherein, ​ ​ ​ ​ 4. The method of claim 2, wherein, ​ ​ ​ ​ 5. A method of calculating a battery evaluation value, characterized by, ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ The standardized scores of the same row are averaged to obtain the weight of the evaluation dimension corresponding to the row. 8.The method of claim 5, wherein, Each of the evaluation dimensions has at least one indicator, and each of the indicators has a corresponding weight; Each of the indicators has at least one sub-indicator, and each of the sub-indicators has a corresponding weight. 9.The method of claim 8, wherein, The product of the score of the battery in at least three evaluation dimensions and the weight of each of the at least three evaluation dimensions is calculated, including: For each evaluation dimension, the scores of each of the sub-indicators of the evaluation dimension are calculated; and The product of the score of the evaluation dimension and the corresponding weight is calculated according to the scores of each of the sub-indicators of the evaluation dimension and the corresponding weight of each of the sub-indicators. 10.The method of claim 9, wherein, The calculation of the scores of each of the sub-indicators of the evaluation dimension includes: For each of the sub-indicators, the result data of the sub-indicator is calculated based on the data set of the battery; and The result data is converted into the corresponding score of the sub-indicator based on the mapping relationship between the result data and the score of the sub-indicator. 11.The method of claim 8, wherein, The stability further includes fault tolerance as an indicator, The fault tolerance is used to represent the tolerance ability of the battery to faults, and the fault tolerance includes at least one of the following sub-indicators: Barrier-free rate, maximum fault signal ratio. 12.An apparatus for calculating the internal consistency of a battery, characterized in that, The apparatus includes: a consistency calculation unit configured to obtain the internal consistency of the battery by calculating a Cronbach's coefficient related to the internal consistency of the battery based on a data set of the battery, wherein the internal consistency of the battery is used to represent the ability of the internal temperature difference and / or voltage difference of the battery to remain within a preset interval. 13.The apparatus of claim 12, wherein, The internal consistency includes at least one of the following sub-indicators: temperature difference consistency, pressure difference consistency; wherein the calculation of the Cronbach's coefficient related to the internal consistency includes: calculating a Cronbach's coefficient related to the temperature difference consistency, and / or calculating a Cronbach's coefficient related to the pressure difference consistency.

14. The apparatus of claim 13, wherein, The calculation of the Cronbach's coefficient related to the temperature difference consistency includes: extracting a plurality of groups of temperature difference data from the data set of the battery; calculating the covariance between each group of temperature difference data to obtain a covariance matrix of the plurality of groups of temperature difference data; and based on the covariance matrix, calculating a Cronbach's coefficient as the Cronbach's coefficient related to the temperature difference consistency.

15. The apparatus of claim 13, wherein, The calculation of the Cronbach's coefficient related to the pressure difference consistency includes: extracting a plurality of groups of voltage difference data from the data set of the battery; calculating the covariance between each group of voltage difference data to obtain a covariance matrix of the plurality of groups of voltage difference data; and based on the covariance matrix, calculating a Cronbach's coefficient as the Cronbach's coefficient related to the pressure difference consistency.

16. An apparatus for calculating battery evaluation values, characterized in that, The apparatus includes: a first computing device configured to calculate, based on the data set of the battery, a product of a score of the battery in at least three evaluation dimensions and a weight of each of the at least three evaluation dimensions, to obtain an evaluation value of the battery, wherein the at least three evaluation dimensions comprise a health, a safety, and a stability, the health represents an ability of the battery to store an electric quantity, the safety represents an ability of the battery to avoid thermal runaway during use, the stability represents an ability of the battery to maintain stable operation, wherein the stability comprises an internal consistency as an index, and the internal consistency is calculated by the device for calculating the internal consistency of the battery according to any one of claims 12 to 15.

17. An electronic device, comprising: the electronic device has the device for calculating the evaluation value of the battery according to claim 16 or the device for calculating the internal consistency of the battery according to any one of claims 12 to 15.

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