Battery pack composite material upper cover parameter determination method and device, electronic equipment and medium

Abstract

The embodiment of the invention discloses a battery pack composite material upper cover parameter determination method and device, electronic equipment and a medium. The method comprises the following steps: enabling a preset ant to search in a preset layer thickness range and a preset layer angle range according to an initialized pheromone concentration and initialized heuristic information to obtain an initial path; inputting each target position point of the initial path into the composite material upper cover finite element model to obtain a first-order modal frequency; updating heuristic information of the target position point, and updating pheromone concentration of the target position point according to the first-order modal frequency; and enabling the preset ant to continue searching iteration according to the updated heuristic information and pheromone concentration of each target position point and the heuristic information and pheromone concentration of other position points to obtain final parameters of the battery pack composite material upper cover. According to the scheme, the optimal upper cover parameter is searched and determined based on the improved ant algorithm, so that the optimal upper cover parameter is quickly and efficiently determined for actual industrial application.

Description

Technical Field

[0001] The present application relates to the technical field of material parameter determination, and in particular to a method, device, electronic device and medium for determining parameters of a composite material upper cover of a battery pack. Background Art

[0002] With the rapid development of the electric vehicle industry, the performance and safety of power battery packs have attracted much attention. As a key component to protect the battery pack, the structural performance of the composite material cover of the power battery pack directly affects the overall performance of the battery pack. When dealing with the optimization of the composite material cover structure, traditional optimization methods often find it difficult to efficiently find a solution that satisfies the constraints and optimizes the objective function in a complex design variable space. Summary of the invention

[0003] The embodiments of the present application provide a method, device, electronic device and medium for determining parameters of a composite material upper cover of a battery pack, so as to search for parameters of the composite material upper cover of a battery pack more quickly and accurately.

[0004] According to one aspect of the present application, a method for determining parameters of a composite upper cover of a battery pack is provided, the method comprising:

[0005] A preset number of ants are ordered to search in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and a preset number of ply thickness and ply angle combinations are obtained as target position points, and an initial path is formed by the preset number of target position points; wherein the ply thickness and the ply angle are the parameters of the upper cover of the battery pack composite material;

[0006] Inputting each target position point of the initial path into the composite material upper cover finite element model to obtain the first-order modal frequency;

[0007] For each target location point, updating the heuristic information of the target location point, and updating the pheromone concentration of the target location point according to the first-order modal frequency;

[0008] The preset ants are ordered to continue searching and iterating according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration conditions are met to obtain the final parameters of the battery pack composite material upper cover; wherein the other position points are the position points other than the target position points in the preset ply thickness range and the preset ply angle range.

[0009] According to one aspect of the present application, a device for determining parameters of a composite material upper cover of a battery pack is provided, the device comprising:

[0010] The initial path determination module can be used to make a preset number of ants search in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and obtain a preset number of ply thickness and ply angle combinations as target position points, and form an initial path by the preset number of target position points; wherein the ply thickness and ply angle are the battery pack composite material upper cover parameters;

[0011] A first-order modal frequency determination module, used for inputting each target position point of the initial path into the composite material upper cover finite element model to obtain the first-order modal frequency;

[0012] An updating module, used for updating the heuristic information of each target location point and updating the pheromone concentration of the target location point according to the first-order modal frequency;

[0013] The iteration module is used to make the preset ants continue to search and iterate according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration conditions are met to obtain the final parameters of the battery pack composite material cover; wherein the other position points are the position points other than the target position points in the preset ply thickness range and the preset ply angle range.

[0014] According to another aspect of the present application, an electronic device is provided, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the method for determining the parameters of the battery pack composite material upper cover according to any embodiment of the present application.

[0018] According to another aspect of the present application, a computer-readable storage medium is provided, which stores computer instructions, and the computer instructions are used to implement the method for determining the parameters of the battery pack composite material upper cover according to any embodiment of the present application when executed by a processor.

[0019] The technical solution of the embodiment of the present application is to let a preset number of ants search in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and obtain a preset number of ply thickness and ply angle combinations as target position points, and form an initial path by the preset number of target position points; wherein the ply thickness and the ply angle are parameters of the battery pack composite material upper cover; each target position point of the initial path is input into the finite element model of the composite material upper cover to obtain the first-order modal frequency; for each target position point, the heuristic information of the target position point is updated, and the pheromone concentration of the target position point is updated according to the first-order modal frequency; let the preset number of ants continue to search and iterate according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration condition is met to obtain the final parameters of the battery pack composite material upper cover; wherein the other position points are position points other than the target position points among the position points included in the preset ply thickness range and the preset ply angle range. The above scheme can determine the optimal upper cover parameters by path search based on the improved ant colony algorithm, realize fast convergence search, and obtain the first-order modal frequency corresponding to the parameters of the initial path based on the finite element model simulation of the upper cover that meets the material requirements, which is used as the objective function and a reference for updating the pheromone concentration. This constrains the convergence optimization direction of the ant colony algorithm from the perspective of upper cover performance, so as to improve the iteration speed and optimization effect, and obtain the optimal battery pack composite material upper cover parameters that meet the performance requirements.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A flow chart of a method for determining parameters of a composite material upper cover of a battery pack provided in an embodiment of the present application;

[0023] Figure 2 A flowchart of a method for determining parameters of a composite material upper cover of a battery pack provided in another embodiment of the present application;

[0024] Figure 3 A flow chart of a method for determining parameters of a composite material upper cover of a battery pack provided in another embodiment of the present application;

[0025] Figure 4 A simulation structure diagram provided for an embodiment of the present application;

[0026] Figure 5 A schematic diagram of the structure of a device for determining parameters of a composite material upper cover of a battery pack provided in an embodiment of the present application;

[0027] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0029] It should be noted that the terms "first", "second", "third", "fourth", "actual", "preset", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Figure 1 The flowchart of a method for determining parameters of a composite material upper cover of a battery pack provided in an embodiment of the present application is applicable to the case of optimizing a composite material upper cover of a battery pack. The method can be executed by a device for determining parameters of a composite material upper cover of a battery pack, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0031] S110, commanding a preset number of ants to search in a preset range of ply thickness and a preset range of ply angle according to the initialization pheromone concentration and the initialization heuristic information, and obtaining a preset number of combinations of ply thickness and ply angle as target position points, and forming an initial path by the preset number of target position points; wherein the ply thickness and the ply angle are the parameters of the upper cover of the battery pack composite material.

[0032] Among them, the meaning of ants refers to the ants in the ant colony algorithm, which refers to virtual individuals that simulate the foraging behavior of ants in nature. The preset is just the number of ants set in advance, which depends on experience and experimental adjustment. Pheromone concentration refers to the content or density of pheromones in the environment. In the ant colony optimization algorithm, pheromone concentration is used to guide ants to choose paths. The probability of an ant choosing the next location point is proportional to the pheromone concentration to each location point. When other conditions are the same, the higher the pheromone concentration, the greater the probability of being selected. Heuristic information in the ant colony algorithm refers to information used to guide ants to choose paths. In the initial case, the initialization pheromone concentration and the initialization heuristic information are set as the initial values. Subsequently, as the ant's path search iterates, the pheromone concentration and the heuristic information are updated. The preset ply thickness and the preset ply angle are the parameters of the battery pack composite material cover that the ant can select in advance, that is, the ant is allowed to search for the optimal ply thickness and ply angle in the preset ply thickness and preset ply angle. The preset number is the number of position points included in the preset path. The combination of a ply thickness and a ply angle searched by the ant is regarded as a target position point, which can be represented by (x, y), where x can be the ply thickness and y can be the ply angle. When the ant searches for the preset number of target position points, the initial path is formed.

[0033] For example, a preset number of ants may be ordered to search within a preset range of pavement thickness and a preset range of pavement angle according to the initialization pheromone concentration and the initialization heuristic information. Each ant searches for a preset number of combinations of pavement thickness and pavement angle, each combination is used as a target position point, and a preset number of target position points are searched to form an initial path. Each ant searches for an initial path. The number of initial paths is the same as the number of ants.

[0034] S120, inputting each target position point of the initial path into a finite element model of a composite material upper cover to obtain a first-order modal frequency.

[0035] Among them, the finite element model of the composite material upper cover is a model established based on simulation software and the geometric shape, material characteristics, etc. of the composite material upper cover of the battery pack. It can design variable ply thickness, ply angle, etc., set objective functions and constraints, and realize model simulation and optimization experiments. The first-order modal frequency refers to the vibration state exhibited by an object when the frequency of the external force is equal to the first-order natural frequency of the object when the object is excited by an external force. In an embodiment of the present application, maximizing the first-order modal frequency is used as the objective function, and the total ply thickness is used as a constraint condition. For example, the constraint condition is generally set to that the total ply thickness does not increase and is less than the preset total thickness.

[0036] Exemplarily, after the initial path is obtained by the ant initial search, each target position point in the initial path is input into the finite element model of the composite material upper cover, that is, the ply thickness and ply angle of each target position point are brought into the variables of the finite element model of the composite material upper cover, and simulation is performed to obtain the first-order modal frequency corresponding to the target position point.

[0037] S130 . For each target location point, update the heuristic information of the target location point, and update the pheromone concentration of the target location point according to the first-order modal frequency.

[0038] Exemplarily, after the ants conduct a preliminary search, the heuristic information and pheromone concentration of the target location points are updated according to the ants' selection of each target location point, thereby guiding the ants' selection process in subsequent iterations. Specifically, for each target location point, the heuristic information of the target location point can be updated according to the ply thickness and ply angle in the target location point, the heuristic information corresponding to the ply thickness can be determined according to an approximate model between the ply thickness and the heuristic information, and the heuristic information corresponding to the ply angle can be determined according to an empirical formula between the ply angle and the heuristic information. The pheromone concentration of the target location point is updated according to the first-order modal frequency. In general, the higher the first-order modal frequency, the stronger the reflection performance, so the first-order modal frequency has a positive effect on the pheromone concentration.

[0039] S140, let the preset ants continue to search and iterate according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration conditions are met to obtain the final parameters of the upper cover of the battery pack composite material; wherein the other position points are the position points other than the target position points among the position points included in the preset ply thickness range and the preset ply angle range.

[0040] Among them, other position points are position points other than the target position point in the preset ply thickness range and the preset ply angle range. The heuristic information and pheromone concentration of the target position point have been updated, and the subsequent execution process is based on the updated heuristic information and pheromone concentration. If the heuristic information and pheromone concentration of other position points have not been updated, the initialization heuristic information and the initialization pheromone concentration shall prevail. Exemplarily, the preset ants are continued to perform search iterations. In the process of continuing the search, the preset ants perform search iterations based on the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, and continue to search for the optimal position point in the preset ply thickness and the preset ply angle to form a search path. After the ants continue to search and obtain the search path, continue to execute the scheme of S120-S130 to update the heuristic information and pheromone concentration of the target position point in the search path, and continue to execute S140 for search iteration until the iteration condition is met, and the ply thickness and ply angle of each target position point in the current search path are used as the final parameters of the battery pack composite material cover. The iteration condition can be determined according to the actual situation, for example, the iteration ends when the number of iterations reaches a preset upper limit, or the change in the first-order modal frequency after continuous iterations is less than a preset change threshold. Otherwise, continue to perform steps S120-S140 to perform search iterations.

[0041] The technical solution of the embodiment of the present application is to let a preset number of ants search in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and obtain a preset number of ply thickness and ply angle combinations as target position points, and form an initial path by the preset number of target position points; wherein the ply thickness and the ply angle are parameters of the battery pack composite material upper cover; each target position point of the initial path is input into the finite element model of the composite material upper cover to obtain the first-order modal frequency; for each target position point, the heuristic information of the target position point is updated, and the pheromone concentration of the target position point is updated according to the first-order modal frequency; let the preset number of ants continue to search and iterate according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration condition is met to obtain the final parameters of the battery pack composite material upper cover; wherein the other position points are position points other than the target position points among the position points included in the preset ply thickness range and the preset ply angle range. The above scheme can determine the optimal upper cover parameters by path search based on the improved ant colony algorithm, realize fast convergence search, and obtain the first-order modal frequency corresponding to the parameters of the initial path based on the finite element model simulation of the upper cover that meets the material requirements, which is used as the objective function and a reference for updating the pheromone concentration. This constrains the convergence optimization direction of the ant colony algorithm from the perspective of upper cover performance, so as to improve the iteration speed and optimization effect, and obtain the optimal battery pack composite material upper cover parameters that meet the performance requirements.

[0042] In the embodiment of the present application, the final parameters of the upper cover of the battery pack composite material are obtained, and the method further includes:

[0043] Input the final parameters into the composite upper cover finite element model to determine whether the total ply thickness meets the total ply thickness constraint, whether the first-order modal frequency meets the preset first-section modal frequency requirement, and whether the preset performance data meets the preset performance requirement;

[0044] If all are met, the final parameters of the battery pack composite material upper cover are applied to the design and manufacture of the battery pack composite material upper cover.

[0045] Exemplarily, after obtaining the final parameters, the final parameters are input into the composite material upper cover finite element model, and the total ply thickness of the model constructed based on the ply thickness and ply angle in the final parameters is determined by simulation whether it meets the total ply thickness constraint, whether the first-order modal frequency meets the preset first-order modal frequency requirement, and whether the preset performance data meets the preset performance requirement. If all are satisfied, it reflects that the final parameters of the battery pack composite material upper cover are the optimal parameters for the composite performance requirements, and are applied to the design and manufacture of the battery pack composite material upper cover. If there are conditions that are not met, the steps of S110-S140 can be continued to search and optimize the optimal parameters.

[0046] Figure 2 This is a flow chart of a method for determining parameters of a composite material upper cover of a battery pack provided in another embodiment of the present application. The present embodiment is optimized based on the above embodiment. For solutions not described in detail in the present embodiment, please refer to the above embodiment. Figure 2 As shown, the method of the embodiment of the present application specifically includes the following steps:

[0047] S210, commanding a preset number of ants to search in a preset range of ply thickness and a preset range of ply angle according to the initialization pheromone concentration and the initialization heuristic information, and obtaining a preset number of combinations of ply thickness and ply angle as target position points, and forming an initial path by the preset number of target position points; wherein, the ply thickness and the ply angle are the parameters of the upper cover of the battery pack composite material.

[0048] S220, inputting each target position point of the initial path into a finite element model of a composite material upper cover to obtain a first-order modal frequency.

[0049] S230. For the ply angle at the target position point, determine updated heuristic information corresponding to the ply angle according to the sine value of the ply angle.

[0050] For example, the sine value of the ply angle can be calculated, and the heuristic information can be positively correlated with the sine value of the ply angle to determine the updated heuristic information of the ply angle. For example, the updated heuristic information corresponding to the ply angle can be determined based on the following formula:

[0051]

[0052] Among them, f(θ) is the heuristic information corresponding to the ply angle, θ is the ply angle, and A, ω, ψ, and B are constants determined according to the composite material and structural characteristics.

[0053] S240: For the ply thickness at the target location point, determine updated heuristic information corresponding to the ply thickness according to a natural logarithm value of the ply thickness.

[0054] Exemplarily, the natural logarithm value of the ply thickness may be calculated, the heuristic information may be positively correlated with the natural logarithm value, and the updated heuristic information corresponding to the ply thickness may be determined.

[0055] Specifically, the updated heuristic information corresponding to the ply thickness may be determined based on the following formula:

[0056] f(t)=Cln(t)+D;

[0057] Among them, f(t) is the heuristic information corresponding to the ply thickness, t is the ply thickness, C and D are constants obtained by fitting the experimental data.

[0058] S250, determining the change in pheromone concentration according to the first-order modal frequency, and determining the enhanced pheromone concentration according to the current pheromone concentration and the change in pheromone at the target location.

[0059] For example, in general, the pheromone concentration of the target location on the path chosen by the ants will be enhanced to guide the subsequent ants to make choices. The pheromone concentration change can be determined based on the first-order modal frequency, and the enhanced pheromone concentration can be determined based on the current pheromone concentration of the target location and the pheromone concentration change, that is, the pheromone concentration after the pheromone is enhanced according to the pheromone concentration change based on the current pheromone concentration.

[0060] In the embodiment of the present application, determining the change in pheromone concentration according to the first-order modal frequency includes:

[0061] The pheromone concentration change is determined by making the pheromone concentration change positively correlated with the first-order modal frequency;

[0062] Determining the enhanced pheromone concentration according to the current pheromone concentration and pheromone change amount of the target location point includes:

[0063] According to the pheromone volatilization coefficient and the current pheromone concentration, the pheromone concentration after volatilization is determined;

[0064] The sum of the volatilized pheromone concentration and the pheromone change amount is taken as the enhanced pheromone concentration.

[0065] For example, after the ant selects the target location, the pheromone concentration at the target location will increase, and the larger the value of the first-order modal frequency, the better the performance of the battery pack composite material cover when the target location is selected. Therefore, the change in pheromone concentration can be positively correlated with the first-order modal frequency to determine the change in pheromone concentration. For example, the change in pheromone concentration is determined according to the following formula:

[0066] Δτk=E×fk ;

[0067] Among them, Δτk is the change of pheromone concentration, E is the proportional coefficient, and fk is the first-order modal frequency.

[0068] In addition, the concentration of pheromones will also evaporate and decrease over time. The concentration of pheromones after evaporation can be determined based on the pheromone volatility coefficient and the current pheromone concentration, for example:

[0069] τ i 挥发 =(1-ρ)·τ i ;

[0070] Among them, τ i 挥发 is the pheromone concentration after volatilization, τi is the current pheromone concentration, and ρ is the volatilization coefficient. It is a value between 0 and 1.

[0071] The sum of the pheromone concentration after volatilization and the pheromone change amount is taken as the enhanced pheromone concentration. Specifically,

[0072] τ i 增强 =(1-ρ)·τ i +E·f k ;

[0073] Among them, τ i 增强 To enhance pheromone concentration.

[0074] By increasing the pheromone concentration, more ants can be attracted to move along the path, forming a stronger pheromone accumulation, thereby increasing the probability of selecting the path, and ultimately prompting the ant colony to concentrate on searching for the global optimal solution.

[0075] S260, determining the diffusion pheromone concentration according to the distance between the target location point and the neighboring location point, and the current pheromone concentration of the neighboring location point; wherein the neighboring location point is a location point within a preset range of the target location point.

[0076] For example, if only the target location is enhanced with pheromones, subsequent ants will be more inclined to choose target locations with higher pheromones, causing the ant algorithm to fall into a local optimal solution prematurely. In the embodiment of the present application, a pheromone diffusion mechanism is introduced, which can gradually smooth the pheromone concentration in the entire search space, avoiding excessive concentration of pheromones in individual paths, thereby making the ant search process more extensive and helping to find the global optimal solution.

[0077] Specifically, the diffusion pheromone concentration can be determined based on the distance between the target position point and the neighboring position point, as well as the current pheromone concentration of the neighboring position point, so that the pheromone concentration of the target position point is also related to the pheromone concentration of the surrounding neighboring position points, as well as the distance between the target position point and the neighboring position point, to achieve smooth diffusion. The neighboring position point can be a position point within a preset range around the target position point. For example, assuming that the pavement thickness obtained at the target position point is t i , the ply angle is θ i , then the neighborhood position points may include points where the ply thickness increases by one unit and the ply angle remains unchanged, points where the ply angle increases by one unit and the ply thickness remains unchanged, points where the ply angle increases by one unit and the ply thickness increases by one unit, etc. It may also increase by two or three units without limitation.

[0078] In the embodiment of the present application, the diffusion pheromone concentration is determined according to the distance between the target location point and the neighboring location point, and the current pheromone concentration of the neighboring location point, including:

[0079] For each neighborhood position point, determine the exponent of the Gaussian function according to the distance between the target position point and the neighborhood position point, determine the constant term according to the current pheromone concentration of the neighborhood position point, and calculate the Gaussian function value corresponding to the neighborhood position point;

[0080] The sum of the Gaussian function values ​​corresponding to each neighborhood position point is taken as the diffusion pheromone concentration corresponding to the target position point.

[0081] For example, for each neighborhood point, the exponent of the Gaussian function can be determined according to the distance between the target point and the neighborhood point, the constant term can be determined according to the current pheromone concentration of the neighborhood point, the Gaussian function value corresponding to the neighborhood point can be calculated, and the sum of the Gaussian function values ​​corresponding to each neighborhood point can be used as the diffusion pheromone concentration corresponding to the target point. For example, the diffusion pheromone concentration can be determined based on the following formula:

[0082]

[0083] Among them, τ i diffused is the diffusion pheromone concentration, (x, y) is the target location, (x', y') is the neighborhood location. N(x, y) is the set of neighborhood locations of the target location, τi(x', y') is the current pheromone concentration of the neighborhood location. σ is the diffusion coefficient. For all target locations in the initial path searched by the ant, the above process is performed to determine the diffusion pheromone concentration of the target location.

[0084] It should be noted that there is no dependency between S250 and S260 and they can be executed independently. In addition, only S250 may be executed and then S270, only S260 may be executed and then S270, or both S250 and S260 may be executed and then S270.

[0085] S270: Determine an updated pheromone concentration according to the enhanced pheromone concentration and / or the diffused pheromone concentration.

[0086] Exemplarily, if only the enhanced pheromone concentration is determined, the updated pheromone concentration is determined only based on the enhanced pheromone concentration; if only the diffused pheromone concentration is determined, the updated pheromone concentration is determined only based on the diffused pheromone concentration; if both the enhanced pheromone concentration and the diffused pheromone concentration are determined, the updated pheromone concentration is determined based on the enhanced pheromone concentration and the diffused pheromone concentration. Specifically, the sum of the enhanced pheromone concentration and the diffused pheromone concentration can be used as the updated pheromone concentration.

[0087] In the embodiment of the present application, determining the updated pheromone concentration according to the enhanced pheromone concentration and the diffused pheromone concentration includes:

[0088] According to the weight value corresponding to the enhanced pheromone concentration and the weight value corresponding to the diffused pheromone concentration, the enhanced pheromone concentration and the diffused pheromone concentration are weightedly summed to obtain an updated pheromone concentration corresponding to the target location point.

[0089] Exemplarily, a corresponding weight value may be set for the enhanced pheromone concentration, a corresponding weight value may be set for the diffuse pheromone concentration, and the enhanced pheromone concentration and the diffuse pheromone concentration may be weighted and summed to obtain an updated pheromone concentration corresponding to the target location point.

[0090] S280, let the preset ants continue to search and iterate according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration conditions are met to obtain the final parameters of the battery pack composite material cover; wherein the other position points are the position points other than the target position points among the position points included in the preset ply thickness range and the preset ply angle range.

[0091] The embodiment of the present application provides a method for determining the parameters of the upper cover of a battery pack composite material. For the ply angle in the target position point, the updated heuristic information corresponding to the ply angle is determined according to the sine value of the ply angle; for the ply thickness in the target position point, the updated heuristic information corresponding to the ply thickness is determined according to the natural logarithm of the ply thickness. By updating the heuristic information, the subsequent search of the ants is guided to search towards a more optimal path. According to the first-order modal frequency, the change in pheromone concentration is determined, and the enhanced pheromone concentration is determined according to the current pheromone concentration and the change in pheromone at the target position point; and / or, the diffuse pheromone concentration is determined according to the distance between the target position point and the neighboring position point, and the current pheromone concentration of the neighboring position point; wherein the neighboring position point is a position point within a preset range of the target position point; the updated pheromone concentration is determined according to the enhanced pheromone concentration and / or the diffuse pheromone concentration. The above scheme can update the pheromone concentration according to the first-order modal frequency, so that the first-order modal frequency can participate in the optimization of the ant's search path, so that the ants can search towards a path with a more optimized first-order modal frequency, so that the parameters of the searched battery pack composite material cover can better meet the performance requirements.

[0092] Figure 3 This is a flow chart of a method for determining parameters of a composite material upper cover of a battery pack provided in another embodiment of the present application. The present embodiment is optimized based on the above embodiment. For solutions not described in detail in the present embodiment, please refer to the above embodiment. Figure 3 As shown, the method of the embodiment of the present application specifically includes the following steps:

[0093] S310, commanding a preset number of ants to search in a preset range of ply thickness and a preset range of ply angle according to the initialization pheromone concentration and the initialization heuristic information, and obtaining a preset number of combinations of ply thickness and ply angle as target position points, and forming an initial path by the preset number of target position points; wherein, the ply thickness and the ply angle are the parameters of the upper cover of the battery pack composite material.

[0094] S320, inputting each target position point of the initial path into a finite element model of a composite material upper cover to obtain a first-order modal frequency.

[0095] S330 . For each target location point, update the heuristic information of the target location point, and update the pheromone concentration of the target location point according to the first-order modal frequency.

[0096] S340. For each location point, determine the probability of the ant selecting the location point according to the pheromone concentration and heuristic information of the location point; wherein the location points include the target location point and the other location points.

[0097] Exemplarily, for each position point, the probability of the ant selecting the position point is determined based on the pheromone concentration of the position point and the heuristic information. The position points include the target position points that have been selected in the last ant search process, as well as other position points that have not been selected by the ant in the preset ply thickness range and the preset ply angle range. That is, when the ant searches again, it actually searches in the global range, so it is necessary to determine the probability of the ant selecting the position point in the global range. The probability of the ant selecting the position point is positively correlated with the pheromone concentration and the heuristic information.

[0098] Specifically, if the location point is the target location point, the pheromone concentration of the location point is the updated pheromone concentration, and the heuristic information is the updated heuristic information. If the location point is any other location point, the pheromone concentration is the pheromone concentration updated after the ant last selected the location point, and the heuristic information is the heuristic information updated after the ant last selected the location point. If the location point has never been selected by an ant, the pheromone concentration is the initialization pheromone concentration, and the heuristic information is the initialization heuristic information.

[0099] In the embodiment of the present application, determining the probability of an ant selecting the location point according to the pheromone concentration of the location point and the heuristic information includes:

[0100] For the target parameter at each position point, the product of the pheromone concentration at the position point and the heuristic information corresponding to the target parameter is used as the selection factor of the target parameter; wherein the target parameters include ply thickness and ply angle;

[0101] For the target parameter in each position point, the ratio of the selection factor of the target parameter to the sum of the selection factors of the target parameters in all the position points is used as the selection probability of the ant selecting the target parameter in the position point.

[0102] Exemplarily, for the ply thickness and ply angle at a position point, the selection factors can be determined according to the pheromone concentration and the heuristic information, respectively, and the selection probability of the ant selecting the ply thickness can be determined according to the selection factor of the ply thickness at the position point and the selection factors of the ply thickness at all the position points, and the selection probability of the ant selecting the ply angle can be determined according to the selection factor of the ply angle at the position point and the selection factors of the ply angle at all the position points. Specifically, the product of the pheromone concentration at the position point and the heuristic information corresponding to the target parameter can be used as the selection factor of the target parameter. For the target parameter, the ratio of the selection factor of the target parameter to the sum of the selection factors of the target parameters at all the position points is used as the selection probability of the ant selecting the target parameter at the position point.

[0103] In the embodiment of the present application, the product of the pheromone concentration of the location point and the heuristic information corresponding to the target parameter is used as the selection factor of the target parameter, including:

[0104] Taking the weight factor of the pheromone concentration as the first exponent, calculating the value of the first exponential power of the pheromone concentration at the location point as the first selected value;

[0105] Taking the weight factor of the heuristic information corresponding to the target parameter as the second exponent, calculating the second exponential power of the heuristic information of the target parameter as the second selected value;

[0106] The product of the first selected value and the second selected value is used as a selection factor of the target parameter.

[0107] Exemplarily, if the target parameter is ply thickness, the selection probability of the ply thickness may be determined based on the following formula:

[0108]

[0109] in, is the probability of selecting the ply thickness at the kth position in path i, τ i is the pheromone concentration at the location, f(t i ) is the heuristic information corresponding to the ply thickness, α is the first index, and β is the second index. τ i α ·f(t i ) β This is the selection factor corresponding to the ply thickness.

[0110] If the target parameter is the ply angle, the probability of selecting the ply angle can be determined based on the following formula:

[0111]

[0112] in, is the probability of selecting the ply angle at the kth position in path j, τ j is the pheromone concentration at the location, f(θ j ) is the heuristic information corresponding to the ply angle, α is the first index, and β is the second index. τ j α ·f(θ j ) β is the selection factor corresponding to the ply angle.

[0113] S350, let the preset ants continue to search and iterate according to the selection probability of each position point until the iteration condition is met to obtain the final parameters of the battery pack composite material cover; wherein the other position points are the position points other than the target position point in the preset layer thickness range and the preset layer angle range.

[0114] The embodiment of the present application provides a method for determining the parameters of a battery pack composite material upper cover, wherein a preset number of ants are searched in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and a preset number of ply thickness and ply angle combinations are obtained as target position points, and an initial path is formed by the preset number of target position points; wherein the ply thickness and the ply angle are parameters of the battery pack composite material upper cover; each target position point of the initial path is input into the composite material upper cover finite element model to obtain the first-order modal frequency; for each target position point, the heuristic information of the target position point is updated, and the pheromone concentration of the target position point is updated according to the first-order modal frequency; for each position point, the selection probability of the ant selecting the position point is determined according to the pheromone concentration and heuristic information of the position point; wherein the position point includes the target position point and the other position points; and the preset number of ants are allowed to continue searching and iterating according to the selection probability of each position point. The above scheme determines the probability of the ant selecting the position point according to the pheromone concentration and the heuristic information, thereby guiding the subsequent search composition of the ant, so as to search the optimal path more quickly and accurately, and obtain the optimal final parameters of the battery pack composite material upper cover.

[0115] This application provides a specific implementation method, specifically: taking a certain type of power battery pack composite material upper cover as an example, its initial design has 5 layers of ply, with a total thickness of T0 = 10mm. During the optimization process, the number of ants k = 30, the initial concentration of pheromone τ0 = 0.3, the pheromone volatility coefficient ρ = 0.2, the heuristic factors α = 1.5, β = 2.5.

[0116] First, construct the finite element model of the upper cover, such as Figure 4 As shown, the ply thickness t is defined i The value range of (i=1,2,3,4,5) is 1mm-3mm, and the ply angle θ j The value range is 0°-90°.

[0117] In the iterative process, the ant determines the combination of ply thickness and ply angle according to the pheromone concentration and heuristic information, and substitutes it into the finite element model to calculate the first-order modal frequency as fitness. For example, an ant determines the combination of ply thickness as {1.2mm, 1.5mm, 1.8mm, 2.0mm, 1.5mm} and the combination of ply angle as {30°, 45°, 60°, 0°, 90°}, and calculates the first-order modal frequency as f1 = 80Hz.

[0118] An improved pheromone update strategy is adopted to enhance and diffuse pheromones for ant paths with better fitness. At the same time, a local search based on gradient is used. If the calculated gradient of the pavement thickness t2 is positive and large, the value of t2 is appropriately increased within the step size limit for optimization.

[0119] After multiple iterations, if the maximum number of iterations I is reached max =100, the optimal ply thickness combination is {1.5mm, 2.0mm, 2.2mm, 1.8mm, 1.5mm}, the ply angle combination is {40°, 50°, 55°, 10°, 85°}, and the maximum first-order modal frequency f * =120Hz.

[0120] Finally, the optimization scheme was substituted into the finite element model for detailed verification. After confirming that the first-order modal frequency was significantly improved without increasing the total thickness and that the structural performance met the requirements under other working conditions, it can be applied to actual production.

[0121] Figure 5 This is a schematic diagram of the structure of a battery pack composite material upper cover parameter determination device provided in an embodiment of the present application. The device can execute the battery pack composite material upper cover parameter determination method provided in any embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. Figure 5 As shown, the device comprises:

[0122] The initial path determination module 410 can be used to enable a preset number of ants to search in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and obtain a preset number of ply thickness and ply angle combinations as target position points, and form an initial path by the preset number of target position points; wherein the ply thickness and the ply angle are the battery pack composite material upper cover parameters;

[0123] A first-order modal frequency determination module 420 is used to input each target position point of the initial path into the composite material upper cover finite element model to obtain a first-order modal frequency;

[0124] An updating module 430, for updating the heuristic information of each target location point, and updating the pheromone concentration of the target location point according to the first-order modal frequency;

[0125] The iteration module 440 is used to make the preset ants continue to search and iterate according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration conditions are met to obtain the final parameters of the battery pack composite material cover; wherein the other position points are the position points other than the target position points among the position points included in the preset ply thickness range and the preset ply angle range.

[0126] In the embodiment of the present application, the updating module 430 updates the heuristic information of each target location point, including:

[0127] For the ply angle at the target position point, determining updated heuristic information corresponding to the ply angle according to the sine value of the ply angle;

[0128] For the ply thickness at the target location point, updated heuristic information corresponding to the ply thickness is determined according to a natural logarithm value of the ply thickness.

[0129] In the embodiment of the present application, the updating module 430 updates the pheromone concentration of each target location point according to the first-order modal frequency, including:

[0130] Determine the change in pheromone concentration according to the first-order modal frequency, and determine the enhanced pheromone concentration according to the current pheromone concentration and the change in pheromone at the target location; and / or,

[0131] Determine the diffusion pheromone concentration according to the distance between the target location point and the neighboring location point, and the current pheromone concentration of the neighboring location point; wherein the neighboring location point is a location point within a preset range of the target location point;

[0132] An updated pheromone concentration is determined according to the enhanced pheromone concentration and / or the diffused pheromone concentration.

[0133] In the embodiment of the present application, the updating module 430 determines the change amount of the pheromone concentration according to the first-order modal frequency, including:

[0134] The pheromone concentration change is determined by making the pheromone concentration change positively correlated with the first-order modal frequency;

[0135] Determining the enhanced pheromone concentration according to the current pheromone concentration and pheromone change amount of the target location point includes:

[0136] According to the pheromone volatilization coefficient and the current pheromone concentration, the pheromone concentration after volatilization is determined;

[0137] The sum of the volatilized pheromone concentration and the pheromone change amount is taken as the enhanced pheromone concentration.

[0138] In the embodiment of the present application, the updating module 430 determines the diffusion pheromone concentration according to the distance between the target location point and the neighboring location point and the current pheromone concentration of the neighboring location point, including:

[0139] For each neighborhood position point, determine the exponent of the Gaussian function according to the distance between the target position point and the neighborhood position point, determine the constant term according to the current pheromone concentration of the neighborhood position point, and calculate the Gaussian function value corresponding to the neighborhood position point;

[0140] The sum of the Gaussian function values ​​corresponding to each neighborhood position point is taken as the diffusion pheromone concentration corresponding to the target position point.

[0141] In the embodiment of the present application, the updating module 430 determines the updated pheromone concentration according to the enhanced pheromone concentration and the diffused pheromone concentration, including:

[0142] According to the weight value corresponding to the enhanced pheromone concentration and the weight value corresponding to the diffused pheromone concentration, the enhanced pheromone concentration and the diffused pheromone concentration are weightedly summed to obtain an updated pheromone concentration corresponding to the target location point.

[0143] In the embodiment of the present application, the iteration module 440 enables the preset ants to continue searching iterations according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, including:

[0144] For each position point, determining the probability of the ant selecting the position point according to the pheromone concentration and heuristic information of the position point; wherein the position points include the target position point and the other position points;

[0145] Let the preset ants continue searching iteratively according to the selection probability of each position point.

[0146] In the embodiment of the present application, the iteration module 440 determines the selection probability of the ant selecting the location point according to the pheromone concentration of the location point and the heuristic information, including:

[0147] For the target parameter at each position point, the product of the pheromone concentration at the position point and the heuristic information corresponding to the target parameter is used as the selection factor of the target parameter; wherein the target parameters include ply thickness and ply angle;

[0148] For the target parameter in each position point, the ratio of the selection factor of the target parameter to the sum of the selection factors of the target parameters in all the position points is used as the selection probability of the ant selecting the target parameter in the position point.

[0149] In the embodiment of the present application, the iteration module 440 uses the product of the pheromone concentration of the location point and the heuristic information corresponding to the target parameter as the selection factor of the target parameter, including:

[0150] Taking the weight factor of the pheromone concentration as the first exponent, calculating the value of the first exponential power of the pheromone concentration at the location point as the first selected value;

[0151] Taking the weight factor of the heuristic information corresponding to the target parameter as the second exponent, calculating the second exponential power of the heuristic information of the target parameter as the second selected value;

[0152] The product of the first selected value and the second selected value is used as a selection factor of the target parameter.

[0153] In the embodiment of the present application, the final parameters of the upper cover of the battery pack composite material are obtained, and the device further includes:

[0154] A simulation module is used to input the final parameters into the composite upper cover finite element model to determine whether the total ply thickness meets the total ply thickness constraint, whether the first-order modal frequency meets the preset first-section modal frequency requirement, and whether the preset performance data meets the preset performance requirement;

[0155] The judgment module is used to apply the final parameters of the battery pack composite material upper cover to the design and manufacture of the battery pack composite material upper cover if all the conditions are met.

[0156] A battery pack composite material upper cover parameter determination device provided in an embodiment of the present application can execute a battery pack composite material upper cover parameter determination method provided in any embodiment of the present application, and has corresponding functional modules and beneficial effects of the execution method.

[0157] Figure 6 A schematic diagram of an electronic device 10 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0158] like Figure 6As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0159] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless battery pack composite material upper cover parameter determination transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0160] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a method for determining parameters of a battery pack composite material upper cover.

[0161] In some embodiments, the method for determining the parameters of the battery pack composite material upper cover may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for determining the parameters of the battery pack composite material upper cover described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for determining the parameters of the battery pack composite material upper cover by any other appropriate means (e.g., by means of firmware).

[0162] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0163] The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable battery pack composite material upper cover parameter determination device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0164] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0165] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0166] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0167] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0168] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the information expected by the technical solution of this application can be achieved, and this document is not limited here.

[0169] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for determining parameters of a composite material upper cover of a battery pack, characterized in that: The method comprises: A preset number of ants are ordered to search in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and a preset number of ply thickness and ply angle combinations are obtained as target position points, and an initial path is formed by the preset number of target position points; wherein the ply thickness and the ply angle are the parameters of the upper cover of the battery pack composite material; Inputting each target position point of the initial path into the composite material upper cover finite element model to obtain the first-order modal frequency; For each target location point, updating the heuristic information of the target location point, and updating the pheromone concentration of the target location point according to the first-order modal frequency; The preset ants are ordered to continue searching and iterating according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration conditions are met to obtain the final parameters of the battery pack composite material upper cover; wherein the other position points are the position points other than the target position points in the preset ply thickness range and the preset ply angle range.

2. The method according to claim 1, characterized in that: For each target location point, updating the heuristic information of the target location point includes: For the ply angle at the target position point, determining updated heuristic information corresponding to the ply angle according to the sine value of the ply angle; For the ply thickness at the target location point, updated heuristic information corresponding to the ply thickness is determined according to a natural logarithm value of the ply thickness.

3. The method according to claim 1, characterized in that For each target location point, updating the pheromone concentration of the target location point according to the first-order modal frequency includes: Determine the change in pheromone concentration according to the first-order modal frequency, and determine the enhanced pheromone concentration according to the current pheromone concentration and the change in pheromone at the target location; and / or, Determine the diffusion pheromone concentration according to the distance between the target location point and the neighboring location point, and the current pheromone concentration of the neighboring location point; wherein the neighboring location point is a location point within a preset range of the target location point; An updated pheromone concentration is determined according to the enhanced pheromone concentration and / or the diffused pheromone concentration.

4. The method according to claim 3, characterized in that Determining the change in pheromone concentration according to the first-order modal frequency includes: The pheromone concentration change is determined by making the pheromone concentration change positively correlated with the first-order modal frequency; Determining the enhanced pheromone concentration according to the current pheromone concentration and pheromone change amount of the target location point includes: According to the pheromone volatilization coefficient and the current pheromone concentration, the pheromone concentration after volatilization is determined; The sum of the volatilized pheromone concentration and the pheromone change amount is taken as the enhanced pheromone concentration.

5. The method according to claim 3, characterized in that: According to the distance between the target location point and the neighboring location point, and the current pheromone concentration of the neighboring location point, the diffusion pheromone concentration is determined, including: For each neighborhood position point, determine the exponent of the Gaussian function according to the distance between the target position point and the neighborhood position point, determine the constant term according to the current pheromone concentration of the neighborhood position point, and calculate the Gaussian function value corresponding to the neighborhood position point; The sum of the Gaussian function values ​​corresponding to each neighborhood position point is taken as the diffusion pheromone concentration corresponding to the target position point.

6. The method according to claim 3, characterized in that Determining an updated pheromone concentration according to the enhanced pheromone concentration and the diffused pheromone concentration includes: According to the weight value corresponding to the enhanced pheromone concentration and the weight value corresponding to the diffused pheromone concentration, the enhanced pheromone concentration and the diffused pheromone concentration are weightedly summed to obtain an updated pheromone concentration corresponding to the target location point.

7. The method according to claim 1, characterized in that The preset ants are ordered to continue searching iteratively based on the updated heuristic information and pheromone concentration of each target location, as well as the heuristic information and pheromone concentration of other locations, including: For each position point, determining the probability of the ant selecting the position point according to the pheromone concentration and heuristic information of the position point; wherein the position points include the target position point and the other position points; Let the preset ants continue searching iteratively according to the selection probability of each position point.

8. The method according to claim 7, characterized in that The probability of the ant choosing the location point is determined based on the pheromone concentration and heuristic information of the location point, including: For the target parameter at each position point, the product of the pheromone concentration at the position point and the heuristic information corresponding to the target parameter is used as the selection factor of the target parameter; wherein the target parameters include ply thickness and ply angle; For the target parameter in each position point, the ratio of the selection factor of the target parameter to the sum of the selection factors of the target parameters in all the position points is used as the selection probability of the ant selecting the target parameter in the position point.

9. The method according to claim 8, characterized in that The product of the pheromone concentration of the location point and the heuristic information corresponding to the target parameter is used as the selection factor of the target parameter, including: Taking the weight factor of the pheromone concentration as the first exponent, calculating the value of the first exponential power of the pheromone concentration at the location point as the first selected value; Taking the weight factor of the heuristic information corresponding to the target parameter as the second exponent, calculating the second exponential power of the heuristic information of the target parameter as the second selected value; The product of the first selected value and the second selected value is used as a selection factor of the target parameter.

10. The method according to claim 1, characterized in that The final parameters of the upper cover of the battery pack composite material are obtained, and the method further comprises: Input the final parameters into the composite upper cover finite element model to determine whether the total ply thickness meets the total ply thickness constraint, whether the first-order modal frequency meets the preset first-section modal frequency requirement, and whether the preset performance data meets the preset performance requirement; If all are met, the final parameters of the battery pack composite material upper cover are applied to the design and manufacture of the battery pack composite material upper cover.

11. A device for determining parameters of a composite material upper cover of a battery pack, characterized in that: The device comprises: The initial path determination module can be used to make a preset number of ants search in a preset ply thickness range and a preset ply angle range according to the initialization pheromone concentration and the initialization heuristic information, and obtain a preset number of ply thickness and ply angle combinations as target position points, and form an initial path by the preset number of target position points; wherein the ply thickness and ply angle are the battery pack composite material upper cover parameters; A first-order modal frequency determination module, used for inputting each target position point of the initial path into the composite material upper cover finite element model to obtain the first-order modal frequency; An updating module, used for updating the heuristic information of each target location point and updating the pheromone concentration of the target location point according to the first-order modal frequency; The iteration module is used to make the preset ants continue to search and iterate according to the updated heuristic information and pheromone concentration of each target position point, as well as the heuristic information and pheromone concentration of other position points, until the iteration conditions are met to obtain the final parameters of the battery pack composite material cover; wherein the other position points are the position points other than the target position points in the preset ply thickness range and the preset ply angle range.

12. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining parameters of a composite material upper cover of a battery pack according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining parameters of a composite material upper cover of a battery pack according to any one of claims 1 to 10 when executed.

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