Battery pack support structure automatic optimization method, device and computer readable storage medium

Abstract

This invention provides an automatic optimization method, apparatus, and computer-readable storage medium for battery pack support structures. The method includes: (1) automatically generating a battery pack support model based on defined battery pack support structure parameters; (2) assigning the current battery pack support structure parameter values ​​to the battery pack support model, performing static or dynamic simulation on the current battery pack support model, and determining the performance parameters under the current battery pack support structure parameter values; (3) updating the battery pack support structure parameter values, returning to step (2), until the optimal battery pack support structure parameter values ​​are found. A battery pack support simulation optimization program model based on Python language combined with Abaqus finite element analysis software is used to realize automated modeling, simulation analysis, and multi-objective optimization of battery pack supports, improving structural performance and design efficiency.

Description

Technical Field

[0001] This invention belongs to the field of battery pack design technology, and more specifically, this invention relates to a method, apparatus and computer-readable storage medium for automatic optimization of battery pack support structure. Background Technology

[0002] The rapid development of new energy vehicles has made the power battery pack a key component. Its support structure needs to take into account high strength, lightweight and durability in order to cope with complex mechanical loads (such as vibration, impact, thermal expansion, etc.).

[0003] Abaqus, a powerful commercial finite element analysis software, is currently widely used for mechanical simulation of battery pack supports.

[0004] However, the traditional Abaqus modeling and analysis process relies on manual operation, which is complex, time-consuming, and difficult to automate the optimization of support structure parameters. In particular, when designing multi-objective optimization (such as stiffness, weight, and fatigue life), it is necessary to repeatedly adjust the structural parameters of the support, resulting in low efficiency. Summary of the Invention

[0005] In view of this, this application provides an automatic optimization method for the base battery pack support structure, which aims to improve at least one of the above-mentioned problems.

[0006] Specifically, the following technical solutions are included:

[0007] On the one hand, embodiments of this application provide an automatic optimization method for pool bag support structures, the method being as follows:

[0008] (1) Automatically generate battery pack bracket model based on defined battery pack bracket structural parameters;

[0009] (2) Assign the current battery pack bracket structural parameter values ​​to the battery pack bracket model, perform static or dynamic simulation on the current battery pack bracket model, and determine at least one performance parameter under the current battery pack bracket structural parameter values;

[0010] (3) Update the battery pack bracket structure parameter values ​​and return to step (2) until the optimal battery pack bracket structure parameter values ​​are found.

[0011] In some embodiments of the present invention, the construction process of the battery pack bracket is as follows:

[0012] (21) Construct a battery pack bracket coordinate system and determine the positions of the key points of the main components in the battery pack bracket coordinate system in sequence.

[0013] (22) Based on the structural parameters of the corresponding components, the base plate, crossbeam, longitudinal beam and column are automatically generated in the coordinate system of the battery pack bracket in sequence;

[0014] (23) Several longitudinal stiffeners are automatically generated at equal intervals on the bottom plate between the two longitudinal beams;

[0015] (24) The weight reduction holes automatically generated on the base plate, crossbeams, longitudinal beams and / or columns complete the construction of the battery pack bracket model.

[0016] In some embodiments of the present invention, the position coordinates of feature points on the top plate, bottom plate and web plate in the beam coordinate system are determined sequentially based on the defined beam structural parameters. The feature points include corner points and inflection points.

[0017] The top plate, bottom plate, and web plate are formed by adjacent feature points in the web plate;

[0018] The web located between the top plate and the bottom plate includes, from the top plate to the bottom plate, the upper web, the intermediate web, and the lower web.

[0019] In some embodiments of the present invention, the performance parameters include at least one of weight, stiffness, and fatigue life.

[0020] In some embodiments of the present invention, the process for obtaining the optimal performance battery pack bracket structure parameter values ​​is as follows:

[0021] (31) Randomly construct an initial population, and a set of battery pack support structure parameter values ​​corresponds to an individual in the population;

[0022] (32) Calculate the fitness value of each individual in the population. The fitness value is the total performance score of the battery pack support corresponding to the battery pack support structure parameter value of the current individual.

[0023] (33) Check whether the current iteration number has reached the threshold. If the detection result is yes, output the individual with the highest total performance score. If the detection result is no, execute step (34).

[0024] (34) Randomly select individuals from the population as parent individuals, perform crossover mutation on the parent individuals to form a new population, and return to step (32).

[0025] Among them, individuals with high fitness are more likely to be selected as parent individuals than individuals with low fitness.

[0026] In some embodiments of the present invention, the performance parameters under the current battery pack bracket structure parameter values ​​are normalized, and the comprehensive performance score of the corresponding battery pack bracket structure parameters is calculated by weighting. The battery pack bracket structure parameter value with the highest comprehensive performance score is the current optimal battery pack bracket structure parameter value.

[0027] On the other hand, embodiments of this application provide an automatic optimization device for battery pack bracket structure, the device comprising:

[0028] The system comprises: a model building unit; a model updating unit connected to the model building unit; a simulation unit connected to the model updating unit; and a parameter optimization unit connected to both the simulation unit and the model updating unit.

[0029] The model building unit is used to build a battery pack bracket model based on the defined battery pack bracket structural parameters.

[0030] The model update unit is used to assign the current battery pack bracket structural parameter values ​​to the battery pack bracket model, update the battery pack bracket model, and send it to the simulation unit.

[0031] The simulation unit is used to perform static and dynamic simulations on the current battery pack bracket model, determine at least one performance parameter under the current battery pack bracket structural parameter values, and output the result to the parameter optimization unit.

[0032] The parameter optimization unit is used to optimize the structural parameter values ​​of the battery pack bracket. The optimized structural parameter values ​​of the battery pack bracket are sent to the model update unit to find the structural parameter values ​​of the battery pack bracket with the best performance.

[0033] In some embodiments of the present invention, the model building unit includes:

[0034] The sub-units include crossbeam construction sub-units, longitudinal beam construction sub-units, other component construction sub-units, and conversion sub-units between crossbeam construction sub-units, longitudinal beam construction sub-units, and other component construction sub-units.

[0035] The beam construction sub-unit is used to construct beams in the beam coordinate system;

[0036] The longitudinal beam construction sub-unit is used to construct the longitudinal beam in the longitudinal beam coordinate system;

[0037] The transformation sub-unit is used to transform the horizontal beam in the horizontal beam coordinate system and the longitudinal beam in the longitudinal beam coordinate system to the battery pack bracket coordinate system.

[0038] Other component building units are used to build other major components in the battery pack, excluding the crossbeams and longitudinal beams, in the battery pack bracket coordinate system. Together with the crossbeams and longitudinal beams in the battery pack bracket coordinate system, they constitute the battery pack bracket model.

[0039] In some embodiments of the present invention, the parameter optimization unit automatically finds the optimal performance battery pack support structure parameter values ​​based on ant colony algorithm or genetic algorithm, wherein the performance parameters include at least one of weight, stiffness and fatigue life.

[0040] On the other hand, embodiments of this application provide a computer-readable storage medium storing a computer program that is executed by a processor to implement the above-described method.

[0041] This invention utilizes Python language combined with Abaqus finite element analysis software to construct a battery pack support model, enabling automated modeling, simulation analysis, and multi-objective optimization of the battery pack support, thereby improving structural performance and design efficiency. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of an automatic optimization method for battery pack support structure provided in an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the automatic optimization device for battery pack support structure provided in an embodiment of the present invention;

[0045] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0046] The technical solutions of 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, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] Unless otherwise defined, all technical terms used in the embodiments of this application have the same meaning as commonly understood by one of ordinary skill in the art. This invention provides a battery pack bracket simulation optimization program model based on Python language combined with Abaqus finite element analysis software, used to achieve automated modeling, simulation analysis, and multi-objective optimization of battery pack brackets, improving structural performance and design efficiency.

[0048] Figure 1 The flowchart of the automatic optimization method for battery pack bracket structure provided in the embodiment of the present invention is as follows:

[0049] (1) Automatically generate battery pack bracket model based on defined battery pack bracket structural parameters;

[0050] In this embodiment of the invention, the battery pack is fixed to the vehicle body by a battery pack bracket. The battery pack bracket consists of the following components, the main components of which include: a base plate; crossbeams, including a front crossbeam, a rear crossbeam, and multiple middle crossbeams (variable number) located between the front and rear crossbeams; longitudinal beams, including a left side beam and a right side beam; multiple longitudinal reinforcing ribs (variable number) located between the left and right side beams; four uprights located at the connection points between the crossbeams and the longitudinal beams; and weight-reducing holes located on the base plate, crossbeams, longitudinal beams, and uprights.

[0051] The following details the construction process of the battery pack bracket described above. The specific construction process of the battery pack bracket is as follows:

[0052] (21) Construct the battery pack bracket coordinate system, including determining the origin of the battery pack bracket coordinate system and the axial direction of the three axes, and sequentially determining the positions of the key points of the main components in the battery pack bracket coordinate system. The main components include: base plate, crossbeam, longitudinal beam, and column. The key points of the main components include the corner points of the base plate, the endpoints of the crossbeam and longitudinal beam, and the centerline point of the column.

[0053] (22) Based on the structural parameters of the corresponding components, the base plate, crossbeam, longitudinal beam and column are automatically generated in the coordinate system of the battery pack bracket in sequence;

[0054] (23) Several longitudinal stiffeners are automatically generated at equal intervals on the bottom plate between the two longitudinal beams;

[0055] (24) The weight reduction holes automatically generated on the base plate, crossbeams, longitudinal beams and / or columns complete the construction of the battery pack bracket model.

[0056] This invention refers to the structural parameters of the main components in the battery pack bracket as battery pack bracket structural parameters. These parameters consist of two types: battery pack bracket structural parameters to be optimized and set battery pack bracket structural parameters. The battery pack bracket structural parameters to be optimized are those that can be optimized, while the set battery pack bracket structural parameters are those that are not optimized. In this embodiment, the direct structural parameters of the battery pack to be optimized include: base plate thickness t_base, profile height h_beam of the crossbeam / longitudinal beam, wall thickness t_beam of the crossbeam / longitudinal beam, upper and lower flange width w_flange of the crossbeam / longitudinal beam, number of intermediate crossbeams n_mid_beam, longitudinal stiffener height h_rib, longitudinal stiffener thickness t_rib, column height corner_post_h, and weight-reducing hole diameter hole_dia.

[0057] In this embodiment of the invention, the total length of the battery pack is defined as L, and the total width of the battery pack is defined as W. A base plate that is adapted to the size of the battery pack needs to be generated. The base plate has the following structural parameters: length L, width W, and thickness t_base. Based on the structural parameters of the base plate, the position of the key corner points of the rectangular base plate in the coordinate system of the battery pack bracket is determined. Later, a base plate of the corresponding size is generated in the coordinate system of the battery pack bracket based on the coordinates of the key corner points of the rectangular base plate.

[0058] In this embodiment of the invention, the coordinates of the two ends of the center lines of the front and rear crossbeams in the battery pack bracket coordinate system are determined based on the width of the crossbeam. Since the intermediate crossbeams are arranged at equal intervals between the front and rear crossbeams, the coordinates of the two ends of the center lines of each intermediate crossbeam in the battery pack bracket coordinate system are calculated sequentially based on the number of intermediate crossbeams n_mid_beam. Later, based on the height, wall thickness, and width of the front, rear, and intermediate crossbeams, the front beam, intermediate crossbeam, and rear crossbeam are generated sequentially in the battery pack bracket coordinate system.

[0059] In this embodiment of the invention, the crossbeam includes a top plate, a bottom plate, and a web located between the top and bottom plates. The web consists of three segments, arranged sequentially from the top plate to the bottom plate: an upper web segment, an intermediate web segment, and a lower web segment. Based on the defined crossbeam structural parameters, the position coordinates of feature points on the top plate, bottom plate, and web in the crossbeam coordinate system are determined sequentially. These feature points include corner points and inflection points. Adjacent feature points in the top plate, bottom plate, and web form the top plate, bottom plate, and feature line segments within the web, thus forming the crossbeam. The constructed crossbeam is placed in the corresponding position in the battery pack bracket coordinate system with a specified orientation. That is, the origin of the crossbeam coordinate system is translated to the position coordinates of the crossbeam in the battery pack bracket coordinate system under the specified orientation. Essentially, this involves transforming the crossbeam from the crossbeam coordinate system to the corresponding position in the battery pack bracket coordinate system, thus completing the construction of the crossbeam in the battery pack bracket model. The generation methods for the front beam, middle crossbeam, and rear crossbeam are all as described above.

[0060] In this embodiment of the invention, the coordinates of the two endpoints of the center lines of the left and right longitudinal beams in the battery pack bracket coordinate system are determined based on the width of the longitudinal beams. Later, based on the height, wall thickness and width of the left and right longitudinal beams, the left and right longitudinal beams are generated sequentially in the battery pack bracket coordinate system.

[0061] In this embodiment, the longitudinal beam includes a top plate, a bottom plate, and a web located between the top and bottom plates. The web consists of three segments, arranged sequentially from the top plate to the bottom plate: an upper web segment, an intermediate web segment, and a lower web segment. Based on the defined longitudinal beam structural parameters, the position coordinates of feature points on the top plate, bottom plate, and web in the longitudinal beam coordinate system are determined sequentially. These feature points include corner points and inflection points. Adjacent feature points in the top plate, bottom plate, and web form the top plate, bottom plate, and feature line segments within the web, thus forming the longitudinal beam. The constructed longitudinal beam is placed in the corresponding position in the battery pack bracket coordinate system with a specified orientation. This means translating the origin of the longitudinal beam coordinate system to the position coordinates of the longitudinal beam in the battery pack bracket coordinate system under the specified orientation. Essentially, this transforms the longitudinal beam from the longitudinal beam coordinate system to the corresponding position in the battery pack bracket coordinate system, completing the construction of the longitudinal beam in the battery pack bracket model. The generation methods for the sitting longitudinal beam and the right longitudinal beam are as described above.

[0062] The structural parameters of the longitudinal stiffeners are generated sequentially between the left and right longitudinal beams. The intersection of the center line of the front crossbeam with the center lines of the left and right longitudinal beams is determined, as well as the intersection of the center line of the rear crossbeam with the center lines of the left and right longitudinal beams. These four intersection points are used as the end center points of the four columns. The columns are stretched to their height based on the column height, thus completing the formation of the four columns in the coordinate system of the battery pack support.

[0063] (2) Assign the current battery pack bracket structural parameter values ​​to the battery pack bracket model, perform static or dynamic simulation on the current battery pack bracket model, and determine at least one performance parameter under the current battery pack bracket structural parameter values;

[0064] In this embodiment of the invention, the performance parameters include at least one of weight, stiffness, and fatigue life. It can be any one of these performance parameters, a combination of any two of these performance parameters, or a combination of the three performance parameters mentioned above. Of course, other performance parameters can also be included according to actual needs, which will be described one by one here. Because the numerical differences between different performance parameters are large, small-value performance parameters have little impact on the evaluation of the battery pack support structure parameters, but they may be relatively important performance parameters. Therefore, when using two or more performance parameters to evaluate the battery pack support structure parameters, the performance parameters collected under the current battery pack support structure parameters are first normalized. The normalized performance parameters are then used for the evaluation of the battery pack structure parameters. The normalization process for weight, stiffness, and fatigue life is described in detail below:

[0065] Weight normalization: The weight is normalized based on the weight range of the battery pack bracket, which is [W]. min W max If the current weight of the battery pack is Wt, then the normalized weight of the battery pack support is: (Wt) max -Wt) / (W max -W min After normalization, the weight of the battery pack bracket is between 0 and 1. The smaller the current weight Wt of the battery pack bracket, the larger the corresponding value of the normalized weight of the battery pack bracket, and the higher its score.

[0066] Stiffness normalization is performed based on the stiffness range of the battery pack bracket, which is [G]. min G max If the current battery pack stiffness is Gt, then the normalized battery pack support stiffness is: (Gt - Gt) mint ) / (G max -G min After normalization, the stiffness of the battery pack bracket is between 0 and 1. The larger the current stiffness Gt of the battery pack bracket, the larger the value of the normalized stiffness of the battery pack bracket, and the higher its corresponding score.

[0067] Fatigue life normalization: Stiffness is normalized based on the fatigue life range of the battery pack bracket. The stiffness range of the battery pack bracket is [S]. min S max If the current fatigue life of the battery pack is St, then the normalized fatigue life of the battery pack bracket is: (St - S) mint ) / (S max -S minAfter normalization, the fatigue life of the battery pack bracket is between 0 and 1. The larger the current fatigue life of the battery pack bracket is St, the larger the value of the fatigue life of the battery pack bracket after normalization, and the higher its corresponding score.

[0068] After normalizing the performance parameters under the current battery pack bracket structure parameters, weight parameters are set based on the importance of each performance parameter. For example, if the weight of the battery pack bracket is of greater concern, the performance parameter "weight" is given a larger weight, and vice versa. The comprehensive performance score of the corresponding battery pack bracket structure parameters is calculated by weighting, and the battery pack bracket structure parameter with the highest comprehensive performance score is the current optimal battery pack bracket structure parameter.

[0069] (3) Update the battery pack bracket structure parameter values ​​and return to step (2) until the optimal battery pack bracket structure parameter values ​​are found.

[0070] In this embodiment of the invention, a battery pack bracket model is constructed based on the battery pack bracket structural parameters. After the values ​​of the battery pack bracket structural parameters are input into the battery pack bracket model, the battery pack bracket model is automatically adjusted to the physical model corresponding to the battery pack bracket structural parameters. This invention uses an ant colony algorithm or a genetic algorithm to automatically find the optimal battery pack bracket structural parameter values. This invention uses a genetic algorithm to illustrate the process of obtaining the optimal battery pack bracket structural parameter values, and the specific process is as follows:

[0071] (31) Randomly construct an initial population, and a set of battery pack support structure parameter values ​​corresponds to an individual in the population;

[0072] (32) Calculate the fitness value of each individual in the population. The fitness value is the total performance score of the battery pack support corresponding to the battery pack support structure parameter value of the current individual.

[0073] (33) Check whether the current iteration number has reached the threshold. If the detection result is yes, output the individual with the highest total performance score. If the detection result is no, execute step (34).

[0074] (34) Randomly select individuals from the population as parent individuals, perform crossover mutation on the parent individuals to form a new population, and return to step (32).

[0075] Among them, individuals with high fitness are more likely to be selected as parent individuals than individuals with low fitness. In addition, since all structural parameters in the battery pack bracket structure have a set reasonable value range, the set value range of each structural parameter in the battery pack bracket structure is used as a boundary constraint. Under the premise of satisfying the boundary constraint, the optimal battery pack bracket structure parameter value with comprehensive performance is found, thus completing the automatic optimization process of the battery pack bracket structure.

[0076] This invention utilizes the interface between Python and Abaqus to automate and intelligently design battery pack brackets, significantly improving design efficiency. Furthermore, through a multi-objective optimization algorithm, it balances the fatigue life, stiffness, and weight of the bracket to meet the lightweight requirements of new energy vehicles. The battery pack bracket model is highly flexible and can quickly adapt to different battery pack models and operating conditions.

[0077] Figure 2 This is a schematic diagram of the automatic optimization device for battery pack support structure provided in an embodiment of the present invention. For ease of explanation, only the parts related to the embodiment of the present invention are shown. The device includes:

[0078] The system comprises: a model building unit; a model updating unit connected to the model building unit; a simulation unit connected to the model updating unit; and a parameter optimization unit connected to both the simulation unit and the model updating unit.

[0079] The model building unit is used to build a battery pack bracket model based on the defined battery pack bracket structural parameters.

[0080] The model update unit is used to assign the current battery pack bracket structural parameter values ​​to the battery pack bracket model, update the battery pack bracket model, and send it to the simulation unit.

[0081] The simulation unit is used to perform static and dynamic simulations on the current battery pack bracket model, determine at least one performance parameter under the current battery pack bracket structural parameter values, and output the result to the parameter optimization unit.

[0082] The parameter optimization unit is used to optimize the structural parameter values ​​of the battery pack bracket. The optimized structural parameter values ​​are sent to the model update unit to find the optimal performance parameters of the battery pack bracket. The structural parameters of the battery pack bracket include the structural parameters to be optimized and the set structural parameters. The structural parameters to be optimized include: base plate thickness t_base, profile height h_beam of crossbeam / longitudinal beam, wall thickness t_beam of crossbeam / longitudinal beam, upper and lower flange width w_flange of crossbeam / longitudinal beam, number of intermediate crossbeams n_mid_beam, height h_rib of longitudinal stiffener, thickness t_rib of longitudinal stiffener, height corner_post_h of column, and diameter hole_dia of weight reduction hole.

[0083] The battery pack support consists of several components, primarily: a base plate; crossbeams, including a front crossbeam, a rear crossbeam, and multiple middle crossbeams (variable number) located between the front and rear crossbeams; longitudinal beams, including a left-side beam and a right-side beam; and multiple longitudinal stiffeners located between the left and right side beams. Ribs (variable quantity) are four columns located at the connection points of the crossbeams and longitudinal beams; and weight-reducing holes are located on the base plate, crossbeams, longitudinal beams, and columns. Based on this, the model building units include: crossbeam building sub-units, longitudinal beam building sub-units, other component building sub-units, and transformation sub-units between the crossbeam building sub-units, longitudinal beam building sub-units, and other component building sub-units. Among them, the crossbeam building sub-unit is used to build the crossbeam in the crossbeam coordinate system; the longitudinal beam building sub-unit is used to build the longitudinal beam in the longitudinal beam coordinate system; the transformation sub-unit is used to transform the crossbeam in the crossbeam coordinate system and the longitudinal beam in the longitudinal beam coordinate system to the battery pack bracket coordinate system; the other component building unit is used to build other main components in the battery pack besides the crossbeams and longitudinal beams in the battery pack bracket coordinate system, which together with the crossbeams and longitudinal beams in the battery pack bracket coordinate system constitute the battery pack bracket model.

[0084] In this embodiment of the invention, the crossbeam includes a top plate, a bottom plate, and a web located between the top and bottom plates. The web consists of three segments, arranged sequentially from the top plate to the bottom plate: an upper web segment, an intermediate web segment, and a lower web segment. Based on the defined crossbeam structural parameters, the position coordinates of feature points on the top plate, bottom plate, and web in the crossbeam coordinate system are determined sequentially. These feature points include corner points and inflection points. Adjacent feature points in the top plate, bottom plate, and web form the top plate, bottom plate, and feature line segments within the web, thus forming the crossbeam. The constructed crossbeam is placed in the corresponding position in the battery pack bracket coordinate system with a specified orientation. That is, the origin of the crossbeam coordinate system is translated to the position coordinates of the crossbeam in the battery pack bracket coordinate system under the specified orientation, completing the construction of the crossbeam in the battery pack bracket model. The generation methods for the front beam, middle crossbeam, and rear crossbeam are all as described above.

[0085] In this embodiment of the invention, the longitudinal beam includes a top plate, a bottom plate, and a web located between the top plate and the bottom plate. The web consists of three segments, which are arranged sequentially from the top plate to the bottom plate as: an upper web segment, an intermediate web segment, and a lower web segment. The crossbeam construction sub-unit determines the position coordinates of feature points on the top plate, bottom plate, and web in the longitudinal beam coordinate system based on the defined longitudinal beam structural parameters. The feature points include corner points and inflection points. Adjacent feature points in the top plate, bottom plate, and web form the top plate, bottom plate, and feature line segments within the web, thus forming the longitudinal beam.

[0086] In this embodiment of the invention, the longitudinal beam includes a top plate, a bottom plate, and a web located between the top plate and the bottom plate. The web consists of three segments, which are arranged sequentially from the top plate to the bottom plate as: an upper web segment, an intermediate web segment, and a lower web segment. The longitudinal beam construction sub-unit determines the position coordinates of feature points on the top plate, bottom plate, and web in the longitudinal beam coordinate system based on the defined longitudinal beam structural parameters. The feature points include corner points and inflection points. Adjacent feature points in the top plate, bottom plate, and web form the top plate and bottom plate. Feature line segments within the web form the longitudinal beam.

[0087] Other component construction units sequentially determine the key points of the main components in the battery pack bracket coordinate system. Based on the structural parameters of other components, the base plate and columns are sequentially generated in the battery pack bracket coordinate system. Several longitudinal reinforcing ribs are generated at equal intervals on the base plate between the two longitudinal beams. Weight reduction holes are generated on the base plate, crossbeams, longitudinal beams and / or columns. The main components include the base plate, crossbeams, longitudinal beams and columns. The key points of the main components include the corner points of the base plate, the endpoints of the crossbeams and longitudinal beams, and the centerline point of the columns. The structural parameters of the longitudinal reinforcing ribs are used to sequentially generate multiple longitudinal reinforcing ribs between the left and right longitudinal beams. The intersection points of the centerline of the front crossbeam with the centerlines of the left and right longitudinal beams, and the intersection points of the centerline of the rear crossbeam with the centerlines of the left and right longitudinal beams are determined. These four intersection points are used as the end center points of the four columns. The columns are stretched to their height based on the column height, thus completing the formation of the four columns in the battery pack bracket coordinate system.

[0088] The transformation sub-unit places the constructed crossbeams and longitudinal beams into their corresponding positions in the battery pack bracket coordinate system with specified orientations. That is, the crossbeams are transformed from the crossbeam coordinate system to their corresponding positions in the battery pack bracket coordinate system, and the longitudinal beams are transformed from the longitudinal beam coordinate system to their corresponding positions in the battery pack bracket coordinate system.

[0089] The parameter optimization unit automatically finds the optimal performance battery pack support structure parameter values ​​based on ant colony algorithm or genetic algorithm. The performance parameters include at least one of weight, stiffness and fatigue life.

[0090] To illustrate the process of obtaining the optimal battery pack bracket structural parameter values ​​using a genetic algorithm, the specific process is as follows: (31) Randomly construct an initial population, with a set of battery pack bracket structural parameter values ​​corresponding to an individual in the population; (32) Calculate the fitness value of each individual in the population, where the fitness value corresponds to the total performance score of the battery pack bracket corresponding to the current individual's battery pack bracket structural parameter value; (33) Check whether the current iteration number has reached the threshold. If the detection result is yes, output the individual with the highest current total performance score. If the detection result is no, execute step (34); (34) Randomly select an individual from the population as a parent individual, perform crossover mutation on the parent individuals to form a new population, and return to step (32); Among them, the probability of an individual with high fitness being selected as a parent individual is greater than that of an individual with low fitness. In addition, since all types of structural parameters in the battery pack bracket structural parameters have a set reasonable value range, the set value range of all types of structural parameters in the battery pack bracket structural parameters is used as a boundary constraint. Under the premise of satisfying the boundary constraint, the optimal battery pack bracket structural parameter value is found.

[0091] When evaluating the battery pack support structure parameters using two or more performance parameters, the performance parameters collected under the current battery pack support structure parameters are first normalized. The normalization process for weight, stiffness, and fatigue life is as described above and will not be repeated here. The normalized performance parameters are then used to evaluate the battery pack structure parameters. After normalizing the performance parameters under the current battery pack support structure parameters, weight parameters are set based on the importance of each performance parameter. For example, if the weight of the battery pack support is of greater concern, the performance parameter "weight" is assigned a larger weight; conversely, if the weight is less of a concern, a smaller weight is assigned. The comprehensive performance score of the corresponding battery pack support structure parameters is calculated by weighting, and the battery pack support structure parameter with the highest comprehensive performance score is the current optimal battery pack support structure parameter value.

[0092] This invention utilizes the interface between Python and Abaqus to automate and intelligently design battery pack brackets, significantly improving design efficiency. Furthermore, through a multi-objective optimization algorithm, it balances the fatigue life, stiffness, and weight of the bracket to meet the lightweight requirements of new energy vehicles. The battery pack bracket model is highly flexible and can quickly adapt to different battery pack models and operating conditions.

[0093] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules when implementing its functions. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0094] One embodiment of this application provides a terminal device including a processor and a memory. The processor may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. The processor may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor may also include a main processor and a coprocessor. The main processor is used to process data in the wake-up state, also known as a central processing unit (CPU); the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content required to be displayed on the screen. In some embodiments, the processor may also include an AI processor, which is used to handle computational operations related to machine learning. The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, a non-transitory computer-readable storage medium in the memory is used to store a computer program configured to be executed by one or more processors to implement the above-described automatic optimization method for battery pack support structure. The terminal device is based on a battery pack support simulation optimization program model using Python language combined with Abaqus finite element analysis software, which is used to realize automated modeling, simulation analysis and multi-objective optimization of battery pack support, thereby improving structural performance and design efficiency.

[0095] In some embodiments, the terminal device may also optionally include: a peripheral device interface and at least one peripheral device. The processor, memory, and peripheral device interface can be connected via a bus or signal lines. Each peripheral device can be connected to the peripheral device interface via a bus, signal lines, or a circuit board. Specifically, the peripheral device includes at least one of: radio frequency circuitry, a display screen, audio circuitry, and a power supply. Those skilled in the art will understand that the above structure does not constitute a limitation on the terminal device, and may include more or fewer components than illustrated, or combine certain components, or employ different component arrangements.

[0096] In an exemplary embodiment, a computer-readable storage medium is also provided, storing a computer program that, when executed by a processor, implements the aforementioned automatic optimization method for the battery pack support structure. This storage medium is based on a battery pack support simulation optimization program model using Python language combined with Abaqus finite element analysis software, used to achieve automated modeling, simulation analysis, and multi-objective optimization of the battery pack support, improving structural performance and design efficiency. Optionally, the computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), solid-state drives (SSDs), or optical discs, etc. The random access memory may include resistive random access memory (ReRAM) and dynamic random access memory (DRAM).

[0097] In an exemplary embodiment, a computer program product is also provided, comprising a computer program stored in a computer-readable storage medium. A processor of a terminal device reads the computer program from the computer-readable storage medium and executes the computer program, causing the terminal device to perform the aforementioned automatic optimization method for the battery pack support structure. This computer program product is based on a battery pack support simulation optimization program model using Python language combined with Abaqus finite element analysis software, used to achieve automated modeling, simulation analysis, and multi-objective optimization of the battery pack support, improving structural performance and design efficiency.

[0098] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only.

[0099] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. An automatic optimization method for a pool bag support structure, characterized in that, The method is as follows: (1) Automatically generate battery pack bracket model based on defined battery pack bracket structural parameters; (2) Assign the current battery pack bracket structural parameter values ​​to the battery pack bracket model, perform static or dynamic simulation on the current battery pack bracket model, and determine the performance parameters under the current battery pack bracket structural parameter values; (3) Update the battery pack bracket structure parameter values ​​and return to step (2) until the optimal battery pack bracket structure parameter values ​​are found.

2. The automatic optimization method for the pool support structure as described in claim 1, characterized in that, The specific construction process of the battery pack bracket is as follows: (21) Construct a battery pack bracket coordinate system and determine the positions of the key points of the main components in the battery pack bracket coordinate system in sequence. (22) Based on the structural parameters of the corresponding components, the base plate, crossbeam, longitudinal beam and column are automatically generated in the coordinate system of the battery pack bracket in sequence; (23) Several longitudinal stiffeners are automatically generated at equal intervals on the bottom plate between the two longitudinal beams; (24) The weight reduction holes automatically generated on the base plate, crossbeams, longitudinal beams and / or columns complete the construction of the battery pack bracket model.

3. The automatic optimization method for the pool support structure as described in claim 1, characterized in that, Based on the defined beam structural parameters, the position coordinates of the feature points on the top plate, bottom plate and web plate in the beam coordinate system are determined sequentially. The feature points include corner points and inflection points. The top plate, bottom plate, and web plate are formed by adjacent feature points in the web plate; The web located between the top plate and the bottom plate includes, from the top plate to the bottom plate, the upper web, the intermediate web, and the lower web.

4. The automatic optimization method for the pool support structure as described in claim 1, characterized in that, Performance parameters include at least one of the following: weight, stiffness, and fatigue life.

5. The automatic optimization method for the pool support structure as described in claim 1, characterized in that, The process for obtaining the optimal performance battery pack bracket structure parameter values ​​is as follows: (31) Randomly construct an initial population, and a set of battery pack support structure parameter values ​​corresponds to an individual in the population; (32) Calculate the fitness value of each individual in the population. The fitness value is the total performance score of the battery pack support corresponding to the battery pack support structure parameter value of the current individual. (33) Check whether the current iteration number has reached the threshold. If the detection result is yes, output the individual with the highest total performance score. If the detection result is no, execute step (34). (34) Randomly select individuals from the population as parent individuals, perform crossover mutation on the parent individuals to form a new population, and return to step (32). Among them, individuals with high fitness are more likely to be selected as parent individuals than individuals with low fitness.

6. The automatic optimization method for the pool support structure as described in claim 5, characterized in that, The performance parameters under the current battery pack bracket structure parameter values ​​are normalized, and the comprehensive performance score of the corresponding battery pack bracket structure parameters is calculated by weighting. The battery pack bracket structure parameter value with the highest comprehensive performance score is the current optimal battery pack bracket structure parameter value.

7. An automatic optimization device for battery pack support structure, characterized in that, The device includes: The system comprises: a model building unit; a model updating unit connected to the model building unit; a simulation unit connected to the model updating unit; and a parameter optimization unit connected to both the simulation unit and the model updating unit. The model building unit is used to build a battery pack bracket model based on the defined battery pack bracket structural parameters. The model update unit is used to assign the current battery pack bracket structural parameter values ​​to the battery pack bracket model, update the battery pack bracket model, and send it to the simulation unit. The simulation unit is used to perform static and dynamic simulations on the current battery pack bracket model, determine at least one performance parameter under the current battery pack bracket structural parameter values, and output the result to the parameter optimization unit. The parameter optimization unit is used to optimize the structural parameter values ​​of the battery pack bracket. The optimized structural parameter values ​​of the battery pack bracket are sent to the model update unit to find the structural parameter values ​​of the battery pack bracket with the best performance.

8. The automatic optimization device for battery pack support structure as described in claim 7, characterized in that, The model building units include: The sub-units include crossbeam construction sub-units, longitudinal beam construction sub-units, other component construction sub-units, and conversion sub-units between crossbeam construction sub-units, longitudinal beam construction sub-units, and other component construction sub-units. The beam construction sub-unit is used to construct beams in the beam coordinate system; The longitudinal beam construction sub-unit is used to construct the longitudinal beam in the longitudinal beam coordinate system; The transformation sub-unit is used to transform the horizontal beam in the horizontal beam coordinate system and the longitudinal beam in the longitudinal beam coordinate system to the battery pack bracket coordinate system. Other component building units are used to build other major components in the battery pack, excluding the crossbeams and longitudinal beams, in the battery pack bracket coordinate system. Together with the crossbeams and longitudinal beams in the battery pack bracket coordinate system, they constitute the battery pack bracket model.

9. The automatic optimization device for battery pack support structure as described in claim 7, characterized in that, The parameter optimization unit automatically finds the optimal performance battery pack support structure parameter values ​​based on ant colony algorithm or genetic algorithm. The performance parameters include at least one of weight, stiffness and fatigue life.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that is executed by a processor to implement the method as described in any one of claims 1 to 6.

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