Battery management system, battery pack, electric vehicle and battery management method

Abstract

A battery management system, a battery pack, an electric vehicle, and a battery management method are provided. The battery management system comprises: a sensing unit which detects a terminal voltage and a charging / discharging current of a battery having a characteristic in which a voltage inflection section changes according to a current rate; a memory unit which stores a first Kalman filter using an equivalent circuit model and an SOC-OCV curve of the battery and a second Kalman filter using a constant current charging / discharging map of the battery; and a control unit which determines a first SOC estimation value by inputting, to the first Kalman filter, a voltage value of the terminal voltage, a current value of the charging / discharging current, and a previous SOC estimation value and determines a second SOC estimation value by inputting, to the second Kalman filter, the current value and the previous SOC estimation value.

Description

Battery management system, battery pack, electric vehicle, and battery management method The present invention relates to a technique for estimating the state of charge of a battery. This application claims priority to Korean Patent Application No. 10-2023-0082153, filed on June 26, 2023, and all contents disclosed in the specification and drawings of the said application are incorporated by reference into this application. Recently, as the demand for portable electronic products such as laptops, video cameras, and mobile phones has rapidly increased, and the development of electric vehicles, energy storage batteries, robots, and satellites has been in full swing, research into high-performance batteries capable of repeated charging and discharging is actively being conducted. Currently commercialized batteries include nickel-cadmium batteries, nickel-hydrogen batteries, nickel-zinc batteries, and lithium batteries. Among these, lithium batteries are receiving attention for their advantages of being able to charge and discharge freely, having a very low self-discharge rate, and having a high energy density, as they have almost no memory effect compared to nickel-based batteries. One of the key parameters required to control the charging and discharging of a battery is the state of charge (SOC). SOC is a parameter that represents the relative ratio of the current capacity to the maximum capacity, which represents the total electrical energy when the battery is fully charged, and can be expressed as 0 to 1 (or 0% to 100%). For example, if the maximum capacity of a battery is 1000 ampere-hours (Ah) and the current stored capacity is 750 Ah, the battery's SOC is 0.75 (or 75%). The Extended Kalman Filter (EKF) is widely used to estimate the SOC of batteries. The conventional extended Kalman filter is a SOC estimation logic that uses an equivalent circuit model (ECM) and SOC-OCV (Open Circuit Voltage) curve that are each pre-written according to the electrochemical characteristics of the battery, and outputs an SOC estimation value, which is one of the state variables, when the voltage and current of the battery are input as input variables. Meanwhile, the SOC-OCV (Open Circuit Voltage) curve of some types of batteries, such as lithium iron phosphate (LFP) batteries, has a voltage inflection section. However, the SOC-CCV (Closed Circuit Voltage) curve obtained by repeatedly measuring the terminal voltage of the battery in constant current charge mode and / or constant current discharge mode has a less distinct voltage inflection section compared to the SOC-OCV curve, and the voltage inflection section becomes fainter or disappears completely as the current rate increases. To faithfully reflect the characteristics of the battery's voltage inflection section in the EKF, the ECM must be precisely designed. However, as the ECM design precision increases, the number of components included in the ECM increases excessively, and the interconnections between these components inevitably become more complex. This leads to increased computational effort and data storage space required for SOC estimation. Furthermore, even with improved ECM design precision, it remains difficult to fully reflect the aforementioned voltage inflection section variation characteristics according to current rate. To address these limitations of ECM, a method for estimating the battery's SOC using ampere counting instead of the EKF during constant current charge / discharge mode can be considered. Ampere counting is a method for estimating the battery's SOC by converting the accumulated current flowing through the battery into a change in SOC. However, as the constant current charge / discharge mode continues for an extended period, current measurement errors accumulate over time, leading to a gradual deterioration in the accuracy of SOC estimation using ampere counting. The present invention has been devised to solve the above problems, and the purpose of the present invention is to provide a battery pack for estimating the SOC of a battery having a characteristic in which a voltage inflection section changes according to a current rate by using two extended Kalman filters having a mutually complementary relationship in parallel, an electric vehicle including the battery pack, and a battery management method. Other objects and advantages of the present invention can be understood through the following description and will be more clearly understood through the embodiments of the present invention. Furthermore, it will be readily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims. A battery management system according to one aspect of the present invention is for a battery having a characteristic in which a voltage inflection section changes according to a current rate. The battery management system includes a sensing unit configured to detect a terminal voltage and a charge / discharge current of the battery, a memory unit configured to store a first Kalman filter, which is an SOC estimation logic using an equivalent circuit model of the battery and an SOC (State Of Charge)-OCV (Open Circuit Voltage) curve, and a second Kalman filter, which is an SOC estimation logic using a constant current charge / discharge map of the battery, and a control unit configured to determine a voltage value of the detected terminal voltage and a current value of the detected charge / discharge current. The control unit is configured to input the voltage value, the current value, and the previous SOC estimation value to the first Kalman filter to determine a first SOC estimation value, and to input the current value and the previous SOC estimation value to the second Kalman filter to determine a second SOC estimation value. The control unit is configured to determine the current SOC of the battery based on at least one of the first SOC estimate value and the second SOC estimate value. The control unit may be configured to determine whether the battery is in a first state in which the battery is not in constant current charging / discharging or a second state in which the battery is in constant current charging / discharging, based on current time series data representing the temporal change history of the current value or the charge / discharge current. The control unit may be configured to determine, in response to determining that the battery is in the first state, the current SOC of the battery to be the same as the first SOC estimate value. The control unit may be configured to determine, in response to determining that the battery is in the second state, the current SOC of the battery to be the same as the second SOC estimate value. The control unit may be configured to determine whether the battery is in a first state in which the battery is not in constant current charging / discharging and a second state in which the battery is in constant current charging / discharging, based on current time series data representing the temporal change history of the current value or the charge / discharge current. In response to determining that the battery is in the first state, the control unit may be configured to determine a first weight having a positive correlation with the duration of the first state and a second weight having a negative correlation with the duration of the first state. The control unit may be configured to determine the current SOC of the battery as being equal to a weighted average of the first SOC estimate value and the second SOC estimate value by the first weight and the second weight. The first weight may be greater than the second weight. The sum of the first weight and the second weight may be 1. The control unit may be configured to determine, based on current time series data representing the temporal change history of the current value or the charge / discharge current, whether the battery is in a first state in which the battery is not in constant current charge / discharge and a second state in which the battery is in constant current charge / discharge. In response to determining that the battery is in the second state, the control unit may be configured to determine a third weight having a negative correlation with a duration of the second state and a fourth weight having a positive correlation with a duration of the second state. The control unit may be configured to determine a weighted average of the first SOC estimate value and the second SOC estimate value by the third weight and the fourth weight as the current SOC of the battery. The third weight may be less than the fourth weight. The sum of the third weight and the fourth weight may be 1. The above constant current charge / discharge map may include a plurality of charge curves representing the relationship between the SOC and voltage of the battery during constant current charging using a plurality of current rates, and a plurality of discharge curves representing the relationship between the SOC and voltage of the battery during constant current discharging using a plurality of current rates. The second SOC estimate value may be output from the second Kalman filter when one of the plurality of charging curves and the plurality of discharging curves is provided to the second Kalman filter. The control unit may be configured to, in response to the battery being charged at a constant current, provide one of the plurality of charging curves, which is associated with a current rate corresponding to the current value, to the second Kalman filter. The control unit may be configured to, in response to the battery being discharged at a constant current, provide one of the plurality of discharging curves, which is associated with a current rate corresponding to the current value, to the second Kalman filter. A battery pack according to another aspect of the present invention includes the battery management system. An electric vehicle according to another aspect of the present invention includes the battery pack. According to another aspect of the present invention, a battery management method is provided for a battery having a characteristic in which a voltage inflection section changes according to a current rate. The battery management method includes the steps of detecting a terminal voltage and a charge / discharge current of the battery, and determining a voltage value of the detected terminal voltage and a current value of the detected charge / discharge current, inputting the voltage value, the current value, and the previous SOC estimation value into a first Kalman filter, which is an SOC estimation logic using an equivalent circuit model of the battery and an SOC (State Of Charge)-OCV (Open Circuit Voltage) curve, to determine a first SOC estimation value, inputting the current value and the previous SOC estimation value into a second Kalman filter, which is an SOC estimation logic using a constant current charge / discharge map of the battery, to determine a second SOC estimation value, and determining a current SOC of the battery based on at least one of the first SOC estimation value and the second SOC estimation value. The step of determining the current SOC of the battery may include the step of determining whether the battery is in a first state in which the battery is not in constant current charging / discharging and a second state in which the battery is in constant current charging / discharging, based on current time series data representing the temporal change history of the current value or the charge / discharge current, the step of determining the first SOC estimate as the current SOC of the battery in response to determining the battery is in the first state, and the step of determining the second SOC estimate as the current SOC of the battery in response to determining the battery is in the second state. The step of determining the current SOC of the battery may include the step of determining whether the battery is in a first state in which the battery is not in constant current charging / discharging and a second state in which the battery is in constant current charging / discharging, based on current time series data representing the temporal change history of the current value or the charge / discharge current; in response to determining that the battery is in the first state, the step of determining a first weight having a positive correlation with the duration of the first state and a second weight having a negative correlation with the duration of the first state; and the step of determining a weighted average of the first SOC estimate value and the second SOC estimate value by the first weight and the second weight as the current SOC of the battery. The step of determining the current SOC of the battery may include the step of determining whether the battery is in a first state in which the battery is not in constant current charging / discharging and a second state in which the battery is in constant current charging / discharging, based on current time series data representing the temporal change history of the current value or the charge / discharge current; in response to determining that the battery is in the second state, the step of determining a third weight having a negative correlation with the duration of the second state and a fourth weight having a positive correlation with the duration of the second state; and the step of determining a weighted average of the first SOC estimate value and the second SOC estimate value by the third weight and the fourth weight as the current SOC of the battery. The above constant current charge / discharge map may include a plurality of charge curves representing the relationship between the SOC and voltage of the battery during constant current charging using a plurality of current rates, and a plurality of discharge curves representing the relationship between the SOC and voltage of the battery during constant current discharging using a plurality of current rates. The second SOC estimate value may be output from the second Kalman filter when one of the plurality of charging curves and the plurality of discharging curves is provided to the second Kalman filter. According to at least one of the embodiments of the present invention, in estimating the SOC of a battery having a characteristic in which a voltage inflection section changes according to a current rate, by using two extended Kalman filters having a mutually complementary relationship in parallel, an SOC estimation error according to a change in the charge / discharge mode of the battery is reduced compared to a method using a single extended Kalman filter, and as a result, the estimation accuracy of the SOC can be improved. The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims. The following drawings attached to this specification illustrate preferred embodiments of the present invention, and together with the detailed description of the invention described below, serve to further understand the technical idea of ​​the present invention, and therefore, the present invention should not be interpreted as being limited to matters described in such drawings. Figure 1 is a drawing exemplarily showing the configuration of an electric vehicle according to the present invention. Figure 2 is a drawing showing an exemplary equivalent circuit model of the battery illustrated in Figure 1. Fig. 3 is a diagram illustrating an SOC-OCV curve of the battery illustrated in Fig. 1. Figure 4 is a drawing used for reference in explaining a constant current charge / discharge map according to the present invention. FIG. 5 is a flowchart exemplarily showing a battery management method for SOC estimation according to a first embodiment of the present invention. FIG. 6 is a flowchart exemplarily showing a battery management method for SOC estimation according to a second embodiment of the present invention. FIG. 7 is a flowchart exemplarily showing a battery management method for SOC estimation according to a third embodiment of the present invention. Figure 8 is a drawing referenced for explaining the method according to Figure 7. FIG. 9 is a flowchart exemplarily showing a battery management method for SOC estimation according to a fourth embodiment of the present invention. FIG. 10 is a drawing referenced for explaining the method according to FIG. 9. FIG. 11 is a flowchart exemplarily showing a battery management method for SOC estimation according to a fifth embodiment of the present invention. Figure 12 is a flowchart exemplifying a method for determining whether a battery is in constant current charging / discharging. Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings. Prior to this, it should be noted that the terms and words used in this specification and claims should not be construed as limited to their conventional or dictionary meanings. Based on the principle that the inventor can appropriately define the concepts of terms to best explain his or her invention, they should be interpreted in a way that conforms to the technical spirit of the present invention. Accordingly, the embodiments described in this specification and the configurations illustrated in the drawings are merely the most preferred embodiments of the present invention and do not represent all of the technical ideas of the present invention. Therefore, it should be understood that there may be various equivalents and modified examples that can replace them at the time of filing this application. Terms that include ordinal numbers, such as first, second, etc., are used to distinguish one of the various components from the rest, and are not used to limit the components by such terms. Throughout the specification, when a part is said to "include" a component, this does not exclude other components, unless otherwise stated, but rather implies that other components may be included. Furthermore, terms such as "control unit" described in the specification mean a unit that processes at least one function or operation, and may be implemented using hardware, software, or a combination of hardware and software. Additionally, throughout the specification, when we say that a part is "connected" to another part, this includes not only cases where it is "directly connected" but also cases where it is "indirectly connected" with other elements in between. Figure 1 is a drawing exemplarily showing the configuration of an electric vehicle according to the present invention. It includes a vehicle controller (2), a battery pack (10), a relay (20), an inverter (30), and an electric motor (40). The charge / discharge terminals (P+, P-) of the battery pack (10) can be electrically connected to a charger (3) via a charging cable or the like. The charger (3) can be included in the electric vehicle (1) or provided in a charging station. The vehicle controller (2) (e.g., ECU: Electronic Control Unit) is configured to transmit a key-on signal to the battery management system (100) in response to a start button (not shown) provided in the electric vehicle (1) being turned to the ON position by a user. The vehicle controller (2) is configured to transmit a key-off signal to the battery management system (100) in response to a start button being turned to the OFF position by a user. The charger (3) can communicate with the vehicle controller (2) and supply charging power of constant current or constant voltage through the charge / discharge terminals (P+, P-) of the battery pack (10). The battery pack (10) includes a battery module (11) and a battery management system (100). The battery module (11) includes at least one battery (B). The battery (B) is capable of repeated charging and discharging. In addition, as long as it has the characteristic of a voltage inflection section changing depending on the current rate, such as an LFP battery, the type of battery (B) is not particularly limited. When the battery module (11) includes multiple batteries, these multiple batteries may be interconnected in series, parallel, or a mixture of series and parallel. The relay (20) is electrically connected in series to the battery module (11) via a power path connecting the battery module (11) and the inverter (30). In Fig. 1, the relay (20) is illustrated as being connected between the positive terminal and the charge / discharge terminal (P+) of the battery module (11). The relay (20) is turned on and off in response to a switching signal from the battery management system (100). The relay (20) may be a mechanical contactor that is turned on and off by the magnetic force of a coil, or a semiconductor switch such as a MOSFET (Metal Oxide Semiconductor Field Effect transistor). An inverter (30) is provided to convert direct current from a battery module (11) into alternating current in response to a command from a battery management system (100) or a vehicle controller (2). The electric motor (40) is driven using AC power from the inverter (30). For example, a three-phase AC motor (40) can be used as the electric motor (40). The battery management system (100) includes a voltage detection unit (111), a current detection unit (113), a temperature detection unit (115), and a control unit (130). The battery management system (100) may further include a communication circuit (150). The voltage detection unit (111) is connected to the positive terminal and negative terminal of the battery (B) included in the battery module (11), detects the terminal voltage, which is the voltage across both ends of the battery (B), and is configured to output a voltage signal (SV) representing the detected terminal voltage to the control unit (130). The current detection unit (113) is connected in series to the battery module (11) through a current path between the battery module (11) and the inverter (30). The current detection unit (113) is configured to detect a charge / discharge current, which is a current flowing through the battery module (11), and output a current signal (SI) representing the detected charge / discharge current to the control unit (130). The current detection unit (113) may be implemented as one or a combination of two or more of known current detection elements, such as a shunt resistor, a Hall effect element, etc. The temperature detection unit (115) is configured to detect the temperature of the battery (B) and output a temperature signal (ST) representing the detected temperature to the control unit (130). The temperature detection unit (115) may be implemented using one or a combination of two or more of known temperature detection elements, such as a thermocouple, a thermistor, a bimetal, etc. The voltage detection unit (111), current detection unit (113), and temperature detection unit (115) can be referred to as a ‘sensing unit.’ The communication circuit (150) is configured to support wired or wireless communication between the control unit (130) and the vehicle controller (2). The wired communication may be, for example, CAN (controller area network) communication, and the wireless communication may be, for example, Zigbee or Bluetooth communication. Of course, as long as it supports wired or wireless communication between the control unit (130) and the vehicle controller (2), the type of communication protocol is not particularly limited. The communication circuit (150) may include an output device (e.g., a display, a speaker) that provides information received from the control unit (130) and / or the vehicle controller (2) in a form recognizable to a user. The control unit (130) is operably coupled to a relay (20), a voltage detection unit (111), a current detection unit (113), a temperature detection unit (115), and a communication circuit (150). The fact that the two components are operably coupled means that the two components are directly or indirectly connected so that signals can be transmitted and received in one direction or both directions. The control unit (130) can collect a voltage signal (SV) from the voltage detection unit (111), a current signal (SI) from the current detection unit (113), and / or a temperature signal (ST) from the temperature detection unit (115). The control unit (130) can convert and record each analog signal collected from the detection units (111, 113, 115) into a digital value using an ADC (Analog to Digital Converter) provided therein. The control unit (130) may be referred to as a 'control circuit' or a 'battery controller', and may be implemented in hardware using at least one of ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), microprocessors, and other electrical units for performing functions. The memory unit (140) may include at least one type of storage medium, for example, a flash memory type, a hard disk type, an SSD (Solid State Disk type), an SDD (Silicon Disk Drive type), a multimedia card micro type, a RAM (random access memory), a SRAM (static random access memory), a ROM (read-only memory), an EEPROM (electrically erasable programmable read-only memory), and a PROM (programmable read-only memory). The memory unit (140) may store data and a program required for an operation by the control unit (130). The memory unit (140) may store data representing a result of an operation by the control unit (130). In FIG. 1, the memory unit (140) is illustrated as being physically independent from the control unit (130), but may also be built into the control unit (130). The memory unit (140) can store an equivalent circuit model (see FIG. 2), an SOC-OCV curve (see FIG. 3), a constant current charge / discharge map (see FIG. 4), a first extended Kalman filter, and a second extended Kalman filter. The SOC-OCV curve, the constant current charge / discharge map, the first extended Kalman filter, and the second extended Kalman filter will each be described in more detail below. The control unit (130) can turn on the relay (20) in response to a key-on signal. The control unit (130) can turn off the relay (20) in response to a key-off signal. The key-off signal indicates a transition from a cycle mode to an idle mode. Alternatively, the on / off control of the relay (20) may be performed by the vehicle controller (2) instead of the control unit (130). While the relay (20) is turned on, the battery (B) of the battery module (11) enters cycle mode. Cycle mode refers to an operating state in which charging and discharging are possible. Cycle mode can be divided into a constant current charging mode, a constant current discharging mode, and a non-constant current charging and discharging mode. Constant current charge mode refers to a state in which a charging current at a constant current rate flows to the battery (B). Constant current discharge mode refers to a state in which a discharging current at a constant current rate flows to the battery (B). Non-constant current charge / discharge mode refers to a state in which an irregular charging current or discharging current flows to the battery (B). While the relay (20) is turned off, the battery (B) of the battery module (11) enters idle mode. The idle mode refers to an operating state in which charging and discharging are impossible because the charging and discharging current is blocked. In this specification, when a battery (B) is in a first operating state, it means that the battery (B) is in a rest mode or a non-constant current charge / discharge mode. When a battery (B) is in a second operating state, it means that the battery (B) is in a constant current charge mode or a constant current discharge mode. The control unit (130) can determine a voltage value, a current value, and a temperature value based on each of a voltage signal (SV), a current signal (SI), and a temperature signal (ST) while the battery module (11) is in cycle mode, and then determine (estimate) the SOC of the battery (B) based on the voltage value, the current value, and / or the temperature value. The SOC represents the ratio of the remaining capacity to the fully charged capacity (maximum capacity) of the battery (B). In this specification, SOC is expressed in the range of 0 to 1, with SOC 0 indicating a fully discharged state, and SOC 1 indicating a fully charged state. In this specification, when U is a variable, it is assumed that 'U[k-1]' represents the value of U in the previous round (previous cycle), and 'U[k]' represents the value of U in the current round. The symbol k used with the symbol [] is a time index that increases by 1 every time a predetermined set time (Δt, for example, 0.001 seconds) elapses from the initial time t0. At the initial time t0, k=0 can be set. For example, k=10 indicates that Δt×10 time has passed from the initial time t0, and during this time, the SOC estimate value has been calculated 10 times. The initial time t0 may be a time when a predetermined event occurs, for example, a time when an event occurs in which the control unit (130) switches from a sleep state to a wake-up state. The control unit (130) may switch from the sleep state to the wake-up state in response to the electric vehicle (1) being keyed on, and may switch from the wake-up state to the sleep state in response to the electric vehicle (1) being keyed off. From now on, the equivalent circuit model and SOC-OCV curve utilized by the first extended Kalman filter will be described. Equations 1 to 8 below relate to the first extended Kalman filter, and in explaining each of Equations 1 to 8, repeated explanations of variables already explained may be omitted. The first extended Kalman filter uses a state equation (see Equations 4-1 and 4-2 below) that includes SOC and polarization voltage as state variables, respectively, and Equation 1 below represents the relationship between SOC and charge / discharge current by ampere counting. <Formula 1> In Equation 1, I[k-1] is the charge / discharge current detected in the previous cycle, Q iis the maximum capacity of the battery (B), SOC[k-1] represents the previous SOC, and SOC[k] represents the current SOC. I[0] can be 0 A. Q i Silver represents the maximum amount of charge that can be stored in the battery (B). That is, the maximum capacity Q i Silver is equal to the accumulated charge and discharge current from one of the fully charged and fully discharged states of the battery (B) to the other. Next, FIG. 2 is a drawing showing an exemplary equivalent circuit model (200) of the battery (B) shown in FIG. 1, and FIG. 3 is a drawing showing an exemplary SOC-OCV curve of the battery (B) shown in FIG. 1. Referring to Figure 2, the equivalent circuit model (200) includes a voltage source (210), a resistor (R DC ) and RC pair (R P , C P ) is included. The symbol I represents the charging current. Output voltage (V) of voltage source (210) OCV ) represents the OCV of the battery (B) that has been maintained in the idle mode for a long period of time and has reached an equilibrium state. Figure 3 shows two SOC-OCV curves (310, 320). The SOC-OCV curve (310) represents the change in OCV of the battery (B) during a charge cycle, and the SOC-OCV curve (320) represents the change in OCV of the battery (B) during a discharge cycle. At the same SOC, the OCV of the SOC-OCV curve (310) is slightly higher than that of the SOC-OCV curve (320), and this difference is due to the hysteresis of the battery (B) due to the charge cycle and the discharge cycle. In either of the two SOC-OCV curves (310, 320), the SOC and OCV of battery (B) are nonlinearly positively correlated. That is, f OCV and f SOC When are inverse functions of each other, OCV = f OCV(SOC), SOC = f SOC (OCV). The SOC-OCV curves (310, 320) illustrated in FIG. 3 are associated with a specific temperature or a specific temperature range, and other SOC-OCV curves associated with other temperatures or temperature ranges may be additionally stored in the memory unit (140). Meanwhile, in both SOC-OCV curves (310, 320), there exists a voltage inflection section, which is a SOC range in which the rate of change (which may be an absolute value) of OCV with respect to SOC is greater than or equal to a reference value. That is, in FIG. 3, reference numeral 311 represents a voltage inflection section of the SOC-OCV curve (310), and reference numeral 321 represents a voltage inflection section of the SOC-OCV curve (320). Resistance (R) DC ) is the IR drop (V) of the battery (B) DC ) is associated with IR drop (V DC ) is an instantaneous change in the terminal voltage of the battery (B) due to the charge / discharge current. In the memory unit (130), SOC, temperature and resistance (R DC ) may be recorded, and the control unit (130) may record the resistance (R) corresponding to the SOC and temperature of the previous (or current) time from the first lookup table. DC ) can be determined. RC pair is a resistor (R P ) and capacitor (C P ) is a parallel circuit of the battery (B), and the polarization voltage (which may also be called 'over potential') (V P ) is related to the resistance (R P ) and capacitor (C P ) is the product of SOC, temperature and RC pair (R P , C P) may be recorded. The control unit (130) may record the resistance (R) corresponding to the SOC and temperature of the previous (or current) time from the second lookup table. P ) and capacitor (C P ) can be determined. Resistance (R P ) and capacitor (C P ) determines the resistance (R P ) and the resistance value of the capacitor (C P ) may mean determining the capacitance. V ecm is a variable representing the voltage across both ends of the equivalent circuit model (200), and can represent the predicted value of the terminal voltage of the battery (B). As shown in Equation 2-1 below, V ecm is the output voltage (V OCV ), IR drop (V DC ) and polarization voltage (V P ) can be expressed as the sum of . <Formula 2-1> In Equation 2-1, R DC [k] is the current resistance (R DC ) is the resistance value, I[k] is the charge / discharge current measured in the current circuit, V OCV [k] is the estimated value of the current meeting OCV, V P [k] is an estimated value of the current polarization voltage. Equation 2-1 can be expressed as Equation 2-2 below. <Formula 2-2> In Equation 2-2, C[k] is a system matrix with two components c[k] and 1. c[k] is a function f OCV From SOC[k] according to V OCV is the conversion coefficient to [k]. That is, the product of c[k] and SOC[k] is V OCV Same as [k]. In the equivalent circuit model (200), the polarization voltage (V P) can be calculated (estimated) using Equation 3-1 or Equation 3-2 below. <Formula 3-1> <Formula 3-2> In Equations 3-1 and 3-2, V P [k] is the current polarization voltage, V P [k-1] is the polarization voltage of the previous cycle, τ is the RC pair (R P , C P ) time constant, R P [k] Current meeting resistance (R P ) represents the resistance value. τ is R P [k-1] and R P One of [k] and C P [k-1] and C P [k] can be a product of one of V P [0] can be set to 0 V. The first extended Kalman filter will now be described in detail. The state equation of the first extended Kalman filter can be expressed as Equation 4-1 or Equation 4-2 below. Equation 4-1 is related to Equations 1 and 3-1, and Equation 4-2 is related to Equations 1 and 3-2. <Formula 4-1> <Formula 4-2> In Equations 4-1 and 4-2, SOC ^ [k-1] is the SOC estimated in the previous round, V P^ [k-1] is the polarization voltage estimated in the previous round, Q i is the maximum capacity of the battery (B), τ is the RC pair (R P , C P ) represents the time constant of x ^ - [k] is the current meeting state matrix, and the SOC included in it ^ - [k] and VP^ - [k] is a state variable representing the SOC and polarization voltage predicted at the current time, respectively. The following equation 5 is the time update equation of the first extended Kalman filter. <Formula 5> In Equation 5, P[k-1] is the error covariance matrix estimated in the previous round, W is the process noise covariance matrix, and P - [k] represents the error covariance matrix predicted in the current iteration. A1 in Equation 5 is the Jacobian of the function f1 in Equations 4-1 and 4-2. The Jacobian (A1) can be expressed as in Equation 5-1 below. <Formula 5-1> A1 T is the transpose matrix of A1. At k=0, P[0]=[ 1 0 ; 0 1 ]. The control unit (130) executes the measurement update process when the time update process using Equation 4-1 or Equation 4-2 and Equation 5 is completed. The following equation 6 is the first measurement update equation of the first extended Kalman filter. <Formula 6> In Equation 6, K[k] is the current Kalman gain, H1 is the Jacobian of function h1 according to Equation 6-1 below, H1 T is the transpose of H1, and L is the measurement noise covariance matrix. Regarding Equation 6, the state matrix (x ^ - By relating [k]) to Equation 2-1, a terminal voltage prediction equation (output equation) such as Equation 6-1 below can be derived. <Formula 6-1> The Jacobian (H1) of Equation 6 can be expressed as Equation 6-2 below. <Formula 6-2> The following equation 7 is the second measurement update equation of the first extended Kalman filter. <Formula 7> In Equation 7, P[k] is P from Equation 5 - [k] is the result corrected by Equation 7. The following equation 8 is the third measurement update equation of the first extended Kalman filter. <Formula 8> In Equation 8, z[k] is the terminal voltage detected at the current time, z ^ [k] is the terminal voltage estimated at the current time, SOC ^ [k] is the estimated SOC at the current time (representing the ‘first SOC estimate’ in the claim), V P^ [k] is the polarization voltage estimated at the current time. x by Equation 8 ^ [k] is x in formula 4 in the next round ^ It can be used as [k-1]. When the first extended Kalman filter is executed by the control unit (130), a first SOC estimate value representing the current SOC of the battery (B) is output from the first extended Kalman filter according to the process described above. The control unit (130) can execute the second extended Kalman filter in parallel while the first extended Kalman filter is executed. That is, the first extended Kalman filter and the second extended Kalman filter can be executed simultaneously. From now on, the constant current charge / discharge map will be explained first, and then the second extended Kalman filter will be explained in detail. Figure 4 is a drawing used for reference in explaining a constant current charge / discharge map (400) according to the present invention. The constant current charge / discharge map (400) includes a plurality of charge curves (411 to 416) and a plurality of discharge curves (421 to 426). Each of the multiple charge curves (411-416) represents the terminal voltage for the SOC of the battery (B) during a constant current charge cycle using a different current rate (which may be referred to as a 'C-rate'). CCV may be a term referring to the terminal voltage of the battery (B) measured during charging or discharging. During a charge cycle, the higher the current rate, the higher the CCV at the same SOC. Each of the multiple discharge curves (421-416) represents the voltage versus state of charge (SOC) of the battery (B) during a constant current discharge cycle using different current rates. During the discharge cycle, the higher the current rate, the lower the CCV at the same SOC. A plurality of charge curves (411 to 416) and a plurality of discharge curves (421 to 416) are each depicted as six, and the current rates are, in order of magnitude, 0.05 C, 0.15 C, 0.25 C, 0.50 C, 1.00 C, and 1.50 C. Each curve included in the constant current charge / discharge map (400) can be stored in the memory unit (140) in the form of a function. To aid understanding, FIG. 4 illustrates two SOC-OCV curves (310, 320) of FIG. 3, along with a plurality of charge curves (411-416) and a plurality of discharge curves (421-416). As can be seen from FIG. 4, as the current rate used to progress the charge cycle increases, the voltage inflection section present in the SOC-OCV curve (310) gradually disappears. Similarly, as the current rate used to progress the discharge cycle increases, the voltage inflection section present in the SOC-OCV curve (320) also gradually disappears. As mentioned above, it is by no means easy to design an equivalent circuit model (200) that fully describes the so-called fading characteristic, in which the voltage inflection section disappears as the current rate increases. Furthermore, if an equivalent circuit model (200) that fails to describe the fading characteristic above a certain level during constant current charging or constant current charging is used to estimate the SOC of a battery (B), an excessive gap may occur between the actual and estimated SOC values. Therefore, during constant current charging or constant current discharging, the SOC of the battery (B) is estimated based only on the output value of the second extended Kalman filter using the constant current charging / discharging map (400) instead of the output value of the first extended Kalman filter, or the SOC of the battery (B) is estimated by combining (e.g., weighted average) the output value of the first extended Kalman filter and the output value from the second extended Kalman filter, thereby significantly resolving the above-described problem. Unlike the first extended Kalman filter whose state variables are SOC and polarization voltage, the second extended Kalman filter uses only SOC excluding polarization voltage as its state variable, which can be expressed as in the following equation 9. <Formula 9> In Equation 9, x ^ [k-1] is the estimated SOC value of the previous cycle, i[k] is the current value of the charge / discharge current detected in the current cycle, and Q i is the maximum capacity of the battery (B), x ^ - [k] is the current meeting SOC prediction value. x ^ - [k] is the SOC representing the SOC predicted in the current session ^ - can be equal to [k], and f2(x ^ [k-1]) is x ^ It can be equal to [k-1]. The following equation 10 is the time update equation of the second extended Kalman filter. <Formula 10> In Equation 10, P[k-1] is the error covariance estimated in the previous round, w is the process noise covariance, and P - [k] represents the predicted error covariance for the current iteration. A2 is the Jacobian of the function f2 in Equation 9. The Jacobian (A2) can be expressed as in Equation 10-1 below. <Formula 10-1> A2 T is the transpose matrix of A2. At k=0, P[0] = 0. When the time update process using Equations 9 and 10 is completed, the control unit (130) executes the measurement update process. The following equation 11 is the first measurement update equation of the second extended Kalman filter. <Formula 11> In Equation 11, K[k] is the current Kalman gain, H2 is the Jacobian of the function h2 in Equation 11-1 below, H2 T is the transpose of H2, and l is the measurement noise covariance. With respect to Equation 11, unlike the first extended Kalman filter, the second extended Kalman filter utilizes a constant current charge / discharge map (400), so that a terminal voltage prediction equation (output equation) such as Equation 12-1 below can be derived. <Formula 12-1> In Equation 12-1, function f CCV_I[k]is a function that defines one charging curve or discharge curve associated with a current rate corresponding to I[k] among the curves included in the constant current charge / discharge map (400). The control unit (130) selects one charging curve corresponding to I[k] among a plurality of charging curves (411 to 416) in response to I[k] being the charging current. Selecting one of the charging curves means receiving a function f from the memory unit (140). CCV_I[k] may mean acquiring. Next, the control unit (130) may acquire a state variable (SOC ^ - [k]) is the input function f CCV_I[k] The output value of (z) ^ [k]), the predicted value of the current terminal voltage of the battery (B) can be set. Additionally, the Jacobian (H) of Equation 12-1 can be expressed as Equation 12-2 below. <Formula 12-2> The following equation 13 is the second measurement update equation of the second extended Kalman filter. <Formula 13> In Equation 13, P[k] is P from Equation 10 - [k] is the result corrected by Equation 13. The following equation 14 is the third measurement update equation of the second extended Kalman filter. <Formula 14> In Equation 14, z[k] is the terminal voltage detected at the current time, z ^ [k] is the terminal voltage estimated at the current time, SOC ^ [k] is the estimated SOC at the current time (representing the 'second SOC estimate' in the claim). x by Equation 14 ^ [k] is x in formula 9 in the next round ^ It can be used as [k-1]. So far, the SOC estimation of the battery (B) by the first extended Kalman filter and the second extended Kalman filter has been explained. The control unit (130) determines the maximum capacity (Q) of the battery (B), which is a basic variable used by the first extended Kalman filter and the second extended Kalman filter. i ) can be determined using the following equation 15. <Formula 15> In Equation 15, ΔSOC is the change in SOC during the capacity update period, and ΔQ is the current integration value by ampere counting during the capacity update period. In Equation 15, a is the time index corresponding to the start of the capacity update period, and b is the time index corresponding to the end of the capacity update period. The capacity update period may be the most recent period during which ΔSOC exceeds the threshold change (e.g., 0.5). As battery (B) degrades, its maximum capacity gradually decreases. Therefore, a battery (B) that has degraded beyond a certain level is highly likely to suddenly become unusable, making it necessary to estimate its SOC more precisely. Figure 5 is a flowchart exemplifying a battery management method for SOC estimation according to a first embodiment of the present invention. The method of Figure 5 can be repeatedly performed at set intervals from the time a predetermined event occurs. Referring to FIGS. 1 to 5, in step S510, the control unit (130) detects the terminal voltage (V[k]) and the charge / discharge current (I[k]) of the battery (B) and determines the voltage value (V[k]) of the terminal voltage and the current value (I[k]) of the charge / discharge current. In step S520, the control unit (130) inputs the voltage value (V[k]), the current value (I[k]) and the previous SOC estimation value into the first extended Kalman filter to determine the first SOC estimation value. The first extended Kalman filter is an SOC estimation logic that uses the equivalent circuit model (200) of the battery (B) and the SOC-OCV curve (300). The first SOC estimation value can be said to be a candidate value representing the SOC of the current battery (B). The voltage value (V[k]) of the terminal voltage can be used as z[k] of Equation 8. If the current value (I[k]) indicates the charging direction, the control unit (130) can provide the SOC-OCV curve (310) among the two SOC-OCV curves (310, 320) to the first extended Kalman filter. On the other hand, when the current value (I[k]) indicates the discharge direction, the control unit (130) can provide the SOC-OCV curve (320) among the two SOC-OCV curves (310, 320) to the first extended Kalman filter. In step S530, the control unit (130) inputs the current value and the previous SOC estimation value into the second extended Kalman filter to determine the second SOC estimation value. The second extended Kalman filter is an SOC estimation logic that uses the constant current charge / discharge map (400) of the battery (B). The second SOC estimation value can be said to be another candidate value representing the SOC of the current battery (B). If the current value (I[k]) represents the charging direction, the control unit (130) can provide one of the charging curves (310) associated with the current rate corresponding to the current value (I[k]) among the plurality of charging curves (411 to 416) to the second extended Kalman filter. On the other hand, when the current value (I[k]) indicates the discharge direction, the control unit (130) can provide one discharge curve associated with the current rate corresponding to the current value (I[k]) among the plurality of discharge curves (421 to 426) to the second extended Kalman filter. When the time index k is 1, the average value of two SOCs corresponding to the OCV at the initial time point (t0) in the two curves (310, 320) can be input to the first extended Kalman filter and the second extended Kalman filter as the previous SOC estimation value in steps S520 and S530. In step S540, the control unit (130) determines the current SOC of the battery (B) based on at least one of the first SOC estimate value and the second SOC estimate value. FIG. 6 is a flowchart exemplarily illustrating a battery management method for SOC estimation according to a second embodiment of the present invention. The method of FIG. 6 may be an example of a sub-routine set of step S540 of the battery management method according to FIG. 5. Referring to FIG. 6, in step S610, the control unit (130) determines whether the battery (B) is in constant current charging / discharging based on current time series data representing the temporal change history of the current value (I[k]) or the charge / discharge current. For example, when the time index k=100, the current time series data is I[1]~I

[0100] are included as data points. The value of step S610 being "No" means that the battery (B) is in a first state that is not in constant current charging / discharging. If the value of step S610 being "No", the process proceeds to step S620. If the value of step S610 being "Yes" means that the battery (B) is in a second state that is in constant current charging / discharging. If the value of step S610 being "Yes", the process proceeds to step S630. In step S620, the control unit (130) determines the current SOC of the battery (B) to be the same as the first SOC estimate. In step S630, the control unit (130) determines the current SOC of the battery (B) to be the same as the second SOC estimate. FIG. 7 is a flowchart exemplarily showing a battery management method for SOC estimation according to a third embodiment of the present invention, and FIG. 8 is a diagram referenced in explaining the method according to FIG. 7. The method of FIG. 7 may be another example of a sub-routine set of step S540 of the battery management method according to FIG. 5. In other words, the third embodiment is a variation of the second embodiment. Referring to FIG. 7, in step S710, the control unit (130) determines whether the battery (B) is in constant current charging / discharging based on current time series data representing the temporal change history of the current value (I[k]) or the charge / discharge current. If the value of step S710 is "No," the process proceeds to step S720. If the value of step S710 is "Yes," the process proceeds to step S730. In step S720, the control unit (130) determines a first weight and a second weight, which have a positive and negative correlation, respectively, with the duration of the first state. The first weight may be greater than the second weight. The sum of the first and second weights may be a predetermined constant (e.g., 1). In this case, if either the first or second weight is determined, the other may also be determined. Figure 8 is a graph exemplarily showing the change in the first weight with respect to the duration of the first state. Referring to Figure 8, the minimum value of the first weight is 0.6, and the time range (0 to t S1 ) As the duration of the first state increases, the first weight also increases, and the duration of the first state is the first reference time (t S1 ) is shown as an example in which the first weight remains constant at 1. In step S722, the control unit (130) determines the current SOC of the battery (B) as the same as the weighted average of the first SOC estimate value and the second SOC estimate value by the first weight and the second weight. For example, if the first weight = 0.8, the second weight = 1 - the first weight = 0.2, the first SOC estimate value = 0.60, and the second SOC estimate value = 0.62, the weighted average = (0.8*0.60) + (0.2*0.62) = 0.604. That is, the current SOC of the battery (B) can be determined as 60.4%. In step S730, the control unit (130) determines the current SOC of the battery (B) to be the same as the second SOC estimate. FIG. 9 is a flowchart exemplarily showing a battery management method for SOC estimation according to a fourth embodiment of the present invention, and FIG. 10 is a diagram referenced in explaining the method according to FIG. 9. The method of FIG. 9 may be another example of a sub-routine set of step S540 of the battery management method according to FIG. 5. In other words, the fourth embodiment is an additional modification of the second embodiment. Referring to FIG. 9, in step S910, the control unit (130) determines whether the battery (B) is in constant current charging / discharging based on current time series data representing the temporal change history of current values ​​or charge / discharge currents. If the value of step S910 is "No," the process proceeds to step S920. If the value of step S910 is "Yes," the process proceeds to step S930. In step S920, the control unit (130) determines the current SOC of the battery (B) to be the same as the first SOC estimate. In step S930, the control unit (130) determines a third weight and a fourth weight, which have a negative correlation and a positive correlation, respectively, with the duration of the second state. The third weight may be smaller than the fourth weight. The sum of the third and fourth weights may be a predetermined constant (e.g., 1). In this case, if either the third or fourth weight is determined, the other may also be determined. Figure 10 is a graph exemplarily showing the change in the third weight with respect to the duration of the second state. Referring to Figure 10, the maximum value of the third weight is 0.4, and the time range (0 to t S2 ) as the duration of the second state increases, the third weight decreases, and the duration of the second state is the second reference time (t S2 ) is shown as being maintained at a constant value of 0. In step S932, the control unit (130) determines the current SOC of the battery (B) as the same as the weighted average of the first SOC estimate value and the second SOC estimate value by the third weight and the fourth weight. For example, if the third weight = 0.1, the fourth weight = 1 - the third weight = 0.9, the first SOC estimate value = 0.60, and the second SOC estimate value = 0.62, the weighted average = (0.1*0.60) + (0.9*0.62) = 0.618. That is, the current SOC of the battery (B) can be determined as 61.8%. FIG. 11 is a flowchart exemplifying a battery management method for SOC estimation according to a fifth embodiment of the present invention. The method of FIG. 11 may be another example of a subset of the routines of step S540 of the battery management method of FIG. 5 . In other words, the fifth embodiment is an additional variation of the second embodiment. Referring to FIG. 11, in step S1110, the control unit (130) determines whether the battery (B) is in constant current charging / discharging based on current time series data representing the temporal change history of the current value or charge / discharge current. If the value of step S1110 is "No," the process proceeds to step S1120. If the value of step S1110 is "Yes," the process proceeds to step S1130. In step S1120, the control unit (130) determines a first weight and a second weight having a positive correlation and a negative correlation, respectively, with the duration of the first state. In step S1122, the control unit (130) determines the current SOC of the battery (B) as equal to the weighted average of the first SOC estimate value and the second SOC estimate value by the first weight and the second weight. Steps S1120 and S1122 are identical to steps S720 and S722 of FIG. 7. In step S1130, the control unit (130) determines a third weight and a fourth weight having a negative correlation and a positive correlation, respectively, with respect to the duration of the second state. In step S1132, the control unit (130) determines the current SOC of the battery (B) as the same as the weighted average of the first SOC estimate value and the second SOC estimate value by the third weight and the fourth weight. Steps S1130 and S1132 are identical to steps S930 and S932 of FIG. 9. Fig. 12 is a flowchart exemplarily illustrating a method for determining whether a battery is undergoing constant current charging and discharging. The method of Fig. 12 may be a set of at least one subroutine among step S610 of Fig. 6, step S710 of Fig. 7, step S910 of Fig. 9, and step S1110 of Fig. 11. In step S1210, the control unit (130) filters the current time series data using a high pass filter (HPF). A high pass filter is a filter that removes signal components below a predetermined cutoff frequency and passes only signal components above the cutoff frequency. If the battery (B) is in the second state or at rest, the output value of the high pass filter may be 0, and otherwise, the output value of the high pass filter may not be 0. The smaller the fluctuation of the current flowing through the battery (B), the closer the output value of the high pass filter becomes to 0. In step S1220, the control unit (130) determines whether the output value of the high-pass filter is within a reference range (e.g., -0.001 to 0.001). If the value of step S1220 is "Yes", the process may proceed to step S1230. The reference range may be appropriately determined in advance in consideration of the filtering precision of the high-pass filter and the detection precision of the current detection unit (113). If the value of step S1220 is "No", the process proceeds to one of step S620 of FIG. 6, step S720 of FIG. 7, step S910 of FIG. 9, and step S1120 of FIG. 11. In step S1230, the control unit (130) determines whether the current value is 0 [A]. If the value of step S1230 is "Yes", the process proceeds to one of steps S620 of FIG. 6, S720 of FIG. 7, S910 of FIG. 9, and S1120 of FIG. 11. If the value of step S1230 is "No", the process proceeds to one of steps S630 of FIG. 6, S730 of FIG. 7, S930 of FIG. 9, and S1130 of FIG. 11. Meanwhile, although steps S610 of FIG. 6, S710 of FIG. 7, S910 of FIG. 9, and S1110 of FIG. 11 have been described as subroutines of step S540, they should be understood as just one example. For example, at least one of steps S610 of FIG. 6, S710 of FIG. 7, S910 of FIG. 9, and S1110 of FIG. 11 may be performed using the current value determined in step S510 before steps S520 or S530 of FIG. 5 are performed. The embodiments of the present invention described above are not implemented only through devices and methods, but may also be implemented through a program that realizes a function corresponding to the configuration of the embodiments of the present invention or a recording medium on which the program is recorded, and such implementation can be easily implemented by an expert in the technical field to which the present invention belongs based on the description of the embodiments described above. Although the present invention has been described above with reference to limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical idea of ​​the present invention and the equivalent scope of the patent claims to be described below by a person having ordinary skill in the art to which the present invention pertains. In addition, the present invention described above is not limited to the above-described embodiments and the attached drawings, and all or part of each embodiment may be selectively combined and configured so that various modifications can be made, as those skilled in the art can make various substitutions, modifications, and changes within the scope of the technical idea of ​​the present invention.

Claims

1. In a battery management system for a battery having a characteristic in which the voltage inflection section changes according to the current rate, A sensing unit configured to detect the terminal voltage and charge / discharge current of the battery; A memory unit configured to store a first Kalman filter, which is an SOC estimation logic using an equivalent circuit model of the battery and an SOC (State Of Charge)-OCV (Open Circuit Voltage) curve, and a second Kalman filter, which is an SOC estimation logic using a constant current charge / discharge map of the battery; and It includes a control unit configured to determine the voltage value of the detected terminal voltage and the current value of the detected charge / discharge current, The above control unit, By inputting the voltage value, the current value, and the previous SOC estimate value into the first Kalman filter, the first SOC estimate value is determined, By inputting the current value and the previous SOC estimate value into the second Kalman filter, a second SOC estimate value is determined, A battery management system configured to determine the current SOC of the battery based on at least one of the first SOC estimate value and the second SOC estimate value.

2. In paragraph 1, The above control unit, Based on the current time series data representing the temporal change history of the current value or the charge / discharge current, it is determined whether the battery is in a first state in which it is not in constant current charge / discharge and a second state in which the battery is in constant current charge / discharge, In response to being determined to be in the first state, the current SOC of the battery is determined to be equal to the first SOC estimate, A battery management system configured to determine the current SOC of the battery in response to being determined to be in the second state, the current SOC of the battery being equal to the second SOC estimate.

3. In paragraph 1, The above control unit, Based on the current time series data representing the temporal change history of the current value or the charge / discharge current, it is determined whether the battery is in a first state in which it is not in constant current charge / discharge and a second state in which the battery is in constant current charge / discharge, In response to being determined to be in the first state, a first weight having a positive correlation with the duration of the first state and a second weight having a negative correlation with the duration of the first state are determined, A battery management system configured to determine the current SOC of the battery as the same as the weighted average of the first SOC estimate value and the second SOC estimate value by the first weight and the second weight.

4. In paragraph 3, The first weight is greater than the second weight, A battery management system wherein the sum of the first weight and the second weight is 1.

5. In paragraph 1, The above control unit, Based on the current time series data representing the temporal change history of the current value or the charge / discharge current, it is determined whether the battery is in a first state in which it is not in constant current charge / discharge and a second state in which the battery is in constant current charge / discharge, In response to being determined to be in the second state, a third weight having a negative correlation with the duration of the second state and a fourth weight having a positive correlation with the duration of the second state are determined, A battery management system configured to determine a weighted average of the first SOC estimate value and the second SOC estimate value by the third weight and the fourth weight as the current SOC of the battery.

6. In paragraph 5, The third weight is smaller than the fourth weight, A battery management system in which the sum of the third weight and the fourth weight is 1.

7. In paragraph 1, The above constant current charge / discharge map is, A plurality of charging curves showing the relationship between the SOC and voltage of the battery during constant current charging using multiple current rates; and A plurality of discharge curves showing the relationship between the SOC and voltage of the battery during constant current discharge using the plurality of current rates; Including, The above second SOC estimate is, A battery management system, wherein when one of the plurality of charging curves and the plurality of discharging curves is provided to the second Kalman filter, the second Kalman filter outputs a curve.

8. In paragraph 7, The above control unit, In response to the battery being charged at a constant current, one of the plurality of charging curves is provided to the second Kalman filter, wherein the charging curve is associated with a current rate corresponding to the current value. A battery management system configured to provide, in response to the battery being discharged at a constant current, one of the plurality of discharge curves, among the discharge curves, to the second Kalman filter, wherein the one of the plurality of discharge curves is associated with a current rate corresponding to the current value.

9. A battery pack comprising a battery management system according to any one of claims 1 to 8.

10. An electric vehicle comprising a battery pack according to Article 9.

11. In a battery management method for a battery having a characteristic in which the voltage inflection section changes according to the current rate, A step of detecting the terminal voltage and charge / discharge current of the battery and determining the voltage value of the detected terminal voltage and the current value of the detected charge / discharge current; A step of inputting the voltage value, the current value, and the previous SOC estimation value into a first Kalman filter, which is an SOC estimation logic using an equivalent circuit model of the battery and an SOC (State Of Charge)-OCV (Open Circuit Voltage) curve, to determine a first SOC estimation value; A step of inputting the current value and the previous SOC estimation value into a second Kalman filter, which is an SOC estimation logic using the constant current charge / discharge map of the battery, to determine a second SOC estimation value; and A step of determining the current SOC of the battery based on at least one of the first SOC estimate value and the second SOC estimate value; A battery management method comprising:

12. In paragraph 11, The step of determining the current SOC of the above battery is: A step of determining whether the battery is in a first state in which it is not in constant current charging / discharging or a second state in which the battery is in constant current charging / discharging based on current time series data representing the temporal change history of the current value or the charge / discharge current; In response to determining that the battery is in the first state, determining the first SOC estimate as the current SOC of the battery; and In response to determining that the second state is present, a step of determining the second SOC estimate as the current SOC of the battery; A battery management method comprising:

13. In paragraph 11, The step of determining the current SOC of the above battery is: A step of determining whether the battery is in a first state in which it is not in constant current charging / discharging or a second state in which the battery is in constant current charging / discharging based on current time series data representing the temporal change history of the current value or the charge / discharge current; In response to being determined to be in the first state, determining a first weight having a positive correlation with the duration of the first state and a second weight having a negative correlation with the duration of the first state; and A step of determining a weighted average of the first SOC estimate value and the second SOC estimate value by the first weight and the second weight as the current SOC of the battery; A battery management method comprising:

14. In paragraph 11, The step of determining the current SOC of the above battery is: A step of determining whether the battery is in a first state in which it is not in constant current charging / discharging or a second state in which the battery is in constant current charging / discharging based on current time series data representing the temporal change history of the current value or the charge / discharge current; In response to being determined to be in the second state, determining a third weight having a negative correlation with the duration of the second state and a fourth weight having a positive correlation with the duration of the second state; and A step of determining a weighted average of the first SOC estimate value and the second SOC estimate value by the third weight and the fourth weight as the current SOC of the battery; A battery management method comprising:

15. In paragraph 11, The above constant current charge / discharge map is, A plurality of charging curves showing the relationship between the SOC and voltage of the battery during constant current charging using multiple current rates; and A plurality of discharge curves showing the relationship between the SOC and voltage of the battery during constant current discharge using the plurality of current rates; Including, The above second SOC estimate is, A battery management method, wherein when one of the plurality of charging curves and the plurality of discharging curves is provided to the second Kalman filter, the second Kalman filter outputs a curve.

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