Battery diagnostic device and method

Abstract

A battery diagnostic method according to an embodiment of the present invention is a method for diagnosing a battery having a positive electrode using an active material, and includes the steps of: generating a differential profile indicating a correspondence relationship between a differential capacity, which is the derivative of the capacity of the positive electrode with respect to the potential of the positive electrode, and the potential of the positive electrode; generating a plurality of Gaussian curves that form a curve corresponding to the differential profile when combined; using the plurality of Gaussian curves to generate diagnostic information about the redox reaction amount of one or two or more elements among a plurality of different elements included in the active material; and diagnosing the battery on the basis of the diagnosis information.

Description

Battery diagnostic device and method

[0001] This application claims priority from Korean Patent Application No. 10-2024-0022841, filed February 16, 2024, the entire disclosure of which is incorporated herein by reference.

[0002] The present invention relates to a battery diagnostic device and method, and more particularly, to a battery diagnostic device and method for non-destructively diagnosing the state of a rechargeable battery.

[0003] Recently, as the demand for portable electronic products such as laptops, digital cameras, and mobile phones has rapidly increased, and the development of electric vehicles, energy storage systems, robots, and satellites has been in full swing, research on high-performance, rechargeable, and high-energy-density batteries is actively being conducted.

[0004] Rechargeable batteries include lithium 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. Among these, lithium batteries offer a relatively long lifespan due to minimal memory effect compared to nickel-based batteries, a very low self-discharge rate, and high energy density. Consequently, their application scope is gradually expanding.

[0005] The positive and negative electrodes of these batteries gradually deteriorate, losing their original electrical capacity as they undergo repeated charge and discharge cycles. Therefore, accurate diagnosis of battery condition is essential to accurately predict the battery's usable lifespan, remaining service life, and replacement timing.

[0006] However, since the existing technology diagnoses the state of the battery through the SOH (State of Health) of the entire battery, when an active material that causes a redox reaction and phase transformation, such as Mn-rich, is applied to the battery electrode, there is a problem in that it cannot provide information on the amount of redox reaction of the active material, and it cannot diagnose the state of the battery related to the amount of redox reaction of the active material.

[0007] The technical problem to be solved by the present invention is to provide a battery diagnosis device and method that can provide information on the amount of redox reaction of an active material applied to a positive electrode of a battery and can diagnose the state of a battery related to the amount of redox reaction of the active material.

[0008] Another technical problem to be solved by the present invention is to provide a battery diagnostic device and method that can extend the life of a battery and improve safety.

[0009] A battery diagnosis method according to one aspect of the present invention is a method for diagnosing a battery having a positive electrode to which an active material is applied, the method comprising: a differential profile generation step of generating, at predetermined diagnosis intervals, a differential capacity obtained by differentiating the capacity of the positive electrode with respect to the potential of the positive electrode, and a differential profile indicating a correspondence between the potential of the positive electrode; a Gaussian fitting step of generating a plurality of Gaussian curves that form a curve corresponding to the differential profile when combined with each other; a diagnostic information generation step of generating diagnostic information regarding a redox reaction amount of one or more elements among a plurality of different elements included in the active material using the plurality of Gaussian curves; and a diagnostic step of diagnosing the battery based on the diagnostic information.

[0010] In one embodiment, the differential profile generation step may include a first generation step of measuring electrical values ​​of the battery using an electrical sensor while the battery is being charged or discharged, and generating a battery profile indicating a correspondence between a capacity and a voltage of the battery based on the measured electrical values; an anode profile acquisition step of obtaining an anode profile indicating a correspondence between a capacity and a potential of the anode based on the battery profile; and a second generation step of generating the differential profile by differentiating the anode profile with respect to the potential of the anode.

[0011] In one embodiment, the battery diagnosis method may further include, before the differential profile generation step, a step of storing a plurality of reference positive electrode profiles and a plurality of reference negative electrode profiles in a memory, and the positive electrode profile acquisition step may include a step of selecting a reference positive electrode profile and a reference negative electrode profile, which generate a profile most similar to the battery profile when combined, from among the plurality of reference positive electrode profiles and the plurality of reference negative electrode profiles stored in the memory; and a step of acquiring the selected reference positive electrode profile as the positive electrode profile.

[0012] In one embodiment, the diagnostic information generating step may include: a step of calculating a first quantification value quantifying the redox reaction amount of the first element based on a first Gaussian curve corresponding to the first element included in the active material among the plurality of Gaussian curves; a step of calculating a second quantification value quantifying the redox reaction amount of the second element based on a second Gaussian curve corresponding to the second element included in the active material among the plurality of Gaussian curves; and a step of generating the diagnostic information including the first quantification value and the second quantification value.

[0013] In one embodiment, the diagnosis step may include a redox ratio calculation step for calculating a redox ratio indicating a ratio of a redox reaction amount of the second element to a redox reaction amount of the first element based on the first quantification value and the second quantification value included in the diagnosis information; and a judgment step for determining a state of the battery based on the redox ratio.

[0014] In one embodiment, the judging step may include a step of judging the state of the battery by referring to a trend in which the redox ratio changes over a plurality of diagnostic cycles.

[0015] In one embodiment, the active material may include lithium manganese oxide, the first element may be manganese, and the second element may be oxygen.

[0016] In one embodiment, the judgment step may further include a step of judging the state of the battery as abnormal when the change trend of the redox ratio changes from a decreasing trend to an increasing trend.

[0017] In one embodiment, the battery diagnosis method may further include a step of controlling a charger that charges the battery according to a diagnosis result in the diagnosis step, thereby controlling a voltage when charging of the battery is completed or controlling a current rate of a current that charges the battery.

[0018] According to another aspect of the present invention, a battery diagnostic device is a device for diagnosing a battery having a positive electrode to which an active material is applied, the device comprising: a differential profile generating unit configured to generate, at each predetermined diagnostic cycle, a differential profile indicating a correspondence between a differential capacity obtained by differentiating a capacity of the positive electrode with respect to a potential of the positive electrode and a potential of the positive electrode; a Gaussian fitting unit configured to generate a plurality of Gaussian curves that form a curve corresponding to the differential profile when combined with each other; a diagnostic information generating unit configured to generate diagnostic information regarding a redox reaction amount of one or more elements among a plurality of different elements included in the active material using the plurality of Gaussian curves; and a diagnostic unit configured to diagnose the battery based on the diagnostic information.

[0019] In one embodiment, the diagnostic information generation unit may be configured to generate the diagnostic information including the first quantification value and the second quantification value by calculating a first quantification value that quantifies the redox reaction amount of the first element based on a first Gaussian curve corresponding to the first element included in the active material among the plurality of Gaussian curves, and to calculate a second quantification value that quantifies the redox reaction amount of the second element based on a second Gaussian curve corresponding to the second element included in the active material among the plurality of Gaussian curves.

[0020] In one embodiment, the diagnostic unit may include a redox ratio calculation module configured to calculate a redox ratio indicating a ratio of a redox reaction amount of the second element to a redox reaction amount of the first element based on the first quantification value and the second quantification value included in the diagnostic information; and a judgment module configured to determine a state of the battery based on the redox ratio.

[0021] In one embodiment, the judgment module may be configured to judge the state of the battery by referring to a trend in which the redox ratio changes over a plurality of diagnostic cycles.

[0022] A battery pack according to another aspect of the present invention includes the battery diagnostic device described above.

[0023] A vehicle according to another aspect of the present invention includes the battery diagnostic device described above.

[0024] The present invention performs Gaussian fitting on a differential profile representing a correspondence between a differential capacity obtained by differentiating the capacity of a positive electrode of a battery with respect to the potential of the positive electrode and the potential of the positive electrode, thereby generating Gaussian curves corresponding to the differential profile, and generating information on the redox reaction amount of an active material applied to the positive electrode using these Gaussian curves, thereby providing information on the redox reaction amount of an active material applied to the positive electrode of the battery, and diagnosing the state of the battery related to the redox reaction amount of the active material.

[0025] In addition, the present invention can increase the accuracy and reliability of diagnostic results by quantifying the redox reaction amount of elements forming the active material and providing a quantification value corresponding to the redox reaction amount.

[0026] In addition, the present invention can extend the life of a battery and improve safety by controlling the charging and / or discharging conditions of the battery according to the diagnosis results regarding the battery.

[0027] 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.

[0028] FIG. 1 is a block diagram showing a battery diagnostic device according to one embodiment of the present invention.

[0029] Figure 2 is a drawing showing an example of a bipolar profile map generated based on a bipolar half-cell.

[0030] Figure 3 is a diagram showing an example of a bipolar profile map supplemented through simulation.

[0031] Figure 4 is a drawing showing an example of a cathode profile map generated based on a cathode half-cell.

[0032] Figure 5 is a drawing showing an example of a positive electrode profile and a negative electrode profile corresponding to a battery profile.

[0033] Figure 6 is a drawing showing a differential profile obtained by differentiating the anode profile with respect to the potential of the anode.

[0034] Figure 7 is a diagram showing Gaussian curves generated by performing Gaussian fitting on the differential profile shown in Figure 6.

[0035] Figure 8 is a graph showing the trend of changes in the amount of redox reactions of elements included in the positive electrode active material as the number of charge / discharge cycles increases.

[0036] Figure 9 is a graph showing the trend of changes in the redox ratio of manganese to oxygen as the number of charge / discharge cycles increases.

[0037] Fig. 10 is a flowchart illustrating a battery diagnosis method according to one embodiment of the present invention.

[0038] FIG. 11 is a drawing showing a battery pack according to one embodiment of the present invention.

[0039] Fig. 12 is a drawing showing a vehicle according to one embodiment of the present invention.

[0040] 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.

[0041] FIG. 1 is a block diagram showing a battery diagnostic device (100) according to one embodiment of the present invention.

[0042] As illustrated in FIG. 1, a battery diagnostic device (100) according to one embodiment of the present invention is configured to non-destructively diagnose a rechargeable battery. To this end, the battery diagnostic device (100) includes a control unit (110). A target battery to be diagnosed according to the present invention has a positive electrode and a negative electrode that are electrically insulated from each other by a separator. An active material containing a plurality of different elements is applied to the positive electrode. For example, the active material may include lithium manganese oxide.

[0043] The above control unit (110) may include one or more general-purpose processors or application-specific integrated circuits (ASICs) for executing battery diagnosis logic, and may optionally further include hardware such as registers and memories depending on the embodiment. The control unit (110) may be configured with a combination of hardware such as a processor and software such as a computer program. That is, the battery diagnosis logic of the control unit (110) may be configured as a computer program and stored in the control unit's (110) own memory or the storage unit (140) described below, and the stored computer program may be configured to be executed through the hardware of the control unit (110).

[0044] Meanwhile, the control unit (110) includes a differential profile generation unit (111), a Gaussian fitting unit (112), a diagnostic information generation unit (113), and a diagnostic unit (114) as detailed components for diagnosing a battery.

[0045] The above differential profile generation unit (111) is configured to generate a differential profile representing a correspondence between the differential capacity obtained by differentiating the capacity of the positive electrode of the target battery with respect to the potential of the positive electrode, at each predetermined diagnostic cycle. In some embodiments, the diagnostic cycle may be set to be identical to the charge / discharge cycle of the target battery.

[0046] For example, the differential profile generation unit (111) may measure electrical values ​​of the target battery using an electrical sensor while the target battery is being charged or discharged, and generate a battery profile indicating a correspondence between the capacity and voltage of the target battery based on the measured electrical values.

[0047] Next, the differential profile generation unit (111) can obtain an anode profile indicating a correspondence between the capacity and potential of the anode based on the battery profile.

[0048] To this end, the control unit (110) may store a plurality of reference anode profiles and a plurality of reference cathode profiles in advance in a predetermined memory before acquiring the anode profile.

[0049] In this case, the differential profile generation unit (111) selects a reference positive electrode profile and a reference negative electrode profile that, when combined with each other, generate a profile most similar to the battery profile among a plurality of reference positive electrode profiles and a plurality of reference negative electrode profiles stored in the memory, and can obtain the selected reference positive electrode profile as the positive electrode profile of the target battery.

[0050] The above Gaussian fitting unit (112) is configured to perform Gaussian fitting on the differential profile and generate a plurality of Gaussian curves that form a curve corresponding to the differential profile when combined with each other.

[0051] The above diagnostic information generation unit (113) is configured to generate diagnostic information regarding the redox reaction amount of one or more elements among the plurality of elements using the plurality of Gaussian curves.

[0052] For example, the diagnostic information generation unit (113) may calculate a first quantification value that quantifies the redox reaction amount of the first element based on a first Gaussian curve corresponding to the first element included in the active material among the plurality of Gaussian curves. In this case, the diagnostic information generation unit (113) may calculate the first quantification value by integrating the first Gaussian curve with respect to the potential of the positive electrode over the entire potential range of the positive electrode.

[0053] In addition, the diagnostic information generation unit (113) can calculate a second quantification value that quantifies the redox reaction amount of the second element based on a second Gaussian curve corresponding to the second element included in the active material among the plurality of Gaussian curves. In this case, the diagnostic information generation unit (113) can calculate the second quantification value by integrating the second Gaussian curve with respect to the potential of the positive electrode over the entire potential range of the positive electrode.

[0054] And the above diagnostic information generation unit (113) can generate diagnostic information including the first quantification value and the second quantification value.

[0055] The above diagnostic unit (114) is configured to diagnose the target battery based on the above diagnostic information.

[0056] In one embodiment, the diagnostic unit (114) may include a redox ratio calculation module (114a) and a judgment module (114b).

[0057] In this case, the redox ratio calculation module (114a) may be configured to calculate a redox ratio indicating a ratio of the redox reaction amount of the second element to the redox reaction amount of the first element, based on the first quantification value and the second quantification value included in the diagnostic information.

[0058] The above judgment module (114b) can be configured to judge the state of the target battery based on the redox ratio.

[0059] For example, the judgment module (114b) can judge the state of the target battery by referring to the trend of change in the redox ratio over a plurality of diagnosis cycles.

[0060] In one embodiment, the active material applied to the positive electrode may be a manganese-rich active material such as lithium manganese oxide.

[0061] In this case, the active material applied to the positive electrode may be represented by the following chemical formula 1.

[0062] [Chemical Formula 1]

[0063] Li 1+a [Ni b Co c Mn d M 1 e ]O 2+a

[0064] In the above chemical formula 1, M 1 The silver metal ions are at least one selected from the group consisting of Al, B, Co, W, Mg, V, Ti, Zn, Ga, In, Ru, Nb, Sn, Sr, and Zr, and 0≤a≤0.5, 0≤b≤0.5, 0≤c≤0.5, 0.5≤d≤1.0, 0≤e≤0.5, and b+c+d+e=1.

[0065] That is, the active material applied to the positive electrode may be an active material in which the mole fraction of manganese (Mn) among all transition metals included in the active material, excluding lithium (Li), is 50% or more.

[0066] In another embodiment, the active material applied to the positive electrode may be represented by the following chemical formula 2.

[0067] [Chemical Formula 2]

[0068] Li 1+a [Ni b Co c Mn d M 1 e ]O 2+a

[0069] In the above chemical formula 1, M 1 The silver metal ions are at least one selected from the group consisting of Al, B, Co, W, Mg, V, Ti, Zn, Ga, In, Ru, Nb, Sn, Sr, and Zr, and 0≤a≤0.4, 0≤b≤0.4, 0≤c≤0.4, 0.6≤d≤1.0, 0≤e≤0.5, and b+c+d+e=1.

[0070] For example, the active material applied to the positive electrode may be an active material in which the mole fraction of manganese (Mn) among all transition metals contained in the active material excluding lithium (Li) is 60% or more. That is, the active material applied to the positive electrode may be a lithium manganese oxide such as Li2MnO3.

[0071] In this case, the redox ratio, which is a diagnostic factor of the target battery, may be the ratio of the redox reaction amount of oxygen to the redox reaction amount of manganese.

[0072] In addition, the judgment module (114b) can determine that the state of the target battery is abnormal when the change trend of the redox ratio according to the increase in charge / discharge cycles changes from a decreasing trend to an increasing trend.

[0073] In one embodiment, the control unit (110) may further include a diagnosis result notification unit (115). In this case, the diagnosis result notification unit (115) may be configured to control a predetermined output device to output a visual, auditory, or audiovisual notification signal corresponding to the diagnosis result of the target battery.

[0074] In one embodiment, the control unit (110) may further include a battery management unit (116). In this case, the battery management unit (116) may be configured to control charging conditions and / or discharging conditions of the target battery according to the diagnosis results of the diagnosis unit (114). That is, the battery management unit (116) may control a charger that charges the target battery to control the voltage upon completion of charging of the target battery or to control the current rate of the current that charges the target battery.

[0075] For example, when the state of the target battery is diagnosed as abnormal, the battery management unit (116) may be configured to control a charger that charges the target battery to reduce the voltage when charging of the target battery is completed or to reduce the current rate of the current that charges the target battery.

[0076] Meanwhile, the battery management unit (116) may be configured to control the cooling device (18) described later to lower the temperature of the target battery.

[0077] The differential profile generation unit (111), Gaussian fitting unit (112), diagnostic information generation unit (113), diagnostic unit (114), diagnostic result notification unit (115), and battery management unit (116) of the above-described control unit (110) may be implemented as a combination of a processor and a program executed by the processor. In this case, the control unit (110) may be implemented as a single processor or as two or more processors that are interconnected.

[0078] In one embodiment, the battery diagnostic device (100) may further include a communication unit (120). The communication unit (120) may be configured to receive data transmitted from a remotely located server or communication terminal via a wired and / or wireless communication network and transmit the data to the control unit (110), or transmit control signals, diagnostic data, etc. processed by the control unit (110) to the remotely located server or communication terminal. To this end, the communication unit (120) may include a communication modem that performs wired communication and / or wireless communication.

[0079] In one embodiment, the battery diagnostic device (100) may further include an input unit (130). The input unit (130) may be configured to receive commands or data from a user or administrator. To this end, the input unit (130) may include an input device such as a keyboard, operation buttons, or a touch panel.

[0080] In one embodiment, the battery diagnostic device (100) may further include a storage unit (140). The storage unit (140) may be configured to store and manage data necessary for the operation of the battery diagnostic device (100). To this end, the storage unit (140) may include a memory. For example, the storage unit (140) may include one or two or more of a ROM, a RAM, an EEPROM, a register, a flash memory, a CD-ROM, a magnetic tape, a hard disk, a floppy disk, and an optical data recording device.

[0081] In one embodiment, the battery diagnostic device (100) may further include an output unit (150). The output unit (150) may be configured to visually, audibly, or audiovisually output a notification signal of the diagnostic result notification unit (115). To this end, the output unit (150) may include a visual output device such as a light-emitting diode, a monitor, a display panel, or a touch screen. In addition, the output unit (150) may further include a sound generating device such as a speaker.

[0082] In one embodiment, the battery diagnostic device (100) may be configured to be linked to a measuring device (12) that measures the voltage and / or current of the target battery, a communication device (14) that communicates with another device, a charging / discharging device (16) that charges / discharges the target battery, a cooling device (18) that cools the target battery, etc.

[0083] In another embodiment, the battery diagnostic device (100) according to the present invention may include one or two or more of the above-described measuring device (12), communication device (14), charging / discharging device (16), and cooling device (18).

[0084] Figure 2 is a drawing showing an example of a bipolar profile map generated based on a bipolar half-cell.

[0085] As illustrated in FIG. 2, the anode profile map generated based on the anode half-cell may include a plurality of reference anode profiles (RP1 to RPn).

[0086] The above multiple reference anode profiles (RP1 to RPn) are profiles generated in different charge / discharge cycles while the charge / discharge cycle of the anode half-cell increases. In addition, each reference anode profile represents a corresponding relationship between the capacity and voltage of the anode half-cell in a corresponding charge / discharge cycle.

[0087] In one embodiment, the anode profile map may be a compilation of reference anode profiles generated by repeatedly charging and discharging the anode half-cell at a low current rate of 0.05 [C].

[0088] In another embodiment, the anode profile map may be a collection of reference anode profiles generated while the anode half-cell is charged and discharged at a low current rate of 0.05 [C] while charging and discharging once at a low current rate of 0.05 [C] and then repeatedly charging and discharging several times at a high current rate of 0.5 [C]. In this case, since the gap between the reference anode profiles is widened, the anode profile map can be supplemented through simulation.

[0089] Figure 3 is a diagram showing an example of a bipolar profile map supplemented through simulation.

[0090] As shown in Fig. 3, when the positive electrode half-cell is charged and discharged once at a low current rate of 0.05 [C] and then rapidly charged and discharged several times at a high current rate of 0.5 [C] while repeating the process, and the reference positive electrode profiles generated while the positive electrode half-cell is charged and discharged at a low current rate of 0.05 [C] are collected to generate a positive electrode profile map, the gap between the collected reference positive electrode profiles becomes wider.

[0091] Therefore, the anode profile map can be supplemented by inserting a simulation profile (SP) between the reference anode profiles.

[0092] The bipolar profile maps or reference bipolar profiles generated in this manner can be stored in the memory of the storage unit (140) before the target battery is diagnosed.

[0093] Figure 4 is a drawing showing an example of a cathode profile map generated based on a cathode half-cell.

[0094] As illustrated in FIG. 4, a cathode profile map generated based on a cathode half-cell may include a plurality of reference cathode profiles (RN1 to RNn).

[0095] The above multiple reference negative electrode profiles (RN1 to RNn) are profiles generated in different charge / discharge cycles while the charge / discharge cycle of the negative electrode half-cell increases. In addition, each reference negative electrode profile represents a corresponding relationship between the capacity and voltage of the negative electrode half-cell in a corresponding charge / discharge cycle.

[0096] Such cathode profile maps can be generated in the same or similar manner as the anode profile maps described above.

[0097] Additionally, the negative profile map or reference negative profiles may be stored in the memory of the storage unit (140) before the target battery is diagnosed.

[0098] Figure 5 is a drawing showing an example of a positive electrode profile (PP) and a negative electrode profile (NP) corresponding to a battery profile (BP).

[0099] As illustrated in FIG. 5, the differential profile generation unit (111) can measure electrical values ​​of the battery using an electrical sensor while the target battery is being charged or discharged, and generate a battery profile (BP) indicating a relationship between the capacity and voltage of the target battery based on the measured electrical values.

[0100] Next, the differential profile generation unit (111) selects a reference positive electrode profile and a reference negative electrode profile that, when combined with each other, generate a profile most similar to the battery profile (BP) from among a plurality of reference positive electrode profiles and a plurality of reference negative electrode profiles stored in the memory, and can obtain the selected reference positive electrode profile and reference negative electrode profile as the positive electrode profile (PP) and the negative electrode profile (NP).

[0101] Meanwhile, the differential profile generation unit (111) can provide the starting point (pi) and the ending point (pf) of the positive electrode profile (PP), the shrinkage rate (ps) of the positive electrode profile (PP) compared with the selected reference positive electrode profile, the starting point (ni) and the ending point (nf) of the negative electrode profile (NP), the shrinkage rate (ns) of the negative electrode profile (NP) compared with the selected reference negative electrode profile, etc. to the diagnostic information generation unit (113). Then, the diagnostic unit (114) can include the starting point (pi), the ending point (pf), and the shrinkage rate (ps) of the positive electrode profile (PP), and the starting point (ni), the ending point (nf), and the shrinkage rate (ns) of the negative electrode profile (NP) in the diagnostic information as diagnostic factors indicating the state of the target battery.

[0102] Next, the differential profile generation unit (111) can generate a differential profile by differentiating the anode profile (PP) with respect to the potential of the anode.

[0103] Figure 6 is a diagram showing a differential profile (DP) obtained by differentiating the anode profile with respect to the potential of the anode.

[0104] As illustrated in Fig. 6, the differential profile (DP) may have multiple peaks located at different potential intervals. The position and intensity of each peak are related to the redox reaction amount of elements contained in the positive electrode active material.

[0105] Figure 7 is a diagram showing Gaussian curves generated by performing Gaussian fitting on the differential profile (DP) shown in Figure 6.

[0106] As illustrated in FIG. 7, the Gaussian fitting unit (112) performs Gaussian fitting on the differential profile (DP) to quantify the amount of redox reaction of elements included in the positive electrode active material, thereby generating a plurality of Gaussian curves (G1, G2, G3) that, when combined together, form an approximation curve (Gt) corresponding to the differential profile (DP).

[0107] Then, the diagnostic information generation unit (113) can generate diagnostic information regarding the redox reaction amount of one or more elements among the plurality of elements included in the positive electrode active material using the plurality of Gaussian curves (G1, G2, G3).

[0108] The above diagnostic information generation unit (113) is configured to generate diagnostic information regarding the redox reaction amount of one or more elements among the plurality of elements using the plurality of Gaussian curves.

[0109] For example, the diagnostic information generation unit (113) may select a first Gaussian curve corresponding to a first element included in the positive electrode active material among a plurality of Gaussian curves (G1, G2, G3), and select a second Gaussian curve corresponding to a second element included in the positive electrode active material.

[0110] For reference, the selection of the Gaussian curve can be made based on the reaction potential of each element. For example, when the reaction potential of the first element is lower than 3.5 [V], among the plurality of Gaussian curves (G1, G2, G3), the Gaussian curve (G1) located in the potential range lower than 3.5 [V] can be selected as the first Gaussian curve corresponding to the first element. In addition, when the reaction potential of the second element is higher than 4 [V], among the plurality of Gaussian curves (G1, G2, G3), the Gaussian curve (G3) located in the potential range higher than 4 [V] can be selected as the second Gaussian curve corresponding to the second element.

[0111] In one embodiment, the first element may be manganese (Mn) and the second element may be oxygen (O).

[0112] Next, the diagnostic information generation unit (113) can calculate a first quantification value that quantifies the redox reaction amount of the first element based on the first Gaussian curve (G1). In this case, the diagnostic information generation unit (113) can calculate the first quantification value by integrating the first Gaussian curve (G1) with respect to the potential of the anode over the entire potential range of the anode. That is, the redox reaction amount of the first element can be proportional to the area of ​​the region between the horizontal axis representing the potential of the anode and the first Gaussian curve (G1).

[0113] In addition, the diagnostic information generation unit (113) can calculate a second quantification value that quantifies the redox reaction amount of the second element based on the second Gaussian curve (G3). In this case, the diagnostic information generation unit (113) can calculate the second quantification value by integrating the second Gaussian curve (G3) with respect to the potential of the anode over the entire potential range of the anode. That is, the redox reaction amount of the second element can be proportional to the area of ​​the region between the horizontal axis representing the potential of the anode and the second Gaussian curve (G3).

[0114] Next, the diagnostic information generation unit (113) can generate diagnostic information including the calculated first quantification value and the second quantification value.

[0115] Figure 8 is a graph showing the trend of changes in the redox reaction amounts of elements contained in a positive electrode active material as the number of charge / discharge cycles increases. For reference, Figure 8 is a graph for a case where the positive electrode active material contains manganese (Mn), nickel (Ni), and oxygen (O).

[0116] As shown in Fig. 8, the redox reaction amount graph (Q1) of manganese (Mn) shows a trend of gradually increasing and then slightly decreasing as the number of charge / discharge cycles increases.

[0117] The graph of the redox reaction amount of nickel (Ni) (Q2) and the graph of the redox reaction amount of oxygen (O) (Q4) generally show a decreasing trend as the number of charge / discharge cycles increases.

[0118] As a result, the graph (Qt) summing the redox reaction amounts of manganese (Mn), nickel (Ni), and oxygen (O) shows a trend of decreasing as the number of charge / discharge cycles increases, then increasing for a while and then decreasing again.

[0119] The above diagnostic unit (114) calculates a redox ratio representing the ratio of the redox reaction amount of the second element to the redox reaction amount of the first element based on the first quantification value and the second quantification value, and can determine the state of the target battery based on the calculated redox ratio.

[0120] For example, the diagnostic unit (114) can determine the state of the target battery by referring to the trend of change in the redox ratio over multiple diagnostic cycles.

[0121] Figure 9 is a graph showing the trend of changes in the redox ratio of manganese to oxygen as the number of charge / discharge cycles increases.

[0122] As illustrated in Fig. 9, the redox ratio, which represents the ratio of the redox reaction amount of oxygen to the redox reaction amount of manganese, generally shows a decreasing trend as the number of charge / discharge cycles increases. However, when the number of charge / discharge cycles becomes greater than n1, the redox ratio shows a gradually increasing trend.

[0123] In this way, when the change trend of the redox ratio changes from a decreasing trend to an increasing trend, the diagnostic unit (114) can determine that the state of the target battery is an abnormal state in which deterioration is in progress.

[0124] Fig. 10 is a flowchart illustrating a battery diagnosis method according to one embodiment of the present invention.

[0125] As illustrated in FIG. 10, a battery diagnosis method according to the present invention is a method for non-destructively diagnosing a battery having a positive electrode to which an active material containing a plurality of different elements is applied, and can be performed by a processor.

[0126] First, the processor generates a differential profile representing the relationship between the differential capacity of the positive electrode of the target battery and the potential of the positive electrode at each predetermined diagnostic cycle (S10). In some embodiments, the diagnostic cycle may be set to be the same as the charge / discharge cycle of the target battery.

[0127] For example, the processor may measure electrical values ​​of the target battery using an electrical sensor while the target battery is being charged or discharged, and generate a battery profile indicating a correspondence between the capacity and voltage of the target battery based on the measured electrical values.

[0128] Next, the processor can obtain an anode profile indicating a correspondence between the capacity and potential of the anode based on the battery profile.

[0129] To this end, the processor may store a plurality of reference positive profiles and a plurality of reference negative profiles in advance in a predetermined memory before acquiring the positive profile.

[0130] In this case, the processor may select a reference positive electrode profile and a reference negative electrode profile that, when combined with each other, create a profile most similar to the battery profile among a plurality of reference positive electrode profiles and a plurality of reference negative electrode profiles stored in the memory, and obtain the selected reference positive electrode profile as the positive electrode profile of the target battery.

[0131] Next, the processor performs Gaussian fitting on the differential profile to generate a plurality of Gaussian curves that form a curve corresponding to the differential profile when combined with each other (S20).

[0132] Next, the processor generates diagnostic information regarding the redox reaction amount of one or more elements among the plurality of elements using the plurality of Gaussian curves and stores the information in the memory (S30).

[0133] For example, the processor may calculate a first quantification value that quantifies the redox reaction amount of the first element based on a first Gaussian curve corresponding to the first element included in the active material among the plurality of Gaussian curves. In this case, the processor may calculate the first quantification value by integrating the first Gaussian curve with respect to the potential of the positive electrode over the entire potential range of the positive electrode.

[0134] In addition, the processor may calculate a second quantification value that quantifies the amount of redox reaction of the second element based on a second Gaussian curve corresponding to the second element included in the active material among the plurality of Gaussian curves. In this case, the processor may calculate the second quantification value by integrating the second Gaussian curve with respect to the potential of the positive electrode over the entire potential range of the positive electrode.

[0135] And the processor can generate diagnostic information including the first quantification value and the second quantification value.

[0136] Next, the processor diagnoses the target battery based on the diagnostic information (S40).

[0137] In one embodiment, the processor can calculate a redox ratio representing a ratio of a redox reaction amount of the second element to a redox reaction amount of the first element, based on the first quantification value and the second quantification value included in the diagnostic information.

[0138] And the processor can determine the status of the target battery based on the redox ratio.

[0139] For example, the processor can determine the condition of the target battery by referring to the trend of the redox ratio changing over a plurality of diagnostic cycles.

[0140] In one embodiment, the active material applied to the positive electrode of the target battery may be a manganese-rich active material, such as lithium manganese oxide.

[0141] In this case, the active material applied to the positive electrode may be represented by the chemical formula 1 or the chemical formula 2.

[0142] Additionally, the redox ratio, which is a diagnostic factor of the target battery, may be the ratio of the redox reaction amount of oxygen to the redox reaction amount of manganese.

[0143] The above processor can determine that the state of the target battery is abnormal when the change trend of the redox ratio according to the increase in charge / discharge cycles changes from a decreasing trend to an increasing trend (S50).

[0144] Next, the processor can adjust the charging conditions and / or discharging conditions of the target battery based on the diagnosis results for the target battery (S60).

[0145] That is, the processor can control a charger that charges the target battery to control the voltage at the completion of charging of the target battery or control the current rate of the current that charges the target battery.

[0146] For example, when the state of the target battery is diagnosed as abnormal, the processor may be configured to control a charger that charges the target battery to reduce the voltage when charging of the target battery is completed or to reduce the current rate of the current that charges the target battery.

[0147] Additionally, the processor can control a cooling device (18) described later to lower the temperature of the target battery.

[0148] In some embodiments, the processor may control a predetermined output device to output a visual, auditory or audiovisual notification signal corresponding to the diagnostic result of the target battery.

[0149] Next, the processor can repeat the above-described steps (S10 to S60) until the use of the target battery is stopped (S70).

[0150] FIG. 11 is a drawing showing a battery pack (10) according to one embodiment of the present invention.

[0151] As illustrated in FIG. 11, the battery pack (10) includes a rechargeable battery (B) and a battery diagnostic device (100) according to the present invention. In one embodiment, the battery pack (10) may optionally further include a measuring device (12), a communication device (14), a charging / discharging device (16), and a cooling device (18).

[0152] The above measuring device (12) may be configured to measure the voltage and / or current of the battery (B). To this end, the measuring device (12) may include at least one voltage sensor for sensing the voltage of the battery (B) and / or at least one current sensor for sensing the current of the battery (B).

[0153] This measuring device (12) can measure the voltage of the battery (B) through the first sensing line (SL1) and the second sensing line (SL2). In addition, the measuring device (12) can measure the current of the battery (B) through the third sensing line (SL3) connected to the current measuring circuit (A). The current measuring circuit (A) may include a shunt resistor.

[0154] A battery diagnostic device (100) according to one embodiment of the present invention can obtain electrical values ​​of a battery (B) through the measuring device (12). For reference, the capacity of the battery (B) can be calculated by applying a current integration method to the current charging the battery (B).

[0155] The above communication unit (14) may be configured to perform communication with another device located remotely. For example, the communication unit (14) may be configured to receive data transmitted from a remote server or communication terminal via a wired and / or wireless communication network and transmit the data to the battery diagnosis device (100), or to transmit data generated in the battery diagnosis device (100) to another server or communication terminal. To this end, the communication unit (14) may include a communication modem that performs wired and / or wireless communication.

[0156] The above charging / discharging device (16) may be configured to charge and / or discharge the battery (B). To this end, the charging / discharging device (16) may include a charger for charging the battery (B), a discharger for discharging the battery (B), at least one switch for electrically connecting the battery (B) to terminals (T1, T2) of the battery pack (10), etc.

[0157] A battery diagnostic device (100) according to one embodiment of the present invention can control the charging / discharging device (16) to proceed with or stop charging or discharging of the battery (B), set charging / discharging conditions, or change set charging / discharging conditions.

[0158] The cooling device (18) may be configured to cool the battery (B). To this end, the cooling device (18) may include a heat sink that absorbs heat from the battery (B) and releases it to the outside.

[0159] Fig. 11 is a drawing showing a vehicle according to one embodiment of the present invention.

[0160] As illustrated in FIG. 11, a vehicle (2) according to one embodiment of the present invention may include a battery pack (10) that provides electric energy required for the operation of the vehicle, and a battery diagnostic device (100) according to the present invention.

[0161] In this case, the battery diagnostic device (100) may be configured to be linked with an ECU (Electronic Control Unit) that controls the operation of the vehicle (2) or a BMS (Battery Management System) of the battery pack (10).

[0162] Additionally, the battery diagnostic device (100) may be configured to receive data transmitted from a remote server (4) via a wired and / or wireless communication network, or to transmit data generated in the battery diagnostic device (100) to the server (4).

[0163] For reference, the battery diagnostic device (100) according to the present invention can be applied to various electrical devices or electrical systems other than vehicles, and can also be applied to ESS (Energy Storage System).

[0164] As described above, the present invention performs Gaussian fitting on a differential profile representing a correspondence between a differential capacity obtained by differentiating the capacity of a positive electrode of a battery with respect to the potential of the positive electrode and the potential of the positive electrode, thereby generating Gaussian curves corresponding to the differential profile, and generating information on a redox reaction amount of an active material applied to the positive electrode using these Gaussian curves, thereby providing information on a redox reaction amount of an active material applied to the positive electrode of the battery, and diagnosing a state of a battery related to a redox reaction amount of the active material.

[0165] In addition, the present invention can increase the accuracy and reliability of diagnostic results by quantifying the redox reaction amount of elements forming the active material and providing a quantification value corresponding to the redox reaction amount.

[0166] In addition, the present invention can extend the life of a battery and improve safety by controlling the charging and / or discharging conditions of the battery according to the diagnosis results regarding the battery.

[0167] 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.

[0168] 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.

[0169] [Explanation of symbols]

[0170] 2: Vehicle

[0171] 10: Battery pack

[0172] 100: Battery Diagnostic Device

[0173] 110: Control unit

[0174] 111: Differential profile generation section

[0175] 112: Gaussian fitting part

[0176] 113: Diagnostic Information Generation Unit

[0177] 114: Diagnostic Department

[0178] 115: Diagnosis result notification section

[0179] 116: Battery Management Unit

[0180] 120: Communications Department

[0181] 130: Input section

[0182] 140: Storage

[0183] 150: Output section

Claims

1. A battery diagnosis method for diagnosing a battery having a positive electrode to which an active material is applied, A differential profile generation step for generating a differential profile representing a correspondence between a differential capacity obtained by differentiating the capacity of the anode with respect to the potential of the anode at each predetermined diagnostic cycle and a differential profile representing a correspondence between the potential of the anode; A Gaussian fitting step for generating a plurality of Gaussian curves that form a curve corresponding to the above differential profile when combined; A diagnostic information generation step for generating diagnostic information on the redox reaction amount of one or more elements among a plurality of different elements included in the active material using the plurality of Gaussian curves; and A battery diagnosis method comprising a diagnosis step of diagnosing the battery based on the above diagnostic information.

2. In paragraph 1, The above differential profile generation step is: A first generation step of measuring electrical values ​​of the battery using an electrical sensor while the battery is being charged or discharged, and generating a battery profile indicating a correspondence between the capacity and voltage of the battery based on the measured electrical values; An anode profile acquisition step for acquiring an anode profile representing a correspondence between the capacity and potential of the anode based on the battery profile; and A battery diagnosis method, characterized in that it includes a second generation step of generating the differential profile by differentiating the positive electrode profile with respect to the potential of the positive electrode.

3. In paragraph 2, The above battery diagnosis method is, Before the above differential profile generation step, further comprising a step of storing a plurality of reference positive profiles and a plurality of reference negative profiles in memory, The above bipolar profile acquisition step is: A step of selecting a reference positive electrode profile and a reference negative electrode profile that, when combined with each other, generate a profile most similar to the battery profile among the plurality of reference positive electrode profiles and the plurality of reference negative electrode profiles stored in the memory; and A battery diagnosis method, characterized in that it comprises a step of obtaining a selected reference anode profile as the anode profile.

4. In paragraph 1, The above diagnostic information generation step is: A step of calculating a first quantification value that quantifies the redox reaction amount of the first element based on a first Gaussian curve corresponding to the first element included in the active material among the plurality of Gaussian curves; A step of calculating a second quantification value that quantifies the redox reaction amount of the second element based on a second Gaussian curve corresponding to the second element included in the active material among the plurality of Gaussian curves; and A battery diagnosis method, characterized by comprising a step of generating the diagnostic information including the first quantification value and the second quantification value.

5. In paragraph 4, The above diagnostic steps are: A redox ratio calculation step for calculating a redox ratio representing the ratio of the redox reaction amount of the second element to the redox reaction amount of the first element based on the first quantification value and the second quantification value included in the diagnostic information; and A battery diagnosis method, characterized in that it includes a judgment step of judging the state of the battery based on the redox ratio.

6. In paragraph 5, The above judgment step is, A battery diagnosis method, characterized by including a step of determining the state of the battery by referring to a trend in which the redox ratio changes during a plurality of diagnosis cycles.

7. In paragraph 6, The above active material includes lithium manganese oxide, The first element is manganese, A battery diagnosis method, characterized in that the second element is oxygen.

8. In paragraph 7, The above judgment step is, A battery diagnosis method characterized in that it further includes a step of determining the state of the battery as abnormal when the change trend of the redox ratio changes from a decreasing trend to an increasing trend.

9. In paragraph 1, A battery diagnosis method characterized in that it further includes a step of controlling a charger that charges the battery according to the diagnosis result in the diagnosis step, thereby controlling the voltage when charging of the battery is completed or controlling the current rate of the current that charges the battery.

10. A battery diagnostic device for diagnosing a battery having a positive electrode to which an active material is applied, A differential profile generation unit configured to generate, at each predetermined diagnostic cycle, a differential capacity obtained by differentiating the capacity of the anode with respect to the potential of the anode and a differential profile indicating a correspondence between the potential of the anode; A Gaussian fitting unit configured to generate a plurality of Gaussian curves forming a curve corresponding to the above differential profile when mutually combined; A diagnostic information generation unit configured to generate diagnostic information regarding the redox reaction amount of one or more elements among a plurality of different elements included in the active material using the plurality of Gaussian curves; and A battery diagnostic device including a diagnostic unit configured to diagnose the battery based on the above diagnostic information.

11. In paragraph 10, The above diagnostic information generation unit, A battery diagnostic device characterized in that it is configured to generate the diagnostic information including the first quantification value and the second quantification value by calculating a first quantification value that quantifies the redox reaction amount of the first element based on a first Gaussian curve corresponding to the first element included in the active material among the plurality of Gaussian curves, and to calculate a second quantification value that quantifies the redox reaction amount of the second element based on a second Gaussian curve corresponding to the second element included in the active material among the plurality of Gaussian curves.

12. In paragraph 11, The above diagnostic section, A redox ratio calculation module configured to calculate a redox ratio representing a ratio of the redox reaction amount of the second element to the redox reaction amount of the first element based on the first quantification value and the second quantification value included in the diagnostic information; and A battery diagnostic device characterized by including a judgment module configured to judge the state of the battery based on the redox ratio.

13. In paragraph 12, The above judgment module, A battery diagnostic device characterized in that it is configured to determine the state of the battery by referring to the trend of change in the redox ratio during a plurality of diagnostic cycles.

14. A battery pack comprising a battery diagnostic device according to any one of claims 10 to 13.

15. A vehicle including a battery diagnostic device according to any one of paragraphs 10 to 13.

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