CN-122029561-A - Battery data analysis server and operation method thereof

Abstract

The battery data analysis server according to one embodiment disclosed in this document includes a first communication unit for receiving battery data from a plurality of vehicles, an analysis unit for determining a target vehicle traveling on a target date among the plurality of vehicles, analyzing each of the battery data corresponding to each of the target vehicles, and generating daily data based on the analysis result, a data lake for storing the daily data, a message queue for acquiring data information including the number of pieces of daily data stored in the data lake in real time, a storage unit for receiving and storing at least some of the daily data from the data lake, and a scheduler for checking a load state according to data processing of the storage unit and storing the daily data in the storage unit based on the load state.

Inventors

• LI JUNHE

Assignees

• 株式会社LG新能源

Dates

Publication Date

20260512

Application Date

20241015

Priority Date

20231023

Claims (16)

1. 1. A battery data analysis server, the battery data analysis server comprising: A first communication unit configured to receive battery data from a plurality of vehicles; An analysis unit configured to determine a target vehicle that runs on a target date among the plurality of vehicles, analyze each of the battery data corresponding to each of the target vehicles, and generate daily data based on an analysis result; a data lake configured to store the daily data; A message queue configured to obtain, in real-time, data information including the number of daily data stored in the data lake; A storage unit configured to receive and store at least a portion of the daily data from the data lake, and A scheduler configured to confirm a load status according to data processing of the storage unit and store the daily data in the storage unit based on the load status.
2. 2. The battery data analysis server according to claim 1, wherein when a load of a Central Processing Unit (CPU) including the storage unit is smaller than a set value, The scheduler stores the daily data by sending the daily data from the data lake to the storage unit.
3. 3. The battery data analysis server of claim 2, wherein the scheduler confirms the load status of the CPU based on an Average Active Session (AAS) of the CPU.
4. 4. The battery data analysis server according to claim 1, wherein the scheduler confirms data information of the message queue, and And deleting data information corresponding to the data transmitted to the storage unit from the data lake among the daily data.
5. 5. The battery data analysis server of claim 1, wherein the scheduler confirms the data information of the message queue at a preset period.
6. 6. The battery data analysis server according to claim 1, wherein the storage unit classifies the daily data corresponding to each of the target vehicles per target vehicle, and stores the classified daily data.
7. 7. The battery data analysis server according to claim 1, wherein the data information includes position information of the daily data stored in the data lake, and The scheduler stores the daily data by transmitting the daily data from the data lake to the storage unit based on the location information.
8. 8. The battery data analysis server according to claim 7, wherein the scheduler transmits the daily data corresponding to a preset number of daily data transmissions from the data lake to the storage unit.
9. 9. A battery data analysis method, the battery data analysis method comprising the operations of: An operation of receiving battery data from a plurality of vehicles; determining an operation of a target vehicle among the plurality of vehicles that is traveling on a target date; An operation of analyzing each of the battery data corresponding to each of the target vehicles, compressing an analysis result, and generating daily data independently; An operation of acquiring data information including the number of daily data stored in the data lake in real time, and And an operation of confirming a load state according to data processing of a storage unit and storing the daily data in the storage unit based on the load state.
10. 10. The battery data analysis method according to claim 9, wherein the operation of storing includes an operation of confirming a load state of a Central Processing Unit (CPU) including the storage unit by confirming the load state of the storage unit.
11. 11. The battery data analysis method according to claim 10, wherein when the load of the CPU including the storage unit is smaller than a set value, The storing operation includes an operation of storing the daily data by transmitting the daily data from the data lake to the storage unit.
12. 12. The battery data analysis method of claim 10, wherein the stored operations include an operation of confirming the load state of the CPU based on an Average Active Session (AAS) of the CPU.
13. 13. The battery data analysis method according to claim 9, further comprising an operation of confirming data information of a message queue and deleting data information corresponding to data transmitted to the storage unit among the daily data from the data lake.
14. 14. The battery data analysis method according to claim 9, wherein the data information includes position information of the daily data stored in the data lake, and The storing operation includes an operation of storing the daily data by transmitting the daily data from the data lake to the storage unit based on the location information.
15. 15. The battery data analysis method according to claim 14, wherein the operation of storing includes an operation of transmitting the daily data equivalent to a preset daily data transmission number from the data lake to the storage unit.
16. 16. The battery data analysis method according to claim 14, wherein the storing operation includes an operation of transmitting daily data corresponding to a preset number of daily data transmissions from the data lake to the storage unit.

Description

Battery data analysis server and operation method thereof Technical Field Cross Reference to Related Applications The present application claims priority and rights of korean patent application No. 10-2023-0142156 filed at korean intellectual property agency on day 10 and 23 of 2023, the entire contents of which are incorporated herein by reference. Technical Field Embodiments disclosed herein relate to a battery data analysis server and a method of operating the same. Background Recently, research and development of secondary batteries have been actively conducted. Here, the secondary battery is a battery capable of being charged and discharged, and includes all recent lithium ion batteries in addition to conventional Ni/Cd batteries and Ni/MH batteries. Among secondary batteries, lithium ion batteries have a much higher energy density than conventional Ni/Cd batteries, ni/MH batteries, and the like. In addition, lithium ion batteries can be manufactured in a compact and lightweight form and thus are used as power sources for mobile devices. In addition, as the range of use is expanded to the power supply of electric vehicles, lithium ion batteries are attracting attention as next-generation energy storage media. In addition, the secondary battery may be generally used as a battery pack including a battery module in which a plurality of battery cells are connected in series and/or parallel. In addition, the secondary battery may be used as a battery rack including a plurality of battery modules and a rack accommodating the battery modules. Further, in order to check the state of the secondary battery included in the Electric Vehicle (EV), the server may collect and analyze battery data and provide a result value to the user. When daily data is collected from a plurality of EVs, the data amount is enormous, so the time required for data analysis is excessively long, and when the analysis result is stored at one time, there is a problem that an excessive load is imposed on the storage unit. Disclosure of Invention Technical problem Embodiments disclosed herein relate to providing a battery data analysis server and an operating method thereof, which are capable of analyzing battery data of a plurality of vehicles. Embodiments disclosed herein also relate to providing a battery data analysis server and an operating method thereof, in which battery data is stored to adjust a load of a storage unit in consideration of performance of the storage unit of data. Embodiments disclosed herein also relate to providing a battery data analysis server and an operating method thereof that improve efficiency of data analysis by independently analyzing battery data of each of a plurality of vehicles. Embodiments disclosed herein also relate to providing a battery data analysis server and an operating method thereof, in which battery data is stored to adjust a load of a storage unit in consideration of performance of the storage unit of data. The objects of the embodiments disclosed herein are not limited to the above objects, and other objects not described will be clearly understood by those skilled in the art to which the present disclosure pertains from the following description. Technical proposal The battery data analysis server according to one embodiment disclosed herein includes a first communication unit configured to receive battery data from a plurality of vehicles, an analysis unit configured to determine a target vehicle traveling on a target date among the plurality of vehicles, analyze each of the battery data corresponding to each of the target vehicles, and generate daily data based on an analysis result, a data lake configured to store the daily data, a message queue configured to acquire data information including the number of daily data stored in the data lake in real time, a storage unit configured to receive and store at least a portion of the daily data from the data lake, and a scheduler configured to confirm a load state according to data processing of the storage unit and store the daily data in the storage unit based on the load state. According to one embodiment, the scheduler may store the daily data by transmitting the daily data from the data lake to the storage unit when a load of a Central Processing Unit (CPU) including the storage unit is less than a set value. According to one embodiment, the scheduler may confirm the load status of the CPU based on an Average Active Session (AAS) of the CPU. According to one embodiment, the scheduler may confirm the data information of the message queue and delete the data information corresponding to the data transmitted to the storage unit among the daily data from the data lake. According to one embodiment, the scheduler may confirm the data information of the message queue at a preset period. According to one embodiment, the storage unit may classify the daily data corresponding to each of the target vehicles by each target vehicle, and store the cla