A physics-driven method for calculating the wheel-rail contact point of rail vehicles

Abstract

The present invention discloses a physically driven method for calculating wheel-rail contact points of rail vehicles, comprising the following steps: obtaining wheel-rail design data, and constructing a discrete expression of a two-dimensional parameterized wheel-rail model based on the wheel-rail design data to obtain discrete wheel-rail geometric coordinate data; collecting the wheel tread wear profile of a turning and repair cycle using a non-contact laser displacement sensor, and obtaining measured wheel-rail profile wear data within different service cycles using a Hausdorff distance method; obtaining vehicle system parameters based on actual service conditions, and obtaining wheel-rail profile evolution simulation data within the service cycle based on the vehicle system parameters using dynamic simulation software; the present invention constructs a wheel-rail contact model based on a unit connection parameterization method, applies a convolution operation operator and a step function method to perform continuous processing of the discrete model, and adopts a moving asymptote method to update the wheel-rail contact connection parameters, thereby achieving continuous optimization and accurate calculation of the wheel-rail contact parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of rail vehicles, and in particular to a physically driven method for calculating wheel-rail contact points of rail vehicles. Background Art

[0002] As rail vehicles develop towards high speed and heavy load, the wheel-rail profile wears seriously during service, and the contact relationship between the wheel and the rail deteriorates accordingly, which in turn causes a series of problems such as wheel vibration, vehicle shaking, fatigue fracture of key components during service, directly affecting the stability, safety and ride comfort of rail vehicles during operation.

[0003] Determining the wheel-rail contact point location is fundamental for subsequent research into wheel-rail contact mechanics calculations, wheel-rail wear physical simulations, and surface optimization design. Possible contact states between the wheel and rail include single-point contact, multi-point contact, and conformal contact. Extensive research has been conducted on single-point and two-point contact theories, but conformal contact remains an unresolved challenge in the wheel-rail contact mechanism. Current wheel-rail contact analysis methods primarily employ dynamic discrete models, making it difficult to establish differential models driven by physical properties. This makes it difficult to achieve continuous optimization and accurate calculation of wheel-rail contact parameters. Summary of the Invention

[0004] The main purpose of the present invention is to provide a physically driven method for calculating the wheel-rail contact points of rail vehicles, aiming to solve the problem that existing wheel-rail contact analysis schemes are difficult to achieve continuous optimization and accurate calculation of wheel-rail contact parameters.

[0005] The technical solution proposed by the present invention is:

[0006] A physically driven method for calculating a rail vehicle wheel-rail contact point comprises:

[0007] Obtain wheel-rail design data, and construct a discrete expression of the wheel-rail two-dimensional parametric model based on the wheel-rail design data to obtain discrete wheel-rail geometric coordinate data;

[0008] The wheel tread wear profile of a turning and repair cycle is collected using a non-contact laser displacement sensor, and the measured wear data of the wheel-rail profile in different service cycles are obtained using the Hausdorff distance method.

[0009] Obtain vehicle system parameters based on actual service conditions, and obtain wheel-rail profile evolution simulation data during the service cycle based on the vehicle system parameters using dynamic simulation software;

[0010] Based on the discrete wheel-rail geometric coordinate data, the measured wheel-rail profile wear data, and the wheel-rail profile evolution simulation data, a discrete wheel-rail contact model based on unit connection parameterization is constructed.

[0011] Based on the discrete wheel-rail contact model, the convolution operator is used to filter the design variables, and the convolution operator and differential step function are introduced to establish a continuous wheel-rail contact optimization model.

[0012] Based on the continuous wheel-rail contact optimization model, the sensitivity analysis method is used to determine the descent relationship between the design variables and the objective function, and the moving asymptote method is used to realize the iterative optimization and updating of the wheel-rail contact parameters.

[0013] Preferably, the continuous wheel-rail contact optimization model adopts a sensitivity analysis method to determine the descent relationship between the design variables and the objective function, and simultaneously adopts a moving asymptote method to achieve iterative optimization and updating of the wheel-rail contact parameters, and then further includes:

[0014] The effectiveness of the continuous wheel-rail contact optimization model is verified based on the measured wheel-rail profile wear data and the wheel-rail profile evolution simulation data.

[0015] Preferably, the step of acquiring wheel-rail design data and constructing a discrete expression of a two-dimensional parametric wheel-rail model according to the wheel-rail design data to obtain discrete wheel-rail geometric coordinate data includes:

[0016] According to the wheel-rail design data, two-dimensional modeling software is used to realize parametric modeling of the wheel-rail profile. Then, the parametric curve is discretized by the discretization method to obtain discrete wheel-rail geometric coordinate data, thereby realizing the discrete expression of the wheel-rail geometric profile.

[0017] Preferably, the method of collecting the wheel tread wear profile of a turning and repairing cycle by a non-contact laser displacement sensor and obtaining the measured wear data of the wheel-rail profile in different service cycles by using the Hausdorff distance method includes:

[0018] A non-contact two-dimensional laser displacement sensor is used to continuously collect data on the surface of the in-service wheel to obtain point cloud data of the measured wheel / rail profile.

[0019] The nearest neighbor point pair matching method is used to adjust the pose of the measured wheel / rail profile to achieve point cloud data registration of the measured wheel / rail profile in different coordinate systems.

[0020] The measured wear data of wheel-rail profiles were calculated using the Hausdorff distance method.

[0021] Preferably, the method of adjusting the pose of the measured wheel / rail profile by using the nearest neighbor point pair matching method to achieve three-dimensional point cloud data registration of the measured wheel / rail profile in different coordinate systems includes:

[0022] Perform registration transformation on the coordinate system where the laser displacement sensor is located and the coordinate system where the standard wheel rail is located. The registration transformation formula is:

[0023]

[0024] Where, the point cloud data of the measured wheel-rail profile is M(m x ,m y ), the point cloud data of the standard wheel and rail profile is N(n x ,n y );

[0025] The registration transformation formula is expressed as a conversion formula based on the rotation transformation matrix R and the translation vector t. The conversion formula is as follows:

[0026]

[0027] The measured wheel-rail profile is transformed into coordinates based on the transformation formula.

[0028] Preferably, the obtaining of vehicle system parameters according to actual service conditions and obtaining wheel-rail profile evolution simulation data within the service cycle based on the vehicle system parameters through dynamic simulation software include:

[0029] Construct a wheel-rail coupled vehicle system dynamics model;

[0030] Calculate the wheel-rail contact geometry parameters during vehicle operation and construct a wheel-rail contact mechanics model to calculate the local contact parameters during service;

[0031] Based on the wheel-rail contact material physics and wheel-rail contact force, a wheel-rail material contact wear model is constructed, and the physical simulation of wheel-rail surface wear during the service process is realized to obtain the simulation data of the wheel-rail profile evolution during the service cycle.

[0032] Preferably, the discrete wheel-rail contact model based on unit connection parameterization is constructed according to the discrete wheel-rail geometric coordinate data, the measured wheel-rail profile wear data and the wheel-rail profile evolution simulation data, including:

[0033] The wheel-rail contact connection parameters are determined by optimizing the wheel-rail wear difference, where the wheel-rail contact connection parameters are expressed as:

[0034] findΩ={ω1,ω2,...,ω n}

[0035] minimize|hv(ω)|2

[0036]

[0037] Where ω represents the wheel-rail contact connection parameter, h is the measured wear data of the wheel-rail profile or the simulated data of the wheel-rail profile evolution, v is the physically driven wheel-rail wear, k is the friction coefficient of the wheel-rail interface, p is the normal contact pressure of the wheel-rail, s is the wheel creep distance, H is the hardness of the softer material at the wheel-rail contact interface, Ω is the wheel-rail connection coefficient, is the set of ω, and i is the subscript index of ω.

[0038] Preferably, the discrete wheel-rail contact model is based on which a convolution operator is used to filter the design variables, and a convolution operator and a differential step function are introduced to establish a continuous wheel-rail contact optimization model, including:

[0039] Make the wheel-rail contact connection parameters continuous;

[0040] The wheel-rail connection parameters are filtered using a convolution operator;

[0041] A differentiable step function is used to project the filtered wheel-rail connection parameters into the integer space of 0-1 to achieve discretization mapping of the connection parameters and obtain a continuous wheel-rail contact optimization model.

[0042] Preferably, the filtering of the wheel-rail connection parameters using a convolution operator includes:

[0043] The wheel-rail contact connection parameters at longer distances are assigned smaller weights, while those at shorter distances are assigned larger weights. The calculation formula is expressed as the following weight function:

[0044]

[0045] Where R e is the radius of the affected area, p i is the coordinate of the contact point to be solved, p e is the coordinate of the contact point in the impact area;

[0046] According to the weight function, the weighted wheel-rail contact connection parameters are constructed, and the calculation formula is expressed as:

[0047]

[0048] Where, is the wheel-rail contact connection parameter after filtering, φ i is the wheel-rail contact connection parameter within the influencing domain;

[0049] The method of using a differentiable step function to project the filtered wheel-rail connection parameters to an integer space of 0-1 to achieve a discretized mapping of the connection parameters to obtain a continuous wheel-rail contact optimization model includes:

[0050] A continuously differentiable step function is introduced to project the filtered wheel-rail connection parameters into the integer space of 0-1. The calculation method is as follows:

[0051]

[0052] Where ω is the wheel-rail contact parameter after projection, and β controls the slope of the projection function;

[0053] Establish a continuous model for wheel-rail contact calculation:

[0054] findΦ={φ1,φ2,...,φ n}

[0055]

[0056]

[0057] Wherein, the wheel-rail contact connection parameter φ is a variable that changes continuously between 0 and 1.

[0058] Preferably, the continuous wheel-rail contact optimization model adopts a sensitivity analysis method to determine the descent relationship between the design variables and the objective function, and simultaneously adopts a moving asymptote method to achieve iterative optimization and updating of the wheel-rail contact parameters, including:

[0059] The chain rule is used to solve the sensitivity of the objective function with respect to the design variables. The calculation formula is as follows:

[0060]

[0061] The following formula can be obtained by derivatizing the filtered wheel-rail connection parameters with respect to the design variables:

[0062]

[0063] The following formula can be obtained by derivatizing the projected wheel-rail connection parameters from the filtered wheel-rail connection parameters:

[0064]

[0065] The derivative of the objective function with respect to the projected wheel-rail connection parameters yields the following chain derivative formula:

[0066]

[0067] According to the sensitivity of the objective function and the design variables obtained by the chain derivation formula, the design variables are iteratively updated using the moving asymptote method until the algorithm converges or reaches the set number of iteration steps.

[0068] The above technical solution can achieve the following beneficial effects:

[0069] The physical-driven rail vehicle wheel-rail contact point calculation method proposed in the present invention constructs a wheel-rail contact model based on the unit connection parameterization method, applies the convolution operation operator and the step function method to carry out continuous processing of the discrete model, and adopts the moving asymptote method to update the wheel-rail contact connection parameters, thereby realizing continuous optimization and accurate calculation of the wheel-rail contact parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0071] Figure 1 This is a flow chart of a first embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention;

[0072] Figure 2 This is a schematic diagram of wheel-rail contact connection calculation of unit connection parameters in the seventh embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention. DETAILED DESCRIPTION

[0073] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0074] The present invention provides a physically driven method for calculating the wheel-rail contact point of a rail vehicle.

[0075] As attached Figure 1 As shown, in a first embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, this embodiment includes the following steps:

[0076] Step S110: obtaining wheel-rail design data, and constructing a discrete expression of the wheel-rail two-dimensional parametric model according to the wheel-rail design data to obtain discrete wheel-rail geometric coordinate data.

[0077] Step S120: The wheel tread wear profile of a turning and repairing cycle is collected by a non-contact laser displacement sensor, and the measured wear data of the wheel-rail profile in different service cycles is obtained by using the Hausdorff distance method.

[0078] Step S130: obtaining vehicle system parameters according to actual service conditions, and obtaining wheel-rail profile evolution simulation data within the service cycle based on the vehicle system parameters through dynamic simulation software.

[0079] Step S140: constructing a discrete wheel-rail contact model based on unit connection parameterization according to the discrete wheel-rail geometric coordinate data, the measured wheel-rail profile wear data and the wheel-rail profile evolution simulation data.

[0080] Step S150: Based on the discrete wheel-rail contact model, a convolution operator is used to filter the design variables, and a convolution operator and a differential step function are introduced to establish a continuous wheel-rail contact optimization model.

[0081] Step S160: Based on the continuous wheel-rail contact optimization model, a sensitivity analysis method is used to determine the descent relationship between the design variables and the objective function, and a moving asymptote method is used to iteratively optimize and update the wheel-rail contact parameters.

[0082] The physical-driven rail vehicle wheel-rail contact point calculation method proposed in the present invention constructs a wheel-rail contact model based on the unit connection parameterization method, applies the convolution operation operator and the step function method to carry out continuous processing of the discrete model, and adopts the moving asymptote method to update the wheel-rail contact connection parameters, thereby realizing continuous optimization and accurate calculation of the wheel-rail contact parameters.

[0083] In a second embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the first embodiment, step S160 further includes the following steps:

[0084] Step S210: Verify the effectiveness of the continuous wheel-rail contact optimization model based on the measured wheel-rail profile wear data and the wheel-rail profile evolution simulation data.

[0085] Specifically, the algorithm is implemented using the MATLAB platform, and the measured wheel-rail profile wear data and the wheel-rail profile evolution simulation data are used to calculate whether the calculation results meet the expected goals. In addition, according to the objective function and the convergence characteristics of the wheel-rail contact parameters, the wheel-rail contact connection parameter optimization step size and the contact parameter filtering radius can be adjusted to achieve efficient calculation of the wheel-rail contact parameters.

[0086] In a third embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the first embodiment, step S110 includes the following steps:

[0087] Step S310: Based on the wheel / rail design data, two-dimensional modeling software (or three-dimensional modeling software) is used to implement parametric modeling of the wheel / rail profile. The parameterized curve is then discretized using a discretization method to obtain discrete wheel / rail geometric coordinate data, thereby achieving a discrete expression of the wheel / rail geometric profile.

[0088] In a fourth embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the second embodiment, step S120 includes the following steps:

[0089] Step S410: Continuously collect data on the surface of the in-service wheel using a non-contact two-dimensional laser displacement sensor to obtain point cloud data of the measured wheel / rail profile.

[0090] Step S420: The pose of the measured wheel / rail profile is adjusted using a nearest neighbor point pair matching method to achieve point cloud data registration of the measured wheel / rail profile in different coordinate systems.

[0091] Step S430: Calculate the measured wheel-rail profile wear data using the Hausdorff distance method.

[0092] Specifically, the measured wheel-rail profile wear data herein refers to the measured wear amount at each position of the wheel-rail profile.

[0093] In a fifth embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the fourth embodiment, step S420 includes the following steps:

[0094] Step S510: Perform registration transformation on the coordinate system where the laser displacement sensor is located and the coordinate system where the standard wheel rail is located. The registration transformation formula is:

[0095]

[0096] Where, the point cloud data of the measured wheel-rail profile is M(m x ,m y ), the point cloud data of the standard wheel and rail profile is N(n x ,n y ).

[0097] Specifically, since the coordinate system of the laser displacement sensor that collects vehicle profile data is inconsistent with the coordinate system of the standard wheel rail, there is a relative rotation and translation relationship between the coordinate systems, so a registration transformation is required.

[0098] Step S520: The registration transformation formula is expressed as a conversion formula based on the rotation transformation matrix R and the translation vector t. The conversion formula is as follows:

[0099]

[0100] Step S530: performing coordinate transformation on the measured wheel-rail profile based on the transformation formula.

[0101] Specifically, the rotation transformation matrix is highly nonlinear in actual solution, so a linearization method is often used instead. Here, the first term is retained according to Taylor expansion, that is, cosα=1, sinα=α, where α is the rotation angle.

[0102] In a sixth embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the first embodiment, step S130 includes the following steps:

[0103] Step S610: constructing a wheel-rail coupled vehicle system dynamics model according to vehicle system dynamics software.

[0104] Specifically, the vehicle system dynamics model constructed in this embodiment includes: 1 frame, 2 wheel sets, 4 axle boxes, a total of 7 rigid bodies, and the established model includes a primary suspension.

[0105] Step S620: Calculate the wheel-rail contact geometric parameters (such as contact points, creep rate, etc.) during vehicle operation, and construct a wheel-rail contact mechanical model to calculate the local contact parameters (such as wheel-rail normal contact force and creep force, etc.) during service.

[0106] The wheel-rail contact mechanics model includes a wheel-rail normal pressure calculation model and a creep force calculation model. The wheel-rail normal pressure calculation model adopts the Kalker simplified theoretical model, which is expressed as:

[0107]

[0108] Where x is the longitudinal coordinate of the wheel-rail contact spot, y is the transverse coordinate of the wheel-rail contact spot, a and b are the semi-axis values of the elliptical contact spot, and p is the wheel-rail normal force.

[0109] The creep force calculation model adopts Kalker simplified theory Fastsim algorithm, which is expressed as:

[0110]

[0111] Where Δp x (x,y) is the tangential stress increment along the longitudinal direction, Δp y (x, y) is the tangential stress increment along the transverse direction, specifically expressed as:

[0112]

[0113] Where, ξ x is the longitudinal creep rate, ξ y is the lateral creep rate, ξ z is the spin creep rate, which is determined by the vehicle system dynamics model, and L is the tangential flexibility coefficient (here L includes L x and L y , L x is the flexibility coefficient in the x direction, L y is the flexibility coefficient in the y direction), which is determined by the table lookup method.

[0114] The tangential force p at (x,y) in the contact patch τ It can be expressed as:

[0115]

[0116] Step S630: Based on the physical properties of the wheel-rail contact material (e.g., material hardness, friction coefficient, etc.) and the wheel-rail contact force, a wheel-rail material contact wear model is constructed to perform a physical simulation of the wheel-rail service process surface wear to obtain simulation data on the wheel-rail profile evolution during the service cycle.

[0117] Among them, the USFD wheel wear model is used to build the wheel-rail material contact wear model. Based on the relationship between the wear energy dissipation of the contact spot and the material wear amount, the material wear rate expression is as follows:

[0118]

[0119] Where K w is the material wear rate, I w is the friction work within the contact patch, which can be expressed as follows:

[0120] I w (x,y)=p τ (x,y)·γ(x,y),

[0121] Where p τ is the tangential stress in the contact patch, γ is the sliding distance of the contact patch unit (x, y), and the wheel wear is specifically expressed as:

[0122]

[0123] Where W is wheel wear, R is the nominal rolling circle radius of the wheel, ρ is the material density, Δx is the contact patch grid length, and v is the vehicle speed.

[0124] In the seventh embodiment of the physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the first embodiment, step S140 includes the following steps:

[0125] Step S710: Determine the wheel-rail contact connection parameters by optimizing the wheel-rail wear difference, wherein the wheel-rail contact connection parameters are expressed as:

[0126] findΩ={ω1,ω2,...,ω n}

[0127] minimize|hv(ω)|2

[0128]

[0129] Where ω represents the wheel-rail contact connection parameter, h is the measured wear data of the wheel-rail profile or the simulated data of the wheel-rail profile evolution, v is the physically driven wheel-rail wear, k is the friction coefficient of the wheel-rail interface, p is the normal contact pressure of the wheel-rail, s is the wheel creep distance, H is the hardness of the softer material at the wheel-rail contact interface, Ω is the wheel-rail connection coefficient, is the set of ω, and i is the subscript index of ω.

[0130] Specifically, attached Figure 2 Schematic diagram of wheel-rail contact connection calculation for unit connection parameters, where green represents potential wheel-rail contact connection point pairs, assigned a value of 1, and red represents virtual wheel-rail contact connection point pairs, assigned a value of 0.

[0131] In the eighth embodiment of the physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the first embodiment, step S150 includes the following steps:

[0132] Step S810: Continuizing the wheel-rail contact connection parameters.

[0133] Step S820: Using a convolution operator to filter the wheel-rail connection parameters to improve the calculation stability of the model.

[0134] Step S830: Projecting the filtered wheel-rail connection parameters to the integer space of 0-1 using a differentiable step function to achieve discretization mapping of the connection parameters to obtain a continuous wheel-rail contact optimization model.

[0135] Specifically, the discrete wheel-rail contact model based on unit connection parameterization established in step S140 is an integer programming problem, and its solution process is complex, and it is impossible to use a gradient operator for continuous optimization. Therefore, it is necessary to implement a discretized mapping of the connection parameters through the solution of this embodiment to obtain a continuous wheel-rail contact optimization model.

[0136] In a ninth embodiment of a physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the eighth embodiment, step S820 includes the following steps:

[0137] Specifically, the wheel-rail connection parameter filtering mainly considers the influence of the nearby connection parameters on it, that is, the influence of each connection parameter p within the radius R e For the current wheel-rail connection parameter p i The role of calculation; here the influence of connection parameters at different positions is considered, that is, different weights are applied to different connection parameters.

[0138] Step S910: Assign smaller weights to wheel-rail contact connection parameters at longer distances, and assign larger weights to wheel-rail contact connection parameters at shorter distances. The calculation formula is expressed as the following weight function:

[0139]

[0140] Where R e is the radius of the affected area, p i is the coordinate of the contact point i to be solved, p e is the coordinate of the contact point e in the influence area;

[0141] Step S920: construct weighted wheel-rail contact connection parameters according to the weight function. The calculation formula is expressed as:

[0142]

[0143] Where, is the wheel-rail contact connection parameter after filtering, φ i is the wheel-rail contact connection parameter in the influence domain, α i,e is the weight of the connection coefficient of contact point e in the influencing area on the connection coefficient of contact point i.

[0144] Step S830 includes the following steps:

[0145] Step S930: Introduce a continuously differentiable step function to project the filtered wheel-rail connection parameters to the integer space of 0-1. The calculation method is as follows:

[0146]

[0147] Where ω is the projected wheel-rail contact parameter, and β controls the slope of the projection function. As β increases, the projection effect of the wheel-rail contact parameter toward 0-1 becomes more obvious. When β approaches infinity, the wheel-rail contact parameter exhibits a strict 0-1 step property. Therefore, in actual projection calculations, a smaller β value is usually used, and then the β value is gradually increased to improve its convergence characteristics.

[0148] Specifically, the use of design variable filtering can improve the stability of the numerical solution, but the solved contact parameters are mostly in the 0-1 continuous space, which does not conform to the physical laws of wheel-rail contact. Therefore, it is necessary to project the wheel-rail contact parameters in the continuous space into the discrete 0-1 space. To meet the continuity requirements of the numerical calculation, a continuously differentiable step function is introduced to project the filtered wheel-rail connection parameters into the 0-1 integer space.

[0149] Step S940: Establishing a continuous model for wheel-rail contact calculation:

[0150] findΦ={φ1,φ2,...,φ n}

[0151]

[0152]

[0153] In the formula, the wheel-rail contact connection parameter φ is a variable that changes continuously between 0 and 1. In this way, the discrete integer programming problem constructed in step S140 is converted into a continuous optimization problem, which can be solved by continuous iterative optimization using a gradient method, such as the moving asymptote method.

[0154] In the tenth embodiment of the physically driven rail vehicle wheel-rail contact point calculation method proposed by the present invention, based on the first embodiment, step S160 includes the following steps:

[0155] Step S1010: Use the chain rule to solve and obtain the sensitivity of the objective function with respect to the design variables. The calculation formula is as follows:

[0156]

[0157] Specifically, to solve continuous optimization problems using gradient methods, we need to determine the sensitivity of the objective function with respect to the design variables. Since solving the sensitivity of the objective function is a composite function differentiation problem, we use the chain rule to solve it.

[0158] Step S1020: Derivatives of the filtered wheel-rail connection parameters with respect to the design variables yield the following formula:

[0159]

[0160] Step S1030: The projected wheel-rail connection parameter is derivatized from the filtered wheel-rail connection parameter to obtain the following formula:

[0161]

[0162] Step S1040: The objective function is derived from the projected wheel-rail connection parameters to obtain the following chain derivation formula:

[0163]

[0164] Step S1050: Based on the objective function obtained from the chain derivation formula and the sensitivity of the design variables, the design variables are iteratively updated using the moving asymptote method until the algorithm converges or reaches a set number of iteration steps (e.g., 200 steps).

[0165] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0166] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0167] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are protected by the present invention.

Claims

1. A physically driven method for calculating the wheel-rail contact point of a railway vehicle, characterized in that: include: Obtain wheel-rail design data, and construct a discrete expression of the wheel-rail two-dimensional parametric model based on the wheel-rail design data to obtain discrete wheel-rail geometric coordinate data; The wheel tread wear profile of a turning and repair cycle is collected using a non-contact laser displacement sensor, and the measured wear data of the wheel-rail profile in different service cycles are obtained using the Hausdorff distance method. Obtain vehicle system parameters based on actual service conditions, and obtain wheel-rail profile evolution simulation data during the service cycle based on the vehicle system parameters using dynamic simulation software; Based on the discrete wheel-rail geometric coordinate data, the measured wheel-rail profile wear data, and the wheel-rail profile evolution simulation data, a discrete wheel-rail contact model based on unit connection parameterization is constructed. Based on the discrete wheel-rail contact model, the convolution operator is used to filter the design variables, and the convolution operator and differential step function are introduced to establish a continuous wheel-rail contact optimization model. Based on the continuous wheel-rail contact optimization model, the sensitivity analysis method is used to determine the descent relationship between the design variables and the objective function, and the moving asymptote method is used to iteratively optimize and update the wheel-rail contact parameters. The discrete wheel-rail contact model based on unit connection parameterization is constructed according to the discrete wheel-rail geometric coordinate data, the measured wheel-rail profile wear data and the wheel-rail profile evolution simulation data, including: The wheel-rail contact connection parameters are determined by optimizing the wheel-rail wear difference, where the wheel-rail contact connection parameters are expressed as: ， Where, represents the wheel-rail contact connection parameters, h is the measured wear data of the wheel-rail profile or the simulated data of the wheel-rail profile evolution, v is the wheel-rail wear driven by physics, k is the friction coefficient of the wheel-rail interface, p is the normal contact pressure of the wheel-rail, s is the wheel creep distance, H is the hardness of the softer material of the wheel-rail contact interface, Ω is the wheel-rail connection coefficient, and is The set of i is The subscript index of .

2. The method for calculating the wheel-rail contact point of a physically driven railway vehicle according to claim 1, characterized in that: The continuous wheel-rail contact optimization model is based on a sensitivity analysis method to determine the descent relationship between the design variables and the objective function, and a moving asymptote method is used to achieve iterative optimization and updating of the wheel-rail contact parameters. The following also includes: The effectiveness of the continuous wheel-rail contact optimization model is verified based on the measured wheel-rail profile wear data and the wheel-rail profile evolution simulation data.

3. The physical driven rail vehicle wheel-rail contact point calculation method according to claim 1, characterized in that: The step of obtaining wheel-rail design data and constructing a discrete expression of a two-dimensional parametric wheel-rail model based on the wheel-rail design data to obtain discrete wheel-rail geometric coordinate data includes: According to the wheel-rail design data, two-dimensional modeling software is used to realize parametric modeling of the wheel-rail profile. Then, the parametric curve is discretized by the discretization method to obtain discrete wheel-rail geometric coordinate data, thereby realizing the discrete expression of the wheel-rail geometric profile.

4. The method for calculating wheel-rail contact points of a physically driven railway vehicle according to claim 2, characterized in that: The wheel tread wear profile of a turning and repair cycle is collected by a non-contact laser displacement sensor, and the measured wear data of the wheel-rail profile in different service cycles is obtained by using the Hausdorff distance method, including: A non-contact two-dimensional laser displacement sensor is used to continuously collect data on the surface of the in-service wheel to obtain point cloud data of the measured wheel / rail profile. The nearest neighbor point pair matching method is used to adjust the pose of the measured wheel / rail profile to achieve point cloud data registration of the measured wheel / rail profile in different coordinate systems. The measured wear data of wheel-rail profiles were calculated using the Hausdorff distance method.

5. The method for calculating the wheel-rail contact point of a physically driven railway vehicle according to claim 4, characterized in that: The method of adjusting the pose of the measured wheel / rail profile by using the nearest neighbor point pair matching method to achieve three-dimensional point cloud data registration of the measured wheel / rail profile in different coordinate systems includes: Perform registration transformation on the coordinate system where the laser displacement sensor is located and the coordinate system where the standard wheel rail is located. The registration transformation formula is: ， In the formula, the point cloud data of the measured wheel-rail profile is , the point cloud data of the standard wheel and rail profile is ; Based on the rotation transformation matrix and translation vector The registration transformation formula is expressed as a conversion formula, which is as follows: ， The measured wheel-rail profile is transformed into coordinates based on the transformation formula.

6. The method for calculating wheel-rail contact points of a physically driven railway vehicle according to claim 1, characterized in that: The method of obtaining vehicle system parameters according to actual service conditions and obtaining wheel-rail profile evolution simulation data within the service cycle through dynamic simulation software based on the vehicle system parameters includes: Construct a wheel-rail coupled vehicle system dynamics model; Calculate the wheel-rail contact geometry parameters during vehicle operation and construct a wheel-rail contact mechanics model to calculate the local contact parameters during service; Based on the physical properties of the wheel-rail contact material and the wheel-rail contact force, a wheel-rail material contact wear model is constructed, and physical simulation of wheel-rail surface wear during the service process is realized to obtain simulation data of the wheel-rail profile evolution during the service cycle.

7. The method for calculating wheel-rail contact points of a physically driven railway vehicle according to claim 1, characterized in that: The method is based on a discrete wheel-rail contact model, uses a convolution operator to filter design variables, and introduces a convolution operator and a differential step function to establish a continuous wheel-rail contact optimization model, including: Make the wheel-rail contact connection parameters continuous; The wheel-rail connection parameters are filtered using a convolution operator; A differentiable step function is used to project the filtered wheel-rail connection parameters into the integer space of 0-1 to achieve discretization mapping of the connection parameters and obtain a continuous wheel-rail contact optimization model.

8. The method for calculating the wheel-rail contact point of a physically driven railway vehicle according to claim 7, characterized in that: The use of a convolution operator to filter the wheel-rail connection parameters includes: The wheel-rail contact connection parameters at longer distances are assigned smaller weights, while those at shorter distances are assigned larger weights. The calculation formula is expressed as the following weight function: ， Where, R e is the radius of the affected area, is the coordinate of the contact point to be solved, is the coordinate of the contact point in the impact area; According to the weight function, the weighted wheel-rail contact connection parameters are constructed, and the calculation formula is expressed as: ， Where, is the wheel-rail contact connection parameter after filtering, is the wheel-rail contact connection parameter within the influencing domain; The method of using a differentiable step function to project the filtered wheel-rail connection parameters to an integer space of 0-1 to achieve a discretized mapping of the connection parameters to obtain a continuous wheel-rail contact optimization model includes: A continuously differentiable step function is introduced to project the filtered wheel-rail connection parameters into the integer space of 0-1. The calculation method is as follows: ， Where, is the wheel-rail contact parameter after projection, Control the slope of the projection function; Establish a continuous model for wheel-rail contact calculation: ， Where, wheel-rail contact connection parameter It is a variable that changes continuously between 0 and 1.

9. The method for calculating the wheel-rail contact point of a physically driven railway vehicle according to claim 8, characterized in that: The continuous wheel-rail contact optimization model adopts a sensitivity analysis method to determine the descent relationship between design variables and objective functions, and simultaneously adopts a moving asymptote method to achieve iterative optimization and updating of wheel-rail contact parameters, including: The chain rule is used to solve the sensitivity of the objective function with respect to the design variables. The calculation formula is as follows: ， The following formula can be obtained by derivatizing the filtered wheel-rail connection parameters with respect to the design variables: ， The following formula can be obtained by derivatizing the projected wheel-rail connection parameters from the filtered wheel-rail connection parameters: ， The derivative of the objective function with respect to the projected wheel-rail connection parameters yields the following chain derivative formula: ， According to the sensitivity of the objective function and the design variables obtained by the chain derivation formula, the design variables are iteratively updated using the moving asymptote method until the algorithm converges or reaches the set number of iteration steps.

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