Coupling design method and equipment for nozzle needle valve cone angle and seat surface stress

Abstract

The application is suitable for the technical field of computer-aided fuel nozzle design, and particularly relates to a coupling design method and equipment for a fuel nozzle needle valve cone angle and a seat surface stress, comprising: obtaining a design variable vector and a target performance vector; generating a geometric model based on the design variable vector; performing thermal analysis and thermal-mechanical coupling analysis on the geometric model to obtain an analysis result; calculating a performance index of the geometric model based on the analysis result; judging whether a convergence condition is met according to the performance index and the target performance vector, and if the convergence condition is met, determining the geometric model as a final design model; if the convergence condition is not met, updating the design variable vector based on the performance index and the target performance vector; and iterating the above process until the convergence condition is met. The method can improve the sealing performance of the fuel nozzle and the engineering applicability of the design result.

Description

Technical Field

[0001] This application belongs to the field of computer-aided fuel injector design technology, and in particular relates to a coupling design method and device for fuel injector needle valve cone angle and seat surface stress. Background Technology

[0002] As diesel and gasoline direct injection engines develop towards higher pressure, higher frequency, and more precise injection, the fuel injector, as a key actuator in the fuel system, faces stringent challenges in terms of reliability and injection consistency. The cone angle of the needle valve directly determines the contact form between the needle valve and the valve seat, the position of the sealing line, and the opening characteristics, while the seat surface stress relates to sealing reliability, wear evolution, and fatigue life. Under high injection pressure and frequent opening and closing conditions, changes in the cone angle significantly affect the seat surface contact stress distribution and stress concentration, which in turn affects the needle valve's motion stability and sealing performance, exhibiting a clear coupling relationship.

[0003] In existing technologies, during the actual operation of fuel injectors, the needle valve and valve seat are not in an ideal, constant geometric and stress state, but rather operate under the combined effects of high temperature, high pressure, and multiple physical fields. However, traditional design approaches determine the structure based on the geometric relationships at room temperature or in the initial assembly state (cold state). During fuel injector operation (hot state), the needle valve and valve seat experience a significant temperature rise. Since they are made of different materials, their thermal expansion behaviors are inconsistent. This difference causes the contact relationship, which was designed as an ideal fit in the cold state, to change under high temperature conditions. This results in a shift in the position, extent, and load distribution of the contact area, leading to significant uneven stress on the sealing interface. Some areas bear excessive loads, while other areas may experience insufficient contact or even lose effective fit.

[0004] In summary, during the design of the fuel injector needle valve and valve seat, there is a problem that the traditional design is based on cold-state geometry, which leads to a distortion of the contact stress distribution between the needle valve and valve seat under hot conditions, thus causing local sealing failure. Summary of the Invention

[0005] This application provides a coupling design method and device for the cone angle and seat surface stress of a fuel injector needle valve. This method can solve the problem in the related art where, in the process of designing fuel injector needle valves and valve seats, the traditional design is based on cold-state geometry, which leads to distortion of the contact stress distribution between the needle valve and valve seat in the hot state, thus causing local sealing failure.

[0006] In a first aspect, embodiments of this application provide a coupling design method for the cone angle of a fuel injector needle valve and the stress on the seat surface, including:

[0007] Acquisition Steps: Acquire the design variable vector and the target performance vector; wherein, the design variable vector includes the needle valve cone angle, seat width, micro-arc radius, Fourier coefficient, and axial pre-compression amount, the Fourier coefficient is used to generate a non-axisymmetric small geometric correction amount in the circumferential direction of the needle valve, the axial pre-compression amount is used to adjust the axial relative position of the needle valve and the valve seat, and the target performance vector includes the target contact pressure non-uniformity between the needle valve and the valve seat, the target maximum contact pressure, the target contact continuity, the target leakage rate, and the target fatigue safety factor;

[0008] Model generation steps: Generate a geometric model based on the design variable vector;

[0009] Finite element analysis steps: Perform thermal analysis and thermo-mechanical coupling analysis on the geometric model to obtain analysis results; wherein, the analysis results include displacement field, stress field, and contact pressure field;

[0010] Performance index calculation steps: Based on the analysis results, calculate the performance index of the geometric model; wherein, the performance index includes simulated contact pressure non-uniformity, simulated maximum contact pressure, simulated contact continuity, simulated leakage rate, and simulated fatigue safety factor;

[0011] Convergence determination step: Based on the performance index and the target performance vector, determine whether the convergence condition is met. If the convergence condition is met, determine the geometric model as the final design model. The convergence condition includes that the absolute value of the difference between the performance index and the target performance vector is less than or equal to the performance threshold.

[0012] Design variable vector update steps: If the convergence condition is not met, update the design variable vector based on the performance index and the target performance vector;

[0013] The process includes iterative model generation, finite element analysis, performance index calculation, convergence judgment, and design variable vector update, until the convergence condition is met.

[0014] The technical solutions described in this application embodiment have at least the following technical effects:

[0015] The coupling design method for the needle valve cone angle and seat surface stress of the fuel injector provided in this application first obtains the design variable vector (needle valve cone angle, seat surface width, micro-arc radius, Fourier coefficient, axial pre-compression) and the target performance vector (target contact pressure non-uniformity between the needle valve and the valve seat, target maximum contact pressure, target contact continuity, target leakage rate, and target fatigue safety factor). Then, based on the design variable vector, a geometric model is generated. Thermal analysis and thermo-mechanical coupling analysis are then performed on the geometric model to obtain the analysis results (displacement field, stress field, contact pressure field). Based on the analysis results, the performance indicators of the geometric model (simulated contact pressure non-uniformity, simulated maximum contact pressure, simulated contact continuity, simulated leakage rate, and simulated fatigue safety factor) are calculated. Next, based on the performance indicators and the target performance vector, it is determined whether the convergence condition is met. If the convergence condition is met, the geometric model is determined as the final design model; if the convergence condition is not met, the design variable vector is updated based on the performance indicators and the target performance vector. This process is iterated until the convergence condition is met. This method, by introducing thermal effects and thermo-mechanical coupling during geometric modeling and analysis, allows design evaluation to move beyond assembly or room temperature conditions. It directly reflects the actual deformation and stress characteristics of the needle valve and valve seat under real-world operating conditions, significantly improving the accuracy of predicting contact state changes. This makes the contact pressure distribution, deformation coordination, and local stress levels closer to the actual operating state, fundamentally enhancing the engineering applicability of the design results. Through an iterative update mechanism, the method continuously adjusts design variables based on performance deviations. Iterative optimization gradually weakens the influence of adverse factors, making the contact load distribution more reasonable and reducing the probability of local overload and contact interruption, thereby improving sealing performance.

[0016] In a second aspect, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in any of the embodiments of the first aspect.

[0017] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1This is a flowchart illustrating the coupling design method of the fuel injector needle valve cone angle and seat surface stress provided in one embodiment of this application;

[0020] Figure 2 This is an example diagram showing the coefficient of thermal expansion, thermal conductivity, and specific heat capacity in the coupled design method of injector needle valve cone angle and seat surface stress provided in the embodiments of this application.

[0021] Figure 3 This is an example value diagram of the elastic modulus in the coupling design method of injector needle valve cone angle and seat surface stress provided in the embodiments of this application;

[0022] Figure 4 This is an example value diagram of yield strength in the coupled design method of injector needle valve cone angle and seat surface stress provided in the embodiments of this application;

[0023] Figure 5 This is an example value diagram of the hardening modulus in the coupling design method of injector needle valve cone angle and seat surface stress provided in the embodiments of this application;

[0024] Figure 6 This is an example value diagram of the fatigue limit in the coupled design method of injector needle valve cone angle and seat surface stress provided in the embodiments of this application. Detailed Implementation

[0025] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0026] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0027] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0028] In related technologies, during the actual operation of fuel injectors, the needle valve and valve seat are not in an ideal, constant geometric and stress state, but rather operate under the combined effects of high temperature, high pressure, and multiple physical fields. However, traditional design approaches determine the structure based on the geometric relationships at room temperature or in the initial assembly state. This assumption ignores the significant changes in material state and structural morphology during operation, leading to a series of engineering problems such as local seal failure, abnormal wear, increased leakage risk, and insufficient lifespan.

[0029] First, during engine operation, the needle valve and valve seat experience a significant temperature rise. Since they are made of different materials, their thermal expansion behaviors are not consistent. This difference causes the contact relationship, which was designed for an ideal fit under cold conditions, to change under high-temperature conditions, resulting in shifts in the position, extent, and load distribution of the contact area. Obvious uneven stress occurs at the sealing interface, with some areas bearing excessive loads while other areas may experience insufficient contact or even lose effective fit.

[0030] Secondly, due to changes in contact conditions under heat, the sealing capability between the needle valve and the valve seat is uncertain. In some areas, excessively high local pressure can easily cause abnormal wear, plastic deformation, or premature damage to the material surface; while in areas with insufficient pressure or interrupted contact, micro-leakage channels may form, leading to decreased fuel sealing performance, poor injection consistency, and even affecting emissions and combustion stability.

[0031] Furthermore, distortions in the distribution of contact loads can have a profound impact on the service life of components. Areas subjected to repeated high stress are more prone to fatigue damage under long-term cyclic conditions, thereby reducing the reliability and durability of the entire fuel injector system. These types of failures are insidious and difficult to detect in their early stages through conventional design verification methods, but they accumulate gradually during actual use and eventually become apparent.

[0032] To address the aforementioned issues, this application provides a coupled design method and apparatus for the needle valve cone angle and seat surface stress of a fuel injector. The method first obtains a design variable vector (needle valve cone angle, seat surface width, micro-arc radius, Fourier coefficient, axial pre-compression) and a target performance vector (target contact pressure non-uniformity between the needle valve and valve seat, target maximum contact pressure, target contact continuity, target leakage rate, and target fatigue safety factor). Then, based on the design variable vector, a geometric model is generated. Thermal and thermo-mechanical coupling analyses are then performed on the geometric model to obtain analysis results (displacement field, stress field, contact pressure field). Based on the analysis results, the performance indicators of the geometric model (simulated contact pressure non-uniformity, simulated maximum contact pressure, simulated contact continuity, simulated leakage rate, and simulated fatigue safety factor) are calculated. Next, based on the performance indicators and the target performance vector, it is determined whether the convergence condition is met. If the convergence condition is met, the geometric model is determined as the final design model; if the convergence condition is not met, the design variable vector is updated based on the performance indicators and the target performance vector. This process is iterated until the convergence condition is met. This method, by introducing thermal effects and thermo-mechanical coupling during geometric modeling and analysis, allows design evaluation to move beyond assembly or room temperature conditions. It directly reflects the actual deformation and stress characteristics of the needle valve and valve seat under real-world operating conditions, significantly improving the accuracy of predicting contact state changes. This makes the contact pressure distribution, deformation coordination, and local stress levels closer to the actual operating state, fundamentally enhancing the engineering applicability of the design results. Through an iterative update mechanism, the method continuously adjusts design variables based on performance deviations. Iterative optimization gradually weakens the influence of adverse factors, making the contact load distribution more reasonable and reducing the probability of local overload and contact interruption, thereby improving sealing performance.

[0033] The coupling design method of injector needle valve cone angle and seat surface stress provided in this application embodiment can be applied to electronic devices. In this case, the electronic device is the subject of execution of the coupling design method of injector needle valve cone angle and seat surface stress provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of electronic device.

[0034] For example, electronic devices can be tablets, laptops, ultra-mobile personal computers (UMPCs), netbooks, desktop computers, computers, laptops, etc.

[0035] To better understand the coupling design method of injector needle valve cone angle and seat surface stress provided in the embodiments of this application, the specific implementation process of the coupling design method of injector needle valve cone angle and seat surface stress provided in the embodiments of this application will be described by way of example below.

[0036] Figure 1A schematic flowchart of the coupling design method for the fuel injector needle valve cone angle and seat surface stress provided in this application embodiment is shown. The coupling design method for the fuel injector needle valve cone angle and seat surface stress includes:

[0037] S100, Acquisition Steps: Acquire the design variable vector and the target performance vector. The design variable vector includes the needle valve cone angle, seat width, micro-arc radius, Fourier coefficients, and axial pre-compression. The Fourier coefficients are used to generate non-axisymmetric micro-geometric corrections in the circumferential direction of the needle valve. The axial pre-compression is used to adjust the axial relative position of the needle valve and valve seat. The target performance vector includes the target contact pressure non-uniformity between the needle valve and valve seat, the target maximum contact pressure, the target contact continuity, the target leakage rate, and the target fatigue safety factor.

[0038] It is understandable that the design variable vector is used to characterize the adjustable features of the sealing interface between the needle valve and the valve seat in terms of geometry and assembly state.

[0039] The target performance vector is used to clarify the performance requirements that the design needs to achieve, and it is the direct basis for subsequent judgments on the rationality and convergence of the design.

[0040] For example, the initial values ​​of the design variable vector can be set manually, and a traditional axisymmetric design scheme that is widely used in engineering, has a clear structure, and is easy to verify can be used as the starting point for calculation. For example, the initial value of the needle valve cone angle is set to 90.0°, indicating that the needle valve and valve seat adopt a conventional conical surface fit; the initial value of the seat width is set to 30.0 μm, indicating the width of the strip area (sealing strip width) in the design of the needle valve and valve seat that participates in sealing along the generatrix direction of the conical surface (the oblique length of the conical surface); the initial value of the micro-arc radius is set to 2.0 mm, which is used to smooth the conical surface and the transition area and reduce the risk of stress concentration; the initial values ​​of all Fourier coefficients are set to 0, indicating that there is no artificially introduced asymmetric geometric correction in the circumferential direction (i.e., the circular direction), that is, the initial state is an ideal axisymmetric structure; the initial value of the axial pre-compression is set to 0, indicating that the needle valve and valve seat only maintain the assembly reference position and no additional axial interference or clamping adjustment is introduced. By setting the initial values ​​mentioned above, the entire design process can start from a standard, comparable, and reproducible baseline state. Subsequent geometric adjustments and performance changes can be attributed to the changes in design variables themselves, rather than the uncertainty of the initial conditions.

[0041] Contact pressure nonuniformity reflects the uniformity of pressure distribution within the contact area between the needle valve and the valve seat, and is quantified by the dispersion or variation level of the contact pressure. The target contact pressure nonuniformity (i.e., P1_target) can be set to a small percentage, such as 10%, indicating that the contact load is distributed as evenly as possible on the sealing interface to avoid local overload and stress concentration.

[0042] The maximum contact pressure reflects the peak pressure level experienced at the contact interface and is used to constrain local contact strength. The target maximum contact pressure (P2_target) can be set based on material yield strength, surface hardening state, and long-term service experience, which helps to meet sealing requirements without inducing plastic deformation or early surface damage, such as P2_target = 220 MPa. By setting an upper limit on the maximum contact pressure, the risk of abnormal wear and structural failure can be effectively controlled.

[0043] Contact continuity describes the degree of complete contact between the needle valve and the valve seat in the circumferential or axial direction, reflecting the presence of contact interruptions, gaps, or partial separation. The target contact continuity (P3_target) can be set to 100%, indicating that the sealing interface is expected to maintain completely continuous and effective contact under design conditions, thereby avoiding the formation of potential leakage channels and promoting the stability and consistency of sealing behavior.

[0044] Leakage rate is used to quantitatively characterize the actual sealing capability of the sealing interface and is one of the indicators that directly reflects the performance of the fuel injector. The target leakage rate (P4_target) can be set according to the system's allowable fuel loss range and emission requirements, such as P4_target = 0.05 ml / min. By setting a strict target for the leakage rate, the contact state can be forced to meet the sealing requirements at both the macroscopic and microscopic scales.

[0045] The fatigue safety factor is used to evaluate the reliability margin of a structure under long-term cyclic loading. The target fatigue safety factor (P5_target) can be set to be greater than 1, such as 1.5, indicating that the structure has sufficient safety margin under design conditions to cope with uncertainties caused by manufacturing deviations, operating condition fluctuations, and long-term service.

[0046] By initializing the design variable vector and the target performance vector, the entire design process has a clear starting point, clear objectives, and quantifiable evaluation criteria, laying a solid foundation for subsequent analysis and iteration.

[0047] S200, Model Generation Steps: Generate a geometric model based on the design variable vector.

[0048] It is understandable that the needle valve cone angle is used to determine the tilt angle of the needle valve cone surface, which affects the position of the contact line and the trend of contact pressure distribution; the seat width is used to limit the actual contact area involved in sealing; and the micro-arc radius is used to introduce a smooth transition at geometric abrupt locations, avoiding non-physical stress singularities caused by sharp corner structures in stress analysis.

[0049] For example, a parametric profile of the needle valve body can be constructed using the needle valve axis as a reference axis; the basic tilt angle of the needle valve sealing cone surface can be defined using the needle valve cone angle; the axial geometry of the valve seat sealing band can be defined using the seat width; and the contact transition area of ​​the needle valve or valve seat can be rounded using a micro-arc radius to avoid numerical singularities caused by sharp geometry. All of the above geometric elements are embedded in the geometric definition as variables, allowing them to be automatically updated as design variables change. This process is completed in a two-dimensional axisymmetric coordinate system, resulting in the baseline geometry.

[0050] After completing the axisymmetric reference geometry construction, the two-dimensional profile can be expanded into a three-dimensional solid model by rotation to obtain the initial three-dimensional geometry of the needle valve and valve seat. This geometry is completely symmetrical in the circumferential direction, corresponding to the case where the Fourier coefficients in the design variables are zero. It serves as the basic model for the subsequent introduction of asymmetric features, providing a stable reference framework for subsequent local geometric corrections.

[0051] Based on the initial three-dimensional geometry, a radial or normal displacement distribution varying with the angle can be generated using a preset periodic function based on the Fourier coefficients in the design variable vector. This displacement distribution is then mapped onto the surface of the contact area between the needle valve and the valve seat, resulting in a non-axisymmetric three-dimensional geometry. In this way, the non-axisymmetric three-dimensional geometry retains the original conical surface structure characteristics on a macroscopic scale, but forms a controllable non-axisymmetric undulating morphology on a microscopic scale, which can be used to simulate or compensate for manufacturing deviations, assembly errors, or uneven contact under operating conditions.

[0052] Using the assembly reference plane, the needle valve can be translated axially in either the forward or reverse direction to obtain a three-dimensional geometric model of the needle valve and valve seat. The translation amount is directly determined by the axial pre-compression amount. This adjustment is used to change the degree of compression and contact position of the needle valve and valve seat in their initial contact state. This process does not change the geometry of individual parts, but it can affect the contact area and contact load distribution of the needle valve and valve seat in subsequent analysis.

[0053] The generated geometric model can be exported as a STEP or IGES format geometric file for subsequent finite element analysis software to read.

[0054] The process of generating the geometric model described above can be implemented using parametric modeling methods in general-purpose 3D modeling software or engineering modeling platforms. It can use scripts or interfaces to directly use the design variable vector as input parameters to automatically drive geometric updates.

[0055] This step enables the accurate and controllable transformation of abstract design variable vectors into geometric models with clear physical meaning. These models not only reflect the characteristics of traditional axisymmetric structures but also flexibly express circumferential asymmetric morphology and assembly position variations at the microscopic scale, providing a realistic, reliable, and iteratively updatable geometric foundation for subsequent thermal and mechanical analyses.

[0056] In one possible implementation, S200, based on the design variable vector, generates a geometric model, including:

[0057] We can assume that the needle valve cone angle, seat width, micro-arc radius, Fourier coefficients (first-order cosine and sine coefficients, second-order cosine and sine coefficients), and axial pre-compression are X1, X2, X3, X4, X5, X6, X7, and X8, respectively. The initial value of the design variable vector can be set to X=[90,30,2,0,0,0,0,0].

[0058] Fixed geometric parameters of the fuel injector can be preset, such as needle valve guide diameter D_guide=4.5mm, total needle valve length L_total=25.0mm, valve seat inlet diameter D_inlet=4.8mm, valve seat outlet diameter D_outlet=4.2mm, and sealing band reference position Z_contact_ref=15.0mm (measured from the top of the needle valve).

[0059] You can use a parametric modeling kernel (such as OpenCASCADE, ACIS, or commercial CAD software API) to create new work sessions: the modeling accuracy can be set to 0.001mm, the origin of the coordinate system can be set to the intersection of the injector axis and the top surface of the needle valve; the Z-axis can be set along the injector axis, pointing in the direction of fuel flow; the X-axis can be set radially, 0° direction; and the Y-axis can be set radially, 90° direction.

[0060] S210, construct the reference geometry based on the needle valve cone angle and seat width. The reference geometry is axisymmetric and includes the reference conical surface, the needle valve body cylindrical surface, and the valve seat geometry.

[0061] For example, the design parameters can be geometrically transformed based on the needle valve cone angle and seat width in the design variable vector: assuming the nominal cone angle α = X1, then the half cone angle θ = α / 2. To facilitate subsequent trigonometric function calculations, the half cone angle can be converted to radians, i.e., θ_rad = θ × π / 180. Since the unit of seat width is μm, it can be converted to mm, i.e., w = X2 / 1000.

[0062] Based on the valve seat outlet diameter D_outlet, θ_rad, and w, the large end radius R_max and small end radius R_min of the sealing strip can be calculated, i.e., R_max = D_outlet / 2, R_min = D_outlet / 2 - w × sin(θ_rad). The axial length of the sealing strip can then be calculated, i.e., L_contact = w × cos(θ_rad). This process allows for the calculation of the spatial position of the sealing strip on the conical surface.

[0063] The sealing strip can be positioned axially based on the reference position Z_contact_ref. The start and end positions of the sealing strip in the axial direction are: Z_min = Z_contact_ref - L_contact / 2; Z_max = Z_contact_ref + L_contact / 2.

[0064] A circular cross section with radius R_min can be created on the plane Z=Z_min, and a circular cross section with radius R_max can be created on the plane Z=Z_max. Using these two circular cross sections as loft sections, a ruled surface connecting the two circular cross sections is generated in the axial direction using the ruled loft method or the sweep method, thereby forming an ideal axisymmetric conical surface, which serves as the reference conical surface S_baseline.

[0065] A rotationally symmetric coordinate system can be established on the axis, and circular cross-sections with a diameter of D_guide can be constructed at Z=0, Z=Z_min, Z=Z_max, and Z=L_total, respectively. The cross-sections can be rotated to form surfaces using an axisymmetric sketch or swept axially along the circular cross-sections. The upstream cylindrical surface segment is obtained by sweeping the circular cross-section at Z=0 to Z=Z_min; the downstream cylindrical surface segment is obtained by sweeping the circular cross-section at Z=Z_max to Z=L_total, thus obtaining the cylindrical surface S_needle_body of the needle valve body. In the reference geometry, except for the conical surface of the sealing zone, its upper and lower sides are represented by cylindrical surfaces of the same diameter. This is an engineering abstraction used to highlight the sealing area and simplify non-critical structures.

[0066] Generation of the conical convergence channel: The valve seat inlet section (diameter D_inlet) and the corresponding section of the sealing strip (related section on the outlet side) can be selected above Z=Z_contact_ref as two control sections. The axisymmetric conical or frustum-shaped inner cavity surface is generated by using the loft or ruled surface generation method, so that the valve seat inner cavity gradually converges from the inlet to the sealing strip position.

[0067] Generation of cylindrical outlet channel: Under Z=Z_contact_ref, with a circular cross-section of diameter D_outlet as the reference, a cylindrical outlet channel surface can be generated along the axis using the sweep / extrude method, so that the fluid enters a stable straight-through area after passing through the sealing strip.

[0068] When modeling the valve seat, the sealing tapered surface of the valve seat cavity can be copied with the same parameters as S_baseline, so that both have completely consistent axisymmetric tapered surface geometry in the sealing tapered area.

[0069] At the junction of the valve seat's conical converging channel and the sealing strip's conical surface, and at the junction of the sealing strip's conical surface and the cylindrical outlet channel, curved surface stitching / merging or fillet / transition operations can be used to ensure the valve seat's curved surface is continuous and without self-intersection or gaps. Through the above process, the valve seat geometry S_seat_body can be formed, enabling precise alignment with the reference conical surface at the sealing strip.

[0070] S220: Based on the Fourier coefficients and the radius correction function in the circumferential direction, the correction amount is calculated, and based on the correction amount, the reference conical surface is non-axisymmetrically corrected to obtain the sealing conical surface. The Fourier coefficients include first-order cosine and sine coefficients, and second-order cosine and sine coefficients.

[0071] For example, a radius correction function in the circumferential direction can be defined according to the Fourier series form: , where θ is the inscribed angle (in radians), a1=X4, b1=X5, a2=X6, b2=X7.

[0072] The surface deformation method can be used to transform... Applying to S_baseline achieves non-axisymmetric correction: S_baseline can be represented by two parameters, namely u∈[0,1], the axial parameter, corresponding to the Z coordinate direction; v∈[0,2π], the circumferential parameter, corresponding to the circumferential angle.

[0073] The discrete sampling resolution can be set, i.e., Nu=100 (number of axial sampling points) and Nv=72 (number of circumferential sampling points); and discrete parameter points can be constructed, i.e. , Where i = 0, 1, ..., Nu-1, j = 0, 1, ..., Nv-1, Indicates the axial sampling point. Let S_baseline represent the sampling points along the circumferential direction. Then the discrete point set of S_baseline can be represented as... .

[0074] For each discrete point It can As the corresponding inscribed angle, that is And based on the radius correction function in the circumferential direction, calculate the radius correction at θ, i.e. .

[0075] You can do it at (point) , At point (), calculate the partial derivatives of S_baseline with respect to parameter u and S_baseline with respect to parameter v, respectively; perform a cross product of the two partial derivatives and normalize them to obtain the local normal vector. .

[0076] The radius correction can be applied to the point along the normal direction. The corrected point position is obtained. .

[0077] Corrected discrete point set Numerical point clouds are insufficient for direct use as the geometric model for subsequent meshing and finite element analysis. A NURBS surface fitting method can be used to fit the point cloud into a smooth, continuous, and parameterizable surface. Since the discrete point set originates from a reference conical surface parametrically (…),… , The point set is obtained by sampling according to the rules and correcting it point by point. Therefore, the point set has a two-dimensional grid topology structure. The point set can be arranged into a point matrix of size Nu×Nv according to the order of parameters u and v, so that each row corresponds to a fixed axial position and each column corresponds to a fixed circumferential angle position.

[0078] The axial direction can be defined as the parameter u direction of the NURBS surface, and the circumferential direction can be defined as the parameter v direction. Parametric coordinate systems can be established for each direction. A quasi-uniform parameter distribution method can be adopted to map the parameter values ​​of discrete points in their respective directions to the interval [0,1], which is conducive to the parameter variation and point cloud distribution being roughly uniform, and avoids local oscillations or distortions of the surface due to unreasonable parameters.

[0079] Cubic B-spline basis functions can be used in two parameter directions to construct node vectors for each direction. The node vectors are quasi-uniformly distributed to match the node spacing with the distribution density of the point cloud in the corresponding direction, thus maintaining the smoothness of the surface shape as a whole.

[0080] It can be a discrete point set Using the target data, the control point positions of the NURBS surface are solved through least-squares fitting. This process uses minimizing the distance between the predicted and actual corrected positions of the surface at each parameter point as the objective function. Given the order and node vectors, the control point coordinates are solved to make the surface fit the discrete point cloud as closely as possible. Simultaneously, a fitting tolerance can be set during the fitting process, such as 0.0001 mm. When the maximum deviation from the surface to each point is less than this tolerance, the fitting is considered to meet the accuracy requirements.

[0081] The above process yields a NURBS surface, which serves as the non-axisymmetric corrected sealed conical surface. This surface maintains the overall shape of the original conical surface while exhibiting minute geometric undulations introduced by the Fourier correction function in the circumferential direction.

[0082] S230, based on the micro-arc radius, the junction between the sealing cone surface and the cylindrical surface of the needle valve body is rounded to obtain a rounded surface.

[0083] For example, the two sides Z=Z_min and Z=Z_max are the spatial curves formed by the intersection of the reference conical surface or the sealing conical surface with the upper and lower cylindrical surfaces, respectively. They are also the locations where the geometric curvature changes abruptly and stress concentration occurs. Therefore, these two boundaries can be determined as the target boundary E for rounding.

[0084] The rounded surface can be generated using the rolling sphere method. This involves constructing a virtual sphere with a rounding radius of X3, making the sphere simultaneously contact two adjacent curved surfaces (a sealed conical surface and a cylindrical surface). The center of the sphere is controlled to move continuously along the direction of edge E, ensuring that the sphere remains tangent to both curved surfaces during the movement. As the sphere rolls, the contact trajectories with the two adjacent curved surfaces form an envelope surface, which is the rounded surface.

[0085] Because the S_baseline underwent a non-axisymmetric correction, the sealing strip width w changes along the circumferential direction, allowing the rounding process to adaptively adjust in the circumferential direction. The correction amount in the circumferential direction is... The corresponding correction amount for the sealing strip width is Then the starting and ending positions of the sealing strip in the axial direction are: , ,Right now , For the target boundary E to be rounded, the rounding is not fixed and only operates at Z_min and Z_max, but moves slightly back and forth along the axial direction at different angles of the circumference to adapt to the changes in the width of the non-axisymmetric sealing band.

[0086] The rounding radius can be adjusted according to changes in the width of the sealing strip, i.e. ,in, This represents the corrected fillet radius, and k represents the adjustment coefficient, which can be 0.5 to 1.0.

[0087] This step generates a smooth rounded surface between the sealing conical surface and the cylindrical surface of the needle valve body, transforming the geometry from an abrupt transition structure of cylindrical surface-acute angle-conical surface to a continuous transition structure of cylindrical surface-rounded surface-conical surface. Furthermore, in the presence of non-axisymmetric correction, the rounding adaptively adjusts in the circumferential direction according to the width of the sealing strip, which is beneficial for the sealing area to have a reasonable, smooth, and physically consistent geometric transition at different circumferential positions.

[0088] S240, the sealing conical surface, the cylindrical surface of the needle valve body, and the rounded surface are stitched together to obtain the needle valve geometry.

[0089] For example, a rounded surface can be used as a cutting tool to delete the acute angle areas on the sealing cone surface and the cylindrical surface of the needle valve body that are replaced by the rounded surface. The rounded surface is then stitched with the cut sealing cone surface and cylindrical surface to form a complete curved surface that includes a continuous transition between the cylindrical surface, the rounded surface, and the sealing cone surface, i.e., the needle valve geometry.

[0090] Through this step, the geometrical abrupt changes at Z=Z_min and Z=Z_max can be replaced by a smooth transition.

[0091] S250, based on the axial pre-compression amount, adjust the axial position of the needle valve geometry relative to the valve seat geometry, and assemble the needle valve geometry and valve seat geometry to obtain the geometric model.

[0092] For example, in the original modeling coordinate system, the needle valve geometry has a reference axial position Z_contact_ref, which corresponds to the assembly reference position of the needle valve without pre-compression and without additional axial adjustment. Therefore, when X8=0, the center of the needle valve sealing cone coincides with the center of the valve seat sealing band.

[0093] When X8 is not 0, we can assume =X8, when When >0, the needle valve moves along the -Z direction, causing the needle valve to retract relative to the valve seat; when When <0, the needle valve moves along the +Z direction, bringing it closer to the valve seat. Geometrically, this can be achieved by applying a uniform spatial translation transformation to all points in the needle valve geometry, defining the translation matrix in homogeneous coordinates as... Assume that the homogeneous coordinates of any point in the needle valve geometry in the original coordinate system are... Then the new coordinates after axial translation are By performing the above transformation on all points in the needle valve geometry, the entire needle valve can be uniformly translated in the axial direction without changing its own geometric shape and relative dimensional relationships.

[0094] After the needle valve geometry has been axially translated, the adjusted needle valve geometry and the stationary valve seat geometry are placed in the same coordinate system and aligned according to a common axial reference to obtain a geometric model, which can be used for subsequent finite element analysis and performance evaluation.

[0095] S300, Finite Element Analysis Steps: Perform thermal analysis and thermo-mechanical coupling analysis on the geometric model to obtain the analysis results. These results include the displacement field, stress field, and contact pressure field.

[0096] It can be understood that the contact pressure field is the normal contact pressure on the contact surface between the needle valve and the valve seat; the displacement field is the nodal displacement between the needle valve and the valve seat, used to determine the contact state and gap; and the stress field is the structural equivalent stress, used for fatigue verification.

[0097] For example, you can launch finite element analysis software (such as Abaqus, ANSYS, or an open-source alternative), import the geometric model into the finite element analysis environment (i.e., read the geometric file in STEP or IGES format generated in the previous step and import it into the finite element software), define the needle valve and valve seat as two separate components, and create an assembly.

[0098] It can pre-establish query and mapping relationships with the material database to query the temperature-related material property parameters corresponding to the grade of needle valve material and valve seat material (e.g., needle valve material is high carbon steel, grade SAE52100; valve seat material is alloy steel, grade AISI4140). The material property parameters are organized into a temperature-parameter table format that can be directly recognized by finite element software, and assigned to the geometry corresponding to the needle valve and valve seat according to the component name. The software can automatically interpolate and call the corresponding parameter values ​​based on the current temperature according to the temperature-parameter table.

[0099] Material properties may include: thermophysical properties (including coefficient of thermal expansion, thermal conductivity, specific heat capacity, density), mechanical properties (including elastic modulus, Poisson's ratio, yield strength, hardening modulus), and fatigue properties (including fatigue limit).

[0100] The coefficient of thermal expansion can be measured experimentally using a thermomechanical analyzer (TMA) or obtained by consulting material handbooks (such as ASM Handbook, SAE / AISI steel standards, GB, DIN standards). Thermal conductivity can be measured experimentally using the laser scintillation method or obtained by consulting material handbooks. Specific heat capacity can be obtained using differential scanning calorimetry (DSC) or by consulting material handbooks. Example values ​​for the coefficient of thermal expansion, thermal conductivity, and specific heat capacity are shown below. Figure 2As shown. Density can be obtained from material handbooks. Since density is not very sensitive to temperature, it can be set as a constant. For example, the material density of SAE52100 is 7810 kg / m³, and the material density of AISI4140 is 7850 kg / m³.

[0101] The elastic modulus and yield strength can be obtained through tensile testing, high-temperature tensile testing, or by consulting material handbooks. Example values ​​for the elastic modulus are as follows: Figure 3 As shown, example values ​​for yield strength are as follows: Figure 4 As shown. The hardening modulus can be measured using cyclic loading experiments or obtained by consulting a material handbook. Example values ​​for the hardening modulus are shown below. Figure 5 As shown.

[0102] Poisson's ratio can be obtained by simultaneously measuring transverse and longitudinal strain in a tensile test or by consulting a material handbook. In most cases, Poisson's ratio does not vary significantly. For example, SAE 52100 has a Poisson's ratio of 0.3 at 20°C and 0.31 at 300°C; AISI 4140 has a Poisson's ratio of 0.29 at 20°C and 0.30 at 300°C.

[0103] Fatigue limit can be measured using high-cycle fatigue testing or rotating bending and tensile-compression fatigue testing. Example values ​​for fatigue limit are as follows: Figure 6 As shown.

[0104] Global mesh control parameters can be set according to preset mesh strategies. For example, the global size is 0.5mm, the minimum size is 0.01mm, the growth rate is 1.3 (adjacent cell size ratio), and cell quality requirements include Jacobian ratio greater than 0.6, skewness less than 0.7, warpage angle less than 5°, and aspect ratio less than 8:1.

[0105] Local meshing can be performed on key areas: For the sealing contact zone area, it can be quickly located by using predefined curved surface labels (such as contact surface markings), and the target size and multi-layer transitions can be set (such as a target size of 0.02 mm and 5 transition layers) to ensure the resolution of the contact pressure field; For rounded and transition surfaces, areas with large curvature changes can be identified by curvature analysis and the target size can be set (such as 0.05 mm) to reduce geometric discretization errors.

[0106] In actual mesh generation, a hexahedral-dominated meshing strategy can be adopted to generate regular meshes along the injector axis using a sweeping method; for complex geometric regions that cannot be swept, tetrahedral filling algorithms (such as the advanced front method) can be used for completion.

[0107] After mesh generation, contact pairs between the needle valve and the valve seat can be established: calculate the minimum distance between each surface of the needle valve and the surface of the valve seat, and filter the surfaces with a distance less than the threshold (e.g., <0.1mm) as candidate contact surfaces; calculate the average normal angle of the candidate contact surfaces, and remove the surfaces whose normal angle does not meet the condition (e.g., normal angle <30°); match the curvature of the needle valve cone surface and the valve seat cone surface, and confirm the surfaces with a curvature difference less than the threshold (e.g., <10%) as contact pairs and output the master-slave surface relationship. The valve seat can be set as the master surface and the needle valve as the slave surface to improve the stability of the contact calculation.

[0108] Contact parameters can be set according to material properties and working conditions: the contact algorithm can use the augmented Lagrangian method, which employs an enhanced contact processing method that balances accuracy and convergence to improve the reliability of contact pressure calculation. The normal contact stiffness Kn can be set to 10·E / h_min, where E represents the elastic modulus of the material and h_min represents the minimum element size; the tangential contact stiffness Kt can be set to 0.1·Kn; and the maximum allowable penetration can be set to 0.001·h_min.

[0109] Contact friction can be achieved using Coulomb friction, with the friction coefficient μ set to 0.1 and the shear stress limit τ_max set to 0.5·σ, where σ represents the yield strength, thus avoiding unreasonable tangential loads.

[0110] Thermal boundary conditions can be set: thermal boundary conditions include convective boundary conditions, contact thermal resistance boundary conditions, and adiabatic boundary conditions. Convective boundary conditions include the convective boundary on the combustion chamber side (i.e., the end face and side face of the injector head) and the convective boundary on the fuel cooling side (the surface of the fuel passage inside the injector).

[0111] The convective boundary parameters on the combustion chamber side can include the convective heat transfer coefficient and the ambient temperature (representing the temperature under engine operating conditions). The convective boundary parameters can be constants, such as a convective heat transfer coefficient set to 5000 W / m²K (range 3000~8000 W / m²K) and an ambient temperature set to 750°C (range 600~900°C); convective boundary parameters can also be empirical formulas for engine heat transfer, such as the Woschni heat transfer formula, and the software can automatically update these parameter values ​​over time.

[0112] The convective boundary parameters on the fuel cooling side can include the convective heat transfer coefficient and the fuel temperature. The convective boundary parameters can be constants, such as setting the convective heat transfer coefficient to 3000 W / m²K (range 2000~5000 W / m²K) and the fuel temperature to 100°C (range 80~120°C); the convective boundary parameters can also be forced convection formulas within the pipe.

[0113] The boundary parameter of the contact thermal resistance boundary condition is the contact thermal conductance. The contact thermal conductance can be obtained using the empirical model of contact heat transfer, i.e., h_contact=A·p^n·exp(-B·Ra), where p represents the contact pressure and Ra represents the surface roughness. The software can automatically update the parameters based on the contact pressure.

[0114] The thermal boundary condition is that the heat flux q at the valve seat mounting flange end face can be set to 0, i.e., assuming good contact with the engine cylinder head.

[0115] Mechanical boundary conditions can be set: These conditions can include constraint conditions and load conditions. Load conditions can include fuel pressure load and spring preload. Constraint conditions can be manually set, such as full constraint at the bottom of the valve seat; radial constraint and axial freedom of the needle valve guide section; symmetrical boundary (if applicable), with zero displacement in the normal direction of the symmetry plane.

[0116] The fuel pressure load includes the application surface and the pressure value. The application surface can be set as the needle valve bearing surface (top); the pressure value can be set as a time function (such as trapezoidal / pulse).

[0117] Spring preload can be applied via coupling points or rigid connections. The preload can be set using the spring mechanics formula: F = k·Δx, where F represents the preload, k represents the spring stiffness (ranging from 30 to 60 N / mm, e.g., 40 N / mm), and Δx represents the preload amount. The software can automatically update the preload value based on the spring displacement (preload amount).

[0118] Thermal Analysis: After completing the above finite element setup, thermal boundary conditions can be applied to the geometric model. Transient thermal analysis can be used, with the temperature field of the previous iteration as the initial condition. The solver can use the implicit time integration method to solve the heat conduction equation and calculate the temperature field. Steady-state thermal analysis can also be used, where the solver uses the direct iteration method to solve the heat conduction equation and obtain the steady-state temperature field.

[0119] Thermo-mechanical coupling analysis: The thermal strain field can be calculated based on the temperature field and mapped onto the geometric model as a known load; mechanical boundary conditions are applied to the geometric model, and the structural mechanical equilibrium equations are solved with the displacement field as the unknown, thereby obtaining the displacement field; the total strain can be calculated based on the displacement field, and the mechanical strain can be obtained by subtracting the thermal strain; the stress field can be calculated based on the mechanical strain through the material constitutive relation; the contact algorithm can calculate the contact reaction force based on the relative displacement (i.e., displacement field) between the contact surfaces, thereby obtaining the contact pressure field.

[0120] This step enables the realistic simulation of the deformation and stress behavior of the needle valve and valve seat under temperature changes and external loads in geometric models and working conditions, obtaining the distribution of displacement, stress and contact pressure. This not only reveals the structural response characteristics of the design scheme under actual working conditions, but also provides a direct and reliable data basis for subsequent performance index calculations.

[0121] In one possible implementation, S300 performs thermal analysis and thermo-mechanical coupling analysis on the geometric model to obtain analysis results, including:

[0122] S310, based on thermal boundary conditions, performs thermal analysis on the geometric model to obtain the temperature field. The thermal boundary conditions include convective boundary conditions, contact thermal resistance boundary conditions, and adiabatic boundary conditions.

[0123] It is understandable that the temperature field can be solved by the direct iteration method in steady-state thermal analysis. Its core objective is to solve the temperature distribution of the fuel injector needle valve and valve seat under long-term stable working conditions, given thermal boundary conditions and material properties. This process does not consider the temperature change over time, but assumes that the system has been running for a long enough time and the temperature of each part has reached thermal equilibrium.

[0124] For example, the thermal boundary condition of step S300 can be applied to the model. The solver uses the initial temperature distribution as the starting point for iteration. The initial temperature can be set to room temperature (e.g., 20°C) or a certain empirical working temperature (e.g., 100°C). This initial temperature is only used to assist numerical iteration convergence and does not affect the final steady-state result. The solver internally adjusts the temperature of each node step by step through iterative calculations so that the heat input and output at any point in the geometric model reach a state of equilibrium.

[0125] During the solution process, the thermal conductivity of each element can be updated according to the current temperature field in each iteration, and the steady-state heat conduction equation can be reassembled until the temperature change between two adjacent iterations is less than the preset convergence threshold, while the heat flow residual meets the accuracy requirements.

[0126] Once the solution converges, the output temperature field can include the temperature values ​​of each node / element, isotherm distribution, and the highest temperature and temperature gradient distribution in key areas (such as the contact zone between the needle valve and the valve seat, the area near the combustion side, and the area near the fuel cooling side). This temperature field can be regarded as the true temperature state of the fuel injector under long-term stable operating conditions and can serve as the basic input for calculating thermal expansion and thermal stress in subsequent thermo-mechanical coupling analysis.

[0127] Optionally, in step S310, based on thermal boundary conditions, a thermal analysis is performed on the geometric model to obtain the temperature field, including:

[0128] S311, based on the temperature field and thermal boundary conditions of the previous iteration, uses the implicit time integration method to solve the heat conduction equation of the geometric model to obtain the temperature field. The initial value of the temperature field is the ambient temperature.

[0129] It is understandable that the goal of transient thermal analysis is to use the temperature field of the previous iteration as the thermal history input under thermal boundary conditions, and to solve the heat conduction equation step by step using the implicit time integration method, so as to obtain the temperature field that evolves with time in the current iteration.

[0130] For example, for the first iteration, the initial temperature of the geometric model is uniformly set to the ambient temperature (i.e., room temperature, such as 20°C), which allows the calculation to start from a cold start or the initial state of assembly. For subsequent iterations, the temperature field of the previous iteration is used as the new initial state to reflect heat accumulation and historical effects, so that the temperature evolution has iterative continuity and physical consistency.

[0131] Transient thermal analysis solves for the time evolution form of the heat conduction equation, i.e. Where T represents the temperature vector of each node / unit at the current moment. The coefficient of thermal conductivity (C) represents the rate of change of temperature with respect to time. C(T) represents the heat capacity matrix (determined by density and specific heat capacity), K(T) represents the thermal conductivity matrix (determined by thermal conductivity), and Q(T,t) is the equivalent heat load term, which includes convective heat transfer, contact heat transfer, and possible heat source terms.

[0132] The total time step can be set, such as 20ms for one injection cycle. Implicit time integration methods can be used to discretize the time term of the heat conduction equation above. Implicit time integration methods (such as backward Euler or implicit generalized trapezoidal rule) can place the unknown at a new time step, thus achieving better stability. Taking backward Euler as an example, at each time step... → And the time increment is Sometimes, ,in, Indicates that Temperature field at any moment ,express Substituting the temperature field at time step (in seconds) into the heat conduction equation above, we can obtain the solution equation for each time step: .

[0133] In transient analysis, time can be progressed from 0 to the total duration. Time increment It can be fixed or adaptive. For example, it can be reduced when the temperature changes rapidly or the boundary heat transfer changes drastically. When the temperature change is gradual, it can be amplified. It can be based on the current time. Update the thermal boundary conditions and apply them to the geometric model in this iteration.

[0134] Since K(T), C(T), and convective heat transfer are temperature-dependent, and the thermal boundary conditions change with temperature or state, the solution is required at each time step. An iterative process can be used: ( The initial value is the temperature field from the previous iteration. Initial temperature estimate; based on the current temperature estimate Update K(T), C(T), and Q(T,t), and substitute them into the above equation to solve for the result. Calculate the temperature residual or iterative increment (such as the maximum node temperature change). If it meets a preset threshold, the time step can be considered converged and accepted. If the condition is not met, the iteration can continue; if the number of iterations exceeds the limit, the iteration count can be reduced. Then repeat the iteration process.

[0135] When time advances to the end point The solver can output the temperature field. Through the above process, the true temperature distribution at any time and key stage can be obtained, providing a reliable, continuous and physically consistent temperature field input for subsequent thermo-mechanical coupling analysis, enabling accurate prediction and evaluation of temperature-induced thermal expansion, thermal stress, and contact state changes.

[0136] S320, based on mechanical boundary conditions and temperature field, performs thermo-mechanical coupling analysis on the geometric model to obtain analysis results. The mechanical boundary conditions include constraint conditions and load conditions.

[0137] For example, the temperature field can be mapped onto the geometric model, so that each element / node has a corresponding temperature value. The solver can convert the temperature of each element / node into thermal strain based on the thermal expansion characteristics of the material.

[0138] The solver determines whether each contact point is in contact or separated at each time increment through nonlinear iteration (such as Newton-Raphson); it applies normal constraints to the contact points and calculates the contact reaction force, as well as the tangential friction force and possible relative slip, until the force residual and displacement correction meet the convergence criteria.

[0139] After the solution converges, it can output the displacement field, stress field (including equivalent stress, principal stress or local stress distribution near the contact) and contact pressure field (normal contact pressure distribution can be extracted on the contact interface) of the structure under the combined action of thermal and mechanical loads.

[0140] Optionally, S320, based on mechanical boundary conditions and temperature field, performs thermo-mechanical coupling analysis on the geometric model to obtain analysis results, including:

[0141] S321, Calculate the thermal strain field based on the temperature field.

[0142] For example, the temperature field can be mapped onto all elements / nodes of the geometric model to obtain the current temperature T(x,y,z) of each element / node, and then compared with a reference temperature. (i.e., at room temperature, such as 20℃) Calculate the temperature change for each element / node, i.e. ,in, It represents the amount of temperature change.

[0143] The coefficient of thermal expansion α(T) of the material at T(x,y,z) can be read, and the formula for calculating thermal strain is: Where I represents the unit tensor, which can be expressed in component form as , , The above process can be repeated for all nodes / elements in the geometric model to calculate the thermal strain value point by point, thus forming a thermal strain field. The thermal strain field can be written as the initial strain into the constitutive integration point of the element, so that it will automatically generate equivalent thermal expansion internal forces in the subsequent structural solution.

[0144] S322, based on the thermal strain field and mechanical boundary conditions, the displacement field is obtained by solving the mechanical equilibrium equations of the geometric model using the Newton-Raphson method.

[0145] For example, mechanical boundary conditions can be applied to the geometric model, where the constraints and load conditions in the mechanical boundary conditions together constitute the external force vector. Thermal strain contributes to the internal forces caused by thermal expansion within the structure through the material constitutive relation. The mechanical equilibrium of the structure after finite element discretization can be written as the residual equation: , where U represents the global displacement vector (displacement field) to be determined. This represents the internal force vector.

[0146] The Newton-Raphson method can be used for iterative solution: set the initial displacement. If we take a zero displacement as the initial guess, the solver can, in the k-th iteration, adjust the current displacement... Calculate the element / nodal displacement gradient and obtain the total strain. ;Will minus Mechanical strain is obtained; stress is updated from material constitutive relations and integrated to form element internal forces; contact reactions are updated based on the current contact gap and contact state; and the global internal force vector is obtained by summing the results. ; Calculate residuals Linearizing the residuals with respect to displacement yields the tangent stiffness matrix, i.e. Solving the linearized system of equations yields the displacement increment, i.e. Update displacement If a line search or damping strategy is adopted, the increment can be multiplied by a coefficient λ∈(0,1] to suppress contact oscillations and improve convergence stability.

[0147] After each update, it can be determined whether the convergence conditions are met, such as whether the residual norm is below the threshold (whether force balance is satisfied); whether the displacement increment is small enough (whether the iteration is stable and convergent); and whether the contact penetration is within the allowable range. If the convergence conditions are met, the current load step can be considered solved, and the displacement field U is output. If convergence is not achieved, the above iterative process is returned to continue iterating.

[0148] This step facilitates accurate prediction of the stress distribution, displacement field, and contact state of the structure under thermo-mechanical coupling conditions, providing reliable basic data for subsequent engineering performance evaluations such as sealing performance and fatigue safety factor.

[0149] S323: Calculate the total strain using the displacement gradient based on the displacement field. Calculate the mechanical strain field based on the total strain and thermal strain field; calculate the stress field based on the material constitutive relation and the mechanical strain field.

[0150] For example, the total strain field The displacement gradient can be calculated from the displacement gradient. For each element / node, the displacement gradient can be obtained through numerical differentiation: , where ∇U is the spatial derivative of the displacement field, representing the deformation rate at each node of the structure, and each element is discretized and solved using the finite element method.

[0151] Since the total strain includes both mechanical and thermal stress, the mechanical strain field can be obtained by subtracting the thermal strain from the total strain: .

[0152] For linear elastic materials, the constitutive relation can be expressed as: Where σ is the stress field and C is the constitutive matrix (elastic matrix) of the material. The solver can solve for the stress field σ based on the material constitutive relation and the calculated mechanical strain field.

[0153] This step provides accurate stress and deformation data for subsequent contact analysis, fatigue assessment, and sealing performance, and is conducive to the prediction of performance under the combined action of thermal effects and mechanical loads with high accuracy and reliability.

[0154] S324, based on the contact surface between the needle valve geometry and the valve seat geometry in the displacement field and geometric model, uses the augmented Lagrange method to calculate the contact pressure field.

[0155] For example, the augmented Lagrange method takes the form of: ,in, This represents the penetration amount at the contact point (or, if there is penetration, the normal displacement between the contact points). For contact stiffness, The Lagrange multiplier represents the contact pressure.

[0156] According to the augmented Lagrange method, contact pressure Through Lagrange multipliers This is represented by [the term]. In each iteration, the contact algorithm adjusts the current penetration amount [based on the current penetration amount]. and contact stiffness Calculate the contact pressure: The contact pressure can be calculated by iteratively adjusting the relative displacement, contact stiffness, and elastic model on the contact surface. In each iteration of the Newton-Raphson method, the contact algorithm can update the penetration amount and contact pressure, and reflect them in the internal force calculation. After several iterations, the contact pressure will gradually converge, thus obtaining the contact pressure field.

[0157] The augmented Lagrangian method can accurately simulate the pressure distribution in the contact area, ensuring the stability and accuracy of the contact state, thus providing reliable data support for subsequent sealing performance evaluation, stress distribution analysis and structural optimization.

[0158] S400, performance index calculation steps: Based on the analysis results, calculate the performance indexes of the geometric model. These performance indexes include simulated contact pressure non-uniformity, simulated maximum contact pressure, simulated contact continuity, simulated leakage rate, and simulated fatigue safety factor.

[0159] For example, the standard deviation and average value of the pressure within the contact area can be calculated based on the contact pressure field to evaluate the non-uniformity of the simulated contact pressure. The maximum contact pressure can be extracted from the contact pressure field as the simulated maximum contact pressure. The contact area is divided into several small segments along the circumference, and the number of effective contacts in each segment is counted. >0), calculate the proportion of the number of effective contacts to the total number, which is the simulated contact continuity.

[0160] Based on the displacement field, the geometric gap of the separation region on the contact surface is calculated (e.g., the gap size is obtained through nodal displacement), and the simulated leakage rate is calculated according to the geometric gap and the fluid dynamics model (e.g., thin film flow model). The fatigue stress amplitude is calculated based on the stress field, and the simulated fatigue safety factor is calculated according to the fatigue stress amplitude and the material fatigue limit.

[0161] In one possible implementation, S400, based on the analysis results, calculates the performance metrics of the geometric model, including:

[0162] It is understandable that the contact pressure field, displacement field, and stress field are actually time history. The pressure, stress, contact state, and sealing effect on the contact surface change dynamically with the changes in time, temperature, load, and other factors. However, in order to simplify the analysis and obtain the most representative performance indicators, the contact pressure field and displacement field at the moment when the needle valve is closed and completely sealed can be selected. The contact pressure field and displacement field at this moment can most realistically reflect the uniformity of the pressure distribution on the contact surface and the contact integrity.

[0163] S410: Extract the contact pressure of all sampling points from the contact pressure field, calculate the average contact pressure of all sampling points, and calculate the standard deviation of the contact pressure of all sampling points based on the average value; calculate the ratio between the standard deviation and the average value to obtain the simulated contact pressure non-uniformity. Here, the sampling points are points along the circumference of the sealing strip's mid-surface, and the contact pressure field is the contact pressure field at the moment the needle valve is closed and completely sealed.

[0164] For example, a representative section of the sealing strip can be selected for circumferential sampling, such as the circumference at the Z_contact_ref point on the mid-surface of the sealing strip. N (e.g., 72) sampling points can be selected at equal intervals along this circumference, that is, within the circumferential angle θ∈[0,2π] of the section, the circumference is divided into 72 equal angle intervals, with each sampling point corresponding to one circumferential angle. , where j=0,1,...,71.

[0165] For each sampling point j, the corresponding contact pressure can be extracted from the contact pressure field. And calculate the average and standard deviation of the contact pressure at all sampling points: , .

[0166] Calculate the ratio between the standard deviation and the mean: in, This indicates the non-uniformity of simulated contact pressure.

[0167] S420 extracts the maximum contact pressure from the contact pressure field as the simulated maximum contact pressure.

[0168] For example, the maximum contact pressure can be directly extracted from the contact pressure field as the simulated maximum contact pressure; or the maximum contact pressure can be selected from the contact pressures of the above N sampling points as the simulated maximum contact pressure.

[0169] S430: Count the number of sampling points with contact pressure greater than the pressure threshold among all sampling points to obtain the number of contact points, and calculate the ratio between the number of contact points and the total number of sampling points to obtain the simulated contact continuity.

[0170] For example, a threshold for contact pressure (i.e., a pressure threshold) can be set. For example, 1 MPa. For each sampling point j, the pressure of that sampling point can be determined. Is it greater than ,like > The sampling point can be considered a valid contact point, and the number of contact points M is counted. The ratio between M and N is the simulated contact continuity.

[0171] Simulated contact pressure non-uniformity, simulated maximum contact pressure, and simulated contact continuity can help evaluate sealing performance, contact strength, and contact surface integrity, and provide a basis for subsequent design optimization and performance verification.

[0172] S440 calculates the simulated leakage rate based on the displacement field and contact pressure field. The displacement field refers to the displacement field at the moment the needle valve is closed and completely sealed.

[0173] It is understood that, unlike the contact points in step S430, the contact points in this step refer to points that can be considered contact points if there is no gap between the needle valve and the valve seat and there is contact pressure; if there is a gap between the needle valve and the valve seat, these points are not contact points.

[0174] For example, the normal displacement of all sampling points can be extracted from the displacement field. For each sampling point j, if >0 and >0, j can be considered an effective contact point; if If ≈0, it means that j may not be in contact or there may be a very small gap; j can be considered the separation point. If the value is less than 0, it means that contact penetration has occurred at j, and j can be considered as the penetration point.

[0175] For each sampling point j, the contact gap can be calculated based on the normal displacement of the sampling point: the contact gap of the contact point is... The contact gap at the penetration point is ,in Indicates the contact gap.

[0176] Fluid dynamics models (such as Poiseuille flow) can be used to estimate the flow rate through the sampling point. Flow rate calculation formula: Where μ is the dynamic viscosity of the fluid (e.g., the viscosity of fuel), and ΔP is the pressure difference across the seal. The total leakage flow rate Q is obtained by summing the flow rates at all sampling points, and Q can be converted into the simulated leakage rate: Leak = Q × 60 × (Unit: ml / min).

[0177] This step allows for accurate assessment of sealing performance, quantification of leakage flow and seal integrity, and provides crucial feedback for seal design.

[0178] S450 searches for the region corresponding to the maximum stress value in the stress field and identifies the region corresponding to the maximum stress value as the fatigue point; extracts the maximum and minimum stress values ​​of the fatigue point from the stress field, and calculates the stress amplitude and average stress based on the maximum and minimum stress values; and calculates the simulation fatigue safety factor based on the stress amplitude, average stress, and material fatigue parameters.

[0179] For example, the maximum stress value can be found in the stress field, and the corresponding node / element location can be recorded, thus identifying the fatigue point. The maximum stress value at this fatigue point can then be extracted from the stress field. and minimum stress value .

[0180] Calculate the stress amplitude: ; Calculate the mean stress: .

[0181] The simulation fatigue safety factor is calculated based on the stress amplitude and average stress using the Goodman criterion. ,in, It is the ultimate fatigue strength of the material. It refers to the symmetrical fatigue strength of the material. Material fatigue parameters. and The SN curve (i.e., the relationship between stress amplitude and fatigue life) comes from the material. The SN curve can be obtained experimentally (i.e., by measuring the fatigue life (number of cycles) of the material under different stress amplitudes through fatigue testing) or from the material handbook.

[0182] S500, Convergence Judgment Steps: Based on the performance index and the target performance vector, determine whether the convergence condition is met. If the convergence condition is met, the geometric model is determined as the final design model. The convergence condition includes that the absolute value of the difference between the performance index and the target performance vector is less than or equal to the performance threshold.

[0183] For example, the absolute value of the difference between each performance index and the corresponding target performance (Pi_target in step S100) can be calculated. If the absolute value of the difference between all performance indices is less than or equal to the corresponding performance threshold (such as the performance threshold ε1=1.0% for contact pressure non-uniformity, the performance threshold ε2=5MPa for maximum contact pressure, the performance threshold ε3=0.005 for contact continuity, the performance threshold ε4=0.02ml / min for leakage rate, and the fatigue safety factor ε5=0.05), it can be said that the design is close to the target state, the current geometric model is used as the final design model, and the optimization process is terminated; otherwise, iterative optimization continues.

[0184] In one possible implementation, the convergence condition also includes:

[0185] S501, the relative rate of change between the current objective function value and the objective function value of the previous iteration is less than a first threshold. Here, the first threshold is a preset threshold for the relative rate of change of the objective function, used to determine whether the improvement in the objective function between two adjacent iterations is less than the preset threshold.

[0186] For example, the formula for calculating the relative rate of change of the objective function can be expressed as follows: ,in, This represents the objective function value in the current iteration. This represents the objective function value from the previous iteration. A first threshold ϵ1 can be set. When the relative rate of change of the objective function is less than ϵ1, it indicates that the objective function has changed very little and may have reached a stable state of optimization.

[0187] Assuming the magnitude of the objective function is between 10 and 1000, a first threshold can be set to ϵ1 = 0.01, indicating that the objective function changes by no more than 1% between consecutive iterations. If the objective function is more complex and has a smaller magnitude, a stricter threshold can be set, such as ϵ1 = 0.001, indicating that the change in the objective function is less than 0.1%.

[0188] S502, the relative rate of change between the current design variable vector and the design variable vector of the previous iteration is less than the second threshold. The second threshold is a preset threshold for the relative rate of change of the design variable vector, used to determine whether the design variable vector tends to stabilize during the iteration process.

[0189] For example, the formula for calculating the relative rate of change of the design variable vector can be expressed as: ,in, This represents the design variables for the current iteration. This represents the design variables from the previous iteration. A second threshold ϵ2 can be set. When the relative rate of change of all design variables is less than ϵ2, it indicates that the changes in the design variables have stabilized, and further iterations will not significantly improve performance.

[0190] A larger second threshold (e.g., ϵ2=0.01) can be set to determine whether the optimization has stabilized in a shorter time, which is suitable for situations with high computational efficiency requirements; a smaller second threshold (e.g., ϵ2=0.001) can provide more accurate optimization results, which is suitable for situations with high design accuracy requirements.

[0191] S503, the number of iterations has reached the preset number of iterations.

[0192] For example, in actual optimization, in order to avoid getting stuck in local optima or infinite iterations caused by tiny changes during the calculation process, a maximum number of iterations can be set in the optimization process to prevent excessively long calculation times.

[0193] If the optimization process is expected to be relatively simple, a small maximum number of iterations can be set, such as n=50; for complex optimization problems, more iterations may be needed to ensure convergence, so n=100 or more can be set.

[0194] These convergence conditions ensure that the optimization process achieves the design goal while avoiding premature termination or unnecessary calculations, thus enabling the design to find the optimal solution or a near-optimal solution within a limited computation time.

[0195] S600, Design Variable Vector Update Steps: If the convergence condition is not met, update the design variable vector based on the performance index and the target performance vector.

[0196] For example, updating the design variable vector can be done using the adjoint method and the finite difference method. Finite difference method: A small perturbation Δxi can be applied to the design variable Xi, such as 1% or 0.1%; for each perturbation, the simulation is rerun with a new design variable Xi+Δxi to obtain a new performance index Pnew; the change in performance index caused by the perturbation ΔPi=Pnew-Pold is calculated; based on Δxi and ΔPi, the sensitivity of the design variable to the performance index is calculated using the finite difference formula: Based on sensitivity, design variables are adjusted. The direction of adjustment can be calculated based on the difference between the current design variables and the target performance, as well as the sensitivity. The adjusted design variables can move in the direction of reducing performance differences. The finite difference method requires multiple simulation calculations (i.e., each design variable is perturbed and calculated once), thus resulting in high computational costs.

[0197] The adjoint method: An objective function J can be constructed, and by solving the adjoint equation, the sensitivity of each design variable to the corresponding target performance can be obtained. The adjoint equation is: Where A is a matrix related to the objective performance function, representing the sensitivity of the objective function to the displacement field, and λ is an adjoint variable, representing the derivative of the objective function with respect to displacement. It is the gradient of the objective function with respect to the design variables; based on the sensitivity, the values ​​of the design variables are updated. The update method can be implemented using optimization algorithms such as gradient descent and quasi-Newton methods. The adjoint method can calculate the sensitivity of all design variables by solving the adjoint equation once, reducing the number of simulation calculations, making it suitable for large-scale problems, and offering a significant advantage in computational efficiency compared to the finite difference method.

[0198] In one possible implementation, S600 updates the design variable vector based on performance metrics and the target performance vector, including:

[0199] S610, based on the design variable vector, performance index, and target performance vector, solves the adjoint equation to obtain the gradient vector of the objective function with respect to the design variable vector. The adjoint equation characterizes the relationship between the partial derivatives of the objective function with respect to the displacement field and the partial derivatives of the mechanical equilibrium equations with respect to the displacement field. The objective function is used to evaluate the degree of deviation of the performance index from the target performance vector.

[0200] For example, the objective function can be in the form of the sum of squares of the differences between the performance metric and the target performance: ,in, Let i represent the i-th performance index. This is achieved by solving the adjoint equation. The gradient vector can be obtained. The gradient vector represents the direction of minimizing the difference between the performance index and the target performance, and it is the basis for updating the design variables in the next step.

[0201] Optionally, S610, based on the design variable vector, performance index, and target performance vector, solves the adjoint equation to obtain the gradient vector of the objective function with respect to the design variable vector, including:

[0202] S611, based on the displacement field, performance index and target performance vector, calculate the partial derivative of the objective function with respect to the displacement field, and based on the displacement field, calculate the partial derivative of the mechanical equilibrium equation with respect to the displacement field.

[0203] For example, since the objective function J depends on Xi both explicitly and indirectly through the displacement field U, the gradient of the objective function with respect to the design variables... It can be written using the chain rule as follows: .

[0204] The formula for calculating the partial derivative of the objective function with respect to the displacement field is as follows: ,in, Indicators of performance Sensitivity to the displacement field U. The partial derivative of the objective function with respect to the displacement field can be obtained by substituting the performance index vector, the target performance index vector, and the displacement field into the above formula.

[0205] The partial derivatives of the mechanical equilibrium equations with respect to the displacement field can be expressed as follows: In most engineering problems =0, then Since K×U= Where K represents the stiffness matrix, reflecting the stiffness of the material and geometry. The partial derivatives of the mechanical equilibrium equations with respect to the displacement field are calculated as follows: Therefore, we can know that the partial derivative of the mechanical equilibrium equation with respect to the displacement field is actually the stiffness matrix K, which has already been calculated in the last step of the Newton-Raphson method.

[0206] S612, based on the partial derivatives of the objective function with respect to the displacement field and the partial derivatives of the mechanical equilibrium equations with respect to the displacement field, the adjoint equations are solved using a linear solver to obtain the adjoint variables.

[0207] For example, the adjoint equation describes the relationship between the partial derivatives of the objective function with respect to the displacement field and the partial derivatives of the mechanical equilibrium equations with respect to the displacement field. The adjoint equation can be expressed as follows: Based on the partial derivatives of the objective function with respect to the displacement field and the partial derivatives of the mechanical equilibrium equation with respect to the displacement field obtained in the previous step, the adjoint equation is solved by a linear solver (such as the conjugate gradient method or the direct solution method) to obtain the adjoint variable λ.

[0208] S613, Calculate the partial derivatives of the mechanical equilibrium equations with respect to the design variable vectors, based on the design variable vectors.

[0209] For example, the design variables can be differentiated from the mechanical equilibrium equations, and the chain rule can also be used, i.e. Transform it: .

[0210] Based on the formula K×U= The partial derivatives of the mechanical equilibrium equations with respect to the design variable vector can be expressed as: The chain rule can be used to... Written as Since the stiffness matrix K, displacement field U, and design variables are known, the partial derivatives of the mechanical equilibrium equations with respect to the design variable vector can be calculated using this formula.

[0211] S614, calculate the gradient vector of the objective function with respect to the design variable vector based on the partial derivatives of the accompanying variables and the mechanical equilibrium equations with respect to the design variable vector.

[0212] For example, it can be , Substitution In the middle, we get Since the objective function J, design variable Xi, adjoint variable λ, and partial derivatives of the mechanical equilibrium equations with respect to the design variable vector are known, the gradient vector of the objective function with respect to the design variable vector can be calculated using this formula.

[0213] S620 constructs the search direction using an optimization algorithm based on the gradient vector.

[0214] For example, it can be based on the gradient vector An optimization algorithm is used to construct the search direction. This algorithm can be gradient descent, quasi-Newton methods, conjugate gradient methods, etc. In gradient descent, the search direction is opposite to the gradient vector direction, i.e., d = - , where d represents the search direction.

[0215] S630 determines the step size using a line search method based on the search direction and objective function.

[0216] Line search can be understood as optimizing the objective function to find the optimal step size α that decreases the objective function's value. Line search methods can include fixed step size methods and backtracking line search methods. Backtracking line search methods are based on the Armijo condition, ensuring that the objective function decreases with each step size selection.

[0217] For example, initialize the step size α (a large initial step size can be set, such as 1.0), calculate the new design variable Xi+αd, and calculate the objective function value. If the objective function value satisfies the Armijo condition, then accept the step size α; otherwise, decrease the step size and recalculate the design variable and objective function value. The Armijo condition is... , where β is a constant (ranging from 0 to 1) and represents the maximum descent percentage that the step size can accept.

[0218] S640 calculates the temporary update vector based on the step size, search direction, and design variable vector.

[0219] For example, after determining the step size α, a temporary update vector can be calculated, which is the amount of update of the design variable in the current search direction: X(i+1)=Xi+αd.

[0220] S650, based on the design constraints, performs boundary projection on the temporary update vector to obtain the updated design variable vector. The design constraints include the range of values ​​for the needle valve cone angle, seat width, micro-arc radius, Fourier coefficients, and axial pre-compression.

[0221] For example, the design constraint range can be set manually, and the value range of each design variable can be expressed as Xi∈ For example, the range of the needle valve cone angle is X1∈[60°,120°], the range of the seat width is X2∈[10μm,50μm], the range of the micro-arc radius is X3∈[0.5mm,5.0mm], the range of the first cosine and sine coefficients of the Fourier series is X4, X5∈[-0.01,0.01], the range of the second cosine and sine coefficients of the Fourier series is X6, X7∈[-0.005,0.005], and the range of the axial precompression is X8∈[0mm,0.01mm].

[0222] Since the design variables are constrained, the temporary update vector can be subjected to boundary projection, that is, the design variables that exceed the allowable range are clipped to their corresponding upper and lower limits, thereby obtaining design variables that satisfy the design constraints: ,in, This represents the updated design variables. The updated design variables are used in the next round of optimization iterations until the convergence condition is met.

[0223] The above steps enable the calculation of the gradient of the objective function and optimization of the design variable vector, gradually adjusting the design to approximate the target performance while ensuring that the design variables remain within legal constraints, thus facilitating the final design to meet the predetermined performance indicators.

[0224] S700 consists of iterative model generation steps, finite element analysis steps, performance index calculation steps, convergence judgment steps, and design variable vector update steps, until the convergence condition is met.

[0225] For example, by iterating through the model generation step, finite element analysis step, performance index calculation step, convergence judgment step, and design variable vector update step until any of the convergence conditions are met, the design can continuously approach the optimal solution, ultimately satisfying the design goals and performance requirements, and obtaining the optimal design.

[0226] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0227] Corresponding to the coupling design method of injector needle valve cone angle and seat surface stress described in the above embodiments, this application embodiment also provides an electronic device. The electronic device of this embodiment includes: at least one processor, at least one memory, and a computer program stored in the at least one memory and executable on the at least one processor. When the processor executes the computer program, the electronic device implements the steps in any of the above embodiments of the coupling design method of injector needle valve cone angle and seat surface stress.

[0228] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0229] The electronic device can be a desktop computer, laptop, handheld computer, or other computing device. This electronic device is not limited to processors and memory; it may also include input / output devices, network access devices, buses, etc.

[0230] The processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0231] In some embodiments, the memory may be an internal storage unit of the electronic device, such as a hard drive or RAM. In other embodiments, the memory may be an external storage device of the electronic device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory may include both internal and external storage units. The memory is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory can also be used to temporarily store data that has been output or will be output.

[0232] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0233] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A coupling design method for the cone angle of a fuel injector needle valve and the stress on the seat surface, characterized in that, include: Acquisition Steps: Acquire the design variable vector and the target performance vector; wherein, the design variable vector includes the needle valve cone angle, seat width, micro-arc radius, Fourier coefficient, and axial pre-compression amount, the Fourier coefficient is used to generate a non-axisymmetric small geometric correction amount in the circumferential direction of the needle valve, the axial pre-compression amount is used to adjust the axial relative position of the needle valve and the valve seat, and the target performance vector includes the target contact pressure non-uniformity between the needle valve and the valve seat, the target maximum contact pressure, the target contact continuity, the target leakage rate, and the target fatigue safety factor; Model generation steps: Generate a geometric model based on the design variable vector; Finite element analysis steps: Perform thermal analysis and thermo-mechanical coupling analysis on the geometric model to obtain analysis results; wherein, the analysis results include displacement field, stress field and contact pressure field; Performance index calculation steps: Based on the analysis results, calculate the performance index of the geometric model; wherein, the performance index includes simulated contact pressure non-uniformity, simulated maximum contact pressure, simulated contact continuity, simulated leakage rate, and simulated fatigue safety factor; Convergence determination step: Based on the performance index and the target performance vector, determine whether the convergence condition is met. If the convergence condition is met, determine the geometric model as the final design model. The convergence condition includes that the absolute value of the difference between the performance index and the target performance vector is less than or equal to the performance threshold. Design variable vector update steps: If the convergence condition is not met, update the design variable vector based on the performance index and the target performance vector; The process includes iterative model generation, finite element analysis, performance index calculation, convergence judgment, and design variable vector update, until the convergence condition is met.

2. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 1, characterized in that, The generation of the geometric model based on the design variable vector includes: Based on the needle valve cone angle and seat width, a reference geometry is constructed; wherein, the reference geometry is an axisymmetric geometry, and the reference geometry includes a reference conical surface, a needle valve body cylindrical surface, and a valve seat geometry; The correction amount is calculated based on the Fourier coefficients and the radius correction function in the circumferential direction, and the reference conical surface is non-axisymmetrically corrected according to the correction amount to obtain a sealed conical surface; wherein, the Fourier coefficients include first-order cosine coefficients, first-order sine coefficients, second-order cosine coefficients and second-order sine coefficients. Based on the micro-arc radius, the junction edge between the sealing cone surface and the cylindrical surface of the needle valve body is rounded to obtain a rounded surface; The sealing conical surface, the cylindrical surface of the needle valve body, and the rounded surface are stitched together to obtain the needle valve geometry; Based on the axial pre-compression amount, adjust the axial position of the needle valve geometry relative to the valve seat geometry, and assemble the needle valve geometry and the valve seat geometry to obtain a geometric model.

3. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 1, characterized in that, The thermal analysis and thermo-mechanical coupling analysis of the geometric model are performed to obtain the analysis results, including: Based on thermal boundary conditions, thermal analysis is performed on the geometric model to obtain the temperature field; wherein, the thermal boundary conditions include convective boundary conditions, contact thermal resistance boundary conditions, and adiabatic boundary conditions. Based on the mechanical boundary conditions and the temperature field, a thermo-mechanical coupling analysis is performed on the geometric model to obtain the analysis results; wherein, the mechanical boundary conditions include constraint conditions and load conditions.

4. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 3, characterized in that, The thermal analysis of the geometric model based on thermal boundary conditions to obtain the temperature field includes: Based on the temperature field and thermal boundary conditions from the previous iteration, the heat conduction equation is solved on the geometric model using the implicit time integration method to obtain the temperature field; wherein the initial value of the temperature field is the ambient temperature.

5. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 3, characterized in that, The geometric model is subjected to thermo-mechanical coupling analysis based on the mechanical boundary conditions and the temperature field to obtain the analysis results, including: Calculate the thermal strain field based on the temperature field. Based on the thermal strain field and the mechanical boundary conditions, the mechanical equilibrium equations of the geometric model are solved using the Newton-Raphson method to obtain the displacement field. Based on the displacement field, the total strain is calculated using the displacement gradient; based on the total strain and the thermal strain field, the mechanical strain field is calculated; based on the material constitutive relation and the mechanical strain field, the stress field is calculated. Based on the displacement field and the contact surface between the needle valve geometry and the valve seat geometry in the geometric model, the contact pressure field is calculated using the augmented Lagrange method.

6. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 2, characterized in that, The calculation of the performance indicators of the geometric model based on the analysis results includes: The contact pressure of all sampling points is extracted from the contact pressure field, the average value of the contact pressure of all sampling points is calculated, and the standard deviation of the contact pressure of all sampling points is calculated based on the average value; the ratio between the standard deviation and the average value is calculated to obtain the simulated contact pressure non-uniformity; wherein, the sampling point is a point on the circumferential direction of the sealing strip, and the contact pressure field is the contact pressure field at the moment when the needle valve is closed and completely sealed; The maximum contact pressure is extracted from the contact pressure field as the simulated maximum contact pressure. The number of sampling points with contact pressure greater than the pressure threshold is counted to obtain the number of contact points. The ratio between the number of contact points and the total number of sampling points is calculated to obtain the simulated contact continuity. The simulated leakage rate is calculated based on the displacement field and the contact pressure field; wherein, the displacement field is the displacement field at the moment when the needle valve is closed and completely sealed; The region corresponding to the maximum stress value is searched in the stress field, and the region corresponding to the maximum stress value is determined as the fatigue point; the maximum stress value and minimum stress value of the fatigue point are extracted from the stress field, and the stress amplitude and average stress are calculated based on the maximum stress value and minimum stress value; the simulated fatigue safety factor is calculated based on the stress amplitude, average stress and material fatigue parameters.

7. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 5, characterized in that, The step of updating the design variable vector based on the performance metric and the target performance vector includes: Based on the design variable vector, the performance index, and the target performance vector, the adjoint equation is solved to obtain the gradient vector of the objective function relative to the design variable vector; wherein, the adjoint equation is used to characterize the relationship between the partial derivative of the objective function with respect to the displacement field and the partial derivative of the mechanical equilibrium equation with respect to the displacement field, and the objective function is used to evaluate the degree of deviation of the performance index from the target performance vector; Based on the gradient vector, an optimization algorithm is used to construct the search direction; The step size is determined using a line search method based on the search direction and the objective function. Calculate the temporary update vector based on the step size, the search direction, and the design variable vector; According to the design constraint range, the temporary update vector is subjected to boundary projection operation to obtain the updated design variable vector; wherein, the design constraint range includes the value range of the needle valve cone angle, the value range of the seat width, the value range of the micro-arc radius, the value range of the Fourier coefficient, and the value range of the axial pre-compression.

8. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 7, characterized in that, The step of solving the adjoint equation based on the design variable vector, the performance index, and the target performance vector to obtain the gradient vector of the objective function with respect to the design variable vector includes: Based on the displacement field, the performance index, and the target performance vector, calculate the partial derivative of the objective function with respect to the displacement field, and based on the displacement field, calculate the partial derivative of the mechanical equilibrium equation with respect to the displacement field. Based on the partial derivatives of the objective function with respect to the displacement field and the partial derivatives of the mechanical equilibrium equations with respect to the displacement field, the adjoint equations are solved using a linear solver to obtain the adjoint variables; Calculate the partial derivatives of the mechanical equilibrium equations with respect to the design variable vectors based on the design variable vectors; The gradient vector of the objective function with respect to the design variable vector is calculated based on the partial derivatives of the accompanying variables and the mechanical equilibrium equations with respect to the design variable vector.

9. The coupling design method of injector needle valve cone angle and seat surface stress as described in claim 7, characterized in that, The convergence conditions also include: The relative rate of change between the current objective function value and the objective function value of the previous iteration is less than a first threshold; wherein, the first threshold is a preset threshold for the relative rate of change of the objective function, used to determine whether the improvement of the objective function between two adjacent iterations is less than the preset threshold; The relative rate of change between the current design variable vector and the design variable vector of the previous iteration is less than the second threshold; wherein, the second threshold is a preset threshold for the relative rate of change of the design variable vector, used to determine whether the design variable vector tends to stabilize during the iteration process; The preset number of iterations has been reached.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

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