Battery device, resistance state estimation method and program

Abstract

The battery device processor estimates the internal resistance of the battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open-circuit voltage of the battery, and a measured temperature of the battery, and estimates a resistance state of the battery based on the internal resistance of the battery at the reference temperature when the battery is in a beginning-of-life state and the estimated internal resistance at the reference temperature.

Description

Technical Field

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to and the benefit of Korean Patent Application No. 10-2020-0137478 filed in the Korean Intellectual Property Office on October 22, 2020, the entire contents of which are incorporated herein by reference.

[0003] The technology relates to a battery device and a method for estimating a resistance state. Background Art

[0004] An electric vehicle or hybrid vehicle is a vehicle that uses batteries as its primary power source, powered by a motor. Electric vehicles are being actively researched as an alternative to internal combustion vehicles, potentially addressing pollution and energy issues. Rechargeable batteries are used in a variety of external devices besides electric vehicles.

[0005] A battery consists of a positive electrode, a negative electrode, a separator interposed between the electrodes, and an electrolyte that undergoes electrochemical reactions with the active materials coated on the positive and negative electrodes. The capacity of a battery decreases with increasing charge / discharge cycles. This decrease in capacity can be due to degradation of the active materials coating the electrodes, negative reactions of the electrolyte, and a reduction in pores in the separator. As battery capacity decreases, the battery's resistance increases, and the amount of electrical energy dissipated as heat increases. Therefore, if the battery's capacity drops below a threshold, the battery's performance will significantly deteriorate and heat generation will increase, necessitating inspection or replacement of the battery.

[0006] In the field of battery technology, the degree of battery capacity degradation can be quantified using a factor called the state of health (SOH). SOH can be calculated in several ways, one of which is to quantify the increase in the resistance of the battery at the current time compared to the resistance at the beginning of life (BOL). For example, if the resistance of the battery has increased by 20% compared to the resistance at the BOL state, the SOH might be estimated to be 80%. By controlling the maximum current based on the SOH, the life of the battery can be extended. To achieve this, it is necessary to accurately detect the internal resistance of the battery and estimate the state of the internal resistance.

[0007] The resistance state (i.e., the degree of resistance degradation) can be estimated by quantifying the increase in resistance estimated under conditions including specific temperature and specific SOC, compared to the resistance in the battery's BOL state, based on previously measured resistance data. Furthermore, the estimated resistance state is applied to all conditions used to estimate output, assuming that the internal resistance degrades to the same level even at temperatures or SOCs different from the specific temperature or SOC. However, the battery's resistance may change with temperature. Therefore, if the estimated resistance at a specific temperature is applied to other temperatures, the result may differ from the actual resistance state. Summary of the Invention

[0008] Technical issues

[0009] Some embodiments may provide a battery device and a method for estimating a resistance state for accurately estimating an internal resistance and a resistance state of a battery.

[0010] Technical Solution

[0011] According to one embodiment, a battery device including a battery and a processor may be provided. The processor may estimate the internal resistance of the battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open-circuit voltage of the battery, and a measured temperature of the battery; and estimate the resistance state of the battery based on the internal resistance and a BOL resistance of the battery at the reference temperature when the battery is in a BOL state.

[0012] In some embodiments, the battery device may further include a memory configured to store a plurality of correction ratios corresponding to a plurality of temperatures. The processor may extract a correction ratio corresponding to the measured temperature from the plurality of correction ratios; and estimate the internal resistance at the reference temperature based on the measured voltage, the measured current, the open-circuit voltage, and the correction ratios.

[0013] In some embodiments, the correction ratio may be a value for converting the resistance at the measurement temperature to the resistance at the reference temperature.

[0014] In some implementations, the processor may estimate the internal resistance at the reference temperature based on the measured voltage, the open circuit voltage, and a current obtained by reflecting the correction ratio in the measured current.

[0015] In some embodiments, the processor can estimate the internal resistance at the reference temperature based on an adaptive filter that uses observation values ​​including the measured voltage and the open circuit voltage, estimated parameters including the internal resistance, and an observation matrix including the measured current and the correction ratio.

[0016] In some embodiments, the correction ratio can be reflected in the measured current in the observation matrix.

[0017] In some embodiments, the adaptive filter may include a recursive least squares (RLS) filter.

[0018] In some embodiments, the processor may estimate a state of charge of the battery and estimate the open circuit voltage based on the state of charge.

[0019] In some implementations, the processor can estimate the resistance state by quantifying an increase in the internal resistance at the reference temperature compared to the BOL resistance at the reference temperature.

[0020] According to another embodiment, a method for estimating a resistance state of a battery may be provided. The resistance state estimation method includes: estimating an internal resistance of the battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open-circuit voltage of the battery, and a measured temperature of the battery; and estimating the resistance state of the battery based on the internal resistance and a BOL resistance of the battery at the reference temperature when the battery is in a BOL state.

[0021] According to yet another embodiment of the present invention, a program configured to be executed by a processor of a battery device and stored in a recording medium may be provided. The program may cause the processor to: estimate the internal resistance of the battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open-circuit voltage of the battery, and a measured temperature of the battery; and estimate the resistance state of the battery based on the internal resistance and a BOL resistance of the battery at the reference temperature when the battery is in a BOL state.

[0022] Beneficial effects

[0023] According to some embodiments, the internal resistance and resistance state of a battery can be accurately estimated regardless of temperature variations. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a diagram showing a battery device according to one embodiment.

[0025] Figure 2 is a diagram for explaining resistance state estimation in a battery management system according to one embodiment.

[0026] Figure 3 is a flowchart illustrating a resistance state estimation method in a battery management system according to one embodiment.

[0027] Figure 4 : is a diagram showing one example of a correspondence relationship between temperature and correction ratio in a battery according to one embodiment.

[0028] Figure 5 is a diagram showing an equivalent circuit model of a battery according to one embodiment.

[0029] Figure 6 is a flow chart illustrating a method for estimating internal resistance in a battery management system according to one embodiment. DETAILED DESCRIPTION

[0030] In the following detailed description, only certain embodiments are shown and described by way of illustration only. As will be appreciated by those skilled in the art, the described embodiments may be modified in various ways, all without departing from the spirit or scope of the present invention. Accordingly, the drawings and description are to be regarded as illustrative rather than restrictive. Throughout the specification, like reference numerals denote like elements.

[0031] As used herein, the singular form shall also include the plural form unless an explicit expression such as "one" or "a" is used.

[0032] In the flowcharts described with reference to the drawings, the order of operations or steps may be changed, several operations or steps may be combined, a certain operation or step may be divided, and a certain operation or step may not be performed.

[0033] Figure 1 is a diagram showing a battery device according to one embodiment.

[0034] refer to Figure 1 The battery device 100 has a structure that can be electrically connected to an external device. When the external device is a load, the battery device 100 is discharged by operating the power supply to supply power to the load. When the external device is a charger, the battery device 100 is charged by receiving external power via the charger. The external device operating as a load can be, for example, an electronic device, a mobile device, or an energy storage system (ESS). The mobile device can be, for example, an electric vehicle, a hybrid vehicle, or a smart mobile device.

[0035] The battery device 100 includes a battery 110 , a voltage measurement circuit 120 , a temperature sensor 130 , a current sensor 140 , a processor 150 , and a memory 160 .

[0036] The battery 110 is a rechargeable battery. The battery 110 may be: a single battery cell; a battery module comprising a plurality of battery cells, or a plurality of modules connected in series or in parallel; a battery pack in which a plurality of battery modules are connected in series or in parallel; or a system in which a plurality of battery packs are connected in series or in parallel.

[0037] The voltage measurement circuit 120 measures the voltage of the battery 110. In some embodiments, the voltage measurement circuit 120 may measure the voltage of each battery cell.

[0038] The temperature sensor 130 measures the temperature of the battery 110. In some embodiments, the temperature sensor 130 may measure the temperature at a predetermined location of the battery 110. In some embodiments, a plurality of temperature sensors 130 may be provided to measure the temperature at a plurality of locations in the battery 110.

[0039] The current sensor 140 is connected to the positive terminal or the negative terminal of the battery 110 and measures the current of the battery 110 , ie, the charging current or the discharging current.

[0040] Processor 150 estimates the resistance state of battery 110 based on the voltage of battery 110 measured by voltage measurement circuit 120, the temperature of battery 110 measured by temperature sensor 130, and the current of battery 110 measured by current sensor 140. In some embodiments, processor 150 may refer to a table stored in memory 160 for estimating the resistance state of battery 110.

[0041] Memory 160 stores a table for estimating the resistance state of processor 150. In some embodiments, memory 160 may store instructions for the operation of processor 150. In some embodiments, memory 160 may be embedded in processor 150 or connected to processor 150 via a bus. In some embodiments, memory 160 storing the table may be a non-volatile memory.

[0042] In some embodiments, the processor 150 and the memory 160 may form a battery management system. In some embodiments, the battery management system may further include at least one of a voltage measurement circuit 120 , a temperature sensor 130 , and a current sensor 140 .

[0043] Figure 2 is a diagram for explaining resistance state estimation in a battery management system according to one embodiment, and Figure 3 is a flowchart illustrating a resistance state estimation method in a battery management system according to one embodiment. Figure 4 is a diagram showing one example of a correspondence relationship between temperature and correction ratio in a battery according to one embodiment, and Figure 5 is a diagram showing an equivalent circuit model of a battery according to one embodiment.

[0044] refer to Figure 2 and Figure 3 , the battery management system processor (e.g. Figure 1 150) uses the adaptive filter 210 to estimate the battery (eg, Figure 1110). The processor 150 may input the current I of the battery 110, the voltage V of the battery 110, the open circuit voltage OCV of the battery 110, and the temperature T of the battery 110 to the adaptive filter 210 at S310, and estimate the internal resistance converted at the reference temperature (i.e., normalized) using the adaptive filter 210 based on the input values ​​at S320. In some embodiments, the reference temperature may be room temperature (e.g., 25°C). In some embodiments, the current of the battery 110 may be a current sensor (e.g., Figure 1 140 in ). In some embodiments, the voltage of the battery 110 may be the voltage of a battery cell. In some embodiments, the voltage of the battery 110 may be an average battery cell voltage, and the average battery cell voltage may be the average value of the voltages of a plurality of battery cells. In some embodiments, the voltage of the battery 110 may be the sum of the voltages of a plurality of battery cells. The open circuit voltage of the battery 110 may be a value converted from the average state of charge of the battery 110. In some embodiments, the temperature of the battery 110 may be a value obtained by a temperature sensor (e.g., Figure 1 In some embodiments, the temperature of the battery 110 may be an average temperature that is an average of temperatures measured by a plurality of temperature sensors.

[0045] The processor 150 can estimate the internal resistance at the reference temperature based on the correction ratio using the adaptive filter 210. In some embodiments, the correction ratio is a value used to convert the resistance at the measured temperature to the resistance at the reference temperature, and can be defined as, for example, the ratio of the resistance at the current temperature to the converted resistance at the reference temperature as in Equation 1.

[0046] Equation 1

[0047]

[0048] In Equation 1, R0* is the resistance at a reference temperature, r(T) is the correction ratio at temperature T, and R0(T) is the resistance at temperature T.

[0049] In some embodiments, the correspondence between temperature and correction ratio can be stored as Figure 4 That is, a plurality of correction ratios corresponding to a plurality of temperatures may be stored. For example, the corresponding relationship may be stored in the form of a lookup table. In some embodiments, the memory of the battery management system (e.g., Figure 1 160) in can store the corresponding relationship. Figure 4 The correspondence between the temperature and the correction ratio shown in is one embodiment, and the value of the correction ratio according to the temperature can be defined, for example, by experiments. Figure 4 As shown in , at a reference temperature (e.g., 25°C), the correction ratio may be 1 and decrease as the temperature rises. Therefore, the resistance at a temperature lower than the reference temperature may be greater than the resistance at the reference temperature, and the resistance at a temperature higher than the reference temperature may be less than the resistance at the reference temperature.

[0050] refer to Figure 5 , the equivalent circuit model of the battery includes an open-circuit voltage source 510, a series resistor 520, and an RC parallel circuit.

[0051] The open circuit voltage source 510 simulates the open circuit voltage, which is the voltage between the positive and negative electrodes of an electrochemically stable battery. The open circuit voltage can be determined based on the state of charge (SOC) of the battery 110 and can have a nonlinear functional relationship with the SOC OCV=f(SOC). In some embodiments, the correspondence between the open circuit voltage and the SOC of the battery 110 can be stored. For example, the correspondence can be stored in the form of a lookup table. In some embodiments, the memory of the battery management system (e.g. Figure 1 The corresponding relationship can be stored in the memory 160. In other embodiments, the corresponding relationship between the open circuit voltage and SOC of the battery 110 can be stored by temperature. Therefore, the processor 150 can refer to the corresponding relationship stored in the memory 160 to determine the open circuit voltage related to the SOC.

[0052] In some embodiments, processor 150 may determine the SOC of battery 110 based on the voltage of battery 110, the current of battery 110, or the temperature of battery 110. Processor 150 may determine the SOC using any of various known methods, and the present invention is not limited to the method of determining the SOC.

[0053] Series resistor 520 simulates the internal resistance of battery 110, which represents the voltage drop inside battery 110 due to the current flowing through battery 110, and represents the instantaneous change in the terminal voltage of the battery due to the current flowing through battery 110. The RC parallel circuit simulates the instantaneous change in polarization voltage (i.e., overpotential) reflected in the battery terminal voltage, and includes resistor 531 and capacitor 532 connected in parallel.

[0054] In the equivalent circuit model, the battery terminal voltage V may be given as in Equation 2. In some embodiments, the battery terminal voltage V may be the voltage of a battery cell or an average battery cell voltage.

[0055] Equation 2

[0056]

[0057] In Equation 2, R0 is the resistance of the internal resistor (ohmic resistor) 520, R1 is the resistance of the resistor 531 of the RC parallel circuit, τ1 is the time constant of the RC parallel circuit, I is the current of the battery 110, and OCV is the open circuit voltage.

[0058] Reference again Figure 2 and Figure 3 In S330, the processor 150 calculates the resistance state based on the internal resistance of the battery 110 estimated by the adaptive filter 210 using the resistance state calculation module 220 and the beginning of life (BOL) resistance at the reference temperature. The BOL resistance may be the internal resistance of the battery when it is in the BOL state. The BOL resistance may change according to the temperature of the battery, and the processor 150 may store the BOL resistance at the reference temperature. In some embodiments, the processor 150 may store the BOL resistance at the reference temperature in a memory of the battery management system (e.g., Figure 1 160).

[0059] In some embodiments, the processor 150 may estimate the resistance state (e.g., the healthy resistance state (SOHR)) as a value obtained by subtracting the ratio of the internal resistance increase compared to the BOL resistance from 100% (as in Equation 3). Such a resistance state may be referred to as a resistance degraded state.

[0060] Equation 3

[0061]

[0062] In Equation 3, R0 is the estimated internal resistance of the battery, and R BOL is the BOL resistance at the reference temperature.

[0063] According to the above embodiment, the internal resistance converted at the reference temperature can be estimated by inputting the information measured from the battery into the adaptive filter 210. In addition, since the estimated internal resistance is compared with the BOL resistance at the reference temperature to determine the degree of estimated internal resistance degradation, the resistance state can be accurately estimated regardless of how the battery temperature changes.

[0064] Next, refer to Figure 6 An embodiment of a method for estimating internal resistance using the adaptive filter 210 is described. In some embodiments, a recursive least squares (RLS) filter may be used as the adaptive filter 210. Hereinafter, the adaptive filter 210 is described as an RLS filter.

[0065] Figure 6 is a flow chart illustrating a method for estimating internal resistance in a battery management system according to one embodiment.

[0066] The processor 150 converts the battery terminal voltage V in the equivalent circuit model based on the reference temperature to estimate the internal resistance converted at the reference temperature. In this case, Equation 2 can be converted into Equation 4.

[0067] Equation 4

[0068]

[0069] In Equation 4, R0* is the resistance to which the internal resistance is converted at the reference temperature, R1* is the resistance to which the resistance of the RC parallel circuit is converted at the reference temperature, and r is the correction ratio.

[0070] Equation 4 can be expressed as Equation 5.

[0071] Equation 5

[0072]

[0073] When Equation 5 is expressed as a matrix equation as Equation 6, the observation value (i.e., the system output y at time k representing the current time) k ) can be expressed as in Equation 7, the estimated parameters can be expressed as in Equation 8, and the observation matrix H at time k is k It can be expressed as in Equation 9. Therefore, the processor 150 at S610 converts the system output y measured at time k into k and the observation matrix H k Input to the adaptive filter 210.

[0074] Equation 6

[0075]

[0076] Equation 7

[0077] y k =V k -OCV k

[0078] Equation 8

[0079]

[0080] Equation 9

[0081]

[0082] In Equation 7 and Equation 9, V k is the battery voltage (e.g., average cell voltage) measured at time k, OCV k is the open circuit voltage estimated based on the SOC at time k, and I kis the current of the battery measured at time k (e.g., the current measured by the current sensor). As shown in Equation 9, the current I k The current obtained by reflecting the correction ratio r can be used to estimate the internal resistance of the conversion at the reference temperature.

[0083] The adaptive filter 210 calculates the gain K at S620. k In some embodiments, the adaptive filter 210 may calculate the gain K k To minimize a cost function that is determined based on the forgetting factor and the error between the observed value (i.e., the battery voltage measured at time k) and the battery voltage estimated based on Equation 6. In some embodiments, the cost function can be determined based on a least squares error weighted by the forgetting factor. For example, the adaptive filter 210 can calculate the gain K as in Equation 10 k .

[0084] Equation 10

[0085]

[0086] In Equation 10, P k-1 represents the covariance, and λ represents the forgetting factor. In some embodiments, the covariance P k-1 It can be the value updated at time k-1 (as in Equation 14).

[0087] The adaptive filter 210 estimates the system output at time k based on the estimated parameters at time k-1 at S630. The estimated system output can be given, for example, in Equation 11. In addition, the adaptive filter 210 calculates the actual system output y at S630. k The error between the estimated output at time k and the estimated output at time k. The error can be given as in Equation 12. Therefore, the adaptive filter 210 updates the estimated parameters at time k at S640 by reflecting the gain of the error. For example, the adaptive filter 210 can update the estimated parameters as in Equation 13.

[0088] Equation 11

[0089]

[0090] Equation 12

[0091]

[0092] Equation 13

[0093]

[0094] The adaptive filter 210 calculates the resistance R0* to which the internal resistance is converted at the reference temperature based on the updated estimated parameters at S650 .

[0095] Meanwhile, regarding the calculation of Equation 10 and Equation 13, the initial values ​​of the estimation parameters when k is 0 and the initial value P0 of the covariance may be determined in advance.

[0096] Next, the adaptive filter 210 updates the factor to be used at time k+1 at S660. In some embodiments, the adaptive filter 210 may update the covariance P to be used at time k+1. k For example, the adaptive filter 210 may update the covariance P as in Equation 14 k In some embodiments, the adaptive filter 210 may further update the forgetting factor λ. For example, the adaptive filter 210 may update the forgetting factor λ based on a previously calculated error.

[0097] Equation 14

[0098]

[0099] Through this process, the RLS filter estimates the resistance R0 converted to the internal resistance at the reference temperature at each time k, updates the factors (e.g., covariance, forgetting factor) to be used for the estimation, and provides the updated factors for the estimation at the next time k+1. Therefore, if the estimation of the internal resistance is not completed at S670, the adaptive filter 210 can continue the estimation at the next time at S680.

[0100] refer to Figure 6 The internal resistance estimation method described is an embodiment of using an RLS filter as the adaptive filter 210, but the present invention is not limited thereto.

[0101] According to the above embodiment, when the internal resistance is estimated by inputting information measured from the battery to adaptive filter 210, the internal resistance converted at the reference temperature can be estimated. Furthermore, since the resistance state is estimated by comparing the estimated internal resistance with the BOL resistance at the reference temperature, resistance changes due to temperature can be offset. In other words, the resistance state can be estimated based on the reference temperature regardless of the current battery temperature.

[0102] In some embodiments, a processor (e.g., Figure 1 150) can operate a program for executing the above-mentioned resistance state estimation method or internal resistance estimation method. The program for executing the resistance state estimation method or internal resistance estimation method can be loaded into a memory. The memory can be the same memory used to store the table (for example, Figure 1The program may be a separate memory (160) or a separate memory. The program may include instructions for causing the processor 150 to perform the resistance state estimation method or the internal resistance estimation method when loaded into the memory. That is, the processor may perform the resistance state estimation method or the internal resistance estimation method by executing the instructions of the program.

[0103] While the present invention has been described in conjunction with what are presently considered to be practical embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A battery device, comprising: Battery; as well as a memory configured to store a plurality of correction ratios corresponding to a plurality of temperatures, respectively; A processor configured to: estimating an internal resistance of the battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open circuit voltage of the battery, and a measured temperature of the battery; and estimating a resistance state of the battery based on the internal resistance and a BOL resistance of the battery at the reference temperature when the battery is in a beginning-of-life (BOL) state, Wherein, the processor is configured to: extracting a correction ratio corresponding to the measured temperature from the plurality of correction ratios; and estimating the internal resistance at the reference temperature based on the measured voltage, the measured current, the open circuit voltage, and the extracted correction ratio, The processor is configured to estimate the internal resistance at the reference temperature based on an adaptive filter using observation values ​​including the measured voltage and the open-circuit voltage, estimated parameters including the internal resistance, and an observation matrix including the measured current and the correction ratio.

2. The battery device according to claim 1, wherein The correction ratio is a value for converting the resistance at the measurement temperature into the resistance at the reference temperature.

3. The battery device according to claim 1, wherein The processor is configured to estimate the internal resistance at the reference temperature based on the measured voltage, the open circuit voltage, and a current obtained by reflecting the correction ratio in the measured current, and The correction ratio is reflected in the measurement current in the observation matrix.

4. The battery device according to claim 1, wherein The adaptive filter includes a recursive least squares RLS filter.

5. The battery device according to claim 1, wherein The processor is configured to estimate a state of charge of the battery and estimate the open circuit voltage based on the state of charge.

6. The battery device according to claim 1, wherein The processor is configured to estimate the resistance state by quantifying an increase in internal resistance at the reference temperature compared to a BOL resistance at the reference temperature.

7. A method for estimating the resistance state of a battery, the method comprising the steps of: estimating an internal resistance of the battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open circuit voltage of the battery, and a measured temperature of the battery; and estimating a resistance state of the battery based on the internal resistance and a BOL resistance of the battery at a reference temperature when the battery is in a beginning-of-life (BOL) state, The step of estimating the internal resistance comprises the following steps: extracting a correction ratio corresponding to the measured temperature from a plurality of correction ratios respectively corresponding to a plurality of temperatures; and estimating the internal resistance at the reference temperature based on the measured voltage, the measured current, the open circuit voltage, and the extracted correction ratio, and The step of estimating the internal resistance at the reference temperature comprises the following steps: The internal resistance at the reference temperature is estimated based on an adaptive filter using observation values ​​including the measured voltage and the open-circuit voltage, estimated parameters including the internal resistance, and an observation matrix including the measured current and the correction ratio.

8. The method according to claim 7, wherein: The correction ratio is a value for converting the resistance at the measurement temperature into the resistance at the reference temperature.

9. The method according to claim 7, wherein: The step of estimating the internal resistance includes estimating the internal resistance at the reference temperature based on the measured voltage, the open circuit voltage, and a current obtained by reflecting the correction ratio in the measured current.

10. The method according to claim 7, wherein: The step of estimating the internal resistance includes estimating the resistance state by quantifying an increase in the internal resistance at the reference temperature compared to the BOL resistance at the reference temperature.

11. A non-transitory storage medium storing a program, wherein when the program is executed by a processor of a battery device, the processor is caused to perform the following steps: estimating an internal resistance of the battery at a reference temperature based on a measured voltage of the battery, a measured current of the battery, an open circuit voltage of the battery, and a measured temperature of the battery; and estimating a resistance state of the battery based on the internal resistance and a BOL resistance of the battery at a reference temperature when the battery is in a beginning-of-life (BOL) state, in, The step of estimating the internal resistance comprises the following steps: extracting a correction ratio corresponding to the measured temperature from a plurality of correction ratios respectively corresponding to a plurality of temperatures; and estimating the internal resistance at the reference temperature based on the measured voltage, the measured current, the open circuit voltage, and the extracted correction ratio, and The step of estimating the internal resistance at the reference temperature comprises the following steps: The internal resistance at the reference temperature is estimated based on an adaptive filter using observation values ​​including the measured voltage and the open-circuit voltage, estimated parameters including the internal resistance, and an observation matrix including the measured current and the correction ratio.

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