Method and apparatus for calculating evaluated value of battery, and electronic device

Abstract

A method and apparatus for calculating an evaluated value of a battery, and an electronic device. The method comprises: on the basis of a data set of a battery, calculating the product of scores of the battery in at least three evaluation dimensions and respective weights of the at least three evaluation dimensions, so as to obtain an evaluated value of the battery, wherein the at least three evaluation dimensions comprise the state of health, the safety and the stability, the state of health represents the capability of the battery to store electrical charge, the safety represents the capability of the battery to avoid thermal runaway in use, and the stability represents the capability of the battery to maintain stable operation (operation 101). In the method, an evaluated value of a battery is calculated on the basis of scores in at least three evaluation dimensions, such that the performance of the battery can be comprehensively evaluated. Moreover, data of the battery can be fully mined, thereby improving the evaluation efficiency.

Description

Method, device and electronic equipment for calculating battery evaluation value TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of batteries, and in particular to a method, device and electronic equipment for calculating a battery evaluation value. 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 batteries, it is necessary to evaluate the batteries through certain evaluation indicators.

[0003] At present, the evaluation indicators of the battery usually include 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 electrical quantity 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 convenience of understanding by 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 methods for batteries have some limitations, for example: the current evaluation indicators for batteries mainly use a single indicator of the state of health, and lack more dimensional evaluation indicators, resulting in insufficient comprehensive evaluation of the state of the used battery; in addition, the existing evaluation methods are mostly based on actual physical tests, which are time-consuming and affect the normal use of the battery.

[0009] To at least one of the above technical problems or other similar problems, the embodiments of the present application provide a method and device for calculating a battery evaluation value and an electronic device. In the method for calculating a battery evaluation value, the evaluation value of a battery is calculated based on scores of 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.

[0010] According to an aspect of the embodiments of the present application, a method for calculating a battery evaluation value is provided, which comprises:

[0011] Based on a data set of the battery, a product of scores of the battery in at least three evaluation dimensions and respective weights of the at least three evaluation dimensions is calculated to obtain an evaluation value of the battery, wherein the at least three evaluation dimensions comprise health, safety and stability,

[0012] The health represents the ability of the battery to store electric quantity,

[0013] The safety represents the ability of the battery to avoid thermal runaway during use,

[0014] The stability represents the ability of the battery to keep stable operation.

[0015] According to another aspect of the embodiments of the present application, a device for calculating a battery evaluation value is provided, which comprises:

[0016] A first calculating device, which calculates 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 a data set of the battery to obtain an evaluation value of the battery,

[0017] Wherein the at least three evaluation dimensions comprise health, safety and stability,

[0018] The health represents the ability of the battery to store electric quantity,

[0019] The safety represents the ability of the battery to avoid thermal runaway during use,

[0020] The stability represents the ability of the battery to keep stable operation.

[0021] According to another aspect of the embodiments of the present application, an electronic device is provided, which comprises 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 a battery evaluation value as described above.

[0022] One of beneficial effects of the embodiment of the present application is that in the method for calculating the battery evaluation value, the evaluation value of the battery is calculated based on the scores of at least three evaluation dimensions, so that the performance of the battery can be comprehensively evaluated, and in addition, the data of the battery can be fully mined, and the evaluation efficiency is improved.

[0023] Specific embodiments of the application are described in detail below with reference to the following description and to the attached drawings. The description and drawings are intended to explain the principles of the application, and to enable anyone skilled in the art to make and use the application. It is understood that the application is not limited to the embodiments described and illustrated, and that various changes can be made to the embodiments described and illustrated without departing from the scope of the present application as defined in the appended claims. BRIEF DESCRIPTION OF DRAWINGS

[0024] The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. It is understood that the drawings are for purposes of illustration only and are not necessarily drawn to scale, that the embodiments in the drawings are intended to be examples of the application and are not intended to be limiting of the scope of the application.

[0025] FIG. 1 is a schematic diagram of a method for calculating a battery evaluation value according to an embodiment of the present application;

[0026] FIG. 2 is a schematic diagram of operation 101;

[0027] FIG. 3 is a schematic diagram of a method for calculating result data of temperature difference consistency;

[0028] FIG. 4 is a schematic diagram of a method for calculating result data of pressure difference consistency;

[0029] FIG. 5 is a schematic diagram of a device for calculating a battery evaluation value according to an embodiment of the present application;

[0030] FIG. 6 is a schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] The foregoing and other features of the present application are hereinafter more fully described and understood when considered in connection with the following description and the accompanying drawings. In the description and drawings, particular embodiments of the present application are disclosed in detail. It should be understood that the application is not limited to the embodiments described and illustrated, and that the application includes all modifications, variations, and equivalents that fall within the scope of the appended claims.

[0032] In the embodiments of the present application, the terms "first", "second" and the like are used to distinguish different elements from each other, but do not indicate the spatial arrangement or time sequence of the elements, 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 mean the presence of the stated features, elements, components or assemblies, but do not exclude the presence or addition of one or more other features, elements, components or assemblies.

[0033] In the embodiments of the present application, the singular form "a", "an" and the like includes the plural form, should be broadly understood as "one" or "a kind of", and not limited to the meaning of "one"; in addition, the term "said" should be understood as including both the singular form and the plural form, unless the context clearly indicates otherwise. In addition, the term "according to" should be understood as "at least partially according to", and the term "based on" should be understood as "at least partially based on", unless the context clearly indicates otherwise.

[0034] 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, combined with or substituted for features in other implementations. The term "comprise / comprising" as used herein indicates the presence of the stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof.

[0035] Embodiments of the first aspect

[0036] The embodiments of the present application provide a method for calculating a battery evaluation value.

[0037] 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:

[0038] Operation 101: based on a data set (U) of the battery, calculating 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, the at least three evaluation dimensions including health, safety and stability.

[0039] In the present application, the battery can be a rechargeable battery (for example, a lithium ion battery or the like), which is formed by a plurality of battery monomers connected in parallel and / or in series.

[0040] According to the embodiments of the present application, in the method for calculating a 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 in addition, the data of the battery can be fully mined to improve the evaluation efficiency.

[0041] In some examples of the present application, the at least three evaluation dimensions can be three evaluation dimensions, for example, health, safety, and stability. In other examples, the at least three evaluation dimensions can be four evaluation dimensions, for example, health, safety, stability, and usage habit, and in addition, the fourth evaluation dimension can also be other evaluation dimensions in addition to usage habit. In yet other examples, the at least three evaluation dimensions can be five or more evaluation dimensions, for example, health, safety, stability, usage habit, and other evaluation dimensions.

[0042] In the following description of the present application, the at least three evaluation dimensions will be described as an example of four evaluation dimensions of health, safety, stability, and usage habit.

[0043] In some embodiments of the present application:

[0044] The health can represent the ability of the battery to store power, for example, the ratio of the current capacity of the battery to the original design capacity;

[0045] The safety can represent a quality of a system (for example, a battery system) to perform the functions of the system under acceptable minimum accident loss conditions, 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 of the internal danger signal of the battery (for example, the severity is related to the type of alarm signal);

[0046] The stability can refer to the ability of a system to recover to or maintain the original state after being disturbed, or at least maintain the state within a certain range, and in terms 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 following parameters: voltage difference consistency of the battery pack internal cells or modules, temperature difference consistency, and tolerance to faults, etc.;

[0047] 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, etc.

[0048] 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.

[0049] For example, the plurality of intervals can be 5 intervals, and the score can be divided into 5 levels:

[0050] The score ≥ 90 points represents that the state of the battery is very good;

[0051] 90 points > score ≥ 80 points, indicating that the state of the battery is good;

[0052] 80 points > score ≥ 70 points, indicating that the state of the battery is general;

[0053] 70 points > score ≥ 60 points, indicating that the state of the battery is poor;

[0054] 60 points > score, indicating that the state of the battery is very poor.

[0055] In addition, the present application is not limited thereto, and the scores of the respective evaluation dimensions can also be other numerical forms, such as a value less than 1.

[0056] 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 is calculated. In some examples, the scores of the respective 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)

[0057] 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 use 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 use habit.

[0058] The respective weights α1, α2, α3, α4 of the respective evaluation dimensions used in operation 102 can be fixed values, or values adjusted according to the use scenario. In addition, the respective weights α1, α2, α3, α4 of the respective evaluation dimensions can be pre-set and stored, or set through a predetermined step before operation 101.

[0059] As shown in FIG. 1, the method of calculating the battery evaluation value further comprises:

[0060] Operation 102, based on the importance score of each of the at least three evaluation dimensions, determines the respective weights of the at least three evaluation dimensions, wherein the importance score reflects the relative importance of each evaluation dimension.

[0061] In some embodiments of the present application, operation 102 can include operation 1021, operation 1022 and operation 1023 as follows.

[0062] Operation 1021, based on the importance score of each evaluation dimension, constructs an importance score matrix, wherein in the importance score matrix, the importance scores of different columns in the same row represent the importance scores of the evaluation dimension corresponding to the row with respect to the evaluation dimensions corresponding to the columns.

[0063] For example, the importance score matrix can be shown as Table 1 below. In Table 1, the total score represents the sum of the importance scores in a column of the importance score matrix.

[0064] Table 1

[0065] In the present application, if the importance score of one evaluation dimension relative to another evaluation dimension is greater than 1, it means that the importance degree of the one evaluation dimension is higher than that of the other evaluation dimension; otherwise, if the importance score of one evaluation dimension relative to another evaluation dimension is less than 1, it means that the importance degree of the one evaluation dimension is lower than that of the other evaluation dimension.

[0066] For example, in Table 1, the number in the second column of the row corresponding to the health degree is 3, which means that the importance score of the security relative to the health degree is 3; otherwise, the number in the first column of the row corresponding to the security is 1 / 3, which means that the importance score of the health degree relative to the security is 1 / 3.

[0067] Operation 1022, dividing each importance score of the importance score matrix by the sum of the importance scores in the column where the importance score is located, to obtain a standardized score corresponding to each importance score.

[0068] For example, after operation 1022, the importance score matrix can be shown as Table 2 below, in which each number represents a standardized score.

[0069] Table 2

[0070] Operation 1023, averaging the standardized scores located in the same row as the weight corresponding to the evaluation dimension of the row.

[0071] For example, in operation 1022, for the health degree row in Table 2, the average value of the 4 standardized scores of the row is calculated as (0.608+0.675+0.549+0.321) / 4=0.54, and the 0.54 is taken as the weight of the health degree.

[0072] The importance score matrix processed by operation 1023 can be shown as Table 3 below, in which Table 3 adds a column of average values (weights) to Table 2, representing the weight of the evaluation dimension corresponding to the row.

[0073] Table 3

[0074] In the example shown in Table 3, the weights a1, a2, a3, a4 corresponding to the evaluation dimensions of health, safety, stability, and usage habit are 0.54, 0.27, 0.155, and 0.035, respectively. Thus, the above formula (1) can be specifically written as the following formula (2).

[0075] In operation 102, the importance score can be a fixed value or a value adjusted based on a 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, greater weight is given to usage habit. Thus, the importance score 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.

[0076] Table 1a

[0077] Table 3a

[0078] As shown in Table 3a, the weight of usage habit is increased.

[0079] In operation 101 of the present application, each evaluation dimension can have at least one index, and 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.

[0080] In some embodiments of the present application, the logical relationship between the evaluation dimensions, indexes, and sub- indexes can be represented by a logical tree or other forms.

[0081] Table 4 is an example of a logical tree, and the present application is not limited thereto. The logical tree used to represent the logical relationship between the evaluation dimensions, indexes, and sub- indexes can also have other forms.

[0082] Table 4

[0083] In at least one embodiment of the present application, the meanings of the indexes of the evaluation dimensions of health, safety, and usage habit in Table 4, and the sub- indexes included in each index can refer to related technologies.

[0084] In at least one embodiment of the present application, the stability includes at least one of the following indexes: internal consistency (for example, number C-1 of Table 4), fault tolerance (for example, number C-2 of Table 4).

[0085] The internal consistency is used to represent the ability that the temperature difference change and / or the voltage difference change of the battery inside (for example, the battery inside can be the battery cell of the battery) are kept within a preset interval. For example, the internal consistency includes at least one of the following sub-indexes: temperature difference consistency (for example, number C-1-1 of Table 4), pressure difference consistency (for example, number C-1-2 of Table 4). Among them, the temperature difference consistency can represent the ability that the temperature difference change of the battery is kept within a preset interval, and the pressure difference consistency can represent the ability that the voltage difference change of the battery is kept within a preset interval.

[0086] The fault tolerance is used to represent the tolerance ability of the battery to faults. For example, the fault tolerance includes at least one of the following sub-indexes: barrier-free rate (for example, number C-2-1 of Table 4), maximum fault signal ratio (for example, number C-2-2 of Table 4). Among them, 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 in the process of using the battery by the electrical appliance (for example, an electric vehicle), for example: in the process of being used, the battery, the sensor will collect data to generate a fault state signal corresponding to the collected data, wherein the collected data includes, for example, the current total voltage, the highest battery monomer voltage, the lowest battery monomer 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" above refers to the total number of fault state signals in a certain period of time (for example, within 6 months) in the state of "fault-free state", and the "total number of fault state signals" above 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).

[0087] 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 in the process of using the battery by the electrical appliance (for example, an electric vehicle) within a certain period of time (for example, within 6 months).

[0088] 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.

[0089] In this application, the weights of the indicators for each evaluation dimension can be obtained based on the importance scores of the indicators for that evaluation dimension. The importance score of an indicator represents its relative importance to the other indicators in that evaluation dimension. In some examples, a method similar to operation 102 can be used to calculate the weights of the indicators for a given evaluation dimension. For instance, stability has two indicators: intrinsic consistency (numbered C-1) and fault tolerance (numbered C-2). Based on the importance scores corresponding to intrinsic consistency and fault tolerance, the weights of intrinsic consistency and fault tolerance can be calculated as 0.12 and 0.035, respectively.

[0090] In this application, the weights of the sub-indicators of each indicator can be obtained based on the importance scores of the sub-indicators of that indicator. The importance score of a sub-indicator represents its relative importance to the other sub-indicators of the indicator. In some examples, a method similar to operation 102 can be used to calculate the weights of the sub-indicators of a given indicator. For example, the inherent consistency of C-1 has two sub-indicators: temperature difference consistency (numbered C-1-1) and pressure difference consistency (numbered C-1-2). Based on the importance scores corresponding to temperature difference consistency and pressure difference consistency, their weights can be calculated as 0.06 and 0.06, respectively.

[0091] In this application, the importance scores of each indicator and the importance scores of each sub-indicator can be fixed values ​​or can vary depending on the scenario.

[0092] Below, based on the logical relationship between the aforementioned evaluation dimensions, indicators, and sub-indicators, operation 101 will be further explained.

[0093] Figure 2 is a schematic diagram of operation 101. As shown in Figure 2, operation 101 includes:

[0094] Operation 201: For each evaluation dimension, calculate the score of each sub-indicator of that evaluation dimension; and

[0095] Operation 202: Calculate the product of the score of the evaluation dimension and the corresponding weight based on the scores of each sub-indicator of the evaluation dimension and the weights corresponding to each sub-indicator.

[0096] Operation 201 may include the following operations 2011 and 2012:

[0097] Operation 2011: For each of the sub-indicators, calculate the result data of the sub-indicator based on the data set of the battery;

[0098] Operation 2012: Based on the mapping relationship between the result data and the score of the sub-indicator, convert the result data into the corresponding score of the sub-indicator.

[0099] In operation 2011, the data set of the battery can be data of the battery in a certain time period obtained based on a certain standard. The data of the battery can be data of the battery obtained based on an operating state of the electrical equipment in a case where the battery is installed in the electrical equipment. The electrical equipment is, for example, an electric vehicle or an energy storage device.

[0100] In the following, the data set of the battery is described by taking an electric vehicle as an example of the electrical equipment. For example, the data set of the battery can be obtained by the following steps:

[0101] Step 1: Obtain operating data of the i-th electric vehicle in a predetermined time period (for example, more than 6 consecutive months) according to a first standard (for example, GB / T32960);

[0102] Step 2: From the data obtained in step 1, screen out a set U of battery-related data (i.e., the data set of the battery) specified by the first standard (for example, GB / T32960). 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.

[0103] The battery-related data items include static data items and dynamic data items.

[0104] The static data items include at least one of the following data items:

[0105] Model, vehicle manufacturer, vehicle model name, vehicle model year, vehicle manufacturing date, vehicle name, battery model, cell manufacturer, battery assembler, positive electrode material of the battery, rated electric quantity (kWh), rated capacity (Ah), rated voltage (v), number of series and parallel connections, battery manufacturing date.

[0106] The dynamic data items include at least one of the following data items:

[0107] Time, vehicle state, state of charge, operating mode, vehicle speed, cumulative mileage, total voltage, total current, state of charge (SOC), DC-DC state, gear, insulation resistance, general alarm flag, maximum alarm level, maximum temperature value, maximum temperature probe serial number, minimum temperature value, minimum temperature probe serial number, maximum battery cell voltage value, maximum voltage battery cell code, minimum battery cell voltage value, minimum voltage battery cell code.

[0108] In operation 2011, based on the data set of the battery Ui, the result data of each sub-indicator of each evaluation dimension can be calculated.

[0109] In some embodiments of operation 2011, the result data of the sub-indicator can be calculated based on a formula corresponding to the sub-indicator.

[0110] 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 and 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, and 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, and the total number is M. Then, the result data of the low-charge rate can be calculated by formula (3). Result data of low-charge rate = L / M*100% (3)

[0111] In addition, in some other embodiments of operation 2011, the result data of the sub-indicator can also be calculated by other ways, for example, the result data of the temperature difference consistency and / or the voltage difference consistency can be calculated based on the Kolmogorov coefficient, and the specific calculation method will be described in detail in the subsequent content of the specification.

[0112] In operation 2012, the result data of the sub-indicator is converted into the score of the sub-indicator based on the mapping relationship between the result data of the sub-indicator and the score, for example, the score can be a percentage score (i.e., the lowest is 0 and the highest is 100).

[0113] For example, the result data of the sub-indicator can be divided into 5 intervals, and each interval can correspond to a different state of the battery (e.g., very good, good, general, poor, very poor, etc.). In addition, the end points of the intervals for different sub-indicators can be the same or different. In addition, the 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.

[0114] In some embodiments of operation 2012, the mapping relationship between the result data of the sub-indicator and the score can be realized by a score conversion equation. For example, the score conversion equation can be in the form of formula (4).

[0115] The meanings of the parameters in formula (4) are as follows:

[0116] X: the result data of the sub-indicator (i.e., the result data of the sub-indicator calculated by operation 2011), for example, the result data of the sub-indicator A-1-1 of remaining capacity is 85%, then X = 85%;

[0117] The interval value of the result data, for example, the interval value of the good result of the sub-indicator A-1-1 of remaining capacity is 10%, i.e., 95%-85%;

[0118] K: is 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;

[0119] Gi: is the score of the sub-index.

[0120] 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 Gi=[(87.5%-85%) / 10%]*10+80=82.5.

[0121] In this application, the parameters in the mapping relationship between the result data and the score of the sub-index (for example, K, and other parameters mentioned above) 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.

[0122] Table 5 is an example of the limit value of each interval of the result data of the sub-index, in which Table 5, A n , B n , C n , D n , △ SOH represents the result data, corresponding to X in formula (4).

[0123] Table 5

[0124] After obtaining the scores of each sub-index through operation 2012, in operation 202, the scores of each sub-index of a certain evaluation dimension are multiplied by the weight corresponding to the sub-index, and the results of the multiplication are added to obtain the product of the score and the weight of the evaluation dimension.

[0125] For example, referring to Table 4, for the stability evaluation dimension, the weight of the evaluation dimension is 0.155, the sub-indices are C-1-1 temperature difference consistency, C-1-2 pressure difference consistency, C-2-1 barrier-free rate, C-2-2 maximum fault signal ratio, and the weights of each sub-index are 0.06, 0.06, 0.02, 0.015 respectively, if the scores of each sub-index are G i1 , G i2 , G i3 , G i4 , then in the above formula (2), C*0.155=G i1 *0.06+G i2 *0.06+G i3 *0.02+Gi4 0.015.

[0126] Similarly, the values of other terms in equation (2), i.e., A*0.54, B*0.27, D*0.035, can be calculated, and thus the evaluation value F of the battery can be obtained.

[0127] In the present application, as shown in FIG. 1, the method further comprises:

[0128] Operation 103, output information related to the evaluation value of the battery.

[0129] 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 indicator or sub-indicator of each evaluation dimension, the weight of each indicator or sub-indicator, and the score of each indicator or sub-indicator.

[0130] 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.

[0131] In the present application, as shown in FIG. 1, the method further comprises:

[0132] Operation 104, adjusting at least one of the following information:

[0133] The output information, the importance score, and the parameter in the mapping relationship between the result data and the score of the sub-indicator.

[0134] 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-indicator. The parameter in the mapping relationship between the result data and the score of the sub-indicator can be a parameter used to adjust the mapping relationship, for example, the parameter K in equation (4), and so on.

[0135] 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.

[0136] 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:

[0137] - Obtain the battery data set Ui of the ith vehicle;

[0138] - Based on the data set Ui, calculate 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);

[0139] - arranging the result data of the B-2-2 differential pressure overrate of each of the plurality of time periods from small to large, calculating the median and the average of the result data;

[0140] - if the average is less than the median, decreasing the K value and / or the value; if the average and the median are close in value (for example, the difference between the two is less than a preset threshold), not adjusting the K value and the value.

[0141] In operation 104 of the present application, the software for calculating the battery evaluation value can be adjusted (for example, 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.

[0142] Next, the calculation method of the result data of the sub-indicators C-1-1 temperature difference consistency and C-1-2 differential pressure consistency in stability is described as a supplementary description of the embodiment of operation 2011.

[0143] The battery can be assembled from battery cells. According to different processes, there are two forms: one form is to assemble the battery cells into a module one by one, and then assemble into a battery pack; the other form is to directly assemble the 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. Because the aging degrees of different battery cells or modules are inconsistent during the use of the battery (especially the power battery), the voltage difference between the battery cells or modules increases, which causes the overall battery to have problems such as capacity decline or inability to run.

[0144] Stability can be used to measure the ability of the battery to maintain stable operation. Generally, the battery will be tested for consistency when it is shipped, that is, the difference between the maximum voltage and the minimum voltage cannot be too large, but this cannot represent the stability state of the battery after being used for a period of time.

[0145] In the present application, the stability of the battery can be measured by evaluating the ability of the battery to run stably through data calculation, so as to facilitate comparison or judgment. In addition, it also provides a reference for the secondary use, sale or recycling of the battery.

[0146] In operation 2011 of the present application, the result data of the temperature difference consistency can be calculated based on the Cronbach's alpha.

[0147] 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:

[0148] Operation 301, extracting multiple sets of temperature difference data from the data set of the battery;

[0149] Operation 302, calculating the covariance between each set of temperature difference data to obtain a covariance matrix of the multiple sets of temperature difference data;

[0150] Operation 303, calculating the Kolmogorov coefficient based on the covariance matrix; and

[0151] Operation 304, calculating the result data of the temperature difference consistency based on the Kolmogorov coefficient.

[0152] In operation 301, the data set of the battery is, for example, the aforementioned set Ui. Operation 301 can include the following sub-steps:

[0153] 3011, dividing 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);

[0154] 3012, subtracting the minimum temperature Tmin from the maximum temperature Tmax of each segment to calculate the temperature difference AT, that is, AT = Tmax-Tmin, so that each segment corresponds to an AT, thereby obtaining multiple ATs;

[0155] 3013, removing invalid data in the multiple ATs, for example, AT≤0 is invalid data;

[0156] 3014, arranging the ATs of each week (or several days) into a set according to the time sequence, denoted as Qj (where j is a natural number, representing the jth set), 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 sets;

[0157] 3015, taking the number of ATs in the Qj with the least amount of data as a reference, deleting (for example, randomly deleting) the ATs that are continuous and the same in each Qj (at least one AT is retained), so that the number of ATs in each Qj is equal, thereby obtaining multiple sets of temperature difference data.

[0158] In operation 302, the covariance between each set of temperature difference data is calculated to obtain a covariance matrix of the multiple sets of temperature difference data.

[0159] For example, the temperature difference data in the first group Q1 is (3, 5, 6, 7, 1), the temperature difference data in the second group Q2 is (8, 6, 9, 2, 3), and 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)

[0160] The above describes the calculation method of the covariance between two groups of temperature difference data by an example. For multiple groups of data, the covariance between two groups of data in the multiple groups of data can be calculated respectively, so as to construct a covariance matrix.

[0161] Table 6 is a schematic diagram of a covariance matrix, which shows the case of constructing a covariance matrix for 4 groups of data. For the multiple 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.

[0162] Table 6

[0163] In operation 303, based on the covariance matrix of Table 6, the Cronbach coefficient a can be calculated by the following equations (9), (10), (11).

[0164] 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.

[0165] In operation 304, the Cronbach coefficient can be multiplied by 100 to convert it into a percentage value as the result data of temperature difference consistency. As shown in the following equation (12). 0.839 * 100 = 83.9 (12)

[0166] In addition, in this application, if the Cronbach coefficient does not need to be converted, operation 304 can also not be performed, that is, the Cronbach coefficient is directly taken as the result data of temperature difference consistency.

[0167] In this application, based on the Cronbach coefficient 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.

[0168] In operation 2011 of the present application, the result data of the voltage difference consistency can be calculated based on a Cronbach's alpha.

[0169] FIG. 4 is a schematic diagram of a method of calculating the result data of the voltage difference consistency. As shown in FIG. 4, the method of calculating the result data of the voltage difference consistency comprises:

[0170] Operation 401, extracting a plurality of sets of voltage difference data from a data set of the battery;

[0171] Operation 402, calculating the covariance between each set of voltage difference data to obtain a covariance matrix of the plurality of sets of voltage difference data;

[0172] Operation 403, calculating a Cronbach's alpha based on the covariance matrix; and

[0173] Operation 404, calculating the result data of the voltage difference consistency based on the Cronbach's alpha.

[0174] In operation 401, the data set of the battery is, for example, the aforementioned set Ui. Operation 401 can comprise the following sub-steps:

[0175] 4011, extracting voltage data of the battery during a charging process from the set Ui, wherein the charging current is negative for more than 2 minutes (for example) until the current suddenly becomes positive, as one data of the charging process, and one complete charging process can comprise a plurality of data;

[0176] 4012, for each data of the charging process, subtracting the minimum voltage Vmin from the maximum voltage Vmax in the data to calculate the voltage difference AV, that is, AV = (Vmax-Vmin)*1000, in millivolts, and retaining two decimal places; thus, each complete charging process can comprise a plurality of voltage differences, and the plurality of 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, which is 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;

[0177] 4013, screening each set of voltage difference data, removing data sets with ASOC≤60%, and retaining the remaining data sets, for example, the number of the remaining data sets is greater than or equal to 48 sets;

[0178] 4014、In the remaining data groups, the number of ΔV continuous same data in the group Qi with the least data amount is taken as a reference, and the ΔV continuous same data in each group Qi is deleted (for example, randomly deleted) (at least one ΔV is reserved), so that the number of ΔV in each group Qi is equal, thereby obtaining multiple groups of voltage difference data.

[0179] In operation 402, the covariance between each group of voltage difference data is calculated to obtain a covariance matrix of the multiple groups of voltage difference data. For the description of covariance and covariance matrix, reference can be made to the description of operation 302 above.

[0180] The method for calculating the Coloumbach coefficient in operation 403 can also refer to the description of operation 303.

[0181] In operation 404, the Coloumbach coefficient calculated in operation 403 can be multiplied by 100 to convert it into a percentage value as the result data of voltage difference consistency. As shown in the above formula (12).

[0182] In addition, in the present application, if the Coloumbach coefficient does not need to be converted, operation 404 can also not be performed, that is, the Coloumbach coefficient calculated in operation 403 is directly taken as the result data of voltage difference consistency.

[0183] In the present application, based on the Coloumbach coefficient, the result data of voltage difference consistency can be calculated, which can accurately evaluate the voltage difference consistency in the case of limited data amount, thereby improving the calculation efficiency and shortening the calculation time.

[0184] The above only describes each step or process 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 refer 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.

[0185] The above each embodiment only exemplarily describes the embodiments of the present application, but the present application is not limited thereto, and appropriate modifications can also be made on the basis of the above each embodiment. For example, each of the above embodiments can be used alone, or one or more of the above each embodiment can be combined.

[0186] According to the embodiments of the first aspect of the present application, 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 smaller amount of data (for example, using data of about 6 months), fully tapping the value of existing data, and improving the efficiency of 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 status of the power battery, which takes at least 4 hours.

[0187] Embodiments of the second aspect

[0188] The embodiments of the present application provide a device for calculating a battery evaluation value, corresponding 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 details are not repeated.

[0189] 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:

[0190] The first calculation device 501 calculates the product of the scores of the battery in at least three evaluation dimensions and the respective weights of the at least three evaluation dimensions based on the data set (U) of the battery, to obtain the evaluation value of the battery, wherein the at least three evaluation dimensions include health (A), safety (B) and stability (C).

[0191] 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 maintain stable operation.

[0192] As shown in FIG. 5, the device 500 further includes:

[0193] The second calculation device 502 determines the respective weights of the at least three evaluation dimensions based on the importance scores of each evaluation dimension in the at least three evaluation dimensions, wherein the importance scores reflect the relative importance of each evaluation dimension.

[0194] As shown in FIG. 5, the device 500 further includes:

[0195] The output device 503 outputs information related to the evaluation value of the battery.

[0196] As shown in FIG. 5, the device 500 further includes:

[0197] The adjustment device 504 is configured to adjust at least one of the following information:

[0198] The output information, the importance scores, the mapping relationship between the result data and the scores of the sub-indicators, and the parameters in the mapping relationship.

[0199] For the description of each component of the device 500 for calculating the battery evaluation value, reference can be made to the description of the related steps in the embodiments of the first aspect.

[0200] It is worth noting that the above only describes 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 can also include other components or modules, and the specific content of these components or modules can be referred to the related art.

[0201] For the sake of simplicity, only the connection relationship or signal path between each component or module is exemplarily shown in FIG. 5, but it should be clear to those skilled in the art that various related technologies such as bus connection can be used. Each of the above components or modules can be implemented by hardware facilities such as processors, memories, etc.; the embodiments of the present application do not limit this.

[0202] The above embodiments of the present application are only exemplarily described, but the present application is not limited thereto, and appropriate modifications can be made on the basis of the above embodiments. For example, each of the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0203] Embodiments of the third aspect

[0204] The embodiments of the present application provide an electronic device including the device 500 for calculating the battery evaluation value 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.

[0205] FIG. 6 is a schematic diagram of an electronic device according to an embodiment of the present application. As shown in FIG. 6, the electronic device 600 can include a processor (such as a central processing unit CPU) 610 and a memory 620; the memory 620 is coupled to the central processing unit 610. The memory 620 can store various data; in addition, it also stores a program 621 for information processing, and executes the program 621 under the control of the processor 610.

[0206] In some embodiments, the function of the device 500 for calculating the battery evaluation value is integrated into the processor 610 to be implemented. The processor 610 is configured to implement the method for calculating the battery evaluation value as described in the embodiments of the first aspect.

[0207] In some embodiments, the device 500 for calculating the battery evaluation value is configured separately from the processor 610, for example, the device 500 for calculating the battery evaluation value can be configured as a chip connected to the processor 610, and the function of calculating the battery evaluation value is realized through the control of the processor 610.

[0208] For example, the processor 610 is configured to control to implement the method for calculating the battery evaluation value according to the embodiments of the first aspect.

[0209] In addition, as shown in FIG. 6, the electronic device 600 can further include an input / output (I / O) device 630, a display 640, and the like; wherein the functions of the above components are similar to the prior art, and will not be described here. It is worth noting that the electronic device 600 does not necessarily include all the components shown in FIG. 6; in addition, the electronic device 600 can also include components not shown in FIG. 6, which can be referred to related technologies.

[0210] 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 the computer to execute the method for calculating the battery evaluation value according to the embodiments of the first aspect in the electronic device.

[0211] The embodiments of the present application also provide a storage medium storing a computer readable program, wherein the computer readable program causes the computer to execute the method for calculating the battery evaluation value according to the embodiments of the first aspect in an electronic device.

[0212] The above apparatus and method of the present application can be realized by hardware, or by hardware combined with software. The present application relates to a computer readable program, which, when executed by a logic component, can enable the logic component to realize the above-described apparatus or component, or to realize the above-described 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.

[0213] The method / apparatus described in combination with the embodiments of the present application can be directly embodied as hardware, a software module 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).

[0214] The software modules 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 modules can be stored in a memory of the mobile terminal, or in a memory card that can be inserted into the mobile terminal. For example, if the device is a mobile terminal, the software modules can be stored in a MEGA-SIM card or a large capacity flash memory device that is inserted into the mobile terminal.

[0215] 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 suitable combination thereof, for performing the functions described in this disclosure. 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.

[0216] The present application has been described above with the attachment of specific embodiments, however, it should be apparent to those skilled in the art that many variations and modifications of the application can be made in view of what has been described above. These modifications and variations are within the scope of the application.

Claims

1. A method of calculating a battery evaluation value, characterized by, The method comprises: calculating, based on the data set of the battery, 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, wherein the at least three evaluation dimensions comprise health, safety and stability, the health represents an ability of the battery to store power, the safety represents an ability of the battery to avoid thermal runaway during use, and the stability represents an ability of the battery to maintain stable operation.

2. The method of claim 1, wherein the method further comprises: determining the 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.

3. The method of claim 2, 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 respective evaluation dimensions, in which the importance scores of different columns in the same row of the importance score matrix represent importance scores of the evaluation dimension corresponding to the row with respect to the evaluation dimensions corresponding to the columns; dividing each importance score of the importance score matrix by a sum of the importance scores of the column in which the importance score is located, to obtain a standardized score corresponding to each importance score; and averaging the standardized scores in the same row to obtain a weight corresponding to the evaluation dimension of the row.

4. The method of claim 1, 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.

5. The method of claim 4, wherein calculating the product of the scores of the battery in the at least three evaluation dimensions and the respective weights of the at least three evaluation dimensions comprises: for each evaluation dimension, calculating scores of the sub-indicators of the evaluation dimension; and calculating, according to the scores of the sub-indicators of the evaluation dimension and the corresponding weights of the sub-indicators, a product of the score of the evaluation dimension and the corresponding weight.

6. The method of claim 5, wherein calculating the scores of the sub-indicators of the evaluation dimension comprises: for each of the sub-indicators, calculating, based on the data set of the battery, result data of the sub-indicator; and converting the result data into a corresponding score of the sub-indicator based on a mapping relationship between the result data and the score.

7. The method of claim 4, wherein at least one indicator of the safety comprises at least one of the following sub-indicators: a micro short circuit failure rate, a pressure difference overrate, and a temperature difference overrate.

8. The method of claim 4, wherein the stability comprises at least one of the following indicators: internal consistency and fault tolerance, wherein the internal consistency is used to represent an ability of the battery to keep the temperature difference and / or the voltage difference within a preset interval; and the fault tolerance is used to represent a tolerance ability of the battery to faults.

9. The method of claim 8, wherein The internal consistency includes at least one of the following sub-indicators: temperature difference consistency, pressure difference consistency; The fault tolerance includes at least one of the following sub-indicators: barrier-free rate, maximum fault signal ratio.

10. The method of claim 9, wherein, The result data of the temperature difference consistency is calculated by the following method: extracting multiple groups of temperature difference data from the data set of the battery; calculating the covariance between each group of temperature difference data to obtain the covariance matrix of the multiple groups of temperature difference data; based on the covariance matrix, calculating the Cronbach coefficient; and based on the Cronbach coefficient, calculating the result data of the temperature difference consistency.

11. The method of claim 9, wherein, The result data of the pressure difference consistency is calculated by the following method: extracting multiple groups of voltage difference data from the data set of the battery; calculating the covariance between each group of voltage difference data to obtain the covariance matrix of the multiple groups of voltage difference data; based on the covariance matrix, calculating the Cronbach coefficient; and based on the Cronbach coefficient, calculating the result data of the voltage difference consistency.

12. The method of claim 2, wherein, The method further includes: outputting information related to the evaluation value of the battery.

13. The method of claim 12, wherein, The method further includes: adjusting at least one of the following information: output information, importance score, mapping relationship between result data and score of sub-indicators.

14. An apparatus for calculating battery evaluation values, characterized in that, The device includes: a first calculation device that, based on a data set of a battery, calculates 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, to obtain an evaluation value of the battery, wherein the at least three evaluation dimensions include health, safety and stability, 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, the stability represents the ability of the battery to maintain stable operation.

15. The device of claim 14, wherein the device further includes: a second calculation device that, based on the importance score of each of the at least three evaluation dimensions, determines the weight of each of the at least three evaluation dimensions, wherein the importance score reflects the relative importance of each evaluation dimension.

16. The apparatus of claim 15, wherein, The device further includes: an output device that outputs information related to the evaluation value of the battery.

17. The apparatus of claim 16, wherein, The device further includes: an adjustment device for adjusting at least one of the following information: output information, importance score, mapping relationship between result data and score of sub-indicators.

18. An electronic device, comprising: The electronic device has a device for calculating the evaluation value of the battery as claimed in any one of claims 14 to 17.

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