CN108398641B - Battery data processing method and battery data server - Google Patents
Battery data processing method and battery data server Download PDFInfo
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- CN108398641B CN108398641B CN201711236991.3A CN201711236991A CN108398641B CN 108398641 B CN108398641 B CN 108398641B CN 201711236991 A CN201711236991 A CN 201711236991A CN 108398641 B CN108398641 B CN 108398641B
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Abstract
The embodiment of the invention provides a battery data processing method and a battery data server, wherein the battery data processing method comprises the following steps: extracting a plurality of target battery data with the same data acquisition time point; aggregating the target battery data to obtain a battery data set; and recording the corresponding relation between the battery data set and the same data acquisition time point. According to the embodiment of the invention, the full-table scanning in the battery data table is not required, so that the data statistical efficiency is improved.
Description
Technical Field
The present invention relates to the field of battery data processing technologies, and in particular, to a battery data processing method and a battery data server.
Background
At present, more and more users go out through electric automobile.
The electric vehicle adopts a vehicle Battery as a power supply source, and centrally controls the operation of the vehicle Battery through a BMS (Battery Management System). In order to ensure normal system operation of the BMS, battery data such as current, voltage, SOC (State of Charge), and battery failure signal of the vehicle battery needs to be collected at high frequency, and the battery data is counted by the battery data server, so as to perform processing such as vehicle battery life prediction, vehicle battery echelon utilization, vehicle battery maintenance, and vehicle battery related research and development based on the data statistics result.
In practical application, the acquired battery data can be recorded through a battery data table. The battery data table comprises BMS numbers and data acquisition time. Generally, the battery data table is sorted by the number of the BMS. Therefore, when the battery data of a certain BMS within a certain time range are counted, the initial positions of all the battery data of the certain BMS in the battery data table can be determined only according to the serial numbers, and the battery data between the initial positions are scanned in sequence without full-table scanning, so that the counting efficiency is high.
However, when the battery data of the plurality of BMSs within a certain time range needs to be counted, the positions of the battery data of the plurality of BMSs in the battery data table need to be searched, and the full-table scan process needs to be performed, which results in low statistical efficiency.
Therefore, the battery data processing method in the prior art has the problem of low data statistical efficiency.
Disclosure of Invention
In view of the above, the present invention has been made to provide a battery data processing method and a corresponding battery data server that overcome or at least partially solve the above problems.
According to an aspect of the present invention, there is provided a battery data processing method applied to a battery data server, the battery data server storing a plurality of battery data, each having a data collection time point, the method including:
extracting a plurality of target battery data with the same data acquisition time point;
aggregating the target battery data to obtain a battery data set;
and recording the corresponding relation between the battery data set and the same data acquisition time point.
Optionally, the battery data server is preset with a plurality of battery data timing index tables, and the method further includes:
writing the same data acquisition time point into a target battery data time sequence index table;
and recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point.
Optionally, the battery data timing index table records written data acquisition time points, where the written data acquisition time points have corresponding first timing strings, and before the step of writing the same data acquisition time point into the target battery data timing index table, the method further includes:
generating a second time sequence character string aiming at the same data acquisition time point;
matching the second time sequence character string with a plurality of first time sequence character strings;
if a target first time sequence character string matched with the second time sequence character string exists, determining a target written data acquisition time point corresponding to the target first time sequence character string;
and extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
Optionally, the method further comprises:
and writing the corresponding relation between the battery data set and the same data acquisition time point into the target battery data time sequence index table.
According to another aspect of the present invention, there is provided a battery data processing method applied to a battery data server, where the battery data server is preset with a plurality of battery data sets and data collection time points corresponding to the battery data sets, the method includes:
receiving a battery data statistics request; the battery data statistics request comprises a statistics time range;
acquiring a target battery data set of a data acquisition time point within the statistical time range;
and sending the target battery data set.
According to another aspect of the present invention, there is provided a battery data server storing a plurality of battery data, each having a data collection time point, the battery data server comprising:
the target battery data extraction module is used for extracting a plurality of target battery data with the same data acquisition time point;
the battery data set acquisition module is used for aggregating the target battery data to obtain a battery data set;
and the first corresponding relation recording module is used for recording the corresponding relation between the battery data set and the same data acquisition time point.
Optionally, the battery data server is preset with a plurality of battery data timing index tables, and the battery data server further includes:
the data acquisition time point writing module is used for writing the same data acquisition time point into a target battery data time sequence index table;
and the second corresponding relation recording module is used for recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point.
Optionally, the battery data timing index table records written data acquisition time points, where the written data acquisition time points have corresponding first timing strings, and the battery data server further includes:
the second time sequence character string generating module is used for generating a second time sequence character string aiming at the same data acquisition time point;
the character string matching module is used for matching the second time sequence character string with a plurality of first time sequence character strings;
the time point determining module is used for determining a target written data acquisition time point corresponding to the target first time sequence character string if the target first time sequence character string matched with the second time sequence character string exists;
and the target index table extraction module is used for extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
Optionally, the battery data server further includes:
and the corresponding relation writing module is used for writing the corresponding relation between the battery data set and the same data acquisition time point into the target battery data time sequence index table.
According to another aspect of the present invention, there is provided a battery data server, which is preset with a plurality of battery data sets and data collection time points corresponding thereto, the battery data server comprising:
the request receiving module is used for receiving a battery data statistics request; the battery data statistics request comprises a statistics time range;
the battery data set acquisition module is used for acquiring a target battery data set of a data acquisition time point within the statistical time range;
and the battery data set sending module is used for sending the target battery data set.
According to the embodiment of the invention, a plurality of target battery data with the same data acquisition point are extracted and aggregated into the battery data set, and the corresponding relation between the battery data set and the data acquisition time point is recorded, so that when the battery data in a certain time range are counted, the data acquisition time point included in the time range can be determined, then the target battery data set corresponding to the data acquisition time point is determined, and the target battery data set is returned to a user as a counting result, so that the full-table scanning in the battery data table is not needed, and the data counting efficiency is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart of a battery data processing method according to a first embodiment of the present invention;
FIG. 2 is a flow chart of a battery data processing method according to a second embodiment of the present invention;
fig. 3 is a block diagram of a battery data server according to a third embodiment of the present invention;
fig. 4 is a block diagram of a battery data server according to a fourth embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Example one
Fig. 1 is a flowchart of a battery data processing method according to an embodiment of the present invention, where the method may be applied to a battery data server, where the battery data server stores a plurality of battery data, and each battery data has a data acquisition time point, and the method specifically includes the following steps:
In specific implementation, the BMS on the vehicle can regularly acquire and upload battery data of the battery to the battery data server. The battery data server may write the received battery data into a preset battery data table, so that the battery data server stores a large amount of battery data of the plurality of BMSs at each time.
Table 1 is a schematic diagram of a battery data table according to an embodiment of the present invention. As can be seen from the table, the battery data table includes a table row key RowKey and a battery data set columniamy, the RowKey specifically includes a device imei and a time stamp of the BMS, and the battery data set columniamy specifically includes a voltage volt, a temperature temp, a soc state of charge, and the like. In the first data, BMS 10001 representing device imei uploaded a battery datum at 1503899995 seconds with voltage volt, temperature temp, soc state of charge 3306, 320 and 990, respectively.
It should be noted that, a person skilled in the art may set the specific data type of the battery data set according to actual needs, and the table is only a reference example and is not limited to the specific data type of the battery data.
TABLE 1
For a plurality of battery data, the plurality of battery data having the same timestamp may be extracted as target battery data.
For example, in table 1, two pieces of battery data corresponding to two rowkeys of "10001, 1503899996" and "10003, 1503899996" may be used as the target battery data.
In practical applications, the timestamp may be converted into a time period. Assuming that a battery data set within 15 minutes currently needs to be aggregated, a value of each timestamp divided by 900 seconds can be calculated. For example, 1503899995/900-1670999, 1503899996/900-1670999, 1503900000/900-1671000, and 1503900001/900-1671000.
Therefore, the plurality of timestamps are converted into the data acquisition time points corresponding to the plurality of 15 minutes, and the battery data at the same data acquisition time point is extracted, so that the plurality of battery data within the same 15 minutes can be extracted.
For example, "10001, 1503899995 (1670999)", "10001, 1503899996 (1670999)", "10002, 1503899995 (1670999)" and "10003, 1503899996 (1670999)" may be set as the target battery data with respect to table 1 described above.
And step 102, aggregating the target battery data to obtain a battery data set.
In a specific implementation, a plurality of target battery data with the same data acquisition time point may be aggregated into one battery data set. When there are a plurality of different data acquisition time points, a plurality of battery data sets are formed accordingly.
And if the time stamp is converted into a data acquisition time point corresponding to a certain time period, acquiring battery data sets according to the same data acquisition time point, wherein each battery data set comprises a plurality of pieces of battery data in a certain time period. For example, "10001, 1503899995 (1670999)", "10001, 1503899996 (1670999)", "10002, 1503899995 (1670999)", and "10003, 1503899996 (1670999)" are the battery data sets, and include a plurality of pieces of battery data collected within 15 minutes.
And 103, recording the corresponding relation between the battery data set and the same data acquisition time point.
In the concrete implementation, the battery data server can record the corresponding relation between each battery data set and the data acquisition time point, so that when a user counts the battery data in a certain time range, the data acquisition time point included in the time range can be firstly determined, then the target battery data set corresponding to the data acquisition time point is determined, and the target battery data set is returned to the user as a statistical result, so that full-table scanning in the battery data table is not needed, and the data statistical efficiency is improved.
According to the embodiment of the invention, a plurality of target battery data with the same data acquisition point are extracted and aggregated into the battery data set, and the corresponding relation between the battery data set and the data acquisition time point is recorded, so that when the battery data in a certain time range are counted, the data acquisition time point included in the time range can be determined, then the target battery data set corresponding to the data acquisition time point is determined, and the target battery data set is returned to a user as a counting result, so that the full-table scanning in the battery data table is not needed, and the data counting efficiency is improved.
Optionally, the battery data server is preset with a plurality of battery data timing index tables, and the method may further include:
writing the same data acquisition time point into a target battery data time sequence index table;
and recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point.
In practical application, a battery data time sequence index table can be established, and the data statistical efficiency is improved by establishing a secondary index mode.
In specific implementation, data acquisition time points corresponding to a plurality of battery data sets can be written into a certain battery data time sequence index table one by one according to the time sequence relation of the data acquisition time points. Therefore, at least one data acquisition time point can be contained in one battery data time sequence index table.
After the data acquisition time points are written into the battery data time sequence index table, the corresponding relation between the data acquisition time points and the battery data time sequence index table can be recorded, so that when the battery data are counted, the target battery data time sequence index table can be determined according to the time, and the battery data time sequence index tables do not need to be scanned one by one.
Optionally, the method may further include:
and writing the corresponding relation between the battery data set and the same data acquisition time point into the target battery data time sequence index table.
In specific implementation, the corresponding relationship between the battery data set and the data acquisition time point may be written into the battery data timing index table. More specifically, the RowKey of the battery data in the battery data table may be added in the battery data timing index table corresponding to the data collection time point. Therefore, when the battery data are counted, a plurality of RowKey of a plurality of pieces of battery data corresponding to the same data acquisition time point in the battery data table can be determined in the battery data timing index table, wherein the plurality of pieces of battery data all belong to a set of battery data corresponding to the same data acquisition time point. Then, corresponding battery data can be extracted from the battery data table directly according to the RowKey without performing full-table scanning on the battery data table, so that the statistical efficiency of the battery data is improved.
Based on table 1, table 2 is one of the schematic diagrams of a battery data timing index table according to the embodiment of the present invention. As can be seen from the table, the battery data timing index table includes the time obtained by converting the time, the device imei of the BMS, and the rowkey value for retrieving the battery data in the battery data table, and the plurality of battery data sets are sorted according to the timing of the data acquisition time point time. When counting battery data in a certain time range, firstly determining a target data acquisition time point time belonging to the time range, determining a corresponding target battery data time sequence index table according to the target data acquisition time point time, searching a rowkey value corresponding to the target data acquisition time point in the target battery data time sequence index table, and searching corresponding battery data in the battery data table according to the searched rowkey value.
TABLE 2
Optionally, the battery data timing index table records written data acquisition time points, where the written data acquisition time points have corresponding first timing strings, and before the step of writing the same data acquisition time point into the target battery data timing index table, the method further includes:
generating a second time sequence character string aiming at the same data acquisition time point;
matching the second time sequence character string with a plurality of first time sequence character strings;
if a target first time sequence character string matched with the second time sequence character string exists, determining a target written data acquisition time point corresponding to the target first time sequence character string;
and extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
It should be noted that, the capacity of a single battery data time sequence index table is limited, and when the number of data acquisition time points written in the single battery data time sequence index table exceeds a certain threshold, the single battery data time sequence index table is automatically split into two battery data time sequence index tables, and each battery data time sequence index table records a part of data acquisition time points.
For example, referring to table 2 above, the data collection time points in the battery data time sequence index table are 6, and exceed 3 preset thresholds, and the data collection time points are divided into a battery data time sequence index table region1 and a battery data time sequence index table region2, where the battery data time sequence index table region1 includes the first three pieces of data, and the battery data time sequence index table region2 includes the last three pieces of data.
In addition, in the writing rule of the battery data time sequence index table, new data acquisition time points are written into a certain battery data time sequence index table according to the dictionary sequence. For example, there are currently two battery data timing index tables, region1 and region2, where the last data collection time point written by one index table region1 is 1670999, and the last data collection time point written by the other index table region2 is 1671001, and for the new data collection time point 1671002, in lexicographic order, it is written to index table region2 and sorted after 1671001.
However, the data collection time point is incremented according to time, so that the new data collection time point is written into the same battery data time sequence index table all the time, and after the battery data time sequence index table is split into two battery data time sequence index tables, namely, region1 and region2, the new data collection time point is still written into the same split battery data time sequence index table, namely, region2, but not into region 1. Thus, region1 is caused to write only half the capacity of data, resulting in a half-full problem, wasting data storage space.
In a specific implementation of the embodiment of the present invention, a corresponding time sequence character string may be randomly generated for a written data acquisition time point in the battery data time sequence index table.
For the sake of explanation, the time series string written at the data acquisition time point is named as a first time series string.
In practical application, a genRandomKey function can be preset, and the function converts a data acquisition time point into a random time sequence character string. For example, 1670999 and 1671000 are input to the genRandomKey function, resulting in conversion result first time series 0x5C92FAE2 and 0x5C5D3DA2, respectively. It follows that unlike the data acquisition time points, the time series string does not increment as time increases.
In practical applications, the first time sequence string may replace the data acquisition time point. Table 3 is a second schematic diagram of a battery data timing index table according to an embodiment of the invention. As can be seen from the table, the partial records a random time-series string for time conversion, and the time-series string 0x5C5D3DA2 corresponding to 1671000 is sorted before the time-series string 0x5C92FAE2 corresponding to 1670999 in the dictionary order, so that the pieces of data are not sorted in time-series relation.
| partition | imei | time | rowkey value |
| 0x5C5D3DA2 | 10002 | 1503900000 | 10002 1503900000 |
| 0x5C5D3DA2 | 10002 | 1503900001 | 10002 1503900001 |
| 0x5C92FAE2 | 10001 | 1503899995 | 10001 1503899995 |
| 0x5C92FAE2 | 10001 | 1503899996 | 10001 1503899996 |
| 0x5C92FAE2 | 10002 | 1503899995 | 10002 1503899995 |
| 0x5C92FAE2 | 10003 | 1503899996 | 10003 1503899996 |
TABLE 3
When a new data acquisition time point needs to be written into the battery data time sequence index table, a random time sequence character string can be obtained from the new data acquisition time point through a genRandomKey function.
For the purpose of explanation, the time sequence character string corresponding to the new data acquisition time point is named as a second time sequence character string.
The second timing string may be matched to a plurality of first timing strings of respective battery data timing index tables. The matching method may be to determine whether the two character strings conform to the dictionary order. And when the target first time sequence character string and the battery data time sequence index table to which the target first time sequence character string belongs are determined to be matched when the target first time sequence character string and the battery data time sequence index table accord with the dictionary sequence, and the target first time sequence character string and the battery data time sequence index table to which the target first time sequence character string belongs are used as the target battery data time sequence index table so as to write the data acquisition time point into the target battery data time sequence index table.
According to the embodiment of the invention, the data acquisition time point is converted into the random time sequence character string, so that the half-full problem caused by writing data into the same battery data time sequence index table all the time is avoided, and the utilization rate of the data storage space is improved.
Example two
Fig. 2 is a flowchart of a battery data processing method according to a second embodiment of the present invention, where the method may be applied to a battery data server, where the battery data server is preset with a plurality of battery data sets and data acquisition time points corresponding to the battery data sets, and the method specifically includes the following steps:
First, it should be noted that the battery data server may preset a battery data table, and a large amount of battery data and its corresponding RowKey are recorded in the battery data table. Since the examples of the battery data table have been described in detail in the above embodiments, they are not described in detail herein.
It should be added that the battery data server may be preset with a plurality of battery data time sequence index tables, each battery data time sequence index table records at least one data acquisition time point, and each data acquisition time point also has a corresponding relationship with at least one battery data time sequence index table. In addition, the corresponding relation between the data acquisition time point and the battery data set is recorded in the battery data time sequence index table. More specifically, it can be seen from the above example of table 2 that, in the battery data timing index table, the RowKey of the battery data in the battery data table is recorded corresponding to the data collection time point. Therefore, the battery data server presets the corresponding relation between a plurality of battery data sets and a plurality of data acquisition time points. Since the example of the battery data timing index table has been described in detail in the above embodiments, it is not described herein again.
In specific implementation, a plurality of statistical time points can be extracted from a statistical time range, the statistical time points are matched with a plurality of data acquisition time points, and if a plurality of target data acquisition time points matched with the statistical time points exist, a plurality of target battery data time sequence index tables corresponding to the target data acquisition time points are determined. And finally, reading RowKey corresponding to the target data acquisition time point in a plurality of target battery data time sequence index tables, and inquiring corresponding battery data in a battery data table according to the RowKey to be used as a target battery data set.
In the above embodiment, it has been described that in the battery data timing index table, the timestamp is first converted into a time period, and then a timing string is randomly generated for the time period, and data is sorted according to the timing string. Thus, in the battery data time-series index table, the pieces of data are not arranged in time-series order, and therefore, the start time and the end time stopTime can be determined for the statistical time range. Assuming that the battery data time series index table is obtained by using 15 minutes as one time period, with respect to the statistical time range [1503899995, 1503899998], startTime is 1503899995/900 1670999, and stopTime is 1503899998/900 is 1670999. It can be seen that only one battery data in 15 minutes needs to be counted. Then, according to a preset genRandomKey function, a time sequence character string corresponding to 1670999 is obtained as 0x5C92FAE2, and a battery data time sequence index table recorded with 0x5C92FAE2 is searched and used as a target battery data time sequence index table. And searching for RowKey corresponding to 0x5C92FAE2 in the target battery data time sequence index table, and inquiring corresponding battery data in the battery data table according to the RowKey to serve as a target battery data set.
For example, for the example of table 3 above, four data sets of RowKey value [10001,1503899995], [10002,1503899995], [10002,1503899996] and [10003,1503899996] may be found, with data collection time points within the statistical time range [1503899995, 1503899998 ]. Then, according to the RowKey, the corresponding battery data can be searched in the battery data table of table 1 as the target battery data set.
The resulting target battery data set may be returned as a statistical result.
According to the embodiment of the invention, the data acquisition time point contained in a certain time range is determined when the battery data in the time range are counted, then the target battery data set corresponding to the data acquisition time point is determined, and the target battery data set is returned to the user as the counting result, so that the whole table scanning in the battery data table is not needed, and the data counting efficiency is improved.
For simplicity of explanation, the method embodiments are described as a series of acts or combinations, but those skilled in the art will appreciate that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently with other steps in accordance with the embodiments of the invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
EXAMPLE III
Fig. 3 is a block diagram of a battery data server according to a third embodiment of the present invention, where the battery data server 300 stores a plurality of battery data, each of the battery data has a data acquisition time point, and the battery data server 300 may specifically include the following modules:
a target battery data extraction module 301, configured to extract multiple target battery data with the same data acquisition time point;
a battery data set obtaining module 302, configured to aggregate the multiple target battery data to obtain a battery data set;
a first correspondence recording module 303, configured to record a correspondence between the battery data set and the same data acquisition time point.
Optionally, the battery data server 300 is preset with a plurality of battery data timing index tables, and the battery data server 300 further includes:
the data acquisition time point writing module is used for writing the same data acquisition time point into a target battery data time sequence index table;
and the second corresponding relation recording module is used for recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point.
Optionally, the battery data timing index table records written data acquisition time points, where the written data acquisition time points have corresponding first timing strings, and the battery data server 300 further includes:
the second time sequence character string generating module is used for generating a second time sequence character string aiming at the same data acquisition time point;
the character string matching module is used for matching the second time sequence character string with a plurality of first time sequence character strings;
the time point determining module is used for determining a target written data acquisition time point corresponding to the target first time sequence character string if the target first time sequence character string matched with the second time sequence character string exists;
and the target index table extraction module is used for extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
Optionally, the battery data server 300 further includes:
and the corresponding relation writing module is used for writing the corresponding relation between the battery data set and the same data acquisition time point into the target battery data time sequence index table.
According to the embodiment of the invention, a plurality of target battery data with the same data acquisition point are extracted and aggregated into the battery data set, and the corresponding relation between the battery data set and the data acquisition time point is recorded, so that when the battery data in a certain time range are counted, the data acquisition time point included in the time range can be determined, then the target battery data set corresponding to the data acquisition time point is determined, and the target battery data set is returned to a user as a counting result, so that the full-table scanning in the battery data table is not needed, and the data counting efficiency is improved.
According to the embodiment of the invention, the data acquisition time point is converted into the random time sequence character string, so that the half-full problem caused by writing data into the same battery data time sequence index table all the time is avoided, and the utilization rate of the data storage space is improved.
Example four
Fig. 4 is a block diagram of a battery data server according to a fourth embodiment of the present invention, where a plurality of battery data sets and data collection time points corresponding to the battery data sets are preset in the battery data server, and the battery data server 400 may specifically include the following modules:
a request receiving module 401, configured to receive a battery data statistics request; the battery data statistics request comprises a statistics time range;
a battery data set obtaining module 402, configured to obtain a target battery data set of a data acquisition time point within the statistical time range;
a battery data set sending module 403, configured to send the target battery data set.
According to the embodiment of the invention, the data acquisition time point contained in a certain time range is determined when the battery data in the time range are counted, then the target battery data set corresponding to the data acquisition time point is determined, and the target battery data set is returned to the user as the counting result, so that the whole table scanning in the battery data table is not needed, and the data counting efficiency is improved.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in a battery data server according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Claims (6)
1. A battery data processing method is applied to a battery data server, and is characterized in that the battery data server stores a plurality of battery data, each battery data has a data acquisition time point, and the method comprises the following steps:
extracting a plurality of target battery data with the same data acquisition time point;
aggregating the target battery data to obtain a battery data set;
recording the corresponding relation between the battery data set and the same data acquisition time point;
the battery data server is preset with a plurality of battery data time sequence index tables, and the method further comprises the following steps:
writing the same data acquisition time point into a target battery data time sequence index table;
recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point;
the method comprises the following steps of writing a battery data time sequence index table, wherein the battery data time sequence index table records written data acquisition time points, the written data acquisition time points have corresponding first time sequence character strings, and before the step of writing the same data acquisition time point into a target battery data time sequence index table, the method further comprises the following steps:
generating a second time sequence character string aiming at the same data acquisition time point;
matching the second time sequence character string with a plurality of first time sequence character strings; the matching method comprises the following steps: judging whether the two character strings accord with the dictionary sequence or not;
if a target first time sequence character string matched with the second time sequence character string exists, determining a target written data acquisition time point corresponding to the target first time sequence character string;
and extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
2. The method of claim 1, further comprising:
and writing the corresponding relation between the battery data set and the same data acquisition time point into the target battery data time sequence index table.
3. A battery data processing method is applied to a battery data server, and is characterized in that a plurality of battery data sets and corresponding data acquisition time points are preset in the battery data server, and the method comprises the following steps:
receiving a battery data statistics request; the battery data statistics request comprises a statistics time range;
acquiring a target battery data set of a data acquisition time point within the statistical time range;
sending the target battery data set;
the battery data server is preset with a plurality of battery data time sequence index tables, and the method further comprises the following steps:
writing the same data acquisition time point into a target battery data time sequence index table;
recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point;
the method comprises the following steps of writing a battery data time sequence index table, wherein the battery data time sequence index table records written data acquisition time points, the written data acquisition time points have corresponding first time sequence character strings, and before the step of writing the same data acquisition time point into a target battery data time sequence index table, the method further comprises the following steps:
generating a second time sequence character string aiming at the same data acquisition time point;
matching the second time sequence character string with a plurality of first time sequence character strings; the matching method comprises the following steps: judging whether the two character strings accord with the dictionary sequence or not;
if a target first time sequence character string matched with the second time sequence character string exists, determining a target written data acquisition time point corresponding to the target first time sequence character string;
and extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
4. A battery data server, wherein the battery data server stores a plurality of battery data, each battery data having a data collection time point, the battery data server comprising:
the target battery data extraction module is used for extracting a plurality of target battery data with the same data acquisition time point;
the battery data set acquisition module is used for aggregating the target battery data to obtain a battery data set;
the first corresponding relation recording module is used for recording the corresponding relation between the battery data set and the same data acquisition time point;
wherein, a plurality of battery data time sequence index tables are preset in the battery data server, and the battery data server further comprises:
the data acquisition time point writing module is used for writing the same data acquisition time point into a target battery data time sequence index table;
the second corresponding relation recording module is used for recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point;
wherein, the battery data time sequence index table records written data acquisition time points, the written data acquisition time points have corresponding first time sequence character strings, and the battery data server further comprises:
the second time sequence character string generating module is used for generating a second time sequence character string aiming at the same data acquisition time point;
the character string matching module is used for matching the second time sequence character string with a plurality of first time sequence character strings; the matching method comprises the following steps: judging whether the two character strings accord with the dictionary sequence or not;
the time point determining module is used for determining a target written data acquisition time point corresponding to the target first time sequence character string if the target first time sequence character string matched with the second time sequence character string exists;
and the target index table extraction module is used for extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
5. The battery data server of claim 4, wherein the battery data server further comprises:
and the corresponding relation writing module is used for writing the corresponding relation between the battery data set and the same data acquisition time point into the target battery data time sequence index table.
6. A battery data server, characterized in that, a plurality of battery data sets and the data acquisition time point that corresponds to it have been preset to the battery data server, the battery data server includes:
the request receiving module is used for receiving a battery data statistics request; the battery data statistics request comprises a statistics time range;
the battery data set acquisition module is used for acquiring a target battery data set of a data acquisition time point within the statistical time range;
a battery data set sending module, configured to send the target battery data set;
wherein, a plurality of battery data time sequence index tables are preset in the battery data server, and the battery data server further comprises:
the data acquisition time point writing module is used for writing the same data acquisition time point into a target battery data time sequence index table;
the second corresponding relation recording module is used for recording the corresponding relation between the target battery data time sequence index table and the same data acquisition time point;
wherein, the battery data time sequence index table records written data acquisition time points, the written data acquisition time points have corresponding first time sequence character strings, and the battery data server further comprises:
the second time sequence character string generating module is used for generating a second time sequence character string aiming at the same data acquisition time point;
the character string matching module is used for matching the second time sequence character string with a plurality of first time sequence character strings; the matching method comprises the following steps: judging whether the two character strings accord with the dictionary sequence or not;
the time point determining module is used for determining a target written data acquisition time point corresponding to the target first time sequence character string if the target first time sequence character string matched with the second time sequence character string exists;
and the target index table extraction module is used for extracting a target battery data time sequence index table to which the target written data acquisition time point belongs.
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