A rapid modeling method and modeling terminal for variable cross-section steel leaf springs used in light trucks

Abstract

This invention provides a rapid modeling method and terminal for variable cross-section leaf springs used in light trucks, relating to the field of light truck technology. The method involves calculating the geometric contours of each leaf spring in its extended state, selecting sample points at equal intervals along the length of each leaf spring in its extended state, and calculating the sample point data including coordinates and thickness. The method then calculates the geometric contours of each leaf spring in its free state. Based on the free state of each leaf spring, sample points are reselected, and corresponding sample point data is obtained through interpolation and exported. A leaf spring modeling file and an assembly parameter file are created. The sample point data of each leaf spring in its free state are imported into the leaf spring modeling file, and the leaf spring assembly parameters are imported into the assembly parameter file. The leaf spring toolbox is run to generate the leaf spring model, defining the leaf spring lugs and material properties to create the leaf spring model. This method uses a procedural approach, which can quickly and accurately calculate the sample point data of the variable cross-section leaf spring, improving the efficiency of leaf spring modeling and the accuracy of model creation.

Description

Technical Field

[0001] This invention relates to the field of light truck technology, and in particular to a modeling terminal for a rapid modeling method of variable cross-section steel leaf springs for light trucks. Background Technology

[0002] Currently, with the increasing demand for freight logistics, different types of commercial vehicles are needed for freight transport. Among them, light trucks are already widely used in freight logistics. Light trucks refer to N2 category vehicles in the N category of cargo trucks, with a maximum design gross vehicle weight of no more than 4.5 tons.

[0003] The use of light trucks in the freight logistics industry has placed higher demands on their safety and driving smoothness. Applying simulation technology in the early stages of light truck design can effectively improve vehicle smoothness and handling, shorten the R&D cycle, and reduce R&D costs.

[0004] In the simulation modeling of the suspension assembly system of light trucks, the modeling of the leaf spring assembly is the most critical. The leaf spring toolbox provided in Adams software allows for the rapid creation of leaf spring models using the discrete beam method. The accuracy of this method depends on the precision of the geometric contours of each leaf spring in its free state. This method is efficient for creating multi-leaf spring models and its accuracy can meet simulation requirements. However, for the variable cross-section leaf springs used in modern light trucks, their ends and roots are typically thickened, making it impossible to directly set these parameters. Therefore, the accuracy of the variable cross-section leaf spring model for light trucks directly created using the leaf spring toolbox is unlikely to meet subsequent simulation requirements. Summary of the Invention

[0005] This invention provides a rapid modeling method for variable cross-section steel leaf springs used in light trucks. The method can quickly and efficiently establish steel leaf spring models to meet the design requirements of light trucks.

[0006] The methods include:

[0007] S101. Calculate the geometric profile of each leaf spring in the straightened state. Select sample points at equal intervals along the length of each leaf spring in the straightened state, and calculate the sample point data including coordinates and thickness.

[0008] S102. Based on the geometric profile of each leaf spring in its straightened state, calculate the geometric profile of each leaf spring in its free state; then, based on the free state of each leaf spring, reselect sample points, obtain the corresponding sample point data through interpolation calculation, and export it.

[0009] S103. Create a leaf spring modeling file and an assembly parameter file. Import the sample point data of each leaf spring in its free state into the leaf spring modeling file and import the leaf spring assembly parameters into the assembly parameter file.

[0010] S104. Run the leaf spring toolbox to generate a leaf spring model, and define the leaf spring lugs and material properties to create a steel leaf spring model.

[0011] It should be further noted that the geometric profiles of each leaf spring in the straightened state are calculated using the leaf spring technical documents;

[0012] Sample points are selected at equal intervals along the length of each leaf spring when it is in the straightened state. The sample point data containing coordinates and thickness is calculated, and the geometric contour of each leaf spring in the straightened state is described by the sample point data matrix.

[0013] It should be further explained that the length of each leaf spring, the free arc height of each leaf spring, and the length of the straight section are imported into the sample point data when each leaf spring is straightened. The sample point data of each leaf spring in the free state is output. The sample point data includes the coordinates of the sample point and the thickness information of the leaf spring at the sample point. The geometric contour of each leaf spring in the free state is described by this sample point data matrix.

[0014] It should be further noted that in step S103, the leaf spring modeling file is the lef file of the leaf spring toolbox. The sample point data of each leaf spring in the free state are imported into the lef file, and the total number of leaf springs is set.

[0015] It should be further noted that the assembly parameter file in step S103 is a leaf spring toolbox lpf file, which is used to define the number of leaf springs, width, clamping distance, and spring clip installation position parameters.

[0016] It should be further explained that when each leaf spring is in the straightened state, the sample points are placed on the upper surface of each leaf spring, and a one-dimensional coordinate is established on the upper surface of each leaf spring. The one-dimensional coordinate is determined along the length direction of each leaf spring.

[0017] It should be further noted that, in the method, the sampling points are set for each leaf spring when it is in a free state;

[0018] When each leaf spring is in its free state, a two-dimensional coordinate system is established on the upper surface of each leaf spring. The coordinate values ​​are determined by the following relationship:

[0019] The upper surface of each leaf spring is a smooth arc with a straight section in the middle, and the curvature of the smooth arc is consistent.

[0020] Let the length of the plate be L, the height of the free arc be H, and the radius of curvature be R. The relationship between these three is: L / R = 2*arcos((RH) / R).

[0021] It should be further explained that the two-dimensional coordinates of each leaf spring in the free state are converted into one-dimensional coordinates in the straightened state, and the leaf spring thickness corresponding to the sample point in the free state of each leaf spring is obtained by one-dimensional coordinate interpolation.

[0022] It should be further noted that the method also exports a preset number of sample points by modifying the sample point quantity parameter in order to obtain the geometric profile of the leaf spring.

[0023] The present invention also provides a modeling terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of a rapid modeling method for variable cross-section steel leaf springs for light trucks.

[0024] As can be seen from the above technical solutions, the present invention has the following advantages:

[0025] The rapid modeling method for variable cross-section steel leaf springs used in light trucks of the present invention uses an interpolation method to calculate the geometric contours of each leaf spring in its free state. As long as a sufficient number of sample points are selected, the accuracy of the geometric contours of each leaf spring in its free state can be guaranteed, thereby ensuring the accuracy of the leaf spring model. The sample point data of each leaf spring in its free state are calculated by a pre-programmed program. After the program is completed, it is repeatable. For different leaf springs, only the corresponding leaf spring parameters need to be input to quickly output the sample point data, thereby realizing the rapid creation of leaf spring models.

[0026] This invention summarizes the states of each leaf spring, facilitating CRUD operations for modelers and effectively improving the efficiency of the modeling process. It also enables efficient collection, storage, and processing of modeling data. Sufficient sample points can be selected based on the straightened and free states of each leaf spring, and the entire modeling process is described using multi-dimensional space, ensuring the accuracy of the geometric contours of each leaf spring in its free state. Based on these methods, the accuracy and efficiency of modeling are improved, and abnormal data is reduced or eliminated during the modeling process, thereby enhancing the precision of the modeling process, controlling design risks in light truck vehicles, and ultimately achieving timely and scientific supervision, management, and control of the light truck vehicle design process. Attached Figure Description

[0027] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 Flowchart of a rapid modeling method for variable cross-section steel leaf springs used in light trucks;

[0029] Figure 2 This is an example diagram showing the geometric profile of a leaf spring half in its extended state.

[0030] Figure 3 Example diagram of the geometric profile of a single leaf spring in its free state;

[0031] Figure 4 This is the stiffness curve of the leaf spring model. Detailed Implementation

[0032] The present invention relates to a rapid modeling method for variable cross-section steel leaf springs for light trucks. This method utilizes Matlab technology to establish a model of the variable cross-section steel leaf spring for light trucks. By combining interpolation methods and using technologies such as sensor monitoring and data transmission, the geometric contours of each leaf spring in the free state are calculated, thereby achieving rapid creation of the leaf spring model and reflecting the state of the steel leaf spring for light trucks.

[0033] like Figure 1 A flowchart illustrating a preferred embodiment of the rapid modeling method for variable cross-section leaf springs for light trucks according to the present invention is shown. The rapid modeling method for variable cross-section leaf springs for light trucks is applied in one or more modeling terminals. The modeling terminal is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0034] The modeling terminal can be any electronic product that can interact with the user, such as a personal computer, tablet computer, smartphone, personal digital assistant (PDA), interactive network television (IPTV), smart wearable device, etc.

[0035] The modeling terminal may also include network devices and / or user devices. The network devices include, but are not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of hosts or network servers.

[0036] The network where the modeling terminal is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, and virtual private network (VPN).

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] The methods include:

[0039] S101. Calculate the geometric profile of each leaf spring in the extended state. Select sample points at equal intervals along the length of each leaf in the extended state, and calculate the sample point data including coordinates and thickness.

[0040] The geometric profile of each leaf spring in its straightened state is calculated using the leaf spring technical documentation. Sample points are selected at equal intervals along the length of each leaf spring in its straightened state, and sample point data including coordinates and thickness is calculated. This sample point data matrix is ​​used to describe the geometric profile of each leaf spring in its straightened state.

[0041] S102. Based on the geometric profile of each leaf spring in its straightened state, calculate the geometric profile of each leaf spring in its free state; then, based on the free state of each leaf spring, reselect sample points, obtain the corresponding sample point data through interpolation calculation, and export it.

[0042] In the embodiments of the present invention, the sample points of each leaf spring in the straightened state are distributed on the upper surface of each leaf, and their coordinates are one-dimensional coordinates. The coordinates of the sample points are determined along the length direction of each leaf.

[0043] The geometric profiles of each leaf spring in its free state are calculated using a pre-programmed procedure. This is achieved by inputting the length of each leaf spring, the free arc height of each leaf spring, the length of the straight section, and importing the sample point data when each leaf spring is straight. The output is the sample point data of each leaf spring in its free state. The sample point data includes information such as the coordinates of the sample point and the thickness of the leaf spring at the sample point. This sample point data matrix is ​​used to describe the geometric profiles of each leaf spring in its free state.

[0044] The sampling points selected in this invention are based on the upper surface of each leaf spring in its extended state. A one-dimensional coordinate system is established on the upper surface of each leaf spring in its extended state, and the one-dimensional coordinate system is set along the length direction of each leaf spring. The sampling points are distributed within the one-dimensional coordinate system.

[0045] This invention establishes two-dimensional coordinates on the surface of each leaf spring when they are in a free state, and the coordinate values ​​are determined by the following relationship:

[0046] The upper surface of each piece is a smooth arc with a straight section in the middle, and the curvature of the smooth arc is consistent.

[0047] Assume that the length of a certain piece (excluding the straight section) is L, the height of the free arc is H, and the radius of curvature is R. The relationship between the three is: L / R = 2*arcos((RH) / R).

[0048] This invention converts the two-dimensional coordinates of each leaf spring in its free state into one-dimensional coordinates in its straightened state, and uses one-dimensional coordinate interpolation to obtain the leaf spring thickness corresponding to the sample point in the free state of each leaf spring.

[0049] The present invention also derives a sufficient number of sample points by modifying the sample point quantity parameter to ensure the accuracy of the leaf spring's geometric profile.

[0050] S103. Create a leaf spring modeling file and an assembly parameter file. Import the sample point data of each leaf spring in its free state into the leaf spring modeling file and import the leaf spring assembly parameters into the assembly parameter file.

[0051] In this invention, the leaf spring modeling file is the leaf spring toolbox .lef file. The sample data of each leaf spring in its free state are imported into the .lef file, and the total number of leaf springs is set to form the leaf spring modeling file.

[0052] The assembly parameter file, also known as the leaf spring toolbox LPF file, is used to define parameters such as the number of leaf springs, width, clamping distance, and spring clip installation position.

[0053] S104. Run the leaf spring toolbox to generate a leaf spring model, and define the leaf spring lugs and material properties to create a steel leaf spring model.

[0054] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0055] This invention summarizes the states of each leaf spring, facilitating CRUD operations for modelers and effectively improving the efficiency of the modeling process. It also enables efficient collection, storage, and processing of modeling data. Sufficient sample points can be selected based on the straightened and free states of each leaf spring, and the entire modeling process is described using multi-dimensional space, ensuring the accuracy of the geometric contours of each leaf spring in its free state. Based on these methods, the accuracy and efficiency of modeling are improved, and abnormal data is reduced or eliminated during the modeling process, thereby enhancing the precision of the modeling process, controlling design risks in light truck vehicles, and ultimately achieving timely and scientific supervision, management, and control of the light truck vehicle design process.

[0056] In one embodiment of the present invention, based on the rapid modeling method for variable cross-section steel leaf springs for light trucks, the following will provide a possible embodiment and describe its specific implementation in a non-limiting manner.

[0057] Step 1: Calculate the geometric profile of each leaf spring in the straightened state. Select sample points at equal intervals along the length of each leaf in the straightened state, and calculate the sample point data including coordinates and thickness.

[0058] The geometric profile of a half-leaf spring with variable cross-section used in a light truck in the straightened state is as follows: Figure 2 Its upper surface is horizontal, with thickened, uniformly thick sections at the ends and root. The thickness varies parabolically in the middle and linearly in the transition section. The specific calculation process for its geometric profile is as follows:

[0059] A one-dimensional coordinate system is established along the length of the leaf spring with the root center as the origin. Sample points are selected at equal intervals along the length of each leaf spring in the straightened state. The sample point data containing coordinates and thickness is calculated according to the technical documents. This sample point data matrix describes the geometric contour of each leaf spring in the straightened state.

[0060] Step 2: Calculate the geometric profile of each leaf spring in its free state based on the geometric profile of the leaf spring in its straightened state. Reselect sample points in the free state of each leaf spring, obtain the sample point data through calculation and interpolation, and export it.

[0061] The geometric profile of a single variable cross-section leaf spring for light trucks in its free state is as follows: Figure 3 The upper surface is a smooth circular arc with a straight section in the middle and a uniform curvature. Assume that the length of a certain piece (excluding the straight section) is L, the free arc height is H, and the radius of curvature is R. The relationship between the three is: L / R=2*arcos((RH) / R).

[0062] Its geometric profile is calculated using a pre-programmed Matlab program. The specific implementation process is as follows: a two-dimensional coordinate system is established with the center of the upper surface of the root as the origin, the direction backward along the straight section as the positive x-axis, and the direction upward perpendicular to the straight section as the positive y-axis. Sample points are selected along the upper surface of each piece in its free state. The coordinates of the sample points are calculated using the program according to the above two-dimensional coordinate system. The two-dimensional coordinates of the sample points are then converted into one-dimensional coordinates in the straightened state. The thickness of the leaf spring corresponding to the sample points in the free state of each piece is obtained by interpolation of the one-dimensional coordinates.

[0063] The interpolation uses the Matlab one-dimensional interpolation function interp1, with the default type being linear interpolation. Generally, the more sample points there are, the higher the accuracy of linear interpolation and the more precise the result.

[0064] By inputting the length of each leaf spring, the free arc height of each leaf spring, and the length of the straight section into the program, and importing the sample point data when each leaf spring is straight, the program can output the sample point data of each leaf spring in the free state. The sample point data includes information such as the coordinates of the sample point and the thickness of the leaf spring at the sample point, and uses this sample point data matrix to describe the geometric contour of each leaf spring in the free state.

[0065] Step 3: Create a leaf spring modeling file and an assembly parameter file. Import the sample point data of each leaf spring in its free state into the leaf spring modeling file, and write the leaf spring assembly parameters into the assembly parameter file.

[0066] In this invention, a leaf spring modeling file is created as follows: Open the file with Notepad, and set the number of leaf springs to 3 after "#_OF_LEAF="; the parameters of each leaf spring in the file include the coordinates and thickness of the sample points, and import the sample point data of each leaf spring in the free state into the corresponding positions; keep the other parameters at their default values, and the creation of the leaf spring modeling file is completed.

[0067] Create an assembly parameter file: Define the number of leaf springs as 3, the width of each leaf as 70, and the clamping distance as 43 (with an invalid clamping coefficient of 0.5).

[0068] Step 4: Run the leaf spring toolbox to generate a leaf spring model. Define the leaf spring lugs, material, and other properties to quickly and accurately create a leaf spring model.

[0069] Specifically, open the Leaf Spring Toolbox Create Leaf Spring dialog box, import the leaf spring modeling file and assembly parameter file respectively, and click "OK" to generate the leaf spring assembly model;

[0070] In the pop-up connector dialog box, set the hanger to be lowered, the length to 90, and keep the default settings for information such as the connection relationship between the leaf spring and the frame axle.

[0071] In the properties dialog box, define the elastic modulus E as 2.06 * 10^5 MPa, and keep the other parameters at their default values. This completes the creation of the leaf spring model.

[0072] In addition, after the leaf spring model is created, it can be loaded to verify whether the model's stiffness is accurate, such as... Figure 4 .

[0073] In this example, the stiffness of the leaf spring model is approximately 149 N / mm, while its design value is 150 N / mm. The stiffness error of the variable cross-section steel leaf spring model established using this method is approximately 7‰, which is very accurate and can meet the requirements of subsequent simulations.

[0074] In the rapid modeling method for variable cross-section leaf springs for light trucks provided by the invention, the units and algorithm steps of the various examples described in the disclosed embodiments can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0075] The accompanying drawings of the rapid modeling method for variable cross-section leaf springs for light trucks illustrate the architecture, functionality, and operation of possible implementations of the apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in the flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0076] In the rapid modeling method for variable cross-section steel leaf springs for light trucks provided by the invention, computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include, but are not limited to, object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or power server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (exemplarily using an Internet service provider for Internet connection).

[0077] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A variable cross-section steel plate spring quick modeling method for light trucks, characterized by, The methods include: S101. Calculate the geometric profile of each leaf spring in the straightened state. Select sample points at equal intervals along the length of each leaf spring in the straightened state, and calculate the sample point data including coordinates and thickness. The geometric profiles of each leaf spring in its extended state are calculated using the leaf spring technical documents; Sample points are selected at equal intervals along the length of each leaf spring in the straightened state. Sample point data containing coordinates and thickness are calculated, and the geometric contour of each leaf spring in the straightened state is described by this sample point data matrix. The length of each leaf spring, the free arc height of each leaf spring, and the length of the straight section are imported into the sample point data when each leaf spring is straightened. The sample point data of each leaf spring in the free state is output. The sample point data includes the coordinates of the sample point and the thickness information of the leaf spring at the sample point. The geometric contour of each leaf spring in the free state is described by this sample point data matrix. S102. Based on the geometric profile of each leaf spring in its straightened state, calculate the geometric profile of each leaf spring in its free state; then, based on the free state of each leaf spring, reselect sample points, obtain the corresponding sample point data through interpolation calculation, and export it. S103. Create a leaf spring modeling file and an assembly parameter file. Import the sample point data of each leaf spring in its free state into the leaf spring modeling file and import the leaf spring assembly parameters into the assembly parameter file. S104. Run the leaf spring toolbox to generate a leaf spring model, and define the leaf spring lugs and material properties to create a steel leaf spring model.

2. The quick modeling method of a variable cross-section steel plate spring for a light truck according to claim 1, characterized by, In step S103, the leaf spring modeling file is the .lef file of the leaf spring toolbox. The sample point data of each leaf spring in the free state are imported into the .lef file, and the total number of leaf springs is set.

3. The quick modeling method of a variable cross-section steel plate spring for a light truck according to claim 2, characterized by, The assembly parameter file in step S103 is a leaf spring toolbox lpf file, which is used to define the number of leaf springs, width, clamping distance, and spring clip installation position parameters.

4. The quick modeling method of a variable cross-section steel plate spring for a light truck according to claim 1, characterized by: When each leaf spring is in the straightened state, sample points are placed on the upper surface of each leaf spring, and one-dimensional coordinates are established on the upper surface of each leaf spring. The one-dimensional coordinates are determined along the length direction of each leaf spring.

5. The quick modeling method of a variable cross-section steel plate spring for a light truck according to claim 4, characterized by: In this method, sampling points are set for each leaf spring when it is in a free state; When each leaf spring is in its free state, a two-dimensional coordinate system is established on the upper surface of each leaf spring. The coordinate values ​​are determined by the following relationship: The upper surface of each leaf spring is a smooth arc with a straight section in the middle, and the curvature of the smooth arc is consistent. Let the length of the plate be L, the height of the free arc be H, and the radius of curvature be R. The relationship between the three is: L / R = 2*arcos((RH) / R).

6. The quick modeling method of a variable cross-section steel plate spring for a light truck according to claim 5, characterized by: The two-dimensional coordinates of each leaf spring in its free state are converted into one-dimensional coordinates in its straightened state, and the leaf spring thickness corresponding to the sample point in the free state of each leaf spring is obtained by one-dimensional coordinate interpolation.

7. The quick modeling method of a variable cross-section steel plate spring for a light truck according to claim 1, characterized by: The method also modifies the sample point quantity parameter to export a preset number of sample points in order to obtain the geometric profile of the leaf spring.

8. A modeling terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the rapid modeling method for variable cross-section steel leaf springs for light trucks as described in any one of claims 1 to 7.

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