Battery data management device and operation method thereof

Abstract

A battery data management device according to one embodiment disclosed in this document may include a data management unit that generates voltage change information depending on the SOC of a battery based on battery data, and a controller that calculates a voltage change function depending on the charge / discharge rate (C-rate) of the battery based on battery data in the beginning of life (BOL) state of the battery among the battery data, and generates OCV change information depending on the SOC of the battery based on the voltage change function depending on the charge / discharge rate of the battery and the voltage change information depending on the SOC of the battery.

Description

[Technical Field]

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2022-0182370, filed December 22, 2022, the entire contents of which are incorporated herein by reference. SUMMARY OF THE INVENTION The embodiments disclosed herein relate to a battery data management device and method of operation. [Background technology]

[0002] An electric vehicle receives electricity from an external source to charge its battery cells, and then drives a motor with the voltage charged in the battery cells to generate power. The battery cells of an electric vehicle may generate heat due to chemical reactions that occur during the charging and discharging of electricity, and this heat may damage the performance and lifespan of the battery cells.

[0003] Battery cells age through repeated charging and discharging during use, gradually shortening their lifespan (SOH, State of Health). The lifespan of a battery cell is greatly affected by conditions such as operating temperature, duration of use, charging voltage, and number of discharges, and cannot be accurately diagnosed by simply measuring the remaining capacity of the battery cell. Therefore, in order to estimate the remaining lifespan of a battery, it is necessary to calculate the battery's accurate OCV (Open Circuit Voltage) value.

[0004] However, the conventional method for calculating the OCV of a battery involves measuring the voltage behavior of the battery by charging and discharging the battery at a low current using a separate charging and discharging device, and this method has the problem that it takes a long time and resources to measure the OCV. Summary of the Invention [Problem to be solved by the invention]

[0005] An object of the embodiments disclosed in this document is to provide a battery data management device and an operating method thereof that can derive an accurate battery OCV graph for estimating the battery's lifespan.

[0006] The technical problems of the embodiments disclosed in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0007] A battery data management device according to one embodiment disclosed in this document may include a data management unit that generates voltage change information depending on the SOC of a battery based on battery data, and a controller that calculates a voltage change function depending on the charge / discharge rate (C-rate) of the battery based on battery data of a specific life state of the battery among the battery data, and generates OCV change information depending on the SOC of the battery based on the voltage change function depending on the charge / discharge rate of the battery and the voltage change information depending on the SOC of the battery.

[0008] According to an embodiment, the data management unit may remove noise from voltage change information according to the SOC of the battery using a Kalman filter.

[0009] According to an embodiment, the data management unit may classify information on voltage changes according to the SOC of the battery based on the SOC and arrange the information at regular intervals.

[0010] According to one embodiment, the controller may fit voltage data according to a predetermined battery charge / discharge rate included in battery data in the beginning of life (BOL) state of the battery, and calculate a quadratic term coefficient of a voltage change function according to the battery charge / discharge rate.

[0011] According to one embodiment, the controller may classify voltage change information according to the SOC of the battery into charge data and discharge data for each SOC of the battery, and may apply interpolation to the charge data and discharge data for each SOC of the battery and the quadratic term coefficient to calculate voltage change information according to the charge / discharge rate for each SOC of the battery.

[0012] According to one embodiment, the controller may extract an OCV, which is the voltage value of the battery when the charge / discharge rate of the battery is "0", from the voltage change information according to the charge / discharge rate of the battery by SOC, and calculate the OCV of the battery by SOC.

[0013] According to an embodiment, the controller may input the OCV for each SOC of the battery to a window filter and smooth it, thereby generating information on the change in OCV according to the SOC of the battery.

[0014] An operating method of a battery management device according to one embodiment disclosed in this document includes the steps of generating voltage change information depending on the SOC of a battery based on battery data, removing noise from the voltage change information depending on the SOC of the battery using a Kalman filter, calculating a voltage change function depending on the charge / discharge rate (C-rate) of the battery based on battery data for a specific life state of the battery among the battery data, and generating OCV change information depending on the SOC of the battery based on the voltage change function depending on the charge / discharge rate of the battery and the voltage change information depending on the SOC of the battery.

[0015] According to an embodiment, the generating information on voltage changes depending on the SOC of the battery based on the battery data may divide the information on voltage changes depending on the SOC of the battery based on the SOC and arrange the information at regular intervals.

[0016] According to one embodiment, the step of calculating a voltage change function according to the charge / discharge rate of the battery based on battery data of a specific life state of the battery among the battery data may involve fitting voltage data according to a predetermined battery charge / discharge rate included in battery data of an initial life (BOL, Beginning Of Life) state of the battery, and calculating a quadratic term coefficient of the voltage change function according to the charge / discharge rate of the battery.

[0017] According to one embodiment, the step of generating information on OCV change according to the SOC of the battery based on a voltage change function according to the charge / discharge rate of the battery and information on voltage change according to the SOC of the battery may include classifying the information on voltage change according to the SOC of the battery into charge data and discharge data for each SOC of the battery, and applying interpolation to the charge data and discharge data for each SOC of the battery and the quadratic term coefficient to calculate information on voltage change according to the charge / discharge rate of the battery for each SOC.

[0018] According to one embodiment, the step of generating information on OCV change according to SOC of the battery based on a voltage change function according to the charge / discharge rate of the battery and information on voltage change according to the SOC of the battery may include extracting an OCV, which is the voltage value of the battery when the charge / discharge rate of the battery is “0”, from the information on voltage change according to the charge / discharge rate of the battery by SOC, and calculating the OCV according to the SOC of the battery.

[0019] According to one embodiment, the step of generating information on OCV change according to the SOC of the battery based on a voltage change function according to the charge / discharge rate of the battery and information on voltage change according to the SOC of the battery may include inputting the OCV of each SOC of the battery to a window filter and smoothing it to generate information on OCV change according to the SOC of the battery. [Effects of the Invention]

[0020] According to an embodiment of the battery data management device and its operating method disclosed in this document, an accurate battery OCV graph can be derived for estimating the battery's lifespan. [Brief explanation of the drawings]

[0021] [Figure 1] FIG. 1 illustrates a battery pack according to one embodiment disclosed herein. [Figure 2] 1 is a block diagram showing the configuration of a battery data management device according to an embodiment disclosed in this document. [Figure 3] 1 is a graph showing voltage variation with SOC for a battery according to an embodiment described herein. [Figure 4] 10 is a graph illustrating an operation of a controller according to an embodiment disclosed herein for calculating a voltage change function depending on a charge / discharge rate of a battery. [Figure 5] FIG. 10 is a diagram illustrating an operation of a controller according to an embodiment disclosed herein to calculate an OCV for each SOC of a battery. [Figure 6] 1 is a graph showing OCV variation with SOC for a battery according to an embodiment disclosed herein. [Figure 7] 10 is a graph showing the change in OCV with SOC for a battery according to another embodiment disclosed herein. [Figure 8] 1 is a flowchart illustrating a method of operating a battery data management device according to an embodiment disclosed herein. [Figure 9] 1 is a block diagram showing the hardware configuration of a computing system that implements an operation method of a battery data management device according to an embodiment disclosed in this document. DETAILED DESCRIPTION OF THE INVENTION

[0022] Some embodiments disclosed herein will be described in detail below with reference to exemplary drawings. When assigning reference numerals to components in each drawing, it should be noted that the same reference numerals are assigned to the same components as long as possible when they appear in other drawings. Furthermore, when describing the embodiments disclosed herein, if a detailed description of related known structures or functions is deemed to hinder understanding of the embodiments disclosed herein, such detailed description will be omitted.

[0023] In describing components of the embodiments disclosed herein, terms such as first, second, A, B, (a), (b), etc. may be used. Such terms are merely used to distinguish the component from other components and do not limit the nature, order, or sequence of the components. Furthermore, unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiments disclosed herein pertain. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the context of the relevant art and should not be interpreted in an idealized or overly formal sense unless expressly defined herein.

[0024] FIG. 1 is a diagram illustrating a battery pack according to one embodiment disclosed herein. 1 , a battery pack 1000 according to one embodiment disclosed herein may include a battery module 100, a battery data management device 200, and a relay 300. According to various embodiments, the battery module 100 may be a battery cell, in which case the battery pack 1000 may have a cell-to-pack structure.

[0025] The battery module 100 may include a plurality of battery cells 110, 120, 130, and 140. Although the number of battery cells is shown as four in FIG. 1, the number of battery cells is not limited to four, and the battery module 100 may include n (n is a natural number equal to or greater than 2) battery cells.

[0026] The battery module 100 can supply power to a target device (not shown). To this end, the battery module 100 can be electrically connected to the target device. Here, the target device can include an electrical, electronic, or mechanical device that operates by receiving power from a battery pack 1000 including a plurality of battery cells 110, 120, 130, and 140. For example, the target device can be, but is not limited to, an electric vehicle (EV) or an energy storage system (ESS).

[0027] The plurality of battery cells 110, 120, 130, 140 are basic units of a battery that can be used by charging and discharging electrical energy, and may be, but are not limited to, lithium ion (Li-ion) batteries, lithium ion polymer (Li-ion polymer) batteries, nickel cadmium (Ni-Cd) batteries, nickel metal hydride (Ni-MH) batteries, etc. Meanwhile, although Fig. 1 shows one battery module 100, according to an embodiment, a plurality of battery modules 100 may be included.

[0028] According to an embodiment, the battery data management device 200 may be implemented in the form of a battery management system (BMS). Also, according to an embodiment, the battery data management device 200 may be mounted in the battery management system.

[0029] The battery data management device 200 can predict the lifespan, i.e., SOH (State of Health), of the multiple battery cells 110, 120, 130, and 140 based on the temperature and voltage data of the multiple battery cells 110, 120, 130, and 140. The battery data management device 200 can remove noise from the battery data of the multiple battery cells 110, 120, 130, and 140 and predict the SOH (State of Health) of the multiple battery cells 110, 120, 130, and 140 based on the data from which the noise has been removed.

[0030] The battery data management device 200 can manage and / or control the state and / or operation of the battery module 100. For example, the battery data management device 200 can manage and / or control the state and / or operation of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. The battery data management device 200 can manage the charging and / or discharging of the battery module 100.

[0031] The battery data management device 200 can control the operation of the relay 300. For example, the battery data management device 200 can short-circuit the relay 300 to supply power to a target device. In addition, the battery data management device 200 can short-circuit the relay 300 when a charging device is connected to the battery pack 1000.

[0032] Furthermore, the battery data management device 200 can monitor the voltage, current, temperature, etc. of the battery module 100 and / or each of the plurality of battery cells 110, 120, 130, 140 included in the battery module 100. For monitoring via the battery data management device 200, sensors and various measurement modules (not shown) can be further provided in the battery module 100, a charge / discharge path, or any position on the battery module 100. The battery data management device 200 can calculate parameters indicating the state of the battery module 100, such as a State of Charge (SOC), based on the measured values ​​of the monitored voltage, current, temperature, etc.

[0033] The battery data management device 200 can estimate the deterioration factors of the positive and negative electrodes of a battery by distinguishing between the states of the positive and negative electrodes of the battery to evaluate the SOH, i.e., the lifespan, of the battery. In this case, the battery data management device 200 can analyze the open circuit voltage (OCV) of the battery to estimate the deterioration factors of the positive and negative electrodes of the battery. Here, OCV refers to the voltage measured when no current flows through the battery. That is, OCV is the voltage between the anode and cathode of a battery when they are not electrically connected. According to Ohm's law, as the resistance of a battery increases infinitely, the current approaches zero, allowing for accurate measurement of the battery's voltage. Therefore, the battery data management device 200 can measure and analyze the OCV of a battery for accurate electrochemical analysis of the battery.

[0034] The battery data management device 200 can differentiate the OCV of a battery and analyze the degradation factors of each of the battery's positive and negative electrodes, such as LLI (Loss of Lithium Inventory), LAMn (Loss of Active Material - negative electrode), or LAMp (Loss of Active Material - positive electrode). Here, LLI is the lithium inventory loss, which refers to the amount of lithium in a battery cell reduced relative to the BOL, LAMn refers to the amount of positive electrode active material reduced relative to the BOL, and LAMp refers to the amount of negative electrode active material reduced relative to the BOL. For example, the battery data management device 200 can extract the battery degradation factors, LLI, LAMn, or LAMp, using an artificial intelligence model that analyzes the battery's OCV or a mathematical modeling technique that calculates the battery degradation factors.

[0035] The battery data management device 200 can calculate an OCV graph of the battery based on predetermined experimental data of a vehicle equipped with the battery pack 1000. That is, the battery data management device 200 can analyze and process predetermined battery data to derive a continuous OCV curve of the battery.

[0036] FIG. 2 is a diagram specifically illustrating the configuration of a battery data management device according to an embodiment disclosed in the document. The configuration of the battery data management device 200 will be specifically described below with reference to FIG.

[0037] Referring to FIG. 2, the battery data management device 200 may include a data management unit 210 and a controller 220. The data management unit 210 can acquire battery data of the plurality of battery cells 110, 120, 130, and 140. Here, according to one embodiment, the battery data may include the voltage (V), current (I), temperature (T), and capacity (Q) of the plurality of battery cells 110, 120, 130, and 140. Specifically, the data management unit 210 can extract battery data by collecting driving test data of a vehicle equipped with the battery pack 1000. For example, the data management unit 210 can select a battery cell that has undergone a predetermined significant deterioration or a battery cell that has undergone a predetermined minor deterioration, which is included in the driving test data of the vehicle equipped with the battery pack 1000, and analyze the battery data of the selected battery cell.

[0038] The data management unit 210 may collect battery data generated as a plurality of charge / discharge cycles of the plurality of battery cells 110, 120, 130, and 140 progress, and classify the battery data for each charge / discharge cycle. Here, the cycle may include an operation cycle of the battery data management device 200, such as power on / off and ignition on / off of the battery data management device 200.

[0039] The data management unit 210 can generate voltage change information according to the SOC of the battery based on battery data of the plurality of battery cells 110, 120, 130, and 140. According to one embodiment, the data management unit 210 can calculate the SOC of the plurality of battery cells 110, 120, 130, and 140 using a current accumulation method. Here, the current accumulation method is a method of determining the state of charge of a battery cell by integrating the charging current and discharging current of the battery cell over time.

[0040] According to the embodiment, the data management unit 210 may calculate SOC data for each charge / discharge cycle of the battery cells 110, 120, 130, and 140 based on battery data generated as the battery cells 110, 120, 130, and 140 go through a plurality of charge / discharge cycles. The data management unit 210 may generate one SOC data by combining the end of the SOC data for a previous cycle and the SOC data for a next cycle in the SOC data for each charge / discharge cycle of the battery cells 110, 120, 130, and 140.

[0041] FIG. 3 is a graph showing voltage variation with SOC for a battery according to one embodiment described herein. 3, the data management unit 210 can generate voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the battery data of the plurality of battery cells 110, 120, 130, and 140. That is, the data management unit 210 can generate an SOC-V profile of the plurality of battery cells 110, 120, 130, and 140.

[0042] According to an embodiment, the data management unit 210 can generate voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on battery data generated as the plurality of charge / discharge cycles of the plurality of battery cells 110, 120, 130, and 140 progress, and plot the information on a display (not provided).

[0043] The data management unit 210 can remove noise from the battery data of the plurality of battery cells 110, 120, 130, and 140. According to one embodiment, the data management unit 210 can remove noise from voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 using a Kalman filter. Here, the Kalman filter is an algorithm that repeats state prediction and measurement value updates. Specifically, the Kalman filter can use previously measured data and new measurement data to remove noise contained in the new measurement data and predict the next measurement value.

[0044] The data management unit 210 can remove noise from the voltage change information depending on the SOC of the plurality of battery cells 110, 120, 130, and 140 using a Kalman filter, and calculate accurate SOC data for each charge / discharge cycle of the plurality of battery cells 110, 120, 130, and 140. That is, the data management unit 210 can correct errors in the voltage change information depending on the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the voltage change information depending on the SOC of the plurality of battery cells 110, 120, 130, and 140 from which noise has been removed.

[0045] According to an embodiment, the data management unit 210 may classify the voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the SOC and arrange the information at regular intervals. For example, the data management unit 210 may classify the voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the SOC and generate a data frame.

[0046] For example, the data management unit 210 may classify the battery data of the plurality of battery cells 110, 120, 130, and 140 based on the SOC and arrange them at regular intervals using an interpolation method. Here, the interpolation method is a method of standardizing given data in a form such as a polynomial, and may estimate data that cannot be obtained through observation or experiment. The data management unit 210 may correct voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 at regular intervals using the interpolation method.

[0047] The controller 220 can calculate information on the OCV changes due to the SOC of the plurality of battery cells 110, 120, 130, 140 based on information on the voltage changes due to the SOC of the plurality of battery cells 110, 120, 130, 140.

[0048] First, the controller 220 can calculate a voltage change function according to the charge / discharge rate (C-rate) of the battery cells 110, 120, 130, and 140 based on battery data arranged at regular intervals based on the SOC of the battery cells 110, 120, 130, and 140.

[0049] The controller 220 can calculate a voltage change function according to the charge / discharge rate of the plurality of battery cells 110, 120, 130, 140 based on battery data of a particular life state of the plurality of battery cells 110, 120, 130, 140 among the battery data. Here, the particular life state can include the beginning of life (BOL), middle of life (MOL), and end of life (EOL) of the battery.

[0050] According to the embodiment, the controller 220 can calculate a voltage change function according to the charge / discharge rate of the plurality of battery cells 110, 120, 130, 140 based on battery data of the plurality of battery cells 110, 120, 130, 140 in their initial life (BOL) states, among the battery data.

[0051] FIG. 4 is a graph showing the operation of calculating a voltage change function according to the charge / discharge rate of a battery in a controller according to an embodiment disclosed herein. 4, the controller 220 can extract predetermined battery data included in the battery data of the battery cells 110, 120, 130, and 140 in the initial state of life (BOL). For example, the controller 220 can extract first battery data, which is battery charge data (meaning that the C-rate is a positive number (+)), second battery data, which is battery discharge data (meaning that the C-rate is a negative number (-)), and third battery data, which is battery OCV data (meaning that the C-rate is 0), from the battery data of the battery cells 110, 120, 130, and 140 in the initial state of life (BOL). Here, the first battery data, the second battery data, and the third battery data include the voltage (V), current (I), temperature (T), and capacity (Q) of the battery cells measured when the battery cells are in the initial state of life (BOL), and the SOCs of the first battery data, the second battery data, and the third battery data may be the same.

[0052] The controller 220 can fit the first battery data, the second battery data, and the third battery data. For example, the controller 220 can fit voltage (V) data according to the charge / discharge rate (C-rate) of the battery cells included in the first battery data, the second battery data, and the third battery data. The controller 220 can calculate a voltage change function according to the charge / discharge rate of the plurality of battery cells 110, 120, 130, and 140 by approximating the first battery data, the second battery data, and the third battery data.

[0053] The controller 220 can extract the slope value of the graph formed by approximating the first battery data, the second battery data, and the third battery data. That is, the controller 220 can calculate the quadratic term coefficient C of the voltage change function according to the charge / discharge rates of the plurality of battery cells 110, 120, 130, and 140 calculated by approximating the first battery data, the second battery data, and the third battery data. For example, the controller 220 can approximate the first battery data, the second battery data, and the third battery data to extract the slope value of the graph formed by approximating the first battery data, the second battery data, and the third battery data. 2 Here, the controller 220 can extract "-0.7" as the quadratic term coefficient C of the function.

[0054] The controller 220 can generate OCV change information depending on the SOC of the multiple battery cells 110, 120, 130, and 140 based on a voltage change function depending on the charge / discharge rate (C-rate) of the multiple battery cells 110, 120, 130, and 140 at the initial state of life (BOL) and voltage change information depending on the SOC of the multiple battery cells 110, 120, 130, and 140.

[0055] Specifically, the controller 220 can calculate the OCV for each SOC of the plurality of battery cells 110, 120, 130, and 140 by applying interpolation to the voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 and the quadratic term coefficient C of the voltage change function according to the charge / discharge rate at the initial life state (BOL) of the plurality of battery cells 110, 120, 130, and 140.

[0056] FIG. 5 is a diagram showing an operation of calculating the OCV for each SOC of a battery by a controller according to an embodiment disclosed herein. 5, first, the controller 220 can acquire charge data D1 (meaning that C-rate is a positive number (+)) and discharge data D2 (meaning that C-rate is a negative number (-)) for each SOC generated by classifying voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the SOC. That is, the controller 220 can acquire two data points corresponding to the charge data D1 and the discharge data D2 for each SOC of the plurality of battery cells 110, 120, 130, and 140.

[0057] The controller 220 can perform quadratic fitting to approximate two data points corresponding to the charge data D1 and discharge data D2 according to the SOC of the plurality of battery cells 110, 120, 130, and 140 and the quadratic term coefficient C of the voltage change function according to the charge and discharge rate of the plurality of battery cells 110, 120, 130, and 140 at the initial state of life (BOL).

[0058] The controller 220 may use a "0" C-rate interpolation method in which two data points corresponding to the charge data D1 and discharge data D2 for each SOC and a quadratic term coefficient C are used to connect the two points, and then search for a point where the x-coordinate becomes "0." Specifically, the controller 220 may apply the two data points corresponding to the charge data D1 and discharge data D2 for each SOC of the plurality of battery cells 110, 120, 130, and 140 and the quadratic term coefficient C of a voltage change function according to the charge and discharge rates of the plurality of battery cells 110, 120, 130, and 140 to the interpolation method, to extract the OCV, which is the voltage value of the battery cell when the charge and discharge rate of the battery is "0," and calculate the OCV for each SOC of the battery.

[0059] For example, the controller 220 can acquire "C-rate: 0.7 C, V: 0.9 V" as charge data D1 and "C-rate: -0.4 C, V: 0.1 V" as discharge data D2 of the plurality of battery cells 110, 120, 130, and 140 at a specific SOC. The controller 220 approximates all of "-0.7", which is the quadratic term coefficient C of the voltage change function depending on the charge and discharge rates of the charge and discharge data D1 and the plurality of battery cells 110, 120, 130, and 140 at the initial state of life (BOL), and obtains "-0.7x 2 +0.94x+0.5". In this quadratic function, the controller 220 can calculate the x-coordinate, i.e., the OCV value, which is the voltage value when the charge / discharge rate (C-rate) is "0", as "0.59".

[0060] The controller 220 can calculate the OCV values ​​for each SOC of the plurality of battery cells 110, 120, 130, and 140, and then aggregate the OCV values ​​for each SOC of the plurality of battery cells 110, 120, 130, and 140 to generate OCV change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140.

[0061] FIG. 6 is a graph showing the change in OCV with SOC for a battery according to one embodiment disclosed herein. Referring to FIG. 6, the controller 220 may generate information on the change in OCV according to the SOC of the battery cells 110, 120, 130, and 140 by combining the OCVs calculated for each SOC of the battery cells 110, 120, 130, and 140.

[0062] The controller 220 may input the OCVs of the battery cells 110, 120, 130, and 140 according to their SOCs to a window-based filter to smooth them, thereby generating information on changes in OCV according to the SOCs of the battery cells 110, 120, 130, and 140.

[0063] FIG. 7 is a graph showing the change in OCV with SOC for a battery according to another embodiment disclosed herein. 7, the controller 220 may input the SOC-specific OCVs of the plurality of battery cells 110, 120, 130, and 140 into a window-based filter to smooth them. The controller 220 may smooth the SOC-specific OCVs of the plurality of battery cells 110, 120, 130, and 140 to derive a smooth OCV curve.

[0064] As described above, the battery data management device 200 according to an embodiment disclosed in this document can generate an accurate battery OCV graph for estimating the battery life.

[0065] The battery data management device 200 takes a short time to calculate the OCV of the battery, and can constantly determine the state of the battery, and if an abnormal state is diagnosed, can immediately provide the user with the information. Furthermore, the battery data management device 200 can obtain battery data from which noise has been removed, thereby improving the accuracy of battery life prediction.

[0066] 8 is a flowchart showing an operation method of the battery data management device according to an embodiment disclosed in the present document. Hereinafter, the operation method of the battery data management device 200 will be described with reference to FIGS.

[0067] The battery data management device 200 is substantially similar to the battery data management device 200 described with reference to FIGS. 1 to 7, and therefore will be described briefly below to avoid duplication of description.

[0068] Referring to FIG. 8, the operating method of the battery data management device 200 includes the steps of: generating voltage change information according to the SOC of the battery based on battery data (S101); removing noise from the voltage change information according to the SOC of the battery using a Kalman filter (S102); calculating a voltage change function according to the charge / discharge rate (C-rate) of the battery based on battery data of a specific life state of the battery among the battery data (S103); and generating OCV change information according to the SOC of the battery based on the voltage change function according to the charge / discharge rate of the battery and the voltage change information according to the SOC of the battery (S104).

[0069] In step S101, the data management unit 210 may acquire battery data of the plurality of battery cells 110, 120, 130, and 140. Here, according to one embodiment, the battery data may include the voltage (V), current (I), temperature (T), and capacity (Q) of the plurality of battery cells 110, 120, 130, and 140. Specifically, in step S101, the data management unit 210 may collect driving test data of a vehicle equipped with the battery pack 1000 and extract the battery data. For example, in step S101, the data management unit 210 may select a battery cell that has undergone a predetermined significant deterioration or a battery cell that has undergone a predetermined minor deterioration, which is included in the driving test data of the vehicle equipped with the battery pack 1000, and analyze the battery data of the selected battery cell.

[0070] In step S101, the data management unit 210 collects battery data generated as the plurality of battery cells 110, 120, 130, and 140 undergo a plurality of charge / discharge cycles, and classifies the battery data for each charge / discharge cycle.

[0071] In step S101, the data management unit 210 can generate voltage change information according to the SOC of the battery based on the battery data of the plurality of battery cells 110, 120, 130, and 140. According to one embodiment, the data management unit 210 can calculate the SOC of the plurality of battery cells 110, 120, 130, and 140 using a current accumulation method.

[0072] In step S101, according to an embodiment, the data management unit 210 may calculate SOC data for each charge / discharge cycle of the plurality of battery cells 110, 120, 130, and 140 based on battery data generated as the plurality of charge / discharge cycles of the plurality of battery cells 110, 120, 130, and 140 progress. In step S101, the data management unit 210 may generate one SOC data by concatenating the end of the SOC data for the previous cycle and the SOC data for the next cycle in the SOC data for each charge / discharge cycle of the plurality of battery cells 110, 120, 130, and 140.

[0073] In step S101, the data management unit 210 can generate voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the battery data of the plurality of battery cells 110, 120, 130, and 140. In other words, in step S101, the data management unit 210 can generate an SOC-V profile of the plurality of battery cells 110, 120, 130, and 140.

[0074] In step S101, according to an embodiment, the data management unit 210 generates voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, 140 based on battery data generated as the plurality of charge / discharge cycles of the plurality of battery cells 110, 120, 130, 140 progress, and can plot the information on a display (not provided).

[0075] In step S102, the data management unit 210 can remove noise from the battery data of the plurality of battery cells 110, 120, 130, and 140. In step S102, according to one embodiment, the data management unit 210 can remove noise from the voltage change information due to the SOC of the plurality of battery cells 110, 120, 130, and 140 using a Kalman filter.

[0076] In step S102, the data management unit 210 uses a Kalman filter to remove noise from the voltage change information depending on the SOC of the plurality of battery cells 110, 120, 130, and 140, thereby calculating accurate SOC data for each charge / discharge cycle of the plurality of battery cells 110, 120, 130, and 140. In other words, in step S102, the data management unit 210 can correct errors in the voltage change information depending on the SOC of the plurality of battery cells 110, 120, 130, and 140, based on the voltage change information depending on the SOC of the plurality of battery cells 110, 120, 130, and 140 from which noise has been removed.

[0077] In step S102, according to an embodiment, the data management unit 210 may classify the voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the SOC and arrange the information at regular intervals. For example, in step S102, the data management unit 210 may classify the voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 based on the SOC and generate a data frame.

[0078] In step S102, for example, the data management unit 210 may also classify the battery data of the plurality of battery cells 110, 120, 130, and 140 based on the SOC and arrange the data at regular intervals based on the interpolation method. In step S102, the data management unit 210 may also correct the voltage change information of the plurality of battery cells 110, 120, 130, and 140 according to the SOC at regular intervals based on the interpolation method.

[0079] In step S103, the controller 220 can calculate a voltage change function according to the charge / discharge rate (C-rate) of the battery cells 110, 120, 130, 140 based on battery data arranged at regular intervals based on the SOC of the battery cells 110, 120, 130, 140.

[0080] In step S103, the controller 220 can calculate a voltage change function according to the charge / discharge rate of the plurality of battery cells 110, 120, 130, 140 based on the battery data of a specific life state of the plurality of battery cells 110, 120, 130, 140. Here, the specific life state can include the beginning of life (BOL), middle of life (MOL), and end of life (EOL) of the battery.

[0081] In step S103, according to an embodiment, the controller 220 can calculate a voltage change function according to the charge / discharge rate of the plurality of battery cells 110, 120, 130, 140 based on the battery data of the initial life (BOL) state of the plurality of battery cells 110, 120, 130, 140 among the battery data.

[0082] In step S103, the controller 220 can extract predetermined battery data included in the battery data of the initial state of life (BOL) of the multiple battery cells 110, 120, 130, and 140. In step S103, for example, the controller 220 can extract first battery data which is battery charge data (meaning that C-rate is a positive number (+)), second battery data which is battery discharge data (meaning that C-rate is a negative number (-)), and third battery data which is battery OCV data (meaning that C-rate is "0") from the battery data of the initial state of life (BOL) of the multiple battery cells 110, 120, 130, and 140.

[0083] In step S103, the controller 220 may fit the first battery data, the second battery data, and the third battery data. For example, the controller 220 may fit voltage (V) data according to the charge / discharge rates (C-rates) of the battery cells included in the first battery data, the second battery data, and the third battery data. In step S103, the controller 220 may fit the first battery data, the second battery data, and the third battery data to calculate a voltage change function according to the charge / discharge rates of the plurality of battery cells 110, 120, 130, and 140.

[0084] In step S103, the controller 220 can extract a slope value of the graph formed by approximating the first battery data, the second battery data, and the third battery data. In step S103, the controller 220 can calculate a quadratic term coefficient C of a voltage change function according to the charge / discharge rates of the multiple battery cells 110, 120, 130, and 140 calculated by approximating the first battery data, the second battery data, and the third battery data.

[0085] In step S104, the controller 220 can generate OCV change information depending on the SOC of the multiple battery cells 110, 120, 130, 140 based on the voltage change function depending on the charge / discharge rate at the initial state of life (BOL) of the multiple battery cells 110, 120, 130, 140 and the voltage change information depending on the SOC of the multiple battery cells 110, 120, 130, 140.

[0086] In step S104, specifically, the controller 220 applies the voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140 and the quadratic term coefficient C of the voltage change function according to the charge / discharge rate of the plurality of battery cells 110, 120, 130, and 140 at the initial state of life (BOL) to interpolation, thereby calculating the OCV according to the SOC of the plurality of battery cells 110, 120, 130, and 140.

[0087] In step S104, the controller 220 may acquire charge data D1 (meaning that C-rate is a positive number (+)) and discharge data D2 (meaning that C-rate is a negative number (-)) for each SOC generated by classifying, based on SOC, voltage change information according to the SOC of the plurality of battery cells 110, 120, 130, and 140. In step S104, the controller 220 may acquire two data points corresponding to the charge data D1 and the discharge data D2 for each SOC of the plurality of battery cells 110, 120, 130, and 140.

[0088] In step S104, the controller 220 may perform quadratic fitting to approximate two data points corresponding to the charge data D1 and discharge data D2 for each SOC of the plurality of battery cells 110, 120, 130, and 140 and a quadratic term coefficient C of a voltage change function depending on the charge and discharge rate at the initial state of life (BOL) of the plurality of battery cells 110, 120, 130, and 140. In step S104, the controller 220 may connect the two points using the two data points corresponding to the charge data D1 and discharge data D2 for each SOC and the quadratic term coefficient C, and then use a “0” C-rate interpolation method to find a point where the x coordinate becomes “0.”

[0089] Specifically, in step S104, the controller 220 applies interpolation to two data points corresponding to the charge data D1 and discharge data D2 for each SOC of the plurality of battery cells 110, 120, 130, and 140 and the quadratic term coefficient C of the voltage change function depending on the charge and discharge rates of the plurality of battery cells 110, 120, 130, and 140, to extract the OCV, which is the voltage value of the battery when the charge and discharge rate of the battery is "0", and calculates the OCV for each SOC of the battery.

[0090] In step S104, the controller 220 calculates the OCV values ​​for each SOC of the multiple battery cells 110, 120, 130, and 140, and then aggregates the OCV values ​​for each SOC of the multiple battery cells 110, 120, 130, and 140 to generate OCV change information according to the SOC of the multiple battery cells 110, 120, 130, and 140.

[0091] In step S104, the controller 220 may combine the OCVs calculated for each SOC of the battery cells 110, 120, 130, and 140 to generate OCV change information according to the SOC of the battery cells 110, 120, 130, and 140.

[0092] In step S104, the controller 220 may input the SOC-specific OCVs of the battery cells 110, 120, 130, and 140 into a window-based filter to smooth them, thereby generating OCV change information according to the SOC of the battery cells 110, 120, 130, and 140.

[0093] In step S104, the controller 220 may input the SOC-specific OCVs of the plurality of battery cells 110, 120, 130, and 140 into a window-based filter to smooth them. The controller 220 may smooth the SOC-specific OCVs of the plurality of battery cells 110, 120, 130, and 140 to derive a smooth OCV curve.

[0094] FIG. 9 is a block diagram showing the hardware configuration of a computing system that implements the method of operating a battery data management device according to an embodiment disclosed herein.

[0095] Referring to FIG. 9, a computing system 2000 according to one embodiment disclosed herein may include an MCU 2100, a memory 2200, an input / output I / F 2300, and a communication I / F 2400.

[0096] The MCU 2100 may be a processor that executes various programs (e.g., a battery voltage change function) stored in the memory 2200, processes various data through such programs, and performs the functions of the battery data management device 200 shown in FIG. 1 described above.

[0097] The memory 2200 can store various programs related to the operation of the battery data management device 200. The memory 2200 can also store operation data of the battery data management device 200.

[0098] A plurality of such memories 2200 may be provided as necessary. The memories 2200 may be volatile memories or nonvolatile memories. The volatile memories 2200 may be RAM, DRAM, SRAM, etc. The nonvolatile memories 2200 may be ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc. The examples of the memories 2200 listed above are merely illustrative and are not limited to these examples.

[0099] The input / output I / F 2300 can provide an interface that connects input devices (not shown) such as a keyboard, mouse, or touch panel, and output devices such as a display (not shown), to the MCU 2100, enabling data to be sent and received.

[0100] The communication I / F 2400 is configured to be able to send and receive various data to and from a server, and may be any device that supports wired or wireless communication. For example, programs for measuring resistance and diagnosing abnormalities and various data can be sent and received from a separately provided external server via the communication I / F 2400.

[0101] In this way, the computer program of one embodiment disclosed in this document may be recorded in memory 2200 and processed by MCU 2100, thereby realizing, for example, a module that performs each function of battery data management device 200 described with reference to Figures 1 and 2.

[0102] The above description merely exemplifies the technical concept of the present disclosure, and various modifications and variations are possible by a person having ordinary knowledge in the technical field to which the present disclosure pertains, without departing from the essential characteristics of the present disclosure.

[0103] Therefore, the embodiments disclosed in this disclosure are intended to illustrate, not limit, the technical idea of ​​the disclosure, and the scope of the technical idea of ​​the disclosure is not limited by such embodiments. The scope of protection of the disclosure should be interpreted by the claims below, and all technical ideas within the equivalent range should be interpreted as being included in the scope of rights of the disclosure. [Explanation of symbols]

[0104] 1000: Battery pack 100: Battery module 200: Battery data management device 210: Data Management Department 220: Controller 2000: Computing Systems 2100:MCU 2200:Memory 2300: Input / output interface 2400:Communication I / F 300: Relay D1: Charging data D2: Discharge data C: Quadratic term coefficient

Claims

1. a data management unit that generates information on voltage changes due to the SOC of the battery based on the battery data; a controller that calculates a voltage change function depending on a charge / discharge rate of the battery based on battery data of a specific life state of the battery among the battery data, and generates OCV change information depending on an SOC of the battery based on the voltage change function depending on the charge / discharge rate of the battery and voltage change information depending on an SOC of the battery; A battery data management device comprising:

2. The battery data management device according to claim 1 , wherein the data management unit uses a Kalman filter to remove noise from the information on voltage changes due to the SOC of the battery.

3. The battery data management device of claim 2 , wherein the data management unit classifies the information on voltage changes according to the SOC of the battery based on the SOC and arranges the information at regular intervals.

4. 4. The battery data management device according to claim 3, wherein the controller approximates voltage data based on a predetermined battery charge / discharge rate included in the battery data for the initial life state of the battery, and calculates a quadratic term coefficient of a voltage change function based on the battery charge / discharge rate.

5. The controller classifies voltage change information according to the SOC of the battery into charge data and discharge data according to the SOC of the battery; 5. The battery data management device according to claim 4, wherein the charge data and discharge data for each SOC of the battery and the quadratic term coefficients are applied to an interpolation method to calculate voltage change information according to the charge / discharge rate for each SOC of the battery.

6. 6. The battery data management device according to claim 4, wherein the controller extracts an OCV, which is a voltage value of the battery when the charge / discharge rate of the battery is "0", from the voltage change information depending on the charge / discharge rate of the battery by SOC, and calculates the OCV of the battery by SOC.

7. 6. The battery data management device according to claim 4, wherein the controller inputs the SOC-specific OCV of the battery to a window filter to smooth the OCV, and generates information on changes in OCV according to the SOC of the battery.

8. generating information on a voltage change due to the SOC of the battery based on the battery data; removing noise from voltage change information due to SOC of the battery using a Kalman filter; calculating a voltage change function according to a charge / discharge rate of the battery based on battery data of a specific life state of the battery among the battery data; generating OCV change information according to an SOC of the battery based on a voltage change function according to a charge / discharge rate of the battery and voltage change information according to an SOC of the battery; A method of operating a battery data management device, comprising:

9. 9. The method of claim 8, wherein the step of generating information on voltage change depending on the SOC of the battery based on the battery data comprises dividing the information on voltage change depending on the SOC of the battery based on the SOC and arranging the information on voltage change depending on the SOC at regular intervals.

10. 10. The method of claim 9, wherein the step of calculating a voltage change function depending on the charge / discharge rate of the battery based on battery data of a specific life state of the battery among the battery data includes approximating voltage data depending on a predetermined battery charge / discharge rate included in the battery data of the initial life state of the battery, and calculating a quadratic term coefficient of the voltage change function depending on the charge / discharge rate of the battery.

11. 11. The method of claim 10, wherein the step of generating the OCV change information depending on the SOC of the battery based on the voltage change function depending on the charge / discharge rate of the battery and the voltage change information depending on the SOC of the battery comprises classifying the voltage change information depending on the SOC of the battery into charge data and discharge data for each SOC of the battery, and applying the charge data and discharge data for each SOC of the battery and the quadratic term coefficient to an interpolation method to calculate the voltage change information depending on the charge / discharge rate of the battery for each SOC.

12. 12. The method of claim 11, wherein the step of generating the OCV change information depending on the SOC of the battery based on the voltage change function depending on the charge / discharge rate of the battery and the voltage change information depending on the SOC of the battery comprises extracting an OCV, which is a voltage value of the battery when the charge / discharge rate of the battery is “0”, from the voltage change information depending on the charge / discharge rate of the battery by SOC, and calculating the OCV by SOC of the battery.

13. 13. The method of claim 12, wherein the step of generating information about OCV change depending on the SOC of the battery based on a voltage change function depending on the charge / discharge rate of the battery and information about voltage change depending on the SOC of the battery comprises inputting the SOC-specific OCV of the battery to a window filter to smooth it, thereby generating information about OCV change depending on the SOC of the battery.

Images