Battery equipment, methods and procedures for estimating battery state

Abstract

The battery device receives a measured current from the battery and estimates the surface state of charge (SOC) representing the potential of the electrode surface based on multiple parameters, including a first parameter determined based on the measured current and a second parameter determined based on the battery's SOC.

Description

Technical Field

[0001] Cross-references to related applications

[0002] This application claims priority and benefit to Korean Patent Application 10-2020-0122153, filed on September 22, 2020, with the Korean Intellectual Property Office, the entire contents of which are incorporated herein by reference.

[0003] The technology relates to a battery device and a method for estimating battery state. Background Technology

[0004] Electric or hybrid vehicles are vehicles that primarily use batteries as their power source, obtaining power through a drive motor. Electric vehicles are being actively researched because they represent an alternative to addressing the pollution and energy problems associated with internal combustion engine vehicles. Rechargeable batteries are used in various external devices beyond electric vehicles.

[0005] An important state used in battery management is the state of charge (SOC). SOC is a factor representing the ratio of remaining capacity to fully charged capacity, which represents the maximum amount of charge that can be stored in the battery. SOC also represents the average concentration of active materials inside the battery.

[0006] The equivalent circuit model using the battery's State of Charge (SOC) is primarily used to estimate the battery's terminal voltage. The SOC in the equivalent circuit model is suitable for estimating the battery's state under static conditions (such as an open circuit). However, in cases of dynamic battery use (such as continuous charging or discharging or when a vehicle with a battery is in operation), it fails to reflect current effects, potentially increasing the error in state estimation. Summary of the Invention

[0007] Technical issues

[0008] Some implementations can provide a battery management system and a battery state estimation method that can accurately estimate the battery state.

[0009] Technical solution

[0010] According to one embodiment, a battery device is provided, the battery device including a battery and a processor. The processor receives a measured current from the battery; and estimates a surface state of charge (SOC) representing the potential of the electrode surfaces of the battery based on a plurality of parameters, the plurality of parameters including a first parameter determined based on the measured current and a second parameter determined based on the SOC of the battery.

[0011] In some implementations, the processor may determine a coefficient based on at least one of the battery temperature, the SOC, and the surface SOC; and determine the first parameter by reflecting the coefficient to the measured current.

[0012] In some embodiments, the battery device may further include a memory configured to store a correspondence between the coefficient and at least one of the battery's temperature, state of charge (SOC), and surface SOC, in which case the processor can determine the coefficient based on the correspondence.

[0013] In some implementations, the processor may determine the second parameter based on the difference between the surface SOC estimated at the previous time and the SOC.

[0014] In some implementations, the processor may determine a coefficient based on at least one of the battery's temperature, the state of charge (SOC), and the surface SOC; and determine the second parameter by reflecting the coefficient onto the difference between the SOC and the surface SOC.

[0015] In some embodiments, the battery device may further include a memory configured to store a correspondence between the coefficient and at least one of the battery temperature, the state of charge (SOC), and the surface SOC. In this case, the processor is configured to determine the coefficient based on the correspondence.

[0016] In some implementations, the processor can estimate the surface SOC at the current time point based on the surface SOC estimated at the previous time point, the first parameter, and the second parameter.

[0017] In some implementations, the processor can reflect the time change between the previous time point and the current time point to the first parameter and the second parameter, respectively.

[0018] In some implementations, the processor can estimate the terminal voltage of the battery based on the surface SOC, the SOC, and the current of the battery.

[0019] In some embodiments, the processor may estimate the open-circuit voltage of the battery based on the surface SOC; estimate the overpotential of the battery based on the SOC and the surface SOC; estimate the voltage caused by the ohmic resistance of the battery based on the current of the battery; and estimate the terminal voltage based on the open-circuit voltage, the overpotential, and the voltage caused by the ohmic resistance.

[0020] In some embodiments, the battery device may further include a memory configured to store a correspondence between the surface SOC as input and the open-circuit voltage as output. In this case, the processor can use the surface SOC as input to the correspondence to estimate the open-circuit voltage.

[0021] In some implementations, the processor may estimate the overpotential based on the ratio or difference between the SOC and the surface SOC.

[0022] According to another embodiment, a method for estimating the state of a battery is provided. The method includes: determining a first parameter based on a measured current of the battery; determining a second parameter based on the state of charge (SOC) of the battery; and estimating a surface state of charge (SOC) representing the potential of an electrode surface of the battery based on a plurality of parameters including the first parameter and the second parameter.

[0023] In some implementations, determining the first parameter may include: determining a coefficient based on at least one of the battery temperature, the SOC, and the surface SOC; and determining the first parameter by reflecting the coefficient to the measured current.

[0024] In some implementations, determining the second parameter may include: determining a coefficient based on at least one of the battery temperature, the SOC, or the surface SOC; and determining the second parameter by reflecting the coefficient to the difference between the SOC and the surface SOC at a previous time point.

[0025] In some implementations, estimating the surface SOC may include estimating the surface SOC at the current time point based on the surface SOC estimated at the previous time point, the first parameter, and the second parameter.

[0026] In some embodiments, the method may further include: estimating a first voltage based on the surface SOC; estimating a second voltage based on the SOC and the surface SOC; estimating a third voltage based on the current of the battery; and estimating the terminal voltage of the battery based on the first voltage, the second voltage, and the third voltage.

[0027] According to another embodiment, a program is provided configured to be executed by a processor of a battery device and stored in a recording medium. The program causes the processor to perform: determining a first parameter based on a measured current of the battery; determining a second parameter based on the state of charge (SOC) of the battery; and estimating a surface SOC representing the potential of the electrode surfaces of the battery based on a plurality of parameters including the first and second parameters.

[0028] Beneficial effects

[0029] According to one embodiment of the present invention, the state of the battery can be accurately estimated not only in the static state of the battery, but also in the dynamic state of repeated charging or discharging. Attached Figure Description

[0030] Figure 1 This is a diagram illustrating a battery device according to one embodiment.

[0031] Figure 2 This is a diagram showing the structure of a battery according to one embodiment.

[0032] Figure 3 This is a diagram illustrating one embodiment of the state changes in a battery.

[0033] Figure 4 This is a graph used to explain the surface SOC estimation in a battery management system according to one embodiment.

[0034] Figure 5 This is a diagram illustrating one embodiment of the correspondence between temperature / SOC and kinetic coefficient in a battery according to one implementation.

[0035] Figure 6 This is a diagram illustrating one embodiment of the correspondence between temperature / SOC and diffusion coefficient in a battery according to one implementation.

[0036] Figure 7 This is a flowchart illustrating a surface SOC estimation method in a battery management system according to one embodiment.

[0037] Figure 8 This is a diagram used to explain the estimation of battery terminal voltage in a battery management system according to one embodiment.

[0038] Figure 9 This is a flowchart illustrating a battery terminal voltage estimation method in a battery management system according to one embodiment.

[0039] Figure 10 This is a diagram illustrating one embodiment of the correspondence between SOC and open-circuit voltage in a battery according to one implementation.

[0040] Figure 11 and Figure 12 This is a graph showing the relationship between the terminal voltage estimated by means of a battery terminal voltage estimation method according to one embodiment and the actual terminal voltage. Detailed Implementation

[0041] In the following detailed description, only 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 ways without departing from the spirit or scope of the invention. Therefore, the drawings and descriptions should be considered illustrative rather than restrictive. Throughout the specification, similar reference numerals denote similar elements.

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

[0043] As used in this article, the singular form should also include the plural form unless an explicit expression such as "a" or "single" is used.

[0044] In the flowchart described with reference to the accompanying drawings, the order of operations or steps may be changed, several operations or steps may be combined, a certain operation or step may be split, and a particular operation or step may not be performed.

[0045] Figure 1 This is a diagram illustrating a battery device according to one embodiment. Figure 2 This is a diagram showing the structure of a battery according to one embodiment, and Figure 3 This is a diagram illustrating one embodiment of battery state changes.

[0046] refer to Figure 1 The battery device 100 has a structure that allows it to be electrically connected to an external device. When the external device is a load, the battery device 100 discharges by operating as a power source supplying 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 or 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] Battery 110 is a rechargeable battery. For example, battery 110 may be 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, battery 110 may be: a single battery cell; a battery module comprising a plurality of battery cells, or wherein the plurality of components are connected in series or in parallel; a battery pack wherein a plurality of battery modules are connected in series or in parallel; or a system wherein a plurality of battery packs are connected in series or in parallel.

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

[0050] Temperature sensor 130 measures the temperature of battery 110. In some embodiments, temperature sensor 130 can measure the temperature at a predetermined location on battery 110. In some embodiments, multiple temperature sensors 130 may be provided to measure the temperature at multiple locations on 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 may further include a memory 160 that stores the data required for state estimation in the processor 150.

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

[0054] refer to Figure 2 The battery 110 includes a positive electrode (or cathode) 111, a negative electrode (or anode) 112, and an electrolyte 113. Figure 2 The structure of the battery 110 shown is an illustrative embodiment for ease of description, and the structure of the battery 110 is not limited thereto. Figure 2 For convenience, it is assumed that lithium is the active material that causes the chemical reaction in battery 110.

[0055] When battery 110 discharges to supply power to external devices, such as Figure 2 As shown, lithium ion exchange (Li+) can occur on the surface of the negative electrode 112. +The chemical reaction (oxidation reaction) that occurs from the negative electrode 112. The discharged lithium ions (Li) + It can pass through the electrolyte 113 and then move to the surface of the positive electrode 111. Therefore, lithium ions (Li) can form on the surface of the positive electrode 111. + The chemical reaction (reduction reaction) absorbed into the positive electrode 111.

[0056] When the battery 110 is charged, lithium ion exchange (Li+) can occur at the boundary surface between the positive electrode 111 and the electrolyte 113. + The chemical reaction (oxidation reaction) that occurs at the positive electrode 111. The discharged lithium ions (Li) + It can pass through the electrolyte 113 and then move to the surface of the negative electrode 112. Therefore, lithium ions can form on the surface of the negative electrode 112. + The chemical reaction (reduction reaction) absorbed into the negative electrode 112.

[0057] The terminal voltage of battery 110 can be expressed as a sum of the following: the potentials corresponding to the battery electrode surfaces of the positive electrode 111 and the negative electrode 112; the voltage drop caused by the ohmic resistance (internal resistance) formed by the electrolyte 113, etc.; and the overpotential caused by the electrochemical reaction. The overpotential can represent the voltage drop that occurs due to the polarization of each battery electrode, deviating from the equilibrium potential. The overpotential is also called the polarization voltage.

[0058] like Figure 3 As shown, when battery 110 begins to discharge, the terminal voltage Vt of battery 110 decreases instantaneously due to the voltage drop Vohmic across the ohmic resistor Rohmic, and then gradually decreases due to the instantaneous overpotential change V1. Generally, the instantaneous overpotential change V1 can be expressed as a change in the time constant defined in the parallel circuit of the resistor and capacitor. At this time, the actual terminal voltage Vt of battery 110 decreases along with the instantaneous overpotential change V1 at a constant slope. That is, as... Figure 3 As shown, the decrease in voltage Vk according to a constant slope and the decrease in voltage 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 mentioned above, the phenomenon that the terminal voltage Vt of the battery 110 decreases with a certain slope occurs 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. That is, the voltage change Vk according to a constant slope may occur due to the voltage change caused by the oxidation / reduction reaction rate (the change caused by discharge or charging) and the voltage change caused by the diffusion resistance (concentration difference) during the relaxation period after the current disappears.

[0059] Generally, the state of charge (SOC) of battery 110 is determined as the average concentration of the battery 110 as a whole, 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 inside battery 110 (e.g., the average concentration at the electrodes), not the concentration on the surface of the battery electrodes, and gradually decreases as battery 110 discharges (e.g., ...). Figure 3 (As shown in the diagram). 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. This 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 interpret surface SOC estimation in a battery management system according to one embodiment. Figure 5 This is a diagram illustrating one embodiment of the correspondence between temperature / SOC and kinetic coefficient in a battery according to one implementation. Figure 6 This is a diagram illustrating one embodiment of the correspondence between temperature / SOC and diffusion coefficient in a battery according to one implementation.

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

[0062] For reference Figure 3As the battery 110 discharges, its terminal voltage may decrease at a certain slope. Since this decrease in terminal voltage is due to a decrease in the concentration of active material caused by oxidation / reduction reactions on the electrode surface, this slope 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 reflecting a specific coefficient to 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 be varied based 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 both the SOC of battery 110 representing the average concentration and the surface SOC of battery 110. 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 can store (e.g., in the form of a lookup table) this correspondence. In some embodiments, the surface SOC estimation model 410 can 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 due to oxidation / reduction reactions on the electrode surface, a resistive component may emerge, where the reaction on the electrode surface is reduced due to the diffusion rate caused by the concentration difference between the concentration on the electrode surface and the average concentration. This diffusion-induced resistance (hereinafter referred to as "diffusion resistance") can be expressed as a force that inhibits the reverse oxidation / reduction reaction. Therefore, the surface SOC estimation model 410 additionally reflects the diffusion resistance when estimating the surface SOC. 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 specific coefficient to the difference between the SOC and the surface SOC. Hereinafter, this specific coefficient is referred to as the "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 battery 110 and the average concentration within battery 110. Therefore, in some embodiments, the diffusion coefficient that inhibits the oxidation / reduction reaction can be varied based 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 both the SOC of battery 110 representing the average concentration and the surface SOC of battery 110. That is, the surface SOC estimation model 410 can determine the diffusion coefficient based on the temperature of battery 110 and the SOC of battery 110. In some embodiments, such as... Figure 6 As shown, the correspondence between the temperature / SOC of battery 110 and the diffusion coefficient can be determined in advance experimentally. In some embodiments, the memory of the battery management system can store (e.g., in the form of a lookup table) this correspondence. In some embodiments, the surface SOC estimation model 410 can determine the diffusion coefficient based on the temperature or SOC of battery 110.

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

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

[0068] refer to Figure 7 processor (e.g., Figure 1 In S710, the battery (e.g., 150) is placed at S710. 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 (140) in the figure. 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 battery cell voltage, which 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] Processor 150 uses a surface SOC estimation model at S720 and S730 to determine multiple parameters at time point t. These multiple parameters may include parameters corresponding to the reaction rate and parameters corresponding to the diffusion resistance.

[0070] At 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 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] Furthermore, at S730, processor 150 uses a surface SOC estimation model to determine the diffusion resistance D[t] of battery 110 at time point t. Processor 150 can calculate the diffusion resistance D[t] as the product of the difference between the SOC at time point t and the surface SOC, ΔSOC[t], and the diffusion coefficient Dc, Dc*ΔSOC[t]. In some embodiments, processor 150 can retrieve the diffusion coefficient Dc corresponding to the temperature and SOC of battery 110 from memory. In some embodiments, this memory may be memory 160 of the battery management system.

[0072] Next, at S740, processor 150 estimates the surface SOC SSOC[t] at time point (t+1) using a surface SOC estimation model based on the surface SOC SSOC[t] estimated at time point t, the reaction rate K[t], and the diffusion resistance D[t]. In some embodiments, processor 150 may estimate the surface SOC SSOC[t+1] according to 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 represents the time difference (time variation) between time point (t+1) and time point t.

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

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

[0080] Next, refer to Figure 8 , Figure 9 and Figure 10 An implementation method for estimating the terminal voltage of battery 110 using surface SOC is described.

[0081] Figure 8 This is a diagram used to explain the estimation of battery terminal voltage in a battery management system according to one embodiment. Figure 9This is a flowchart illustrating a battery terminal voltage estimation method in a battery management system according to one embodiment, and Figure 10 This is a diagram illustrating one embodiment of the correspondence between SOC and open-circuit voltage in a battery according to one implementation.

[0082] refer to 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 The processor, at S910, will transfer 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 at S920 and S930, and the surface SOC SSOC[t+1] is estimated at S940 based on the reaction rate K[t] and diffusion resistance D[t].

[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] To this end, processor 150 estimates the open-circuit voltage of battery 110 at S950 based on surface SOC. Processor 150 can estimate the open-circuit voltage Voc based on the nonlinear functional relationship between surface SOC (SSOC) and open-circuit voltage Voc, Voc = f(SSOC). Generally, the memory of the battery management system (e.g., Figure 1 160) Pre-stores the correspondence between the open-circuit voltage Voc of battery 110 and the state of charge (SOC) of battery 110. For example, the correspondence between open-circuit voltage Voc and SOC can be defined as follows: Figure 10 As shown in the diagram. In this case, the processor 150 determines the open-circuit voltage Voc by inputting the surface SOC instead of the SOC. For example, when the surface SOC is 70%, the processor 150 can retrieve the open-circuit voltage corresponding to 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 in various correspondences, corresponding to the temperature of the battery 110.

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

[0086] Equation 3

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

[0088] In Equation 3, α represents the overpotential coefficient.

[0089] In some embodiments, the overpotential coefficient α can be determined experimentally. In some embodiments, the overpotential coefficient α can be determined by repeatedly performing overpotential estimation using an adaptive filter. In some embodiments, the processor 150 can predetermine an initial overpotential value V1[0] for estimating the overpotential.

[0090] Furthermore, at S970, processor 150 estimates the voltage generated due to the ohmic resistance of battery 110. Processor 150 estimates the voltage Vohmic generated due to the ohmic resistance as the product of the ohmic resistance of battery 110 and the current of battery 110. In some embodiments, processor 150 may use any of a variety of known methods to estimate the ohmic resistance, and the present invention is not limited to methods for estimating ohmic resistance.

[0091] Next, at S980, processor 150 determines the terminal voltage of battery 110 based on the open-circuit voltage Voc, the overpotential V1, and the voltage Vohmic caused by the ohmic resistance. In some embodiments, as shown in Equation 4, processor 150 may determine the terminal voltage Vt of battery 110 as the sum of the open-circuit voltage Voc, the overpotential V1, and the voltage Vohmic based on the ohmic resistance.

[0092] Equation 4

[0093] Vt = Voc + V1 + Vohmic

[0094] Although the surface SOC estimation method or terminal voltage estimation method has been described in the case of battery discharge, the surface SOC estimation method or terminal voltage estimation method according to the above embodiments can also be applied to the case of battery charging. Figure 3 As shown, during discharge, the surface SOC, representing surface concentration, exhibits a lower value than the SOC, representing average concentration, while during charging, the surface SOC may exhibit a higher value than the average SOC.

[0095] Figure 11 and Figure 12 This is a graph showing the relationship between the terminal voltage estimated by a battery terminal voltage estimation method according to one embodiment and the actual terminal voltage. Figure 11 and Figure 12 The estimated and actual terminal voltages are shown when the surface SOC is 5%, 60%, and 100%. Figure 11 The terminal voltages during battery charging are shown, and Figure 12 The terminal voltages during battery discharge are shown.

[0096] like Figure 11 and Figure 12 As shown in the figure, it can be seen that the terminal voltage (solid line) estimated by the battery terminal voltage estimation method according to one embodiment undergoes a similar change to the actual terminal voltage (dashed line).

[0097] According to the above embodiments, by estimating the surface SOC, which represents the potential of the electrode surface, based on the battery current and the oxidation / reduction reaction of the active material, the state of the battery can be accurately estimated not only in the static state of the battery, but also in the dynamic state of repeated charging or discharging.

[0098] In some implementations, the processor (e.g. Figure 1 The 150) can be used to perform calculations on the program for executing the above-described surface SOC estimation method or terminal voltage estimation method. The program for executing the surface SOC estimation method or terminal voltage estimation method can be loaded into memory. This memory can be a memory used for storing tables (e.g., ...). Figure 1 The program may include the same memory as (160 in the original text) or a separate memory. The program may include instructions, when loaded into memory, for causing the processor 150 to perform a surface SOC estimation method or a terminal voltage estimation method. That is, the processor can perform the surface SOC estimation method or the terminal voltage estimation method by executing the instructions of the program.

[0099] While the invention has been described in conjunction with embodiments currently considered practical, it should be understood that the invention is not limited to the disclosed embodiments. Rather, various variations and equivalent arrangements included within the spirit and scope of the appended claims are to be embraced.

Claims

1. A battery device, the battery device comprising: Battery; as well as Processor, the processor being configured to: Receive the measured current of the battery; and The surface state of charge (SPC) representing the potential of the electrode surface of the battery is estimated based on multiple parameters, including a first parameter determined based on the measured current and a second parameter determined based on the SPC of the battery. The processor is configured to determine the second parameter based on the difference between the surface state of charge estimated at a previous time point and the state of charge.

2. The battery device according to claim 1, wherein, The processor is configured to: A coefficient is determined based on at least one of the battery temperature, the state of charge, and the surface state of charge; and The first parameter is determined by reflecting the coefficient into the measured current.

3. The battery device of claim 2, further comprising a memory configured to store a correspondence between the coefficient and at least one of the battery temperature, the state of charge, and the surface state of charge. in, The processor is configured to determine the coefficients based on the correspondence.

4. The battery device according to claim 1, wherein, The processor is configured to: A coefficient is determined based on at least one of the battery temperature, the state of charge, and the surface state of charge; and The second parameter is determined by reflecting the coefficient to the difference between the state of charge and the surface state of charge.

5. The battery device of claim 4, further comprising a memory configured to store a correspondence between the coefficient and at least one of the battery temperature, the state of charge, and the surface state of charge. in, The processor is configured to determine the coefficients based on the correspondence.

6. The battery device according to claim 1, wherein, The processor is configured to estimate the surface charge state at the current time point based on the surface charge state estimated at the previous time point, the first parameter, and the second parameter.

7. The battery device according to claim 6, wherein, The processor is configured to reflect the time change between the previous time point and the current time point in the first parameter and the second parameter, respectively.

8. The battery device according to claim 1, wherein, The processor is configured to estimate the terminal voltage of the battery based on the surface state of charge, the state of charge, and the battery current.

9. The battery device according to claim 8, wherein, The processor is configured to: The open-circuit voltage of the battery is estimated based on the surface state of charge; The overpotential of the battery is estimated based on the state of charge and the surface state of charge. Based on the current of the battery, estimate the voltage caused by the ohmic resistance of the battery; as well as The terminal voltage is estimated based on the open-circuit voltage, the overpotential, and the voltage caused by the ohmic resistance.

10. The battery device of claim 9, further comprising a memory configured to store a correspondence between the state of charge as input and the open-circuit voltage as output. in, The processor is configured to use the surface state of charge as input to the correspondence to estimate the open-circuit voltage.

11. The battery device according to claim 9, wherein, The processor is configured to estimate the overpotential based on the ratio or difference between the state of charge and the surface state of charge.

12. A method for estimating the state of a battery, the method comprising the following steps: The first parameter is determined based on the measured current of the battery; The second parameter is determined based on the state of charge of the battery; as well as Based on multiple parameters, including the first parameter and the second parameter, the surface state of charge representing the potential of the electrode surface of the battery is estimated. The second parameter is determined based on the difference between the surface state of charge estimated at the previous time point and the state of charge.

13. The method according to claim 12, wherein, The steps to determine the first parameter include: A coefficient is determined based on at least one of the battery temperature, the state of charge, and the surface state of charge; and The first parameter is determined by reflecting the coefficient into the measured current.

14. The method according to claim 12, wherein, The steps to determine the second parameter include: A coefficient is determined based on at least one of the battery temperature, the state of charge, and the surface state of charge; and The second parameter is determined by reflecting the coefficient as the difference between the state of charge and the surface state of charge at the previous time point.

15. The method according to claim 12, wherein, The step of estimating the surface state of charge includes estimating the surface state of charge at the current time point based on the surface state of charge estimated at the previous time point, the first parameter, and the second parameter.

16. The method of claim 12, further comprising the following steps: The first voltage is estimated based on the surface state of charge. The second voltage is estimated based on the state of charge and the surface state of charge; Estimate the third voltage based on the current of the battery; as well as The terminal voltage of the battery is estimated based on the first voltage, the second voltage, and the third voltage.

17. A program configured to be executed by a processor of a battery device and stored in a recording medium, wherein, This program causes the processor to execute: The first parameter is determined based on the measured current of the battery; The second parameter is determined based on the state of charge of the battery; and Based on multiple parameters, including the first parameter and the second parameter, the surface state of charge representing the potential of the electrode surface of the battery is estimated. The second parameter is determined based on the difference between the surface state of charge estimated at the previous time point and the state of charge.

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