Method for estimating state of health of lithium-sulfur battery

Abstract

To solve the problems in the prior art and provide a method for estimating a state of health (SoH) of a lithium-sulfur battery, capable of quickly and reliably estimating the state of health of the lithium-sulfur battery in a simple manner.SOLUTION: A method for estimating a state of health (SoH) of a lithium-sulfur battery includes the steps of: a) maintaining a target battery whose state of health is to be checked, in an idle state for 0.01 seconds or more in a fully charged state; b) measuring OCV(det) in a state in which the voltage drops during the idle state; c) obtaining ΔOCV by subtracting the OCV(det) from OCV(ini) measured in advance in the same way as in the steps a) and b) at the beginning of use of the target battery whose state of health is to be checked; and d) estimating the state of health (%) of the battery from the magnitude of the ΔOCV.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2021-0160919 dated November 22, 2021, and all contents disclosed in the documents of the relevant Korean patent application are incorporated herein by reference.

[0002] The present invention relates to a state of health estimation method for lithium-sulfur batteries. [Background technology]

[0003] Recently, the need for large-capacity batteries has been growing with the development of portable electronic devices, electric vehicles, and large-capacity power storage systems. Lithium-sulfur batteries are secondary batteries that use a sulfur-based material with a sulfur-sulfur bond (SS bond) as the positive electrode active material and lithium metal as the negative electrode active material. Sulfur, the main material for the positive electrode active material, has the advantages of being abundant, non-toxic, and having a low atomic weight.

[0004] The theoretical discharge capacity of the lithium-sulfur battery is 1672mAh / g-sulfur, and its theoretical energy density is 2,600Wh / kg, which is much higher than the theoretical energy density of other battery systems currently being researched, and it is therefore attracting attention as a battery with high energy density characteristics.

[0005] A typical lithium-sulfur battery includes an anode (negative electrode) formed of lithium metal or a lithium metal alloy, and a cathode (positive electrode) formed of elemental sulfur or other electroactive sulfur material.

[0006] The sulfur in the cathode of a lithium-sulfur battery is reduced in two stages during discharge. In the first stage, sulfur (e.g., elemental sulfur) is reduced to lithium polysulfides (Li2S8, Li2S6, Li2S5, Li2S4). These species are largely dissolved in the electrolyte. In the second stage, the lithium polysulfides are reduced to Li2S, which may be deposited on the surface of the anode. Conversely, during charge, Li2S is oxidized to lithium polysulfides (Li2S8, Li2S6, Li2S5, Li2S4), which are then oxidized to lithium and sulfur.

[0007] Like conventional batteries, lithium-sulfur batteries gradually deteriorate with repeated charging and discharging. A deteriorated battery's usable capacity is smaller than its initial usable capacity even when fully charged to its upper voltage limit. The ratio of the current usable capacity to the initial usable capacity can be expressed as its state of health.

[0008] Theoretically, the health condition can be calculated by the following formula:

[0009] SoH%=[C (det) / C (ini) ]X100 C (det) : Available capacity after degradation, C (ini) : Initial (before degradation) available capacity

[0010] Such battery state of health (SoH) information allows users to establish appropriate battery usage plans, thereby improving battery usage efficiency, reliability, and safety.

[0011] On the other hand, the above C (det) The SoH can be calculated by fully discharging a fully charged battery and measuring the charge amount. However, in actual battery usage, there are not many situations where a battery is fully charged and then fully discharged again, so estimating the SoH using this method has the disadvantage of being impractical.

[0012] Therefore, there is a need for a practical and reliable method for estimating the SoH. In particular, for lithium-sulfur batteries, which have chemical behavior different from other lithium-ion batteries, there is a need for an SoH estimation method that is suitable for these characteristics. [Prior art documents] [Patent documents]

[0013] [Patent Document 1] Japanese Patent Publication No. 2005-172784 Summary of the Invention [Problem to be solved by the invention]

[0014] The present invention has been devised to solve the above-mentioned problems of the prior art, and aims to provide a method for estimating the state of health (SoH) of a lithium-sulfur battery, which can quickly and reliably estimate the SoH of a lithium-sulfur battery in a simple manner.

[0015] Another object of the present invention is to provide a practical method for estimating the state of health of a lithium-sulfur battery. [Means for solving the problem]

[0016] In order to achieve the above object, the present invention provides As a way to check the deterioration state of lithium-sulfur batteries, 1. A method for estimating a state of health (SoH) of a battery, comprising: a) keeping the battery whose health status is to be checked in a fully charged state in a rest state for 0.01 seconds or more; b) When the voltage drop occurs during the rest state, the OCV (det) the measuring stage; c) The OCV measured in advance using the same method as a) and b) above at the beginning of use of the battery whose health condition is to be confirmed (ini) From the OCV (det) subtracting to obtain △OCV; and d) estimating the state of health (%) of the battery from the magnitude of the ΔOCV. [Effects of the Invention]

[0017] The method for estimating the state of health of a lithium-sulfur battery of the present invention provides a simple method for quickly and reliably estimating the state of health (SoH) of a lithium-sulfur battery.

[0018] In addition, a practical method for estimating the state of health of a lithium-sulfur battery is provided. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a graph showing voltage drops during a rest period after full charge of an initial lithium-sulfur battery and a deteriorated lithium-sulfur battery. [Figure 2] This graph shows the battery state of health (SoH (%)) data (obtained during each charge / discharge cycle of a lithium-sulfur battery) and β data obtained at a specific time point during the rest period after full charge. The y-axis shows SoH (%) and the x-axis shows β, and the data was fitted with a specific function. (β: OCV obtained by subtracting the OCV (det) measured at a specific time point during the rest period after full charge from the OCV (ini) measured at the time of charging the battery during the initial cycle and at a specific time point during the rest period after full charge.) [Figure 3] FIG. 1 is a flowchart illustrating a health condition estimation method according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0020] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to describing the present invention, detailed descriptions of related known functions and configurations will be omitted if it is determined that such descriptions may unnecessarily obscure the gist of the present invention.

[0021] The following description and drawings illustrate specific embodiments to enable those skilled in the art to easily implement the described apparatus and methods. Other embodiments may include other structural and logical variations. Individual components and functions may be generally selected and process orders may be varied unless expressly required. Portions and features of some embodiments may be included in or substituted for other embodiments.

[0022] When a lithium-sulfur battery is charged to its upper limit voltage and enters a rest period, a voltage drop occurs. This voltage drop is understood to be due to the self-discharge phenomenon caused by the polysulfide shuttle phenomenon, which is unique to lithium-sulfur batteries, as well as the elimination of charging overvoltage.

[0023] As shown in Figure 1, the voltage drop in a deteriorated battery becomes larger as the deterioration progresses compared to an initial battery. This phenomenon is caused by an increase in battery resistance due to deterioration of the electrodes and electrolyte, which increases charging overvoltage, and by a worsening polysulfide shuttle phenomenon due to deterioration of the electrolyte. Therefore, the voltage drop during the rest period after charging is considered to be data that provides information about battery deterioration.

[0024] Based on the above-mentioned research results, the present inventors have completed the present invention by utilizing the magnitude of voltage drop (ΔOCV) during the rest period after charging as an estimation parameter for the state of health (SoH) of the battery.

[0025] In the present invention, the state of health of the battery can also be expressed as the state of deterioration of the battery.

[0026] The present invention will be specifically described below.

[0027] The present invention provides a method for checking the degradation state of a lithium-sulfur battery, which includes: 1. A method for estimating a state of health (SoH) of a battery, comprising: a) keeping the battery whose health status is to be checked in a fully charged state in a rest state for 0.01 seconds or more; b) When the voltage drop occurs during the rest state, the OCV (det) the measuring stage; c) The OCV measured in advance using the same method as a) and b) above at the beginning of use of the battery whose health condition is to be confirmed (ini) From the OCV (det) subtracting to obtain △OCV; and d) estimating the state of health (%) of the battery from the magnitude of the ΔOCV.

[0028] In the present invention, OCV is an abbreviation for Open Circuit Voltage and means the open circuit voltage of a battery.

[0029] Figure 2 shows the state of health (SoH%) data (SoH%) obtained at each charge / discharge cycle of a lithium-sulfur battery, as well as β data obtained at a specific time point during a rest period after full charge. The graph plots SoH (%) on the y-axis and β on the x-axis.

[0030] As can be seen from FIG. 2, the ΔOCV value increases as the deterioration of the battery progresses, and the magnitude of the ΔOCV value has a negative correlation with SoH (%). Based on this relationship, it is possible to estimate the state of health of the battery from the ΔOCV.

[0031] In the present invention, the term "state of health (%)" refers to the State of Health (SoH) (%), and may also refer to the State of Deterioration (%). Also, in the present invention, the term "OCV" refers to the Open Circuit Voltage.

[0032] In one embodiment of the present invention, in step d), the estimation of the state of health (%) of the battery may be performed using a function that has a negative correlation between the state of health (%) of the lithium-sulfur battery and the magnitude of ΔOCV. The negative correlation function may be, for example, a function that expresses a relationship in which the SoH (%) value gradually decreases as ΔOCV increases in the relationship between SoH (%) and ΔOCV.

[0033] The negative correlation function can be expressed as SoH(%)=f(ΔOCV).

[0034] In one embodiment of the present invention, in step d), the estimation of the battery's state of health (%) may be performed by comparing the measured ΔOCV with a pre-prepared mapping reference of the battery's state of health (%) corresponding to the magnitude of ΔOCV.

[0035] In one embodiment of the present invention, the mapping reference of the battery state of health (%) corresponding to the magnitude of the ΔOCV may be data created by repeating full charge and full discharge of a battery manufactured in the same manner as the battery to be checked for the state of health, and by obtaining battery state of health (%) (SoH(%)) data according to the following Equation 1 at each charge / discharge cycle and ΔOCV data in the same manner as above, and then matching them one-to-one.

[0036] [Formula 1] SoH(%)=[C (det) / C (ini) ]X100 C (ini) : Available capacity before degradation, C (det) : Available capacity after degradation

[0037] As is well known in the art, the usable capacity can be determined by completely discharging a fully charged battery and measuring the amount of charge. Specifically, the usable capacity before and after degradation of a battery can be determined by repeatedly charging the battery with a current of 0.2 C until the battery voltage reaches 2.5 V, discharging with a current of 0.3 C until the battery voltage reaches 1.8 V, and measuring the amount of charge obtained during discharge. However, the method is not limited to this method, and the usable capacity can also be determined using methods well known in the art.

[0038] In one embodiment of the present invention, the mapping reference may be, for example, a graph in which the SoH (%) is plotted on the y-axis and the magnitude of ΔOCV is plotted on the x-axis, or a lookup table in which the SoH (%) and the corresponding magnitude of ΔOCV correspond one-to-one.

[0039] In one embodiment of the present invention, the resting state maintenance time in step a) may be 0.01 seconds or more, preferably 0.05 seconds or more, and more preferably 0.1 seconds or more. If the resting state maintenance time is less than 0.01 seconds, the difference in ΔOCV due to the deterioration state of the battery may be small, making it difficult to estimate the battery health (%) and reducing accuracy.

[0040] The resting state maintenance period may be 0.01 seconds to 3 minutes, preferably 0.01 seconds to 2 minutes, more preferably 0.01 seconds to 1 minute, and even more preferably 0.01 seconds to 30 seconds. If the resting state maintenance period exceeds 3 minutes, it takes too long to estimate the SoH(%), making it difficult to estimate the SoH(%) in real time, which is undesirable.

[0041] In one embodiment of the present invention, in step c), the "initial stage" may be from the first use of the battery to the time when the battery degradation rate is within 10%, preferably from the first use to the time when the battery degradation rate is within 5%, 3%, or 1%, more preferably at the time of first use.

[0042] In one embodiment of the present invention, in step d), the estimation of the battery state of health (%) from the magnitude of ΔOCV may be performed by: repeating full charge and full discharge of a battery manufactured identical to the battery to be checked for its health state; obtaining a scatter plot graph using battery state of health (%) data obtained at each cycle as the y-axis value and ΔOCV data obtained in the same manner as above as the x-axis value; applying the least squares method to the scatter plot graph to obtain a fitting function; and substituting the ΔOCV obtained from the battery to be checked for the fitting function.

[0043] In one embodiment of the present invention, the estimation of the battery state of health (%) from the magnitude of ΔOCV in step d) may be performed using the following Equation 2:

[0044]

number

[0045] In the above formula, OCV (ini) is the OCV measured after the battery is fully charged and kept in a rest state for 0.01 seconds or more at the beginning of use, The OCV (det) is the OCV measured after the battery to be checked for health status is fully charged and kept in a resting state for the same period as the resting state maintenance period, j is the highest dimension of the polynomial function, a i is the coefficient of the ith term, c is OCV (ini) is the corresponding SoH (%) value.

[0046] In the above, j may be 2 to 10, and may preferably be 3 to 5.

[0047] Although ai and c may vary depending on various design factors of the cell, they can be assumed to have the same values ​​for the same design. Therefore, if ai and c are determined through experiments on a manufactured battery, the battery's state of health (%) can be reliably estimated very easily by simply calculating the ΔOCV of the battery whose state of health is to be checked.

[0048] The ai is a coefficient of each degree term in a polynomial function having an arbitrarily set highest degree term j, which is obtained by fitting a scatter plot graph using the least squares method to a scatter plot of battery health (%) data obtained at each cycle of repeated full charge and full discharge for a battery manufactured identical to the battery to be verified, with the y-axis representing the battery health (%) data and the x-axis representing ΔOCV data obtained in the same manner as above. The least squares method is a method well known to those skilled in the art.

[0049] In the above, j is the adjustment coefficient after fitting (Adj.R 2 ) can be arbitrarily set in the range of 2 to 10, preferably 3 to 5, so that it has a value of 0.90 or more, preferably 0.95 or more, and more preferably 0.98 or more.

[0050] Equation 2 can also be expressed as Equation 3 below.

[0051]

number

[0052] The method for estimating the state of health of a lithium-sulfur battery according to the present invention is shown in the flowchart of Figure 3. As shown in Figure 3, the present invention provides a practical and reliable method for estimating the state of health of a battery.

[0053] Hereinafter, preferred examples will be presented to aid in understanding the present invention. However, the following examples are merely illustrative of the present invention, and it will be apparent to those skilled in the art that various changes and modifications are possible within the scope of the scope and technical idea of ​​the present invention. It is of course understood that such changes and modifications also fall within the scope of the appended claims.

[0054] Example 1: State of Health Estimation of Lithium-Sulfur Batteries An unused lithium-sulfur battery was repeatedly fully charged and fully discharged, and the battery state of health (SoH(%)) data and △OCV data were obtained for each charge / discharge cycle.

[0055] Specifically, the SoH (%) data for each cycle was calculated using the following formula 1:

[0056] [Formula 1] SoH(%)=[C (det) / C (ini) ]X100 C (ini) : Available capacity before degradation, C (det) : Available capacity after degradation

[0057] Specifically, the battery was charged by applying a current of 0.2 C until the battery voltage reached 2.5 V, and then discharged by a current of 0.3 C until the battery voltage reached 1.8 V, and the amount of charge obtained during discharge was measured. This cycle was repeated to determine the usable capacity before and after degradation of the battery, and the SoH (%) data was obtained.

[0058] The △OCV data is calculated by first fully charging the battery in one cycle, then resting it for 10 seconds, and measuring the OCV after the voltage has dropped. (ini) After that, after fully charging the battery in each cycle, keep it in a rest state for 10 seconds, and measure each OCV in the state where the voltage drops. (det) After determining the OCV (ini) From each OCV (det) The △OCV for each cycle was calculated by subtracting

[0059] The SoH (%) data obtained in each cycle was plotted on the y-axis and ΔOCV on the x-axis, resulting in a scatter plot graph as shown in Figure 2. From the graph in Figure 2, it can be seen that the magnitude of the ΔOCV value has a negative correlation with the SoH (%) value, and that this graph can be used as a mapping reference to check the health state of a battery by comparing it with the ΔOCV measured at a certain point in time.

[0060] Therefore, by using such a mapping reference, when determining the ΔOCV at a certain point in time for a battery whose health state is to be checked, the SoH (%) can be easily determined by comparing the ΔOCV value with the mapping reference.

[0061] Example 2: State of Health Estimation of Lithium-Sulfur Batteries The ΔOCV function for SoH (%) corresponding to the graph of FIG. 2 obtained in Example 1 was designed as follows.

[0062]

number

[0063] In the above formula OCV (ini) is the OCV measured after a 10-second rest period in one cycle, The OCV (det) is the OCV measured after the battery to be checked for health status is fully charged and left in a rest state for 10 seconds or more, j is the highest dimension of the polynomial function, a i is the coefficient of the ith term, c is OCV (ini) is the corresponding SoH (%) value.

[0064] In the function, ai is a polynomial function having an arbitrarily set highest order term j, which is fitted to the scatter plot of Example 1 by applying the least squares method, and is the coefficient of each order term. As shown in Figure 2, it was confirmed that the polynomial function fitted in this manner fits the scatter plot graph obtained in Example 1 with a very high adjusted coefficient of determination (Adj, R2 = 0.983).

[0065] Although ai and c may vary depending on various design factors of the cell, they can be assumed to have the same value for the same design.

[0066] Therefore, from the fitting results, it can be seen that when the function of Equation 2 is used, the SoH (%) can be calculated very easily by calculating the ΔOCV at a fixed point in time for the battery whose health state is to be checked.

Claims

1. 1. A method for estimating a battery state of health (SoH), comprising: a) maintaining a fully charged battery to be checked in a rest state for 0.01 seconds or more; b) OCV with voltage drop during the rest state （ｄｅｔ） measuring the c) The OCV measured in advance in the same manner as a) and b) above at the beginning of use of the battery whose health condition is to be confirmed. （ｉｎｉ） to the OCV （ｄｅｔ） subtracting ΔOCV; and d) estimating the state of health (%) of the battery from the magnitude of the ΔOCV.

2. 2. The method of claim 1, wherein in step d), the estimation of the battery's state of health (%) is performed using a function in which the state of health (%) of the lithium-sulfur battery is negatively correlated with the magnitude of ΔOCV.

3. 2. The method of claim 1, wherein in step d), the estimation of the battery's state of health (%) is performed by comparing the measured ΔOCV with a pre-prepared mapping reference of the battery's state of health (%) corresponding to the magnitude of the ΔOCV.

4. 4. The method of claim 3, wherein the mapping reference of the battery state of health (%) corresponding to the magnitude of the ΔOCV is data created by repeating full charge and full discharge of a battery manufactured in the same manner as the battery to be checked for the state of health, and by determining battery state of health (%) (SoH(%)) data according to the following Equation 1 for each charge / discharge cycle and ΔOCV data in the same manner as the SoH(%) data, and then matching these data one-to-one: [Formula 1] SoH(%)=[C （ｄｅｔ） / C （ｉｎｉ） ]X100 C （ｉｎｉ） : Available capacity before degradation, C （ｄｅｔ） : Available capacity after degradation

5. 5. The method of claim 4, wherein the mapping reference is a graph in which SoH (%) is plotted on a y-axis and ΔOCV magnitude is plotted on an x-axis, or a lookup table in which SoH (%) and the corresponding ΔOCV magnitude are in one-to-one correspondence.

6. 2. The method of claim 1, wherein in step c), the initial period is a time from the first use of the battery until a deterioration rate of the battery is within 10%.

7. 2. The method of claim 1, wherein in step d), the estimation of the battery's state of health (%) from the magnitude of the ΔOCV is performed by: generating a scatter plot graph using battery state of health (%) data obtained at each cycle of repeated full charge and full discharge of a battery manufactured identical to the battery to be checked for health status as a y-axis value and ΔOCV data obtained in the same manner as above as an x-axis value; applying a least squares method to the scatter plot graph to obtain a fitting function; and substituting the ΔOCV obtained from the battery to be checked for the fitting function.

8. 2. The method of claim 1, wherein the estimation of the state of health (%) of the battery from the magnitude of ΔOCV in step d) is performed using the following Equation 2: [Equation 1] In the above formula, OCV （ｉｎｉ） is the OCV measured after the battery is fully charged and kept in a rest state for 0.01 seconds or more at the beginning of use, The OCV （ｄｅｔ） is the OCV measured after the battery to be checked for health status is fully charged and kept in a resting state for the same period as the period during which the resting state is maintained, j is the highest dimension of the polynomial function, a ｉ is the coefficient of the i-th term, c is OCV （ｉｎｉ） is the SoH (%) value corresponding to

9. 2. The method of claim 1, wherein the resting state is maintained for 0.01 seconds to 3 minutes in step a).

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