Battery data collection server and operation method thereof

Abstract

A battery data collection server according to one embodiment disclosed in the present document comprises: a communication unit for receiving first data related to a battery of a vehicle from at least one of a data collection device or a data storage of the vehicle; a first storage unit for classifying and storing the first data into 2_1th data and 2_2th data on the basis of a reception path of the first data; a preprocessing unit which generates third data by converting the formats of the 2_1th data and the 2_2th data, generates a plurality of first databases by classifying the third data according to the type of vehicle, and generates a second database by extracting preset data from the plurality of first databases; and a second storage unit for storing the plurality of first databases and the second database.

Description

Battery data collection server and its operation method

[0001] Cross-citation with related applications

[0002] This invention claims the benefit of priority to Korean Patent Application No. 10-2023-0146623, filed October 30, 2023, the entire contents of which are incorporated herein by reference.

[0003] Technology field

[0004] Embodiments disclosed in this document relate to a battery data collection server and an operating method thereof.

[0005] Recently, active research and development is being conducted on secondary batteries. Here, the term "secondary battery" refers to a rechargeable battery, encompassing both conventional Ni / Cd and Ni / MH batteries, as well as recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of a much higher energy density than conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a compact and lightweight form, making them suitable for use as power sources for mobile devices. Furthermore, lithium-ion batteries are attracting attention as a next-generation energy storage medium, as their use is expanding to include power sources for electric vehicles.

[0006] Additionally, secondary batteries can be utilized as battery packs, which typically include battery modules in which multiple battery cells are connected in series and / or parallel. Furthermore, secondary batteries can be utilized as battery racks, which include multiple battery modules and a rack frame that accommodates these battery modules.

[0007] Meanwhile, to inspect the condition of the secondary batteries contained in EVs, data collection devices within the vehicle collected and analyzed data from the batteries. However, when data collection devices analyzed battery data, the amount of data collected was limited and the collected data was not systematically managed, limiting the efficiency of data analysis.

[0008] One purpose of the embodiments disclosed in this document is to provide a battery data collection server capable of analyzing battery data of multiple vehicles and an operating method thereof.

[0009] One purpose of the embodiments disclosed in this document is to provide a battery data collection server and an operating method thereof that improve the efficiency of battery data analysis by unifying the format of battery data acquired from different data sources.

[0010] One purpose of the embodiments disclosed in this document is to provide a battery data collection server and an operating method thereof that separately generate a database regarding batteries of a specific vehicle type and a database regarding all vehicle types, thereby improving the efficiency of data analysis regarding a specific vehicle type and data analysis regarding all vehicle types.

[0011] The technical problems of the embodiments described in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art to which the present invention pertains from the description below.

[0012] A battery data collection server according to an embodiment disclosed in this document includes a communication unit that receives first data related to a battery of a vehicle from at least one of a data collection device or a data storage of the vehicle, a first storage unit that classifies and stores the first data into 2_1 data and 2_2 data based on a reception path of the first data, a preprocessing unit that converts the formats of the 2_1 data and the 2_2 data to generate third data, classifies the third data according to the type of the vehicle, thereby generating a plurality of first databases, and extracts preset data from the plurality of first databases to generate a second database, and a second storage unit that stores the plurality of first databases and the second database.

[0013] According to one embodiment, the battery data collection server may further include an analysis unit that performs analysis of battery data based on the second database.

[0014] According to one embodiment, the analysis unit extracts a target database corresponding to a target vehicle type from among the plurality of first databases, and the target vehicle type may be included based on the target database.

[0015] According to one embodiment, the preprocessing unit can unify the formats of the 2_1 data and the 2_2 data by converting the formats of the 2_1 data and the 2_2 data using different methods, respectively.

[0016] According to one embodiment, the preprocessing unit can generate the third data by correcting data omissions and errors in the 2_1 data and the 2_2 data.

[0017] According to one embodiment, the preprocessing unit can correct for omission of the 2_1 data by adding at least a portion of the daily data received at a second point in time, which is a point in time subsequent to the first point in time, to the real-time data stored at a first point in time among the 2_1 data.

[0018] According to one embodiment, the preprocessing unit can correct errors in the 2_1 data by modifying at least some of the real-time data stored at a first point in time among the 2_1 data with at least some of the daily data stored at a second point in time that is a point in time subsequent to the first point in time.

[0019] According to one embodiment, the second storage unit may store the storage time points of each of the plurality of first databases and the second databases, and extract data for which a preset period of time has elapsed from the storage time points of each of the plurality of first databases and the second databases to create a third database, which is a long-term storage database.

[0020] According to one embodiment, the second storage unit can transfer the third database to the third storage unit, and delete the third database and the first database and the second database corresponding to the third database.

[0021] According to one embodiment, the battery data collection server may further include a scheduler that controls the operating cycle of the first storage unit and the preprocessing unit.

[0022] A battery data analysis method according to an embodiment disclosed in the present document includes an operation of receiving first data related to a battery of a vehicle from at least one of a data collection device or a data storage of the vehicle, an operation of classifying and storing the first data into 2_1 data and 2_2 data based on a reception path of the first data, an operation of converting the formats of the 2_1 data and the 2_2 data to generate third data, an operation of classifying the third data according to the type of the vehicle to generate a plurality of first databases, an operation of extracting preset data from the plurality of first databases to generate a second database, and an operation of storing the plurality of first databases and the second database.

[0023] According to one embodiment, the battery data collection method may further include an operation of performing analysis of battery data based on the second database.

[0024] According to one embodiment, the operation of performing analysis of the battery data may include an operation of extracting a target database corresponding to a target vehicle model from among the plurality of first databases, and performing data analysis of a battery included in the target vehicle model based on the target database.

[0025] According to one embodiment, the operation of generating the third data may unify the formats of the 2_1 data and the 2_2 data by converting the formats of the 2_1 data and the 2_2 data using different methods, respectively.

[0026] According to one embodiment, the operation of generating the third data may include an operation of correcting data omissions and errors in the 2_1 data and the 2_2 data.

[0027] According to one embodiment, the operation of generating the third data may include an operation of correcting an omission of the 2_1 data by adding at least a portion of daily data received at a second point in time, which is a point in time subsequent to the first point in time, to real-time data stored at a first point in time among the 2_1 data, and an operation of correcting an error of the 2_1 data by modifying at least a portion of real-time data stored at a first point in time among the 2_1 data to at least a portion of daily data stored at a second point in time, which is a point in time subsequent to the first point in time.

[0028] According to one embodiment, the method may further include storing the storage time of each of the plurality of first databases and the second database, and extracting data for which a preset period of time has elapsed from the storage time of each of the plurality of first databases and the second database, thereby creating a third database as a long-term storage database.

[0029] According to one embodiment, the operation of creating the third database may include an operation of transferring the third database to a third storage unit and deleting the third database and the first database and the second database corresponding to the third database.

[0030] Specific details of other embodiments are included in the detailed description and drawings.

[0031] The battery data collection server and its operation method according to the embodiments disclosed in this document can analyze battery data of multiple vehicles.

[0032] The battery data collection server and its operation method according to the embodiments disclosed in this document can improve the efficiency of battery data analysis by unifying the format of battery data acquired from different data sources.

[0033] The battery data collection server and its operation method according to the embodiments disclosed in this document can separately create a database regarding batteries of a specific vehicle type and a database regarding all vehicle types, thereby improving the efficiency of data analysis regarding a specific vehicle type and data analysis regarding all vehicle types.

[0034] The effects of the battery data collection server and its operating method according to the disclosure of this document are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art according to the disclosure of this document.

[0035] FIG. 1 is a block diagram showing a battery data analysis system according to one embodiment disclosed in this document.

[0036] FIG. 2 is a diagram showing an operation of a server classifying and storing battery data according to an embodiment disclosed in this document.

[0037] FIG. 3 is a diagram showing an operation of a server generating third data according to an embodiment disclosed in this document.

[0038] FIG. 4 is a diagram showing an operation of a server according to an embodiment disclosed in this document to create a first database and a second database.

[0039] FIG. 5 is a flowchart showing a battery data analysis method according to an embodiment disclosed in this document.

[0040] In connection with the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0041] Hereinafter, embodiments of the present invention will be described with reference to the attached drawings. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that the present invention encompasses various modifications, equivalents, and / or alternatives of the embodiments.

[0042] The embodiments and terminology used in this document are not intended to limit the technical features described in this document to a specific embodiment, but should be understood to encompass various modifications, equivalents, or alternatives of the embodiment. In connection with the description of the drawings, similar reference numerals may be used to refer to similar or related components. The singular form of a noun corresponding to an item may include one or more of the item, unless the relevant context clearly indicates otherwise.

[0043] In this document, the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can each include any one of the items listed together in that phrase, or all possible combinations thereof. Terms such as "first", "second", "first", "second", "A", "B", "(a)", or "(b)" may be used merely to distinguish the corresponding component from other corresponding components, and do not limit the corresponding components in any other respect (e.g., importance or order) unless specifically stated otherwise.

[0044] In this document, when a component (e.g., a first component) is referred to as being “connected,” “coupled,” or “connected,” with or without the terms “functionally” or “communicatively,” or “coupled” or “connected,” it means that the component can be connected to the other component directly (e.g., wired or wirelessly), or indirectly (e.g., via a third component).

[0045] The methods according to various embodiments disclosed in this document may be provided as included in a computer program product. The computer program product may be traded as a commodity between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory, CD-ROM), or may be distributed online (e.g., downloaded or uploaded) through an application store or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0046] According to the embodiments disclosed in this document, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to the embodiments disclosed in this document, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to the embodiments disclosed in this document, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0047] FIG. 1 is a block diagram showing a battery data analysis system according to one embodiment disclosed in this document.

[0048] Referring to FIG. 1, a battery data collection system (10) may include a target vehicle (100), a data storage (200), and a server (300). The battery data collection system (10) may analyze battery data of the target vehicle (100) in the server (300).

[0049] The target vehicle (100) may be an electric vehicle. The target vehicle (100) may be an electric vehicle including a battery (120). That is, the target vehicle (100) may be an electric vehicle (EV), a hybrid EV (HEV), a plug-in HEV (PHEV), or a fuel cell EV (FCEV) including a battery (120).

[0050] The target vehicle (100) may include an information acquisition device (110). Here, the information acquisition device (110) may be an onboard diagnostic device. That is, the information acquisition device (110) may acquire data of the target vehicle (100) and data related to the battery (120) included in the target vehicle (100).

[0051] The information acquisition device (110) can generate battery data. According to an embodiment, the information acquisition device (110) can generate battery data based on the SOC (State Of Charge), SOH (State Of Health), OCV (Open Circuit Voltage), charge capacity, or discharge capacity of the battery (120) obtained from the battery (120).

[0052] According to an embodiment, the information acquisition device (110) can generate battery data at regular intervals. The information acquisition device (110) can generate battery data at regular intervals set in advance while the target device is in operation, or can generate battery data by synthesizing battery (120) information for a day at a daily cycle.

[0053] The information acquisition device (110) can transmit battery data. According to an embodiment, the information acquisition device (110) can transmit the battery data to at least one of the data storage (200) and the server (300). For example, the information acquisition device (110) can transmit the battery data to the data storage (200), to the server (300), or to both the data storage (200) and the server (300). According to an embodiment, the information acquisition device (110) can transmit the battery data to at least one of the data storage (200) and the server (300) via LTE communication.

[0054] The data storage (200) can store battery data. The data storage (200) can classify and store battery data received from the target vehicle (100).

[0055] The data storage (200) can transmit battery data to the server (300). According to an embodiment, the data storage (200) can store battery data received from multiple vehicles and transmit the battery data to the server (300) in response to a request from the server (300).

[0056] The server (300) may include a communication unit (310), a first storage unit (320), a preprocessing unit (330), a second storage unit (340), an analysis unit (350), a scheduler (360), and a third storage unit (370). The server (300) may use each configuration to receive battery data from the information acquisition device (110) and classify, store, and analyze the same.

[0057] The communication unit (310) can receive first data from a plurality of vehicles. According to an embodiment, the communication unit (310) can receive first data from a plurality of vehicles including the target vehicle (100). For example, the communication unit (310) can receive first data from each of the plurality of vehicles by communicating with an information acquisition device (110) included in each of the plurality of vehicles. Here, the first data may be battery data related to the battery (120) of the target vehicle (100).

[0058] The communication unit (310) can receive first data from the data storage (200). According to an embodiment, the communication unit (310) can receive first data from one or more data storages (200).

[0059] The first storage unit (320) can classify the first data. According to an embodiment, the first storage unit (320) can classify the first data into 2_1 data and 2_2 data based on the reception path of the first data. For example, the first storage unit (320) can distinguish between the first data received from the information acquisition device (110) of the target vehicle (100) and the first data received from the data storage unit (200) among the first data. Accordingly, the first storage unit (320) can define the first data received from the information acquisition device (110) of the target vehicle (100) as 2_1 data and define the data received from the data storage unit (200) as 2_2 data. Through this, the first storage unit (320) can classify the 2_1 data received from the information acquisition device (110) and the 2_2 data received from the data storage unit (200).

[0060] The first storage unit (320) can store the first data. The first storage unit (320) can separately store the second_1 data and the second_2 data included in the first data.

[0061] The preprocessing unit (330) can convert the format of data. According to an embodiment, the preprocessing unit (330) can convert the formats of the 2_1 data and the 2_2 data. For example, the preprocessing unit (330) can convert the format of the 2_1 data set based on CAN communication into a separate format that can be confirmed by the user.

[0062] The preprocessing unit (330) can generate third data. The preprocessing unit (330) can generate third data by converting the formats of the 2_1 data and the 2_2 data, thereby unifying the formats of the 2_1 data and the 2_2 data. That is, the third data may be data whose format is unified through format conversion of the 2_1 data and the 2_2 data. According to an embodiment, since the 2_1 data and the 2_2 data have different formats, the preprocessing unit (330) can change the formats of the 2_1 data and the 2_2 data using different methods. That is, the preprocessing unit (330) can generate third data using the first method for the 2_1 data, and generate third data using the second method, which is different from the first method, for the 2_2 data.

[0063] The preprocessing unit (330) can correct missing data. The preprocessing unit (330) can correct missing data of the 2_1 data and the 2_2 data. According to an embodiment, the preprocessing unit (330) can compare real-time data stored at a first point in time among the 2_1 data with daily data received at a second point in time, which is a point in time after the first point in time. Accordingly, the preprocessing unit (330) can correct missing real-time data by extracting data that does not correspond to real-time data among the daily data and adding it to the real-time data.

[0064] The preprocessing unit (330) can correct data errors. The preprocessing unit (330) can correct errors in the 2_1 data and the 2_2 data. According to an embodiment, the preprocessing unit (330) can compare real-time data stored at a first point in time among the 2_1 data with daily data received at a second point in time, which is a point after the first point in time. Accordingly, the preprocessing unit (330) can extract data where the real-time data and the daily data do not match. If the real-time data and the daily data do not match, the preprocessing unit (330) can correct errors in the real-time data by modifying the real-time data to the daily data.

[0065] The preprocessing unit (330) can generate a first database (ST). The preprocessing unit (330) can generate the first database (ST) based on the third data. According to an embodiment, the preprocessing unit (330) can generate a plurality of first databases (ST) by classifying the third data according to the type of vehicle. That is, the preprocessing unit (330) can obtain vehicle information that is the basis of the third data from the third data, and can generate a plurality of first databases (ST) based on the vehicle information that is the basis of the third data. In other words, in the case of the third data generated based on data directly or indirectly acquired from the first vehicle type, the preprocessing unit (330) can generate a 1_1 database based on the third data, and in the case of the third data generated based on data directly or indirectly acquired from a second vehicle type different from the first vehicle type, the preprocessing unit (330) can generate a 1_2 database that is different from the 1_1 database based on the third data. Through this, the preprocessing unit (330) can classify the third data according to the type of vehicle.

[0066] The preprocessing unit (330) can generate a second database (D2). The preprocessing unit (330) can generate the second database (D2) based on a plurality of first databases (ST). According to an embodiment, the preprocessing unit (330) can extract preset data from the plurality of first databases (ST) to generate the second database (D2). For example, the preprocessing unit (330) can extract elements necessary for general battery data analysis from the plurality of first databases (ST) and synthesize them to generate the second database (D2). Here, the second database (D2) can include data on various vehicle types, regardless of the vehicle type.

[0067] The second storage unit (340) can store the first database (ST) and the second database (D2). The second storage unit (340) can receive the first database (ST) and the second database (D2) from the preprocessing unit (330) and store the first database (ST) and the second database (D2).

[0068] The second storage unit (340) can store the storage time. According to an embodiment, the storage unit can store the storage time of the first database (ST) and the second database (D2).

[0069] The second storage unit (340) can create a third database. According to an embodiment, the second storage unit (340) can extract data that has passed a preset period of time from the storage time of the first database (ST) or the second database (D2), and create a third database based on the extracted data. Here, the preset period of time can be determined based on the load, performance, etc. of the second storage unit (340). In addition, the third database can be a long-term storage database.

[0070] The second storage unit (340) transfers the third database to a separately provided third storage unit (370) and can delete the first database (ST) or the second database (D2) corresponding to the third database. Through this, the second storage unit (340) can efficiently manage storage space.

[0071] The second storage unit (340) can store analysis results. The second storage unit (340) can receive and store analysis result information from the analysis unit (350). For example, the storage unit can store analysis results of battery data included in various vehicle models and analysis results of battery data included in a target vehicle model.

[0072] According to an embodiment, the second storage unit (340) can transmit the analysis results to the user. The second storage unit (340) can transmit the battery data analysis results to the user using the communication unit (310). That is, the second storage unit (340) can transmit general battery data analysis results to each of a plurality of vehicles, or transmit the battery data analysis results of the target vehicle (100) to the target vehicle (100). According to an embodiment, the second storage unit (340) can transmit the battery data analysis results to the user by uploading the battery data analysis results to the cloud and allowing the user to check them in the cloud, and can also directly provide the battery data analysis results to the user's terminal or PC. In addition, the second storage unit (340) can also provide the battery data analysis results through a display equipped in the target vehicle (100).

[0073] The analysis unit (350) can perform battery data analysis. The analysis unit (350) can perform battery data analysis for batteries (120) included in various vehicle models. According to an embodiment, the analysis unit (350) can perform battery data analysis for batteries (120) included in various vehicle models based on the second database (D2). For example, the analysis unit (350) can perform real-time battery data analysis or daily data analysis based on the second database (D2).

[0074] The analysis unit (350) can perform battery data analysis on the battery (120) included in the target vehicle model. According to an embodiment, the analysis unit (350) can perform battery data analysis on the battery (120) included in the target vehicle model based on the first database (ST). For example, the analysis unit (350) can extract a target database corresponding to the target vehicle model from among a plurality of first databases (ST) and perform data analysis on the battery (120) included in the target vehicle model based on the target database.

[0075] The scheduler (360) can control the operating cycle of the first storage unit (320), the preprocessing unit (330), or the second storage unit (340). The scheduler (360) can control the first storage unit (320) to control the classification cycle of the first data. The scheduler (360) can control the preprocessing unit (330) to control the operating cycles of format conversion of the second_1 data and the second_2 data, classification of the third data, creation of the second database (D2), etc. In addition, the scheduler (360) can control the second storage unit (340) to control the generation of the third database, and the deletion cycles of the first database (ST) and the second database (D2).

[0076] The third storage unit (370) can store data. The third storage unit (370) can receive the third database from the second storage unit (340) and store the third database. According to an embodiment, the third storage unit (370) can be a long-term storage device.

[0077] FIG. 2 is a diagram showing an operation of a server classifying and storing battery data according to an embodiment disclosed in this document.

[0078] Referring to FIG. 2, the server (300) can classify and store battery data. According to an embodiment, the communication unit (310) receives first data, which is battery data, the first storage unit (320) classifies the first data to generate and store second data, the preprocessing unit (330) converts the format of the second data and generates a first database (ST) and a second database (D2), and the second storage unit (340) can store the first database (ST) and the second database (D2).

[0079] The communication unit (310) can receive first data from the target vehicle (100) or the data storage unit (200). Here, the first data may be battery data. The communication unit (310) can transmit the first data to the first storage unit (320).

[0080] The first storage unit (320) can classify the first data. The operation of the first storage unit (320) to classify the first data is described later in FIG. 3.

[0081] The preprocessing unit (330) can convert the formats of the 2_1 data and the 2_2 data to generate the third data, and can generate the first database (ST) and the second database (D2) based on the third data. In addition, the preprocessing unit (330) can correct omissions or errors in the 2_1 data and the 2_2 data. The operation of the preprocessing unit (330) to convert the formats of the 2_1 data and the 2_2 data and to correct omissions or errors will be described later in FIG. 3.

[0082] The preprocessing unit (330) can create a first database (ST) and a second database (D2). The operation of the preprocessing unit (330) to create the first database (ST) and the second database (D2) is described later in FIG. 4.

[0083] The second storage unit (340) can store the first database (ST) and the second database (D2). The second storage unit (340) can receive the first database (ST) and the second database (D2) from the preprocessing unit (330) and store the first database (ST) and the second database (D2).

[0084] FIG. 3 is a diagram showing an operation of a server generating third data according to an embodiment disclosed in this document.

[0085] Referring to FIG. 3, the first storage unit (320) can classify the first data. According to an embodiment, the first storage unit (320) can classify the first data into 2_1 data and 2_2 data based on the reception path of the first data. For example, the first storage unit (320) can distinguish between the first data received from the information acquisition device (110) of the target vehicle (100) and the first data received from the data storage unit (200) among the first data. Accordingly, the first storage unit (320) can define the first data received from the information acquisition device (110) of the target vehicle (100) as 2_1 data and define the data received from the data storage unit (200) as 2_2 data. Through this, the first storage unit (320) can classify the 2_1 data received from the information acquisition device (110) and the 2_2 data received from the data storage unit (200). In this manner, the first storage unit (320) can classify the first data into multiple data. For example, if the first storage unit (320) has n receiving paths, the first storage unit (320) can classify the first data into n data.

[0086] The preprocessing unit (330) can generate third data. The preprocessing unit (330) can generate third data by converting the formats of the 2_1 data and the 2_2 data, thereby unifying the formats of the 2_1 data and the 2_2 data. That is, the third data may be data whose format is unified through format conversion of the 2_1 data and the 2_2 data. According to an embodiment, since the 2_1 data and the 2_2 data have different formats, the preprocessing unit (330) can change the formats of the 2_1 data and the 2_2 data using different methods. That is, the preprocessing unit (330) can generate third data using the first method for the 2_1 data, and generate third data using the second method, which is different from the first method, for the 2_2 data. The preprocessing unit (330) can transfer the generated third data to the first storage unit (320).

[0087] The preprocessing unit (330) can correct missing data. The preprocessing unit (330) can correct missing data of the 2_1 data and the 2_2 data. According to an embodiment, the preprocessing unit (330) can compare real-time data stored at a first point in time among the 2_1 data with daily data received at a second point in time, which is a point in time after the first point in time. Accordingly, the preprocessing unit (330) can correct missing real-time data by extracting data that does not correspond to real-time data among the daily data and adding it to the real-time data.

[0088] The preprocessing unit (330) can correct data errors. The preprocessing unit (330) can correct errors in the 2_1 data and the 2_2 data. According to an embodiment, the preprocessing unit (330) can compare real-time data stored at a first point in time among the 2_1 data with daily data received at a second point in time, which is a point after the first point in time. Accordingly, the preprocessing unit (330) can extract data where the real-time data and the daily data do not match. If the real-time data and the daily data do not match, the preprocessing unit (330) can correct errors in the real-time data by modifying the real-time data to the daily data.

[0089] FIG. 4 is a diagram showing an operation of a server according to an embodiment disclosed in this document to create a first database and a second database.

[0090] Referring to FIG. 4, the preprocessing unit (330) can generate a first database (ST). The preprocessing unit (330) can generate the first database (ST) based on the third data. According to an embodiment, the preprocessing unit (330) can generate a plurality of first databases (ST) by classifying the third data according to the type of vehicle. That is, the preprocessing unit (330) can obtain vehicle information that is the basis of the third data from the third data, and can generate a plurality of first databases (ST) based on the vehicle information that is the basis of the third data. In other words, in the case of the third data generated based on data directly or indirectly acquired from the first vehicle type, the preprocessing unit (330) can generate a 1_1 database based on the third data, and in the case of the third data generated based on data directly or indirectly acquired from the second vehicle type different from the first vehicle type, the preprocessing unit (330) can generate a 1_2 database that is different from the 1_1 database based on the third data. Through this, the preprocessing unit (330) can classify the third data according to the type of vehicle.

[0091] The preprocessing unit (330) can generate a second database (D2). The preprocessing unit (330) can generate the second database (D2) based on a plurality of first databases (ST). According to an embodiment, the preprocessing unit (330) can extract preset data from the plurality of first databases (ST) to generate the second database (D2). For example, the preprocessing unit (330) can extract elements necessary for general battery data analysis from the plurality of first databases (ST) and synthesize them to generate the second database (D2). Here, the second database (D2) can include data on various vehicle types, regardless of the vehicle type.

[0092] The preprocessing unit (330) can transfer the first database (ST) and the second database (D2) to the second storage unit (340). According to an embodiment, the preprocessing unit (330) can separate the first database (ST) and the second database (D2) and transfer them to the second storage unit (340). Accordingly, the second storage unit (340) can store the first database (ST) and the second database (D2).

[0093] The second storage unit (340) can store the first database (ST) and the second database (D2). The second storage unit (340) can receive the first database (ST) and the second database (D2) from the preprocessing unit (330) and store the first database (ST) and the second database (D2).

[0094] The second storage unit (340) can store the storage time. According to an embodiment, the storage unit can store the storage time of the first database (ST) and the second database (D2).

[0095] The second storage unit (340) can create a third database. According to an embodiment, the second storage unit (340) can extract data that has passed a preset period of time from the storage time of the first database (ST) or the second database (D2), and create a third database based on the extracted data. Here, the preset period of time can be determined based on the load, performance, etc. of the second storage unit (340). In addition, the third database can be a long-term storage database.

[0096] The second storage unit (340) transfers the third database to a separately provided third storage unit (370) and can delete the first database (ST) or the second database (D2) corresponding to the third database. Through this, the second storage unit (340) can efficiently manage storage space.

[0097] FIG. 5 is a flowchart showing a battery data analysis method according to an embodiment disclosed in this document.

[0098] The embodiment illustrated in FIG. 5 is only one embodiment, and the order of operations according to various embodiments of the present invention may be different from that illustrated in FIG. 5, and some of the steps illustrated in FIG. 5 may be omitted, the order between the steps may be changed, or the steps may be merged.

[0099] Referring to FIG. 5, the battery data analysis method includes an operation (S100) of receiving first data related to a battery (120) of a vehicle from at least one of a data collection device or a data storage (200) of the vehicle, an operation (S200) of classifying and storing the first data into 2_1 data and 2_2 data based on a reception path of the first data, an operation (S300) of converting the formats of the 2_1 data and the 2_2 data to generate third data, an operation (S400) of generating a plurality of first databases (ST) by classifying the third data according to the type of vehicle, an operation (S500) of generating a second database (D2) by extracting preset data from the plurality of first databases (ST), an operation (S600) of storing the plurality of first databases (ST) and the second database (D2), an operation (S700) of performing analysis of battery data based on the second database (D2), and storing the storage time points of each of the plurality of first databases (ST) and the second database (D2), and It may include an operation (S800) of extracting data for which a preset period of time has elapsed from each of the storage points of the first database (ST) and the second database (D2) to create a third database, which is a long-term storage database.

[0100] Below, the above operations S100 to S800 are specifically described with reference to FIGS. 1 to 4.

[0101] In operation S100, the server (300) may receive first data related to the vehicle's battery (120) from at least one of the vehicle's data collection device or data storage (200).

[0102] The server (300) can receive first data from a plurality of vehicles. According to an embodiment, the server (300) can receive first data from a plurality of vehicles including the target vehicle (100). For example, the server (300) can receive first data from each of the plurality of vehicles by communicating with an information acquisition device (110) included in each of the plurality of vehicles. Here, the first data may be battery data related to the battery (120) of the target vehicle (100).

[0103] The server (300) can receive first data from the data storage (200). According to an embodiment, the server (300) can receive first data from one or more data storages (200).

[0104] In operation S200, the server (300) can classify and store the first data into 2_1 data and 2_2 data based on the reception path of the first data.

[0105] The server (300) can classify the first data. According to an embodiment, the server (300) can classify the first data into 2_1 data and 2_2 data based on the reception path of the first data. For example, the server (300) can distinguish between the first data received from the information acquisition device (110) of the target vehicle (100) and the first data received from the data storage (200) among the first data. Accordingly, the server (300) can define the first data received from the information acquisition device (110) of the target vehicle (100) as 2_1 data and define the data received from the data storage (200) as 2_2 data. Through this, the server (300) can classify the 2_1 data received from the information acquisition device (110) and the 2_2 data received from the data storage (200).

[0106] The server (300) can store the first data. The server (300) can store the second_1 data and the second_2 data included in the first data separately.

[0107] In operation S300, the server (300) can convert the formats of the 2_1 data and the 2_2 data to generate the 3rd data.

[0108] The server (300) can convert the format of data. According to an embodiment, the server (300) can convert the formats of the 2_1 data and the 2_2 data. For example, the server (300) can convert the format of the 2_1 data set based on CAN communication into a separate format that can be confirmed by the user.

[0109] The server (300) can generate third data. The server (300) can generate third data by unifying the formats of the 2_1 data and the 2_2 data by converting the formats of the 2_1 data and the 2_2 data. That is, the third data may be data whose format is unified through format conversion of the 2_1 data and the 2_2 data. According to an embodiment, since the 2_1 data and the 2_2 data have different formats, the server (300) can change the formats of the 2_1 data and the 2_2 data using different methods. That is, the server (300) can generate third data using the first method for the 2_1 data, and generate third data using the second method, which is different from the first method, for the 2_2 data.

[0110] In operation S400, the server (300) can create a plurality of first databases (ST) by classifying third data according to the type of vehicle.

[0111] The server (300) can generate a first database (ST). The server (300) can generate the first database (ST) based on the third data. According to an embodiment, the server (300) can generate a plurality of first databases (ST) by classifying the third data according to the type of vehicle. That is, the server (300) can obtain vehicle information that is the basis of the third data from the third data, and can generate a plurality of first databases (ST) based on the vehicle information that is the basis of the third data. In other words, in the case of third data generated based on data directly or indirectly acquired from a first vehicle type, the server (300) can generate a 1_1 database based on the third data, and in the case of third data generated based on data directly or indirectly acquired from a second vehicle type different from the first vehicle type, the server (300) can generate a 1_2 database that is different from the 1_1 database based on the third data. Through this, the server (300) can classify the third data according to the type of vehicle.

[0112] In operation S500, the server (300) can extract preset data from multiple first databases (ST) to create a second database (D2).

[0113] The server (300) can create a second database (D2). The server (300) can create the second database (D2) based on a plurality of first databases (ST). According to an embodiment, the server (300) can extract preset data from the plurality of first databases (ST) to create the second database (D2). For example, the server (300) can extract elements necessary for general battery data analysis from the plurality of first databases (ST) and synthesize them to create the second database (D2). Here, the second database (D2) can include data on various types of vehicles, regardless of the type of vehicle.

[0114] In operation S600, the server (300) can store a plurality of first databases (ST) and second databases (D2).

[0115] In operation S700, the server (300) can perform analysis of battery data based on the second database (D2).

[0116] The server (300) can perform battery data analysis. The server (300) can perform battery data analysis for batteries (120) included in various vehicle models. According to an embodiment, the server (300) can perform battery data analysis for batteries (120) included in various vehicle models based on the second database (D2). For example, the server (300) can perform real-time battery data analysis or daily data analysis based on the second database (D2).

[0117] The server (300) can perform battery data analysis on the battery (120) included in the target vehicle model. According to an embodiment, the server (300) can perform battery data analysis on the battery (120) included in the target vehicle model based on the first database (ST). For example, the server (300) can extract a target database corresponding to the target vehicle model from among a plurality of first databases (ST) and perform data analysis on the battery (120) included in the target vehicle model based on the target database.

[0118] In operation S800, the server (300) stores the storage points of each of a plurality of first databases (ST) and second databases (D2), and extracts data for which a preset period of time has elapsed from the storage points of each of the plurality of first databases (ST) and second databases (D2) to create a third database, which is a long-term storage database.

[0119] The server (300) may create a third database. According to an embodiment, the server (300) may extract data that has passed a preset period of time from the storage time of the first database (ST) or the second database (D2), and create a third database based on the extracted data. Here, the preset period of time may be determined based on the load, performance, etc. of the server (300). In addition, the third database may be a long-term storage database.

[0120] The above description is merely an example of the technical idea disclosed in this document, and those skilled in the art to which the embodiments disclosed in this document pertain may make various modifications and variations without departing from the essential characteristics of the embodiments disclosed in this document.

[0121] Accordingly, the embodiments disclosed in this document are intended to illustrate, rather than limit, the technical concepts disclosed in this document, and the scope of the technical concepts disclosed in this document is not limited by these embodiments. The scope of protection of the technical concepts disclosed in this document should be interpreted by the claims below, and all technical concepts within the equivalent scope should be interpreted as being included within the scope of the rights of this document.

[0122] [Explanation of symbols]

[0123] 10: Battery data collection system

[0124] 100: Target vehicle

[0125] 110: Information acquisition device

[0126] 200: Data storage

[0127] 300: Server

[0128] 310: Communications Department

[0129] 320: First storage unit

[0130] 330: Preprocessing unit

[0131] 340: Second storage unit

[0132] 350: Analysis Department

[0133] 360: Scheduler

[0134] 370: Third storage unit

Claims

1. A communication unit that receives first data related to a battery of the vehicle from at least one of a data collection device or a data storage of the vehicle; A first storage unit that classifies and stores the first data into 2_1 data and 2_2 data based on the reception path of the first data; Converting the formats of the above 2_1 data and 2_2 data to generate 3rd data, By classifying the above third data according to the type of the vehicle, a plurality of first databases are created, A preprocessing unit that extracts preset data from the plurality of first databases to create a second database; and A battery data collection server comprising a second storage unit storing the plurality of first databases and the second database.

2. In paragraph 1, A battery data collection server further comprising an analysis unit that performs analysis of battery data based on the second database.

3. In paragraph 2, The above analysis unit extracts a target database corresponding to the target vehicle model from among the plurality of first databases, A battery data collection server that performs data analysis of a battery included in the target vehicle model based on the target database.

4. In paragraph 1, The above preprocessing unit is a battery data collection server that unifies the formats of the 2_1 data and the 2_2 data by converting the formats of the 2_1 data and the 2_2 data using different methods, respectively.

5. In paragraph 1, The above preprocessing unit is a battery data collection server that corrects data omissions and errors in the 2_1 data and 2_2 data to generate the 3rd data.

6. In paragraph 5, The above preprocessing unit adds at least a portion of the daily data received at a second point in time, which is a point in time after the first point in time, to the real-time data stored at the first point in time among the 2_1 data. Battery data collection server that corrects the omission of the above 2_1 data.

7. In paragraph 5, The above preprocessing unit modifies at least some of the real-time data stored at the first point in time among the 2_1 data into at least some of the daily data stored at the second point in time, which is a point in time after the first point in time. A battery data collection server that corrects errors in the above 2_1 data.

8. In paragraph 1, The second storage unit stores the storage time of each of the plurality of first databases and the second database, A battery data collection server that extracts data for which a preset period of time has elapsed from each of the plurality of first databases and the second databases, and creates a third database, which is a long-term storage database.

9. In paragraph 8, The second storage unit transfers the third database to the third storage unit, A battery data collection server that deletes the third database and the first database and the second database corresponding to the third database.

10. In paragraph 1, A battery data collection server further comprising a scheduler that controls the operating cycle of the first storage unit and the preprocessing unit.

11. An operation of receiving first data related to a battery of the vehicle from at least one of a data collection device or a data storage of the vehicle; An operation of classifying and storing the first data into 2_1 data and 2_2 data based on the reception path of the first data; An operation of generating third data by converting the formats of the above 2_1 data and 2_2 data; An operation of generating a plurality of first databases by classifying the third data according to the type of the vehicle; An operation of extracting preset data from the plurality of first databases to create a second database; and A battery data collection method comprising an operation of storing the plurality of first databases and the second database.

12. In paragraph 11, A battery data collection method further comprising an operation of performing analysis of battery data based on the second database.

13. In paragraph 12, The operation of performing the analysis of the above battery data is as follows: Extracting a target database corresponding to a target vehicle type from among the plurality of first databases, A battery data collection method including an operation of performing data analysis of a battery included in the target vehicle model based on the target database.

14. In paragraph 11, The action of generating the above third data is: A battery data collection method that unifies the formats of the 2_1 data and the 2_2 data by converting the formats of the 2_1 data and the 2_2 data using different methods, respectively.

15. In paragraph 11, The action of generating the above third data is: A battery data collection method including an operation for correcting data omissions and errors in the above 2_1 data and 2_2 data.

16. In paragraph 15, The action of generating the above third data is: An operation of correcting omission of the 2_1 data by adding at least a portion of the daily data received at a second point in time, which is a point in time after the first point in time, to the real-time data stored at a first point in time among the 2_1 data, and A battery data collection method including an operation of correcting an error in the 2_1 data by correcting at least a portion of the real-time data stored at a first point in time among the 2_1 data with at least a portion of the daily data stored at a second point in time that is a point in time subsequent to the first point in time.

17. In paragraph 11, Store the storage time of each of the plurality of first databases and the second database, A battery data collection method further comprising an operation of extracting data for which a preset period of time has elapsed from each of the plurality of first databases and the second databases to create a third database, which is a long-term storage database.

18. In paragraph 17, The action of creating the above third database is: A battery data collection method comprising an operation of transferring the third database to a third storage unit and deleting the third database and the first database and the second database corresponding to the third database.

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