CN117932843A - Method, system and storage medium for automatically calibrating whole vehicle collision model - Google Patents
Method, system and storage medium for automatically calibrating whole vehicle collision model Download PDFInfo
- Publication number
- CN117932843A CN117932843A CN202211257690.XA CN202211257690A CN117932843A CN 117932843 A CN117932843 A CN 117932843A CN 202211257690 A CN202211257690 A CN 202211257690A CN 117932843 A CN117932843 A CN 117932843A
- Authority
- CN
- China
- Prior art keywords
- model
- whole vehicle
- vehicle
- mass
- whole
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000004364 calculation method Methods 0.000 claims abstract description 38
- 238000012360 testing method Methods 0.000 claims abstract description 32
- 238000004140 cleaning Methods 0.000 claims abstract description 10
- 230000003247 decreasing effect Effects 0.000 claims description 30
- 239000002184 metal Substances 0.000 claims description 21
- 230000004888 barrier function Effects 0.000 claims description 19
- 238000013101 initial test Methods 0.000 claims description 6
- 230000004048 modification Effects 0.000 claims description 5
- 238000012986 modification Methods 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 4
- 238000004088 simulation Methods 0.000 abstract description 12
- 230000004044 response Effects 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000007423 decrease Effects 0.000 description 2
- 230000000977 initiatory effect Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
Abstract
The invention relates to the technical field of automobile simulation experiments, and provides a method, a system and a storage medium for automatically calibrating a whole automobile collision model, wherein the method comprises the following steps: inputting and identifying parameters of a test vehicle; speed control key word identification and instantaneous collision speed automatic updating; cleaning a whole vehicle model; automatically iterating and calculating the model; the whole car weight balancing scheme and weight key word identification and automatic update; automatically checking and updating the weight of the vehicle and controlling the error of the X-direction coordinate. By adopting the scheme of the invention, the CAE simulation model of the whole vehicle can be updated rapidly according to the real parameters of the test vehicle, the X-direction centroid coordinate error of the model of the whole vehicle is controlled within 1mm through iterative calculation, and the accuracy of the collision model of the whole vehicle is ensured.
Description
Technical Field
The invention relates to the technical field of automobile simulation experiments, in particular to a method, a system and a storage medium for automatically calibrating a whole automobile collision model.
Background
Multiple whole car crash tests can be carried out in the whole car development process, and the instantaneous speed and the mass of the whole car crash and the mass center of the whole car in the X direction can be different in each test. Before the calibration of the simulation experiment, parameters of the simulation model need to be adjusted to keep the model state consistent with the state of the tested vehicle model as much as possible. The traditional adjustment method is to manually change related parameters, so that time and labor are wasted, the barycenter coordinates of the model and the barycenter coordinates of the real vehicle are difficult to be adjusted to be consistent, and errors after multiple adjustments are mostly more than 20mm, so that the simulation precision of the collision of the whole vehicle is affected.
In view of the above problems, the present inventors have finally achieved the present invention through long-time studies and practices.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method, a system and a storage medium for automatically calibrating a collision model of a whole car, which can quickly adjust a simulation model according to initial input of an experiment to obtain a more accurate CAE whole car model.
The invention adopts the technical scheme that:
In one aspect, a method for automatically calibrating a vehicle crash model according to an initial test input is provided, comprising:
s10, inputting parameters of a test real vehicle;
S20, judging collision working conditions, and updating the speed of the whole vehicle model according to the working conditions;
S30, cleaning the whole vehicle model to obtain a pure whole vehicle model;
S40, performing trial calculation based on the pure whole vehicle model to obtain the total mass of the whole vehicle model and the X-direction centroid coordinate;
S50, calculating a difference value between the X-direction centroid coordinates of the whole vehicle model and the X-direction centroid coordinates of the test real vehicle; if the difference value is smaller than a preset value, the whole vehicle model calibration is completed; if the difference is greater than the preset value, executing step S60;
S60, calculating the mass required to be increased or decreased of the front axle and the rear axle of the whole vehicle model according to the parameters input in the step S10 and the total mass and the X-direction centroid coordinates of the whole vehicle model obtained in the step S40;
S70, correspondingly increasing and decreasing the mass required to be increased and decreased of the front shaft and the rear shaft obtained in the step S60 on a sheet metal part at the front end of a vehicle body and a sheet metal part at the rear end of the vehicle body of the whole vehicle model respectively; returning to step S40.
Further, the parameters input in the step S10 include: instantaneous collision speed, mass of a front axle of the whole vehicle, mass of a rear axle of the whole vehicle, X-direction barycenter coordinates of the front axle of the whole vehicle and X-direction barycenter coordinates of the rear axle of the whole vehicle.
Further, the step S10 further includes:
checking the input parameters, including checking whether the input is digital, checking the parameter unit and checking the mass center range, wherein the mass unit is kg, the speed unit is km/h and the coordinate unit is mm.
Further, the step S20: judging collision working conditions, and updating collision speed according to the working conditions, wherein the method specifically comprises the following steps:
Judging whether the collision test is a frontal collision working condition or a side collision working condition according to the barrier file in the model; if the collision working condition is met, updating the whole vehicle speed and the wheel rotating speed of the model based on the parameters input in the step S10; and if the vehicle is in the side collision working condition, updating the whole vehicle speed of the model based on the parameters input in the step S10.
Further, the step S30: cleaning the whole vehicle model to obtain a pure whole vehicle model, which specifically comprises the following steps: the barrier and ground in the model are annotated so that a clean complete vehicle model is obtained.
Further, the step S40: based on the pure whole vehicle model, trial calculation is carried out, and the total mass and X-direction centroid coordinates of the whole vehicle model are obtained, and the method specifically comprises the following steps:
and performing trial calculation based on the pure whole vehicle model, and obtaining the total mass and X-direction centroid coordinates of the whole vehicle model by traversing LIS files generated during the trial calculation.
Further, in the step S60, the method for calculating the mass of the front axle and the rear axle of the whole vehicle model, which needs to be increased or decreased, is as follows:
The mass of the rear axle which needs to be increased or decreased is as follows: the mass of the rear axle of the real vehicle- (the X-direction barycenter coordinate of the whole vehicle model-the X-direction barycenter coordinate of the front axle of the real vehicle) is multiplied by the total mass of the whole vehicle model/the X-direction barycenter coordinate of the front axle of the real vehicle;
The mass of the front axle which needs to be increased or decreased is as follows: front axle mass of real vehicle- (total mass of whole vehicle model-front axle mass of whole vehicle model).
Further, in the step S50, after the calibration of the whole vehicle model is completed, the barrier and the ground annotation are released.
In another aspect, a system for automatically calibrating a vehicle crash model based on a test initiation input is provided, comprising:
The test parameter input module is used for inputting test real vehicle parameters;
the speed modification module is used for judging collision working conditions and updating the speed of the whole vehicle model according to the working conditions;
The model cleaning module is used for annotating and de-annotating barriers and the ground in the model;
The model trial calculation module is used for carrying out trial calculation on the whole vehicle model so as to obtain the total mass of the whole vehicle model and the X-direction centroid coordinates;
And the whole vehicle counterweight module is used for updating the counterweight of the whole vehicle model according to the trial calculation result and the real vehicle parameters.
In yet another aspect, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the above method.
By adopting the scheme of the invention, the CAE simulation model of the whole vehicle can be updated rapidly according to the real parameters of the test vehicle, the X-direction centroid coordinate error of the model of the whole vehicle is controlled within 1mm through iterative calculation, and the accuracy of the collision model of the whole vehicle is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a schematic diagram of a complete vehicle coordinate system employed in the present invention;
FIG. 2 illustrates a flow chart of a method of automatically calibrating a vehicle crash model based on a trial initial input in accordance with one embodiment of the invention;
FIG. 3 shows a flowchart of a method of automatically calibrating a vehicle crash model based on experimental initial inputs in accordance with another embodiment of the invention.
Detailed Description
The above and further technical features and advantages of the present invention are described in more detail below with reference to the accompanying drawings.
In the description of the invention, the words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (stated condition or event)" may be interpreted as "when determined" or "in response to determination" or "when detected (stated condition or event)" or "in response to detection (stated condition or event), depending on the context.
Fig. 1 shows a whole vehicle coordinate system adopted in the present invention, wherein the X-direction mentioned in the present invention corresponds to the X-coordinate axis direction in the whole vehicle coordinate system shown in fig. 1, and the X-direction centroid coordinate is the coordinate position of the centroid on the X-coordinate axis.
An embodiment of the present application provides a method for automatically calibrating a complete vehicle collision model according to an initial test input, as shown in fig. 2, fig. 2 shows a flowchart of an automatic calibration method according to an embodiment of the present application, so as to quickly update a complete vehicle CAE simulation model according to actual parameters of a test vehicle.
S10: inputting parameters of a test real vehicle;
S20: judging collision working conditions, and updating the speed of the whole vehicle model according to the working conditions;
s30: cleaning the whole vehicle model to obtain a pure whole vehicle model;
s40: performing trial calculation based on the pure whole vehicle model to obtain the total mass of the whole vehicle model and the X-direction centroid coordinate;
S50: calculating the difference between the X-direction centroid coordinates of the whole vehicle model and the X-direction centroid coordinates of the test real vehicle; if the difference value is smaller than a preset value, the whole vehicle model calibration is completed; if the difference is greater than the preset value, executing step S60;
S60: calculating the mass required to be increased or decreased of the front axle and the rear axle of the whole vehicle model according to the parameters input in the step S10 and the total mass and the X-direction barycenter coordinate of the whole vehicle model obtained in the step S40;
s70: the mass of the front axle and the rear axle which are obtained in the step S60 and need to be increased or decreased is correspondingly increased or decreased on a sheet metal part at the front end of the vehicle body and a sheet metal part at the rear end of the vehicle body of the whole vehicle model respectively; returning to step S40.
Before simulation experiments are carried out, parameters of a simulation model are required to be adjusted, and barycenter coordinates of the model and barycenter coordinates of a real vehicle are difficult to be adjusted to be consistent, so that simulation precision of collision of the whole vehicle is affected. In order to solve the problem, in this embodiment, the mass to be added to the front axle and the rear axle is calculated according to the mass and the mass center of the current model and the mass center of the target model, and the mass cannot be directly added to the front axle and the rear axle, so that the mass is added to the front end sheet metal part and the rear end sheet metal part of the vehicle body to replace the front end sheet metal part and the rear end sheet metal part, and therefore, each time of modification can make the mass and the mass center of the model close to the mass center of the real vehicle, but because the mass center of the front end sheet metal part and the rear end sheet metal part is different from the mass center of the axle, repeated calculation is needed for a plurality of times to approach the required value, so that the accuracy of the collision model of the whole vehicle is ensured.
An exemplary specific scheme is:
Step one: the input and identification of the parameters of the test real vehicle comprise instantaneous collision speed, mass of the front axle of the whole vehicle, mass of the rear axle of the whole vehicle, X-direction barycenter coordinates of the front axle of the whole vehicle and X-direction barycenter coordinates of the rear axle of the whole vehicle. The input quality unit of the identification and control parameters is kg, the speed unit is km/h, and the X coordinate unit is mm.
Step two: and (5) identifying a speed control keyword and automatically updating the speed of the whole vehicle model. Judging whether the collision test is a frontal collision working condition or a side collision working condition according to the barrier file in the model. For example, a keyword 'INVEL' is defined according to the speed of the collision searching whole vehicle model, and a keyword control range is judged: vehicle body/tire, whether to change the tire rotation speed is controlled according to the type of barrier: the updating speed is input according to the instantaneous collision speed in the first step, and if the instantaneous collision speed is the frontal collision working condition, the whole speed and the wheel rotating speed of the model are updated; and if the vehicle is in the side collision working condition, updating the speed of the whole vehicle of the model.
Step three: and cleaning the whole vehicle model. Searching barrier and ground definition files and related contact definition key fields in the model, annotating the barrier and ground definition files to obtain a pure whole vehicle model;
Step four: and (3) automatically iterating and calculating the model, and calculating the mass required to be increased or decreased of the front axle and the rear axle of the whole vehicle model. The whole vehicle model can determine the accurate quality and mass center through trial calculation, and a person skilled in the art can know that the trial calculation can be completed by calling the existing trial calculation script, namely, a solver can check the model and run a time step before the formal calculation of the model, the calculation can be defined in the model after the trial calculation, and the quality and mass center of the whole vehicle model can be obtained through traversing lis files.
Step five: and (5) a whole car weight balancing scheme, weight balancing keyword identification and automatic update. According to the whole vehicle model definition mode, the balance weight is increased and decreased through the balance weight key words of the vehicle body sheet metal part. According to the fixed ID numbers of the automobile parts, the sheet metal part of which the front end is close to the front shaft and the sheet metal part of which the rear end is close to the rear shaft are provided with fixed ID ranges, and the weight increase and decrease of the sheet metal part of the front end and the rear end of the whole automobile model are finished through detection keywords (such as NSMAS), so that the aim of changing the weight of the front shaft and the rear shaft is fulfilled.
Step six: returning to the fourth step, automatically checking and updating the vehicle weight and controlling the error of the X-direction coordinate. Through multiple trial calculations and weight change, the error of the X-direction coordinate of the whole vehicle model meets the requirements, and finally the calibration of the model is realized.
In another embodiment of the present application, a method for automatically calibrating a crash model of a whole vehicle based on an initial input of a test is provided, as shown in fig. 3.
Step 1, acquiring an instantaneous collision speed V, a front axle mass M1 of the whole vehicle, a rear axle mass M2 of the whole vehicle, a front axle mass X1 of the whole vehicle and a rear axle mass X2 of the whole vehicle through experimental real vehicle parameter input.
And 2, judging the accuracy of the input parameters, including judging whether the input parameters are numbers, judging parameter units and judging mass center range, and re-inputting if the input is wrong.
And 3, judging the working condition, and judging whether the working condition is a frontal collision working condition according to the barrier file in the model.
And 4, if the collision working condition is met, the speed of the whole vehicle and the rotation speed of wheels need to be updated.
And 5, updating the speed of the whole vehicle under other working conditions.
And 6. Annotating the barriers and the ground in the model to obtain a pure whole vehicle model (because the barriers and the ground model also have mass, the annotation is used for enabling the barriers and the ground model not to participate in later trial calculation and ensuring accurate data of the mass and the mass center of the whole vehicle).
And 7, model trial calculation, namely calling a trial calculation script to carry out trial calculation, dynamically displaying the trial calculation process, monitoring LIS files generated during the trial calculation in real time, and ending the execution of the next step.
And 8, acquiring the total mass and the barycenter coordinates of the model, and acquiring the total mass M0 and the barycenter X-direction coordinates X0 of the model by traversing the LIS file generated in the step 27.
And 9, judging the error between the current mass center and the mass center of the real vehicle, if the error is smaller than 1mm, executing the step 10, and if the error is larger than 1mm, executing the step 11.
And 10, removing the comments of the barrier and the ground, and completing the calibration of the whole vehicle model.
And 11, calculating the mass to be increased or decreased on the front and rear axes, and calculating the mass MF and MH to be increased or decreased on the front and rear axes of the model according to the parameters in the step 1 and the total mass and mass center coordinates of the model obtained in the step 8.
Step 10, identifying a counterweight keyword, adding mass to be increased or decreased of a front axle and a rear axle of the model to sheet metal parts of a vehicle body at the front end and the rear end of the model, increasing or decreasing mass MF of the sheet metal parts at the front end of the vehicle body, and increasing or decreasing mass MH of the sheet metal parts at the rear end of the vehicle body; after which the process returns to step 7.
Preferably, in step 11, the calculation method for calculating the mass MF and MH of the front and rear axes of the model, which need to be increased or decreased, is as follows:
The mass of the rear axle which needs to be increased or decreased is as follows: the mass of the rear axle of the real vehicle- (the X-direction barycenter coordinate of the whole vehicle model-the X-direction barycenter coordinate of the front axle of the real vehicle) is multiplied by the total mass of the whole vehicle model/the X-direction barycenter coordinate of the front axle of the real vehicle;
The mass of the front axle which needs to be increased or decreased is as follows: front axle mass of real vehicle- (total mass of whole vehicle model-front axle mass of whole vehicle model).
In one embodiment, according to a second aspect of the present invention, there is provided a system for automatically calibrating a vehicle crash model based on a test initiation input, comprising:
The test parameter input module is used for inputting test real vehicle parameters;
the speed modification module is used for judging collision working conditions and updating the speed of the whole vehicle model according to the working conditions;
The model cleaning module is used for annotating and de-annotating barriers and the ground in the model;
The model trial calculation module is used for carrying out trial calculation on the whole vehicle model so as to obtain the total mass of the whole vehicle model and the X-direction centroid coordinates;
And the whole vehicle counterweight module is used for updating the counterweight of the whole vehicle model according to the trial calculation result and the real vehicle parameters.
The test real vehicle parameters include: instantaneous collision speed, mass of a front axle of the whole vehicle, mass of a rear axle of the whole vehicle, X-direction barycenter coordinates of the front axle of the whole vehicle and X-direction barycenter coordinates of the rear axle of the whole vehicle. The test parameter input module is also used for checking input parameters, including checking whether the input is digital, checking parameter units and checking mass center range, wherein the mass units are kg, the speed units are km/h, and the coordinate units are mm.
The speed modification module judges whether the collision test is a frontal collision working condition or a side collision working condition according to the barrier file in the model; if the collision working condition is met, updating the whole vehicle speed and the wheel rotating speed of the model; and if the vehicle is in the side collision working condition, updating the speed of the whole vehicle of the model.
The model trial calculation module performs trial calculation based on the pure whole vehicle model, and obtains the total mass of the whole vehicle model and the X-direction centroid coordinate by traversing LIS files generated during the trial calculation.
And the whole car counterweight module calculates the mass required to be increased or decreased of the front shaft and the rear shaft of the whole car model, and correspondingly increases or decreases the obtained mass required to be increased or decreased of the front shaft and the rear shaft on the sheet metal part at the front end of the car body and the sheet metal part at the rear end of the car body of the whole car model respectively.
The method for calculating the mass of the front axle and the rear axle of the whole vehicle model, which needs to be increased or decreased, comprises the following steps:
The mass of the rear axle which needs to be increased or decreased is as follows: the mass of the rear axle of the real vehicle- (the X-direction barycenter coordinate of the whole vehicle model-the X-direction barycenter coordinate of the front axle of the real vehicle) is multiplied by the total mass of the whole vehicle model/the X-direction barycenter coordinate of the front axle of the real vehicle;
The mass of the front axle which needs to be increased or decreased is as follows: front axle mass of real vehicle- (total mass of whole vehicle model-front axle mass of whole vehicle model).
In one embodiment, according to a third aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above method of automatically calibrating a vehicle crash model based on experimental initial inputs. Accordingly, the computer-readable storage medium has all the advantageous effects of the method, and is not described in detail herein.
The foregoing description of the preferred embodiment of the invention is merely illustrative of the invention, and is not intended to be limiting. The structure, connection mode and the like of each component in the invention can be changed, and all equivalent changes and improvements performed on the basis of the technical scheme of the invention are not excluded from the protection scope of the invention.
Claims (10)
1. A method for automatically calibrating a crash model of a whole vehicle based on an initial input of a test, comprising:
s10, inputting parameters of a test real vehicle;
S20, judging collision working conditions, and updating the speed of the whole vehicle model according to the working conditions;
S30, cleaning the whole vehicle model to obtain a pure whole vehicle model;
S40, performing trial calculation based on the pure whole vehicle model to obtain the total mass of the whole vehicle model and the X-direction centroid coordinate;
S50, calculating a difference value between the X-direction centroid coordinates of the whole vehicle model and the X-direction centroid coordinates of the test real vehicle; if the difference value is smaller than a preset value, the whole vehicle model calibration is completed; if the difference is greater than the preset value, executing step S60;
S60, calculating the mass required to be increased or decreased of the front axle and the rear axle of the whole vehicle model according to the parameters input in the step S10 and the total mass and the X-direction centroid coordinates of the whole vehicle model obtained in the step S40;
S70, correspondingly increasing and decreasing the mass required to be increased and decreased of the front shaft and the rear shaft obtained in the step S60 on a sheet metal part at the front end of a vehicle body and a sheet metal part at the rear end of the vehicle body of the whole vehicle model respectively; returning to step S40.
2. A method for automatically calibrating a crash model of a vehicle based on initial inputs of a test as set forth in claim 1, wherein said parameters input in step S10 include: instantaneous collision speed, mass of a front axle of the whole vehicle, mass of a rear axle of the whole vehicle, X-direction barycenter coordinates of the front axle of the whole vehicle and X-direction barycenter coordinates of the rear axle of the whole vehicle.
3. A method for automatically calibrating a crash model of a vehicle based on an initial input of a test as recited in claim 2, wherein said step S10 further comprises:
checking the input parameters, including checking whether the input is digital, checking the parameter unit and checking the mass center range, wherein the mass unit is kg, the speed unit is km/h and the coordinate unit is mm.
4. A method for automatically calibrating a crash model of a vehicle based on an initial test input as recited in claim 2, wherein said step S20: judging collision working conditions, and updating collision speed according to the working conditions, wherein the method specifically comprises the following steps:
Judging whether the collision test is a frontal collision working condition or a side collision working condition according to the barrier file in the model; if the collision working condition is met, updating the whole vehicle speed and the wheel rotating speed of the model based on the parameters input in the step S10; and if the vehicle is in the side collision working condition, updating the whole vehicle speed of the model based on the parameters input in the step S10.
5. A method for automatically calibrating a crash model of a vehicle based on an initial test input as set forth in claim 1, wherein said step S30: cleaning the whole vehicle model to obtain a pure whole vehicle model, which specifically comprises the following steps:
the barrier and ground in the model are annotated so that a clean complete vehicle model is obtained.
6. A method for automatically calibrating a crash model of a vehicle based on an initial test input as recited in claim 1, wherein said step S40: based on the pure whole vehicle model, trial calculation is carried out, and the total mass and X-direction centroid coordinates of the whole vehicle model are obtained, and the method specifically comprises the following steps:
and performing trial calculation based on the pure whole vehicle model, and obtaining the total mass and X-direction centroid coordinates of the whole vehicle model by traversing LIS files generated during the trial calculation.
7. The method for automatically calibrating a collision model of a vehicle according to an initial test input of claim 1, wherein in the step S60, the method for calculating the mass of the front and rear axles of the vehicle model to be increased or decreased is as follows:
The mass of the rear axle which needs to be increased or decreased is as follows: the mass of the rear axle of the real vehicle- (the X-direction barycenter coordinate of the whole vehicle model-the X-direction barycenter coordinate of the front axle of the real vehicle) is multiplied by the total mass of the whole vehicle model/the X-direction barycenter coordinate of the front axle of the real vehicle;
The mass of the front axle which needs to be increased or decreased is as follows: front axle mass of real vehicle- (total mass of whole vehicle model-front axle mass of whole vehicle model).
8. The method according to claim 5, wherein in step S50, after the calibration of the whole vehicle model is completed, the barrier and the ground annotation are released.
9. A system for automatically calibrating a crash model of a vehicle based on an initial input of a test, comprising:
The test parameter input module is used for inputting test real vehicle parameters;
the speed modification module is used for judging collision working conditions and updating the speed of the whole vehicle model according to the working conditions;
The model cleaning module is used for annotating and de-annotating barriers and the ground in the model;
The model trial calculation module is used for carrying out trial calculation on the whole vehicle model so as to obtain the total mass of the whole vehicle model and the X-direction centroid coordinates;
And the whole vehicle counterweight module is used for updating the counterweight of the whole vehicle model according to the trial calculation result and the real vehicle parameters.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211257690.XA CN117932843A (en) | 2022-10-13 | 2022-10-13 | Method, system and storage medium for automatically calibrating whole vehicle collision model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211257690.XA CN117932843A (en) | 2022-10-13 | 2022-10-13 | Method, system and storage medium for automatically calibrating whole vehicle collision model |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117932843A true CN117932843A (en) | 2024-04-26 |
Family
ID=90761637
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211257690.XA Pending CN117932843A (en) | 2022-10-13 | 2022-10-13 | Method, system and storage medium for automatically calibrating whole vehicle collision model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117932843A (en) |
-
2022
- 2022-10-13 CN CN202211257690.XA patent/CN117932843A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107590322B (en) | Drive shaft jumping checking method | |
| CN108801387B (en) | System and method for measuring remaining oil quantity of airplane fuel tank based on learning model | |
| CN107292013B (en) | Method and device for testing strength of suspension system | |
| CN110263414B (en) | Method for predicting frictional abnormal sound danger points of automotive interior system | |
| TW200912249A (en) | Method for determining dynamic errors in a measuring machine | |
| JP2004177191A (en) | Method and device for judging damaged part | |
| CN113433950B (en) | Vehicle control data calibration method, device, computer equipment and storage medium | |
| CN115510553A (en) | Modeling method and device for predicting tire failure in small offset collision | |
| CN116223066B (en) | Method, equipment and medium for evaluating biological fidelity of chest of automobile collision dummy | |
| CN111753463A (en) | Active control method for running deviation of vehicle | |
| US20110238401A1 (en) | Structural Optimization for Vehicle Crashworthiness | |
| CN117932843A (en) | Method, system and storage medium for automatically calibrating whole vehicle collision model | |
| Ünal et al. | Real-time hardware-in-the-loop simulation of time to rollover warning for heavy commercial vehicles | |
| CN113696890B (en) | Lane keeping method, apparatus, device, medium, and system | |
| Zhu et al. | Lateral stability simulation and analysis for wheel loaders based on the steady-state margin angle | |
| CN115081116A (en) | Method and system for calculating maximum stress of vehicle chassis part and storage medium | |
| Kanchwala et al. | Model Building, Hardpoint Optimization & Experimental Correlation of a Single Seater EV-Toyota COMS | |
| CN108537791A (en) | A kind of stamping parts punching online test method based on machine vision | |
| CN114818123A (en) | Method for calibrating control stability of complete vehicle dynamic model and storage medium | |
| JP5059084B2 (en) | Design support program and design support apparatus | |
| CN113361079A (en) | Road surface flatness detection method, device, equipment and storage medium | |
| CN106896240A (en) | A kind of automotive speed sensor test experimental bed and its method of testing | |
| CN113836737B (en) | Tire interference risk monitoring method, device and equipment | |
| CN114861335B (en) | Calibration method of automobile dynamics calculation model and related equipment | |
| JP2021088227A (en) | Avoidance vehicle maneuver assist system and avoidance maneuver assist method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination |