A method and device for completing data

Abstract

The present invention provides a data completion method and device, the method comprising: obtaining the current data type of the data to be processed; determining the data update time period corresponding to the data to be processed based on the current data type; judging whether new data to be processed is received in the current data update time period; if new data to be processed is received in the current data update time period, adding the new data to be processed to the current storage position corresponding to the current data update time period. Thus, by setting the corresponding data update time period according to the type of data to be processed, and updating and storing the data according to a fixed period, since the data is stored according to a fixed period, dynamic data completion is achieved, the alignment of the data time axis is guaranteed, and the data comparison is convenient for horizontal comparison, which provides convenience for subsequent data analysis.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a data completion method and device. Background Art

[0002] In the big data platform of the battery and other energy storage industries, it is necessary to store various parameter data of the battery's entire life cycle, so as to evaluate the battery's performance and design battery optimization solutions in the future by means of big data analysis. However, the energy storage data generated by the characteristics of the energy storage scenario is not aligned on the time axis. For example, the differences in the sampling frequency and sampling method of different data make it impossible to align the data on the time axis. When the data is imported into the big data platform for analysis or display, it cannot be compared horizontally due to the misalignment of the time axis, which causes inconvenience to data analysis. Summary of the invention

[0003] In view of this, an embodiment of the present invention provides a data completion method and device to overcome the problem in the prior art that the data generated by the battery in the energy storage scenario is not aligned on the time axis, causing inconvenience in subsequent data analysis.

[0004] An embodiment of the present invention provides a data completion method, including:

[0005] Get the current data type of the data to be processed;

[0006] Determine a data update time period corresponding to the data to be processed based on the current data type;

[0007] Determine whether new data to be processed is received during the current data update time period;

[0008] If new data to be processed is received during the current data update time period, the new data to be processed is added to the current storage location corresponding to the current data update time period.

[0009] Optionally, determining a current data update time period corresponding to the to-be-processed data based on the current data type includes:

[0010] Based on the relationship between the preset data type and the data update time period, the data update time period corresponding to the current data type is determined.

[0011] Optionally, if no new data to be processed is received in the current data update time period, the previous data of the previous storage location corresponding to the previous data update period is obtained;

[0012] The previous data is added to a current storage location corresponding to the current data update time period.

[0013] Optionally, obtaining the current data type of the data to be processed includes:

[0014] Obtain the data usage scenario corresponding to the data to be processed;

[0015] Based on the relationship between the data usage scenario and the preset data usage scenario and data type, the current data type of the to-be-processed data is determined.

[0016] The embodiment of the present invention further provides a data completion device, comprising:

[0017] An acquisition module is used to obtain the current data type of the data to be processed;

[0018] A first processing module, configured to determine a data update time period corresponding to the data to be processed based on the current data type;

[0019] The second processing module is used to determine whether new data to be processed is received in the current data update time period;

[0020] The third processing module is configured to add the new data to be processed to a current storage location corresponding to the current data update time period if new data to be processed is received in the current data update time period.

[0021] Optionally, the first processing module is specifically configured to:

[0022] Based on the relationship between the preset data type and the data update time period, the data update time period corresponding to the current data type is determined.

[0023] Optionally, the device further comprises:

[0024] A fourth processing module, configured to obtain the last data of the last storage location corresponding to the last data update period if no new data to be processed is received in the current data update time period;

[0025] A fifth processing module is used to add the previous data to a current storage location corresponding to the current data update time period.

[0026] Optionally, the acquisition module includes:

[0027] An acquisition unit, used to acquire a data usage scenario corresponding to the data to be processed;

[0028] The processing unit is used to determine the current data type of the data to be processed based on the relationship between the data usage scenario and the preset data usage scenario and the data type.

[0029] An embodiment of the present invention further provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method provided by the embodiment of the present invention by executing the computer instructions.

[0030] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method provided by the embodiment of the present invention.

[0031] The technical solution of the present invention has the following advantages:

[0032] The embodiment of the present invention provides a data completion method and device, which obtains the current data type of the data to be processed; determines the data update time period corresponding to the data to be processed based on the current data type; determines whether new data to be processed is received in the current data update time period; if new data to be processed is received in the current data update time period, the new data to be processed is added to the current storage position corresponding to the current data update time period. Thus, by setting the corresponding data update time period according to the type of data to be processed, and updating and storing the data according to a fixed period, since the data is stored according to a fixed period, dynamic data completion is achieved, the alignment of the data time axis is guaranteed, and the horizontal data comparison is convenient, which provides convenience for subsequent data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 is a flow chart of a data completion method in an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of the working process of data completion in an embodiment of the present invention;

[0036] Figure 3 Schematic diagram of the structure of a data completion device in an embodiment of the present invention;

[0037] Figure 4 Schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0039] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0040] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal connection of two components, it can be a wireless connection, or it can be a wired connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0041] The technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0042] In the big data platform of the battery and other energy storage industries, it is necessary to store various parameter data of the battery's entire life cycle, so as to evaluate the battery's performance and design battery optimization solutions in the future by means of big data analysis. However, the energy storage data generated by the characteristics of the energy storage scenario is not aligned on the time axis. For example, the differences in the sampling frequency and sampling method of different data make it impossible to align the data on the time axis. When the data is imported into the big data platform for analysis or display, it cannot be compared horizontally due to the misalignment of the time axis, which causes inconvenience to data analysis.

[0043] Based on the above problems, an embodiment of the present invention provides a data completion method, such as Figure 1 As shown, the data completion method specifically includes the following steps:

[0044] Step S101: Obtain the current data type of the data to be processed.

[0045] Specifically, in one embodiment, the above step S101 specifically includes the following steps:

[0046] Step S201: Obtain the data usage scenario corresponding to the data to be processed.

[0047] Step S202: Determine the current data type of the data to be processed based on the data usage scenario and the relationship between the preset data usage scenario and the data type.

[0048] Among them, when the data completion method is applied to the battery energy storage scenario, the data to be processed can be various collected data of the battery, such as the battery charging voltage, charging current, battery capacity, etc. The data type can be divided in advance according to the data usage scenario of the battery data, such as: divided into cell layer data, device layer data and summary layer data, etc. The present invention is only taken as an example and is not limited to this.

[0049] Specifically, the type of field corresponding to the data to be processed can be dynamically identified to determine what the data to be processed is, and the data usage scenario corresponding to the data to be processed can be determined based on the relationship between the field type and the data usage scenario determined in advance.

[0050] Step S102: Determine a data update time period corresponding to the data to be processed based on the current data type.

[0051] Specifically, the above step S102 determines the data update time period corresponding to the current data type based on the relationship between the preset data type and the data update time period.

[0052] Furthermore, the correspondence between different data types and data update time periods can be flexibly set according to the actual needs of data analysis and processing. For example, for battery layer data such as battery voltage, temperature, SOC, etc., due to the high time accuracy requirement, a shorter data update time period can be set, such as 10ms, while other data that do not require high time progress can extend the data update time period, such as 200ms, which will not have a significant impact on the subsequent analysis data results. The present invention is only taken as an example and is not limited to this.

[0053] Step S103: Determine whether new data to be processed is received in the current data update time period.

[0054] Specifically, in actual applications, the voltage, temperature and other data of the battery cells are monitored according to a fixed sampling period. It is possible that data sampling is performed within a certain data update period to obtain new data, or it is possible that data sampling is not performed within a certain data update period. Therefore, by judging whether new data to be processed is received, it is determined whether there is a data update.

[0055] Step S104: if new data to be processed is received in the current data update time period, the new data to be processed is added to the current storage location corresponding to the current data update time period.

[0056] Specifically, by adding new data to be processed to the corresponding storage location, data is stored according to the data update time period, and through the corresponding relationship between the data and the corresponding data update time period, the data is aligned on the time axis.

[0057] By executing the above steps, the data completion method provided by the embodiment of the present invention sets the corresponding data update time period according to the type of data to be processed, and updates and stores the data according to a fixed period. Since the data are stored according to a fixed period, dynamic data completion is achieved, the alignment of the data time axis is ensured, and horizontal data comparison is facilitated, which provides convenience for subsequent data analysis.

[0058] Specifically, in one embodiment, the above data completion method further includes the following steps:

[0059] Step S105: If no new data to be processed is received in the current data update time period, the previous data of the previous storage location corresponding to the previous data update period is obtained.

[0060] Step S106: Add the previous data to the current storage location corresponding to the current data update time period.

[0061] Specifically, if no new processing data is received during the current data update time period, the value of the last recent data is automatically continued, and all data values ​​of the same type are completed using the same time axis so that they can be analyzed and displayed under the same time axis.

[0062] The data completion method provided by the embodiment of the present invention will be described in detail below with reference to specific application examples.

[0063] The purpose of the technical solution provided by the present invention is to organize the energy storage data accessed by the big data platform through a data alignment solution so that it can be displayed and analyzed by the platform on a timeline. Its characteristic is that the data alignment method can dynamically determine the step size of the timeline alignment according to different types of data.

[0064] In order to achieve the above-mentioned purpose, the present invention adopts dynamic identification of field types and matches the preset fixed time step. A piece of data is generated for each step time of the connected data point. If the latest data is not received within the step time, the value of the last recent data is automatically continued, and all data values ​​of the same type are filled in the same time axis so that they can be analyzed and displayed under the same time axis; the energy storage scenario can be analyzed and displayed preliminarily. The data can be divided into cell layer data, equipment layer data, and summary layer data. The voltage, temperature, SOC, etc. of the cell can be classified as the cell layer. Since the cell layer has high requirements for time accuracy, 10ms can be used as a fixed step. The data generated by equipment such as air conditioning, fire protection, PCS, and electric meters can be classified as the equipment layer, and 200ms can be used as a fixed step. The data statistically generated by other EMS can be classified as the summary layer, and 500ms can be used as a fixed step. The fixed step corresponding to the above different types of data can be changed according to actual conditions. The present invention only takes this as an example and is not limited to this.

[0065] like Figure 2 As shown, by generating multiple rolling windows according to the preset data type, automatically matching the data type of the data, determining whether there is new data within the window period, and if not, taking the data of the previous window period as the latest data to complete the data filling. Therefore, by aligning the data according to a fixed time step, the time step can be dynamically generated for different types of data, and then the data can be dynamically filled according to the generated time step, which can solve the problem of data time misalignment. Fully consider the inconsistency and diversity of energy storage scenario data, design a general data structure, expand compatibility, and use the method of dynamically matching data types. For different data types, different data alignment methods are used to ensure the effectiveness of data alignment and improve data readability.

[0066] By executing the above steps, the data completion method provided by the embodiment of the present invention sets the corresponding data update time period according to the type of data to be processed, and updates and stores the data according to a fixed period. Since the data are stored according to a fixed period, dynamic data completion is achieved, the alignment of the data time axis is ensured, and horizontal data comparison is facilitated, which provides convenience for subsequent data analysis.

[0067] The embodiment of the present invention also provides a data completion device, such as Figure 3 As shown, the data completion device includes:

[0068] The acquisition module 101 is used to acquire the current data type of the data to be processed. For details, please refer to the relevant description of step S101 in the above method embodiment, which will not be repeated here.

[0069] The first processing module 102 is used to determine the data update time period corresponding to the data to be processed based on the current data type. For details, please refer to the relevant description of step S102 in the above method embodiment, which will not be repeated here.

[0070] The second processing module 103 is used to determine whether new data to be processed is received in the current data update time period. For details, please refer to the relevant description of step S103 in the above method embodiment, which will not be repeated here.

[0071] The third processing module 104 is used to add the new data to be processed to the current storage location corresponding to the current data update time period if new data to be processed is received in the current data update time period. For details, please refer to the relevant description of step S104 in the above method embodiment, which will not be repeated here.

[0072] Through the coordinated cooperation of the above-mentioned components, the data completion device provided in the embodiment of the present invention sets the corresponding data update time period according to the type of data to be processed, and updates and stores the data according to a fixed period. Since the data are stored according to a fixed period, dynamic data completion is achieved, the alignment of the data time axis is ensured, and horizontal data comparison is facilitated, which provides convenience for subsequent data analysis.

[0073] Specifically, in one embodiment, the acquisition module 101 includes:

[0074] The acquisition unit is used to acquire the data usage scenario corresponding to the data to be processed. For details, please refer to the relevant description of step S201 in the above method embodiment, which will not be repeated here.

[0075] The processing unit is used to determine the current data type of the data to be processed based on the data usage scenario and the relationship between the preset data usage scenario and the data type. For details, please refer to the relevant description of step S202 in the above method embodiment, which will not be repeated here.

[0076] Specifically, in one embodiment, the first processing module 102 is specifically used to determine the data update time period corresponding to the current data type based on the relationship between the preset data type and the data update time period. For details, see the relevant description of step S102 in the above method embodiment, which will not be repeated here.

[0077] Specifically, in one embodiment, the data completion device further includes:

[0078] The fourth processing module is used to obtain the last data of the last storage location corresponding to the last data update period if no new data to be processed is received in the current data update period. For details, please refer to the relevant description of step S105 in the above method embodiment, which will not be repeated here.

[0079] The fifth processing module is used to add the previous data to the current storage location corresponding to the current data update time period. For details, please refer to the relevant description of step S106 in the above method embodiment, which will not be repeated here.

[0080] Through the coordinated cooperation of the above-mentioned components, the data completion device provided in the embodiment of the present invention sets the corresponding data update time period according to the type of data to be processed, and updates and stores the data according to a fixed period. Since the data are stored according to a fixed period, dynamic data completion is achieved, the alignment of the data time axis is ensured, and horizontal data comparison is facilitated, which provides convenience for subsequent data analysis.

[0081] The further functional description of each of the above modules is the same as that of the above corresponding method embodiments and will not be repeated here.

[0082] According to an embodiment of the present invention, there is also provided an electronic device, such as Figure 4 As shown, the electronic device may include a processor 901 and a memory 902, wherein the processor 901 and the memory 902 may be connected via a bus or other means. Figure 4 The example of connecting through bus is taken in the following.

[0083] The processor 901 may be a central processing unit (CPU). The processor 901 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0084] The memory 902 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the methods in the method embodiments of the present invention. The processor 901 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 902, that is, implementing the methods in the above method embodiments.

[0085] The memory 902 may include a program storage area and a data storage area, wherein the program storage area may store an application required for operating the device and at least one function; the data storage area may store data created by the processor 901, etc. In addition, the memory 902 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 902 may optionally include a memory remotely arranged relative to the processor 901, and these remote memories may be connected to the processor 901 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0086] One or more modules are stored in the memory 902 , and when executed by the processor 901 , the method in the above method embodiment is executed.

[0087] The specific details of the above electronic device can be understood by referring to the corresponding descriptions and effects in the above method embodiments, and will not be repeated here.

[0088] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the implemented program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0089] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A data completion method, characterized in that: include: Get the current data type of the data to be processed; Determine a data update time period corresponding to the data to be processed based on the current data type; Determine whether new data to be processed is received during the current data update time period; If new data to be processed is received during the current data update time period, the new data to be processed is added to the current storage location corresponding to the current data update time period; If no new data to be processed is received in the current data update time period, the previous data of the previous storage location corresponding to the previous data update period is obtained; Adding the previous data to the current storage location corresponding to the current data update time period; The determination of whether new data to be processed is received in the current data update time period includes: generating multiple rolling windows according to preset data types, automatically matching the current data type of the data to be processed, and determining whether there is new data within the window period. If not, the data in the previous window period needs to be used as the latest data to complete the data completion so that it can be analyzed and displayed on the same timeline.

2. The method according to claim 1, characterized in that The determining, based on the current data type, a current data update time period corresponding to the data to be processed includes: Based on the relationship between the preset data type and the data update time period, the data update time period corresponding to the current data type is determined.

3. The method according to claim 1, characterized in that The obtaining of the current data type of the data to be processed includes: Obtain the data usage scenario corresponding to the data to be processed; Based on the data usage scenario and the relationship between the preset data usage scenario and the data type, the current data type of the to-be-processed data is determined.

4. A data completion device, characterized in that: include: An acquisition module is used to obtain the current data type of the data to be processed; A first processing module, configured to determine a data update time period corresponding to the data to be processed based on the current data type; The second processing module is used to determine whether new data to be processed is received in the current data update time period; The determining whether new data to be processed is received in the current data update time period includes: generating multiple rolling windows according to preset data types, automatically matching the current data type of the data to be processed, determining whether there is new data in the window period, and if there is no need to use the data in the previous window period as the latest data, completing the data completion so that it can be analyzed and displayed on the same time axis; A third processing module, configured to add new data to be processed to a current storage location corresponding to the current data update time period if new data to be processed is received in the current data update time period; A fourth processing module, configured to obtain the last data of the last storage location corresponding to the last data update period if no new data to be processed is received in the current data update time period; A fifth processing module is used to add the previous data to a current storage location corresponding to the current data update time period.

5. The device according to claim 4, characterized in that The first processing module is specifically configured to determine the data update time period corresponding to the current data type based on the relationship between the preset data type and the data update time period.

6. The device according to claim 4, characterized in that The acquisition module comprises: An acquisition unit, used to acquire a data usage scenario corresponding to the data to be processed; The processing unit is used to determine the current data type of the data to be processed based on the relationship between the data usage scenario and the preset data usage scenario and the data type.

7. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 3 by executing the computer instructions.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 3.

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