A method, device, and storage medium for determining a state of a battery pack

Abstract

The application discloses a kind of battery pack state determination method, device, equipment and storage medium.The method comprises: obtaining the current monitoring data of target battery pack;Wherein, the current monitoring data includes the index parameter corresponding to at least two index types;Parameter importance between the index parameter of different index types is obtained, and the data score of the current monitoring data is determined according to the parameter importance and the parameter value of the index parameter;According to the data score, the battery pack state of the target battery pack is determined.Through running the technical solution provided in the embodiment of the application, the problem that the current state of the battery pack cannot be determined in time and accurately can be solved, and the accuracy and timeliness of the battery pack state determination are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the battery technology, and particularly to a battery pack state determination method, device, equipment and storage medium. BACKGROUND

[0002] The battery pack is a group of independent reliable power supply, plays an especially important role in the process of normal operation of the transformer substation, when the accident occurs in the station, can guarantee the reliable continuous work of the electrical equipment in the DC system, is the last barrier to ensure uninterrupted power supply.

[0003] The existing battery pack is usually maintained by periodic inspection, however, due to the long interval of periodic inspection, it is difficult to find the problems existing in the battery pack in time; some battery packs are also monitored by online monitoring devices or systems, however, the existing online monitoring devices or systems are usually single in function, can only realize the basic voltage monitoring function, the amount of information obtained is less, and the current state of the battery pack cannot be accurately determined. SUMMARY

[0004] The present application provides a battery pack state determination method, device, electronic equipment and storage medium, to realize the improvement of the accuracy and timeliness of the battery pack state determination.

[0005] According to one aspect of the present application, a battery pack state determination method is provided, which comprises:

[0006] Obtaining the current monitoring data of the target battery pack; wherein the current monitoring data comprises the index parameters corresponding to at least two index types;

[0007] Obtaining the parameter importance between the index parameters of different index types, and determining the data score of the current monitoring data according to the parameter importance and the parameter value of the index parameters;

[0008] Determining the battery pack state of the target battery pack according to the data score.

[0009] According to another aspect of the present application, a battery pack state determination device is provided, which comprises:

[0010] The monitoring data acquisition module is configured to obtain the current monitoring data of the target battery pack; wherein the current monitoring data comprises the index parameters corresponding to at least two index types;

[0011] The data score determination module is configured to obtain the parameter importance between the index parameters of different index types, and determine the data score of the current monitoring data according to the parameter importance and the parameter value of the index parameters;

[0012] a battery pack state determination module configured to determine a battery pack state of the target battery pack according to the data score.

[0013] According to another aspect of the present application, there is provided an electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein

[0016] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the battery pack state determination method according to any one of the embodiments of the present application.

[0017] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to perform the battery pack state determination method according to any one of the embodiments of the present application when executed by the processor.

[0018] The technical solution of the embodiments of the present application enriches the information amount contained in the current monitoring data by obtaining the current monitoring data of the target battery pack including the index parameters corresponding to at least two index types, and improves the objectivity of the subsequent data score determination. The parameter importance between the index parameters of different index types is obtained, so as to determine the importance of each index parameter relative to other index parameters, and the data score of the current monitoring data is determined according to the parameter importance and the parameter value of the index parameter, so that the determination of the data score is based on the index parameter itself and the influence between the index parameters, and the accuracy and effectiveness of the data score determination are improved. The battery pack state of the target battery pack is determined according to the data score, the accuracy and timeliness of the battery pack state determination are improved, and it is convenient for subsequent determination of the corresponding battery pack maintenance strategy according to the battery pack state, for example, the higher the frequency of the state is high risk, the higher the accuracy of the maintenance strategy is.

[0019] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 a flowchart of a battery pack state determination method provided for the first embodiment of the present application;

[0021] Figure 2 a flowchart of a battery pack state determination method provided for the second embodiment of the present application;

[0022] Figure 3 A structural schematic diagram of a battery pack state determination device provided for the third embodiment of the present application is shown in the figure.

[0023] Figure 4 A structural schematic diagram of an electronic device for implementing the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0024] In order to make the personnel in the technical field better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the figures in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by the personnel in the field without creative labor should belong to the protection scope of the present application.

[0025] It should be noted that the terms “first”, “second”, “target” and the like in the specification and claims of the present application and the above-mentioned figures are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be exchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms “include” and “have” and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0026] Embodiment one

[0027] Figure 1 A flowchart of a battery pack state determination method provided for the first embodiment of the present application, the present embodiment can be applicable to the case of determining the health state of a battery pack, the method can be executed by the battery pack state determination device provided by the embodiments of the present application, and the device can be realized by software and / or hardware. Referring to Figure 1 , the battery pack state determination method provided by the present embodiment includes:

[0028] Step 110, obtaining the current monitoring data of the target battery pack; wherein the current monitoring data includes index parameters corresponding to at least two index types.

[0029] The target battery pack is a battery pack in the application scenario whose state needs to be determined, for example, all or part of the battery packs in the application scenario, which is not limited in the embodiment. The current monitoring data is the monitoring data analyzed at present, for example, a plurality of sets of monitoring data of the target battery pack are obtained, and the current monitoring data is the data selected for analysis.

[0030] The index type is the type of the index parameter, which is related to the battery pack, for example, the index type is the voltage change of the battery pack in a preset time period, the temperature change of the battery pack, etc., and the index parameter is the specific parameter corresponding to the index type collected. The index parameters corresponding to at least two index types are included in the current monitoring data, that is, at least two different types of data are included in the current monitoring data.

[0031] In step 120, the parameter importance between the index parameters of different index types is obtained, and the data score of the current monitoring data is determined according to the parameter importance and the parameter value of the index parameter.

[0032] The parameter importance indicates the importance of parameter one relative to parameter two when the two index parameters are compared. The higher the parameter importance, the greater the importance of parameter one relative to parameter two. The parameter importance can be determined in advance, which is not limited in the embodiment.

[0033] The importance of index parameter i to index parameter j is denoted as S ij , and the importance of index parameter j to index parameter i is denoted as S ji . The following conditions are met:

[0034] 0≤S ij ≤1, S ii =0.5 and S ij +S ji =1, (i, j=1, 2, …, n) (1)

[0035] Wherein, n is the total number of index types.

[0036] For example, if S ij is 0.5, it means that index parameter i and index parameter j are equally important. If S ij is 0.8, it means that index parameter i is very important compared to index parameter j.

[0037] The data score Score of the current monitoring data is determined according to the parameter importance and the parameter value of the index parameter, which can be determined by the following formula:

[0038]

[0039] Among them, S i F represents the importance of indicator parameter i to other indicator parameters. i Here, S represents the specific parameter value of index parameter i; where S i Through S ij Determine, for example, all S associated with index parameter i ij Adding them together gives S i For example, the current monitoring data includes four types of indicator parameters, namely parameter type 1, 2, 3, and 4. Then S1 = S 12 +S 13 +S 14 This embodiment does not impose any limitations on this. Accordingly, the data score at this time is S1×F1+S2×F2+S3×F3+S4×F4.

[0040] In this embodiment, optionally, obtaining the parameter importance among indicator parameters of different indicator types includes:

[0041] Obtain the first indicator parameter of the first indicator type, the second indicator parameter of the second indicator type, and the third indicator parameter of the third indicator type;

[0042] Obtain the importance of the first parameter of the first indicator parameter and the first parameter of the second indicator parameter; obtain the importance of the second parameter of the third indicator parameter and the second parameter of the second indicator parameter.

[0043] The importance of the third parameter of the first indicator parameter and the third indicator parameter is determined based on the importance of the first parameter and the importance of the second parameter.

[0044] The importance of parameters among different indicator types can be determined using the following formula:

[0045] S ij =S ik -S jk +0.5, (i,j,k=1,2,…,n) (3)

[0046] Where k is an indicator type that is different from i and j.

[0047] For example, if we obtain the first indicator parameter 1 of the first indicator type, the second indicator parameter 2 of the second indicator type, and the third indicator parameter 3 of the third indicator type, then the importance of the first parameter is S. 12 The importance of the second parameter is S. 23 The importance of the third parameter is S. 13 , of which S 23 With S 13 Given that, then S 13 =S 12 -S 32 +0.5, and S determined in the above manner.13 replacing the originally predetermined S 13 .

[0048] By introducing the second index parameter in addition to the first index parameter and the third index parameter, the third parameter importance of the first index parameter and the third index parameter is confirmed, so that the determination of the third parameter importance is not a separate comparison of the first index parameter and the third index parameter, but a comprehensive consideration of other index parameters, so that the determined third parameter importance has integrity, and the effectiveness of the determination of the third parameter importance is improved.

[0049] Step 130, determining the battery pack state of the target battery pack according to the data score.

[0050] The battery pack state is used to evaluate the operation risk of the target battery pack, which can be divided into high risk, higher risk, medium risk, lower risk and low risk, and the embodiment is not limited thereto.

[0051] According to the data score, the battery pack state of the target battery pack is determined, which can be a score threshold range corresponding to each battery pack state where the data score is located, for example, the score threshold range corresponding to the low risk, and then the battery pack state is determined as low risk.

[0052] The technical scheme provided by the embodiment enriches the amount of information contained in the current monitoring data by obtaining the current monitoring data of the target battery pack including at least two index parameters corresponding to different index types, improves the objectivity of subsequent data score determination, obtains the parameter importance between index parameters of different index types, thereby determining the importance of each index parameter relative to other index parameters, and determines the data score of the current monitoring data according to the parameter importance and the parameter value of the index parameter, so that the determination of the data score is based on the index parameter itself and the influence between the index parameters, and the accuracy and effectiveness of the data score determination are improved. According to the data score, the battery pack state of the target battery pack is determined, which improves the accuracy and timeliness of the battery pack state determination, and facilitates subsequent determination of the corresponding battery pack maintenance strategy according to the battery pack state, for example, the higher the frequency of the state is high risk, the higher the accuracy of the maintenance strategy is.

[0053] Embodiment two

[0054] Figure 2 The flowchart of the battery pack state determination method provided by the embodiment two of the application, the technical scheme is a supplementary description of the process before the parameter importance between index parameters of different index types is obtained. Compared with the above scheme, the specific optimization of the present scheme is that before the parameter importance between index parameters of different index types is obtained, it further includes:

[0055] determine a target parameter according to the parameter acquisition time of the index parameter and the index type, and construct a first preset matrix according to the target parameter, and obtain a target parameter sum of each target parameter;

[0056] determine a selection coefficient according to the target parameter sum and the monitoring duration corresponding to the current monitoring data, and construct a second preset matrix according to the selection coefficient;

[0057] determine the data consistency of the current monitoring data according to the first preset matrix and the second preset matrix, and determine whether to retain the current monitoring data according to the data consistency. Specifically, the flowchart of the storage battery pack state determination method is as shown in Figure 2

[0058] Step 210, obtaining the current monitoring data of the target storage battery pack; wherein the current monitoring data includes index parameters corresponding to at least two index types.

[0059] In this embodiment, optionally, the index type includes at least one of the storage battery pack capacity, the storage battery pack charge-discharge times, the storage battery pack voltage and the storage battery pack ambient temperature.

[0060] The storage battery pack capacity can be the current overall capacity of the target storage battery pack. As the storage battery pack is used, the battery pack capacity will gradually decrease. In order to better guarantee the output performance of the storage battery pack, the service life of the storage battery pack needs to be understood in time, and the capacity change is one of the verification factors. Therefore, the index parameter corresponding to the index type can be the current storage battery pack capacity.

[0061] The storage battery pack charge-discharge times are the number of times of charging and discharging of the storage battery pack. The number of charge-discharge times is also one of the factors affecting the state of the storage battery pack. Therefore, the index parameter corresponding to the index type can be the current charge-discharge times. The storage battery pack voltage can be the current voltage of the target storage battery pack. If the storage battery pack voltage decreases greatly, the service life of the storage battery pack will also be affected. Therefore, the index parameter corresponding to the index type can be the change value of the voltage. The storage battery pack ambient temperature is the temperature of the environment where the target storage battery pack is currently located. If the temperature difference is large, it will also have a certain impact on the service life of the storage battery pack. Therefore, the index parameter corresponding to the index type can be the change value of the ambient temperature.

[0062] By finding factors related to the state of the storage battery pack and determining the factors as corresponding index types, the effectiveness and comprehensiveness of the index type determination are improved, thereby improving the accuracy of the subsequent battery pack state determination.

[0063] In this embodiment, optionally, after obtaining the current monitoring data of the target storage battery pack, the method further includes:

[0064] determining a normalization processing mode according to the index type; ​

[0065] According to the normalization processing mode, the index data in the current monitoring data is normalized.

[0066] For example, if the index type includes the battery pack capacity, the normalization processing can be performed by the following formula:

[0067]

[0068] wherein, S(T, I, K) is the capacity released by the battery pack at the current battery state K and temperature T, from full charge to stop discharging at the load current I; S(T, I) is the capacity released by the battery pack at the initial state and temperature T, from full charge to stop discharging at the load current I.

[0069] If the index type includes the battery pack charge-discharge times, the normalization processing can be performed by the following formula:

[0070]

[0071] wherein, P is the current charge-discharge times; H is the total number of charge-discharge times of the battery pack.

[0072] If the index type includes the battery pack voltage, the normalization processing can be performed by the following formula:

[0073]

[0074] wherein, V max and V min are the maximum and minimum voltage values of all batteries in the target battery pack in a preset time period; V0 is the rated operating voltage of the battery pack, which can be determined in advance.

[0075] If the index type includes the battery pack environmental temperature, the normalization processing can be performed by the following formula:

[0076]

[0077] wherein, T max and T min are the maximum and minimum temperature values of the battery pack environment in a preset time period; T0 is the most suitable operating environmental temperature of the target battery pack, which can be determined in advance.

[0078] For example, if the data score Score is determined by formula (2), and the index types 1234 are the battery pack capacity, the battery pack charge-discharge times, the battery pack voltage and the battery pack environmental temperature respectively, then Score = S1 x AS + S2 x AP + S3 x AV + S4 x AT.

[0079] According to the index type, the corresponding normalization processing mode is determined, so that the index data is normalized, and index data in the same standard is obtained, thereby avoiding the problem that different types of index data cannot be calculated with each other, and the rationality of the current monitoring data determination is improved.

[0080] In step 220, the target parameter is determined according to the parameter acquisition time and the index type of the index parameter, and the first preset matrix is constructed according to the target parameter, and the target parameter sum of each target parameter is obtained.

[0081] The parameter acquisition time can be the collection time of the index parameter, for example, if the collection time of the index parameter is 1-100 days, and the index parameter is collected once a day, then the parameter acquisition time can be any day in 1-100 days. The target parameter is the index parameter of the index type obtained in the parameter acquisition time, for example, the index parameter of the index type 1 obtained on the 2nd day.

[0082] If the target parameter determined according to the parameter acquisition time and the index type of the index parameter is denoted as t mk Wherein, m is the parameter acquisition time of the index parameter, and k is the index type; then the first preset matrix T can be denoted as:

[0083]

[0084] Wherein, l is the monitoring duration, that is, the duration of the parameter acquisition time, for example, if the collection time of the index parameter is 1-100 days, then l is 100.

[0085] The target parameter sum of each target parameter is obtained, that is, the sum of the index parameters of different parameter types in the same parameter acquisition time, which can be determined by the following formula:

[0086]

[0087] In step 230, the selection coefficient is determined according to the target parameter sum and the corresponding monitoring duration of the current monitoring data, and the second preset matrix is constructed according to the selection coefficient.

[0088] Wherein, the selection coefficient r m Can be determined by the following formula:

[0089]

[0090] According to the selection coefficient of a single different parameter acquisition time, the coefficient comparison of the selection coefficients between different parameter acquisition times can be obtained, for example, denoted as r mq , which is the coefficient comparison between the parameter acquisition time m and the parameter acquisition time q, which can be determined by the following formula:

[0091]

[0092] The second preset matrix A can be constructed according to the selection coefficient.

[0093]

[0094] Step 240, determining the data consistency of the current monitoring data according to the first preset matrix and the second preset matrix, and determining whether to retain the current monitoring data according to the data consistency.

[0095] The data consistency CI(T, A) of the current monitoring data according to the first preset matrix and the second preset matrix can be realized by the following formula:

[0096]

[0097] According to the data consistency, it is determined whether to retain the current monitoring data. The smaller the CI value is, the better the data consistency is. It can be determined whether the CI value is smaller than a preset threshold, for example, 0.1. If yes, the current monitoring data is retained. If not, the current monitoring data is discarded, and other monitoring data is calculated.

[0098] Step 250, obtaining the parameter importance between the index parameters of different index types, and determining the data score of the current monitoring data according to the parameter importance and the parameter value of the index parameter.

[0099] Step 260, determining the battery pack state of the target battery pack according to the data score.

[0100] According to the parameter acquisition time and the index type of the index parameter, the target parameter is determined, the first preset matrix is constructed according to the target parameter, and the target parameter sum of each target parameter is obtained. The selection coefficient is determined according to the target parameter sum and the monitoring duration corresponding to the current monitoring data, and the second preset matrix is constructed according to the selection coefficient. According to the first preset matrix and the second preset matrix, the data consistency of the current monitoring data is determined from two dimensions of the parameter acquisition time and the parameter type, the accuracy of the data consistency determination is improved, whether to retain the current monitoring data is determined according to the data consistency, the battery pack state judgment error caused by the poor consistency of the current monitoring data is avoided, and the accuracy of the battery pack state judgment is improved.

[0101] Embodiment three

[0102] Figure 3 A structure schematic diagram of a battery pack state determination device provided by the embodiment three of the application. The device can be realized by hardware and / or software, can execute the battery pack state determination method provided by any embodiment of the application, has the corresponding function modules and beneficial effects of the execution method. For example, Figure 3As shown, the device comprises:

[0103] The monitoring data acquisition module 310 is configured to acquire current monitoring data of the target battery pack; wherein the current monitoring data comprises index parameters corresponding to at least two index types;

[0104] The data score determination module 320 is configured to acquire parameter importance between the index parameters of different index types, and determine a data score of the current monitoring data according to the parameter importance and parameter values of the index parameters;

[0105] The battery pack state determination module 330 is configured to determine a battery pack state of the target battery pack according to the data score.

[0106] On the basis of the above technical solutions, the device further comprises:

[0107] The first matrix construction module is configured to determine a target parameter according to the parameter acquisition time of the index parameters and the index types before the data score determination module acquires the parameter importance between the index parameters of different index types, and construct a first preset matrix according to the target parameter, and obtain a target parameter sum of each target parameter.

[0108] The second matrix construction module is configured to determine a selection coefficient according to the target parameter sum and the monitoring duration corresponding to the current monitoring data, and construct a second preset matrix according to the selection coefficient.

[0109] The data retention determination module is configured to determine data consistency of the current monitoring data according to the first preset matrix and the second preset matrix, and determine whether to retain the current monitoring data according to the data consistency. The data score determination module comprises:

[0110] The parameter acquisition unit is configured to acquire a first index parameter of a first index type, a second index parameter of a second index type, and a third index parameter of a third index type.

[0111] The first parameter importance acquisition unit is configured to acquire a first parameter importance between the first index parameter and the second index parameter, and acquire a second parameter importance between the third index parameter and the second index parameter.

[0112] The second parameter importance acquisition unit is configured to acquire a third parameter importance between the first index parameter and the third index parameter according to the first parameter importance and the second parameter importance.

[0113] On the basis of the above technical solutions, the device further comprises:

[0114] The processing mode determination module is used after the monitoring data acquisition module, and determines a normalization processing mode according to the index type;

[0115] The normalization processing module is used for normalizing index data in the current monitoring data according to the normalization processing mode.

[0116] On the basis of the above technical solutions, optionally, the index type includes at least one of a battery pack capacity, a battery pack charge-discharge times, a battery pack voltage, and a battery pack environment temperature.

[0117] Embodiment four

[0118] Figure 4 A structural schematic diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application as described and / or claimed in this document.

[0119] As shown in Figure 4 The electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0120] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, a speaker, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunications networks.

[0121] The processor 11 can be various general and / or special purpose processing components having processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes various methods and processes described above, such as the battery state determination method.

[0122] In some embodiments, the battery state determination method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the battery state determination method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the battery state determination method by any other appropriate means, such as by means of firmware.

[0123] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0124] Computer programs used to implement the methods of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0125] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0126] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0127] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), blockchain network, and the Internet.

[0128] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0129] It should be understood that the various forms of flow shown above can be used to reorder, add or delete steps. For example, each step described in the present application can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which is not limited herein.

[0130] The above detailed description does not constitute a limitation on the scope of protection of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method of determining the state of a battery pack, characterized by, The method comprises the following steps: obtaining current monitoring data of a target battery pack; wherein the current monitoring data comprises index parameters corresponding to at least two index types; obtaining parameter importance between the index parameters of different index types, and determining a data score of the current monitoring data according to the parameter importance and parameter values of the index parameters; determining a battery pack state of the target battery pack according to the data score; before obtaining the parameter importance between the index parameters of different index types, the method further comprises the following steps: determining target parameters according to parameter acquisition times of the index parameters and the index types, constructing a first preset matrix according to the target parameters, and obtaining target parameter sums of the target parameters; determining selection coefficients according to the target parameter sums and monitoring durations corresponding to the current monitoring data, and constructing a second preset matrix according to the selection coefficients; determining data consistency of the current monitoring data according to the first preset matrix and the second preset matrix, and determining whether to retain the current monitoring data according to the data consistency.

2. The method of claim 1, wherein, The step of obtaining the parameter importance between the index parameters of different index types comprises the following steps: obtaining a first index parameter of a first index type, a second index parameter of a second index type, and a third index parameter of a third index type; obtaining a first parameter importance between the first index parameter and the second index parameter, and a second parameter importance between the third index parameter and the second index parameter; determining a third parameter importance between the first index parameter and the third index parameter according to the first parameter importance and the second parameter importance.

3. The method of claim 1, wherein, After obtaining the current monitoring data of the target battery pack, the method further comprises the following steps: determining a normalization processing mode according to the index types; normalizing index data in the current monitoring data according to the normalization processing mode.

4. The method according to any one of claims 1 to 3, characterized in that, The index types comprise at least one of a battery pack capacity, a battery pack charge-discharge frequency, a battery pack voltage, and a battery pack ambient temperature.

5. A battery pack state determination device characterized by comprising: The device comprises: a monitoring data obtaining module, configured to obtain current monitoring data of a target battery pack; wherein the current monitoring data comprises index parameters corresponding to at least two index types; a data score determining module, configured to obtain parameter importance between the index parameters of different index types, and determine a data score of the current monitoring data according to the parameter importance and parameter values of the index parameters; a battery pack state determining module, configured to determine a battery pack state of the target battery pack according to the data score; The device further comprises: a first matrix constructing module, configured to, before the data score determining module performs the step of obtaining the parameter importance between the index parameters of different index types, determine target parameters according to parameter acquisition times of the index parameters and the index types, construct a first preset matrix according to the target parameters, and obtain target parameter sums of the target parameters; a second matrix constructing module, configured to determine selection coefficients according to the target parameter sums and monitoring durations corresponding to the current monitoring data, and construct a second preset matrix according to the selection coefficients; The data retention determination module is configured to determine data consistency of the current monitoring data according to the first preset matrix and the second preset matrix, and determine whether to retain the current monitoring data according to the data consistency.

6. The apparatus of claim 5, wherein, The data score determination module comprises: The parameter acquisition unit is configured to acquire a first index parameter of a first index type, a second index parameter of a second index type, and a third index parameter of a third index type; The first parameter importance acquisition unit is configured to acquire a first parameter importance of the first index parameter and the second index parameter, and acquire a second parameter importance of the third index parameter and the second index parameter; The second parameter importance acquisition unit is configured to acquire a third parameter importance of the first index parameter and the third index parameter according to the first parameter importance and the second parameter importance.

7. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected with the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the battery pack state determination method of any one of claims 1-4.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to implement the battery pack state determination method of any one of claims 1-4 when executed.

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