Electronic device, recording medium, and method for calculating output reduction rate of battery cell

Abstract

An electronic device disclosed in this document includes an information acquisition interface for acquiring time-series information related to voltage, current, temperature, and state of charge of a plurality of battery cells included in a battery pack; a memory; and a processor, wherein the processor is capable of: calculating a first resistance of a first battery cell based on current and voltage of the first battery cell; calculating a second resistance of the first battery cell based on temperature and SoC of the first battery cell; calculating an instantaneous resistance increase rate of the first battery cell based on the first resistance and the second resistance; calculating an average resistance increase rate of the first battery cell based on a plurality of instantaneous resistance increase rates of the first battery cell corresponding to respective points in time; and calculating an output reduction rate of the first battery cell based on the average resistance increase rate of the first battery cell.

Description

Technical Field

[0001] Example embodiments of this disclosure relate to an electronic device, a recording medium, and a method for calculating the output reduction rate of a single battery cell. Background Technology

[0002] In recent years, we have seen active research and development in the field of rechargeable batteries. Here, rechargeable batteries refer to batteries that can be recharged, including conventional Ni / Cd and Ni / MH batteries, as well as the more recent lithium-ion batteries. Among rechargeable batteries, lithium-ion batteries have the advantage of high energy density compared to conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in compact and lightweight forms for use as power sources in portable devices, and with their applications expanding to vehicle power, lithium-ion batteries are attracting significant attention as a next-generation energy storage medium.

[0003] To manage the quality of batteries installed in vehicles, it is important to verify and diagnose battery data. In particular, it is crucial to accurately estimate the battery resistance based on vehicle driving conditions to determine the rate of battery output degradation. Summary of the Invention

[0004] Technical goals

[0005] According to an example embodiment of this disclosure, the technical objective is to calculate a stable and accurate rate of increase in resistance by using instantaneous resistance and an estimated resistance at the beginning of life (BOL) state to calculate the rate of increase in resistance (or the rate of decrease in resistance) without applying a filter to remove noise when measuring (or estimating) the instantaneous resistance of the cell.

[0006] According to an example embodiment of this disclosure, the technical objective is to minimize measurement errors caused by variations in the battery's state of charge (SoC) or temperature by applying a filter to remove noise from the rate of increase in resistance measured for each driving cycle of the vehicle (in other words, battery charging and discharging cycles).

[0007] According to an example embodiment of this disclosure, the technical objective is to use the rate of increase in resistance of a single battery cell to calculate the rate of decrease in output.

[0008] The technical objectives to be achieved by the exemplary embodiments of this disclosure are not limited to those described above, and other technical objectives can be inferred from the following exemplary embodiments.

[0009] Technical solution

[0010] An electronic device according to an example embodiment of the present disclosure may include: an information acquisition interface that acquires time-series information about the voltage, current, temperature, and state of charge (SoC) of a plurality of battery cells included in a battery pack; a memory; and a processor. The processor may be configured to: calculate a first resistance of a first battery cell based on the current and voltage of the first battery cell; calculate a second resistance of the first battery cell based on the temperature and SoC of the first battery cell; calculate an instantaneous resistance increase rate of the first battery cell based on the first and second resistances; calculate an average resistance increase rate of the first battery cell based on a plurality of instantaneous resistance increase rates corresponding to a plurality of time points; and calculate an output reduction rate of the first battery cell based on the average resistance increase rate of the first battery cell.

[0011] The processor according to the example embodiment can be configured to: identify whether the current exceeds a predetermined threshold during a predetermined time period; calculate the voltage change and current change during the predetermined time period in response to the current exceeding the predetermined threshold; and calculate a first resistance based on the voltage change and current change.

[0012] The processor according to the example embodiment can be configured to: identify the resistance map of a first battery cell in a beginning-of-life (BOL) state; and calculate a second resistance based on the resistance map, temperature, and SoC of the first battery cell. The resistance map may be a table representing the resistance based on the temperature and SoC of the first battery cell in the BOL state.

[0013] The processor according to the example embodiment can be configured to: determine whether a first measurement condition regarding a temperature range is met based on the temperature of the first battery cell; determine whether a second measurement condition regarding a SoC range is met based on the SoC of the first battery cell; and determine the validity of the instantaneous resistance increase rate of the first battery cell in response to whether the first and second measurement conditions are met.

[0014] The processor according to the example embodiment can be configured to: determine whether a third measurement condition regarding temperature deviation is met based on the temperature of multiple battery cells; determine whether a fourth measurement condition regarding SoC error is met based on the SoC of the multiple battery cells; and determine, in response to meeting all of the first to fourth measurement conditions, calculate the instantaneous resistance increase rate of the first battery cell.

[0015] The processor according to the example embodiment can be configured to calculate the average resistance increase rate of a first battery cell by applying multiple instantaneous resistance increase rates and multiple effective decision values ​​of instantaneous resistance increase rates to a recursive averaging filter.

[0016] The processor according to the example embodiment can be configured to: identify a maximum average resistance increase rate and a minimum average resistance increase rate based on a plurality of average resistance increase rates calculated at each of a plurality of time points; and determine whether the average resistance increase rate of the first cell has converged based on the maximum average resistance increase rate and the minimum average resistance increase rate.

[0017] The processor according to the example embodiment can be configured to: when it is determined that the average resistance increase rate of the first battery cell converges, calculate the output reduction rate of the first battery cell based on the average resistance increase rate of the first battery cell.

[0018] According to an example embodiment, the processor can be configured to calculate multiple output reduction rates of a first battery cell for each of multiple driving cycles of a vehicle including a battery pack.

[0019] The processor according to the example embodiment can be configured to: calculate the long-term output degradation rate of a first battery cell based on multiple output degradation rates.

[0020] The processor according to the example embodiment can be configured to provide the vehicle with the long-term output reduction rate of the first battery cell.

[0021] According to the example embodiment, the first resistor can indicate the instantaneous measured resistance of the first battery cell.

[0022] The second resistor, according to the example embodiment, can indicate the estimated resistance of the first cell in the BOL state.

[0023] A method for calculating the output degradation rate of a battery cell, performed by an electronic device according to an example embodiment of the present disclosure, includes: calculating a first resistance of the first battery cell based on the current and voltage of the first battery cell; calculating a second resistance of the first battery cell based on the temperature and SoC of the first battery cell; calculating an instantaneous resistance increase rate of the first battery cell based on the first resistance and the second resistance; calculating an average resistance increase rate of the first battery cell based on a plurality of instantaneous resistance increase rates of the first battery cell corresponding to a plurality of time points; and calculating an output degradation rate of the first battery cell based on the average resistance increase rate of the first battery cell.

[0024] A computer-readable recording medium according to an example embodiment of the present disclosure includes a program for performing on a computer a method for calculating the output degradation rate of a battery cell executed by an electronic device. The method for calculating the output degradation rate of a battery cell includes: calculating a first resistance of a first battery cell based on the current and voltage of a first battery cell; calculating a second resistance of a first battery cell based on the temperature and SoC of the first battery cell; calculating an instantaneous resistance increase rate of the first battery cell based on the first resistance and the second resistance; calculating an average resistance increase rate of the first battery cell based on a plurality of instantaneous resistance increase rates of the first battery cell corresponding to a plurality of time points; and calculating an output degradation rate of the first battery cell based on the average resistance increase rate of the first battery cell.

[0025] Effects of the present invention

[0026] According to an example embodiment of this disclosure, a stable and accurate rate of increase in resistance can be calculated by using the instantaneous resistance and the estimated resistance at the beginning of life (BOL) state to calculate the rate of increase in resistance (or the rate of decrease in resistance) without applying a filter to remove noise when measuring (or estimating) the instantaneous resistance of the cell.

[0027] According to an example embodiment of this disclosure, measurement errors caused by variations in the battery's state of charge (SoC) or temperature can be minimized by applying a filter to the rate of increase in resistance measured for each driving cycle of the vehicle (in other words, battery charging and discharging cycles) to remove noise.

[0028] According to an example embodiment of this disclosure, the rate of increase in resistance of a single battery cell can be used to calculate the rate of decrease in output.

[0029] In addition, various effects can be provided, either directly or indirectly, through this instruction manual. Attached Figure Description

[0030] Figure 1 This is a block diagram of an electronic device according to an exemplary embodiment of the present disclosure.

[0031] Figure 2 This is an operation flowchart of an electronic device according to an example embodiment of the present disclosure.

[0032] Figure 3 This is an operation flowchart of an electronic device according to an example embodiment of the present disclosure.

[0033] Figure 4 This is a graph illustrating the count of the effective instantaneous resistance reduction rate over time according to an example embodiment of the present disclosure.

[0034] Figure 5 This is a graph illustrating the distribution of the instantaneous resistance increase rate based on a count, according to an exemplary embodiment of the present disclosure.

[0035] Figure 6 It is a graph illustrating the fluctuation of the average resistance increase rate based on counts according to an example embodiment of the present disclosure. Detailed Implementation

[0036] In the following description, various exemplary embodiments of the present disclosure will be illustrated with reference to the accompanying drawings. However, it should be understood that the present disclosure is not limited to the specific exemplary embodiments, but includes various modifications, equivalents, and / or substitutions to the exemplary embodiments of the present disclosure.

[0037] In this specification, the singular form of a noun corresponding to an item may include one or more such items unless otherwise clearly indicated in the context. In this specification, each of the expressions “A or B,” “at least one of A and B,” “at least one of A or B,” “A, B, or C,” “at least one of A, B, and C,” and “at least one of A, B, or C” may include any one of the items listed together in the corresponding expression or each possible combination thereof. Terms such as “first” or “second” may be used only to distinguish the corresponding element from another element, and these terms do not limit the elements in any other way (e.g., in terms of importance or order). When referring to (e.g., first) an element as “coupled” or “connected” to another (e.g., second) element, whether or not terms such as “functionally” or “communically” are used, it indicates that the element can be connected to the other element directly (e.g., via a wire), wirelessly, or via a third element.

[0038] Each element (e.g., a module or program) described in this specification may include one or more instances. According to various example embodiments, one or more elements or operations between corresponding elements may be omitted, or one or more other elements or operations may be added. Typically or additionally, multiple elements (e.g., modules or programs) may be integrated into one element. In this case, the integrated element may perform one or more functions of each of the multiple elements in the same or similar manner as the corresponding elements among the multiple elements performed prior to integration. According to various example embodiments, operations performed by a module or program or another element may be performed sequentially, in parallel, repeatedly, or heuristically, or one or more of these operations may be implemented in a different order, omitted, or one or more other operations may be added.

[0039] The terms "module" or "unit" can include units implemented by hardware, software, or firmware, and are used interchangeably with terms such as logic, logic block, component, or circuit. A module can constitute an integrated component, or the smallest unit or part of a component that performs one or more functions. For example, according to an example embodiment, a module can be implemented as an application-specific integrated circuit (ASIC).

[0040] The various exemplary embodiments described herein can be implemented by software (e.g., a program or application) that includes one or more commands stored in a machine-readable storage medium (e.g., memory). For example, a machine's processor can invoke and implement at least one of the one or more stored commands from the storage medium. This enables the machine to be operated to perform at least one function by at least one invoked command. The one or more commands may include code generated by a compiler or code that can be executed by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, "non-transitory" may simply indicate that the storage medium is a tangible device and does not include signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently in the storage medium and cases where data is stored temporarily in the storage medium.

[0041] Figure 1 This is a block diagram of an electronic device 100 according to an exemplary embodiment of the present disclosure. Reference Figure 1 The electronic device 100 may include a processor 110, a memory 120, and an information acquisition interface 130. At least one of the elements included in the electronic device 100 may be omitted, or another element may be added to the electronic device 100. Additionally or generally, some elements may be integrated to be implemented, or implemented as singular or plural units. At least some elements within the electronic device 100 may be integrated to be implemented, or implemented as singular or plural units.

[0042] Electronic device 100 can diagnose the condition of multiple battery cells included in a battery pack. The battery pack may include multiple battery cells arranged in series and / or parallel. The battery pack may be configured within units of a battery module (or battery bank), which is an assembly of battery cells. The battery pack can be installed in various devices, and is installed in, for example, electric vehicles.

[0043] Electronic device 100 can acquire voltage and / or current information from multiple battery cells. Electronic device 100 can diagnose the state of each of the multiple battery cells by calculating voltage relationship information based on the state of charge of each battery cell (e.g., OCV-SOC curve) or by calculating voltage relationship based on capacity (e.g., capacity-voltage curve). Electronic device 100 can also use field battery data to diagnose the state of battery cells.

[0044] Electronic device 100 may be a battery management device (or battery management system (BMS)) included in a battery pack, an on-board diagnostic (OBD) device included in an electric vehicle, a server or cloud device, or a charger-discharger and charger.

[0045] The processor 110 of the electronic device 100 according to the example embodiment may be configured to perform control and / or communication or data processing operations with respect to each element of the electronic device 100, and may be functionally connected to the elements of the electronic device 100. The processor 110 may load commands or data received from other elements of the electronic device 100 into memory 120, process the commands or data stored in memory 120, and store the resulting data. Unless otherwise specifically described, processor 110 may refer to a collection of one or more processors 110 as described in this disclosure.

[0046] According to an example embodiment, the memory 120 of the electronic device 100 may store various data used by at least one element (e.g., processor 110). The memory 120 may store instructions regarding the operation of the processor 110. Programs may be stored in the memory as software and may include, for example, an operating system, middleware, or an application. Unless otherwise specifically described, memory 120 may refer to a collection of one or more memories 120 as described in this disclosure.

[0047] According to the example embodiment, the information acquisition interface 130 can acquire voltage and / or current information of multiple battery cells included in the battery pack. The information acquisition interface 130 can also acquire time-series information about the voltage and current of the multiple battery cells.

[0048] When the electronic device 100 is a battery pack BMS, the information acquisition interface 130 can be a configuration that directly measures the state of the battery pack, such as a sensor. Furthermore, when the electronic device 100 is an OBD device, server, cloud, or charger-discharger, the information acquisition interface 130 can be a communication interface that receives measured information from a configuration that measures the state of the battery pack (e.g., the battery pack's BMS).

[0049] Information acquisition interface 130 can acquire voltage and / or current information of multiple battery cells included in the battery pack. The voltage information of the multiple battery cells can refer to the operating voltage or open-circuit voltage (OCV) of each battery cell. For example, information acquisition interface 130 can acquire the operating voltage of a battery cell during battery pack operation and acquire the OCV of a battery cell in an idle state. Furthermore, the current information of the battery cells can include the current of each battery cell and the current of the battery pack. The current of the battery pack and the current of each battery cell can be the same. Information acquisition interface 130 can continuously acquire information about the voltage and current of the battery pack over time. For example, information acquisition interface 130 can periodically acquire the voltage and current information of the battery pack. According to an example embodiment, information acquisition interface 130 can acquire the voltage and current information of multiple battery cells via over-the-air (OTA). For example, information acquisition interface 130 can acquire the voltage and current information of battery cells from the battery pack's BMS via OTA.

[0050] Information acquisition interface 130 can acquire information about the temperature and state of charge (SoC) of multiple battery cells included in the battery pack. Information acquisition interface 130 can acquire time-series information about the temperature and SoC of the multiple battery cells. Based on information about the voltage and / or current of the battery cells, the processor can determine (or estimate) information about the SoC. Using an SoC estimation algorithm, the processor can calculate the SoC using the voltage and / or current information of the battery cells.

[0051] According to the example embodiment, the processor 110 can calculate the instantaneous resistance of a battery cell based on the current and voltage of the battery cell. The instantaneous resistance can refer to the measured resistance of the battery cell corresponding to the point in time when the current and voltage are measured (in other words, the current point in time). Based on the temperature and SoC of the battery cell, the processor 110 can calculate the estimated resistance of a battery cell in a beginning-of-life (BOL) state. The estimated resistance can be calculated using a resistance profile of a first battery cell in the BOL state and the current and voltage measured at the current point in time. The BOL state can refer to information about the lifespan of the battery cell and its state at the point in time when the battery cell was manufactured and shipped.

[0052] According to an example embodiment, the processor 110 can use the instantaneous resistance and estimated resistance of a battery cell to calculate the instantaneous resistance increase rate of the battery cell. The processor 110 can calculate multiple instantaneous resistance increase rates during multiple charge and discharge cycles, and calculate the average resistance increase rate of the battery cell based on the multiple instantaneous resistance increase rates. Based on the average resistance increase rate of the battery cell, the processor 110 can calculate the output reduction rate of the battery cell. Based on the output reduction rate of the battery cell, the processor 110 can diagnose whether the battery cell is abnormal.

[0053] Figure 2 This is an operation flowchart of an electronic device 100 according to an example embodiment of the present disclosure.

[0054] Referring to the operation flowchart 200, the processor 110 of the electronic device 100 according to the example embodiment can calculate the first resistance of the first battery cell in operation 210. Based on the current and voltage of the first battery cell, the processor 110 can calculate the first resistance of the first battery cell. The first resistance of the first battery cell can refer to the instantaneous resistance corresponding to the time point at which the current and voltage of the first battery cell are measured. The first resistance can be an ohmic resistance. The processor 110 can determine the first resistance of the first battery cell by calculating the slope (dV / dI) of the voltage-current curve of the first battery cell.

[0055] Processor 110 can use a tuning factor to determine a first resistance of a first battery cell. Processor 110 can identify whether the current of the first battery cell exceeds a predetermined threshold during a predetermined time period. For example, processor 110 can identify that the current of the first battery cell exceeds 5A during a period of 0.1 seconds. The predetermined time (e.g., 0.1s) can be set short enough to measure instantaneous resistance. The predetermined threshold for current (e.g., 5A) can be variably set as a tuning factor. When the current exceeds the threshold, processor 110 can calculate the first resistance using Equation 1 below. Processor 110 can calculate the voltage and current changes during the predetermined time period in response to the current exceeding the threshold. Processor 110 can calculate the first resistance based on the voltage and current changes.

[0056] [Equation 1]

[0057] R1 can be the first resistor, ΔV can be the voltage change, and ΔI can be the current change. present and I present It can be the voltage and current at the current time point, V previous and I previous This can be the voltage and current at the previous time point. The unit of the first resistance can be ohms (Ω).

[0058] The previous time point and the current time point can differ by a predetermined time (e.g., 0.1 s). The current time point can be a time point after the current change exceeds a threshold during the predetermined time period, and the previous time point can be a time point before the current change exceeds the threshold. In this manner, the processor 110 can calculate the first resistance, i.e., the instantaneous resistance, of the first battery cell. In other words, the calculated first resistance may not be a value to which a filter (e.g., a recursive least squares (RLS) algorithm) has been applied to remove noise. In other words, since the first resistance may not be a value of the instantaneous resistance that has been over-tuned by applying a filter, changes in the instantaneous resistance based on temperature changes or SoC changes of the first battery cell can be tracked.

[0059] According to an example embodiment, processor 110 can calculate a second resistance of the first battery cell in operation 220. The second resistance can indicate an estimated resistance of the first battery cell in a BOL state. In other words, the second resistance can be a resistance identified by applying the SoC and temperature measured at the current time point to a resistance graph of the first battery cell in a BOL state. The unit of the second resistance can be ohms (Ω). Processor 110 can identify the resistance graph of the first battery cell in a BOL state. The resistance graph can be stored in the memory 120 of electronic device 100, or obtained from an external device (e.g., a server) via information acquisition interface 130. The resistance graph can be a predefined table for the first battery cell in a BOL state, and can be information such as, for example, the table below. The table below can be an exemplary table, and the resistance values ​​included in the table can vary depending on the type of battery cell. Processor 110 can use the resistance graph to identify resistance values ​​corresponding to the temperature and SoC of the first battery cell, and determine the identified resistance values ​​as the second resistance of the first battery. For example, when the temperature of the first battery cell is 25°C and the SoC is 50%, the processor 110 can determine the second resistance of the first battery cell to be 1.000Ω.

[0060] [Table 1]

[0061] According to the example embodiment, the processor 110 can calculate the instantaneous resistance increase rate of the first battery cell in operation 230. Based on the first resistance and the second resistance, the processor 110 can calculate the instantaneous resistance increase rate of the first battery cell. The processor 110 can use the following Equation 2 to calculate the instantaneous resistance increase rate.

[0062] [Equation 2]

[0063] SOHR instantIt can be the instantaneous rate of increase in resistance, and the unit can be a percentage (%). R1 ​​can be the first resistor, and R2 can be the second resistor.

[0064] According to an example embodiment, processor 110 can calculate the instantaneous resistance increase rate when the first battery cell meets at least one measurement condition. The at least one measurement condition may include a first measurement condition regarding a temperature range, a second measurement condition regarding an SoC range, a third measurement condition regarding temperature deviation, or a fourth measurement condition regarding SoC error. For example, processor 110 can determine to calculate the instantaneous resistance increase rate when the first battery cell meets all of the first to fourth measurement conditions. For example, processor 110 can determine not to calculate the instantaneous resistance increase rate when the first battery cell does not meet any of the first to fourth measurement conditions. The first to fourth measurement conditions may be conditions for determining whether the first resistance measured for the first battery cell is reliable. Figure 3 This is an operation flowchart of an electronic device 100 according to an exemplary embodiment of the present disclosure. Specifically, Figure 3 It could be a flowchart for determining whether to calculate the instantaneous resistance increase rate.

[0065] Referring to the operation flowchart 300, the processor 110 of the electronic device 100 according to the example embodiment can determine in operation 310 whether a first measurement condition regarding a temperature range is met. The first measurement condition may be a condition regarding whether the temperature of a first battery cell is included within a predetermined temperature range. For example, the first measurement condition may be a condition regarding whether the temperature of the first battery cell is greater than 10°C and less than 50°C. When the temperature of the first battery cell is included within this temperature range, the processor 110 can determine that the first measurement condition is met. The aforementioned temperature range is exemplary and can be significantly changed according to a tuning factor.

[0066] According to an example embodiment, the processor 110 may determine in operation 320 that a second measurement condition regarding the SoC range is met. The second measurement condition may be a condition regarding whether the SoC of the second battery cell is included in a predetermined SoC range. For example, the second measurement condition may be a condition regarding whether the SoC of the first battery cell is greater than 30% and less than 90%. When the SoC of the first battery cell is included in the SoC range, the processor 110 may determine that the second measurement condition is met. The aforementioned SoC range is exemplary and can be significantly changed according to a tuning factor.

[0067] According to the example embodiment, the processor 110 can determine in operation 330 whether a third measurement condition regarding temperature deviation is met. The third measurement condition may be a condition regarding whether the temperature deviation determined based on the temperatures of multiple battery cells included in the battery pack is less than a predetermined threshold deviation. Here, the battery pack may refer to a battery pack including first battery cells. For example, the third measurement condition may be a condition regarding whether the temperature deviation determined above is less than 3°C. The processor 110 can identify the maximum and minimum temperatures among the temperatures of the multiple battery cells and determine the difference between the maximum and minimum temperatures as the temperature deviation. The processor 110 can identify whether the determined temperature deviation is less than the threshold deviation. When the temperature deviation is less than the threshold deviation, the processor 110 can determine that the third measurement condition is met. The aforementioned temperature deviation value is exemplary and can be significantly changed according to the tuning factor.

[0068] According to an example embodiment, the processor 110 may determine in operation 340 whether a fourth measurement condition regarding SoC error is met. The fourth measurement condition may be a condition regarding whether the SoC error range determined based on the SoC of a plurality of battery cells included in a battery pack is less than a predetermined threshold error value. Here, the battery pack may refer to a battery pack including first battery cells. For example, the fourth measurement condition may be a condition regarding whether the determined SoC error range is less than 3%. Based on the SoC of the plurality of battery cells, the processor 110 may calculate the error range and identify whether the calculated error range is less than the predetermined threshold error. When the error range is less than the threshold error, the processor 110 may determine that the fourth measurement condition is met. The aforementioned SoC range is exemplary and can be significantly changed according to a tuning factor.

[0069] Based on whether the first to fourth measurement conditions are met, the processor 110 according to the example embodiment can determine whether to calculate the instantaneous resistance increase rate of the first battery cell. When the first battery cell meets all of the first to fourth measurement conditions, the processor 110 can output a valid decision value. instant The condition is determined to be true (T). When Valid instant When T is determined, processor 110 can determine that the first resistor is reliable and calculate the instantaneous resistance increase rate. Based on the first resistor and the second resistor, processor 110 can calculate the instantaneous resistance increase rate.

[0070] When the first battery cell does not meet any of the first to fourth measurement conditions, the processor 110 according to the example embodiment can output a valid decision value. instant The result is determined to be false (F). When Valid instant When the value is determined to be F, the processor 110 can determine that the first resistor is unreliable and does not calculate the instantaneous resistance increase rate.

[0071] Back Figure 2 According to the example embodiment, the processor 110 can calculate the average resistance increase rate of the first battery cell in operation 240. Based on multiple instantaneous resistance increase rates of the first battery cell corresponding to multiple time points, the processor 110 can calculate the average resistance increase rate of the first battery cell.

[0072] Processor 110 can calculate the average resistance increase rate of the first battery cell by applying multiple instantaneous resistance increase rates corresponding to multiple time points and multiple effective decision values ​​of instantaneous resistance increase rates to a recursive averaging filter. Whenever an effective instantaneous resistance increase rate is calculated, processor 110 can increment a count by 1. For example, when the effective decision value is T, processor 110 can increment the count by 1, while when the effective decision value is F, processor 110 may not change the count. Processor 110 can use a recursive averaging filter such as Equation 3 below to calculate the average resistance increase rate of the first battery cell.

[0073] [Equation 3]

[0074] SOHR mean It can be the average rate of increase in resistance at the current point in time, and count can be a count, SOHR mean,prev It can be the average rate of increase in resistance at the previous time point, SOHR instant This could be the instantaneous rate of increase in resistance at the current point in time. In other words, processor 110 can calculate the average rate of increase in resistance by sequentially accumulating the effective instantaneous rates of increase in resistance using a recursive averaging filter. Recursive averaging can refer to a technique that adds an additional data point based on the definition of an average, and can differ from batch processing methods that calculate the average all at once by collecting all the data together.

[0075] According to the example embodiment, the processor 110 can identify whether the average resistance increase rate has converged. Based on multiple average resistance increase rates calculated at each of multiple time points, the processor 110 can identify the maximum and minimum average resistance increase rates. Based on the maximum and minimum average resistance increase rates, the processor 110 can determine whether the average resistance increase rate of the first battery cell has converged.

[0076] When calculating the average resistance increase rate using a recursive averaging filter, processor 110 can identify multiple average resistance increase rates at each time point across multiple time points because the average resistance increase rate is calculated based on the cumulative effective average resistance increase rate at each time point. Processor 110 can identify the maximum average resistance increase rate (SOHR) among the multiple average resistance increase rates. mean,max) and minimum average resistance increase rate (SOHR) mean,min The processor 110 calculates the difference between the maximum and minimum average resistance increase rates. The processor 110 can identify whether the difference between the maximum and minimum average resistance increase rates is less than a predetermined convergence decision value (e.g., 2.5). When the difference between the maximum and minimum average resistance increase rates is less than this convergence decision value, the processor 110 can determine that the average resistance increase rate has converged and set the convergence flag to true (T). When the difference between the maximum and minimum average resistance increase rates is equal to or greater than this convergence decision value, the processor 110 can determine that the average resistance increase rate has not converged and set the convergence flag to false (F).

[0077] According to the example embodiment, the processor 110 can calculate the output degradation rate of the first battery cell in operation 250. When it is determined that the average resistance increase rate of the first battery cell has converged, the processor 110 can calculate the output degradation rate of the first battery cell based on the average resistance increase rate of the first battery cell. When the convergence flag value is F, the processor 110 can determine that the average resistance increase rate of the first battery cell has not yet converged, and determines not to calculate the output degradation rate of the first battery cell. When the convergence flag value is T, the processor 110 can determine that the average resistance increase rate of the first battery cell has converged and determines to calculate the output degradation rate of the first battery cell. The processor 110 can use the following Equation 4 to calculate the output degradation rate of the first battery cell.

[0078] [Equation 4]

[0079] SOHP st It can be the output reduction rate expressed as a percentage (%), SOHR mean It can be the average resistance increase rate expressed as a percentage.

[0080] According to an example embodiment, the processor 110 can calculate multiple output degradation rates for a first battery cell for each of multiple driving cycles in a vehicle including a battery pack. The processor 110 can calculate and accumulate each of the multiple output degradation rates during the multiple driving cycles and calculate a long-term output degradation rate. For example, the processor 110 can calculate 20 output degradation rates during the most recent 20 driving cycles, accumulate the 20 output degradation rates, and calculate the long-term output degradation rate. The long-term output degradation rate can be the average of the multiple output degradation rates. The long-term output degradation rate can also be the average of the remaining output degradation rates excluding the maximum and minimum output degradation rates of the multiple output degradation rates.

[0081] According to an example embodiment, the processor 110 can provide the vehicle with a long-term output reduction rate. The processor 110 can send the long-term output reduction rate to the vehicle's electronic control unit (ECU) via a communication interface (e.g., a controller area network (CAN) communication module or a local interconnect network (LIN) communication module).

[0082] Figure 4 This is a graph 400 illustrating the count of the effective instantaneous resistance reduction rate over time according to an example embodiment of the present disclosure.

[0083] refer to Figure 4 The processor 110 can calculate multiple instantaneous resistance reduction rates during a driving cycle. As described above, when at least one measurement condition is met at a predetermined measurement time point, the processor 110 can determine that a first resistance calculated at the predetermined measurement time point is valid (in other words, determine the valid decision value as T) and determine the instantaneous resistance reduction rate to be calculated. The count can refer to the number of times the valid decision value is determined to be T. In other words, the count can refer to the number of times the instantaneous resistance reduction rate is calculated.

[0084] Figure 5 Figure 500 illustrates the distribution of count-based SOHR according to an exemplary embodiment of the present disclosure.

[0085] refer to Figure 5 The SOHR value corresponding to each count can be labeled as point 501, and the SOHR distribution based on the count can be identified. The curve 503, represented by a solid line, can be a graph illustrating multiple instantaneous resistance increase rates calculated from multiple first resistors obtained at multiple time points after applying a filter (e.g., an RLS filter or a moving average filter) to remove noise. When the noise removal filter is applied to the first resistor, the trend of curve 503 may be identified as unstable due to changes in resistance characteristics caused by variations in the SoC and temperature of the battery cell.

[0086] Therefore, according to various example embodiments of this disclosure, the graph 505, represented by a single dashed line indicating the average resistance increase rate based on a stable trend count, can be obtained by calculating the instantaneous resistance increase rate using a first resistor without applying a noise removal filter instead of using a first resistor with a noise removal filter applied, and then applying a recursive averaging filter to multiple instantaneous resistance increase rates calculated at multiple time points to calculate the average resistance increase rate. For example, the instantaneous resistance increase rate can be measured and accumulated over 1000 driving cycles to calculate the average resistance increase rate. With the recursive averaging filter applied, the trend of the graph 505 represented by the single dashed line can converge and become stable as the count accumulates. Reference Figure 5The average resistance increase rate was identified as converging to a convergence value of 510 on curve 505. The convergence value could be, for example, 109%.

[0087] Figure 6 Figure 600 illustrates a graph showing the fluctuation of the average resistance increase rate based on counts according to an exemplary embodiment of the present disclosure.

[0088] refer to Figure 6 The graph 601 can be a graph illustrating the fluctuation of the average resistance increase rate during a recent predetermined period (e.g., the most recent 300 counts). The convergence threshold 610, represented by the dashed line, can be, for example, 2.5%. Figure 5 As identified in curve 505, the average resistance increase rate calculated using the recursive averaging filter converges as the count accumulates. Therefore, curve 601 shows a decrease in the fluctuation of the average resistance increase rate.

[0089] Through the aforementioned process, the instantaneous resistance value varying with the temperature and SoC of a single battery cell can be calculated, thereby determining the instantaneous resistance increase rate. By calculating the average resistance increase rate and output decrease rate based on the instantaneous resistance increase rate, the dependence of battery cells on temperature and SoC can be addressed, and the accuracy of the results can be improved. Opportunities to measure the first resistance—which is the instantaneous resistance—occur frequently during a vehicle's driving cycle, allowing a large amount of resistance data to accumulate in a short period, and the resistance increase rate and output decrease rate to converge to their estimated values ​​within a short timeframe.

[0090] This specification and accompanying drawings have been described with reference to exemplary embodiments of this disclosure. While specific terminology has been used, it is only for the general purpose of readily explaining the technical content of this disclosure and aiding in understanding the invention, and is not intended to limit the scope of this specification. It will be apparent to those skilled in the art that other modifications based on the technical spirit of this disclosure can be made in addition to the embodiments disclosed herein.

[0091] The device or terminal according to the above example embodiments may include a processor, a memory for storing and executing program data, permanent memory such as a disk drive, a communication port for communicating with external devices, and a user interface device such as a touch panel, buttons, and keypads. Methods implemented by software modules or algorithms can be stored in a computer-readable recording medium as computer-readable code or program instructions executable by a processor. Here, the computer-readable recording medium can be a magnetic storage medium (e.g., read-only memory (ROM), random access memory (RAM), floppy disk, or hard disk) or an optical reading medium (e.g., CD-ROM or digital versatile optical disc (DVD)). The computer-readable recording medium can be distributed across a network-connected computer system, allowing the computer-readable code to be stored and executed in a distributed manner. The medium can be read by a computer, stored in memory, and executed by a processor.

[0092] The methods implemented by the software or algorithms disclosed in this specification can be implemented by a program and stored in a computer-readable recording medium (or storage medium). The program may include computer-readable code or program instructions for performing multiple steps. In example embodiments, the recording medium may be implemented by a device such as a server, hard disk drive (HDD), solid-state drive (SSD), read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device. In example embodiments, QR codes and documents can be considered recording media when a camera on a machine such as a computer recognizes a QR code or document, and therefore, the recording medium is not limited to any particular type, as long as it is readable and executable by a computer. In example embodiments, the program may be stored on a single recording medium, or it may be distributed and stored across multiple recording media within a computer system connected via a network to enable distributed execution of a portion of the program.

[0093] In the example embodiment, the computer-readable recording medium may be provided as a non-transitory recording medium. Here, "non-transitory" may indicate that the recording medium is a type of device rather than a temporary signal (e.g., electromagnetic waves), and this term is not intended to distinguish between cases where data stored on the recording medium is permanently or temporarily stored. Furthermore, this is merely an example embodiment, and the recording medium may be modified and embodied as a temporary medium.

[0094] The method according to the example embodiments can be included in a computer program product. The computer program product can be distributed in the form of a computer-readable medium (e.g., CD-ROM), distributed online through an app store (e.g., by uploading and downloading), or distributed directly between two or more terminal devices. The method according to the example embodiments can also be implemented as the computer program itself.

[0095] This example embodiment can be represented by functional blocks and various processing steps. These functional blocks can be implemented by various numbers of hardware and / or software configurations that perform specific functions. For example, this example embodiment can employ direct circuit configurations, such as memory, processors, logic circuits, and lookup tables, which can perform various functions by controlling one or more microprocessors or other control devices. Similar elements can be implemented by software programming or software elements, this example embodiment can be implemented by programming or scripting languages ​​such as C, C++, Java, assembler, and Python, including various algorithms implemented by combinations of data structures, procedures, routines, or other programming configurations. Functional aspects can be implemented by algorithms executed by one or more processors. Furthermore, this example embodiment can employ related techniques for, for example, electronic environment setup, signal processing, and / or data processing. The terms “mechanism,” “element,” “device,” and “configuration” can be used broadly and are not limited to mechanical and physical components. For example, these terms can include the meaning of a series of software routines associated with a processor.

Claims

1. An electronic device, comprising: An information acquisition interface acquires time-series information about the voltage, current, temperature, and SoC of multiple battery cells included in the battery pack. Memory; as well as processor, The processor is configured as follows: Calculate the first resistance of the first battery cell based on its current and voltage. Calculate the second resistance of the first battery cell based on its temperature and SoC. Based on the first resistor and the second resistor, calculate the instantaneous resistance increase rate of the first battery cell; Based on the instantaneous resistance increase rate of the first battery cell corresponding to multiple time points, the average resistance increase rate of the first battery cell is calculated; and The output reduction rate of the first battery cell is calculated based on the average resistance increase rate of the first battery cell.

2. The electronic device according to claim 1, in, The processor is configured to: Identify whether the current exceeds a predetermined threshold during a predetermined time period; In response to the current exceeding the predetermined threshold, the voltage change and current change during the predetermined time period are calculated; as well as The first resistance is calculated based on the voltage change and the current change.

3. The electronic device according to claim 1, in, The processor is configured to: Identify the resistance diagram of the first battery cell in the BOL state; Based on the resistance diagram, temperature, and SoC of the first battery cell, the second resistance is calculated, and The resistance diagram is A table showing the temperature of the first battery cell in the BOL state and the resistance of the SoC.

4. The electronic device according to claim 1, in, The processor is configured to: Based on the temperature of the first battery cell, determine whether a first measurement condition regarding the temperature range is met; Based on the SoC of the first battery cell, determine whether a second measurement condition regarding the SoC range is met; as well as The validity of the instantaneous resistance increase rate of the first battery cell is determined in response to whether the first measurement condition and the second measurement condition are met.

5. The electronic device according to claim 4, in, The processor is configured to: Based on the temperatures of the plurality of individual battery cells, determine whether a third measurement condition regarding temperature deviation is met; Based on the SoC of the plurality of individual cells, determine whether the fourth measurement condition regarding SoC error is met; as well as In response to the satisfaction of all of the first to fourth measurement conditions, the instantaneous resistance increase rate of the first battery cell is determined.

6. The electronic device according to claim 5, in, The processor is configured to: The average resistance increase rate of the first battery cell is calculated by applying the plurality of instantaneous resistance increase rates and the effective decision values ​​of the plurality of instantaneous resistance increase rates to a recursive averaging filter.

7. The electronic device according to claim 6, in, The processor is configured to: Based on multiple average resistance increase rates calculated at each of the multiple time points, the maximum and minimum average resistance increase rates are identified; as well as Based on the maximum average resistance increase rate and the minimum average resistance increase rate, determine whether the average resistance increase rate of the first battery cell has converged.

8. The electronic device according to claim 7, in, The processor is configured to: When it is determined that the average resistance increase rate of the first battery cell converges, the output reduction rate of the first battery cell is calculated based on the average resistance increase rate of the first battery cell.

9. The electronic device according to claim 1, in, The processor is configured to calculate multiple output reduction rates of the first battery cell for each of multiple driving cycles in a vehicle including a battery pack.

10. The electronic device according to claim 9, in, The processor is configured to: Based on the multiple output reduction rates, the long-term output reduction rate of the first battery cell is calculated.

11. The electronic device according to claim 1, in, The processor is configured to: Provide the vehicle with the long-term output reduction rate of the first battery cell.

12. The electronic device according to claim 1, in, The first resistor indicates the instantaneous measured resistance of the first battery cell.

13. The electronic device according to claim 1, in, The second resistor indicates the estimated resistance of the first cell in the BOL state.

14. A method for calculating the output reduction rate of a single battery cell, performed by an electronic device, the method comprising: Calculate the first resistance of the first battery cell based on its current and voltage. Calculate the second resistance of the first battery cell based on its temperature and SoC. Based on the first resistor and the second resistor, calculate the instantaneous resistance increase rate of the first battery cell; The average resistance increase rate of the first battery cell is calculated based on the multiple instantaneous resistance increase rates corresponding to multiple time points of the first battery cell. as well as The output reduction rate of the first battery cell is calculated based on the average resistance increase rate of the first battery cell.

15. A computer-readable recording medium, wherein a program is recorded for performing on a computer a method for calculating the output degradation rate of a battery cell, the method for calculating the output degradation rate of the battery cell comprising: Calculate the first resistance of the first battery cell based on its current and voltage. Calculate the second resistance of the first battery cell based on its temperature and SoC. Based on the first resistor and the second resistor, calculate the instantaneous resistance increase rate of the first battery cell; The average resistance increase rate of the first battery cell is calculated based on the multiple instantaneous resistance increase rates corresponding to multiple time points of the first battery cell. as well as The output reduction rate of the first battery cell is calculated based on the average resistance increase rate of the first battery cell.

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