A Dynamic Storage Method for Automotive Electric Drive Fault Data

Abstract

The present invention discloses a method for dynamically storing automotive electric drive fault data, comprising the following steps: S0: presetting reference standard values and reasonable ranges of current data of an automotive motor under different working environments; S1: collecting current data of the automotive motor under the current working environment in a plurality of time periods to form a current time period data set; S2: performing overall data definition on the current time period data set to be stored, and defining corresponding storage policies through data attributes of each attribute column in each current time period data set; The present invention realizes the data preprocessing method by comparing current information with standard values, identifies the importance degree of each current information, and defines the storage policy of each current data, which not only realizes the weight calibration work of data anomalies, facilitates the subsequent data observation work of detection personnel, but also enhances the utilization rate of the dynamic storage space of automotive electric drive fault data.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing and relates to a method for dynamically storing automotive electric drive fault data. Background Art

[0002] During the driving process of an automobile, collecting and analyzing the current data of the automotive motor plays an important role in analyzing the operating state of the automotive motor function and predicting the remaining service life. For example, by analyzing the collected data, potential safety hazards or potential faults that may exist during the use of the automobile can be detected in a timely manner. However, as the usage time of the automobile increases, the amount of collected data also increases, which will lead to a huge consumption of memory space for storing the collected data; therefore, the compressed storage of data becomes very important.

[0003] In conventional data collection work, the collected data is uploaded to the storage unit for subsequent detection work, resulting in an excessive workload for data storage and reducing the utilization rate of the dynamic storage space for automotive electric drive fault data; and data screening cannot be performed in conventional data collection work, and the detection personnel also need a large amount of work to screen the data in subsequent work, resulting in a low overall work efficiency and unable to meet the work requirements of high-efficiency data processing. Summary of the Invention

[0004] In order to solve the implementation technical problems, the present invention adopts the following technical solutions:

[0005] A method for dynamically storing automotive electric drive fault data includes the following steps: S0: Preset the reference standard value and reasonable range of the current data of the automotive motor under different working environments;

[0006] S1: Collect the current data of the automotive motor in the current working environment in several time periods to form a current time period data set;

[0007] S2: Perform overall data definition on the current time period data set to be stored, and define the corresponding storage strategy through the data attributes of each column in each current time period data set.

[0008] As a further solution of the present invention: In step S1, the current ripple value of the automotive motor current is adopted in real time, and the pre-peak value and pre-valley value are determined according to the current ripple value;

[0009] Obtain the preset ripple effective range value, and determine the true valley value according to the pre-valley value, the preset ripple effective range value and the current ripple value;

[0010] Determine the true peak value according to the pre-peak value, the preset ripple effective range value and the current ripple value.

[0011] As a further solution of the present invention: in step S2, the true trough value and the true peak value of the automotive motor current obtained are compared with the preset reference standard values in terms of data.

[0012] As a further solution of the present invention: when calibrating and storing the abnormal data set in step S201, a corresponding calibration data partition will be newly created in the data storage area for storing the abnormal data set.

[0013] As a further solution of the present invention: in step S201, when storing the abnormal data set into the calibration data partition, the average value of the difference between the current data in each time period in the collected current time period data set and the reference standard value is marked into the metadata of this current time period data set;

[0014] Then, according to the average value of the difference of the abnormal data set, the attention degree is sorted. The higher the difference, the higher the corresponding attention degree. In the case of the same difference, the sorting is carried out in chronological order.

[0015] As a further solution of the present invention: when calibrating and storing the abnormal data set in step S201, the current data in the abnormal time period in the abnormal data set and the current data in at least two time periods before and after this time period are selected together, and a calibration link is generated. Through the calibration link, the selected current data can be directly selected and observed.

[0016] As a further solution of the present invention: when excerpting the current data, if the current data in the abnormal time period is the first or the last data time period of this current time period data set, then the data time period connected to it in the previous or the next current time period data set is extracted and incorporated into this current time period data set.

[0017] As a further solution of the present invention: in step S202, a corresponding conventional storage area will be newly created in the data storage area, and the ordinary data set after data screening will be stored in the conventional storage area in a lossy compression manner.

[0018] Advantages of the present invention: The present invention realizes the data preprocessing method by comparing the current information with the standard value, identifies the importance degree of each current information, and defines the storage strategy of each current data, which not only realizes the weight calibration work of data anomalies, facilitates the subsequent data observation work of the detection personnel, but also enhances the utilization rate of the dynamic storage space of automotive electric drive fault data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is the flow chart of the present invention.

[0020] Figure 2 is the flow chart of step S2 of the present invention. Detailed implementation manners

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. It should be understood that the present application is not limited by the example embodiments disclosed herein. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0022] The present invention provides for reference Figures 1-2 In an embodiment of the present invention, a method for dynamically storing automotive electric drive fault data includes the following steps:

[0023] S0: According to the standard data obtained by official personnel through detection under different working environments when the vehicle leaves the factory, a reference standard value and a reasonable range of the current data of the automotive motor under different working environments are preset;

[0024] S1: The acquisition sensor is used to perform the acquisition work of the automotive motor. When the automotive motor is working, the acquisition sensor acquires the current data of the automotive motor under the current working environment at several time periods to form a current time period data set;

[0025] S2: After the acquisition work is completed, the acquired information is uploaded to the processing terminal. The processing terminal performs overall data definition on the current time period data set to be stored, and defines the corresponding storage strategy through the data attributes of each attribute column in each current time period data set;

[0026] The specific content of step S2 is: The current data in the current time period data set is compared with the reference standard value preset in step S0;

[0027] If there is a difference in the comparison result and the difference in the value is greater than the reasonable floating range, then step S201 is entered. If the comparison result is a normal value, then step S202 is entered;

[0028] S201: The current time period data set with anomalies is marked as an abnormal data set, and the abnormal data set is stored with a completely complete lossless storage strategy;

[0029] S202: The current time period data without anomalies is classified as a normal data set, and the normal data set is stored with a lossy storage strategy for data screening;

[0030] Enable the inspectors to obtain the current data of the abnormal data set more intuitively and losslessly. For the ordinary data set with relatively low importance, a lossy storage method is adopted, which can effectively reduce the storage pressure of the data.

[0031] In step S1, in order to improve the accuracy of acquisition and comparison, the acquisition sensor will continuously adopt the current ripple value of the automotive motor current, and determine the pre-wave peak value and pre-wave trough value according to the current ripple value.

[0032] Obtain the preset ripple effective range value, and determine the true trough value according to the pre-wave trough value, the preset ripple effective range value, and the current ripple value.

[0033] Determine the true peak value according to the pre-wave peak value, the preset ripple effective range value, and the current ripple value.

[0034] In step S2, the true trough value and true peak value of the automotive motor current obtained are compared with the preset reference standard value.

[0035] Furthermore, when calibrating and storing the abnormal data set in step S201, a corresponding calibration data partition will be newly created in the data storage area for storing the abnormal data set.

[0036] And when calibrating and storing the abnormal data set, if multiple consecutive current period data sets are calibrated as abnormal data sets, first store these current period data sets normally in the calibration data partition; and mark these current period data as abnormal time zone data sets together, and create another abnormal data partition in the data storage area, and store the abnormal time zone data set in the abnormal data partition to achieve the effect of double backup, and at the same time facilitate the inspectors to see the abnormal time zone data set more quickly and intuitively.

[0037] Further, in step S201, when storing the abnormal data set into the calibration data partition, the average value of the difference between the current data in each period in the collected current period data set and the reference standard value is marked into the metadata of the current period data set, which is convenient for the operators to more intuitively see the data information of this information set when observing the data.

[0038] In addition, the processing terminal will also sort according to the average value of the difference of the abnormal data set. The higher the difference, the higher the attention. In the case of the same difference, the sorting will be carried out according to the time sequence.

[0039] Further, in order for the inspector to more intuitively see the abnormal positions of each abnormal data set in the calibrated data partition, when calibrating and storing the abnormal data set in step S201, the current data during the abnormal time period in the abnormal data set and the current data of at least two time periods before and after that time period are selected together, and a calibration link is generated. Through the calibration link, the selected current data can be directly selected and observed.

[0040] Furthermore, when selecting the current data, if the current data during the abnormal time period is the first or last data period of the current time period data set, the data period connected to it in the previous or next current time period data set is extracted and incorporated into the current time period data set;

[0041] Therefore, in step S201, after filtering the ordinary data set, a corresponding temporary storage area is newly created in the data storage area, and the current time period data without abnormalities is temporarily stored in the temporary storage area. After the processing is completed, the corresponding current time period data in the temporary storage area is deleted.

[0042] Further, in step S202, a corresponding regular storage area is newly created in the data storage area, and the ordinary data set after data filtering is stored in the regular storage area in a lossy compression manner.

[0043] Preferably, in step S202, for the ordinary data set stored in the regular storage area, after data filtering, only the current average value, current maximum value, current minimum value, and basic data information (for example: acquisition time, acquisition object, and acquisition environment information, etc.) of this time period are saved to reduce the storage size of the ordinary data set and reduce the data storage pressure.

[0044] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for dynamically storing automobile electric drive fault data, characterized in that: The following steps are involved: S0: preset reference standard values ​​and reasonable ranges of current data of automobile motors under different working conditions; S1: collecting the current data of the automobile motor under the current working environment in several time periods to form a current time period data set; S2: Perform overall data definition on the current period data set to be stored, and define corresponding storage strategies through data attribute columns in each current period data set; The step S2 specifically includes: comparing the current data in the current period data set with the reference standard value preset in step S0; If there is a difference in the comparison result, and the difference is greater than a reasonable floating range, then go to step S201; if the comparison result is normal, then go to step S202; S201: Marking a current period data set with an abnormality as an abnormal data set, and storing the current period data set with a complete storage strategy for the abnormal data set; S202: The current period data without abnormality is classified as a common data set, and a data screening storage strategy is performed on the common data set to store the current period data set; When the abnormal data set is calibrated and stored in step S201, a corresponding calibration data partition is newly created in the data storage area to store the abnormal data set; And when the abnormal data set is calibrated and stored, if there are multiple consecutive current period data sets calibrated as abnormal data sets, these current period data sets are first stored normally in the calibration data partition; And these current time period data are marked together as abnormal time zone data sets, and a new abnormal data partition is created again in the data storage area, and the abnormal time zone data sets are stored in the abnormal data partition; When the abnormal data set is calibrated and stored in step S201, the current data in the abnormal period and the current data in at least two periods before and after the abnormal period are extracted from the abnormal data set, and a calibration link is generated, through which the extracted current data can be directly selected and observed.

2. The method for dynamically storing automobile electric drive fault data according to claim 1, characterized in that: In step S1, the current ripple value of the automobile motor current is used in real time, and the pre-wave peak value and the pre-wave valley value are determined according to the current ripple value; Obtaining a preset ripple effective range value, and determining a real valley value according to the pre-valley value, the preset ripple effective range value, and the current ripple value; The actual peak value is determined according to the pre-peak value, the preset ripple effective range value and the current ripple value.

3. The method for dynamically storing automobile electric drive fault data according to claim 2, characterized in that: In step S2, a data comparison is performed between the acquired real valley value and real peak value of the vehicle motor current and the preset reference standard value.

4. The method for dynamically storing automobile electric drive fault data according to claim 1, characterized in that: In step S201, when storing the abnormal data set in the calibration data partition, the average value of the difference between the current data in each period and the reference standard value collected in the current period data set is marked in the metadata of the current period data set; The attention is then sorted according to the average value of the difference in the abnormal data set. The higher the difference, the higher the attention. If the difference is the same, it is sorted in chronological order.

5. The method for dynamically storing automobile electric drive fault data according to claim 1, characterized in that: When selecting current data, if the current data in the abnormal period is the first or last data period of the current period data set, the data period connected to it in the previous or next current period data set is extracted and incorporated into the current period data set; Therefore, in step S201, after the normal data set is screened, a corresponding temporary storage area is newly created in the data storage area, and the current period data without abnormalities is temporarily stored in the temporary storage area. After the processing is completed, the corresponding current period data in the temporary storage area is deleted.

6. The method for dynamically storing automobile electric drive fault data according to claim 1, characterized in that: In step S202, a corresponding regular storage area is newly created in the data storage area, and the ordinary data set after data screening is stored in the regular storage area in a lossy compression manner.

7. The method for dynamically storing automobile electric drive fault data according to claim 1, characterized in that: In step S202, the common data set stored in the regular storage area, after data screening, only saves the current average value, current maximum value, current minimum value and basic data information of the time period.

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