CN116341092A - Frame cross beam optimization method and system, cross beam and vehicle - Google Patents
Frame cross beam optimization method and system, cross beam and vehicle Download PDFInfo
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Abstract
The application relates to a frame cross beam optimization method, and relates to the field of automobile optimization. It comprises the following steps: decomposing the CAD model of the whole vehicle into a beam model and a residual model; establishing a finite element model according to the residual model, and performing reduced-order processing on the finite element model to obtain a reduced-order model; establishing a full-parameterized beam model according to the beam model, and realizing non-spatial assembly of the full-parameterized beam model and the residual model through a node ID number corresponding relation to obtain an assembly model; applying the whole vehicle working condition on the working condition applying point according to the node ID number to obtain a working condition model, wherein the whole vehicle working condition comprises a torsion working condition and a bending working condition; loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result; queuing the optimization result, and leading out a visual comparison result. The invention solves the problem that structural design engineers cannot directly optimize variable design by parameters.
Description
Technical Field
The application relates to the field of automobile optimization, in particular to a method and a system for optimizing a frame cross beam, the cross beam and a vehicle.
Background
In the design process of the prior frame cross beam, the structural design engineer of the prior frame cross beam can not directly obtain the parameter optimization variable of the frame cross beam, and the prior frame cross beam needs to be frequently communicated with CAE simulation personnel of the frame cross beam so as to optimize the frame cross beam according to the optimization parameters provided by the CAE simulation personnel, thereby meeting the frame cross beam design requirement of the whole vehicle.
In the above prior art, a great deal of time is required to be consumed in the process of frequently communicating with CAE simulation personnel of the frame cross member by structural design engineers of the frame cross member, so that the efficiency of the existing frame cross member optimization method is low, and therefore, improvement is necessary.
Disclosure of Invention
The embodiment of the application provides a vehicle frame beam optimization method, which aims to solve the problem that the efficiency of the existing vehicle frame beam optimization method is low.
In a first aspect, a method of optimizing a cross frame member is provided, comprising: decomposing the CAD model of the whole vehicle into a beam model and a residual model; establishing a finite element model according to the residual model, and performing reduced order processing on the finite element model to obtain a reduced order model; establishing a full-parameterized beam model according to the beam model, and realizing non-spatial assembly of the full-parameterized beam model and the reduced model through a node ID number corresponding relation to obtain an assembly model; applying a whole vehicle worker to the assembly model on the working condition applying point according to the node ID number to obtain a working condition model; loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result; and generating an optimized cross beam optimization model according to the optimization result.
In some embodiments, the decomposing the CAD model of the whole vehicle into the beam model and the remaining model includes: removing all cross beams in the whole CAD model from the whole CAD model to obtain a cross beam model; labeling the hole sites of the longitudinal beam and the transverse beam in the CAD model of the whole vehicle to obtain labeled hole sites; and the marked hole site and the part except the beam model in the CAD model of the whole vehicle are used as the residual model.
In some embodiments, the reduced order model is used to reflect the stiffness matrix, mass matrix, damping matrix and modal shape relationship between the beam external connection node and the working condition loading node.
In some embodiments, the non-spatial assembly of the fully parameterized beam model and the remaining model is implemented by a node ID number correspondence, to obtain an assembly model, including: classifying the full-parameterized beam model according to the topological connection relationship to obtain a plurality of CAD parameterized models; automatically establishing a plurality of CAD parameterized models according to a set grid division standard to obtain a beam finite element model through secondary development; identifying the mounting direction of the cross beam, and renumbering the central node of the bolt mounting hole of the cross beam according to the bolt mounting node numbering rule of the direction longitudinal beam to obtain a node ID number; according to the node algorithm relation, the beam finite element model and the reduced order model are assembled in a non-space mode through the same node ID number, and an assembly model is obtained.
In some embodiments, loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result includes: optimizing parameters in the full-parameterized beam model, and taking the parameters in the full-parameterized beam model as optimization variables; loading the optimization variable, the beam stress response and the beam mass response into the working condition model to obtain an optimization result.
In some embodiments, the applying the working condition of the whole vehicle to the assembly model at the working condition applying point according to the node ID number to obtain the working condition model further includes: identifying loading positions of a front axle and a rear axle or a saddle through a preset working condition loading point numbering rule; and loading the loading position onto a loading node of the working condition model through a preset loading rule according to the working condition set by a design engineer to obtain the working condition model.
In some embodiments, the generating an optimized beam optimization model according to the optimization result includes: sequencing the optimized results according to a preset result arrangement rule to obtain sequencing results; and determining final parameters of the cross beam according to the sorting result, and automatically generating an optimized CAD model according to the final parameters of the cross beam.
In a second aspect, the present invention provides a frame rail optimization system comprising: the model decomposition module is used for decomposing the CAD model of the whole vehicle into a beam model and a residual model; the reduced order processing module is used for establishing a finite element model according to the residual model, and performing reduced order processing on the finite element model to obtain a reduced order model; the assembly processing module is used for establishing a full-parameterized beam model according to the beam model, and realizing non-spatial assembly of the full-parameterized beam model and the reduced order model through a node ID number corresponding relation to obtain an assembly model; the working condition loading module is used for applying the whole vehicle working condition to the assembly model on the working condition applying point according to the node ID number to obtain a working condition model; the optimization processing module is used for loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result; and the model regeneration module is used for generating an optimized cross beam optimization model according to the optimization result.
In a third aspect, the present invention provides a cross member optimized by the frame cross member optimization method.
In a fourth aspect, the invention provides a vehicle comprising the cross beam.
The embodiment of the application provides a method, a system, a cross beam and a vehicle for optimizing a cross beam, which comprise the steps of obtaining a cross beam model, a residual model, a reduced order model, an assembly model, a working condition model, an optimization result and a cross beam optimization model, wherein after the cross beam optimization model is obtained, a structural design engineer of the cross beam can optimize the cross beam only by the cross beam corresponding to the optimization parameters in the cross beam optimization model, so that the structural design engineer of the cross beam can independently complete parameter optimization variable design and optimization treatment on the cross beam, the communication time between the structural design engineer and CAE simulation personnel is reduced, and the production efficiency is improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for optimizing a cross beam of a vehicle frame according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present application based on the embodiments herein.
The embodiment of the application provides a vehicle frame cross beam optimization method, which can solve the problem that engineers cannot directly optimize variable design by parameters in related technologies. It should be noted that, if there are substantially the same results, the method of the present invention is not limited to the flow sequence shown in fig. 1.
As shown in fig. 1, the frame cross member optimization method includes:
s1, decomposing a CAD model of the whole vehicle into a beam model and a residual model;
the step of decomposing the CAD model of the whole vehicle into a beam model and a residual model comprises the following steps: s11, removing all cross beams in the whole CAD model from the whole CAD model to obtain a cross beam model; s12, labeling the hole sites of the longitudinal beam and the transverse beam in the CAD model of the whole vehicle to obtain labeled hole sites; and S13, the marked hole site and the part except the beam model in the CAD model of the whole vehicle are used as the residual model.
In actual operation, in all planned vehicle types, several basic vehicle types are selected according to market demands, or new vehicle types are required to be developed, all beam models are removed from developed CAD models of the whole vehicle to obtain residual models, and meanwhile, hole sites of the longitudinal beams and the beam links are subjected to labeling treatment, wherein the distance between upper holes and lower holes is generally a multiple of 30mm, and the distance between front holes and rear holes is generally a multiple of 50 mm.
In actual operation, the numbers of the bolt hole nodes linked with the cross beam in the remaining models are renumbered, and the rule of the numbers is a four-digit number starting with 1, such as 1001, 1002 and the like. The odd number is the node number of the bolt connection point of the left longitudinal beam in the CAD model of the whole vehicle, and the even number is the node number of the bolt connection point of the right longitudinal beam in the CAD model of the whole vehicle. The pitch hole pitch is one bit after the node numbering, and when the pitch hole pitch is twice the standard pitch hole pitch, the node numbering is two bits. The operating mode loading point (e.g., tire ground point, saddle loading point for a tractor, etc.), for example, the node number starts at 1 and ends at 100.
S2, establishing a finite element model according to the residual model, and performing reduced-order processing on the finite element model to obtain a reduced-order model;
in actual operation, a CAE finite element model is built on the basis of the step S1, and the CAE finite element model fully comprises all models (and the rest models) except the cross beam, including finite element models of the upper part, the plate spring, the axle, the tire and the like.
In actual operation, the model after the reduced order processing (namely the reduced order model) is used for reflecting the relation among the rigidity matrix, the quality matrix, the damping matrix and the mode vibration mode between the external joint of the cross beam and the working condition loading joint.
S3, establishing a full-parameterized beam model according to the beam model, and realizing non-spatial assembly of the full-parameterized beam model and the reduced order model through a node ID number corresponding relation to obtain an assembly model;
in actual operation, the steps for obtaining the assembly model comprise: s31, classifying the full-parameterized beam model according to the topological connection relation to obtain a plurality of CAD parameterized models; s32, automatically establishing a plurality of CAD parameterized models into finite element models according to established grid division standards through secondary development to obtain a beam finite element model; s33, identifying the mounting direction of the cross beam, and renumbering a central node of a bolt mounting hole of the cross beam according to a bolt mounting node numbering rule of the direction longitudinal beam to obtain a node ID number; s34, according to the node algorithm relation, the beam finite element model and the reduced order model are assembled in a non-space mode through the same node ID number, and an assembly model is obtained.
In actual operation, the invention establishes a full-parameterized beam model through parameterization modeling and classifies according to topological connection relations. Through secondary development, the CAD parameterized model is automatically built into a finite element model according to a set grid division standard, and re-grid division is automatically performed according to parameter changes, so that the condition that grid quality is invalid due to deformation of the grid size of finite element software or the stress average value is inconsistent due to grid size change (namely, the stress value gradually increases and approaches to a numerical value along with grid reduction) is avoided.
S4, applying the whole vehicle working condition to the assembly model on the working condition applying point according to the node ID number to obtain a working condition model;
in actual operation, the step of obtaining the working condition model comprises the following steps: s41, identifying loading positions of a front axle and a rear axle or a saddle through a preset working condition loading point numbering rule; s42, loading the loading position onto a loading node of the working condition model through a preset loading rule according to the working condition set by a design engineer, so as to obtain the working condition model.
S5, loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result;
in actual operation, the step of obtaining the optimization result comprises the following steps: s51, optimizing parameters in the full-parameterized beam model, and taking the parameters in the full-parameterized beam model as optimization variables; s52, loading the optimization variables, the beam stress response and the beam mass response into the working condition model to obtain an optimization result.
In order to make the optimization result better, the step further comprises:
k1, identifying the mounting direction of the cross beam through secondary development, renumbering the central node of the bolt mounting hole of the cross beam according to the bolt mounting node numbering rule of the direction longitudinal beam, and automatically adjusting the node number along with the change of the front and rear mounting positions of the cross beam;
and K2, according to the node algorithm relation, the cross beam and the longitudinal beam are automatically assembled through the same node ID number, and node coordinate superposition in a physical sense is not required to be truly realized. The process of coordinate adjustment by the design engineer is reduced.
Furthermore, in step K2, a plurality of beams may be introduced, and the system may automatically close and open the opening and closing of a certain beam according to the occupation condition of the node, and load or unload a certain beam in sequence. Thereby realizing DOE simulation analysis of the multi-beam connection structure.
Furthermore, in the step K2, the invention can also comprise a multi-model optimization scheme, namely the invention can generate reduced order models of various basic whole vehicles, a single beam connecting structure can be simultaneously displayed on a plurality of positions of a plurality of vehicle types, and the change of optimized variable parameters is kept consistent in the optimization process so as to keep the consistency of the beam models of the plurality of positions in the plurality of vehicle types.
S6, generating an optimized cross beam optimization model according to the optimization result.
In actual operation, the step of obtaining the beam optimization model comprises the following steps: s61, sorting the optimized results according to a preset result arrangement rule to obtain sorting results; s62, determining final parameters of the cross beam according to the sorting result, and automatically generating an optimized CAD model according to the final parameters of the cross beam.
In actual operation, the invention can list the identified CAD model parameters, and allow a design engineer (such as a structural engineer) to confirm, and finally, the design engineer is used as an optimization variable, and the beam stress response and the beam mass response are automatically loaded for the self-contained response of the system. The design engineer (e.g., structural engineer) may set the stress constraint value by itself based on the beam material, may set the mass constraint value by itself based on the mass target, or may set the mass to an optimal target value. Meanwhile, a design engineer can set torsional rigidity constraint, hope to remove rigidity constraint, modal shape constraint and the like according to torsional rigidity and bending rigidity of the same type of vehicle model.
When the system is in actual work, after the optimization process is finished, the system automatically sorts analysis results, and a design engineer can sort according to design quality, stress and the like. Aiming at each optimized result, the applicability of each beam connection structure and the influence of each parameter change on the result are subjected to curves, curved surfaces or column diagrams, so that the influence of each parameter on the result is more intuitively shown;
when the vehicle frame design engineer actually works, after determining final parameters of the cross beam, software automatically generates a final CAD model with parameters according to the final determined parameters, and the CAD model can be directly called and assembled by the vehicle frame design engineer.
In a second aspect, as shown in FIG. 1, a second embodiment of the present invention provides a frame rail optimization system comprising:
the model decomposition module is used for decomposing the CAD model of the whole vehicle into a beam model and a residual model;
the reduced order processing module is used for establishing a finite element model according to the residual model, and performing reduced order processing on the finite element model to obtain a reduced order model;
the assembly processing module is used for establishing a full-parameterized beam model according to the beam model, and realizing non-spatial assembly of the full-parameterized beam model and the reduced order model through a node ID number corresponding relation to obtain an assembly model;
the working condition loading module is used for applying the whole vehicle working condition to the assembly model on the working condition applying point according to the node ID number to obtain a working condition model;
the optimization processing module is used for loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result;
for specific limitations on the frame rail optimization system, reference may be made to the limitations of the frame rail optimization method hereinabove, and no further description is given herein. The various modules in the frame rail optimization system described above may be implemented in whole or in part in software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In a third aspect, the invention also provides a vehicle frame cross beam, which is obtained after the vehicle frame cross beam is optimized by the vehicle frame cross beam optimization method.
In a fourth aspect, the present invention also provides a vehicle comprising the frame rail.
In actual operation, compared with the prior art, the invention has the following effective effects:
1. the problem that a structural design engineer cannot directly optimize variable design by parameters is solved, the CAD design engineer can directly operate by hands and autonomously complete the optimization process, so that time consumption generated by communication with CAE simulation personnel and information asymmetry generated by communication are avoided;
2. the traditional vehicle frame beam simulation model comprises external models such as vehicle frame beams and the like, has poor pertinence, realizes model reduction except for the vehicle frame beams through the related technology, greatly reduces the degree of freedom of an analyzed model, and can vacate calculation resources for algorithms consuming more resources such as nonlinear analysis optimization, global optimization and the like;
3. because of the related limitation of CAE software, the optimization parameters cannot realize full parameterization, such as the relation setting of the number change of beam mounting holes and the length of the beam in the front-rear direction, and the like, the optimization parameters can be set in CAD software, and the variables can be set by using knowledge engineering tools in the CAD software, so that the full parameterization design concept is truly realized, and the optimization schemes are more diversified for design engineers to select;
4. the working condition loading is applied through external joint points such as tires, saddles (tractors) and the like, the working condition is more real, the working condition can be changed according to the working condition characteristics of real vehicle types, and the use is more flexible;
5. the whole vehicle reduced order model comprises matrix parameters such as rigidity, damping, quality and the like of a beam mounting point and a working condition loading point under the comprehensive action of important components such as a tire, a leaf spring, a suspension, an upper mounting and the like, and the beam is optimized in the real whole vehicle mounting environment and is closer to reality;
6. the position of the cross beam is judged by using a node algorithm relationship for the first time, so that the front and rear position coordinates of the cross beam are optimized, and the arrangement sequence of the cross beam from front to rear becomes an optimized variable, and the full-parameterized optimization is more comprehensively embodied;
7. according to the model library data, beam scheme selection in various connection structure forms can be provided for frames of all vehicle types, and local optimal solutions under a single beam structure are avoided.
8. The influence relation curves of the single parameter or the multiple parameter changes on the stress change, the weight change and the rigidity change of the whole vehicle can be output, so that a designer can directly know the influence of each parameter change, and an experience foundation is laid for design standardization;
9. in the aspects of universalization and modularized design, the optimization modules such as MMO and the like can improve the universalization and modularization of the same frame cross beam structure of the frame according to the same parameter variable values of the same cross beam structure and the same optimization results of different vehicle types and different frame parts;
10. report composition, guide design, generate the visual parameters of most concern to the design engineer to influence the result trend.
In the description of the present application, it should be noted that the azimuth or positional relationship indicated by the terms "upper", "lower", etc. are based on the azimuth or positional relationship shown in the drawings, and are merely for convenience of description of the present application and simplification of the description, and are not indicative or implying that the apparatus or element in question must have a specific azimuth, be configured and operated in a specific azimuth, and thus should not be construed as limiting the present application. Unless specifically stated or limited otherwise, the terms "mounted," "connected," and "coupled" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art as the case may be.
It should be noted that in this application, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is merely a specific embodiment of the application to enable one skilled in the art to understand or practice the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of optimizing a cross member of a vehicle frame, comprising:
decomposing the CAD model of the whole vehicle into a beam model and a residual model;
establishing a finite element model according to the residual model, and performing reduced order processing on the finite element model to obtain a reduced order model;
establishing a full-parameterized beam model according to the beam model, and realizing non-spatial assembly of the full-parameterized beam model and the reduced model through a node ID number corresponding relation to obtain an assembly model;
applying the whole vehicle working condition to the assembly model on the working condition applying point according to the node ID number to obtain a working condition model;
loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result;
and generating an optimized cross beam optimization model according to the optimization result.
2. The frame rail optimization method of claim 1, wherein:
decomposing the CAD model of the whole vehicle into a beam model and a residual model comprises the following steps:
removing all cross beams in the whole CAD model from the whole CAD model to obtain a cross beam model;
labeling the hole sites of the longitudinal beam and the transverse beam in the CAD model of the whole vehicle to obtain labeled hole sites;
and the marked hole site and the part except the beam model in the CAD model of the whole vehicle are used as the residual model.
3. The frame rail optimization method of claim 1, wherein:
the reduced order model is used for reflecting the relation among the rigidity matrix, the mass matrix, the damping matrix and the mode vibration mode between the external joint of the beam and the working condition loading joint.
4. The frame rail optimization method of claim 1, wherein:
the non-space assembly of the full parameterized beam model and the residual model is realized through a node ID number corresponding relation to obtain an assembly model, which comprises the following steps:
classifying the full-parameterized beam model according to the topological connection relationship to obtain a plurality of CAD parameterized models;
automatically establishing a plurality of CAD parameterized models according to a set grid division standard to obtain a beam finite element model through secondary development;
identifying the mounting direction of the cross beam, and renumbering the central node of the bolt mounting hole of the cross beam according to the bolt mounting node numbering rule of the direction longitudinal beam to obtain a node ID number;
according to the node algorithm relation, the beam finite element model and the reduced order model are assembled in a non-space mode through the same node ID number, and an assembly model is obtained.
5. The frame rail optimization method of claim 1, wherein:
loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result, wherein the method comprises the following steps:
optimizing parameters in the full-parameterized beam model, and taking the parameters in the full-parameterized beam model as optimization variables;
loading the optimization variable, the beam stress response and the beam mass response into the working condition model to obtain an optimization result.
6. The frame rail optimization method of claim 5, wherein:
the method for applying the whole vehicle working condition to the assembly model on the working condition applying point according to the node ID number to obtain the working condition model comprises the following steps:
identifying loading positions of a front axle and a rear axle or a saddle through a preset working condition loading point numbering rule;
and loading the loading position onto a loading node of the working condition model through a preset loading rule according to the working condition set by a design engineer to obtain the working condition model.
7. The frame rail optimization method of claim 1, wherein:
the generating an optimized beam optimization model according to the optimization result comprises the following steps:
sequencing the optimized results according to a preset result arrangement rule to obtain sequencing results;
and determining final parameters of the cross beam according to the sorting result, and automatically generating an optimized CAD model according to the final parameters of the cross beam.
8. A frame rail optimization system, characterized by:
the model decomposition module is used for decomposing the CAD model of the whole vehicle into a beam model and a residual model;
the reduced order processing module is used for establishing a finite element model according to the residual model, and performing reduced order processing on the finite element model to obtain a reduced order model;
the assembly processing module is used for establishing a full-parameterized beam model according to the beam model, and realizing non-spatial assembly of the full-parameterized beam model and the reduced order model through a node ID number corresponding relation to obtain an assembly model;
the working condition loading module is used for applying the whole vehicle working condition to the assembly model on the working condition applying point according to the node ID number to obtain a working condition model;
the optimization processing module is used for loading the whole vehicle optimization variable, the corresponding constraint and the optimization target into the working condition model to obtain an optimization result;
and the model regeneration module is used for generating an optimized cross beam optimization model according to the optimization result.
9. A cross member, wherein the cross member is optimized by the frame cross member optimization method of any one of claims 1-7.
10. A vehicle comprising the cross beam of claim 9.
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| CN202211216355.5A CN116341092A (en) | 2022-09-30 | 2022-09-30 | Frame cross beam optimization method and system, cross beam and vehicle |
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