CN114510781A - High-dimensional multi-objective optimization design method for electric motor coach framework - Google Patents
High-dimensional multi-objective optimization design method for electric motor coach framework Download PDFInfo
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Abstract
The invention provides a high-dimensional multi-objective optimization design method of an electric motor coach framework, which comprises the following steps: establishing a finite element model of a passenger car framework; performing basic performance analysis, modal analysis and vehicle framework side collision analysis on the model; dividing the passenger car skeleton into a plurality of groups; setting the acceleration of a driver, the acceleration of a seat near a middle door and low-order modal frequency during the side collision of the whole vehicle as optimization constraints, setting the mass of the whole vehicle, the maximum deformation of the limit torsion working condition and the side collision intrusion amount as optimization targets, and taking the thickness of the grouped design variables as optimization variables; screening out subsequent optimization variables; carrying out test design; fitting an approximate model and checking the precision of the model; establishing a mathematical optimization model for optimization; screening out a group of data meeting the requirements, reintroducing the finite element model, comparing the finite element model with the initial model, and judging the optimization effect.
Description
Technical Field
The invention relates to the field of automobiles, in particular to a high-dimensional multi-objective optimization design method for an electric bus framework.
Background
With the development of computer technology and the continuous development and perfection of technologies such as a numerical analysis theory, an optimization algorithm and the like, a more advanced, accurate and efficient method appears in the design of a skeleton system.
The multi-objective optimization design method for the automobile proposed by the existing patent comprises the following steps:
the invention discloses a multi-objective optimization design method for a hybrid power bus frame, which is a multi-disciplinary collaborative optimization design method considering a plurality of linear and highly nonlinear responses such as first-order modal frequency, ultimate torsion working condition, acceleration of a driver during front collision of a whole bus, energy absorption of front collision of the whole bus and the like
The invention patent of China (application number: 201910215479.3) discloses a collaborative optimization design method and a collaborative optimization design system for a vehicle body frame, wherein the collaborative optimization design method for the vehicle body frame is provided with a plurality of sub-working condition models, and the plurality of sub-working condition models comprise a non-linear working condition of bending rigidity, torsional rigidity, modal linear working conditions and collision working conditions.
Although the above patents relate to the consideration of collision performance, only the frontal collision and the collision deformation are considered, and other collision situations and relevant collision safety data are not considered in the design scheme, meanwhile, the optimization targets considered by the optimization design methods are few, and are both two targets, and for the passenger car frame, the performance relates to the aspect, so that the optimization needs to be carried out by taking various performances as the targets.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a high-dimensional multi-target optimization design method for an electric bus framework, which is a high-dimensional multi-target collaborative optimization design considering multiple linear and highly nonlinear responses such as first-order modal frequency, extreme torsion working condition, side impact intrusion amount, acceleration of a driver during side impact of a whole bus, acceleration of a seat near a middle door and the like.
The present invention achieves the above-described object by the following technical means.
A high-dimensional multi-objective optimization design method for a framework of an electric motor coach is characterized by comprising the following steps:
s1: establishing a passenger car skeleton finite element model for optimization analysis;
s2: performing basic performance analysis, modal analysis and whole vehicle framework side collision analysis on the passenger vehicle framework finite element model, wherein the basic performance analysis comprises static force analysis of a horizontal bending working condition, a limit torsion working condition, an emergency braking working condition and an emergency turning working condition;
s3: dividing the passenger car framework into a plurality of groups by taking the position, the function and the thickness of the passenger car framework components as grouping modes;
s4: setting the acceleration of a driver, the acceleration of a seat near a middle door and the low-order modal frequency as optimization constraints during the side collision of the whole vehicle, setting the mass of the whole vehicle, the maximum deformation of the limit torsion working condition and the side collision invasion amount as optimization targets, and taking the thicknesses of all parts grouped by the passenger vehicle frameworks in the step S3 as optimization variables;
s5: according to the linear main effect graphs of five optimized responses of the passenger car skeleton grouping design variables to the side collision acceleration of the driver, the side collision intrusion amount of the whole vehicle, the first-order modal frequency, the whole vehicle mass and the maximum deformation of the whole vehicle static analysis in the step S3, screening out the variables of which the sensitivity values to the responses exceed a certain numerical value as subsequent optimized variables;
s6: carrying out test design on the screened variables by a test design method;
s7: for the sampled data in S6, fitting approximate models of quality, stress of torsion condition, first-order modal frequency, acceleration of driver and acceleration of middle door seat through approximate models, and determining coefficient R2Checking the precision of the model;
s8: establishing a mathematical optimization model, and performing final optimization by adopting a multi-objective optimization algorithm;
s9: and screening a group of data meeting the requirements from the optimized data, rounding the optimized variables, then reintroducing the variables into the finite element model, and comparing the models with the initial model to judge the optimization effect.
Furthermore, the frame of the outer frame of the passenger car frame in the finite element model of the passenger car frame is made of Q235 structural steel, and the frame and the floor frame are made of Qste700tm structural steel.
Further, the speed of the vehicle coming in the side collision simulation analysis in step S2 is 40 km/h.
Further, in step S3, the outer frame, the frame, and the floor frame of the passenger car are divided into 50 groups, and the number of the corresponding optimization variables in step S4 is 50.
Further, the test design method adopted in step S6 is a latin hypercube test design method.
Further, the approximate model fitting method employed in step S7 is to fit the radial basis function neural network.
Further, step S7 specifically includes the following steps:
the acceleration and the rollover center-of-mass acceleration of the driver in the frontal collision are fitted with the energy absorption and the rollover intrusion amount of the whole vehicle in the frontal collision and the whole vehicle mass by a Radial Basis Function (RBF) method, and the coefficient R is determined2Checking the accuracy of the RBF model, i.e.
In the formula yiIn order to design the true response values of the space,
in response to the sum of the squares of the mean differences,
is a calculated value of the proxy model.
Further, the multi-objective optimization algorithm adopted in step S8 is an NSGA-III algorithm.
Further, the optimized mathematical model established in S8 is:
in the formula, x is a design variable, m is the mass of the whole vehicle, and S is a framework variableMaximum shape, w is the side impact intrusion amount, f1，f2For the first-order and second-order modes of the passenger car skeleton, G (x) is the maximum acceleration at the seat of the side-impact middle door, U (x) is the maximum acceleration at the seat of the side-impact driver, G (x)0(x)，U0(x) The initial values for the maximum acceleration of the door seat and the driver seat in a side impact.
The advantages of the invention are as follows:
the invention overcomes the defect of optimization of side collision of a passenger car framework, provides a high-dimensional multi-objective optimization design method of the electric passenger car framework, determines that the side collision is carried out on the passenger car framework based on a CAE technology and a finite element method, takes the plate thickness of the framework as a design variable, takes the acceleration of a side collision driver and the acceleration of a middle door seat as optimization constraints, and takes the mass of a whole car and the rollover intrusion amount as targets. And performing experimental design on each design variable by adopting an optimal Latin hypercube method based on a Hyperstudy integration platform, establishing an approximate model, and optimizing the plate thickness of the framework by adopting an NSGA-III multi-objective optimization algorithm to finally obtain optimal design parameters. Therefore, the invention provides a reliable analysis method for the comprehensive performance and the lightweight design of the framework for a high-dimensional multi-target collaborative optimization design method which gives consideration to a plurality of linear and highly nonlinear responses such as first-order modal frequency, limit torsion working condition, side impact intrusion amount, acceleration of a driver during the side impact of the whole vehicle, acceleration of a seat near a middle door and the like, thereby effectively improving the product development efficiency.
Drawings
FIG. 1 is a flow chart of a high-dimensional multi-objective optimization design method for a framework of an electric motor coach in the embodiment of the invention;
FIG. 2 is a schematic diagram of a finite element of an outer frame skeleton of a passenger car according to an embodiment of the present invention;
FIG. 3 is a schematic finite element diagram of a roof of a passenger vehicle according to an embodiment of the present invention;
FIG. 4 is a schematic view of passenger car parameter screening in the embodiment of the present invention
FIG. 5 is a graph of acceleration time at the operator's seat in an embodiment of the present invention;
FIG. 6 is a graph of acceleration time at a center door seat in an embodiment of the present invention;
FIG. 7 is a graph of side impact intrusion in accordance with an embodiment of the present invention;
FIG. 8 is a stress cloud of torsional mode in an embodiment of the present invention;
FIG. 9 is a finite element model diagram of a side impact of a passenger car in an embodiment of the invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.
The light-weight design method of the pure electric bus framework is described in the following with reference to an example, and comprises the following specific implementation steps:
s1, establishing an automobile frame finite element model for optimization analysis based on a CAE technology and a finite element method, wherein the size of a unit is set to be 10mm, the whole automobile is provided with 2400554 units and 2511692 nodes, the whole automobile is made of two materials, an outer frame framework of an automobile body is made of Q235 structural steel, the frame and a floor framework are made of Qste700tm structural steel, and the material properties are shown in Table 1;
TABLE 1 Properties of the materials
And S2, performing basic performance analysis, unconstrained modal analysis and 40km/h side collision simulation on the passenger car skeleton finite element model, arranging a collision coming car model on the left side of the passenger car skeleton finite element model, and applying loads of a battery, passengers, glass, an engine and the like on the car in a mass point mode. Wherein, the basic performance analysis is the static analysis of four kinds of operating modes, namely horizontal bending operating mode, limit torsion operating mode, emergency braking operating mode, emergency turning operating mode respectively, specifically as follows:
in the limit torsion working condition, the degree of freedom YZ of the left front wheel, the degree of freedom XYZ of the left rear wheel and the degree of freedom XZ of the right rear wheel are restrained; in the horizontal bending working condition, the constraint is the XYZ freedom degree of the left front wheel, the XZ freedom degree of the right front wheel, the YZ freedom degree of the left rear wheel and the Z freedom degree of the right rear wheel. In the emergency braking working condition, the constraint is the XYZ freedom degree of the left front wheel, the XZ freedom degree of the right front wheel, the YZ freedom degree of the left rear wheel and the Z freedom degree of the right rear wheel; in an emergency turning working condition, the constraint is the XYZ freedom degree of the left front wheel, the XZ freedom degree of the right front wheel, the YZ freedom degree of the left rear wheel and the Z freedom degree of the right rear wheel. The maximum stress of the passenger car skeleton under four road conditions is shown in table 2:
TABLE 2 maximum stress of passenger car skeleton under four working conditions
The ultimate torsional working condition stress result is shown in fig. 2, the maximum stress position is at the joint of the bottom of the passenger car framework and the power assembly, and the passenger car framework has enough safety space allowance and a certain light-weight design space is reserved because the material at the maximum stress position of the framework is Qste700tm and the yield limit of the material is 650 MPa;
and (3) modal analysis:
at present, the requirement on the comfort of a passenger car is higher and higher, in order to ensure the comfort, modal analysis needs to be carried out on a passenger car framework, and the first-order modal frequency is shown in figure 3; in the process of driving a passenger car on a road surface, a car body structure can generate vibration due to excitation of various vibration sources, so that riding experience is influenced; when the self frequency of the passenger car framework is close to the road vibration frequency, resonance can be generated, so that not only can severe vibration and noise be generated, but also the service life of the passenger car framework can be influenced; by carrying out modal analysis on the passenger car skeleton, the frequency range of the skeleton can be clearly known, and whether resonance occurs or not can be judged; the modal of the passenger car skeleton in the free state, the first 6 th order natural frequency are shown in table 3:
TABLE 3 front six-order mode of passenger car skeleton
When a passenger car runs on a road, the passenger car is influenced by external excitation and vibration of wheels, an engine, an air conditioner, a transmission system and the like of the passenger car; the excitation frequency of the road surface is less than 3Hz, the resonance frequency of the vehicle body and the suspension is 2.0Hz-3.6Hz, and the idle frequency of the engine is about 40 Hz; the result of 6 orders of modal frequency before modal analysis can be obtained, the modal frequency of the framework of the passenger car is distributed between 7Hz and 25Hz, and the vibration frequency of the road surface and the passenger car can be effectively avoided;
side collision analysis of a finite element model of a passenger car framework:
acceleration values of a driver and a mass center of the passenger car skeleton during head-on collision, whether energy is conserved before and after collision of the whole car and a displacement curve after collision are important reference data for judging whether a collision result is good or bad; in the collision simulation process of the initial model, the vehicle speed is 40km/h, and the collision calculation time is 0.2 second.
The speed and the acceleration of the moving passenger car are not changed within 0-50 ms, because the moving trolley and the passenger car do not collide in the time period, and the speed of the passenger car reaches a peak value state at the moment of 80 ms; the acceleration change of the passenger car reaches a peak value in the moving time of about 120ms and 200ms, but the acceleration is simultaneously accompanied by rebound, and the acceleration is maximum because the deformation does not occur in 200 ms.
And S3, in order to improve the optimization calculation efficiency, the outer frame framework, the frame and the floor framework of the passenger car are divided into 50 groups according to the characteristics of functions, thickness, shapes and the like. Wherein: T1-T7 are vehicle body roof frames, T8-T25 are left and right side wall frames, and T26-T50 are floor and bottom frames.
S4, taking the first-order modal frequency, the second-order modal frequency, the limit torsion working condition, the side impact invasion amount, the acceleration of a driver during the side impact of the whole vehicle and the acceleration of a seat near a middle door as optimization responses, and taking the thicknesses of 50 groups of variables as optimization variables.
S5, firstly, an optimal Latin hypercube method is used for making preliminary DOE test data, variables with response sensitivity values exceeding 0.3 are screened out according to a linear main effect diagram method of hyperudy software, and the variables screened out by different responses are combined to serve as final variables of the next optimization, as shown in figure 4.
S6, carrying out optimal Latin hypercube test design according to the design variables screened out according to the sensitivity, and carrying out complete test design aiming at the optimized variables;
s7, establishing an approximate model for DOE data, fitting the acceleration and the rollover centroid acceleration of the frontal collision driver with the frontal collision energy absorption and rollover intrusion amount of the whole vehicle and the whole vehicle quality by a Radial Basis Function (RBF) method, and checking the precision of the RBF model by determining coefficients, namely
In the formula yiIn order to design the true response values of the space,
in response to the sum of the squares of the mean differences,
is a calculated value of the proxy model. The complex correlation coefficient R2 is a value which changes in the range of 0-1, and the closer the value is to 1, the higher the proxy model precision is.
TABLE 3 approximate model error analysis
S8, establishing an optimized mathematical model
Where x is the design variable, m is the mass of the whole vehicle, S is the maximum deformation of the frame, w is the side impact intrusion amount, f1，f2For first and second order modes of the passenger car skeleton, G (x) is lateralMaximum acceleration at the center-of-collision door seat, U (x) is the maximum acceleration at the side-collision driver seat,G 0(x)，U0(x) The initial values for the maximum acceleration of the door seat and the driver seat in a side impact. And (4) performing final optimization by adopting an NSGA-III type algorithm.
And S9, finally, rounding a group of variable values meeting the requirements after balancing the optimization results, then reintroducing the finite element model, and comparing the rounded variable values with the optimized maximum deformation value of the front upright post, the accelerated speed of a side collision driver, the accelerated speed of the side turning mass center, the energy absorption of the whole vehicle and the side turning invasion amount to judge the optimization effect.
The final optimization effect is shown in table 4:
TABLE 4 Pre-and post-response optimization comparison
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (9)
1. A high-dimensional multi-objective optimization design method for a framework of an electric motor coach is characterized by comprising the following steps:
s1: establishing a passenger car skeleton finite element model for optimization analysis;
s2: performing basic performance analysis, modal analysis and whole vehicle framework side collision analysis on the passenger vehicle framework finite element model, wherein the basic performance analysis comprises static force analysis of a horizontal bending working condition, a limit torsion working condition, an emergency braking working condition and an emergency turning working condition;
s3: dividing the passenger car framework into a plurality of groups by taking the position, the function and the thickness of the passenger car framework components as grouping modes;
s4: setting the acceleration of a driver, the acceleration of a seat near a middle door and the low-order modal frequency as optimization constraints during the side collision of the whole vehicle, setting the mass of the whole vehicle, the maximum deformation of the limit torsion working condition and the side collision intrusion amount as optimization targets, and taking the thickness of the design variable of the passenger vehicle framework grouping in the step S3 as an optimization variable;
s5: according to the linear main effect graphs of five optimized responses of the passenger car skeleton grouping design variables to the side collision acceleration of the driver, the side collision intrusion amount of the whole vehicle, the first-order modal frequency, the whole vehicle mass and the maximum deformation of the whole vehicle static analysis in the step S3, screening out the variables of which the sensitivity values to the responses exceed a certain numerical value as subsequent optimized variables;
s6: carrying out test design on the screened variables by a test design method;
s7: for the sampled data in S6, fitting approximate models of quality, stress of torsion condition, first-order modal frequency, acceleration of driver and acceleration of middle door seat through approximate models, and determining coefficient R2Checking the precision of the model;
s8: establishing a mathematical optimization model, and performing final optimization by adopting a multi-objective optimization algorithm;
s9: and screening a group of data meeting the requirements from the optimized data, rounding the optimized variables, then reintroducing the variables into the finite element model, and comparing the models with the initial model to judge the optimization effect.
2. The high-dimensional multi-objective optimization design method of the electric motor coach skeleton as claimed in claim 1, wherein the method comprises the following steps: the frame of the outer frame of the passenger car frame in the finite element model is made of Q235 structural steel, and the frame and the floor frame are made of Qste700tm structural steel.
3. The high-dimensional multi-objective optimization design method of the electric motor coach skeleton as claimed in claim 1, wherein the method comprises the following steps: the speed of the incoming vehicle in the side impact simulation analysis in step S2 is 40 km/h.
4. The high-dimensional multi-objective optimization design method of the electric motor coach skeleton as claimed in claim 1, wherein the method comprises the following steps: in step S3, the outer frame, the frame, and the floor frame of the passenger car are divided into 50 groups, and the number of the corresponding optimization variables in step S4 is 50.
5. The high-dimensional multi-objective optimization design method of the electric motor coach skeleton as claimed in claim 1, wherein the method comprises the following steps: the test design method adopted in step S6 is a latin hypercube test design method.
6. The high-dimensional multi-objective optimization design method of the electric motor coach skeleton as claimed in claim 1, wherein the method comprises the following steps: the approximate model fitting method employed in step S7 fits for the radial basis function neural network.
7. The high-dimensional multi-objective optimization design method of the electric motor coach skeleton as claimed in claim 1, wherein the method comprises the following steps: the step S7 includes the following steps:
the acceleration and the rollover center-of-mass acceleration of the driver in the frontal collision are fitted with the energy absorption and the rollover intrusion amount of the whole vehicle in the frontal collision and the whole vehicle mass by a Radial Basis Function (RBF) method, and the coefficient R is determined2Checking the accuracy of the RBF model, i.e.
In the formula yiIn order to design the true response values of the space,
in response to the sum of the squares of the mean differences,
is a calculated value of the proxy model.
8. The automotive framework multi-objective optimization method of claim 1, characterized in that: the multi-objective optimization algorithm adopted in step S8 is an NSGA-III type algorithm.
9. The high-dimensional multi-objective optimization design method of the electric motor coach skeleton as claimed in claim 1, wherein the method comprises the following steps: the optimized mathematical model established in S8 is:
wherein x is a design variable, m is the mass of the whole vehicle, S is the maximum value of the deformation of the framework, w is the side impact intrusion amount, f1，f2For the first-order and second-order modes of the passenger car skeleton, G (x) is the maximum acceleration at the seat of the side-impact middle door, U (x) is the maximum acceleration at the seat of the side-impact driver, G (x)0(x)，U0(x) The initial values for the maximum acceleration of the door seat and the driver seat in a side impact.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116522581A (en) * | 2023-03-01 | 2023-08-01 | 中国民航大学 | Structure optimization design method and system for passenger seat |
| CN117709167A (en) * | 2024-02-02 | 2024-03-15 | 山西省机电设计研究院有限公司 | Finite element model-based motor design optimization method, storage medium and equipment |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116522581A (en) * | 2023-03-01 | 2023-08-01 | 中国民航大学 | Structure optimization design method and system for passenger seat |
| CN116522581B (en) * | 2023-03-01 | 2024-04-26 | 中国民航大学 | Structure optimization design method and system for passenger seat |
| CN117709167A (en) * | 2024-02-02 | 2024-03-15 | 山西省机电设计研究院有限公司 | Finite element model-based motor design optimization method, storage medium and equipment |
| CN117709167B (en) * | 2024-02-02 | 2024-04-19 | 山西省机电设计研究院有限公司 | Finite element model-based motor design optimization method, storage medium and equipment |
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