Apparatus for managing charging and operating method thereof

Abstract

A charging management device according to one embodiment disclosed in this document may include: an interface for obtaining a C-rate value and a voltage value of the battery during a charging process that repeats a charging section and a resting section; and a controller for calculating an internal resistance value of the battery based on a change in the voltage value, generating an SOC-internal resistance profile including a correlation between the internal resistance value and the SOC of the battery, identifying a SOC section to be diagnosed based on the C-rate value, calculating a moving average of the internal resistance values ​​included in the SOC section to be diagnosed in the SOC-internal resistance profile, and controlling the charging of the battery based on the magnitude relationship of the calculated moving averages.

Description

Technology Field

[0001] The embodiments disclosed in this document relate to a charging management device and a method of operating the same. Background Technology

[0002] Recently, active research and development on secondary batteries has been underway. Here, the term "secondary battery" refers to a rechargeable battery, encompassing conventional Ni / Cd and Ni / MH batteries as well as the more recent lithium-ion batteries. Among secondary batteries, lithium-ion batteries have the advantage of significantly higher energy density compared to conventional Ni / Cd and Ni / MH batteries. Furthermore, lithium-ion batteries can be manufactured in a compact and lightweight form factor, making them suitable for use as power sources for mobile devices. Recently, their scope of application has expanded to include electric vehicles, drawing attention as a next-generation energy storage medium.

[0003] As the industrial sectors utilizing batteries expand, the demand for high-capacity batteries is also increasing. While increasing battery capacity offers the advantage of extended usage time, it also increases the time required to charge such batteries. Rapid charging using high current shortens charging time, but it leads to side effects such as heat generation and lithium deposition. Consequently, active research has recently been conducted to design charging protocols for the rapid charging of high-capacity batteries. To design such a charging protocol, it is necessary to identify the points where lithium deposition occurs during the battery charging process. The problem to be solved

[0004] During the rapid charging process, it can be observed that the internal resistance of the battery decreases when lithium precipitation occurs. Although lithium precipitation can be prevented by tracking the point at which the battery's internal resistance decreases, there is a problem in that it is difficult to accurately predict the point of lithium precipitation because the voltage data obtained to calculate the internal resistance value may contain noise, and the calculated internal resistance value is less than 1 mOhm and the change is minute.

[0005] The technical problems of the embodiments disclosed in this document are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0006] A charging management device according to one embodiment disclosed in this document may include: an interface for obtaining a C-rate value and a voltage value of the battery during a charging process that repeats a charging section and a resting section; and a controller for calculating an internal resistance value of the battery based on a change in the voltage value, generating an SOC-internal resistance profile including a correlation between the internal resistance value and the SOC of the battery, identifying a SOC section to be diagnosed based on the C-rate value, calculating a moving average of the internal resistance values ​​included in the SOC section to be diagnosed in the SOC-internal resistance profile, and controlling the charging of the battery based on the magnitude relationship of the calculated moving averages.

[0007] In one embodiment, the controller can divide the diagnosis target SOC range into designated SOC ranges and calculate the moving average of the internal resistance values ​​for each designated SOC range.

[0008] In one embodiment, the designated SOC interval may include a first SOC interval and a second SOC interval, and the controller may calculate a first moving average for internal resistance values ​​included in the first SOC interval and a second moving average for internal resistance values ​​included in the second SOC interval starting from the end point of the first SOC interval.

[0009] In one embodiment, the controller may control the charging of the battery to end when the second moving average is less than the first moving average.

[0010] In one embodiment, the controller can control the charging of the battery to continue when the second moving average is greater than or equal to the first moving average.

[0011] In one embodiment, the controller can calculate the internal resistance value based on the current value based on the C-rate value and the amount of change of the voltage value.

[0012] In one embodiment, the controller can calculate the amount of change between a voltage value corresponding to the end of a first charging section and a voltage value included in a first resting section immediately after the first charging section, and calculate the internal resistance value based on the amount of change.

[0013] In one embodiment, the internal resistance value may be the charge transfer resistance (Rct) value of the battery.

[0014] A method of operation of a charging management device according to an embodiment disclosed in this document may include: acquiring a C-rate value and a voltage value of the battery during a charging process that repeats a charging section and a resting section; calculating an internal resistance value of the battery based on a change in the voltage value; generating an SOC-internal resistance profile including a correlation between the internal resistance value and the SOC of the battery; identifying a target SOC section based on the C-rate value; calculating a moving average of internal resistance values ​​included in the target SOC section in the SOC-internal resistance profile; and controlling the charging of the battery based on the magnitude relationship of the calculated moving averages.

[0015] In one embodiment, the operation of calculating the moving average of the internal resistance values ​​may include the operation of dividing the diagnosis target SOC section into designated SOC sections, and the operation of calculating the moving average of the internal resistance values ​​for each designated SOC section.

[0016] In one embodiment, the designated SOC interval may include a first SOC interval and a second SOC interval, and the operation of calculating a moving average of the internal resistance values ​​for each designated SOC interval may include an operation of calculating a first moving average for the internal resistance values ​​included in the first SOC interval, and an operation of calculating a second moving average for the internal resistance values ​​included in the second SOC interval starting from the end point of the first SOC interval.

[0017] In one embodiment, the operation of controlling the charging of the battery may include the operation of controlling the charging of the battery to end when the second moving average is less than the first moving average.

[0018] In one embodiment, the operation of controlling the charging of the battery may include the operation of controlling the charging of the battery to continue when the second moving average is greater than or equal to the first moving average.

[0019] In one embodiment, the operation of calculating the internal resistance value of the battery may include the operation of calculating the internal resistance value based on the change amount of the current value based on the C-rate value and the voltage value.

[0020] In one embodiment, the operation of calculating the internal resistance value of the battery may include the operation of calculating the amount of change between a voltage value corresponding to the end of the first charging section and a voltage value included in the first resting section immediately after the first charging section, and the operation of calculating the internal resistance value based on the amount of change.

[0021] In one embodiment, the internal resistance value may be the charge transfer resistance (Rct) value of the battery. Effects of the invention

[0022] The charging management device and the method of operation thereof according to the various embodiments disclosed in this document can predict the point where lithium precipitation occurs more accurately than conventional methods by calculating an internal resistance value based on the voltage value of the battery and calculating a moving average of the internal resistance values ​​for each specified SOC.

[0023] The effects of the charging management device and the method of operation thereof disclosed in this document are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art in accordance with the disclosure of this document. Brief explanation of the drawing

[0024] FIG. 1 is a block diagram of a charging management system according to one embodiment disclosed in this document. FIG. 2 illustrates a battery pack according to one embodiment disclosed in this document. FIG. 3 illustrates a time-voltage graph according to one embodiment disclosed in this document. FIG. 4 is an enlarged view of a specific section of a time-voltage graph according to one embodiment disclosed in this document. FIG. 5 illustrates an SOC-internal resistance profile according to one embodiment disclosed in this document. Figure 6 illustrates the result of calculating a moving average based on the SOC-internal resistance profile of Figure 5. FIGS. 7 to 9 illustrate an SOC-internal resistance profile generated during a constant current charging process based on a specific C-rate value according to an embodiment disclosed in this document, and the result of calculating a moving average based thereon. FIG. 10 is a flowchart illustrating the operation method of a charging management device according to one embodiment disclosed in this document. FIG. 11 illustrates a computing system for executing operations of a charging management device according to an embodiment disclosed in this document. In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Specific details for implementing the invention

[0025] Hereinafter, embodiments of the present invention are described with reference to the accompanying drawings. However, this is not intended to limit the present invention to specific embodiments and should be understood to include various modifications, equivalents, and / or alternatives of the embodiments of the present invention.

[0026] The embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise.

[0027] In this document, each of the following phrases may include any one of the items listed together in the corresponding phrase, or any combination thereof: "A or B," "at least one of A and B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C." Terms such as "first," "second," "first," "second," "A," "B," "(a)" or "(b)" may be used simply to distinguish a component from another component and, unless specifically stated otherwise, do not limit the components in any other aspect (e.g., importance or order).

[0028] In this document, where it is stated that any (e.g., 1) component is "connected," "coupled," or "joined" to another (e.g., 2) component, with or without the terms "functionally" or "communicationly," or where it is stated that the component is "coupled" or "connected," it means that the component may be connected to the other component directly (e.g., by wire or wirelessly) or indirectly (e.g., through a 3) component.

[0029] Methods according to the various embodiments disclosed in this document may be provided as part of a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory, CD-ROM) or distributed online (e.g., download or upload) through an application store or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0030] According to the embodiments disclosed in this document, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to the embodiments disclosed in this document, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the components of the multiple components in the same or similar manner as those performed by the corresponding components among the multiple components prior to the integration. According to the embodiments disclosed in this document, operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0031] FIG. 1 is a block diagram of a charging management system (1) according to one embodiment disclosed in this document.

[0032] Referring to FIG. 1, the charging management system (1) may include a charging management device (10), a charger / discharger (12), and battery units (120, 140, 160).

[0033] The charging management device (10) may be connected to the charging / discharging device (12) via wired and / or wireless connections. The charging / discharging device (12) is a device that charges or discharges each of the battery units (120, 140, 160) and can obtain values ​​(or information) related to the state of each of the battery units (120, 140, 160). In one embodiment, the values ​​related to the state may include one or more values ​​for the voltage, current, resistance, state of charge (SOC), state of health (SOH), temperature, or a combination thereof of each of the battery units (120, 140, 160). Hereinafter, the values ​​related to the state may be referred to as 'state values'.

[0034] Each of the battery units (120, 140, 160) may correspond to any one of a battery rack, a battery pack, and a battery module. Each of the battery units (120, 140, 160) may include one or more battery cells (121, 122, 123). For example, the battery cells (121, 122, 123) included in the first battery unit (120) may be electrically connected to each other (series and / or parallel connection). According to an embodiment, the battery cells (121, 122, 123) may be included in the first battery unit (120) in an electrically disconnected state. In FIG. 1, for convenience of explanation, only the first battery cell (121) to the third battery cell (123) included in the first battery unit (120) have been described, but this is not limited thereto, and the second battery unit (140) and the third battery unit (160) may also include one or more battery cells.

[0035] The charging management device (10) can obtain a voltage value during the process of charging the battery. Here, the battery may correspond to at least one of the battery units (120, 140, 160) according to the embodiment and may correspond to at least one of the battery cells (121, 122, 123). The charging management device (10) can calculate the internal resistance value of the battery based on the amount of change in the voltage value of the battery. Here, the internal resistance is the charge transfer resistance (R) of the battery. ct : May include charge transfer resistance)

[0036] The charging management device (10) can generate an SOC-internal resistance profile that includes the relationship between the internal resistance value and the SOC of the battery. Based on the SOC-internal resistance profile, the charging management device (10) can calculate a moving average of the internal resistance values ​​included in a designated SOC range. The reason the charging management device (10) calculates the moving average is that, since noise may be included in the voltage value obtained during the process of charging the battery, the influence of noise can be reduced by calculating the moving average of n (n: a natural number greater than or equal to 2) internal resistance values ​​included in the designated SOC range.

[0037] The charging management device (10) can control the charging of the battery based on the relationship between the magnitudes of the calculated moving averages. The charging management device (10) can control the charging of the battery based on the relationship between the first moving average calculated at a first time point and the second moving average calculated after the first time point. The charging management device (10) can control the charging to stop by determining that lithium precipitation will occur when the second moving average is less than the first moving average. Specifically, since the charge transfer resistance tends to decrease at the point where lithium precipitation occurs, the charging management device (10) can control the charging to stop by determining that lithium precipitation may occur when the second moving average is less than the first moving average.

[0038] In one embodiment, the charging management device (10) may be included in a BMS capable of diagnosing battery cells included in an electronic device, and operations performed by the charging management device (10) may be performed in the BMS. In one embodiment, the charging management device (10) may be included in a server or a charger / discharger capable of diagnosing battery cells outside the electronic device, and operations performed by the charging management device (10) may be performed in an external server or charger / discharger.

[0039] Hereinafter, for the convenience of explanation, the operations performed in each of the components included in the charging management device (10) are described in detail.

[0040] The charging management device (10) may include an interface (100) and a controller (102). According to an embodiment, the charging management device (10) illustrated in FIG. 1 may further include at least one component (e.g., a display, an input device, or an output device) other than the components illustrated in FIG. 1.

[0041] The interface (100) can obtain a voltage value of the battery during a charging process that repeats charging and resting periods. The interface (100) can obtain a status value including the voltage value of the battery from the charger / discharger (12). The interface (100) can obtain the voltage value of the battery being charged in real time, and can also obtain the voltage value of the battery based on charging data that has already been completed. According to an embodiment, the interface (100) can further obtain charging information (e.g., C-rate (current rate) value, etc.). According to various embodiments, the interface (100) may include various interface circuits for obtaining signals, information, and / or data, such as sensors and communication circuits.

[0042] The controller (102) can calculate the internal resistance value of the battery based on the amount of change in the voltage value. To calculate the internal resistance value, the controller (102) can calculate the amount of change in the acquired voltage value and can calculate the current value based on the C-rate (current rate) value. The controller (102) can calculate the internal resistance value by dividing the amount of change in the voltage value by the current value based on the C-rate value. A specific method for calculating the internal resistance is described later in FIGS. 3 and FIGS. 4.

[0043] The controller (102) can generate an SOC-internal resistance profile that includes a correlation between the internal resistance value and the SOC of the battery. Here, the SOC-internal resistance profile may be a graph that includes a correlation showing the change in the internal resistance value as the SOC of the battery increases during the process of charging the battery.

[0044] The controller (102) can calculate a moving average of internal resistance values ​​included in a specified SOC interval based on an SOC-internal resistance profile. Here, a moving average may be a term referring to the arithmetic average calculated for each subset by dividing the entire set into subsets of a specified size (e.g., the size of a window). Depending on the calculation method, the moving average may include a simple moving average and a cumulative moving average. A simple moving average may be a method of dividing n data points (n: a natural number greater than or equal to 2) into subsets with a window size of m (m: a natural number greater than or equal to 1) and calculating the arithmetic average of each subset. For example, if the entire set is {0, 1, 2, 3, 4, 5, 6, 7} and the window size is 2, the first moving average can be calculated as the arithmetic mean of 0 and 1, the second moving average can be calculated as the arithmetic mean of 1 and 2, and the third moving average can be calculated as the arithmetic mean of 2 and 3. A cumulative moving average may be a method of calculating the average while adding new data without setting the window size. For example, if the entire set is {0, 1, 2, 3, 4, 5, 6, 7}, the first moving average is 0, the second moving average can be calculated as the arithmetic mean of 0 and 1, and the third moving average can be calculated as the arithmetic mean of 0, 1, and 2. In the following description, it is assumed that the moving average is a simple moving average, but this is for convenience of explanation only and is not limited thereto.

[0045] The designated SOC range may correspond to the size of the window for calculating the moving average. Specifically, the designated SOC range may refer to a subset separated according to the size of the set window, as a subset comprising the entire set of the SOC range to be diagnosed. Here, the SOC range to be diagnosed may refer to an SOC range where lithium precipitation is expected to occur according to battery characteristics, including the C-rate value, the type of battery, and / or the characteristics of the active material. The SOC range to be diagnosed may be designated by the setter based on experimental data previously performed for each battery characteristic. Specifically, if the SOC range to be diagnosed is between 30% and 100%, the designated SOC range may be identified by separating the SOC range to be diagnosed in 1% increments. For example, when the C-rate value is 1.5C and the battery's SOC is charged from 0(%) to 100(%), the charging management device (10) can identify the diagnosis target SOC range as 30(%) to 100(%) based on prior experimental data, identify the window size as SOC 1(%), and identify the designated SOC range as the first SOC range (30% to 31%), the second SOC range (31% to 32%), ..., the m-th SOC range (m: natural number).

[0046] The controller (102) can reduce the influence of noise included in the battery voltage value by calculating a moving average for each designated SOC interval. In particular, the controller (102) can increase diagnostic efficiency because it can monitor based on the SOC intervals that are significant for each battery characteristic by calculating a moving average for each designated SOC interval.

[0047] In one embodiment, the controller (102) can calculate a first moving average of internal resistance values ​​corresponding to a first SOC section included in a designated SOC section. The controller (102) can calculate a second moving average of internal resistance values ​​corresponding to a second SOC section included in a designated SOC section. Here, the first SOC section and the second SOC section may refer to sub-SOC sections of the designated SOC section. For example, if the SOC section to be diagnosed is 30(%) to 100(%), the designated SOC section can be identified as a first SOC section (30% to 31%), a second SOC section (31% to 32%), a third SOC section (32% to 33%), ..., a m-th SOC section (m: natural number), etc., and the controller (102) can calculate a moving average for each SOC section.

[0048] The controller (102) can control the charging of the battery based on the relative magnitudes of the calculated moving averages. The controller (102) can control the charging of the battery based on the relative magnitudes of the first moving average and the second moving average. The controller (102) can control the charging of the battery to end if the second moving average is less than the first moving average. The controller (102) can control the charging of the battery to continue if the second moving average is greater than or equal to the first moving average.

[0049] FIG. 2 illustrates a battery pack according to one embodiment disclosed in this document.

[0050] Referring to FIG. 2, the battery pack (2) may be included in an electronic device. Here, the electronic device may be a mobile device (e.g., mobile phone, laptop computer, smartphone, smart pad), an electric vehicle (e.g., EV (electric vehicle), HEV (hybrid EV), PHEV (plug-in HEV), FCEV (fuel cell EV)), an energy storage system (ESS), or a battery swapping system (BSS).

[0051] The battery pack (2) may include a BMS (20) and battery modules (220, 240, 260). The BMS (20) can diagnose the condition of the battery modules (220, 240, 260) and the battery cells (221, 222, 223) included therein. In FIG. 2, three battery modules are shown, but this is for convenience of explanation only, and the battery pack (2) may include one or more battery modules. Also, in FIG. 1, only the battery cells (221, 222, 223) included in the first battery module (220) are shown, but this is for convenience of explanation only, and the second battery module (240) and the third battery module (260) may also include multiple battery cells. Additionally, although the plurality of battery cells (221, 222, 223) included in the first battery module (220) in FIG. 1 are shown as being three, they are not limited thereto, and each of the battery cells (221, 222, 223) may be configured to include n (n is a natural number greater than or equal to 2) battery cells.

[0052] According to various embodiments, when the battery pack (2) has a Cell To Pack (CTP) structure, the battery pack (2) may be configured to include a plurality of battery cells (121, 122, 123) without distinction of battery modules.

[0053] The BMS (20) may include a charging management device (10) and a sensing device (not shown) to diagnose the status of battery modules (220, 240, 260) and battery cells (121, 122, 123) included therein. The sensing device (not shown) can obtain the status value of each of the battery modules (220, 240, 260) and / or battery cells included therein included in the battery pack (2).

[0054] The charging management device (10) can control whether each of the battery modules (220, 240, 260) and / or the battery cells included therein continues charging based on a state value obtained by a sensing device (not shown). In one embodiment, the charging management device (10) may be a processor (not shown) of the BMS (20) and may be a device included in the processor (not shown). In one embodiment, the operations performed by the charging management device (10) may be executed by the processor (not shown) of the BMS (20) as a diagnostic algorithm.

[0055] FIG. 3 illustrates a time-voltage graph according to an embodiment disclosed in this document. FIG. 4 is an enlarged view of a specific section of the time-voltage graph according to an embodiment disclosed in this document.

[0056] Referring to FIG. 3, the charging management device (10) can obtain a time-voltage graph (30) regarding voltage values ​​according to charging time during the process in which the battery is charged according to a specific C-rate value (e.g., 0.5C). By referring to the time-voltage graph (30), it can be confirmed that the battery has been charged by repeating charging and idle periods.

[0057] Referring to FIG. 4, the graph (40) of FIG. 4 may be a graph that magnifies a specific area of ​​the time-voltage graph (30). Referring to the graph (40) of FIG. 4, the first point (400) may correspond to a first charging section where the battery is charged, the section from the first point (400) to the second point (402) may correspond to a first idle section, and the second point (404) may be the point where the second charging section begins. The charging management device (10) can calculate the internal resistance of the battery based on the graph (40) of FIG. 4. The charging management device (10) can calculate the amount of change between the voltage value corresponding to the first point (400) and the voltage value corresponding to the second point (402). The charging management device (10) can calculate the current value based on a specific C-rate value. The charging management device (10) can calculate the internal resistance of the battery by dividing the amount of change by the current value.

[0058] FIG. 5 illustrates an SOC-internal resistance profile according to one embodiment disclosed in this document. FIG. 6 illustrates the result of calculating a moving average based on the SOC-internal resistance profile of FIG. 5.

[0059] Referring to FIG. 5, the graph (50) of FIG. 5 may be an SOC-internal resistance profile that includes the relationship between the internal resistance calculated and the SOC of the battery when the C-rate value is set to 1.5C and the battery is charged. However, the graph (50) of FIG. 5 may include a noise region (500) calculated based on a voltage value corresponding to noise. Referring to the noise region (500), since the variability of the internal resistance value is large due to the noise, the charging management device (10) can minimize the noise region (500) by calculating a moving average of the internal resistance values. Referring to FIG. 6, the graph (60) of FIG. 6 may include an internal resistance value (600) corresponding to the graph (50) of FIG. 5 and a moving average (602) calculated based on the internal resistance value (600).

[0060] Referring to FIG. 6, the charging management device (10) can determine whether to continue charging the battery based on the relationship between moving averages. For example, referring to the graph (60) of FIG. 6, the charging management device (10) can control the charging of the battery to end if the second moving average calculated in a designated SOC interval including a point (62) where the SOC is about 73 (%) is less than the first moving average calculated in a designated SOC interval ending at the start of the designated SOC interval.

[0061] FIGS. 7 to 9 illustrate an SOC-internal resistance profile generated during a constant current charging process based on a specific C-rate value according to an embodiment disclosed in this document, and the result of calculating a moving average based thereon.

[0062] Referring to FIGS. 7 to 9, the graph (70) of FIG. 7, the graph (80) of FIG. 8, and the graph (90) of FIG. 9 may each be an SOC-internal resistance graph generated during the process of charging a battery by setting the C-rate value to 0.5C, 1.5C, and 3.0C.

[0063] Hereinafter, with reference to FIGS. 7 to 9, a method for a charging management device (10) to identify a diagnostic target SOC range based on a C-rate value and a method for controlling the charging of a battery based on a moving average calculated in the identified diagnostic target SOC range will be explained separately.

[0064] Method for identifying the SOC segments to be diagnosed

[0065] Referring to FIG. 7, the charging management device (10) can identify the SOC range to be diagnosed based on the graph (70) of FIG. 7. Referring to the graph (70) of FIG. 7, it can be confirmed that the SOC of the battery is charged from approximately 0 (%) to approximately 95 (%). Here, the battery may be a battery cell designed with a positive electrode material of High-Ni NCM (Ni content greater than 80%) and a negative electrode material of graphite (100%), and the charging environment may be an environment in which the C-rate of the battery cell is charged at 0.5C. The charging process of the battery may be divided into sections (A) to (D). Section (A) is a section where the SOC of the battery is approximately 0 (%), in which de-lithiation of the positive electrode proceeds and lithiation of the negative electrode occurs, so that the internal resistance of both the positive and negative electrodes can be calculated to be high. Sections (B) and (C) are sections where the internal resistance increases or decreases depending on the charge state of the negative electrode, and may be sections where the internal resistance changes at a specific SOC (e.g., 50%). Section (D) may be a section where charging continues up to the upper limit voltage. That is, among sections (A) to (D) included in the graph (70) of FIG. 7, sections (B) and (C) are sections where the internal resistance increases or decreases, and may be unsuitable as SOC sections for diagnosis. This is because the increase or decrease in internal resistance in sections (B) and (C) occurs due to charging characteristics rather than due to lithium deposition. On the other hand, section (A) or section (D) may be set as SOC sections for diagnosis. In addition, through a preliminary experiment, values ​​for the SOC start and end points of section (D) during the charging process to 0.5C can be obtained in advance, and the charging management device (10) can identify the SOC section to be diagnosed based on the SOC start and end points of section (D) obtained in advance.

[0066] Referring to FIGS. 8 and FIG. 9, the charging management device (10) can identify a diagnostic target SOC range based on a specific C-rate value based on the graph (80) of FIG. 8 and the graph (90) of FIG. 9, respectively. Referring to the graph (80) of FIG. 8 and the graph (90) of FIG. 9, ranges (A) to (D) can be identified, similar to the graph (70) of FIG. 7. Each of ranges (A) to (C) may correspond to each of ranges (A) to (C) of the graph (70) of FIG. 7. However, it can be confirmed that the SOC value at the time of range (D) of the graph (80) of FIG. 8 is lower than the SOC value at the time of range (D) of the graph (70) of FIG. 7. Likewise, it can be seen that the SOC point of section (D) of the graph (90) in FIG. 9 has a lower SOC value compared to the SOC point of section (D) of the graph (80) in FIG. 8. This is because as the C-rate value increases, overvoltage occurs, causing the shape of the charging graph to contract. In other words, since the SOC point of section (D) is measured differently depending on the C-rate value, the charging management device (10) can identify the SOC section to be diagnosed based on the C-rate value.

[0067] How to control battery charging

[0068] The charging management device (10) can divide the diagnostic target SOC range into a plurality of designated ranges and calculate a moving average for each designated SOC range. The charging management device (10) can determine whether to continue charging the battery based on the relationship between the calculated moving averages.

[0069] Referring to FIG. 7, the charging management device (10) can identify a diagnosis target SOC section (e.g., section (D)) corresponding to 0.5C by identifying that the C-rate value is 0.5C. The charging management device (10) can calculate a moving average for each designated SOC section in section (D) of the graph (70) of FIG. 7. Since the second moving average calculated in section (D) of the graph (70) of FIG. 7 is greater than or equal to the first moving average, the charging management device (10) can control the battery to continue charging.

[0070] Referring to FIG. 8, the charging management device (10) can identify a diagnosis target SOC section (82) corresponding to 1.5C by identifying that the C-rate value is 1.5C. Here, the diagnosis target SOC section (82) may be a section included in section (D) of the graph (80) of FIG. 8. The charging management device (10) can calculate a moving average for each designated SOC section in the diagnosis target SOC section (82). The charging management device (10) can identify a point (820) where the second moving average calculated in the diagnosis target SOC section (82) is less than the first moving average. In this case, the charging management device (10) can diagnose that lithium precipitation has occurred due to a decrease in internal resistance at the identified point (820) and can control the battery to terminate charging based on the identified point (820).

[0071] Referring to FIG. 9, the charging management device (10) can identify a diagnosis target SOC section (92) corresponding to 3.0C by identifying that the C-rate value is 3.0C. Here, the diagnosis target SOC section (92) may be a section included in section (D) of the graph (90) of FIG. 9. The charging management device (10) can calculate a moving average for each designated SOC section in the diagnosis target SOC section (92). The charging management device (10) can identify a point (920) where the second moving average calculated in the diagnosis target SOC section (92) is less than the first moving average. In this case, the charging management device (10) can diagnose that lithium precipitation has occurred due to a decrease in internal resistance at the identified point (920), and can control the battery to terminate charging based on the identified point (920).

[0072] FIG. 10 is a flowchart illustrating the operation method of a charging management device according to one embodiment disclosed in this document.

[0073] Referring to FIG. 10, in operation 1000, the charging management device (10) can obtain a voltage value of the battery. The charging management device (10) can obtain a voltage value of the battery during a charging process that repeats a charging period and a resting period. The charging management device (10) can obtain a status value including the voltage value of the battery from a charger / discharger. The charging management device (10) can obtain a voltage value of the battery being charged in real time, and can also obtain a voltage value of the battery based on charging data that has already been completed.

[0074] In operation 1010, the charging management device (10) can calculate the internal resistance value of the battery based on the amount of change in the voltage value. To calculate the internal resistance value, the charging management device (10) can calculate the amount of change in the acquired voltage value and calculate the current value based on the C-rate value. The charging management device (10) can calculate the internal resistance value by dividing the amount of change in the voltage value by the current value based on the C-rate value.

[0075] In one embodiment, the charging management device (10) can calculate the internal resistance value of the battery based on the amount of change between the voltage value at a point corresponding to the end of the first charging section and the voltage value at a point included in the first resting section immediately after the first charging section.

[0076] In operation 1020, the charging management device (10) can generate an SOC-internal resistance profile that includes the relationship between the internal resistance value and the SOC of the battery.

[0077] In operation 1030, the charging management device (10) can calculate a moving average of internal resistance values ​​included in a specified SOC interval based on an SOC-internal resistance profile.

[0078] In one embodiment, the charging management device (10) can identify a target SOC range based on a C-rate value and can identify a designated SOC range based on the target SOC range. The charging management device (10) can calculate a first moving average of internal resistance values ​​corresponding to a first SOC range included in the designated SOC range. The charging management device (10) can calculate a second moving average of internal resistance values ​​corresponding to a second SOC range included in the designated SOC range.

[0079] In operation 1040, the charging management device (10) can control the charging of the battery based on the relationship between the calculated moving averages.

[0080] In one embodiment, the charging management device (10) can control the charging of the battery based on the relationship between the first moving average and the second moving average. The charging management device (10) can control the charging of the battery to end when the second moving average is less than the first moving average. The charging management device (10) can control the charging of the battery to continue when the second moving average is greater than or equal to the first moving average.

[0081] FIG. 11 illustrates a computing system that executes the operations of a charging management device according to one embodiment disclosed in this document.

[0082] Referring to FIG. 11, a computing system (1100) according to one embodiment disclosed in this document may include an MCU (1110), a memory (1120), an input / output I / F (1130), and a communication I / F (1140).

[0083] The MCU (1110) may be a processor that executes various programs (e.g., a charging management program) stored in memory (1120), processes various data from these programs, and performs the functions of the charging management device (10) shown in FIGS. 1 to 10.

[0084] The memory (1120) can store various programs regarding the operation of the charging management device (10). In addition, the memory (1120) can store operation data of the charging management device (10) (e.g., prior experimental data, etc.).

[0085] These memories (1120) may be provided in multiple quantities as needed. The memories (1120) may be volatile memories or non-volatile memories. As volatile memories, the memory (1120) may use RAM, DRAM, SRAM, etc. As non-volatile memories, the memory (1120) may use ROM, PROM, EAROM, EPROM, EEPROM, flash memory, etc. The memories (1120) listed above are merely examples and are not limited to these examples.

[0086] The input / output I / F (1130) can provide an interface that enables data transmission and reception between an input device (not shown), such as a keyboard, mouse, or touch panel, an output device (not shown), and an MCU (1110).

[0087] The communication I / F (1140) is configured to transmit and receive various data to and from a server and may be various devices capable of supporting wired or wireless communication. For example, through the communication I / F (1140), a program for diagnosing abnormalities or various data (e.g., status values) can be transmitted and received from a separately provided external server.

[0088] Terms such as "include," "compose," or "have" as used above, unless specifically stated otherwise, mean that the relevant component may be inherent; therefore, they should be interpreted as allowing for the inclusion of additional components rather than excluding them. All terms, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the embodiments disclosed in this document pertain, unless otherwise defined. Commonly used terms, such as those defined in advance, should be interpreted in accordance with their meaning in the context of the relevant technology and, unless explicitly defined in this document, should not be interpreted in an ideal or overly formal sense.

[0089] The foregoing description is merely an illustrative explanation of the technical concept disclosed in this document, and a person skilled in the art to which the embodiments disclosed in this document pertain can make various modifications and variations within the scope of the essential characteristics of the embodiments disclosed in this document. Accordingly, the embodiments disclosed in this document are intended to explain, not limit, the technical concept of the embodiments disclosed in this document, and the scope of the technical concept disclosed in this document is not limited by these embodiments. The scope of protection of the technical concept disclosed in this document shall be interpreted by the claims below, and all technical concepts within an equivalent scope shall be interpreted as being included within the scope of rights of this document.

Claims

Claim 1 A charging management device comprising: an interface for obtaining a C-rate value and a voltage value of the battery during a charging process that repeats a charging section and a resting section; and a controller for calculating an internal resistance value of the battery based on a change in the voltage value, generating an SOC-internal resistance profile including a correlation between the internal resistance value and the SOC of the battery, identifying a SOC section to be diagnosed based on the C-rate value, calculating a moving average of the internal resistance values ​​included in the SOC section to be diagnosed in the SOC-internal resistance profile, and controlling the charging of the battery based on the magnitude relationship of the calculated moving averages. Claim 2 A charging management device according to claim 1, wherein the controller divides the diagnosis target SOC range into designated SOC ranges and calculates a moving average of the internal resistance values ​​for each designated SOC range. Claim 3 A charging management device according to claim 2, wherein the designated SOC interval includes a first SOC interval and a second SOC interval, and the controller calculates a first moving average for internal resistance values ​​included in the first SOC interval and calculates a second moving average for internal resistance values ​​included in the second SOC interval starting from the end point of the first SOC interval. Claim 4 A charging management device according to claim 3, wherein the controller controls the charging of the battery to terminate when the second moving average is less than the first moving average. Claim 5 A charging management device according to claim 3, wherein the controller controls the charging of the battery to continue when the second moving average is greater than or equal to the first moving average. Claim 6 A charging management device according to claim 1, wherein the controller calculates the internal resistance value based on the change amount of the current value based on the C-rate value and the voltage value. Claim 7 A charging management device according to claim 1, wherein the controller calculates a change amount between a voltage value corresponding to the end of a first charging section and a voltage value included in a first resting section immediately after the first charging section, and calculates an internal resistance value based on the change amount. Claim 8 A charge management device according to claim 1, wherein the internal resistance value is the charge transfer resistance (Rct) value of the battery. Claim 9 A method of operation of a charging management device comprising: obtaining a C-rate value and a voltage value of the battery during a charging process that repeats a charging section and a resting section; calculating an internal resistance value of the battery based on a change in the voltage value; generating an SOC-internal resistance profile including a correlation between the internal resistance value and the SOC of the battery; identifying a target SOC section based on the C-rate value; calculating a moving average of internal resistance values ​​included in the target SOC section in the SOC-internal resistance profile; and controlling the charging of the battery based on the magnitude relationship of the calculated moving averages. Claim 10 A method of operation of a charging management device according to claim 9, wherein the operation of calculating the moving average of the internal resistance values ​​comprises the operation of dividing the diagnosis target SOC section into designated SOC sections, and the operation of calculating the moving average of the internal resistance values ​​for each designated SOC section. Claim 11 A method of operation of a charging management device according to claim 10, wherein the designated SOC interval includes a first SOC interval and a second SOC interval, and the operation of calculating a moving average of the internal resistance values ​​for each designated SOC interval includes the operation of calculating a first moving average for the internal resistance values ​​included in the first SOC interval, and the operation of calculating a second moving average for the internal resistance values ​​included in the second SOC interval starting from the end point of the first SOC interval. Claim 12 A method of operation of a charging management device according to claim 11, wherein the operation of controlling the charging of the battery includes the operation of controlling the charging of the battery to terminate when the second moving average is less than the first moving average. Claim 13 A method of operation of a charging management device according to claim 11, wherein the operation of controlling the charging of the battery includes the operation of controlling the charging of the battery to continue when the second moving average is greater than or equal to the first moving average. Claim 14 A method of operation of a charging management device according to claim 9, wherein the operation of calculating the internal resistance value of the battery includes the operation of calculating the internal resistance value based on a current value based on the C-rate value and a change amount of the voltage value. Claim 15 A method of operation of a charging management device according to claim 9, wherein the operation of calculating the internal resistance value of the battery comprises: an operation of calculating a change amount between a voltage value corresponding to the end of a first charging section and a voltage value included in a first resting section immediately after the first charging section, and an operation of calculating the internal resistance value based on the change amount. Claim 16 A method of operation of a charge management device according to claim 9, wherein the internal resistance value is the charge transfer resistance (Rct) value of the battery. Claim 17 A computer-readable medium storing a program for executing the method described in any one of claims 9 to 16 on a computer.

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