Vehicle body structure optimization method, device and equipment and storage medium

Abstract

The embodiment of the invention discloses a vehicle body structure optimization method and device, equipment and a storage medium, and the method comprises the steps: determining to-be-optimized vehicle body structure parameters; the vehicle body structure parameters comprise at least one of cabin temperature parameters, strength and rigidity parameters, quality parameters, noise, vibration and roughness parameters and side collision parameters; performing parameter optimization on the vehicle body structure parameters to obtain a parameter solution set; wherein the parameter solution set comprises at least one group of optimal solutions about the vehicle body structure parameters; and taking the determined optimal solution as a target parameter solution corresponding to the vehicle body structure parameter based on a determination operation for the optimal solution in the parameter solution set. According to the technical scheme, the problems that in the prior art, the analysis angle of the vehicle body structure parameters is limited, and the optimized vehicle body structure parameters have certain defects are solved, the analysis angle of the vehicle body structure parameters can be expanded, and the comprehensive performance of the optimized vehicle body structure parameters is improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of vehicle body structure analysis, and in particular, to a vehicle body structure optimization method, device, equipment and storage medium. Background Art

[0002] The body structure design is a complex engineering system, and its design process covers multiple disciplines, such as modern automobile noise, structural mechanics, and collision safety. The body structure design not only covers multiple disciplines, but also the disciplines are highly related and coupled with each other, so the body structure design is a complex multi-stage design process that requires repeated iterative optimization.

[0003] At present, the existing body structure design contents mostly analyze the body structure parameters from the perspectives of strength and stiffness, mass and NVH (Noise Vibration and Harshness). Since the analysis angles of the body structure have certain limitations, it is easy to cause the analyzed body structure parameters to have certain defects in other aspects. Summary of the invention

[0004] The embodiments of the present invention provide a vehicle body structure optimization method, device, equipment and storage medium, which can expand the analysis angle of vehicle body structure parameters and improve the comprehensive performance of optimized vehicle body structure parameters.

[0005] In a first aspect, an embodiment of the present invention provides a vehicle body structure optimization method, the method comprising:

[0006] Determine the vehicle body structure parameters to be optimized; the vehicle body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side impact parameters; perform parameter optimization on the vehicle body structure parameters to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the vehicle body structure parameters; based on the determination operation of the preferred solutions in the parameter solution set, use the determined preferred solutions as target parameter solutions corresponding to the vehicle body structure parameters.

[0007] In a second aspect, an embodiment of the present invention provides a vehicle body structure optimization device, the device comprising:

[0008] Determine the vehicle body structure parameters to be optimized; the vehicle body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side impact parameters; perform parameter optimization on the vehicle body structure parameters to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the vehicle body structure parameters; based on the determination operation of the preferred solutions in the parameter solution set, use the determined preferred solutions as target parameter solutions corresponding to the vehicle body structure parameters.

[0009] In a third aspect, an embodiment of the present invention provides a computer device, the computer device comprising:

[0010] one or more processors;

[0011] A memory for storing one or more programs;

[0012] When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle body structure optimization method described in any embodiment.

[0013] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle body structure optimization method described in any embodiment.

[0014] The technical solution provided by the embodiment of the present invention determines the body structure parameters to be optimized; the body structure parameters include: cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and at least one of side collision parameters; the body structure parameters are optimized to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the body structure parameters; based on the determination operation of the preferred solutions in the parameter solution set, the determined preferred solutions are used as the target parameter solutions corresponding to the body structure parameters. The technical solution of the embodiment of the present invention solves the problem that the existing technology has limitations on the analysis angle of body structure parameters, which easily leads to certain defects in the optimized body structure parameters. It can expand the analysis angle of body structure parameters and improve the comprehensive performance of optimized body structure parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flow chart of a vehicle body structure optimization method provided by an embodiment of the present invention;

[0016] Figure 2 is a flow chart of another vehicle body structure optimization method provided by an embodiment of the present invention;

[0017] Figure 3is a work flow chart for optimizing a vehicle body structure provided by an embodiment of the present invention;

[0018] Figure 4 is a structural schematic diagram of a vehicle body structure optimization device provided by an embodiment of the present invention;

[0019] Figure 5 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Figure 1 It is a flow chart of a vehicle body structure optimization method provided by an embodiment of the present invention. The embodiment of the present invention can be used to optimize the vehicle body structure parameters. The method can be executed by a vehicle body structure optimization device, which can be implemented by software and / or hardware.

[0022] like Figure 1 As shown, the vehicle body structure optimization method includes the following steps:

[0023] S110: Determine vehicle body structure parameters to be optimized.

[0024] Among them, the body structure parameters may be parameters related to the body structure that need to be optimized. Among them, the body structure parameters include: cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and at least one of side collision parameters. Exemplarily, the body structure parameters to be optimized may be determined by interactive operations. For example, a list of structural parameters may be displayed in a preset interactive interface, and the user may select the structural parameters to be optimized from the list through interactive operations. The device of the embodiment of the present invention then uses the determined structural parameters as the body structure parameters to be optimized based on the interactive operations.

[0025] S120: Optimizing the vehicle body structure parameters to obtain a parameter solution set.

[0026] Among them, parameter optimization can be a process of finding the optimal solution corresponding to the body structure parameters. Exemplarily, for each body structure parameter, the parameter value of the body structure parameter can be searched within the corresponding adjustable range. The parameter solution set can be a set of preferred solutions for the body structure parameters. The parameter solution set includes at least one set of preferred solutions for the body structure parameters. Specifically, after each parameter optimization, the evaluation index corresponding to the set of parameter solutions after optimization can be determined, and after the evaluation index meets the corresponding standard, the corresponding set of parameter solutions can be added to the parameter solution set.

[0027] S130. Based on the determination operation of the preferred solution in the parameter solution set, the determined preferred solution is used as the target parameter solution corresponding to the vehicle body structure parameter.

[0028] The target parameter solution may be the optimal solution for the vehicle body structure parameters that is finally determined. Specifically, the parameter solution set may include multiple sets of optimal solutions for the vehicle body structure parameters. The user may determine a set of optimal solutions from multiple sets of candidate parameter solutions through interactive operations. The device of the embodiment of the present invention may use the determined set of optimal solutions as the target parameter solution.

[0029] The technical solution provided by the embodiment of the present invention determines the body structure parameters to be optimized; the body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side impact parameters; the body structure parameters are optimized to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the body structure parameters; based on the determination operation of the preferred solution in the parameter solution set, the determined preferred solution is used as the target parameter solution corresponding to the body structure parameters. The technical solution of the embodiment of the present invention solves the problem that the existing technology has limitations in the analysis angle of the body structure parameters, which easily leads to certain defects in the optimized body structure parameters. It can expand the analysis angle of the body structure parameters and improve the comprehensive performance of the optimized body structure parameters.

[0030] Figure 2 It is another flow chart of a vehicle body structure optimization method provided by an embodiment of the present invention. The embodiment of the present invention can be suitable for optimizing the vehicle body structure parameters. Based on the above embodiment, this embodiment further illustrates how to perform parameter optimization on the vehicle body structure parameters to obtain a parameter solution set. The device can be implemented by software and / or hardware and integrated in a computer device with application development function.

[0031] like Figure 2 As shown, the vehicle body structure optimization method includes the following steps:

[0032] S210: Determine vehicle body structure parameters to be optimized.

[0033] Among them, the body structure parameters may be parameters related to the body structure that need to be optimized. Among them, the body structure parameters include: cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and at least one of side collision parameters. Exemplarily, the body structure parameters to be optimized may be determined by interactive operations. For example, a list of structural parameters may be displayed in a preset interactive interface, and the user may select the structural parameters to be optimized from the list through interactive operations. The device of the embodiment of the present invention then uses the determined structural parameters as the body structure parameters to be optimized based on the interactive operations.

[0034] Among them, the cabin temperature parameter can be the internal temperature of the vehicle's passenger compartment; further, the car will be affected by various forces during driving, so the car body must have sufficient strength to withstand the influence of these forces to ensure that the vehicle can remain stable and safe under various environmental conditions. Through numerical simulation methods such as finite element analysis, the stress conditions of the vehicle body can be simulated to obtain the stress and deformation results of each part, so as to judge whether the current structure has insufficient strength and further optimize the design; stiffness refers to the deformation and vibration of the vehicle body under different driving conditions. Stiffness optimization is improved by adjusting the body structure and material layout; the mass of the vehicle body directly affects the total weight of the vehicle. Lower body mass means better economy, improves the acceleration performance and handling of the vehicle, and also improves the braking effect and cornering performance of the vehicle. However, reducing the weight of the vehicle body also means reduced safety. Therefore, the optimization design of the vehicle body structure needs to find a balance between lightweight and safety, and the lightweight of the vehicle body is closely related to material properties; NVH stands for noise, vibration and roughness, which refers to the noise, vibration and roughness generated by the car during operation, which affects driving comfort and other issues; in the design of the vehicle body structure, side collision restraint refers to the protection measures and structural design for side collisions during driving, which involves driving safety issues.

[0035] S220: Determine at least one particle to be optimized and a transformable range corresponding to the particle to be optimized according to the vehicle body structure parameters.

[0036] The particle to be optimized may be a particle corresponding to the vehicle body structure parameter to be optimized. The particle to be optimized includes at least one optimizable dimension, and the number of optimizable dimensions is the same as the type of vehicle body structure parameter. The transformable range may be a spatial range in which the particle to be optimized can transform its position. Specifically, the spatial dimension of the transformable range is also the same as the type of vehicle body structure parameter. Furthermore, the adjustable range of each spatial dimension in the transformable range may be determined based on the adjustable range of the vehicle body structure parameter of each dimension, thereby obtaining a complete transformable range.

[0037] Among them, the position change of the particle to be optimized within the transformable range can be understood as the numerical change of the body structure parameters of different dimensions. By finding the preferred position of the particle to be optimized in the transformable range, the preferred solution for the body structure parameters can be determined. Optionally, multiple particles to be optimized can be configured for the body structure parameters, and the preferred position can be searched from the transformable range based on the multiple particles to be optimized, which can improve the efficiency of determining the preferred solution corresponding to the body structure parameters.

[0038] S230, for each particle to be optimized, iteratively transform the position of the particle to be optimized within the transformable range.

[0039] The iterative transformation may be to transform the spatial position of the particle to be optimized within the transformable range. Exemplarily, after an iterative transformation of the particle to be optimized, the evaluation index corresponding to the spatial position of the particle to be optimized may be determined. If the evaluation index meets the corresponding standard, the vehicle body structure parameter value corresponding to the spatial position may be used as a set of preferred solutions. Furthermore, based on the corresponding transformation speed and transformation distance, the position may be changed in the next transformation direction to start the next round of iterative transformation of the position.

[0040] Optionally, the particle to be optimized is iteratively transformed in position within a transformable range, including: for each iterative transformation of the particle to be optimized, determining the position density information of the particle to be optimized according to the current candidate parameter solution in the parameter solution set; determining the position transformation direction according to the position density information, and transforming the particle to be optimized in the position transformation direction.

[0041] Among them, the candidate parameter solution can be a preferred solution that already exists in the parameter solution set. The position density information can be the density information of the particle positions that exist in the parameter solution set. Specifically, the transformable range can be divided into multiple subspaces, and for each subspace, the position density information corresponding to the subspace is determined according to the number of particle positions in the subspace in the parameter solution set. The position transformation direction can be the direction of the next iterative position transformation. Exemplarily, the direction of the subspace with smaller position density can be used as the position transformation direction. By using the direction of the subspace with smaller position density as the spatial transformation direction, the particles to be optimized can traverse each sub-region in the transformable range as much as possible, thereby improving the diversity of the candidate parameter solutions.

[0042] Optionally, before iteratively transforming the particle to be optimized, the method further includes: determining a current mutation rate according to a current number of iterations of the particle to be optimized; and performing a position mutation operation on the particle to be optimized when the current mutation rate is less than a preset random value.

[0043] The current number of iterations may be the number of iterative transformations that the particle to be optimized has undergone at the current moment, and the current mutation rate may be the mutation rate of the particle to be optimized after the current iterative transformation. Specifically, the current mutation rate p m The calculation formula is as follows:

[0044]

[0045] Among them, p m,min represents the minimum mutation rate; p m,max represents the maximum mutation rate; k represents the current number of iterations; n represents the maximum number of iterations. If the mutation rate of a particle is greater than the random number rand between 0 and 1, the particle is mutated and its position is updated; otherwise, no mutation is performed and the particle speed and position are updated using the standard method.

[0046] Furthermore, the preset random value may be a preset threshold for determining the current mutation rate. Specifically, the preset random value may be randomly selected between 0 and 1. Whether a particle meets the conditions for mutation depends on the mutation rate. A larger mutation rate is used at the beginning of the iteration to increase the diversity of the population to improve the global optimization capability. As the number of iterations increases, the mutation rate gradually decreases to improve the convergence accuracy. When particles approach the historical optimal particles and appear to be seriously aggregated, particles that meet the mutation conditions are mutated to increase the diversity of the population and enhance the global optimization capability of the particles. Furthermore, when the current mutation rate is less than the preset random value, a position mutation operation is performed on the particle to be optimized. The specific mutation operations are as follows:

[0047]

[0048] c=min{b1-a1,b2-a2,...,b n -a n}

[0049] Among them, x i k represents the position of the i-th particle at the k-th iteration; represents the position of the ith particle at the k+1th iteration; rand represents a random function (here the random function uses a certain dimension as 1 and the rest are all 0, that is, only the value of a certain dimension of the particle is changed); c represents the mutation factor, and its value range is the minimum definition domain of all particles; [a t ,b t ] represents the domain of the tth parameter dimension.

[0050] Optionally, the iterative transformation operation on the position of the particle to be optimized may be stopped when the number of iterative transformations reaches a preset number threshold, or the fitness value corresponding to the particle position of the particle to be optimized is greater than a preset fitness threshold.

[0051] S240, determining a parameter solution set according to the particle positions of the particles to be optimized after each iterative transformation.

[0052] The particle position may be the spatial position of the particle to be optimized after each iterative transformation. The parameter solution set may be a set of preferred solutions for the vehicle body structure parameters. The parameter solution set includes at least one set of preferred solutions for the vehicle body structure parameters. Specifically, after each point transformation, the evaluation index corresponding to the particle to be optimized at the particle position may be determined. After the evaluation index meets the corresponding standard, the vehicle body structure parameter value corresponding to the particle position may be added to the parameter solution set as a set of preferred solutions.

[0053] Optionally, a parameter solution set is determined based on the particle position of the particle to be optimized, including: determining a current fitness corresponding to the current particle position based on the current particle position of the particle to be optimized; when the current fitness is greater than a preset fitness threshold, determining a candidate parameter solution corresponding to the current particle position, and adding the candidate parameter solution to the parameter solution set.

[0054] Among them, the current particle position may be the position of the particle to be optimized at the current moment. Specifically, the position of the optimized particle after each iterative transformation may be used as the current particle position. The current fitness may be an evaluation parameter of the vehicle body structure parameter value corresponding to the current particle position. Specifically, the method for calculating the particle fitness may be an existing fitness method, which is not limited here. Furthermore, the preset fitness threshold may be a reference threshold for evaluating the current fitness. When the current fitness is greater than the preset fitness threshold, it means that the parameter solution of the vehicle body structure parameters corresponding to the current particle position is better, so the candidate parameter solution corresponding to the current particle position may be added to the parameter solution set.

[0055] Optionally, before adding the candidate parameter solutions to the parameter solution set, it also includes: when the number of candidate parameter solutions in the parameter solution set is greater than a preset number threshold, determining the parameter solution to be deleted based on the fitness corresponding to the candidate parameter solution, and deleting the parameter solution to be deleted from the parameter solution set.

[0056] The preset number threshold may be a number threshold of candidate parameter solutions that can be stored in the parameter solution set. When the number of candidate parameter solutions in the parameter solution set is greater than the preset number threshold, a candidate parameter solution with a smaller fitness may be selected from the candidate parameter solutions as a parameter solution to be deleted, and the parameter solution to be deleted may be deleted from the parameter solution set.

[0057] S250: Based on the determination operation of the preferred solution in the parameter solution set, the determined preferred solution is used as the target parameter solution corresponding to the vehicle body structure parameter.

[0058] The target parameter solution may be the optimal solution for the vehicle body structure parameters that is finally determined. Specifically, the parameter solution set may include multiple sets of optimal solutions for the vehicle body structure parameters. The user may determine a set of optimal solutions from multiple sets of candidate parameter solutions through interactive operations. The device of the embodiment of the present invention may use the determined set of optimal solutions as the target parameter solution.

[0059] For illustrative purposes, in order to better understand the technical solution provided by the present invention, specific embodiments are introduced below. Figure 3 FIG. 1 is a flowchart of a vehicle body structure optimization process provided by an embodiment of the present invention. Figure 3 As shown in the figure, the workflow for body structure optimization includes the following steps:

[0060] (1) Initialization parameters

[0061] Initialize the particle swarm and related parameters;

[0062] (2) Calculate fitness and create rep set

[0063] Calculate the fitness vector of the initialized particles, and use the concept of domination to select the non-dominated solutions among the initial particles, that is, the better solutions, and add them to the rep set. The fitness of the particle swarm is expressed in the form of a vector according to the number of objective functions. Single values ​​can be easily compared, but in this algorithm, the way to compare the sizes of vectors uses the concept of domination: Domination: When S_i and S_j meet the following two conditions, S_i is said to dominate S_j:

[0064] Condition 1: For all objective functions S_i is not worse than S_j;

[0065] Condition 2: On at least one objective function, S_i is strictly better than S_j.

[0066] Example: S_i = [1,2,3,4], S_j = [1,2,5,4]

[0067] Each value of S_i is less than or equal to the corresponding value of S_j (satisfying the first condition);

[0068] The third value of S_i is strictly smaller than the third value of S_j (satisfying the second condition);

[0069] S_i dominates S_j, which means S_i is better than S_j.

[0070] (3) Calculate the particle density information of the rep set

[0071] The density evaluation technology used is to divide the target space into small areas with a grid, and use the number of particles contained in each area as the density information of the particles. The more particles contained in the grid where the particle is located, the greater its density value, and vice versa.

[0072] (4) Select the global optimum in the rep set

[0073] The quality of the global optimal particle determines the convergence performance of the MOPSO algorithm and the diversity of the non-inferior solution set. Its selection is based on the density information of the particles in the rep set. Specifically, for the particles in the rep set, the lower the density value, the greater the probability of selection, and vice versa.

[0074] (5) Update particle position and velocity

[0075] Update the particle velocity according to the current global optimum, local optimum and particle velocity; update the particle position using the updated particle velocity.

[0076] (6) Calculate fitness

[0077] Recalculate the fitness vector after updating the particle position.

[0078] (7) Update individual optimality

[0079] The updated particle is the best individual of the current particle. Use the concept of dominance to compare and select the dominant solution (the dominant solution is better than the dominated solution) as the new best individual. If there is no dominance relationship between the two, a random number method is used to select them randomly.

[0080] (8) Update the rep set and truncate it

[0081] The updated particles and the current rep set are combined into a new solution set. Using the concept of domination, the dominating set is selected as the new rep set, that is, the rep set is updated. The rep set cannot be stored infinitely. The maximum storage quantity of the rep set needs to be preset in advance. If the number in the current rep set exceeds the upper limit, a truncation operation is required, and the excess part can be randomly deleted until the number in the rep set is equal to the upper limit.

[0082] The technical solution of the embodiment of the present invention optimizes the design of the vehicle body structure from multiple angles, and adds thermal management content on the basis of common factors such as vehicle body mass, NVH and side collision. That is, when using a multidisciplinary optimization design method to comprehensively consider various aspects of the vehicle's performance, additional consideration is given to aspects such as vehicle heat dissipation and controlling the passenger compartment temperature within a specified range in steady state, so as to achieve the purpose of synergistically optimizing the vehicle's power, economy, safety, thermal management, energy consumption and many other aspects.

[0083] The technical solution provided by the embodiment of the present invention determines the body structure parameters to be optimized; the body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side collision parameters; according to the body structure parameters, at least one particle to be optimized and the transformable range corresponding to the particle to be optimized are determined; wherein the particle to be optimized includes at least one optimizable dimension, and the number of optimizable dimensions is the same as the type of body structure parameters; for each particle to be optimized, the particle to be optimized is iteratively transformed in position within the transformable range; according to the particle position of the particle to be optimized after each iterative transformation, the parameter solution set is determined; based on the determination operation of the optimal solution in the parameter solution set, the determined optimal solution is used as the target parameter solution corresponding to the body structure parameters. The technical solution of the embodiment of the present invention solves the problem that the existing technology has limitations in the analysis angle of the body structure parameters, which easily leads to certain defects in the optimized body structure parameters, and can expand the analysis angle of the body structure parameters and improve the comprehensive performance of the optimized body structure parameters.

[0084] Figure 4 It is a structural schematic diagram of a vehicle body structure optimization device provided by an embodiment of the present invention. The embodiment of the present invention can be used to optimize the vehicle body structure parameters. The device can be implemented by software and / or hardware and integrated into a computer device with application development function.

[0085] like Figure 4 As shown, the vehicle body structure optimization device includes: a road information acquisition module 310 , a control parameter determination module 320 and a control parameter determination module 330 .

[0086] Among them, the body structure parameter determination module 310 is used to determine the body structure parameters to be optimized; the body structure parameters include: cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and at least one of side collision parameters; the parameter solution set determination module 320 is used to perform parameter optimization on the body structure parameters to obtain a parameter solution set; wherein the parameter solution set includes at least one group of preferred solutions for the body structure parameters; the target parameter solution determination module 330 is used to determine the preferred solution as the target parameter solution corresponding to the body structure parameters based on the determination operation of the preferred solution in the parameter solution set.

[0087] The technical solution provided by the embodiment of the present invention determines the body structure parameters to be optimized; the body structure parameters include: cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and at least one of side collision parameters; the body structure parameters are optimized to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the body structure parameters; based on the determination operation of the preferred solutions in the parameter solution set, the determined preferred solutions are used as the target parameter solutions corresponding to the body structure parameters. The technical solution of the embodiment of the present invention solves the problem that the existing technology has limitations on the analysis angle of body structure parameters, which easily leads to certain defects in the optimized body structure parameters. It can expand the analysis angle of body structure parameters and improve the comprehensive performance of optimized body structure parameters.

[0088] In an optional embodiment, the parameter solution set determination module 320 is specifically used to: determine at least one particle to be optimized and a transformable range corresponding to the particle to be optimized according to the vehicle body structure parameters; wherein the particle to be optimized includes at least one optimizable dimension, and the number of the optimizable dimensions is the same as the type of the vehicle body structure parameters; for each particle to be optimized, iteratively transform the position of the particle to be optimized within the transformable range; and determine the parameter solution set according to the particle position of the particle to be optimized after each iterative transformation.

[0089] In an optional embodiment, the parameter solution set determination module 320 includes: a particle position analysis unit, used to: determine the current fitness corresponding to the current particle position according to the current particle position of the particle to be optimized; when the current fitness is greater than a preset fitness threshold, determine the candidate parameter solution corresponding to the current particle position, and add the candidate parameter solution to the parameter solution set.

[0090] In an optional embodiment, the parameter solution set determination module 320 includes: a position iterative transformation unit, which is used to: determine the position density information of the particle to be optimized according to the current candidate parameter solution in the parameter solution set for each iterative transformation of the particle to be optimized; determine the position transformation direction according to the position density information, and make the particle to be optimized change its position in the position transformation direction.

[0091] In an optional embodiment, the parameter solution set determination module 320 also includes: a variation analysis unit, which is used to: determine a current variation rate according to a current number of iterations of the particle to be optimized; and perform a position variation operation on the particle to be optimized when the current variation rate is less than a preset random value.

[0092] In an optional embodiment, the parameter solution set determination module 320 also includes: an iteration number management unit, which is used to stop the iterative change operation on the position of the particle to be optimized when the number of iterative transformations reaches a preset threshold number, or the fitness value corresponding to the particle position of the particle to be optimized is greater than a preset fitness threshold.

[0093] In an optional embodiment, the vehicle body structure optimization device also includes: a parameter solution quantity management module, which is used to: before adding the candidate parameter solution to the parameter solution set, when the number of candidate parameter solutions in the parameter solution set is greater than a preset quantity threshold, determine the parameter solution to be deleted based on the fitness corresponding to the candidate parameter solution, and delete the parameter solution to be deleted from the parameter solution set.

[0094] The vehicle body structure optimization device provided in the embodiment of the present invention can execute the vehicle body structure optimization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Figure 5 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Figure 5 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 5 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention. The computer device 12 can be any terminal device with computing capability and can be configured in the vehicle body structure optimization device.

[0096] like Figure 5 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0097] The bus 18 may be one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0098] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0099] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0100] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0101] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed through an input / output (I / O) interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 20. Figure 5 As shown, the network adapter 20 communicates with other modules of the computer device 12 via the bus 18. It should be understood that although Figure 5 Not shown, other hardware and / or software modules may be used in conjunction with computer device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0102] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the vehicle body structure optimization method provided by the embodiment of the present invention, the method comprising:

[0103] Determine the vehicle body structure parameters to be optimized; the vehicle body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side impact parameters; perform parameter optimization on the vehicle body structure parameters to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the vehicle body structure parameters; based on the determination operation of the preferred solutions in the parameter solution set, use the determined preferred solutions as target parameter solutions corresponding to the vehicle body structure parameters.

[0104] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the vehicle body structure optimization method provided by any embodiment of the present invention is implemented, including:

[0105] Determine the vehicle body structure parameters to be optimized; the vehicle body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side impact parameters; perform parameter optimization on the vehicle body structure parameters to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the vehicle body structure parameters; based on the determination operation of the preferred solutions in the parameter solution set, use the determined preferred solutions as target parameter solutions corresponding to the vehicle body structure parameters.

[0106] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0107] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0108] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0109] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or combinations thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0110] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0111] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A vehicle body structure optimization method, characterized in that: include: Determine the body structure parameters to be optimized; The vehicle body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side impact parameters; Performing parameter optimization on the vehicle body structure parameters to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the vehicle body structure parameters; Based on the determination operation of the preferred solution in the parameter solution set, the determined preferred solution is used as the target parameter solution corresponding to the vehicle body structure parameter.

2. The method according to claim 1, characterized in that The step of performing parameter optimization on the vehicle body structure parameters to obtain a parameter solution set includes: According to the vehicle body structure parameters, at least one particle to be optimized and a transformable range corresponding to the particle to be optimized are determined; wherein the particle to be optimized includes at least one optimizable dimension, and the number of the optimizable dimensions is the same as the type of the vehicle body structure parameters; For each particle to be optimized, iteratively transform the position of the particle to be optimized within the transformable range; The parameter solution set is determined according to the particle position of the particle to be optimized after each iterative transformation.

3. The method according to claim 2, characterized in that Determining the parameter solution set according to the particle position of the particle to be optimized includes: According to the current particle position of the particle to be optimized, determining the current fitness corresponding to the current particle position; When the current fitness is greater than a preset fitness threshold, a candidate parameter solution corresponding to the current particle position is determined, and the candidate parameter solution is added to the parameter solution set.

4. The method according to claim 2, characterized in that: The iterative transformation of the position of the particle to be optimized within the transformable range comprises: For each iterative transformation of the particle to be optimized, determining the position density information of the particle to be optimized according to the current candidate parameter solution in the parameter solution set; The position change direction is determined according to the position density information, and the particle to be optimized is caused to change position in the position change direction.

5. The method according to claim 2, characterized in that: Before iteratively transforming the particles to be optimized, the method further includes: Determine the current mutation rate according to the current number of iterations of the particle to be optimized; When the current mutation rate is less than a preset random value, a position mutation operation is performed on the particle to be optimized.

6. The method according to claim 2, characterized in that The method further comprises: When the number of iterative transformations reaches a preset number threshold, or the fitness value corresponding to the particle position of the particle to be optimized is greater than the preset fitness threshold, the iterative transformation operation on the position of the particle to be optimized is stopped.

7. The method according to claim 3, characterized in that Before adding the candidate parameter solution to the parameter solution set, the method further includes: When the number of candidate parameter solutions in the parameter solution set is greater than a preset number threshold, a parameter solution to be deleted is determined based on the fitness corresponding to the candidate parameter solutions, and the parameter solution to be deleted is deleted from the parameter solution set.

8. A vehicle body structure optimization device, characterized in that: The device comprises: A vehicle body structure parameter determination module, used to determine the vehicle body structure parameters to be optimized; the vehicle body structure parameters include: at least one of cabin temperature parameters, strength and stiffness parameters, mass parameters, noise and vibration and roughness parameters, and side impact parameters; A parameter solution set determination module, used for performing parameter optimization on the body structure parameters to obtain a parameter solution set; wherein the parameter solution set includes at least one set of preferred solutions for the body structure parameters; The target parameter solution determination module is used to determine the optimal solution in the parameter solution set based on the determination operation of the optimal solution as the target parameter solution corresponding to the vehicle body structure parameter.

9. A computer device, characterized in that: The computer device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle body structure optimization method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the vehicle body structure optimization method as described in any one of claims 1 to 7 is implemented.

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