A Multi-body Dynamics Modeling and Parameter Verification Method for Steering Mechanisms Based on ADAMS

Abstract

A multi-body dynamics modeling and parameter confirmation method for a steering mechanism based on ADAMS. According to the composition characteristics of the steering system, a multi-rigid body dynamics model is established through virtual prototype technology, and an equivalent power source for driving the steering rod by the steering gear is applied. The dimensions and centroid position coordinates of each part in the multi-rigid body dynamics are used as the input values of the simulation, and the system steering angle is used as the output value. The original left and right turn angle time-angle motion states of the steering system are simulated and tested to obtain the motion distance of the parts and the change value of the steering angle. Within the design boundary range, the data groups are evenly divided and input to obtain the output results. The motion characteristics under the Ackermann steering angle theory are regarded as the ideal left and right angle relationship of the steering knuckle. Taking the cumulative minimum of the root mean square value of the difference in the entire steering process as the optimization goal, it is transformed into a mathematical relationship and a function algorithm is built to calculate the target result. It is applied to the design of the steering system in the vehicle development process, which is of great significance for improving the development efficiency of the steering system parameters and saving development resources.

Description

Technical Field

[0001] The present invention relates to an efficient multi-body dynamics modeling method and a method for confirming key parameters of components, which are applied to the design of the steering system in the whole vehicle development process. Background Technique

[0002] In the existing steering system design process, complete digital model shapes are used for the simulation of various parameters of the steering system. A large number of mesh details irrelevant to the test purpose are involved in the simulation process, which requires a very high computing power of the workstation. And after the simulation, the influence degree of the parameter adjustment process on the parameters is not graded, which further increases the computing power pressure of the workstation. In the subsequent real vehicle tuning process, more engineer resources are required to adjust numerous parameters, resulting in low efficiency;

[0003] Therefore, the present invention is needed. Using the thinking of multi-body dynamics and based on the motion characteristics of the steering system, each component is regarded as a rigid body. Only the basic dimensions, center-of-mass positions, and kinematic pairs between components that affect the motion are required in the simulation process, greatly reducing the computing power pressure. And the sensitivity of the target parameters is graded, and a small number of high-sensitivity parameters are selected for directional optimization. This has guiding significance for subsequent computing power saving and making different parameter parts for real vehicle adjustment. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention proposes a multi-body dynamics modeling of a steering mechanism based on ADAMS and a method for confirming the best component parameters, which is of great significance for improving the development efficiency of steering system parameters and saving development resources.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A multi-body dynamics modeling and parameter confirmation method of a steering mechanism based on ADAMS, the steps of which include:

[0007] 1) According to the composition characteristics of the steering system, define all key dimension points, center-of-mass positions, and kinematic pairs, and establish a multi-rigid-body dynamics model through virtual prototyping technology, and apply an equivalent power source of the steering gear to drive the steering rod;

[0008] 2) Simulate and test the original left and right turning angle time-angle motion states of the steering system to obtain the motion distance of the parts and the change value of the steering angle. Taking the dimensions and center-of-mass position coordinates of each part of the multi-rigid-body dynamics as the input values of the simulation and the system steering angle as the output value. Within the design boundary range, it is evenly divided into a certain number of data groups for input and the output results are obtained. According to the change amount of the dimension center of mass and the change amplitude of the system steering angle, the parameter points of each rigid body are distinguished in terms of "sensitivity". Screen out the high-sensitivity data, and only optimize the motion relationship of this part of the data in the following to reduce the data operation pressure;

[0009] 3) Consider the motion characteristics under the Ackermann steering angle theory as the ideal left - right angle relationship of the steering knuckle: Taking the ideal steering angle and the actual steering angle, with the cumulative minimum of the root - mean - square value of the difference during the entire steering process as the optimization goal, convert it into a mathematical relationship and build a function algorithm, and obtain the target result through the operation of the virtual machine.

[0010] In step 1), according to the characteristics of each component of the steering system, using the method of multi - body dynamics theory, obtain the size data of the centroid and simple structures, and complete the coordinate system transformation; According to the obtained multi - body centroid coordinates and sizes, combined with the kinematic pair situation of the actual parts, establish a multi - body dynamics model in ADAMS, simulate the motion mode of the steering gear driving the tie rod, apply a virtual power source, and add an angle sensor in the system to obtain the required motion state of the steering knuckle.

[0011] In step 2), select the centroid points and sizes of all rigid bodies in the system, evenly input the data for parameters within the design boundary range and run it in the virtual machine. According to the size, the change amount of the centroid, and the change amplitude of the system steering angle, determine the sensitivity level of each parameter point of the rigid body. Confirm the sensitivity of each parameter, that is, the influence level on the result. To save computing power, only perform operations on a part of the parameters with relatively high sensitivity selected, calculate and compare to obtain the best result, and obtain the target parameters.

[0012] Advantages of the invention:

[0013] 1. The multi - body dynamics modeling of the steering mechanism based on ADAMS and the method for confirming the best component parameters of the present invention establish a multi - rigid - body dynamics model according to the composition characteristics of the steering system, and distinguish the sensitivity of all parameter points of the system, and screen out the high - sensitivity ones for the next - step data optimization. Compared with the method of directly adjusting parameters for non - rigid bodies without screening sensitivity, it greatly reduces the data operation pressure and reduces the time period of result calculation. The selected high - sensitivity parameters guide the subsequent real - vehicle tuning, reducing the number of sample parts required and the number of real - vehicle tests.

[0014] 2. The multi - body dynamics modeling of the steering mechanism based on ADAMS and the method for confirming the best component parameters of the present invention set the motion correspondence relationship under the ideal steering angle with the result of the Ackermann steering angle relationship. Taking the ideal steering angle and the actual steering angle, with the cumulative minimum of the root - mean - square value of the difference during the entire steering process as the optimization goal, convert it into a mathematical relationship and build a function algorithm, and obtain the target result through the operation of the virtual machine. Compared with repeatedly adjusting parameters and inputting, obtaining different results and then conducting manual comparison and screening, the algorithm can directly obtain the optimal solution according to the preset goal by the virtual machine, greatly improving the acquisition efficiency of the steering system. It is of great significance for improving the development efficiency of steering system parameters and saving development resources. Description of the drawings

[0015] Figure 1The figure shows a schematic diagram of extracting and measuring the centroid position and the actual moving length dimension of the complete steering system in CATIA;

[0016] Figure 2 The figure shows that in ADAMS, a multi-body dynamics model of the steering system is built;

[0017] Figure 3 The figure shows the test results of obtaining the parameter sensitivity by simulating the movement and testing the relationship between parameter input and rotation angle output;

[0018] Figure 4 The figure shows, under a given algorithm, the difference between the actual moving point and the ideal angle (upper part), and during the whole movement process, the fitting situation between the actual movement state represented by the solid line and the ideal body movement state represented by the dotted line. Specific implementation mode

[0019] In order to make the technical concept and advantages of the invention for achieving its invention purpose clearer and more understandable, the technical solution of the present invention will be further described in detail below with reference to the drawings. It should be understood that the following embodiments are only used to explain and illustrate the preferred implementation modes of the present invention, and should not constitute a limitation on the scope of patent protection required by the present invention.

[0020] Embodiment 1

[0021] The multi-body dynamics modeling and parameter confirmation method of the steering mechanism based on ADAMS of the present invention is implemented as follows:

[0022] 1) Refer to Figure 1 and Figure 2 , define all key dimension points, centroid positions, and kinematic pairs according to the composition characteristics of the steering system. Through virtual prototype technology, establish a multi-rigid-body dynamics model and apply an equivalent power source of the steering gear to drive the steering rod;

[0023] 2) Simulate and test the original left and right rotation angle time-angle movement states of the steering system to obtain the moving distance of parts and the change value of the steering angle. Use the dimensions and centroid position coordinates of each part of the multi-rigid-body dynamics as the input values of the simulation, and the system steering angle as the output value. Evenly divide them into a certain number of data groups within the design boundary range for input and obtain the output results. According to the change amount of the dimension centroid and the change amplitude of the system steering angle, distinguish the parameter points of each rigid body in terms of "sensitivity". Screen out the high-sensitivity data, and only further optimize the movement relationship of this part of the data in the following to reduce the data operation pressure. After simulating the movement, test the relationship between parameter input and rotation angle output, and obtain the test results of parameter sensitivity as shown in Figure 3 shown.

[0024] 3) Regarding the motion characteristics under the Ackermann steering angle theory as the ideal left - right angle relationship of the steering knuckle: Taking the root - mean - square value of the cumulative difference between the ideal steering angle and the actual steering angle during the entire steering process as the optimization goal, converting it into a mathematical relationship and building a function algorithm, and obtaining the target result through the operation of the virtual machine. As Figure 4 shown.

[0025] Example 2

[0026] The multi - body dynamics modeling and parameter confirmation method of the steering mechanism based on ADAMS in this example is different from that in Example 1 in that: Refer to Figure 1 , in step 1), according to the characteristics of each component of the steering system, by the method of multi - body dynamics theory, obtain the centroid and the dimensional data of the simple rigid body, and complete the coordinate system transformation.

[0027] According to the obtained multi - body centroid coordinates and dimensions, combined with the kinematic pair situation of the actual parts, establish a multi - body dynamics model in ADAMS, simulate the motion mode of the steering gear driving the tie rod to apply a virtual power source, and add an angle sensor in the system to obtain the required motion state of the steering knuckle. As Figure 2 shown.

[0028] Example 3

[0029] The multi - body dynamics modeling and parameter confirmation method of the steering mechanism based on ADAMS described in this example is different from that in Example 1 and Example 2 in that: As Figure 3 shown, in step 2), select the centroid points and dimensions of all rigid bodies in the system, evenly input the data for the parameters within the design boundary range and run in the virtual machine. According to the dimensions, the change amount of the centroid and the change amplitude of the system steering angle, determine the sensitivity level of each parameter point of each rigid body. Confirm the sensitivity of each parameter, that is, the influence level on the result. Then, confirm the optimization goal and edit the corresponding mathematical function to convert the goal realization into a mathematical operation quantity.

[0030] As Figure 4 shown. Set the motion correspondence relationship under the ideal steering angle according to the Ackermann steering angle relationship result. Taking the root - mean - square value of the cumulative difference between the ideal steering angle and the actual steering angle during the entire steering process as the optimization goal, convert it into a mathematical relationship and build a function algorithm. To save computing power, only perform operations on a part of the parameters with relatively high sensitivity selected. The virtual machine calculates and compares to obtain the best result according to the edited algorithm and obtains the target parameters.

[0031] In summary, the present invention provides an efficient multi-body dynamics modeling method and a method for confirming key parameters of components for the steering system design in the whole vehicle development process. According to the composition characteristics of the steering system, a multi-rigid body dynamics model is established by virtual prototype technology and a power source is applied. The time-angle motion states of the left and right steering angles are simulated and tested. Through the Design evaluation tool of ADAMS, the sensitivities of all parameter points are distinguished, and high-sensitivity data is screened and optimized to reduce the data operation pressure. The motion correspondence relationship under the ideal steering angle is set according to the Ackermann steering angle relationship result. Taking the minimum difference between the ideal steering angle and the actual steering angle during the whole steering process as the optimization goal, it is transformed into a mathematical relationship and a function algorithm is built, and the target result is obtained by the virtual machine operation. It is of great significance to improve the development efficiency of the steering system parameters and save development resources.

[0032] The above is only the preferred embodiment of the present invention and does not constitute a limitation to the present invention. Under the guidance of the prior art, those skilled in the art can make other modifications to the implementation of the present invention without creative labor. Any modification made within the spirit and principle of the present invention or any simple substitution or equivalent replacement using the conventional technical means in the art shall be included in the protection scope of the present invention.

Claims

1. A multi-body dynamics modeling and parameter confirmation method for a steering mechanism based on ADAMS, characterized in that The steps are as follows: 1) Define all key dimension points, centroid positions, and kinematic pairs according to the composition characteristics of the steering system. Through virtual prototype technology, establish a multi-rigid-body dynamics model and apply an equivalent power source of the steering gear to drive the steering rod; 2) Use the dimensions and centroid position coordinates of each part in the multi-rigid-body dynamics as input values for the simulation, and the system steering angle as the output value; Simulate and test the original left and right turning angle time-angle motion states of the steering system to obtain the motion distances of the parts and the change values of the steering angles; within the design boundary range, evenly divide the input of the data group and obtain the output results; Select the centroid points and dimensions of all rigid bodies in the system. Run the evenly divided input data of the parameters within the design boundary range in the virtual machine. According to the change amounts of the dimensions and centroids and the change amplitude of the system steering angle, confirm the sensitivity of each parameter, distinguish the parameter points of each rigid body in terms of "sensitivity", screen out the high-sensitivity data, and only further optimize the motion relationship of this part of the data in the following to reduce the data operation pressure; 3) Regard the motion characteristics under the Ackermann steering angle theory as the ideal left and right angle relationship of the steering knuckle: Take the ideal steering angle and the actual steering angle, and use the cumulative minimum of the root mean square value of the difference during the entire steering process as the optimization goal, convert it into a mathematical relationship and build a function algorithm, and obtain the target result through the operation of the virtual machine.

2. The multi-body dynamics modeling and parameter confirmation method of a steering mechanism based on ADAMS according to claim 1, characterized in that: In step 1), according to the characteristics of each component of the steering system, obtain the centroid and dimension data of simple structures according to the method of multi-body dynamics theory, and complete the coordinate system transformation; according to the obtained multi-body centroid coordinates and dimensions, combined with the kinematic pair situation of the actual parts, establish a multi-rigid-body dynamics model in ADAMS, simulate the motion mode of the steering gear driving the steering rod and apply a virtual power source, and add an angle sensor in the system to obtain the required motion state of the steering knuckle.

3. The multi-body dynamics modeling and parameter confirmation method of the steering mechanism based on ADAMS according to claim 1 or 2, characterized in that: To save computing power, only perform operations on a part of the parameters with relatively high sensitivity selected. The virtual machine calculates and compares to obtain the best result and obtain the target result according to the edited algorithm.

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