Secondary battery diagnosing device and method

Abstract

A secondary battery diagnosing device according to the present invention comprises: a thickness sensor for sensing a thickness change of a secondary battery according to a volume change of a negative electrode active material during charging or discharging of the secondary battery to which the negative electrode active material including silicon or silicon oxide is applied; and a processor for estimating a capacity ratio, which is a ratio of the capacity of the secondary battery provided by the negative electrode active material to the capacity provided by the silicon or the silicon oxide, by using the sensing result of the thickness sensor, and diagnosing the state of the secondary battery on the basis of the capacity ratio.

Description

Secondary battery diagnostic device and method

[0001] This application claims priority from Korean Patent Application No. 10-2023-0104441, filed on August 9, 2023, the entire disclosure of which is incorporated herein by reference.

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

[0003] In general, a secondary battery is a battery that can be repeatedly charged and discharged. Types of secondary batteries include lithium secondary batteries that utilize lithium ions, such as lithium-ion batteries and lithium-ion polymer batteries, as well as nickel-cadmium batteries, nickel-metal hydride batteries, and nickel-zinc batteries.

[0004] Recently, as secondary batteries are applied to various devices that require high output voltage and large charging capacity, such as electric vehicles and energy storage systems (ESS), lithium secondary batteries are widely used because they have the advantages of having almost no memory effect, low self-discharge rate, and high energy density compared to secondary batteries using nickel.

[0005] These secondary batteries gradually deteriorate as they undergo repeated charge-discharge cycles, losing the electrical capacity they possessed at the time of manufacture. If the current condition of these secondary batteries cannot be accurately diagnosed, it becomes difficult to measure or predict their state of charge (SoC), usable time, remaining lifespan, and replacement timing. This can result in unexpected losses for secondary battery users.

[0006] However, existing technologies have the problem that diagnosing secondary batteries requires a lot of cost and has a high possibility of errors in the diagnosis results because they measure various electrical factors such as voltage, current, and resistance of secondary batteries and diagnose the condition of the secondary batteries by inputting the measured values ​​into complex formulas.

[0007] In particular, existing technologies have a problem in that they cannot provide a method for efficiently and accurately diagnosing the status of secondary batteries that use negative active materials containing silicon or silicon oxide to increase energy density.

[0008] The technical problem to be solved by the present invention is to provide a secondary battery diagnostic device and method that efficiently and accurately diagnoses the state of a secondary battery to which a negative electrode active material including silicon or silicon oxide is applied.

[0009] Another technical problem to be solved by the present invention is to provide a battery pack and a vehicle that efficiently and accurately diagnose the state of a secondary battery to which a negative active material including silicon or silicon oxide is applied.

[0010] A secondary battery diagnosis device according to one aspect of the present invention is a device for diagnosing a state of a secondary battery to which a negative electrode active material including silicon or silicon oxide is applied, the device comprising: a thickness sensor for sensing a change in the thickness of the secondary battery according to a change in the volume of the negative electrode active material while the secondary battery is being charged or discharged; and a processor for estimating a capacity ratio, which is a ratio of a capacity provided by the silicon or silicon oxide among the capacities of the secondary battery provided by the negative electrode active material, using a sensing result of the thickness sensor, and diagnosing a state of the secondary battery based on the capacity ratio.

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

[0012] In one embodiment, the processor may be configured to, before estimating the capacity ratio, generate a first profile representing a thickness of the secondary battery that changes over time or with a change in the state of charge of the secondary battery, and a second profile representing a slope of the first profile that changes over time or with a change in the state of charge of the secondary battery, using a sensing result of the thickness sensor, and 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 related to the silicon or the 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 based on the first axis direction.

[0014] In one embodiment, the processor may be configured to divide the second profile into the plurality of sections according to a slope change trend of the first profile shown in the second profile.

[0015] In one embodiment, the processor may be configured to select, as the target section, a section corresponding to a range in which the state of charge of the secondary battery is below a predetermined threshold among the plurality of sections, and in which a slope change trend of the first profile appears different from other sections.

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

[0017] In one embodiment, the processor may be configured to further estimate a weight ratio, which is a ratio of the weight of the silicon or silicon oxide among the total weight of the negative active material, before diagnosing the state of the secondary battery, and compare the capacity ratio with a reference capacity ratio corresponding to the weight ratio to diagnose the state of the secondary battery.

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

[0019] In one embodiment, the processor may be configured to repeatedly estimate the capacity ratio while the charge cycle or discharge cycle of the secondary battery is repeated, and to diagnose the state of the secondary battery based on a change trend of the estimated capacity ratios.

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

[0021] In one embodiment, the secondary battery may be configured as a pouch-type secondary battery.

[0022] A secondary battery diagnosis method according to another aspect of the present invention is a method for diagnosing a state of a secondary battery to which a negative electrode active material including silicon or silicon oxide is applied, the method comprising: a step A in which a thickness sensor senses a change in the thickness of the secondary battery according to a change in the volume of the negative electrode active material while the secondary battery is being charged or discharged; a step B in which a processor estimates a capacity ratio, which is a ratio of a capacity provided by the silicon or silicon oxide among the capacities of the secondary battery provided by the negative electrode active material, using the sensing result of the thickness sensor; and a step C in which the processor diagnoses a state of the secondary battery based on the capacity ratio.

[0023] In one embodiment, the step B may include a step B1 of generating a first profile representing a thickness of the secondary battery that changes over time or according to a change in the state of charge of the secondary battery using a sensing result of the thickness sensor; a step B2 of generating a second profile representing a slope of the first profile that changes over time or according to a change in the state of charge of the secondary battery based on the first profile; and a step B3 of estimating the capacity ratio based on the second profile.

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

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

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

[0027] According to the present invention, while a secondary battery to which an anode active material including silicon or silicon oxide is applied is being charged or discharged, a thickness sensor senses a change in the thickness of the secondary battery according to a change in the volume of the anode 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 a capacity ratio, which is a ratio of an electrical capacity provided by silicon oxide among the electrical capacities provided by the anode active material of the secondary battery, and diagnoses the state of the secondary battery based on this capacity ratio, thereby enabling the state of the secondary battery to be diagnosed efficiently and accurately.

[0028] In addition, the processor, before estimating the capacity ratio, sequentially generates a first profile representing the thickness of the secondary battery that changes with the passage of time or with a change in the state of charge of the secondary battery, and a second profile representing the slope of the first profile that changes with the passage of time or with a change in the state of charge of the secondary battery, using the sensing result of the thickness sensor, and estimates the capacity ratio based on this second profile, thereby making it possible to diagnose the state of the secondary battery in a simplified manner independent of electrical factors of the secondary battery.

[0029] In addition, the processor divides the second profile into a plurality of sections, selects a target section exhibiting unique characteristics of silicon or silicon oxide from among the plurality of sections, and estimates the capacity ratio by comparing the length of the entire plurality of sections with the length of the target section, thereby reducing the amount of computation required to diagnose the state of the secondary battery, and as a result, improving the speed of diagnosing the secondary battery.

[0030] In addition, the processor estimates a weight ratio, which is a ratio of the weight of silicon or silicon oxide among the total weight of the negative active material, and compares the capacity ratio with a reference capacity ratio corresponding to the estimated weight ratio to diagnose the state of the secondary battery, thereby diagnosing the state of the target secondary battery even when the weight ratio of silicon or silicon oxide included in the negative active material of the target secondary battery is unknown.

[0031] In addition, since a thickness sensor for sensing a change in the thickness of a secondary battery is configured to sense a change in the thickness of the secondary battery by measuring a distance from a predetermined position to the surface of the secondary battery, not only can the change in the thickness of the secondary battery be sensed for each secondary battery, but a plurality of secondary batteries stacked in the thickness direction can be made into one secondary battery module, and a change in the overall thickness of the secondary battery module can be sensed. That is, the secondary battery diagnosis device according to the present invention can be included in a battery pack or vehicle having a plurality of secondary batteries, and can diagnose the status of the plurality of secondary batteries in units of secondary battery modules.

[0032] Furthermore, those skilled in the art will readily understand from the following description that various embodiments of the present invention can solve various technical problems not mentioned above.

[0033] FIG. 1 is a block diagram showing a secondary battery diagnostic device according to one embodiment of the present invention.

[0034] Figure 2 is an exploded perspective view showing an example of a secondary battery.

[0035] Figure 3 is a front view showing the secondary battery illustrated in Figure 2.

[0036] Figure 4 is a profile showing the thickness change during charging and discharging of a secondary battery.

[0037] Figure 5 is a drawing showing the first and second profiles of a secondary battery to which a negative active material not including silicon oxide is applied.

[0038] Figure 6 is a drawing showing the first profile and the second profile of a first secondary battery to which a negative active material containing silicon oxide at a weight ratio of 3% is applied.

[0039] Figure 7 is a drawing showing the first and second profiles of a second secondary battery to which a negative active material containing silicon oxide at a weight ratio of 5% is applied.

[0040] Figure 8 is a drawing showing the first and second profiles of a third secondary battery to which a negative active material containing silicon oxide at a weight ratio of 10% is applied.

[0041] Figure 9 is a graph showing the change in thickness during charging and discharging of a secondary battery according to the number of charge / discharge cycles of the secondary battery.

[0042] Figure 10 is a drawing showing a second profile in which the thickness is differentiated with respect to time during discharge of a secondary battery.

[0043] Figure 11 is a diagram showing a second profile in which the thickness of a secondary battery is differentiated with respect to time during discharge, according to the number of discharge cycles of the secondary battery.

[0044] Figure 12 is a flowchart illustrating a secondary battery diagnosis method according to one embodiment of the present invention.

[0045] Fig. 13 is a flowchart illustrating a capacity ratio estimation process of a secondary battery diagnosis method according to one embodiment of the present invention.

[0046] Fig. 14 is a drawing showing a vehicle according to one embodiment of the present invention.

[0047] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings to clarify solutions corresponding to the technical challenges of the present invention. However, when describing the present invention, descriptions of related known technologies may be omitted if they obscure the gist of the present invention. Furthermore, the terms used in this specification are defined in consideration of their functions in the present invention, and these may vary depending on the intentions or practices of designers, manufacturers, etc. Therefore, the definitions of terms described below should be based on the contents throughout this specification.

[0048] FIG. 1 is a block diagram illustrating a secondary battery diagnostic device (100) according to one embodiment of the present invention.

[0049] As illustrated in FIG. 1, a secondary battery diagnostic device (100) according to one embodiment of the present invention is configured to diagnose the state of a secondary battery to which a negative electrode active material including silicon or silicon oxide is applied. To this end, the secondary battery diagnostic device (100) includes a thickness sensor (110) and a processor (120).

[0050] The above thickness sensor (110) is configured to sense a change in the thickness of the secondary battery according to a change in the volume of the negative active material applied to the secondary battery while the secondary battery is being charged or discharged.

[0051] The processor (120) is configured to estimate the capacity ratio of silicon or silicon oxide included in the negative electrode active material using the sensing result of the thickness sensor (110) and to diagnose the state of the secondary battery based on the capacity ratio. Here, the capacity ratio refers to the ratio of the capacity provided by the silicon or silicon oxide among the capacity of the secondary battery provided by the negative electrode active material.

[0052] In one embodiment, the thickness sensor (110) may be configured to sense a change in the thickness of the secondary battery by measuring the distance from a predetermined position to the surface of the secondary battery. In this case, the thickness sensor (110) may be configured as a contact sensor, such as a micrometer, or a non-contact sensor, such as a displacement sensor using a laser or light.

[0053] Additionally, 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 previously stored data to the processor (120) or store data transmitted from the processor (120).

[0054] For example, the memory (130) may be configured to store data regarding a reference capacity ratio that should be provided by silicon or silicon oxide included in the negative active material of a normal secondary battery. In this case, the memory (130) may store data regarding the reference capacity ratio by weight ratio of silicon or silicon oxide included in the negative active material. In addition, the memory (130) may be configured to further store data regarding the capacity ratio of silicon or silicon oxide estimated by the processor (120), data regarding secondary battery diagnosis results, and the like.

[0055] Such memory (130) may include at least one of RAM (Random Access Memory), SRAM (Static RAM), 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).

[0056] Additionally, 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 or information through visual, auditory, or audiovisual means. To this end, the output device (140) may optionally include a visual display device such as a display, a light-emitting diode, or the like, and an audio device such as a speaker.

[0057] For example, if the secondary battery diagnosis result indicates that the secondary battery is in a bad condition, the processor (120) can control the output device (140) to output a predetermined alarm.

[0058] Figure 2 shows an exploded perspective view of an example of a secondary battery (200).

[0059] As illustrated in FIG. 2, a secondary battery (200) may include an electrode assembly (222) in which a positive electrode and a negative electrode are mutually laminated with a separator therebetween, and a case (228) that accommodates the electrode assembly (222) together with an electrolyte material in an internal space (S1).

[0060] In addition, the secondary battery (200) may further include an electrode lead (224) electrically connected to the electrode assembly (222), and a sealing tape (226) sealing the circumference of the electrode lead (224).

[0061] The case (228) of the secondary battery (200) may include a first case portion (228a) and a second case portion (228b) that are mutually coupled to form an internal space (S1). The case (228) may be sealed by hermetically coupling the edge portion of the first case portion (228a) and the edge portion of the second cable portion (228b) to each other while the electrode assembly (222) is accommodated in the internal space (S1).

[0062] The positive electrode constituting the electrode assembly (222) of the secondary battery (200) may include a positive electrode substrate made of a material including aluminum, and a positive electrode active material applied to the positive electrode substrate. The positive electrode active material may include a lithium-based oxide. The positive electrode active material may be applied to the positive electrode substrate together with a conductive material, a binder, and the like.

[0063] The negative electrode of the above electrode assembly (222) may include a negative electrode substrate made of a material including copper, and a negative electrode active material applied to the negative electrode substrate. The negative electrode active material may be silicon (Si) or silicon oxide (SiO x ) and graphite. That is, the negative electrode active material may include a mixture in which a silicon-based material and graphite are each blended at a predetermined weight ratio. This negative electrode active material may be applied to the negative electrode substrate together with a conductive material, a binder, etc.

[0064] In this way, 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.

[0065] Meanwhile, silicon (Si) or silicon oxide (SiO x ) Silicon-based materials, such as silicon dioxide, have unique characteristics of high reaction potential and large volume changes due to electrochemical reactions compared to graphite, which is blended with silicon-based materials.

[0066] Accordingly, the secondary battery diagnostic device (100) according to the present invention can diagnose the state of the secondary battery, such as the deterioration state, capacity loss rate, and remaining lifespan, by utilizing the unique characteristics of silicon-based materials.

[0067] In Fig. 3, the secondary battery (200) illustrated in Fig. 2 is illustrated in a front view.

[0068] As illustrated in FIG. 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 accommodated inside the secondary battery (200).

[0069] The thickness (TH) of such a secondary battery (200) changes along with the change in volume of the negative electrode active material that occurs while charging or discharging the secondary battery (200).

[0070] The secondary battery diagnostic device (100) according to the present invention can diagnose the state of the secondary battery by sensing a change in the thickness of the secondary battery.

[0071] In addition, the secondary battery to be diagnosed by the secondary battery diagnosis device (100) according to the present invention may be configured in various forms in which the thickness in a specific direction changes according to the change in the volume of the negative electrode active material during charging or discharging.

[0072] For example, as illustrated in FIGS. 2 and 3, the secondary battery to be diagnosed by the secondary battery diagnosis 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 diagnosis device (100) according to the present invention may also be configured as a secondary battery of another type in which the thickness of a specific portion changes according to a change in the volume of the negative electrode active material, such as a square secondary battery or a cylindrical secondary battery.

[0073] Figure 4 shows a profile showing the thickness change during charging and discharging of a secondary battery.

[0074] In Fig. 4, the horizontal axis represents the time elapsed after the start of the charge / discharge cycle, and the vertical axis represents the ratio of the surface position change value to the original thickness value of the secondary battery.

[0075] As illustrated in Fig. 4, the thickness change during charging and discharging of a secondary battery may 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 weight ratio of silicon or silicon oxide to the total weight of the negative electrode active material.

[0076] That is, during charging, resting, and discharging, a secondary battery including SiO, a type of silicon oxide, as a negative active material exhibits a greater volume change than a secondary battery that does not include SiO.

[0077] In addition, among secondary batteries containing silicon oxide as a negative active material, secondary batteries containing a relatively large weight ratio (10%) of silicon oxide exhibit greater volume change than secondary batteries containing a relatively small weight ratio (3% or 5%) of silicon oxide.

[0078] Figure 5 shows the first profile (TH) and the second profile (dTH / dt) according to the discharge of a secondary battery to which a negative active material not including silicon oxide is applied.

[0079] In Fig. 5, the horizontal axis represents the time elapsed 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).

[0080] In addition, the first profile (TH) represents the thickness of the secondary battery that changes over time or with a change in the state of charge of the secondary battery during the discharge cycle of the secondary battery to which the negative active material containing 100% weight ratio of graphite is applied. In addition, the second profile (dTH / dt) represents the slope of the first profile (TH) that changes over time or with a change in the state of charge 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).

[0081] As illustrated in FIG. 5, the first profile (TH) of the secondary battery shows that the thickness of the secondary battery gradually decreases while discharge is in progress.

[0082] Additionally, the second profile (dTH / dt) of the secondary battery shows that the slope of the first profile (TH) gradually decreases as discharge progresses.

[0083] That is, the second profile (dTH / dt) can be divided into multiple sections (a, b, c). In this case, although an increase or decrease in the slope may occur within each section, the slope of each section gradually decreases as it moves from the first section (a), which corresponds to the early stage of discharge, to the third section (c), which corresponds to the late stage of discharge.

[0084] FIG. 6 shows the first profile (TH1) and the second profile (dTH1 / dt) of a first secondary battery to which a negative active material containing silicon oxide at a weight ratio of 3% is applied.

[0085] In Fig. 6, the horizontal axis represents the time elapsed 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). In some embodiments, the horizontal axis may also represent the SoC (State of Charge) of the first secondary battery.

[0086] As illustrated in Fig. 6, the negative active material of the first secondary battery may include silicon or a mixture of silicon oxide and graphite.

[0087] In addition, the first profile (TH1) of the first secondary battery applied with the negative active material containing graphite and SiO at weight ratios of 97% and 3%, respectively, shows the thickness of the first secondary battery that changes with the passage of time or change in the state of charge of the first secondary battery during the discharge cycle of the first secondary battery.

[0088] Additionally, the second profile (dTH1 / dt) of the first secondary battery represents the slope of the first profile (TH1) that changes with the passage of time or with changes in the state of charge 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).

[0089] The first profile (TH1) of the first secondary battery shows that the thickness of the first secondary battery gradually decreases while the first secondary battery is being discharged.

[0090] However, the second profile (dTH1 / dt) of the first secondary battery shows that the slope of the first profile (TH1) gradually decreases while the first secondary battery is being discharged, and then increases again at a certain point.

[0091] That is, the second profile (dTH1 / dt) can be divided into multiple sections (a1, b1, c1, d1). In this case, in the first section (a1) corresponding to the early stage of discharge, the slope of each section gradually decreases as it goes from the second section (b1) corresponding to the middle stage of discharge to the third section (c1), but in the fourth section (d1) corresponding to the late stage of discharge, the slope changes to an increasing trend.

[0092] This phenomenon is due to the unique characteristics of silicon or silicon oxide that come into play when the SoC (State of Charge) of the secondary battery is relatively low, since the reaction potential of silicon or silicon oxide is relatively higher than that of graphite.

[0093] Accordingly, the secondary battery diagnostic device (100) according to the present invention can diagnose the state of the secondary battery, such as the degree of deterioration of the secondary battery, capacity loss rate, remaining lifespan, etc., by utilizing the unique characteristics of silicon or silicon oxide.

[0094] That is, the processor (120) of the secondary battery diagnosis device (100) according to one embodiment of the present invention estimates the capacity ratio of silicon or silicon oxide using the sensing result of the thickness sensor (110) that senses the thickness change of the secondary battery being charged or discharged, and can diagnose the state of the secondary battery based on this capacity ratio.

[0095] As mentioned above, the capacity ratio refers to the ratio of the capacity provided by silicon or silicon oxide among the capacity of the secondary battery provided by the negative active material.

[0096] For example, the thickness sensor (110) can sense a change in the thickness of the first secondary battery while the first secondary battery is being discharged.

[0097] In addition, the processor (120) uses the sensing result of the thickness sensor (110) to generate a first profile (TH1) representing the thickness of the first secondary battery that changes over time or with a change in the state of charge, as shown in FIG. 6, and a second profile (dTH1 / dt) representing the slope of the first profile (TH1) that changes over time or with a change in the state of charge of the first secondary battery, and can estimate the capacity ratio of SiO corresponding to silicon oxide based on the second profile (dTH1 / dt).

[0098] Specifically, the processor (120) can divide the second profile (dTH1 / dt) into a plurality of sections (a1, b1, c1, d1) and select a target section related to silicon or silicon oxide from among the plurality of sections (a1, b1, c1, d1).

[0099] In this case, the processor (120) can divide the second profile (dTH1 / dt) into a plurality of sections (a1, b1, c1, d1) according to the slope change trend of the first profile (TH1) shown in the second profile (dTH1 / dt). In Fig. 6, the second profile (dTH1 / dt) is divided into four sections, but it can also be divided into two sections. That is, the second profile (dTH1 / dt) can be divided into a first section (a1, b1, c1) in which the slope change trend of the first profile (TH1) is a decreasing trend, and a second section (d1) in which the slope change trend is an increasing trend.

[0100] In addition, the processor (120) may select, as a target section, a section corresponding to a range in which the state of charge of the first secondary battery is below a predetermined threshold among a plurality of sections (a1, b1, c1, d1), and in which the slope change trend of the first profile (TH1) appears different from other sections.

[0101] For example, when the thickness sensor (110) senses a change in the thickness of the first secondary battery while the first secondary battery is being discharged, the processor (120) can select a section (d1) among a plurality of sections (a1, b1, c1, d1) in which the slope change trend of the first profile (TH1) changes from a decreasing trend to an increasing trend, as the target section.

[0102] In this case, the processor (120) may select, as a target section, a fourth section (d1) in which the slope change trend of the first profile (TH1) is increasing, as a section in which the SoC of the first secondary battery is 50% or less among the first to fourth sections (a1, b1, c1, d1).

[0103] Thus, the reason why the target section is selected in a range where the state of charge of the secondary battery is below a predetermined threshold is that, in the case of a secondary battery using nickel as a cathode material, a section in which the slope of the first profile (TH1) temporarily increases appears even at the end of charging or the beginning of discharging when the SoC of the secondary battery is high, and silicon or silicon oxide acts at the beginning of charging or the end of discharging when the SoC of the secondary battery is relatively low.

[0104] As described above, when a target section is selected, the processor (120) can estimate the capacity ratio of silicon or silicon oxide by comparing the total length (L1) of a plurality of sections (a1, b1, c1, d1) with the length (L1') of the target section based on the first axis (horizontal axis) direction indicating time or state of charge (SoC).

[0105] For example, the capacity ratio can be calculated as in mathematical equation 1.

[0106] [Mathematical Formula 1]

[0107] CR = k(L t / L p ) × 100 [%]

[0108] In mathematical expression 1, CR is the capacity ratio of silicon or silicon oxide, and L p is the total length of the second profile, L t is the length of the target section, and k is a predetermined proportional constant. Therefore, the capacity ratio CR1 of SiO in Fig. 6 can be calculated as k(L1' / L1)×100 [%].

[0109] Once the capacity ratio is estimated in this manner, the processor (120) can diagnose the condition of the first secondary battery using the estimated capacity ratio. For example, the processor (120) can diagnose the condition of the first secondary battery by comparing the estimated capacity ratio with a reference capacity ratio of silicon or silicon oxide obtained in advance from a normal secondary battery.

[0110] In one embodiment, the secondary battery diagnosis device (100) according to the present invention may be configured to store reference capacity ratio information of a secondary battery to be diagnosed in advance in the memory (130). The reference capacity ratio information may include information indicating a reference capacity ratio corresponding to a predetermined number of charge cycles or a predetermined number of discharge cycles of the secondary battery to be diagnosed. In this case, the processor (120) may compare the estimated capacity ratio related to the first secondary battery with the reference capacity ratio of the first secondary battery stored in advance in the memory (130) to diagnose the state of the first secondary battery.

[0111] In another embodiment, the processor (120) may be configured to further estimate a weight ratio, which is a ratio of the weight of silicon or silicon oxide to the total weight of the negative active material, before diagnosing the state of the secondary battery to be diagnosed, and compare the estimated capacity ratio with a reference capacity ratio corresponding to the weight ratio to diagnose the state of the secondary battery to be diagnosed.

[0112] In this case, the processor (120) can estimate the weight ratio before the number of charge cycles or discharge cycles of the secondary battery to be diagnosed exceeds a predetermined number.

[0113] For example, the processor (120) can estimate the capacity ratio of silicon oxide after the end of a charge cycle or discharge cycle that has been performed before degradation of the secondary battery to be diagnosed occurs, and estimate the weight ratio of silicon oxide corresponding to the estimated capacity ratio.

[0114] Table 1 shows the capacity ratio corresponding to the weight ratio of SiO contained in the negative electrode active material.

[0115] Weight Ratio (%) Volume Ratio (%) Graphite SiO Graphite SiOCASE 197389.810.2CASE 295583.716.3CASE 3901070.929.1

[0116] As shown in Table 1, silicon oxide contained in the negative active material exhibits a high capacity ratio relative to its weight ratio. Therefore, by including silicon or silicon oxide in the negative active material of a secondary battery, the energy density of the secondary battery can be improved. Thus, since the weight ratio of silicon or silicon oxide and the capacity ratio are correlated, estimating either one can also lead to the estimation of the other.

[0117] Accordingly, the processor (120) can estimate the capacity ratio of silicon or silicon oxide included in the negative electrode active material of the secondary battery to be diagnosed at the initial stage of use of the secondary battery to be diagnosed, and estimate the weight ratio of the silicon or silicon oxide through the estimated capacity ratio.

[0118] Next, the processor (120) can obtain reference capacity ratio information corresponding to the estimated weight ratio among the reference capacity ratio information by weight ratio pre-stored in the memory (130).

[0119] Thereafter, the processor (120) can diagnose the state of the secondary battery to be diagnosed by comparing the acquired reference capacity ratio information with the capacity ratio of silicon or silicon oxide repeatedly estimated in relation to the secondary battery to be diagnosed.

[0120] Figure 7 shows the first and second profiles of a second secondary battery to which a negative active material containing silicon oxide at a weight ratio of 5% is applied.

[0121] In Fig. 7, the horizontal axis represents the time elapsed 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 second secondary battery, and the right vertical axis represents the slope of the first profile (TH2). In some embodiments, the horizontal axis may also represent the SoC (State of Charge) of the second secondary battery.

[0122] As shown in Fig. 7, the first profile (TH2) of the second secondary battery applied with the negative active material containing graphite and SiO at weight ratios of 95% and 5%, respectively, represents the thickness of the second secondary battery that changes with the passage of time or change in the state of charge of the second secondary battery during the discharge cycle of the second secondary battery.

[0123] Additionally, the second profile (dTH2 / dt) of the second secondary battery represents the slope of the first profile (TH2) that changes with the passage of time or with changes in the state of charge of the second secondary battery. In this case, the second profile (dTH2 / dt) can be obtained by differentiating the first profile (TH2) with respect to time (t).

[0124] The first profile (TH2) of the second secondary battery shows that the thickness of the second secondary battery gradually decreases while the second secondary battery is being discharged.

[0125] However, the second profile (dTH2 / dt) of the second secondary battery shows that the slope of the first profile (TH2) gradually decreases while the discharge of the second secondary battery progresses and then increases again at a certain point.

[0126] That is, the second profile (dTH2 / dt) can be divided into multiple sections (a2, b2, c2, d2). In this case, the slope of each section gradually decreases from the first section (a2) corresponding to the early stage of discharge to the second section (b2) and third section (c2) corresponding to the middle stage of discharge, but the slope changes to an increasing trend in the fourth section (d2) corresponding to the late stage of discharge.

[0127] Accordingly, the processor (120) of the secondary battery diagnosis device (100) according to the present invention, as described with reference to FIG. 6, estimates the capacity ratio of silicon or silicon oxide using the sensing result of the thickness sensor (110) that senses the thickness change of the secondary battery being charged or discharged, and can diagnose the state of the secondary battery based on this capacity ratio.

[0128] That is, the thickness sensor (110) can sense the change in thickness of the second secondary battery while the second secondary battery is being discharged.

[0129] In addition, the processor (120) uses the sensing result of the thickness sensor (110) to generate a first profile (TH2) representing the thickness of the second secondary battery that changes over time or with a change in the state of charge, and a second profile (dTH2 / dt) representing the slope of the first profile (TH2) that changes over time or with a change in the state of charge of the second secondary battery, and can estimate the capacity ratio of SiO corresponding to silicon oxide based on the second profile (dTH2 / dt).

[0130] To this end, the processor (120) divides the second profile (dTH2 / dt) into a plurality of sections (a2, b2, c2, d2) and can select a target section related to silicon or silicon oxide from among these plurality of sections (a2, b2, c2, d2).

[0131] For example, the processor (120) divides the second profile (dTH2 / dt) into first to fourth sections (a2, b2, c2, d2), and selects, as a target section, the fourth section (d2), which is a section in which the state of charge of the second secondary battery is below a predetermined threshold among the first to fourth sections (a2, b2, c2, d2), and in which the slope change trend of the first profile (TH2) appears different from other sections.

[0132] Next, the processor (120) can estimate the capacity ratio of silicon or silicon oxide by comparing the total length (L2) of the plurality of sections (a2, b2, c2, d2) with the length (L2') of the target section based on the first axis (horizontal axis) direction indicating time or state of charge (SoC).

[0133] For example, the capacity ratio CR2 of SiO in Fig. 7 can be calculated as k(L2' / L2)×100 [%] according to the above mathematical formula 1.

[0134] When the capacity ratio is estimated in this way, the processor (120) can diagnose the state of the second secondary battery using the estimated capacity ratio as described with reference to FIG. 6.

[0135] Figure 8 shows the first and second profiles of a third secondary battery to which a negative active material containing silicon oxide at a weight ratio of 10% is applied.

[0136] In Fig. 8, the horizontal axis represents the time elapsed 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). In some embodiments, the horizontal axis may also represent the SoC (State of Charge) of the third secondary battery.

[0137] As illustrated in FIG. 8, the first profile (TH3) of the third secondary battery containing graphite and SiO at weight ratios of 90% and 10%, respectively, represents the thickness of the third secondary battery that changes over time or with changes in the state of charge of the third secondary battery during a discharge cycle of the third secondary battery.

[0138] Additionally, the second profile (dTH3 / dt) of the third secondary battery represents the slope of the first profile (TH3) that changes with the passage of time or with changes in the state of charge 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).

[0139] The first profile (TH3) of the third secondary battery shows that the thickness of the third secondary battery gradually decreases while the third secondary battery is being discharged.

[0140] However, the second profile (dTH3 / dt) of the third secondary battery shows that the slope of the first profile (TH3) gradually decreases while the third secondary battery is being discharged, and then increases again at a certain point.

[0141] That is, the second profile (dTH3 / dt) can be divided into multiple sections (a3, b3, c3, d3). In this case, in the first section (a3) ​​corresponding to the early stage of discharge, the slope of each section gradually decreases as it goes from the second section (b3) corresponding to the middle stage of discharge to the third section (c3), but in the fourth section (d3) corresponding to the late stage of discharge, the slope changes to an increasing trend.

[0142] Accordingly, the processor (120) of the secondary battery diagnosis device (100) according to the present invention, as described with reference to FIG. 6, estimates the capacity ratio of silicon or silicon oxide using the sensing result of the thickness sensor (110) that senses the thickness change of the secondary battery being charged or discharged, and can diagnose the state of the secondary battery based on this capacity ratio.

[0143] That is, the thickness sensor (110) can sense the change in thickness of the third secondary battery while the third secondary battery is being discharged.

[0144] In addition, the processor (120) uses the sensing result of the thickness sensor (110) to generate a first profile (TH3) representing the thickness of the third secondary battery that changes over time or with a change in the state of charge, and a second profile (dTH3 / dt) representing the slope of the first profile (TH3) that changes over time or with a change in the state of charge of the third secondary battery, and can estimate the capacity ratio of SiO corresponding to silicon oxide based on the second profile (dTH3 / dt).

[0145] To this end, the processor (120) divides the second profile (dTH3 / dt) into a plurality of sections (a3, b3, c3, d3) and can select a target section related to silicon or silicon oxide from among these plurality of sections (a3, b3, c3, d3).

[0146] For example, the processor (120) may divide the second profile (dTH3 / dt) into first to fourth sections (a3, b3, c3, d3), and select, as a target section, the fourth section (d3), which is a section in which the state of charge of the third secondary battery is below a predetermined threshold among the first to fourth sections (a3, b3, c3, d3), and in which the slope change trend of the first profile (TH3) appears different from other sections.

[0147] Next, the processor (120) can estimate the capacity ratio of silicon or silicon oxide by comparing the total length (L3) of the plurality of sections (a3, b3, c3, d3) with the length (L3') of the target section based on the first axis (horizontal axis) direction indicating time or state of charge (SoC).

[0148] For example, the capacity ratio CR3 of SiO in Fig. 8 can be calculated as k(L3' / L3)×100 [%] according to the above mathematical formula 1.

[0149] When the capacity ratio is estimated in this way, the processor (120) can diagnose the state of the third secondary battery using the estimated capacity ratio as described with reference to FIG. 6.

[0150] Figure 9 shows a graph showing the change in thickness during charging and discharging of a secondary battery according to the number of charge / discharge cycles of the secondary battery.

[0151] As illustrated in Figure 9, as the number of charge / discharge cycles increases, the thickness of the secondary battery gradually increases. Furthermore, if the pause time between the end of charge (t1) and the start of discharge (t2) is the same for all charge / discharge cycles, the total charge / discharge time gradually decreases as the number of charge / discharge cycles increases.

[0152] Accordingly, the first profile representing the thickness of the secondary battery that changes over time or with a change in the state of charge, and the second profile obtained by differentiating the first profile with respect to time or SoC also change according to the number of cycles of the secondary battery, and if the secondary batteries to be diagnosed are normal secondary batteries, the profiles will show similar change patterns according to the number of cycles.

[0153] Figure 10 shows a second profile in which the thickness of a secondary battery is differentiated with respect to time during discharge.

[0154] As illustrated in Fig. 10, the second profile, which is obtained by differentiating the thickness of a secondary battery with respect to time during discharge to which a negative active material including silicon or silicon oxide is applied, gradually decreases as discharge progresses and then increases in the target section (TS) at the end of discharge.

[0155] The length of this target section (TS) in the horizontal direction varies depending on the number of discharge cycles of the secondary battery.

[0156] In Fig. 11, a second profile in which the thickness of a secondary battery is differentiated with respect to time during discharge is shown for each number of discharge cycles of the secondary battery.

[0157] As illustrated in Fig. 11, the pattern of the second profile and the length of the target section may vary 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 exhibit a tendency to gradually shrink. Furthermore, as the pattern of the second profile changes, the location and length of the target section may also change.

[0158] For example, when a secondary battery having a negative active material containing graphite and SiO at weight ratios of 90% and 10%, respectively, is in a normal state, 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%. In addition, the target sections (TS2, TS3, TS4) of the second profiles corresponding to the 50th, 100th, and 150th discharge cycles, respectively, may gradually become longer depending on the number of discharge cycles and may have lengths corresponding to a capacity ratio close to 29.1%.

[0159] On the other hand, if the secondary battery is in an abnormal state, such as swelling occurring in the secondary battery as the discharge cycle is repeated or loss of the conductive path occurring due to pulverization of SiO, the target sections (TS1, TS2, TS3, TS4) of the second profiles gradually lengthen according to the number of discharge cycles and then abruptly shorten again.

[0160] Accordingly, the processor (120) of the secondary battery diagnosis device (100) according to the present invention can repeatedly estimate the capacity ratio of silicon or silicon oxide included in the negative electrode active material while the charge cycle or discharge cycle of the secondary battery to be diagnosed is repeated, and can diagnose the state of the secondary battery to be diagnosed based on the change trend of the estimated capacity ratios.

[0161] FIG. 12 is a flowchart illustrating a secondary battery diagnosis method according to one embodiment of the present invention.

[0162] With reference to FIG. 12, detailed operations of the secondary battery diagnostic device (100) according to the present invention can be described in time series.

[0163] When a charge and / or discharge cycle of a secondary battery to which a negative electrode active material including silicon or silicon oxide is applied is initiated, a thickness sensor (110) of a secondary battery diagnostic device (100) senses a change in the thickness of the secondary battery according to a change in the volume of the negative electrode active material while the secondary battery is being charged or discharged (S10, S20).

[0164] Next, the processor (120) of the secondary battery diagnostic device (100) estimates a capacity ratio, which is the ratio of the capacity provided by the silicon or silicon oxide among the capacity of the secondary battery provided by the negative electrode active material, using the sensing result of the thickness sensor (110). In this case, the estimated capacity ratio can be stored in the memory (130) of the secondary battery diagnostic device (100) (S30).

[0165] Next, when the number of cycles of the secondary battery reaches a predetermined standard number of cycles, the processor (120) can diagnose the condition of the secondary battery based on the estimated capacity ratio (S40, S50).

[0166] On the other hand, if the number of cycles of the secondary battery has not reached the 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 initiated, the secondary battery thickness sensing process (S20) and the capacity ratio estimation process of silicon or silicon oxide can be repeated (S40, S80, S90).

[0167] In the secondary battery status diagnosis process (S50), if the secondary battery status is diagnosed as being poor, the processor (120) can control the output device (140) to output a predetermined alarm (S60, S70).

[0168] On the other hand, in the secondary battery status diagnosis process (S50), if the secondary battery is diagnosed as not being in a bad condition, the processor (120) stores the diagnosis result in the memory (130) and then waits, and when the next charging and / or discharging cycle of the secondary battery is initiated, the above-described processes (S20 to S50) can be repeated (S60, S80, S90).

[0169] FIG. 13 is a flowchart illustrating a capacity ratio estimation process of a secondary battery diagnosis method according to one embodiment of the present invention.

[0170] As illustrated in FIG. 13, when the thickness sensor (110) senses a change in the thickness of the secondary battery while the secondary battery is being charged and / or discharged, the processor (120) can use the sensing result of the thickness sensor (110) to generate a first profile indicating the thickness of the secondary battery that changes over time or according to a change in the state of charge (SoC) of the secondary battery (S32).

[0171] Next, the processor (120) can generate a second profile based on the first profile, which represents the slope of the first profile that changes over time or according to changes in the state of charge (SoC) of the secondary battery (S34). In this case, the second profile can be obtained by differentiating the first profile with respect to time or SoC.

[0172] Next, the processor (120) can estimate the capacity ratio of silicon or silicon oxide based on the second profile.

[0173] Specifically, the processor (120) can divide the second profile into a plurality of sections and select a target section related to the silicon or the silicon oxide from among the plurality of sections (S36).

[0174] Next, the processor (120) can estimate the capacity ratio by comparing the length of the entire plurality of sections with the length of the target section based on the first axis direction (S38).

[0175] In this case, the processor (120) can divide the second profile into multiple sections according to the slope change trend of the first profile shown in the second profile.

[0176] In addition, the processor (120) may select, as a target section, a section corresponding to a range in which the state of charge of the first secondary battery among the plurality of sections is below a predetermined threshold, and a section in which the slope change trend of the first profile appears different from other sections.

[0177] For example, if the first profile relates to a change in thickness during discharge of the secondary battery, the processor (120) may select, as the target section, a section among a plurality of sections of the second profile in which the slope change trend of the first profile changes from a decreasing trend to an increasing trend.

[0178] As described above, when a target section is selected, the processor (120) can estimate the capacity ratio of silicon or silicon oxide by comparing the total length of the plurality of sections with the length of the target section. The capacity ratio can be calculated as in the mathematical expression 1.

[0179] Once the capacity ratio is estimated in this way, the processor (120) can diagnose the condition of the secondary battery using the estimated capacity ratio. For example, the processor (120) can diagnose the condition of the secondary battery by comparing the estimated capacity ratio with a reference capacity ratio of silicon or silicon oxide obtained in advance from a normal secondary battery.

[0180] In one embodiment, the secondary battery diagnosis device (100) according to the present invention can store reference capacity ratio information of a secondary battery to be diagnosed in advance in the memory (130). The reference capacity ratio information can include information indicating a reference capacity ratio corresponding to a predetermined number of charge cycles or a 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 related to the secondary battery with the reference capacity ratio stored in advance in the memory (130).

[0181] In another embodiment, before diagnosing the state of the secondary battery, the processor (120) may further estimate a weight ratio, which is a ratio of the weight of silicon or silicon oxide to the total weight of the negative active material, and compare the estimated capacity ratio with a reference capacity ratio corresponding to the weight ratio, thereby diagnosing the state of the secondary battery.

[0182] In this case, the processor (120) can estimate the weight ratio before the number of charge cycles or discharge cycles of the secondary battery to be diagnosed exceeds a predetermined number.

[0183] For example, the processor (120) can estimate the capacity ratio of silicon oxide after the end of a charge cycle or discharge cycle that has been performed before degradation of the secondary battery to be diagnosed occurs, and estimate the weight ratio of silicon oxide corresponding to the estimated capacity ratio.

[0184] Next, the processor (120) can obtain reference capacity ratio information corresponding to the estimated weight ratio among the reference capacity ratio information by weight ratio pre-stored in the memory (130).

[0185] Thereafter, 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 repeatedly estimated in relation to the secondary battery.

[0186] Fig. 14 illustrates a vehicle (2) according to one embodiment of the present invention.

[0187] As illustrated in FIG. 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 a secondary battery of a battery pack (10) mounted on the vehicle (2). In this case, the secondary battery diagnostic device may be configured to be linked with an ECU (Electronic Control Unit) of the vehicle (2).

[0188] In another embodiment, the secondary battery diagnostic device may be included in a battery pack (10) mounted on the vehicle (2). In this case, the secondary battery diagnostic device may be configured to be linked with a BMS (Battery Management System) of the battery pack (10).

[0189] For reference, the secondary battery diagnostic device according to the present invention can be applied to various electric devices or electric systems that use secondary batteries other than vehicles, and can also be applied to ESS (Energy Storage System).

[0190] As described above, according to the present invention, while a secondary battery to which an anode active material including silicon or silicon oxide is applied is being charged or discharged, a thickness sensor senses a change in the thickness of the secondary battery according to a change in the volume of the anode 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 a capacity ratio, which is a ratio of the electrical capacity provided by silicon oxide among the electrical capacities provided by the anode active material of the secondary battery, and diagnoses the state of the secondary battery based on this capacity ratio, thereby enabling the state of the secondary battery to be diagnosed efficiently and accurately.

[0191] In addition, the processor, before estimating the capacity ratio, sequentially generates a first profile representing the thickness of the secondary battery that changes with the passage of time or with a change in the state of charge of the secondary battery, and a second profile representing the slope of the first profile that changes with the passage of time or with a change in the state of charge of the secondary battery, using the sensing result of the thickness sensor, and estimates the capacity ratio based on this second profile, thereby making it possible to diagnose the state of the secondary battery in a simplified manner independent of electrical factors of the secondary battery.

[0192] In addition, the processor divides the second profile into a plurality of sections, selects a target section exhibiting unique characteristics of silicon or silicon oxide from among the plurality of sections, and estimates the capacity ratio by comparing the length of the entire plurality of sections with the length of the target section, thereby reducing the amount of computation required to diagnose the state of the secondary battery, and as a result, improving the speed of diagnosing the secondary battery.

[0193] In addition, the processor estimates a weight ratio, which is a ratio of the weight of silicon or silicon oxide among the total weight of the negative active material, and compares the capacity ratio with a reference capacity ratio corresponding to the estimated weight ratio to diagnose the state of the secondary battery, thereby diagnosing the state of the target secondary battery even when the weight ratio of silicon or silicon oxide included in the negative active material of the target secondary battery is unknown.

[0194] In addition, since a thickness sensor for sensing a change in the thickness of a secondary battery is configured to sense a change in the thickness of the secondary battery by measuring a distance from a predetermined position to the surface of the secondary battery, not only can the change in the thickness of the secondary battery be sensed for each secondary battery, but a plurality of secondary batteries stacked in the thickness direction can be made into one secondary battery module, and a change in the overall thickness of the secondary battery module can be sensed. That is, the secondary battery diagnosis device according to the present invention can be included in a battery pack or vehicle having a plurality of secondary batteries, and can diagnose the status of the plurality of secondary batteries in units of secondary battery modules.

[0195] Furthermore, it goes without saying that embodiments according to the present invention can solve various technical problems other than those mentioned in the present specification, not only in the relevant technical field but also in related technical fields.

[0196] The present invention has been described with reference to specific embodiments. However, those skilled in the art will clearly understand that various modifications can be implemented within the technical scope of the present invention. Therefore, the embodiments disclosed above should be considered illustrative rather than limiting. In other words, the true scope of the present invention is set forth in the claims, and all differences within the scope equivalent thereto should be construed as being encompassed by the present invention.

[0197] [Explanation of symbols]

[0198] 100: Secondary battery diagnostic device

[0199] 110: Thickness sensor

[0200] 120: Processor

[0201] 130: Memory

[0202] 140: Output device

Claims

1. A secondary battery diagnostic device that diagnoses the status of a secondary battery to which a negative electrode active material including silicon or silicon oxide is applied. A thickness sensor that senses a change in the thickness of the secondary battery according to a change in the volume of the negative active material while the secondary battery is being charged or discharged; and A secondary battery diagnostic device including a processor that estimates a capacity ratio, which is a ratio of the capacity provided by the silicon or silicon oxide among the capacities of the secondary battery provided by the negative electrode active material, using the sensing results of the thickness sensor, and diagnoses the state of the secondary battery based on the capacity ratio.

2. In paragraph 1, A secondary battery diagnostic device characterized in that the thickness sensor is configured to sense a change in the thickness of the secondary battery by measuring the distance from a predetermined position to the surface of the secondary battery.

3. In paragraph 1, A secondary battery diagnostic device characterized in that the processor is configured to generate, before estimating the capacity ratio, a first profile representing the thickness of the secondary battery that changes with the passage of time or with a change in the state of charge of the secondary battery, and a second profile representing the slope of the first profile that changes with the passage of time or with a change in the state of charge of the secondary battery, using the sensing result of the thickness sensor, and to estimate the capacity ratio based on the second profile.

4. In paragraph 3, A secondary battery diagnostic device characterized in that the processor is configured to divide the second profile into a plurality of sections, select a target section related to the silicon or the 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 based on the first axis direction.

5. In paragraph 4, A secondary battery diagnostic device, characterized in that the processor is configured to divide the second profile into the plurality of sections according to the slope change trend of the first profile shown in the second profile.

6. In paragraph 4, A secondary battery diagnostic device characterized in that the processor is configured to select, as the target section, a section corresponding to a range in which the state of charge of the secondary battery is below a predetermined threshold among the plurality of sections, and in which a slope change trend of the first profile appears different from other sections.

7. In paragraph 4, The thickness sensor is configured to sense a change in the thickness of the secondary battery while the secondary battery is being discharged, A secondary battery diagnostic device characterized in that the processor is configured to select, as the target section, a section in which the slope change trend of the first profile among the plurality of sections has changed from a decreasing trend to an increasing trend.

8. In paragraph 1, A secondary battery diagnosis device characterized in that the processor is configured to further estimate a weight ratio, which is a ratio of the weight of the silicon or silicon oxide among the total weight of the negative active material, before diagnosing the state of the secondary battery, and compare the capacity ratio with a reference capacity ratio corresponding to the weight ratio to diagnose the state of the secondary battery.

9. In paragraph 8, A secondary battery diagnostic device 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. In paragraph 1, A secondary battery diagnostic device characterized in that the processor is configured to repeatedly estimate the capacity ratio while the charge cycle or discharge cycle of the secondary battery is repeated, and to diagnose the state of the secondary battery based on a change trend of the estimated capacity ratios.

11. In any one of paragraphs 1 to 10, A secondary battery diagnostic device, characterized in that the negative electrode active material comprises a mixture of the silicon or the silicon oxide and graphite.

12. In any one of paragraphs 1 to 10, A secondary battery diagnostic device characterized in that the secondary battery is composed of a pouch-type secondary battery.

13. A secondary battery diagnosis method for diagnosing the state of a secondary battery to which a negative electrode active material including silicon or silicon oxide is applied, Step A, in which a thickness sensor senses a change in the thickness of the secondary battery according to a change in the volume of the negative active material while the secondary battery is being charged or discharged; Step B, in which the processor uses the sensing result of the thickness sensor to estimate a capacity ratio, which is a ratio of the capacity provided by the silicon or silicon oxide among the capacities of the secondary battery provided by the negative active material; and A secondary battery diagnosis method including a step C in which the processor diagnoses the state of the secondary battery based on the capacity ratio.

14. In paragraph 13, Step B above is, Step B1 of generating a first profile representing the thickness of the secondary battery that changes over time or according to a change in the charging state of the secondary battery using the sensing result of the thickness sensor; Step B2 of generating a second profile based on the first profile, which represents the slope of the first profile that changes over time or according to a change in the state of charge of the secondary battery; and A secondary battery diagnosis method characterized by including a B3 step of estimating the capacity ratio based on the second profile.

15. In paragraph 14, The above step B3 is, A step of dividing the second profile into a plurality of sections and selecting a target section related to the silicon or the silicon oxide from among the plurality of sections; and A secondary battery diagnosis method characterized by including a step of estimating the capacity ratio by comparing the length of the entire plurality of sections with the length of the target section based on the first axis direction.

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