Battery diagnostic device, battery pack, electric vehicle, and battery diagnostic method

Abstract

The invention provides a battery diagnosis apparatus, a battery pack, an electric vehicle, and a battery diagnosis method. The battery diagnosis apparatus includes a control circuit configured to generate a Q-V profile, a standardized Q-V profile, and a Q-dV / dQ profile based on capacity-voltage relationship data of a battery cell acquired by a data acquisition unit. The control circuit identifies a cutoff reference point located in the reference capacity range according to the Q-dV / dQ curve. The control circuit determines a profile fitting factor associated with a Q-V profile of interest, the Q-V profile of interest being a higher capacity side portion of the standardized Q-V profile based on the capacity value of the cutoff reference point. The control circuit determines at least one degradation parameter of the battery cell based on the profile fitting factor.

Description

Technical Field

[0001] The present disclosure relates to the diagnosis of deterioration in battery cells.

[0002] This application claims priority to Korean Patent Application No. 10-2023-0119680, filed in Korea on September 8, 2023, the disclosure of which is incorporated herein by reference. Background Art

[0003] Recently, the demand for portable electronic products such as laptop computers, video cameras, and mobile phones has increased rapidly, and with the widespread development of electric vehicles, storage batteries for energy storage, robots, and artificial satellites, much research has been conducted on high-performance batteries that can be repeatedly charged and discharged.

[0004] Currently, commercially available batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, lithium batteries, etc. Among them, lithium batteries have little or no memory effect, and thus are more concerned than nickel-based batteries because they have the advantages of being able to be recharged conveniently at any time, having a very low self-discharge rate, and a high energy density.

[0005] There are many different deterioration monitoring techniques for battery cells. Specifically, differential voltage analysis (DVA) is based on time-series data of at least one battery parameter (e.g., voltage, current) that can be observed outside the battery cell.

[0006] In DVA, peaks in the differential voltage curve (also referred to as the "Q-dV / dQ profile") are regarded as key factors, and some types of battery cells have voltage plateau characteristics - the change in voltage during charging or discharging is almost maintained at 0. Since the differential voltage is also close to 0 in the capacity range where the voltage plateau characteristics are found, it is difficult to detect peaks from the Q-dV / dQ profile. Therefore, a method for accurately and easily diagnosing the deterioration of battery cells without extracting peak information indicating deterioration from the Q-dV / dQ profile is needed. Summary of the Invention

[0007] Technical Problem

[0008] The present disclosure is designed to solve the above problems, and thus the present disclosure relates to providing a battery diagnosis device and method for accurately estimating at least one deterioration parameter of the deterioration state of a battery cell having voltage plateau characteristics without disassembling the battery cell.

[0009] These and other objects and advantages of the present disclosure will be understood from the following description and will become apparent from the exemplary embodiments of the present disclosure. In addition, it will be readily understood that the objects and advantages of the present disclosure can be achieved by the means set forth in the appended claims and combinations thereof.

[0010] Technical solution

[0011] A battery diagnosis device according to an aspect of the present disclosure includes: a data acquisition unit configured to acquire capacity-voltage relationship data of battery cells; and a control circuit configured to generate a Q-V profile indicating the correspondence between the capacity and voltage of the battery cells, a normalized Q-V profile indicating the correspondence between the normalized capacity and voltage of the battery cells, and a Q-dV / dQ profile indicating the correspondence between the normalized capacity and differential voltage of the battery cells based on the capacity-voltage relationship data. The control circuit is configured to identify a cut-off reference point located in a reference capacity range from the Q-dV / dQ profile. The control circuit is configured to determine a profile fitting factor associated with the Q-V profile of interest, where the Q-V profile of interest is a higher-capacity-side portion of the normalized Q-V profile based on the capacity value of the cut-off reference point. The control circuit is configured to determine at least one degradation parameter of the battery cell based on the profile fitting factor.

[0012] The control circuit may be configured to generate a normalized Q-V profile by normalizing the Q-V profile based on the entire capacity range of the Q-V profile. The control circuit may be configured to generate a Q-dV / dQ profile by differentiating the normalized Q-V profile.

[0013] The control circuit may be configured to identify a local minimum point in the reference capacity range as the cut-off reference point according to the Q-dV / dQ profile.

[0014] The control circuit may be configured to generate a corrected Q-V profile of interest by performing a profile adjustment process for respectively matching the starting point and the ending point of the Q-V profile of interest to a first reference point and a second reference point. The control circuit may be configured to obtain a polynomial equation of the corrected Q-V profile of interest by applying a curve fitting algorithm to the corrected Q-V profile of interest. The control circuit may be configured to determine that the profile fitting factor is equal to the coefficient of the highest-degree term of the polynomial equation.

[0015] The control circuit may be configured to determine a first degradation parameter by using the profile fitting factor as an input variable of a linear regression model. The linear regression model may be pre-prepared as a relationship function between the profile fitting factor and the positive electrode degradation state.

[0016] The first degradation parameter may indicate the capacity reduction ratio caused by the degradation of the positive electrode of the battery cell.

[0017] The control circuit may be configured to determine a second degradation parameter based on the total capacity reduction ratio of the battery cell and a first degradation parameter. The second degradation parameter may indicate the capacity reduction ratio caused by the loss of available lithium in the battery cell.

[0018] The capacity-voltage relationship data may indicate the history of capacity change and voltage change of the battery while the battery cell is being charged or discharged.

[0019] A battery pack according to another aspect of the present disclosure includes the battery diagnostic device.

[0020] An electric vehicle according to still another aspect of the present disclosure includes the battery pack.

[0021] A battery diagnostic method according to yet another aspect of the present disclosure includes: obtaining capacity-voltage relationship data of a battery cell; generating a Q-V profile indicating the correspondence between the capacity and voltage of the battery cell, a normalized Q-V profile indicating the correspondence between the normalized capacity and voltage of the battery cell, and a Q-dV / dQ profile indicating the correspondence between the normalized capacity and differential voltage of the battery cell based on the capacity-voltage relationship data. Identifying a cut-off reference point located in a reference capacity range from the Q-dV / dQ profile; determining a profile fitting factor associated with the Q-V profile of interest, where the Q-V profile of interest is the higher-capacity-side portion of the normalized Q-V profile based on the capacity value of the cut-off reference point; and determining at least one degradation parameter of the battery cell based on the profile fitting factor.

[0022] Generating the Q-dV / dQ profile may include: generating a normalized Q-V profile by normalizing the Q-V profile over the entire capacity range of the Q-V profile; and generating the Q-dV / dQ profile by differentiating the normalized Q-V profile.

[0023] Determining the profile fitting factor of the battery cell may include generating a corrected Q-V profile of interest by performing a profile adjustment process for respectively matching the starting point and the ending point of the Q-V profile of interest to a predetermined first reference point and a predetermined second reference point; obtaining a polynomial equation of the corrected Q-V profile of interest by applying a curve fitting algorithm to the corrected Q-V profile of interest; and determining that the profile fitting factor is equal to the coefficient of the highest-degree term of the polynomial equation.

[0024] Determining at least one degradation parameter of the battery cell may include determining a first degradation parameter by using the profile fitting factor as an input variable of a linear regression model. The linear regression model may be pre-prepared as a relationship function between the profile fitting factor and the cathode degradation state.

[0025] Determining at least one degradation parameter of a battery cell may further include determining a second degradation parameter based on a total capacity reduction ratio of the battery cell and a first degradation parameter. The second degradation parameter may indicate a capacity reduction ratio caused by loss of available lithium of the battery cell.

[0026] Advantageous Effects

[0027] According to at least one of the embodiments of the present disclosure, at least one degradation parameter of the degradation state of a battery cell can be accurately estimated without disassembling the battery cell. Specifically, the present disclosure can diagnose the degradation state of the positive electrode of an LFP battery cell having a voltage plateau characteristic in a non-destructive manner.

[0028] In addition, according to at least one of the embodiments of the present disclosure, the degradation state of the positive electrode of the battery cell (the capacity degradation rate derived from the degradation of the positive electrode) can be more accurately determined by extracting and analyzing a part of the voltage curve (the "Q-V profile" described below) in which the degradation characteristic of the positive electrode material dominates over the degradation characteristic of the negative electrode material in the entire voltage curve (the "Q-V profile" described below) of the battery cell for a predetermined voltage range.

[0029] In addition, according to at least one of the embodiments of the present disclosure, by using the relationship between the total capacity reduction ratio of the battery cell, the capacity reduction ratio derived from the degradation of the positive electrode, and the capacity reduction ratio derived from lithium loss, the capacity reduction ratio derived from lithium loss can be easily calculated based on the total capacity reduction ratio of the battery cell and the capacity reduction ratio derived from the degradation of the positive electrode.

[0030] The effects of the present disclosure are not limited to the foregoing effects, and those skilled in the art will clearly understand these and other effects from the appended claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings illustrate exemplary embodiments of the present disclosure and are used together with the following detailed description to provide a better understanding of the technical aspects of the present disclosure, and thus the present disclosure should not be construed as being limited to the drawings.

[0032] Figure 1 is an exemplary view of an electric vehicle according to the present disclosure.

[0033] Figure 2 is a graph showing an example of a Q-V profile of a battery cell.

[0034] Figure 3 Shows according to Figure 2 An example of a normalized Q-V profile obtained from the Q-V profile of.

[0035] Figure 4 Shows the same as Figure 3An example of a Q-dV / dQ profile associated with the standardized Q-V profile shown in

[0036] Figure 5 is a graph showing an example of a Q-V profile of interest extracted from the standardized Q-V profile of Figure 4

[0037] Figure 6 shows an example of a corrected Q-V profile of interest obtained based on the Q-V profile of interest of Figure 5

[0038] Figure 7 is a diagram referred to in exemplarily describing the relationship between different positive electrode degradation levels and the corrected Q-V profile of interest.

[0039] Figures 8 to 10 shows the result of fitting a polynomial equation to each of the three corrected Q-V profiles of interest shown in Figure 7 by a curve fitting algorithm.

[0040] Figure 11 is a diagram referred to in exemplarily describing the relationship between different positive electrode degradation levels and the profile fitting factor.

[0041] Figure 12 is a flowchart schematically showing a battery diagnosis method according to an embodiment of the present disclosure.

[0042] Figure 13 is a flowchart exemplarily showing a subroutine that can be included in step S1220 in Figure 12

[0043] Figure 14 is a flowchart exemplarily showing a subroutine that can be included in step S1230 in Figure 12

[0044] Figure 15 is a flowchart exemplarily showing a subroutine that can be included in step S1250 in Figure 12 Detailed Description of the Invention

[0045] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Before the description, it should be understood that the terms or words used in this specification and the appended claims should not be construed as being limited to the general and dictionary meanings, but should be interpreted based on the meanings and concepts corresponding to the technical aspects of the present disclosure on the basis that the inventor appropriately defines the terms for the best explanation.

[0046] ​​​​​Accordingly, the embodiments described herein and the illustrations shown in the accompanying drawings are exemplary embodiments of the present disclosure to describe the technical aspects of the present disclosure and are not intended to be restrictive. Therefore, it should be understood that various other equivalents and modifications can be made thereto when this application is filed.

[0047] Terms including ordinal numbers such as "first", "second", etc. are used to distinguish one element from another among various elements, but are not intended to limit these elements by the terms.

[0048] Unless the context clearly indicates otherwise, the terms "comprising" and "including" when used in this specification specify the presence of the stated elements, but do not exclude the presence or addition of one or more other elements. In addition, as used herein, the term "control circuit 130" refers to a processing unit for at least one function or operation, and can be implemented by hardware and software alone or in combination.

[0049] Furthermore, throughout the specification, it should also be understood that when an element is referred to as being "connected to" another element, it can be directly connected to that other element, or there can be intermediate elements.

[0050] Figure 1 is a diagram exemplarily showing an electric vehicle according to the present disclosure.

[0051] Reference Figure 1 , the electric vehicle 1 includes a system controller 2, a battery pack 10, an inverter 30, and a motor 40. The charge / discharge terminals P+, P- of the battery pack 10 can be electrically coupled to a charger 3 through a charging cable. The charger 3 can be included in the electric vehicle 1 or can be present in a charging station. The electric vehicle 1 is an example of a battery system, which is a system of an upper concept including the battery pack 10 for at least one of energy storage or energy supply. Therefore, the following description can be generally applicable to the battery system including the electric vehicle 1.

[0052] The system controller 2 (e.g., an electronic control unit (ECU)) is configured to send a key-on signal to the battery diagnostic device 100 in response to a user changing the start button (not shown) of the electric vehicle 1 to the on position. The system controller 2 is configured to send a key-off signal to the battery diagnostic device 100 in response to a user changing the start button to the off position. The charger 3 can supply a charging power selected from constant power, constant current, and constant voltage via communication with the system controller 2 through the charge / discharge terminals P+, P- of the battery pack 10.

[0053] The battery pack 10 includes batteries 11 and a relay 20. The battery pack 10 may further include a battery diagnostic device 100.

[0054] The battery 11 includes at least one battery cell BC. In Figure 1 it is shown by way of illustration a battery 11 including a plurality of battery cells BC1 to BC N connected in series (N is a natural number of 2 or more). The plurality of battery cells BC1 to BC N may be provided with the same electrochemical specifications. Hereinafter, in the common description of the plurality of battery cells BC1 to BC N the battery cell is attached with the symbol "BC". The charger 3 can perform charge / discharge cycles required for diagnosing the degradation state of the battery cell BC by cooperating with the inverter 30 having a discharge function.

[0055] The battery cell BC is to be diagnosed by the battery diagnostic device 100. The battery cell BC is not limited to a specific type and may include any electrochemical device that can be repeatedly charged and discharged. Preferably, the battery cell BC may be a lithium iron phosphate battery cell having a voltage plateau characteristic. The voltage plateau characteristic means a characteristic in which the change in voltage is maintained less than a predetermined threshold within at least one capacity range (or SOC range). The lithium iron phosphate battery cell may also be referred to as a "LiFePO4 battery cell", an "LFP battery cell", or an "LFP cell". Hereinafter, it is assumed that the battery cell BC is an LFP battery cell including LFP and graphite as the positive electrode material and the negative electrode material, respectively.

[0056] The relay 20 is serially electrically connected to the battery 11 through a power path connecting the battery 11 and the inverter 30. Figure 1 The relay 20 shown is connected between the positive terminal of the battery 11 and the charge / discharge terminal P+. The relay 20 controls on / off in response to a switching signal from the battery diagnostic device 100. The relay 20 may be a mechanical contactor that is turned on or off by the magnetic force of a coil, or may be a semiconductor switch such as a metal oxide semiconductor field effect transistor (MOSFET).

[0057] The inverter 30 is configured to convert a direct current from the battery 11 included in the battery pack 10 into an alternating current in response to a command from the battery diagnostic device 100 or the system controller 2. The motor 40 operates using the alternating current from the inverter 30. The motor 40 may include, for example, a three-phase AC motor. Components in the electric vehicle 1 that are supplied with discharge power from the battery 11 (including the inverter 30 and the motor 40) may be collectively referred to as electrical loads.

[0058] The battery diagnostic device 100 can be implemented as a cloud server disposed at a position remote from the battery pack 10. The battery diagnostic device 100 includes a control circuit 130. The battery diagnostic device 100 may further include at least one of a sensing unit 110 or a communication circuit 150. The "data acquisition unit" described in the appended claims may refer to the sensing unit 110 or the communication circuit 150 or both.

[0059] The sensing unit 110 includes a voltage sensor 111. The sensing unit may further include a current sensor 112.

[0060] The voltage sensor 111 is connected to the positive and negative terminals of the battery cell BC and is configured to detect the voltage across the battery cell BC (referred to as "full cell voltage") and generate a voltage signal indicative of the detected value of the voltage. The voltage sensor 111 may include one of known voltage detection devices such as a voltage measurement IC or a combination thereof.

[0061] The current sensor 112 is serially connected to the battery 11 through the current path between the battery 11 and the inverter 30. The current sensor 112 is configured to detect the current flowing through the battery 11 (referred to as "charge / discharge current") and generate a current signal indicative of the detected value of the current. Since multiple battery cells BC1 - BC N are connected in series, the current flowing in the battery 11 is the same as the current flowing in the battery cell BC. The current sensor 112 may include one of known current detection devices such as a shunt resistor or a Hall effect device or a combination thereof.

[0062] The communication circuit 150 is configured to support wired or wireless communication between the control circuit 130 and the system controller 2. The wired communication may be, for example, Controller Area Network (CAN) communication, while the wireless communication may be, for example, Zigbee or Bluetooth communication. The communication protocol is not limited to a specific type and may include protocols that support wired / wireless communication between the control circuit 130 and the system controller 2. The communication circuit 150 may include output devices (e.g., a display, a speaker) to provide the information received from the control circuit 130 and / or the system controller 2 in a format recognizable by the user (driver).

[0063] The control circuit 130 is operably coupled to the relay 20, the voltage sensor 111, and the communication circuit 150. "Operably coupled" means directly / indirectly connected to enable signal transmission and reception in one or both directions.

[0064] The control circuit 130 can collect a voltage signal from the voltage sensor 111 and a current signal from the current sensor 112. In this specification, the detection signal as used herein can refer only to the voltage signal, or can refer to both the voltage signal and the current signal. That is, the control circuit 130 can convert and record each analog signal collected from the sensors 111, 112 into a digital value by using the analog-to-digital converter (ADC) equipped therein. Alternatively, the voltage sensor 111 and the current sensor 112 can include an ADC therein and send the digital value to the control circuit 130.

[0065] The control circuit 130 can also be referred to as a "battery controller" and can be implemented in hardware by using at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a microprocessor, or an electrical unit for performing other functions.

[0066] The memory 131 can include at least one type of storage medium such as a flash memory type, a hard disk type, a solid state disk (SSD) type, a silicon disk drive (SDD) type, a multimedia card micro type, a random access memory (RAM), a static random access memory (SRAM), a read only memory (ROM), an electrically erasable programmable read only memory (EEPROM), or a programmable read only memory (PROM). The memory 131 can store data and programs required for the calculation operations performed by the control circuit 130. The memory 131 can store data indicating the results of the calculation operations performed by the control circuit 130. The memory 131 can store a data set and software for diagnosing the degradation state of the battery cell BC. The memory 131 can be integrated in the control circuit 130.

[0067] When the relay 20 is turned on during the operation of the electrical loads 30, 40 and / or the charger 3, the battery 11 is in the charging mode or the discharging mode. When the relay 20 is turned off while the battery 11 is being used in the charging mode or the discharging mode, the battery 11 is changed to the rest mode.

[0068] The control circuit 130 can turn on the relay 20 in response to a key-on signal. The control circuit 130 can turn off the relay 20 in response to a key-off signal. The key-on signal is a signal requesting a change from rest to charging or discharging. The key-off signal is a signal requesting a change from charging or discharging to rest. Alternatively, the system controller 2 can be responsible for the on and off control of the relay 20 instead of the control circuit 130.

[0069] In this specification, the time series data of a parameter indicates the time-related change history of the parameter. Additionally, a profile (or curve) indicating the correspondence between two parameters obtained at the same timing for a time period can be a polynomial equation obtained by mapping the time series data of the two parameters to be represented in the form of a 2D curve graph or by applying a predetermined curve fitting logic to a set of the two mapped time series data. Here, the degree of the highest order term of the polynomial equation can be preset.

[0070] Figure 2 is a curve graph showing an example of the Q-V profile of a battery cell, Figure 3 showing from Figure 2 an example of the normalized Q-V profile obtained from the Q-V profile, and Figure 4 showing an example of the Q-dV / dQ profile associated with the normalized Q-V profile shown in FIG. 3.

[0071] Figure 2 The curve graph 200 shown in [reference] is a Q-V profile indicating the correspondence between the capacity and voltage of the battery cell BC according to the capacity-voltage relationship data described below. In the curve graph 200, the vertical axis indicates the voltage of the battery cell BC, and the horizontal axis indicates the capacity (unit: mAh).

[0072] The Q-V profile 200 can also be referred to as a "capacity-voltage profile", a "capacity-voltage curve", or a "full cell profile". As described above, the battery cell BC has a voltage plateau characteristic, and the Q-V profile 200 shows that the voltage is maintained almost uniformly within the capacity range of approximately 20 mAh to 40 mAh.

[0073] Assume that the Q-V profile 200 is obtained through the charge cycle of the battery cell BC. In the charge cycle, a constant power or a constant current can be used.

[0074] In the constant power charge cycle, as the voltage of the battery increases, the charging current gradually decreases. Therefore, basically, not only the voltage time series data indicating the time-related change history of the voltage of the battery but also the current time series data indicating the time-related change history of the current flowing through the battery are required.

[0075] During a constant current charging cycle, a charging current having a predetermined current rate is controlled to flow through the battery cell BC. Accordingly, it can be assumed that the capacity at a specific time is equal to a value obtained by multiplying the elapsed time from the start time of the constant current charging cycle to the specific time (i.e., the time difference between the start time and the specific time) by the predetermined current rate. Even during the constant current charging cycle, the actual charging current may temporarily be less than or greater than the expected charging current. Thus, the control circuit 130 can calculate the capacity during charging or discharging in real time by periodically and repeatedly accumulating current measurement values obtained by directly measuring the current flowing through the battery cell BC using the current sensor 112 to generate current time series data.

[0076] The charging cycle can continue until the voltage of the battery cell BC changes at least within a predetermined voltage range. The Q-V profile 200 indicates the correspondence between the capacity and the voltage of the battery cell BC obtained during a period until the voltage of the battery cell BC reaches the upper voltage limit from the lower voltage limit of the predetermined voltage range through the constant current charging cycle.

[0077] Figure 2 The Q-V profile 200 shown in shows that the voltage of the battery cell BC rises from 2.6 V (lower voltage limit) to 3.6 V (upper voltage limit), while the capacity of the battery cell BC changes from 0 mAh to 52 mAh. Here, the range between 0 mAh and 52 mAh can be the entire capacity range of the Q-V profile 200, and this corresponds to the predetermined voltage range.

[0078] Correspondingly, the entire capacity range corresponding at least to the predetermined voltage range may change depending on the deterioration state of the battery cell BC. Additionally, even if two different battery cells BC have the same deterioration state, the capacity ranges of the two battery cells BC may be different due to process variations in manufacturing. To improve the simplicity and sufficiency of data processing required for diagnosing the deterioration state of the battery cell BC and to ensure the accuracy of the diagnosis result, it is necessary to apply a standardization process across the entire capacity range.

[0079] Figure 3 The graph 300 shown in is an example of a standardized Q-V profile obtained by applying a standardization process to the Q-V profile 200. In the graph 300, the vertical axis indicates the voltage of the battery cell BC in the same manner as Figure 2 and the horizontal axis indicates the standardized capacity (unit: %). The standardized capacity can be a term of a concept equivalent to the state of charge (SOC).

[0080] When the voltage and capacity according to the Q-V profile 200 have a mathematical relationship according to Equation 1 below, the voltage and the standardized capacity according to the Q-V profile 300 have a mathematical relationship according to Equation 2 below.

[0081] <Formula 1>

[0082]

[0083] <Formula 2>

[0084]

[0085] In Formula 1, Q B represents any capacity value within the entire capacity range, and V B represents the voltage value of Q mapped to the Q-V profile 200. In Formula 2, Q B represents the normalized capacity value corresponding to Q B_normal , and Q B represents the size of the entire capacity range (i.e., the capacity upper limit of the entire capacity range). For reference, total shows the result of normalizing each data point of the entire capacity range of Figure 3 in percentage (range between 0% and 100%), but this should be understood as an example. For example, it can be normalized to a different range between 0 and 1 instead of the range between 0% and 100%. Figure 2 The graph 400 shown in

[0086] Figure 4 is an example of a Q-dV / dQ profile. The Q-dV / dQ profile 400 can also be referred to as the "capacity-differential voltage profile" or the "capacity-differential voltage curve".

[0087] The control circuit 130 differentiates the voltage of the normalized Q-V profile 300 with respect to the normalized capacity to generate the Q-dV / dQ profile 400. Specifically, the control circuit 130 can determine the ratio [%] of the differential voltage dV / dQ or the change dV of the voltage V to the change dQ of the normalized capacity Q, and record the Q-dV / dQ profile 400 as relationship data indicating the correspondence between the normalized capacity Q and the differential voltage dV / dQ in the memory.

[0088] The control circuit 130 can set a cut-off reference point located in a predetermined reference capacity range according to the Q-dV / dQ profile 400. The reference capacity range can partially overlap with the capacity range where the voltage platform characteristics of the battery cell BC are found.

[0089] Specifically, the control circuit 130 can identify the local maximum point P MAX having the maximum differential voltage in the reference capacity range from the Q-dV / dQ profile 400. Subsequently, the control circuit 130 can identify (detect) from the Q-dV / dQ profile 400 the one located at a position higher than the local maximum point P MAXCut-off reference point P on the higher capacity side cut-off The cut-off reference point P cut-off may be a local minimum point having a capacity value Q in the reference capacity range cut-off .

[0090] When there are two or more local minimum points in the reference capacity range, the local minimum point having the largest capacity difference from the local maximum point P MAX may be identified as the cut-off reference point P cut-off . The cut-off reference point P cut-off may be the last local minimum point in the Q-dV / dQ profile 400 derived from the voltage characteristics of the negative electrode material of the battery cell BC. That is, the higher capacity side than the cut-off reference point P cut-off may be a capacity range in which the voltage characteristics of the positive electrode material of the battery cell BC dominate over the voltage characteristics of the negative electrode material. Therefore, those skilled in the art will readily understand that when only analyzing the higher capacity side portion of the standardized Q-V profile 300, the degradation state of the positive electrode of the battery cell BC can be accurately estimated.

[0091] The present inventors have confirmed through multiple experiments the fact that the voltage characteristics of the negative electrode material are reflected to a relatively very small extent on the higher capacity side portion compared to other portions of the standardized Q-V profile 300 than the cut-off reference point P cut-off . Therefore, the present inventors have recognized that among many different degradation parameters associated with the degradation state of the battery cell BC, by analyzing the higher capacity side portion of the standardized Q-V profile 300, the parameter for accurately diagnosing the degradation of the positive electrode can be obtained. In this specification, when the standardized Q-V profile 300 is divided into a lower capacity side portion and a higher capacity side portion based on the cut-off reference point P Figure 3 as shown in cut-off , the higher capacity side portion of the standardized Q-V profile 300 may be referred to as the "Q-V profile of interest" (see Figure 5 500 in Figure 4 ). As shown in

[0092] Figure 5 , a range between 50% and 99% is set as the reference capacity range. Figure 4 FIG. Figure 6 is a graph showing an example of the Q-V profile of interest extracted from the standardized Q-V profile of Figure 5 , and

[0093] FIG. Figure 5, the Q-V profile 500 of interest is an enlarged form of a portion of the normalized Q-V profile 300 corresponding to a range of capacities of interest (e.g., 92% to 99%), where the range of capacities of interest uses the capacity value (e.g., 92%) of the cut-off reference point P cut-off and the upper capacity limit of the reference capacity range (e.g., 99%) as the lower and upper capacity limits, respectively.

[0094] Correspondingly, even when the state of degradation of the positive electrode of the battery cell BC is the same, when other degradation factors of the battery cell BC (such as the state of degradation of the negative electrode or the available lithium amount) are different, the starting point, ending point, and / or shape (e.g., curvature) of the Q-V profile 500 of interest extracted from the Q-V profile 500 of interest may change. Therefore, in a manner similar to the normalization process applied to the Q-V profile 200, a normalization process needs to be applied to the Q-V profile 500 of interest.

[0095] Reference Figure 6 shows the corrected Q-V profile 600 of interest obtained through the normalization process (profile adjustment process) performed on the Q-V profile 500 of interest.

[0096] Specifically, the control circuit 130 can generate the corrected Q-V profile 600 of interest by performing at least one of shifting or scaling on the Q-V profile 500 of interest so that the starting point P S and the ending point P E of the Q-V profile 500 of interest match a predetermined first reference point P R1 and a predetermined second reference point P R2 , respectively. The starting point P S of the Q-V profile 500 of interest can be the point with the minimum capacity value of the Q-V profile 500 of interest. The ending point P E of the Q-V profile 500 of interest can be the point with the maximum capacity value of the Q-V profile 500 of interest.

[0097] The capacitance value of the first reference point P R1 is less than the capacitance value of the starting point P S , and the voltage value of the first reference point P R1 is less than the voltage value of the starting point P S . In addition, the capacitance value of the second reference point P R2 is greater than the capacitance value of the ending point P E , and the voltage value of the second reference point P R2 is greater than the voltage value of the ending point P E .

[0098] The control unit 130 may perform a first operation of shifting the Q-V profile 500 of interest along at least one of the capacity axis or the voltage axis, and a second operation of scaling the Q-V profile 500 of interest along at least one of the capacity axis or the voltage axis, so that the starting point P S matches the first reference point P R1 or makes the ending point P E match the second reference point P R2 . The first operation may include at least one of horizontal movement (moving left or right with respect to the horizontal axis) or vertical movement (moving up or down with respect to the vertical axis). The second operation may include at least one of reduction or enlargement based on at least one of the horizontal axis or the vertical axis.

[0099] Assume that the 2D coordinates of the starting point P S , the ending point P E , the first reference point P R1 and the second reference point P R2 are (Q S , V S ), (Q E , V E ), (Q R1 , V R1 ), (Q R2 , V R2 ), respectively. In Figure 6 , the 2D coordinates (Q R1 , V R1 ) of the first reference point P R1 are (90%, 0V), and the 2D coordinates (Q R2 , V R2 ) of the second reference point P R2 are (100%, 1V).

[0100] The control circuit 130 may shift the Q-V profile 500 of interest to the lower capacity side by Q S -Q R1 , and shift it to the lower voltage side by V S -V R1 . Thus, the starting point P S matches the first reference point P R1 , and now it is necessary to make the ending point P E match the second reference point P R2 . Therefore, the control circuit 130 may scale the Q-V profile 500 of interest along the capacity axis at a ratio of (Q R2 -Q R1 ) / (Q E -Q S ), and scale it along the voltage axis at a ratio of (V R2 -V R1 ) / (VE -V S The Q-V profile 500 of interest is scaled by the ratio of ) to generate the corrected Q-V profile 600 of interest. Thus, the operation of generating the corrected Q-V profile 600 of interest based on the Q-V profile 500 of interest is completed. That is to say, the corrected Q-V profile 600 of interest can be the result of projecting the Q-V profile 500 of interest onto the standardized voltage range between 0 V and 1 V and the standardized capacity range between 90% and 100%.

[0101] When the voltage and standardized capacity of the Q-V profile 500 of interest have a mathematical relationship according to Equation 3 below, the standardized voltage and standardized capacity of the corrected Q-V profile 600 of interest have mathematical relationships according to Equation 4-1 and Equation 4-2 below.

[0102] <Equation 3>

[0103]

[0104] <Equation 4-1>

[0105]

[0106] <Equation 4-2>

[0107]

[0108] In Equation 3, Q B_normal represents the standardized capacity value of any point in the Q-V profile 500 of interest, and V B represents the voltage value mapped to Q B_normal in the Q-V profile 500 of interest.

[0109] In Equation 4-1 and Equation 4-2, Q B_normal_2 represents the standardized capacity value of the corrected Q-V profile 600 of interest corresponding to Q B_normal . For reference, Figure 6 shows the result of standardizing each data point of the entire voltage range of Figure 5 based on the range between 0 V and 1 V, but this should be understood as an example.

[0110] The control circuit 130 can determine the profile fitting factor of the battery cell BC based on the corrected Q-V profile 600 of interest. Specifically, the control circuit 130 can determine the polynomial equation of the corrected Q-V profile 600 of interest by applying a curve fitting algorithm to the corrected Q-V profile 600 of interest. Subsequently, the control circuit 130 can determine that the profile fitting factor is equal to the coefficient of the highest-degree term of the polynomial equation. The degree of the highest-degree term can be preset.

[0111] The control circuit 130 may determine a first degradation parameter associated with the degradation state of the battery cell BC by inputting the profile fitting factor as an input variable into the linear regression model. The first degradation parameter may indicate a capacity reduction ratio caused by degradation of the positive electrode of the battery cell. The capacity reduction ratio caused by degradation of the positive electrode may be referred to as a "positive electrode degradation level" or a "positive electrode degradation-induced capacity reduction ratio." hereinafter, reference will be made to Figures 7 to 11 Describe the linear regression model in more detail.

[0112] The present inventors created relational data that can be used to generate a linear regression model by combining a process of forcibly degrading a plurality of battery cells BC prepared for an experiment to different positive electrode degradation levels, a process of calculating a profile fitting factor for each of the forcibly degraded battery cells BC, a process of disassembling each of the forcibly degraded battery cells BC to manufacture positive electrode half cells, and a process of measuring and recording the available capacity of each positive electrode half cell in this order.

[0113] Figure 7 is a diagram referenced in exemplarily describing the relationship between different positive electrode degradation levels and the corrected QV profile of interest, Figures 8 to 10 The polynomial equation is fitted to Figure 7 The results for each of the three corrected QV profiles of interest shown in , and Figure 11 is a diagram referred to in exemplarily describing the relationship between different positive electrode degradation levels and profile fitting factors.

[0114] Figure 7 A graph is shown in which the corrected QV profile of interest changes as the positive electrode degradation level increases. The positive electrode degradation level may refer to a capacity reduction ratio derived from positive electrode degradation.

[0115] refer to Figure 7 , curve 710 indicates the corrected QV profile of interest obtained at a positive electrode degradation level of 0% - that is, when the positive electrode is new - curve 720 indicates the corrected QV profile of interest obtained at a positive electrode degradation level of 1.75% through 200 charge / discharge cycles, and curve 730 indicates the corrected QV profile of interest obtained at a positive electrode degradation level of 9.40% through 600 charge / discharge cycles.

[0116] That is, as the cathode degradation level becomes higher, the corrected QV profile of interest gradually changes to be closer to the first reference point P R1 Connected to the second reference point P R2 The shape of the straight line, and therefore the profile fit factor, is reduced, as from Figure 7 It can be seen in.

[0117] According to Figures 8 to 10 , each of the curves 710, 720, and 730 is shown as a polynomial equation of degree 3 for the highest-degree term. Additionally, the coefficients of the highest-degree terms of the polynomial equations of the curves 710, 720, and 730 are 0.0056, 0.0036, and 0.0004, respectively, showing that as the positive electrode degradation level increases, the coefficient of the highest-degree term of the polynomial equation decreases. The pattern of the polynomial equation depends greatly on the coefficient of the highest-degree term among the terms of the polynomial equation.

[0118] Referring to Figure 11 , the linear regression model 1100 can be prepared in advance as a relational function of the correspondence between the profile fitting factor (the coefficient of the highest-degree term) and the positive electrode degradation state. The point 1110 is associated with the curve 710 of Figure 7 , the point 1120 is associated with the curve 720 of Figure 7 , and the point 1130 is associated with the curve 730 of Figure 7 . Although not fully shown, in addition to the points 1110, 1120, and 1130, the inventors also obtained additional points as the above experimental results and then used them to obtain the linear regression model 1100 through linear regression analysis. The linear regression model 1100 can be pre-stored in the memory 131. The following Formula 5 is an example of the linear regression model 1100.

[0119] <Formula 5>

[0120]

[0121] In Formula 5, A and B are two coefficients respectively indicating the slope and the y-axis intercept of the straight line according to the linear regression model 1100. x represents the profile fitting factor as the input variable, and y represents the positive electrode degradation level as the output variable. A and B can vary depending on the type and composition ratio of each of the positive electrode material and the negative electrode material. Therefore, A and B can be appropriately adjusted according to the type and manufacturing information (e.g., the type and composition ratio of each of the positive electrode material and the negative electrode material) of the battery cell BC provided for diagnosis. For example, Figure 11 the A and B of the linear regression model 1100 shown in

[0122] are -1898 and 9.88, respectively.

[0123] Table 1 below summarizes the relationships among the number of cycles (cycle count) of the above-described constant power charge cycle, the total capacity reduction ratio, the profile fitting factor, the first degradation parameter (capacity reduction ratio derived from cathode degradation), and the second degradation parameter (capacity reduction ratio derived from available lithium loss). Here, available lithium may refer to lithium ions that can participate in the charge / discharge reaction of the battery cell BC.

[0124] [Table 1]

[0125]

[0126] From Table 1, it can be seen that as the cycle count increases, each of the total capacity reduction ratio, the profile fitting factor, the capacity reduction ratio derived from cathode degradation, and the capacity reduction ratio derived from available lithium loss increases together. For reference, the cycle count can be counted each time a charge (or discharge) cycle using constant power (or constant current) is completed.

[0127] The total capacity reduction ratio can be the ratio of the reduction in the fully charged capacity due to degradation to the fully charged capacity when the battery cell BC is new. When assuming that the fully charged capacity of a new battery = P, the fully charged capacity of a degraded battery = U, and the reduction in the fully charged capacity = W (W = P - U), the total capacity reduction ratio = (W / P) × 100%.

[0128] The fact recognized by the present inventors is that the sum of the capacity reduction ratio derived from cathode degradation and the capacity reduction ratio derived from available lithium loss is substantially equal to the total capacity reduction ratio. Therefore, the control circuit 130 can determine the capacity reduction ratio derived from available lithium loss as the second degradation parameter by subtracting the cathode degradation level determined by the above formula 5 from the total capacity reduction ratio.

[0129] Figure 12 is a flowchart schematically showing a battery diagnosis method according to an embodiment of the present disclosure. According to Figure 12 the method includes steps S1210 to S1260. According to Figure 12 the method further includes step S1270.

[0130] Referring to Figures 1 to 12 , in step S1210, the control circuit 130 acquires the capacity-voltage relationship data of the battery cell BC using the data acquisition unit. In this specification, the acquisition of data or information may refer to generation by software processing, input by a user or an input device, and / or reception through a communication channel.

[0131] For example, when the data acquisition unit includes the sensing unit 110, the control circuit 130 may generate a voltage time series and a capacity time series based on the detection signal generated by the sensing unit 110. The capacity-voltage relationship data may include the voltage time series and the capacity time series. The data points of the voltage time series and the data points of the current time series may be mapped into a one-to-one relationship.

[0132] The voltage time series may indicate the time-related change history of the voltage of the battery cell BC while charging (or discharging) the battery cell BC with a constant power (or constant current) within a predetermined voltage range. The current time series may indicate the time-related change history of the current flowing through the battery cell BC during the same time period as the time period for acquiring the voltage time series.

[0133] As another example, when the data acquisition unit includes the communication circuit 150, the control circuit 130 may receive the capacity-voltage relationship data from an external device by using the communication circuit 150.

[0134] In step S1220, the control circuit 130 generates a Q-V profile 200, a normalized Q-V profile 300, and a Q-dV / dQ profile 400 of the battery cell BC based on the capacity-voltage relationship data.

[0135] In step S1230, the control circuit 130 identifies (detects) a cut-off reference point P from the Q-dV / dQ profile 400 cut-off .

[0136] In step S1240, the control circuit 130 extracts an interested Q-V profile 500, and the interested Q-V profile 500 is the higher-capacity side portion of the normalized Q-V profile 300 based on the capacity value Q of the cut-off reference point P cut-off of cut-off the cut-off reference point P.

[0137] In step S1250, the control circuit 130 determines a profile fitting factor associated with the interested Q-V profile 500.

[0138] In step S1260, the control circuit 130 determines at least one degradation parameter associated with the degradation state of the battery cell BC based on the profile fitting factor. Therefore, at least one of the first degradation parameter or the second degradation parameter can be determined.

[0139] In step S1270, the control circuit 130 may determine at least one protection parameter of the battery cell BC based on at least one degradation parameter determined in step S1260. For example, at least one of the maximum charging voltage, the minimum discharging voltage, the maximum allowable current, or the maximum allowable power may be determined as the protection parameter.

[0140] When (i) the voltage of the battery cell BC is equal to or greater than the maximum charging voltage or equal to or less than the minimum discharging voltage, (ii) the current flowing through the battery cell BC is equal to or greater than the maximum allowable current, and / or (iii) the charging or discharging power of the battery cell BC is equal to or greater than the maximum allowable power, the control circuit 130 may change the relay 20 to the open state or send an operation stop request to the inverter 30 and / or the charger 3.

[0141] Figure 13 is a flowchart of a subroutine that may be included in Figure 12 step S1220.

[0142] In step S1310, the control circuit 130 generates a Q-V profile 200 based on the capacity-voltage relationship data obtained in step S1210.

[0143] In step S1320, the control circuit 130 normalizes the Q-V profile 200 over the entire capacity range of the Q-V profile 200 to generate a normalized Q-V profile 300.

[0144] In step S1330, the control circuit 130 may differentiate the normalized Q-V profile 300 to generate a Q-dV / dQ profile 400 indicating the correspondence between the normalized capacity and the differential voltage of the battery cell BC.

[0145] Figure 14 is a flowchart of a subroutine that may be included in Figure 12 step S1230.

[0146] Referring to Figure 14 , in step S1410, the control circuit 130 identifies a local maximum point P having the maximum differential voltage in the reference capacitance range from the Q-dV / dQ profile 400 MAX .

[0147] In step S1420, the control circuit 130 identifies a local minimum point located on the higher capacity side than the local maximum point P as a cut-off reference point P MAX according to the Q-dV / dQ profile 400 cut-off .

[0148] Figure 15 is a flowchart of a subroutine that may be included in Figure 12 step S1250.

[0149] Referring to Figure 15, in step S1510, the control circuit 130 performs a cross-section adjustment operation on the Q-V cross-section 500 of interest to make the starting point P S and the end point P E of the Q-V cross-section 500 of interest match the predetermined first reference point P R1 and the predetermined second reference point P R2 respectively, to generate the corrected Q-V cross-section 600 of interest.

[0150] In step S1520, the control circuit 130 applies a curve fitting algorithm to the corrected Q-V cross-section 600 of interest to obtain the polynomial equation of the corrected Q-V cross-section 600 of interest.

[0151] In step S1530, the control circuit 130 determines that the cross-section fitting factor is equal to the coefficient of the highest-degree term of the polynomial equation.

[0152] In step S1260, the control circuit 130 can determine the first degradation parameter y associated with the degradation state of the battery cell BC (see Equation 3) by using the cross-section fitting factor determined in step S1530 as the input variable x of the linear regression model 1100. The linear regression model 1100 can be pre-prepared as a relationship function between the cross-section fitting factor and the cathode degradation state. Optionally, the control circuit 130 can also additionally determine the second degradation parameter by subtracting the first degradation parameter from the total capacity reduction ratio.

[0153] The embodiments of the present disclosure described above are not only implemented by devices and methods, but can also be implemented by a program that executes functions corresponding to the exemplary configurations of the present disclosure or a recording medium having the program recorded thereon, and those skilled in the art can easily implement such implementations based on the disclosure content of the embodiments described above.

[0154] Although the present disclosure has been described above with respect to a limited number of embodiments and drawings, the present disclosure is not limited thereto, and it is obvious to those skilled in the art that various modifications and changes can be made within the scope of the technical aspects of the present disclosure content and the appended claims and their equivalents.

[0155] In addition, those skilled in the art can make many substitutions, modifications, and changes to the present disclosure described above without departing from the technical aspects of the present disclosure. The present disclosure is not limited by the above embodiments and drawings, and some or all of the embodiments can be selectively combined to allow various modifications.

Claims

1. A battery diagnostic device, comprising: a data acquisition unit configured to acquire capacity-voltage relationship data of a battery cell; and a control circuit configured to generate a Q-V profile indicating the correspondence between the capacity and voltage of the battery cell, a normalized Q-V profile indicating the correspondence between the normalized capacity of the battery cell and the voltage, and a Q-dV / dQ profile indicating the correspondence between the normalized capacity of the battery cell and the differential voltage based on the capacity-voltage relationship data, wherein the control circuit is configured to: identify a cut-off reference point located in a reference capacity range from the Q-dV / dQ profile, determine a profile fitting factor associated with an interested Q-V profile, wherein the interested Q-V profile is a higher-capacity-side portion of the normalized Q-V profile based on the capacity value of the cut-off reference point, and determine at least one degradation parameter of the battery cell based on the profile fitting factor.

2. The battery diagnosis device according to claim 1, wherein, The control circuit is configured to: generate the normalized Q-V profile by normalizing the Q-V profile over the entire capacity range of the Q-V profile, and generate the Q-dV / dQ profile by differentiating the normalized Q-V profile.

3. The battery diagnosis device according to claim 1, wherein, The control circuit is configured to identify the local minimum point in the reference capacity range as the cut-off reference point according to the Q-dV / dQ profile.

4. The battery diagnosis device according to claim 1, wherein, The control circuit is configured to: generate a corrected interested Q-V profile by performing a profile adjustment process for matching the start point and end point of the interested Q-V profile to a first reference point and a second reference point respectively, obtain a polynomial equation of the corrected interested Q-V profile by applying a curve fitting algorithm to the corrected interested Q-V profile, and determine that the profile fitting factor is equal to the coefficient of the highest-degree term of the polynomial equation.

5. The battery diagnosis device according to claim 1, wherein, The control circuit is configured to determine a first degradation parameter by using the profile fitting factor as an input variable of a linear regression model, and wherein the linear regression model is pre-prepared as a relationship function between the profile fitting factor and the positive electrode degradation state.

6. The battery diagnostic device according to claim 5, wherein, The first degradation parameter indicates the capacity reduction ratio caused by the degradation of the positive electrode of the battery cell.

7. The battery diagnosis device according to claim 5, wherein, The control circuit is configured to determine a second degradation parameter based on the total capacity reduction ratio of the battery cell and the first degradation parameter, and wherein the second degradation parameter indicates the capacity reduction ratio caused by the loss of available lithium in the battery cell.

8. The battery diagnosis device according to claim 1, wherein, The capacity-voltage relationship data indicates the capacity change history and voltage change history of the battery while the battery cell is being charged or discharged.

9. A battery pack, comprising the battery diagnostic device according to any one of claims 1 to 8.

10. An electric vehicle, comprising the battery pack according to claim 9.

11. A battery diagnostic method, comprising: acquiring capacity-voltage relationship data of a battery cell; Generate a Q-V profile indicating the correspondence between the capacity and voltage of the battery cell, a normalized Q-V profile indicating the correspondence between the normalized capacity of the battery cell and the voltage, and a Q-dV / dQ profile indicating the correspondence between the normalized capacity of the battery cell and the differential voltage based on the capacity-voltage relationship data; Identify a cut-off reference point located within a reference capacity range from the Q-dV / dQ profile; Determine a profile fitting factor associated with the Q-V profile of interest, where the Q-V profile of interest is the higher-capacity side portion of the normalized Q-V profile based on the capacity value of the cut-off reference point; And Determine at least one degradation parameter of the battery cell based on the profile fitting factor.

12. The battery diagnosis method according to claim 11, wherein, Generating the Q-dV / dQ profile includes: Generating the normalized Q-V profile by normalizing the Q-V profile over the entire capacity range of the Q-V profile; and Generating the Q-dV / dQ profile by differentiating the normalized Q-V profile.

13. The battery diagnosis method according to claim 11, wherein, Determining the profile fitting factor of the battery cell includes: Generating a corrected Q-V profile of interest by performing a profile adjustment process for respectively matching the start point and end point of the Q-V profile of interest to a predetermined first reference point and a predetermined second reference point; Obtaining a polynomial equation of the corrected Q-V profile of interest by applying a curve fitting algorithm to the corrected Q-V profile of interest; and Determining that the profile fitting factor is equal to the coefficient of the highest-degree term of the polynomial equation.

14. The battery diagnosis method according to claim 13, wherein, Determining the at least one degradation parameter of the battery cell includes determining a first degradation parameter by using the profile fitting factor as an input variable of a linear regression model, and where the linear regression model is pre-prepared as a relationship function between the profile fitting factor and the state of positive electrode degradation.

15. The battery diagnosis method according to claim 14, wherein, Determining the at least one degradation parameter of the battery cell further includes: Determining a second degradation parameter based on the total capacity reduction ratio of the battery cell and the first degradation parameter, and where the second degradation parameter indicates the capacity reduction ratio caused by the loss of available lithium in the battery cell.

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