Battery Diagnosis Method, Device, Electronic Device, Storage Medium and Program Product

Abstract

The present application provides a battery diagnosis method, apparatus, electronic device, storage medium, and program product. The battery diagnosis method may include: obtaining a first evaluation value of the battery within a first time interval; obtaining a second evaluation value of the battery within a first reference interval; calculating a difference between the first evaluation value and the second evaluation value; the difference is used to represent the degree of change in the battery performance of the battery; in the case where the difference is greater than a threshold, based on one or more influencing factors associated with at least one battery indicator, determining the influence information of each influencing factor among the one or more influencing factors to identify the cause of the battery failure; the influence information is used to represent the degree of influence of each influencing factor on the difference. By obtaining a plurality of influencing factors and determining the degree of influence of each influencing factor on the degree of change in battery performance when the degree of change in battery performance is greater than the threshold, the embodiments of the present application can achieve attribution of battery failures and meet the needs of users.

Description

Technical Field

[0001] This application relates to the technical field of batteries, and in particular, to a battery diagnosis method, apparatus, electronic device, storage medium, and program product. Background Art

[0002] Since batteries involve complex electrochemical reactions and transfer mechanisms, they are susceptible to various factors in practical applications, such as overcharging, over-discharging, overheating, etc. These factors may all cause battery failures.

[0003] However, the battery analysis in related technologies mainly focuses on identifying battery failures and it is difficult to attribute the battery failures. Summary of the Invention

[0004] This application provides a battery diagnosis method, apparatus, electronic device, storage medium, and program product to attribute battery failures and meet the needs of users.

[0005] In a first aspect, this application provides a battery diagnosis method, including: obtaining a first evaluation value of the battery within a first time interval, where the first evaluation value is obtained through the index values of at least one battery index within the first time interval; obtaining a second evaluation value of the battery within a first reference interval, where the second evaluation value is obtained through the index values of at least one battery index within the first reference interval; the first reference interval is an interval among multiple reference time intervals that has the same battery state as the first time interval; the multiple reference time intervals are divided according to the battery state of the battery; calculating the difference between the first evaluation value and the second evaluation value; the difference is used to represent the degree of change in the battery performance of the battery; in the case where the difference is greater than a threshold, based on one or more influencing factors associated with at least one battery index, determining the influence information of each influencing factor among the one or more influencing factors to identify the cause of the battery failure; the influence information is used to represent the influence degree of each influencing factor on the difference.

[0006] In some possible implementation manners, obtaining the second evaluation value of the battery within the first reference interval includes: obtaining multiple reference time intervals corresponding to each battery index among at least one battery index; obtaining the first reference interval corresponding to each battery index from the multiple reference time intervals according to the battery state corresponding to the first time interval; obtaining the second evaluation value of the battery according to the index values within the first reference interval corresponding to each battery index.

[0007] In some possible implementation manners, obtaining multiple reference time intervals corresponding to each battery metric in at least one battery metric includes: obtaining multiple initial metric values corresponding to each battery metric in at least one battery metric, where the multiple initial metric values are sorted in sequence according to the acquisition time; performing smoothing processing on the multiple initial metric values to obtain multiple metric values; grouping the multiple metric values to obtain multiple groups of metric values corresponding to different battery states, where each group of metric values includes multiple metric values; determining multiple reference time intervals according to the multiple groups of metric values, where one group of metric values corresponds to one reference time interval.

[0008] In some possible implementation manners, performing smoothing processing on the multiple initial metric values to obtain multiple metric values includes: starting from the first initial metric value among the multiple initial metric values, sliding a time window according to a preset sliding position until it slides to the last initial metric value among the multiple initial metric values; when the time window slides to each sliding position, performing averaging processing on the multiple initial metric values within the time window to obtain multiple metric values, where one sliding position corresponds to one metric value.

[0009] In some possible implementation manners, determining the influence information of each of one or more influencing factors associated with at least one battery metric to identify the cause of battery failure includes: obtaining one or more influencing factors associated with at least one battery metric; classifying and decomposing the one or more influencing factors to obtain a group of influencing factors, where the group of influencing factors includes multiple factors, and the multiple factors include one or more upper-level factors formed by the one or more influencing factors and one or more lower-level factors corresponding to each upper-level factor in the one or more upper-level factors; the group of influencing factors is used to comprehensively evaluate the battery performance; determining the influence value of each factor in the group of influencing factors on the difference to identify the cause of battery failure, where the influence value is used to represent the influence degree of each factor on the difference.

[0010] In some possible implementation manners, determining the influence value of each factor in the group of influencing factors includes: calculating a first parameter value and a second parameter value corresponding to each factor, where the first parameter value is used to represent the ratio change of each factor in the group of influencing factors; the second parameter value is used to represent the proportion change of each factor in the group of influencing factors; calculating the influence value of each factor according to the first parameter value and the second parameter value.

[0011] Second aspect, an embodiment of the present application provides a battery diagnosis device. The battery diagnosis device may include: a first obtaining module configured to obtain a first evaluation value of the battery within a first time interval, where the first evaluation value is obtained based on the index values of at least one battery index within the first time interval; a second obtaining module configured to obtain a second evaluation value of the battery within a first reference interval, where the second evaluation value is obtained based on the index values of at least one battery index within the first reference interval; the first reference interval is an interval among a plurality of reference time intervals that has the same battery state as the first time interval; the plurality of reference time intervals are divided according to the battery state of the battery; a calculation module configured to calculate the difference between the first evaluation value and the second evaluation value, where the difference is used to represent the degree of change in the battery performance of the battery; a determination module configured to, when the difference is greater than a threshold, determine the influence information of each of one or more influencing factors associated with at least one battery index based on the one or more influencing factors, so as to identify the cause of the battery failure; the influence information is used to represent the influence degree of each influencing factor on the difference.

[0012] In some possible implementation manners, the second obtaining module is further configured to obtain a plurality of reference time intervals corresponding to each battery index among at least one battery index; obtain the first reference interval corresponding to each battery index from the plurality of reference time intervals according to the battery state corresponding to the first time interval; and obtain the second evaluation value of the battery according to the index values within the first reference interval corresponding to each battery index.

[0013] In some possible implementation manners, the second obtaining module is further configured to obtain a plurality of initial index values corresponding to each battery index among at least one battery index, where the plurality of initial index values are sorted in sequence according to the acquisition time; perform smoothing processing on the plurality of initial index values to obtain a plurality of index values; group the plurality of index values to obtain a plurality of index value groups corresponding to different battery states, where each index value group includes a plurality of index values; and determine a plurality of reference time intervals according to the plurality of index value groups, where one index value group corresponds to one reference time interval.

[0014] In some possible implementation manners, the second obtaining module is further configured to start from the first initial index value among the plurality of initial index values, slide a time window according to a preset sliding position until it slides to the last initial index value among the plurality of initial index values; when the time window slides to each sliding position, perform averaging processing on the plurality of initial index values within the time window to obtain a plurality of index values, where one sliding position corresponds to one index value.

[0015] In some possible embodiments, the determination module is further configured to obtain one or more influencing factors associated with at least one battery metric; classify and decompose the one or more influencing factors to obtain an influencing factor group, where the influencing factor group includes multiple factors, and the multiple factors include one or more upper-level factors formed by the one or more influencing factors, and one or more lower-level factors corresponding to each upper-level factor in the one or more upper-level factors; the influencing factor group is used to comprehensively evaluate the battery performance of the battery; determine the influence value of each factor in the influencing factor group to identify the cause of the battery failure, where the influence value is used to represent the degree of influence of each factor on the difference.

[0016] In some possible embodiments, the determination module is further configured to calculate a first parameter value and a second parameter value corresponding to each factor, where the first parameter value is used to represent the ratio change of each factor in the influencing factor group; the second parameter value is used to represent the proportion change of each factor in the influencing factor group; according to the first parameter value and the second parameter value, calculate the influence value of each factor.

[0017] In a third aspect, the present application further provides an electronic device, which includes a memory and one or more processors, and a computer program is stored on the memory. When the computer program is executed by the electronic device, the battery diagnosis method described in any item of the first aspect is implemented.

[0018] In a fourth aspect, the present application further provides a computer-readable storage medium, which stores executable instructions. When the executable instructions are executed by a processor, the battery diagnosis method described in any item of the first aspect is implemented.

[0019] In a fifth aspect, the present application further provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, the battery diagnosis method described in any item of the first aspect is implemented.

[0020] The beneficial effects of the technical solution provided by the present application compared with the prior art are as follows:

[0021] In the present application, when it is determined that there is a difference between the first evaluation value of the battery in the first time period and the second evaluation value of the battery in the first reference period, and the difference is greater than the threshold, it is determined that the change degree of the battery performance is too large and the battery has a failure. At this time, by obtaining multiple influencing factors and determining the influence degree of each influencing factor on the change degree of the battery performance, the attribution of the battery failure can be realized, meeting the needs of users.

[0022] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the protection scope of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application;

[0024] Figure 2 It is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application;

[0025] Figure 3 It is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application;

[0026] Figure 4 It is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application;

[0027] Figure 5 It is a schematic structural diagram of an influence factor group provided by an embodiment of the present application;

[0028] Figure 6 It is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application;

[0029] Figure 7 It is a schematic structural diagram of a battery diagnosis device provided by an embodiment of the present application;

[0030] Figure 8 It is an optional structural schematic diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0031] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0032] In order to illustrate the technical solutions described in the present application, the following will be described through specific embodiments.

[0033] As an efficient electrochemical energy storage product, the battery has the advantages of high energy density, long cycle life, low self-discharge rate, etc., and is widely used in multiple application fields such as electric vehicles, distributed energy storage, and large-scale energy storage. With the global pursuit of renewable energy and energy conservation and emission reduction, the market demand for batteries is continuously increasing, and its role in the power system is also becoming increasingly prominent.

[0034] Although batteries have many advantages, there are still certain safety hazards and failure risks during their actual operation. Since batteries involve complex electrochemical reactions and transfer mechanisms, they are prone to being affected by various factors in practical applications, such as overcharging, over-discharging, overheating, etc. These factors may lead to a rapid decline in battery performance or even cause safety problems. In addition, in the applications in the fields of electric vehicles, distributed energy storage, large-scale energy storage, etc., a large number of single batteries need to be connected in series and parallel to form battery packs, battery modules, and even battery clusters, which further increases the complexity of the battery system and the probability of failures.

[0035] To ensure the safety, stability, and reliability of batteries during actual operation, effective fault diagnosis technologies are needed to timely identify and eliminate potential fault factors. Fault attribution diagnosis technologies can uncover the reasons for the operating status and health conditions of batteries, and can also provide theoretical, methodological, and technical support for the precise operation and maintenance of batteries.

[0036] However, the battery analysis in related technologies mainly focuses on identifying battery failures and it is difficult to attribute battery failures. To solve the above technical problems, the embodiments of this application provide a battery diagnosis method, device, electronic device, storage medium, and program product to achieve the attribution of battery failures and meet the needs of users.

[0037] In a first aspect, this application provides a battery diagnosis method, which can be executed by an electronic device. Figure 1 For the schematic flowchart of a battery diagnosis method provided by the embodiments of this application, see Figure 1 As shown, the battery diagnosis method may include:

[0038] Step S101, obtaining a first evaluation value of the battery within a first time interval.

[0039] It can be understood that the electronic device can obtain the index values of at least one battery index of the battery within the first time interval, and then comprehensively evaluate the working status of the battery according to the index values corresponding to each battery index in the at least one battery index to obtain the first evaluation value.

[0040] In some embodiments, the first time interval is any time interval. In one embodiment, in order to timely give early warnings and diagnoses of battery failures, the first time interval may be the current time interval.

[0041] It can be understood that battery indexes are important parameters for measuring battery performance and safety.

[0042] In some embodiments, the battery metrics may at least include: battery capacity, voltage, current, battery temperature, state of health (SOH), state of charge (SOC), state of energy (SOE), internal resistance, voltage difference, and temperature difference. Among them, the battery capacity refers to the amount of electricity that the battery can discharge under certain conditions (discharge rate, temperature, termination voltage, etc.), usually measured in milliamperes per hour (mAh) or ampere-hours (Ah). The voltage includes the open-circuit voltage and the working voltage. The open-circuit voltage is the potential difference between the positive and negative electrodes of the battery when the battery is in a non-working state. The working voltage is the potential difference between the positive and negative electrodes of the battery when the battery is in a working state. The state of health of the battery refers to the ability of the current battery to store electrical energy relative to a new battery. The state of charge is the ratio of the remaining capacity of the battery after being used for a period of time to the capacity in a fully charged state, usually expressed as a percentage. The state of energy of the battery is the ratio of the remaining energy (releasable energy) of the battery to the rated energy. The internal resistance is the resistance that the current encounters when flowing through the battery during operation. The voltage difference is the voltage difference between individual cells in a battery pack. The temperature difference is the temperature difference between different regions inside the battery or between different individual cells.

[0043] In some embodiments, the metric values of the battery metrics within a first time interval may be a set of metric values, and the set of metric values includes multiple metric values. Each of the multiple metric values is collected within the first time interval, so that based on the above multiple metric values, the changes of the battery within the first time period can be obtained.

[0044] In some embodiments, the metric values can be represented in numerical form, and the numerical values can be used to quantitatively measure the battery metrics. That is to say, by obtaining the metric values, multiple numerical values of quantitative information regarding battery performance, battery state, and battery safety can be obtained.

[0045] In some embodiments, by aggregating the metric values corresponding to each battery metric, a first evaluation value of the battery within the first time interval can be calculated. Here, the method for calculating the first evaluation value of the battery can be selected according to actual needs, and the embodiments of the present application do not limit this.

[0046] Exemplarily, the electronic device can obtain the metric values of the battery voltage within the first time interval (such as 1.12V (volts), 1.22V, 1.28V) and the metric values of the battery current within the first time interval (such as 0.55A (amperes), 0.58A, 0.56A), and then determine the first evaluation value of the battery within the first time interval based on the metric values of the voltage within the first time interval and the metric values of the current within the first time interval.

[0047] In some embodiments, the electronic device may monitor the battery in real time to obtain the metric values of the battery within the first time interval. In some embodiments, the electronic device may obtain the metric values of the battery within the first time interval through a database. In one embodiment, the database may be a local database or a cloud database. In one example, the cloud database may be a big data cloud platform connected to the battery management system. Here, the battery management system may be a device for monitoring and managing a battery pack. The battery management system can collect the metric values of each battery metric and send the collected metric values to the big data cloud platform. The big data cloud platform may be a platform for processing and storing battery status information constructed using big data technology. The big data cloud platform may be a software platform running on the electronic device, enabling the electronic device to obtain the metric values of the battery within the first time interval through the big data cloud platform.

[0048] Step S102: Obtain a second evaluation value of the battery within the first reference interval.

[0049] It can be understood that the electronic device may obtain a first reference interval having the same battery state as the first time interval according to the battery state corresponding to the first time interval. At the same time, after determining at least one battery metric corresponding to the first evaluation value, the electronic device may comprehensively evaluate the working state of the battery based on the metric values of the at least one battery metric within the first reference interval to obtain a second evaluation value.

[0050] It can be understood that based on the same method as obtaining the first evaluation value according to the metric values of at least one battery metric within the first time interval, the second evaluation value can be obtained according to the metric values of at least one battery metric within the first reference interval. For the sake of simplicity of the specification, it will not be elaborated here.

[0051] In some embodiments, the battery state refers to the working state of the battery. The working state of the battery may at least include a charging state, a discharging state, and a power-holding state. Among them, the charging state may refer to the state in which the battery receives electrical energy from an external power source such as a charger. The discharging state may refer to the state in which the battery supplies electrical energy to an external circuit. The power-holding state may refer to the state in which the battery neither charges nor discharges. In some embodiments, the charging state may be further subdivided into: a constant current (CC) charging state, a constant voltage (CV) charging state, a trickle charging state, etc. It can be understood that the above states may all be the battery states corresponding to the first time interval.

[0052] In some embodiments, the electronic device may obtain a plurality of reference time intervals, and the plurality of reference time intervals respectively correspond to a plurality of different battery states. The first reference interval may be an interval among the plurality of reference time intervals that has the same battery state as the first time interval.

[0053] In some embodiments, the electronic device may obtain the index value of the battery within the first reference interval through a database. For the description of the database, reference may be made to the description in the above embodiments, which will not be elaborated herein.

[0054] In some embodiments, there is no battery failure within the reference time interval of the battery.

[0055] Step S103, calculate the difference between the first evaluation value and the second evaluation value.

[0056] It can be understood that after the electronic device obtains the first evaluation value through step S101 and the second evaluation value through step S102, it can calculate the difference between the first evaluation value and the second evaluation value. This difference can characterize the degree of change in the battery performance of the battery during the process of time advancing from the first reference interval to the first time interval.

[0057] It can be understood that the first evaluation value is the evaluation value of the battery within the first time interval, and the second evaluation value is the evaluation value of the battery within the first reference time interval. The first time interval and the first reference time have the same battery state, so that the evaluation values of the above two time intervals are comparable, and by comparing the evaluation values, the degree of change in the battery performance of the battery can be further determined.

[0058] Step S104, when the difference is greater than the threshold, based on one or more influencing factors associated with at least one battery indicator, determine the influence information of each influencing factor among the one or more influencing factors to identify the cause of the battery failure.

[0059] It can be understood that after the electronic device obtains the difference that can represent the degree of change in the battery performance, the electronic device can determine whether the difference is greater than the threshold. When the difference is greater than the threshold, that is, when the degree of change in the battery performance of the battery is relatively large, the battery can be fault-attributed. It can be understood that fault-attributing the battery when the difference is greater than the threshold makes the battery diagnosis method more practical. When the difference is less than or equal to the threshold, the electronic device does not temporarily fault-attribute the battery. At this time, the electronic device can mainly realize real-time monitoring and diagnosis of the battery according to the difference to meet the user's usage requirements.

[0060] It can be understood that the electronic device can obtain one or more influencing factors associated with at least one battery indicator, and based on the one or more influencing factors, obtain the influence information of each influencing factor, and then determine the influence degree of each influencing factor on the difference, so as to identify the cause of the battery failure.

[0061] It can be understood that the indicator values of at least one battery indicator are used to determine the first evaluation value. Then, one or more influencing factors associated with at least one battery indicator can affect the indicator value, and further affect the first evaluation value and the difference. Therefore, by obtaining the influence information of each influencing factor on the difference, the cause of the battery failure can be identified.

[0062] In some embodiments, the influencing factors include: time factor, operation factor, production factor, and other factors. Among them, the time factor can be a quantitative indicator describing the change of time. The operation factor can be a quantitative indicator describing the change of the operation environment. The production factor can be a quantitative indicator describing the change of the production scenario. The other factors can be quantitative indicators describing other variable parameters. For example, the other factors can be weather factors, and the weather factor can be a quantitative indicator describing the change of weather. In one embodiment, the influencing factors associated with different battery indicators can be different. Exemplarily, the current can be associated with the time factor and the operation factor, and the battery capacity can be associated with the production factor and the operation factor.

[0063] In some embodiments, after the electronic device obtains the influencing factors corresponding to each battery indicator, it can obtain all the influencing factors corresponding to all battery indicators. According to the number of battery indicators that each influencing factor in all influencing factors can be associated with, determine the weight of each influencing factor, so as to determine the influence degree of each influencing factor on the difference. Based on the influence degree of each influencing factor on the difference, identify the cause of the battery failure.

[0064] It can be understood that when attributing the battery failure, the influencing factor with a high influence degree is the main cause of the battery failure, and the influencing factor with a low influence degree is the secondary cause of the battery failure, so as to realize the attribution of the battery failure and meet the needs of users.

[0065] In the embodiments of the present application, when it is determined that there is a difference between the first evaluation value of the battery in the first time period and the second evaluation value of the battery in the first reference period, and the difference is greater than the threshold, it is determined that the change degree of the battery performance is too large and the battery has a failure. At this time, by obtaining multiple influencing factors and determining the influence degree of each influencing factor on the change degree of the battery performance, the attribution of the battery failure can be realized and the needs of users can be met.

[0066] In some possible implementation manners, Figure 2 is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application. SeeFigure 2 As shown in Figure 2 , step S102 may include:

[0067] Step S201, obtaining multiple reference time intervals corresponding to each battery metric among at least one battery metric.

[0068] It can be understood that the electronic device can obtain at least one battery metric corresponding to the first evaluation value, and thus, based on the at least one battery metric, obtain multiple reference time intervals corresponding to each battery metric among the at least one battery metric.

[0069] In some embodiments, the multiple reference time intervals corresponding to each battery metric may be different. In some embodiments, the multiple reference time intervals corresponding to each battery metric may be divided according to the battery state of the battery. Exemplarily, the reference time intervals corresponding to the current may include a first reference time interval and a second reference time interval, where the first reference time interval corresponds to the charging state and the second reference time interval corresponds to the discharging state. In some embodiments, the multiple reference time intervals corresponding to each battery metric may be further divided according to the metric value of each battery metric on the basis of being divided according to the battery state. Exemplarily, assuming that the metric value (temperature value) corresponding to the temperature is the same in the charging state and the discharging state, then the reference time interval corresponding to the temperature may include a third reference time interval, and the third reference time interval corresponds to both the charging state and the discharging state.

[0070] Step S202, obtaining a first reference interval corresponding to each battery metric from the multiple reference time intervals according to the battery state corresponding to the first time interval.

[0071] It can be understood that after the electronic device obtains multiple reference time intervals corresponding to each battery metric, for each battery metric, the electronic device can determine a first reference interval having the same battery state as the first time interval from the multiple reference time intervals corresponding to the battery metric.

[0072] Exemplarily, assume that the reference time intervals corresponding to the current may include a first reference time interval and a second reference time interval, where the first reference time interval corresponds to the charging state and the second reference time interval corresponds to the discharging state. Assume that the reference time interval corresponding to the temperature may include a third reference time interval, and the third reference time interval corresponds to both the charging state and the discharging state. Assume that the battery state corresponding to the first time interval is the charging state. Then, when the electronic device needs to obtain the first reference interval corresponding to the charging state, it can obtain the first reference time interval corresponding to the current and the third reference time interval corresponding to the temperature. Assume that the battery state corresponding to the first time interval is the discharging state. Then, when the electronic device needs to obtain the first reference interval corresponding to the discharging state, it can obtain the second reference time interval corresponding to the current and the third reference time interval corresponding to the temperature.

[0073] In one embodiment, the electronic device can obtain the state information of the battery within the first time interval through the battery management system, and then determine the battery state corresponding to the first time interval according to the state information.

[0074] Step S203: Obtain a second evaluation value of the battery according to the index values within the first reference interval corresponding to each battery index.

[0075] It can be understood that after the electronic device obtains the first reference interval corresponding to each battery index, it can obtain the index values of each battery index within the first reference interval. The electronic device can comprehensively evaluate the working state of the battery based on the index values corresponding to each battery index to obtain the second evaluation value.

[0076] In some embodiments, the electronic device can obtain the evaluation value corresponding to each battery index according to the index value corresponding to each battery index, and then sum up the evaluation values corresponding to each index to obtain the second evaluation value.

[0077] In the embodiment of the present application, through the battery state corresponding to the first time interval, the first reference interval can be obtained, and then the second evaluation value corresponding to the first reference interval can be obtained according to the index values within the first reference interval. In this process, the first reference interval and the first time interval have the same battery state, thus ensuring the comparability between the first reference interval and the first time interval and meeting the requirements for battery fault diagnosis.

[0078] In some possible implementation manners, Figure 3 is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application. Refer to Figure 3 As shown, step S201 may include:

[0079] Step S301: Obtain multiple initial index values corresponding to each battery index among at least one battery index.

[0080] It can be understood that the electronic device can obtain the historical data of the battery, and then obtain multiple initial index values corresponding to each battery index in at least one battery index.

[0081] In some embodiments, the historical data of the battery is stored in a database, and the electronic device can obtain the historical data of the battery through the database. In some embodiments, the historical data of the battery includes the initial index values collected within a past period of time. The multiple initial index values can be obtained by selecting the initial index values corresponding to any multiple consecutive time points in the historical data. That is to say, the multiple initial index values obtained by the electronic device can be multiple initial index values arranged in sequence according to the collection time. In one embodiment, the initial index value can be the data directly detected by the battery management system without data processing.

[0082] It can be understood that when there is one battery index, the electronic device can obtain multiple initial index values corresponding to one battery index. When there are multiple battery indexes, the electronic device can simultaneously obtain multiple initial index values corresponding to multiple battery indexes, and each battery index can correspond to multiple initial index values.

[0083] Step S302: Smooth the multiple initial index values to obtain multiple index values.

[0084] It can be understood that the index value is obtained by smoothing the initial index value. The electronic device smooths the multiple initial index values in order to better obtain the change trend of the battery performance, thereby improving the effectiveness of the historical data.

[0085] In some embodiments, the electronic device can smooth the multiple initial index values by removing abnormal initial index values. It can be understood that the multiple initial index values arranged over time can represent the change trend of the corresponding battery index. By eliminating the abnormal index values, the electronic device can smooth the change trend, making the multiple index values obtained after smoothing more reliable.

[0086] In some embodiments, the electronic device can also smooth the multiple initial index values in other ways, which are not limited in the embodiments of the present application.

[0087] Step S303: Group the multiple index values to obtain multiple index value groups corresponding to different battery states.

[0088] It can be understood that the electronic device can segment the multiple index values according to the change trend of the multiple index values corresponding to each battery index, so as to obtain multiple index value groups. The battery states corresponding to the multiple index value groups are different, and each index value group corresponds to at least one battery state.

[0089] Exemplarily, according to the change trend of the index values corresponding to the current, multiple index values corresponding to the current can be divided into a first index value group and a second index value group. In some embodiments, the first index value group corresponds to the current value in the battery charging state. At this time, the first index value group may include multiple approximate current values; the second index value group corresponds to the current value in the battery discharging state. At this time, the second index value group may include multiple uniformly changing current values.

[0090] In some embodiments, each index value group may include multiple index values. These multiple index values together characterize the battery performance when the battery continuously remains in the corresponding battery state.

[0091] Step S304, determine multiple reference time intervals according to multiple index value groups.

[0092] It can be understood that the electronic device can obtain multiple index value groups and each index value in each index value group. Subsequently, the electronic device can determine the time interval corresponding to the multiple index values in the index value group according to the acquisition time of each index value, and determine the time interval corresponding to the index value group as the time interval corresponding to the index value group, and then determine a reference time interval according to the time interval corresponding to each index value group. Determine multiple reference time intervals according to the time intervals corresponding to multiple index value groups. Each index value group among the multiple index values corresponds to a reference time interval.

[0093] In some embodiments, the electronic device can also determine the time interval corresponding to each index value group by obtaining the acquisition time corresponding to the first index value and the acquisition time corresponding to the last index value in each index value group.

[0094] It can be understood that the multiple index values in the index value group are sorted in sequence according to the acquisition time. Therefore, the time interval corresponding to each index value group can be determined according to the first index value and the last index value.

[0095] In the embodiments of the present application, by obtaining the historical data of the battery and processing and segmenting the historical data, multiple reference time intervals corresponding to the battery can be obtained. The multiple reference time intervals correspond to different battery states, so as to be used for analyzing the battery performance in different states.

[0096] In some possible implementation manners, step S302 may include: starting from the first initial index value among the multiple initial index values, sliding the time window according to a preset sliding position until it slides to the last initial index value among the multiple initial index values; when the time window slides to each sliding position, perform averaging processing on the initial index values within the time window to obtain multiple index values.

[0097] It can be understood that after the electronic device obtains multiple initial index values corresponding to the battery index, it can perform smoothing processing on the multiple initial index values. The electronic device can obtain multiple index values by sliding a time window according to a preset sliding position. Specifically, during the process of the time window sliding among the multiple initial index values, the electronic device can calculate the mean value of the multiple initial index values within the time window when the time window is at each sliding position, so as to obtain an index value at each sliding position, and traverse all sliding positions to obtain multiple index values.

[0098] It can be understood that the electronic device can start from the first initial index value among the multiple initial index values and end at the last initial index value among the multiple initial index values, and slide the time window according to the preset sliding position, so as to obtain multiple index values.

[0099] In some embodiments, the time window has a window value, which is used to define the number of initial index values within the time window, so as to determine the granularity of data processing for the multiple initial index values. It can be understood that through the window value, the time range corresponding to the time window can be defined. In some embodiments, the window value is greater than or equal to 2, that is to say, at least two initial index values are included within the time window.

[0100] In some embodiments, calculating the mean value of the initial index values within the time window when the time window is at each sliding position may include: calculating the weighted mean value of the multiple initial index values within the time window when the time window is at each sliding position.

[0101] It can be understood that multiple initial index values are included within the time window. Calculating the weighted mean value of the multiple initial index values within the time window may be to calculate the mean value of the multiple initial indexes after assigning different weights to the multiple initial index values.

[0102] In some embodiments, different weights are assigned to each initial index value according to the position of each initial index value among the multiple initial index values included within the time window. For example, lower weights are assigned to the initial index values at both sides (far from the middle time point) within the time window, and higher weights are assigned to the initial index values at the middle position (corresponding to the middle time point) within the time window, so that the electronic device pays more attention to the initial index values at the middle position within the time window, and thus it is convenient for the electronic device to more accurately obtain the change trend of the multiple initial index values within the time window.

[0103] In an example, formula (1) is used to calculate the index value when the time window is at each sliding position.

[0104] (1)

[0105] Wherein, m is the window value of the time window, and m≥2. t is an intermediate time point within the time window (equivalent to the acquisition time of the intermediate initial index value within the time window), that is, the distance from the first time point within the time window (equivalent to the acquisition time of the first initial index value within the time window) to the intermediate time point t is k time points, and the distance from the last time point within the time window (equivalent to the acquisition time of the last initial index value within the time window) to t is k time points, that is, k=(m - 1) / 2; is the index value of the time point that is j time points away from the intermediate time point t, and the value range of j is from -k to k; is the weight value of the time point that is j time points away from the intermediate time point t. Among them, the weights of each time point within the time window are respectively: [1 / (2m), 1 / m, …, 1 / m, 1 / (2m)], the sum of the weights of all time points is 1, and the weights of the time points on both sides of the intermediate time point t are symmetric; is the index value of the sliding position corresponding to the intermediate time point.

[0106] It can be understood that by setting an appropriate window value m, the trend curves corresponding to multiple index values can be made smoother. j = -k is just a starting point used to traverse all time points within the time window. By traversing j from -k to k, it is possible to process the initial index values within the time window and calculate an index value. This method ensures the balanced contribution of the data points before and after the intermediate time point t to the calculation result, thereby smoothing multiple initial index values.

[0107] It can be understood that the estimated value of the trend of the intermediate time point t is obtained by adding or subtracting the weighted average of the index values within k time points from the index value of the intermediate time point t. In the case where the time points are adjacent, the observed values are also likely to be close. Thus, the way of obtaining the average value eliminates some randomness in the data, so that a relatively smooth index value and the change trend of the index value can be obtained. Further, to ensure that the change trend of the index value is presented as a smooth curve as much as possible. Inside the time window, the weight values of the first and last time points within the time window are kept small, and the weight value of the intermediate time point is large, so that the fluctuations in the continuous data can be reduced, and the change trend of the index value can be made smoother.

[0108] In the embodiments of the present application, by sliding the time window and determining the mean value according to the initial index values within each time window, multiple index values are obtained. In this process, the change trend formed by multiple index values can be made smoother, the fluctuations in the continuous data can be reduced, which is helpful for obtaining multiple reference time periods subsequently.

[0109] In some possible implementation manners, Figure 4 is a schematic flowchart of a battery diagnosis method provided by the embodiments of the present application. Refer toFigure 4 As shown in Figure 4 , step S104 may include:

[0110] Step S401, obtaining one or more influencing factors associated with at least one battery metric.

[0111] It can be understood that the electronic device may obtain at least one battery metric corresponding to the first evaluation value and obtain one or more influencing factors associated with the at least one battery metric.

[0112] In some embodiments, according to the performance change of the battery, the influencing factors associated with each battery metric may be preset, so that the electronic device can obtain one or more influencing factors associated with at least one battery metric.

[0113] Step S402, classifying and decomposing the one or more influencing factors to obtain an influencing factor group.

[0114] It can be understood that after obtaining the one or more influencing factors, the multiple influencing factors may be classified, or the one or more influencing factors may be decomposed, so as to obtain an influencing factor group with multiple levels. Here, the influencing factor group is used to comprehensively evaluate the battery performance of the battery. Each factor in the influencing factor group can affect the difference, or it can be considered that the influencing factor group is associated with the difference.

[0115] In some embodiments, the influencing factor group includes multiple factors, and the multiple factors include one or more upper-level factors formed by one or more influencing factors, and one or more lower-level factors corresponding to each upper-level factor in the one or more upper-level factors. Here, any upper-level factor may also be a lower-level factor of an upper-level factor, and any lower-level factor may also be an upper-level factor of a lower-level factor, so that the influencing factor group can have multiple levels.

[0116] In some embodiments, classifying the multiple influencing factors may include: classifying the influencing factors corresponding to different battery metrics so that the same influencing factors can be combined. In some embodiments, decomposing the multiple influencing factors may include: layer-by-layer disassembling the influencing factors to obtain the lower-level factors of the influencing factors.

[0117] In some embodiments, the upper-level factors may include: time factor, operation factor, business factor, production factor, and other factors. Among them, the lower-level factors of the time factor may include: year, month, day, unit time, and time interval. The lower-level factors of the operation factor may include: operation status, power, location, and environment. The lower-level factors of the business factor may include: software deployment release version, parameter update, policy control, and management of the management system. The lower-level factors of the production factor may include: raw material batch, production batch, and transportation method; the lower-level factors of the other factors may include: weather factor, emergency, and special business scenario.

[0118] It can be understood that the influencing factors causing abnormal battery operation are multiple and dynamic. However, there will always be some factors that play a decisive role within a certain period. By classifying and decomposing the factors to establish an influencing factor group, the battery failure can be attributed more accurately. For example, the reason for the failure may be the time factor. Based on the time factor, it can be further decomposed into seasons, months, morning, afternoon, evening, and other time periods. This makes it possible to analyze that the probability of failure is higher in different seasons or time periods. For example, in summer, the probability of failure may be higher because the ambient temperature is relatively higher than in other seasons. At the same time, combined with the production factor causing the failure, it can be concluded that the heat dissipation design of the product is insufficient, resulting in a higher failure rate in summer.

[0119] In some embodiments, step S402 may include: classifying and decomposing one or more influencing factors to construct a first influencing factor group associated with a first evaluation value; classifying and decomposing one or more influencing factors to construct a second influencing factor group associated with a second evaluation value, and obtaining an influencing factor group based on the first influencing factor group and the second influencing factor group.

[0120] It can be understood that the electronic device can construct a first influencing factor group and associate the first influencing factor group with a first evaluation value. The electronic device can also construct a second influencing factor group and associate the second influencing factor group with a second evaluation value. Since the battery indicators corresponding to the first evaluation value are the same as those corresponding to the second evaluation value, the first influencing factor group and the second influencing factor group have the same hierarchical structure. After obtaining the first influencing factor group and the second influencing factor group, the electronic device can obtain an influencing factor group associated with the difference based on at least one of the first influencing factor group and the second influencing factor group.

[0121] In one example, Figure 5 is a schematic structural diagram of an influencing factor group provided by an embodiment of the present application. Refer to Figure 5As shown, the first time interval ΔT' is associated with a first evaluation value. The first evaluation value is abstracted into a factor Y'. The first factor group affecting the factor Y' can be composed of factor A', factor B', factor C', and factor D', and the lower-level factors corresponding to the above factors. Similarly, the first reference interval ΔT is associated with a second evaluation value. The second evaluation value is abstracted into a factor Y. The second factor group affecting the factor Y can be composed of factor A, factor B, factor C, and factor D, and the lower-level factors corresponding to the above factors. Here, since the battery indicators corresponding to the first evaluation value are the same as those corresponding to the second evaluation value, factor A corresponds to factor A', factor B corresponds to factor B', and so on.

[0122] Furthermore, the Y factor can be decomposed into the factor sum (A*B + C*D) between the factor product of factor A and factor B (A*B) and the factor product of factor C and factor D (C*D). At the same time, factor A can be decomposed into the factor sum (A1 + A2) of factor A1 and factor A2, and factor D can be decomposed into the factor sum (D1 + D2) of factor D1 and factor D2. Factor A1 can be decomposed into the factor sum (a1 + a2*a3) between the factor product of factor a2 and factor a3 (a2*a3) and factor a1. Factor D1 can be decomposed into the factor sum (d1 + d2*d3) between the factor product of factor d2 and factor d3 (d2*d3) and factor d1. Factor a2 can be decomposed into the factor sum (e1 + e2) of factor e1 and factor e2. Factor d2 can be decomposed into the factor sum (f1 + f2) of factor f1 and factor f2. By analogy, the first factor group corresponding to the Y' factor can also be of the above structure.

[0123] Step S403, determine the influence value of each factor in the factor group to identify the cause of the battery failure.

[0124] It can be understood that after the electronic device obtains the factor group associated with the difference, it can determine the influence degree of each factor in the factor group on the difference, so as to determine the influence value of each factor in the factor group to identify the cause of the battery failure.

[0125] In some embodiments, the electronic device can obtain the factor values corresponding to each factor in the first time interval and the first reference interval respectively, and compare the change of the factor values with the difference to determine the influence degree of each factor on the difference.

[0126] In some embodiments, in the field of battery performance, the factor value usually refers to the numerical value of various parameters or variables that affect battery performance. By monitoring the changes of these factor values, the changes in battery performance can be evaluated, and the influence degree of each factor on the changes in battery performance can be determined.

[0127] Exemplarily, assume that the difference determined based on the first evaluation value and the second evaluation value is 5%, the change value of the battery performance caused by the change of the first factor is 6%, and the change value of the battery performance caused by the change of the second factor is 4%. Then, the influence degree of the first factor on the difference is higher, and the influence degree of the second factor on the difference is lower. Thus, it is determined that the first factor is the main cause of the battery failure.

[0128] In some embodiments, after performing various analyses such as regression analysis and correlation analysis on each factor, the influence degree of each factor on the difference can be determined. In one embodiment, regression analysis is a common method for determining the influence degree of factors. By simulating the linear relationship between the factors and the difference, the influence degrees of different factors on the difference can be compared. In one embodiment, correlation analysis can measure the correlation and association degree between different factors and evaluate the dependence relationship between the factors and variables.

[0129] In one example, still referring to Figure 5 as shown, the difference ΔY can be associated with the first influencing factor group and the second influencing factor group. By obtaining the factor values corresponding to each factor within the first time interval and the first reference interval, the change of the factor value corresponding to each factor can be determined, and then the influence degree of each factor on the difference ΔY can be determined. Here, each factor includes: factor A, factor B, factor C, factor D, factor A1, factor A2, factor D1, factor D2, …, factor f2, etc.

[0130] It can be understood that Figure 5 the factors shown can not only independently affect the difference but also be associated to jointly affect the difference. Therefore, multiple analysis methods such as regression analysis and correlation analysis can be used to determine the influence degree of each factor on the difference.

[0131] In some possible implementation manners, step S403 may include: calculating the first parameter value corresponding to each factor, where the first parameter value is used to represent the ratio change of each factor in the influencing factor group; calculating the second parameter value corresponding to each factor, where the second parameter value is used to represent the proportion change of each factor in the influencing factor group; and calculating the influence value corresponding to each factor according to the first parameter value and the second parameter value.

[0132] It can be understood that by comparing the corresponding data of each factor within the first time period and the first reference period, the ratio change of each factor in the influencing factor group can be obtained. By comparing the proportion of each factor in the influencing factor group within the first time period and the proportion of each factor in the influencing factor group within the first reference period, the proportion change of each factor in the influencing factor group can be determined. Furthermore, based on the ratio change and the proportion change, the contribution of each factor to the whole can be determined, and thus the influence value corresponding to each factor can be calculated.

[0133] In one embodiment, the first parameter value and the second parameter value of each factor can be generated through the following formula (2) and formulas (3) to (8) obtained according to formula (2).

[0134] (2)

[0135] (3)

[0136] (4)

[0137] (5)

[0138] (6)

[0139] (7)

[0140] (8)

[0141] Wherein, R represents the overall ratio (100%); A represents the sum of the numerators of all dimensions; T represents the sum of the denominators of all dimensions; represents the overall ratio of the i-th dimension; represents the numerator of the i-th dimension; represents the denominator of the i-th dimension; represents the ratio of the i-th dimension; represents the proportion of the i-th dimension; N is a constant representing the maximum dimension.

[0142] It can be understood that the first parameter value of each factor is obtained through ; the second parameter value of each factor is obtained through . Among them, the electronic device first needs to calculate the and of each factor; subsequently, the of each factor is calculated according to formula (6); the of each factor is calculated through formula (7). It can be understood that after obtaining the and of each factor, it can be explained whether the data change corresponding to each factor is caused by the numerator or the denominator , that is, whether it is caused by a change in the ratio or a change in the proportion. Subsequently, the electronic device can determine the overall ratio of each factor, that is, the influence value corresponding to each factor, according to the and of each factor.

[0143] It should be noted that the above dimensions are equivalent to the levels described in the impact factor group. The numerator is equivalent to the number or quantity of occurrences of the specific feature corresponding to the factor. The denominator is equivalent to the total number of features corresponding to the factor. The numerator divided by the denominator is used to calculate the proportion of the occurrence of the specific feature.

[0144] In some embodiments, the electronic device can determine the ratio change of each factor as the overall ratio of each factor, so as to pay more attention to the impact brought by the numerator. In some embodiments, the electronic device can comprehensively consider the ratio change and proportion change of each factor to determine the overall ratio of each factor. It can be understood that by comprehensively considering the ratio change and proportion change of each factor, the electronic device can analyze and obtain more abundant information, which helps the electronic device to deeply understand the performance, reliability and failure causes of the battery.

[0145] Exemplarily, a specific example is used to illustrate how to calculate the impact value corresponding to each factor in the impact factor group. Assume that the abnormal rate of the cell voltage increases from 6.8% (equivalent to the second evaluation value) in the first reference interval to 16% (equivalent to the first evaluation value) in the first time interval, and the difference is 9.2%. Then, referring to the data in Table 1, the impact value of each factor can be calculated.

[0146] Table 1

[0147]

[0148] It can be understood that the electronic device can decompose the whole battery into Unit 1 to Unit 5 according to the position dimension. Unit 1 to Unit 5 are each an impact factor. Here, the difference corresponding to the abnormal rate of the cell voltage of the battery can be determined according to the evaluation value of the whole battery. Subsequently, the numerator and denominator of the abnormal rate corresponding to each factor are obtained, and then the proportion change and ratio change of each factor are determined according to the numerator and denominator corresponding to each factor, and further the impact value corresponding to each factor is determined according to the proportion change and ratio change of each factor.

[0149] In the embodiments of the present application, by splitting one or more impact factors, an impact factor group associated with the difference can be obtained. In the impact factor group, each factor is independent and interrelated with each other. Thus, after determining the influence degree of each factor on the difference, the failure cause of the battery can be identified.

[0150] In some possible implementation manners, Figure 6 is a schematic flowchart of a battery diagnosis method provided by an embodiment of the present application. Referring to Figure 6 as shown, after step S403, it may include:

[0151] Step S601, sorting each factor according to the magnitude of the impact value to obtain a factor sequence.

[0152] It can be understood that the electronic device can sort multiple factors in the influence factor group in descending order of the influence value, so as to obtain a factor sequence.

[0153] It can be understood that through sorting, the contribution degree of different factors in the influence factor group can be observed. The greater the contribution degree, the more forward the factor is arranged in the factor sequence, and the greater the influence degree of the factor on the difference, so it is more likely to become the cause of battery failure.

[0154] In an example, still referring to the data shown in Table 1. Assuming that the ratio change of each factor is the overall ratio change, so as to determine the influence value corresponding to each factor, then, the influence value of Unit 3# is the largest, the influence value of Unit 5# is the second largest, the influence value of Unit 2# is the third largest, and so on.

[0155] Step S602, based on the position of each factor in the factor sequence, to identify the cause of the battery failure.

[0156] It can be understood that after the electronic device obtains the factor sequence, it can obtain the position of each factor in the factor sequence, so as to be able to identify the cause of the battery failure based on the position of the factor.

[0157] In some embodiments, the electronic device identifies the cause of the battery failure according to the first factor in the factor sequence. In some embodiments, the electronic device identifies the cause of the battery failure according to multiple factors arranged in the front in the factor sequence.

[0158] In an example, still referring to the data shown in Table 1. Assuming that the influence value of Unit 3# is the largest, the influence value of Unit 5# is the second largest, the influence value of Unit 2# is the third largest, and so on. Then, the electronic device can at least identify that Unit 3# constitutes the main cause of the battery failure.

[0159] In the embodiments of the present application, compared with the related art that can only judge whether the battery fails, rather than the attribution diagnosis of the failure and cannot find the root cause of the failure, in this embodiment, an influence factor group is generated, and further according to the contribution degree of each factor in the influence factor group to the difference, the corresponding type of the failure is determined, the corresponding failure point is found, and the failure is solved from the root cause.

[0160] In a second aspect, the embodiments of the present application provide a battery diagnosis device. Figure 7 For the schematic structural diagram of a battery diagnosis device provided by the embodiments of the present application, see Figure 7 As shown, the battery diagnosis device 700 may include:

[0161] The first acquisition module 701 is configured to acquire a first evaluation value of the battery within a first time interval, where the first evaluation value is obtained based on the index values of at least one battery index within the first time interval;

[0162] The second acquisition module 702 is configured to acquire a second evaluation value of the battery within a first reference interval, where the second evaluation value is obtained based on the index values of at least one battery index within the first reference interval; the first reference interval is an interval among multiple reference time intervals that has the same battery state as the first time interval; the multiple reference time intervals are divided according to the battery state of the battery;

[0163] The calculation module 703 is configured to calculate the difference between the first evaluation value and the second evaluation value, where the difference is used to represent the degree of change in the battery performance of the battery;

[0164] The determination module 704 is configured to, when the difference is greater than a threshold, determine the influence information of each of one or more influencing factors associated with at least one battery index based on the one or more influencing factors to identify the cause of the battery failure; the influence information is used to represent the influence degree of each influencing factor on the difference.

[0165] In some possible implementation manners, the second acquisition module 702 is further configured to acquire multiple reference time intervals corresponding to each battery index among at least one battery index; obtain the first reference interval corresponding to each battery index from the multiple reference time intervals according to the battery state corresponding to the first time interval; and acquire the second evaluation value of the battery based on the index values within the first reference interval corresponding to each battery index.

[0166] In some possible implementation manners, the second acquisition module 702 is further configured to acquire multiple initial index values corresponding to each battery index among at least one battery index, where the multiple initial index values are sorted in sequence according to the acquisition time; perform smoothing processing on the multiple initial index values to obtain multiple index values; group the multiple index values to obtain multiple index value groups corresponding to different battery states, where each index value group includes multiple index values; and determine multiple reference time intervals according to the multiple index value groups, where one index value group corresponds to one reference time interval.

[0167] In some possible implementation manners, the second acquisition module 702 is further configured to start from the first initial index value among the multiple initial index values, slide a time window according to a preset sliding position until it slides to the last initial index value among the multiple initial index values; when the time window slides to each sliding position, perform averaging processing on the multiple initial index values within the time window to obtain multiple index values, where one sliding position corresponds to one index value.

[0168] In some possible embodiments, the determination module 704 is further configured to obtain one or more influencing factors associated with at least one battery metric; classify and decompose the one or more influencing factors to obtain an influencing factor group, where the influencing factor group includes multiple factors, and the multiple factors include one or more upper-level factors formed by the one or more influencing factors, and one or more lower-level factors corresponding to each upper-level factor in the one or more upper-level factors; the influencing factor group is used to comprehensively evaluate the battery performance of the battery; determine the influence value of each factor in the influencing factor group to identify the cause of the battery failure, where the influence value is used to represent the degree of influence of each factor on the difference.

[0169] In some possible embodiments, the determination module 704 is further configured to calculate a first parameter value and a second parameter value corresponding to each factor, where the first parameter value is used to represent the ratio change of each factor in the influencing factor group; the second parameter value is used to represent the proportion change of each factor in the influencing factor group; according to the first parameter value and the second parameter value, calculate the influence value of each factor.

[0170] In a third aspect, an embodiment of the present application provides an electronic device, including at least a memory and a processor, where the memory stores a computer program that can be run on the processor, and when the processor executes the program, it implements the steps in the battery diagnosis method provided in the above embodiments.

[0171] Figure 8 FIG. is an optional structural schematic diagram of the electronic device provided in the embodiment of the present application. Below, in conjunction with Figure 8 the electronic device 800 shown in FIG., the structure of the electronic device will be described.

[0172] In one example, as Figure 8 shown in FIG., the electronic device 800 includes: a processor 801, at least one communication bus, at least one external communication interface, and a memory 802. Among them, the communication bus is configured to implement connection communication between these components. Among them, the external communication interface may include a standard wired interface and a wireless interface.

[0173] The memory 802 is configured to store instructions and applications executable by the processor 801, and can also cache data to be processed or already processed by the processor 801 and each module in the electronic device (for example, image data, audio data, voice communication data, and video communication data), and can be implemented by flash memory (FLASH) or random access memory (Random Access Memory, RAM).

[0174] In another example, the electronic device may be an intelligent terminal such as a server or a computer. The electronic device is used to execute the steps in the battery diagnosis method provided in the above embodiments.

[0175] Fourthly, the present application also provides a storage medium, on which a readable storage medium stores executable instructions. When the executable instructions are executed by a processor, the steps in the battery diagnosis method provided by the embodiments of the present application are implemented.

[0176] Fifthly, the present application also provides a computer program product, including a computer program or instructions. When the computer program or instructions are executed by a processor, the steps in the above-mentioned battery diagnosis method are implemented.

[0177] It should be pointed out here that the descriptions of the above storage medium and device embodiments are similar to those of the above method embodiments and have beneficial effects similar to those of the method embodiments. For the technical details not disclosed in the storage medium and device embodiments of the present application, please refer to the descriptions of the method embodiments of the present application for understanding.

[0178] The above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or replace some of the technical features therein. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application and should all be included in the protection scope of the present application.

Claims

1. A battery diagnosis method, characterized in that: include: Obtaining a first evaluation value of the battery in a first time interval, wherein the first evaluation value is obtained by an indicator value of at least one battery indicator in the first time interval; Obtaining a second evaluation value of the battery within a first reference interval, wherein the second evaluation value is obtained by the indicator value of the at least one battery indicator within the first reference interval; the first reference interval is an interval in a plurality of reference time intervals having the same battery state as the first time interval; the plurality of reference time intervals are divided according to the battery state of the battery; calculating a difference between the first evaluation value and the second evaluation value, wherein the difference is used to indicate a degree of change in battery performance of the battery; In the case where the difference is greater than a threshold, determining, based on one or more influencing factors associated with the at least one battery indicator, influence information of each of the one or more influencing factors, so as to identify a cause of failure of the battery; the influence information is used to indicate the degree of influence of each influencing factor on the difference; Among them, based on the one or more influencing factors associated with the at least one battery indicator, determining the influence information of each of the one or more influencing factors to identify the cause of the failure of the battery includes: obtaining the one or more influencing factors associated with the at least one battery indicator; classifying and decomposing the one or more influencing factors to obtain an influencing factor group, wherein the influencing factor group includes multiple factors, and the multiple factors include one or more upper factors formed by the one or more influencing factors, and one or more lower factors corresponding to each of the one or more upper factors; the influencing factor group is used to comprehensively evaluate the battery performance of the battery; determining the influence value of each factor in the influencing factor group to identify the cause of the failure of the battery, wherein the influence value is used to indicate the degree of influence of each factor on the difference.

2. The method according to claim 1, characterized in that The obtaining of a second evaluation value of the battery within the first reference interval includes: Obtaining the multiple reference time intervals corresponding to each battery indicator of the at least one battery indicator; According to the battery state corresponding to the first time interval, obtaining a first reference interval corresponding to each battery indicator from the multiple reference time intervals; The second evaluation value of the battery is obtained according to the indicator value within the first reference interval corresponding to each battery indicator.

3. The method according to claim 2, characterized in that The obtaining the multiple reference time intervals corresponding to each battery indicator of the at least one battery indicator includes: Obtaining a plurality of initial indicator values ​​corresponding to each battery indicator of the at least one battery indicator, wherein the plurality of initial indicator values ​​are sorted in sequence according to acquisition time; Smoothing the multiple initial indicator values ​​to obtain multiple indicator values; Grouping the plurality of indicator values ​​to obtain a plurality of indicator value groups corresponding to different battery states, wherein each indicator value group includes a plurality of the indicator values; A plurality of the reference time intervals are determined according to the plurality of indicator value groups, wherein one of the indicator value groups corresponds to one of the reference time intervals.

4. The method according to claim 3, characterized in that: The smoothing process is performed on the multiple initial indicator values ​​to obtain the multiple indicator values, including: Taking the first initial indicator value among the multiple initial indicator values ​​as a starting point, sliding the time window according to a preset sliding position until sliding to the last initial indicator value among the multiple initial indicator values; When the time window slides to each of the sliding positions, a plurality of initial indicator values ​​within the time window are averaged to obtain a plurality of the indicator values, wherein one of the sliding positions corresponds to one of the indicator values.

5. The method according to claim 1, characterized in that Determining the influence value of each factor in the influence factor group includes: Calculate a first parameter value and a second parameter value corresponding to each factor, wherein the first parameter value is used to represent a change in the ratio of each factor in the influencing factor group; and the second parameter value is used to represent a change in the proportion of each factor in the influencing factor group; The influence value of each factor is calculated according to the first parameter value and the second parameter value.

6. A battery diagnostic device, characterized in that: include: A first obtaining module, configured to obtain a first evaluation value of a battery in a first time interval, wherein the first evaluation value is obtained by an indicator value of at least one battery indicator in the first time interval; A second obtaining module is used to obtain a second evaluation value of the battery within a first reference interval, wherein the second evaluation value is obtained by the indicator value of the at least one battery indicator within the first reference interval; the first reference interval is an interval in a plurality of reference time intervals having the same battery state as the first time interval; the plurality of reference time intervals are divided according to the battery state of the battery; a calculation module, configured to calculate a difference between the first evaluation value and the second evaluation value, wherein the difference is used to indicate a degree of change in battery performance of the battery; A determination module is used to obtain one or more influencing factors associated with at least one battery indicator when the difference is greater than a threshold; classify and decompose the one or more influencing factors to obtain an influencing factor group, wherein the influencing factor group includes multiple factors, and the multiple factors include one or more upper factors formed by the one or more influencing factors, and one or more lower factors corresponding to each of the one or more upper factors; the influencing factor group is used to comprehensively evaluate the battery performance of the battery; determine the influence value of each factor in the influencing factor group to identify the cause of the battery failure, wherein the influence value is used to indicate the degree of influence of each factor on the difference.

7. An electronic device, characterized in that: The electronic device comprises a memory and one or more processors. A computer program is stored in the memory. When the computer program is executed by the electronic device, the battery diagnosis method as claimed in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: The readable storage medium stores executable instructions, wherein when the executable instructions are executed by a processor, the battery diagnosis method according to any one of claims 1 to 5 is implemented.

9. A computer program product, comprising a computer program or instructions, characterized in that: When the computer program or instruction is executed by a processor, the battery diagnosis method as claimed in any one of claims 1 to 5 is implemented.

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