KR101661102B1 - Tuning Method of Vehicle Using 3D Scan Data - Google Patents
Tuning Method of Vehicle Using 3D Scan Data Download PDFInfo
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- KR101661102B1 KR101661102B1 KR1020150137790A KR20150137790A KR101661102B1 KR 101661102 B1 KR101661102 B1 KR 101661102B1 KR 1020150137790 A KR1020150137790 A KR 1020150137790A KR 20150137790 A KR20150137790 A KR 20150137790A KR 101661102 B1 KR101661102 B1 KR 101661102B1
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- G06F17/5009—
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/20—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring contours or curvatures, e.g. determining profile
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- G06F17/5095—
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- Vehicle Body Suspensions (AREA)
Abstract
Description
The present invention relates to a vehicle tuning simulation method using 3D scan data, and more particularly, to a method of performing a vehicle tuning simulation through a vehicle model made using 3D scan data.
The existing virtual tuning environment does not properly reflect actual vehicle information and is utilized at the level of a game, which does not provide accurate tuning results.
And since the carmaker does not provide specific information on the car model, it was difficult to construct an analytical model that would yield results similar to those of the test maker.
For this reason, you have no choice but to tune the actual vehicle to see the correct tuning results.
In this case, in order to change the parts of the vehicle according to the purpose of tuning and to predict the performance of the tuning part, expert knowledge is required, and the cost burden is large and it is difficult to recognize the satisfaction after tuning in advance.
The inventors of the present invention have focused on a tuning method using 3D scan data and have conducted research and development thereof in order to solve the problems of the related art.
The 3D scan data is used as a technique for performing the diagnosis of a vehicle.
For example, Japanese Unexamined Patent Publication (Kokai) No. 2003-285701 discloses a vehicle diagnosis system in which a diagnosis area is moved by a scanning unit to display a diagnosis target area, thereby displaying a failure area.
Korean Patent Laid-Open Publication No. 10-2005-0070548 discloses a component deformation system that can easily and accurately measure the deformation degree and degree of a component to be inspected by measuring component deformation using a 3D scanner.
Therefore, by using such 3D scan data for vehicle tuning, a simulation method that can perform effective vehicle tuning at low cost can be derived.
SUMMARY OF THE INVENTION The present invention has been made in order to solve the problems of the related art as described above, and it is an object of the present invention to provide a tuning vehicle, And to provide a tuning simulation method capable of performance evaluation similar to the verification and test.
It is another object of the present invention to provide a method of performing vehicle tuning simulation so as to enable efficient tuning at low cost.
According to another aspect of the present invention, there is provided a method of tuning a vehicle using 3D scan data, the method including: a scan data forming step of scanning a vehicle part in 3D; An analysis data generation step of generating 3D CAD data, hard point extraction data, and mass information calculation data from the scan data; And constructing a vehicle analysis model through the analysis data.
The method may further include the step of storing the vehicle analysis model in a database, the step of replacing or inputting a tuning part from a vehicle analysis model stored in the database, or a step of replacing the tuning part, And outputting the output signal.
In addition, the step of replacing the tuning parts from the vehicle analysis model includes: Replacing the replacement input tuning part; Performing a performance evaluation analysis according to the replaced tuning part; And outputting a performance evaluation result according to the performance evaluation analysis.
The vehicle tuning simulation method according to the present invention can use the 3D scan data to enable the user to change the parts of the vehicle according to the purpose of tuning without the need for expert knowledge and predict the performance thereof, .
The vehicle tuning simulation method according to the present invention can be used to obtain dynamic loads and stresses to be received by a component maker, which is difficult to secure vehicle information, while the vehicle is being driven, by an analytical method.
The vehicle tuning simulation method according to the present invention can facilitate an analytical approach to a tuning vehicle even in a tuning company in which 3D CAD modeling and vehicle simulation are difficult.
1 is a conceptual diagram of a process of constructing a vehicle analysis model according to the present invention.
2 is a conceptual diagram illustrating a process of performing a tuning simulation through a vehicle analysis model according to the present invention.
Hereinafter, the present invention will be described in detail.
The vehicle tuning simulation method of the present invention uses a precise vehicle analysis model similar to an actual vehicle using 3D scan data to enable tuning simulation.
This vehicle analysis model allows the user to evaluate vehicle performance without expert knowledge.
It also provides precise performance evaluation results for tuned vehicles, allowing users to optimize tuning without trial and error. In addition, since the appearance of the tuning vehicle can be confirmed through the simulation, it is possible to make the tuning desired by the user.
The vehicle tuning simulation method of the present invention includes: a scan data forming step of scanning a vehicle part in 3D, as shown in FIG. 1; An analysis data generation step of generating 3D CAD data, hard point extraction data, and mass information calculation data from the scan data; And constructing a vehicle analysis model through the analysis data, wherein the simulation is enabled through the stored vehicle analysis model by storing the vehicle analysis model in a database.
The vehicle analysis model applied to the tuning simulation of the present invention is a multibody dynamics analysis model in which flexible elements can be considered.
The multibody dynamic analysis model is a numerical model composed of a plurality of rigid bodies, spring elements, and kinematic constraints.
At this time, the kinematic structure is based on points in space called a hard point.
The hard point refers to a reference point that defines the position and posture of various links.
Further, the flexible element is applied to several specific parts such as a stabilizer bar and a trailing arm in order to increase the reliability of the analysis result.
Unlike the conventional tuning process, the present invention uses a 3D scan data and a component test result to construct a highly accurate vehicle analysis model.
A method for producing such a vehicle analysis model is as follows.
A 3D scan is performed on the actual vehicle components constituting the front / rear suspension, the front / rear wheel sub frame, the steering wheel, and the like, and 3D CAD data is generated through the 3D scan.
In addition, hard points are extracted from the 3D CAD data of the generated parts and the part mass information is calculated.
Separately, the stiffness values are derived from the stiffness tests of the main bushes and suspension springs such as the subframe bushes and the engine mount bushes, and the damping coefficient is determined by testing the damping force of the main bushes and suspension damper. , Dampers, subframes, various links, etc., to derive density, elastic modulus and tensile strength.
Thus, the vehicle analysis model is constructed using the hard points, parts, and material information obtained from the 3D scan data and the simulation test.
Such a vehicle analysis model is stored in a database, and a vehicle performance evaluation simulation is performed.
Generally, vehicle performance means fuel efficiency, power performance, braking performance, steering stability, endurance performance, vibration / ride comfort, and noise performance.
At this time, the fuel efficiency evaluation is based on the domestic combined fuel consumption mode, the US combined fuel consumption mode, the NEDC mode, and the JC08 mode, and the power performance is evaluated through the acceleration performance and the ramp performance of the ramp.
In addition, the braking performance evaluates both rapid braking performance and braking stability such as vehicle leaning. The stability of the braking performance is assessed for transient response, heading turn, hand lay stability, lane change, slam course, straight stability, and frequency response.
The durability performance evaluates the component fatigue life due to the durability of the road surface and the design stress of the part according to the maximum load action. The vibration / ride feeling is evaluated by shimmy, shake, steering wheel kickback, And the noise performance evaluates exhaust noise and engine noise from the driver's seat and outside the vehicle.
The present invention can provide a configuration and performance evaluation method of an automated tuning vehicle model.
That is, it is characterized by automating the configuration of the vehicle analysis model and the performance evaluation analysis so that the user can evaluate the performance of the vehicle without expert knowledge.
In addition, the tuning target part has the hard point of the specific ID in advance for the position where it is assembled in the vehicle, and the parts are subordinate to the hard point of the vehicle, And then automatically assembles the tuning part model into the vehicle model.
In addition, the performance evaluation analysis is performed through multibody dynamics analysis based on the scenario corresponding to the performance evaluation definition 5 times.
Since the result of the evaluation of the performance of the vehicle includes a number of results of the test (analysis), three indexes are provided according to the performance of the vehicle to provide useful results to the user.
The exponentiation method can be determined by summing the results of individual tests (analysis) times the weight factors.
Finally, the vehicle tuning simulation method of the present invention can confirm the appearance of the tuning vehicle without directly tuning.
In other words, since the 3D scan data is used, it is possible to confirm almost the same vehicle design. The replacement of the tuning parts is automated by using the hard point, so that the appearance change can be confirmed in three dimensions.
While the present invention has been described with reference to the preferred embodiments thereof, it is to be understood that the present invention is not limited to the above-described embodiments. Those skilled in the art can, It is obvious that various changes can be made within the scope of the present invention.
Claims (6)
An analysis data generation step of generating 3D CAD data, hard point extraction data, and mass information calculation data from the scan data;
Constructing a vehicle analysis model through the analysis data;
Storing the vehicle analysis model in a database;
Replacing a tuning part from a vehicle analysis model stored in the database;
Replacing the replacement input tuning part;
Performing a performance evaluation analysis according to the replaced tuning part;
And outputting a performance evaluation result according to the performance evaluation analysis.
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| Application Number | Priority Date | Filing Date | Title |
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| KR1020150137790A KR101661102B1 (en) | 2015-09-30 | 2015-09-30 | Tuning Method of Vehicle Using 3D Scan Data |
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| Application Number | Priority Date | Filing Date | Title |
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| KR1020150137790A KR101661102B1 (en) | 2015-09-30 | 2015-09-30 | Tuning Method of Vehicle Using 3D Scan Data |
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| KR101661102B1 true KR101661102B1 (en) | 2016-09-30 |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108121866A (en) * | 2017-12-07 | 2018-06-05 | 山东工艺美术学院 | A kind of city planning design intelligent noumenon model building method |
| KR20210008968A (en) * | 2019-07-15 | 2021-01-26 | 현대자동차주식회사 | System and method for providing service of chancing vehicle parts |
| KR20220135528A (en) | 2021-03-30 | 2022-10-07 | 이호진 | Vehicle tuning service method using augmented reality |
| KR102454452B1 (en) * | 2022-07-11 | 2022-10-14 | 주식회사 에이투지오토 | Method, device and system for processing reverse engineering of car body structure using 3d scan data |
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| KR20050070548A (en) | 2003-12-30 | 2005-07-07 | 주식회사 팬택앤큐리텔 | Mobile communication terminal having wave observative means |
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| KR101550137B1 (en) * | 2014-03-31 | 2015-09-03 | 쌍용자동차 주식회사 | Measuring method of sealing gap with 3D scanning |
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2015
- 2015-09-30 KR KR1020150137790A patent/KR101661102B1/en active IP Right Grant
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| JP2003186917A (en) * | 2001-12-18 | 2003-07-04 | Mitsubishi Heavy Ind Ltd | Vehicle virtual performance evaluating device |
| JP2003285701A (en) | 2002-03-28 | 2003-10-07 | Calsonic Kansei Corp | Vehicle diagnosis system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108121866A (en) * | 2017-12-07 | 2018-06-05 | 山东工艺美术学院 | A kind of city planning design intelligent noumenon model building method |
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| KR102391007B1 (en) * | 2019-07-15 | 2022-04-27 | 현대자동차주식회사 | System and method for providing service of chancing vehicle parts |
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| KR20220135528A (en) | 2021-03-30 | 2022-10-07 | 이호진 | Vehicle tuning service method using augmented reality |
| KR102454452B1 (en) * | 2022-07-11 | 2022-10-14 | 주식회사 에이투지오토 | Method, device and system for processing reverse engineering of car body structure using 3d scan data |
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