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

Abstract

A battery diagnostic device, a battery pack, an electric vehicle, and a battery diagnostic method are provided. The battery diagnostic device includes a sensing unit that acquires capacity-voltage relationship data of battery cells, and a control circuit that generates a QV profile, a normalized QV profile, and a Q-dV / dQ profile based on the capacity-voltage relationship data. The control circuit determines the characteristic parameters of the QV profile of interest, which is the high-capacity side portion of the normalized QV profile, with reference to a cutoff reference point detected from the Q-dV / dQ profile. The control circuit determines at least one degradation parameter based on the profile characteristic parameters.

Description

Technical Field

[0001] The present invention relates to a technique for diagnosing the degradation state of a battery cell.

[0002] This application claims priority based on Korean Patent Application No. 10-2023-0117255 filed on September 4, 2023, and all the contents disclosed in the specification and drawings of the application are incorporated into this application.

Background Art

[0003] In recent years, with the rapid growth in the demand for portable electronic products such as notebook computers, video cameras, and mobile phones, and the full-scale development of electric vehicles, energy storage batteries, robots, artificial satellites, etc., research on high-performance rechargeable batteries has been actively conducted.

[0004] Currently, commercially available batteries include nickel-cadmium batteries, nickel-metal hydride batteries, nickel-zinc batteries, lithium batteries, etc. Among them, lithium batteries are in the spotlight because they can be charged and discharged freely with almost no memory effect compared to nickel-based batteries, have a very low self-discharge rate, and a high energy density.

[0005] There are various techniques for monitoring the degradation of battery cells. In particular, differential voltage analysis (also referred to as "DVA") is based on time-series data of at least one battery parameter (e.g., voltage, current) observable from the outside of the battery cell.

[0006] In DVA (Dynamic Voltage Analysis), peaks appearing in the differential voltage curve (also called the "Q-dV / dQ profile") are considered as the main factors. However, some types of battery cells have a voltage flatness characteristic in which the rate of voltage change is maintained at nearly zero during charging or discharging. In the capacity range in which the voltage flatness characteristic appears, the differential voltage is also close to zero, making it difficult to detect peaks from the Q-dV / dQ profile. Therefore, there is a need for a method that can accurately and easily diagnose the degradation state of a battery cell without having to extract peak information indicating the degradation state from the Q-dV / dQ profile. [Overview of the Initiative] [Problems that the invention aims to solve]

[0007] The present invention was devised to solve the above-mentioned problems, and aims to provide a battery diagnostic device and a battery diagnostic method for precisely estimating at least one degradation parameter related to the degradation state of a battery cell having voltage flat characteristics without disassembling the battery cell.

[0008] Other objects and advantages of the present invention can be understood from the following description and more clearly from the embodiments of the present invention. Furthermore, the objects and advantages of the present invention can be realized by the means and combinations thereof shown in the claims. [Means for solving the problem]

[0009] A battery diagnostic device according to one aspect of the present invention includes a data acquisition unit that acquires capacity-voltage relationship data of a battery cell, and a control circuit configured to generate, based on the capacity-voltage relationship data, a QV profile showing the correspondence between the capacity and voltage of the battery cell, a normalized QV profile showing the correspondence between the normalized capacity and voltage of the battery cell, and a Q-dV / dQ profile showing the correspondence between the normalized capacity and differential voltage of the battery cell. The control circuit identifies a cutoff reference point located within a reference capacity range from the Q-dV / dQ profile. The control circuit determines profile characteristic parameters related to the QV profile of interest, which is the high-capacity portion of the normalized QV profile, with respect to 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 characteristic parameters.

[0010] The control circuit may normalize the QV profile based on the overall capacitance range of the QV profile to generate a normalized QV profile. The control circuit may be configured to differentiate the normalized QV profile to generate a Q-dV / dQ profile.

[0011] The control circuit may be configured to set the minimum point within the reference capacitance range as the cutoff reference point from the Q-dV / dQ profile.

[0012] The control circuit may be configured to generate a corrected QV profile by performing a profile adjustment process to match the start and end points of the QV profile of interest to a first reference point and a second reference point, respectively. The control circuit may be configured to determine the area of ​​the region of interest defined by the corrected QV profile of interest, the first reference point, and the second reference point as profile characteristic parameters.

[0013] The control circuit may be configured to determine the first degradation parameter using the determined area as an input variable to a linear regression model. The linear regression model may be pre-defined as a relationship function between the profile characteristic parameter and the positive electrode degradation state.

[0014] The first degradation parameter may indicate the rate of capacity reduction due to the degradation of the positive electrode of the battery cell.

[0015] The control circuit may determine a second degradation parameter based on the total capacity degradation rate of the battery cells and a first degradation parameter. The second degradation parameter may represent the capacity degradation rate due to the loss of available lithium in the battery cells.

[0016] Capacity-voltage related data may show the history of capacity and voltage changes of a battery cell during charging or discharging.

[0017] A battery pack according to another aspect of the present invention includes a battery diagnostic device.

[0018] An electric vehicle according to yet another aspect of the present invention includes a battery pack.

[0019] A battery diagnostic method according to yet another aspect of the present invention includes the steps of: acquiring capacity-voltage relationship data of a battery cell; generating a QV profile showing the correspondence between the capacity and voltage of the battery cell, a normalized QV profile showing the correspondence between the normalized capacity and voltage of the battery cell, and a Q-dV / dQ profile showing the correspondence between the normalized capacity and differential voltage of the battery cell, based on the capacity-voltage relationship data; identifying a cutoff reference point located within a reference capacity range from the Q-dV / dQ profile; determining profile characteristic parameters related to the QV profile of interest, which is the high-capacity portion of the normalized QV profile, based on the capacity value of the cutoff reference point; and determining at least one degradation parameter of the battery cell based on the profile characteristic parameters.

[0020] The steps for generating a Q-dV / dQ profile may include: normalizing the QV profile based on the overall capacity range of the QV profile to generate a normalized QV profile; and differentiating the normalized QV profile to generate a Q-dV / dQ profile.

[0021] The steps for determining the profile characteristic parameters of a battery cell may include: generating a corrected QV profile by performing a profile adjustment process to match the start and end points of the QV profile of interest to a first reference point and a second reference point, respectively; and determining the area of ​​the region of interest defined by the corrected QV profile of interest, the first reference point, and the second reference point as profile characteristic parameters.

[0022] The step of determining at least one degradation parameter of a battery cell may include the step of determining a first degradation parameter by inputting the determined area as an input variable into a linear regression model. The linear regression model may be pre-defined as a relationship function between profile characteristic parameters and the cathode degradation state.

[0023] The step of determining at least one degradation parameter of a battery cell may further include the step of determining a second degradation parameter based on the total capacity degradation rate of the battery cell and the first degradation parameter. The second degradation parameter may represent the capacity degradation rate due to the loss of available lithium of the battery cell. [Effects of the Invention]

[0024] According to one aspect of the present invention, at least one degradation parameter relating to the degradation state of a battery cell can be precisely estimated without disassembling the battery cell. In particular, the present invention has the advantage of being able to non-destructively diagnose the positive electrode degradation state of an LFP (Litium Iron Phosphate) battery cell having voltage flatness characteristics.

[0025] Furthermore, according to one aspect of the present invention, by extracting a portion of the battery cell's voltage curve (described later as the "QV profile") over a predetermined voltage range where the degradation characteristics of the positive electrode material overwhelmingly outweigh those of the negative electrode material (described later as the "QV profile of interest"), the positive electrode degradation state of the battery cell (for example, the capacity degradation rate due to positive electrode degradation) can be grasped more precisely.

[0026] Furthermore, according to one aspect of the present invention, the rate of capacity reduction due to lithium loss can be easily calculated from the total rate of capacity reduction of the battery cell and the rate of capacity reduction due to positive electrode degradation, using the relationship between the rate of total capacity reduction of the battery cell, the rate of capacity reduction due to positive electrode degradation, and the rate of capacity reduction due to lithium loss.

[0027] The effects of the present invention are not limited to those described above, and other effects of the present invention not mentioned herein will be clearly understood by those skilled in the art from the claims.

[0028] The drawings accompanying this specification illustrate preferred embodiments of the present invention and, together with the detailed description of the invention, are intended to facilitate a better understanding of the technical concept of the invention. Therefore, the present invention is not to be construed as being limited solely to what is shown in the drawings. [Brief explanation of the drawing]

[0029] [Figure 1] This diagram illustrates the configuration of an electric vehicle according to one embodiment of the present invention. [Figure 2] This graph shows an example of a battery cell's QV profile. [Figure 3] This is an example of a normalized QV profile obtained from the QV profile in Figure 2. [Figure 4] Figure 3 shows an example of a Q-dV / dQ profile related to the normalized QV profile. [Figure 5] This graph shows an example of a QV profile of interest extracted from the normalized QV profile in Figure 4. [Figure 6] Figure 5 shows an example of a corrected interest-based QV profile obtained from the interest-based QV profile. [Figure 7] This figure is provided to illustrate the relationship between different positive electrode degradation levels and the corrected QV profile of interest. [Figure 8] This figure is used to illustrate the relationship between different positive electrode degradation levels and the area of ​​the region of interest. [Figure 9] This is a flowchart illustrating a battery diagnostic method according to one embodiment of the present invention. [Figure 10] This flowchart illustrates the subroutines that may be included in step S920 of Figure 9. [Figure 11] This flowchart illustrates the subroutines that may be included in step S930 of Figure 9. [Figure 12] This flowchart illustrates the subroutines that may be included in step S950 of Figure 9. [Modes for carrying out the invention]

[0030] Preferred embodiments of the present invention will now be described in detail with reference to the attached drawings. Prior to this, terms and words used in this specification and in the claims shall not be interpreted in their general and dictionary sense, but in accordance with the principle that inventors can appropriately define the concepts of terms in order to best describe their invention, and shall be interpreted in the sense and concepts corresponding to the technical idea of ​​the present invention.

[0031] Therefore, the embodiments described herein and the configurations shown in the drawings represent only one of the most preferred embodiments of the present invention and do not represent the entire technical concept of the present invention. It should be understood that there are various equivalents and modifications that can substitute for them at the time of filing this application.

[0032] Terms that include ordinal numbers, such as "first," "second," etc., are used to distinguish one of several components from other components, and these terms do not limit the components themselves.

[0033] Throughout the specification, when a part of it "comprises" or "includes" a component, this does not exclude other components unless otherwise specified, but rather means that it may further include other components. Furthermore, terms such as <control circuit 130> in the specification mean a unit that processes at least one function or operation, which may be implemented in hardware, software, or a combination of hardware and software.

[0034] Furthermore, when a part of the specification is described as being "connected" to another part, this includes not only "direct connections" but also "indirect connections" mediated by other elements.

[0035] Figure 1 is a diagram illustrating the configuration of an electric vehicle according to one embodiment of the present invention.

[0036] Referring to Figure 1, the electric vehicle 1 includes a system controller 2, a battery pack 10, an inverter 30, and an electric motor 40. The charge and discharge terminals P+ and P- of the battery pack 10 can be electrically coupled to a charger 3 via a charging cable or the like. The charger 3 may be included in the electric vehicle 1 or provided at a charging station. The electric vehicle 1 is an example of a battery system, which is a higher-level system that includes the battery pack 10 as at least one of energy storage and energy supply. Therefore, the contents described later are applicable in common to battery systems, including the electric vehicle 1.

[0037] The system controller 2 (for example, an electronic control unit (ECU)) is configured to transmit a key-on signal to the battery diagnostic device 100 in response to the user switching the engine start button (not shown) on the electric vehicle 1 to the ON position. The system controller 2 is also configured to transmit a key-off signal to the battery diagnostic device 100 in response to the user switching the engine start button to the OFF position. The charger 3 communicates with the system controller 2 and can supply charging power selected from constant power, constant current, and constant voltage through the charge / discharge terminals P+ and P- of the battery pack 10.

[0038] The battery pack 10 includes a battery 11 and a relay 20. The battery pack 10 may further include a battery diagnostic device 100.

[0039] Battery 11 includes at least one battery cell BC. Figure 1 shows multiple battery cells BC1~BC connected in series to battery 11. N The diagram illustrates the inclusion of multiple battery cells BC1~BC (where N is a natural number greater than or equal to 2). N These may be configured to have the same electrochemical specifications. Below are multiple battery cells BC1 to BC N When explaining the common features of the battery cells, the reference designation "BC" will be used. The charger 3 can work in cooperation with the inverter 30, which has a discharge function, to perform the charge-discharge cycles necessary to diagnose the degradation state of the battery cells BC.

[0040] The battery cell BC is the subject of diagnosis by the battery diagnostic device 100. The type of battery cell BC is not particularly limited as long as it is an electrochemical element 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. A voltage plateau characteristic means that the rate of change of the voltage is maintained below a predetermined threshold over at least one capacity interval (or SOC (State of Charge) interval). A lithium iron phosphate battery cell may also be called a "LiFePO4 battery cell," an "LFP battery cell," or an "LFP cell." In the following, it is assumed that the battery cell BC is an LFP battery cell containing LFP and graphite as the positive electrode material and negative electrode material, respectively.

[0041] Relay 20 is electrically connected in series with battery 11 through a power path connecting battery 11 and inverter 30. Figure 1 illustrates that relay 20 is connected between the positive terminal and the charge / discharge terminal P+ of battery 11. Relay 20 is controlled on / off in response to a switching signal from battery diagnostic device 100. Relay 20 may be a mechanical contactor that is switched on / off by the magnetic force of a coil, or a semiconductor switch such as a MOSFET (Metal Oxide Semiconductor Field Effect Transistor).

[0042] The inverter 30 is configured to respond to commands from the battery diagnostic device 100 or the system controller 2 and convert the DC current from the battery 11 contained in the battery pack 10 into AC current. The electric motor 40 is driven using the AC power from the inverter 30. For example, a three-phase AC motor may be used as the electric motor 40. The components within the battery system that receive the discharge power from the battery 11, including the inverter 30 and the electric motor 40, may be referred to as an electrical load.

[0043] The battery diagnostic device 100 may be implemented in the form of a kind of cloud server located remotely 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 and a communication circuit 150. The term “data acquisition unit” as described in the claims of the present invention may refer to either one of the sensing unit 110 and the communication circuit 150, or to both.

[0044] The sensing unit 110 includes a voltage sensor 111. The sensing unit 110 may further include a current sensor 112.

[0045] 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 both ends of the battery cell BC (which may also be called the "full-cell voltage") and to generate a voltage signal indicating the detected voltage value. The voltage sensor 111 can be implemented using one or more combinations of known voltage detection elements such as a voltage measurement IC.

[0046] The current sensor 112 is connected in series with the battery 11 through a 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 (which may also be called the "charge / discharge current") and to generate a current signal indicating the detected value of the detected current. Multiple battery cells BC1~BC N Since they are connected in series, the current flowing through battery 11 is equal to the current flowing through battery cell BC. The current sensor 112 can be implemented using one or more combinations of known current sensing elements such as a shunt resistor or a Hall effect element.

[0047] The communication circuit 150 is configured to support wired or wireless communication between the control circuit 130 and the system controller 2. Wired communication may be, for example, CAN (Controller Area Network) communication, and wireless communication may be, for example, ZigBee® or Bluetooth® communication. Of course, the type of communication protocol is not particularly limited as long as it supports wired or wireless communication between the control circuit 130 and the system controller 2. The communication circuit 150 may include an output device (e.g., display, speaker) that provides information received from the control circuit 130 and / or the system controller 2 in a form that can be recognized by the user (driver).

[0048] The control circuit 130 is operably coupled to the relay 20, the voltage sensor 111, and the communication circuit 150. The operably coupled nature of the two components means that they are directly or indirectly connected to enable the transmission and reception of signals in one direction or bidirectionally.

[0049] The control circuit 130 can collect voltage signals from the voltage sensor 111 and current signals from the current sensor 112. In this specification, the term "detection signal" may refer to the voltage signal only, or it may be a general term referring to both the voltage signal and the current signal. That is, the control circuit 130 can use an internally provided ADC (Analog to Digital Converter) to convert and record the respective analog signals collected from the sensors (voltage sensor 111, current sensor 112) into digital values. Alternatively, the voltage sensor 111 and the current sensor 112 may each contain an internal ADC and transmit digital values ​​to the control circuit 130.

[0050] The control circuit 130 may be called a "battery controller" and may be implemented in hardware using at least one of the following: ASICs (application-specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), microprocessors, or other electrical units for performing functions.

[0051] Memory 131 may include at least one form of storage medium, such as flash memory, hard disk, SSD (Solid State Disk), SDD (Solid Disk Drive), multimedia microcard, RAM (Random Access Memory), SRAM (Static RAM), ROM (Read Only Memory), EEPROM (Electrically Erasable Programmable ROM), or PROM (Programmable ROM). Memory 131 can store data and programs required for the calculation operations of the control circuit 130. Memory 131 can store data indicating the results of the calculation operations of the control circuit 130. Memory 131 can store datasets and software used to diagnose the degradation state of battery cells BC. Memory 131 can be integrated into the control circuit 130.

[0052] When the relay 20 is turned on while the electrical load (inverter 30, electric motor 40) and / or charger 3 is operating, the battery 11 enters charging mode or discharging mode. When the relay 20 is turned off while the battery 11 is operating in charging mode or discharging mode, the battery 11 switches to rest mode.

[0053] 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 that requests a switch from standby to charging or discharging. The key-off signal is a signal that requests a switch from charging or discharging to standby. Alternatively, the on / off control of the relay 20 may be handled by the system controller 2 instead of the control circuit 130.

[0054] In this specification, time-series data of a parameter represents the history of its change over time. Furthermore, a profile (or curve) showing the correspondence between two parameters obtained at the same time intervals during the same period may be a mapping of the time-series data of the two parameters so that it can be represented in the form of a two-dimensional graph, or a polynomial equation obtained by applying a predetermined curve-fitting logic to the two mapped sets of time-series data. Here, the degree of the highest-order term in the polynomial may be predetermined.

[0055] Figure 2 is a graph showing an example of a battery cell QV profile, Figure 3 is an example of a normalized QV profile obtained from the QV profile in Figure 2, and Figure 4 is an example of a Q-dV / dQ profile related to the normalized QV profile shown in Figure 3.

[0056] Graph 200, shown in Figure 2, is a QV profile illustrating the correspondence between the capacity and voltage of battery cell BC, based on the capacity-voltage relationship data described later. In Graph 200, the vertical axis represents the voltage of battery cell BC, and the horizontal axis represents the capacity (in mAh).

[0057] The QV profile 200 can also be referred to as the "capacity-voltage profile," "capacity-voltage curve," or "full cell profile." As mentioned above, the battery cell BC has a voltage flatness characteristic, and it can be confirmed that the voltage is maintained almost constant over a capacity range of approximately 20mAh to 40mAh in the QV profile 200.

[0058] Assume that the QV profile 200 was obtained through a charging cycle for battery cell BC. Constant power or constant current may be used when performing the charging cycle.

[0059] In a constant-power charging cycle, the charging current gradually decreases as the battery voltage increases. Therefore, not only voltage time-series data showing the history of changes in battery voltage over time, but also current time-series data showing the history of changes in the current flowing through the battery over time is essential.

[0060] In a constant-current charging cycle, a charging current with a predetermined current rate is controlled to flow through the battery cell BC. Therefore, the capacity at a particular point in time may be assumed to be equal to the value obtained by multiplying the elapsed time from the start of the constant-current charging cycle to the specific point in time (i.e., the time difference between the start and the specific point in time) by the predetermined current rate. Of course, even in a constant-current charging cycle, the actual charging current may temporarily become larger or smaller than the originally intended charging current. Therefore, the control circuit 130 may generate current time-series data by calculating the capacity during charging or discharging in real time by periodically repeating and integrating current measurements obtained by directly measuring the current flowing through the battery cell BC using the current sensor 112.

[0061] The charging cycle may continue until the voltage of the battery cell BC changes over at least a predetermined voltage range. The QV profile 200 shows the correspondence between the capacity and voltage of the battery cell BC, obtained over the period from when the voltage of the battery cell BC reaches the upper limit of the predetermined voltage range by a constant current charging cycle.

[0062] The QV profile 200 shown in Figure 2 illustrates how the voltage of battery cell BC increases from 2.6V (lower voltage limit) to 3.6V (upper voltage limit) as the capacity of battery cell BC increases from 0mAh to 52mAh. Here, the range from 0mAh to 52mAh is called the overall capacity range of the QV profile 200, and this corresponds to a predetermined voltage range.

[0063] In this regard, the overall capacity range corresponding to at least a predetermined voltage range may change depending on the degradation state of the battery cells BC. Furthermore, even if two different battery cells BC have the same degradation state, their capacity ranges may differ due to manufacturing process deviations, etc. To improve the ease and appropriateness of data processing required for diagnosing the degradation state of battery cells BC, and to ensure the accuracy of the diagnostic results, it is necessary to apply a normalization process to the overall capacity range.

[0064] Graph 300, shown in Figure 3, is an example of a normalized QV profile obtained by applying a normalization process to QV profile 200. In graph 300, the vertical axis shows the voltage of battery cell BC, similar to Figure 2, and the horizontal axis shows the normalized capacity (in %). Normalized capacity can be a term equivalent to the usual SOC (State of Charge).

[0065] Assuming that the voltage and capacitance according to QV Profile 200 have a mathematical relationship as shown in Equation 1 below, the voltage and normalized capacitance according to QV Profile 300 have a mathematical relationship as shown in Equation 2 below.

[0066]

Mathematics

[0067]

Mathematics

[0068] In Equation 1, Q B represents any capacitance value within the total capacitance range, and V B represents the voltage value mapped to Q in the Q-V profile 200. In Equation 2, Q B represents the normalized capacitance value corresponding to Q, and Q B_normal represents Q B represents the normalized capacitance value corresponding to it, and Q total represents the magnitude of the total capacitance range (i.e., the upper capacitance value of the total capacitance range). For reference, FIG. 3 shows the result of normalizing each data point in the total capacitance range of FIG. 2 as a percentage (range of 0 to 100%), which is to be understood as one example. For example, it may be normalized in other ranges such as 0 to 1 instead of the range of 0 to 100%.

[0069] The graph 400 shown in FIG. 4 is an example of a Q-dV / dQ profile. The Q-dV / dQ profile 400 may also be referred to as a "capacitance-differential voltage profile" or a "capacitance-differential voltage curve".

[0070] The control circuit 130 can generate the Q-dV / dQ profile 400 by differentiating the voltage of the normalized Q-V profile 300 with respect to the normalized capacitance. Specifically, the control circuit 130 determines the differential voltage dV / dQ, which is the ratio of the change amount dV of the voltage to the change amount dQ of the normalized capacitance Q [%], and can record the Q-dV / dQ profile 400 as relation data indicating the correspondence between the normalized capacitance Q and the differential voltage dV / dQ in the memory.

[0071] The control circuit 130 can set a cutoff reference point located within a predetermined reference capacity range from the Q-dV / dQ profile 400. The reference capacity range may partially overlap with the capacity range in which the voltage flatness characteristic of the battery cell BC is exhibited.

[0072] Specifically, the control circuit 130 determines the maximum point P having the maximum differential voltage within the reference capacitance range from the Q-dV / dQ profile 400. MAX It can identify the maximum point P from the Q-dV / dQ profile 400. Then the control circuit 130 identifies the maximum point P MAX Cutoff reference point P is located on the higher capacitance side. cut-off It can identify (detect). Cutoff reference point P cut-off Q is a capacity value within the standard capacity range. cut-off It may be a local minimum having [a specific value].

[0073] If there are two or more local minimums within the standard volume range, then the local maximum point P MAX The point where the difference in capacity is greatest is the local minimum point P. cut-off It can be identified as: Cutoff reference point P cut-off This may be the last local minimum on the Q-dV / dQ profile 400, due to the voltage characteristics of the negative electrode material of battery cell BC. That is, the cutoff reference point P. cut-off The higher capacity range may be one in which the voltage characteristics of the positive electrode material of the battery cell BC overwhelmingly outperform those of the negative electrode material. Therefore, it is easy for those skilled in the art to understand that by identifying only the high-capacity portion of the normalized QV profile 300 as the target of analysis, it should be possible to precisely estimate the positive electrode degradation state of the battery cell BC.

[0074] The inventors have found that the voltage characteristics of the negative electrode material are better than other parts of the normalized QV profile 300, compared to the cutoff reference point P cut-offWe have confirmed through numerous experiments that this is reflected in a relatively very small amount in the higher capacity portion. Therefore, we have also recognized that by analyzing the higher capacity portion of the normalized QV profile 300 as a whole, it is possible to accurately diagnose the parameters related to positive electrode degradation among the various degradation parameters related to the degradation state of battery cell BC. In this specification, the cutoff reference point P cut-off When the normalized QV profile 300 is divided into a low-capacity portion and a high-capacity portion based on this reference, as shown in Figure 3, the high-capacity portion of the normalized QV profile 300 will be referred to as the "QV profile of interest" (see reference numeral 500 in Figure 5). Figure 4 illustrates that 50% to 99% is defined as the reference capacity range.

[0075] Figure 5 is a graph showing an example of a QV profile of interest extracted from the normalized QV profile in Figure 4, and Figure 6 is an example of a corrected QV profile of interest obtained from the QV profile of interest in Figure 5.

[0076] Referring to Figure 5, the QV profile of interest 500 is at the cutoff reference point P. cut-off This is an enlarged portion of the normalized QV profile 300, corresponding to the volume range of interest (e.g., 92% to 99%), where the volume value (e.g., 92%) and the upper volume value of the reference volume range (e.g., 99%) are set as the lower and upper volume limits, respectively.

[0077] In this regard, even if the positive electrode degradation state of battery cell BC is the same, if other degradation factors such as the negative electrode degradation state of battery cell BC and the amount of available lithium differ, the start point, end point, and / or general shape (e.g., curvature) of the QV profile of interest extracted from the QV profile of interest 500 may change. Therefore, a normalization process must be applied to the QV profile of interest 500, similar to the normalization process applied to the QV profile 200.

[0078] Referring to Figure 6, we can see the corrected interest QV profile 600 obtained through the normalization process (profile adjustment process) performed on the interest QV profile 500.

[0079] Specifically, the control circuit 130 controls the starting point P of the QV profile of interest 500. S and endpoint P E Each of these is a predetermined first reference point P R1 and the second reference point P R2 To match the starting point P of the QV profile of interest, at least one of shifting or scaling can be performed on the QV profile of interest 500 to generate a corrected QV profile of interest 600. S This could be the point having the minimum capacity value of the QV profile 500 of interest. The endpoint P of the QV profile 500 of interest. E This could be the point that has the maximum capacity value of the QV profile 500 of interest.

[0080] 1st reference point P R1 The capacity value is at the starting point P S It is smaller than the capacity value of the first reference point P R1 The voltage value is at the starting point P S It is smaller than the voltage value of the second reference point P. R2 The capacity value is greater than the capacity value at the endpoint PE, and the second reference point P R2 The voltage value is at the endpoint P E It is greater than the voltage value.

[0081] The control circuit 130 controls the starting point P S This is the first reference point P R1 To match or end point P E This is the second reference point P. R2A first operation may be performed to shift the QV profile of interest 500 along at least one of the capacitance axis or voltage axis to match the specified parameters, and a second operation may be performed to scale the QV profile of interest 500 along at least one of the capacitance axis or voltage axis. The first operation may include at least one of horizontal movement (moving left or right along the horizontal axis) and vertical movement (moving up or down along the vertical axis). The second operation may include at least one of reduction and expansion with respect to at least one of the horizontal axis or vertical axis.

[0082] starting point P S , ending point P E , first reference point P R1 , and the second reference point P R2 The 2D coordinates of each are (Q S ,V S ), (Q E ,V E ), (Q R1 ,V R1 ), (Q R2 ,V R2 ) Figure 6 shows the first reference point P. R1 The 2D coordinates are (90%, 3.25V), and the second reference point P R2 The 2D coordinates are exemplified as (100%, 3.55V). The control circuit 130 controls the QV profile 500 of interest towards the low capacitance side. S -Q R1 Shift only by V to the lower voltage side. S -V R1 It can only be shifted by that much. This allows the starting point P to shift. S This is the first reference point P R1 Since this matches, the next endpoint P E to the second reference point P R2 It needs to be matched. Therefore, the control circuit 130 moves the QV profile 500 of interest along the capacitance axis (Q R2 -Q R1 ) / (Q E -Q S ) scaled by the ratio and along the capacitance axis (V R2 -V R1 ) / (V E -V SIt can be scaled by the ratio of (P). This completes the process of generating the corrected interest QV profile 600 from the interest QV profile 500. As a result, two points (P) on the interest QV profile 500 are obtained. S , P E As shown in Figure 6, this will move away from the corrected interest QV profile 600.

[0083] The control circuit 130 can determine profile characteristic parameters based on the corrected interest QV profile 600. The control circuit 130 uses the corrected interest QV profile 600 and the first reference point P R1 , and the second reference point P R2 The area of ​​region of interest A, as defined by [the specified method], can be determined as a profile characteristic parameter. That is, region of interest A may be a closed region enclosed by the corrected interest QV profile 600, the first baseline, and the second baseline. The first baseline is the first reference point P R1 It could be a horizontal line (parallel to the capacity axis) passing through it. The second baseline is the second reference point P. R2 It could be a vertical line passing through (parallel to the voltage axis).

[0084] The control circuit 130 can input the area of ​​region A, determined as a profile characteristic parameter, as an input variable to a linear regression model to determine a first degradation parameter related to the degradation state of battery cell BC. The first degradation parameter may indicate the capacity reduction rate due to positive electrode degradation of the battery cell. The capacity reduction rate due to positive electrode degradation may be called the "degree of positive electrode degradation" or "capacity reduction rate due to positive electrode degradation (positive electrode degradation derived capacity reduction ratio)". The linear regression model will be explained in detail below with reference to Figures 8 and 9.

[0085] The inventors obtained relational data that can generate a linear regression model by sequentially performing the following steps: forcibly degrading multiple battery cells BC prepared as experimental subjects so that each of them has a different degree of positive electrode degradation; calculating the area of ​​the region of interest associated with each forcibly degraded battery cell BC; disassembling each forcibly degraded battery cell BC to produce a positive electrode half-cell; and measuring and recording the usable capacity of each positive electrode half-cell.

[0086] Figure 7 is a reference figure used to illustrate the relationship between different cathode degradation levels and the corrected QV profile of interest, and Figure 8 is a reference figure used to illustrate the relationship between different cathode degradation levels and the area of ​​the region of interest.

[0087] Figure 7 shows the pattern in which the corrected QV profile of interest changes with increasing positive electrode degradation. Positive electrode degradation can refer to the rate of capacity reduction due to positive electrode degradation.

[0088] Referring to Figure 7, curve 710 illustrates a corrected QV of interest profile obtained in a brand-new state with no positive electrode degradation, curve 720 illustrates a corrected QV of interest profile obtained with a positive electrode degradation of 1.75%, and curve 730 illustrates a corrected QV of interest profile obtained with a positive electrode degradation of 9.40%.

[0089] In other words, the higher the degree of positive electrode degradation, the more the corrected interest QV profile becomes at the first reference point P R1 and the second reference point P R2 Figure 7 shows that the shape gradually changes to approach that of a straight line connecting the two points, and as a result, the area of ​​the region of interest increases.

[0090] Referring to Figure 8, the linear regression model 800 is pre-defined as a function of the relationship between the profile characteristic parameter (area of ​​the region of interest) and the positive electrode degradation state. Point 810 relates to curve 710 in Figure 7, point 820 relates to curve 720 in Figure 7, and point 830 relates to curve 730 in Figure 7. Although not all are shown, the inventors obtained additional points outside of points (810, 820, 830) as a result of the above-described experiment, and then used them to obtain the linear regression model 800 through linear regression analysis. The linear regression model 800 can be pre-recorded in memory 131. Equation 3 below is an example of the linear regression model 800.

[0091]

number

[0092] In Equation 3, A and B are two coefficients representing the slope and y-intercept of the line by the linear regression model 800, respectively. x represents the area of ​​the region of interest as an input variable, and y represents the degree of positive electrode degradation as an output variable. A and B can vary depending on the type and composition ratio of the positive and negative electrode materials, respectively. Therefore, A and B can be appropriately adjusted to match the type and manufacturing information of the battery cell BC provided as the subject of diagnosis (e.g., the type and composition ratio of the positive and negative electrode materials, respectively). As an example, A and B in the linear regression model 800 shown in Figure 8 are 5.63 and -8.76, respectively.

[0093] The control circuit 130 inputs the area of ​​the region of interest (A in Figure 6) obtained from a battery cell BC having an unknown positive electrode degradation state as the input variable x to the linear regression model 800, and can obtain the degree of positive electrode degradation as the output variable y. Point 840 is a point on the linear regression model 800 that corresponds to the area of ​​the region of interest (A in Figure 6).

[0094] Table 1 below summarizes the number of constant-power charging cycles, total capacity degradation rate, area of ​​the region of interest, first degradation parameter (capacity degradation rate due to positive electrode degradation), and second degradation parameter (capacity degradation rate due to available lithium loss) described above. Here, available lithium can refer to the amount of lithium ions that can participate in the charge-discharge reaction of the battery cell BC.

[0095] [Table 1]

[0096] Table 1 shows that as the number of cycles increases, the total capacity degradation rate, the area of ​​the region of interest, the capacity degradation rate due to cathode degradation, and the capacity degradation rate due to available lithium loss all increase together. For reference, the number of cycles can be incremented by 1 each time a constant power (or constant current) charge (or discharge) cycle is completed.

[0097] The total capacity reduction rate can be the ratio of the decrease in full charge capacity due to degradation to the full charge capacity of a new battery cell BC. For example, if the full charge capacity in a new state is P, the full charge capacity in a degraded state is U, and the decrease in full charge capacity is W, then W is PU, and the total capacity reduction rate is "(W / P) × 100%".

[0098] The inventors recognized that the sum of the capacity reduction rate due to positive electrode degradation and the capacity reduction rate due to available lithium loss is substantially equal to the total capacity reduction rate. Therefore, the control circuit 130 can determine the capacity reduction rate due to available lithium loss as a second degradation parameter by subtracting the degree of positive electrode degradation determined through the above-mentioned formula 3 from the total capacity reduction rate.

[0099] Figure 9 is a schematic flowchart illustrating a battery diagnostic method according to one embodiment of the present invention. The method according to Figure 9 includes steps S910 to S960. The method according to Figure 9 may further include step S970.

[0100] Referring to Figures 1 to 9, in step S910, the control circuit 130 acquires capacity-voltage relationship data of the battery cell BC using the data acquisition unit. In this specification, the acquisition of data or information may mean generation through software processing, input through a user input device, and / or reception through a communication channel.

[0101] For example, if the data acquisition unit includes a sensing unit 110, the control circuit 130 can generate voltage time series and capacitance time series based on the detection signals generated by the sensing unit 110. Capacitance-voltage relationship data may include voltage time series and capacitance time series. Data points in the voltage time series and data points in the current time series can be mapped to each other on a one-to-one basis.

[0102] A voltage time series may show the history of the voltage change of a battery cell BC over time while the battery cell BC is being charged (or discharged) at a constant power (or constant current) over a predetermined voltage range. A current time series may show the history of the current change over time over the same period as the acquisition period of the voltage time series.

[0103] As another example, if the data acquisition unit includes a communication circuit 150, the control circuit 130 may use the communication circuit 150 to receive capacitance-voltage relationship data from an external device.

[0104] In step S920, the control circuit 130 generates a QV profile 200, a normalized QV profile 300, and a Q-dV / dQ profile 400 for the battery cell BC based on the capacity-voltage relationship data.

[0105] In step S930, the control circuit 130 determines the cutoff reference point P from the Q-dV / dQ profile 400. cut-off Identify.

[0106] In step S940, the control circuit 130 controls the cutoff reference point P cut-off Capacity value Q cut-offBased on this, the QV profile of interest, 500, which is the high-capacity portion of the normalized QV profile 300, is extracted.

[0107] In step S950, the control circuit 130 determines the profile characteristic parameters related to the QV profile of interest 500.

[0108] In step S960, the control circuit 130 determines at least one degradation parameter related to the degradation state of the battery cell BC based on the profile characteristic parameters. This may determine at least one of the first degradation parameter and the second degradation parameter.

[0109] In step S970, the control circuit 130 may determine at least one protection parameter for the battery cell BC based on at least one degradation parameter determined in step S960. As an example, at least one of the following may be determined as a protection parameter: maximum charge voltage, minimum discharge voltage, maximum allowable current, and maximum allowable power.

[0110] The control circuit 130 may switch the relay 20 to the off state or transmit a stop operation request to the inverter 30 and / or charger 3 if (i) the voltage of the battery cell BC is equal to or greater than the maximum charging voltage or less than or equal to the minimum discharge 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 power or discharge power of the battery cell BC is equal to or greater than the maximum allowable power.

[0111] Figure 10 is a flowchart illustrating the subroutines that may be included in step S920 of Figure 9.

[0112] In step S1010, the control circuit 130 generates a QV profile 200 from the voltage time series data generated in step S910.

[0113] In step S1020, the control circuit 130 normalizes the QV profile 200 based on the overall capacitance range of the QV profile 200 and generates a normalized QV profile 300.

[0114] In step S1030, the control circuit 130 differentiates the normalized QV profile 300 to generate a Q-dV / dQ profile 400 that shows the correspondence between the normalized capacity and the differential voltage of the battery cell BC.

[0115] Figure 11 is a flowchart illustrating the subroutines that may be included in step S930 of Figure 9.

[0116] Referring to Figure 11, in step S1110, the control circuit 130 determines from the Q-dV / dQ profile 400 the maximum point P having the maximum differential voltage within the reference capacitance range. MAX Identify.

[0117] In step S1120, the control circuit 130 determines the maximum point P from the Q-dV / dQ profile 400. MAX The minimum point located on the higher capacitance side is the cutoff reference point P. cut-off Set it as follows.

[0118] Figure 12 is a flowchart illustrating the subroutines that may be included in step S950 of Figure 9.

[0119] Referring to Figure 12, in step S1210, the control circuit 130 controls the starting point P of the QV profile of interest 500. S and endpoint P E Each of these is a predetermined first reference point P R1 and the second reference point P R2 To match this, shifting and scaling operations are performed on the interest QV profile 500 to generate a corrected interest QV profile 600.

[0120] In step S1220, the control circuit 130 controls the corrected interest QV profile 600 and the first reference point P.R1 and the second reference point P R2 calculates the area of the region of interest A defined by. The region of interest A can be a region surrounded by the corrected Q-V profile 600, the first baseline L1, and the second baseline L2. The first baseline L1 can be a horizontal line passing through the first reference point P R1 . The second baseline L2 can be a vertical line passing through the second reference point P R2 .

[0121] In step S1230, the control circuit 130 determines profile characteristic parameters equal to the area of the region of interest A. In step S970, the control circuit 130 may use the profile characteristic parameters determined in step S1130 as the input variable x for the linear regression model 800 to determine a first degradation parameter y related to the degradation state of the battery cell BC (see Equation 3). The linear regression model 800 can be one prepared in advance as a relational function showing the correspondence between the profile characteristic parameters and the cathode degradation state.

[0122] The above-described embodiments of the present invention are not implemented only by the apparatus and method, but can also be implemented through a program that realizes functions corresponding to the configurations of the embodiments of the present invention or a recording medium on which the program is recorded. The program or the recording medium can be easily implemented by those skilled in the art from the description of the above embodiments.

[0123] As described above, the present invention has been described with reference to limited embodiments and drawings. However, the present invention is not limited thereto, and it is needless to say that various changes and modifications can be made within the equivalent scope of the technical idea of the present invention and the claims by those having ordinary knowledge in the technical field to which the present invention belongs.

[0124] Furthermore, the present invention described above can be substituted, modified, and altered in various ways by a person with ordinary skill in the art to which the present invention pertains, without departing from the technical spirit of the invention, and is not limited by the embodiments described above and the accompanying drawings. For diverse modifications, all or part of each embodiment may be selectively combined to form the present invention.

Claims

1. A data acquisition unit that acquires capacity-voltage relationship data for battery cells, The control circuit is configured to generate, based on the capacity-voltage relationship data, a Q-V profile showing the correspondence between the capacity and voltage of the battery cell, a normalized Q-V profile showing the correspondence between the normalized capacity and voltage of the battery cell, and a Q-dV / dQ profile showing the correspondence between the normalized capacity and differential voltage of the battery cell. The aforementioned control circuit is From the aforementioned Q-dV / dQ profile, a cutoff reference point located within the reference capacitance range is identified. Based on the capacity value of the cutoff reference point, the profile characteristic parameters related to the Q-V profile of interest, which is the high-capacity portion of the normalized Q-V profile, are determined. A battery diagnostic device configured to determine at least one degradation parameter of the battery cell based on the profile characteristic parameters.

2. The aforementioned control circuit is The Q-V profile is normalized based on the overall capacity range of the Q-V profile to generate the normalized Q-V profile. The battery diagnostic device according to claim 1, configured to generate the Q-dV / dQ profile by differentiating the normalized Q-V profile.

3. The aforementioned control circuit is The battery diagnostic device according to claim 1, configured to set the minimum point within the reference capacity range as the cutoff reference point from the Q-dV / dQ profile.

4. The aforementioned control circuit is A profile adjustment process is performed to match the start and end points of the aforementioned interest Q-V profile to the first and second reference points, respectively, in order to generate a corrected interest Q-V profile. The battery diagnostic device according to any one of claims 1 to 3, configured to determine the area of ​​the region of interest defined by the corrected Q-V profile of interest, the first reference point, and the second reference point as the profile characteristic parameter.

5. The control circuit is configured to determine the first degradation parameter by using the determined area as an input variable for a linear regression model. The battery diagnostic device according to claim 4, wherein the linear regression model is provided in advance as a relationship function between the profile characteristic parameters and the positive electrode degradation state.

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

7. The control circuit determines a second degradation parameter based on the total capacity reduction rate of the battery cells and the first degradation parameter. The battery diagnostic device according to claim 5, wherein the second degradation parameter indicates the rate of capacity reduction due to the loss of available lithium in the battery cell.

8. The battery diagnostic device according to any one of claims 1 to 3, wherein the capacity-voltage relationship data indicates the capacity change history and voltage change history of the battery cell during charging or discharging of the battery cell.

9. A battery pack including a battery diagnostic device according to any one of claims 1 to 3.

10. An electric vehicle comprising the battery pack described in claim 9.

11. Steps to acquire battery cell capacity-voltage relationship data, The steps include generating a Q-V profile showing the correspondence between the capacity and voltage of the battery cell, a normalized Q-V profile showing the correspondence between the normalized capacity and voltage of the battery cell, and a Q-dV / dQ profile showing the correspondence between the normalized capacity and differential voltage of the battery cell, based on the capacity-voltage relationship data. The steps include: identifying a cutoff reference point located within the reference capacity range from the Q-dV / dQ profile; The steps include determining profile characteristic parameters related to the Q-V profile of interest, which is the high-capacity portion of the normalized Q-V profile, based on the capacity value of the cutoff reference point, A battery diagnostic method comprising the step of determining at least one degradation parameter of the battery cell based on the profile characteristic parameters.

12. The step of generating the Q-dV / dQ profile is: The steps include: normalizing the Q-V profile based on the overall capacity range of the Q-V profile to generate the normalized Q-V profile; The battery diagnostic method according to claim 11, comprising the step of differentiating the normalized Q-V profile to generate the Q-dV / dQ profile.

13. The step of determining the profile characteristic parameters of the battery cell is: The steps include: generating a corrected Q-V profile of interest by performing a profile adjustment process to match the start and end points of the aforementioned Q-V profile of interest to a first reference point and a second reference point, respectively; A battery diagnostic method according to claim 11 or 12, comprising the step of determining the area of ​​the region of interest defined by the corrected Q-V profile of interest, the first reference point, and the second reference point as the profile characteristic parameter.

14. The step of determining at least one degradation parameter of the battery cell includes the step of inputting the determined area as an input variable into a linear regression model to determine a first degradation parameter, The battery diagnostic method according to claim 13, wherein the linear regression model is provided in advance as a relationship function between the profile characteristic parameters and the positive electrode degradation state.

15. The step of determining at least one degradation parameter of the battery cell further includes the step of determining a second degradation parameter based on the total capacity reduction rate of the battery cell and the first degradation parameter, The battery diagnostic method according to claim 14, wherein the second degradation parameter indicates the rate of capacity reduction due to the loss of available lithium in the battery cell.

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