A battery tab number optimization method, device, equipment and readable storage medium

Abstract

The application relates to the technical field of batteries, and discloses a battery tab quantity optimization method, device, equipment and readable storage medium, which comprises the following steps: constructing a plurality of battery parameterized simulation models with a unified geometric configuration taking a tab quantity as a variable; obtaining a direct-current resistance of each battery parameterized simulation model under the same working condition according to a standardized electrochemical simulation test method; based on all the direct-current resistances, respectively performing optimal solving on a benefit trade-off analysis model and a geometric shape inflection point identification model to obtain a first tab quantity recommended interval and a second tab quantity recommended interval; and performing set operation on the first tab quantity recommended interval and the second tab quantity recommended interval to obtain a target tab quantity design interval. The application significantly improves the scientificity and reliability of battery tab quantity decision-making, and effectively enhances the implementability and stability of the optimization result in actual production.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a method, apparatus, device and readable storage medium for optimizing the number of battery tabs. Background Technology

[0002] The DC internal resistance (DCR) of lithium-ion batteries is a core parameter affecting their high-power discharge and fast-charging capabilities. Increasing the number of tabs to reduce internal resistance has become a common technical approach in the industry, and a series of structural evolutions have been formed from single tabs, dual tabs, multi-tabs to all-tabs.

[0003] Current technologies still heavily rely on engineers' experience or discrete comparative experiments with a small number of physical prototypes when determining the optimal number of tabs, making it difficult to systematically characterize the continuous impact of the number of tabs on DCR across the entire range. At the same time, the lack of an objective quantitative definition mechanism for the "performance improvement saturation zone" makes it impossible to avoid wasting performance potential due to insufficient tab quantity, and also difficult to prevent increased manufacturing costs, process complexity, and safety risks caused by excessive tab addition. More fundamentally, a standardized method that is reproducible, transferable, and embeddable into the forward design process has not yet been established, resulting in repeated trial and error for the tab configuration of each new battery, leading to low R&D efficiency, poor decision reliability, and difficulty in accumulating optimization results. Summary of the Invention

[0004] In view of this, embodiments of this application provide a method, apparatus, device and readable storage medium for optimizing the number of battery tabs, which can effectively solve the key problems in the prior art, such as high blindness in the decision-making of the number of tabs, imbalance of cost and benefit, and non-reusability of design process, caused by reliance on experience trial and error, lack of full-range performance modeling and saturation point quantification criteria.

[0005] In a first aspect, embodiments of this application provide a method for optimizing the number of battery tabs, including: Construct multiple battery parameterized simulation models with unified geometric configurations, using the number of tabs as a variable; Based on standardized electrochemical simulation testing methods, the DC internal resistance of each battery parameterized simulation model under the same preset operating conditions is obtained; Based on all the DC internal resistances, the benefit-trade analysis model and the geometric inflection point identification model are optimally solved to obtain the recommended interval for the number of first and second electrodes. A set operation is performed on the first recommended range for the number of electrodes and the second recommended range for the number of electrodes to obtain the target range for the number of electrodes.

[0006] In some embodiments, constructing multiple battery parameterized simulation models with a unified geometric configuration, using the number of tabs as a variable, includes: Establish a three-dimensional electrochemical model of the target battery model as a benchmark geometric model; The baseline geometric model is transformed into a battery parametric simulation model, and the number of tabs is configured as a variable parameter of the battery parametric simulation model. Based on the multiple values ​​of the variable parameter, a geometric array operation is performed on the battery parameterized simulation model to construct multiple battery parameterized simulation models with uniform geometric configuration and the number of tabs as the only variable.

[0007] In some embodiments, obtaining the DC internal resistance of each battery parameterized simulation model under preset identical operating conditions according to a standardized electrochemical simulation testing method includes: For each battery parameterized simulation model, constant current discharge pulse tests were performed at multiple state of charge points under constant ambient temperature. Collect the open-circuit voltage at the start time and the instantaneous voltage at the end time of each constant current discharge pulse test; Based on the open-circuit voltage, instantaneous voltage, and corresponding pulse current value, calculate the DC internal resistance at each state of charge point, and determine the DC internal resistance of each battery parameterized simulation model at a specified state of charge point.

[0008] In some embodiments, the step of optimally solving the benefit-trade analysis model and the geometric inflection point identification model based on all the DC internal resistances to obtain the recommended interval for the number of first and second electrodes includes: Based on all the DC internal resistances, the number of first key tabs is determined, and a recommended range for the number of first tabs in the form of a first closed range is generated according to the preset range construction rules. Based on all the DC internal resistances, the number of second key tabs is determined, and a recommended range for the number of second tabs in the form of a second closed interval is generated according to the preset interval construction rules. Wherein, the domains of the first closed interval and the second closed interval are both sets of positive integers, and the endpoints of the intervals are taken from the set of the number of tabs corresponding to the DC internal resistance.

[0009] In some embodiments, the step of generating a first closed interval in the form of a first recommended interval for the number of first pole pieces includes: The reference DC internal resistance is determined when the number of electrodes is a reference value; Based on the reference DC internal resistance and all the DC internal resistances, calculate the normalized performance gain corresponding to the number of each tab; Based on the pre-defined cost impact model, calculate the cost impact factor corresponding to the number of each electrode; Based on the normalized performance gains and the cost impact factors, a benefit function is constructed and the number of electrodes that make the benefit function take an extreme value is determined, generating a first recommended interval for the number of electrodes in the form of a first closed interval.

[0010] In some embodiments, the step of generating the second closed interval in the form of a second electrode number recommendation interval includes: A two-dimensional coordinate point set is constructed based on all the aforementioned DC internal resistances; Connect the first and last coordinate points of the coordinate point set to form a reference straight line; Calculate the perpendicular distance from each intermediate coordinate point to the reference line; Determine the number of electrodes corresponding to the maximum vertical distance, and generate a second recommended interval for the number of electrodes in the form of a second closed interval.

[0011] In some embodiments, performing a set operation on the first recommended range for the number of electrodes and the second recommended range for the number of electrodes to obtain the target range for the number of electrodes includes: Perform an intersection operation on the first recommended interval for the number of electrodes and the second recommended interval for the number of electrodes to obtain the common part of the first recommended interval for the number of electrodes and the second recommended interval for the number of electrodes on the positive integer axis; determine the common part as the target electrode number design interval in the form of a closed interval.

[0012] Secondly, embodiments of this application provide a battery tab quantity optimization device, comprising: The model building module is used to build multiple battery parameterized simulation models with a unified geometric configuration, using the number of tabs as a variable. The simulation test module is used to obtain the DC internal resistance of each battery parameterized simulation model under the same preset operating conditions according to the standardized electrochemical simulation test method; The data processing module is used to perform optimal solutions on the benefit-trade analysis model and the geometric inflection point identification model based on all the DC internal resistances, respectively, to obtain the recommended interval for the number of first and second electrodes. The electrode number acquisition module is used to perform set operations on the first electrode number recommendation interval and the second electrode number recommendation interval to obtain the target electrode number design interval.

[0013] Thirdly, embodiments of this application provide a terminal device, the terminal device including a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the battery tab number optimization method of the first aspect described above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium, wherein when the computer program is executed on a processor, it implements the battery tab number optimization method of the first aspect described above.

[0015] The embodiments of this application have the following beneficial effects: Multiple battery parameterized simulation models with unified geometric configurations and tab number as variables are constructed; the DC internal resistance of each battery parameterized simulation model under the same operating conditions is obtained according to standardized electrochemical simulation testing methods; based on all DC internal resistances, the benefit-trade analysis model and the geometric inflection point identification model are optimally solved to obtain the first recommended tab number interval and the second recommended tab number interval; a set operation is performed on the first recommended tab number interval and the second recommended tab number interval to obtain the target tab number design interval. This method controls the uniqueness of variables from the modeling source, eliminates single analysis bias through cross-validation of dual-principle models, and forces convergence through mathematical intersection, ensuring that the output interval has both optimal performance and engineering feasibility. This significantly improves the scientificity, robustness, and reproducibility of tab number decisions, avoiding design redundancy or insufficient performance caused by trial and error. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart of a method for optimizing the number of battery tabs according to an embodiment of this application is shown; Figure 2 Another flowchart of the battery tab number optimization method according to an embodiment of this application is shown; Figure 3 This illustrates yet another flowchart of the battery tab number optimization method according to an embodiment of this application; Figure 4 This paper shows a schematic diagram of the simulated battery geometric model in the battery tab number optimization method of the present application embodiment; Figure 5 This paper shows a schematic diagram of the 3C discharge curves of batteries with different numbers of tabs in the battery tab number optimization method of the present application embodiment; Figure 6 This paper illustrates a schematic diagram of the DC internal resistance of a battery with different numbers of tabs in the battery tab number optimization method of this application embodiment; Figure 7 The diagram illustrates the variation law of the DC internal resistance of the battery with different numbers of tabs in the battery tab number optimization method of this application, as well as the perpendicular line diagram of each point to the straight line. Figure 8 A schematic diagram of a battery tab number optimization device according to an embodiment of this application is shown. Detailed Implementation

[0018] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0019] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0020] In the following text, the terms "comprising," "having," and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more combinations thereof. Furthermore, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0021] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0022] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0023] Considering the key problems in existing technologies, such as high blindness in deciding the number of tabs, cost-benefit imbalance, and non-reusable design processes due to reliance on experience-based trial and error and lack of full-range performance modeling and saturation point quantification criteria, a method for optimizing the number of battery tabs is proposed. This method involves constructing multiple battery parameterized simulation models with unified geometric configurations, using the number of tabs as a variable; obtaining the DC internal resistance of each battery parameterized simulation model under the same operating conditions using standardized electrochemical simulation testing methods; optimizing the benefit-trade analysis model and the geometric inflection point identification model based on all DC internal resistances to obtain the first and second recommended tab number intervals; and performing a set operation on the first and second recommended tab number intervals to obtain the target tab number design interval.

[0024] The following examples illustrate the method for optimizing the number of battery tabs.

[0025] Figure 1 A flowchart illustrating a method for optimizing the number of battery tabs according to an embodiment of this application is shown. Exemplarily, the method for optimizing the number of battery tabs includes the following steps: Step S100: Construct multiple battery parameterized simulation models with unified geometric configurations, using the number of tabs as the variable.

[0026] In this context, the number of tabs as a variable means that during parametric modeling, the number of tabs is explicitly defined as a core control quantity that can be programmed and iteratively driven, while all other physical and geometric parameters are locked as constants. Geometric configuration uniformity means that all models are completely consistent in terms of topology, component composition, dimensional parameters, and material distribution in three-dimensional space, with differences stemming solely from the single design variable of the number of tabs. Demonstratively, by establishing a benchmark model and parametrically encapsulating it, discrete model instances are generated in batches based on different values ​​of the number of tabs, thereby providing a data foundation with consistent structure and controllable variables for subsequent standardized simulations. This ensures that the differences in the obtained performance data are caused only by changes in the number of tabs, excluding interference from other factors.

[0027] In an optional embodiment, step S100 includes the following sub-steps: S101. Establish a three-dimensional electrochemical model of the target battery model as a benchmark geometric model.

[0028] The baseline geometric model is a complete assembly model built according to the specifications of actual battery products, including all key components such as the positive electrode, negative electrode, separator, electrolyte, current collector, and casing. Its geometric accuracy meets the convergence requirements of electrochemical simulation. For example, for a ternary lithium-ion cylindrical battery with a rated capacity of 5Ah, the baseline model uses millimeter-level meshing, with the coating thicknesses of the positive and negative electrode active materials set to 65μm and 180μm, respectively. The separator porosity is 45%, and the electrolyte conductivity is 0.72 S / m. All parameters are derived from the company's database and process specifications, thus ensuring the consistency between the model and the actual physical object.

[0029] S102 transforms the baseline geometric model into a battery parametric simulation model and configures the number of tabs as a variable parameter of the battery parametric simulation model.

[0030] Among them, the battery parametric simulation model refers to defining the key dimensions, material properties and boundary conditions of the benchmark model as editable variables through the parameter-driven module in the CAE platform, and setting the number of tabs as an independent control variable N. For example, by creating an integer parameter named tab_count in the modeling software and binding it to the array number of tab geometric entities, when the user inputs N equal to 1, 5 or 20, the system automatically updates the corresponding number of tab entities while keeping the rest of the structure unchanged. This process does not require manual model reconstruction, significantly improves modeling efficiency, and ensures that the geometric configuration of all derived models is strictly consistent.

[0031] S103, based on multiple values ​​of the variable parameters, performs a geometric array operation on the battery parameterized simulation model to construct multiple battery parameterized simulation models with uniform geometric configuration and only the number of tabs as the unique variable.

[0032] The geometric array operation refers to the operation of generating multiple identical tab geometries on a specified geometric reference according to a preset number and spacing rule using the copy-distribution function built into the modeling software. For example, for a cylindrical battery, the tabs are set to be evenly distributed along the circumferential direction of the inner wall of the casing, with an initial angle of 0 degrees and an angular spacing of 360 degrees divided by N. When N takes the values ​​1, 2, 5, 10, 20, 50, 100, and 200, the system executes the array operation 8 times in sequence to generate 8 independent model files. In other embodiments, the array method can be replaced by a linear array suitable for prismatic batteries and a radial array suitable for pouch battery stacked structures, but it must be ensured that each array only changes the number of tabs and does not adjust the tab size or position offset.

[0033] Step S200: Based on the standardized electrochemical simulation test method, obtain the DC internal resistance of each battery parameterized simulation model under the same preset operating conditions.

[0034] Standardized electrochemical simulation testing refers to performing a completely consistent numerical solution process on all models under uniformly set physical boundaries and excitation conditions to ensure that the obtained electrochemical response data are comparable and have unique attribution. The preset identical operating conditions are a set of immutable operational constraints set in advance to ensure the robustness of the test results, including ambient temperature, state of charge scan range, current excitation form and sampling sequence. Demonstratively, the eight models built by S100 are sequentially imported into the electrochemical module, and simulation tasks are run under the same solver settings. Each task completes multi-condition calculations according to preset conditions, and finally outputs a structured DC internal resistance dataset.

[0035] In one alternative embodiment, such as Figure 2 As shown, step S200 includes the following sub-steps: S201 performs constant current discharge pulse tests at multiple state-of-charge points for each battery parameterized simulation model under constant ambient temperature.

[0036] In this context, a constant ambient temperature refers to maintaining the thermal boundary conditions unchanged throughout the entire simulation test cycle to avoid temperature drift leading to changes in conductivity and reaction kinetic parameters. Multiple state of charge (SOC) points refer to a set of discrete SOC values ​​covering the typical operating range of the battery, the selection of which must consider both data representativeness and computational efficiency. For example, the ambient temperature is fixed at 25 degrees Celsius, and 10 SOC points are selected with SOCs of 1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, and 0.1, with each point starting a simulation task independently. In other implementations, the constant ambient temperature can be set to any constant value within the range of 0 to 45 degrees Celsius, and the multiple SOC points can be replaced with 7 points with SOCs between 0.2 and 0.8 in a step size of 0.1, or an adaptive algorithm can be used to dynamically select the 5 key points with the largest gradient of internal resistance change, but all models must be tested under the exact same temperature and SOC point set.

[0037] S202 collects the open-circuit voltage at the start time and the instantaneous voltage at the end time of each constant current discharge pulse test.

[0038] Here, open-circuit voltage refers to the potential difference between the positive and negative electrodes before the pulsed current is applied and the system reaches electrochemical equilibrium; instantaneous voltage refers to the terminal voltage recorded at the instant the pulsed current returns to zero after its continuous application ends; both are key transient response quantities characterizing the coupling effect of ohmic polarization and concentration polarization in the battery; demonstratively, in each SOC point test, the model is first allowed to stand still to establish thermal-electrical equilibrium, and the voltage at this time is recorded as follows. Subsequently, a constant current pulse with an amplitude of 3 times the rated capacity is applied and lasts for 10 seconds. The terminal voltage is immediately read at the pulse termination time t=10 seconds later. For example, all and The sampling can be automatically extracted at the boundary between the positive and negative current collectors using a probe, with a sampling accuracy down to the microvolt level. In other embodiments, the constant current pulse can last from 5 to 30 seconds, and the settling time before open-circuit voltage acquisition can be extended to 7200 seconds.

[0039] S203 calculates the DC internal resistance at each state of charge point based on the open-circuit voltage, instantaneous voltage, and corresponding pulse current value, and determines the DC internal resistance of each battery parameterized simulation model at a specified state of charge point.

[0040] The corresponding pulse current value is a constant current amplitude determined based on the battery's rated capacity and preset discharge rate. For example, in the simulation of a 5Ah battery, a 3C discharge rate is used, meaning the pulse current amplitude is constant at 15 A. This current value remains unchanged in each constant current discharge pulse test, regardless of the number of tabs N or the state of charge (SOC), ensuring consistent excitation conditions for DCR calculation. The calculation is based on the DC internal resistance formula: ,in, The open-circuit voltage and instantaneous voltage are collected when the number of tabs is N and the state of charge is SOC, respectively, and I is the amplitude of the aforementioned constant pulse current. The DC internal resistance value corresponding to the specified state of charge point, i.e., 50% state of charge (SOC=0.5), is extracted from these values ​​and denoted as [missing value]. And assign N to one of the eight values: 1, 2, 5, 10, 20, 50, 100, and 200. Arranged in ascending order of N, this forms a sequence of DC internal resistances containing 8 elements. .

[0041] Step S300: Based on all DC internal resistances, perform optimal solutions for the benefit trade-off analysis model and the geometric inflection point identification model respectively to obtain the recommended interval for the number of first and second electrodes.

[0042] Among them, the benefit-trade analysis model is a mathematical tool that quantifies and synthesizes battery performance gains and manufacturing costs, outputting a comprehensive benefit evaluation based on the number of tabs N; the geometric morphology inflection point identification model is a morphological analysis method that identifies points of significant performance degradation based on the geometric distribution characteristics of all DC internal resistances along the tab number axis; both the first and second recommended tab number intervals are closed intervals, meaning their endpoint values ​​are contained within the intervals, and they together form the input basis for subsequent intersection operations; exemplarily, all DC internal resistances are... As a unified input, it drives two models with independent principles and separate computational paths to run in parallel, avoiding decision distortion caused by the bias of a single model, and finally outputs two recommendation intervals with consistent structure and comparable and computable results, providing dual verification for robust design.

[0043] In one alternative embodiment, such as Figure 3 As shown, step S300 includes the following sub-steps: S301, based on all DC internal resistances, determine the number of first critical tabs, and generate a recommended range for the number of first tabs in the form of a first closed interval according to preset interval construction rules. This generation process includes the following operations: The reference DC internal resistance when the number of tabs is determined as a reference value.

[0044] The reference value is taken as N, which corresponds to the smallest number of tabs among all DC internal resistances, i.e., N=1. Therefore, the reference DC internal resistance is... ;Exemplary, in In the middle, take the first term directly. As .

[0045] Based on the reference DC internal resistance and all DC internal resistances, calculate the normalized performance gain corresponding to the number of tabs.

[0046] The normalized performance gain is calculated using the following formula:

[0047] For each N value in the sequence, calculate P(N). This represents the DC internal resistance value corresponding to N in the sequence; for example, when N=5, =R5, substituting it gives... ; Based on the pre-defined cost impact model, the cost impact factor corresponding to the number of each tab is calculated.

[0048] The cost impact factor is calculated using the following formula:

[0049] in, This represents the maximum number of electrodes in the simulation sequence; exemplarily, =200, therefore .

[0050] Based on the normalized performance benefit and cost impact factors, a benefit function is constructed and the number of electrodes that make the benefit function take an extreme value is determined, generating a first recommended interval for the number of electrodes in the form of a first closed interval.

[0051] The benefit function is constructed using the following formula: ; in, A cost tradeoff factor greater than 0; exemplarily, calculate E(N) for all N values ​​to determine the number of tabs when E(N) reaches its maximum value. ; then take the satisfied For all values ​​of N, i.e., N=5,10,20, find the minimum and maximum values ​​to form a closed interval. That is, the recommended interval for the number of first pole ears in the form of the first closed interval.

[0052] It is understandable that the specific functional form of the cost impact factor C(N) can be defined according to the actual production cost structure, such as using a linear, piecewise linear, or convex function. Using a linear model is a preferred simplification, which is sufficient to reveal the basic trade-off between performance gains and cost, and to determine the optimal design range.

[0053] S302, based on all DC internal resistances, determine the number of second critical tabs, and generate a recommended interval for the number of second tabs in the form of a second closed interval according to a preset interval construction rule. This generation process includes the following operations: A two-dimensional coordinate point set is constructed based on all DC internal resistances.

[0054] The two-dimensional coordinate point set is a discrete set of points formed by arranging all DC internal resistances in ascending order according to the number of tabs N. ; Exemplary, will Directly mapped to a point set: .

[0055] Connect the first and last coordinate points of the coordinate point set to form a reference line.

[0056] The reference line is the line connecting the first coordinate point. and the last coordinate point The resulting straight line.

[0057] Calculate the perpendicular distance from each intermediate coordinate point to the reference line.

[0058] Wherein, the vertical distance is ;Exemplary example, for the midpoints of i=2 to 7 ,calculate .

[0059] Determine the number of electrodes corresponding to the maximum vertical distance, and generate a second recommended interval for the number of electrodes in the form of a second closed interval.

[0060] The maximum value corresponds to the number of electrodes that make Take the global maximum value , Recorded as Its physical meaning is that, within a preset set of discrete tab count values, the integer number of tabs representing the "marginal benefit cliff point" where the DC internal resistance decreases with increasing tab count. That is, before this number, a unit increase in tab count leads to a relatively significant reduction in internal resistance; from this number onwards, the rate of internal resistance decay slows drastically, performance improvement tends to saturate, and further increasing the number of tabs will mainly lead to negative effects such as increased manufacturing costs, increased process complexity, and decreased structural reliability. In other words, the geometric inflection point; it represents the position where the curve deviates most significantly from the linear downward trend, i.e., the inflection point where the "marginal benefit" undergoes a dramatic change, usually the position where the performance improvement benefit begins to weaken sharply. Exemplarily, if... If it is the maximum value, then Take the closed interval Recommended interval for the number of second pole ears in the form of the second closed interval; The domains of both the first and second closed intervals are sets of positive integers, and the endpoints of these intervals are derived from the set of the number of tabs corresponding to all DC internal resistance sequences; that is, all endpoint values ​​originate from... This ensures that the interval is defined on the physically realizable number of tabs axis, excluding extrapolation results of non-integer or unsimulated N values.

[0061] Step S400: Perform a set operation on the first recommended range of electrode number and the second recommended range of electrode number to obtain the target electrode number design range.

[0062] The intersection operation refers to finding the common coverage of two closed intervals on the positive integer axis. The result is a new closed interval, whose left endpoint is the larger of the left endpoints of the two input intervals, and whose right endpoint is the smaller of the right endpoints of the two input intervals. The common part refers to the set of values ​​obtained by the intersection operation, whose elements are all positive integers that simultaneously belong to the two input intervals. The target tab quantity design interval in the form of a closed interval refers to the interval whose endpoint values ​​are contained within the interval, and whose endpoint values ​​are taken from the set of tab quantities corresponding to the DC internal resistance sequence. For example, when the recommended interval for the first tab quantity is [5,20] and the recommended interval for the second tab quantity is [2,10], the common part obtained by performing the intersection operation is {5,6,7,8,9,10}, whose minimum upper bound on the positive integer axis is 10 and maximum lower bound is 5. Therefore, the target tab quantity design interval in the form of a closed interval is determined to be [5,10]. This interval is the finally recommended optimal tab quantity design interval, which can be directly used for revising battery structure drawings or issuing process parameters.

[0063] In an optional embodiment, step S400 includes the following sub-steps: Perform an intersection operation on the first and second recommended intervals for the number of electrodes to obtain the common part of the first and second recommended intervals for the number of electrodes on the positive integer axis.

[0064] The mathematical expression for the intersection operation is: ,in The recommended range for the number of first electrodes is as follows: Recommended range for the number of second electrodes. The function guarantees that the endpoints of the result are integers and lie on the positive integer axis; exemplarily, let... ,but Therefore, the intersection is In other embodiments, if the two intervals do not overlap If the intersection is empty, the system triggers a backup strategy and uses the union operation. This serves as a target range, or as a prompt for the user to adjust the benefit-loss model. The value is used to expand the first interval.

[0065] The common part is defined as the target number of tabs in the form of a closed interval.

[0066] In this context, the closed interval form refers to the fact that the endpoint value is explicitly included, and the endpoint must be taken from the set of the number of tabs corresponding to all DC internal resistances {1,2,5,10,20,50,100,200}. For example, the left endpoint 5 and the right endpoint 10 of the intersection result [5,10] both exist in this set, so [5,10] is directly determined as the target tab number design interval. If the intersection calculation yields [7,12], and 7 and 12 are not in the set, then the nearest integer is rounded down to 5 and up to 20 to obtain [5,20]. The intersection with the original intersection is then taken to obtain [5,10], ensuring that the final endpoint is physically achievable. In other embodiments, the endpoint calibration can be performed by rounding, rounding up, or table lookup mapping, but the endpoint of the final target interval must belong to the set of tab numbers.

[0067] In one optional embodiment, the method of this application can be illustrated by the following specific example: taking a ternary lithium battery with a rated capacity of 5Ah (positive electrode NCA811, negative electrode graphite) as the object, a series of three-dimensional electrochemical simulation models with the number of tabs N being 1, 2, 5, 10, 20, 50, 100, and 200, respectively, are constructed, such as... Figure 4 As shown; all models have the same geometric configuration, and only the number of pole pieces is a variable parameter.

[0068] At a constant ambient temperature of 25°C, constant current discharge pulse tests with an amplitude of 3C and a duration of 10 seconds were performed on each model at the state of charge (SOC) points of 1.0, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, and 0.1. Figure 5 , 6As shown, the open-circuit voltage at the start of each pulse and the instantaneous voltage at the end of each pulse are collected. Based on the open-circuit voltage, instantaneous voltage, and corresponding pulse current values, the DC internal resistance at each state of charge point is calculated, and the DC internal resistance value corresponding to the specified state of charge point, i.e., 50% state of charge, is extracted to form the DC internal resistance. (Unit: mΩ) The corresponding number of electrodes N = [1, 2, 5, 10, 20, 50, 100, 200], such as Figure 7 As shown.

[0069] Based on all DC internal resistances, a recommended range for the number of first tabs in the form of a first closed interval is generated by the benefit-trade analysis model: taking the reference DC internal resistance. The normalized performance gains were calculated using a linear cost impact model. Constructing the benefit function ,in ; calculated The maximum value is obtained at point , and the value that satisfies this condition is taken. Given all the N values, the first closed interval is determined as [5,15]; the endpoints 5 and 15 of this interval are both taken from the set of the number of tabs corresponding to all DC internal resistances {1,2,5,10,20,50,100,200}.

[0070] Simultaneously, the geometric inflection point recognition model generates a second closed interval for recommending the number of second pole ears: The data is sorted in ascending order of N to construct a two-dimensional coordinate point set: ; Connect the first coordinate point and the last coordinate point Form a reference line L; according to Calculate the perpendicular distance from each intermediate point to L, and determine... The maximum value corresponds to the number of poles N=10, generating the second closed interval [2,10]; the endpoints 2 and 10 of this interval both take values ​​from the set of pole numbers.

[0071] Perform an intersection operation on the first recommended interval [5,15] and the second recommended interval [2,10] to obtain the common part of the two on the positive integer axis; according to calculate: get: Therefore, the intersection is [5,10]; the common part is determined as the target electrode number design interval in the form of a closed interval; the endpoints 5 and 10 of this interval are both taken from the electrode number set.

[0072] Figure 8A schematic diagram of a battery tab number optimization device according to an embodiment of this application is shown. Exemplarily, the device 100 includes: Model building module 110 is used to build multiple battery parameterized simulation models with a unified geometric configuration, using the number of tabs as a variable. The simulation test module 120 is used to obtain the DC internal resistance of each of the battery parameterized simulation models under the same preset operating conditions according to the standardized electrochemical simulation test method. Data processing module 130 is used to perform optimal solutions on the benefit trade-off analysis model and the geometric inflection point identification model based on all the DC internal resistances, respectively, to obtain the recommended interval for the number of first tabs and the recommended interval for the number of second tabs; The electrode number acquisition module 140 is used to perform set operations on the first electrode number recommendation interval and the second electrode number recommendation interval to obtain the target electrode number design interval.

[0073] It is understood that the apparatus of this embodiment corresponds to the method of the above embodiments, and the options in the above embodiments are also applicable to this embodiment, so they will not be described again here.

[0074] This application also provides a terminal device, exemplary of which includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to enable the terminal device to perform the functions of the various modules in the above-described method or apparatus.

[0075] The processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, including at least one of a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Network Processor (NP), Digital Signal Processor (DSP), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0076] The memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory is used to store computer programs, and the processor can execute the computer programs accordingly after receiving execution instructions.

[0077] This application also provides a computer-readable storage medium for storing the computer program used in the aforementioned terminal device. For example, the computer-readable storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0078] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, in alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0079] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0080] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a smartphone, personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0081] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for optimizing the number of battery tabs, characterized in that, The method includes: Construct multiple battery parameterized simulation models with unified geometric configurations, using the number of tabs as a variable; Based on standardized electrochemical simulation testing methods, the DC internal resistance of each battery parameterized simulation model under the same preset operating conditions is obtained; Based on all the DC internal resistances, the benefit-trade analysis model and the geometric inflection point identification model are optimally solved to obtain the recommended interval for the number of first and second electrodes. A set operation is performed on the first recommended range for the number of electrodes and the second recommended range for the number of electrodes to obtain the target range for the number of electrodes.

2. The method for optimizing the number of battery tabs according to claim 1, characterized in that, The construction of multiple battery parameterized simulation models with unified geometric configurations, using the number of tabs as a variable, includes: Establish a three-dimensional electrochemical model of the target battery model as a benchmark geometric model; The baseline geometric model is transformed into a battery parametric simulation model, and the number of tabs is configured as a variable parameter of the battery parametric simulation model. Based on the multiple values ​​of the variable parameter, a geometric array operation is performed on the battery parameterized simulation model to construct multiple battery parameterized simulation models with uniform geometric configuration and the number of tabs as the only variable.

3. The method for optimizing the number of battery tabs according to claim 1, characterized in that, The method of obtaining the DC internal resistance of each battery parameterized simulation model under the same preset operating conditions based on standardized electrochemical simulation testing methods includes: For each battery parameterized simulation model, constant current discharge pulse tests were performed at multiple state of charge points under constant ambient temperature. Collect the open-circuit voltage at the start time and the instantaneous voltage at the end time of each constant current discharge pulse test; Based on the open-circuit voltage, instantaneous voltage, and corresponding pulse current value, calculate the DC internal resistance at each state of charge point, and determine the DC internal resistance of each battery parameterized simulation model at a specified state of charge point.

4. The method for optimizing the number of battery tabs according to claim 1, characterized in that, Based on all the DC internal resistances, the benefit-trade analysis model and the geometric inflection point identification model are optimally solved to obtain the recommended intervals for the number of first and second electrodes, including: Based on all the DC internal resistances, the number of first key tabs is determined, and a recommended range for the number of first tabs in the form of a first closed range is generated according to the preset range construction rules. Based on all the DC internal resistances, the number of second key tabs is determined, and a recommended range for the number of second tabs in the form of a second closed interval is generated according to the preset interval construction rules. Wherein, the domains of the first closed interval and the second closed interval are both sets of positive integers, and the endpoints of the intervals are taken from the set of the number of tabs corresponding to all the DC internal resistances.

5. The method for optimizing the number of battery tabs according to claim 4, characterized in that, The step of generating the first recommended interval for the number of first pole ears in the form of a first closed interval includes: The reference DC internal resistance is determined when the number of electrodes is a reference value; Based on the reference DC internal resistance and all the DC internal resistances, calculate the normalized performance gain corresponding to the number of each tab; Based on the pre-defined cost impact model, calculate the cost impact factor corresponding to the number of each electrode; Based on the normalized performance gains and the cost impact factors, a benefit function is constructed and the number of electrodes that make the benefit function take an extreme value is determined, generating a first recommended interval for the number of electrodes in the form of a first closed interval.

6. The method for optimizing the number of battery tabs according to claim 4, characterized in that, The step of generating the second closed interval form of the recommended interval for the number of second pole ears includes: A two-dimensional coordinate point set is constructed based on all the aforementioned DC internal resistances; Connect the first and last coordinate points of the coordinate point set to form a reference straight line; Calculate the perpendicular distance from each intermediate coordinate point to the reference line; Determine the number of electrodes corresponding to the maximum vertical distance, and generate a second recommended interval for the number of electrodes in the form of a second closed interval.

7. The method for optimizing the number of battery tabs according to claim 1, characterized in that, The step of performing a set operation on the first recommended range for the number of electrodes and the second recommended range for the number of electrodes to obtain the target range for the number of electrodes includes: Perform an intersection operation on the first recommended interval for the number of electrodes and the second recommended interval for the number of electrodes to obtain the common part of the first recommended interval for the number of electrodes and the second recommended interval for the number of electrodes on the positive integer axis; determine the common part as the target electrode number design interval in the form of a closed interval.

8. A device for optimizing the number of battery tabs, characterized in that, include: The model building module is used to build multiple battery parameterized simulation models with a unified geometric configuration, using the number of tabs as a variable. The simulation test module is used to obtain the DC internal resistance of each battery parameterized simulation model under the same preset operating conditions according to the standardized electrochemical simulation test method; The data processing module is used to perform optimal solutions on the benefit-trade analysis model and the geometric inflection point identification model based on all the DC internal resistances, respectively, to obtain the recommended interval for the number of first and second electrodes. The electrode number acquisition module is used to perform set operations on the first electrode number recommendation interval and the second electrode number recommendation interval to obtain the target electrode number design interval.

9. A terminal device, characterized in that, The terminal device includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the battery tab number optimization method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed on a processor, implements the method for optimizing the number of battery tabs according to any one of claims 1-7.

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