Battery capacity prediction device and operation method thereof

Abstract

According to one embodiment of the present disclosure, the battery capacity prediction device may include an extraction unit that extracts comparison data that compares a measured capacity of the battery with a reference capacity of the battery, and extracts capacity change data that measures a capacity change of the battery due to cycle changes of the battery, and a controller that predicts the capacity of the battery based on the comparison data and the capacity change data.

Description

[Technical field]

[0001] [CROSS REFERENCE TO RELATED APPLICATIONS] The embodiments disclosed in this document claim the benefit of priority based on Korean Patent Application No. 10-2022-0003018 filed on January 7, 2022, and all contents disclosed in the documents of that Korean patent application are incorporated herein by reference.

[0002] SUMMARY OF THE DISCLOSURE The embodiments disclosed herein relate to a battery capacity prediction apparatus and method of operation. [Background technology]

[0003] 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 obtain power. The battery cells of an electric vehicle may generate heat due to chemical reactions that occur during the process of charging and discharging electricity, and such heat may damage the performance and lifespan of the battery cells.

[0004] Battery cells age through repeated use and charging / discharging, gradually shortening their lifespan and reducing their capacity. The reduction in the capacity of a battery cell can vary depending on the operating temperature, charging current, discharging current and depth of discharge of the battery cell, and the capacity of a battery cell can decrease rapidly due to the reduction in the amount of positive or negative electrode material and lithium ions inside the battery cell. When the capacity of a battery cell decreases rapidly, it leads to a reduction in the available battery energy, reducing the utility of the battery and impairing the stability of the battery. Summary of the Invention [Problem to be solved by the invention]

[0005] One objective of the embodiments disclosed herein is to provide a battery capacity prediction device and an operating method thereof that can analyze the capacity loss of a battery in various temperature, current and voltage ranges and diagnose the rapid capacity loss phenomenon of the battery in advance.

[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] According to one embodiment disclosed herein, a battery capacity prediction device may include an extraction unit that extracts comparison data that compares a measured capacity of the battery with a reference capacity of the battery and extracts capacity change data that measures a capacity change of the battery due to cycle changes of the battery, and a controller that predicts the capacity of the battery based on the comparison data and the capacity change data.

[0008] According to an embodiment, the extracting unit may extract a comparison value obtained by comparing a measured capacity of the battery with a reference capacity of the battery measured through a Reference Performance Test (RPT).

[0009] According to an embodiment, the extractor may measure a change in the comparison value due to a change in temperature of the battery or a change in the comparison value due to a change in current of the battery.

[0010] According to one embodiment, the controller can predict the capacity of the battery at reference performance test conditions based on the capacity change data and the comparison value.

[0011] According to one embodiment, the controller may convert the reference capacity into a nominal capacity of the battery to predict the capacity of the battery under a full equivalent cycle (FEC) condition.

[0012] According to one embodiment, the controller can extract a capacity change pattern of the battery based on the capacity of the battery under the equivalent cycle condition.

[0013] According to an embodiment, the controller may extract a capacity change pattern of the battery and analyze a capacity change pattern immediately after a reference performance test of the battery, a normal capacity change pattern, and a rapid capacity deterioration pattern.

[0014] An operating method of a battery capacity prediction device according to one embodiment disclosed herein includes steps of comparing a measured capacity of the battery to a reference capacity of the battery to extract comparison data, measuring a capacity change of the battery due to cycle changes of the battery, and predicting the capacity of the battery based on the comparison data and the capacity change data.

[0015] According to one embodiment, the step of comparing the measured capacity of the battery to a reference capacity of the battery and extracting comparison data may extract a comparison value by comparing the measured capacity of the battery to a reference capacity of the battery measured through a Reference Performance Test (RPT).

[0016] According to one embodiment, the step of comparing the measured capacity of the battery to the reference capacity of the battery to extract comparison data may measure a change in the comparison value due to a change in temperature of the battery or a change in the comparison value due to a change in current of the battery.

[0017] According to one embodiment, the step of predicting the capacity of the battery based on the comparison data and the capacity change data may predict the capacity of the battery under standard performance test conditions based on the capacity change data and the comparison value.

[0018] According to one embodiment, the step of predicting the capacity of the battery based on the comparison data and the capacity change data may predict the capacity of the battery under full equivalent cycle (FEC) conditions by converting the reference capacity into a nominal capacity of the battery.

[0019] According to an embodiment, predicting the capacity of the battery based on the comparison data and the capacity change data may extract a capacity change pattern of the battery based on the capacity of the battery under the equivalent cycle condition.

[0020] According to one embodiment, the step of predicting the capacity of the battery based on the comparison data and the capacity change data may include extracting a capacity change pattern of the battery and analyzing a capacity change pattern immediately after a reference performance test of the battery, a normal capacity change pattern, and a rapid capacity degradation pattern. Effect of the Invention

[0021] According to an embodiment of a battery capacity prediction device and an operating method thereof disclosed in this document, it is possible to provide a battery capacity prediction device and an operating method thereof that can diagnose a rapid capacity reduction phenomenon of a battery in advance by analyzing the capacity reduction of a battery in various temperature, current and voltage ranges. [Brief description of the drawings]

[0022] [Figure 1] FIG. 1 illustrates a battery pack according to one embodiment disclosed herein. [Diagram 2]1 is a block diagram showing a configuration of a battery capacity prediction device according to an embodiment disclosed in this document; [Diagram 3] 1 is a graph showing the change in capacity data and the change in baseline capacity data of a battery due to cycling of the battery according to one embodiment disclosed herein; [Figure 4a] 1 is a graph showing the change in comparison value with temperature change of a battery according to one embodiment described herein. [Figure 4b] 1 is a graph showing the change in comparison value with the change in current of a battery according to one embodiment described herein. [Diagram 5] 1 is a graph showing the change in capacity fade per cycle of a battery due to cycling of the battery according to an embodiment described herein; [Figure 6a] 1 is a graph showing a capacity change pattern of a battery according to an equivalent cycle change of a battery according to an embodiment described herein. [Figure 6b] 1 is a graph showing the capacity change of a battery with equivalent cycle change according to an embodiment described herein. [Figure 7] 1 is a flowchart illustrating a method of operation of a battery capacity prediction device according to one embodiment disclosed herein. [Figure 8] 1 is a block diagram showing a hardware configuration of a computer system implementing a battery capacity prediction device according to an embodiment disclosed herein; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Some embodiments disclosed in this document will be described in detail below with reference to exemplary drawings. When attaching reference numerals to components in each drawing, it should be noted that the same components are given the same numerals as much as possible even if they are displayed in different drawings. In addition, when describing the embodiments disclosed in this document, if a detailed description of related known configurations or functions is determined to hinder understanding of the embodiments disclosed in this document, the detailed description will be omitted.

[0024] In describing the components of the embodiments disclosed in this document, terms such as first, second, A, B, (a), (b) and the like can be used. Such terms are used only to distinguish the components from other components, and do not limit the essence, order, or sequence of the components. In addition, 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 in this document belong. Terms as defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning they have in the context of the relevant art, and should not be interpreted as being ideal or overly formal unless expressly defined in this document.

[0025] FIG. 1 illustrates a battery pack according to one embodiment disclosed herein.

[0026] As shown in FIG. 1 , a battery pack 1000 according to an embodiment disclosed in this document may include a battery module 100, a battery capacity prediction device 200, and a relay 300.

[0027] The battery module 100 may include a number of battery cells 110, 120, 130, and 140. In FIG. 1, the number of battery cells is illustrated as four, but this is not limited thereto, and the battery module 100 may be configured to include n (n is a natural number equal to or greater than 2) battery cells.

[0028] The battery module 100 can supply power to a target device (not shown). To this end, the battery module 100 may be electrically connected to the target device. Here, the target device may 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, and for example, the target device may be, but is not limited to, an electric vehicle (EV) or an energy storage system (ESS).

[0029] The battery cells 110, 120, 130, 140 are basic units of a battery that can charge and discharge electrical energy, and may be, but are not limited to, a lithium-ion (Li-ion) battery, a lithium-ion polymer (Li-ion polymer) battery, a nickel-cadmium (Ni-Cd) battery, a nickel-metal hydride (Ni-MH) battery, etc. Meanwhile, although FIG. 1 illustrates a case in which there is one battery module 100, there may be a plurality of battery modules 100 according to an embodiment.

[0030] The battery capacity prediction device 200 can predict the capacity of the plurality of battery cells 110, 120, 130, 140 based on temperature, current, and voltage data of the plurality of battery cells 110, 120, 130, 140. The battery capacity prediction device 200 can predict the capacity of the plurality of battery cells 110, 120, 130, 140 for each temperature, current, and voltage of the battery based on battery data of the plurality of battery cells 110, 120, 130, 140.

[0031] According to an embodiment, the battery capacity prediction apparatus 200 may be implemented in the form of a battery management system (BMS). Also, according to an embodiment, the battery capacity prediction apparatus 200 may be installed in the battery management system.

[0032] Here, the battery management device may manage and / or control the state and / or operation of the battery module 100. For example, the battery management device may manage and / or control the state and / or operation of the multiple battery cells 110, 120, 130, and 140 included in the battery module 100. The battery management device may manage charging and / or discharging of the battery module 100.

[0033] In addition, the battery management device may 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. In addition, sensors and various measurement modules (not shown) for monitoring by the battery management device may be additionally installed in the battery module 100, a charge / discharge path, or any position of the battery module 100. The battery management device may calculate parameters indicating the state of the battery module 100, such as a state of charge (SOC) or a state of health (SOH), based on the measured values ​​of the monitored voltage, current, temperature, etc.

[0034] The battery management unit can control the operation of the relay 300. For example, the battery management unit can short-circuit the relay 300 to supply power to a target device. In addition, the battery management unit can short-circuit the relay 300 when a charging device is connected to the battery pack 1000.

[0035] The battery management unit may calculate a cell balancing time for each of the battery cells 110, 120, 130, and 140. Here, the cell balancing time may be defined as a time required for balancing the battery cells. For example, the battery management unit may calculate the cell balancing time based on a state of charge (SOC), a battery capacity, and a balancing efficiency for each of the battery cells 110, 120, 130, and 140.

[0036] Hereinafter, the configuration and operation of the battery capacity prediction device 200 will be described in detail.

[0037] FIG. 2 is a block diagram showing a configuration of a battery capacity prediction device according to an embodiment disclosed in this document.

[0038] Hereinafter, the configuration of the battery capacity prediction device 200 will be described in detail with reference to FIG.

[0039] First, as shown in FIG. 2 , a battery capacity prediction device 200 may include an extractor 210 and a controller 220 .

[0040] The extracting unit 210 may acquire capacity data (C) by measuring the capacity of the plurality of battery cells 110, 120, 130, and 140.

[0041] The extraction unit 210 measures the reference capacity of the plurality of battery cells 110, 120, 130, and 140 to obtain reference capacity data (C RPT) can be obtained. Here, the reference capacity is the capacity of the battery measured through a reference performance test (RPT). The reference performance test may periodically measure the life or capacity of the battery under conditions of a specific temperature, a specific current, and a specific voltage range in order to check the deterioration performance of the target device. According to one embodiment, the reference performance test may repeat charging and discharging under conditions of a specific temperature and a specific current from a voltage value at which the battery's SOC is 0% to a voltage value at which the battery's SOC is 100%.

[0042] 3 is a graph showing a change in capacity data and a change in reference capacity data of a battery according to a cycle change of the battery according to an embodiment disclosed herein. As shown in FIG. 3, the extracting unit 210 extracts reference capacity data (C RPT ) to the measured capacity data (C) of the plurality of battery cells 110, 120, 130, 140 to obtain a reference capacity (C RPT ) of the plurality of battery cells 110, 120, 130, 140 may be compared to extract comparison data. RPT ) Comparison of measured capacities (C) of multiple battery cells 110, 120, 130, and 140 (C / C RPT ) can be extracted.

[0043] Figure 4a is a graph showing the change in the comparison value due to the temperature change of a battery according to an embodiment described herein, and Figure 4b is a graph showing the change in the comparison value due to the current change of a battery according to an embodiment described herein.

[0044] 4a and 4b, the extractor 210 may generate a graph showing a change in the comparison value due to a change in temperature of the battery cells 110, 120, 130, and 140. In addition, the extractor 210 may generate a graph showing a change in the comparison value (C / C RPT The extraction unit 210 may generate a graph showing a change in the comparison value (C / C) according to a change in temperature of the battery cells 110, 120, 130, and 140 or a change in current of the battery cells 110, 120, 130, and 140. RPT ) to obtain a comparison value (C / C) according to the temperature change of the battery cells 110, 120, 130, and 140. RPT ) or the comparison value due to the change in battery current (C / C RPT ) trends can be measured.

[0045] The extracting unit 210 may measure the capacity change amount per cycle of the plurality of battery cells 110, 120, 130, 140 due to the cycle change of the plurality of battery cells 110, 120, 130, 140. That is, the extracting unit 210 may measure the capacity deterioration amount (ΔC) per cycle of the plurality of battery cells 110, 120, 130, 140 due to the cycle change of the plurality of battery cells 110, 120, 130, 140.

[0046] 5 is a graph illustrating a change in the amount of capacity degradation per cycle of a battery according to an embodiment described herein. As shown in FIG. 5, the extractor 210 may extract capacity change data measuring a change in the capacity of the battery per cycle according to the cycle change of the plurality of battery cells 110, 120, 130, 140. For example, the extractor 210 may extract capacity change data measuring a change in the capacity of the battery per cycle according to the cycle change of the plurality of battery cells 110, 120, 130, 140 when the number of cycle repetitions is n, where C n The capacities of the battery cells 110, 120, 130, and 140 before the kth cycle are denoted by C n―kWhen the capacity degradation amount per cycle of the battery cells 110, 120, 130, and 140 is defined as ΔC=C n -C n―k It can be calculated as follows.

[0047] The extraction unit 210 calculates the capacity deterioration amount (C n ) can be extracted.

[0048] The controller 220 can predict the capacity of the plurality of battery cells 110, 120, 130, 140 based on the comparison data and the capacity change data. Specifically, the controller 220 can predict the capacity change of the plurality of battery cells 110, 120, 130, 140 under the reference performance test condition based on the capacity change data and the comparison value.

[0049] The controller 210 calculates the reciprocal of the comparison value (C RPT / C) to obtain Equation 1.

number

[0050] The controller 220 can predict the capacity of the multiple battery cells under full equivalent cycle (FEC) conditions by converting the reference capacity of the multiple battery cells 110, 120, 130, 140 under the predicted reference performance test conditions into a nominal capacity of the multiple battery cells.

[0051] The controller 220 is configured to compare the capacity degradation per cycle (ΔC) values ​​of the plurality of battery cells 110, 120, 130, 140 under the reference performance test conditions with the measured capacity (C) of the plurality of battery cells 110, 120, 130, 140 versus the nominal capacity (C nominal ) was compared (C nominal / C) value to determine the capacity deterioration ((ΔC)) of the multiple battery cells 110, 120, 130, and 140 under the equivalent cycle (FEC) condition. FEC ) can be calculated.

number

[0052] Here, the controller 220 detects the small capacity deterioration ((ΔC) FEC ) the value of k can be chosen to be a multiple.

[0053] The controller 220 can extract a capacity change pattern of the battery based on the capacity of the battery under the equivalent cycle condition.

[0054] 6a is a graph showing a capacity change pattern of a battery according to an embodiment described herein due to an equivalent cycle change of the battery. As shown in FIG. 6a, specifically, the controller 220 calculates the capacity deterioration amount ((ΔC)) of the multiple battery cells 110, 120, 130, 140 under the equivalent cycle (FEC) condition. FEC ) can be calculated.

[0055] The controller 220 may extract and analyze the capacity change patterns of the various battery cells 110, 120, 130, and 140, such as Pattern A, Pattern B, Pattern C, and Pattern D.

[0056] 6a, the pattern A calculated by the controller 220 is a pattern that appears when the deterioration rate of the multiple battery cells 110, 120, 130, 140 decreases, and may appear in a battery cycle immediately after a reference performance test of the multiple battery cells 110, 120, 130, 140. The controller 220 can analyze the pattern A as a capacity change pattern that appears when the temperature or current of the multiple battery cells 110, 120, 130, 140 differs.

[0057] 6a, the C pattern calculated by the controller 220 may be analyzed as a pattern that appears when the deterioration rate of the multiple battery cells 110, 120, 130, and 140 is constant. The controller 220 may analyze the C pattern as a capacity change pattern that appears when the Loss of Active Material (LAM) of the multiple battery cells 110, 120, 130, and 140 deteriorates linearly.

[0058] 6a, the pattern D calculated by the controller 220 may be analyzed as a pattern that appears when the deterioration rate of the battery cells 110, 120, 130, and 140 is accelerated. The controller 220 may analyze the pattern D as a pattern that appears when the capacity of the battery cells 110, 120, 130, and 140 is exponentially decreased due to a rapid decrease in lithium plating or electrolyte of the battery cells 110, 120, 130, and 140.

[0059] 6b is a graph showing a change in capacity of a battery according to an embodiment described herein, the controller 220 may collect the patterns of changes in capacity of the battery according to the equivalent cycle changes of the various batteries shown in FIG 6a and extract a graph showing a change in capacity of the battery according to the equivalent cycle changes of the battery.

[0060] The controller 220 can analyze the capacity change pattern of the multiple battery cells 110, 120, 130, 140 immediately after the reference performance test, the normal capacity change pattern of the multiple battery cells 110, 120, 130, 140, and the rapid capacity deterioration pattern of the multiple battery cells 110, 120, 130, 140 based on FIG. 6b.

[0061] As described above, according to an embodiment of the battery capacity prediction device 200 disclosed in this document, the battery capacity reduction in various temperature, current and voltage ranges can be analyzed to diagnose the rapid capacity reduction phenomenon of the battery in advance.

[0062] In addition, the battery capacity prediction device 200 can more accurately diagnose rapid capacity deterioration of the battery in advance, thereby improving the utility and stability of battery management. Furthermore, the battery capacity prediction device 200 can extract a capacity change pattern of the battery by defining a relationship between a reference capacity of the battery measured through a reference performance test and a deterioration cycle of the battery.

[0063] FIG. 7 is a flow chart illustrating a method of operation of a battery capacity prediction apparatus according to one embodiment disclosed herein.

[0064] Hereinafter, an operation method of the battery capacity prediction device 200 will be described with reference to FIGS. 1 to 6b.

[0065] The battery capacity prediction device 200 may be substantially the same as the battery capacity prediction device 200 described with reference to FIGS. 1 to 6b, and therefore will be described briefly below to avoid duplication of description.

[0066] As shown in FIG. 7, the operating method of the battery capacity prediction device 200 may include a step of comparing a measured capacity of the battery with a reference capacity of the battery to extract comparison data (S101), a step of measuring a capacity change of the battery due to cycle changes of the battery (S102), and a step of predicting the capacity of the battery based on the comparison data and the capacity change data (S103).

[0067] In step S101, the extraction unit 210 measures the reference capacity of the plurality of battery cells 110, 120, 130, and 140 to obtain reference capacity data (C RPT ) can be obtained. Here, the reference capacity is the capacity of the battery measured through a reference performance test (RPT). The reference performance test may periodically measure the life or capacity of the battery under conditions of a specific temperature, a specific current, and a specific voltage range in order to check the deterioration performance of the target device. According to one embodiment, the reference performance test may repeat charging and discharging under conditions of a specific temperature and a specific current from a voltage value at which the battery's SOC is 0% to a voltage value at which the battery's SOC is 100%.

[0068] In step S101, the extraction unit 210 extracts reference capacity data (C RPT ) to the measured capacity data (C) of the plurality of battery cells 110, 120, 130, 140, and obtain a reference capacity (C RPT ) Comparison data can be extracted by comparing the measured capacities (C) of the multiple battery cells 110, 120, 130, 140.

[0069] In step S101, the extracting unit 210 extracts the reference capacity (C RPT ) Comparison value (C / C) comparing the measured capacities (C) of multiple battery cells 110, 120, 130, and 140 RPT ) can be extracted.

[0070] In step S101, the extraction unit 210 may generate a graph showing a change in the comparison value according to a change in temperature of the battery cells 110, 120, 130, and 140. In step S101, the extraction unit 210 may generate a graph showing a change in the comparison value according to a change in current of the battery cells 110, 120, 130, and 140 (C / C RPT In step S101, the extraction unit 210 may generate a graph showing a change in the comparison value (C / C RPT ) and compare the temperature changes of the battery cells 110, 120, 130, and 140 (C / C RPT ) or the comparison value due to the change in battery current (C / C RPT ) trends can be measured.

[0071] In step S102, the extraction unit 210 may measure a capacity change amount per cycle of the plurality of battery cells 110, 120, 130, 140 due to a cycle change of the plurality of battery cells 110, 120, 130, 140. In step S102, the extraction unit 210 may measure a capacity deterioration amount (ΔC) per cycle of the plurality of battery cells 110, 120, 130, 140 due to a cycle change of the plurality of battery cells 110, 120, 130, 140.

[0072] In step S103, the controller 220 can predict the capacity of the plurality of battery cells 110, 120, 130, 140 based on the comparison data and the capacity change data. In step S103, the controller 220 can predict the capacity change of the plurality of battery cells 110, 120, 130, 140 under the reference performance test condition based on the capacity change data and the comparison value.

[0073] In step S103, the controller 210 calculates the reciprocal of the comparison value (C RPT / C) to obtain Equation 3.

number

[0074] In step S103, the controller 220 can predict the capacity of the plurality of battery cells under full equivalent cycle (FEC) conditions by converting the reference capacity of the plurality of battery cells 110, 120, 130, 140 under the predicted reference performance test conditions into a nominal capacity of the plurality of battery cells.

[0075] In step S103, the controller 220 compares the capacity deterioration amount (ΔC) per cycle of the plurality of battery cells 110, 120, 130, 140 under the reference performance test condition with the measured capacity (C) of the plurality of battery cells 110, 120, 130, 140 and the nominal capacity (C nominal ) was compared (C nominal / C) value to determine the capacity deterioration ((ΔC)) of the multiple battery cells 110, 120, 130, and 140 under the equivalent cycle (FEC) condition. FEC ) can be calculated.

[0076] In step S103, the controller 220 can extract a capacity change pattern of the battery based on the capacity of the battery under the equivalent cycle condition.

[0077] In step S103, the controller 220 may collect a pattern of a capacity change of the battery according to an equivalent cycle change of the battery, and extract a graph showing a capacity change of the battery according to an equivalent cycle change of the battery.

[0078] In step S103, the controller 220 can analyze the capacity change pattern of the multiple battery cells 110, 120, 130, 140 immediately after the reference performance test, the normal capacity change pattern of the multiple battery cells 110, 120, 130, 140, and the rapid capacity deterioration pattern of the multiple battery cells 110, 120, 130, 140.

[0079] FIG. 8 is a block diagram illustrating a hardware configuration of a computer system that implements a battery capacity prediction device according to an embodiment disclosed herein.

[0080] As shown in FIG. 8, a computer system 2000 according to an embodiment disclosed in this document may include an MCU 2100, a memory 2200, an input / output I / F 2300, and a communication I / F 2400.

[0081] The MCU 2100 may be a processor that executes various programs (e.g., battery capacity prediction functions) stored in the memory 2200, processes various data through such programs, and performs the functions of the battery capacity prediction device 200 shown in FIG. 1 described above.

[0082] The memory 2200 can store various programs related to the operation of the equipment control device 200. The memory 2200 can also store operation data for the equipment control device 200.

[0083] A plurality of such memories 2200 may be provided as necessary. The memory 2200 may be a volatile memory or a non-volatile memory. The memory 2200 as a volatile memory may be a RAM, a DRAM, an SRAM, or the like. The memory 2200 as a non-volatile memory may be a ROM, a PROM, an EAROM, an EPROM, an EEPROM, a flash memory, or the like. The examples of the memory 2200 listed above are merely illustrative and are not limited to these examples.

[0084] 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 to transmit and receive data.

[0085] The communication I / F 2400 is configured to be capable of transmitting and receiving various data to and from a server, and may be any of various devices capable of supporting wired or wireless communication. For example, programs for resistance measurement and abnormality diagnosis, various data, and the like can be transmitted and received from a separately provided external server via the communication I / F 2400.

[0086] In this manner, a computer program according to one embodiment disclosed in the present document may be recorded in memory 2200 and processed by MCU 2100 to be embodied as a module performing each function of battery capacity prediction device 200 described with reference to Figures 1 and 2, for example.

[0087] The above description is merely an illustrative example of the technical ideas of the present disclosure, and a person having ordinary knowledge in the technical field to which the present disclosure pertains would be able to make various modifications and variations without departing from the essential characteristics of the present disclosure.

[0088] Therefore, the embodiments disclosed in this disclosure are intended to explain, not to limit, the technical idea of ​​the disclosure, and such embodiments do not limit the scope of the technical idea of ​​the disclosure. The scope of protection of the disclosure should be interpreted according to the following claims, and all technical ideas within the scope equivalent thereto should be interpreted as being included in the scope of rights of the disclosure.

Claims

1. an extracting unit that extracts comparison data that compares a measured capacity of the battery with a reference capacity of the battery, and extracts capacity change data that measures a capacity change of the battery due to a cycle change of the battery; and a controller for predicting a capacity of the battery based on the comparison data and the capacity change data.

2. The device of claim 1 , wherein the extracting unit extracts a comparison value by comparing a measured capacity of the battery with a reference capacity of the battery measured through a reference performance test.

3. The battery capacity prediction device according to claim 2 , wherein the extracting unit measures at least one of a change in the comparison value caused by a temperature change of the battery, or a change in the comparison value caused by a current change of the battery.

4. The battery capacity prediction device according to claim 3 , wherein the controller predicts the capacity of the battery under a reference performance test condition based on the capacity change data and the comparison value.

5. The battery capacity prediction device according to claim 1 , wherein the controller predicts the capacity of the battery under an equivalent cycle condition by converting a reference capacity of the battery into a nominal capacity of the battery.

6. The battery capacity prediction device according to claim 5 , wherein the controller extracts a capacity change pattern of the battery based on the capacity of the battery under the equivalent cycle condition.

7. The battery capacity prediction device according to claim 6 , wherein the controller extracts a capacity change pattern of the battery and analyzes a capacity change pattern immediately after a reference performance test of the battery, a normal capacity change pattern, and a rapid capacity deterioration pattern.

8. comparing a measured capacity of the battery to a reference capacity of the battery to extract comparison data; Measuring capacity change data of the battery due to cycle changes of the battery; and predicting the capacity of the battery based on the comparison data and the capacity change data.

9. 9. The method of claim 8, wherein the step of comparing the measured capacity of the battery to a reference capacity of the battery and extracting comparison data comprises extracting a comparison value obtained by comparing the measured capacity of the battery to a reference capacity of the battery measured through a reference performance test.

10. 10. The method of claim 9, wherein the step of comparing the measured capacity of the battery to a reference capacity of the battery to extract comparison data comprises measuring at least one of a change in the comparison value due to a change in temperature of the battery or a change in the comparison value due to a change in current of the battery.

11. predicting the capacity of the battery based on the comparison data and the capacity change data, The method of claim 10, further comprising predicting a capacity of the battery under a reference performance test condition based on the capacity change data and the comparison value.

12. predicting the capacity of the battery based on the comparison data and the capacity change data, The method for operating the battery capacity prediction device according to any one of claims 8 to 11, further comprising converting the reference capacity of the battery into a nominal capacity of the battery to predict the capacity of the battery under an equivalent cycle condition.

13. predicting the capacity of the battery based on the comparison data and the capacity change data, The method for operating a battery capacity prediction device according to claim 12, further comprising extracting a capacity change pattern of the battery based on the capacity of the battery under the equivalent cycle condition.

14. predicting the capacity of the battery based on the comparison data and the capacity change data, The method of claim 13, further comprising extracting a capacity change pattern of the battery and analyzing a capacity change pattern immediately after a reference performance test of the battery, a normal capacity change pattern, and a rapid capacity deterioration pattern.

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