Method and system for designing battery module

Abstract

The invention relates to a method and a system for designing a battery module. The method for designing the optimal battery module comprises the following steps: receiving target design information about a target battery module, wherein the target battery module comprises a target battery monomer; predicting an aging of the target battery cell based on the target design information by using a cell aging prediction model associating a design of a battery module including the battery cell with the aging of the battery cell; and determining whether the target design information is feasible based on the target design information and the predicted aging of the target battery cell.

Description

Technical Field

[0001] This disclosure relates to methods and systems for designing battery modules using a single-cell aging prediction model that models the correlation between battery module design and the aging of individual battery cells. Background Technology

[0002] Unlike primary batteries, which are designed not to be (re)charged, secondary (or rechargeable) batteries are designed to be discharged and recharged. Low-capacity secondary batteries are used in portable small electronic devices such as smartphones, feature phones, laptops, digital cameras, and portable camcorders, while high-capacity secondary batteries are widely used as power sources for motors in hybrid and electric vehicles and for storing electricity (e.g., household and / or utility-scale power storage). A secondary battery typically includes an electrode assembly containing positive and negative electrodes, a housing of the electrode assembly, and electrode terminals connected to the electrode assembly.

[0003] As batteries, including individual rechargeable cells, become more energy efficient and require faster charging, battery aging is accelerating with continued use. To slow down battery aging, it is becoming important to develop materials incorporated into batteries and systems and / or modules that include them. However, determining battery aging rates requires significant time, cost, and manpower.

[0004] The information disclosed in this Background section is intended to enhance the understanding of the background of this disclosure, and therefore may contain information that does not constitute related (prior) art. Summary of the Invention

[0005] This disclosure provides a method for evaluating the safety of the negative electrode of a battery and a battery system using the method.

[0006] These and other aspects and features of this disclosure will be described in the following description of embodiments of this disclosure, or will become apparent from the following description of embodiments of this disclosure.

[0007] According to embodiments of this disclosure, a method for designing a battery module may include: receiving target design information about a target battery module, the target battery module including target battery cells; predicting the aging of the target battery cells based on the target design information by using a cell aging prediction model, the cell aging prediction model associating the design of the battery module including the battery cells with the aging of the battery cells; and determining whether the target design information is feasible based on the target design information and the predicted aging of the target battery cells.

[0008] According to embodiments of this disclosure, the target design information may include cell specification information about the target battery cell and module specification information about the target battery module; and determining whether the target design information is feasible may include: calculating the size of the target breathing space based on the cell specification information and the module specification information; and determining whether the target design information is feasible based on the size of the target breathing space and the predicted aging of the target battery cell.

[0009] According to embodiments of this disclosure, the target design information may further include target aging information about the target battery cell; and determining whether the target design information is feasible based on the size of the target breathing space and the predicted aging of the target battery cell may include: determining whether the target design information is feasible based on the size of the target breathing space, the target aging information, and the predicted aging of the target battery cell.

[0010] According to embodiments of this disclosure, determining whether target design information is feasible based on the size of the target breathing space, target aging information, and the predicted aging of the target battery cell may include: generating a first comparison result by comparing the size of the breathing space associated with the predicted aging of the target battery cell and the size of the target breathing space; generating a second comparison result by comparing the target aging information with the predicted aging of the target battery cell; and determining whether the target design information is feasible based on the first comparison result and the second comparison result.

[0011] According to embodiments of this disclosure, the method may further include: receiving experimental design data and charging / discharging data of experimental battery cells corresponding to the experimental design data, wherein the experimental design data represents the design environment of an experimental battery module including experimental battery cells; and generating a cell aging prediction model based on the experimental design data and the charging / discharging data.

[0012] According to embodiments of this disclosure, experimental design data may include parameters that affect the lifespan of experimental battery cells; and the parameters may include control parameters adjusted in the design environment and operating parameters that depend on the control parameters.

[0013] According to embodiments of this disclosure, the control parameters may include information relating to at least one of the stiffness of the end plate of the experimental battery module, the compressive force, and the thickness of the insulation of the experimental battery module.

[0014] According to embodiments of this disclosure, the operating parameters may include information related to at least one of the following: the expansion force of the experimental battery module, the DC internal resistance of the experimental battery cell, the DC internal resistance of the experimental battery module, the temperature deviation of the experimental battery cell, and the temperature deviation of the experimental battery module.

[0015] According to embodiments of this disclosure, control parameters and operating parameters can be distinguished based on the degree to which control parameters and operating parameters affect the lifespan of experimental battery cells.

[0016] According to embodiments of this disclosure, generating a single-cell aging prediction model may include: generating aging information of experimental battery cells based on charge / discharge data and control parameters.

[0017] According to embodiments of this disclosure, generating a single-cell aging prediction model may further include: calculating the size of the breathing space of the experimental battery cell based on charge / discharge data and control parameters; and calculating the correlation between the size of the breathing space of the experimental battery cell and the aging information of the experimental battery cell.

[0018] According to embodiments of this disclosure, charging / discharging data can be generated by an experimental device, and the experimental device may include: a receiving part for receiving an experimental battery cell; a compression adjustment unit for adjusting the compression force applied to the experimental battery cell; a stiffness adjustment unit for adjusting the stiffness of the opposite end of the experimental battery cell; and a thickness measurement unit for measuring the thickness change of the experimental battery cell.

[0019] According to embodiments of this disclosure, the predicted aging of a target battery cell may include the state of health (SOH) information of the target battery cell that has undergone charge / discharge cycles.

[0020] According to embodiments of this disclosure, the size of the target breathing space can be correlated with the degree of expansion of the target battery cell during charging and discharging.

[0021] A battery module designed using the battery module design method according to embodiments of this disclosure can be provided.

[0022] According to embodiments of the present disclosure for solving the above-mentioned technical problems, a system for designing a battery module may include: at least one processor configured to read and execute instructions stored in at least one memory; a target information receiver configured to receive target design information about a target battery module, the target battery module including target battery cells; a battery aging predictor configured to predict the aging of the target battery cells based on the target design information by using a cell aging prediction model, the cell aging prediction model associating the design of the battery module including the battery cells with the aging of the battery cells; and a determination unit configured to determine whether the target design information is feasible based on the target design information and the predicted aging of the target battery cells.

[0023] According to embodiments of this disclosure, the target design information may include cell specification information about the target battery cell and module specification information about the target battery module; and the determining unit may be further configured to calculate the size of the target breathing space based on the cell specification information and the module specification information, and the determining unit is further configured to determine whether the target design information is feasible based on the size of the target breathing space and the predicted aging of the target battery cell.

[0024] According to embodiments of this disclosure, the target design information may further include target aging information about the target battery cell; and determining whether the target design information is feasible based on the size of the target breathing space and the predicted aging of the target battery cell may include: determining whether the target design information is feasible based on the size of the target breathing space, the target aging information, and the predicted aging of the target battery cell.

[0025] According to embodiments of this disclosure, determining whether the target design information is feasible may further include: generating a first comparison result by comparing the size of the breathing space associated with the predicted aging of the target battery cell with the size of the target breathing space; generating a second comparison result by comparing the target aging information with the predicted aging of the target battery cell; and determining whether the target design information is feasible based on the first comparison result and the second comparison result.

[0026] According to embodiments of this disclosure, the system may further include: an experimental data receiver configured to receive experimental design data and charging / discharging data of experimental battery cells corresponding to the experimental design data, wherein the experimental design data represents the design environment of an experimental battery module including experimental battery cells; and an aging prediction model generator configured to generate a cell aging prediction model based on the experimental design data and the charging / discharging data.

[0027] According to various embodiments of this disclosure, it is possible to identify the feasibility of a battery module without actually manufacturing it, thereby reducing the cost of manufacturing the battery module. Furthermore, by identifying the suitability of the design in advance from an early stage of battery module design, the risk of having to redesign the battery module can be reduced.

[0028] According to various embodiments of this disclosure, it is possible to reduce the cost of manufacturing battery modules by obtaining charging / discharging data of battery cells with design environments corresponding to parameters using experimental equipment without directly implementing the design environment as a battery module.

[0029] According to various embodiments of this disclosure, charge / discharge data of experimental battery cells can be obtained using experimental equipment while easily controlling factors that apply mechanical stress to the experimental battery cells.

[0030] According to various embodiments of this disclosure, it is possible to predict battery aging based on the size of the breathing space of the individual battery cells when adjusting the design environment of the battery module.

[0031] According to various embodiments of this disclosure, it is possible to easily determine whether the target design information is actually feasible by inputting target design information via an optimal battery module design interface and comparing the target aging information with the predicted aging information. Furthermore, it is possible to determine the feasibility of various target design information and obtain the optimal battery module design information among various target design information by changing and inputting the target design information.

[0032] However, the aspects and features of this disclosure are not limited to those described above, and those skilled in the art will clearly understand from the detailed description provided below that other aspects and features not mentioned will be apparent. Attached Figure Description

[0033] The accompanying drawings illustrate embodiments of the present disclosure and further describe aspects and features of the disclosure together with its detailed description. Therefore, the present disclosure is not limited to the drawings.

[0034] Figure 1 This is a schematic diagram of the optimal battery module design system according to an embodiment of the present disclosure.

[0035] Figure 2 This is a schematic diagram of the optimal battery module design system according to an embodiment of the present disclosure.

[0036] Figure 3 This is a diagram illustrating an example of a battery cell according to an embodiment of the present disclosure.

[0037] Figure 4 This is a diagram illustrating an example of a battery module according to an embodiment of the present disclosure.

[0038] Figure 5 This is a flowchart illustrating an example of a preferred battery module design method according to an embodiment of the present disclosure.

[0039] Figure 6 This is a flowchart illustrating an example of a method for generating charge / discharge data for an experimental battery cell according to an embodiment of the present disclosure.

[0040] Figure 7 This is a diagram illustrating an example of a battery module according to an embodiment of the present disclosure.

[0041] Figure 8 This is a perspective view of an experimental apparatus according to an embodiment of the present disclosure.

[0042] Figure 9This is a top view of an experimental apparatus according to an embodiment of the present disclosure.

[0043] Figure 10 This is a side view of an experimental apparatus according to an embodiment of the present disclosure.

[0044] Figure 11 These are graphs and tables showing the control parameters used in several experimental examples in this disclosure.

[0045] Figure 12 This is a table illustrating the experimental results of several experimental examples disclosed herein.

[0046] Figure 13 This is a graph showing the correlation between monomer aging information and breathing space size.

[0047] Figure 14 This is a detailed flowchart of the steps for determining whether target design information is feasible according to embodiments of the present disclosure.

[0048] Figure 15 This is a diagram illustrating an example of a preferred battery module design interface according to an embodiment of the present disclosure. Detailed Implementation

[0049] In the following, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Based on the principle that the inventor can be his / her own lexicographer to appropriately define the concepts of terms in order to best illustrate his / her invention, the terms or words used in this specification and claims should not be construed as limited to their ordinary or dictionary meanings, but should be interpreted as having meanings and concepts consistent with the technical spirit of the present disclosure.

[0050] The embodiments described in this specification and the constructions shown in the accompanying drawings are only some of the embodiments of this disclosure and do not represent all the technical ideas, aspects, and features of this disclosure. Accordingly, it should be understood that various equivalents and modifications that can replace or modify the embodiments described herein can be made at the time of filing this application.

[0051] It will be understood that when an element or layer is referred to as being "on" another element or layer, "connected to," or "linked to" another element or layer, the element or layer may be directly on, connected to, or linked to the other element or layer, or one or more intermediary elements or layers may be present. When an element or layer is referred to as being "directly on" another element or layer, "directly connected to," or "directly linked to" another element or layer, no intermediary element or layer is present. For example, when a first element is described as being "linked" or "connected" to a second element, the first element may be directly linked to or connected to the second element, or the first element may be indirectly linked to or connected to the second element via one or more intermediary elements.

[0052] In the accompanying drawings, the dimensions of various elements, layers, etc., may be exaggerated for clarity of illustration. The same reference numerals denote the same elements. As used herein, the term "and / or" includes any and all combinations of one or more of the related listed items. Furthermore, when describing embodiments of this disclosure, the use of "may" means "one or more embodiments of this disclosure." The expressions "at least one of" and "any one of" when placed after the list of elements modify the entire list of elements without modifying individual elements in the list. When phrases such as "at least one of A, B, and C," "at least one selected from the group of A, B, and C," or "at least one selected from A, B, and C" are used to specify a list of elements A, B, and C, the phrase may refer to any and all suitable combinations or subsets of A, B, C, A and B, A and C, B and C, or A and B and C, A, B, and C. As used herein, the term "use" and variations thereof may be considered synonymous with the term "utilize" and variations thereof, respectively. As used herein, the terms “substantially,” “approximately,” and similar terms are used as approximate terms rather than terms of degree and are intended to describe the inherent biases of measurements or calculations that would be recognized by one of ordinary skill in the art.

[0053] It will be understood that although the terms "first," "second," "third," etc., can be used to describe various elements, components, areas, layers, and / or portions, these elements, components, areas, layers, and / or portions should not be limited by these terms. These terms are used to distinguish one element, component, area, layer, or portion from another element, component, area, layer, or portion. Therefore, without departing from the teachings of the exemplary embodiments, the first element, component, area, layer, or portion discussed below may be referred to as the second element, component, area, layer, or portion.

[0054] In this document, spatial relative terms such as “below,” “under,” “down,” “above,” and “above” are used to describe the relationship between one element or feature as shown in the figures and another (or several) other elements or features. It will be understood that, in addition to the orientation shown in the figures, spatial relative terms are intended to include different orientations of the device in use or operation. For example, if the device in the figures is flipped, an element described as “below” or “under” other elements or features will be oriented “above” or “directly above” other elements or features. Therefore, the term “below” can include both above and below orientations. The device may be oriented in other ways (rotated 90 degrees or in other orientations), and the spatial relative descriptive terms used herein should be interpreted accordingly.

[0055] The terminology used herein is for the purpose of describing embodiments of this disclosure and is not intended to limit this disclosure. As used herein, unless the context clearly indicates otherwise, the singular forms “a” and “an” are intended to include the plural forms as well. It will be further understood that, when used in this specification, the term “comprising” specifies the presence of stated features, integrals, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof.

[0056] Furthermore, any numerical range disclosed and / or enumerated herein is intended to include all subranges with the same numerical precision within the enumerated range. For example, the range “1.0 to 10.0” is intended to include, for example, 2.4 to 7.6, all subranges between the stated minimum value of 1.0 and the stated maximum value of 10.0 (inclusive), i.e., all subranges with a minimum value equal to or greater than 1.0 and a maximum value equal to or less than 10.0. Any maximum numerical limit described herein is intended to include all smaller numerical limits, and any minimum numerical limit described in this specification is intended to include all larger numerical limits. Therefore, the applicant reserves the right to amend this specification (including the claims) to explicitly detail any subranges included within the scope expressly described herein.

[0057] Referring to two compared elements, features, etc., as "identical" can mean that they are "substantially identical." Therefore, the phrase "substantially identical" can include cases with a deviation considered low in the art (e.g., 5% or less). Additionally, when a parameter is said to be consistent in a given region, this can mean that it is consistent in terms of average value.

[0058] Throughout this specification, unless otherwise stated, each element may be singular or plural.

[0059] Placing any element "above (or below)" or "above (below)" another element can mean that the arbitrary element can contact the upper (or lower) surface of the element, and that another element can also be located between the element and the arbitrary element disposed on (or below) the element.

[0060] Additionally, it will be understood that when a component is referred to as “linked,” “connected,” or “attached” to another component, these components can be directly “linked,” “attached,” or “attached” to each other, or another component can be “between” these components.

[0061] Throughout this specification, unless otherwise stated, when “A and / or B” is mentioned, it means A, B, or A and B. That is, “and / or” includes any or all combinations of the enumerated items. Unless otherwise stated, when “C to D” is mentioned, it means C and below D.

[0062] Figure 1 This is a schematic diagram of an optimal battery module design system according to an embodiment of the present disclosure. The optimal battery module design system may include a target information receiver 110, a battery aging predictor 120, and a determination unit 130.

[0063] In this implementation, the target information receiver 110 can receive target design information for a target battery module 140, including target battery cells. The target battery cell is a battery cell (hereinafter referred to as a "cell") that is a defined target, and the target battery module 140 is a battery module (hereinafter referred to as a "module") that is a defined target. The target design information may include information about the design environment or conditions (for implementing the target battery module 140). For example, the target design information may include cell specification information for the target battery cell and module specification information for the target battery module. Cell specification information may include information about the type, size, or thickness of the cell's material, and module specification information may include information about the type and thickness of the insulation included in the module, or the stiffness of the plates included in the module. (See reference...) Figure 15 Provide detailed specifications for individual units and modules.

[0064] The target information receiver 110 can receive target design information input through the target information input interface. For example, a user can input target design information through the target information input interface, and the target information receiver 110 can receive the input target design information. (See reference) Figure 15 The target information input interface is described in detail. Additionally or alternatively, the target information receiver 110 can communicate with other systems and / or devices to receive target design information. The target information receiver 110 can transmit the target design information to the battery aging predictor 120.

[0065] The battery aging predictor 120 can receive target design information and predict the aging of target battery cells using a single-cell aging prediction model based on the target design information. The single-cell aging prediction model can be a model that associates the design of a battery module including battery cells with the aging of individual battery cells. Single-cell aging information can indicate the state of capacity of the battery after repeated charge / discharge cycles. For example, single-cell aging information can include the state of health (SOH) information of battery cells that have undergone a predetermined number of charge / discharge cycles. (Reference) Figure 2Describe in detail the method used to generate monomer aging prediction models.

[0066] In this implementation, the aging information of the target battery cell can be correlated with the size of the target breathing space. Here, the size of the breathing space can be related to the degree of expansion of the battery cell during charging and discharging. For example, as the battery cell is repeatedly charged and discharged, expanding and contracting, the breathing space size can represent the change between the thickness of the expanding and contracting battery cell. The target breathing space size can indicate the desired breathing space size of the target battery cell. In other words, the cell aging prediction model can predict aging information based on the target design information and the size of the breathing space of the target battery cell.

[0067] The determination unit 130 can receive target design information and predicted aging information. Based on the target design information and the predicted aging information, the determination unit 130 can determine whether the target design information is feasible. Specifically, the determination unit 130 can calculate the size of the target breathing space based on the unit specification information and module specification information included in the target design information. Based on the size of the target breathing space and the predicted aging information, the determination unit 130 can determine whether the target design information is feasible.

[0068] In this implementation, the target design information may further include target aging information for the target battery cell. The target aging information may indicate the desired aging information for the target battery cell. The determination unit 130 may determine whether the target design information is feasible based on the size of the target breathing space, the target aging information, and the predicted aging information. Specifically, the determination unit 130 may generate a first comparison result by comparing the size of the breathing space associated with the predicted aging information with the size of the target breathing space. The determination unit 130 may compare the target aging information with the predicted aging information to generate a second comparison result. The determination unit 130 may determine whether the target design information is feasible based on the first comparison result and the second comparison result.

[0069] In one embodiment, the determination unit 130 may determine the target design information as the optimal design in response to determining that the target design information is feasible. Alternatively, the determination unit 130 may change the target design information in response to determining that the target design information is infeasible. The changed target design information may be input to the target information receiver 110, allowing the optimal battery module design method according to this disclosure to be executed again.

[0070] Users who have been provided with optimal design information determined by the determination unit 130 and / or the determination results of the determination unit 130 can implement the target battery module 140 based on the determination results. Specifically, users can manufacture a battery module including target battery cells based on the target design information. As the battery module ages with repeated charge / discharge cycles, the actual degree of aging of the battery module can be substantially the same as or similar to the aging information predicted by the battery aging predictor 120.

[0071] As described above, before actually manufacturing battery cells and battery modules, the feasibility of the target design information can be output by inputting the target design information of the target battery module into a system used to design battery modules (hereinafter referred to as the "optimal battery module design system"). In other words, since it is possible to know whether a battery module is feasible without actually manufacturing it, the cost of manufacturing battery modules, etc., can be reduced. Furthermore, by determining the suitability of the design in advance from an early stage of battery module design, the risk of redesigning the battery module can be reduced.

[0072] Figure 2 This is a schematic diagram of an optimal battery module design system according to an embodiment of the present disclosure. Optimal battery module design system (e.g., referring to...) Figure 1 The battery module design system described may include experimental equipment 210, experimental data receiver 220, aging prediction model generator 230 and battery aging predictor 120.

[0073] Experimental apparatus 210 can generate charge / discharge data for individual experimental battery cells. For example, experimental apparatus 210 can measure the state of harmonics (SOH) of an experimental battery cell while repeating charge / discharge cycles. Experimental apparatus 210 can also measure the SOH of an experimental battery cell while adjusting its design environment.

[0074] In this implementation, the experimental apparatus 210 can adjust the design environment of the experimental battery cells in response to experimental design data. The experimental design data can represent the design environment of an experimental battery module including the experimental battery cells. For example, the experimental design data can include parameters affecting the lifespan of the experimental battery cells. Here, the experimental battery module can be a virtual battery module implemented using the experimental design data, and it can be assumed that the experimental battery module is in a state that accommodates the experimental battery cells.

[0075] In implementations, parameters may include control parameters that can be adjusted in the design environment and operating parameters that depend on the control parameters. Control parameters may include information associated with at least one of, for example, the stiffness of the endplate of the experimental battery module, the compressive force of the endplate, and the thickness of the insulation of the experimental battery module. Operating parameters may include information associated with at least one of, for example, the expansion force of the experimental battery module, the DC internal resistance of the experimental battery cell, the temperature deviation of the experimental battery cell (here, temperature deviation includes temperature deviation occurring within the experimental battery cell and temperature deviation of each of the plurality of experimental battery cells), and the temperature deviation of the experimental battery module. Reference Figure 7 Provide a detailed description of the control and operating parameters.

[0076] The experimental apparatus 210 may include components for adjusting the design environment of the battery cell. For example, the experimental apparatus 210 may include a receiving portion for receiving the experimental battery cell, a compression adjustment unit for adjusting the compressive force applied to the experimental battery cell, a stiffness adjustment unit for adjusting the stiffness at both ends of the experimental battery cell, and a thickness measurement unit for measuring the thickness change of the experimental battery cell. (Reference) Figure 7 Describe in detail the configuration and structure of experimental equipment 210.

[0077] The experimental data receiver 220 can receive charging / discharging data generated by the experimental device 210. Additionally, the experimental data receiver 220 can receive experimental design data. This experimental design data can be input by the user or generated by the experimental device 210. For example, when the design environment of a single experimental battery cell is changed by adjusting components included in the experimental device 210, information corresponding to the changed design environment can be generated as experimental design data.

[0078] The aging prediction model generator 230 can receive charge / discharge data and experimental design data. The aging prediction model generator 230 can generate a single-cell aging prediction model based on the experimental design data and the charge / discharge data. Specifically, the aging prediction model generator 230 can generate aging information for the experimental battery cells based on the charge / discharge data and control parameters. The aging prediction model generator 230 can calculate the size of the breathing space of the experimental battery cells based on the charge / discharge data and control parameters. The aging prediction model generator 230 can calculate the correlation between the breathing space size of the experimental battery cells and the aging information of the experimental battery cells. The aging prediction model generator 230 can generate a single-cell aging prediction model that models the correlation with the aging information of the battery cells based on the experimental design data. Here, the aging information of the battery cells may also have a correlation with the breathing space of the battery cells. (Reference) Figures 6 to 13 Describe in detail the process of generating an aging prediction model.

[0079] The aging prediction model generator 230 can transmit the generated single-cell aging prediction model to the battery aging predictor 120. (See reference...) Figure 1 As described, the battery aging predictor 120 can predict the aging information of a target battery cell based on the target design information by using a single cell aging prediction model.

[0080] In this implementation, the optimal battery module design system may include at least one memory and at least one processor. The at least one processor is configured to read and execute instructions stored in the at least one memory. (Reference) Figure 1 and Figure 2 The optimal battery module design system may include a target information receiver 110, a battery aging predictor 120, a determination unit 130, an experimental device 210, an experimental data receiver 220, and an aging prediction model generator 230. In this case, at least some of the components included in the optimal battery module design system may include a memory and a processor.

[0081] The memory may include any non-transitory computer-readable recording medium. According to embodiments, the memory may include random access memory (RAM) and permanent mass storage devices such as read-only memory (ROM), disk drives, solid-state drives (SSDs), or flash memory. As another example, permanent mass storage devices such as ROM, SSDs, flash memory, or disk drives may be included in the optimal battery module design system as separate permanent storage devices distinct from the memory. Additionally, the memory may store an operating system and at least one program code (e.g., code installed in the optimal battery module design system for determining the feasibility of target design information).

[0082] The processor can be configured to process instructions of a computer program by performing basic arithmetic, logic, and input / output operations. These instructions can be provided to experimental equipment 210, external devices, or external systems via memory or a communication module. For example, the processor can use a single-cell aging prediction model to predict the aging information of a target battery cell based on target design information. The processor can then determine the feasibility of the target design information based on the target design information and the predicted aging information.

[0083] Furthermore, the optimal battery module design system may further include a communication module. The communication module can provide configuration or functions for communicating with experimental equipment 210, and can also provide configuration or functions for communicating with external devices or systems. For example, control signals, commands, or data provided under the control of the processor of the optimal battery module design system can be transmitted to the charging device, external device, and / or external system via the communication module of experimental equipment 210, external devices, and / or external systems.

[0084] Figure 3 This is a diagram illustrating an example of a battery cell 300 according to an embodiment of the present disclosure. Figure 4 This is a diagram illustrating an example of a battery module 30 according to an embodiment of the present disclosure. Reference Figure 3 The battery cell 300 may include an electrode assembly (not shown), an exhaust portion 310, an electrolyte injection hole 330, a first terminal, a second terminal, a short sidewall 340, and a long sidewall 350.

[0085] Electrode assemblies can be formed by winding or stacking a first electrode plate, a diaphragm, and a second electrode plate in the shape of a thin plate or film. When the electrode assembly is a wound stack, the winding axis can be parallel to the length direction of the housing. Alternatively, the electrode assembly can be a stacked type other than a wound type. Therefore, this disclosure does not limit the shape of the electrode assembly. Furthermore, the electrode assembly can be a Z-stacked electrode assembly in which a positive electrode plate and a negative electrode plate are inserted on both sides of a diaphragm bent in a Z-stack configuration. The first electrode plate of the electrode assembly can act as a negative electrode, and the second electrode plate can act as a positive electrode. Obviously, the reverse is also possible. Those skilled in the art will recognize that different types of electrode assembly configurations can be used in embodiments of this disclosure.

[0086] The first electrode terminal of the first electrode plate and the second electrode terminal of the second electrode plate can be located at opposite ends of the electrode assembly. In some examples, the electrode assembly can be housed together with the electrolyte in the casing of the battery cell 300. Additionally, in the electrode assembly, the first current collector and the second current collector can be welded to the first electrode terminal of the first electrode plate and the second electrode terminal of the second electrode plate exposed on both sides of the electrode assembly.

[0087] The venting section 310 can be located at the upper part of the battery cell 300. The venting section 310 can prevent the secondary battery cell from exploding or an exothermic chain reaction of closely arranged secondary battery cells. The electrolyte injection hole 330 can be formed on the upper surface of the housing of the battery cell 300. Electrolyte can be injected into the housing through the electrolyte injection hole 330.

[0088] As shown in the attached diagram, the first direction X can refer to the X-axis direction. The second direction Y can be orthogonal to the first direction X. The second direction Y can refer to the Y-axis direction. The third direction Z can be orthogonal to both the first direction X and the second direction Y. The third direction Z can refer to the Z-axis direction.

[0089] The long side wall 350 may include a first long side wall and a second long side wall. The first long side wall and the second long side wall may face each other. The first long side wall and the second long side wall may be spaced apart from each other, while facing each other in the second direction Y.

[0090] The short sidewall 340 may include a first short sidewall and a second short sidewall. The first short sidewall and the second short sidewall may face each other. That is, the first short sidewall and the second short sidewall may be spaced apart from each other, while facing each other in the first direction X. The area of ​​the first short sidewall and the second short sidewall may be smaller than the area of ​​the first long sidewall and the second long sidewall.

[0091] exist Figure 3 In the illustration, the battery cell 300 is shown as a prismatic secondary battery cell, but this is merely an example, and the present disclosure is not limited to prismatic secondary battery cells. For example, the battery cell 300 may be a cylindrical secondary battery cell, a coin-shaped secondary battery cell, or a secondary battery cell with side terminals.

[0092] refer to Figure 4 The battery module 30 includes a plurality of battery cells 300 arranged in a second direction Y, electrode portions located between adjacent battery cells 300, connecting tabs connecting adjacent battery cells 300, and a protection circuit module having one end connected to the connecting tab. The protection circuit module may be a battery management system (BMS). Additionally, the connecting tab includes a body that contacts the electrode portions between adjacent battery cells and an extension portion extending from the body and connecting to the protection circuit module. The connecting tab may be a busbar.

[0093] It should be understood that Figure 4 The battery module 30 shown is merely an example of this disclosure. The battery module 30 may include more or fewer individual cells, as illustrated. Furthermore, one or more columns having one or more individual cells in the first direction X may be further arranged in the battery module 30. Alternatively, the battery module 30 may be a battery pack in which one or more battery modules are combined.

[0094] It will now be described that, for a target battery module including target battery cells, the aging information of the target battery cells can be predicted based on the target design information, and the feasibility of the target design information can be determined based on the target design information and the predicted aging information.

[0095] Figure 5 This is a flowchart illustrating an example of the optimal battery module design method S500 according to an embodiment of the present disclosure.

[0096] The optimal battery module design method S500 (i.e., the method for designing a battery module) can be executed using an optimal battery module design system. Here, the optimal battery module design system may include a target information receiver ( Figure 1 The target information receiver 110 and the battery aging predictor (in the middle) Figure 1 Battery aging predictor 120 and determination unit (in the middle) Figure 1The determination part 130), experimental equipment ( Figure 2 Experimental equipment 210), experimental data receiver ( Figure 2 The experimental data receiver 220 and the aging prediction model generator (in the middle) Figure 2 Aging prediction model generator 230 in the middle.

[0097] First, the experimental data receiver can receive experimental design data and charging / discharging data of the experimental battery cells corresponding to the experimental design data (step S510). Here, the experimental design data can represent the design environment of the experimental battery module including the experimental battery cells. The experimental design data may include, for example, parameters that affect the lifespan of the experimental battery cells, and these parameters may include control parameters adjusted in the design environment and operating parameters that depend on the control parameters.

[0098] In implementation, control parameters and operating parameters can be distinguished based on the degree to which they affect the lifespan of the experimental battery cells. For example, control parameters may include information associated with at least one of the stiffness of the endplate of the experimental battery module, the compressive force of the endplate, and the thickness of the insulation of the experimental battery module. Operating parameters may include information associated with at least one of the expansion force of the experimental battery module, the DC internal resistance of the experimental battery cells, the DC internal resistance of the experimental battery module, the temperature deviation of the experimental battery cells, and the temperature deviation of the experimental battery module.

[0099] In this implementation, the aging prediction model generator can generate a single-cell aging prediction model based on experimental design data and charge / discharge data (step S520). Specifically, the aging prediction model generator can generate aging information of the experimental battery cells based on the charge / discharge data and control parameters. The aging prediction model generator can calculate the size of the breathing space of the experimental battery cells based on the charge / discharge data and control parameters. Here, the size of the target breathing space can be related to the degree of expansion of the target battery cell during charging and discharging. The aging prediction model generator can also calculate the correlation between the breathing space size of the experimental battery cells and the aging information of the experimental battery cells. Here, the aging information can include the state of health (SOH) information of the target battery cells that have undergone a preset number of charge / discharge cycles.

[0100] In this implementation, the charging / discharging data can be generated by the experimental equipment. The experimental equipment may include a receiving part for receiving the experimental battery cell, a compression adjustment unit for adjusting the compressive force applied to the experimental battery cell, a stiffness adjustment unit for adjusting the stiffness at both ends of the experimental battery cell, and a thickness measurement unit for measuring the thickness change of the experimental battery cell.

[0101] The target information receiver can receive target design information for a target battery module, which includes target battery cells (step S530). The target design information may include, for example, individual cell specifications and module specifications for the target battery module. Furthermore, the target design information may further include target aging information for the target battery cells.

[0102] The battery aging predictor can use a cell aging prediction model that models the correlation between the design of the battery module, including the battery cells, and the aging of the battery cells to predict the aging information of the target battery cell based on the target design information (step S540).

[0103] The determination unit can determine whether the target design information is feasible based on the target design information and the predicted aging information (step S550). Specifically, the determination unit can calculate the size of the target breathing space based on the unit specification information and the module specification information. The determination unit can determine whether the target design information is feasible based on the size of the target breathing space and the predicted aging information.

[0104] The determination unit can determine the feasibility of the target design information based on the size of the target breathing space, target aging information, and predicted aging information. For example, the determination unit can generate a first comparison result by comparing the size of the breathing space associated with the aging information with the size of the target breathing space. The determination unit can also compare the target aging information with the predicted aging information to generate a second comparison result. The determination unit can determine the feasibility of the target design information based on the first comparison result and the second comparison result.

[0105] In embodiments of this disclosure, a battery module designed using the optimal battery module design method of this disclosure can be provided. The optimal battery module design method may include: receiving target design information about a target battery module, the target battery module including target battery cells; predicting the aging of the target battery cells based on the target design information using a cell aging prediction model, the cell aging prediction model associating the design of the battery module including the battery cells with the aging of the battery cells; and determining whether the target design information is feasible based on the target design information and the predicted aging of the target battery cells.

[0106] Figure 6 This is a flowchart illustrating an example of a method for generating charge / discharge data for an experimental battery cell according to an embodiment of the present disclosure. Experimental equipment (e.g., Figure 2 The experimental equipment 210 can generate charge / discharge data for individual experimental battery cells. This data can be received at a target information receiver (e.g., Figure 1 The step of receiving charging / discharging data of experimental battery cells by the target information receiver 110 (e.g., Figure 5Before step S510, the step of generating charge / discharge data for the experimental battery cells is performed.

[0107] The method for generating charge / discharge data for experimental battery cells can begin by arranging the experimental battery cells in the receiving section of the experimental equipment (step S610). One or more experimental battery cells can be arranged in the receiving section of the experimental equipment. The arrangement of the experimental battery cells in the receiving section can simulate the arrangement of battery cells in a battery module.

[0108] The design environment of the experimental battery module corresponding to the experimental design data can be adjusted (step S620). For example, the design environment of the experimental battery module can be adjusted by using the compression adjustment unit, stiffness adjustment unit, and thickness adjustment unit included in the experimental equipment.

[0109] In this implementation, the experimental design data may include parameters affecting the lifespan of the experimental battery cells. These parameters may include control parameters adjusted within the design environment of the experimental battery module and operating parameters dependent on those control parameters. (See reference...) Figure 7 Describe in detail the standards used to distinguish between control parameters and operating parameters.

[0110] The experimental equipment can generate charge / discharge data for the experimental battery cells (step S630). Specifically, the experimental equipment can measure the state of equilibrium (SOH) of the experimental battery cells by repeating charge / discharge cycles. For example, the experimental equipment can measure the SOH of the experimental battery cells in each charge / discharge cycle. SOH can be measured by continuously measuring the capacity of the experimental battery cells and calculating the SOH of the experimental battery cells based on the measured capacity.

[0111] Figure 7 This is a diagram illustrating an example of a battery module 700 according to an embodiment of the present disclosure. Figure 7 The battery module 700 is Figure 4 A simplified representation of a portion of the interior of battery module 30, with battery module 700 viewed from its side. (See reference...) Figure 7 Describe the parameters that affect the lifespan of a single battery cell.

[0112] In one embodiment, end plates 710 may be formed at both ends of the battery module 700. One or more battery cells 720 may be accommodated between the end plates 710 at both ends. For example, the long sidewalls of the battery cells 720 and the end plates 710 may face each other. The battery module 700 may include a heat insulation body 730 between the end plates 710 and the battery cells 720. Alternatively, the heat insulation body 730 may be located between the battery cells 720. The heat insulation body 730 may face the long sidewalls of the battery cells 720.

[0113] With repeated charging and discharging, the lifespan of the battery cell 720 shortens. In other words, the battery cell 720 ages with each charging and discharging process. Therefore, with repeated charging and discharging, the state of harmonics (SOH) of the battery cell 720 decreases. However, depending on the design environment of the battery module 700 including the battery cell 720, the aging rate of the battery cell 720 can be accelerated or slowed down. In other words, by adjusting the design environment corresponding to the parameters affecting the lifespan of the battery cell 720, the aging rate of the battery cell 720 can be accelerated or slowed down.

[0114] The parameters affecting the aging rate of the battery cell 720 can be related to the design environment of the battery module 700. For example, parameters may include the end plate stiffness EPS, compressive force CF, insulation thickness (e.g., heat shield thickness, HST), expansion force of the battery module 700, DC internal resistance of the battery cell 720, DC internal resistance of the battery module 700, temperature deviation of the battery cell 720, and temperature deviation of the battery module 700, etc.

[0115] When battery cell 720 is subjected to mechanical stress, its aging rate may decrease. If relatively strong pressure is applied to battery cell 720, the cell, which expands and contracts during charging and discharging, may not expand and contract smoothly, potentially accelerating its degradation. Conversely, if relatively weak pressure is applied, the gas generated inside the cell increases, increasing its internal resistance. Therefore, parameters associated with the mechanical stress applied to battery cell 720 can significantly impact its lifespan.

[0116] Among the parameters associated with the mechanical stress on the battery cell 720, the end plate stiffness EPS, compressive force CF, and insulation thickness can have a significant impact on the lifespan of the battery cell 720. These parameters can be referred to as control parameters. Parameters other than control parameters can be referred to as operating parameters.

[0117] When generating charge / discharge data for experimental battery cells, this data can be generated by adjusting the design environment corresponding to the control parameters. By adjusting the design environment corresponding to the control parameters, the degree of aging of the experimental battery cells caused by the control parameters can be determined. See below for reference. Figure 11 Describe in detail the experimental design data with adjustable control parameters.

[0118] Figure 8 This is a perspective view of an experimental apparatus 800 according to an embodiment of the present disclosure. Figure 9 This is a top view of experimental equipment 800, and Figure 10 This is a side view of experimental equipment 800.

[0119] The experimental apparatus 800 may include a base 810, a receiving part 820, and a design adjustment part 830. The base 810 may be the main body of the experimental apparatus 800, and other components of the experimental apparatus 800 may be disposed on the base 810. Wheels and the like may be formed on the lower surface of the base 810 to facilitate the movement of the experimental apparatus 800.

[0120] A receiving portion 820 can be formed between a fixed portion 822 and a design adjustment portion 830. The fixed portion 822 can be fixed to the bottom 810. The receiving portion 820 can receive the experimental battery cell 850. The fixed portion 822 can support the experimental battery cell 850, preventing it from moving. Figure 8 In the diagram, the fixing portion 822 is shown as supporting the long sidewall of the experimental battery cell 850, but the fixing portion 822 can also support the short sidewall of the experimental battery cell 850.

[0121] The experimental battery cell 850 can be housed in the receiving portion 820. Specifically, the experimental battery cell 850 can be mounted on a support plate and housed in the receiving portion 820. However, the experimental battery cell 850 can also be housed separately in the receiving portion 820. Figure 8 The diagram shows three experimental battery cells 850. However, fewer or more than three experimental battery cells 850 may be accommodated in the receiving section 820.

[0122] In one embodiment, the thermal insulator is located between one experimental battery cell 850 and another experimental battery cell 850. Additionally or alternatively, the thermal insulator may be located between the experimental battery cell 850 and the design adjustment portion 830 and / or between the fixing portion 822 and the experimental battery cell 850.

[0123] The design adjustment section 830 can adjust the design environment of the experimental battery cell 850. For example, the design adjustment section 830 can adjust the design environment corresponding to the control parameters provided in the experimental design data. Here, the experimental design data can represent the design environment of an experimental battery module including the experimental battery cells. Furthermore, the experimental battery module can be a virtual battery module that can be implemented using the experimental design data, and can be assumed to house the experimental battery cells.

[0124] In this implementation, the parameters may include information regarding the end plate stiffness EPS, compression force CF, and the thickness of the insulation. The design adjustment section 830 may include a load measurement unit 832, a stiffness adjustment unit 834, a thickness measurement unit 836, and a compression adjustment unit 838. The load measurement unit 832 can measure the load applied to the experimental battery cell 850 housed in the receiving section 820. The load measured by the load measurement unit 832 can be correlated with the expansion force of the experimental battery cell 850. The stiffness adjustment unit 834 can adjust the stiffness at both ends of the experimental battery cell 850. For example, the stiffness adjustment unit 834 can adjust the stiffness at both ends of the experimental battery cell 850 by adjusting the spring constant. The stiffness adjustment unit 834 can be correlated with the stiffness of the end plate of the experimental battery module. The thickness measurement unit 836 can measure the thickness change of the experimental battery cell 850 as it expands and contracts during charging and discharging. For example, the thickness measurement unit 836 can measure the thickness of the experimental battery cell 850 using a linear gauge. In addition, information about the thickness of the insulation can be determined by changing the type and thickness of the insulation disposed between the experimental cell 850 and between the experimental cell 850 and the design adjustment part 830 and / or the fixing part 822.

[0125] By using the aforementioned experimental equipment 800, it is possible to obtain charge / discharge data for battery cells with a design environment corresponding to the parameters affecting the battery modules and battery cells, without directly implementing the design environment with battery modules and / or battery cells, thereby reducing the cost of manufacturing battery modules, etc. Furthermore, charge / discharge data for the experimental battery cell 850 can be obtained while easily adjusting factors that apply mechanical stress to the experimental battery cell 850.

[0126] Figure 11 These are graphs and tables showing the control parameters used in several experimental examples in this disclosure. Figure 12 This is a table showing the experimental results of several experimental examples of this disclosure.

[0127] Figure 11 The table shows the control parameters for each of the multiple experimental examples. Figure 11 The graphs in the diagrams illustrate the control parameters for each of the multiple experimental examples. Figure 11 The curves in the graph can represent the control parameters. The stiffness of the end plate of the experimental battery module is used as the X-axis, the compressive force as the Y-axis, and the thickness of the insulation (heat shield) as the Z-axis. Figure 11 In the curve graph, T1 to T9 can refer to Experimental Example 1 to Experimental Example 9.

[0128] By arranging the experimental battery cells in the experimental apparatus (e.g., Figure 8In the experimental equipment 800), and the manipulation design adjustment part (e.g., Figure 8 The design adjustment section 830 allows for adjustments to the design environment. Each of the multiple experimental examples illustrates a scenario where the design environment is altered. For instance, the stiffness adjustment unit in the design adjustment section can be used to adjust the design corresponding to the stiffness of the end plate of the corresponding battery module. As another example, the compression adjustment unit in the design adjustment section can be used to adjust the design corresponding to the compressive force of the corresponding battery module. As yet another example, the thickness of the insulation can be adjusted by changing the thickness and type of the insulation in contact with the experimental battery cell.

[0129] refer to Figure 11 In the table below, in the first experimental example, the end plate stiffness is approximately 5 kN / mm, the compressive force is approximately 1 kN, and the insulation thickness is approximately 1.2 mm. The control parameters for each of the second through ninth experimental examples are shown in... Figure 11 In the table. Here, "rigid" can mean that no elastic structure such as a spring is placed in the stiffness adjustment unit of the experimental equipment, and "rigid" can mean that the stiffness of the end plate is approximately 100 kN / mm.

[0130] Typically, for a single battery cell housed within a battery module, the thickness of the insulation can be approximately 1 mm to 4 mm, the stiffness of the battery module's end plate can be approximately 0 kN / mm to 100 kN / mm, and the compressive force can be approximately 0 kN to 100 kN. To facilitate the interpretation of charge / discharge data, it may be desirable to include information in the control parameters at the extremes or in the middle of values ​​that are generally determinable. Therefore, 5 kN / mm, 25 kN / mm, and 100 kN / mm can be selected as values ​​for the stiffness of the battery module's end plate; 1 kN, 4 kN, and 10 kN can be selected as values ​​for the compressive force; and 1.2 mm, 2.4 mm, and 3.6 mm can be selected as values ​​for the thickness of the insulation. In the depicted embodiment, a total of nine cases are provided from the combinations of selected values, and multiple experimental examples can be corresponding to these nine cases respectively. Figure 11 The graphs in the figure confirm that multiple experimental examples were placed at opposite ends or in the middle of the values.

[0131] refer to Figure 12 Confirm reference Figure 11The experimental results for each of the described multiple experimental examples are possible. Furthermore, experimental results for a first comparative example and a second comparative example are also provided. The first comparative example is an actual experimental battery module as a result of direct experimentation. In the first comparative example, the end plate stiffness of the experimental battery module is approximately 100 kN / mm, the compressive force of the experimental battery module is approximately 4 kN, and the thickness of the insulation is approximately 1.2 mm. The second comparative example shows the experimental results for an experimental battery cell not housed within a battery module.

[0132] In the first comparative example, the second comparative example, and the first to ninth experimental examples, the SOH was measured once for every preset number of charge / discharge cycles. Figure 12 The table shows the SOH results measured every 50 charge / discharge cycles. In the first and third through ninth experimental examples, measurements were performed up to 200 charge / discharge cycles, and in the second experimental example, measurements were performed after 350 charge / discharge cycles. In the first and second comparative examples, measurements were performed after 400 charge / discharge cycles. (Reference) Figure 12 The table shows that the state of harmonics (SOH) of the experimental battery cells decreases with the increase of the number of charge / discharge cycles. In other words, the experimental battery cells age as they undergo charge and discharge cycles.

[0133] refer to Figure 12 The experimental results show that the surface area (SOH) of the experimental battery cells decreases when the stiffness of the end plate increases, the compressive force increases, and the thickness of the insulation decreases. In other words, the stiffer the end plate, the greater the compressive force, and the thinner the insulation, the faster the experimental battery cells may age. Based on these experimental results, the correlation between control parameters and the degree of aging of battery cells can be determined.

[0134] To more specifically determine the correlation between the control parameters and aging degree of individual battery cells, the design environment corresponding to the first through ninth experimental examples can be further refined to generate experimental design data and charge / discharge data for the experimental battery cells. (Reference) Figure 13 The methods for generating more experimental results are described in detail, as well as the correlation between the control parameters of individual battery cells and aging information.

[0135] Figure 13 This is graph 1300 showing the correlation between monomer aging information and breathing space size. (Reference) Figure 11 and Figure 12The first through ninth experimental examples described were designed with three control parameters divided into three levels. For example, values ​​of 5 kN / mm, 25 kN / mm, and 100 kN / mm were selected for the end plate stiffness, 1 kN, 4 kN, and 10 kN for the compressive force, and 1.2 mm, 2.4 mm, and 3.6 mm for the insulation thickness. More specifically than the first through ninth experimental examples, values ​​of 5 kN / mm, 15 kN / mm, 25 kN / mm, 50 kN / mm, and 100 kN / mm were selected for the end plate stiffness, 1 kN, 1.75 kN, 2.5 kN, 3.25 kN, 4 kN, 5.5 kN, 7 kN, 8.5 kN, and 10 kN for the compressive force, and 1.2 mm, 1.5 mm, 1.8 mm, 2.1 mm, 2.4 mm, 2.7 mm, 3 mm, and 3.6 mm for the insulation thickness. A total of 405 design environments can be derived from the combinations of selected values. Based on the experimental results of the first to ninth experimental examples, simulations were performed on all 405 cases using Taguchi sensitivity analysis. Using the simulation results, the size of the breathing space of the experimental cell and the expansion force SF of the experimental cell according to the state of state of equilibrium (SOH) after 200 charge / discharge cycles were determined. Figure 13 As shown in the image.

[0136] The size of the breathing space can be related to the degree of expansion of the battery cell during charging and discharging. For example, as the battery cell is repeatedly charged and discharged, it expands and contracts, and the size of the breathing space can indicate the change in thickness of the expanding and contracting battery cell. The size of the breathing space of an experimental battery cell can be calculated by measuring the thickness of the contracted experimental battery cell and the thickness of the expanded experimental battery cell using the thickness measurement unit of the experimental equipment.

[0137] The expansion force of a battery cell can be expressed as the force per unit area generated when a charged battery cell expands. The expansion force of an experimental battery cell can be measured using the load measurement unit of the experimental equipment. Alternatively or additionally, the expansion force of an experimental battery cell can be calculated based on the stiffness of the end plate, compressive force, and the thickness of the insulation, etc.

[0138] Figure 13The graph 1300 includes first data 1310 and second data 1320. First data 1310 represents the breathing space and aging information of the experimental battery cells based on simulation results for 405 scenarios. In first data 1310, the X-axis represents the state of harmonics (SOH) of the battery cell after 200 charge / discharge cycles, and the Y-axis represents the breathing space of the experimental battery cell. Referring to first data 1310, it can be seen that the larger the breathing space of the experimental battery cell, the better the SOH of the experimental battery cell after 200 charge / discharge cycles. In other words, the data shows that the larger the breathing space of the battery cell, the slower the aging of the battery cell.

[0139] Data point 1320 is based on simulation results from 405 scenarios, providing information on the expansion force and aging of individual battery cells. In data point 1320, the X-axis represents the state of equilibrium (SOH) of a battery cell after 200 charge / discharge cycles, and the Y-axis represents the expansion force of the battery cell. Referring to data point 1320, it can be confirmed that the greater the expansion force of a battery cell, the smaller the SOH of the battery cell after 200 charge / discharge cycles. In other words, the greater the expansion force of a battery cell, the faster it ages.

[0140] Figure 13 T1 to T9, as shown, represent the first to ninth experimental examples. S1 to S4 represent the experimental results of actual experimental battery modules with four of the 405 simulated scenarios. Here, the values ​​in parentheses represent the error between the actual experimental results and the simulated results. "Module similarity" indicates the experimental results of the first comparative example, and "cell similarity" indicates the experimental results of the second comparative example. E1 represents the experiment with an end plate stiffness of 25 kN / mm, a compressive force of 10 kN, and an insulation thickness of 2.4 mm. In experiment E1, the SOH of the battery cell that has undergone 200 charge / discharge cycles is 87.5%. E2 represents the experiment with an end plate stiffness of 25 kN / mm, a compressive force of 4 kN, and an insulation thickness of 2.4 mm. In experiment E2, the SOH of the battery cell that has undergone 200 charge / discharge cycles is 90%.

[0141] As described above, the correlation between the breathing space dimensions of individual battery cells included in a battery module and the aging information of those cells can be determined. Furthermore, the correlation between the expansion force of individual battery cells included in a battery module and aging information can be determined. When these correlations are used to adjust the design environment corresponding to the control parameters, the aging information of the battery based on the breathing space dimensions of the individual cells can be predicted.

[0142] Figure 14This is a detailed flowchart of step S550 for determining whether target design information is feasible according to an embodiment of this disclosure. The determination unit (e.g., Figure 1 The determination unit 130 can be used to determine whether the target design information is feasible based on the target design information and the predicted aging information (step S550).

[0143] In this implementation, the step of determining whether the target design information is feasible can begin by calculating the size of the target breathing space based on the target design information (step S1410). The target design information may include the individual cell specification information and the module specification information of the target battery module. The size of the target breathing space can be calculated based on the individual cell specification information and the module specification information. Information about the specifications of the individual cells and the specifications of the battery modules can be stored in a specification database. For each individual cell specification and each battery module specification, the specification database may include information about possible mechanical stresses. For example, for the specifications of a specific individual cell and a specific battery module, the specification database may include information about the stiffness of the end plate of the specific battery module, the compressive force of the specific battery module, the thickness of the insulation of the specific battery module, and the expansion force of the specific individual cell. The determination unit can extract information related to the control parameters of the specifications of the target individual cell and the target battery module included in the target design information from the specification database. Then, the determination unit can calculate the size of the breathing space of the target individual cell based on the information associated with the extracted control parameters.

[0144] In implementation, a battery aging predictor (e.g., Figure 1 The battery aging predictor 120 can predict the aging of a target battery cell based on target design information by using a cell aging prediction model. The battery aging predictor can calculate the size of the breathing space associated with the predicted aging information. Furthermore, the determination unit can generate a first comparison result (step S1420) by comparing the size of the breathing space associated with the predicted aging information with the size of the target breathing space. The determination unit can also generate a second comparison result (step S1430) by comparing the target aging information with the predicted aging information. The target aging information can be included in the target design information and can indicate the expected aging information of the target battery cell.

[0145] The determination unit can determine whether the target design information is feasible based on the first comparison result and the second comparison result (step S1440). For example, if the size of the breathing space associated with the predicted aging information is less than or equal to the size of the target breathing space, and the target aging information is greater than or equal to the predicted aging information, then the determination unit can determine that the target design information is feasible. If the size of the breathing space associated with the predicted aging information is greater than the size of the target breathing space, or the target aging information is less than the predicted aging information, then the determination unit can determine that the target design information is not feasible.

[0146] Figure 5 , Figure 6 and Figure 14 The flowcharts and related descriptions in the above are examples of this disclosure, but the scope of this disclosure is not limited to the above. Figure 5 , Figure 6 and Figure 14 The flowchart and related descriptions are provided. For example, in the flowchart and / or description above, one or more steps can be added / changed / deleted, the order of one or more steps can be changed, and one or more steps can be executed simultaneously.

[0147] Figure 15 This is an example of an optimal battery module design interface 1500 according to an embodiment of the present disclosure. The optimal battery module design interface 1500 may include a target information input interface 1510, a confirmation result output interface 1520, and a confirmation request button 1530.

[0148] Users can input target design information through the target information input interface 1510. Target design information may include individual cell specifications, target battery module specifications, target aging information, target charging speed, and target number of charge / discharge cycles, etc. (Reference) Figure 15 Information regarding the material, width, thickness, and depth of individual battery cells can be input as cell specification information through the target information input interface 1510. Information regarding the structure of the battery module (e.g., the number of battery cells arranged in series or in parallel), the type, quantity, and thickness of the spacers between the end cells, the type, quantity, and thickness of the insulation material placed between the battery cells, and the rigidity and compressive force of the battery module can be input as module specification information through the target information input interface 1510.

[0149] After the target information input interface 1510 receives the required information, in response to the input of the confirmation request button 1530, the confirmation result output interface 1520 can output a confirmation result based on whether the target design information is feasible. The confirmation result output interface 1520 can output the dimensions of the target breathing space 1528 calculated based on the target design information. Furthermore, the confirmation result output interface 1520 can output the aging information of the target battery cell predicted based on the target design information.

[0150] The determination result output interface 1520 can also output the dimensions of multiple target breathing spaces 1528. In response to this output, the determination result output interface 1520 can output predicted aging information 1526 and the dimensions of the breathing spaces 1529 associated with the predicted aging information. For example, the dimensions of the multiple target breathing spaces 1528 can be output in response to the expansion force of the target battery cell. The predicted aging information 1526 and the dimensions of the breathing spaces 1529 associated with the predicted aging information can be output in response to the expansion force of the target battery cell from which the dimensions of the multiple target breathing spaces 1528 are derived.

[0151] In an implementation, the result output interface 1520 can output a first result comparing the size of the target breathing space 1528 with the size of the breathing space associated with the predicted aging information 1526. For example, if the size of the target breathing space 1528 is smaller than the size of the breathing space associated with the predicted aging information 1526, a result indicating insufficient breathing space size can be output (e.g., Figure 15 (The "insufficiency" in the text). Furthermore, if the size of the target breathing space 1528 is greater than or equal to the size of the breathing space associated with the predicted aging information 1526, a result indicating that the breathing space size is sufficient can be output (e.g., Figure 15 (The word "sufficient" in the context).

[0152] In this implementation, the maximum value of the predicted aging information 1526 from the data indicating that the breathing space size is sufficient can be provided as a representative value 1522 of the aging information. A second result 1524 comparing the representative value 1522 of the aging information with the target aging information can be output. For example, if the representative value 1522 of the aging information is less than the target aging information, the determination result output interface 1520 can output a determination result indicating that the target design information is not feasible (e.g., Figure 15 (Failure in the context of aging information). If the representative value 1522 of the aging information is greater than or equal to the target aging information, the determination result output interface 1520 can output a determination result indicating that the target design information is feasible.

[0153] As described above, by inputting target design information via the optimal battery module design interface 1500 and comparing the target aging information with the predicted aging information, it is easy to determine whether the target design information is actually feasible. Furthermore, by inputting changed target design information, it is possible to determine whether various target design information is actually feasible, and to obtain the optimal battery module design information among various target design information.

[0154] Although this disclosure has been described above with respect to its embodiments, it is not limited thereto. Those skilled in the art will be able to make various modifications and variations within the spirit of this disclosure.

Claims

1. A method of designing a battery module, the method comprising: receiving target design information about a target battery module, the target battery module including target battery cells; predicting, based on the target design information, aging of the target battery cells by using a cell aging prediction model that relates a design of a battery module including a battery cell to aging of the battery cell; and determining, based on the target design information and the predicted aging of the target battery cells, whether the target design information is feasible.

2. The method of claim 1, wherein, the target design information includes cell specification information about the target battery cells and module specification information about the target battery module, and wherein determining whether the target design information is feasible includes: calculating, based on the cell specification information and the module specification information, a size of a target breathing space; and determining, based on the size of the target breathing space and the predicted aging of the target battery cells, whether the target design information is feasible.

3. The method of claim 2, wherein, the target design information further includes target aging information about the target battery cells, and wherein determining, based on the size of the target breathing space and the predicted aging of the target battery cells, whether the target design information is feasible includes determining, based on the size of the target breathing space, the target aging information, and the predicted aging of the target battery cells, whether the target design information is feasible.

4. The method of claim 3, wherein, determining, based on the size of the target breathing space, the target aging information, and the predicted aging of the target battery cells, whether the target design information is feasible includes: generating a first comparison result by comparing a size of a breathing space associated with the predicted aging of the target battery cells and the size of the target breathing space; generating a second comparison result by comparing the target aging information and the predicted aging of the target battery cells; and determining, based on the first comparison result and the second comparison result, whether the target design information is feasible.

5. The method of any one of claims 1 to 4, further comprising: receiving experimental design data and charge / discharge data of an experimental battery cell corresponding to the experimental design data, wherein the experimental design data represents a design environment of an experimental battery module including the experimental battery cell; and generating the cell aging prediction model based on the experimental design data and the charge / discharge data.

6. The method of claim 5, wherein, the experimental design data includes a parameter that affects a lifetime of the experimental battery cell, and wherein the parameter includes a control parameter adjusted in the design environment and an operation parameter dependent on the control parameter.

7. The method of claim 6, wherein, the control parameter relates to at least one of a stiffness of an end plate of the experimental battery module, a compression force, and a thickness of an insulator of the experimental battery module.

8. The method of claim 6, wherein, The operation parameter is related to at least one of a swelling force of the experimental battery module, a DC internal resistance of the experimental battery cell, a DC internal resistance of the experimental battery module, a temperature deviation of the experimental battery cell, and a temperature deviation of the experimental battery module.

9. The method of claim 6, wherein, The control parameter and the operation parameter are distinguished based on how much the control parameter and the operation parameter affect the life of the experimental battery cell.

10. The method of claim 6, wherein, Generating the cell aging prediction model includes generating, based on the charge / discharge data, aging information of the experimental battery cell from the control parameter.

11. The method of claim 10, wherein, Generating the cell aging prediction model further includes: calculating, based on the charge / discharge data, a size of a breathing space of the experimental battery cell from the control parameter; and calculating a correlation between the size of the breathing space of the experimental battery cell and the aging information of the experimental battery cell.

12. The method of claim 5, wherein, The charge / discharge data is generated by an experimental apparatus including: a receiving portion to receive the experimental battery cell; a compression adjustment unit to adjust a compression force applied to the experimental battery cell; a rigidity adjustment unit to adjust rigidity of opposite ends of the experimental battery cell; and a thickness measurement unit to measure a thickness change of the experimental battery cell.

13. The method of any one of claims 1 to 4, wherein, The predicted aging of the target battery cell includes state of health (SOH) information of the target battery cell that has experienced charge / discharge cycles.

14. The method of any one of claims 2 to 4, wherein, The size of the target breathing space is associated with how much the target battery cell swells when the target battery cell is charged and discharged.

15. A system for designing a battery module, the system comprising: at least one processor configured to read out and execute instructions stored in at least one memory, thereby causing the system to function as: a target information receiver configured to receive target design information about a target battery module, the target battery module including target battery cells; a battery aging predictor configured to predict aging of the target battery cells based on the target design information by using a cell aging prediction model that associates a design of a battery module including battery cells with aging of the battery cells; and a determiner configured to determine whether the target design information is feasible based on the target design information and the predicted aging of the target battery cells.

16. The system of claim 15, wherein, The target design information includes cell specification information about the target battery cells and module specification information about the target battery module, and wherein the determiner is further configured to calculate a size of a target breathing space based on the cell specification information and the module specification information, and the determiner is further configured to determine whether the target design information is feasible based on the size of the target breathing space and the predicted aging of the target battery cells.

17. The system of claim 16, wherein, The target design information further includes target aging information about the target battery cells, and the determiner is further configured to determine whether the target design information is feasible based on the target aging information. The determining whether the target design information is feasible based on the size of the target breathing space and the predicted aging of the target battery cell includes determining whether the target design information is feasible based on the size of the target breathing space, the target aging information, and the predicted aging of the target battery cell.

18. The system of claim 17, wherein, The determining whether the target design information is feasible further includes: generating a first comparison result by comparing a size of a breathing space associated with the predicted aging of the target battery cell and the size of the target breathing space; generating a second comparison result by comparing the target aging information and the predicted aging of the target battery cell; and determining whether the target design information is feasible based on the first comparison result and the second comparison result.

19. The system of any one of claims 15 to 18, further comprising: an experimental data receiver configured to receive experimental design data and charge / discharge data of an experimental battery cell corresponding to the experimental design data, wherein the experimental design data represents a design environment of an experimental battery module including the experimental battery cell; and an aging prediction model generator configured to generate the cell aging prediction model based on the experimental design data and the charge / discharge data.

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