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KR-20260064085-A - APPARATUS FOR DIAGNOSING BATTERY AND METHOD THEREOF

KR20260064085AKR 20260064085 AKR20260064085 AKR 20260064085AKR-20260064085-A

Abstract

A battery diagnostic device according to one embodiment of the present document includes a memory for storing at least one instruction and at least one processor for executing said at least one instruction, wherein the at least one processor acquires a set of reference data for a reference battery cell corresponding to each of a plurality of designated temperatures, acquires cell data of a battery cell at a specific temperature, fits said reference data to said cell data such that the deviations between said reference data and said cell data included in said set of reference data are minimized, identifies a first specific reference data included in said set of reference data and corresponding to the smallest deviation among said fitted reference data and said cell data, and diagnoses the state of said battery cell based on the value of a parameter related to the fitting of said first specific reference data.

Inventors

  • 최현준
  • 김혜영
  • 김영덕

Assignees

  • 주식회사 엘지에너지솔루션

Dates

Publication Date
20260507
Application Date
20241031

Claims (20)

  1. Memory for storing at least one instruction; and It includes at least one processor that executes the above at least one instruction, and The above-mentioned at least one processor is, A set of reference data for a reference battery cell corresponding to each of a plurality of designated temperatures is obtained, and Acquire cell data of a battery cell at a specific temperature, and Each reference data included in the set of reference data is fitted to the cell data such that the deviations between each reference data and the cell data are minimized, and Identifying a first specific reference data included in the set of reference data above, corresponding to the smallest deviation among the deviations of each fitted reference data and the cell data, and Configured to diagnose the state of the battery cell based on the value of a parameter related to the fitting of the first specific reference data, Battery diagnostic device.
  2. In claim 1, Each of the above reference data is, It includes the capacity profile of the reference battery cell and the voltage profile of the reference battery cell, and The above-mentioned at least one processor is, A configuration configured to fit each of the reference data to the cell data by performing at least one of the operation of a specific first value, the addition of a specific second value, or any combination thereof with respect to the above-mentioned capacity profile or the above-mentioned voltage profile. Battery diagnostic device.
  3. In claim 2, The above-mentioned at least one processor is, Configured to identify the value of the parameter based on the first value above, Battery diagnostic device.
  4. In claim 1, The above-mentioned at least one processor is, Before obtaining the set of reference data above, identify the first reference data of the reference battery cell obtained at the lowest first temperature among the plurality of designated temperatures, and the second reference data of the reference battery cell obtained at the highest second temperature among the plurality of designated temperatures, and Based on the first reference data and the second reference data, configured to identify a set of reference data corresponding to each of the plurality of designated temperatures, Battery diagnostic device.
  5. In claim 4, The above-mentioned at least one processor is, By interpolating the first reference data and the second reference data, a portion of the set of reference data corresponding to each of the temperatures among a plurality of designated temperatures that are higher than the first temperature and lower than the second temperature is identified, and A set of reference data configured to identify the set of reference data based on a part of the set of reference data, the first reference data, and the second reference data. Battery diagnostic device.
  6. In claim 3, The first value related to the value of the above parameter, and The capacity of the above battery cell is, Configured to have a positive correlation, Battery diagnostic device.
  7. In claim 1, The above cell data is, A capacity profile of the battery cell included in a specified capacity range, and A voltage profile of the battery cell according to the above capacity profile, Battery diagnostic device.
  8. In claim 1, The above reference data is, The above reference battery cell is obtained while being charged at a specified rate or while being discharged, and The above cell data is, The battery cell obtained while being charged at the specified rate, or obtained while being discharged Battery diagnostic device.
  9. In claim 1, The above-mentioned at least one processor is, Configured to obtain the capacity of the battery cell based on the value of a parameter related to the fitting of the first specific reference data, Battery diagnostic device.
  10. In claim 9, The above-mentioned at least one processor is, Based on inputting the value of the above parameter into a learning model that has learned the correlation between the above parameter and the capacity of the above battery cell, Configured to identify the capacity of the battery cell output from the above learning model, Battery diagnostic device.
  11. The operation of obtaining a set of reference data for a reference battery cell corresponding to each of a plurality of designated temperatures; Operation of acquiring cell data of a battery cell at a specific temperature; An operation of fitting each reference data to the cell data such that the deviations between each reference data included in the set of reference data and the cell data are minimized; An operation to identify a first specific reference data included in the set of reference data above, corresponding to the smallest deviation among the deviations of each fitted reference data and the cell data; and The operation of diagnosing the state of the battery cell based on the value of a parameter related to the fitting of the first specific reference data, Battery diagnostic method.
  12. In claim 11, Each of the above reference data is, It includes the capacity profile of the reference battery cell and the voltage profile of the reference battery cell, and The operation of fitting each reference data to the cell data such that the deviations between each reference data and the cell data included in the set of reference data are minimized is: With respect to the above-mentioned capacitance profile or the above-mentioned voltage profile, the operation of fitting each of the reference data to the cell data by performing at least one of the operation of a specific first value, the addition of a specific second value, or any combination thereof. Battery diagnostic method.
  13. In claim 12, The operation of diagnosing the state of the battery cell based on the value of a parameter related to the fitting of the first specific reference data is, A method including an operation to identify the value of the parameter based on the first value. Battery diagnostic method.
  14. In claim 11, The operation of obtaining a set of reference data of the reference battery cell corresponding to each of the plurality of specified temperatures is, Before acquiring the set of reference data above, an operation of identifying the first reference data of the reference battery cell acquired at the lowest first temperature among the plurality of designated temperatures, and the second reference data of the reference battery cell acquired at the highest second temperature among the plurality of designated temperatures; and Based on the first reference data and the second reference data, the operation of identifying a set of reference data corresponding to each of the plurality of designated temperatures, Battery diagnostic method.
  15. In claim 14, Based on the first reference data and the second reference data, the operation of identifying the set of reference data corresponding to each of the plurality of designated temperatures is, An operation of identifying a portion of a set of reference data corresponding to each of the temperatures among a plurality of designated temperatures that are higher than the first temperature and lower than the second temperature by interpolating the first reference data and the second reference data; A method comprising identifying a set of reference data based on a part of a set of reference data, the first reference data, and the second reference data. Battery diagnostic method.
  16. In claim 13, The first value related to the value of the above parameter, and The capacity of the above battery cell is, Configured to have a positive correlation, Battery diagnostic method.
  17. In claim 11, The above cell data is, A capacity profile of the battery cell included in a specified capacity range, and A voltage profile of the battery cell according to the above capacity profile, Battery diagnostic method.
  18. In claim 11, The above reference data is, The above reference battery cell is obtained while being charged at a specified rate or while being discharged, and The above cell data is, The battery cell obtained while being charged at the specified rate, or obtained while being discharged Battery diagnostic method.
  19. In claim 11, The operation of diagnosing the state of the battery cell based on the value of a parameter related to the fitting of the first specific reference data is, The operation of obtaining the capacity of the battery cell based on the value of a parameter related to the fitting of the first specific reference data, Battery diagnostic method.
  20. In claim 19, The operation of obtaining the state of the battery cell based on the value of a parameter related to the fitting of the first specific reference data is, The operation of identifying the capacity of the battery cell output from the learning model based on inputting the value of the parameter to the learning model that has learned the correlation between the parameter and the capacity of the battery cell, Battery diagnostic method.

Description

Battery Diagnostic Apparatus and Method Thereof The embodiments disclosed in this document relate to a battery diagnostic device and a method thereof. Recently, active research and development on secondary batteries has been underway. Here, secondary batteries are rechargeable batteries that can be interpreted to encompass conventional Ni/Cd and Ni/MH batteries, as well as recent lithium-ion batteries. With their scope of application expanding to include power sources for electric vehicles, they are garnering attention as a next-generation energy storage medium. With the proliferation of various electronic devices due to the Fourth Industrial Revolution, battery usage is rapidly increasing. Batteries are gaining prominence as an essential energy source in various fields, such as electric vehicles, portable electronic devices, and renewable energy storage systems. Consequently, the importance of battery condition diagnostic technology to improve battery performance and reliability is growing. In particular, technology is being developed to identify the temperature of each battery cell included in a battery unit. By identifying the temperature of each battery cell, the battery condition diagnostic performance of the battery diagnostic device can be improved. This enables the optimization of battery performance and ensures the quality stability of the battery cells by inspecting for abnormalities. FIG. 1 is a block diagram showing a battery pack in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 2 is a block diagram showing the configuration of a battery diagnostic device in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 3 illustrates an example of a graph showing reference data fitted to cell data and cell data in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 4 illustrates an example of a graph showing the deviation between reference data and cell data in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 5 illustrates an example of a graph showing a line in which the voltage included in reference data is differentiated by the capacity and a line in which the voltage included in cell data is differentiated by the capacity, in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 6 illustrates an example of a graph showing a line in which the capacity included in reference data is differentiated by voltage and a line in which the capacity included in cell data is differentiated by voltage in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 7 illustrates an example of a graph representing a set of reference data in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 8 illustrates a diagram and a table showing the temperature distribution of battery cells in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 9 illustrates an example of a learning model for identifying the capacity of a battery cell in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 10 illustrates an example of a diagram showing the influence of a plurality of factors of a learning model for identifying the capacity of a battery cell in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 11 illustrates a graph showing the temperature and parameters of a battery cell predicted in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 12 illustrates a graph showing the accuracy of the capacity prediction of a battery cell by a learning model in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 13 illustrates an example of the flow of operation of a battery diagnostic device for identifying the temperature of a battery cell in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 14 illustrates an example of the flow of operation of a battery diagnostic device for identifying the capacity of a battery cell in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. FIG. 15 is a block diagram showing the hardware configuration of a computing system performing a battery diagnostic method in a battery diagnostic device and a battery diagnostic method according to one embodiment of the present document. Some embodiments disclosed herein a