CN112417608A - Vehicle door model construction method and system, electronic device and storage medium - Google Patents
Vehicle door model construction method and system, electronic device and storage medium Download PDFInfo
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Abstract
The invention discloses a vehicle door model construction method and system, electronic equipment and a storage medium, wherein the vehicle door model construction method comprises the following steps: obtaining an initial vehicle door model, wherein the initial vehicle door model comprises vehicle door component parameters; obtaining influence parameters of the fatigue life of the vehicle door from the parameters of the vehicle door parts, wherein the influence parameters comprise quality parameters and non-quality parameters; obtaining a first optimization objective function according to the quality parameters, and obtaining a second optimization objective function according to the quality parameters and the non-quality parameters; and taking a preset vehicle door rigidity condition as a constraint condition, and carrying out parameter optimization on the vehicle door component parameters of the initial vehicle door model according to the first optimization objective function, the second optimization objective function and the constraint condition to establish a vehicle door model. The influence of the first optimization objective function and the second optimization objective function on the parameters of the vehicle door component is considered at the same time, so that the optimized vehicle door structure can meet the requirements of two aspects.
Description
Technical Field
The invention relates to the technical field of automobile engineering, in particular to a method and a system for designing and constructing a vehicle door structure, electronic equipment and a storage medium.
Background
At present, the light weight of automobiles becomes one of important research directions in the field of automobile research, and the light weight puts higher requirements on the fatigue durability and the safety performance of the automobiles. In recent years, a lot of researches on automobile door lightweight are carried out by many scholars at home and abroad, and a lot of research results are obtained, generally, a door lightweight design method mainly takes dimensional parameters such as thickness of a sheet metal part as design variables, carries out optimization design with the aim of minimum quality, verifies the reliability of the optimization design through fatigue strength, and has a long development period. In addition, the influence of non-quality parameters such as dimensional parameter changes of components and quality parameters such as the quality of door accessories on the fatigue life of the door is not considered in the conventional door light weight design, so that the performance of the door obtained by the door light weight design cannot meet the manufacturing requirement of the door.
Disclosure of Invention
The present disclosure provides a vehicle door model building method and system, an electronic device, and a storage medium to solve the deficiencies in the related art.
Obtaining an initial vehicle door model, wherein the initial vehicle door model comprises vehicle door component parameters;
obtaining influence parameters of the fatigue life of the vehicle door from the parameters of the vehicle door parts, wherein the influence parameters comprise quality parameters and non-quality parameters;
obtaining a first optimization objective function according to the quality parameters, and obtaining a second optimization objective function according to the quality parameters and the non-quality parameters;
taking a preset vehicle door rigidity condition as a constraint condition, and performing parameter optimization on the vehicle door component parameters of the initial vehicle door model according to the first optimization objective function, the second optimization objective function and the constraint condition to obtain optimized vehicle door component parameters;
and establishing a vehicle door model according to the initial vehicle door model and the optimized vehicle door component parameters.
In some embodiments, said obtaining a first optimization objective function based on said quality parameter comprises:
obtaining a quality expression of the quality parameter, wherein the quality expression is used for indicating to obtain the quality corresponding to the quality parameter;
accumulating the quality expression to obtain a first function;
determining the first optimization objective function according to the minimum value of the first function.
In some embodiments, said deriving a second optimization objective function from said quality parameter and said non-quality parameter comprises:
acquiring a first fatigue life corresponding to the quality parameter and a second fatigue life of the non-quality parameter;
determining an influence parameter with the minimum fatigue life according to the minimum value of the first fatigue life and the minimum value of the second fatigue life;
and determining the second optimization objective function according to the maximum fatigue life of the influence parameter with the minimum fatigue life.
In some embodiments, the predetermined vehicle door rigidity condition is determined according to an initial deformation value and a deformation value of any point on the static lower vehicle door frame.
In some embodiments, said parameter optimizing said door component parameters of said initial door model according to said first and second optimization objective functions and said constraints comprises:
obtaining a second function according to the first optimization objective function and the second optimization objective function;
acquiring the second function and the upper limit value and the lower limit value of each variable in the constraint condition;
and carrying out parameter optimization on the door component parameters of the initial door model according to the second function, the constraint condition, the second function and the upper limit value and the lower limit value of each variable in the constraint condition.
In some embodiments, said performing a parameter optimization on said door component parameters of said initial door model according to said second function, said constraint, and upper and lower values of each variable in said second function and said constraint comprises:
performing parameter optimization on the vehicle door component parameters of the initial vehicle door model by adopting a multi-objective particle swarm optimization algorithm according to the second function, the constraint condition, the second function and the upper limit value and the lower limit value of each variable in the constraint condition;
the particle swarm optimization algorithm comprises a multi-objective particle swarm optimization algorithm, wherein the particle swarm optimization algorithm comprises a first number of iterative algebras and a second number of iterative algebras.
In some embodiments, the objective of the multi-objective particle swarm optimization algorithm is the first optimization objective function and the second optimization objective function.
In a second aspect, a vehicle door model series construction system is provided, including:
the system comprises an initial vehicle door model obtaining module, a vehicle door model obtaining module and a vehicle door model selecting module, wherein the initial vehicle door model obtaining module is used for obtaining an initial vehicle door model, and the initial vehicle door model comprises vehicle door component parameters;
the vehicle door fatigue life influence parameter acquisition module is used for acquiring the influence parameters of the vehicle door fatigue life from the vehicle door component parameters, and the influence parameters comprise quality parameters and non-quality parameters;
the optimization objective function obtaining module is used for obtaining a first optimization objective function according to the quality parameters and obtaining a second optimization objective function according to the quality parameters and the non-quality parameters;
the vehicle door component parameter optimization module is used for performing parameter optimization on the vehicle door component parameters of the initial vehicle door model according to the first optimization objective function, the second optimization objective function and the constraint condition by taking a preset vehicle door rigidity condition as the constraint condition to obtain optimized vehicle door component parameters;
and the vehicle door model establishing module is used for establishing a vehicle door model according to the initial vehicle door model and the optimized vehicle door component parameters.
In a third aspect, an electronic device is provided, including:
a processor;
a memory for storing processor-executable instructions;
wherein the processor executes the executable instructions to implement the method of any of the above embodiments.
In a fourth aspect, a computer-readable storage medium is provided, on which computer instructions are stored, which instructions, when executed by a processor, implement the steps of the method of any of the above embodiments.
According to the embodiment, the influence of the parameters of the vehicle door component on the fatigue life and the quality is considered at the same time, so that the optimized vehicle door structure can meet the requirements of two aspects, and the optimization speed is accelerated. Meanwhile, the problem that the dead loop is easy to be caused in multi-target calculation is reduced by adding non-quality parameters.
In the above embodiment, when designing the light weight of the vehicle door, the influence parameter of the fatigue life of the vehicle door is obtained from the vehicle door component parameter, the influence parameter includes a quality parameter and a non-quality parameter, a first optimization objective function is obtained through the quality parameter, a second optimization objective function is obtained according to the quality parameter and the non-quality parameter, and the first optimization objective function and the second optimization objective function are optimized by using the vehicle door stiffness condition as the constraint condition. Therefore, when the car door is designed in a light weight mode, the influence of non-mass parameters in car door component parameters on the fatigue life of the car door is considered, the influence of mass parameters in the car door component parameters on the fatigue life of the car door is also considered, and in addition, a car door rigidity condition is introduced to serve as a constraint condition in parameter optimization of the car door component parameters, so that a finally established car door model meets the performance requirements of actual car door manufacturing.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
FIG. 1 is a flow chart of a vehicle door structure design construction method in an exemplary embodiment.
FIG. 2 is a flowchart of a method for obtaining a second optimization objective function based on the quality parameter and the non-quality parameter.
FIG. 3 is a front door assembly finite element model.
FIG. 4 is a graph of shackle torsional stiffness versus vehicle door fatigue life.
FIG. 5 is a graph of pin offset versus fatigue life for a vehicle door.
FIG. 6 is a graph of the effect of the inner panel cut transition radius on the fatigue life of a vehicle door.
FIG. 7 is a graph showing the effect of door glass thickness on door fatigue life.
FIG. 8 is a graph of the effect of door trim mass on door fatigue life.
FIG. 9 shows the effect of the thickness of the sheet metal of the inner panel of the door on the fatigue life of the door.
FIG. 10 is a graph of the effect of exterior rearview mirror mass on door fatigue life.
FIG. 11 is a graph of the effect of door opening strip sealing force on fatigue life of a vehicle door.
Fig. 12 is a door model distribution diagram.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of systems and methods consistent with certain aspects of the present application, as detailed in the appended claims. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
FIG. 1 is a flow chart of a vehicle door model building method in an exemplary embodiment, which, as shown in FIG. 1, may include the steps of:
it should be understood that the door component parameters may be all or part of the parameters required on the door model, and the user may set the parameters as required, and if part of the parameters are not listed as door component parameters, the initial values may be used instead. The vehicle door model can be established through software or other modes, such as Hypermesh, CATIA, UG and other software.
it should be understood that the vehicle door optimization mode may adopt algorithms such as an NSGA algorithm, a PAES algorithm, an SPEA algorithm, an MOPSO algorithm, and the like, and the first optimization objective function and the second optimization objective function are used as targets to continuously iterate through the algorithms until iteration is finished under an iteration finishing condition (the iteration finishing condition may be that the iteration number reaches an upper limit or a preset target is obtained), so as to obtain optimized vehicle door component parameters.
And 500, establishing a vehicle door model according to the initial vehicle door model and the optimized vehicle door component parameters.
The initial vehicle door model comprises vehicle door component parameters, and the optimized vehicle door model can be reestablished by taking the vehicle door component parameters obtained after optimization as the corresponding vehicle door component parameters in the initial vehicle door model. At the moment, the parameters of all the door parts in the door model meet the actual door manufacturing requirements, and the door obtained by guiding and controlling the door production through the door model can better meet the actual use requirements in terms of performance.
In the above embodiment, when designing the light weight of the vehicle door, the influence parameter of the fatigue life of the vehicle door is obtained from the vehicle door component parameter, the influence parameter includes a quality parameter and a non-quality parameter, a first optimization objective function is obtained through the quality parameter, a second optimization objective function is obtained according to the quality parameter and the non-quality parameter, and the first optimization objective function and the second optimization objective function are optimized by using the vehicle door stiffness condition as the constraint condition. Therefore, when the car door is designed in a light weight mode, the influence of non-mass parameters in car door component parameters on the fatigue life of the car door is considered, the influence of mass parameters in the car door component parameters on the fatigue life of the car door is also considered, and in addition, a car door rigidity condition is introduced to serve as a constraint condition in parameter optimization of the car door component parameters, so that a finally established car door model meets the performance requirements of actual car door manufacturing.
In some embodiments, obtaining the first optimization objective function from the quality parameter comprises:
step 310, obtaining a quality expression of the quality parameter, wherein the quality expression is used for indicating to obtain the quality corresponding to the quality parameter;
step 320, accumulating the quality expression to obtain a first function;
step 330, determining a first optimization objective function according to the minimum value of the first function.
It should be understood that several quality parameters are certainly included in the door model, so that the influence of the several quality parameters on the quality of the door model needs to be considered, and therefore, the accumulation processing is performed. Meanwhile, it should be understood that the quality expression can be in various forms, and if some quality parameters are directly corresponding to the quality, such as the quality parameters of the door inner guard plate, excessive calculation is not needed when the quality expression is accumulated, and the quality parameters are directly substituted. But the relationship between some parameters such as the thickness parameter and the quality of the sheet metal of the inner door panel is not directly corresponding,
in some embodiments, obtaining the second optimization objective function from the quality parameter and the non-quality parameter comprises:
and step 360, determining a second optimization objective function according to the maximum fatigue life of the influence parameter with the minimum fatigue life.
Specifically, the first fatigue life and the second fatigue life are also functions, the first fatigue life is a function with the quality parameter as an independent variable, and the second fatigue life is a function with the quality parameter and the non-quality parameter as independent variables. Therefore, the first fatigue life and the second fatigue life are firstly calculated, the minimum influence parameter of the fatigue life is determined by the minimum value of the first fatigue life and the second fatigue life, and the second optimization objective function finally obtained according to the minimum influence parameter of the fatigue life is actually a function with the quality parameter and the non-quality parameter as independent variables.
In some embodiments, the predetermined vehicle door rigidity condition is determined according to an initial deformation value and a deformation value of any point on the static lower vehicle door frame.
In some embodiments, the parameter optimizing the door component parameters of the initial door model according to the first and second optimization objective functions and the constraints comprises:
step 410, obtaining a second function according to the first optimization objective function and the second optimization objective function;
step 420, acquiring an upper limit value and a lower limit value of each variable in the second function and the constraint condition;
and 430, performing parameter optimization on the door component parameters of the initial door model according to the second function, the constraint condition, the upper limit value and the lower limit value of each variable in the second function and the constraint condition.
In some embodiments, the second function is a multi-objective function, including two objectives — a first optimization objective function and a second optimization objective function. In some embodiments, an attempt is made to make the first optimization objective function relatively low and the second optimization objective function relatively high. In some embodiments, the parameters of the door component may be optimized by a multi-objective optimization algorithm, optionally a multi-objective particle swarm optimization algorithm. Certainly, in some embodiments, algorithms such as an NSGA algorithm, a PAES algorithm, and a SPEA algorithm are adopted, and the algorithm is continuously iterated with the goal of minimizing the vehicle door mass and maximizing the vehicle door life as targets until an iteration end condition (the iteration end condition may be that the iteration number reaches an upper limit or a preset target is obtained) is reached, and then the iteration is ended to finally obtain optimized vehicle door component parameters.
To better illustrate how the optimization is performed, the present disclosure illustrates one particular process. Firstly, a user can geometrically simplify and clean a vehicle door three-dimensional model by using three-dimensional software (such as Hypermesh), a plate-shell unit is selected for dividing grids, the size of the grid unit is 4mm, a four-node straight edge unit (QUAD4) is used more frequently, stress precision is improved by a local grid encryption mode, a three-node straight edge unit (TRIA3) is selected for improving transition grid quality, a block unit and a short beam are adopted for simulating welding spots, a point-surface contact connection mode is adopted for simulating a viscose part, and a vehicle door finite element model is obtained, wherein the total number of model units is 161154, and is shown in FIG. 3.
The accuracy of the finite element model directly influences the accuracy of fatigue life analysis and optimization, and in order to verify the accuracy of the model, a vehicle door assembly sample is trial-manufactured for test verification. According to experience, static deformation (namely rigidity) of a door frame has a direct influence on the fatigue life of a vehicle door, under test load, the pair of a deformation simulation calculation result and an actual measurement result is shown in a table 1, the numerical values shown in the table are percentage values of comparison between calculated deformation and actual measurement deformation and a design requirement limit value, and if the numerical value is more than 100%, the product deformation exceeds the design requirement, namely the product is unqualified. The comparison results in the table 1 show that certain errors exist between the simulation result and the actual measurement result, and the errors are within an acceptable range, so that the rigidity of the vehicle door assembly is qualified, and the model precision meets the engineering requirements. However, the deformation calculation value of the door frame is close to the design requirement value, so that the deformation range of the door frame is reasonably restricted in the optimization calculation so as to ensure that the static rigidity of the door frame meets the design requirement.
TABLE 1
In order to ensure that simulation is consistent with fatigue test, a finite element model of components such as a blank car door, a door opening strip, a car window guide rail, car door glass, a car door hinge, a door lock, a lock pin and the like is established, a rearview mirror and a door protection plate are used as mass concentrated loads, the finite element model of the car door and a car door system is established in an assembling mode, a connection mode of node rigid bodies is adopted for mass concentrated units, and if the rearview mirror is used as a mass concentrated load, the rearview mirror is connected through an RB2 unit. The door opening strip model adopts an OGDEN material model in software, and the sealing force curve of the door opening strip model is kept consistent with the design requirement by adjusting the model parameters.
Setting a model according to the standard requirements of a vehicle door switch fatigue test to keep the closing speed and closing energy of a vehicle door consistent with those of a real vehicle fatigue test, performing dynamic simulation calculation by using a RADIOSS solver in Hyperworks software, wherein the result shows that a larger stress concentration exists at the triangular window cut of a vehicle door inner plate, the maximum stress danger unit is 181192, simulating to obtain a Von-Mises stress curve of the danger unit in the vehicle door closing process, performing fatigue life calculation by using FEMFAT software by using a fatigue damage theory, and predicting that the vehicle door switch fatigue test is likely to generate fatigue failure about 3.1 x 104 times.
And (3) mounting the trial-manufactured vehicle door assembly on a vehicle door for performing a vehicle door switch fatigue test, and finding cracks when the sheet metal at the notch of the triangular window of the inner door panel is opened and closed for about 27743 times. The fatigue simulation service life of the same position is about 3.1 multiplied by 104 times, the error between the fatigue calculation service life and the test result is about 14.81 percent, and the calculation result of the established simulation model is closer to the actual test result, and the accuracy of the vehicle door and the vehicle door system model meets the engineering requirement.
Because the door assembly appears fatigue failure problem in the user use easily mainly be the metal sheet metal component, based on the finite element model that has established, this paper selects 8 parameters relevant with metal sheet metal component fatigue life to study, latch hook torsional rigidity promptly, lockpin position offset, incision panel beating fillet, door glass thickness, door inner panel quality, door inner panel thickness, rear-view mirror quality and door opening strip sealing power, because the door planking panel beating is related to the reason in aspects such as appearance molding, this time optimization is with door inner panel beating as main optimization object.
In order to confirm the effect of the different parameters on the door life for the subsequent selection of initial values of the parameters and the establishment of specific parameter ranges, the applicant made the following simulations:
2.1 influence of the torsional stiffness of the latch hook
At the moment of closing and impacting the vehicle door, the torsional rigidity of the lock hook directly influences the impact load transmitted from the door lock to the vehicle door metal plate, and the simulation result is shown in fig. 4; there is an optimum for the hook torsional stiffness to have an effect on the fatigue life of the vehicle door that should be found and reasonably utilized in the optimization and design.
2.2 detent position offset Effect
The offset of the door lock pin directly influences the gap in the vehicle door, thereby influencing the compression amount of the door opening sealing strip and the impact degree of the lock pin and the door lock, and finally influencing the load borne by the vehicle door assembly. During calculation, the position of the lock pin is defined to be shifted to the outside of the door to be a positive direction, and the position of the lock pin is defined to be shifted to the inside of the door to be a negative direction, and the simulation result is shown in fig. 5.
2.3 door inner panel metal notch fillet influence
The notch at the triangular window of the inner door panel is an area which is easy to have fatigue problems, the radius of the transition fillet has a positive effect on eliminating stress concentration and increasing the fatigue life of the area, the simulation result is shown in figure 6, the fatigue life of the notch area is firstly reduced and then increased along with the increase of the radius of the notch fillet, the minimum value of the fatigue life exists, the transition fillet at the notch is known to be higher than the smooth fatigue life, the transition point of the fatigue life is found when optimizing and designing, and the transition fillet radius is reasonably designed.
2.4 door glass thickness Effect
The thickness of the door glass directly affects the mass and the rigidity of the door assembly, and further affects the fatigue life of the door, and the simulation result is shown in fig. 7.
2.5 door inner panel quality impact
The door inner casing mainly bears some function keys and aesthetic function, its quality also has certain influence to door fatigue life, the simulation result is as shown in fig. 8, the existence of door inner casing quality can improve door fatigue life, there is the extreme value, door fatigue life descends after exceeding this extreme value quality, continue to increase the quality, door fatigue life descends and tends to stably, the quality that explains door inner casing should not be undersized, and too big quality is unfavorable for door lightweight and fatigue life, the appropriate design door inner casing quality is favorable to the door to compromise lightweight and fatigue life requirement.
2.6 door inner panel sheet metal thickness influence
The thickness of door inner panel beating directly influences the quality of door assembly, fatigue life and rigidity, and the simulation result is shown in fig. 9, and door inner panel beating thickness increases, and the door quality increases, and fatigue life can increase and can increase rapidly about after 0.70mm simultaneously, and the less partial characteristic of slope when needing rational utilization thickness to be less than 0.70mm during the design obtains great lightweight result through reducing fatigue life less.
2.7 exterior rearview mirror quality impact
The quality of the outer rearview mirror has direct influence on the local stress of a metal plate at a triangular window of the inner plate of the door, so that the fatigue life of the door is influenced, the simulation result is shown in fig. 10, the quality of the outer rearview mirror at the same position is reduced, the fatigue life of the door is prolonged, and the slope of a curve is not large, so that the quality of the outer rearview mirror is reasonably matched during design, and the fatigue life of the door is prolonged.
2.8 door opening strip seal effect
The door hole sealing strip is located between the door and the door, fills the inner gap of the door, provides support for the door, and directly influences the impact load at the moment of closing the door according to the sealing force, so that the fatigue life of the door is influenced. The method comprises the steps of adopting an OGDEN material model in software, adjusting model parameters to enable a sealing force curve of a door opening strip model to be consistent with design requirements, setting automatic modification parameters through the software to adjust different sealing forces of the door opening strip to carry out simulation calculation, obtaining the influence of the different sealing forces on the fatigue life of a door inner plate, obtaining a simulation result as shown in figure 11, increasing the fatigue life of a vehicle door along with the increase of the sealing force of the door opening strip, increasing the sealing force after a curve slope inflection point, rapidly increasing the fatigue life of the vehicle door, finding the slope inflection point during optimization and design, reasonably utilizing the characteristics of the larger slope part, obtaining a larger fatigue life improving effect by reasonably increasing the sealing force, and having little influence on the total quality of the vehicle door due to the change of the sealing force.
And taking the 8 influence parameters as design variables, wherein 4 parameters are quality parameters, and the rest 4 non-quality parameters participate in optimization calculation, so that a more appropriate optimization result is obtained. And determining according to a relation curve between each parameter variable and the service life, wherein each design variable is shown in table 2, the initial value in table 2 is an actual value of each parameter of the vehicle door assembly, and the upper limit and the lower limit are constraint values of optimized calculation of each parameter variable.
TABLE 2 design variables
The mass (M) of four optimized parts of the vehicle door is taken as an optimization target, and the expression is as follows:
M(x)＝min[M(x4)+M(x5)+M(x6)+M(x7)]
in the formula: m (x4) is the door glass mass, M (x5) is the door inner guard plate mass, M (x6) is the door inner sheet metal mass, and M (x7) is the rearview mirror mass.
The fatigue life (L) of the vehicle door component is taken as an optimization target, and the expression is as follows:
L＝max{min(Li)}
in the formula: li is the fatigue life of the ith component. And i is a part of the vehicle door, and is taken as [1,8 ].
3.3 Multi-objective Integrated optimization of vehicle door Assembly
The mass, fatigue life and rigidity (deformation) performance indexes of the vehicle door are comprehensively considered, multi-objective comprehensive optimization design is carried out on the vehicle door assembly, the mass and fatigue life performance is taken as an optimization target, the rigidity (deformation) is kept as a constraint condition, and therefore an optimization mathematical model can be expressed as follows:
in the formula: m (x) is the door assembly mass, L (x) is the door assembly fatigue life; p1(x) and P10 are the point deformation and initial value of the door frame P1, and P10 is 76.51%; p2(x) and P20 are deformation points and initial values of the door frame P2, and P20 is 86.23%; d1 and d2 are respectively constraint coefficients of points P1 and P2 of the door frame, and in view of the initial values of P10 and P20, d 1-d 2-10% and the static rigidity variation of the door frame are-10% and 10%]To ensure that the optimized rear door frame is deformed to be qualified (<100%); x is a design variable, and xL and xU are the lower limit and the upper limit of each design variable, respectively. Wherein P1 and P2 are two points in the door frame. Therefore, in some embodiments, min (m (x), — l (x)) may be understood as the second function. I P1(x)-P10|≤d1P10And | P2(x)-P20|≤d2P20Is a constraint, and x ∈ (x)L,xU) The upper limit value and the lower limit value of each variable in the second function and the constraint condition.
The method selects a particle swarm multi-objective optimization algorithm, the particle swarm scale of the particle swarm algorithm is defined to be 60, and the iterative algebra is 100. That is, the first number may be 60 and the second number may be 100. And performing optimization operation on the optimized mathematical model by adopting a particle swarm multi-objective optimization algorithm. And the optimization operation process takes the first optimization objective function and the second optimization objective function as targets for optimization. The distribution diagram of the optimized vehicle door model is shown in FIG. 12.
As shown in fig. 12, the mass targets of the four components of the door and the fatigue life target of the door are generally contradictory to each other, and based on the consideration of improvement of the overall performance, the optimization result with the minimum door mass should be selected as much as possible while satisfying the requirement of the fatigue life (1 × 105 times), and the optimization result with the fatigue life of about 1.21 × 105 times and the mass of about 11.18kg is selected in consideration of the model calculation error (about 14.81%), so as to ensure that the real object obtained according to the model can approach the ideal design target, and the optimization results of the design parameter variables are rounded as shown in table 3. The optimized rear door danger point is the notch (position No. 1) of the triangular window of the inner plate of the door, the calculated maximum Von-Mises stress of the danger unit (174624) is 80.1MPa, the maximum Von-Mises stress is obviously reduced compared with the maximum Von-Mises stress before optimization, the fatigue life is about 4 times of that before optimization, and the mass of the door assembly is reduced by 2.44kg compared with the maximum Von-Mises stress before optimization.
Fatigue simulation calculation is carried out on main components of the vehicle door assembly to optimize stress distribution at the sheet metal notch of the triangular window of the inner plate of the rear vehicle door, the stress distribution of the inner plate of the whole vehicle door is not changed greatly, the fatigue life of other stress concentration points of the vehicle door exceeds the standard required times, and the test also proves that the positions are not subjected to fatigue failure; in conclusion, after the vehicle door assembly is optimized, no great influence is generated on the stress distribution of other structural members of the vehicle door, partial local maximum stress is reduced, new fatigue life dangerous points are not generated, and the vehicle door optimization result is feasible.
And (3) trial-producing a vehicle door sample piece according to an optimized result, quickly forming or modifying the equipment piece with reduced mass into a substitute piece for ensuring the assembling position and the quality requirement, measuring the static deformation of the vehicle door frame according to the same method, and comparing the measured static deformation with the simulation and actual measurement results before optimization, wherein as shown in the table 3, although the deformation of the optimized vehicle door frame is increased, the deformation design requirement of the vehicle door frame is also met, and the optimization requirement for ensuring the rigidity of the vehicle door to be basically unchanged is met.
TABLE 3 comparison of calculated deformation with measured deformation before and after optimization (example data)
And (3) mounting the trial-manufactured vehicle door assembly on the vehicle door to perform a vehicle door switch fatigue test, and after 1 x 105 times of vehicle door switches, performing visual inspection on the test vehicle door, wherein fatigue damage is not found, which indicates that the optimized vehicle door meets the design requirement. In order to verify the accuracy of simulation calculation, the fatigue test of the opening and closing of the vehicle door is continued until fatigue failure occurs, after 109428 times of opening and closing of the vehicle door, sheet metal cracks are found at the sheet metal cuts of the triangular window of the vehicle door, the error between the calculated fatigue life and the test result after optimization is about 10.57%, the fatigue failure is not found at other parts after the vehicle door is disassembled and inspected, and the accuracy of the construction method and the result is proved.
As can be seen from the above description, in an embodiment of the present specification, a door optimization model with a goal of minimizing the door mass and maximizing the door life is established in advance, and meanwhile, the influence of specific parameters on the door mass and the door life is considered, so that a door model with a small door mass and a long door life can be directly obtained after a user performs a simulation optimization design, and the development cycle and the cost are greatly reduced.
Based on the same inventive concept, the embodiment of the application also provides a vehicle door model construction system corresponding to the vehicle door model construction method, and as the problem solving principle of the system is similar to that of the vehicle door model construction method in the embodiment of the application, the implementation of the system can refer to the implementation of the method, and repeated parts are not described again.
The vehicle door model building system can be applied to a server and comprises the following components:
the system comprises an initial vehicle door model obtaining module, a vehicle door model generating module and a vehicle door model generating module, wherein the initial vehicle door model obtaining module is used for obtaining an initial vehicle door model, and the initial vehicle door model comprises vehicle door component parameters;
the vehicle door fatigue life influence parameter acquisition module is used for acquiring the influence parameters of the vehicle door fatigue life from the vehicle door part parameters, and the influence parameters comprise quality parameters and non-quality parameters;
the optimization objective function obtaining module is used for obtaining a first optimization objective function according to the quality parameters and obtaining a second optimization objective function according to the quality parameters and the non-quality parameters;
the vehicle door component parameter optimization module is used for performing parameter optimization on the vehicle door component parameters of the initial vehicle door model according to the first optimization objective function, the second optimization objective function and the constraint condition by taking a preset vehicle door rigidity condition as the constraint condition to obtain optimized vehicle door component parameters;
and the vehicle door model establishing module is used for establishing a vehicle door model according to the initial vehicle door model and the optimized vehicle door component parameters.
The embodiment of the vehicle door model building system can be applied to the server. The system embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. Taking a software implementation as an example, as a system in a logical sense, the system is formed by reading corresponding computer program instructions in the nonvolatile memory into the memory for operation through the processor of the server where the system is located. In addition to the processor, the memory, the network interface, and the nonvolatile memory, the server where the system is located in the embodiment may also include other hardware according to the actual function of the server, which is not described herein again.
The present disclosure also provides an electronic device, comprising: a processor and a memory for storing processor-executable instructions; the processor executes the executable instructions to realize the construction method of any one of the above embodiments.
The present disclosure also provides a computer readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the construction method as described in any of the above embodiments.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above embodiments are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, and any insubstantial changes and substitutions made by those skilled in the art based on the present invention are within the protection scope of the present invention.
Claims (10)
1. A vehicle door model construction method is characterized by comprising the following steps:
obtaining an initial vehicle door model, wherein the initial vehicle door model comprises vehicle door component parameters;
obtaining influence parameters of the fatigue life of the vehicle door from the parameters of the vehicle door parts, wherein the influence parameters comprise quality parameters and non-quality parameters;
obtaining a first optimization objective function according to the quality parameters, and obtaining a second optimization objective function according to the quality parameters and the non-quality parameters;
taking a preset vehicle door rigidity condition as a constraint condition, and performing parameter optimization on the vehicle door component parameters of the initial vehicle door model according to the first optimization objective function, the second optimization objective function and the constraint condition to obtain optimized vehicle door component parameters;
and establishing a vehicle door model according to the initial vehicle door model and the optimized vehicle door component parameters.
2. The method of constructing according to claim 1, wherein said obtaining a first optimization objective function according to the quality parameter comprises:
obtaining a quality expression of the quality parameter, wherein the quality expression is used for indicating to obtain the quality corresponding to the quality parameter;
accumulating the quality expression to obtain a first function;
determining the first optimization objective function according to the minimum value of the first function.
3. The method of construction according to claim 1, wherein said deriving a second optimization objective function from said quality parameter and said non-quality parameter comprises:
acquiring a first fatigue life corresponding to the quality parameter and a second fatigue life of the non-quality parameter;
determining an influence parameter with the minimum fatigue life according to the minimum value of the first fatigue life and the minimum value of the second fatigue life;
and determining the second optimization objective function according to the maximum fatigue life of the influence parameter with the minimum fatigue life.
4. The building method according to claim 1, wherein the predetermined door rigidity condition is determined based on an initial value of deformation and a deformation value of any point on the static lower door frame.
5. The construction method according to claim 1, wherein the parameter optimizing the door component parameters of the initial door model according to the first and second optimization objective functions and the constraints comprises: obtaining a second function according to the first optimization objective function and the second optimization objective function;
acquiring the second function and the upper limit value and the lower limit value of each variable in the constraint condition;
and carrying out parameter optimization on the door component parameters of the initial door model according to the second function, the constraint condition, the second function and the upper limit value and the lower limit value of each variable in the constraint condition.
6. The construction method according to claim 5, wherein the parameter optimizing the door component parameters of the initial door model according to the second function, the constraint condition, and upper and lower values of variables in the second function and the constraint condition includes:
performing parameter optimization on the vehicle door component parameters of the initial vehicle door model by adopting a multi-objective particle swarm optimization algorithm according to the second function, the constraint condition, the second function and the upper limit value and the lower limit value of each variable in the constraint condition;
the particle swarm optimization algorithm comprises a multi-target particle swarm optimization algorithm, wherein the particle swarm scale in the multi-target particle swarm optimization algorithm is a first number, and the algebra of iteration of the multi-target particle swarm optimization algorithm is a second number.
7. The building method according to claim 6, wherein the objective of the multi-objective particle swarm optimization algorithm is the first optimization objective function and the second optimization objective function.
8. A vehicle door model series construction system is characterized by comprising:
the system comprises an initial vehicle door model obtaining module, a vehicle door model obtaining module and a vehicle door model selecting module, wherein the initial vehicle door model obtaining module is used for obtaining an initial vehicle door model, and the initial vehicle door model comprises vehicle door component parameters;
the vehicle door fatigue life influence parameter acquisition module is used for acquiring the influence parameters of the vehicle door fatigue life from the vehicle door component parameters, and the influence parameters comprise quality parameters and non-quality parameters;
the optimization objective function obtaining module is used for obtaining a first optimization objective function according to the quality parameters and obtaining a second optimization objective function according to the quality parameters and the non-quality parameters;
the vehicle door component parameter optimization module is used for performing parameter optimization on the vehicle door component parameters of the initial vehicle door model according to the first optimization objective function, the second optimization objective function and the constraint condition by taking a preset vehicle door rigidity condition as the constraint condition to obtain optimized vehicle door component parameters;
and the vehicle door model establishing module is used for establishing a vehicle door model according to the initial vehicle door model and the optimized vehicle door component parameters.
9. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor implements the method of any one of claims 1-7 by executing the executable instructions.
10. A computer-readable storage medium having stored thereon computer instructions, which when executed by a processor, perform the steps of the method according to any one of claims 1-7.
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