Secondary battery diagnostic device and method

Abstract

The secondary battery diagnostic device according to the present invention includes a thickness sensor that senses a change in the thickness of a secondary battery due to a change in the volume of the negative electrode active material while the secondary battery to which the negative electrode active material containing silicon or silicon oxide is applied is being charged or discharged, and a processor that estimates the capacity ratio, which is the ratio of the capacity provided by silicon or silicon oxide to the capacity provided by the negative electrode active material of the secondary battery, using the sensing result of the thickness sensor, and diagnoses the state of the secondary battery based on the capacity ratio.

Description

Technical Field

[0001] This application claims priority based on Korean Patent Application No. 10-2023-0104441 filed on August 9, 2023, and all the content disclosed in the specification and drawings of the application is incorporated herein.

[0002] The present invention relates to a secondary battery diagnosis device and method, and more particularly, to a secondary battery diagnosis device and method for diagnosing the state of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied.

Background Art

[0003] Generally, a secondary battery refers to a battery that can be repeatedly charged and discharged. Such secondary batteries include lithium secondary batteries using lithium ions, such as lithium ion batteries and lithium ion polymer batteries, and nickel cadmium batteries, nickel metal hydride batteries, nickel zinc batteries, and the like.

[0004] Recently, as secondary batteries are applied to devices that require a high output voltage and a large charge capacity, such as electric vehicles (EVs) and energy storage systems (ESSs), lithium secondary batteries, which have advantages such as almost no memory effect, low self-discharge rate, and high energy density compared to secondary batteries using nickel, are widely used.

[0005] As such secondary batteries are repeatedly charged and discharged, they cannot maintain their electrical capacity at the time of manufacture and gradually deteriorate. If the current state of such secondary batteries is not accurately diagnosed, it becomes difficult to measure and predict the state of charge (SoC), usable time, remaining life, replacement time, etc. of the secondary batteries, and as a result, unexpected damage is caused to the users of the secondary batteries.

[0006] However, conventional technology measures various electrical factors such as voltage, current, and resistance of a secondary battery and diagnoses its condition by substituting the measured values ​​into a complex formula. This has the drawbacks of being costly to diagnose a secondary battery and having a high probability of errors in the diagnostic results.

[0007] In particular, conventional technology has the problem of not being able to provide an efficient and accurate method for diagnosing the state of secondary batteries that use silicon or silicon oxide as the negative electrode active material to increase energy density. [Overview of the Initiative] [Problems that the invention aims to solve]

[0008] The present invention aims to provide a secondary battery diagnostic device and method for efficiently and accurately diagnosing the state of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied.

[0009] Another objective of the present invention is to provide a battery pack and vehicle that can efficiently and accurately diagnose the state of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied. [Means for solving the problem]

[0010] A secondary battery diagnostic device in one aspect of the present invention is a device for diagnosing the state of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied, and includes: a thickness sensor that senses a change in the thickness of the secondary battery due to a change in the volume of the negative electrode active material while the secondary battery is being charged or discharged; and a processor that estimates a capacity ratio, which is the ratio of the capacity provided by silicon or silicon oxide to the capacity of the secondary battery provided by the negative electrode active material, using the sensing result of the thickness sensor, and diagnoses the state of the secondary battery based on the capacity ratio.

[0011] In one embodiment, the thickness sensor may be configured to detect changes in the thickness of a secondary battery by measuring the distance from a predetermined position to the surface of the secondary battery.

[0012] In one embodiment, the processor may be configured to generate a first profile showing the thickness of the secondary battery, which changes over time or with changes in the charge state of the secondary battery, and a second profile showing the slope of the first profile, which changes over time or with changes in the charge state of the secondary battery, using the sensing results of the thickness sensor before estimating the capacity ratio, and to estimate the capacity ratio based on the second profile.

[0013] In one embodiment, the processor may be configured to divide the second profile into a plurality of sections, select a target section relating to silicon or silicon oxide from among the plurality of sections, and estimate the capacity ratio by comparing the total length of the plurality of sections with the length of the target section with respect to the first axial direction.

[0014] In one embodiment, the processor may be configured to divide the second profile into multiple intervals based on the change in the slope of the first profile shown in the second profile.

[0015] In one embodiment, the processor may be configured to select as a target interval an interval in which the charge state of the secondary battery is below a predetermined critical value, and in which the slope change progression of the first profile differs from that of the other intervals.

[0016] In one embodiment, the thickness sensor is configured to sense changes in the thickness of the secondary battery while the secondary battery is being discharged, and the processor may be configured to select as a target interval the interval in which the slope change of the first profile changes from a decreasing trend to an increasing trend among a plurality of intervals.

[0017] In one embodiment, the processor may be configured to diagnose the state of the secondary battery by further estimating the weight ratio, which is the ratio of the weight of silicon or silicon oxide to the total weight of the negative electrode active material, and comparing it with a reference capacity ratio and capacity ratio corresponding to the weight ratio.

[0018] In one embodiment, the processor may be configured to estimate the weight ratio before the number of charge or discharge cycles of the secondary battery exceeds a predetermined number.

[0019] In one embodiment, the processor may be configured to iteratively estimate the capacity ratio while the secondary battery undergoes a charge or discharge cycle, and to diagnose the state of the secondary battery based on the changes in the estimated capacity ratio.

[0020] In one embodiment, the negative electrode active material may include a mixture of silicon or silicon oxide and graphite.

[0021] In one embodiment, the secondary battery may consist of a pouch-type secondary battery.

[0022] Another embodiment of the present invention is a method for diagnosing a secondary battery, which diagnoses the state of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied, and includes: step A, during charging or discharging of the secondary battery, a thickness sensor senses a change in the thickness of the secondary battery due to a change in the volume of the negative electrode active material; step B, a processor uses the sensing result of the thickness sensor to estimate a capacity ratio, which is the ratio of the capacity provided by silicon or silicon oxide to the capacity of the secondary battery provided by the negative electrode active material; and step C, a processor diagnoses the state of the secondary battery based on the capacity ratio.

[0023] In one embodiment, step B may include: step B1, which uses the sensing results of a thickness sensor to generate a first profile showing the thickness of the secondary battery which changes over time or due to changes in the charge state of the secondary battery; step B2, which generates a second profile based on the first profile showing the slope of the first profile which changes over time or due to changes in the charge state of the secondary battery; and step B3, which estimates the capacity ratio based on the second profile.

[0024] In one embodiment, the B3 stage may include dividing the second profile into a plurality of sections and selecting a target section related to silicon or silicon oxide among the plurality of sections, and estimating a capacity ratio by comparing the total length of the plurality of sections with the length of the target section based on the first axial direction.

[0025] A battery pack according to still another aspect of the present invention may include the secondary battery diagnostic device described above.

[0026] A vehicle according to still another aspect of the present invention may include the secondary battery diagnostic device described above.

Advantages of the Invention

[0027] According to the present invention, while the secondary battery to which the negative electrode active material containing silicon or silicon oxide is applied is being charged or discharged, the thickness sensor senses the thickness change of the secondary battery due to the volume change of the negative electrode active material, and the processor uses the sensing result of the thickness sensor regarding the thickness change of the secondary battery to estimate the capacity ratio, which is the ratio of the electrical capacity provided by silicon oxide among the electrical capacities provided by the negative electrode active material of the secondary battery, and diagnoses the state of the secondary battery based on such a capacity ratio, thereby efficiently and accurately diagnosing the state of the secondary battery to which the negative electrode active material containing silicon or silicon oxide is applied.

[0028] Further, before estimating the capacity ratio, the processor sequentially generates a first profile indicating the thickness of the secondary battery that changes with the passage of time or the change in the charge state of the secondary battery using the sensing result of the thickness sensor, and a second profile indicating the slope of the first profile that changes with the passage of time or the change in the charge state of the secondary battery, and diagnoses the state of the secondary battery in a simplified manner regardless of the electrical factors of the secondary battery by estimating the capacity ratio based on such a second profile.

[0029] Furthermore, the processor can reduce the amount of computation required to diagnose the state of the secondary battery by dividing the second profile into multiple sections, selecting a target section from among the multiple sections that exhibits the intrinsic characteristics of silicon or silicon oxide, and estimating the capacity ratio by comparing the total length of the multiple sections with the length of the target section. As a result, the diagnostic speed for the secondary battery can be improved.

[0030] Furthermore, the processor estimates the weight ratio, which is the ratio of the weight of silicon or silicon oxide to the total weight of the negative electrode active material. By comparing the estimated weight ratio with a reference capacity ratio and capacity ratio, the state of the secondary battery can be diagnosed even when the weight ratio of silicon or silicon oxide contained in the negative electrode active material of the target secondary battery is unknown.

[0031] Furthermore, by configuring the thickness sensor that detects changes in the thickness of the secondary battery to measure the distance from a predetermined position to the surface of the secondary battery and detect the change in the thickness of the secondary battery, it is possible not only to detect the change in thickness of each secondary battery, but also to consider multiple secondary batteries stacked in the thickness direction as a single secondary battery module and detect the change in the total thickness of the secondary battery module. In other words, the secondary battery diagnostic device according to the present invention is included in a battery pack or vehicle having multiple secondary batteries and can diagnose the state of multiple secondary batteries on a secondary battery module basis.

[0032] Furthermore, anyone with ordinary skill in the art to which the present invention pertains will obviously understand from the following description that other technical problems not mentioned by the various embodiments of the present invention can be solved. [Brief explanation of the drawing]

[0033] [Figure 1] This is a block diagram showing a secondary battery diagnostic device according to one embodiment of the present invention. [Figure 2] This is a disassembled perspective view showing an example of a rechargeable battery. [Figure 3]Figure 2 is a front view of the secondary battery. [Figure 4] This is a profile showing the change in thickness of a secondary battery during charging and discharging. [Figure 5] This figure shows the first and second profiles of a secondary battery in which a silicon oxide-free negative electrode active material is used. [Figure 6] This figure shows the first and second profiles of a primary secondary battery to which a negative electrode active material containing silicon oxide at a weight ratio of 3% is applied. [Figure 7] This figure shows the first and second profiles of a secondary battery to which a negative electrode active material containing silicon oxide at a weight ratio of 5% is applied. [Figure 8] This figure shows the first and second profiles of a third-generation secondary battery to which a negative electrode active material containing silicon oxide at a weight ratio of 10% is applied. [Figure 9] This graph shows the change in thickness of a secondary battery during charging and discharging, categorized by the number of charge-discharge cycles. [Figure 10] This figure shows the second profile obtained by differentiating the thickness of a secondary battery during discharge with respect to time. [Figure 11] This figure shows the second profile, obtained by differentiating the thickness of a secondary battery during discharge with respect to time, for different numbers of discharge cycles of the secondary battery. [Figure 12] This is a flowchart illustrating a diagnostic method for a secondary battery according to one embodiment of the present invention. [Figure 13] This is a flowchart illustrating the process of estimating the capacity ratio of a secondary battery diagnostic method according to one embodiment of the present invention. [Figure 14] This diagram shows a vehicle according to one embodiment of the present invention. [Modes for carrying out the invention]

[0034] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings. Prior to this, terms and words used in this specification and in the claims should not be interpreted in a manner limited to their usual or dictionary meanings, but rather in a manner appropriate to the technical idea of ​​the present invention, in accordance with the principle that the inventor himself may appropriately define the concept of terms in order to best describe the invention. Accordingly, it should be understood that the embodiments and configurations shown in the drawings described herein are merely the most preferred embodiments of the present invention and do not represent the entirety of the technical idea of ​​the present invention, and that there may be a variety of equivalents and modifications that can be substituted thereat the time of this application.

[0035] Figure 1 is a block diagram showing a secondary battery diagnostic device 100 according to one embodiment of the present invention.

[0036] As shown in Figure 1, a secondary battery diagnostic device 100 according to one embodiment of the present invention is configured to diagnose the condition of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied. For this purpose, the secondary battery diagnostic device 100 includes a thickness sensor 110 and a processor 120.

[0037] The thickness sensor 110 is configured to sense changes in the thickness of the secondary battery due to changes in the volume of the negative electrode active material applied to the secondary battery while the secondary battery is being charged or discharged.

[0038] The processor 120 is configured to estimate the capacity ratio of silicon or silicon oxide contained in the negative electrode active material using the sensing results of the thickness sensor 110, and to diagnose the state of the secondary battery based on the capacity ratio. Here, the capacity ratio means the ratio of the capacity provided by silicon or silicon oxide to the capacity of the secondary battery provided by the negative electrode active material.

[0039] In one embodiment, the thickness sensor 110 may be configured to measure the distance from a predetermined position to the surface of the secondary battery and detect changes in the thickness of the secondary battery. In this case, the thickness sensor 110 may consist of a contact sensor such as a micrometer, or a non-contact sensor such as a displacement sensor using a laser or light.

[0040] In one embodiment, the secondary battery diagnostic device 100 may further include a memory 130. In this case, the memory 130 may be configured to transmit pre-stored data to the processor 120 or to store data transmitted from the processor 120.

[0041] For example, the memory 130 may be configured to store data relating to a reference capacity ratio that should be provided by the silicon or silicon oxide contained in the negative electrode active material of a normal secondary battery. In this case, the memory 130 may store data relating to the reference capacity ratio for each weight ratio of silicon or silicon oxide contained in the negative electrode active material. The memory 130 may also be configured to further store data relating to the capacity ratio of silicon or silicon oxide estimated by the processor 120, and data relating to the diagnostic results of the secondary battery, etc.

[0042] Such memory 130 may include at least one of the following: RAM (random access memory), SRAM (static random access memory), ROM (read-only memory), EEPROM (electrically erasable programmable read-only memory), PROM (programmable read-only memory), flash® memory, hard disk, SSD (Solid State Disk), and SDD (Solid Disk Drive).

[0043] In one embodiment, the secondary battery diagnostic device 100 may further include an output device 140. In this case, the output device 140 may be configured to output data and information through visual, auditory, or audiovisual means. For this purpose, the output device 140 may selectively include a visual display device such as a display or light-emitting diode and an acoustic device such as a speaker.

[0044] For example, if the diagnostic results for the secondary battery indicate that the secondary battery is in a poor condition, the processor 120 may control the output device 140 to output a predetermined alarm.

[0045] Figure 2 shows an exploded perspective view of an example of a secondary battery 200.

[0046] As shown in Figure 2, the secondary battery 200 may include an electrode assembly 222 in which a positive electrode and a negative electrode are stacked on top of each other with a separator in between, and a case 228 that houses such an electrode assembly 222 together with an electrolyte material in an internal space S1.

[0047] The secondary battery 200 may further include electrode leads 224 electrically connected to the electrode assembly 222, and sealing tape 226 that seals around such electrode leads 224.

[0048] The case 228 of the secondary battery 200 may include a first case portion 228a and a second case portion 228b that are coupled together to form an internal space S1. The case 228 can be sealed by hermetically coupling the edges of the first case portion 228a and the second case portion 228b with respect to each other, with the electrode assembly 222 housed in its internal space S1.

[0049] The positive electrode forming the electrode assembly 222 of such a secondary battery 200 may include a positive electrode substrate made of an aluminum-containing material and a positive electrode active material coated on the positive electrode substrate. The positive electrode active material may include a lithium-based oxide. Such a positive electrode active material may be coated on the positive electrode substrate together with a conductive material, a binder, etc.

[0050] The negative electrode of the electrode assembly 222 may include a negative electrode substrate made of a copper-containing material and a negative electrode active material coated on the negative electrode substrate. The negative electrode active material may be silicon (Si) or silicon oxide (SiO x The negative electrode active material may include a silicon-based material such as ) and graphite. That is, the negative electrode active material may include a mixture in which the silicon-based material and graphite are mixed in a predetermined weight ratio. Such a negative electrode active material can be applied to a negative electrode substrate together with a conductive material, a binder, etc.

[0051] Thus, by including silicon or silicon oxide in the negative electrode active material of a secondary battery, the electrical capacity provided by the same weight of negative electrode active material can be increased, and as a result, the energy density of the secondary battery can be increased.

[0052] On the other hand, silicon (Si) or silicon oxide (SiO x Silicon-based materials such as ) have unique properties compared to graphite, which is mixed with silicon-based materials, including a higher reaction potential and a larger volume change due to electrochemical reactions.

[0053] Therefore, the secondary battery diagnostic device 100 according to the present invention can diagnose the condition of a secondary battery, such as its degradation state, the rate of capacity loss, and its remaining lifespan, by using the inherent properties of silicon-based materials.

[0054] Figure 3 is a front view of the secondary battery 200 shown in Figure 2.

[0055] As shown in Figure 3, the manufactured secondary battery 200 may have a predetermined thickness TH. In this case, the thickness TH of the secondary battery 200 may correspond to the thickness of the electrode assembly housed inside the secondary battery 200.

[0056] The thickness TH of such a secondary battery 200 changes along with the volume change of the negative electrode active material that occurs during charging or discharging of the secondary battery 200.

[0057] The secondary battery diagnostic device 100 according to the present invention can detect such changes in the thickness of a secondary battery and diagnose the state of the secondary battery.

[0058] Furthermore, the secondary battery to be diagnosed by the secondary battery diagnostic device 100 according to the present invention can be configured in various forms in which the thickness in a specific direction changes due to a change in the volume of the negative electrode active material during charging or discharging.

[0059] For example, as shown in Figures 2 and 3, the secondary battery to be diagnosed by the secondary battery diagnostic device 100 according to the present invention may be configured as a pouch-type secondary battery. Depending on the embodiment, the secondary battery to be diagnosed by the secondary battery diagnostic device 100 according to the present invention may also be configured as another type of secondary battery in which the thickness of a specific part changes due to a change in the volume of the negative electrode active material, such as a prismatic secondary battery or a cylindrical secondary battery.

[0060] Figure 4 shows a profile illustrating the change in thickness during charging and discharging of a secondary battery.

[0061] In Figure 4, the horizontal axis represents the elapsed time after the start of the charge-discharge cycle, and the vertical axis represents the ratio of the change in surface position to the original thickness of the secondary battery.

[0062] As shown in Figure 4, the change in thickness during charging and discharging of a secondary battery can vary depending on the weight ratio of silicon or silicon oxide contained in the negative electrode active material of the secondary battery. Here, the weight ratio refers to the proportion of the weight of silicon or silicon oxide to the total weight of the negative electrode active material.

[0063] In other words, during charging, resting, and discharging, a secondary battery containing SiO, a type of silicon oxide, as the negative electrode active material exhibits a larger volume change than a secondary battery that does not contain SiO.

[0064] Furthermore, among secondary batteries containing silicon oxide as the negative electrode active material, those containing a relatively large weight ratio (10%) of silicon oxide show a larger volume change than those containing a relatively small weight ratio (3% or 5%) of silicon oxide.

[0065] Figure 5 shows the first profile TH and the second profile dTH / dt of a secondary battery using a silicon oxide-free negative electrode active material during discharge.

[0066] In Figure 5, the horizontal axis represents the elapsed time after the start of the discharge cycle, the left vertical axis represents the ratio of the surface position change value to the original thickness value of the secondary battery, and the right vertical axis represents the slope of the first profile TH.

[0067] Furthermore, the first profile TH represents the thickness of a secondary battery that has been subjected to a discharge cycle in which a negative electrode active material containing 100% graphite by weight is applied, and this thickness changes over time or with changes in the charge state of the secondary battery. The second profile dTH / dt represents the slope of the first profile TH, which changes over time or with changes in the charge state of the secondary battery. In this case, the second profile dTH / dt can be obtained by differentiating the first profile TH with respect to time t.

[0068] As shown in Figure 5, the first profile TH of the secondary battery indicates that the thickness of the secondary battery gradually decreases during discharge.

[0069] Furthermore, the second profile dTH / dt of the secondary battery shows that the slope of the first profile TH gradually decreases during discharge.

[0070] In other words, the second profile dTH / dt can be divided into multiple intervals a, b, and c. In this case, the slope may increase or decrease within each interval, but as we progress from the first interval a, which is the initial stage of discharge, to the third interval c, which is the final stage of discharge, the slope of each interval gradually decreases.

[0071] Figure 6 shows the first profile TH1 and the second profile dTH1 / dt of a first secondary battery to which a negative electrode active material containing silicon oxide at a weight ratio of 3% is applied.

[0072] In Figure 6, the horizontal axis represents the elapsed time after the start of the discharge cycle, the left vertical axis represents the ratio of the surface position change value to the original thickness value of the first secondary battery, and the right vertical axis represents the slope of the first profile TH1. Depending on the embodiment, the horizontal axis may represent the SoC (State of Charge) of the first secondary battery.

[0073] As shown in Figure 6, the negative electrode active material of the first secondary battery may include silicon or a mixture of silicon oxide and graphite.

[0074] Furthermore, the first profile TH1 of the primary secondary battery to which the negative electrode active material containing graphite and SiO in weight ratios of 97% and 3%, respectively, is applied shows the thickness of the primary secondary battery, which changes over time or with changes in the charge state of the primary secondary battery during the discharge cycle of the primary secondary battery.

[0075] Furthermore, the second profile dTH1 / dt of the first secondary battery represents the slope of the first profile TH1, which changes with the passage of time or the change in the charge state of the first secondary battery. In this case, the second profile dTH1 / dt can be obtained by differentiating the first profile TH1 with respect to time t.

[0076] The first profile TH1 of the first secondary battery shows that the thickness of the first secondary battery gradually decreases during the discharge of the first secondary battery.

[0077] However, the second profile dTH1 / dt of the primary secondary battery shows that the slope of the first profile TH1 gradually decreases during the discharge of the primary secondary battery, and then increases further at a specific point in time.

[0078] In other words, the second profile dTH1 / dt can be divided into multiple sections a1, b1, c1, and d1. In this case, the slope of each section gradually decreases as the discharge progresses from the first section a1, which is the initial stage of discharge, to the second section b1 and third section c1, which are the middle stages of discharge. However, in the fourth section d1, which is the final stage of discharge, the slope changes to an increasing trend.

[0079] This phenomenon is due to the inherent properties of silicon or silicon oxide, which act when the State of Charge (SoC) of a secondary battery is relatively low, because the reaction potential of silicon or silicon oxide is relatively higher than that of graphite.

[0080] Therefore, the secondary battery diagnostic device 100 according to the present invention can diagnose the condition of a secondary battery, such as its degradation attitude, the rate of capacity loss, and its remaining lifespan, by using the unique properties of silicon or silicon oxide.

[0081] In other words, the processor 120 of the secondary battery diagnostic device 100 according to one embodiment of the present invention can estimate the capacity ratio of silicon or silicon oxide using the sensing result of a thickness sensor 110 that senses the change in thickness of a secondary battery during charging or discharging, and diagnose the state of the secondary battery based on such a capacity ratio.

[0082] As mentioned above, the capacity ratio refers to the ratio of the capacity provided by silicon or silicon oxide to the capacity provided by the negative electrode active material of the secondary battery.

[0083] For example, the thickness sensor 110 can detect changes in the thickness of the first secondary battery while the first secondary battery is being discharged.

[0084] Furthermore, the processor 120 uses the sensing results from the thickness sensor 110 to generate a first profile TH1, which shows the thickness of the first secondary battery that changes over time or with changes in the charge state, as shown in Figure 6, and a second profile dTH1 / dt, which shows the slope of the first profile TH1 that changes over time or with changes in the charge state of the first secondary battery. Based on the second profile dTH1 / dt, the processor 120 can estimate the capacity ratio of silicon oxide (SiO).

[0085] Specifically, the processor 120 divides the second profile dTH1 / dt into multiple sections a1, b1, c1, and d1, and can select a target section relating to silicon or silicon oxide from among these multiple sections a1, b1, c1, and d1.

[0086] In this case, the processor 120 can divide the second profile dTH1 / dt into multiple intervals a1, b1, c1, and d1 based on the change in the slope of the first profile TH1 shown in the second profile dTH1 / dt. In Figure 6, the second profile dTH1 / dt is divided into four intervals, but it can also be divided into two intervals. That is, the second profile dTH1 / dt can be divided into a first interval a1, b1, and c1 where the change in the slope of the first profile TH1 is decreasing, and a second interval d1 where it is increasing.

[0087] Furthermore, the processor 120 may select as a target interval one of several intervals a1, b1, c1, and d1 in which the charge state of the first secondary battery is below a predetermined critical value, and in which the slope change progression of the first profile TH1 differs from that of the other intervals.

[0088] For example, while the first secondary battery is being discharged, if the thickness sensor 110 detects a change in the thickness of the first secondary battery, the processor 120 may select as the target interval the interval d1 in which the slope change of the first profile TH1 changes from a decreasing trend to an increasing trend, from among a plurality of intervals a1, b1, c1, and d1.

[0089] In this case, the processor 120 may select as the target interval the fourth interval d1 is in which the SoC of the first secondary battery is in the range of 50% or less among the first interval a1, second interval b1, third interval c1, and fourth interval d1, and which, unlike the first interval a1, second interval b1, and third interval c1, shows an increasing trend in the slope change of the first profile TH1.

[0090] Thus, the reason why the target interval is selected within a range where the charge state of the secondary battery is below a predetermined critical value is that, in the case of secondary batteries using nickel as the cathode material, there is an interval in which the slope of the first profile TH1 temporarily increases even at the end of charging or the beginning of discharge when the SoC is high, while silicon or silicon oxide acts at the beginning of charging or the end of discharge when the SoC of the secondary battery is relatively low.

[0091] As described above, once a target interval is selected, the processor 120 can estimate the capacity ratio of silicon or silicon oxide by comparing the total length L1 of multiple intervals a1, b1, c1, and d1 with the length L1' of the target interval, using the first axis (horizontal axis) direction, which indicates time or charge state of the SoC, as a reference.

[0092] For example, the volume ratio can be calculated using Equation 1.

[0093] CR=k(L t / L p ) × 100 [%] (Formula 1)

[0094] In formula 1, CR is the volume ratio of silicon or silicon oxide, L p This is the total length of the second profile, L tis the length of the target interval, and k is a predetermined proportionality constant. Therefore, in Figure 6, the SiO volume ratio CR1 can be calculated by k(L1' / L1) × 100 [%].

[0095] Once the capacity ratio is estimated in this way, the processor 120 can use the estimated capacity ratio to diagnose the state of the primary secondary battery. For example, the processor 120 can diagnose the state of the primary secondary battery by comparing the estimated capacity ratio with a reference capacity ratio of silicon or silicon oxide previously obtained from a normal secondary battery.

[0096] In one embodiment, the secondary battery diagnostic device 100 according to the present invention may be configured to pre-store reference capacity ratio information of the secondary battery to be diagnosed in the memory 130. The reference capacity ratio information may include information indicating the reference capacity ratio corresponding to a predetermined number of charge cycles or predetermined number of discharge cycles for the secondary battery to be diagnosed. In this case, the processor 120 can diagnose the state of the first secondary battery by comparing the capacity ratio estimated for the first secondary battery with the reference capacity ratio of the first secondary battery pre-stored in the memory 130.

[0097] In another embodiment, the processor 120 may be configured to diagnose the state of the secondary battery by further estimating the weight ratio, which is the ratio of the weight of silicon or silicon oxide to the total weight of the negative electrode active material, before diagnosing the state of the secondary battery to be diagnosed, and by comparing the estimated capacity ratio with a reference capacity ratio corresponding to the weight ratio.

[0098] In this case, the processor 120 can estimate the weight ratio before the number of charge or discharge cycles of the secondary battery being diagnosed exceeds a predetermined number.

[0099] For example, the processor 120 may estimate the silicon oxide capacity ratio after the completion of a charge cycle or discharge cycle that occurred before degradation of the secondary battery being diagnosed occurred, and estimate the silicon oxide weight ratio corresponding to the estimated capacity ratio.

[0100] Table 1 shows the volume ratios corresponding to the weight ratio of SiO contained in the negative electrode active material.

[0101] [Table 1]

[0102] As shown in Table 1, the capacity ratio of silicon oxide contained in the negative electrode active material is high compared to its weight ratio. Therefore, including silicon or silicon oxide in the negative electrode active material of a secondary battery can improve the energy density of the secondary battery. Thus, since there is a correlation between the weight ratio of silicon or silicon oxide and the capacity ratio, if one of the two is estimated, it is possible to estimate the other.

[0103] Therefore, the processor 120 can estimate the capacity ratio of silicon or silicon oxide contained in the negative electrode active material of the secondary battery under diagnosis during the initial period of use, and estimate the weight ratio of silicon or silicon oxide from the estimated capacity ratio.

[0104] Subsequently, the processor 120 may acquire reference capacity ratio information corresponding to the estimated weight ratio from the reference capacity ratio information for each weight ratio that has been previously stored in the memory 130.

[0105] Subsequently, the processor 120 can diagnose the state of the secondary battery by comparing the acquired reference capacity ratio information with the silicon or silicon oxide capacity ratio that is iteratively estimated for the secondary battery under diagnosis.

[0106] Figure 7 shows the first and second profiles of a secondary battery to which a negative electrode active material containing silicon oxide at a weight ratio of 5% is applied.

[0107] In Figure 7, the horizontal axis represents the elapsed time after the start of the discharge cycle, the left vertical axis represents the ratio of the surface position change value to the original thickness value of the secondary battery, and the right vertical axis represents the slope of the first profile TH2. Depending on the embodiment, the horizontal axis may represent the SoC (State of Charge) of the secondary battery.

[0108] As shown in Figure 7, the first profile TH2 of a secondary battery to which a negative electrode active material containing graphite and SiO in weight ratios of 95% and 5%, respectively, is applied, shows the thickness of the secondary battery, which changes over time or with changes in the charge state of the secondary battery during the discharge cycle of the secondary battery.

[0109] Furthermore, the second profile dTH2 / dt of the secondary battery represents the slope of the first profile TH2, which changes with the passage of time or the change in the charge state of the secondary battery. In this case, the second profile dTH2 / dt can be obtained by differentiating the first profile TH2 with respect to time t.

[0110] The first profile TH2 of the secondary battery shows that the thickness of the secondary battery gradually decreases while the secondary battery is being discharged.

[0111] However, the second profile dTH2 / dt of the secondary battery shows that the slope of the first profile TH2 gradually decreases while the secondary battery is discharging, and then increases further at a specific point in time.

[0112] In other words, the second profile dTH2 / dt can be divided into multiple sections a2, b2, c2, and d2. In this case, as the discharge progresses from the first section a2, which is the initial stage of discharge, to the second section b2 and third section c2, which are the middle stages of discharge, the slope of each section gradually decreases, but in the fourth section d2, which is the final stage of discharge, the slope changes to an increasing trend.

[0113] Therefore, as described with reference to Figure 6, the processor 120 of the secondary battery diagnostic device 100 according to the present invention can estimate the capacity ratio of silicon or silicon oxide using the sensing result of the thickness sensor 110 which senses the change in thickness of the secondary battery during charging or discharging, and diagnose the state of the secondary battery based on such a capacity ratio.

[0114] In other words, the thickness sensor 110 can detect changes in the thickness of the secondary battery while the secondary battery is being discharged.

[0115] Furthermore, the processor 120 uses the sensing results from the thickness sensor 110 to generate a first profile TH2 showing the thickness of the secondary battery which changes over time or with changes in the charge state, and a second profile dTH2 / dt showing the slope of the first profile TH2 which changes over time or with changes in the charge state of the secondary battery. Based on the second profile dTH2 / dt, the processor can estimate the capacity ratio of silicon oxide (SiO).

[0116] To achieve this, the processor 120 can divide the second profile dTH2 / dt into multiple sections a2, b2, c2, and d2, and select a target section relating to silicon or silicon oxide from among these multiple sections a2, b2, c2, and d2.

[0117] For example, the processor 120 divides the second profile dTH2 / dt into a first section a2, a second section b2, a third section c2, and a fourth section d2, and may select the fourth section d2 as a target section, which is the section in which the charge state of the second secondary battery is below a predetermined critical value and in which the slope change progression of the first profile TH2 is different from that of the other sections.

[0118] Subsequently, the processor 120 can estimate the capacity ratio of silicon or silicon oxide by comparing the total length L2 of multiple sections a2, b2, c2, and d2 with the length L2' of the target section, using the first axis (horizontal axis) direction representing time or charge state of the SoC as a reference.

[0119] For example, in Figure 7, the SiO volume ratio CR2 can be calculated using formula 1 as k(L2' / L2) × 100[%].

[0120] Once the capacity ratio is estimated in this way, the processor 120 can use the estimated capacity ratio to diagnose the state of the secondary battery, as explained with reference to Figure 6.

[0121] Figure 8 shows the first and second profiles of a third-stage secondary battery to which a negative electrode active material containing silicon oxide at a weight ratio of 10% is applied.

[0122] In Figure 8, the horizontal axis represents the elapsed time after the start of the discharge cycle, the left vertical axis represents the ratio of the surface position change value to the original thickness value of the third secondary battery, and the right vertical axis represents the slope of the first profile TH3. Depending on the embodiment, the horizontal axis may represent the SoC (State of Charge) of the third secondary battery.

[0123] As shown in Figure 8, the first profile TH3 of a tertiary battery containing graphite and SiO in weight ratios of 90% and 10%, respectively, represents the thickness of the tertiary battery, which changes over time or with changes in the charge state of the tertiary battery during the discharge cycle of the tertiary battery.

[0124] Furthermore, the second profile dTH3 / dt of the third secondary battery represents the slope of the first profile TH3, which changes with the passage of time or the change in the charge state of the third secondary battery. In this case, the second profile dTH3 / dt can be obtained by differentiating the first profile TH3 with respect to time t.

[0125] The first profile TH3 of the third secondary battery shows that the thickness of the third secondary battery gradually decreases during the discharge process.

[0126] However, the second profile dTH3 / dt of the third secondary battery shows that the slope of the first profile TH3 gradually decreases during the discharge of the third secondary battery, and then increases further at a specific point in time.

[0127] In other words, the second profile (dTH3 / dt) can be divided into several intervals a3, b3, c3, and d3. In this case, the slope of each interval gradually decreases as we progress from the first interval a3, which is the initial stage of discharge, to the second interval b3 and the third interval c3, which are the middle stages of discharge, but in the fourth interval d3, which is the final stage of discharge, the slope changes to an increasing trend.

[0128] Therefore, as explained with reference to Figure 6, the processor 120 of the secondary battery diagnostic device 100 according to the present invention can estimate the capacity ratio of silicon or silicon oxide using the sensing result of the thickness sensor 110 which senses the change in thickness of the secondary battery during charging or discharging, and diagnose the state of the secondary battery based on such a capacity ratio.

[0129] In other words, the thickness sensor 110 can detect changes in the thickness of the third secondary battery while the third secondary battery is being discharged.

[0130] Furthermore, the processor 120 uses the sensing results from the thickness sensor 110 to generate a first profile TH3 showing the thickness of the third secondary battery which changes over time or with changes in the charge state, and a second profile dTH3 / dt showing the slope of the first profile TH3 which changes over time or with changes in the charge state of the third secondary battery. Based on the second profile dTH3 / dt, the processor can estimate the capacity ratio of silicon oxide (SiO).

[0131] To achieve this, the processor 120 can divide the second profile dTH3 / dt into multiple sections a3, b3, c3, and d3, and select a target section relating to silicon or silicon oxide from among these multiple sections a3, b3, c3, and d3.

[0132] For example, the processor 120 divides the second profile dTH3 / dt into a first section a3, a second section b3, a third section c3, and a fourth section d3, and can select the fourth section d3 as a target section, which is the section in which the charge state of the third secondary battery is below a predetermined critical value and in which the slope change progression of the first profile TH3 is different from that of the other sections.

[0133] Subsequently, the processor 120 can estimate the capacity ratio of silicon or silicon oxide by comparing the total length L3 of multiple sections a3, b3, c3, and d3 with the length L3' of the target section, using the first axis (horizontal axis) direction, which indicates time or charge state of the SoC, as a reference.

[0134] For example, in Figure 8, the SiO volume ratio CR3 can be calculated using formula 1 as k(L3' / L3) × 100[%].

[0135] Once the capacity ratio is estimated in this way, the processor 120 can use the estimated capacity ratio to diagnose the state of the third secondary battery, as explained with reference to Figure 6.

[0136] Figure 9 is a graph showing the change in thickness of a secondary battery during charging and discharging, categorized by the number of charge-discharge cycles.

[0137] As shown in Figure 9, the thickness of the secondary battery gradually increases as the number of charge-discharge cycles increases. Also, if the rest time between the end of charging (t1) and the start of discharging (t2) is the same for all charge-discharge cycles, the total charge-discharge time gradually decreases as the number of charge-discharge cycles increases.

[0138] Therefore, both the first profile, which shows the thickness of the secondary battery that changes over time or with changes in the charge state, and the second profile, which is obtained by differentiating such a first profile with respect to time or SoC, change with the number of cycles of the secondary battery. If the secondary battery being diagnosed is a normal secondary battery, the profiles will show mutually similar change patterns according to the number of cycles.

[0139] Figure 10 shows the second profile obtained by differentiating the thickness of the secondary battery with respect to time during discharge.

[0140] As shown in Figure 10, the second profile obtained by differentiating the thickness with respect to time during discharge of a secondary battery to which silicon or silicon oxide-containing negative electrode active material is applied gradually decreases as discharge progresses and increases in the target interval TS at the end of discharge.

[0141] The length of such a target interval TS in the horizontal direction varies depending on the number of discharge cycles of the secondary battery.

[0142] Figure 11 shows the second profile obtained by differentiating the thickness of the secondary battery with respect to time during discharge, categorized by the number of discharge cycles of the secondary battery.

[0143] As shown in Figure 11, the pattern of the second profile and the length of the target section can change depending on the number of discharge cycles of the secondary battery. That is, as the number of discharge cycles of the secondary battery increases and the secondary battery deteriorates, the pattern of the second profile may tend to gradually contract. In addition, the position and length of the target section may also change due to the change in the pattern of the second profile.

[0144] For example, in a secondary battery with a negative electrode active material containing graphite and SiO in weight ratios of 90% and 10%, respectively, the target section TS1 of the second profile corresponding to the second discharge cycle may have a length corresponding to a capacity ratio of 25%. Furthermore, the target sections TS2, TS3, and TS4 of the second profile corresponding to the 50th, 100th, and 150th discharge cycles, respectively, gradually lengthen with increasing discharge cycle counts, and may have lengths corresponding to a capacity ratio approximating 29.1%.

[0145] On the other hand, if the secondary battery is in an abnormal state, such as when swelling occurs in the secondary battery as the discharge cycle is repeated, or when conductive path loss occurs due to SiO2 pulverization, the target sections TS1, TS2, TS3, and TS4 of the second profile will gradually lengthen in proportion to the number of discharge cycles, and then shorten more rapidly.

[0146] Therefore, the processor 120 of the secondary battery diagnostic device 100 according to the present invention can repeatedly estimate the capacity ratio of silicon or silicon oxide contained in the negative electrode active material while the charging or discharging cycle of the secondary battery to be diagnosed is repeated, and diagnose the state of the secondary battery to be diagnosed based on the changes in the estimated capacity ratio.

[0147] Figure 12 is a flowchart illustrating a diagnostic method for a secondary battery according to one embodiment of the present invention.

[0148] Referring to Figure 12, the detailed operation of the secondary battery diagnostic device 100 according to the present invention will be explained in chronological order.

[0149] When a charge and / or discharge cycle is started in a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied, the thickness sensor 110 of the secondary battery diagnostic device 100 senses the change in the thickness of the secondary battery due to the change in the volume of the negative electrode active material while the secondary battery is being charged or discharged (S10, S20).

[0150] Subsequently, the processor 120 of the secondary battery diagnostic device 100 uses the sensing result from the thickness sensor 110 to estimate the capacity ratio, which is the ratio of the capacity provided by silicon or silicon oxide to the capacity provided by the negative electrode active material of the secondary battery. In this case, the estimated capacity ratio can be stored in the memory 130 of the secondary battery diagnostic device 100 (S30).

[0151] Subsequently, when the number of cycles of the secondary battery reaches a predetermined reference number, the processor 120 can diagnose the state of the secondary battery based on the estimated capacity ratio (S40, S50).

[0152] On the other hand, if the number of cycles of the secondary battery has not reached a reference number, the processor 120 waits without diagnosing the state of the secondary battery, and when the next charge and / or discharge cycle of the secondary battery is started, it may repeat the secondary battery thickness sensing process (S20) and the silicon or silicon oxide capacity ratio estimation process (S40, S80, S90).

[0153] If the secondary battery condition is diagnosed as being poor during the secondary battery condition diagnosis process S50, the processor 120 may control the output device 140 to output a predetermined alarm (S60, S70).

[0154] On the other hand, if the secondary battery condition diagnosis process S50 diagnoses that the secondary battery is not in a bad state, the processor 120 saves the diagnosis result to the memory 130 and then waits. When the next charge and / or discharge cycle of the secondary battery begins, the process described above (S20 to S50) may be repeated (S60, S80, S90).

[0155] Figure 13 is a flowchart showing the capacity ratio estimation process of a secondary battery diagnostic method according to one embodiment of the present invention.

[0156] As shown in Figure 13, when the thickness sensor 110 detects a change in the thickness of the secondary battery while the secondary battery is being charged and / or discharged, the processor 120 may use the detection results from the thickness sensor 110 to generate a first profile showing the thickness of the secondary battery as it changes over time or as the charge state (SoC) of the secondary battery changes (S32).

[0157] Subsequently, the processor 120 may generate a second profile based on the first profile, which shows the slope of the first profile that changes with the passage of time or with changes in the charge state of the secondary battery (SoC) (S34). In this case, the second profile may be obtained by differentiating the first profile with respect to time or SoC.

[0158] Subsequently, the processor 120 can estimate the capacity ratio of silicon or silicon oxide based on the second profile.

[0159] Specifically, the processor 120 can divide the second profile into multiple sections and select a target section relating to silicon or silicon oxide from among the multiple sections (S36).

[0160] Subsequently, the processor 120 can estimate the capacity ratio by comparing the total length of multiple sections with the length of the target section, using the first axis direction as a reference (S38).

[0161] In this case, the processor 120 can divide the second profile into multiple intervals based on the change in the slope of the first profile shown in the second profile.

[0162] Furthermore, the processor 120 may select as a target interval an interval in which the charge state of the first secondary battery is below a predetermined critical value, and in which the slope change progression of the first profile differs from that of the other intervals.

[0163] For example, if the first profile relates to the thickness change during the discharge of a secondary battery, the processor 120 may select as the target interval the slope change of the first profile changes from a decreasing trend to an increasing trend among several intervals of the second profile.

[0164] As described above, once a target interval is selected, the processor 120 can estimate the capacity ratio of silicon or silicon oxide by comparing the total length of multiple intervals with the length of the target interval. The capacity ratio can be calculated using Equation 1.

[0165] Once the capacity ratio is estimated in this way, the processor 120 can use the estimated capacity ratio to diagnose the state of the secondary battery. For example, the processor 120 can diagnose the state of the secondary battery by comparing the estimated capacity ratio with a reference capacity ratio of silicon or silicon oxide previously obtained from a normal secondary battery.

[0166] In one embodiment, the secondary battery diagnostic device 100 according to the present invention may pre-store reference capacity ratio information of the secondary battery to be diagnosed in the memory 130. The reference capacity ratio information may include information indicating the reference capacity ratio corresponding to a predetermined number of charge cycles or predetermined number of discharge cycles of the secondary battery to be diagnosed. In this case, the processor 120 can diagnose the state of the secondary battery by comparing the estimated capacity ratio with the reference capacity ratio pre-stored in the memory 130.

[0167] In another embodiment, the processor 120 may diagnose the state of the secondary battery by further estimating the weight ratio, which is the ratio of the weight of silicon or silicon oxide to the total weight of the negative electrode active material, and comparing the estimated capacity ratio with a reference capacity ratio corresponding to the weight ratio.

[0168] In this case, the processor 120 can estimate the weight ratio before the number of charge or discharge cycles of the secondary battery being diagnosed exceeds a predetermined number.

[0169] For example, the processor 120 may estimate the silicon oxide capacity ratio after the completion of a charge cycle or discharge cycle that occurred before degradation of the secondary battery being diagnosed occurred, and estimate the silicon oxide weight ratio corresponding to the estimated capacity ratio.

[0170] Subsequently, the processor 120 may obtain reference capacity ratio information corresponding to the estimated weight ratio from the reference capacity ratio information for each weight ratio that has been previously stored in the memory 130.

[0171] Subsequently, the processor 120 can diagnose the state of the secondary battery by comparing the acquired reference capacity ratio information with the capacity ratio of silicon or silicon oxide that is iteratively estimated for the secondary battery.

[0172] Figure 14 shows a vehicle 2 according to one embodiment of the invention.

[0173] As shown in Figure 14, a vehicle 2 according to one embodiment of the present invention may include a secondary battery diagnostic device according to the present invention. The secondary battery diagnostic device may be configured to diagnose the secondary battery of a battery pack 10 mounted on the vehicle 2. In this case, the secondary battery diagnostic device may be configured to work in conjunction with the ECU (Electronic Control Unit) of the vehicle 2.

[0174] In another embodiment, the secondary battery diagnostic device may be included in the battery pack 10 mounted on the vehicle 2. In this case, the secondary battery diagnostic device may be configured to work in conjunction with the Battery Management System (BMS) of the battery pack 10.

[0175] For reference, the secondary battery diagnostic device according to the present invention is applicable not only to vehicles but also to a variety of electrical devices and systems that use secondary batteries, as well as to energy storage systems (ESS).

[0176] As described above, according to the present invention, while a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied is being charged or discharged, a thickness sensor senses the change in the thickness of the secondary battery due to a change in the volume of the negative electrode active material, and a processor uses the sensing result of the thickness sensor regarding the change in the thickness of the secondary battery to estimate the capacity ratio, which is the ratio of the electrical capacity provided by silicon oxide to the electrical capacity provided by the negative electrode active material of the secondary battery, and diagnoses the state of the secondary battery based on such a capacity ratio, thereby enabling efficient and accurate diagnosis of the state of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied.

[0177] Furthermore, before estimating the capacity ratio, the processor sequentially generates a first profile showing the thickness of the secondary battery, which changes over time or due to changes in the secondary battery's charge state, and a second profile showing the slope of the first profile, which also changes over time or due to changes in the secondary battery's charge state, using the sensing results from the thickness sensor. By estimating the capacity ratio based on this second profile, the state of the secondary battery can be diagnosed in a simplified manner, independent of the electrical factors of the secondary battery.

[0178] Furthermore, the processor can reduce the amount of computation required to diagnose the state of the secondary battery by dividing the second profile into multiple sections, selecting a target section from among the multiple sections that exhibits the intrinsic characteristics of silicon or silicon oxide, and estimating the capacity ratio by comparing the total length of the multiple sections with the length of the target section. As a result, the secondary battery diagnostic speed can be improved.

[0179] Furthermore, the processor estimates the weight ratio, which is the ratio of the weight of silicon or silicon oxide to the total weight of the negative electrode active material. By comparing the estimated weight ratio with a reference capacity ratio and capacity ratio, the state of the secondary battery can be diagnosed even when the weight ratio of silicon or silicon oxide contained in the negative electrode active material of the target secondary battery is unknown.

[0180] Furthermore, by configuring the thickness sensor that detects changes in the thickness of secondary batteries to measure the distance from a predetermined position to the surface of the secondary battery and detect the change in the thickness of the secondary battery, it is possible to detect changes in the thickness of secondary batteries individually, and it is also possible to detect changes in the total thickness of a secondary battery module by combining multiple secondary batteries stacked in the thickness direction into a single secondary battery module. In other words, the secondary battery diagnostic device according to the present invention is included in a battery pack or vehicle having multiple secondary batteries, and can diagnose the state of multiple secondary batteries on a secondary battery module basis.

[0181] Consequently, embodiments of the present invention can certainly solve a variety of other technical problems not only in the relevant technical field but also in related technical fields, beyond those mentioned herein.

[0182] The present invention has been described above with reference to specific embodiments. However, those skilled in the art will clearly understand that a variety of modified embodiments can be realized within the technical scope of the present invention. Therefore, the embodiments described above should be considered from an explanatory rather than restrictive viewpoint. That is, the true technical idea of ​​the present invention is shown in the claims, and all differences within the equivalent scope should be interpreted as being included in the present invention. [Explanation of Symbols]

[0183] 100 Secondary Battery Diagnostic Device 110 Thickness Sensor 120 processors 130 memory 140 Output device

Claims

1. A secondary battery diagnostic device for diagnosing the condition of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied, A thickness sensor that senses the change in the thickness of the secondary battery due to a change in the volume of the negative electrode active material while the secondary battery is being charged or discharged, A secondary battery diagnostic device comprising: a processor that estimates a capacity ratio, which is the ratio of the capacity provided by the silicon or silicon oxide to the capacity of the secondary battery provided by the negative electrode active material, using the sensing result of the thickness sensor, and diagnoses the state of the secondary battery based on the capacity ratio.

2. The secondary battery diagnostic device according to claim 1, characterized in that the thickness sensor is configured to detect changes in the thickness of the secondary battery by measuring the distance from a predetermined position to the surface of the secondary battery.

3. The secondary battery diagnostic device according to claim 1, characterized in that the processor is configured to generate a first profile showing the thickness of the secondary battery which changes over time or due to changes in the charge state of the secondary battery, and a second profile showing the slope of the first profile which changes over time or due to changes in the charge state of the secondary battery, using the sensing results of the thickness sensor before estimating the capacity ratio, and to estimate the capacity ratio based on the second profile.

4. The secondary battery diagnostic device according to claim 3, characterized in that the processor is configured to divide the second profile into a plurality of sections, select a target section relating to silicon or silicon oxide from among the plurality of sections, and estimate the capacity ratio by comparing the total length of the plurality of sections with the length of the target section with respect to the first axial direction.

5. The secondary battery diagnostic device according to claim 4, characterized in that the processor is configured to divide the second profile into the plurality of sections based on the change in the slope of the first profile shown in the second profile.

6. The secondary battery diagnostic device according to claim 4, characterized in that the processor is configured to select as the target interval an interval in which the charge state of the secondary battery is below a predetermined critical value among the plurality of intervals, and in which the slope change progression of the first profile is different from that of the other intervals.

7. The thickness sensor is configured to detect changes in the thickness of the secondary battery while the secondary battery is being discharged. The secondary battery diagnostic device according to claim 4, characterized in that the processor is configured to select as the target interval an interval in which the slope change of the first profile changes from a decreasing trend to an increasing trend among the plurality of intervals.

8. The secondary battery diagnostic device according to claim 1, characterized in that the processor is configured to diagnose the state of the secondary battery by further estimating a weight ratio, which is the ratio of the weight of silicon or silicon oxide to the total weight of the negative electrode active material, and comparing the weight ratio with a reference capacity ratio corresponding to the capacity ratio.

9. The secondary battery diagnostic device according to claim 8, characterized in that the processor is configured to estimate the weight ratio before the number of charge cycles or discharge cycles of the secondary battery exceeds a predetermined number.

10. The secondary battery diagnostic device according to claim 1, characterized in that the processor is configured to iteratively estimate the capacity ratio while the secondary battery undergoes a charging cycle or a discharging cycle, and to diagnose the state of the secondary battery based on the changes in the estimated capacity ratio.

11. The secondary battery diagnostic device according to any one of claims 1 to 10, characterized in that the negative electrode active material includes silicon or a mixture of silicon oxide and graphite.

12. The secondary battery diagnostic device according to any one of claims 1 to 10, characterized in that the secondary battery is composed of a pouch-type secondary battery.

13. A method for diagnosing the condition of a secondary battery to which a negative electrode active material containing silicon or silicon oxide is applied, During the charging or discharging of the secondary battery, a thickness sensor detects a change in the thickness of the secondary battery due to a change in the volume of the negative electrode active material (stage A), Step B involves the processor using the sensing result of the thickness sensor to estimate the capacity ratio, which is the ratio of the capacity provided by the silicon or silicon oxide to the capacity of the secondary battery provided by the negative electrode active material. A method for diagnosing a secondary battery, comprising step C, in which the processor diagnoses the state of the secondary battery based on the capacity ratio.

14. The aforementioned stage B is, Step B1 involves generating a first profile showing the thickness of the secondary battery, which changes over time or due to changes in the charge state of the secondary battery, using the sensing results of the thickness sensor. Step B2 involves generating a second profile based on the first profile, which shows the slope of the first profile that changes over time or with changes in the charge state of the secondary battery, The method for diagnosing a secondary battery according to claim 13, further comprising a B3 step of estimating the capacity ratio based on the second profile.

15. The aforementioned B3 stage is, The steps include dividing the second profile into multiple sections and selecting a target section relating to silicon or silicon oxide from among the multiple sections, The method for diagnosing a secondary battery according to claim 14, comprising the step of estimating the capacity ratio by comparing the total length of the plurality of sections with the length of the target section, with respect to the first axial direction.

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