Tire noise determination method and device and electronic equipment

Abstract

The invention discloses a tire noise determination method and device and electronic equipment. The method comprises the steps that a pattern model of a target tire is built according to pattern groove depth information and pitch information of the target tire, the pattern model comprises a three-dimensional plane model corresponding to tread patterns of the target tire, and the pitch information is at least used for reflecting the arrangement rule of pattern blocks on the tread of the whole circumference; a scanning curved surface corresponding to the grounding mark of the target tire is determined, and the scanning curved surface comprises curved surfaces corresponding to the front edge and the rear edge of the grounding mark respectively; the noise index of the target tire is determined according to the pattern model and the scanning curved surface, and the noise index is used for quantifying the gas pumping and releasing capacity of the pattern groove in the grounding process of the target tire; and determining tire noise corresponding to the noise index. The technical problem that a tire pattern noise simulation prediction method adopted in the related technology cannot effectively balance prediction precision and complexity is solved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device and electronic device for determining tire noise. Background Art

[0002] Tire rolling noise mainly consists of pump noise, friction noise and structure-borne noise. Pump noise is the main source of tire rolling noise, accounting for about 80% of the total noise. It refers to the noise generated by the pressure wave formed by the air being squeezed in the contact area between the tire and the ground during driving.

[0003] However, the tire pattern noise simulation prediction method used in related technologies relies on image recognition technology to identify patterns, which easily leads to the loss of tire tread details and pattern depth information. Constructing a three-dimensional solid model of the complete tire will make the model too complex and difficult to adapt to the requirements of the tire design cycle.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] The embodiments of the present application provide a tire noise determination method, device, and electronic device to at least solve the technical problem that the tire pattern noise simulation prediction method used in the related art cannot effectively balance prediction accuracy and complexity.

[0006] According to one aspect of an embodiment of the present application, a method for determining tire noise is provided, comprising: constructing a pattern model of a target tire based on groove depth information and pitch information of the target tire, wherein the pattern model includes a three-dimensional plane model corresponding to the tread pattern of the target tire, and the pitch information is used to at least reflect the regularity of the arrangement of pattern blocks on the entire tread; determining a scanning surface corresponding to the contact footprint of the target tire, wherein the scanning surface includes surfaces corresponding to the leading edge and the trailing edge of the contact footprint, respectively; determining a noise index of the target tire based on the pattern model and the scanning surface, wherein the noise index is used to quantify the gas pumping and release capacity of the pattern groove during the contact process of the target tire; and determining the tire noise corresponding to the noise index.

[0007] In some embodiments of the present application, a pattern model of a target tire is constructed based on the groove depth information and pitch information of the target tire, including: obtaining the groove depth information and pitch information of the target tire, wherein the pitch information includes information corresponding to multiple types of pitches of the target tire; constructing multiple pattern block solid models based on the groove depth information and the information corresponding to the multiple types of pitches, wherein the pattern block solid models are used to reflect the groove depth and shape corresponding to the pitch type; arranging the multiple pattern block solid models based on the pitch arrangement information in the pitch information to obtain a three-dimensional plane model, wherein the pitch arrangement information is used to indicate the arrangement order of the multiple types of pitches in the circumferential direction.

[0008] In some embodiments of the present application, determining a scanning surface corresponding to the contact footprint of a target tire includes: acquiring a contact footprint image of the target tire, and extracting outer contour curves of the leading and trailing edges of the contact footprint of the target tire from the contact footprint image; stretching the outer contour curves of the leading and trailing edges along a direction perpendicular to the tread of the target tire to obtain a scanning surface, wherein the stretching height is greater than the maximum transverse groove depth in the pattern model.

[0009] In some embodiments of the present application, the noise index of the target tire is determined based on the pattern model and the scanning surface, including: aligning the starting point of the scanning surface with the starting position of the pattern model, and starting from the starting position, advancing the scanning surface along the circumference of the target tire according to the scanning step; each time the scanning step is advanced, determining the first overlapping area of ​​the scanning surface and the pattern groove of the target tire in the pattern model; determining the volume of gas pumped or released at the corresponding scanning position based on the first overlapping area, and obtaining a first volume change sequence, wherein the first volume change sequence includes the volume of gas pumped or released corresponding to the entire circumference of the tread of the target tire; and determining the noise index based on the first volume change sequence.

[0010] In some embodiments of the present application, the noise index of the target tire is determined based on the pattern model and the scanning surface, including: obtaining multiple pitch types of the target tire from the pitch information; for each pitch type, scanning the pitch once using the scanning surface, and determining the second overlapping area of ​​the scanning surface and the pattern groove; determining the volume of gas pumped or released corresponding to the pitch type at the scanning position based on the second overlapping area, and obtaining a second volume change, wherein the second volume change is the volume change obtained by scanning each pitch type separately; determining the relative phase of each pitch type in the circumferential direction of the target tire based on the pitch arrangement information in the pitch information; superimposing and summing multiple second volume changes corresponding to the multiple pitch types in the time domain according to the relative phase to obtain a third volume change sequence, wherein the third volume change sequence is the volume change sequence corresponding to the entire tread of the target tire; and determining the noise index based on the third volume change sequence.

[0011] In some embodiments of the present application, the noise index is determined in the following manner: determining a target function of the volume change over time based on a target volume change sequence and a driving speed of a target tire, wherein the target volume change sequence is a volume change sequence corresponding to the entire tread of the target tire; performing time domain fitting on the leading sound pressure and the trailing sound pressure of the target tire on the basis of the target function, respectively, to obtain a leading sound pressure fitting result and a trailing sound pressure fitting result, wherein the leading sound pressure is the sound pressure generated when air is pumped into the target tire, and the trailing sound pressure is the sound pressure generated when air is released from the target tire; and determining the noise index corresponding to the leading sound pressure fitting result and the trailing sound pressure fitting result.

[0012] In some embodiments of the present application, the noise index corresponding to the leading edge sound pressure fitting result and the trailing edge sound pressure fitting result is determined, including: performing a phase shift on the trailing edge sound pressure fitting result to obtain a target trailing edge sound pressure fitting result, wherein the phase shift distance is the crown center imprint length; obtaining an adjustment coefficient corresponding to the trailing edge sound pressure fitting result, wherein the adjustment coefficient is used to compensate for the difference between the trailing edge sound pressure and the leading edge sound pressure; and superimposing the leading edge sound pressure fitting result and the target trailing edge sound pressure fitting result on the basis of the adjustment coefficient to obtain the noise index.

[0013] In some embodiments of the present application, the noise index includes a noise time domain signal, wherein the noise time domain signal is used to describe the time domain characteristics of the pump noise of the target tire during the grounding process; determining the tire noise corresponding to the noise index includes: intercepting the noise time domain signal based on the circumference of the target tire and the scanning step size corresponding to the scanning surface to obtain a first noise time domain signal corresponding to the entire tread of the target tire; converting the first noise time domain signal into a frequency domain signal, and determining the tire noise based on the frequency domain signal.

[0014] In some embodiments of the present application, it also includes: determining a plurality of pattern ribs formed by dividing the pattern longitudinal grooves in the transverse direction of the pattern of the target tire in the pattern model; using a scanning surface to scan the plurality of pattern ribs respectively to obtain a scanning matrix, wherein the rows of the scanning matrix represent the pattern ribs and the columns represent the scanning points, and the scanning matrix is ​​used to store the volume of gas pumped in or released by the plurality of pattern ribs at different scanning positions; determining that the plurality of pattern ribs correspond to the second noise time domain signals respectively according to the scanning matrix, and superimposing and synthesizing all the second noise time domain signals to obtain a first total noise signal; optimizing the position of the pattern ribs of the target tire according to the second noise time domain signal and the first total noise signal.

[0015] In some embodiments of the present application, the position of the pattern ribs of the target tire is optimized based on the second noise time domain signal and the first total noise signal, including: determining the areas of coherent superposition and coherent cancellation from the first total noise signal; determining the misalignment ranges corresponding to the multiple pattern ribs, wherein the misalignment in the misalignment range is used to perform phase adjustment on the pattern ribs, and the goal of the phase adjustment is to maximize the area of ​​coherent cancellation; iteratively adjusting each pattern rib in turn based on the misalignment range to obtain the second total noise signal corresponding to each iteration, and determining the target misalignment corresponding to the multiple pattern ribs when the second total noise signal meets preset conditions; and optimizing the position of the pattern ribs based on the target misalignment.

[0016] In some embodiments of the present application, determining the range of misalignment amounts corresponding to a plurality of pattern ribs respectively includes: determining the type of pattern of the target tire; when the type indicates that the pattern is a symmetrical pattern, determining a first misalignment amount corresponding to the pattern ribs that are symmetrical based on the center line, wherein the number of the first misalignment amounts is the same as the number of pattern ribs that are symmetrical based on the center line; when the type indicates that the pattern is an asymmetrical pattern, determining a second misalignment amount corresponding to the plurality of pattern ribs.

[0017] According to another aspect of an embodiment of the present application, a device for determining tire noise is also provided, including: a construction module for constructing a pattern model of a target tire based on the tread groove depth information and pitch information of the target tire, wherein the pattern model includes a three-dimensional plane model corresponding to the tread pattern of the target tire, and the pitch information is used to reflect the regularity of the arrangement of pattern blocks on the tread of the target tire; a determination module for determining a scanning surface corresponding to the ground contact footprint of the target tire, wherein the scanning surface includes surfaces corresponding to the leading edge and the trailing edge of the ground contact footprint, respectively; a conversion module for determining a noise index of the target tire based on the pattern model and the scanning surface, wherein the noise index is used to quantify the gas pumping and release capacity of the pattern groove during the ground contact process of the target tire; and an execution module for determining the tire noise corresponding to the noise index.

[0018] According to another aspect of the embodiments of the present application, an electronic device is provided, including: a memory and a processor, the memory being used to store program instructions; and the processor being connected to the memory and being used to execute the above-mentioned tire noise determination method.

[0019] According to another aspect of the embodiments of the present application, a non-volatile storage medium is provided. The non-volatile storage medium includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned tire noise determination method by running the computer program.

[0020] According to yet another aspect of the embodiments of the present application, a computer program product is provided, including computer instructions, which implement the above tire noise determination method when executed by a processor.

[0021] In an embodiment of the present application, a method of constructing only a three-dimensional plane model of the tire tread pattern is adopted. By constructing a tire pattern model and combining it with a scanned surface of its contact patch, the gas pumping and release capabilities during the tire contact process are quantified, and tire noise is predicted. This achieves the purpose of accurately predicting the noise level of the tire under different road conditions, thereby achieving the technical effect of improving prediction accuracy and simplifying the complexity of traditional noise testing, and thus solving the technical problem that the tire pattern noise simulation prediction method adopted in the related art cannot effectively balance prediction accuracy and complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0023] Figure 1 is a hardware structure block diagram of a computer terminal according to a tire noise determination method according to an embodiment of the present application;

[0024] Figure 2 is a flow chart of a method for determining tire noise according to an embodiment of the present application;

[0025] Figure 3 1 is a schematic diagram of the overall process of a method for determining tire noise according to an embodiment of the present application;

[0026] Figure 4 is a schematic diagram of a pattern model of a method for determining tire noise according to an embodiment of the present application;

[0027] Figure 5 is a schematic diagram of the pattern scanning principle of a method for determining tire noise according to an embodiment of the present application;

[0028] Figure 6 is a schematic diagram of time domain results of a method for determining tire noise according to an embodiment of the present application;

[0029] Figure 7 is a schematic diagram of harmonic results of a method for determining tire noise according to an embodiment of the present application;

[0030] Figure 8 is a schematic diagram of frequency domain results of a method for determining tire noise according to an embodiment of the present application;

[0031] Figure 9is a schematic diagram of a misalignment optimization result of a tire noise determination method according to an embodiment of the present application;

[0032] Figure 10 3 is a schematic structural diagram of a device for determining tire noise according to an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] Since electric vehicles don't require engines, eliminating engine noise as the primary noise source, tire noise becomes the primary source of road noise at low and medium speeds. To meet noise requirements, tire manufacturers are currently using simulation methods, such as simulation calculations or analytical algorithms, to evaluate and improve tire noise during the design phase. However, simulation involves three-dimensional modeling and calculations, requiring the construction of a complete three-dimensional solid tire model. However, due to the complexity of the tire structure and tread pattern, model drawing, meshing, and calculations are time-consuming, and the computational structure is difficult to converge. Complex solutions can take up to a month to complete, making them difficult to adapt to the required pattern design cycle. Furthermore, techniques that use image recognition to identify tread patterns are limited by drawing accuracy and image noise, leading to errors and loss of detail in small tread grooves and structures. Furthermore, binary matrices only consider the circumferential and lateral dimensions of the tread and do not factor in the effects of depth, resulting in inaccurate predictions.

[0036] In order to solve the above technical problems, the embodiments of the present application provide corresponding solutions, which are described in detail below.

[0037] The tire noise determination method provided in the embodiments of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Figure 1 FIG1 shows a hardware structure block diagram of a computer terminal for implementing a method for determining tire noise. Figure 1 As shown, the computer terminal 10 may include one or more (illustrated by 102a, 102b, ..., 102n in the figure) processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module 106 for communication functions connected via a wired and / or wireless network. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0038] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 10. As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0039] Memory 104 can be used to store software programs and modules for application software, such as the program instructions / data storage device corresponding to the tire noise determination method in the embodiments of the present application. The processor executes the software programs and modules stored in memory 104 to perform various functional applications and data processing, thereby implementing the tire noise determination method described above. Memory 104 can include high-speed random access memory (RAM) and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 may further include memory remotely located from the processor, which can be connected to computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0040] The transmission module 106 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission module 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission module 106 may be a radio frequency (RF) module, which is configured to communicate with the Internet wirelessly.

[0041] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .

[0042] It should be noted that, in some optional embodiments, the above Figure 1 The computer terminal shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computer terminal described above.

[0043] In the above operating environment, an embodiment of the present application provides an embodiment of a method for determining tire noise. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0044] Figure 2 is a flow chart of a method for determining tire noise according to an embodiment of the present application, such as Figure 2 As shown, the method includes the following steps:

[0045] Step S202: construct a pattern model of the target tire based on the groove depth information and pitch information of the target tire, wherein the pattern model includes a three-dimensional plane model corresponding to the tread pattern of the target tire, and the pitch information is at least used to reflect the regularity of the arrangement of pattern blocks on the entire tread.

[0046] In step S202 above, the groove depth information refers to the depth of the grooves in the tire tread. Pitch information refers to the circumferential arrangement of the tire tread blocks, including the length, number, and arrangement order of different types of pitches (i.e., pitch arrangement information, which indicates the circumferential arrangement order of different pitch types on the tire tread), and is used to simulate the geometric characteristics of the tread pattern.

[0047] A tread pattern model is a mathematical or visual model constructed based on the target tire's groove depth and pitch information, used to simulate and predict tire noise performance. It should be noted that in some embodiments of this application, to simplify the pattern model and focus on the impact of the tread pattern, a three-dimensional planar model, taken along the tire's radial direction and reflecting only the target tire's tread pattern depth, width, and pitch arrangement, may be used.

[0048] In some embodiments of the present application, by collecting the groove depth information and pitch information (such as pitch length L p , total number of pitches n all 、Number of various pitches n p , the number of pitch types (p). Then, in 3D modeling software, p types of tread block solid models are constructed based on the dimensional data provided on the CAD drawings. These block solid models are then arranged according to the tire pitch arrangement information (sequence), ultimately creating a 3D planar model of the pattern corresponding to the entire tread. By modeling only the tread pattern portion, ignoring the complexity of the tire's internal structure while ensuring that the model includes groove depth information, this solves the modeling difficulties and time-consuming issues caused by the complex tire structure in traditional simulation methods. In particular, unnecessary modeling of internal structures such as belts and plies is avoided, allowing the modeling process to focus more on the tread pattern that is directly related to noise generation.

[0049] In order to simulate the geometric characteristics of tire patterns under different pitch types in detail, the pattern model of the target tire can be constructed by the following steps: obtaining the groove depth information and pitch information of the target tire, wherein the pitch information includes information corresponding to multiple types of pitches of the target tire; constructing multiple pattern block solid models based on the groove depth information and the information corresponding to multiple types of pitches, wherein the pattern block solid models are used to reflect the groove depth and shape corresponding to the pitch type; arranging the multiple pattern block solid models based on the pitch arrangement information in the pitch information to obtain a three-dimensional plane model, wherein the pitch arrangement information is used to indicate the arrangement order of multiple types of pitches in the circumferential direction.

[0050] The model construction of related technologies may ignore the depth and shape details of the pattern, resulting in inaccurate estimation of pump noise in simulation calculations. In some embodiments of the present application, 3D modeling software can be used to create a single tread block model based on groove depth information and pitch shape information, ensuring that the model reflects both the groove depth and the specific geometric shape of the pitch. For multiple types of pitch, corresponding tread block solid models are constructed separately to ensure that the model uniqueness of each pitch type matches its role in tire design. According to the pitch arrangement information, the different types of tread block solid models are arranged in a predetermined order in the circumferential direction and finally spliced ​​into a complete 3D planar model that reflects the layout of the entire tread pattern.

[0051] It should be noted that when constructing the model, the pitch types used may include but are not limited to inline pitch, staggered pitch, random pitch, etc., to cover various tire design possibilities.

[0052] In tire design, the order of tread pattern arrangement directly affects the airflow state and noise generation mechanism when the tire contacts the ground. The above steps, by precisely arranging the tread block models, resolve the noise simulation deviation caused by improper model layout and ensure the accuracy of the results.

[0053] Step S204 : determining a scanning curved surface corresponding to the contact patch of the target tire, wherein the scanning curved surface includes curved surfaces corresponding to the leading edge and the trailing edge of the contact patch, respectively.

[0054] In step S204, the contact patch is the mark left by the tire tread on the ground when the tire contacts the ground. The scanned surface is a virtual surface constructed based on the leading and trailing edges of the contact patch and used to extract the overlapping area of ​​the tire tread grooves in the 3D model. The leading and trailing edges are the front and rear boundaries of the tire contact patch, marking the start and end of the tire tread's contact with the ground during rolling.

[0055] In some embodiments of the present application, image recognition technology can be used to process a photograph of the tire contact footprint to automatically extract the contour curves of the leading and trailing edges. For example, the clear boundaries of the footprint are identified through an edge detection algorithm, and then the extracted curves are converted into a format readable by three-dimensional modeling software; the extracted leading and trailing edge contour curves are imported into the three-dimensional modeling software and stretched in a direction perpendicular to the tread to form a leading edge surface and a trailing edge surface. These two parts together constitute the scanning surface. The stretching height should exceed the maximum tread groove depth of the tire to ensure that no information about the pattern part is missed during the scanning process.

[0056] It should be noted that in order to solve the problem that the construction of scanning surfaces may be too time-consuming and reduce the overall process efficiency, a preset template surface method can be used. For common tire sizes and contact patch shapes, a set of standard scanning surface templates can be pre-built. In this way, when designing a new tire, the corresponding template can be directly called and applied to the specific tire model with only minor adjustments. In addition, a parametric surface generation method can also be used, that is, a set of algorithms that automatically generate leading and trailing edge surfaces based on key parameters (such as tire width, contact patch length, etc.) can be designed. In this way, after obtaining the basic properties of the tire, the algorithm can be used to quickly generate customized scanning surfaces.

[0057] Accurately capturing the air flow during tire tread-ground contact is a challenge in tire noise simulation. By constructing a sweep surface that matches the tire's contact patch, this step addresses the challenge of reproducing the dynamic process of air pumping and releasing during rolling in a real tire within the model.

[0058] In order to accurately reflect the contact patch of the tire under a specific load, the scanning surface corresponding to the contact patch of the target tire can be determined in the following manner: specifically, an image of the contact patch of the target tire is acquired, and the outer contour curves of the leading and trailing edges of the contact patch of the target tire are extracted from the contact patch image; the outer contour curves of the leading and trailing edges are stretched in a direction perpendicular to the tread of the target tire to obtain a scanning surface, wherein the stretching height is greater than the maximum transverse groove depth in the pattern model.

[0059] The contact patch image is a visual record of the tire's contact patch area during driving. The outer contour curves are the boundary lines at the front and rear ends of the contact patch, representing the tire's contact edge at ground level. The scan surface is a virtual surface formed by stretching the outer contour curve. This surface is used for scanning within a 3D plane model to extract the volumetric change in the area where the tire tread groove overlaps the surface. The stretch height is the distance the scan surface is stretched perpendicular to the tire tread to ensure coverage of the entire tread groove and avoid missing information during scanning.

[0060] The scanning methods used in related technologies focus solely on the two-dimensional projection of the tire tread, ignoring information in the depth direction. By constructing a three-dimensional scanning surface, this method overcomes the inability of traditional methods to accurately simulate the gas pumping and release in the depth direction of the tire tread grooves, thereby improving the accuracy of noise assessment.

[0061] It should be noted that the stretching height of the scanned surface can also be adaptively adjusted according to the depth information of the tire pattern to ensure that the scanned surface covers all the groove parts of the pattern while avoiding excessive stretching that causes waste of computing resources.

[0062] Step S206 : determining a noise index of the target tire based on the pattern model and the scanned surface, wherein the noise index is used to quantify the gas pumping and releasing capabilities of the pattern grooves during the ground contact process of the target tire.

[0063] In step S206, the scanning surface can be moved along the tire circumference at a fixed step size (e.g., 0.5 mm). Each scan is subjected to a Boolean operation with the groove portion of the tread model to extract the area of ​​the overlapping region. Since the step size of each scan is fixed, the overlapping area is multiplied by the step size to obtain the gas volume change at the corresponding location. Through continuous scanning, a series of gas volume change data is generated, forming a volume change sequence, which is then converted into a noise index.

[0064] In the process of determining the noise index, by dynamically comparing the scanning surface with the tire pattern model, the change in the volume of gas pumped in and released when the pattern groove contacts the ground during the rolling process of the tire can be accurately calculated. Specifically: the starting point of the scanning surface is aligned with the starting position of the pattern model, and starting from the starting position, the scanning surface is advanced along the circumference of the target tire according to the scanning step length; each time the scanning step length is advanced, the area of ​​the first overlapping area between the scanning surface and the pattern groove of the target tire in the pattern model is determined; based on the area of ​​the first overlapping area, the volume of gas pumped in or released at the corresponding scanning position is determined to obtain a first volume change sequence, wherein the first volume change sequence includes the volume of gas pumped in or released corresponding to the entire circumference of the tread of the target tire; and the noise index is determined based on the first volume change sequence.

[0065] The scanning step size refers to the distance the scanning surface advances each time in a 3D model. The choice of this distance directly impacts the accuracy of the acquired data and the efficiency of the calculation. The first overlap area is the area where the scanning surface overlaps with the grooves in the pattern model at a certain point during the advancement process. The first volume change sequence is the sequence of gas volume changes obtained by multiplying the first overlap area determined by each advancement of the scanning surface by the scanning step size.

[0066] In some embodiments of the present application, the starting point of the scanning surface can be positioned at the starting position of the pattern model in the three-dimensional modeling software to ensure that the initial position of the scan is aligned with the model; a loop algorithm is used to advance the scanning surface along the circumference of the tire according to the set scanning step (such as 0.5 mm) in each loop until the scanning surface covers the entire tire pattern model; the overlapping area between the scanning surface at the current scanning position and the pattern groove model is calculated, and the overlapping area is projected to the circumferential direction of the tire to calculate the projected area, that is, the area of ​​the first overlapping area; the area of ​​the first overlapping area of ​​each scanning position is multiplied by the scanning step to obtain the volume of gas pumped in or released at that position; the gas volume change data at all scanning positions are collected and recorded to form a first volume change sequence, which serves as input data for subsequent noise index calculations.

[0067] For example, according to the actual accuracy requirements, the scanning surface is scanned at a fixed step length l of 0.5 mm from the starting position of the tread pattern. Each time the scanning surface overlaps with the groove part model, the Boolean operation function in the 3D modeling software is used to extract the surface area S of the overlapping part. Since the step length is fixed each time, the i-th overlapping surface area S i Multiplying by the fixed step length l, we can get the volume V of the gas pumped (or released) in this part i .

[0068] In order to solve the problem in the related art that it is difficult to distinguish the impact of different pitch types on tire noise, the noise index of the target tire can also be determined in the following way: obtain multiple pitch types of the target tire from the pitch information; for each pitch type, use a scanning surface to scan the pitch once, and determine the second overlapping area of ​​the scanning surface and the pattern groove; determine the volume of gas pumped or released corresponding to the pitch type at the scanning position based on the second overlapping area, and obtain a second volume change, wherein the second volume change is the volume change obtained by scanning each pitch type separately; determine the relative phase of each pitch type in the circumferential direction of the target tire based on the pitch arrangement information in the pitch information; superimpose and sum multiple second volume changes corresponding to multiple pitch types in the time domain according to the relative phase to obtain a third volume change sequence, wherein the third volume change sequence is the volume change sequence corresponding to the entire tread of the target tire; determine the noise index based on the third volume change sequence.

[0069] In some embodiments of the present application, in addition to conventional scanning methods, a highly efficient scanning method can be employed. Since the tread pattern is composed of multiple pitches arranged in a pitch order, the scanning results for individual pitches of the same type should be consistent. Because extracting volumetric results through repeated Boolean operations requires high memory and is time-consuming, each pitch can be scanned only once, and the phases can be superimposed and summed in the time domain. This mathematical calculation method avoids the inefficiency associated with repeated Boolean operations on the model.

[0070] Specifically, each independent pitch type is separated from the pattern model to facilitate individual scanning; for each pitch type, a precise scan is performed using the scanning surface, and the areas of all second overlapping regions with the pattern grooves during the scan are recorded; the area of ​​each second overlapping region is multiplied by the corresponding scanning step length to obtain the volume of gas pumped in or released at a specific scanning position for each pitch type; the pitch arrangement information is used to calculate the relative starting point of each pitch type in the circumferential direction of the tire, and then determine its relative phase relative to the tire circumference; in the time domain, all second volume changes are superimposed and summed according to the relative phase of each pitch type to generate a third volume change sequence, and finally the noise index is determined based on the third volume change sequence.

[0071] In order to solve the problem of difficulty in converting gas flow effects into sound pressure changes in traditional noise assessment, the noise index can be determined in the following way: determine the objective function of the volume change over time based on the target volume change sequence and the driving speed of the target tire, where the target volume change sequence is the volume change sequence corresponding to the entire tread of the target tire; based on the objective function, perform time domain fitting on the leading sound pressure and trailing sound pressure of the target tire respectively to obtain the leading sound pressure fitting results and the trailing sound pressure fitting results, where the leading sound pressure is the sound pressure generated when air is pumped into the target tire, and the trailing sound pressure is the sound pressure generated when the air is released from the target tire; determine the noise index corresponding to the leading sound pressure fitting results and the trailing sound pressure fitting results.

[0072] The target volume change sequence may include a first volume change sequence or a third volume change sequence. The objective function is a function expression that converts the target volume change sequence into a time-varying volume change, taking into account the tire's travel speed. The leading edge sound pressure fitting result represents a model of the sound pressure variation over time, obtained through mathematical fitting, based on the sound pressure variation generated by pumping air into the target tire upon contact. The trailing edge sound pressure fitting result represents a model of the sound pressure variation over time, obtained through mathematical fitting, based on the sound pressure variation generated by releasing air from the target tire upon leaving the ground.

[0073] In some embodiments of the present application, the driving speed of the target tire can be converted into a speed parameter in the time domain, which is used to adjust the timestamp of each data point in the target volume change sequence; using mathematical modeling techniques, the adjusted timestamp is combined with the volume change at the corresponding position to construct an objective function, which describes the change in the gas pumping and release rate of the tire over time during the rolling process; using the Dirichlet function or other suitable mathematical model, the part of the objective function that represents the air pumping into the leading edge and the air releasing at the trailing edge of the tire is fitted to obtain the fitting results of the leading edge sound pressure and the trailing edge sound pressure changing with time; and determining the noise index corresponding to the fitting results of the leading edge sound pressure and the trailing edge sound pressure.

[0074] In the process of determining the noise index, the phase difference between the sound pressures at the front and rear edges of the tire is taken into account. By introducing phase shift and adjustment coefficients, the overall picture of tire noise can be more accurately reflected. Specifically: the trailing edge sound pressure fitting result is phase shifted to obtain the target trailing edge sound pressure fitting result, where the phase shift distance is the crown center imprint length; the adjustment coefficient corresponding to the trailing edge sound pressure fitting result is obtained, where the adjustment coefficient is used to compensate for the difference between the trailing edge sound pressure and the leading edge sound pressure; the leading edge sound pressure fitting result and the target trailing edge sound pressure fitting result are superimposed on the basis of the adjustment coefficient to obtain the noise index.

[0075] The crown-to-center footprint length is the actual length of the contact patch created by the crown (the widest part of the tire) when the tire contacts the ground. There's a spatial difference between the leading and trailing edges of the footprint, known as the crown-to-center footprint length. Therefore, in the time-domain acoustic wave superposition synthesis, it's important to consider the phase difference between the two sets of sound waves. The adjustment factor accounts for the acoustic differences between the leading and trailing edge sound pressures due to the different gas pumping and release mechanisms, helping to more realistically reflect tire noise characteristics. The target trailing edge sound pressure fitting result is the tire trailing edge sound pressure fitting result after phase shifting to match its phase difference relative to the leading edge sound pressure.

[0076] For example, based on the preset tire speed v, the volume change-time objective function V can be established. i (t), using the Dirichlet function as the vocalization model, fitting the time domain sound wave formula:

[0077]

[0078] Among them, P 前沿 (t) is the fitting result of the front sound pressure; V i (t) is the objective function; δ(t-t_i) is the Dirichlet function, which is used to represent the tire tread groove at a specific time point t i Transient event that starts pumping gas.

[0079] According to experiments and simulations, the sound of air pumped into the leading edge is slightly louder than that of air released at the trailing edge. Therefore, a coefficient γ can be given to the trailing edge. At the same time, the trailing edge needs to be phase shifted by the length of the crown mark. The final noise index is:

[0080] P pumping (t) = P 前沿 (t)+γ*P 后沿 (t) Formula 2

[0081] Among them, P pumping (t) is the noise index; γ is the adjustment coefficient. Since experiments and simulations show that the sound pressure generated by the front edge pumping air is slightly greater than the sound pressure generated by the rear edge releasing air, γ<1 is used to appropriately reduce the weight of the rear edge sound pressure; P 后沿 (t) is the fitting result of the trailing edge sound pressure.

[0082] It should be noted that the tire is actually a ring unit, and the tread is considered as a plane during scanning. In the actual sounding process, some elements at the beginning and end of the scan should sound at the same time. However, if you simply scan from the beginning to the end, information will be lost. To solve this problem, it is necessary to supplement the beginning of the complete circle of the flat tread model with a part of the end model, and similarly, supplement the end of the beginning model with a part of the end model, to ensure that the P obtained by scanning is accurate. 前沿 (t) Completely encompass the entire tread sound. Similarly, for the efficient scanning method, a preset number (e.g., 2-3) of ending pitches are added to the starting end in accordance with the pitch order. Similarly, a preset number (e.g., 2-3) of starting pitches are added to the ending end, and the superposition is followed by a truncation operation.

[0083] Step S208: Determine the tire noise corresponding to the noise index.

[0084] In the above-mentioned step S208, the noise index may include a noise time domain signal, which is used to describe the time domain characteristics of the pump noise of the target tire during the ground contact process. On this basis, the tire noise corresponding to the noise index can be determined through the following steps: intercepting the noise time domain signal based on the circumference of the target tire and the scanning step size corresponding to the scanning surface to obtain a first noise time domain signal corresponding to the entire tread of the target tire; converting the first noise time domain signal into a frequency domain signal, and determining the tire noise based on the frequency domain signal.

[0085] The noise time-domain signal reflects the temporal evolution of pump noise during tire contact, encompassing both the instantaneous intensity and temporal evolution of the sound. The first noise time-domain signal is a truncated version of the noise time-domain signal based on the tire circumference and scan step size. This signal specifically captures the time-domain representation of tread noise across the entire circumference of the target tire. The frequency-domain signal is generated by applying a fast Fourier transform (FFT) to the first noise time-domain signal, describing the frequency components and intensity distribution of tire noise.

[0086] Specifically, due to the addition of some models in the scan, the data needs to be intercepted. pumping The number of signal points in (t) should be C / l, that is, circumference / step length. The length data intercepted in the time domain signal is the pump noise time domain signal of a complete circle of the tire; pumping (t) function is fast Fourier transformed to convert the time domain function into the frequency domain function P pumping (ω). It should be noted that a harmonic result function can also be obtained during the conversion process. To facilitate subsequent analysis, the conversion process can also perform dB conversion, signal filtering, A-weighting, windowing, interpolation, smoothing, and other processing. Based on the frequency domain function, its RMS value (arithmetic mean root) is calculated. For example, the RMS value within 0-5000 Hz is calculated as the result representing the tire pattern pump noise (i.e., tire noise). In some embodiments of the present application, the time domain sound wave, harmonic results, and frequency domain result images can ultimately be output, as well as the RMS value from 0-5000 Hz as the noise result.

[0087] In some embodiments of the present application, the following steps may also be performed: determining a plurality of pattern ribs formed by dividing the pattern longitudinal grooves in the transverse direction of the pattern of the target tire in the pattern model; using a scanning surface to scan the plurality of pattern ribs separately to obtain a scanning matrix, wherein the rows of the scanning matrix represent the pattern ribs and the columns represent the scanning points, and the scanning matrix is ​​used to store the volume of gas pumped in or released by the plurality of pattern ribs at different scanning positions; determining that the plurality of pattern ribs correspond to the second noise time domain signals respectively according to the scanning matrix, and superimposing and synthesizing all the second noise time domain signals to obtain a first total noise signal; and optimizing the position of the pattern ribs of the target tire based on the second noise time domain signal and the first total noise signal.

[0088] Ribs are the longitudinally arranged blocks within the tire tread pattern, divided by the longitudinal grooves of the tire tread. Each section is independent in the transverse direction and contributes independently to tire noise. The scan matrix is ​​a two-dimensional array that stores information about the volume of gas pumped into or released from the tire ribs at different scanning positions. The rows of the matrix correspond to different ribs, while the columns correspond to different points in the scanning process. The second noise time-domain signal corresponds to the noise time-domain signal of each rib, reflecting the pumping noise characteristics generated by different ribs during tire rolling. The first total noise signal is the signal synthesized by superimposing all the second noise time-domain signals and represents the overall pumping noise performance of the tire.

[0089] Specifically, in the tire pattern model, the tread is laterally divided into multiple pattern rib areas according to the position of the pattern longitudinal grooves, and each area independently participates in the subsequent scanning process; each pattern rib is scanned separately using a scanning surface, and the volume data of gas pumped in or released by the pattern rib at each scanning position is recorded; the collected volume change data are organized into a scanning matrix in the order of pattern ribs and scanning positions; based on the gas volume change data in the scanning matrix, a second noise time domain signal corresponding to each pattern rib is constructed to reflect the pump noise characteristics of each area; taking into account the relative phase and acoustic coupling effect of each pattern rib, all second noise time domain signals are superimposed and synthesized to generate a first total noise signal to comprehensively reflect the overall pump noise level of the tire; and the position of the pattern ribs of the target tire is optimized based on the first total noise signal.

[0090] In order to solve the problem that it is difficult to effectively reduce noise by adjusting the position of pattern ribs in tire design, the position of the pattern ribs of the target tire can be optimized in the following way: determine the areas of coherent superposition and coherent cancellation from the first total noise signal; determine the misalignment ranges corresponding to multiple pattern ribs, wherein the misalignment in the misalignment range is used to phase adjust the pattern ribs, and the goal of the phase adjustment is to maximize the area of ​​coherent cancellation; iteratively adjust each pattern rib in turn according to the misalignment range to obtain a second total noise signal corresponding to each iteration, and determine the target misalignment corresponding to multiple pattern ribs when the second total noise signal meets the preset conditions; and optimize the position of the pattern ribs according to the target misalignment.

[0091] Coherent superposition refers to the phenomenon that the sound waves of different tire ribs reinforce each other in certain areas due to the same phase, resulting in an increase in the local noise level. Coherent cancellation refers to the phenomenon that the sound waves of the tire ribs cancel each other in certain areas due to the opposite phase, which helps to reduce the noise level. The offset is the offset distance of the tire ribs in the circumferential direction. The second total noise signal is the overall tire noise signal sequence calculated during the iterative adjustment of the rib position, which is used to evaluate the change in noise level after each iteration. The preset condition is the standard or threshold used to terminate the iterative optimization process, such as reaching the minimum noise level, the number of iterations reaching the upper limit, or the difference between the results of two adjacent iterations being less than a certain threshold. The target offset is determined through the iterative optimization process and is the amount of rib offset that can maximize coherent cancellation and minimize the overall tire noise.

[0092] Specifically, a spectral analysis is performed on the first total noise signal to identify frequency regions where the noise intensity increases abnormally (e.g., meets a preset threshold), i.e., regions of coherent superposition; by comparing the phases of the second noise time domain signals of different pattern ribs, the frequency intervals where coherent cancellation occurs, i.e., regions of coherent cancellation are determined; according to tire design specifications and / or design requirements, the maximum and minimum allowable misalignment amounts of each pattern rib are determined; an initial misalignment amount is assigned to each pattern rib, for example, zero misalignment or an estimated value based on historical data is selected as the starting point for iterative optimization; an iterative optimization algorithm such as a genetic algorithm, a particle swarm optimization algorithm, or a gradient descent method is used to successively adjust the misalignment amount of each pattern rib until the second total noise signal meets the preset conditions, and the misalignment amount configuration at this time is the target misalignment amount.

[0093] In some embodiments of the present application, the range of misalignment amounts corresponding to multiple pattern ribs can be determined by the following steps: determining the type of pattern of the target tire; when the type indicates that the pattern is a symmetrical pattern, determining a first misalignment amount corresponding to the pattern ribs that are symmetrical based on the center line, wherein the number of the first misalignment amounts is the same as the number of pattern ribs that are symmetrical based on the center line; when the type indicates that the pattern is an asymmetrical pattern, determining a second misalignment amount corresponding to multiple pattern ribs.

[0094] To facilitate understanding of the above-mentioned misalignment optimization process, it is explained below with reference to some specific embodiments.

[0095] The pattern is divided into multiple pattern ribs (i.e., Ribs) in the transverse direction by the longitudinal grooves. Each rib has pattern blocks and transverse grooves arranged in pitch order. When scanning the pattern, the scanning results of each pattern rib can be stored separately in the jth row of the matrix to form the matrix V ji ,j=1,2,…,Rib num .

[0096] Therefore, if each Rib is considered a separate sound source, the resulting pattern noise is the sum of all Ribs. Based on the theory of sound wave superposition, phase differences during the superposition of time-domain sound waves can lead to coherent cancellation or coherent superposition, reducing or increasing the total sound pressure. To optimize the pattern noise level, the phase of each Rib needs to be shifted to maximize coherent cancellation during superposition.

[0097] For tire tread patterns, the phase change of each Rib in the time domain is equivalent to the circumferential displacement of the Ribs relative to each other. It's important to note that for conventional symmetrical patterns, the Ribs' displacement can be consistent across the tread's centerline, while asymmetrical patterns can be freely displaced. Furthermore, for aesthetic and other mechanical considerations, the displacement should be less than the minimum pitch length.

[0098] Through the above steps S202 to S208, a three-dimensional plane model of only the tire tread pattern is constructed. By constructing the tire pattern model and combining it with the scanned surface of its contact patch, the gas pumping and release capabilities during the tire contact process are quantified, and tire noise is predicted. This achieves the purpose of accurately predicting the noise level of the tire under different road conditions, thereby achieving the technical effect of improving prediction accuracy and simplifying the complexity of traditional noise testing, and thus solving the technical problem that the tire pattern noise simulation prediction method adopted by related technologies cannot effectively balance prediction accuracy and complexity.

[0099] Figure 3 FIG. 1 is a schematic diagram of the overall flow of a method for determining tire noise according to an embodiment of the present application. In some embodiments of the present application, tire noise can be determined by the following steps:

[0100] Step S302: Pitch arrangement.

[0101] Based on the tire tread design drawings or CAD models, specific pitch information is extracted, including pitch length, total number of pitches, number of pitch types, and the number of pitches of each type. This pitch information is used to construct a three-dimensional model of the tire pattern and determine the arrangement order of tread blocks and grooves.

[0102] Step S304: constructing a pattern model.

[0103] Based on the pitch arrangement information obtained in S302, a tread pattern model is created using 3D modeling software, which includes 3D solid models of the tread blocks, transverse grooves, and longitudinal grooves, with particular emphasis on accurate reflection of the groove depth information.

[0104] Step S306: Scan the pattern.

[0105] Based on the tire contact patch information, a scanning surface is generated. Then, along the tire circumference, the groove volume change data of each pattern rib at different positions is extracted from the pattern model with a fixed step size (e.g., 0.5 mm) and recorded in the scanning matrix.

[0106] Step S308: Constructing a volume-time function.

[0107] The volume change data in the scanning matrix is ​​converted into a time-related function expression, namely the volume change-time function. Taking into account the tire driving speed, a direct relationship between volume change and time is established. The abstract geometric and physical information is converted into a mathematical model to facilitate further signal processing and noise evaluation, ensuring the accuracy and operability of noise simulation.

[0108] Step S310: Determine the time domain sound wave.

[0109] Using the volume-time function obtained in the previous stage, combined with the pump noise generation mechanism and acoustic models (such as the Dirichlet function), the time-domain sound pressure signal of the tire during rolling is calculated, reflecting the transient characteristics of the noise. This time-domain acoustic wave simulation can intuitively demonstrate the changes in tire noise at different time points, providing a foundation for frequency-domain noise analysis and optimization.

[0110] Step S312: signal processing.

[0111] The time-domain sound pressure signal undergoes a series of processing, including but not limited to dB conversion, signal filtering, A-weighting, windowing, interpolation, and smoothing, to improve the signal-to-noise ratio and frequency resolution, making it more consistent with human auditory perception. Unprocessed noise signals may contain a large amount of irrelevant noise and pseudo-spectral information. Signal processing can purify the signal and adjust its form to more accurately reflect the true spectral characteristics of tire pump noise.

[0112] Step S314: performing misalignment optimization.

[0113] By phase-adjusting the second noise time-domain signal of each rib, i.e., varying the relative position of the ribs along the tire's circumference, an iterative algorithm is employed to find the optimal offset configuration to maximize coherent cancellation, thereby reducing the tire's overall noise level. The noise emitted by different ribs may reinforce each other at certain frequencies due to phase differences. Stagger optimization, by adjusting the relative positions of the ribs, cancels out these noises, ultimately reducing overall noise.

[0114] Step S316: Output the noise result.

[0115] The processed noise signal is converted into visual results, including time domain sound waves, harmonic results and frequency domain result images. At the same time, specific noise indicators (such as the RMS value of 0-5000Hz) are output to provide an intuitive tire pump noise assessment report.

[0116] Figure 4 FIG. 1 is a schematic diagram of a tire pattern model according to a method for determining tire noise according to an embodiment of the present application. Figure 4 As shown in the figure, the tire tread is divided into multiple independent areas, namely pattern ribs (Rib). Inside the pattern ribs, each pattern rib consists of a series of pattern blocks and pattern grooves, which are arranged according to a specific pitch and directly affect the generation of tire pumping noise. It should be noted that although Figure 4 A partial cross-sectional view of the tire is shown, but the actual model is built based on a three-dimensional flat model of the tire tread. This means that the model does not include the complex details of the tire's internal structure, but instead focuses on the geometric structure of the tread pattern.

[0117] To facilitate understanding of the above tire noise determination method, a specific embodiment is provided below for explanation.

[0118] Take a 215 / 60R16 tire as an example, its pattern is as follows Figure 5 As shown in , it consists of 5 pitches and a total of 5 pattern ribs, named Rib1 to Rib5 from the inside to the outside of the tire. The front surface of the imprint steps in the scanning direction, and each step intersects with the pattern groove. The intersection area on each pattern rib is extracted and multiplied by the step length and stored in the matrix to obtain a matrix of size (number of pattern ribs, number of step points). The matrix is ​​second-order differentiated according to time to obtain the actual amplitude. Signal processing is performed on the matrix, considering the phase difference between the front and rear edges of the imprint, the sound pressure coefficient, the front and rear edge sound emission coefficient, etc., to obtain the time domain sound pressure signal on each pattern rib, as shown in Figure 6 As shown (Time Domain is the time domain, the horizontal axis represents time, and the vertical axis represents the time domain signal), and then the matrix is ​​fast Fourier transformed to obtain its harmonic results, as shown Figure 7 As shown in the figure (Harmonics Domain, the horizontal axis represents harmonics and the vertical axis represents amplitude), if the harmonic result is converted to the frequency domain, we get Figure 8 As shown (Frequency Domain is the frequency domain, the horizontal axis represents the frequency, and the vertical axis represents the amplitude).

[0119] According to the theory of misalignment optimization, the time domain signals of each pattern rib in the matrix are shifted, and the RMS value is calculated after each shift, and the minimum result is extracted. In this embodiment, the maximum misalignment of each pattern rib is set to 20mm in both directions, and the misalignment value is 0.5mm each time, and the phase information between different pattern ribs is adjusted by shifting the pattern rib position to minimize the total sound wave value after superposition. The misalignment optimization result is shown as follows: Figure 9 As shown (OP (Optimized Position) represents the optimized position, OR (Original Position) represents the original position), the RMS noise value is reduced by 0.84dB(A), Rib1 does not move, Rib2 is displaced 15mm in the opposite direction of rotation, Rib3 does not move, and Rib4 and Rib5 are displaced the same distance in the opposite direction of Rib1 and Rib2.

[0120] Figure 10 is a structural diagram of a tire noise determination device according to an embodiment of the present application, such as Figure 10 As shown, the device includes:

[0121] A construction module 1002 is configured to construct a tread model of the target tire based on the groove depth information and pitch information of the target tire, wherein the pattern model includes a three-dimensional plane model corresponding to the tread pattern of the target tire, and the pitch information is used to reflect the regularity of the arrangement of the tread blocks on the entire circumference of the tread;

[0122] a determination module 1004 for determining a scanning curved surface corresponding to a contact patch of a target tire, wherein the scanning curved surface includes curved surfaces corresponding to a leading edge and a trailing edge of the contact patch;

[0123] a conversion module 1006 for determining a noise index of a target tire based on the tread model and the scanned surface, wherein the noise index is used to quantify the gas pumping and releasing capabilities of the tread grooves during the contact process of the target tire;

[0124] The execution module 1008 is configured to determine the tire noise corresponding to the noise index.

[0125] It should be noted that Figure 10 The tire noise determination device shown is used to perform Figure 2 The tire noise determination method shown is therefore Figure 2 The explanations in the determination method of tire noise also apply to Figure 10 The tire noise determination device shown is not described in detail here.

[0126] An embodiment of the present application further provides an electronic device comprising a memory and a processor, wherein the memory is used to store program instructions; the processor is connected to the memory and is used to execute the steps of the tire noise determination method in each embodiment of the present application.

[0127] For example, the processor performs the following functions by executing program instructions stored in the memory: constructing a pattern model of the target tire based on the tread groove depth information and pitch information of the target tire, wherein the pattern model includes a three-dimensional plane model corresponding to the tread pattern of the target tire, and the pitch information is at least used to reflect the regularity of the arrangement of the pattern blocks on the entire tread; determining a scanning surface corresponding to the contact footprint of the target tire, wherein the scanning surface includes surfaces corresponding to the leading edge and the trailing edge of the contact footprint, respectively; determining a noise index of the target tire based on the pattern model and the scanning surface, wherein the noise index is used to quantify the gas pumping and release capacity of the pattern groove during the contact process of the target tire; and determining the tire noise corresponding to the noise index.

[0128] An embodiment of the present application further provides a non-volatile storage medium, which includes a stored computer program. The device containing the non-volatile storage medium executes the steps of the tire noise determination method in each embodiment of the present application by running the computer program.

[0129] An embodiment of the present application further provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the tire noise determination method in each embodiment of the present application.

[0130] The embodiments of the present application further provide a computer program, which, when executed by a processor, implements the steps of the method for determining tire noise in various embodiments of the present application.

[0131] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0132] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0133] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0134] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0135] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0136] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0137] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining tire noise, characterized in that: include: Constructing a tread model of the target tire based on groove depth information and pitch information of the target tire, wherein the pattern model includes a three-dimensional plane model corresponding to the tread pattern of the target tire, and the pitch information is used to at least reflect the regularity of the arrangement of pattern blocks on the entire tread; Determining a scanning curved surface corresponding to a contact patch of the target tire, wherein the scanning curved surface includes curved surfaces corresponding to a leading edge and a trailing edge of the contact patch respectively; determining a noise index of the target tire based on the pattern model and the scanned curved surface, wherein the noise index is used to quantify gas pumping and releasing capabilities of the pattern grooves of the target tire during ground contact; A tire noise corresponding to the noise index is determined.

2. The method according to claim 1, characterized in that Constructing a tread model of a target tire based on groove depth information and pitch information of the target tire, including: Acquiring groove depth information and pitch information of the target tire, wherein the pitch information includes information corresponding to multiple types of pitches of the target tire; Constructing a plurality of pattern block solid models based on the groove depth information and the information corresponding to the plurality of types of pitches, wherein the pattern block solid models are used to reflect the groove depth and shape corresponding to the pitch type; The plurality of pattern block solid models are arranged according to pitch arrangement information in the pitch information to obtain the three-dimensional plane model, wherein the pitch arrangement information is used to indicate an arrangement order of the plurality of types of pitches in a circumferential direction.

3. The method according to claim 1, characterized in that Determining a scan surface corresponding to a contact patch of the target tire includes: Acquiring a contact patch image of the target tire, and extracting outer contour curves of a leading edge and a trailing edge of the contact patch of the target tire from the contact patch image; The outer contour curves of the leading edge and the trailing edge are stretched along a direction perpendicular to the tread of the target tire to obtain the scanning curved surface, wherein the stretching height is greater than the maximum transverse groove depth in the pattern model.

4. The method according to claim 1, wherein Determining the noise index of the target tire according to the pattern model and the scanned curved surface includes: Aligning the starting point of the scanning curved surface with the starting position of the pattern model, and starting from the starting position, advancing the scanning curved surface along the circumference of the target tire according to the scanning step length; Whenever the scanning step is advanced, determining the area of ​​a first overlapping region between the scanning curved surface and the tread groove of the target tire in the tread model; Determining, based on the area of ​​the first overlapping region, a volume of gas pumped in or released at a corresponding scanning position, to obtain a first volume change sequence, wherein the first volume change sequence includes the volume of gas pumped in or released corresponding to the entire circumference of the tread of the target tire; The noise index is determined according to the first volume change sequence.

5. The method according to claim 1, wherein Determining the noise index of the target tire according to the pattern model and the scanned curved surface includes: Acquire multiple pitch types of the target tire from the pitch information; For each pitch type, the scanning curved surface is used to scan the pitch once, and the area of ​​a second overlapping region between the scanning curved surface and the pattern groove is determined; based on the area of ​​the second overlapping region, the volume of gas pumped or released corresponding to the pitch type at the scanning position is determined to obtain a second volume change, wherein the second volume change is the volume change obtained by scanning each pitch type separately; determining a relative phase of each pitch type in the circumferential direction of the target tire based on pitch arrangement information in the pitch information; superimposing and summing a plurality of second volume changes corresponding to the plurality of pitch types in the time domain according to the relative phases to obtain a third volume change sequence, wherein the third volume change sequence is a volume change sequence corresponding to the entire circumference of the tread of the target tire; The noise index is determined according to the third volume change sequence.

6. The method according to claim 4 or 5, characterized in that The noise index is determined by the following method: Determining an objective function of volume change over time based on a target volume change sequence and a running speed of the target tire, wherein the target volume change sequence is a volume change sequence corresponding to the entire circumference of the tread of the target tire; Based on the objective function, time-domain fitting is performed on the leading edge sound pressure and the trailing edge sound pressure of the target tire to obtain leading edge sound pressure fitting results and trailing edge sound pressure fitting results, wherein the leading edge sound pressure is the sound pressure generated when air is pumped into the target tire, and the trailing edge sound pressure is the sound pressure generated when air is released from the target tire; The noise index corresponding to the leading edge sound pressure fitting result and the trailing edge sound pressure fitting result is determined.

7. The method according to claim 6, characterized in that Determining the noise index corresponding to the leading edge sound pressure fitting result and the trailing edge sound pressure fitting result includes: Performing a phase shift on the trailing edge sound pressure fitting result to obtain a target trailing edge sound pressure fitting result, wherein the distance of the phase shift is the length of the crown mid-imprint; Obtaining an adjustment coefficient corresponding to the trailing edge sound pressure fitting result, wherein the adjustment coefficient is used to compensate for the difference between the trailing edge sound pressure and the leading edge sound pressure; The leading edge sound pressure fitting result and the target trailing edge sound pressure fitting result are superimposed on the basis of the adjustment coefficient to obtain the noise index.

8. The method according to claim 1, characterized in that The noise index includes a noise time domain signal, wherein the noise time domain signal is used to describe the time domain characteristics of the pump noise of the target tire during the grounding process; Determining the tire noise corresponding to the noise index includes: intercepting the noise time domain signal according to the circumference of the target tire and the scanning step length corresponding to the scanning curved surface to obtain a first noise time domain signal corresponding to the entire tread of the target tire; The first noise time domain signal is converted into a frequency domain signal, and the tire noise is determined according to the frequency domain signal.

9. The method according to claim 1, characterized in that The method further comprises: Determining a plurality of pattern ribs formed by dividing the pattern longitudinal grooves in the transverse direction of the pattern of the target tire in the pattern model; Scanning the plurality of patterned ribs respectively using the scanning curved surface to obtain a scanning matrix, wherein rows of the scanning matrix represent patterned ribs and columns represent scanning points, and the scanning matrix is ​​used to store the volumes of gas pumped into or released from the plurality of patterned ribs at different scanning positions; Determining, based on the scanning matrix, that the plurality of patterned ribs respectively correspond to second noise time domain signals, and superimposing and synthesizing all the second noise time domain signals to obtain a first total noise signal; The position of the tread rib of the target tire is optimized according to the second noise time-domain signal and the first total noise signal.

10. The method according to claim 9, characterized in that Optimizing the position of the tread rib of the target tire according to the second noise time-domain signal and the first total noise signal, comprising: determining regions of coherent addition and coherent cancellation from the first total noise signal; Determining a range of offset amounts corresponding to each of the plurality of pattern ribs, wherein the offset amounts within the range of offset amounts are used to perform phase adjustment on the pattern ribs, wherein a goal of the phase adjustment is to maximize the area of ​​coherent cancellation; Iteratively adjusting each of the patterned ribs in sequence according to the misalignment range to obtain a second total noise signal corresponding to each iteration, and determining target misalignments corresponding to each of the plurality of patterned ribs if the second total noise signal satisfies a preset condition; The position of the pattern rib is optimized according to the target offset amount.

11. The method according to claim 9, characterized in that Determining the offset ranges corresponding to the plurality of pattern ribs respectively includes: Determining the type of the tread pattern of the target tire; When the type indicates that the pattern is a symmetrical pattern, determining a first offset amount corresponding to pattern ribs that are symmetrical based on a center line, wherein the number of the first offset amounts is the same as the number of the pattern ribs that are symmetrical based on the center line; In a case where the type indicates that the pattern is an asymmetric pattern, a second offset amount corresponding to the plurality of pattern ribs is determined.

12. A device for determining tire noise, characterized in that: include: a construction module, configured to construct a pattern model of a target tire based on groove depth information and pitch information of the target tire, wherein the pattern model includes a three-dimensional plane model corresponding to the tread pattern of the target tire, and the pitch information is used to reflect the regularity of pattern block arrangement on the entire tread; a determination module, configured to determine a scanning curved surface corresponding to a contact patch of the target tire, wherein the scanning curved surface includes curved surfaces corresponding to a leading edge and a trailing edge of the contact patch, respectively; a conversion module, configured to determine a noise index of the target tire based on the pattern model and the scanned curved surface, wherein the noise index is used to quantify gas pumping and releasing capabilities of the pattern grooves of the target tire during ground contact; The execution module is configured to determine the tire noise corresponding to the noise index.

13. An electronic device, characterized in that: include: A memory and a processor, wherein the memory is used to store program instructions; the processor is connected to the memory and is used to execute the tire noise determination method according to any one of claims 1 to 11.

14. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the tire noise determination method according to any one of claims 1 to 11 by running the computer program.

15. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the tire noise determination method according to any one of claims 1 to 11 is implemented.

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