Method for estimating the health status of lithium-sulfur batteries

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 priority based on Korean Patent Application No. 10-2021-0160919 dated November 22, 2021, and all contents disclosed in the documents of the said Korean Patent Application are included as part of this specification.

[0002] This invention relates to a method for estimating the health status of lithium-sulfur batteries. [Background technology]

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

[0004] The theoretical discharge capacity of lithium-sulfur batteries is 1672 mAh / g-sulfur, and their theoretical energy density is 2,600 Wh / kg. These values ​​are significantly higher than the theoretical energy densities of other battery systems currently under study, making them noteworthy as batteries 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 polysulfide (Li2S8, Li2S6, Li2S5, Li2S4). These species are largely dissolved in the electrolyte. In the second stage, the lithium polysulfide is reduced to Li2S, which can also be deposited on the surface of the anode. Conversely, during charging, Li2S is oxidized to lithium polysulfide (Li2S8, Li2S6, Li2S5, Li2S4), and then oxidized to lithium and sulfur.

[0007] Like conventional batteries, lithium-sulfur batteries gradually degrade with repeated charging and discharging. A degraded battery, even when fully charged to its upper voltage limit, has a smaller usable capacity compared to its initial usable capacity. The ratio of the current usable capacity to the initial usable capacity can be expressed as the State of Health.

[0008] The aforementioned health condition can theoretically be determined by the following formula.

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

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

[0011] On the other hand, C (det) While it is possible to determine SoH by completely discharging a fully charged battery and measuring the amount of charge, this method has the disadvantage of being impractical because situations where a battery is fully charged and then completely discharged again are not common in actual battery usage environments.

[0012] Therefore, the development of a method that can practically and reliably estimate the SoH is required. In particular, in the case of lithium-sulfur batteries, since they have different chemical behaviors from other lithium-ion batteries, the development of a SoH estimation method suitable for such characteristics is required.

Prior Art Documents

Patent Documents

[0013]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

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

[0015] Another object is to provide a method for estimating the state of health of a lithium-sulfur battery that can be practically used.

Means for Solving the Problems

[0016] To achieve the above object, the present invention as a method for confirming the deterioration state of a lithium-sulfur battery, a method for estimating the state of health (SoH, state of health) of a battery, comprising: a) maintaining the battery to be confirmed for the state of health in a rest state for 0.01 seconds or more in a fully charged state; b measuring the OCV (det) in a state where a voltage drop is made during the rest state; c) subtracting the OCV (ini) previously measured in the same manner as in a) and b) at the initial stage of use of the battery to be confirmed for the state of health from the OCV (det) to obtain ΔOCV; and d) A method for estimating the health status of a lithium-sulfur battery is provided, which includes the step of estimating the health status (%) of the battery from the magnitude of the ΔOCV. [Effects of the Invention]

[0017] The present invention provides a method for estimating the health status of a lithium-sulfur battery that can quickly and reliably estimate the health status (SoH) of a lithium-sulfur battery in a simple manner.

[0018] Furthermore, this invention provides a practical method for estimating the health status of lithium-sulfur batteries. [Brief explanation of the drawing]

[0019] [Figure 1] This graph shows the voltage drop during the rest period after full charge for both an early lithium-sulfur battery and a degraded lithium-sulfur battery. [Figure 2] This graph shows the health status (%) (SoH(%)) data obtained for each charge-discharge cycle and the β data obtained at a specific point during the rest period after full charge, while repeatedly fully charging and fully discharging a lithium-sulfur battery. The SoH(%) is plotted on the y axis and β on the x axis, and the obtained data is fitted with a specific function. (β: OCV obtained by subtracting the OCV (det) measured at a specific point during the rest period after full charge obtained for each cycle from the OCV (ini) measured during the initial charging cycle and at a specific point during the rest period after full charge.) [Figure 3] This diagram shows a flowchart illustrating the health status estimation method of the present invention. [Modes for carrying out the invention]

[0020] In the following, preferred embodiments of the present invention will be described in detail with reference to the attached drawings. Prior to describing the present invention, if it is determined that a specific description of related known functions and configurations would unnecessarily obscure the gist of the present invention, such description will be omitted.

[0021] The following description and drawings illustrate specific embodiments so that those skilled in the art can easily carry out the apparatus and method described. Other embodiments may include other structural and logical variations. Individual components and functions may be selected generally unless explicitly required, and the order of processes may vary. Parts and features of some embodiments may be included in or replaced by other embodiments.

[0022] When a lithium-sulfur battery is charged to its upper voltage limit and charging is complete, a voltage drop occurs when it enters a resting phase. This voltage drop is understood to be a self-discharge phenomenon caused by the shuttle effect of polysulfide, which is unique to lithium-sulfur batteries, along with the resolution of the overvoltage during charging.

[0023] As shown in Figure 1, compared to an initial battery, a degraded battery exhibits a greater voltage drop as degradation progresses. This phenomenon is caused by increased battery resistance due to electrode and electrolyte degradation, leading to increased charging overvoltage, and by worsened polysulfide shuttle effect due to electrolyte degradation. Therefore, the voltage drop during the post-charge pause period is considered to provide information about battery degradation.

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

[0025] In this invention, the health of a battery can also be expressed as the degradation state of the battery.

[0026] The present invention will be described in detail below.

[0027] The present invention provides a method for confirming the degradation state of a lithium-sulfur battery, A method for estimating the state of health (SoH) of a battery, a) A step of maintaining the battery to be confirmed for its health state in a fully charged state for 0.01 seconds or more in a rest state; b) A step of measuring the OCV (det) in a state where a voltage drop is made during the rest state; c) A step of obtaining ΔOCV by subtracting the OCV (ini) previously measured in the same manner as in a) and b) at the initial stage of use of the battery to be confirmed for its health state from the OCV (det) ; and d) A step of estimating the health state (%) of the battery from the magnitude of the ΔOCV; The present invention relates to a method for estimating the health state of a lithium-sulfur battery including the above steps.

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

[0029] FIG. 2 is a graph showing the health state (%) (SoH%) data of the battery obtained in each charge-discharge cycle and the β data obtained at a certain point during the rest period after full charge while repeatedly fully charging and completely discharging the lithium-sulfur battery, with SoH (%) on the y-axis and β on the x-axis.

[0030] As confirmed from FIG. 2, the ΔOCV value becomes larger as the deterioration of the battery progresses, and since the magnitude of the ΔOCV value has a negative correlation with SoH (%), it is possible to estimate the health state of the battery from such a relationship of the ΔOCV.

[0031] In the present invention, the health state (%) means State of Health (SoH) (%) and also indicates the deterioration state (%) as another meaning. Also, in the present invention, the OCV means Open Circuit Voltage.

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

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

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

[0035] In one embodiment of the present invention, the mapping reference for the battery health status (%) corresponding to the magnitude of ΔOCV may be data created by repeatedly fully charging and fully discharging a battery manufactured in the same manner as the battery whose health status is to be checked, obtaining battery health status (%) (SoH(%)) data according to the following formula 1 and ΔOCV data in the same manner as described above for each charge-discharge cycle, and then creating a one-to-one correspondence between these.

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

[0037] The available capacity can be obtained by completely discharging a fully charged battery and measuring the amount of charge, as is well known in this field. Specifically, for example, the battery can be charged by applying a current of magnitude 0.2C until the battery voltage reaches 2.5V, then discharged with a current of magnitude 0.3C until the battery voltage reaches 1.8V, and the amount of charge obtained during discharge can be measured. This cycle is repeated to determine the available capacity of the battery before and after degradation. However, this method is not limited to this method, and it can also be determined using methods well known in this field.

[0038] In one embodiment of the present invention, the mapping reference may be, for example, a graph showing SoH(%) on the y-axis and the magnitude of △OCV on the x-axis, or a lookup table that shows a one-to-one correspondence between SoH(%) and the corresponding magnitude of △OCV.

[0039] In one embodiment of the present invention, the resting 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 time is less than 0.01 seconds, the difference in magnitude of ΔOCV due to the degradation state of the battery may be small, making it difficult to estimate the battery's health status (%), and the accuracy may also decrease.

[0040] The aforementioned pause 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 pause period exceeds 3 minutes, it is undesirable because it takes too long to estimate SoH(%), making it difficult to estimate SoH(%) in real time.

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

[0042] In one embodiment of the present invention, the estimation of the battery health status (%) from the magnitude of △OCV in step d) can be performed by repeatedly fully charging and completely discharging a battery manufactured identically to the battery to be checked, using the battery health status (%) data obtained in each cycle as the y-axis value, and the △OCV data obtained in the same manner as described above as the x-axis value to obtain a scatter plot graph, applying the least squares method to the scatter plot graph to obtain a fitting function, and substituting the △OCV obtained from the battery to be checked into the fitting function.

[0043] In one embodiment of the present invention, the estimation of the battery health (%) from the magnitude of △OCV in step d) may be performed by the following formula 2:

[0044]

number

[0045] In the above formula, OCV (ini) This is the OCV measured after maintaining a fully charged state in a stagnant state for 0.01 seconds or more at the beginning of battery use. The aforementioned OCV (det) This is the OCV measured after fully charging the battery subject to health status check and maintaining it in a dormant state for the same period as the aforementioned dormant state maintenance period. j is the highest dimension of the polynomial function, a i is the coefficient of the i-th term, c is OCV (ini) This is the corresponding SoH(%) value.

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

[0047] As mentioned above, ai and c may vary depending on the various design elements of the cell, but it can be assumed that they have the same value for the same design. Therefore, if ai and c are secured through experiments on manufactured batteries, the health status (%) of the battery can be reliably estimated very easily simply by determining the ΔOCV of the battery to be checked.

[0048] The aforementioned 'ai' is a polynomial function with an arbitrarily set highest-order term 'j', which is fitted to a scatter plot graph plotted using the least squares method. The scatter plot graph plotted with the battery health status (%) data obtained in each cycle by repeatedly fully charging and completely discharging a battery identical to the battery under inspection as the y-axis value, and the ΔOCV data obtained using the same method as described above as the x-axis value, is then fitted to this graph. The least squares method is a method well known to engineers in this field.

[0049] In the above, j is the adjustment decision coefficient (Adj.R) after fitting. 2 The value can be arbitrarily set within the range of 2 to 10, preferably 3 to 5, such that the result is 0.90 or higher, preferably 0.95 or higher, and more preferably 0.98 or higher.

[0050] The aforementioned equation 2 can also be expressed as equation 3 below.

[0051]

number

[0052] The method for estimating the health status of a lithium-sulfur battery according to the present invention is shown in a flowchart in Figure 3. According to the present invention, as shown in Figure 3, the health status of a battery can be provided practically and reliably by a simple method.

[0053] The following are preferred embodiments to aid in understanding the present invention. However, these embodiments are merely illustrative of the present invention, and it will be obvious to those skilled in the art that various changes and modifications are possible within the scope of the present invention and the technical concept, and that such changes and modifications will naturally fall within the scope of the attached claims.

[0054] Example 1: Estimation of the health status of lithium-sulfur batteries Unused lithium-sulfur batteries were repeatedly fully charged and completely discharged, and battery health (%) (SoH (%)) data and △OCV data were obtained for each charge-discharge cycle.

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

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

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

[0058] Furthermore, the aforementioned ΔOCV data is obtained by first fully charging the battery in one cycle, then maintaining a 10-second idle state, and measuring the OCV while a voltage drop has occurred. (ini) After obtaining the result, fully charge the battery in each cycle, maintain a 10-second pause, and measure the OCV of each unit while the voltage has dropped. (det) After determining the OCV, (ini) From each OCV (det) We subtracted the coefficient to find the triangle OCV for each cycle.

[0059] When the SoH(%) data obtained in each cycle was plotted on the y-axis and △OCV on the x-axis, a scatter plot graph like the one in Figure 2 was obtained. From the graph in Figure 2, it can be seen that the magnitude of the △OCV value has a negative correlation with the SoH(%) value, and that such a graph can be used as a mapping reference to check the health status of a battery by comparing it with the △OCV 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 status is being checked, the State of Health (%) can be easily determined by comparing such ΔOCV values ​​with the aforementioned mapping reference.

[0061] Example 2: Estimation of the health status of lithium-sulfur batteries The △OCV function for SoH(%) corresponding to the graph in Figure 2 obtained in Example 1 was designed as follows.

[0062]

number

[0063] In the above formula OCV (ini) This is the OCV measured after maintaining a 10-second resting state in one cycle. The aforementioned OCV (det) This is the OCV measured after the battery subject to health status check has been fully charged and kept in a dormant state for 10 seconds or more. j is the highest dimension of the polynomial function, a i is the coefficient of the i-th term, c is OCV (ini) This is the corresponding SoH(%) value.

[0064] In the function described above, ai is the coefficient of each degree term in 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. It was confirmed that the polynomial function fitted in this way has a very high adjustment decision coefficient (Adj, R2 = 0.983) when fitted to the scatter plot graph obtained in Example 1, as shown in Figure 2.

[0065] As mentioned above, ai and c may vary depending on the various design elements of the cell, but it can be assumed that they have the same value for the same design.

[0066] Therefore, from the fitting results, it can be seen that when using the function of formula 2, SoH(%) can be calculated very easily by determining △OCV at a certain point in time for the battery whose health status is being checked.

Claims

1. A method for estimating the state of health (SoH) of a battery, a) A step in which the battery to be checked for health status is fully charged and kept in a dormant state for 0.01 seconds or more and 30 seconds or less; b) OCV in the state where a voltage drop occurs during the aforementioned idle state （ｄｅｔ） The stage of measurement; c) The OCV measured in advance using the same method as a) and b) above at the initial stage of use of the battery subject to health status check. （ｉｎｉ） from the OCV （ｄｅｔ） The step of subtracting to find △OCV; and d) A method for estimating the health status of a lithium-sulfur battery, comprising the step of estimating the health status (%) of the battery from the magnitude of the ΔOCV.

2. The method for estimating the health status of a lithium-sulfur battery according to claim 1, characterized in that, in step d) above, the estimation of the health status (%) of the battery is performed using a function in which the health status (%) of the lithium-sulfur battery has a negative correlation with the magnitude of △OCV.

3. The method for estimating the health status of a lithium-sulfur battery according to claim 1, characterized in that, in step d) above, the estimation of the battery health status (%) is performed by comparing the measured ΔOCV with a pre-prepared mapping reference of battery health status (%) corresponding to the magnitude of ΔOCV.

4. The method for estimating the health status of a lithium-sulfur battery according to claim 3 is characterized in that the mapping reference for the battery health status (%) corresponding to the magnitude of ΔOCV is obtained by repeatedly fully charging and fully discharging a battery manufactured in the same manner as the battery whose health status is to be checked, and obtaining battery health status (%) (SoH (%)) data using the following formula 1 and ΔOCV data in the same manner as described above, and then creating a one-to-one correspondence between these: [Formula 1] SoH(%)=[C （ｄｅｔ） / C （ｉｎｉ） ]X100 C （ｉｎｉ） : Usable capacity before degradation, C （ｄｅｔ） : Usable capacity after degradation

5. The method for estimating the health status of a lithium-sulfur battery according to claim 4, characterized in that the mapping reference is a graph showing SoH (%) on the y-axis and the magnitude of △OCV on the x-axis, or a lookup table that shows a one-to-one correspondence between SoH (%) and the corresponding magnitude of △OCV.

6. The method for estimating the health status of a lithium-sulfur battery according to claim 1, characterized in that, in step c) above, the initial use period is from the first use of the battery until the battery degradation rate is within 10%.

7. The method for estimating the health status of a lithium-sulfur battery according to claim 1, characterized in that, in step d) above, the estimation of the battery health status (%) from the magnitude of ΔOCV is performed by repeatedly fully charging and completely discharging a battery manufactured in the same manner as the battery to be checked for health status, using the battery health status (%) data obtained in each cycle as the y-axis value and the ΔOCV data obtained in the same manner as above as the x-axis value to obtain a scatter plot graph, 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 health status into the fitting function.

8. The method for estimating the health status of a lithium-sulfur battery according to claim 1, characterized in that the estimation of the battery health status (%) from the magnitude of △OCV in step d) is performed by the following formula 2: [Math 1] In the above formula 2, OCV （ｉｎｉ） This is the OCV measured after maintaining a fully charged state in a quiescent state for 0.01 seconds or more and 30 seconds or less at the beginning of battery use. The OCV （ｄｅｔ） is the OCV measured after maintaining the rest state for the same period as the maintenance period of the rest state with the battery to be checked for health fully charged. j is the highest dimension of the polynomial function, a ｉ is the coefficient of the i-th term, c is OCV （ｉｎｉ） This is the corresponding SoH (%) value.

Images