A non-pneumatic tire multi-parameter optimization design method based on bionic noise reduction
By using bionic principles and orthogonal experimental design, the optimal parameter combination for the leading edge serrated structure of non-pneumatic tires was determined. Combined with numerical simulation, the aerodynamic noise reduction effect of non-pneumatic tires was achieved, solving the problem of unclear aerodynamic noise generation mechanism of non-pneumatic tires. The optimized design method saves resources and improves the noise reduction effect.
Patent Information
- Application Number
- CN202610343915.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-20
- Publication Date
- 2026-06-19
AI Technical Summary
The mechanism of aerodynamic noise generation in non-pneumatic tires at high speeds is unclear, and the applicability of biomimetic noise reduction structures and the influence of parameters on them are not clear. Traditional experimental methods are time-consuming and resource-intensive.
A multi-parameter optimization design method based on bionics principles was adopted. Through orthogonal experimental design and range analysis, the optimal parameter combination of the leading edge sawtooth structure of the non-pneumatic tire was determined. A three-dimensional numerical simulation model was established using CATIA software, and numerical simulation calculations and range analysis were performed to further optimize it into an asymmetric sawtooth structure.
The system achieved a systematic noise reduction effect on the aerodynamic noise of non-pneumatic tires, with a total noise reduction of 4.89dB. The optimized design method is reproducible and saves resources.
Smart Images
Figure CN122241917A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of numerical simulation technology for non-pneumatic tires, specifically to a multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction. Background Technology
[0002] Traditional pneumatic tires rely on compressed air to support vehicle loads and provide cushioning. However, over long-term use, pneumatic tires have become increasingly problematic due to issues such as severe pollution, susceptibility to blowouts, high maintenance costs, and poor adaptability to various operating conditions. Against this backdrop, non-pneumatic tires have gained widespread attention due to their structural advantages. Aerodynamic noise control technology is mainly divided into two categories: active control and passive control. Active control requires external energy input to intervene in the flow field, such as wall suction, air blowing, and plasma actuators; passive control achieves noise suppression by applying local geometric modifications to surfaces, such as eddy current generators. With the slowdown in the progress of traditional noise reduction technologies, there is an urgent need to introduce new design approaches.
[0003] Against this backdrop, biomimetic design, drawing inspiration from the structural and functional principles of biological systems, offers a new technological path for aerodynamic noise control. The owl, a quintessential example of silent flight in nature, utilizes the serrated feather structure on the leading edge of its wings to effectively control airflow distribution, disperse airflow entering the wing's leading edge, and reduce vortex generation, thus achieving near-silent gliding. Noise reduction research inspired by the owl has been validated in several aerodynamic components: serrated leading edges of duct fans can significantly reduce broadband noise below 2kHz; axial fans equipped with serrated leading edges under non-uniform flow conditions experience a reduction in average total sound pressure level; serrated leading edges of airfoil structures can effectively suppress laminar boundary layer instability noise; and UAV rotors employing a coupled leading-edge and trailing-edge serrated structure have achieved noise reduction optimization. These studies demonstrate that owl-inspired serrated structures have good noise reduction applicability in rotating machinery and airfoil components.
[0004] However, the aerodynamic characteristics of non-pneumatic tires, with their unique open support structure, differ significantly from those of traditional pneumatic tires during high-speed rotation. The mechanism of aerodynamic noise generation in non-pneumatic tires remains unclear, and the applicability of biomimetic noise reduction structures to non-pneumatic tires and the influence of their parameters require systematic research. Therefore, it is necessary to establish a systematic noise reduction structure design method suitable for non-pneumatic tires, incorporating biomimetic principles. In the field of optimization design, when it is necessary to simultaneously examine the influence of multiple factors on experimental indicators, traditional comprehensive experimental methods require numerous experiments, consuming significant time and resources. Summary of the Invention
[0005] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.
[0006] To address the aforementioned technical problems, according to one aspect of the present invention, the present invention provides the following technical solution: A multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction includes the following steps: S1: Define optimization parameters: Taking into account the ratio of tooth pitch to tooth height, the spacing between sawtooth structures, the difficulty of mesh generation, and computational resources, the sawtooth structure at the leading edge of the non-pneumatic tire support is selected as the optimization object, and three geometric parameters to be optimized are defined. S2: Orthogonal experimental factor level setting: Referring to the existing research results on biomimetic sawtooth noise reduction, and taking into account the ratio of sawtooth height to tooth pitch, the difficulty of mesh generation and computing resources, three levels are selected for each optimization parameter, and a three-factor, three-level orthogonal experimental factor level table is established. S3: Orthogonal experimental design: Based on the three-factor, three-level experimental design, L9(3) was adopted. 4 Nine parameter combination schemes are arranged in an orthogonal array, with the total sound pressure level of the far-field noise 1 meter away from the rotation center of the non-pneumatic tire as the evaluation index; S4: Establish a three-dimensional numerical simulation model of a non-pneumatic tire; S5: Perform orthogonal experimental simulation: Modify the geometric parameters of the leading edge sawtooth of the model respectively, perform numerical simulation calculations in sequence, and record the total sound pressure level of the far field noise for each scheme; S6: Range Analysis: Perform range analysis on the experimental results, calculate the average response and range R of each factor at each level, and analyze the influence of the three optimization parameters on the aerodynamic noise of non-pneumatic tires based on the magnitude of the range R. S7: Main effect analysis: Establish the main effect diagram of the sawtooth structure parameters and analyze the influence trend of each parameter on noise; S8: Determine the optimal parameter combination: Based on the results of range analysis and main effect analysis, select the parameter combination that minimizes the total sound pressure level of aerodynamic noise; S9: Verification of noise reduction effect of optimal parameters: Establish a model according to the optimal parameter combination determined in S8 and perform numerical simulation. Compare the noise results obtained from the simulation with the original non-pneumatic tire. S10: Improved design of asymmetric sawtooth structure: Based on the optimal symmetric sawtooth structure obtained in S8, the deflection angle is designed. According to the geometric dimensions of the optimal sawtooth structure, the deflection angle is calculated and determined, and the original symmetric sawtooth structure is transformed into an asymmetric sawtooth configuration. S11: Verification of the effect of asymmetric sawtooth structure: Perform numerical simulation calculations on a non-pneumatic tire with an asymmetric sawtooth structure, and compare the results with the results of the symmetric sawtooth structure obtained in step 9.
[0007] As a preferred embodiment of the non-pneumatic tire multi-parameter optimization design method based on biomimetic noise reduction described in this invention, the three geometric parameters to be optimized in S1 include: 1) Sawtooth height h2: The height of the sawtooth protrusion along the normal direction of the front edge of the support; 2) Spacing s1 along the front edge of the support: The distance between adjacent saw teeth along the front edge of the support; 3) Spacing s2 perpendicular to the front edge of the support: The distance between adjacent saw teeth perpendicular to the front edge of the support.
[0008] As a preferred embodiment of the non-pneumatic tire multi-parameter optimization design method based on biomimetic noise reduction described in this invention, the specific method of step S4 is as follows: Geometric modeling: Based on the actual dimensions of the non-pneumatic tire, a 1:1 scale 3D model is created in CATIA software; Computation domain setup: Construct a computation domain with dimensions of 12.5 times the tire diameter × 17 times the tire width × 2.8 times the tire diameter; Mesh generation: A polyhedral mesh is used for mesh generation, with progressively denser mesh areas set in the support area; Boundary conditions are set as follows: the inlet is set as a velocity inlet with a wind speed of 80 km / h; the outlet is set as a pressure outlet; the model surface and ground are set as walls; the sides and top are set as symmetrical planes. Solution method selection: First, the multi-coordinate reference system method is used for steady-state calculation to initialize the flow field; then, the sliding mesh method is used for transient calculation.
[0009] As a preferred embodiment of the non-pneumatic tire multi-parameter optimization design method based on biomimetic noise reduction described in this invention, the calculation formulas for the average response value and range R in step S6 are as follows: average response ; Range .
[0010] Compared with the prior art, the beneficial effects of this invention are: a systematic multi-parameter optimization design method is established: through orthogonal experimental design and range analysis, this invention establishes the quantitative relationship between three geometric parameters (serration height, spacing along the leading edge direction, and spacing perpendicular to the leading edge direction) of the non-pneumatic tire leading edge serration structure and aerodynamic noise, providing a reproducible systematic method for the structural design of low-noise non-pneumatic tires.
[0011] 2. The influence of each parameter on noise was clarified: Range analysis revealed the order of influence of the three parameters on aerodynamic noise, with sawtooth height having the most significant impact, followed by the spacing along the leading edge, and the spacing perpendicular to the leading edge having the least impact. Main effect plot analysis revealed the changing trends of each parameter, namely, the influence of sawtooth height and vertical spacing on noise showed a trend of first decreasing and then increasing, while the influence of spacing along the leading edge on noise showed a continuous increasing trend.
[0012] 3. Optimal parameter combination and noise reduction effect were obtained: The biomimetic leading edge sawtooth structure designed by determining the optimal parameter combination through multi-parameter optimization can achieve a noise reduction effect of 3.64dB.
[0013] 4. Secondary optimization of noise reduction effect was achieved: Based on the optimal symmetrical sawtooth structure, an offset angle design was introduced. The offset angle was calculated to be 14° based on a tooth width of 2mm and a tooth height of 4mm, forming an asymmetrical sawtooth structure. Verification showed that the asymmetrical sawtooth structure can further reduce aerodynamic noise by 1.25dB compared to the symmetrical sawtooth structure, achieving a total noise reduction of 4.89dB. Attached Figure Description
[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and detailed embodiments. Obviously, the 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. Wherein: Figure 1 This is a flowchart of a multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction according to the present invention; Figure 2 This is a parameter diagram of the leading edge serrated structure in an embodiment of the multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction of the present invention. Figure 3 This is a model diagram of an optimized and corrected non-pneumatic tire in an embodiment of a non-pneumatic tire multi-parameter optimization design method based on biomimetic noise reduction according to the present invention. Figure 4 This is a schematic diagram of the flow field simulation calculation domain in an embodiment of the non-pneumatic tire multi-parameter optimization design method based on biomimetic noise reduction of the present invention; Figure 5 This is a diagram showing the setting of the flow field simulation encryption zone in an embodiment of the multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction according to the present invention. Figure 6 This is a principal effect diagram of the serrated structure parameters in an embodiment of the multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction according to the present invention. Figure 7This is a comparison of aerodynamic noise spectrum diagrams before and after adding a biomimetic sawtooth structure in an embodiment of the multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction of the present invention. Figure 8 This is a comparison diagram of the traditional sawtooth structure and the asymmetric sawtooth structure in an embodiment of the multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction of the present invention. Figure 9 This is a comparison of aerodynamic noise spectrum diagrams of symmetrical and asymmetrical sawtooth structures in an embodiment of the multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction of the present invention. Detailed Implementation
[0015] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
[0016] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
[0017] The purpose of this invention is to provide a multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction. By establishing a quantitative relationship between the parameters of the leading edge sawtooth structure and aerodynamic noise, and using the orthogonal experimental design principle, a three-factor, three-level L9 orthogonal array is established. The total sound pressure level of far-field noise is used as the evaluation index. Noise data under various parameter combinations are obtained through a finite number of simulation experiments. Then, the experimental results are processed using the range analysis method to determine the order and trend of the influence of each parameter on noise, thereby obtaining the optimal parameter combination. Finally, asymmetric design is introduced to achieve secondary optimization of the noise reduction effect.
[0018] Example Please see Figure 1 A multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction includes the following steps: S1: Define optimization parameters: Considering the ratio of tooth pitch to tooth height, the spacing between serrated structures, the ease of mesh generation, and computational resources, the serrated structure at the leading edge of the non-pneumatic tire support is selected as the optimization object. Three geometric parameters to be optimized are defined (e.g., Figure 2 ); 1) Sawtooth height h2: The height of the sawtooth protrusion along the normal direction of the front edge of the support; 2) Spacing s1 along the front edge of the support: The distance between adjacent saw teeth along the front edge of the support; 3) Spacing s2 perpendicular to the front edge of the support: The distance between adjacent saw teeth perpendicular to the front edge of the support.
[0019] The three parameters mentioned above together determine the shape and distribution density of the serrated structure, which are key variables affecting the aerodynamic noise of non-pneumatic tires.
[0020] S2: Orthogonal Experiment Factor Level Setting: Referring to existing research results on biomimetic sawtooth noise reduction, and comprehensively considering the ratio of sawtooth height to tooth pitch, the difficulty of mesh generation, and computational resources, three levels are selected for each optimization parameter, and a three-factor, three-level orthogonal experimental factor level table is established (as shown in Table 1): Table 1. Factor Level Table for Orthogonal Experiment
[0021] S3: Orthogonal experimental design: Based on the three-factor, three-level experimental design, L9(3) was adopted. 4 Nine parameter combination schemes were arranged using an orthogonal array. The total sound pressure level of the far-field noise at a distance of 1 meter from the rotation center of the non-pneumatic tire was used as the evaluation index, and the following experimental scheme was determined (as shown in Table 2): Table 2 Orthogonal Experimental Scheme
[0022] S4: Establish a 3D numerical simulation model of a non-pneumatic tire: specifically including: (1) Geometric Modeling: Based on the actual dimensions of the non-pneumatic tire (diameter 0.64 m, width 0.175 m), a 1:1 scale 3D model was created in CATIA software. To better explore the impact of the support structure on noise, the tire surface and rim were appropriately simplified (e.g., ...) while ensuring calculation accuracy. Figure 3 ); (2) Computation domain setup: Construct a computation domain with dimensions of 12.5 times the tire diameter (length) × 17 times the tire width (width) × 2.8 times the tire diameter (height), ensuring a blockage ratio of less than 5% (e.g., Figure 4 ); (3) Mesh generation: Polyhedral meshes are used for mesh generation. Layer-by-layer mesh regions are set in the support area, with a minimum mesh size of 2 mm. The total number of meshes is approximately 8.4 million (e.g., ...). Figure 5 ); (4) Boundary conditions: The inlet is set as a velocity inlet with a wind speed of 80 km / h; the outlet is set as a pressure outlet; the model surface and ground are set as walls; the sides and top are set as symmetrical planes; (5) Solution method selection: First, the multiple reference frame method (MRF) is used for steady-state calculation to initialize the flow field; then, the sliding mesh method (SM) is used for transient calculation, with the time step set to 2×10⁻ 5 s, the total calculation time is 0.1s; S5: Perform orthogonal experimental simulation: According to the 9 sets of parameter combinations designed in Table 2, modify the geometric parameters of the leading edge sawtooth of the model respectively, perform numerical simulation calculations in sequence, record the total sound pressure level of the far field noise of each scheme, and obtain the experimental results as shown in Table 3.
[0023] Table 3. Results of Orthogonal Experiments on Stationary Non-Pneumatic Tires
[0024] S6: Range Analysis: Perform range analysis on the experimental results to calculate the average response and range R for each factor at each level. The calculation formula is as follows: average response ; Range ; The range analysis results calculated using the above formula are shown in Table 4.
[0025] Table 4. Range Analysis Results of Non-Pneumatic Tires
[0026] S7: Main Effect Analysis: Based on the magnitude of the range R value, the influence of the three optimization parameters on the aerodynamic noise of the non-pneumatic tire is ranked as follows: serration height h2 (R=0.90) > spacing s1 along the leading edge of the support (R=0.59) > spacing s2 perpendicular to the leading edge of the support (R=0.34). This is confirmed by the main effect diagram (e.g., ...). Figure 6 )Analyze the influence trend of each parameter on noise; 1) As the sawtooth height h2 increases, the noise level shows a trend of first decreasing and then increasing; 2) As the interval s2 perpendicular to the front edge of the support increases, the noise level also shows a trend of first decreasing and then increasing. 3) As the interval s1 along the leading edge of the support increases, the noise level shows a continuous upward trend. S8: Determine the optimal parameter combination: Based on the results of range analysis and main effect analysis, select the parameter combination that minimizes the total sound pressure level of aerodynamic noise, namely, sawtooth height h2=4mm, spacing s1=2mm along the front edge of the support, and spacing s2=4mm perpendicular to the front edge of the support. S9: Verification of Noise Reduction Effect with Optimal Parameters: A model was established according to the optimal parameter combination determined in S8, and numerical simulation was performed. The noise results obtained from the simulation were compared with those of the original non-pneumatic tire (without serrated structure). The total sound pressure level was calculated, and the optimal biomimetic leading-edge serrated structure can achieve a noise reduction effect of 3.64dB (e.g., Figure 7 ); S10: Improved Design of Asymmetric Serrated Structure: Based on the study of the oblique arc characteristic of the leading edge serrations of real owl wing feathers, the deflection angle was designed on the basis of the optimal symmetrical serrated structure obtained in S8. According to the geometric dimensions of the optimal serrated structure (tooth width 2mm, tooth height 4mm), the deflection angle was calculated and determined to be 14°, transforming the original symmetrical serrated structure into an asymmetric serrated configuration (e.g., ...). Figure 8 ); S11: Verification of the effect of the asymmetric sawtooth structure: Numerical simulation calculations were performed on a non-pneumatic tire with an asymmetric sawtooth structure, and the results were compared with those obtained in S9 for the symmetrical sawtooth structure. Simulation results show that the asymmetric sawtooth structure can further reduce aerodynamic noise by 1.25 dB compared to the symmetrical sawtooth structure, with a total noise reduction of 4.89 dB (e.g., ...). Figure 9 ).
[0027] Although the present invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, as long as there is no structural conflict, the features in the disclosed embodiments can be combined with each other in any manner. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.
Claims
1. A multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction, characterized in that, Includes the following steps: S1: Define optimization parameters: Taking into account the ratio of tooth pitch to tooth height, the spacing between sawtooth structures, the difficulty of mesh generation, and computational resources, the sawtooth structure at the leading edge of the non-pneumatic tire support is selected as the optimization object, and three geometric parameters to be optimized are defined. S2: Orthogonal experimental factor level setting: Referring to the existing research results on biomimetic sawtooth noise reduction, and taking into account the ratio of sawtooth height to tooth pitch, the difficulty of mesh generation and computing resources, three levels are selected for each optimization parameter, and a three-factor, three-level orthogonal experimental factor level table is established. S3: Orthogonal experimental design: Based on the three-factor, three-level experimental design, L9(3) was adopted. 4 Nine parameter combination schemes are arranged in an orthogonal array, with the total sound pressure level of the far-field noise 1 meter away from the rotation center of the non-pneumatic tire as the evaluation index; S4: Establish a three-dimensional numerical simulation model of a non-pneumatic tire; S5: Perform orthogonal experimental simulation: Modify the geometric parameters of the leading edge sawtooth of the model respectively, perform numerical simulation calculations in sequence, and record the total sound pressure level of the far field noise for each scheme; S6: Range Analysis: Perform range analysis on the experimental results, calculate the average response and range R of each factor at each level, and analyze the influence of the three optimization parameters on the aerodynamic noise of non-pneumatic tires based on the magnitude of the range R. S7: Main effect analysis: Establish the main effect diagram of the sawtooth structure parameters and analyze the influence trend of each parameter on noise; S8: Determine the optimal parameter combination: Based on the results of range analysis and main effect analysis, select the parameter combination that minimizes the total sound pressure level of aerodynamic noise; S9: Verification of noise reduction effect of optimal parameters: Establish a model according to the optimal parameter combination determined in S8 and perform numerical simulation. Compare the noise results obtained from the simulation with the original non-pneumatic tire. S10: Improved design of asymmetric sawtooth structure: Based on the optimal symmetric sawtooth structure obtained in S8, the deflection angle is designed. According to the geometric dimensions of the optimal sawtooth structure, the deflection angle is calculated and determined, and the original symmetric sawtooth structure is transformed into an asymmetric sawtooth configuration. S11: Verification of the effect of asymmetric sawtooth structure: Perform numerical simulation calculations on a non-pneumatic tire with an asymmetric sawtooth structure, and compare the results with the results of the symmetric sawtooth structure obtained in step 9.
2. The multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction according to claim 1, characterized in that, The three geometric parameters to be optimized in S1 include: 1) Sawtooth height h2: The height of the sawtooth protrusion along the normal direction of the front edge of the support; 2) Spacing s1 along the front edge of the support: The distance between adjacent saw teeth along the front edge of the support; 3) Spacing s2 perpendicular to the front edge of the support: The distance between adjacent saw teeth perpendicular to the front edge of the support.
3. The multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction according to claim 1, characterized in that, The specific method of S4 is as follows: Geometric modeling: Based on the actual dimensions of the non-pneumatic tire, a 1:1 scale 3D model is created in CATIA software; Computation domain setup: Construct a computation domain with dimensions of 12.5 times the tire diameter × 17 times the tire width × 2.8 times the tire diameter; Mesh generation: A polyhedral mesh is used for mesh generation, with progressively denser mesh areas set in the support area; Boundary conditions are set as follows: the inlet is set as a velocity inlet with a wind speed of 80 km / h; the outlet is set as a pressure outlet; the model surface and ground are set as walls; the sides and top are set as symmetrical planes. Solution method selection: First, the multi-coordinate reference system method is used for steady-state calculation to initialize the flow field; then, the sliding mesh method is used for transient calculation.
4. The multi-parameter optimization design method for non-pneumatic tires based on biomimetic noise reduction according to claim 1, characterized in that, The formulas for calculating the average response value and range R in S6 are as follows: average response Range .