Methods, systems, electronic devices, and storage media for optimizing bolt distribution in complex automotive systems

Abstract

The application discloses a kind of automobile complex system bolt distribution optimization method, system, electronic equipment and storage medium;Belong to bolt distribution optimization technical field, method includes: obtaining the external force of all external connection points of target vehicle complex system under various load conditions;Build the twin finite element model of complex system, input the external force into twin finite element model, calculate and solve to obtain the actual connecting force of bolt connection point;The size between actual connecting force and preset target connecting force is analyzed, if actual connecting force is greater than target connecting force, then increase the number of bolt connection point in twin finite element model;Space design optimization is carried out to twin finite element model, and the twin finite element model is optimized;Output optimized twin finite element model, obtain the optimal distribution of bolt of target vehicle complex system;Compared with traditional trial-and-error method, virtual analysis and optimization using simulation software can significantly shorten the design cycle, reduce the number of physical prototype production and test.

Description

Technical Field

[0001] This application belongs to the field of bolt distribution optimization technology, specifically relating to a bolt distribution optimization method, system, electronic device and storage medium for complex automotive systems. Background Technology

[0002] The battery pack system is a crucial component in the complex system of new energy vehicles. It is typically connected to the frame or body system via bolts. If the system structure is poorly designed, the stiffness of the various subsystems is not well matched, or the bolt placement and distribution are unreasonable, the shear force on the bolt connections of each subsystem will be very high. This can easily lead to bolt loosening or breakage during use, reducing the reliability and safety of the vehicle. Optimizing bolt force (shear force) manually is difficult and time-consuming.

[0003] Therefore, there is an urgent need for an efficient optimization method to achieve bolt distribution in the complex systems of new energy vehicles, in order to improve vehicle safety and shorten product development cycles. Summary of the Invention

[0004] The purpose of this application is to provide a method, system, electronic device, and storage medium for optimizing the bolt distribution in complex automotive systems, in order to solve the technical problem of bolt loosening and breakage caused by unreasonable bolt distribution in complex new energy vehicle systems in the prior art.

[0005] To solve the above-mentioned technical problems, this application is implemented as follows:

[0006] In a first aspect, embodiments of this application provide a method for optimizing bolt distribution in a complex automotive system, the method comprising:

[0007] Obtain the external forces at all external connection points of the target vehicle's complex system under various load conditions;

[0008] A twin finite element model of the complex system is built in simulation software. The external force is input into the twin finite element model to obtain the actual connection force of the bolt connection point in the twin finite element model.

[0009] Analyze the relationship between the actual connection force and the preset target connection force. If the actual connection force is greater than the target connection force, increase the number of bolt connection points in the twin finite element model.

[0010] The twin finite element model with increased bolt connection points is spatially optimized to optimize the twin finite element model.

[0011] The optimized twin finite element model is output to obtain the optimal bolt distribution of the target vehicle complex system.

[0012] As an optional embodiment of the first aspect of this application, the load conditions include bump conditions and vehicle torsion conditions; the complex system includes a frame system, a battery pack and a battery pack support system, and the twin finite element model includes a frame system sub-model, a battery pack sub-model and a battery pack support system sub-model.

[0013] As an optional implementation of the first aspect of this application, the step of obtaining the external forces at all external connection points of the target vehicle complex system under various load conditions specifically involves:

[0014] A multibody dynamics model of the target vehicle is built in multibody dynamics software, and the multibody dynamics model of the vehicle is placed on a virtual ground.

[0015] A first preset value of vertical gravity field is applied to the vehicle multibody dynamics model to solve the external forces at the connection points between the assembly consisting of the vehicle frame, battery pack, and battery pack bracket and other system models under the bump condition.

[0016] A second preset vertical displacement is applied to the centers of the two wheels on opposite sides of the front and rear of the vehicle's multibody dynamics model, and vertical displacement constraints are applied to the other two wheels to solve for the external forces at the connection points under the torsional condition of the vehicle.

[0017] As an optional implementation of the first aspect of this application, the steps for building the twin finite element model are as follows:

[0018] Import the three-dimensional model of the target vehicle complex system into the simulation software, switch the processing module to the Optistruct processor module, and perform finite element modeling.

[0019] Shell element modeling is performed on the shell parts in the three-dimensional model, and solid element modeling is performed on the castings of the complex system of the target vehicle.

[0020] The bolted connections between the vehicle frame system, battery pack, and battery pack bracket system in the 3D model are simulated using bar elements; the external connection points and the complex system are connected through rb2 elements, with the master node of the rb2 element being the external connection point.

[0021] As an optional implementation of the first aspect of this application, the spatial design optimization of the twin finite element model after increasing the number of bolt connection points specifically includes:

[0022] In the twin finite element model after increasing the number of bolt connection points, all bolt connection points are numbered and their diameters are defined as variables.

[0023] Set constraints and optimization objectives for the bolt point connections between the twin finite element models;

[0024] Based on the constraints and optimization objectives, calculate the cancelable bolt connection points, delete the cancelable bolt connection points, and obtain the optimized twin finite element model.

[0025] As an optional implementation of the first aspect of this application, the optimization objective includes a first optimization objective and a second optimization objective; the constraint condition includes: the ratio of the number of bolt connection points in the optimized twin finite element model to the number of bolt connection points in the twin finite element model is greater than a first preset value;

[0026] The first optimization objective represents the optimization objective for the bolt connection points between the battery pack bracket sub-model and the battery pack model;

[0027] The second optimization objective represents the optimization objective for the bolt connection points between the vehicle frame system sub-model and the battery pack bracket sub-model.

[0028] As an optional implementation of the first aspect of this application, the first optimization objective is specifically as follows:

[0029] minmax(S i / objref(M10));

[0030] The second optimization objective is specifically as follows:

[0031] minmax(S j / objref(M14));

[0032] The Minmax function outputs the minimum value after applying optimization and constraint conditions to the maximum value; S represents the calculated bolt shear force; i represents the bolt connection point number between the battery pack bracket sub-model and the battery pack sub-model; j represents the bolt connection point number between the frame system sub-model and the battery pack bracket sub-model; objref represents the allowable shear force reference value; M10 represents the bolt type between the battery pack bracket sub-model and the battery pack model; M14 represents the bolt type between the frame system sub-model and the battery pack bracket sub-model; objref(M10) represents the reference value of the allowable shear force of the bolt between the battery pack bracket sub-model and the battery pack model; objref(M14) represents the reference value of the allowable shear force of the bolt between the frame system sub-model and the battery pack bracket model.

[0033] Secondly, embodiments of this application provide a bolt distribution optimization system for complex automotive systems, the system comprising:

[0034] The first acquisition module is used to acquire the external forces at all external connection points of the target vehicle's complex system under various load conditions.

[0035] The first modeling module is used to establish a twin finite element model of the complex system.

[0036] The first processing module inputs the external force of the external connection point obtained by the first acquisition module into the first modeling module, and obtains the actual connection force of the bolt connection point in the twin finite element model through simulation calculation.

[0037] The first judgment module determines the magnitude between the actual connection force obtained by the first processing module and the preset target connection force.

[0038] The second processing module increases the number of bolt connection points in the twin finite element model if the actual connection force is greater than the preset target connection force.

[0039] The first optimization module optimizes the twin finite element model with added bolt connection points in the second processing module, and deletes the bolt connection points that can be canceled.

[0040] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0041] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0042] In this embodiment, through precise simulation and analysis, it is ensured that the bolted connection points can withstand the required load under actual working conditions, reducing the risk of structural damage or accidents caused by bolt connection failure. By increasing the necessary number of bolts and optimizing the spatial design, materials can be allocated more rationally, avoiding increased costs and weight due to excessive use of bolts. Compared with traditional trial-and-error methods, using simulation software for virtual analysis and optimization can significantly shorten the design cycle and reduce the number of physical prototypes and tests. The simulation model allows designers to simulate and optimize under various working conditions, making the design more flexible and better adaptable to different usage environments and needs. By optimizing bolt distribution and spatial design, the complexity and error rate in the manufacturing process can be reduced, thereby lowering manufacturing costs. Attached Figure Description

[0043] Figure 1 This is a flowchart of a method for optimizing bolt distribution in a complex automotive system, provided by some embodiments of this application. Detailed Implementation

[0044] 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.

[0045] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0046] The following description, in conjunction with the accompanying drawings, details a method, system, electronic device, and storage medium for optimizing bolt distribution in a complex automotive system provided by this application, through specific embodiments and application scenarios.

[0047] Example

[0048] A method for optimizing bolt distribution in a complex automotive system includes the following steps:

[0049] S100: Obtain the external forces at all external connection points of the target vehicle's complex system under various load conditions;

[0050] S200: Build a twin finite element model of a complex system in simulation software, input external forces into the twin finite element model, and obtain the actual connection force of the bolt connection point in the twin finite element model;

[0051] Furthermore, the S100 and S200 load conditions include bump conditions and vehicle torsion conditions; the complex system includes the frame system, battery pack and battery pack support system; the twin finite element model includes the frame system sub-model, the battery pack sub-model and the battery pack support system sub-model.

[0052] Furthermore, S100 specifically refers to:

[0053] S110: Build a full-vehicle multibody dynamics model of the target vehicle in multibody dynamics software, and place the full-vehicle multibody dynamics model on a virtual ground;

[0054] S120: Apply a first preset value of vertical gravity field to the multibody dynamics model of the whole vehicle, and solve the external forces at the connection points between the assembly consisting of the frame, battery pack and battery pack bracket and other system models under the bump condition;

[0055] S130: Apply a second preset vertical displacement to the centers of the two wheels on opposite sides of the front and rear of the vehicle's multibody dynamics model, constrain the vertical displacement of the other two wheels, and solve for the external forces at the connection points under the torsional condition of the vehicle.

[0056] Specifically, the first preset value is 3.5g, where g is the acceleration due to gravity; the second preset value is 100m.

[0057] It is important to understand that, based on the aforementioned characteristics, in multibody dynamics software, a multibody dynamics model of the target vehicle is constructed according to its geometric and physical characteristics. This model should accurately reflect the chassis system, battery pack, battery pack support system, and the connections between them. The constructed multibody dynamics model is placed on a virtual ground, ensuring that parameters such as contact and friction between the model and the ground are set reasonably to simulate real road conditions. A first preset vertical gravity field is applied to the multibody dynamics model, which is usually equal to the Earth's gravitational acceleration, to simulate the vehicle's state under normal gravity. Under the influence of the gravity field, dynamic simulation is performed on the model to simulate the vehicle passing over bumps. The motion state is analyzed; the force data of each bolt connection point in the frame system sub-model under bump conditions is extracted, including the direction and magnitude of the force; a second preset vertical displacement is applied to the center of the two wheels on opposite sides of the front and rear of the vehicle multibody dynamics model to simulate the torsion that may occur when the vehicle is driving on an uneven road surface; vertical displacement constraints are applied to the other two wheels to ensure that the model maintains a certain stability during torsion; after applying vertical displacement and constraints, dynamic simulation is performed on the model to simulate the motion state of the vehicle under torsion conditions; the force data of each external connection point in the frame system sub-model, battery pack sub-model, and battery pack bracket system sub-model under torsion conditions are extracted; these are the external forces at the external connection points.

[0058] It should be noted that by building a full-vehicle multibody dynamics model in multibody dynamics software and setting virtual ground and applying conditions such as vertical gravity field and vertical displacement, the motion state of the vehicle under different working conditions can be simulated more accurately, thereby obtaining more realistic external force data. Accurate external force data is the foundation for subsequent finite element simulation analysis, which helps to improve the accuracy and reliability of the simulation. Based on accurate external force data, finite element simulation analysis can identify weak points in the frame system, battery pack assembly, and battery pack bracket system, and increase the number of bolt connection points accordingly. A reasonable bolt distribution can significantly improve the structural strength and durability of the entire system, especially under bump and vehicle torsion conditions. In complex operating conditions, optimizing the number and layout of bolts can reduce unnecessary bolt usage while ensuring structural strength, thereby reducing manufacturing costs and the overall system weight. Using simulation software for virtual analysis and optimization can significantly shorten the design cycle and reduce the number of physical prototypes and tests. Simulation analysis can also provide more detailed and accurate data support, helping designers better understand the system's stress conditions and performance, improving design accuracy and efficiency. The optimized bolt distribution can better adapt to different operating environments and requirements, especially under complex and variable conditions (such as bump conditions and vehicle torsion conditions), where the optimized system exhibits better adaptability and reliability.

[0059] Furthermore, the steps for building the twin finite element model in S200 are as follows:

[0060] S210: Import the 3D model of the target vehicle's complex system into the simulation software, switch the processing module to the Optistruct processor module, and perform finite element modeling.

[0061] S220: Perform shell element modeling for shell parts in the 3D model, and perform solid element modeling for castings of complex systems of the target vehicle.

[0062] S230: The bolted connections between the frame system, battery pack, and battery pack bracket system in the 3D model are simulated using bar elements; external connection points and complex systems are connected using rb2 elements, with the master node of the rb2 element being the external connection point.

[0063] It is important to understand that, based on the aforementioned characteristics, the simulation software first imports the 3D model of the target vehicle's complex system. This typically includes CAD files of the chassis system, battery pack, battery pack support system, and related connectors. This step requires ensuring that the model's geometry, dimensions, and connections are consistent with the real system. In the simulation software, the current switching processing module is set to the Optistruct processor module. Optistruct is a powerful finite element analysis software, particularly suitable for structural optimization and strength analysis. For shell components in the 3D model (such as parts of the chassis system's shell structure, the battery pack's outer shell, etc.), shell elements are used for modeling. Shell elements can simulate the bending and shearing behavior of thin-shell structures and are suitable for analyzing the stress conditions of such components. For castings in the target vehicle's complex system (such as the casting structures inside the battery pack), solid elements are used for modeling. Solid elements can simulate the internal stress and deformation of three-dimensional solid structures, making them suitable for analyzing the complex stress conditions of such parts. For bolts between the frame system, battery pack, and battery pack bracket in the three-dimensional model, bar elements are used for simulation. Bar elements can simulate the tensile, compressive, and bending behavior of one-dimensional rods, making them suitable for analyzing the stress conditions of such connections. For external connection points between the assembly consisting of the frame system, battery pack, and battery pack bracket and other system components in the three-dimensional model, rb2 elements are used for simulation. The rb2 element is a rigid-hinged connection element that can simulate the relative motion and stress conditions between rigid bodies, making it suitable for analyzing such complex connections.

[0064] It should be noted that precise 3D modeling and element selection can more accurately simulate the geometry and stress conditions of complex target vehicle systems; reasonable mesh generation and material property settings can further improve the accuracy and precision of the simulation; through simulation analysis, weak points and potential risks in the frame system, battery pack, and battery pack bracket can be identified; optimization design based on simulation results can significantly improve the structural strength and durability of the system; and using simulation software for virtual analysis and optimization can significantly shorten the design cycle and reduce the number of physical prototypes and tests.

[0065] S300: Analyze the difference between the actual connection force and the preset target connection force. If the actual connection force is greater than the target connection force, increase the number of bolt connection points in the twin finite element model.

[0066] S400: Perform spatial design optimization on the twin finite element model after increasing the number of bolt connection points, and optimize the twin finite element model;

[0067] Furthermore, the specific steps for optimizing the spatial design are as follows:

[0068] S410: Number all bolt connection points in the twin finite element model after increasing the number of bolt connection points and define the diameter as a variable;

[0069] S420: Set constraints and optimization objectives for bolt point connections between twin finite element models;

[0070] S430: Calculate the cancelable bolt connection points based on the constraints and optimization objectives, delete the cancelable bolt connection points, and obtain the optimized twin finite element model.

[0071] It's important to understand that, based on the aforementioned feature constraints, all bolt connections in the twin finite element model after increasing the number of bolt connection points are numbered, and the diameter of each bolt is defined as a variable. Numbering helps track and manage each bolt connection point, while defining the bolt diameter as a variable is for subsequent optimization calculations. By adjusting these variables, we can explore the impact of different bolt sizes on model performance. Constraints and optimization objectives are set for the bolt connection points between the twin finite element models. Constraints ensure the optimization process remains within a reasonable range, avoiding unrealistic designs; optimization objectives guide the direction of the optimization process, ensuring the final design meets specific performance requirements. Using optimization algorithms and finite element analysis software, according to... The core of the optimization process is determining which bolt connections can be eliminated (deleted) without affecting the model's performance, based on constraints and optimization objectives. This step aims to identify bolt connections that contribute little or no to the model's performance, thereby reducing the number of bolts, lowering manufacturing costs, and maintaining or improving the model's performance. Based on the calculation results from the previous step, eliminateable bolt connections from the twin finite element model to achieve a lightweight and simplified structure, while ensuring the model's performance meets design requirements. After deleting bolt connections, perform a new finite element analysis to verify if the model's performance meets the design requirements. If not, adjust the constraints or optimization objectives and repeat the above steps until a satisfactory optimization result is obtained.

[0072] It should be noted that by reducing unnecessary bolt connection points, the model achieves a lightweight design, reducing the overall vehicle weight and thus improving fuel economy or extending the driving range of electric vehicles. Reducing the number of bolts means reducing material and manufacturing costs, which helps improve product competitiveness. Simplifying the structure can reduce assembly time and complexity, and improve production efficiency. The optimization process ensures that while reducing the number of bolts, the model's performance (such as structural strength, durability, and safety) is maintained or improved. Through space design optimization, designers can more easily adjust the bolt layout and number to meet the needs and usage scenarios of different customers.

[0073] Furthermore, the optimization objectives include a first optimization objective and a second optimization objective; the constraints include: the ratio of the number of bolt connection points in the twin finite element model to the total number of bolt connection points in the twin finite element model is greater than a first preset value;

[0074] The first optimization objective represents the optimization objective for the bolt connection points between the battery pack bracket sub-model and the battery pack model;

[0075] The second optimization objective represents the optimization objective for the bolt connection points between the vehicle frame system sub-model and the battery pack bracket sub-model.

[0076] It is important to understand that, based on the aforementioned feature constraints, firstly, according to the first and second optimization objectives, the optimization direction of bolt connection points between the battery pack bracket sub-model and the battery pack sub-model, and between the vehicle frame system sub-model and the battery pack bracket sub-model, is determined; then, under the constraint that the ratio of the number of bolt connection points is greater than a first preset value, the bolt connection points are iteratively optimized using an optimization algorithm; in each iteration, the performance of the optimized model (such as structural strength, stiffness, weight, etc.) is evaluated, and the optimization parameters are adjusted according to the evaluation results; until a satisfactory optimization result is achieved.

[0077] It should be noted that by reducing unnecessary bolt connection points, the model achieves a lightweight design, reducing the overall vehicle weight; reducing the number of bolts means reducing material and manufacturing costs, which helps improve the product's competitiveness; the optimized connection design may have better stiffness and strength distribution, thereby improving the stability and safety of the entire vehicle structure; the optimization process provides more design freedom, allowing designers to adjust the bolt layout and number according to actual needs.

[0078] Furthermore, the first optimization objective is specifically:

[0079] minmax(S i / objref(M10));

[0080] The second optimization objective is specifically as follows:

[0081] minmax(S j / objref(M14));

[0082] The `minmax` function outputs the minimum value after applying optimization and constraint conditions to the maximum value; `S` represents the calculated bolt shear force; `i` represents the bolt connection point number between the battery pack bracket sub-model and the battery pack sub-model; `j` represents the bolt connection point number between the frame system sub-model and the battery pack bracket sub-model; `objref` represents the allowable shear force reference value; `M10` represents the bolt type between the battery pack bracket sub-model and the battery pack model; `M14` represents the bolt type between the frame system sub-model and the battery pack bracket sub-model; `objref(M10)` represents the allowable shear force reference value for the bolts between the battery pack bracket sub-model and the battery pack model; `objref(M14)` represents the allowable shear force reference value for the bolts between the frame system sub-model and the battery pack bracket sub-model.

[0083] It is important to understand that, based on the above-mentioned feature limitations, by using the minmax function on the bolt connection point, the diameter of the bolt is reduced according to preset conditions. If the bolt diameter is reduced to less than 5mm, it means that the bolt connection point can be deleted.

[0084] S500: Outputs an optimized twin finite element model to obtain the optimal bolt distribution of the target vehicle's complex system.

[0085] According to one embodiment, firstly, external force data of all bolt connection points of the target vehicle's complex system under various load conditions are collected; this is the starting point of the analysis, ensuring the accuracy of subsequent simulation and optimization depends on these precise external force data. In the simulation software, a corresponding twin finite element model is established based on the target vehicle's complex system. This step is the foundation of virtual simulation, simulating the mechanical behavior of the real system. The previously collected external force data is input into this twin finite element model to simulate the force situation under real working conditions. The actual connection force is calculated: through simulation calculation, the actual connection force of each bolt connection point in the model is obtained; these actual connection forces are compared with the preset target connection force. The preset target connection force is usually determined based on design specifications and safety margins. The number of bolts is increased: if the actual connection force exceeds the target connection force, it indicates that the current bolt distribution is insufficient to support the load, and the number of bolt connection points needs to be increased. After increasing the number of bolts, the model is spatially optimized to ensure that the bolt layout is reasonable and effective, while considering factors such as space constraints and manufacturing difficulty. The optimized model is output: after completing the above steps, the optimized twin finite element model is output, which represents the optimal bolt distribution of the target vehicle's complex system.

[0086] Through precise simulation and analysis, it is ensured that bolted connections can withstand the required loads under actual working conditions, reducing the risk of structural damage or accidents caused by bolt failure. By increasing the necessary number of bolts and optimizing spatial design, materials can be allocated more rationally, avoiding increased costs and weight due to excessive use of bolts. Compared to traditional trial-and-error methods, using simulation software for virtual analysis and optimization can significantly shorten the design cycle and reduce the number of physical prototypes and tests. Simulation models allow designers to simulate and optimize under various working conditions, making the design more flexible and better adaptable to different usage environments and needs. By optimizing bolt distribution and spatial design, the complexity and error rate in the manufacturing process can be reduced, thereby lowering manufacturing costs.

[0087] It should be noted that the bolt distribution optimization method for a complex automotive system provided in this application can be executed by a bolt distribution optimization system for a complex automotive system, or by a control module within that system for executing the bolt distribution optimization method. This application uses the execution of the bolt distribution optimization method by a bolt distribution optimization system for a complex automotive system as an example to illustrate the bolt distribution optimization method for a complex automotive system provided in this application.

[0088] A bolt distribution optimization system for complex automotive systems, comprising:

[0089] The first acquisition module is used to acquire the external forces at all external connection points of the target vehicle's complex system under various load conditions.

[0090] The first modeling module is used to establish twin finite element models of complex systems;

[0091] The first processing module inputs the external force of the external connection point obtained by the first acquisition module into the first modeling module, and calculates the actual connection force of the bolt connection point in the twin finite element model through simulation.

[0092] The first judgment module determines the magnitude of the actual connection force obtained by the first processing module and the preset target connection force;

[0093] The second processing module increases the number of bolt connection points in the twin finite element model if the actual connection force is greater than the preset target connection force.

[0094] The first optimization module optimizes the twin finite element model with added bolt connection points in the second processing module, and deletes bolt connection points that can be canceled.

[0095] The bolt distribution optimization system for complex automotive systems in this application embodiment can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network-attached storage (NAS), personal computers (PCs), etc. This application embodiment does not impose specific limitations.

[0096] The bolt distribution optimization system for a complex automotive system in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit it.

[0097] This application provides a bolt distribution optimization system for complex automotive systems that can achieve... Figure 1 The various processes implemented in the method embodiment of the bolt distribution optimization method for a complex automotive system will not be described again here to avoid repetition.

[0098] According to the bolt distribution optimization system for complex automotive systems provided in this embodiment, intelligent optimization algorithms such as genetic algorithms and particle swarm optimization can be introduced in the first optimization module to find the optimal bolt distribution scheme more efficiently. The system can integrate real-time monitoring functions to collect stress data of bolt connection points in real time and dynamically adjust the bolt distribution according to data changes, thereby improving the system's adaptability and safety. In the first acquisition module, in addition to considering various load conditions, factors such as different speeds and different road conditions can also be considered to more comprehensively evaluate the rationality of the bolt distribution. During the optimization process, in addition to considering the number and distribution of bolts, the impact of bolts made of different materials on the overall system performance can also be considered to select bolt materials with higher cost performance. An intuitive and easy-to-use user interface is designed to allow users to view the optimization results of the bolt distribution and manually adjust or set optimization parameters as needed.

[0099] Optionally, this application embodiment also provides an electronic device, including a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, they implement the various processes of the above-described embodiment of the method for optimizing bolt distribution in a complex automotive system and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0100] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described embodiment of the method for optimizing bolt distribution in a complex automotive system and achieve the same technical effect. To avoid repetition, these will not be described again here.

[0101] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0102] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this application.

[0104] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for optimizing bolt distribution in a complex system of an automobile, characterized in that, The method comprises: acquiring external forces of all external connection points of a target vehicle complex system under various load conditions; building a twin finite element model of the complex system in simulation software, inputting the external forces into the twin finite element model, and obtaining actual connection forces of bolt connection points in the twin finite element model; analyzing the size between the actual connection forces and preset target connection forces, and if the actual connection forces are greater than the target connection forces, increasing the number of bolt connection points in the twin finite element model; performing spatial design optimization on the twin finite element model after increasing the number of bolt connection points, and optimizing the twin finite element model; outputting the optimized twin finite element model, and obtaining an optimal distribution of bolts of the target vehicle complex system; wherein the load conditions comprise a bump condition and a whole vehicle torsion condition; the complex system comprises a frame system, a battery pack and a battery pack support system; and the twin finite element model comprises a frame system submodel, a battery pack submodel and a battery pack support system submodel. The acquiring of the external forces of all external connection points of the target vehicle complex system under various load conditions is specifically: building a whole vehicle multi-body dynamics model of the target vehicle in multi-body dynamics software, and placing the whole vehicle multi-body dynamics model on a virtual ground; applying a first preset value of vertical gravity field to the whole vehicle multi-body dynamics model, and solving external forces of connection points of an assembly composed of the frame, the battery pack and the battery pack support and other system models under the bump condition; applying a second preset value of vertical displacement to centers of two wheels on different sides of the front and rear of the whole vehicle multi-body dynamics model, and performing vertical displacement constraint on the other two wheels, and solving connection point external forces under the whole vehicle torsion condition.

2. The method of claim 1, wherein, The building of the twin finite element model comprises the following steps: importing a three-dimensional model of the target vehicle complex system in the simulation software, switching a processing module to an optistruct processor module, and performing finite element modeling; performing shell element modeling on shell parts in the three-dimensional model, and performing solid element modeling on castings of the target vehicle complex system; simulating bolts by using bar elements for bolt connections between the frame system, the battery pack and the battery pack support system in the three-dimensional model; the external connection points and the complex system are connected by rb2 elements, and a master node of the rb2 element is the external connection point.

3. The method of claim 1, wherein, The spatial design optimization of the twin finite element model after increasing the number of bolt connection points comprises: numbering all bolt connection points in the twin finite element model after increasing the number of bolt connection points and defining diameters as variables; setting constraint conditions and optimization targets for bolt point connections between the twin finite element models; calculating cancelable bolt connection points according to the constraint conditions and the optimization targets, deleting the cancelable bolt connection points, and obtaining an optimized twin finite element model.

4. The method of claim 3, wherein, The optimization target includes a first optimization target and a second optimization target; the constraint condition includes that a ratio of a number of bolt connection points in the optimized twin finite element model to a number of bolt connection points of the twin finite element model is greater than a first preset value; The first optimization target represents a bolt connection point optimization target between the battery pack support system submodel and the battery pack submodel; The second optimization target represents a bolt connection point optimization target between the vehicle frame system submodel and the battery pack support system submodel.

5. The method of claim 4, wherein, The first optimization target is specifically, ； The second optimization target is specifically, ； The Minmax function represents that a maximum value is outputted as a minimum value after optimization conditions and constraint conditions; S represents a calculated shear force of a bolt; i represents a bolt connection point number between a battery pack support submodel and a battery pack submodel; j represents a bolt connection point number between a vehicle frame system submodel and the battery pack support submodel; objref represents a reference value of an allowable shear force; M10 represents a bolt type number between the battery pack support submodel and the battery pack submodel; M14 represents a bolt type number between the vehicle frame system submodel and the battery pack support submodel; objref(M10) represents a reference value of a bolt allowable shear force between the battery pack support submodel and the battery pack submodel; and objref(M14) represents a reference value of a bolt allowable shear force between the vehicle frame system submodel and the battery pack support submodel.

6. An automotive complex system bolt distribution optimization system, capable of implementing the automotive complex system bolt distribution optimization method of any one of claims 1-5, characterized in that, The system includes: A first acquisition module configured to acquire external forces of all external connection points of a target vehicle complex system under various load conditions; A first modeling module configured to establish a twin finite element model of the complex system; A first processing module configured to input the external forces of the external connection points acquired by the first acquisition module to the first modeling module, and obtain actual connection forces of bolt connection points in the twin finite element model through simulation calculation; A first judgment module configured to judge a size between the actual connection forces obtained by the first processing module and a preset target connection force; A second processing module configured to increase a number of bolt connection points in the twin finite element model if the actual connection force is greater than the preset target connection force; A first optimization module configured to optimize the twin finite element model in which the bolt connection points are increased in the second processing module, and delete cancelable bolt connection points; The load conditions include a bump condition and a whole vehicle torsion condition; the complex system includes a vehicle frame system, a battery pack, and a battery pack support system; and the twin finite element model includes a vehicle frame system submodel, a battery pack submodel, and a battery pack support system submodel. The method comprises the following steps: acquiring external forces of all external connection points of a target vehicle complex system under various load conditions, specifically: building a whole vehicle multi-body dynamics model of the target vehicle in multi-body dynamics software, and placing the whole vehicle multi-body dynamics model on a virtual ground; applying a first preset vertical gravity field to the whole vehicle multi-body dynamics model, and solving external forces of connection points of an assembly composed of a frame, a battery pack and a battery pack support and other system models under a bump condition; applying a second preset vertical displacement to centers of two wheels on opposite sides of the front and rear of the whole vehicle multi-body dynamics model, and applying vertical displacement constraints to the other two wheels, so as to solve connection point external forces under a whole vehicle torsion condition.

7. An electronic device, comprising: The device comprises a processor, a memory and a program or instruction stored on the memory and executable on the processor, and the program or instruction is executed by the processor to realize the steps of the bolt distribution optimization method of the automobile complex system according to any one of claims 1-5.

8. A readable storage medium, characterized by, The program or instruction is stored on the readable storage medium, and the program or instruction is executed by the processor to realize the steps of the bolt distribution optimization method of the automobile complex system according to any one of claims 1-5.

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