Vehicle data processing method and device

Abstract

This application provides a vehicle data processing method and apparatus. The method includes: traversing vehicle historical data to determine initial label values ​​for null fields and initial label values ​​for non-null fields; determining group label values ​​for null fields and non-null fields based on the initial label values ​​of the null and non-null fields; grouping the null and non-null fields in the vehicle historical data according to the vehicle identifier, the group label values ​​of the null fields, and the group label values ​​of the non-null fields, obtaining at least one group of fields to be filled; and filling the null fields in the group of fields to be filled according to the target values ​​of the non-null fields in the group of fields to be filled. This application can fill fields with missing values ​​based on the vehicle data itself, making the filled data closer to the actual data and improving the efficiency of data processing.

Description

Technical Field

[0001] This application relates to the field of vehicle data processing technology, and in particular to a vehicle data processing method and apparatus. Background Technology

[0002] With economic development and improved living standards, the demand for driving has increased. Furthermore, the rapid development of information and internet technologies has enabled remote collection of data from various sensors, generating a large amount of vehicle operation data. However, due to equipment, network, or design limitations, some data values ​​may be missing. Currently, when filling in fields with missing data values, methods can be used to calculate the average value of all data in the current field or to calculate data similarity using algorithms. However, this method may result in significant discrepancies between the filled data and the actual data, and it is unsuitable for filling large amounts of vehicle data, leading to reduced efficiency in vehicle data processing. Summary of the Invention

[0003] In view of this, embodiments of this application provide a vehicle data processing method, apparatus, electronic device, and computer-readable storage medium to solve the problems in related technologies where the filled vehicle data differs significantly from the actual data and the efficiency of vehicle data processing is reduced when using average or similarity methods to fill vehicle data.

[0004] A first aspect of this application provides a vehicle data processing method, the method comprising: acquiring vehicle historical data; traversing the vehicle historical data to determine initial label values ​​for null fields and initial label values ​​for non-null fields in the vehicle historical data; determining group label values ​​for null fields and group label values ​​for non-null fields in the vehicle historical data based on the initial label values ​​for null fields and non-null fields in the vehicle historical data; grouping the null fields and non-null fields in the vehicle historical data according to the vehicle identifier, the group label values ​​for null fields, and the group label values ​​for non-null fields in the vehicle historical data to obtain at least one group of fields to be filled in the vehicle historical data; and filling the null fields in the group of fields to be filled according to the target values ​​of the non-null fields in the group of fields to be filled.

[0005] A second aspect of this application provides a vehicle data processing apparatus, comprising: an acquisition module for acquiring vehicle historical data; an initial label value determination module for traversing the vehicle historical data and determining initial label values ​​for null fields and non-null fields in the vehicle historical data; a group label value determination module for determining group label values ​​for null fields and group label values ​​for non-null fields in the vehicle historical data based on the initial label values ​​for null fields and non-null fields in the vehicle historical data; a grouping module for grouping null fields and non-null fields in the vehicle historical data according to vehicle identifiers, group label values ​​for null fields, and group label values ​​for non-null fields in the vehicle historical data, to obtain at least one field group to be filled in the vehicle historical data; and a filling module for filling null fields in the field group to be filled according to target values ​​of non-null fields in the field group to be filled.

[0006] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0007] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0008] The beneficial effects of this application embodiment compared with the prior art include at least the following: This application embodiment can traverse vehicle historical data to determine the initial label values ​​of null fields and non-null fields in the vehicle historical data, and determine the group label values ​​of null fields and non-null fields in the vehicle historical data based on the initial label values ​​of null fields and non-null fields in the vehicle historical data. Then, based on the vehicle identifier, the group label values ​​of null fields, and the group label values ​​of non-null fields in the vehicle historical data, the null fields and non-null fields in the vehicle historical data are grouped to obtain at least one group of fields to be filled in the vehicle historical data. Based on the target values ​​of the non-null fields in the group of fields to be filled, the null fields in the group of fields to be filled are filled. In this way, fields with missing values ​​can be filled based on the vehicle data itself, so that the filled data is closer to the real data, and the efficiency of processing vehicle data can also be improved. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown;

[0011] Figure 2 This is a flowchart of a vehicle data processing method according to an embodiment of this application;

[0012] Figure 3 This is a flowchart illustrating the steps of determining the grouping label values ​​of null value fields and non-null value fields in vehicle history data according to an embodiment of this application.

[0013] Figure 4 This is a flowchart illustrating another step in an embodiment of this application to determine the grouping label value of a null value field and the grouping label value of a non-null value field in vehicle history data;

[0014] Figure 5 This is a flowchart illustrating the steps of grouping null and non-null fields in vehicle history data according to an embodiment of this application.

[0015] Figure 6 This is a flowchart of another vehicle data processing method according to an embodiment of this application;

[0016] Figure 7 This is a flowchart illustrating another vehicle data processing method according to an embodiment of this application.

[0017] Figure 8 This is a block diagram of a vehicle data processing device according to an embodiment of this application;

[0018] Figure 9 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0019] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0020] The vehicle data processing method and apparatus according to embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0021] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown.

[0022] like Figure 1 As shown, system architecture 100 may include one or more of vehicle devices 101, 102, and 103, network 104, and server 105. Network 104 is used as a medium to provide a communication link between vehicle devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0023] It should be understood that Figure 1 The number of vehicles, devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of vehicles, devices, networks, and servers can be included. For example, server 105 could be a server cluster composed of multiple servers.

[0024] Users can use vehicle devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send vehicle data, etc. Vehicle devices 101, 102, and 103 can be various electronic devices with displays.

[0025] Server 105 can be a server providing various services. For example, server 105 can obtain vehicle historical data from vehicle device 103 (or vehicle device 101 or 102), traverse the vehicle historical data, determine the initial label values ​​of null fields and non-null fields in the vehicle historical data, and determine the group label values ​​of null fields and non-null fields in the vehicle historical data based on the initial label values ​​of null fields and non-null fields in the vehicle historical data. Then, based on the vehicle identifier, the group label values ​​of null fields, and the group label values ​​of non-null fields in the vehicle historical data, the null fields and non-null fields in the vehicle historical data are grouped to obtain at least one group of fields to be filled. Based on the target values ​​of the non-null fields in the group of fields to be filled, the null fields in the group of fields to be filled are filled. In this way, fields with missing values ​​can be filled based on the vehicle data itself, so that the filled data is closer to the real data, and the efficiency of processing vehicle data can also be improved.

[0026] In some embodiments, the vehicle data processing method provided in this invention is generally executed by server 105, and correspondingly, the vehicle data processing device is generally located in server 105. In other embodiments, certain vehicle devices may have functions similar to those of a server to execute this method. Therefore, the vehicle data processing method provided in this invention is not limited to execution on the server side.

[0027] Figure 2 This is a flowchart illustrating a vehicle data processing method according to an embodiment of this application. The method provided in this application embodiment can be executed by any electronic device with computer processing capabilities; for example, the electronic device may be... Figure 1 The server shown.

[0028] like Figure 2 As shown, the method includes steps S210 to S250.

[0029] In step S210, historical vehicle data is acquired.

[0030] In step S220, the vehicle history data is traversed to determine the initial label values ​​of null fields and non-null fields in the vehicle history data.

[0031] In step S230, based on the initial label values ​​of the null value fields and the initial label values ​​of the non-null value fields in the vehicle history data, the group label values ​​of the null value fields and the group label values ​​of the non-null value fields in the vehicle history data are determined.

[0032] In step S240, based on the vehicle identifier in the vehicle history data, the grouping label value of the null value field in the vehicle history data, and the grouping label value of the non-null value field in the vehicle history data, the null value field and the non-null value field in the vehicle history data are grouped to obtain at least one group of fields to be filled in the vehicle history data.

[0033] In step S250, the null value fields in the field group to be filled are filled according to the target value of the non-null value fields in the field group to be filled.

[0034] This method can traverse vehicle historical data, determine the initial label values ​​of null and non-null fields, and then determine the group label values ​​of null and non-null fields based on these initial label values. Next, based on the vehicle identifier, the group label values ​​of null and non-null fields in the historical data, the null and non-null fields are grouped to obtain at least one group of fields to be filled. Finally, based on the target values ​​of the non-null fields in the group, the null fields are filled. This method fills in missing values ​​in the fields based on the vehicle data itself, making the filled data closer to the actual data and improving the efficiency of vehicle data processing.

[0035] In some embodiments, the aforementioned vehicle historical data may be vehicle operation data collected from vehicle equipment. For example, vehicle location data, vehicle mileage data, etc., but not limited to these. The vehicle historical data in this application embodiment is specifically shown in Table 1 or Table 2 below:

[0036] Table 1

[0037] Serial Number vin Time field Field to be filled 1 LMR1111 2023 / 2 / 11 9:13:32 \N 2 LMR1111 2023 / 2 / 11 9:13:33 \N 3 LMR1111 2023 / 2 / 11 9:13:34 \N 4 LMR1111 2023 / 2 / 11 9:13:36 20 5 LMR1111 2023 / 2 / 11 9:13:37 \N 6 LMR1111 2023 / 2 / 11 9:13:38 \N 7 LMR1111 2023 / 2 / 11 9:13:39 \N 8 LMR1111 2023 / 2 / 11 9:13:40 21 9 LMR1111 2023 / 2 / 11 9:13:41 \N 10 LMR2222 2023 / 2 / 11 9:13:32 \N 11 LMR2222 2023 / 2 / 11 9:13:33 \N 12 LMR2222 2023 / 2 / 11 9:13:34 50 13 LMR2222 2023 / 2 / 11 9:13:35 \N 14 LMR2222 2023 / 2 / 11 9:13:36 \N 15 LMR2222 2023 / 2 / 11 9:13:37 52 16 LMR2222 2023 / 2 / 11 9:13:38 \N 17 LMR2222 2023 / 2 / 11 9:13:39 \N

[0038] Table 2

[0039] Serial Number vin Time field Field to be filled 1 LMR1111 2023 / 2 / 11 9:13:32 18 2 LMR1111 2023 / 2 / 11 9:13:33 \N 3 LMR1111 2023 / 2 / 11 9:13:34 \N 4 LMR1111 2023 / 2 / 11 9:13:36 20 5 LMR1111 2023 / 2 / 11 9:13:37 \N 6 LMR1111 2023 / 2 / 11 9:13:38 \N 7 LMR1111 2023 / 2 / 11 9:13:39 \N 8 LMR1111 2023 / 2 / 11 9:13:40 21 9 LMR1111 2023 / 2 / 11 9:13:41 \N 10 LMR2222 2023 / 2 / 11 9:13:32 \N 11 LMR2222 2023 / 2 / 11 9:13:33 \N 12 LMR2222 2023 / 2 / 11 9:13:34 49 13 LMR2222 2023 / 2 / 11 9:13:35 \N 14 LMR2222 2023 / 2 / 11 9:13:36 \N 15 LMR2222 2023 / 2 / 11 9:13:37 50 16 LMR2222 2023 / 2 / 11 9:13:38 \N 17 LMR2222 2023 / 2 / 11 9:13:39 \N

[0040] Table 1 shows the first row of fields to be filled, which are null fields (e.g., represented by \N). Table 2 shows the first row of fields to be filled, which are non-null fields. In this embodiment, null fields are fields with missing values. Non-null fields are fields with actual values. The vin field in Table 1 or Table 2 identifies the vehicle identifier.

[0041] In some embodiments, vehicle history data is traversed to determine the initial label values ​​for null fields and non-null fields. For example, the vehicle history data in Table 1 or Table 2 above is traversed, and null and non-null fields are marked. In this embodiment, 0 can be used as the initial label value for marking null fields, and any value other than 0 can be used as the initial label value for non-null fields. For example, an initial label value of 0 can be used to mark null fields, and an initial label value of 1 can be used to mark non-null fields. The marked vehicle history data is shown in Table 3 or Table 4 below:

[0042] Table 3

[0043] Serial Number vin Time field Field to be filled Tag field 1 LMR1111 2023 / 2 / 11 9:13:32 \N 0 2 LMR1111 2023 / 2 / 11 9:13:33 \N 0 3 LMR1111 2023 / 2 / 11 9:13:34 \N 0 4 LMR1111 2023 / 2 / 11 9:13:36 20 1 5 LMR1111 2023 / 2 / 11 9:13:37 \N 0 6 LMR1111 2023 / 2 / 11 9:13:38 \N 0 7 LMR1111 2023 / 2 / 11 9:13:39 \N 0 8 LMR1111 2023 / 2 / 11 9:13:40 21 1 9 LMR1111 2023 / 2 / 11 9:13:41 \N 0 10 LMR2222 2023 / 2 / 11 9:13:32 \N 0 11 LMR2222 2023 / 2 / 11 9:13:33 \N 0 12 LMR2222 2023 / 2 / 11 9:13:34 50 1 13 LMR2222 2023 / 2 / 11 9:13:35 \N 0 14 LMR2222 2023 / 2 / 11 9:13:36 \N 0 15 LMR2222 2023 / 2 / 11 9:13:37 52 1 16 LMR2222 2023 / 2 / 11 9:13:38 \N 0 17 LMR2222 2023 / 2 / 11 9:13:39 \N 0

[0044] Table 4

[0045]

[0046]

[0047] In some embodiments, the grouping label values ​​of the null fields and the grouping label values ​​of the non-null fields in the vehicle history data are determined based on the initial label values ​​of the null fields and the non-null fields in the vehicle history data. For example, the initial label values ​​of all fields to be filled for the same vehicle identifier are summed from the current row to all previous rows in chronological order (ascending order for upward filling, descending order for downward filling) to obtain the grouping label values ​​of the null fields and the intermediate label values ​​of the non-null fields in the vehicle history data. Specifically, referring to Table 3, for the data corresponding to vehicle identifier LMR1111, the current row is the second row. The intermediate label value of the null fields in the second row can be obtained by summing the initial label values ​​of the null fields in the second row with the initial label values ​​of the null fields in the first row, i.e., the intermediate label value of the null fields in the second row is 0. Referring to Table 4, for the data corresponding to vehicle identifier LMR1111, the current row is the second row. The intermediate label value of the null field in the second row can be obtained by summing the initial label value of the null field in the second row with the initial label value of the non-null field in the first row, i.e., the intermediate label value of the null field in the second row is 1. Through the above calculation method, the intermediate label values ​​of all null fields and all non-null fields in the vehicle historical data can be obtained, as shown in Table 5 or Table 6:

[0048] Table 5

[0049]

[0050]

[0051] Table 6

[0052]

[0053] In some embodiments, it is determined whether the intermediate label value of the current null value field is the same as the initial label value of the current null value field. If they are the same, the initial label value of the non-null value field in the vehicle history data is used as the group label value of the current null value field in the vehicle history data; or, if they are not the same, the intermediate label value of the current null value field is determined as the group label value of the current null value field in the vehicle history data. The intermediate label value of the current non-null value field is determined as the group label value of the current non-null value field in the vehicle history data. Referring to Table 5, the initial label value and intermediate label value of the null value field in the first row are both zero. In this case, the initial label value of the non-null value field in Table 5 can be used as the group label value of the null value field, that is, the group label value of the null value field is 1. The initial label value of the null value field in the fifth row is 0, and the intermediate label value is 1. In this case, the intermediate label value of the null value field can be used as the group label value of the null value field, that is, 1. Referring to Table 6, the initial label value and intermediate label value of the null field in row 10 are both zero. Therefore, the initial label value of the non-null fields in Table 6 can be used as the grouping label value for this null field, i.e., the grouping label value for this null field is 1. The initial label value of the null field in row 13 is 0, and the intermediate label value is 1. Therefore, the intermediate label value of this null field can be used as the grouping label value for this null field, i.e., 1. Using the above method, the grouping label values ​​of null fields and non-null fields in the vehicle history data can be obtained, as shown in Tables 7 and 8 below:

[0054] Table 7

[0055]

[0056] Table 8

[0057]

[0058] In some embodiments, the null and non-null fields in the vehicle history data are grouped according to the vehicle identifier, the grouping label value of the null field in the vehicle history data, and the grouping label value of the non-null field in the vehicle history data, to obtain at least one group of fields to be filled in the vehicle history data. The null fields in the group of fields to be filled are then filled according to the target value of the non-null field in the group of fields to be filled. (See reference) Figure 7For the same vehicle identifier LMR1111, the null and non-null fields in rows 1 to 7 are grouped together as fields to be filled. The null fields in this group are filled with a value of 20 based on the target value of 20 for the non-null fields in row 4. Similarly, the null and non-null fields in rows 8 and 9 are grouped together as fields to be filled. The null fields in this group are filled with a value of 21 based on the target value of 21 for the non-null fields in row 8. (Reference) Figure 8 For the same vehicle identifier LMR1111, the null and non-null fields in rows 1 to 3 are grouped together as fields to be filled. The null fields in this group are filled with the target value of 18 for the non-null fields in row 1, resulting in a fill value of 18 for the null fields. Similarly, the null and non-null fields in rows 4 to 7 are grouped together as fields to be filled. The null fields in this group are filled with the target value of 20 for the non-null fields in row 4, resulting in a fill value of 20 for the null fields. Finally, the null and non-null fields in rows 8 and 9 are grouped together as fields to be filled. The null fields in this group are filled with the target value of 21 for the non-null fields in row 8, resulting in a fill value of 21 for the null fields. This method allows for the filling of null fields in vehicle history data based on the actual values ​​of the vehicle data itself. The filling results are shown in Tables 9 and 10 below.

[0059] Table 9

[0060]

[0061] Table 10

[0062]

[0063] In some embodiments, the method further includes: when the target value of a non-nullable field in the field group to be filled is less than the group label value in the field group to be filled, filling the nullable field in the field group to be filled according to the group label value in the field group to be filled.

[0064] The vehicle data processing method provided in this application can be used to fill in vehicle data containing latitude and longitude or vehicle data containing mileage, thereby obtaining filled data that is closer to the real data.

[0065] Figure 3 This is a flowchart illustrating the steps of determining the grouping label values ​​of null value fields and non-null value fields in vehicle historical data according to an embodiment of this application.

[0066] like Figure 3 As shown, step S230 may include steps S310 to S330.

[0067] In step S310, according to the time order of the fields in the vehicle history data, the intermediate label value of the current null value field is determined based on the initial label value of the current null value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current null value field, and the vehicle identifier corresponding to the current null value field.

[0068] In step S320, according to the time order of the fields in the vehicle history data, the intermediate label value of the current non-empty value field is determined based on the initial label value of the current non-empty value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current non-empty value field, and the vehicle identifier corresponding to the non-empty value field.

[0069] In step S330, the grouping label values ​​of the null value fields and the grouping label values ​​of the non-null value fields in the vehicle history data are determined based on the intermediate label value of the current null value field and the intermediate label value of the current non-null value field.

[0070] This method can determine the grouping label values ​​of the null value fields and the non-null value fields in the vehicle history data based on the intermediate label values ​​of the current null value fields and the current non-null value fields, so as to facilitate subsequent grouping of the null value fields and non-null value fields in the vehicle history data according to the vehicle identifier and the grouping label values.

[0071] In some embodiments, the intermediate label value of the current null field is determined according to the chronological order of the fields in the vehicle history data, based on the initial label value of the current null field, the initial label values ​​of all fields preceding the time information corresponding to the current null field, and the vehicle identifier corresponding to the current null field. Similarly, the intermediate label value of the current non-null field is determined according to the chronological order of the fields in the vehicle history data, based on the initial label value of the current non-null field, the initial label values ​​of all fields preceding the time information corresponding to the current non-null field, and the vehicle identifier corresponding to the non-null field. For example, the initial label values ​​of all fields to be filled for the same vehicle identifier are summed from the current row to all previous rows in chronological order (ascending order for upward filling, descending order for downward filling) to obtain the group label value of the null field and the intermediate label value of the non-null field in the vehicle history data, as shown in Table 5 or Table 6.

[0072] Figure 4 This is a flowchart illustrating another step in determining the grouping label values ​​of null fields and non-null fields in vehicle history data, according to an embodiment of this application.

[0073] like Figure 4 As shown, step 330 may specifically include steps S410 to S430.

[0074] In step S410, it is determined whether the intermediate label value of the current null value field is the same as the initial label value of the current null value field.

[0075] In step S420, if they are the same, the initial label value of the non-null value field in the vehicle history data is used as the group label value of the current null value field in the vehicle history data; or, if they are different, the intermediate label value of the current null value field is determined as the group label value of the current null value field in the vehicle history data.

[0076] In step S430, the intermediate label value of the current non-empty value field is determined as the group label value of the current non-empty value field in the vehicle history data.

[0077] This method can determine whether the intermediate label value of the current null field is the same as the initial label value of the current null field. If they are the same, the initial label value of the non-null field in the vehicle history data is used as the group label value of the current null field in the vehicle history data. Alternatively, if they are different, the intermediate label value of the current null field is determined as the group label value of the current null field in the vehicle history data. This method can quickly and accurately determine the group label of the null field.

[0078] Referring to Table 5 above, the initial label value and intermediate label value of the null value field in the first row are both zero. In this case, the initial label value of the non-null value field in Table 5 can be used as the group label value of the null value field, that is, the group label value of the null value field is 1. The initial label value of the null value field in the fifth row is 0, and the intermediate label value is 1. In this case, the intermediate label value of the null value field can be used as the group label value of the null value field, that is, 1, as shown in Table 7 above.

[0079] Referring to Table 6, the initial and intermediate label values ​​of the null value field in row 10 are both zero. Therefore, the initial label value of the non-null value field in Table 6 can be used as the grouping label value for this null value field, i.e., the grouping label value for this null value field is 1. The initial label value of the null value field in row 13 is 0, and the intermediate label value is 1. Therefore, the intermediate label value of this null value field can be used as the grouping label value for this null value field, i.e., 1. Using the above method, the grouping label values ​​for null value fields and non-null value fields in vehicle history data can be obtained, as shown in Table 8 above.

[0080] Figure 5 This is a flowchart illustrating the steps of grouping null and non-null fields in vehicle history data according to an embodiment of this application.

[0081] like Figure 5As shown, step S240 may specifically include steps S510 and S520.

[0082] In step S510, null and non-null fields with the same group label value corresponding to the same vehicle identifier are grouped into a field group to be filled.

[0083] In step S520, the above steps are repeated to group the null and non-null fields in the vehicle history data to obtain at least one group of fields to be filled in the vehicle history data.

[0084] This method can group null and non-null fields with the same grouping label value corresponding to the same vehicle identifier into a field group to be filled. By repeating the above steps, the null and non-null fields in the vehicle history data are grouped to obtain at least one field group to be filled in the vehicle history data. In this way, the null and non-null fields of the vehicle data corresponding to the same vehicle identifier can be grouped simply and conveniently, further improving the efficiency of filling data.

[0085] In some embodiments, null and non-null fields with the same grouping label value corresponding to the same vehicle identifier are grouped into a single field group to be filled. (Refer to the above...) Figure 7 For the same vehicle identifier LMR1111, the null and non-null fields in rows 1 through 7 are grouped together as one field to be filled. The null and non-null fields in rows 8 and 9 are grouped together as another field to be filled. (See reference) Figure 8 For the same vehicle identifier LMR1111, the null and non-null fields in rows 1 to 3 are grouped together as a single field to be filled. The null and non-null fields in rows 4 to 7 are grouped together as a single field to be filled. The null and non-null fields in rows 8 and 9 are grouped together as a single field to be filled.

[0086] Figure 6 This is a flowchart of another vehicle data processing method according to an embodiment of this application. In this embodiment, before determining the initial label values ​​of null value fields and non-null value fields in the vehicle historical data, the method further includes steps S610 and S620, as follows: Figure 6 As shown.

[0087] In step S610, it is determined whether all fields in the vehicle history data to be filled are empty fields.

[0088] In step S620, if all fields in the vehicle history data to be filled are empty fields, a prompt message is sent.

[0089] This method can determine whether all fields in the vehicle history data to be filled are empty fields. If all fields in the vehicle history data to be filled are empty fields, a prompt message is sent, which helps to remind relevant personnel to check the data acquisition equipment or communication equipment of the vehicle equipment in a timely manner.

[0090] Figure 7 This is a flowchart of another vehicle data processing method according to an embodiment of this application. In this embodiment, if the data to be filled in the vehicle historical data is mileage data, the method further includes steps S710 to S740, such as... Figure 7 As shown.

[0091] In step S710, the vehicle's battery system status, DC charging status, DC charging connection status, AC charging status, and AC charging connection status are acquired.

[0092] In step S720, the current state of the vehicle is determined to be either charging or discharging based on the vehicle's battery system state, DC charging state, DC charging connection state, AC charging state, and AC charging connection state.

[0093] In step S730, when the current state of the vehicle is charging, the voltage difference of the vehicle during charging is determined, or when the current state of the vehicle is discharging, the voltage difference of the vehicle during discharging is determined.

[0094] In step S740, a mileage-voltage difference trend map is generated based on the voltage difference of the vehicle during charging and its corresponding filled mileage data, or a mileage-voltage difference trend map is generated based on the voltage difference of the vehicle during discharging and its corresponding filled mileage data.

[0095] This method can generate a voltage difference trend chart for the vehicle during charging based on the voltage difference during charging and the corresponding mileage data after charging, or a voltage difference trend chart for the vehicle during discharging based on the voltage difference during discharging and the corresponding mileage data after discharging. The trend charts of dynamic voltage difference and mileage of the battery pack obtained in this way can accurately help relevant personnel understand the performance of the battery under real vehicle conditions, monitor the voltage consistency of the vehicle battery during cycle use, and proactively balance the battery in a timely manner to improve the battery's lifespan.

[0096] In some embodiments, when the vehicle is currently in a charging state, the voltage difference during charging is determined; or when the vehicle is currently in a discharging state, the voltage difference during discharging is determined. For example, during the vehicle charging process, the difference between the battery's maximum and minimum voltages is calculated to obtain the voltage difference at each moment. Then, the maximum voltage difference and the corresponding mileage data are taken during each charging process. This allows for the statistical analysis of the dynamic trend of the voltage difference during charging in different mileage ranges.

[0097] In some embodiments, when the vehicle is currently in a discharging state, the voltage difference during discharge is determined. For example, the voltage difference at each moment is obtained by calculating the difference between the maximum and minimum battery voltage during the vehicle's discharge process. Then, the maximum voltage difference and the corresponding mileage data are taken in each discharge process, which allows for the statistical analysis of the dynamic trend of the voltage difference during discharge in different mileage ranges.

[0098] In some embodiments, the current state of the vehicle, whether it is in a charging or discharging state, is determined based on the vehicle's battery system state, DC charging state, DC charging connection state, AC charging state, and AC charging connection state. For example, consecutive data with the same state constitute one process; when the state changes, the process ends and another process begins, as detailed in Table 11 below:

[0099] Table 11

[0100]

[0101] The value of 'q' in Table 11 above can be set to any value according to the actual business scenario. The configuration values ​​for the vehicle's battery system status, DC charging status, DC charging connection status, AC charging status, and AC charging connection status can be set according to the actual configuration file at the time of vehicle delivery.

[0102] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. The vehicle data processing apparatus described below corresponds to the vehicle data processing method described above. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method of this application.

[0103] Figure 8 This is a block diagram of a vehicle data processing device according to an embodiment of this application.

[0104] like Figure 8 As shown, the vehicle data processing device 800 includes an acquisition module 810, an initial tag value determination module 820, a group tag value determination module 830, a grouping module 840, and a filling module 850.

[0105] Specifically, module 810 is used to acquire historical vehicle data.

[0106] The initial label value determination module 820 is used to traverse vehicle historical data and determine the initial label values ​​of null fields and non-null fields in the vehicle historical data.

[0107] The group label value determination module 830 is used to determine the group label values ​​of the null value fields and the group label values ​​of the non-null value fields in the vehicle history data based on the initial label values ​​of the null value fields and the initial label values ​​of the non-null value fields in the vehicle history data.

[0108] The grouping module 840 is used to group the null and non-null fields in the vehicle history data according to the vehicle identifier, the grouping label value of the null field in the vehicle history data, and the grouping label value of the non-null field in the vehicle history data, to obtain at least one group of fields to be filled in the vehicle history data.

[0109] The fill module 850 is used to fill empty fields in the field group to be filled based on the target value of the non-empty field in the field group to be filled.

[0110] The vehicle data processing device 800 can traverse vehicle historical data, determine the initial label values ​​of null fields and non-null fields in the vehicle historical data, and determine the group label values ​​of null fields and non-null fields in the vehicle historical data based on the initial label values ​​of null fields and non-null fields in the vehicle historical data. Then, based on the vehicle identifier, the group label values ​​of null fields, and the group label values ​​of non-null fields in the vehicle historical data, the null fields and non-null fields in the vehicle historical data are grouped to obtain at least one group of fields to be filled. Based on the target values ​​of the non-null fields in the group of fields to be filled, the null fields in the group of fields to be filled are filled. In this way, fields with missing values ​​can be filled based on the vehicle data itself, so that the filled data is closer to the real data and the efficiency of processing vehicle data can be improved.

[0111] In some embodiments, the vehicle data processing device 800 described above can also be used to: fill the null value field in the field to be filled according to the grouping label value when the target value of the non-null value field in the field to be filled group is less than the grouping label value in the field to be filled group.

[0112] In some embodiments, the group label value determination module 830 is configured to: determine the intermediate label value of the current null value field according to the time order of the fields in the vehicle history data, based on the initial label value of the current null value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current null value field, and the vehicle identifier corresponding to the current null value field; determine the intermediate label value of the current non-null value field according to the time order of the fields in the vehicle history data, based on the initial label value of the current non-null value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current non-null value field, and the vehicle identifier corresponding to the non-null value field; and determine the group label value of the null value field and the group label value of the non-null value field in the vehicle history data based on the intermediate label value of the current null value field and the intermediate label value of the current non-null value field.

[0113] In some embodiments, determining the grouping label value of the null field and the grouping label value of the non-null field in the vehicle history data based on the intermediate label value of the current null field and the intermediate label value of the current non-null field includes: determining whether the intermediate label value of the current null field is the same as the initial label value of the current null field; if they are the same, using the initial label value of the non-null field in the vehicle history data as the grouping label value of the current null field in the vehicle history data; or, if they are not the same, determining the intermediate label value of the current null field as the grouping label value of the current null field in the vehicle history data; and determining the intermediate label value of the current non-null field as the grouping label value of the current non-null field in the vehicle history data.

[0114] In some embodiments, the grouping module 840 is configured to: group null and non-null fields with the same grouping label value corresponding to the same vehicle identifier into a field group to be filled; repeat the above steps to group null and non-null fields in the vehicle history data to obtain at least one field group to be filled in the vehicle history data.

[0115] In some embodiments, the vehicle data processing device 800 described above can also be used to: determine whether all fields in the data to be filled in the vehicle historical data are null fields; if all fields in the data to be filled in the vehicle historical data are null fields, send a prompt message.

[0116] In some embodiments, the vehicle data processing device 800 described above can also be used to: acquire the vehicle's battery system status, DC charging status, DC charging connection status, AC charging status, and AC charging connection status; determine whether the vehicle's current status is a charging state or a discharging state based on the vehicle's battery system status, DC charging status, DC charging connection status, AC charging status, and AC charging connection status; when the vehicle's current status is a charging state, determine the voltage difference of the vehicle during charging, or when the vehicle's current status is a discharging state, determine the voltage difference of the vehicle during discharging; generate a mileage-voltage difference trend map of the vehicle during charging based on the voltage difference of the vehicle during charging and its corresponding filled mileage data, or generate a mileage-voltage difference trend map of the vehicle during discharging based on the voltage difference of the vehicle during discharging and its corresponding filled mileage data.

[0117] Figure 9 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0118] like Figure 9 As shown, the electronic device 900 of this embodiment includes a processor 910, a memory 920, and a computer program 930 stored in the memory 920 and executable on the processor 910. When the processor 910 executes the computer program 930, it implements the steps in the various method embodiments described above. Alternatively, when the processor 910 executes the computer program 930, it implements the functions of each module in the various device embodiments described above.

[0119] Electronic device 900 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 900 may include, but is not limited to, processor 910 and memory 920. Those skilled in the art will understand that... Figure 9 This is merely an example of electronic device 900 and does not constitute a limitation on electronic device 900. It may include more or fewer components than shown, or different components.

[0120] The processor 910 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0121] The memory 920 can be an internal storage unit of the electronic device 900, such as a hard disk or RAM of the electronic device 900. The memory 920 can also be an external storage device of the electronic device 900, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the electronic device 900. The memory 920 can also include both internal and external storage units of the electronic device 900. The memory 920 is used to store computer programs and other programs and data required by the electronic device.

[0122] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0123] If an integrated module is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in a computer-readable medium can be appropriately added to or subtracted according to the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0124] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions 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 this application, and should all be included within the protection scope of this application.

Claims

1. A vehicle data processing method, characterized in that, The method includes: Obtain vehicle historical data; Traverse the vehicle history data to determine the initial label values ​​of null value fields and non-null value fields in the vehicle history data; Based on the initial label values ​​of the null value fields and the initial label values ​​of the non-null value fields in the vehicle history data, determine the group label values ​​of the null value fields and the group label values ​​of the non-null value fields in the vehicle history data. Based on the vehicle identifier in the vehicle history data, the grouping label value of the null value field in the vehicle history data, and the grouping label value of the non-null value field in the vehicle history data, the null value field and the non-null value field in the vehicle history data are grouped to obtain at least one group of fields to be filled in the vehicle history data. Fill the empty value fields in the group of fields to be filled according to the target value of the non-empty value fields in the group of fields to be filled. Based on the initial label values ​​of the null value fields and the initial label values ​​of the non-null value fields in the vehicle history data, determine the group label values ​​of the null value fields and the group label values ​​of the non-null value fields in the vehicle history data, including: Based on the time order of the fields in the vehicle history data, the intermediate label value of the current null value field is determined according to the initial label value of the current null value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current null value field, and the vehicle identifier corresponding to the current null value field. According to the time order of the fields in the vehicle history data, the intermediate label value of the current non-empty value field is determined based on the initial label value of the current non-empty value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current non-empty value field, and the vehicle identifier corresponding to the non-empty value field. Based on the intermediate label value of the current null value field and the intermediate label value of the current non-null value field, determine the group label value of the null value field and the group label value of the non-null value field in the vehicle history data.

2. The method according to claim 1, characterized in that, Based on the intermediate label value of the currently null value field and the intermediate label value of the currently non-null value field, determine the group label value of the null value field and the group label value of the non-null value field in the vehicle history data, including: Determine whether the intermediate label value of the current null value field is the same as the initial label value of the current null value field; If they are the same, the initial label value of the non-null value field in the vehicle history data is used as the group label value of the current null value field in the vehicle history data; or, if they are not the same, the intermediate label value of the current null value field is determined as the group label value of the current null value field in the vehicle history data. The intermediate label value of the current non-empty value field is determined as the group label value of the current non-empty value field in the vehicle history data.

3. The method according to claim 1, characterized in that, Based on the vehicle identifier, the grouping label value of the null value field in the vehicle history data, and the grouping label value of the non-null value field in the vehicle history data, the null value field and the non-null value field in the vehicle history data are grouped to obtain at least one group of fields to be filled in the vehicle history data, including: The null and non-null fields with the same group label value corresponding to the same vehicle identifier are grouped into one field group to be filled. Repeat the above steps to group the null and non-null fields in the vehicle history data to obtain at least one group of fields to be filled in the vehicle history data.

4. The method according to claim 1, characterized in that, The method further includes: When the target value of a non-empty field in the field group to be filled is less than the group label value in the field group to be filled, the empty field in the field group to be filled is filled according to the group label value in the field group to be filled.

5. The method according to claim 1, characterized in that, Before determining the initial label values ​​for null fields and non-null fields in the vehicle history data, the method further includes: Determine whether all fields in the vehicle history data to be filled are empty fields; If all fields in the vehicle history data to be filled are empty, a prompt message will be sent.

6. The method according to any one of claims 1 to 5, characterized in that, If the data to be filled in the vehicle history data is mileage data, the method further includes: Acquire the vehicle's battery system status, DC charging status, DC charging connection status, AC charging status, and AC charging connection status; Based on the vehicle's battery system status, DC charging status, DC charging connection status, AC charging status, and AC charging connection status, determine whether the vehicle's current status is charging or discharging. When the current state of the vehicle is charging, determine the voltage difference of the vehicle during charging; or when the current state of the vehicle is discharging, determine the voltage difference of the vehicle during discharging. Based on the voltage difference of the vehicle during charging and its corresponding filled mileage data, a mileage-voltage difference trend chart of the vehicle during charging is generated; or based on the voltage difference of the vehicle during discharging and its corresponding filled mileage data, a mileage-voltage difference trend chart of the vehicle during discharging is generated.

7. A vehicle data processing device, characterized in that, The device includes: The acquisition module is used to acquire historical vehicle data; The initial label value determination module is used to traverse the vehicle historical data and determine the initial label values ​​of null value fields and non-null value fields in the vehicle historical data. The group label value determination module is used to determine the group label value of the null value field and the group label value of the non-null value field in the vehicle history data based on the initial label value of the null value field and the initial label value of the non-null value field in the vehicle history data. The grouping module is used to group the null and non-null fields in the vehicle history data according to the vehicle identifier, the grouping label value of the null field in the vehicle history data, and the grouping label value of the non-null field in the vehicle history data, to obtain at least one group of fields to be filled in the vehicle history data. The fill module is used to fill the null value fields in the field group to be filled according to the target value of the non-null value fields in the field group to be filled; The grouping label value determination module is specifically used for: determining the intermediate label value of the current null value field according to the time order of the fields in the vehicle history data, based on the initial label value of the current null value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current null value field, and the vehicle identifier corresponding to the current null value field; determining the intermediate label value of the current non-null value field according to the time order of the fields in the vehicle history data, based on the initial label value of the current non-null value field in the vehicle history data, the initial label values ​​of all fields before the time information corresponding to the current non-null value field, and the vehicle identifier corresponding to the non-null value field; and determining the grouping label value of the null value field and the grouping label value of the non-null value field in the vehicle history data based on the intermediate label value of the current null value field and the intermediate label value of the current non-null value field.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

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