CN114879536B - Method and device for acquiring real-time characteristics of suspension system based on digital twinning technology - Google Patents
Method and device for acquiring real-time characteristics of suspension system based on digital twinning technology Download PDFInfo
- Publication number
- CN114879536B CN114879536B CN202210810109.6A CN202210810109A CN114879536B CN 114879536 B CN114879536 B CN 114879536B CN 202210810109 A CN202210810109 A CN 202210810109A CN 114879536 B CN114879536 B CN 114879536B
- Authority
- CN
- China
- Prior art keywords
- suspension system
- suspension
- real
- simulation model
- whole vehicle
- 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.)
- Active
Links
- 239000000725 suspension Substances 0.000 title claims abstract description 191
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000005516 engineering process Methods 0.000 title claims abstract description 18
- 238000004088 simulation Methods 0.000 claims abstract description 93
- 238000000418 atomic force spectrum Methods 0.000 claims abstract description 47
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 42
- 238000006073 displacement reaction Methods 0.000 claims abstract description 33
- 238000013016 damping Methods 0.000 claims abstract description 30
- 238000004364 calculation method Methods 0.000 claims abstract description 14
- 238000012360 testing method Methods 0.000 claims description 31
- 239000006096 absorbing agent Substances 0.000 claims description 18
- 230000035939 shock Effects 0.000 claims description 18
- 238000004519 manufacturing process Methods 0.000 claims description 9
- 238000012795 verification Methods 0.000 claims description 7
- 238000011161 development Methods 0.000 abstract description 8
- 238000012938 design process Methods 0.000 abstract description 3
- 238000004904 shortening Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012804 iterative process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
- G01M17/04—Suspension or damping
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2206/00—Indexing codes related to the manufacturing of suspensions: constructional features, the materials used, procedures or tools
- B60G2206/01—Constructional features of suspension elements, e.g. arms, dampers, springs
- B60G2206/90—Maintenance
- B60G2206/99—Suspension element selection procedure depending on loading or performance requirements, e.g. selection of damper, spring or bush
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/25—Stroke; Height; Displacement
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60G—VEHICLE SUSPENSION ARRANGEMENTS
- B60G2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
- B60G2400/50—Pressure
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- Automation & Control Theory (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- Aviation & Aerospace Engineering (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Vehicle Body Suspensions (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method and a device for acquiring real-time characteristics of a suspension system based on a digital twinning technology, wherein the method comprises the following steps: collecting mechanical change and displacement change signals of a suspension system; calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system; building a finished automobile simulation model, and performing iterative updating of the characteristics of a suspension system and simulation of finished automobile operation stability and smoothness according to the obtained hysteresis force curve; and outputting optimized suspension damping and rigidity parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target. The invention can obtain the real-time suspension characteristics without using a rack, and transmits the result to the whole vehicle simulation model in real time, thereby meeting the requirement of digital twin calculation, greatly simplifying the design process of the suspension system, improving the efficiency and the precision and shortening the development cycle of the suspension system.
Description
Technical Field
The invention relates to a method and a device for acquiring real-time characteristics of a suspension system based on a digital twinning technology, and belongs to the technical field of animation production.
Background
In the forward development of automobiles, the suspension system is the most important subsystem, namely, all the force and moment transmission connecting devices between the frame and the wheels of the automobile, the function of the suspension system is to transmit the force and the moment acting between the wheels and the frame, and buffer the impact force transmitted to the frame or the automobile body from an uneven road surface and damp the vibration caused by the impact force, so as to ensure that the automobile can run smoothly and safely. The rigidity and damping characteristics (generally called as suspension system characteristics) of a suspension system have a crucial influence on the steering stability and smoothness of an automobile, the accuracy of a suspension system characteristic result and the economy of an acquisition means directly influence the development cycle and the cost of the whole automobile, and how to acquire accurate suspension characteristics by adopting a lower-cost and higher-efficiency means is a problem which needs to be solved urgently.
The existing suspension system mainly designs the characteristics of the suspension system according to the operation stability and the smoothness of the whole vehicle by combining experience or a calibration result, and a suspension sample which is manufactured in a trial mode needs to be installed on a professional test bed, a relevant test is carried out to obtain characteristic parameters, and the characteristic parameters are used as boundary conditions and input to a multi-body dynamic model of the whole vehicle for use.
However, the performance of the existing suspension system is mainly acquired by a professional test bed, so that the acquisition cost is high and professional equipment is seriously relied on; the simulation model is constructed according to the given input of the bench result, the influence of the assembly state of the real vehicle on the characteristics of the suspension system is not considered, so that the simulation precision is lower and the result is influenced; meanwhile, the characteristic acquisition process and the whole vehicle simulation are performed in sequence, and real-time interaction cannot be realized, so that the development cycle is greatly limited.
Disclosure of Invention
In order to solve the problems, the invention provides a method and a device for acquiring the real-time characteristic of a suspension system based on a digital twinning technology, which can acquire the real-time suspension characteristic without using a rack, transmit the result to a whole vehicle simulation model in real time, meet the requirement of digital twinning calculation and shorten the development cycle of the suspension system.
The technical scheme adopted for solving the technical problems is as follows:
on one hand, the method for acquiring the real-time characteristics of the suspension system based on the digital twinning technology provided by the embodiment of the invention comprises the following steps:
collecting mechanical change and displacement change signals of a suspension system;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system;
building a finished automobile simulation model, performing iterative updating on the characteristics of a suspension system according to the obtained hysteresis force curve, and performing simulation on finished automobile operation stability and smoothness;
and outputting optimized suspension damping and rigidity parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target.
As a possible implementation manner of this embodiment, the acquiring signals of the mechanical change and the displacement change of the suspension system includes:
collecting pressure data of a suspension shock absorber;
and collecting displacement data of the suspension leaf spring.
As a possible implementation manner of this embodiment, the obtaining a hysteresis force curve of a suspension system by performing calculation by using a linear recognition algorithm of a momentum includes:
taking the mechanical change and displacement change signals of the suspension system as input conditions, and calculating by utilizing a linear identification algorithm of the driving amount to obtain a hysteresis force curve of the suspension system; the hysteresis curves of the suspension system include those of the shock absorber and those of the leaf spring.
As a possible implementation manner of this embodiment, building a complete vehicle simulation model, performing iterative update of suspension system characteristics according to an obtained hysteresis force curve, and performing simulation of stability and smoothness of the complete vehicle operation includes:
carrying out real vehicle test on the suspension system and taking the obtained hysteresis force curve of the suspension system as a basic real vehicle test result;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system, and comparing and checking with a basic real vehicle test result;
and (3) building a finished automobile simulation model, and performing iterative updating of the characteristics of the suspension system and simulation of the stability and smoothness of finished automobile operation according to a hysteresis force curve obtained by calculation by utilizing a linear identification algorithm with momentum.
As a possible implementation manner of this embodiment, in the iterative update process of the characteristics of the suspension system, the Isight software is used as a central software and is responsible for iteratively calling the linear identification algorithm with momentum and the entire vehicle simulation model, and the linear identification algorithm with momentum and the entire vehicle simulation model are cooperatively matched in the iterative update process.
As a possible implementation manner of this embodiment, the outputting, by the vehicle simulation model, optimized suspension damping and stiffness parameters according to the set vehicle handling stability and smoothness target includes:
and according to the set stability and smoothness target of the whole vehicle, the whole vehicle simulation model outputs optimized suspension damping and rigidity parameters, and performs suspension trial production and whole vehicle real vehicle test verification of the next round according to the optimized suspension damping and rigidity parameters until the whole vehicle acceptance standard is met, and the whole vehicle simulation model outputs the final optimized suspension damping and rigidity parameters.
On the other hand, the device for acquiring the real-time characteristic of the suspension system based on the digital twinning technology comprises a sensor and a suspension system real-time characteristic acquisition device, wherein the suspension system real-time characteristic acquisition device is provided with linear recognition algorithm software with momentum and whole vehicle simulation model software, the sensor is arranged between an upper mounting point and a lower mounting point of a suspension shock absorber and is used for acquiring mechanical change and displacement change signals of the suspension system; the linear identification algorithm software of the momentum calculates by using a linear identification algorithm of the momentum to obtain a hysteresis force curve of the suspension system; the whole vehicle simulation model software builds a whole vehicle simulation model, and carries out iterative updating of the characteristics of a suspension system and simulation of whole vehicle operation stability and smoothness according to the obtained hysteresis force curve; and the whole vehicle simulation model software also outputs optimized suspension damping and stiffness parameters according to the set whole vehicle operation stability and smoothness target.
As a possible implementation manner of this embodiment, the sensor includes a pressure sensor and a displacement sensor, the pressure sensor collects pressure data of the suspension shock absorber, and the displacement sensor collects displacement data of the suspension leaf spring.
As a possible implementation manner of this embodiment, the linear identification algorithm software with motion amount is specifically configured to: taking the mechanical change and displacement change signals of the suspension system as input conditions, and calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system; the hysteresis curves of the suspension system include those of the shock absorber and those of the leaf spring.
As a possible implementation manner of this embodiment, the entire vehicle simulation model software is specifically configured to:
carrying out real vehicle test on the suspension system and taking the obtained hysteresis force curve of the suspension system as a basic real vehicle test result;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system, and comparing and checking with a basic real vehicle test result;
building a finished automobile simulation model, and performing iterative update on the characteristics of a suspension system and simulation on finished automobile operation stability and smoothness according to a hysteresis force curve obtained by calculation by utilizing a linear identification algorithm with momentum;
and outputting optimized suspension damping and stiffness parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target, performing suspension trial production of the next round and whole vehicle real vehicle test verification according to the optimized suspension damping and stiffness parameters until the whole vehicle acceptance standard is met, and outputting the finally optimized suspension damping and stiffness parameters by the whole vehicle simulation model.
As a possible implementation manner of this embodiment, the suspension system real-time characteristic obtaining device is further equipped with Isight software, which is used as pivot software, and is responsible for invoking the linear identification algorithm with momentum and the finished automobile simulation model in an iterative update process of the suspension system characteristics in an iterative manner, and enabling the linear identification algorithm and the finished automobile simulation model to cooperate with each other in the iterative update process.
The technical scheme of the embodiment of the invention has the following beneficial effects:
the invention can obtain the real-time suspension characteristics without using a rack, and transmits the result to the whole vehicle simulation model in real time, thereby meeting the requirement of digital twin calculation, greatly simplifying the design process of the suspension system, improving the efficiency and the precision and shortening the development cycle of the suspension system.
According to the invention, the sensor is arranged between the upper mounting point and the lower mounting point of the shock absorber, the pressure sensor and the displacement sensor are arranged in the sensor, under the running state of a vehicle, the data of force and plate spring displacement are acquired according to the position change of the upper mounting point and the lower mounting point, and the sampling point can be set according to the requirement; force and displacement data are synchronously transmitted to a linear identification algorithm with momentum built in a computer, and a hysteresis force curve of a suspension system (comprising a shock absorber and a plate spring) can be obtained within 2.5 ms; the simulation model obtains a hysteresis force curve to perform relevant simulation work (such as vehicle dynamics simulation and ride comfort simulation), when the working condition changes, the hysteresis force changes in real time, and the simulation model can obtain a new result in real time. Compared with the prior art, the invention has the following characteristics: 1) the acquisition of the suspension characteristic result does not depend on a rack, is directly acquired on the whole vehicle, and has low cost and short time; 2) the characteristics obtained by the method are more suitable for the real vehicle state and have high precision; 3) the characteristic parameter identification can be completed within 2.5ms, the real-time interaction of simulation and real vehicles can be realized, digital twin calculation can be performed, and the development period of a suspension system is shortened.
Drawings
FIG. 1 is a flow diagram illustrating a method for obtaining real-time suspension system characteristics based on a digital twinning technique in accordance with an exemplary embodiment;
FIG. 2 is a block diagram of an apparatus for obtaining real-time suspension system characteristics based on a digital twinning technique in accordance with an exemplary embodiment;
FIG. 3 is a functional diagram illustrating an apparatus for deriving real-time suspension system characteristics based on digital twinning techniques in accordance with an exemplary embodiment.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
in order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
As shown in fig. 1, a method for acquiring real-time characteristics of a suspension system based on a digital twinning technique according to an embodiment of the present invention includes the following steps:
collecting mechanical change and displacement change signals of a suspension system;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system;
building a finished automobile simulation model, performing iterative updating on the characteristics of a suspension system according to the obtained hysteresis force curve, and performing simulation on finished automobile operation stability and smoothness;
and outputting optimized suspension damping and rigidity parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target.
As a possible implementation manner of this embodiment, the acquiring signals of the mechanical change and the displacement change of the suspension system includes:
collecting pressure data of a suspension shock absorber;
and collecting displacement data of the suspension leaf spring.
As a possible implementation manner of this embodiment, the obtaining a hysteresis force curve of a suspension system by performing calculation using a linear identification algorithm of a momentum includes:
taking the mechanical change and displacement change signals of the suspension system as input conditions, and calculating by utilizing a linear identification algorithm of the driving amount to obtain a hysteresis force curve of the suspension system; the hysteresis curves of the suspension system include those of the shock absorber and those of the leaf spring.
As a possible implementation manner of this embodiment, building a complete vehicle simulation model, performing iterative update of suspension system characteristics according to an obtained hysteresis force curve, and performing simulation of stability and smoothness of the complete vehicle operation includes:
carrying out real vehicle test on the suspension system and taking the obtained hysteresis force curve of the suspension system as a basic real vehicle test result;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system, and comparing and checking with a basic real vehicle test result;
and (3) building a finished automobile simulation model, and performing iterative updating of the characteristics of the suspension system and simulation of the stability and smoothness of finished automobile operation according to a hysteresis force curve obtained by calculation by utilizing a linear identification algorithm with momentum.
As a possible implementation manner of this embodiment, in the iterative update process of the characteristics of the suspension system, the Isight software is used as a central software and is responsible for iteratively calling the linear identification algorithm with momentum and the entire vehicle simulation model, and the linear identification algorithm with momentum and the entire vehicle simulation model are cooperatively matched in the iterative update process.
As a possible implementation manner of this embodiment, the outputting, by the vehicle simulation model, optimized suspension damping and stiffness parameters according to the set vehicle handling stability and smoothness target includes:
and outputting optimized suspension damping and stiffness parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target, performing suspension trial production of the next round and whole vehicle real vehicle test verification according to the optimized suspension damping and stiffness parameters until the whole vehicle acceptance standard is met, and outputting the finally optimized suspension damping and stiffness parameters by the whole vehicle simulation model.
As shown in fig. 2, the device for acquiring the real-time characteristic of the suspension system based on the digital twinning technology provided by the embodiment of the invention comprises a sensor and a suspension system real-time characteristic acquiring device, wherein the suspension system real-time characteristic acquiring device is provided with linear recognition algorithm software with momentum and whole vehicle simulation model software, the sensor is arranged between an upper mounting point and a lower mounting point of a suspension shock absorber and is used for acquiring mechanical change and displacement change signals of the suspension system; the linear identification algorithm software of the momentum calculates by using a linear identification algorithm of the momentum to obtain a hysteresis force curve of the suspension system; the whole vehicle simulation model software builds a whole vehicle simulation model, and carries out iterative updating of the characteristics of a suspension system and simulation of whole vehicle operation stability and smoothness according to the obtained hysteresis force curve; and the whole vehicle simulation model software also outputs optimized suspension damping and rigidity parameters according to the set whole vehicle operation stability and smoothness target.
As a possible implementation manner of this embodiment, the sensor includes a pressure sensor and a displacement sensor, the pressure sensor collects pressure data of the suspension shock absorber, and the displacement sensor collects displacement data of the suspension leaf spring.
As a possible implementation manner of this embodiment, the linear identification algorithm software with momentum is specifically configured to: taking the mechanical change and displacement change signals of the suspension system as input conditions, and calculating by utilizing a linear identification algorithm of the driving amount to obtain a hysteresis force curve of the suspension system; the hysteresis curves of the suspension system include those of the shock absorber and those of the leaf spring.
As a possible implementation manner of this embodiment, the entire vehicle simulation model software is specifically configured to:
carrying out real vehicle test on the suspension system and taking the obtained hysteresis force curve of the suspension system as a basic real vehicle test result;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system, and comparing and checking with a basic real vehicle test result;
building a finished automobile simulation model, and performing iterative update on the characteristics of a suspension system and simulation on finished automobile operation stability and smoothness according to a hysteresis force curve obtained by calculation by utilizing a linear identification algorithm with momentum;
and outputting optimized suspension damping and stiffness parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target, performing suspension trial production of the next round and whole vehicle real vehicle test verification according to the optimized suspension damping and stiffness parameters until the whole vehicle acceptance standard is met, and outputting the finally optimized suspension damping and stiffness parameters by the whole vehicle simulation model.
As a possible implementation manner of this embodiment, the suspension system real-time characteristic obtaining device further includes Isight software, which is used as central software and is responsible for iteratively calling a linear identification algorithm with momentum and a finished vehicle simulation model during an iterative update process of suspension system characteristics, and enabling the linear identification algorithm and the finished vehicle simulation model to cooperate with each other during the iterative update process.
As shown in FIG. 3, the invention provides a system for acquiring suspension characteristics in real time and performing digital twinning calculation based on the state of a whole vehicle, by adopting the system, the real-time suspension characteristics can be acquired without using a rack, the result is transmitted to a whole vehicle simulation model in real time, and the digital twinning calculation is performed, the system mainly comprises a sensor, a linear recognition algorithm with momentum, a simulation model and a suspension system, and the working principle of the system is as follows.
1. The suspension is installed and is carried out the real car experiment on the whole car, and installs the sensor between the mounting point about the suspension bumper shock absorber, and the inside contains pressure and displacement sensor, and under the vehicle running state, according to the position change of mounting point about, the data of acquisition power and leaf spring displacement, the sampling point can be according to the demand setting.
2. The acquired force and displacement signals are used as input conditions and are synchronously input into Matlab software, a linear identification algorithm with momentum is run in the Matlab software, and a hysteresis force curve (namely suspension system characteristics) of a suspension system (comprising a shock absorber and a plate spring) can be obtained within 2.5 ms.
3. And (3) building a finished automobile simulation model by using Trucksim software, comparing and checking with a basic real automobile test result before the whole iteration is started so as to confirm the simulation precision of the model (checking is only needed once), updating the characteristics of the suspension system according to the hysteresis force curve obtained in the step, and simulating the operation stability and the smoothness of the finished automobile.
4. In the iterative updating process, Isight software is used as central software and is responsible for invoking the Matlab software and the Trucksim software in an iterative mode, and therefore cooperation of the Isight software and the Trucksim software in each iterative process is achieved.
5. And outputting optimized suspension damping and rigidity parameters by Trucksim software according to a set finished vehicle operation stability and smoothness target, and performing suspension trial production and finished vehicle real-time test verification on the next round according to the parameters until the finished vehicle acceptance standard is met.
After the invention is adopted, the design flow of the whole suspension system is greatly simplified, thereby improving the efficiency and the precision. The suspension design process adopting the invention is as follows:
1. designing the characteristic of the suspension system by a designer;
2. trial production of a suspension and a whole vehicle is carried out;
3. building a finished automobile multi-body dynamics simulation model, carrying out a finished automobile test, and carrying out real-time interactive updating on a test result and the simulation model by using the method;
4. and completing the development work.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A method for acquiring real-time characteristics of a suspension system based on a digital twinning technology is characterized by comprising the following steps:
collecting mechanical change and displacement change signals of a suspension system;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system;
building a finished automobile simulation model, performing iterative updating on the characteristics of a suspension system according to the obtained hysteresis force curve, and performing simulation on finished automobile operation stability and smoothness;
and outputting optimized suspension damping and rigidity parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target.
2. The method for acquiring the real-time characteristics of the suspension system based on the digital twin technology as claimed in claim 1, wherein the acquiring of the mechanical change and displacement change signals of the suspension system comprises:
collecting pressure data of a suspension shock absorber;
and collecting displacement data of the suspension leaf spring.
3. The method for acquiring the real-time characteristic of the suspension system based on the digital twin technology as claimed in claim 1, wherein the calculating by using the linear identification algorithm of the momentum to acquire the hysteresis force curve of the suspension system comprises:
taking the mechanical change and displacement change signals of the suspension system as input conditions, and calculating by utilizing a linear identification algorithm of the driving amount to obtain a hysteresis force curve of the suspension system; the hysteresis curves of the suspension system include those of the shock absorber and those of the leaf spring.
4. The method for acquiring the real-time characteristics of the suspension system based on the digital twinning technology as claimed in claim 1, wherein a finished automobile simulation model is built, iterative updating of the characteristics of the suspension system is performed according to the obtained hysteresis force curve, and finished automobile operation stability and smoothness simulation is performed, and the method comprises the following steps:
carrying out real vehicle test on the suspension system and taking the obtained hysteresis force curve of the suspension system as a basic real vehicle test result;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system, and comparing and checking with a basic real vehicle test result;
and (3) building a finished automobile simulation model, and performing iterative updating of the characteristics of the suspension system and simulation of the stability and smoothness of finished automobile operation according to a hysteresis force curve obtained by calculation by utilizing a linear identification algorithm with momentum.
5. The method for acquiring the real-time characteristics of the suspension system based on the digital twin technology as claimed in claim 1, wherein in the iterative update process of the characteristics of the suspension system, Isight software is used as central software and is responsible for iteratively calling a linear identification algorithm with momentum and a finished automobile simulation model, and the linear identification algorithm with momentum and the finished automobile simulation model are cooperatively matched in the iterative update process.
6. The method for acquiring the real-time characteristics of the suspension system based on the digital twinning technology as claimed in any one of claims 1 to 5, wherein the step of outputting optimized suspension damping and stiffness parameters by a finished automobile simulation model according to the set finished automobile operation stability and smoothness target comprises the following steps:
and outputting optimized suspension damping and stiffness parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target, performing suspension trial production of the next round and whole vehicle real vehicle test verification according to the optimized suspension damping and stiffness parameters until the whole vehicle acceptance standard is met, and outputting the finally optimized suspension damping and stiffness parameters by the whole vehicle simulation model.
7. A device for acquiring real-time characteristics of a suspension system based on a digital twinning technology is characterized by comprising a sensor and a suspension system real-time characteristic acquisition device, wherein the suspension system real-time characteristic acquisition device is provided with linear recognition algorithm software with momentum and whole vehicle simulation model software, the sensor is arranged between an upper mounting point and a lower mounting point of a suspension shock absorber and is used for acquiring mechanical change and displacement change signals of the suspension system; the linear identification algorithm software of the moving amount calculates by using a linear identification algorithm of the moving amount to obtain a hysteresis force curve of the suspension system; the whole vehicle simulation model software builds a whole vehicle simulation model, and carries out iterative updating of the characteristics of a suspension system and simulation of whole vehicle operation stability and smoothness according to the obtained hysteresis force curve; and the whole vehicle simulation model software also outputs optimized suspension damping and stiffness parameters according to the set whole vehicle operation stability and smoothness target.
8. The apparatus for acquiring the real-time characteristic of the suspension system based on the digital twin technology as claimed in claim 7, wherein the sensor comprises a pressure sensor and a displacement sensor, the pressure sensor acquires pressure data of a suspension shock absorber, and the displacement sensor acquires displacement data of a suspension leaf spring.
9. The device for acquiring the real-time characteristics of the suspension system based on the digital twinning technology as claimed in claim 7, wherein the whole vehicle simulation model software is specifically configured to:
carrying out real vehicle test on the suspension system and taking the obtained hysteresis force curve of the suspension system as a basic real vehicle test result;
calculating by utilizing a linear identification algorithm with momentum to obtain a hysteresis force curve of the suspension system, and comparing and checking with a basic real vehicle test result;
building a finished automobile simulation model, and performing iterative update on the characteristics of a suspension system and simulation on finished automobile operation stability and smoothness according to a hysteresis force curve obtained by calculation by utilizing a linear identification algorithm with momentum;
and outputting optimized suspension damping and stiffness parameters by the whole vehicle simulation model according to the set whole vehicle operation stability and smoothness target, performing suspension trial production of the next round and whole vehicle real vehicle test verification according to the optimized suspension damping and stiffness parameters until the whole vehicle acceptance standard is met, and outputting the finally optimized suspension damping and stiffness parameters by the whole vehicle simulation model.
10. The device for acquiring the real-time characteristics of the suspension system based on the digital twinning technology as claimed in any one of claims 7 to 9, wherein Isight software is further installed on the device for acquiring the real-time characteristics of the suspension system, the Isight software serves as central software, and in the iterative updating process of the characteristics of the suspension system, the device is responsible for iteratively calling a linear identification algorithm with momentum and a finished automobile simulation model, and the linear identification algorithm with momentum and the finished automobile simulation model are cooperatively matched in the iterative updating process.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210810109.6A CN114879536B (en) | 2022-07-11 | 2022-07-11 | Method and device for acquiring real-time characteristics of suspension system based on digital twinning technology |
| GB2301077.0A GB2616348A (en) | 2022-07-11 | 2023-01-25 | Method and device for acquiring real-time characteristics of suspension system based on digital twin technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210810109.6A CN114879536B (en) | 2022-07-11 | 2022-07-11 | Method and device for acquiring real-time characteristics of suspension system based on digital twinning technology |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114879536A CN114879536A (en) | 2022-08-09 |
| CN114879536B true CN114879536B (en) | 2022-09-16 |
Family
ID=82683246
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210810109.6A Active CN114879536B (en) | 2022-07-11 | 2022-07-11 | Method and device for acquiring real-time characteristics of suspension system based on digital twinning technology |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN114879536B (en) |
| GB (1) | GB2616348A (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117048860B (en) * | 2023-08-09 | 2024-01-23 | 南京航空航天大学 | Multi-information measurement microgravity simulation platform for suspension type equivalent test impact |
| CN116839783B (en) * | 2023-09-01 | 2023-12-08 | 华东交通大学 | Method for measuring stress value and deformation of automobile leaf spring based on machine learning |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110454290A (en) * | 2019-07-02 | 2019-11-15 | 北京航空航天大学 | A kind of automobile engine management-control method based on the twin technology of number |
| CN110456635A (en) * | 2019-07-02 | 2019-11-15 | 北京航空航天大学 | The control method of power system of electric automobile based on the twin technology of number |
| CN110488629A (en) * | 2019-07-02 | 2019-11-22 | 北京航空航天大学 | A kind of management-control method of the hybrid vehicle based on the twin technology of number |
| CN112419775A (en) * | 2020-08-12 | 2021-02-26 | 华东师范大学 | Digital twin intelligent parking method and system based on reinforcement learning |
| WO2021222384A1 (en) * | 2020-04-28 | 2021-11-04 | Strong Force Intellectual Capital, Llc | Digital twin systems and methods for transportation systems |
| CN113759753A (en) * | 2021-08-31 | 2021-12-07 | 广东利元亨智能装备股份有限公司 | Simulation debugging system based on digital twin platform |
| CN113792406A (en) * | 2021-07-15 | 2021-12-14 | 意欧斯物流科技(上海)有限公司 | AGV dolly simulation system based on digital twinning |
| CN114329779A (en) * | 2021-12-28 | 2022-04-12 | 南京理工大学 | Algorithm verification system and method based on digital twin |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10752269B2 (en) * | 2017-03-09 | 2020-08-25 | General Electric Company | System for vehicle subsystem control |
| CN104331556A (en) * | 2014-10-31 | 2015-02-04 | 郑州宇通客车股份有限公司 | Simulated test method based on nonlinear vehicle ride comfort simulation model |
| CN109614703B (en) * | 2018-12-11 | 2020-07-28 | 南京天航智能装备研究院有限公司 | Multidisciplinary integrated modeling and optimization method for automobile electro-hydraulic composite steering system |
| GB2598785B (en) * | 2020-09-14 | 2022-10-19 | Jaguar Land Rover Ltd | Monitoring system |
| CN114580971A (en) * | 2022-01-23 | 2022-06-03 | 中国人民解放军国防科技大学 | Dynamic adjustment method, system and equipment based on performance digital twinning |
-
2022
- 2022-07-11 CN CN202210810109.6A patent/CN114879536B/en active Active
-
2023
- 2023-01-25 GB GB2301077.0A patent/GB2616348A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110454290A (en) * | 2019-07-02 | 2019-11-15 | 北京航空航天大学 | A kind of automobile engine management-control method based on the twin technology of number |
| CN110456635A (en) * | 2019-07-02 | 2019-11-15 | 北京航空航天大学 | The control method of power system of electric automobile based on the twin technology of number |
| CN110488629A (en) * | 2019-07-02 | 2019-11-22 | 北京航空航天大学 | A kind of management-control method of the hybrid vehicle based on the twin technology of number |
| WO2021222384A1 (en) * | 2020-04-28 | 2021-11-04 | Strong Force Intellectual Capital, Llc | Digital twin systems and methods for transportation systems |
| CN112419775A (en) * | 2020-08-12 | 2021-02-26 | 华东师范大学 | Digital twin intelligent parking method and system based on reinforcement learning |
| CN113792406A (en) * | 2021-07-15 | 2021-12-14 | 意欧斯物流科技(上海)有限公司 | AGV dolly simulation system based on digital twinning |
| CN113759753A (en) * | 2021-08-31 | 2021-12-07 | 广东利元亨智能装备股份有限公司 | Simulation debugging system based on digital twin platform |
| CN114329779A (en) * | 2021-12-28 | 2022-04-12 | 南京理工大学 | Algorithm verification system and method based on digital twin |
Non-Patent Citations (5)
| Title |
|---|
| Bouc-Wen滞回系统的跟踪控制与动力学行为研究;刘雅倩等;《军事交通学院学报》;20200125(第01期);第95-98页 * |
| Principles of application of virtual and physical simulation technology in production of digital twin of active vehicle safety systems;Dygalo V,et al.;《Transportation Research Procedia》;20200131;第121-129页 * |
| 复合材料板簧迟滞特性线性辨识方法;李伟 等;《吉林大学学报(工学版)》;20220430;第52卷(第4期);第829-836页 * |
| 数字孪生技术在航天制造领域中的应用;袁胜华等;《强度与环境》;20200615(第03期);第59-66页 * |
| 融合数字孪生的自动驾驶场景仿真模型构建研究综述;叶少槟 等;《现代计算机》;20220125;第28卷(第2期);第1-11页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| GB2616348A (en) | 2023-09-06 |
| GB202301077D0 (en) | 2023-03-08 |
| CN114879536A (en) | 2022-08-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114879536B (en) | Method and device for acquiring real-time characteristics of suspension system based on digital twinning technology | |
| CN113010964B (en) | Virtual test field-based vehicle bench test load spectrum analysis method | |
| CN107247830B (en) | Method and system for optimizing K & C characteristic tolerance of automobile suspension | |
| CN112287551B (en) | Driving performance system level index decomposition method based on whole vehicle conceptual model | |
| CN110298125A (en) | A kind of fatigue analysis method based on virtual test field technology | |
| CN106294939A (en) | Finite element occupant restraint system model based on Modularization modeling and modeling method thereof | |
| CN105092261A (en) | Road load test method and system | |
| CN106066921A (en) | A kind of CAE simulated prediction method of car load road vibration noise | |
| CN103822789B (en) | A kind of core wheel determination of six components of foree method and system | |
| CN112131672A (en) | Durable load spectrum simulation method, device, storage medium and device | |
| CN110414052A (en) | A kind of vehicle structure fatigue life calculation method composed based on digital sample car and virtual road | |
| CN111581716B (en) | Simulation method for dynamic performance of loop accelerated loading device | |
| CN113570057A (en) | Vehicle wheel center vertical displacement measuring method and device based on model training | |
| CN110083949B (en) | Pre-sensor signal reproduction method and system | |
| CN111291446A (en) | Suspension system multidisciplinary optimization design method based on front suspension flutter and idle speed vibration | |
| CN114115200A (en) | NVH (noise, vibration and harshness) testing system and NVH testing method for electric automobile electric drive assembly | |
| CN109598005A (en) | The construction method of tire positional parameter acquisition methods and automobile tire motion envelope | |
| CN111090959A (en) | Vehicle load spectrum acquisition method and system | |
| CN109858120B (en) | Method and device for optimizing dynamic parameters of bogie suspension system of motor train unit | |
| CN114676648B (en) | Vehicle load spectrum prediction method and device based on machine learning | |
| CN116415494A (en) | Road noise optimization method, system and storage medium | |
| CN114923649A (en) | Vehicle body composite vibration identification method based on test and simulation technology | |
| CN115081208A (en) | Application method and system of virtual load in automobile swing arm endurance test, electronic device and storage medium | |
| CN113656994A (en) | Method and device for acquiring suspension force of automobile suspension system | |
| CN115096613A (en) | Road simulation test method and system for finished automobile suspension assembly |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |