Battery device and method for predicting battery output

Abstract

A battery device estimates a surface SOC that represents a potential of an electrode surface of a battery, and predicts an output of the battery during a request time based on the surface SOC, a cut-off voltage, and the request time.

Description

TECHNICAL FIELD

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to and the benefit of Korean Patent Application No. 10-2020-0127981, filed on October 5, 2020, in the Korean Intellectual Property Office, the entire contents of which are incorporated herein by reference.

[0003] The described technology relates to a battery device and method for predicting a battery output. BACKGROUND

[0004] An electric vehicle or a hybrid vehicle is a vehicle that obtains power through a driving motor mainly using a battery as a power source. Electric vehicles are being actively researched as alternatives that can solve the pollution and energy problems of internal combustion vehicles. A rechargeable battery is used in various external devices other than electric vehicles.

[0005] In order to use a battery in various external devices, it is necessary to predict the output of the battery. A battery management system pre-stores a maximum output power (a maximum discharge current or a maximum charge current) for a predetermined time based on a state of charge (SOC) of the battery and a temperature of the battery, and provides an output power based on the maximum output power corresponding to a current SOC and a current temperature in response to a request from an external device.

[0006] However, in the case of using a previously stored value, if an external device requests an output power at a time that is not stored, the output power cannot be provided. In addition, even if the SOC and the temperature are in the same state, the output power of a battery in a static state for a predetermined time can be different from that of a battery in a dynamic state of repeated charging or discharging. Therefore, when an external device requests an output power for a predetermined time, a method is needed to predict an output power for a request time based on a current state of the battery. SUMMARY

[0007] TECHNICAL PROBLEM

[0008] Some embodiments can provide a battery device and method for predicting a battery output to predict an output during any time.

[0009] TECHNICAL SOLUTION

[0010] According to one embodiment, a battery device including a battery and a processor can be provided. The processor can estimate a surface state of charge (SOC) representing a potential of an electrode surface of the battery as a first surface SOC, and predict a battery output during a request time based on the first surface SOC, a cutoff voltage, and the request time.

[0011] In some embodiments, the processor can determine the surface SOC of the battery when the terminal voltage of the battery becomes the cut-off voltage as a second surface SOC, estimate the current of the battery to allow estimation of the second surface SOC from the first surface SOC after the request time, and predict the output based on the current estimation.

[0012] In some embodiments, the processor can determine the open-circuit voltage of the battery when the terminal voltage of the battery becomes the cut-off voltage, and determine the second surface SOC based on the open-circuit voltage.

[0013] In some embodiments, the processor can estimate the current of the battery to allow estimation of the second surface SOC from the first surface SOC after the request time, and predict the output based on the current of the battery. In this case, the terminal voltage of the battery determined based on the second surface SOC and the current can be the cut-off voltage.

[0014] In some embodiments, the terminal voltage can be determined based on the open-circuit voltage of the battery corresponding to the second surface SOC and the voltage corresponding to the current.

[0015] In some embodiments, the terminal voltage can be determined based on the open-circuit voltage of the battery, the voltage corresponding to the current, and the overpotential of the battery.

[0016] In some embodiments, the processor can determine the cut-off voltage based on the temperature of the battery.

[0017] In some embodiments, the processor can reduce the predicted output in response to the battery voltage corresponding to the predicted output reaching the derated voltage.

[0018] In some embodiments, the processor can estimate the first surface SOC based on a plurality of parameters including a first parameter determined based on the measured current of the battery and a second parameter determined based on the SOC of the battery.

[0019] According to another embodiment, a method of predicting an output of a battery can be provided. The method can include estimating a state of the battery, and predicting an output of the battery during a request time based on the state of the battery, a cut-off voltage, and the request time.

[0020] In some embodiments, the state of the battery can include a surface SOC representing a potential of an electrode surface of the battery.

[0021] In some embodiments, predicting the output of the battery can include estimating a current of the battery to allow estimation of a specific surface SOC from the estimated surface SOC after the request time, and predicting the output based on the current. In this case, the terminal voltage of the battery determined based on the specific surface SOC and the current can be the cut-off voltage.

[0022] In some embodiments, the terminal voltage can be determined based on an open circuit voltage of the battery corresponding to a particular surface SOC and a voltage corresponding to a current.

[0023] In some embodiments, estimating the state of the battery can include estimating a surface SOC based on a plurality of parameters including a first parameter determined based on a measured current of the battery and a second parameter determined based on an SOC of the battery.

[0024] According to still another embodiment, a program configured to be executed by a processor of a battery device and stored in a recording medium can be provided. The program can cause the processor to perform estimating a state of a battery and predicting an output of the battery during a requested time based on the state of the battery, a cut-off voltage, and the requested time.

[0025] Advantageous Effects

[0026] According to some embodiments, the power that the battery can provide during an external device requested time can be accurately predicted and provided in real time. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 FIG. 1 is a diagram illustrating a battery device according to an embodiment.

[0028] Figure 2 FIG. 2 is a diagram illustrating a structure of a battery according to an embodiment.

[0029] Figure 3 FIG. 3 is a diagram illustrating an example of a state change of a battery.

[0030] Figure 4 FIG. 4 is a diagram for explaining surface SOC estimation in a battery management system according to an embodiment.

[0031] Figure 5 FIG. 5 is a diagram illustrating an example of a correspondence between a temperature / SOC and a kinetic coefficient in a battery according to an embodiment.

[0032] Figure 6 FIG. 6 is a diagram illustrating an example of a correspondence between a temperature / SOC and a diffusion coefficient in a battery according to an embodiment.

[0033] Figure 7 FIG. 7 is a flowchart illustrating a surface SOC estimation method in a battery management system according to an embodiment.

[0034] Figure 8 FIG. 8 is a diagram for explaining battery terminal voltage estimation in a battery management system according to an embodiment.

[0035] Figure 9 FIG. 9 is a flowchart illustrating a battery terminal voltage estimation method in a battery management system according to an embodiment.

[0036] Figure 10 FIG. 1 is a graph showing an example of a correspondence relationship between an SOC and an open-circuit voltage in a battery according to an embodiment.

[0037] Figure 11 FIG. 2 is a graph for explaining a battery output prediction in a battery management system according to an embodiment.

[0038] Figure 12 FIG. 3 is a flowchart showing a battery output prediction method in a battery management system according to an embodiment.

[0039] Figure 13 FIG. 4 is a graph for explaining a battery output prediction in a battery management system according to another embodiment.

[0040] Figure 14 FIG. 5 is a flowchart showing a battery output prediction method in a battery management system according to another embodiment. DETAILED DESCRIPTION

[0041] In the following detailed description, certain embodiments are shown and described by way of illustration only. As those skilled in the art will recognize, the described embodiments can be modified in various different ways without departing from the spirit or scope of the application. Accordingly, the drawings and description are to be regarded as illustrative in nature and not restrictive. Like reference numerals designate like elements throughout the specification.

[0042] When it is described that an element is "connected" to another element, it should be understood that the element can be directly connected to the other element or connected to the other element through a third element. On the other hand, when it is described that an element is "directly connected" to another element, it should be understood that the element is not connected to the other element through a third element.

[0043] As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0044] In the flowcharts described with reference to the accompanying drawings, the order of the operations or steps can be changed, several operations or steps can be merged, a certain operation or step can be divided into several operations or steps, and a certain operation or step can not be performed.

[0045] Figure 1 FIG. 6 is a graph showing a battery device according to an embodiment, Figure 2 FIG. 7 is a graph showing a structure of a battery according to an embodiment, and Figure 3 FIG. 8 is a graph showing an example of a state change in a battery.

[0046] Reference Figure 1The battery device 100 has a structure that can be electrically connected to an external device. When the external device is a load, the battery device 100 is discharged by operating as a power source that supplies power to the load. When the external device is a charger, the battery device 100 is charged by receiving external power through the charger. The external device operating as a load can be, for example, an electronic device, a mobile device, or an energy storage system (ESS). The mobile device can be, for example, a vehicle such as an electric vehicle, a hybrid vehicle, or a smart mobile device.

[0047] The battery device 100 includes a battery 110, a voltage measurement circuit 120, a temperature sensor 130, a current sensor 140, and a processor 150.

[0048] The battery 110 is a rechargeable battery. The battery 110 can be, for example, a lithium battery such as a lithium-ion battery or a lithium-ion polymer battery, or a nickel battery such as a nickel-cadmium (NiCd) battery or a nickel-metal hydride (NIMH) battery. In some embodiments, the battery 110 can be a single battery cell, an assembly including a plurality of battery cells, a battery module in which a plurality of assembly is connected in series or in parallel, a battery pack in which a plurality of battery modules is connected in series or in parallel, or a system in which a plurality of battery packs is connected in series or in parallel.

[0049] The voltage measurement circuit 120 measures the voltage of the battery 110. In some embodiments, the voltage measurement circuit 120 can measure the voltage of each battery cell.

[0050] The temperature sensor 130 measures the temperature of the battery 110. In some embodiments, the temperature sensor 130 can measure the temperature at a predetermined position of the battery 110. In some embodiments, a plurality of temperature sensors 130 can be provided to measure the temperature at a plurality of positions in the battery 110.

[0051] The current sensor 140 is connected to the positive or negative output terminal of the battery 110 and measures the current of the battery 110, i.e., the charging current or the discharging current.

[0052] The processor 150 estimates the state of the battery 110 based on the voltage of the battery 110 measured by the voltage measurement circuit 120, the temperature of the battery 110 measured by the temperature sensor 130, or the current of the battery 110 measured by the current sensor 140. In some embodiments, the battery device 100 can further include a memory 160 that stores data required for state estimation in the processor 150.

[0053] In some embodiments, the processor 150 can form a battery management system. In some embodiments, the battery management system can further include at least one of the voltage measurement circuit 120, the temperature sensor 130, or the current sensor 140.

[0054] Referring to Figure 2 , the battery 110 includes a positive electrode 111, a negative electrode 112, and an electrolyte 113. Figure 2 The structure of the battery 110 illustrated is a schematic example for convenience of description, and the structure of the battery 110 is not limited thereto. In Figure 2 , for convenience of description, it is assumed that lithium is an active material that causes a chemical reaction in the battery 110.

[0055] When the battery 110 is discharged to supply power from the battery 110 to an external device, as Figure 2 illustrated, a chemical reaction (oxidation reaction) in which lithium ions Li + are discharged from the negative electrode 112 can occur on the surface of the negative electrode 112. The discharged lithium ions Li + may pass through the electrolyte 113 and then move to the surface of the positive electrode 111. Accordingly, a chemical reaction (reduction reaction) in which lithium ions Li + are absorbed into the positive electrode 111 can occur on the surface of the positive electrode 111.

[0056] When the battery 110 is charged, a chemical reaction (oxidation reaction) in which lithium ions Li + are discharged from the positive electrode 111 can occur on the boundary surface between the positive electrode 111 and the electrolyte 113. The discharged lithium ions Li + may pass through the electrolyte 113 and then move to the surface of the negative electrode 112. Accordingly, a chemical reaction (reduction reaction) in which lithium ions Li + are absorbed into the negative electrode 112 can occur on the surface of the negative electrode 112.

[0057] The terminal voltage of the battery 110 can be expressed as the sum of the potential of the battery electrode surface corresponding to the positive electrode 111 and the negative electrode 112, the voltage drop caused by the ohmic resistance (internal resistance) formed by the electrolyte 113 or the like, and the overpotential caused by the electrochemical reaction. The overpotential can indicate a voltage drop that deviates from the equilibrium potential due to polarization at each battery electrode. The overpotential is also called polarization voltage.

[0058] As Figure 3 illustrated, when the battery 110 starts discharging, the terminal voltage Vt of the battery 110 instantaneously decreases due to the voltage drop Vohmic of the ohmic resistance Rohmic and then gradually decreases due to the instantaneous change V1 of the overpotential. In general, the instantaneous change V1 of the overpotential can be expressed as a change depending on a time constant defined in a parallel circuit of a resistor and a capacitor. At this time, the actual terminal voltage Vt of the battery 110 decreases with a constant slope together with the instantaneous change V1 of the overpotential. That is, as Figure 3As shown, the decrease in Vk according to a constant slope and the decrease in V1 according to the instantaneous change in overpotential occur together. This slope is determined by the magnitude of the current flowing through the battery 110. As described above, because the concentration of active material on the electrode surface is lower than the average concentration due to the oxidation / reduction reaction of the active material, the terminal voltage Vt of the battery 110 decreases at a certain slope. That is, the voltage change Vk according to a constant slope can occur through the voltage change caused by the oxidation / reduction reaction rate (the change due to discharge or charging) and the voltage change caused by diffusion resistance (concentration difference) during the relaxation period after the current disappears.

[0059] Typically, the state of battery 110 is determined as the state of charge (SOC), representing the average concentration throughout battery 110, and the terminal voltage Vt of battery 110 is estimated based on the open-circuit voltage of battery 110, the voltage drop (Vohmic) due to ohmic resistance, and overpotential. In this case, the open-circuit voltage is estimated based on the SOC of battery 110. However, SOC represents the average concentration within battery 110 (e.g., the average concentration at the electrodes) rather than the concentration on the surface of the battery electrodes, and it gradually decreases as battery 110 discharges, such as... Figure 3 As shown. Therefore, when estimating the open-circuit voltage of battery 110 based on SOC, the terminal voltage of battery 110 may not be accurately estimated. Therefore, in some embodiments, a surface state of charge (SOC) is provided that can determine the potential of the electrode surface of battery 110. Such a surface SOC can represent the concentration of active material on the electrode surface of battery 110.

[0060] Figure 4 This is a graph used to explain the surface SOC estimation in the battery management system according to an embodiment. Figure 5 This is a graph illustrating an example of the correspondence between temperature / SOC and kinetic coefficient in a battery according to an embodiment, and Figure 6 This is a graph illustrating an example of the correspondence between temperature / SOC and diffusion coefficient in a battery according to an embodiment.

[0061] refer to Figure 4 The processor of the battery management system (e.g., Figure 1 (150) can use the surface SOC estimation model 410 to estimate the battery (e.g., based on the measurement information of the battery 110, including the current of the battery 110) using the surface SOC estimation model 410. Figure 1 The surface SOC of battery 110 (in the context of battery 110). In some embodiments, the surface SOC may be estimated as a percentage. In some embodiments, processor 150 may use surface SOC estimation model 410 to estimate the SOC of battery 110 representing the average concentration based on measurements of the current of battery 110.

[0062] For reference Figure 3 As the battery 110 discharges, its terminal voltage can decrease at a certain slope. Because the concentration of active material on the electrode surface decreases due to the oxidation / reduction reaction of the active material, the terminal voltage of the battery 110 decreases at a certain slope, which is proportional to the current of the battery 110. Therefore, the surface SOC estimation model 410 can estimate the surface SOC based on the reaction rate determined by the current of the battery 110. In some embodiments, the reaction rate (kinetics) can be determined based on a value obtained by a specific coefficient reflecting the current of the battery 110. Hereinafter, this specific factor is referred to as the "kinetic coefficient". In one embodiment, the reaction rate can be determined based on the product of the current of the battery 110 and the kinetic coefficient.

[0063] The reaction rate of the oxidation / reduction reaction can be determined by the temperature of battery 110 and the average concentration within battery 110. Therefore, in some embodiments, the kinetic coefficients can vary depending on the temperature of battery 110 and the state of charge (SOC) of battery 110. In one embodiment, the SOC of battery 110 may include the SOC of battery 110 representing the average concentration. In another embodiment, the SOC of battery 110 may include the surface SOC of battery 110. In yet another embodiment, the SOC of battery 110 may include the SOC of battery 110 representing both the average concentration and the surface SOC. That is, the surface SOC estimation model 410 can determine the kinetic coefficients based on the temperature of battery 110 and the SOC of battery 110. In some embodiments, such as Figure 5 As shown, the correspondence between the temperature / SOC of battery 110 and the kinetic coefficient can be determined in advance through experiments. In some embodiments, the memory of the battery management system may store this correspondence, for example, in the form of a lookup table. In some embodiments, the surface SOC estimation model 410 may determine the kinetic coefficient based on the temperature or SOC of battery 110.

[0064] When the concentration on the electrode surface is lower than the average concentration caused by the oxidation / reduction reaction on the electrode surface, a resistance component can occur in which the diffusion rate caused by the concentration difference between the concentration on the electrode surface and the average concentration reduces the reaction on the electrode surface. This resistance caused by diffusion (hereinafter referred to as "diffusion resistance") can be expressed as a force that suppresses the oxidation / reduction reaction in the opposite direction. Accordingly, when estimating the surface SOC, the surface SOC estimation model 410 additionally reflects the diffusion resistance. In some embodiments, the diffusion resistance can be determined based on the difference between the SOC representing the average concentration and the surface SOC representing the concentration on the electrode surface. In some embodiments, the surface SOC estimation model 410 can estimate the surface SOC based on a value obtained by reflecting a certain coefficient to the difference between the SOC and the surface SOC. Hereinafter, such a certain coefficient is referred to as a "diffusion coefficient". In one embodiment, the surface SOC estimation model 410 can estimate the surface SOC based on the product of the diffusion coefficient and the difference between the SOC and the surface SOC.

[0065] The reaction rate of the oxidation / reduction reaction can be determined based on the temperature of the battery 110 and the average concentration within the battery 110. Accordingly, in some embodiments, the diffusion coefficient that suppresses the oxidation / reduction reaction can vary according to the temperature of the battery 110 and the SOC of the battery 110. In one embodiment, the SOC of the battery 110 can include the SOC of the battery 110 representing the average concentration. In another embodiment, the SOC of the battery 110 can include the surface SOC of the battery 110. In yet another embodiment, the SOC of the battery 110 can include the SOC of the battery 110 representing the average concentration and the surface SOC of the battery 110. That is, the surface SOC estimation model 410 can determine the diffusion coefficient based on the temperature of the battery 110 and the SOC of the battery 110. In some embodiments, as shown, the correspondence between the temperature / SOC of the battery 110 and the diffusion coefficient can be determined in advance through experiments. In some embodiments, the memory of the battery management system can store the correspondence, for example, in the form of a lookup table. In some embodiments, the surface SOC estimation model 410 can determine the diffusion coefficient based on the temperature of the battery 110 or the SOC of the battery 110. Figure 6

[0066] In some embodiments, the surface SOC estimation model 410 can estimate the surface SOC of the current time point by reflecting at least the surface SOC estimated at the previous time point to the change in the reaction rate from the previous time point to the current time point and to the change in the diffusion resistance from the previous time point to the current time point. In some embodiments, the processor 150 can predefine an initial value SSOC[0] of the surface SOC to estimate the surface SOC.

[0067] Figure 7 ​This is a flowchart illustrating a surface SOC estimation method in a battery management system according to an embodiment.

[0068] refer to Figure 7 In the S710, the processor (e.g., Figure 1 150 in the middle) will be the battery (e.g., Figure 1 The measurement information of battery 110 is input into the surface SOC estimation model. The measurement information of battery 110 may include the current of battery 110. In some embodiments, the current of battery 110 may be measured by a current sensor (e.g., Figure 1 The charging or discharging current of battery 110 is measured by (e.g., 140). In some embodiments, the measurement information of battery 110 may further include the measured voltage of battery 110. In some embodiments, the measured voltage of battery 110 may be the average cell voltage, and the average cell voltage may be the average of the voltages of multiple battery cells. In some embodiments, the measured voltage of battery 110 may be the sum of the voltages of multiple battery cells. In some embodiments, the measurement information of battery 110 may further include the temperature of battery 110. In some embodiments, the temperature of battery 110 may be measured by a temperature sensor (e.g., ...). Figure 1 The temperature measured at 130).

[0069] In S720 and S730, processor 150 uses a surface SOC estimation model to determine multiple parameters at time point t. These multiple parameters may include parameters corresponding to the reaction rate and parameters corresponding to diffusion resistance.

[0070] In S720, processor 150 uses a surface SOC estimation model to determine the reaction rate K[t] of battery 110 at time t. Processor 150 can calculate the reaction rate K[t] as the product of the kinetic coefficient Kc and the temperature of battery 110 at time t, Kc*I[t]. In some embodiments, processor 150 can retrieve the kinetic coefficient Kc corresponding to the temperature and SOC of battery 110 from memory. In some embodiments, the memory may be the memory of the battery management system (e.g., ...). Figure 1 (160 in the original text). In some embodiments, processor 150 may estimate the state of charge (SOC) of battery 110 based on measurement information of battery 110. In some embodiments, processor 150 may use any of a variety of known methods to estimate SOC, and the present invention is not limited to methods for estimating SOC.

[0071] Further, at S730, the processor 150 determines the diffusion resistance D[t] of the battery 110 at the time point t using the surface SOC estimation model. The processor 150 can calculate the diffusion resistance D[t] as a product Dc*ΔSOC[t] of the difference ΔSOC[t] between the SOC at the time point t and the surface SOC and the diffusion coefficient Dc. In some embodiments, the processor 150 can extract the diffusion coefficient Dc corresponding to the temperature of the battery 110 and the SOC of the battery 110 from the memory. In some embodiments, the memory can be the memory 160 of the battery management system.

[0072] Next, at S740, the processor 150 estimates the surface SOC SSOC[t+1] at the time point (t+1) based on the surface SOC SSOC[t] estimated at the time point t, the reaction rate K[t], and the diffusion resistance D[t] using the surface SOC estimation model. In some embodiments, the processor 150 can estimate the surface SOC SSOC[t+1] as in Equation 1 or 2.

[0073] [Equation 1]

[0074] SSOC[t+1] = SSOC[t] + (K[t] + D[t]) · Δt

[0075] [Equation 2]

[0076] SSOC[t+1] = SSOC[t] + (Kc · I[t] + Dc · ΔSOC[t]) · Δt

[0077] In Equations 1 and 2, Δt denotes a change in time (a time difference) between the time point (t+1) and the time point t.

[0078] In some embodiments, the surface SOC estimation model can accurately estimate the surface SOC by repeatedly performing estimation of the surface SOC. In some embodiments, an adaptive filter can be used as the surface SOC estimation model.

[0079] According to the above-described embodiments, the state of the battery 110 can be accurately estimated by using the surface SOC that can accurately represent the potential of the electrode surface of the battery 110.

[0080] Next, embodiments of estimating the terminal voltage of the battery 110 using the surface SOC are described with reference to Figure 8 , Figure 9 and Figure 10 .

[0081] Figure 8 is a graph for explaining estimation of a battery terminal voltage in a battery management system according to an embodiment, Figure 9This is a flowchart illustrating a battery terminal voltage estimation method in a battery management system according to an embodiment, and Figure 10 This is a diagram illustrating an example of the correspondence between SOC and open-circuit voltage in a battery according to an embodiment.

[0082] Reference Figure 8 and Figure 9 processor (e.g., Figure 1 150) uses a surface SOC estimation model (e.g., Figure 4 410) Estimate the surface SOC. That is, as referenced Figure 7 As mentioned above, the processor in S910 will send the battery ( Figure 1 The measurement information of cell 110 is input into surface SOC estimation model 410. The reaction rate K[t] and diffusion resistance D[t] of cell 110 are calculated in S920 and S930, and the surface SOC SSOC[t+1] is estimated based on the reaction rate K[t] and diffusion resistance D[t] in S940.

[0083] Next, the processor 150 inputs the SOC, surface SOC and current of the battery 110 to the terminal voltage estimation model 810, and uses the terminal voltage estimation model 810 to estimate the terminal voltage of the battery 110.

[0084] Therefore, in S950, processor 150 estimates the open-circuit voltage of battery 110 based on surface SOC. Processor 150 can estimate the open-circuit voltage of battery 110 based on surface SOC (SSOC) and open-circuit voltage (V). OC The nonlinear functional relationship between V OC =f(SSOC) to estimate the open-circuit voltage V OC Typically, the battery management system's memory (e.g., Figure 1 The 160) pre-stores the open-circuit voltage V of battery 110. OC The correspondence between the open-circuit voltage V and the state of charge (SOC) of battery 110. For example, the open-circuit voltage V. OC The correspondence between SOC and SOC can be defined as follows: Figure 10 As shown. In this case, the processor 150 determines the open-circuit voltage V by input surface SOC instead of SOC. OC For example, when the surface SOC is 70%, the processor 150 can retrieve the open-circuit voltage corresponding to the 70% SOC from memory. In some embodiments, the correspondence between open-circuit voltage and SOC can be stored at temperature. In this case, the processor 150 can determine the open-circuit voltage based on the correspondence between SOC and open-circuit voltage corresponding to the temperature of the battery 110 among various correspondences.

[0085] Further, at S960, the processor 150 estimates an overpotential due to polarization. Since the overpotential is caused by a deviation of the potential of the electrode surface from the equilibrium potential, the processor 150 estimates the overpotential based on the surface SOC representing the potential of the electrode surface and the SOC representing the equilibrium potential. In some embodiments, the processor 150 can estimate the overpotential based on a value obtained by comparing the SOC and the surface SOC. In one embodiment, the value obtained by comparing the SOC and the surface SOC can be a ratio of the SOC and the surface SOC. In another embodiment, the value obtained by comparing the SOC and the surface SOC can be a difference between the SOC and the surface SOC. In some embodiments, the processor 150 can estimate the overpotential V1[t+1] at a time point (t+1) based on the overpotential V1[t] at the time point t, the SOC SOC[t], and the surface SOC SSOC[t] using the terminal voltage estimation model 810. In some embodiments, the processor 150 can estimate the overpotential V1[t+1], for example, as in Equation 3.

[0086] [Equation 3]

[0087] V1[t+1] = V1[t] + a · (SOC[t] / SSOC[t])

[0088] In Equation 3, a denotes an overpotential coefficient.

[0089] In some embodiments, the overpotential coefficient a can be determined through experiments. In some embodiments, the overpotential coefficient a can be determined by repeatedly performing overpotential estimation using an adaptive filter. In some embodiments, the processor 150 can determine an initial value V1[0] of the overpotential for estimating the overpotential in advance.

[0090] Further, at S970, the processor 150 estimates a voltage due to the ohmic resistance of the battery 110. The processor 150 estimates the voltage Vohmic due to the ohmic resistance as a product of the ohmic resistance of the battery 110 and the current of the battery 110. In some embodiments, the processor 150 can estimate the ohmic resistance using any one of various known methods, and the present application is not limited to the method for estimating the ohmic resistance.

[0091] Next, at S980, the processor 150 determines the terminal voltage of the battery 110 based on the open-circuit voltage V OC , the overpotential VI, and the voltage Vohmic due to the ohmic resistance. In some embodiments, as shown in Equation 4, the processor 150 can determine the sum of the open-circuit voltage V OC , the overpotential VI, and the voltage Vohmic as the terminal voltage Vt of the battery 110 through the ohmic resistance.

[0092] [Equation 4]

[0093] Vt = Voc + V1 + Vohmic

[0094] Although the surface SOC estimation method or the terminal voltage estimation method has been described in the case of battery discharge, the surface SOC estimation method or the terminal voltage estimation method according to the above-described embodiments can be applied to the case of battery charge. As shown in FIG. 10, the surface SOC representing the surface concentration appears to be lower than the SOC representing the average concentration at the time of discharge, and the surface SOC can appear to be higher than the SOC at the time of charge. Figure 3

[0095] According to the above-described embodiments, by estimating the surface SOC representing the potential of the electrode surface based on the current of the battery and the oxidation / reduction reaction of the active material, the state of the battery at the static state and at the dynamic state of repeated charge or discharge can be accurately estimated.

[0096] Next, a method for predicting battery output in a battery management system according to embodiments is described with reference to Figure 11 and Figure 12

[0097] Figure 11 is a graph for explaining battery output prediction in a battery management system of an embodiment, Figure 12 is a flowchart illustrating a battery output prediction method in a battery management system of an embodiment.

[0098] With reference to Figure 11 and Figure 12 , a processor (e.g., 150 in Figure 1 uses the output prediction model 1110 to predict the battery output. At S1210, the processor 150 receives a desired request time from an external device (e.g., a vehicle). Accordingly, the processor 150 can predict the battery output (e.g., power) at the requested time and provide the battery output to the vehicle.

[0099] ​​To predict the battery output, the processor 150 inputs the state of the battery estimated at the current time point to the output prediction model 1110 at S1220. In some embodiments, the state of the battery can include the surface SOC described above. In some embodiments, the processor 150 can additionally input the SOC calculated at the current time point to the output prediction model 1110 at S1220. Further, the processor 150 inputs the cut-off voltage received from the vehicle and the request time to the output prediction model 1110 at S1220. In some embodiments, the cut-off voltage can be a lower limit voltage when the battery 110 is discharged. In some embodiments, the processor 150 can determine the cut-off voltage based on the temperature of the battery 110. In some embodiments, a correspondence between the temperature of the battery 110 and the cut-off voltage can be determined in advance. In some embodiments, the memory (e.g., 160 in FIG. 1) of the battery management system can store the correspondence. Figure 1

[0100] In some embodiments, the processor 150 can determine the cut-off voltage in response to a request from an external device.

[0101] The output prediction model 1110 predicts the battery output based on the surface SOC, the cut-off voltage, and the request time at S1230, S1240, and S1250. In some embodiments, the output prediction model 1110 can determine the surface SOC at which the terminal voltage of the battery becomes the cut-off voltage at S1230, and estimate the current based on the input surface SOC to allow the surface SOC at which the terminal voltage becomes the cut-off voltage to be estimated after the request time at S1240.

[0102] In some embodiments, as described with reference to Figure 8 and Figure 9 , the terminal voltage of the battery can be determined based on the open-circuit voltage V OC of the battery, the overpotential V1, and the voltage caused by the ohmic resistance, and the voltage caused by the ohmic resistance can be determined as the product of the size of the ohmic resistance R0 and the size of the current of the battery. As described above, since the overpotential V1 and the ohmic resistance R0 can be estimated and converge to a certain value after a certain time elapses, the output prediction model 1110 can estimate the current I and the open-circuit voltage V OC of the battery when the terminal voltage of the battery reaches the cut-off voltage Vc based on Equation 5. OC In this case, the open-circuit voltage V OC corresponding to various sizes I of the current can be estimated, respectively.

[0103] [Equation 5]

[0104] ​Vc = Voc + V1 + R0·I

[0105] In Equation 5, the cutoff voltage Vc, the overpotential Vi, and the magnitude of the ohmic resistance Ro have predetermined values.

[0106] For reference Figure 4 to Figure 7 As described, since the open-circuit voltage of the battery is determined by the surface SOC, the output prediction model 1110 can be based on the estimated open-circuit voltage V. OC To determine the surface SOC SSOC[k+1] when the terminal voltage reaches the cutoff voltage. In some embodiments, the output prediction model 1110 may determine the current I[k] based on the input surface SOC SSOC[k], which is used to allow estimation of the determined surface SOC SSOC[k+1] corresponding to the cutoff voltage after a requested time Δt. In one embodiment, the output prediction model 1110 may predict the battery current I[k] based on Equation 6.

[0107] [Equation 6]

[0108] SSOC[k+1]=SSOC[k]+(Kc·I[k]+D[k])·Δt

[0109] In Equation 6, SSOC[k+1] is the surface SOC when the terminal voltage reaches the cutoff voltage, SSOC[k] is the surface SOC estimated by the input-to-output prediction model 1110 at the current time, and D[k] is the diffusion resistance, and Δt is the request time. In some implementations, D[k] can be determined based on the difference between the input surface SOC SSOC[k] and SOC SOC[k].

[0110] The output prediction model 1110 can determine the battery current that simultaneously satisfies equations 5 and 6. For example, the output prediction model 1110 can determine the battery current from the open-circuit voltage V. OC Among the various combinations of currents that can satisfy Equation 5, determine the combination that can satisfy Equation 6, i.e., the current.

[0111] In S1250, processor 150 may predict the battery output during the requested time based on the current estimated by output prediction model 1110, and provide the predicted battery output to the vehicle. In some embodiments, output prediction model 1110 may predict the estimated battery current as the current that the battery can provide during the requested time. In some embodiments, output prediction model 1110 may calculate the battery power based on the estimated battery current, and predict the calculated battery power as the power that the battery can provide during the requested time.

[0112] According to the above-described embodiments, the battery output that the battery can provide during a requested time by an external device (e.g., a vehicle) can be accurately predicted and provided in real time. In some embodiments, the battery management system can predict the output based on the periodically estimated surface SSOC, so that the output can be predicted considering the battery usage history. In some embodiments, the battery management system can predict the output by considering the cut-off voltage, thereby preventing the terminal voltage of the battery from falling below the cut-off voltage.

[0113] Figure 13 is a graph for explaining battery output prediction in a battery management system according to another embodiment, Figure 14 is a flowchart illustrating a battery output prediction method in a battery management system according to another embodiment.

[0114] Referring to Figure 13 and Figure 14 , the processor (e.g., 150 in Figure 1 predicts the battery output using the output prediction model 1310. In S1410, the processor 150 receives a desired requested time from an external device (e.g., a vehicle). To predict the battery output, in S1420, the processor 150 inputs the battery state estimated at the current time to the output prediction model 1310. In some embodiments, the state of the battery can include the surface SOC. Further, in S1420, the processor 150 inputs the cut-off voltage and the requested time received from the vehicle to the output prediction model 1310. Further, in S1420, the processor 150 inputs the derating voltage to the output prediction model 1310. In some embodiments, the processor 150 can determine the derating voltage based on the temperature of the battery 110. In some embodiments, a correspondence between the temperature of the battery 110 and the reduced rated voltage can be determined in advance. In some embodiments, a memory (e.g., 160 in Figure 1 ) of the battery management system can store the correspondence.

[0115] As described with reference to S1230, S1240, and S1250 in Figure 12 , in S1430 and S1440, the output prediction model 1310 estimates the current of the battery based on the surface SOC, the cut-off voltage, and the requested time, and in S1450, the battery output during the requested time is predicted based on the estimated current.

[0116] Next, in S1460, the processor 150 determines whether the voltage of the battery (e.g., the terminal voltage of the battery) reaches the derating voltage. In some embodiments, reference can be made to Figure 8 to Figure 10The process describes estimating the battery terminal voltage. When the battery voltage reaches the derating voltage, in S1470, the processor 150 reduces the predicted battery output by a predetermined ratio and provides the reduced battery output as the predicted battery output. In some embodiments, the processor 150 may reduce the battery power predicted by the output prediction model 1310 by a predetermined ratio and provide the reduced battery power as the predicted battery output. In some embodiments, the predetermined ratio may be a predefined ratio.

[0117] According to the above implementation, when predicting and providing battery output, derating voltage can be considered to predict battery output, thereby preventing undervoltage diagnosis due to the decrease in battery voltage.

[0118] In some implementations, the processor (e.g., Figure 1 150 in the above-mentioned method can be used to calculate the program for performing the surface SOC estimation method, terminal voltage estimation method, or battery output prediction method. The program for performing the surface SOC estimation method, terminal voltage estimation method, or battery output prediction method can be loaded into memory. The memory can be a memory used for storing tables (e.g., ...). Figure 1 The program may be the same memory as (160 in the original text) or a separate memory. When loaded into memory, the program may include instructions for causing the processor 150 to execute a surface SOC estimation method, a terminal voltage estimation method, or a battery output prediction method. That is, the processor can execute the operations of the surface SOC estimation method, the terminal voltage estimation method, or the battery output prediction method by executing the instructions of the program.

[0119] While the invention has been described in conjunction with what is now considered to be practical embodiments, it should be understood that the invention is not limited to the disclosed embodiments. Rather, the invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A battery apparatus, the battery apparatus comprising: a battery; and a processor configured to: estimate a surface state of charge (SOC) representing a potential of an electrode surface of the battery as a first surface SOC; and predict an output of the battery during a request time based on the first surface SOC, a cut-off voltage, and the request time, wherein the processor is configured to estimate the first surface SOC based on a plurality of parameters including a reaction rate determined based on a measured current of the battery and a diffusion resistance determined based on an SOC of the battery. the processor is configured to:

2. The battery device of claim 1, wherein, determine a surface SOC at which a terminal voltage of the battery becomes the cut-off voltage as a second surface SOC; estimate a current of the battery to allow estimation of the second surface SOC from the first surface SOC after the request time; and predict the output based on the current. the processor is configured to: determine an open circuit voltage of the battery when a terminal voltage of the battery becomes the cut-off voltage; and 3. The battery device of claim 2, wherein, determine the second surface SOC based on the open circuit voltage. the processor is configured to: estimate a current of the battery to allow estimation of a second surface SOC from the first surface SOC after the request time; and 4. The battery device of claim 1, wherein, predict the output based on the current of the battery, and wherein a terminal voltage of the battery determined based on the second surface SOC and the current is the cut-off voltage. the terminal voltage is determined based on an open circuit voltage of the battery corresponding to the second surface SOC and a voltage corresponding to the current. the terminal voltage is determined based on an open circuit voltage of the battery, a voltage corresponding to the current, and an overpotential of the battery. the processor is configured to determine the cut-off voltage based on a temperature of the battery.

5. The battery device of claim 4, wherein, the processor is configured to reduce a predicted output in response to a voltage of the battery corresponding to the predicted output reaching a derated voltage.

6. The battery device of claim 5, wherein, the cut-off voltage is a lower limit voltage when the battery is discharging or is determined based on a temperature of the battery.

7. The battery device of claim 1, wherein, 10. A method of predicting an output of a battery, the method comprising the steps of:

8. The battery device of claim 1, wherein, estimating a state of the battery, wherein the state of the battery includes a surface SOC representing a potential of an electrode surface of the battery; and 9. The battery device of claim 1, wherein, predicting an output of the battery during a request time based on the state of the battery, a cut-off voltage, and the request time, wherein the step of estimating the state of the battery includes estimating the surface SOC based on a plurality of parameters including a reaction rate determined based on a measured current of the battery and a diffusion resistance determined based on an SOC of the battery. the step of predicting the output of the battery includes: estimating a current of the battery to allow estimation of a particular surface SOC from the estimated surface SOC after the request time; and predicting the output based on the current, and 11. The method of claim 10, wherein, wherein a terminal voltage of the battery determined based on the particular surface SOC and the current is the cut-off voltage. ​ ​ ​ 12. The method of claim 11, wherein, determining the terminal voltage based on an open circuit voltage of the battery corresponding to the particular surface SOC and a voltage corresponding to the current.

13. The method of claim 10, wherein, The cutoff voltage is a lower limit voltage when the battery is discharged or is determined based on a temperature of the battery.

14. A recording medium having a program recorded thereon, the program configured to be executed by a processor of a battery device, wherein, The program causes the processor to perform: estimating a state of a battery, wherein the state of the battery includes a surface SOC representing a potential of an electrode surface of the battery; and predicting an output of the battery during a request time based on the state of the battery, a cutoff voltage, and the request time, wherein estimating the state of the battery includes estimating the surface SOC based on a plurality of parameters including a reaction rate determined based on a measured current of the battery and a diffusion resistance determined based on an SOC of the battery.

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