Apparatus and method for calculating battery energy

Abstract

The invention discloses equipment and a method for calculating battery energy, which can eliminate the problems of test complexity, time consumption and test data dependence caused by a typical battery energy calculation method. To this end, the present disclosure provides a configuration for calculating a target power based on a target SOC, a target OCV, and a target resistance value defined for a plurality of nodes, and then calculating battery energy for the calculated target power using a weighted sum method.

Description

Technical Field

[0001] The present invention relates to an apparatus and method for calculating battery energy. Background Art

[0002] The energy stored in a battery (e.g., a lithium-ion battery), hereinafter referred to as battery energy, is defined as the cumulative power of the battery when the battery is discharged from a defined maximum state of charge (SOC) to a defined minimum SOC, and is a key indicator of the performance of the battery. For example, battery energy is directly related to the mileage that an electric vehicle can travel when the battery is fully or partially charged, where the charge level of the battery is defined as the SOC. In addition, battery energy is also used as a measure of the state of health (SOH), which is the ratio of the stored energy in the current state to the energy defined for a new battery cell at the beginning of life (BOL), and the end-of-life (EOL) condition of the battery can be defined based on the battery energy.

[0003] A discharge method applied to battery energy measurement is implemented through a standard curve (such as the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) or the Urban Dynamometer Driving Schedule (UDDS)) or through a specific curve (such as constant power or constant current). Battery energy is calculated as the integral value of the power extracted from the battery when discharging the battery at a specific temperature and within a specific SOC range according to the above discharge method. A common method for calculating battery energy is to perform a discharge test at various SOHs of the battery, and then record the test results in a look-up table or find a suitable fitting function. However, this method is complex, time-consuming, and dependent on specific test data. In addition, when the test conditions change, it is inconvenient to repeat all the necessary tests again. Therefore, there is a need to improve the typical method for calculating battery energy.

[0004] This section is only intended to provide a better understanding of the background of the present invention, and thus may include information that is not necessarily prior art. Summary of the Invention

[0005] One aspect of the present invention is to provide an apparatus and method for calculating battery energy, which eliminates the problems of test complexity, time consumption, and test data dependence associated with typical methods for calculating battery energy.

[0006] From the following description of the embodiments of the present invention, the above and other aspects and features of the present invention will become readily understood.

[0007] According to one aspect of the present invention, there is provided an apparatus and method for calculating battery energy, which calculates a target power based on target SOCs, target OCVs, and target resistance values defined for a plurality of nodes, and then sums the weighted sum of the calculated target powers to calculate the battery energy.

[0008] According to one aspect of the present invention, there is provided a device for calculating battery energy, the device comprising: a memory storing relationship information between a stepped state of charge of a battery device and a plurality of battery characteristic information corresponding to each stepped state of charge; and a processor operably connected to the memory; wherein the processor performs the following operations: calculating a plurality of target states of charge, each target state of charge in the plurality of target states of charge being defined for a preset plurality of nodes; calculating a plurality of target battery characteristic information based on the relationship information stored in the memory and the calculated plurality of target states of charge, each target battery characteristic information in the plurality of target battery characteristic information being defined for the plurality of nodes; calculating a plurality of target powers through the calculated plurality of target battery characteristic information, each target power in the plurality of target powers being defined for the plurality of nodes; and determining the energy of the battery device by using a weighted sum method for the calculated plurality of target powers.

[0009] According to one aspect of the present invention, there is provided a method for calculating battery energy, the method comprising the steps of: calculating, by a processor, a plurality of target states of charge, calculating a plurality of target battery characteristic information based on the calculated plurality of target states of charge and relationship information, each target state of charge in the plurality of target states of charge being defined for a preset plurality of nodes, each target battery characteristic information in the plurality of target battery characteristic information being defined for the plurality of nodes, the relationship information defining a relationship between a stepped state of charge of a battery device and a plurality of battery characteristic information corresponding to each stepped state of charge; calculating, by the processor, a plurality of target powers according to the calculated plurality of target battery characteristic information, each target power in the plurality of target powers being defined for the plurality of nodes; and calculating, by the processor, the energy of the battery device by using a weighted sum method for the calculated plurality of target powers.

[0010] According to an aspect of the present invention, there is provided a computer-readable storage medium storing a computer program which, in combination with hardware, performs the following steps: calculating a plurality of target state of charge, calculating a plurality of target battery characteristic information based on the calculated plurality of target state of charge and relationship information, each of the plurality of target state of charge being defined for a plurality of preset nodes, each of the plurality of target battery characteristic information being defined for the plurality of nodes, and the relationship information defining the relationship between the stepped state of charge of the battery device and the plurality of battery characteristic information corresponding to each stepped state of charge; calculating a plurality of target powers based on the calculated plurality of target battery characteristic information, each of the plurality of target powers being defined for the plurality of nodes; and calculating the energy of the battery device using a weighted sum method for the calculated plurality of target powers.

[0011] The device and method according to the present invention eliminate the problems of test complexity, time consumption, and test data dependence associated with typical methods for calculating battery energy by calculating battery energy based on a simple and improved model.

[0012] However, the aspects and features of the present invention are not limited to those described above, and those skilled in the art will clearly understand other aspects and features not mentioned from the specific embodiments given below. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The following drawings attached to this specification illustrate embodiments of the present invention and further describe the aspects and features of the present invention together with the specific embodiments of the present invention. Therefore, the present invention should not be construed as being limited to the drawings, in which:

[0014] Figure 1 is a block diagram of a device for calculating battery energy according to an embodiment of the present invention;

[0015] Figure 2 is a diagram showing battery characteristic information in a device for calculating battery energy according to an embodiment of the present invention;

[0016] Figures 3A to 3D is a diagram showing the error rate of battery energy calculated by a device for calculating battery energy according to an embodiment of the present invention;

[0017] Figure 4 is a flowchart showing a method for calculating battery energy according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Based on the principle that the inventor can be his / her own lexicographer to appropriately define terms in order to best explain his / her invention, the terms or words used in this specification and claims should not be construed as limited to the ordinary meaning or the meaning in the dictionary, and should be construed as having meanings and concepts consistent with the technical concept of the present invention. The embodiments described in this specification and the configurations shown in the accompanying drawings are only some embodiments of the present invention, and do not represent all technical ideas, aspects, and features of the present invention. Therefore, it should be understood that there may be various equivalent solutions and modifications that can replace or modify the embodiments described herein at the time of filing this application. It will be further understood that the terms "comprising" and / or "including" when used in this specification specify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. In addition, when describing embodiments of the present invention, the use of "may" relates to "one or more embodiments of the present invention".

[0019] In the drawings, for clarity of illustration, the dimensions of various elements, layers, etc. may be exaggerated. The same reference numerals denote the same elements.

[0020] Referring to two compared elements, features, etc. as "the same" may mean that they are "substantially the same". Thus, the phrase "substantially the same" may include cases having a deviation considered to be low in the art (e.g., a deviation of 5% or less). Additionally, when a specific parameter is said to be uniform in a given region, it may mean that it is uniform in terms of the average value.

[0021] It will be understood that although the terms "first", "second", "third", etc. may be used herein to describe various elements, components, regions, layers, and / or parts, these elements, components, regions, layers, and / or parts should not be limited by these terms. These terms are used to distinguish one element, component, region, layer, or part from another element, component, region, layer, or part. Thus, without departing from the teachings of the exemplary embodiments, the first element, first component, first region, first layer, or first part discussed below may be referred to as the second element, second component, second region, second layer, or second part.

[0022] Throughout the specification, unless otherwise specified, each element may be single or plural.

[0023] When any element is said to be "above" (or "below") or "on" (or "under") a component, it can mean that the any element is placed in contact with the upper (or lower) surface of the component, and it can also mean that another component can be interposed between the component and any any element that is set (or located or positioned) on (or under) the component.

[0024] In addition, it will be understood that when an element is said to be "coupled", "linked" or "connected" to another element, the elements can be "coupled", "linked" or "connected" directly to each other, or there can be intermediate elements between them through which the elements can be "coupled", "linked" or "connected" to another element. In addition, when a component is said to be "electrically coupled" to another component, the component can be directly connected to the other component, or there can be intermediate components between them such that the component and the other component are indirectly connected to each other.

[0025] Throughout the specification, unless otherwise specified, when stating "A and / or B", it means A, B or A and B. That is, "and / or" includes any or all combinations of the recited items. When stating "C to D", unless otherwise specified, it means C or greater and D or less.

[0026] First, for a clear understanding of the embodiments of the present invention, the following is assumed. In the following embodiments, a battery device refers to a single battery cell, and battery energy refers to the cumulative energy of the battery device (i.e., the integral value of the power discharged from the battery) (i.e., the remaining energy of the battery device) when the battery device (i.e., the battery cell) discharges within a specific temperature and SOC range, and the specific temperature and SOC range are set according to the user input to the input module 100 described below.

[0027] Embodiments of the present invention focus on the process of calculating battery energy using experimental data obtained in advance through a discharge test of a battery device and battery parameters set by a user (described below), rather than the process of calculating battery energy through a physical discharge test of the battery device. The energy obtained from a discharge test according to a typical Worldwide Harmonized Light Vehicles Test Procedure (WLTP) curve or a constant current curve is used as a reference for determining the reliability of the battery energy calculated by the processor 400 according to an embodiment of the present invention.

[0028] As used herein, the term "target" is adopted to clarify that it corresponds to a parameter directly considered in the calculation of battery energy, and the term "step" is adopted to clarify that it corresponds to a parameter used to derive the "target" parameter.

[0029] Based on the above definitions, the following description will focus in detail on the operation of a device for calculating battery energy according to an embodiment of the present invention with reference to the accompanying drawings.

[0030] Figure 1 is a block diagram of a device for calculating battery energy according to an embodiment of the present invention; Figure 2 is a diagram showing battery characteristic information in a device for calculating battery energy according to an embodiment of the present invention; and Figures 3A to 3D is a diagram showing the error rate of battery energy calculated by a device for calculating battery energy according to an embodiment of the present invention. In Figure 2 it shows the SOC (state of charge) curve including SOC 1 、SOC 2 to SOC 100 the OCV (open circuit voltage) curve including OCV 1 、OCV 2 to OCV 100 the CCV (closed circuit voltage) curve, the Udrop (voltage drop) curve, and the resistance value (R) curve including R 1 、R 2 to R 100 .

[0031] Referring to Figure 1 , a device for calculating battery energy according to an embodiment of the present invention may include an input module 100, an output module 200, a memory 300, and a processor 400.

[0032] The input module 100 may receive from a user parameters (hereinafter referred to as battery parameters for the sake of clarity of terminology) used by the processor 400 to calculate battery energy. The input module 100 may be implemented by a computing device (e.g., a personal computer (PC) or a mobile device) providing a user interface (UI) for receiving battery parameters. The battery parameters input through the input module 100 may be sent to the processor 400 through wired communication (such as, universal asynchronous receiver / transmitter (UART), controller area network (CAN), Ethernet local area network (Ethernet LAN), serial peripheral interface (SPI), or inter-integrated circuit bus (I2C)) or through wireless communication (such as, WI-FI, Bluetooth, etc.).

[0033] The battery parameters input through the input module 100 may include: i) a first SOC (maximum SOC); ii) a second SOC (minimum SOC); iii) a current parameter for changing the SOC from the first SOC to the second SOC; iv) the temperature at which the battery energy is calculated; v) a capacity degradation parameter indicating the degree of capacity degradation of the battery device; vi) a resistance degradation parameter indicating the degree of resistance degradation of the battery device; vii) the number of battery devices connected in series; and viii) the number of battery devices connected in parallel.

[0034] In this embodiment, the battery energy is calculated by a method of simulating the process of changing the SOC of the device, where the above-mentioned first SOC (SOC MAX ) and the second SOC (SOC MIN ) respectively define the maximum value and the minimum value of the range of SOC change. The value of the first SOC is larger than the value of the second SOC.

[0035] The current parameter (I D ) is the discharge current drawn from the battery to allow the SOC to change from the first SOC (SOC MAX ) to the second SOC (SOC MIN ), and is set to the average value over time.

[0036] The temperature (Temp) is the temperature of the environment where the battery energy (i.e., the energy extracted from the battery) is obtained.

[0037] The capacity degradation parameter (facQ) is a parameter indicating the SOH of the capacity of the battery device, and is defined as the ratio of the capacity (Q cur ) at the current time to the capacity (Q bol ) at the beginning of life (BOL) of the battery device (i.e., facQ = Q cur / Q bol ×100).

[0038] The resistance degradation parameter is a parameter indicating the SOH of the direct current internal resistance (DCIR) (hereinafter referred to as "resistance value") of the battery device, and is defined as the ratio of the resistance value (R cur ) at the current time to the resistance value (R bol ) at the beginning of life (BOL) of the battery device (i.e., facR = R cur / R bol ×100).

[0039] The number of serially connected battery devices (nS) and the number of parallel connected battery devices (nP) are parameters for calculating the total energy of the battery system. In other words, if the values of both nS and nP are 1, the energy of a single battery cell is calculated, and if the value of nS or nP is 2 or greater, the energy of a battery module or a battery pack is calculated. Therefore, nS and nP are used as parameters to determine whether the target for calculating the battery energy is a battery cell, a battery module, or a battery pack.

[0040] The symbols and units of the above battery parameters are set according to Table 1 below, and the symbols and units in Table 1 are applied consistently throughout the specification.

[0041] Table 1

[0042]

[0043]

[0044] Next, the output module 200 can display the battery energy calculated by the processor 400, and can be implemented by a computing device (such as a PC or a mobile device) that provides a user interface (UI) for displaying the battery energy. The battery energy calculated by the processor 400 can be sent to the output module 200 via wired communication (such as UART, CAN, Ethernet LAN, SPI, or I2C) or via wireless communication (such as WI-FI, Bluetooth, etc.) for display thereon.

[0045] The memory 300 can store data and applications (programs or applets) related to the operation of calculating the battery energy by the processor 400 and the operating system for operating the processor 400, and the information stored in the memory 300 can be selected by the processor 400 as needed. The memory 300 can be implemented by a non-volatile storage device (such as non-volatile memory NVM), a solid-state drive (SSD) / hard disk drive (HDD) memory, a memory card (SD card), a magnetic storage medium, or a flash storage medium, etc., and can be connected to the processor 400 via wired communication (such as UART, CAN, Ethernet LAN, SPI, or I2C) or via wireless communication (such as WI-FI, Bluetooth, etc.).

[0046] To calculate the battery energy, the memory 300 can store the relationship information between the stepped state of charge (SOC) of the battery device (for example, multiple SOCs with a 1% step) and multiple battery characteristic information corresponding to each stepped SOC, where the battery characteristic information can include the stepped open circuit voltage (OCV) and the stepped resistance value corresponding to each stepped SOC. Therefore, the relationship information refers to the information that defines the relationship between each stepped SOC, each stepped OCV, and each stepped resistance value.

[0047] The relationship information can be based on experimental data obtained through a discharge test on the battery device. Here, the discharge test can adopt Figure 2 the well-known galvanostatic intermittent titration technique (GITT) test shown, where the battery device placed in a temperature chamber is charged to 100% SOC and then discharged to 0% SOC, and its temperature is stabilized at a specific temperature. Through the GITT test, a data sheet of the battery device (i.e., a battery cell) can be obtained in advance, and a function for calculating the OCV corresponding to a specific SOC (hereinafter referred to as the "first function") and the capacity (Q (Ah)) of the battery cell can be defined. According to such a data sheet, the SOC, OCV, and resistance value (R) of the battery device can be calculated and expressed according to the following Equation 1.

[0048] <Equation 1>

[0049]

[0050] OCV(t) = F OCV (SOC(t))

[0051] CCV(t) = Ucell(t)

[0052] Udrop(t) = Ucell(t) - OCV(t)

[0053]

[0054] In Equation 1, the unit of t is [sec] (this also applies to all subsequent equations), I c is the discharge current in [A], Q is the cell capacity in [Ah], and a is the unit conversion constant with a value of 36. F OCV () is the first-order function for calculating the OCV corresponding to a specific SOC. CCV represents the closed-circuit voltage, Ucell represents the cell voltage, and Udrop represents the voltage drop across the cell terminals.

[0055] Based on Equation 1, each stepped SOC and the corresponding stepped OCV and stepped resistance values can be calculated to create a lookup table of relationship information. The multiple SOCs reflected in the lookup table can have a grid with a step size of 1%, so the lookup table can define the matching relationship between the SOC for each 1% step size and the stepped OCV and stepped resistance values corresponding to each stepped SOC.

[0056] Once the lookup table is established, a function for calculating the resistance value corresponding to a specific SOC (hereinafter referred to as the "second function") can be defined. As will be described in more detail below, in this embodiment, the SOC, OCV, and resistance values for calculating the battery energy correspond to the target values defined for multiple preset nodes, rather than the values for each step size in the lookup table. The target OCV corresponding to a specific target SOC can be derived by the above first function, and since obtaining the target resistance value from a specific target SOC requires a function for converting the specific SOC to the specific resistance value (i.e., the second function), such a second function can be derived by the designer based on the lookup table and predefined in the memory 300. The analysis method for deriving the second function from the lookup table can be a regression analysis method known in the art, such as linear regression analysis or polynomial regression analysis.

[0057] Therefore, the lookup table recording the matching relationship between the stepped SOC, stepped OCV, and stepped resistance values, the first function for calculating the OCV corresponding to a specific SOC, and the second function for calculating the resistance value corresponding to a specific SOC can be stored in the memory 300 as relationship information.

[0058] On the other hand, based on the results of multiple tests (e.g., GITT tests) performed on the battery device at multiple temperatures, a multivariate form of relationship information (i.e., a look-up table and first and second functions) can be obtained and stored in the memory 300.

[0059] The processor 400 is an entity that calculates the battery energy. The processor 400 can be implemented by a central processing unit (CPU) or a system-on-chip (SoC), can run an operating system or an application to control multiple hardware or software components connected to the processor 400, and can perform various data processing and calculations. The processor 400 can be configured to execute at least one instruction stored in the memory 300 and store the data generated by the execution in the memory 300.

[0060] In particular, the processor 400 can be implemented by a vehicle controller (e.g., a battery management system BMS) to derive the driving range of the vehicle based on the battery energy calculated through the processes described below, and display the driving range through the output module 200 so that the user can identify the driving range of the vehicle at the current time. To this end, a look-up table or a function defining the relationship between the battery energy and the driving range of the vehicle can be pre-stored in the memory 300.

[0061] To calculate the battery energy, the processor 400 can be operated to perform the following: (i) calculate multiple target SOCs, and calculate multiple target battery characteristic information based on the relationship information stored in the memory 300 and the calculated multiple target SOCs, each of the multiple target SOCs being defined for a preset multiple of nodes, and each of the multiple target battery characteristic information being defined for the multiple nodes; (ii) calculate multiple target powers according to the calculated multiple target battery characteristic information, each of the multiple target powers being defined for the multiple nodes, and (iii) calculate the energy of the battery device by applying a weighted sum method to the calculated multiple target powers.

[0062] This operation of the processor 400 is based on the Gauss-Legendre Quadrature Rule. As is well known in the art, the Gauss-Legendre Quadrature Rule is a rule for approximating the definite integral of a function in numerical analysis, which can be expressed as the following Equation 2:

[0063] <Equation 2>

[0064]

[0065] where, x i is the quadrature node, w iis the quadrature weight, and n is the number of sampling points.

[0066] This embodiment focuses on the process of calculating the energy of the battery device based on the relationship information stored in the memory 300 and the Gauss-Legendre quadrature rule according to Equation 2. Multiple nodes x i , weights w i and target power P xi correspond to the quadrature nodes, quadrature weights, and function f of the Gauss-Legendre quadrature rule according to Equation 2, respectively.

[0067] Based on the above characteristics, the following description will focus on the process of calculating the battery energy with reference to the detailed operations of the processor 400.

[0068] First, the processor 400 can calculate multiple target SOCs (SOC xi ) based on the relationship information stored in the memory 300 and the calculated multiple target SOCs (SOC xi ), and can calculate multiple target OCVs (OCV xi ) and multiple target resistance values (R xi ). Each target SOC in the multiple target SOCs is defined for a preset multiple of nodes (x i ), each target OCV in the multiple target OCVs is defined for the multiple of nodes (x i ), and each target resistance value in the multiple target resistance values is defined for the multiple of nodes (x i ).

[0069] As described above, the multiple nodes (x i ) can correspond to the quadrature nodes of the Gauss-Legendre quadrature rule, and the number (n) of the nodes (x i ) can be predefined as a value for optimizing the energy of the battery device (i.e., minimizing the error of the calculated battery energy) (e.g., n = 5). In addition, each node in the multiple nodes (x i ) can be assigned a corresponding one of multiple predefined set points to optimize the energy of the battery device, and according to the Gauss-Legendre quadrature rule, the set points for each node are shown in Table 2 (n = 5).

[0070] Table 2

[0071] <![CDATA[x i > Node set point <![CDATA[x 1 > 0 <![CDATA[x 2 > -0.538469310105683 <![CDATA[x 3 > 0.538469310105683 <![CDATA[x 4 > -0.906179845938664 <![CDATA[x 5 > 0.906179845938664

[0072] Based on the configuration and set points of the nodes shown in Table 2, the processor 400 can apply the multiple set points to the first SOC (SOC MAX ), the second SOC (SOC MIN ) and the node (x i)As a function of the independent variable to calculate multiple target SOCs (SOC xi ), which can be expressed according to Equation 3:

[0073] <Equation 3>

[0074]

[0075] In an example where the number (n) of nodes (x i ) is 5, each of the five set points shown in Table 2 can be substituted into the right side of Equation 3 to calculate five target SOCs (SOC X1 , SOC X2 , SOC X3 , SOC X4 , SOC X5 ).

[0076] Once the multiple target SOCs are calculated, the processor 400 can apply the above first function (i.e., the function for converting a specific SOC to a specific OCV) to each of the multiple target SOCs (SOC xi ) calculated according to Equation 3 to calculate multiple target OCVs (OCV xi ), which can be expressed as shown in Equation 4:

[0077] <Equation 4>

[0078] OCV xi = F OCV (SOC xi ),

[0079] where F OCV () represents the first function.

[0080] In an example where the number (n) of nodes (x i ) is 5, the five target SOCs (SOC X1 , SOC X2 , SOC X3 , SOC X4 , SOC X5 ) can be substituted into the right side of Equation 4 to calculate five target OCVs (OCV X1 , OCV X2 , OCV X3 , OCV X4 , OCV X5 ).

[0081] In addition, the processor 400 can calculate multiple target resistance values (R xi ) by applying the resistance degradation parameters in Table 1 to the result values obtained by applying the multiple target SOCs (SOC ) to the above second function (i.e., the function for converting a specific SOC to a specific resistance value).xi )。Since the second function corresponds to the theoretical function defined based on Equation 1 and the look-up table in the memory 300, and the degree of resistance deterioration of the actual battery device is not reflected in the second function, the processor 400 can apply the resistance deterioration parameter (facR) to the result value obtained by applying a plurality of target SOCs (SOC xi ) to the second function to calculate a plurality of target resistance values (R xi ) in order to calculate more accurate target resistance values that reflect the degree of resistance deterioration of the actual battery device. The plurality of target resistance values (R xi ) can be calculated according to Equation 5:

[0082] <Equation 5>

[0083] R xi = R(SOC xi )·facR / b,

[0084] wherein, R() represents the second function, and b is a unit conversion constant and its value is 100.

[0085] In an example where the number (n) of nodes (x i ) is 5, the five target SOCs (SOC X1 , SOC X2 , SOC X3 , SOC X4 , SOC X5 ) can be substituted into the right side of Equation 5 to calculate the five target resistance values (R x1 , R x2 , R x3 , R x4 , R x5 ).

[0086] Once a plurality of target OCVs (OCV xi ) and a plurality of target resistance values (R xi ) are calculated according to Equation 4 and Equation 5, the processor 400 can calculate a plurality of target powers (P xi ) based on the calculated plurality of target OCVs (OCV xi ) and the calculated plurality of target resistance values (R xi ), and each target power in the plurality of target powers (P xi ) is defined for a plurality of nodes. Here, the processor 400 can calculate the plurality of target powers (P xi ) based on the plurality of target OCVs (OCV xi ), the plurality of target resistance values (R D ) and the current parameter (I xi ) in Table 1, and the plurality of target powers (P xi) Each target power in is defined for multiple nodes (x i ) This can be expressed according to Equation 6:

[0087] <Equation 6>

[0088] P xi =(OCV xi +R xi I D )I D .

[0089] Once the multiple target powers P xi are calculated according to Equation 6, the processor 400 can calculate the energy of the battery device by applying a weighted sum to the calculated multiple target powers P xi . The weighted sum follows the Gauss-Legendre quadrature rule of Equation 2.

[0090] On the other hand, in this embodiment, since the weighted sum target is the target power (P xi ) and the calculation target is the battery energy, a time interval parameter is required to calculate the battery energy. The time period (T xi ) from the time point when the SOC of the battery is the first SOC (i.e., the maximum SOC) (i.e., from the discharge start time point) to the time point when the battery discharges to a specific SOC xi can be expressed according to Equation 7 based on the relationship between current, time, capacity, and SOC (in Equation 7, the capacity of the battery device is corrected by the capacity degradation parameter (facQ)).

[0091] <Equation 7>

[0092]

[0093] Where a and b are unit conversion constants and their values are 36 and 100 respectively.

[0094] According to Equation 7, the time period (T END ) from the time point when the SOC of the battery is the first SOC (i.e., the maximum SOC) (i.e., from the discharge start time point) to the time point when the battery discharges to the second SOC (i.e., the minimum SOC) (i.e., to the discharge termination time point) can be expressed according to Equation 8:

[0095] <Equation 8>

[0096]

[0097] On the other hand, the process of calculating the battery energy (E) by applying the Gauss-Legendre quadrature rule to the multiple target powers (P xi ) calculated by Equation 6 can be expressed according to Equation 9:

[0098] <Equation 9>

[0099]

[0100] Among them, c and d are unit conversion constants, and their values are 3600 and 1000 respectively.

[0101] According to Equation 9, the time scale parameter required to calculate the battery energy (E) is equal to T END / 2. Therefore, according to Equation 8, the time scale parameter (T SCALE ) can be expressed according to Equation 10:

[0102] <Equation 10>

[0103]

[0104] As a result, the time scale parameter (T D ) applied to the weighted sum method can be calculated based on the capacity (Q) of the battery device, the current parameter (I MAX ) shown in Table 1, the capacity degradation parameter (facQ), and the first SOC (SOC MIN ) and the second SOC (SOC SCALE ).

[0105] Finally, the processor 400 can apply the time scale parameter (T SCALE ) to the result value obtained by applying the weighted sum method to multiple target powers (P xi ) to calculate the energy (E) of the battery device, which can be expressed according to Equation 11:

[0106] <Equation 11>

[0107]

[0108] The weight (w i ) according to Equation 11 is related to the node set points (x i ) according to the Gauss-Legendre quadrature rule, where the relationship means that the node set points (x i ) and the weights (w i ) of the sampling points (i) have a one-to-one correspondence with each other. The relationship is shown in Table 3.

[0109] Table 3

[0110] <![CDATA[x i > Node set point <![CDATA[w i > Weight <![CDATA[x 1 > 0 <![CDATA[w 1 > 0.5688888888888889 <![CDATA[x 2 > -0.538469310105683 <![CDATA[w 2 > 0.478628670499366 <![CDATA[x 3 > 0.538469310105683 <![CDATA[w 3 > 0.478628670499366 <![CDATA[x 4 > -0.906179845938664 <![CDATA[w 4 > 0.236926885056189 <![CDATA[x 5 > 0.906179845938664 <![CDATA[w 5 > 0.236926885056189

[0111] On the other hand, the battery energy calculated according to Equation 11 is for a single battery cell, and when a battery structure of nS battery cells connected in series or nP battery cells connected in parallel is defined as a battery system (battery module or battery pack), the total energy of the battery system can be calculated by applying at least one of the nS value and the nP value to Equation 11 and is expressed according to Equation 12:

[0112] <Equation 12>

[0113]

[0114] In addition, as described above, relationship information (i.e., look-up table and first and second functions) can be obtained based on the results of multiple tests (e.g., GITT test) performed on the battery device at multiple temperatures, stored in the memory 300, and the processor 400 can be configured to read from the memory 300 the relationship information corresponding to the current temperature input (set) through the input module 100 to calculate the energy of the battery device.

[0115] Figures 3A to 3D The process of calculating the battery energy through a typical WLTP curve is shown. Figure 3A The change in SOC is shown, Figure 3B The change in discharge current is shown, Figure 3C The change in the voltage of the battery device is shown, and Figure 3D The change in battery energy is shown. In Figures 3A to 3D Two vertical lines corresponding to the time coordinates 33.39 and 123.6 match the Figures 3A to 3D vertical lines in, and respectively indicate the change range of SOC, the change range of discharge current, the change range of the voltage of the battery device, and the change range of battery energy. Table 4 shows the battery parameters applied to Figures 3A to 3D and the battery energy is derived as 11.14 kWh.

[0116] Table 4

[0117]

[0118] When the battery parameters in Table 4 used for calculating the battery energy through the WLTP curve are equally applied to Equation 12 adopted in this embodiment, the battery energy is calculated as 11.24 kWh.

[0119] When the error rate (ε ENERGY ) is defined as shown in Equation 13, compared with the battery energy calculation result (E EXPER ) obtained through the WLTP curve, the battery energy calculation result (E eq12) The error rate is 0.89%, and it can be seen that the reliability of the method for calculating the battery energy adopted in this embodiment can be guaranteed.

[0120] <Equation 13>

[0121]

[0122] Figure 4 is a flowchart showing a method for calculating the battery energy according to an embodiment of the present invention. As described above, in this embodiment, the processor 400 operates to calculate the energy of the battery device by simulating the process of changing the SOC of the battery device from the first SOC to the second SOC, and will refer to Figure 4 describe the method for calculating the battery energy according to this embodiment. The detailed description of the same configuration as the above description will be omitted, and the following description will focus on the time series of the configuration.

[0123] First, the processor 400 calculates a plurality of target SOCs, and calculates a plurality of target battery characteristic information based on the calculated plurality of target SOCs and the relationship information stored in the memory 300 (that is, the relationship information between the stepped SOC of the battery device and the plurality of battery characteristic information corresponding to each stepped SOC). Each target SOC among the plurality of target SOCs is defined for a plurality of preset nodes, and each target battery characteristic information among the plurality of target battery characteristic information is defined for the plurality of nodes (S100). Here, the battery characteristic information may include the stepped OCV and the stepped resistance value corresponding to each stepped SOC, and the relationship information refers to the information defining the relationship between each stepped SOC, each stepped OCV, and each stepped resistance value. On the other hand, a corresponding one of a plurality of predefined set points can be assigned to each of the plurality of nodes to optimize the energy of the battery device calculated according to the weighted sum method.

[0124] In step S100, the processor 400 applies the plurality of set points to a function with the first SOC, the second SOC, and the node as independent variables to calculate the plurality of target SOCs, and then applies the calculated plurality of target SOCs to the relationship information to calculate the plurality of target OCVs and the plurality of target resistance values. Each target OCV among the plurality of target OCVs is defined for the plurality of nodes, and each target resistance value among the plurality of target resistance values is defined for the plurality of nodes. When calculating the plurality of target resistance values, the processor 400 calculates the target resistance value based on the relationship information and the resistance degradation parameter indicating the degree of resistance degradation of the battery device.

[0125] Next, the processor 400 calculates a plurality of target powers based on the plurality of target battery characteristic information calculated in step S100, where each target power among the plurality of target powers is defined for a plurality of nodes (S200). Here, the processor 400 calculates the plurality of target powers based on the plurality of target OCVs, the plurality of target resistance values, and the current parameters applied for the change from the first SOC to the second SOC, and each target power among the plurality of target powers is defined for a plurality of nodes.

[0126] Next, the processor 400 calculates a time scale parameter applied to the weighted sum method based on the capacity of the battery device, the current parameters applied to the change from the first SOC to the second SOC, the capacity degradation parameter indicating the degree of capacity degradation of the battery device, and the first SOC and the second SOC (S300). Steps S200 and S300 can be executed in any order.

[0127] Next, the processor 400 uses the weighted sum method for the plurality of target powers calculated in step S200 to calculate the energy of the battery device (S400). Specifically, the processor 400 calculates the energy of the battery device by applying the time scale parameter calculated in step S300 to the result value obtained by applying the weighted sum method to the plurality of target powers. The weights used in the weighted sum method can be related to the set points assigned to the nodes according to predefined rules (e.g., the Gauss-Legendre quadrature rule). On the other hand, in step S400, when the battery device is implemented by a single battery cell and the battery structure of nS battery cells connected in series or nP battery cells connected in parallel is defined as a battery system (where nS and nP are natural numbers greater than or equal to 2, respectively), the processor 400 can apply at least one of the nS value and the nP value to the energy of the battery device to calculate the total energy of the battery system.

[0128] Finally, the processor 400 can derive the driving range of the vehicle based on the battery energy calculated in step S400, and display the driving range through the output module 200 so that the user can identify the driving range of the vehicle at the current time (S500).

[0129] In addition, when multiple tests are performed at multiple temperatures, the multiple relationship information between the stepped SOC of the battery device and the plurality of battery characteristic information corresponding to each stepped SOC can be stored in the memory 300 in a multivariate form. Therefore, the processor 400 can read the relationship information corresponding to the current set temperature from the memory 300 to execute steps S100 to S500.

[0130] On the other hand, the method for calculating battery energy according to the present embodiment can be recorded as a computer program for executing the above steps S100 to S500 in combination with hardware, and this computer program can be stored on a computer-readable recording medium to be implemented on a general-purpose digital computer to run the computer program. The computer-readable recording medium can be a hardware device specifically configured to store and execute program instructions, such as ROM, RAM, hard disk, floppy disk, magnetic media including magnetic tape, optical media including CD-ROM and DVD, magneto-optical media including magneto-optical floppy disk, and flash memory.

[0131] Thus, the device and method according to the present invention can eliminate the problems of test complexity, time-consuming, and test data dependence associated with typical methods for calculating battery energy by calculating battery energy based on a simple and improved model.

[0132] As used herein, the term "module" may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A "module" can be an overall formed component or the smallest unit or smallest part of a component that executes one or more functions. For example, according to one embodiment, a "module" can be implemented in the form of an application-specific integrated circuit (ASIC). Additionally, the embodiments described herein can be implemented as, for example, a method or process, a device, a software program, a data stream, or a signal. Although discussed in the context of a single type of implementation (e.g., only as a method), the features discussed herein can also be implemented in other forms (e.g., a device or a program). The device can be implemented by appropriate hardware, software, firmware, etc. The method can be implemented on a device such as a processor, which generally refers to a processing device including a computer, a microprocessor, an integrated circuit, a programmable logic device, etc. The processor includes a communication device, such as a computer, a cellular phone, a personal digital assistant (PDA), and other devices that facilitate information communication between the device and the end user.

[0133] Although the present invention has been described with reference to some embodiments and drawings showing aspects of the present invention, the present invention is not limited thereto. Those skilled in the art to which the present invention pertains can make various modifications and variations within the scope of the technical spirit of the present invention and the claims and their equivalents.

Claims

1. A device for calculating battery energy, comprising: A memory storing relationship information between a step-by-step state of charge of a battery device and a plurality of battery characteristic information corresponding to each step-by-step state of charge; and a processor operatively connected to the memory; The processor performs the following operations: Calculating a plurality of target states of charge, each of the plurality of target states of charge being defined for a plurality of preset nodes; calculating a plurality of target battery characteristic information based on the relationship information stored in the memory and the plurality of target states of charge calculated, each of the plurality of target battery characteristic information being defined for the plurality of nodes; calculating a plurality of target powers through the calculated plurality of target battery characteristic information, each of the plurality of target powers being defined for the plurality of nodes; and The energy of the battery device is determined using a weighted sum method for the calculated plurality of target powers.

2. The device for calculating battery energy according to claim 1, wherein: The plurality of battery characteristic information includes a step open circuit voltage and a step resistance value corresponding to each step state of charge; and the relationship information defines a relationship among the step state of charge, the step open circuit voltage, and the step resistance value.

3. The device for calculating battery energy according to claim 2, wherein: The processor calculates the energy of the battery device by simulating a process of changing the state of charge of the battery device from a first state of charge to a second state of charge.

4. The device for calculating battery energy according to claim 3, wherein: Each of the plurality of nodes is assigned a corresponding one of a plurality of predefined set points to optimize the energy of the battery device calculated according to the weighted sum method.

5. The device for calculating battery energy according to claim 4, wherein: The processor applies the plurality of set points to a function having the first state of charge, the second state of charge, and the plurality of nodes as independent variables to calculate the plurality of target states of charge, and applies the calculated plurality of target states of charge to the relationship information to calculate a plurality of target open circuit voltages and a plurality of target resistance values, each of the plurality of target open circuit voltages being defined for the plurality of nodes, and each of the plurality of target resistance values ​​being defined for the plurality of nodes.

6. The device for calculating battery energy according to claim 5, wherein: The processor calculates the plurality of target resistance values ​​based on the relationship information and a resistance degradation parameter indicating a degree of resistance degradation of the battery device.

7. The device for calculating battery energy according to claim 5, wherein: The processor calculates the multiple target powers based on the multiple target open circuit voltages, the multiple target resistance values, and a current parameter applied to change the state of charge of the battery device from the first state of charge to the second state of charge, each of the multiple target powers being defined for the multiple nodes.

8. The device for calculating battery energy according to claim 5, wherein: The processor calculates a time scale parameter applied to the weighted sum method based on the capacity of the battery device, a current parameter applied to change the state of charge of the battery device from the first state of charge to the second state of charge, a capacity degradation parameter indicating a degree of capacity degradation of the battery device, and the first state of charge and the second state of charge.

9. The device for calculating battery energy according to claim 8, wherein: The processor calculates the energy of the battery device by applying the time scale parameter to a result value obtained by applying the weighted sum method to the plurality of target powers.

10. The device for calculating battery energy according to claim 1, wherein: Each of the plurality of nodes is assigned a corresponding one of a plurality of predefined set points so that the energy of the battery device calculated according to the weighted sum method is optimized, and the plurality of set points assigned to the plurality of nodes and the weights applied to the weighted sum method have a relationship according to a predefined rule.

11. The device for calculating battery energy according to claim 1, wherein: The battery device is implemented by a single battery cell, and when a battery structure of nS battery cells connected in series or nP battery cells connected in parallel is defined as a battery system, the processor applies at least one of an nS value and an nP value to the calculated energy of the battery device to calculate the total energy of the battery system, wherein nS and nP are natural numbers greater than or equal to 2, respectively.

12. The device for calculating battery energy according to claim 1, wherein: The relationship information is obtained based on the results of a test performed on the battery device at a specific temperature and stored in the memory, and the relationship information includes multiple relationship information based on the results of multiple tests performed at multiple temperatures, and the processor reads the relationship information corresponding to the current set temperature from the memory to calculate the energy of the battery device.

13. A method for calculating battery energy, comprising the following steps: Calculating a plurality of target states of charge by a processor, and calculating a plurality of target battery characteristic information based on the calculated plurality of target states of charge and relationship information, wherein each of the plurality of target states of charge is defined for a plurality of preset nodes, each of the plurality of target battery characteristic information is defined for the plurality of nodes, and the relationship information defines a relationship between a stepped state of charge of a battery device and a plurality of battery characteristic information corresponding to each stepped state of charge; Calculating, by the processor, a plurality of target powers according to the calculated plurality of target battery characteristic information, each of the plurality of target powers being defined for the plurality of nodes; as well as The processor calculates energy of the battery device using a weighted sum method for the calculated plurality of target powers.

14. The method for calculating battery energy according to claim 13, wherein: The plurality of battery characteristic information includes a step open circuit voltage and a step resistance value corresponding to each step state of charge; and the relationship information defines a relationship among the step state of charge, the step open circuit voltage, and the step resistance value.

15. The method for calculating battery energy according to claim 14, wherein: The processor operates to calculate the energy of the battery device by simulating a process of changing the state of charge of the battery device from a first state of charge to a second state of charge, and each of the multiple nodes is assigned a corresponding one of a predefined multiple set points to optimize the energy of the battery device calculated according to the weighted sum method.

16. The method for calculating battery energy according to claim 15, wherein: In the steps of calculating multiple target states of charge and calculating multiple target battery characteristic information, the processor applies the multiple set points to a function with the first state of charge, the second state of charge, and the multiple nodes as independent variables to calculate the multiple target states of charge, and applies the calculated multiple target states of charge to the relationship information to calculate multiple target open circuit voltages and multiple target resistance values, each of the multiple target open circuit voltages being defined for the multiple nodes, and each of the multiple target resistance values ​​being defined for the multiple nodes.

17. The method for calculating battery energy according to claim 16, wherein: In the step of calculating multiple target powers, the processor calculates the multiple target powers based on the multiple target open-circuit voltages, the multiple target resistance values, and the current parameters applied to change the state of charge of the battery device from the first state of charge to the second state of charge, each of the multiple target powers being defined for the multiple nodes.

18. The method for calculating battery energy according to claim 16, further comprising: The processor calculates a time scale parameter applied to the weighted sum method based on the capacity of the battery device, a current parameter applied to change the state of charge of the battery device from the first state of charge to the second state of charge, a capacity degradation parameter indicating the degree of capacity degradation of the battery device, and the first state of charge and the second state of charge.

19. The method for calculating battery energy according to claim 18, wherein: In the step of calculating the energy of the battery device, the processor calculates the energy of the battery device by applying the time scale parameter to a result value obtained by applying the weighted sum method to the plurality of target powers.

20. A computer-readable storage medium storing a computer program, wherein the computer program is combined with hardware to perform the following steps: Calculating a plurality of target states of charge, and calculating a plurality of target battery characteristic information based on the calculated plurality of target states of charge and relationship information, wherein each of the plurality of target states of charge is defined for a plurality of preset nodes, each of the plurality of target battery characteristic information is defined for the plurality of nodes, and the relationship information defines a relationship between a stepped state of charge of a battery device and a plurality of battery characteristic information corresponding to each stepped state of charge; calculating a plurality of target powers according to the calculated plurality of target battery characteristic information, each of the plurality of target powers being defined for the plurality of nodes; as well as The energy of the battery device is calculated using a weighted sum method with respect to the calculated plurality of target powers.

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