Apparatus and method for diagnosing battery

Abstract

An apparatus for diagnosing a battery, according to an embodiment of the present disclosure, comprises: a data obtainment unit configured to obtain battery data including at least one of a voltage, a current and a temperature of a battery; and a control unit configured to estimate a loss rate of available lithium of the battery on the basis of the battery data, with reference to a first profile preset for anode potential estimation, a second profile preset for cathode potential estimation, a third profile preset for anode lithium stoichiometry estimation, and a fourth profile preset for acceleration factor estimation.

Description

Battery diagnostic device and method

[0001] The present invention relates to a battery diagnostic device and method, and more specifically, to a battery diagnostic device and method for estimating the available lithium loss rate of a battery.

[0002] The present application claims priority based on Korean application No. 10-2024-0175759 filed on November 29, 2024 and Korean application No. 10-2025-0050979 filed on April 18, 2025, and all contents disclosed in the specification of said application are incorporated by reference into the present application.

[0003]

[0004] Recently, as the demand for portable electronic products such as laptops, video cameras, and mobile phones has increased rapidly, and the development of electric vehicles, energy storage batteries, robots, and satellites has accelerated, research on high-performance batteries capable of repeated charging and discharging is actively underway.

[0005] Currently commercialized batteries include nickel-cadmium, nickel-hydrogen, nickel-zinc, and lithium batteries. Among these, lithium batteries are gaining attention for their advantages, such as the ability to freely charge and discharge with almost no memory effect compared to nickel-based batteries, a very low self-discharge rate, and high energy density.

[0006] Pseudo Two-Dimensional (P2D) models are primarily used in existing battery state estimation technologies. P2D models predict performance by mathematically simulating electrochemical reactions and mass transport occurring within lithium-ion batteries, and they can explain battery behavior by combining phenomena at the particle and domain levels. Specifically, P2D models simulate lithium ion diffusion and electrochemical reactions by reflecting the porous structure of electrodes and ion transport within the electrolyte, and can analyze structural deformation and performance degradation occurring during charging and discharging through concentration gradients and changes in mechanical stress within electrode particles. Through this, P2D models can model battery degradation mechanisms, such as available lithium loss.

[0007] The P2D model is a detailed, physics-based electrochemical model that offers the advantage of enabling precise predictions regarding changes in battery state. Therefore, the P2D model is suitable for detailed analysis of battery degradation mechanisms based on high prediction accuracy.

[0008] However, high computational power and memory resources are essential for the high prediction accuracy of P2D models. In other words, because applying P2D models requires complex calculation processes and large-scale data storage, there is a limitation in that it is difficult to apply P2D models in real-time processing system environments. In particular, if P2D models are directly implemented in onboard BMS (Battery Management System) systems within the vehicle or in Cloud BMS operating over a network, a large amount of computational resources is required, which poses a problem as it is inefficient for rapidly diagnosing and controlling battery status.

[0009] Therefore, there is a need to develop a Reduced Model (RM) capable of real-time processing and reduce the complexity of the P2D model.

[0010]

[0011] The present invention was devised to solve the above-mentioned problems and aims to provide a battery diagnostic device and method capable of accurately estimating the available lithium loss rate by utilizing battery data based on a lightweight model and improving the efficiency of battery diagnosis by ensuring real-time capability.

[0012] Other objects and advantages of the present invention may be understood from the following description and will become more clearly apparent from the embodiments of the present invention. Furthermore, it will be readily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims.

[0013]

[0014] A battery diagnostic device according to one aspect of the present invention may include: a data acquisition unit configured to acquire battery data including at least one of the voltage, current, and temperature of the battery; and a control unit configured to estimate the available lithium loss rate of the battery by referring to a first profile pre-set for estimating the negative potential, a second profile pre-set for estimating the positive potential, a third profile pre-set for estimating the negative lithium stoichiometry, and a fourth profile pre-set for estimating the acceleration factor, based on the battery data.

[0015] The above first profile may be configured to represent a correspondence relationship between a plurality of reference battery data and a plurality of first reference state data.

[0016] The control unit above may be configured to determine a first reference state data corresponding to the battery data by referring to the first profile.

[0017] The above control unit may be configured to estimate the negative potential of the battery based on the determined first reference state data.

[0018] The above second profile may be configured to represent a correspondence between a plurality of reference battery data and a plurality of second reference state data.

[0019] The control unit above may be configured to determine second reference state data corresponding to the battery data by referring to the second profile.

[0020] The above control unit may be configured to estimate the positive potential of the battery based on the determined second reference state data.

[0021] The above third profile may be configured to represent a correspondence between a plurality of reference battery data and a plurality of third reference state data.

[0022] The control unit above may be configured to determine third reference state data corresponding to the battery data by referring to the third profile.

[0023] The above control unit may be configured to estimate the negative lithium stoichiometry of the battery based on the determined third reference state data.

[0024] The above-mentioned fourth profile may be configured to represent a correspondence between a plurality of reference battery data and a plurality of fourth reference state data.

[0025] The control unit above may be configured to determine a fourth reference state data corresponding to the battery data by referring to the fourth profile.

[0026] The above control unit may be configured to estimate the acceleration factor of the battery based on the determined fourth reference state data.

[0027] The control unit may be configured to estimate the negative potential, positive potential, negative lithium stoichiometry, and acceleration factor of the battery by referring to the first profile, the second profile, the third profile, and the fourth profile.

[0028] The control unit may be configured to estimate a first loss rate related to SEI layer growth of the battery, a second loss rate related to transition metal dissolution, and a third loss rate related to oxidation, based on at least one of the estimated negative potential, positive potential, negative lithium stoichiometry, and acceleration factor of the battery.

[0029] The control unit may be configured to estimate the available lithium loss rate based on the first loss rate, the second loss rate, and the third loss rate.

[0030] The control unit may be configured to estimate the first loss rate based on the cathode potential, the cathode lithium stoichiometry, and the acceleration factor.

[0031] The control unit may be configured to estimate the second loss rate based on the anode potential and the acceleration factor.

[0032] The above control unit may be configured to estimate the third loss rate based on the anode potential.

[0033] The control unit above may be configured to estimate the available lithium loss rate by summing the first loss rate, the second loss rate, and the third loss rate.

[0034] The control unit may be configured to estimate the amount of available lithium loss of the battery during the reference period based on the available lithium loss rate and the reference period between the previous diagnosis time and the current diagnosis time.

[0035] The control unit may be configured to estimate the accumulated available lithium loss amount up to the current diagnosis point by adding the available lithium loss amount to the accumulated available lithium loss amount up to the previous diagnosis point.

[0036] A battery pack according to another aspect of the present invention may include the battery diagnostic device.

[0037] A server according to another aspect of the present invention may include the battery diagnostic device.

[0038] A battery diagnostic method according to another aspect of the present invention may include the step of acquiring battery data comprising at least one of the voltage, current, and temperature of the battery; and the step of estimating the available lithium loss rate of the battery based on the battery data by referring to a first profile pre-set for estimating the negative potential, a second profile pre-set for estimating the positive potential, a third profile pre-set for estimating the negative lithium stoichiometry, and a fourth profile pre-set for estimating the acceleration factor.

[0039] A computer-readable recording medium according to another aspect of the present invention may be a computer-readable recording medium having a program recorded thereon for performing the battery diagnostic method on a computer.

[0040]

[0041] According to one aspect of the present invention, based on a lightweight model that approximates a P2D model, computation speed can be improved while maintaining a high level of accuracy similar to that of a P2D model.

[0042] In addition, according to one aspect of the present invention, the available lithium loss rate related to SEI layer growth, transition metal dissolution, and oxidation can be independently estimated to accurately diagnose the condition of the battery.

[0043] The effects of the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description in the claims.

[0044]

[0045] The following drawings attached to this specification serve to further enhance understanding of the technical concept of the invention in conjunction with the detailed description of the invention set forth below; therefore, the invention should not be interpreted as being limited only to the matters described in such drawings.

[0046] FIG. 1 is a schematic diagram illustrating a battery diagnostic device according to one embodiment of the present invention.

[0047] Figure 2 is a schematic diagram illustrating an example of a profile.

[0048] Figures 3 to 6 illustrate the correlation between the available lithium loss rate estimated using a P2D model and a battery diagnostic device.

[0049] Figure 7 is a schematic diagram illustrating the change in SOH according to the charge / discharge cycle.

[0050] Figure 8 is a schematic diagram illustrating the change in the accumulated available lithium loss amount according to the charge / discharge cycle.

[0051] FIG. 9 is a schematic diagram illustrating a battery pack according to another embodiment of the present invention.

[0052] FIG. 10 is a schematic drawing illustrating an automobile according to another embodiment of the present invention.

[0053] FIG. 11 is a schematic diagram illustrating a server according to another embodiment of the present invention.

[0054] FIG. 12 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0055] FIG. 13 is a schematic diagram illustrating the sub-steps of step S1220 of FIG. 12.

[0056] FIG. 14 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0057] FIG. 15 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0058]

[0059] Terms and words used in this specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings, but should be interpreted in a meaning and concept consistent with the technical spirit of the invention, based on the principle that the inventor can appropriately define the concept of the terms to best describe his invention.

[0060] Therefore, the embodiments described in this specification and the configurations illustrated in the drawings are merely the most preferred embodiments of the present invention and do not represent all of the technical ideas of the present invention; thus, it should be understood that various equivalents and modifications that can replace them may exist at the time of filing this application.

[0061] In addition, in describing the present invention, if it is determined that a detailed description of related known components or functions may obscure the essence of the invention, such detailed description is omitted.

[0062] Terms including ordinal numbers, such as first, second, etc., are used for the purpose of distinguishing one of the various components from the rest, and are not used to limit the components by such terms.

[0063] Throughout the specification, when a part is described as "including" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0064] Additionally, throughout the specification, when it is said that a part is "connected" to another part, this includes not only cases where they are "directly connected," but also cases where they are "indirectly connected" with other components in between.

[0065]

[0066] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0067] FIG. 1 is a schematic diagram illustrating another battery diagnostic device (100) of an embodiment of the present invention.

[0068] Referring to FIG. 1, the battery diagnostic device (100) may include a data acquisition unit (110) and a control unit (120). The battery diagnostic device (100) may further include a storage unit (130).

[0069] The data acquisition unit (110) may be configured to acquire battery data including at least one of the voltage, current, and temperature of the battery.

[0070] Here, a battery refers to a single, independent cell that is physically separable and equipped with a negative terminal and a positive terminal. For example, a lithium-ion battery or a lithium-polymer battery may be considered a battery. Additionally, the battery may be of the cylindrical, prismatic, or pouch type. Furthermore, a battery may refer to a battery bank, battery module, or battery pack in which multiple cells are connected in series and / or parallel. For the sake of convenience of explanation, the term "battery" below is described as referring to a single, independent cell.

[0071] In one embodiment, the data acquisition unit (110) can directly measure at least one of the voltage, current, and temperature of the battery.

[0072] For example, the data acquisition unit (110) can measure the positive voltage and the negative voltage through a pair of voltage sensing lines connected to the positive and negative electrodes of the battery, respectively. Then, the data acquisition unit (110) can measure the voltage across the two ends of the battery based on the voltage difference between the measured positive voltage and the negative voltage.

[0073] For example, the data acquisition unit (110) can measure the current of the battery through a current measurement unit. For example, the current measurement unit may be a current sensor or a shunt resistor that is provided in the battery's charging / discharging path to measure the battery's current. Here, the battery's charging / discharging path may be a high-current path where a charging current is applied to the battery or a discharging current is output from the battery.

[0074] For example, the data acquisition unit (110) can measure the temperature of the battery using a temperature sensor.

[0075] The data acquisition unit (110) can acquire battery data by measuring at least one of the voltage, current, and temperature of the battery on a regular or irregular basis.

[0076] In another embodiment, the data acquisition unit (110) can receive battery data from the outside. That is, the data acquisition unit (110) can receive battery data from the outside by being connected via wired and / or wireless so as to be able to communicate with the outside. For example, the data acquisition unit (110) can receive battery data from the outside using CAN (Controller Area Network) communication or CAN-FD (CAN with Flexible Data rate) communication. As another example, the data acquisition unit (110) can receive battery data from the outside using Zigbee, Bluetooth, WIFI, or a mobile communication network. Of course, as long as it supports communication between the data acquisition unit (110) and the outside, the type of communication protocol is not particularly limited.

[0077] Meanwhile, current and C-rate can be converted to each other when the rated capacity of the cell (maximum capacity in BOL state) is clearly defined. Accordingly, current and C-rate may be interpreted as having the same meaning in this specification, and using either of the two values ​​does not affect the technical scope of the present invention. For example, the data acquisition unit (110) may acquire battery data including at least one of the battery voltage, C-rate, and temperature.

[0078] The data acquisition unit (110) may be connected via wired and / or wireless means to communicate with the control unit (120). The data acquisition unit (110) may transmit acquired battery data to the control unit (120). The control unit (120) may receive battery data from the data acquisition unit (110).

[0079] The control unit (120) may be configured to estimate the available lithium loss rate of the battery by referring to one of a first profile pre-set for estimating the negative potential, a second profile pre-set for estimating the positive potential, a third profile pre-set for estimating the negative lithium stoichiometry, and a fourth profile pre-set for estimating the acceleration factor, based on battery data.

[0080] The control unit (120) may be configured to estimate the available lithium loss rate of the battery by referring to a first profile pre-set for estimating the negative potential, a second profile pre-set for estimating the positive potential, a third profile pre-set for estimating the negative lithium stoichiometry, and a fourth profile pre-set for estimating the acceleration factor, based on battery data.

[0081] Here, available lithium loss refers to a decrease in the amount of available lithium ions within the battery and is one of the major causes of battery degradation. Specifically, available lithium loss can occur due to the growth of the Solid Electrolyte Interphase (SEI) layer, Transition Metal Dissolution, and electrolyte oxidation at the anode. When available lithium loss occurs, problems such as reduced battery capacity, increased internal resistance, performance degradation, and shortened lifespan may arise. Specifically, side reactions occurring at the cathode and anode are the primary cause of available lithium loss, and this available lithium loss can be expressed by an electrochemical reaction equation of the Butler-Volmer type.

[0082] The available lithium loss rate represents the amount of available lithium lost from a battery per unit time and can be used as an indicator to evaluate the rate of battery degradation. Specifically, the available lithium loss rate quantitatively indicates the rate at which available lithium is lost during charging, discharging, or storage of the battery. For example, the unit of the available lithium loss rate is [Ah / sec].

[0083] Here, lithium stoichiometry is defined as the molar ratio of lithium concentration within the electrode material in a lithium-ion battery. In other words, lithium stoichiometry quantitatively represents the change in lithium concentration during the insertion and extraction processes of lithium ions in the electrode material.

[0084] The cathodic lithium stoichiometry represents the molar ratio of lithium concentration within the cathode material. For example, if the cathode active material is graphite, the chemical formula is generally Li xIt is represented as C6. Here, x is the cathodic lithium stoichiometry, representing the molar ratio of lithium atoms within the graphite structure. Based on the molar ratio of lithium atoms within the cathode, x can be set to a value between 0 and 1. When x is 1, lithium is fully inserted into the graphite structure, representing a lithium saturated state (fully charged state). When x is 0.5, lithium is partially inserted into the graphite structure, representing a battery that is half-charged. When x is 0, lithium is completely detached from the graphite structure, representing a lithium depleted state (fully discharged state).

[0085] The acceleration factor is a parameter that reflects the difference in lithium ion concentration between the surface and the interior of the electrode. Alternatively, the acceleration factor is a parameter that quantifies the stress received by the electrode and the SEI layer.

[0086] Specifically, mechanical defects may occur in the electrode and SEI layers due to stress applied to the cathode and SEI layers, and as a result of such defects, additional SEI layers may form on surfaces newly exposed to the electrolyte in the cathode and SEI layers, leading to increased available lithium loss. Specifically, cycle degradation can be simulated more precisely by introducing an acceleration factor based on the fact that stress increases at low temperatures and high C-rates.

[0087] The first profile is a data set (e.g., lookup table, mathematical function) used to estimate the negative potential of a battery, and represents a correspondence between at least one of the battery's voltage, current, and temperature and the negative potential.

[0088] The second profile is a data set (e.g., lookup table, mathematical function) used to estimate the positive potential of a battery, and represents the correspondence between at least one of the battery's voltage, current, and temperature and the positive potential.

[0089] The third profile is a data set (e.g., lookup table, mathematical function) used to estimate the lithium stoichiometry of the cathode, and represents the correspondence between at least one of the voltage, current, and temperature of the battery and the lithium stoichiometry of the cathode.

[0090] The fourth profile is a dataset (e.g., lookup table, mathematical function) used to estimate the acceleration factor, and represents the correspondence between at least one of the battery voltage, current, and temperature and the acceleration factor.

[0091] The control unit (120) can estimate the available lithium loss rate of the battery based on the estimated cathodic potential, anode potential, cathodic lithium stoichiometry, and acceleration factor by referring to the first to fourth profiles.

[0092] Specifically, the control unit (120) can estimate the negative potential of the battery using a first profile, estimate the positive potential of the battery using a second profile, estimate the negative lithium stoichiometry of the battery using a third profile, and estimate the acceleration factor of the battery using a fourth profile. In addition, the control unit (120) can estimate the available lithium loss rate of the battery based on the negative potential, positive potential, negative lithium stoichiometry, and acceleration factor.

[0093] A battery diagnostic device (100) according to one embodiment of the present invention has the advantage of being able to estimate the negative potential, positive potential, negative lithium stoichiometry, and acceleration factor of a battery by referring to a first to fourth profile stored in advance, and to estimate the available lithium loss rate quickly and efficiently based thereon.

[0094]

[0095] Meanwhile, the data acquisition unit (110) and / or control unit (120) provided in the battery diagnostic device (100) may optionally include a processor, an application-specific integrated circuit (ASIC), other chipsets, logic circuits, registers, communication modems, data processing devices, etc., known in the art, to execute various control logics performed in the present invention. Additionally, when the control logic is implemented in software, the data acquisition unit (110) and / or control unit (120) may be implemented as a set of program modules. In this case, the program modules may be stored in memory and executed by the data acquisition unit (110) and / or control unit (120). The memory may be located inside or outside the data acquisition unit (110) and / or control unit (120) and may be connected to the data acquisition unit (110) and / or control unit (120) by various well-known means.

[0096] Additionally, the battery diagnostic device (100) may further include a storage unit (130). The storage unit (130) may store data or programs necessary for each component of the battery diagnostic device (100) to perform operations and functions, or data generated during the process of performing operations and functions. The storage unit (130) is not limited in its type as long as it is a known information storage means known to be able to record, erase, update, and read data. As an example, the information storage means may include RAM, flash memory, RM, EEPRM, registers, etc. Additionally, the storage unit (130) may store program codes in which processes executable by the data acquisition unit (110) and / or the control unit (120) are defined.

[0097] Specifically, the storage unit (130) can store information necessary for the control unit (120) to estimate the available lithium loss rate of the battery. For example, the storage unit (130) can store battery data, a first profile, a second profile, a third profile, and a fourth profile, etc. And, the control unit (120) can access the storage unit (130) to obtain information necessary for the control unit (120) to estimate the available lithium loss rate of the battery. For example, battery data obtained by the data acquisition unit (110) is stored in the storage unit (130), and the control unit (120) can access the storage unit (130) to obtain the stored battery data.

[0098]

[0099] Below, the first to fourth profiles will be described in detail.

[0100] FIG. 2 is a schematic diagram illustrating an example of a profile. Here, the term profile is a term including the first to fourth profiles.

[0101] Referring to FIG. 2, the profile may include reference battery data and reference state data corresponding to voltage and current according to each temperature. Here, reference state data is a term that includes first to fourth reference state data. A description of each of the first to fourth reference state data will be provided together with a description of each of the first to fourth profiles.

[0102] For example, in FIG. 2, the value of each grid point is not listed, but the value of each grid point represents reference state data corresponding to reference battery data. That is, the profile can express the correspondence between reference battery data and reference state data regarding three variables: voltage, current, and temperature.

[0103] Here, the reference battery data is basic data input into the first to fourth models, and includes voltage ranges, current ranges, and temperature ranges during the charging and discharging of the battery. For example, the reference battery data is voltage, current, and temperature data of a reference battery of the same type as the battery to be diagnosed. Preferably, the reference battery data may be set to voltage, current, and temperature data when the reference battery is in the BOL state.

[0104] The first profile may be configured to represent a correspondence between a plurality of reference battery data and a plurality of first reference state data. Specifically, the first profile may be configured based on a pre-configured first model. Here, the first model may be a model capable of estimating the negative potential of a battery by utilizing a P2D model. For example, the first model may estimate the negative potential corresponding to the voltage, current, and temperature of the reference battery. Furthermore, the first profile may be configured to include information regarding the negative potential estimated by the first model. The first reference state data is an output value obtained by inputting at least one of the voltage, current, and temperature of a reference battery of the same type as the battery to be diagnosed into the first model. Preferably, the first reference state data may be configured as the negative potential obtained by inputting voltage, current, and temperature data when the reference battery is in the BOL state into the first model.

[0105] The second profile may be configured to represent a correspondence between a plurality of reference battery data and a plurality of second reference state data. Specifically, the second profile may be configured based on a pre-configured second model. Here, the second model may be a model capable of estimating the positive potential of a battery by utilizing a P2D model. For example, the second model may estimate the positive potential corresponding to the voltage, current, and temperature of the reference battery. Furthermore, the second profile may be configured to include information regarding the positive potential estimated by the second model. The second reference state data is an output value obtained by inputting at least one of the voltage, current, and temperature of a reference battery of the same type as the battery under diagnosis into the second model. Preferably, the second reference state data may be configured as the positive potential obtained by inputting voltage, current, and temperature data when the reference battery is in the BOL state into the second model.

[0106] The third profile may be configured to represent the correspondence between multiple reference battery data and multiple third reference state data. Specifically, the third profile may be configured based on a pre-configured third model. Here, the third model may be a model capable of estimating the negative lithium stoichiometry of a battery by utilizing a P3D model. For example, the third model may estimate the negative lithium stoichiometry corresponding to the voltage, current, and temperature of the reference battery. Furthermore, the third profile may be configured to include information regarding the negative lithium stoichiometry estimated by the third model. The third reference state data is an output value obtained by inputting at least one of the voltage, current, and temperature of a reference battery of the same type as the battery under diagnosis into the third model. Preferably, the third reference state data may be configured as the negative lithium stoichiometry obtained by inputting voltage, current, and temperature data when the reference battery is in the BOL state into the third model.

[0107] The fourth profile may be configured to represent a correspondence between a plurality of reference battery data and a plurality of fourth reference state data. Specifically, the fourth profile may be configured based on a pre-configured fourth model. Here, the fourth model may be a model capable of estimating the acceleration factor of a battery by utilizing a P4D model. For example, the fourth model may estimate an acceleration factor corresponding to the voltage, current, and temperature of the reference battery. Furthermore, the fourth profile may be configured to include information regarding the acceleration factor estimated by the fourth model. The fourth reference state data is an output value obtained by inputting at least one of the voltage, current, and temperature of a reference battery of the same type as the battery under diagnosis into the fourth model. Preferably, the fourth reference state data may be configured as an acceleration factor obtained by inputting voltage, current, and temperature data when the reference battery is in the BOL state into the fourth model.

[0108] The control unit (120) may be configured to estimate the negative potential, positive potential, negative lithium stoichiometry, and acceleration factor of the battery by referring to the first profile, second profile, third profile, and fourth profile.

[0109] The control unit (120) may be configured to determine first reference state data corresponding to battery data by referring to the first profile.

[0110] Specifically, the control unit (120) can determine first reference state data corresponding to the voltage, current, and temperature of the battery data by referring to the first profile. And, the control unit (120) can be configured to estimate the negative potential of the battery based on the determined first reference state data.

[0111] The control unit (120) can estimate the determined first reference state data as the negative potential of the battery.

[0112] The control unit (120) may be configured to determine second reference state data corresponding to battery data by referring to the second profile.

[0113] Specifically, the control unit (120) can determine second reference state data corresponding to the voltage, current, and temperature of the battery data by referring to the second profile. And, the control unit (120) can be configured to estimate the positive potential of the battery based on the determined second reference state data.

[0114] The control unit (120) can estimate the determined second reference state data as the positive potential of the battery.

[0115] The control unit (120) may be configured to determine third reference state data corresponding to battery data by referring to the third profile.

[0116] Specifically, the control unit (120) can determine third reference state data corresponding to the voltage, current, and temperature of the battery data by referring to the third profile. And, the control unit (120) can be configured to estimate the negative lithium stoichiometry of the battery based on the determined third reference state data.

[0117] The control unit (120) can estimate the determined third reference state data as the negative lithium stoichiometry of the battery.

[0118] The control unit (120) may be configured to determine a fourth reference state data corresponding to the battery data by referring to the fourth profile.

[0119] Specifically, the control unit (120) can determine fourth reference state data corresponding to the voltage, current, and temperature of the battery data by referring to the fourth profile. And, the control unit (120) can be configured to estimate the acceleration factor of the battery based on the determined fourth reference state data.

[0120] The control unit (120) can estimate the determined fourth reference state data as the acceleration factor of the battery.

[0121]

[0122] Hereinafter, specific embodiments in which the control unit (120) estimates the first to third loss rates are described.

[0123] The control unit (120) may be configured to estimate a first loss rate related to SEI layer growth of the battery, a second loss rate related to transition metal dissolution, and a third loss rate related to oxidation, based on at least one of the estimated negative potential, positive potential, negative lithium stoichiometry, and acceleration factor of the battery.

[0124] The first loss rate refers to the available lithium loss rate related to SEI layer growth.

[0125] The control unit (120) may be configured to estimate a first loss rate based on the negative electrode potential, the negative lithium stoichiometry, and the acceleration factor.

[0126] For example, the control unit (120) can calculate the first loss rate using Equation 1 and Equation 2.

[0127] [Formula 1]

[0128]

[0129] Here, is the first loss rate. Specifically, represents the amount of available lithium loss related to SEI layer growth per unit time. f ACC (C s (t)) is an acceleration factor based on the difference in lithium ion concentration between the electrode surface and the interior at a specific time t, A is the electrode plate area, and L n is the thickness of the cathode, and a n is the specific interfacial surface area of ​​the negative electrode. And, i RE(t) is the SEI layer growth-related current at a specific time t. The SEI layer growth-related current refers to the current formed by the flow of electrons consumed by electrochemical reactions during the process of forming the SEI layer.

[0130] [Equation 2]

[0131]

[0132] Here, i RE (t) is the current related to SEI layer growth at a specific time t. f RE is a function determining the SEI layer growth-related current, indicating that the SEI layer growth-related current depends on electrode surface concentration, cathodic potential, and temperature. Z n,surf (t) is the electrode surface concentration at a specific time t, and U n (t) is the cathodic potential at a specific time t, and T(t) is the temperature at a specific time t.

[0133] The second loss rate refers to the loss rate of available lithium related to the dissolution of transition metals.

[0134] The control unit (120) may be configured to estimate a second loss rate based on the positive potential and acceleration factor.

[0135] For example, the control unit (120) can calculate the second loss rate using Equation 3 and Equation 4.

[0136] [Equation 3]

[0137]

[0138] Here, is the second loss rate. Specifically, represents the amount of available lithium loss related to transition metal dissolution per unit time. f ACC (C s (t)) is an acceleration factor based on the difference in lithium ion concentration between the electrode surface and the interior at a specific time t, A is the electrode plate area, and L n is the thickness of the cathode, and a nis the cathode interface area. And, i TM (t) is the current related to the dissolution of a transition metal at a specific time t. The current related to the dissolution of a transition metal refers to the current formed by the flow of electrons consumed during the dissolution process in which a transition metal is converted into ions through an electrochemical reaction.

[0139] [Equation 4]

[0140]

[0141] Here, i TM (t) is the current related to the dissolution of the transition metal at a specific time t. f TM is a function that determines the current related to transition metal dissolution, indicating that the current related to transition metal dissolution depends on the anodic potential and temperature. U p (t) is the positive potential at a specific time t, and T(t) is the temperature at a specific time t.

[0142] The third loss rate refers to the available lithium loss rate related to oxidation.

[0143] The control unit (120) may be configured to estimate a third loss rate based on the positive potential.

[0144] For example, the control unit (120) can calculate the third loss rate using Equation 5 and Equation 6.

[0145] [Formula 5]

[0146]

[0147] Here, is the third loss rate. Specifically, represents the amount of available lithium loss related to oxidation per unit time. A is the electrode plate area, and L p is the thickness of the anode, and a p is the anode interface area. And, i OX (t) is the oxidation-related current at a specific time t. The oxidation-related current refers to the current formed by the flow of electrons consumed by the oxidation reaction of the electrolyte at the anode.

[0148] [Equation 6]

[0149]

[0150] Here, i OX (t) is the oxidation-related current at a specific time t. f ox is a function that determines the oxidation-related current, indicating that the oxidation-related current depends on the anodic potential and temperature. U p (t) is the positive potential at a specific time t, and T(t) is the temperature at a specific time t.

[0151] A battery diagnostic device (100) according to one embodiment of the present invention has the advantage of being able to diagnose the condition of a battery more precisely by independently estimating the available lithium loss rate related to SEI layer growth, transition metal dissolution, and oxidation.

[0152]

[0153] The control unit (120) may be configured to estimate the available lithium loss rate based on the first loss rate, the second loss rate, and the third loss rate.

[0154] Here, the available lithium loss rate may refer to a value calculated by comprehensively reflecting various available lithium loss factors occurring within the battery.

[0155] In one embodiment, the control unit (120) may estimate a first loss rate, a second loss rate, or a third loss rate as a available lithium loss rate. For example, if the first loss rate is estimated as a available lithium loss rate, the available lithium loss rate represents the amount of available lithium lost due to SEI layer growth per unit time. As another example, if the second loss rate is estimated as a available lithium loss rate, the available lithium loss rate represents the amount of available lithium lost due to transition metal dissolution per unit time. As yet another example, if the third loss rate is estimated as a available lithium loss rate, the available lithium loss rate represents the amount of available lithium lost due to electrolyte oxidation at the anode per unit time.

[0156] In another embodiment, the control unit (120) may be configured to estimate the available lithium loss rate by summing at least two of the first loss rate, the second loss rate, or the third loss rate. For example, if the sum of the first loss rate and the second loss rate is estimated as the available lithium loss rate, the available lithium loss rate represents the total amount of available lithium lost per unit time due to SEI layer growth and transition metal dissolution. In another example, if the sum of the first loss rate and the third loss rate is estimated as the available lithium loss rate, the available lithium loss rate represents the total amount of available lithium lost per unit time due to SEI layer growth and electrolyte oxidation at the anode. In yet another example, if the sum of the second loss rate and the third loss rate is estimated as the available lithium loss rate, the available lithium loss rate represents the total amount of available lithium lost per unit time due to transition metal dissolution and electrolyte oxidation at the anode. As another example, the control unit (120) may be configured to estimate the available lithium loss rate by summing the first loss rate, the second loss rate, and the third loss rate. In this case, the available lithium loss rate represents the total loss rate of available lithium due to the SEI layer growth phenomenon, the transition metal dissolution phenomenon, and the electrolyte oxidation phenomenon at the anode. That is, the available lithium loss rate is the total amount of available lithium lost per unit time in the battery, and can be calculated as the sum of the amount of available lithium lost due to SEI layer growth per unit time, the amount of available lithium lost due to transition metal dissolution per unit time, and the amount of available lithium lost due to electrolyte oxidation at the anode per unit time.

[0157] A battery diagnostic device (100) according to one embodiment of the present invention has the advantage of being able to comprehensively diagnose the progression of battery degradation by estimating the available lithium loss rate, which reflects the total available lithium consumed by the combined action of various factors such as SEI layer growth, transition metal dissolution, and oxidation.

[0158]

[0159] Below, a specific embodiment in which the control unit (120) estimates the available lithium loss amount is described.

[0160] The control unit (120) may be configured to estimate the amount of available lithium loss of the battery during the reference period based on the available lithium loss rate and the reference period between the previous diagnosis time and the current diagnosis time.

[0161] The amount of available lithium loss during the reference period indicates how much the available lithium in the battery has decreased during the reference period, and can be used as an indicator to evaluate the battery's degradation status and the rate of degradation.

[0162] Specifically, the reference period may refer to the time interval between the previous diagnosis point and the current diagnosis point. For example, if the time interval between the previous diagnosis point and the current diagnosis point is 0.1 seconds, the reference period is 0.1 seconds.

[0163] The amount of available lithium loss may refer to the amount of available lithium that decreased according to the available lithium loss rate during the reference period.

[0164] In one embodiment, the control unit (120) can calculate the amount of available lithium loss by multiplying the reference period by the available lithium loss rate. For example, if the reference period is 0.1 seconds and the available lithium loss rate is 0.5 Ah / second per hour, the amount of available lithium loss during the reference period can be calculated as 0.05 Ah.

[0165] In another embodiment, the control unit (120) can calculate the amount of available lithium loss during a reference period by integrating the available lithium loss rate for a reference period over time.

[0166] In a similar manner, the control unit (120) can calculate the amount of available lithium loss related to SEI layer growth during the reference period based on the reference period and the first loss rate. The control unit (120) can calculate the amount of available lithium loss related to transition metal dissolution during the reference period based on the reference period and the second loss rate. The control unit (120) can calculate the amount of available lithium loss related to oxidation during the reference period based on the reference period and the third loss rate.

[0167] A battery diagnostic device (100) according to one embodiment of the present invention can monitor and diagnose the condition of a battery by calculating the amount of available lithium loss during a reference period based on a reference period and an available lithium loss rate.

[0168]

[0169] Below, a specific embodiment in which the control unit (120) estimates the accumulated available lithium loss amount is described.

[0170] The control unit (120) can estimate the cumulative available lithium loss up to the current diagnosis point based on the available lithium loss amount and the cumulative available lithium loss amount up to the previous diagnosis point.

[0171] Specifically, the control unit (120) may be configured to estimate the cumulative available lithium loss amount up to the current diagnosis point by adding the available lithium loss amount during the reference period at the current diagnosis point to the cumulative available lithium loss amount up to the previous diagnosis point.

[0172] Here, the cumulative available lithium loss represents the total amount of available lithium loss accumulated over time.

[0173] The cumulative available lithium loss amount up to the previous diagnosis point refers to the total amount of available lithium loss accumulated up to the previous diagnosis point. If a reference period is set, the cumulative available lithium loss amount up to the previous diagnosis point may represent the cumulative loss amount prior to the start of the reference period.

[0174] For example, the control unit (120) can estimate the cumulative available lithium loss amount up to the nth time point by summing the available lithium loss amount between the n-1st time point and the nth time point and the cumulative available lithium loss amount up to the n-1st time point.

[0175] As a more specific example, if the cumulative available lithium loss amount up to the previous diagnosis point is 5 Ah / m³ and the available lithium loss amount during the reference period is 0.5 Ah / m³, the control unit (120) can determine the cumulative available lithium loss amount up to the current diagnosis point as 5.5 Ah / m³ by adding the available lithium loss amount (0.5 Ah / m³) to the cumulative available lithium loss amount up to the previous diagnosis point (5 Ah / m³).

[0176] In a similar manner, the control unit (120) can calculate the cumulative available lithium loss related to SEI layer growth based on a first loss rate. The control unit (120) can calculate the cumulative available lithium loss related to transition metal dissolution based on a second loss rate. The control unit (120) can calculate the cumulative available lithium loss related to oxidation based on a third loss rate.

[0177] A battery diagnostic device (100) according to one embodiment of the present invention can effectively diagnose the long-term deterioration state of battery performance by determining the accumulated available lithium loss amount at each reference period and tracking the accumulated degradation state of the battery over time.

[0178]

[0179] FIGS. 3 to 6 are diagrams illustrating the correlation between the available lithium loss rate estimated using a P2D model and a battery diagnostic device (100).

[0180] Each data point represents the degree of agreement between the estimates of the battery diagnostic device (100) to which the P2D model and the lightweight model are applied, and the closer the data points are distributed to the linear trend line, the higher the degree of agreement between the two models.

[0181] The horizontal axis of Fig. 3 represents the cumulative available lithium loss (LLI) related to SEI layer growth estimated through the P2D model. RE [P2D]) represents the cumulative available lithium loss amount (LLI) related to SEI layer growth estimated through the battery diagnostic device (100), and the vertical axis represents the amount of accumulated available lithium loss (LLI) related to SEI layer growth estimated through the battery diagnostic device (100). RE [RM]) represents.

[0182] Referring to FIG. 3, the cumulative available lithium loss amount (LLI) related to SEI layer growth estimated through the battery diagnostic device (100) RE [RM]) is the cumulative available lithium loss (LLI) related to SEI layer growth estimated through the P2D model RE [P2D]) shows a tendency close to a linear relationship. That is, the data points of the graph are located close to the linear relationship trend line, so the cumulative available lithium loss amount (LLI) related to SEI layer growth of the battery diagnostic device (100) RE [RM]) The cumulative available lithium loss (LLI) related to SEI layer growth in the P2D model RE [P2D]) indicates a high degree of agreement.

[0183] The horizontal axis of Fig. 4 represents the cumulative available lithium loss (LLI) related to transition metal dissolution estimated through the P2D model. TM [P2D]) is represented, and the vertical axis represents the cumulative available lithium loss (LLI) related to transition metal dissolution estimated through the battery diagnostic device (100). TM [RM]) represents.

[0184] Referring to FIG. 4, the cumulative available lithium loss (LLI) related to transition metal dissolution estimated through the battery diagnostic device (100) TM [RM]) is the cumulative available lithium loss (LLI) related to transition metal dissolution estimated through the P2D model TM[P2D]) can be observed to show a tendency close to a linear relationship. That is, the data points of the graph are located close to the linear relationship trend line, so the cumulative available lithium loss amount (LLI) related to transition metal dissolution of the battery diagnostic device (100) TM [RM]) is the cumulative available lithium loss (LLI) related to transition metal dissolution in the P2D model TM [P2D]) indicates a high degree of agreement.

[0185] The horizontal axis of Fig. 5 represents the oxidation-related cumulative available lithium loss (LLI) estimated through the P2D model. OX [P2D]) is represented, and the vertical axis represents the oxidation-related cumulative available lithium loss (LLI) estimated through the battery diagnostic device (100). OX [RM]) represents.

[0186] Referring to FIG. 5, the oxidation-related cumulative available lithium loss (LLI) estimated through the battery diagnostic device (100) OX [RM]) is the oxidation-related cumulative available lithium loss (LLI) estimated through the P2D model OX [P2D]) shows a tendency close to a linear relationship. That is, the data points of the graph are located close to the linear relationship trend line, so the oxidation-related cumulative available lithium loss amount (LLI) of the battery diagnostic device (100) OX [RM]) is the oxidation-related cumulative available lithium loss (LLI) of the P2D model OX [P2D]) indicates a high degree of agreement.

[0187] The horizontal axis of FIG. 6 represents the cumulative available lithium loss amount (LLI[P2D]) estimated through the P2D model, and the vertical axis represents the cumulative available lithium loss amount (LLI[RM]) estimated through the battery diagnostic device (100).

[0188] Referring to FIG. 6, it can be seen that the cumulative available lithium loss amount (LLI[RM]) estimated through the battery diagnostic device (100) shows a tendency close to a linear relationship with the cumulative available lithium loss amount (LLI[P2D]) estimated through the P2D model. That is, the data points of the graph are located close to the linear relationship trend line, indicating that the cumulative available lithium loss amount (LLI[RM]) of the battery diagnostic device (100) shows a high degree of agreement with the cumulative available lithium loss amount (LLI[P2D]) of the P2D model.

[0189] A battery diagnostic device (100) according to one embodiment of the present invention is based on a lightweight model that approximates a P2D model, and can improve computational speed while maintaining a high level of accuracy similar to that of a P2D model. Specifically, the battery diagnostic device (100) uses a profile (e.g., a lookup table, etc.) composed of data pre-calculated using a P2D model to rapidly estimate the accumulated available lithium loss amount, and has the advantage of maintaining accuracy close to the precise calculation result of a P2D model.

[0190]

[0191] Below, a specific embodiment in which the control unit (120) estimates the available lithium loss rate using a damping factor is described.

[0192] Figure 7 is a schematic diagram illustrating the change in State of Health (SOH) according to charge-discharge cycles. In Figure 7, the horizontal axis represents charge-discharge cycles (times), and the vertical axis represents SOH ([%]).

[0193] Referring to Figure 7, it can be seen that the SOH of the battery gradually decreases as the charge / discharge cycle increases.

[0194] Figure 8 is a schematic diagram illustrating the change in the accumulated available lithium loss amount according to the charge-discharge cycle. In Figure 8, the horizontal axis represents the charge-discharge cycle (times), and the vertical axis represents the accumulated available lithium loss amount (LLI[Ah]).

[0195] Referring to Figure 8, it can be seen that the accumulated available lithium loss gradually increases as the charge-discharge cycle increases. That is, the accumulated available lithium loss increases rapidly during the initial charge-discharge cycle, but the rate of increase slows down as the cycle progresses.

[0196] The battery diagnostic device (100) can estimate the available lithium loss rate using a damping factor to more realistically reflect the degradation state of the battery. That is, the battery diagnostic device (100) can model the saturation characteristic in which the available lithium loss rate gradually slows down over time through the damping factor.

[0197] For example, the damping factor can be set in the form of exp(-γ), where γ is the damping rate coefficient. The damping rate coefficient is a coefficient designed to reflect the characteristic that the rate at which available lithium is lost gradually slows down or stabilizes as battery degradation progresses. In this case, it can be modeled that the larger the damping rate coefficient, the faster the slowing of the available lithium loss rate, and the smaller the damping rate coefficient, the more gradual the slowing of the available lithium loss rate.

[0198] In addition, the initial damping factor can be set to 0 to calculate the available lithium loss rate without applying damping effects in the initial state of life (SOH 100%). In this case, if the initial damping factor is set to 0, the initial available lithium loss rate is calculated without damping effects, and then the damping factor can be set to apply a damping term of the form exp(-γ) to reflect the effect of the loss rate slowing down over time.

[0199] The damping coefficient can be set based on a negative correlation with SOH. For example, relationship data indicating a negative correlation between SOH and the damping coefficient may be stored in advance in the storage unit (130), and the control unit (120) can determine the damping coefficient from the relationship data by referring to the SOH value of the battery.

[0200] In other words, the damping coefficient can be set to increase as the battery's SOH decreases, and as a result, the damping factor, which has a negative correlation with the damping coefficient, gradually decreases as degradation progresses.

[0201] The control unit (120) can determine a damping factor corresponding to the SOH of the battery.

[0202] Specifically, the control unit (120) can obtain the SOH of the battery. For example, the control unit (120) can estimate the SOH of the battery based on battery data. As another example, the data acquisition unit (110) can receive SOH data from an external source. And, the control unit (120) can receive SOH data from the data acquisition unit (110). And, the control unit (120) can determine a damping factor corresponding to the SOH of the battery based on pre-stored relational data.

[0203] The control unit (120) can correct the estimated first loss rate based on the attenuation factor. For example, the control unit (120) can correct the first loss rate by multiplying the estimated first loss rate by the attenuation factor. That is, the control unit (120) can determine the value obtained by multiplying the estimated first loss rate by the attenuation factor based on the cathode potential, cathode lithium stoichiometry, and acceleration factor as the corrected first loss rate.

[0204] The control unit (120) can correct the estimated second loss rate based on the attenuation factor. For example, the control unit (120) can correct the second loss rate by multiplying the estimated second loss rate by the attenuation factor. That is, the control unit (120) can determine the value obtained by multiplying the estimated second loss rate based on the positive potential and acceleration factor by the attenuation factor as the corrected second loss rate.

[0205] The control unit (120) can correct the estimated third loss rate based on the attenuation factor. For example, the control unit (120) can correct the third loss rate by multiplying the estimated third loss rate by the attenuation factor. That is, the control unit (120) can determine the value obtained by multiplying the estimated third loss rate based on the positive potential by the attenuation factor as the third loss rate.

[0206] Meanwhile, the damping factors used to estimate each of the first to third loss rates may be set to be the same or different.

[0207] For example, the damping factor can be set by considering the pattern of change in the available lithium loss rate due to SEI layer growth, the pattern of change in the available lithium loss rate due to transition metal dissolution, and the pattern of change in the available lithium loss rate due to oxidation.

[0208] As another example, a first attenuation factor for the pattern of change in the available lithium loss rate due to SEI layer growth, a second attenuation factor for the pattern of change in the available lithium loss rate due to transition metal dissolution, and a third attenuation factor for the pattern of change in the available lithium loss rate due to oxidation may each be set independently. In this case, the available lithium loss rate according to each degradation mechanism can be estimated more precisely.

[0209] The control unit (120) can estimate the available lithium loss rate based on the corrected first to third loss rates. Specifically, the control unit (120) can estimate the available lithium loss rate by summing the corrected first loss rate, the corrected second loss rate, and the corrected third loss rate.

[0210] A battery diagnostic device (100) according to one embodiment of the present invention has the advantage of being able to more accurately simulate the actual degradation pattern of a battery and improve the reliability of battery condition diagnosis by estimating the available lithium loss rate using a damping factor.

[0211]

[0212] Below, a specific embodiment in which the control unit (120) diagnoses the state of the battery is described.

[0213] The control unit (120) can diagnose the condition of the battery based on an estimated value related to SEI layer growth.

[0214] For example, the control unit (120) can compare the loss amount (including available lithium loss amount and accumulated available lithium loss amount) with a corresponding threshold value and diagnose the state of the battery based on the comparison result. Here, the loss amount is a term including available lithium loss amount and accumulated available lithium loss amount.

[0215] Here, the threshold is a value compared with the amount of loss, serving as a criterion for distinguishing the battery's state as normal or abnormal. Here, the threshold is a term that includes the first threshold and the second threshold.

[0216] Specifically, the control unit (120) can compare the magnitude between the loss amount and the corresponding threshold value, and diagnose the state of the battery based on the comparison result.

[0217] The control unit (120) can compare the available lithium loss amount with a preset first threshold value. If the available lithium loss amount is greater than or equal to the first threshold value, the control unit (120) can diagnose the battery's condition as abnormal. Conversely, if the available lithium loss amount is less than the first threshold value, the control unit (120) can diagnose the battery's condition as normal.

[0218] The control unit (120) can compare the accumulated available lithium loss amount with a preset second threshold. If the accumulated available lithium loss amount is greater than or equal to the second threshold, the control unit (120) can diagnose the battery's condition as abnormal. Conversely, if the accumulated available lithium loss amount is less than the second threshold, the control unit (120) can diagnose the battery's condition as normal.

[0219] A battery diagnostic device (100) according to one embodiment of the present invention has the advantage of being able to precisely diagnose the condition of the battery by comparing a threshold value of the loss amount and improve the safety of the battery.

[0220]

[0221] The accumulated available lithium loss can be used to calculate the battery's State of Health (SOH).

[0222] In one embodiment, the control unit (120) may consider the accumulated available lithium loss amount together with the accumulated positive active material loss amount and the accumulated negative active material loss amount to calculate the SOH of the battery.

[0223] Cathode active material loss refers to the phenomenon of active material decreasing in the cathode of a lithium-ion battery and acts as one of the major causes of battery degradation. The cumulative amount of cathode active material loss can represent the difference between the initial cathode active material capacity and the current cathode active material capacity.

[0224] Cathode active material loss refers to the phenomenon of active material decreasing at the negative electrode of a lithium-ion battery and acts as one of the major causes of battery degradation. The cumulative amount of negative active material loss can represent the difference between the initial negative active material capacity and the current negative active material capacity.

[0225] The control unit (120) can calculate SOH by adjusting a pre-stored reference positive profile and reference negative profile based on the accumulated positive active material loss amount, the accumulated negative active material loss amount, and the accumulated available lithium loss amount. The accumulated positive active material loss amount and the accumulated negative active material loss amount can be obtained in various known ways.

[0226] A reference positive profile is a profile representing the correspondence between the capacity and voltage of a reference positive cell that is preset to correspond to the positive of a battery. For example, the reference positive cell may be the positive of a positive coin half cell or a three-electrode cell. And, a reference negative profile is a profile representing the correspondence between the capacity and voltage of a reference negative cell that is preset to correspond to the negative of a battery. For example, the reference negative cell may be the negative of a negative coin half cell or a three-electrode cell.

[0227] The control unit (120) can shrink the reference anode profile considering the accumulated amount of positive active material loss and shrink the reference cathode profile considering the accumulated amount of negative active material loss. The amount of shrinkage of the reference anode profile and the amount of accumulated positive active material loss may have a predetermined corresponding relationship. The amount of shrinkage of the reference cathode profile and the amount of accumulated negative active material loss may have a predetermined corresponding relationship.

[0228] And, the control unit (120) can generate a corrected positive profile and a corrected negative profile by moving the contracted reference positive profile and the contracted reference negative profile based on the accumulated available lithium loss amount. For example, the control unit (120) can generate a corrected positive profile and a corrected negative profile by moving the contracted reference positive profile and the contracted reference negative profile in parallel along the capacity axis in a negative direction (i.e., the low capacity side) based on the accumulated available lithium loss amount.

[0229] The amount of parallel shift and the amount of accumulated available lithium loss can have a corresponding relationship of a certain amount.

[0230] Subsequently, the control unit (120) can generate a full cell profile based on the difference between the corrected positive profile and the corrected negative profile. The full cell profile represents the correspondence between the voltage and capacity of the battery.

[0231] The control unit (120) can estimate the SOH of the battery by comparing the generated full cell profile with a previously stored reference full cell profile.

[0232] Here, the reference full cell profile represents the correspondence between voltage and capacity obtained for a battery in the BOL (beginning of life) state. The reference full cell profile may be stored in advance in memory, etc., based on the difference between the potential of the reference positive profile and the potential of the reference negative profile within a predetermined capacity range. For example, the control unit (120) can calculate the SOH of the battery by calculating the ratio between the size of the capacity range of the generated full cell profile and the size of the capacity range of the reference full cell profile.

[0233] A battery diagnostic device (100) according to one embodiment of the present invention can estimate the SOH of a battery based on the accumulated available lithium loss amount, and thereby effectively diagnose the performance degradation of the battery.

[0234]

[0235] The battery diagnostic device (100) can be configured to set usage conditions based on the results of a condition diagnosis for the battery.

[0236] In one embodiment, the control unit (120) may be configured to set the battery usage conditions based on at least one of the available lithium loss rate, available lithium loss amount, cumulative available lithium loss amount, battery state and SOH.

[0237] For example, if the battery condition is diagnosed as normal, the control unit (120) may maintain the existing usage conditions. Conversely, if the battery condition is diagnosed as abnormal, the control unit (120) may change the existing usage conditions. For example, if the battery condition is diagnosed as abnormal, the control unit (120) may be configured to reduce the maximum charge / discharge rate. As another example, if the battery condition is diagnosed as abnormal, the control unit (120) may be configured to reduce the charge end voltage. Here, the charge end voltage may refer to the maximum voltage allowed during charging of the battery. As yet another example, if the battery condition is diagnosed as abnormal, the control unit (120) may increase the discharge end voltage. Here, the discharge end voltage may refer to the minimum voltage allowed during discharging of the battery.

[0238] In another embodiment, the control unit (120) can set the battery usage conditions according to a pre-set protocol to define a correspondence between at least one of the available lithium loss rate, available lithium loss amount, cumulative available lithium loss amount, battery state and SOH and the usage conditions.

[0239] Meanwhile, regarding specific embodiments for setting the usage conditions of the battery, it goes without saying that various methods easily applicable by a person skilled in the art to which the present invention belongs can be used.

[0240] A battery diagnostic device (100) according to one embodiment of the present invention can mitigate performance degradation of the battery and improve lifespan and stability by appropriately controlling the usage conditions of the battery in consideration of the condition diagnosis results of the battery.

[0241]

[0242] The battery diagnostic device (100) according to the present invention may be applied to a BMS. That is, the BMS according to the present invention may include the battery diagnostic device (100) described above. In this configuration, at least some of the components of the battery diagnostic device (100) may be implemented by supplementing or adding the functions of the components included in a conventional BMS. For example, the data acquisition unit (110), control unit (120), and storage unit (130) of the battery diagnostic device (100) may be implemented as components of the BMS.

[0243]

[0244] FIG. 9 is a schematic diagram illustrating a battery pack (10) according to another embodiment of the present invention.

[0245] The battery diagnostic device (100) according to the present invention may be provided in a battery pack (10). That is, the battery pack (10) according to the present invention may include the battery diagnostic device (100) described above and one or more battery cells. In addition, the battery pack (10) may further include electrical components (relays, fuses, etc.) and a case, etc.

[0246] The positive terminal of the battery (11) can be connected to the positive terminal (P+) of the battery pack (10), and the negative terminal of the battery (11) can be connected to the negative terminal (P-) of the battery pack (10).

[0247] The measuring unit (12) can be connected to the first sensing line (SL1), the second sensing line (SL2), and the third sensing line (SL3). Specifically, the measuring unit (12) can be connected to the positive terminal of the battery (11) through the first sensing line (SL1) and to the negative terminal of the battery (11) through the second sensing line (SL2). The measuring unit (12) can measure the voltage of the battery (11) based on the voltage measured at each of the first sensing line (SL1) and the second sensing line (SL2).

[0248] The measuring unit (12) can be connected to a current measuring unit (A) via a third sensing line (SL3). For example, the current measuring unit (A) may be an ammeter or a shunt resistor capable of measuring the charging current and discharging current of the battery (11). The measuring unit (12) can calculate the charging amount by measuring the charging current of the battery (11) via the third sensing line (SL3). Additionally, the measuring unit (12) can calculate the discharging amount by measuring the discharging current of the battery (11) via the third sensing line (SL3).

[0249] The measuring unit (12) may include a temperature sensor (not shown). The measuring unit (12) can measure the temperature of the battery using the temperature sensor.

[0250] The data acquisition unit (110) can be connected via wired and / or wireless means to communicate with the measurement unit (12). The data acquisition unit (110) can receive voltage, current, and / or temperature information of the battery (11) from the measurement unit (12).

[0251]

[0252] FIG. 10 is a schematic drawing illustrating a vehicle (1) according to another embodiment of the present invention.

[0253] Referring to FIG. 10, the battery pack (10) described above with reference to FIG. 9 may be included in a vehicle (1), such as an electric vehicle (EV) or a hybrid vehicle (HV). The battery pack (10) can drive the vehicle (1) by supplying power to a motor through an inverter provided in the vehicle (1). Here, the battery pack (10) may include a battery diagnostic device (100). In this case, the battery diagnostic device (100) may be an on-board device included in the vehicle (1).

[0254]

[0255] FIG. 11 is a schematic diagram illustrating a server (2) according to another embodiment of the present invention.

[0256] Referring to FIG. 11, the battery diagnostic device (100) according to the present invention may be provided in a server (2). The server (2) provides high-performance computing resources and data storage functions to estimate the available lithium loss rate, available lithium loss amount, and / or cumulative available lithium loss amount of the battery.

[0257] The server (2) can individually acquire battery data from a plurality of BMSs (3), analyze it in real time, and continuously monitor the available lithium loss rate per battery, the amount of available lithium loss during a reference period, and / or the cumulative amount of available lithium loss. Specifically, the server (2) can estimate the first to third loss rates by referring to the first to fourth profiles based on the battery data. Furthermore, the server (2) can estimate at least one of the available lithium loss rate of the battery, the amount of available lithium loss during a reference period, and the cumulative amount of available lithium loss. Additionally, the server (2) can diagnose the condition of the battery based on the amount of available lithium loss during a reference period and / or the cumulative amount of available lithium loss.

[0258] The server (2) can be linked with a plurality of BMS (3) and / or user terminals (4), etc., to perform integrated management of a battery system including a plurality of batteries. The server (2) can be connected via wired and / or wireless connections to communicate with a plurality of BMS (3) and / or user terminals (4).

[0259] The server (2) is linked with the BMS (3) and can transmit the available lithium loss rate of the battery, the amount of available lithium loss during a reference period, the cumulative amount of available lithium loss, and / or the diagnosis results to the corresponding BMS (3). Alternatively, if the server (2) diagnoses that the battery condition is abnormal, it can transmit a warning or control signal to the corresponding BMS (3).

[0260] The server (2) can be linked with the user terminal (4) to allow the user to remotely monitor the status of the battery. The user can check the status of the battery in real time using a dedicated application.

[0261]

[0262] FIG. 12 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention. FIG. 13 is a schematic diagram illustrating the sub-steps of step S1220 of FIG. 12.

[0263] Each step of the battery diagnostic method can be performed by a battery diagnostic device (100). For convenience of explanation, details that overlap with previously described content will be omitted or briefly explained below.

[0264] Referring to FIG. 12, the battery diagnostic method includes steps S1210 and S1220.

[0265] Step S1210 is a step of acquiring battery data including at least one of the voltage, current, and temperature of the battery, and can be performed by a data acquisition unit (110).

[0266] Step S1220 is a step of estimating the available lithium loss rate of a battery by referring to a first profile pre-set for estimating the negative potential, a second profile pre-set for estimating the positive potential, a third profile pre-set for estimating the negative lithium stoichiometry, and a fourth profile pre-set for estimating the acceleration factor based on battery data, and can be performed by a control unit (120).

[0267] Referring to FIG. 13, step S1220 may include step S1221, step S1222, step S1223, step S1224, step S1225, and step S1226.

[0268] Step S1221 is a step of estimating the negative potential of a battery by referring to a first profile, and can be performed by a control unit (120).

[0269] Step S1222 is a step of estimating the positive potential of the battery by referring to the second profile, and can be performed by the control unit (120).

[0270] Step S1223 is a step of estimating the negative lithium stoichiometry of the battery by referring to the third profile, and can be performed by the control unit (120).

[0271] Step S1224 is a step of estimating the acceleration factor of the battery by referring to the fourth profile, and can be performed by the control unit (120).

[0272] Step S1225 is a step of estimating a first loss rate based on the cathode potential, cathode lithium stoichiometry, and acceleration factor, and can be performed by the control unit (120). For example, the control unit (120) can calculate the first loss rate using the previously described Equation 1 and Equation 2.

[0273] Step S1226 is a step of estimating a second loss rate based on the positive potential and acceleration factor, and can be performed by the control unit (120). For example, the control unit (120) can calculate the second loss rate using the previously described Equations 3 and 4.

[0274] Step S1227 is a step of estimating a third loss rate based on positive potential, which can be performed by the control unit (120). For example, the control unit (120) can calculate the third loss rate using the previously described Equations 5 and 6.

[0275] Step S1228 is a step of calculating the available lithium loss rate by summing the first to third loss rates, and can be performed by the control unit (120).

[0276]

[0277] FIG. 14 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0278] Referring to FIG. 14, the battery diagnostic method includes steps S1210, S1220, and S1230.

[0279] Steps S1210 and S1220 of Fig. 14 are the same steps as steps S1210 and S1220 of Fig. 12.

[0280] Step S1230 is a step of calculating the amount of available lithium loss of the battery during a reference period based on the available lithium loss rate and a reference period between the previous diagnosis time and the current diagnosis time, and can be performed by the control unit (120).

[0281] In one embodiment, the control unit (120) can calculate the amount of available lithium loss by multiplying the reference period by the available lithium loss rate. For example, if the reference period is 0.1 seconds and the available lithium loss rate is 0.5 Ah / second per hour, the amount of available lithium loss during the reference period can be calculated as 0.05 Ah.

[0282] In another embodiment, the control unit (120) can calculate the amount of available lithium loss during a reference period by integrating the available lithium loss rate for a reference period over time.

[0283]

[0284] FIG. 15 is a schematic diagram illustrating a battery diagnostic method according to another embodiment of the present invention.

[0285] Referring to FIG. 15, the battery diagnostic method includes steps S1210, S1220, S1230, and S1240.

[0286] Steps S1210 and S1220 of Fig. 14 are the same steps as steps S1210 and S1220 of Fig. 12, and step S1230 of Fig. 14 is the same step as step S1230 of Fig. 13.

[0287] Step S1240 is a step of calculating the cumulative available lithium loss amount up to the current diagnosis point by adding the available lithium loss amount to the cumulative available lithium loss amount up to the previous diagnosis point, and can be performed by the control unit (120).

[0288] Specifically, the control unit (120) may be configured to estimate the accumulated available lithium loss amount up to the current diagnosis point by adding the available lithium loss amount to the accumulated available lithium loss amount up to the previous diagnosis point.

[0289] For example, the control unit (120) can estimate the cumulative available lithium loss amount up to the nth time point by summing the available lithium loss amount between the n-1st time point and the nth time point and the cumulative available lithium loss amount up to the n-1st time point.

[0290]

[0291] Another embodiment of the present invention may provide a computer-readable recording medium having a program recorded thereon for executing the various embodiments described above on a computer.

[0292] A program may be implemented as hardware components, software components, and / or a combination of hardware and software components. A program may be executed by any system capable of executing computer-readable instructions.

[0293] Software may include computer programs, code, instructions, or a combination thereof, and may configure a processing unit to operate as desired or command the processing unit independently or collectively.

[0294] Software can be implemented as a computer program containing instructions stored on a computer-readable storage medium. Examples of computer-readable storage media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disks, hard disks, etc.) and optical reading media (e.g., CD-ROMs, DVDs (Digital Versatile Discs)). Computer-readable storage media can be distributed across networked computer systems, allowing computer-readable code to be stored and executed in a distributed manner. The storage medium is readable by a computer, stored in memory, and can be executed by a processor.

[0295] Computer-readable recording media may be provided in the form of non-transitory recording media. Here, 'non-transitory storage media' simply means that it is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily. For example, 'non-transitory storage media' may include a buffer in which data is stored temporarily.

[0296] In addition, the program may be provided by being included in a computer program product. A computer program product may be traded between a seller and a buyer as a product.

[0297] A computer program product may include a software program or a computer-readable recording medium on which the software program is stored. For example, a computer program product may include a product in the form of a software program that is distributed electronically through a manufacturer of an electronic device or an electronic market (e.g., a downloadable application). For electronic distribution, at least a portion of the software program may be stored on a recording medium or temporarily created. In this case, the recording medium may be a server of the manufacturer of the electronic device, a server of the electronic market, or a recording medium of a relay server that temporarily stores the software program.

[0298]

[0299] The embodiments of the present invention described above are not limited to implementation through devices and methods, but may also be implemented through a program that realizes a function corresponding to the configuration of the embodiments of the present invention or a recording medium on which such a program is recorded. Such implementation can be easily achieved by a person skilled in the art to which the present invention pertains, based on the description of the embodiments described above.

[0300] Although the present invention has been described above by limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical spirit of the present invention and the equivalent scope of the claims described below by those skilled in the art to which the present invention belongs.

[0301] Furthermore, since the present invention described above allows for various substitutions, modifications, and changes within the scope of the technical concept of the present invention to those skilled in the art without departing from the technical spirit of the present invention, it is not limited by the aforementioned embodiments and attached drawings, but rather all or part of each embodiment may be selectively combined to allow for various modifications.

[0302]

[0303] (Explanation of symbols)

[0304] 1: Vehicle

[0305] 2: Server

[0306] 3: BMS

[0307] 4: User terminal

[0308] 10: Battery pack

[0309] 11: Battery

[0310] 12: Measurement section

[0311] 100: Battery Diagnostic Device

[0312] 110: Data acquisition unit

[0313] 120: Control unit

[0314] 130: Storage section

Claims

1. A data acquisition unit configured to acquire battery data including at least one of the voltage, current, and temperature of the battery; and A battery diagnostic device comprising a control unit configured to estimate the available lithium loss rate of the battery by referring to a first profile pre-set for estimating the negative potential, a second profile pre-set for estimating the positive potential, a third profile pre-set for estimating the negative lithium stoichiometry, and a fourth profile pre-set for estimating the acceleration factor, based on the battery data above.

2. In Paragraph 1, The above first profile is, It is configured to represent a correspondence relationship between multiple reference battery data and multiple first reference state data, and The above control unit is, A battery diagnostic device configured to determine a first reference state data corresponding to the battery data by referring to the first profile, and to estimate the negative potential of the battery based on the determined first reference state data.

3. In Paragraph 1, The above second profile is, It is configured to represent a correspondence relationship between multiple reference battery data and multiple second reference state data, and The above control unit is, A battery diagnostic device configured to determine second reference state data corresponding to the battery data by referring to the second profile above, and to estimate the positive potential of the battery based on the determined second reference state data.

4. In Paragraph 1, The above third profile is, It is configured to represent a correspondence relationship between multiple reference battery data and multiple third reference state data, and The above control unit is, A battery diagnostic device configured to determine third reference state data corresponding to the battery data by referring to the third profile above, and to estimate the negative lithium stoichiometry of the battery based on the determined third reference state data.

5. In Paragraph 1, The above fourth profile is, It is configured to represent a correspondence relationship between multiple reference battery data and multiple fourth reference state data, and The above control unit is, A battery diagnostic device configured to determine a fourth reference state data corresponding to the battery data by referring to the fourth profile above, and to estimate the acceleration factor of the battery based on the determined fourth reference state data.

6. In Paragraph 1, The above control unit is, A battery diagnostic device configured to estimate the negative potential, positive potential, negative lithium stoichiometry, and acceleration factor of the battery by referring to the first profile, the second profile, the third profile, and the fourth profile, and to estimate the first loss rate related to SEI layer growth, the second loss rate related to transition metal dissolution, and the third loss rate related to oxidation of the battery based on at least one of the estimated negative potential, positive potential, negative lithium stoichiometry, and acceleration factor of the battery, and to estimate the available lithium loss rate based on the first loss rate, the second loss rate, and the third loss rate.

7. In Paragraph 6, The above control unit is, A battery diagnostic device configured to estimate the first loss rate based on the above cathode potential, the above cathode lithium stoichiometry, and the above acceleration factor.

8. In Paragraph 6, The above control unit is, A battery diagnostic device configured to estimate the second loss rate based on the anode potential and the acceleration factor.

9. In Paragraph 6, The above control unit is, A battery diagnostic device configured to estimate the third loss rate based on the above positive potential.

10. In Paragraph 6, The above control unit is, A battery diagnostic device configured to estimate the available lithium loss rate by summing the first loss rate, the second loss rate, and the third loss rate.

11. In Paragraph 1, The above control unit is, A battery diagnostic device configured to estimate the amount of available lithium loss of the battery during the reference period, based on the available lithium loss rate and the reference period between the previous diagnostic point and the current diagnostic point.

12. In Paragraph 11, The above control unit is, A battery diagnostic device configured to estimate the cumulative available lithium loss amount up to the current diagnostic point by adding the above available lithium loss amount to the cumulative available lithium loss amount up to the previous diagnostic point.

13. A battery pack comprising a battery diagnostic device according to any one of paragraphs 1 to 12.

14. A server comprising a battery diagnostic device according to any one of paragraphs 1 through 12.

15. A step of acquiring battery data including at least one of the voltage, current, and temperature of the battery; and A battery diagnostic method comprising the step of estimating the available lithium loss rate of the battery by referring to a first profile pre-set for estimating the negative potential, a second profile pre-set for estimating the positive potential, a third profile pre-set for estimating the negative lithium stoichiometry, and a fourth profile pre-set for estimating the acceleration factor, based on the battery data above.

16. A computer-readable recording medium having a program recorded thereon for performing the battery diagnostic method of paragraph 15 on a computer.

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