Battery temperature estimation device and operation method thereof

Abstract

A battery temperature estimation device according to one embodiment disclosed in this document may include a data acquisition unit that acquires electrochemical impedance spectroscopy (EIS) data of a battery unit, a data extraction unit that extracts parameter values ​​of designated elements in an equivalent circuit of the battery unit based on the EIS data, and an identification unit that identifies a temperature value corresponding to the extracted parameter value based on reference parameter values ​​corresponding to different temperatures that are acquired based on a reference battery unit of the same type as the battery unit, and identifies the temperature value from the temperature value of the battery unit at the time the EIS data was acquired.

Description

[Technical Field]

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2023-0009080, filed on January 20, 2023, and all contents disclosed in the documents of this Korean patent application are incorporated herein by reference.

[0002] SUMMARY OF THE INVENTION The embodiments disclosed herein relate to a battery temperature estimation apparatus and method of operation. [Background technology]

[0003] In recent years, research and development into secondary batteries has been actively pursued. Here, secondary batteries are batteries that can be charged and discharged, and include both conventional Ni / Cd batteries, Ni / MH batteries, and more recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of significantly higher energy density than conventional Ni / Cd batteries, Ni / MH batteries, and other batteries. Furthermore, lithium-ion batteries can be manufactured to be compact and lightweight, and are used as power sources for mobile devices. Furthermore, lithium-ion batteries are gaining attention as a next-generation energy storage medium, with their range of use expanding to include power sources for electric vehicles.

[0004] Furthermore, the secondary battery can be used as a battery pack including a battery module in which a plurality of battery cells are connected in series and / or parallel, or as a battery rack including a plurality of battery modules and a rack frame for accommodating the battery modules.

[0005] Such battery cells, battery modules, battery packs, or battery racks can be used in a variety of devices. For example, the batteries can be used in mobile devices such as mobile phones, laptop computers, smartphones, and smart pads, as well as in fields such as electrically powered automobiles (EVs, HEVs, and PHEVs) and large-capacity energy storage systems (ESS).

[0006] Such batteries can be managed and controlled in status and operation by a battery management system (BMS), which can be contained with the batteries in a device, or which can manage and control the batteries remotely from the device containing the batteries. Summary of the Invention [Problem to be solved by the invention]

[0007] Without a temperature sensor inside the battery, it is difficult to measure the battery temperature accurately, and if the battery temperature is not measured accurately, it is difficult to measure other battery parameters (e.g., SOC, SOH) that are affected by temperature with high accuracy.

[0008] Furthermore, if the communication information of the battery is not known (for example, if the communication method or signal configuration of the battery is not made public), it may be difficult to receive temperature information measured by the battery itself from the battery.

[0009] Therefore, there is a need for a method that can measure the temperature of a battery even when there is no temperature sensor inside the battery or when communication with the battery is difficult.

[0010] The technical problems of the embodiments disclosed in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0011] A battery temperature estimation device according to one embodiment disclosed in this document may include a data acquisition unit that acquires electrochemical impedance spectroscopy (EIS) data of a battery unit, a data extraction unit that extracts parameter values ​​of designated elements in an equivalent circuit of the battery unit based on the EIS data, and an identification unit that identifies a temperature value corresponding to the extracted parameter value based on reference parameter values ​​corresponding to different temperatures that are acquired based on a reference battery unit of the same type as the battery unit, and identifies the temperature value from the temperature value of the battery unit at the time the EIS data was acquired.

[0012] An operating method of a battery temperature estimation device according to one embodiment disclosed herein may include the following operations: acquiring electrochemical impedance spectroscopy (EIS) data of a battery unit; extracting parameter values ​​of designated elements in an equivalent circuit of the battery unit based on the EIS data; identifying a temperature value corresponding to the extracted parameter value based on reference parameter values ​​corresponding to different temperatures that are acquired based on a reference battery unit of the same type as the battery unit; and identifying the temperature value as the temperature value of the battery unit at the time the EIS data was acquired. [Effects of the Invention]

[0013] The battery temperature estimation apparatus and its operating method according to various embodiments disclosed herein can estimate the temperature of a battery even if the battery does not have a temperature sensor.

[0014] The effects of the battery temperature estimation device and its operating method disclosed in this document are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the disclosure of this document. [Brief explanation of the drawings]

[0015] [Figure 1]1 is a block diagram of a battery temperature estimation device according to an embodiment of the present disclosure. [Figure 2] FIG. 10 is a diagram illustrating an example of the impedance of a battery depending on a change in frequency. [Figure 3] FIG. 1 is a diagram showing an example of battery impedance with frequency change at different SOH (state of health). [Figure 4] 1 is a flowchart illustrating a method of operating a battery temperature estimation device according to an embodiment of the present disclosure. [Figure 5] 1 is a flowchart illustrating a method for generating a database by a battery temperature estimation device according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that this is not intended to limit the present invention to the particular embodiments, but rather to encompass various modifications, equivalents, and / or alternatives of the embodiments of the present invention.

[0017] The embodiments and terms used in this document should not be understood to limit the technical features described in this document to a specific embodiment, but should be understood to include various modifications, equivalents, or alternatives of the embodiment. In connection with the description of the drawings, similar reference numerals are used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the said item, unless a clearly different meaning is indicated in the relevant context.

[0018] In this document, each of 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" may include any one of the items listed with that phrase or all possible combinations thereof. Terms such as "first," "second," "first," "second," "A," "B," "(a)," or "(b)" are used merely to distinguish one element from other elements and do not limit the element in other respects (e.g., weight or order) unless specifically stated to the contrary.

[0019] In this document, when a (e.g., first) component is referred to as being "coupled," "coupled," or "connected" to another (e.g., second) component, with or without the terms "functionally" or "communicatively," or when a reference is made to being "coupled" or "connected," it means that the component can be coupled to the other component directly (e.g., by wire or wirelessly) or indirectly (e.g., via a third component).

[0020] The methods according to various embodiments disclosed herein may be provided 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., a compact disc read-only memory, CD-ROM) or may be distributed online (e.g., downloaded or uploaded) via 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 at least temporarily stored in or temporarily generated on a machine-readable storage medium, such as the memory of a manufacturer's server, an application store server, or an intermediary server.

[0021] According to the embodiments disclosed herein, each of the aforementioned components (e.g., modules or programs) may include one or more entities, and some of the entities may be located separately in other components. According to the embodiments disclosed herein, one or more of the aforementioned components or operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., modules or programs) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the respective components of the multiple components before the integration. According to the embodiments disclosed herein, operations performed by modules, programs, or other components may be performed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be performed in a different order, omitted, or one or more other operations may be added.

[0022] Fig. 1 is a block diagram of a battery temperature estimation device 101 according to an embodiment of the present disclosure. Fig. 2 shows an example of battery impedance 200 with respect to a change in frequency. Fig. 3 shows an example of battery impedance 300 with respect to a change in frequency at different states of health (SOH).

[0023] In one embodiment, each of the one or more battery units 111, 113, and 115 may be a battery cell, a battery module, a battery pack, or a battery rack. In one embodiment, each of the battery units 111, 113, and 115 may be installed in a mobile device (e.g., a mobile phone, a laptop computer, a smartphone, or a smart pad), an electric vehicle (e.g., an electric vehicle (EV), a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV), or a fuel cell electric vehicle (FCEV)), an energy storage system (ESS), or a battery swapping system (BSS). In this case, the battery temperature estimation apparatus 101 may be included in the mobile device (e.g., a mobile phone, a laptop computer, a smart pad), an electric vehicle (e.g., an EV, a HEV, a PHEV, or a FCEV), an energy storage system (ESS), or a battery swapping system (BSS).

[0024] 1, the battery temperature estimation device 101 may include a sensor 130, a memory 140, and a processor 150. According to an embodiment, the battery temperature estimation device 101 shown in FIG. 1 may further include at least one component (e.g., a communication circuit, a display, an input device, or an output device) in addition to the components shown in FIG. 1.

[0025] In one embodiment, the sensor 130 may obtain a value related to the status of the battery units 111, 113, and 115. In one embodiment, the value related to the status may indicate one or more values ​​related to the voltage, current, resistance, or a combination thereof of the battery units 111, 113, and 115. Hereinafter, the value related to the status may be referred to as a "status value."

[0026] In one embodiment, memory 140 may include volatile memory and / or non-volatile memory.

[0027] In one embodiment, the memory 140 can store data used by at least one component (e.g., the processor 150) of the battery temperature estimation apparatus 101. For example, the data can include database software (or instructions therefor), input data, or output data. In one embodiment, the instructions, when executed by the processor 150, can cause the battery temperature estimation apparatus 101 to perform the operation defined by the instructions.

[0028] In one embodiment, memory 140 may include one or more pieces of software (eg, database builder 141, data acquirer 143, data extractor 145, and identifier 147).

[0029] In one embodiment, processor 150 may include a central processing unit, an application processor, a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor.

[0030] In one embodiment, the processor 150 executes software (e.g., the database construction unit 141, the data acquisition unit 143, the data extraction unit 145, and the identification unit 147), controls at least one other component (e.g., a hardware or software component) of the battery temperature estimation device 101 coupled to the processor 150, and can perform various data processing or calculations.

[0031] The following describes how the battery temperature estimation device 101 estimates the temperatures of the battery units 111, 113, and 115 using the database construction unit 141, data acquisition unit 143, data extraction unit 145, and identification unit 147, with reference to Figures 2 and 3.

[0032] Building a database In one embodiment, the database builder 141 can acquire electrochemical impedance spectroscopy (EIS) data from the reference battery unit. In one embodiment, the database builder 141 can acquire EIS data from the reference battery unit using the sensor 130. Here, the reference battery unit can be the same type of battery unit as the battery units 111, 113, and 115.

[0033] In one embodiment, the database builder 141 may acquire EIS data while the reference battery unit has a specified state of charge (SOC), where the specified SOC may be 75, 90, or 100. However, the specified SOC is not limited thereto and may be variously set.

[0034] In one embodiment, the database builder 141 may acquire EIS data of the reference battery units at different reference temperatures. In one embodiment, the different reference temperatures may be in increments of 5 degrees (or other increments). For example, the different reference temperatures may include 10, 15, 20, 25, 30, 35, 40, and 45 degrees. However, the different reference temperatures are not limited to 10, 15, 20, 25, 30, 35, 40, and 45 degrees.

[0035] In one embodiment, the database construction unit 141 can generate an equivalent circuit model of the reference battery unit based on the EIS data. Here, the equivalent circuit model can be a circuit model consisting of at least four parts. For example, the at least four parts can include an Ro (resistive) region, an SEI (solid electrolyte interphase) region, a CT (charge transfer) region, and a constant phase (i.e., Zw) region. Referring to FIG. 2, it can be seen that, according to the equivalent circuit model, Rsei is measured in the high-frequency region, Zw is measured in the low-frequency region, and Rct is measured between the high-frequency region and the low-frequency region.

[0036] In one embodiment, the database constructor 141 may generate equivalent circuit models of reference battery units at different reference temperatures.

[0037] In one embodiment, the database construction unit 141 may extract the resistance value of Rsei (solid electrolyte interphase resistance) using an equivalent circuit model at different reference temperatures. For example, the database construction unit 141 may extract the resistance value of Rsei based on the real value of the impedance in a specified frequency domain (i.e., a high-frequency domain). Referring to FIG. 3, it can be seen that the resistance value of Rsei is similar for battery units at the same temperature (e.g., 25°C) regardless of the degree of degradation. For example, EIS graph 310 of a battery unit having a state of health (SOH) of 98.6% after 100 charge / discharge cycles, EIS graph 320 of a battery unit having a SOH of 97.3% after 200 charge / discharge cycles, and EIS graph 330 of a battery unit having a SOH of 96.0% after 300 charge / discharge cycles show the same values ​​for Rsei but different trends in other areas (e.g., Rct).

[0038] In one embodiment, the database creator 141 can generate a database 142 that indicates the relationship between different reference temperatures and the resistance value of Rsei. For example, the database 142 can be generated in a form in which different reference temperatures and the resistance value of Rsei are linked in pairs (e.g., temperature-Rsei pairs).

[0039] In one embodiment, the database construction unit 141 can acquire different reference temperatures and the resistance values ​​of Rsei at different temperatures. In one embodiment, the database construction unit 141 can acquire the resistance values ​​of Rsei at different temperatures based on the relationship between the different reference temperatures and the resistance values ​​of Rsei. In one embodiment, the database construction unit 141 can acquire the resistance values ​​of Rsei based on interpolation.

[0040] In one embodiment, the database construction unit 141 can obtain the resistance value of Rsei at the temperature to be determined by taking a weighted average of the resistance values ​​of Rsei at the two reference temperatures closest to the temperature to be determined. For example, the database construction unit 141 can obtain the resistance value of Rsei at 12.5 degrees by taking the average of the resistance value of Rsei at 10 degrees and the resistance value of Rsei at 15 degrees. As another example, the database construction unit 141 can obtain the resistance value of Rsei at 12 degrees by taking a weighted average of the resistance value of Rsei at 10 degrees and the resistance value of Rsei at 15 degrees (for example, assigning a weight of 0.6 to the resistance value of Rsei at 10 degrees and a weight of 0.4 to the resistance value of Rsei at 15 degrees).

[0041] According to an embodiment, the database construction unit 141 can construct the database 142 for each different SOC. For example, the database construction unit 141 can construct the database 142 based on the relationship between the temperature and the resistance value of Rsei obtained when the SOC is 75. The database construction unit 141 can also construct the database 142 based on the relationship between the temperature and the resistance value of Rsei obtained when the SOC is 90 and / or 100. Here, the SOCs of 75, 90, and 100 are exemplified, but this is merely an example. The database construction unit 141 can construct the database 142 based on the relationship between the temperature and the resistance value of Rsei obtained for each different SOC.

[0042] Temperature estimation In one embodiment, the data acquisition unit 143 can acquire EIS data of the battery unit (e.g., the battery unit 111). In one embodiment, the data acquisition unit 143 can acquire EIS data of the battery unit by the sensor 130.

[0043] In one embodiment, the data acquisition unit 143 may acquire EIS data of the battery unit while the battery unit has a designated SOC. In one embodiment, if the battery unit does not have the designated SOC, the battery temperature estimation apparatus 101 may charge the battery unit so that the battery unit has the designated SOC, in response to a request from the data acquisition unit 143. Here, the designated SOC may be 75, 90, or 100. However, the designated SOC is not limited thereto and may be variously set.

[0044] In one embodiment, the data extraction unit 145 can generate an equivalent circuit model of the battery unit based on the EIS data. Here, the equivalent circuit model can be a circuit model consisting of at least four parts. For example, the at least four parts can include an Ro region, an SEI region, a CT region, and a Zw region.

[0045] In one embodiment, the data extraction unit 145 may extract a parameter value of a designated element in the equivalent circuit model of the battery unit. Here, the designated element may be Rsei. For example, the data extraction unit 145 may extract the resistance value of Rsei in the equivalent circuit model of the battery unit.

[0046] In one embodiment, the identification unit 147 can identify the temperature value of the battery at the time the EIS data was acquired based on the resistance value of Rsei of the battery unit. In one embodiment, the identification unit 147 can refer to the database 142 to identify the temperature value of the battery corresponding to the resistance value of Rsei. For example, if the resistance value of Rsei of the battery unit is 15 mΩ, the identification unit 147 can refer to the database 142 to identify the temperature value associated with 15 mΩ.

[0047] In one embodiment, the identification unit 147 can identify the temperature value of the parameter value corresponding to the extracted Rsei from among a first reference parameter value (e.g., the resistance value of Rsei) corresponding to a reference temperature and a second reference parameter value (e.g., the resistance value of Rsei) obtained by interpolating the first reference parameter value, as the temperature value of the battery at the time the EIS data was acquired.

[0048] The battery temperature estimation device 101 according to one embodiment of the present disclosure as described above can solve the problem of difficulty in obtaining temperature information of the battery units 111, 113, 115 when the battery units 111, 113, 115 do not have temperature sensors or when the battery units 111, 113, 115 are not communicatively connected.

[0049] The battery temperature estimation device 101 according to one embodiment of the present disclosure as described above generates an equivalent circuit model of the battery units 111, 113, and 115 based on the EIS data of the battery units 111, 113, and 115, and utilizes a parameter (i.e., the value of Rsei) that is not related to the degree of degradation of the battery units 111, 113, and 115 among the parameter values ​​(e.g., the values ​​of Rsei and Rct) that can be obtained from the equivalent circuit model, thereby making it possible to measure the temperature of the battery units 111, 113, and 115 with high accuracy.

[0050] According to the embodiment, the identification unit 147 can identify the temperature value of the battery at the time the EIS data was acquired by referring to the database 142 constructed for each different SOC. For example, the identification unit 147 can identify the temperature value of the battery corresponding to the resistance value of Rsei by referring to the database 142 corresponding to the SOC of the battery at the time the EIS data was acquired.

[0051] Unlike the description with reference to FIGS. 1 to 3, the battery temperature estimation device 101 according to an embodiment of the present disclosure can be used even when the battery units 111, 113, and 115 have temperature sensors.

[0052] For example, the data acquiring unit 143 can acquire EIS data of a battery unit (e.g., battery unit 111) using the sensor 130. The data acquiring unit 143 can also acquire temperature data from the battery unit (e.g., battery unit 111) via a communication circuit (not shown). Here, the temperature data can be data acquired by a temperature sensor in the battery unit (e.g., battery unit 111) itself.

[0053] Next, the data extraction unit 145 generates an equivalent circuit model of the battery unit based on the EIS data, and then extracts the resistance value of Rsei from the equivalent circuit model of the battery unit.

[0054] Next, the identification unit 147 can identify the temperature value of the battery at the time the EIS data was acquired based on the resistance value of Rsei of the battery unit.

[0055] Next, the identification unit 147 may compare the identified temperature value with temperature data acquired from the battery unit (e.g., battery unit 111) to identify whether the temperature data is abnormal. For example, if the difference between the identified temperature value and the temperature data is equal to or greater than a critical temperature value, the identification unit 147 may determine that an error (or failure) has occurred in the temperature sensor of the battery unit (e.g., battery unit 111) itself.

[0056] 4 is a flowchart illustrating a method of operating a battery temperature estimation device according to an embodiment of the present disclosure, which can be described with reference to the configuration of FIG.

[0057] 4 , in operation 410, the battery temperature estimation apparatus 101 may acquire EIS data of a battery unit (e.g., battery unit 111). In one embodiment, the data acquisition unit 143 may acquire the EIS data of the battery unit via the sensor 130.

[0058] In one embodiment, the battery temperature estimation apparatus 101 can acquire EIS data of the battery unit while the battery unit has a specified SOC. In one embodiment, if the battery unit does not have the specified SOC, the battery temperature estimation apparatus 101 can charge the battery unit so that the battery unit has the specified SOC. Here, the specified SOC may be 75, 90, or 100. However, the specified SOC is not limited thereto and can be set in various ways.

[0059] In operation 420, the battery temperature estimation device 101 can extract parameter values ​​of designated elements on the equivalent circuit of the battery unit.

[0060] Specifically, the battery temperature estimation device 101 can generate an equivalent circuit model of the battery unit based on the EIS data. Here, the equivalent circuit model can be a circuit model consisting of at least four parts. For example, the at least four parts can include an Ro region, an SEI region, a CT region, and a Zw region.

[0061] Then, the battery temperature estimation device 101 can extract a parameter value of a designated element in the equivalent circuit model of the battery unit. Here, the designated element can be Rsei. For example, the battery temperature estimation device 101 can extract the resistance value of Rsei in the equivalent circuit model of the battery unit.

[0062] In operation 430, the battery temperature estimation device 101 can identify the temperature value of the battery at the time the EIS data was acquired based on the resistance value of Rsei of the battery unit. In one embodiment, the battery temperature estimation device 101 can refer to the database 142 to identify the temperature value of the battery according to the resistance value of Rsei.

[0063] In one embodiment, the battery temperature estimation device 101 can identify the temperature value of the parameter value corresponding to the extracted Rsei from among a first reference parameter value (e.g., the resistance value of Rsei) corresponding to a reference temperature and a second reference parameter value (e.g., the resistance value of Rsei) interpolated from the first reference parameter value, as the temperature value of the battery at the time the EIS data was acquired.

[0064] 5 is a flowchart illustrating an operation method for generating a database by the battery temperature estimation apparatus 101 according to an embodiment of the present disclosure. FIG. 5 can be described with reference to the configuration of FIG.

[0065] 5 , in operation 510, the battery temperature estimation apparatus 101 may acquire EIS data from a reference battery unit. In one embodiment, the battery temperature estimation apparatus 101 may acquire EIS data from the reference battery unit using the sensor 130. Here, the reference battery unit may be the same type of battery unit as the battery units 111, 113, and 115.

[0066] In one embodiment, the battery temperature estimation device 101 may acquire EIS data while the reference battery unit has a specified SOC, where the specified SOC may be 75, 90, or 100. However, the specified SOC is not limited thereto and may be variously set.

[0067] In one embodiment, the battery temperature estimation device 101 may acquire EIS data of the reference battery unit at different reference temperatures. In one embodiment, the different reference temperatures may be in increments of 5 degrees. For example, the different reference temperatures may include 10, 15, 20, 25, 30, 35, 40, and 45 degrees.

[0068] In operation 520, the battery temperature estimation apparatus 101 can generate an equivalent circuit model of the reference battery unit based on the EIS data. Here, the equivalent circuit model can be a circuit model consisting of at least four parts. For example, the at least four parts can include an Ro (resistive) region, an SEI region, a CT region, and a constant phase (i.e., Zw) region. The equivalent circuit model can measure Rsei in the high-frequency region, measure Zw in the low-frequency region, and measure Rct between the high-frequency region and the low-frequency region.

[0069] In one embodiment, the battery temperature estimation device 101 can generate equivalent circuit models of reference battery units at different reference temperatures.

[0070] In operation 530, the battery temperature estimation apparatus 101 can extract a parameter value (e.g., the resistance value of Rsei) of a specified element on the equivalent circuit of the reference battery unit. For example, the battery temperature estimation apparatus 101 can extract the resistance value of Rsei in the equivalent circuit model at different reference temperatures.

[0071] For example, the battery temperature estimation apparatus 101 can extract the resistance value of Rsei based on the real value of the impedance in a specified frequency domain (ie, a high frequency domain).

[0072] In operation 540, the battery temperature estimating device 101 may generate a database 142 that indicates the relationship between temperature and parameter values.

[0073] In one embodiment, the battery temperature estimation apparatus 101 can generate a database 142 indicating the relationship between different reference temperatures and the resistance value of Rsei. For example, the database 142 can be generated in a form in which different reference temperatures and the resistance value of Rsei are linked in pairs (e.g., temperature-Rsei pairs).

[0074] In one embodiment, the battery temperature estimation apparatus 101 can obtain different reference temperatures and the resistance values ​​of Rsei at different temperatures. In one embodiment, the battery temperature estimation apparatus 101 can obtain the resistance values ​​of Rsei at different temperatures based on the relationship between the different reference temperatures and the resistance values ​​of Rsei. In one embodiment, the battery temperature estimation apparatus 101 can obtain the resistance value of Rsei based on interpolation.

[0075] In one embodiment, the battery temperature estimation device 101 can obtain the resistance value of Rsei at a desired temperature by taking a weighted average of the resistance values ​​of Rsei at two reference temperatures closest to the desired temperature. For example, the database construction unit 141 can obtain the resistance value of Rsei at 12.5 degrees by taking the average of the resistance value of Rsei at 10 degrees and the resistance value of Rsei at 15 degrees. As another example, the database construction unit 141 can obtain the resistance value of Rsei at 12 degrees by taking a weighted average of the resistance value of Rsei at 10 degrees and the resistance value of Rsei at 15 degrees (e.g., assigning a weight of 0.6 to the resistance value of Rsei at 10 degrees and a weight of 0.4 to the resistance value of Rsei at 15 degrees).

Claims

1. a data acquisition unit that acquires EIS data of the battery unit; a data extraction unit that extracts parameter values ​​of designated elements in an equivalent circuit of the battery unit based on the EIS data; an identification unit that identifies a temperature value corresponding to the extracted parameter value based on reference parameter values ​​corresponding to different temperatures obtained based on a reference battery unit of the same type as the battery unit, and identifies the temperature value from the temperature value of the battery unit at the time the EIS data was obtained.

2. The battery temperature estimation device according to claim 1 , wherein the identification unit identifies a temperature value of a parameter value corresponding to the extracted parameter value from among the reference parameter values ​​according to a reference temperature, as the temperature value of the battery unit.

3. the reference parameter values ​​include a first reference parameter value obtained from the reference battery unit at a reference temperature and a second reference parameter value obtained by interpolating the first reference parameter value; The battery temperature estimation device according to claim 1 , wherein the second reference parameter value is a parameter value relating to a temperature different from the reference temperature.

4. The battery temperature estimation device of claim 1 , wherein the specified element is Rsei.

5. The battery temperature estimation device according to claim 1 , wherein the EIS data is data obtained at a time when the SOC of the battery unit is a specified SOC.

6. the data acquisition unit acquires temperature data from the battery unit; The battery temperature estimation device according to claim 1 , wherein the identification unit compares the temperature value with the temperature data to identify whether or not the temperature data is abnormal.

7. An operation of acquiring EIS data of the battery unit; An operation of extracting parameter values ​​of designated elements in an equivalent circuit of the battery unit based on the EIS data; identifying a temperature value corresponding to the extracted parameter value based on reference parameter values ​​corresponding to different temperatures, the reference parameter values ​​being obtained based on a reference battery unit of the same type as the battery unit; and identifying the temperature value from the temperature value of the battery unit at the time the EIS data was acquired.

8. 8. The method for operating the battery temperature estimation device according to claim 7, further comprising: an operation of identifying a temperature value of a parameter value corresponding to the extracted parameter value among the reference parameter values ​​according to a reference temperature, from the temperature value of the battery unit.

9. the reference parameter values ​​include a first reference parameter value obtained from the reference battery unit at a reference temperature and a second reference parameter value obtained by interpolating the first reference parameter value; The method for operating a battery temperature estimation device according to claim 7 , wherein the second reference parameter value is a parameter value relating to a temperature different from the reference temperature.

10. 8. The method of claim 7, wherein the specified element is Rsei.

11. The method for operating a battery temperature estimation device according to claim 7 , wherein the EIS data is data acquired at a time when the SOC of the battery unit is at a specified SOC.

12. acquiring temperature data from the battery unit; The method for operating the battery temperature estimation device according to claim 7 , further comprising: comparing the temperature value with the temperature data and identifying whether or not the temperature data is abnormal.

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