Method and system for evaluating adhesion state between wheel rails of vehicle

Abstract

The invention relates to a method and system for evaluating the adhesion state between vehicle wheel rails, and the method comprises the steps: setting weight information corresponding to at least one type of influence factors and a plurality of corresponding judgment value intervals under various road conditions, and constructing a corresponding membership function according to the judgment value intervals corresponding to the influence factors; when it is monitored that the vehicle axle slides for the first time, real-time numerical values of at least one type of influence factors are obtained, the real-time numerical values of the at least one type of influence factors are substituted into the corresponding membership functions, weighted summation calculation is conducted on the real-time numerical values and the corresponding weight information, and road condition indexes are obtained; and setting a plurality of road condition numerical value intervals according to the adhesion degree between the wheel rails, and judging that the road condition indexes are in at least one road condition numerical value interval to obtain the current adhesion state between the wheel rails. According to the method and the device, the problem that the capability of monitoring the adhesion state between the wheel rails in real time is low is solved, and the capability of monitoring the adhesion state between the wheel rails in real time in the vehicle running process is improved.

Description

Technical Field

[0001] The present application relates to the field of rail transit vehicles, and in particular to a method and system for evaluating the adhesion state between vehicle wheels and rails. Background Art

[0002] During rail transit, vehicle control systems rely on adhesion to achieve traction or braking. Once maximum adhesion between the wheel and rail is achieved, further increasing the driving or braking force causes relative slip between the wheel and rail, disrupting adhesion and resulting in both rolling and sliding between the wheel and rail. This can cause the wheel to spin or slide, both of which can damage the wheel and rail surface.

[0003] Existing technologies typically use factors such as locomotive speed, creep speed, and wheel flange acceleration as a basis for sanding control, determining whether to sand the track and adjusting the amount of sand applied, thereby adjusting the adhesion between the wheel and rail. However, sanding is only a remedial measure after abnormal adhesion occurs, and there is no method that can monitor the adhesion status between the wheel and rail in real time. Summary of the Invention

[0004] The embodiments of the present application provide a method and system for evaluating the adhesion state between a vehicle wheel and rail, so as to at least solve the problem of low monitoring capability of the adhesion state between the wheel and rail in the related art.

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating the adhesion state between a vehicle wheel and rail, comprising:

[0006] The step of constructing a membership function includes setting a plurality of judgment value intervals corresponding to at least one type of influencing factor under a plurality of road conditions, and constructing a membership function corresponding to the at least one type of influencing factor based on the plurality of judgment value intervals; the influencing factor is a factor that affects the adhesion state of the wheel-rail contact interface;

[0007] Obtaining road condition index: setting weight information corresponding to each influencing factor, obtaining the real-time value of at least one type of influencing factor when the vehicle axle is detected to slip for the first time, substituting the real-time value of each influencing factor into the corresponding membership function to obtain an evaluation matrix, and performing a weighted sum calculation on the evaluation matrix and the weight information corresponding to each influencing factor to obtain the road condition index;

[0008] Adhesion state determination step: setting a plurality of road condition value intervals according to the degree of adhesion between the wheel and the rail, determining that the road condition index is within at least one road condition value interval, and obtaining the current wheel-rail adhesion state.

[0009] In some embodiments, in the membership function corresponding to each influencing factor, multiple membership degrees are set, and the membership degrees correspond one-to-one to the judgment value intervals; wherein, in the membership function corresponding to an influencing factor, each membership degree corresponds to a unique judgment value interval.

[0010] In some embodiments, for any influencing factor, the real-time value of the influencing factor is substituted into the corresponding membership function, and multiple single factor evaluation values are calculated based on the membership degree and the judgment value interval;

[0011] Integrate the multiple single factor evaluation values corresponding to each influencing factor to form an evaluation matrix;

[0012] The weight information corresponding to multiple influencing factors is formed into a weight set, and the weight set and the evaluation matrix are weighted and summed to obtain the road condition index.

[0013] In some embodiments, the influencing factor includes vehicle deceleration. The current time and current vehicle speed are periodically recorded, and the ratio of the difference between the current vehicle speeds at two adjacent time points and the difference between the current vehicle speeds at two adjacent time points is calculated to obtain the vehicle deceleration. The membership function corresponding to the vehicle deceleration is: Among them, x1 is the real-time value of the vehicle deceleration during the vehicle driving process.

[0014] In some embodiments, the influencing factor includes a speed difference. The vehicle speed and the axle speed at the same moment are obtained, and the difference between the vehicle speed and the axle speed is calculated to obtain the speed difference. The membership function corresponding to the speed difference is: x3 is the real-time value of the speed difference during vehicle driving.

[0015] In some embodiments, the influencing factors include the number of sliding axles. The number of vehicle axles in a sliding state at a moment is obtained to obtain the number of sliding axles. The membership function corresponding to the number of sliding axles is: Among them, x4 is the real-time value of the number of sliding axes during vehicle driving.

[0016] In some embodiments, the influencing factors include the coasting duration, and the moment when the vehicle axle starts to coast, any moment when the vehicle axle is still in the coasting state, and / or the moment when the vehicle axle leaves the coasting state are obtained. If the vehicle axle is still in the coasting state, the duration from the moment when the vehicle axle starts to coast to the moment when the vehicle axle is in the coasting state is the coasting duration; if the vehicle axle is not in the coasting state, the duration from the moment when the vehicle axle starts to coast to the moment when the vehicle axle leaves the coasting state is the coasting duration; the membership function corresponding to the coasting duration is: Among them, x2 is the real-time value of the coasting time during driving.

[0017] In a second aspect, an embodiment of the present application provides a vehicle wheel-rail adhesion state assessment system, comprising:

[0018] a membership function construction module configured to set multiple judgment value intervals corresponding to at least one type of influencing factor under multiple road conditions, and construct a membership function corresponding to the at least one type of influencing factor based on the multiple judgment value intervals; the influencing factor is a factor that affects the adhesion state of the wheel-rail contact interface;

[0019] A road condition index acquisition module is configured to set weight information corresponding to each influencing factor, obtain a real-time value of at least one type of influencing factor when the vehicle axle first slips, substitute the real-time value of each influencing factor into the corresponding membership function to obtain an evaluation matrix, and perform a weighted sum calculation on the evaluation matrix and the weight information corresponding to each influencing factor to obtain a road condition index;

[0020] The adhesion state determination module is configured to set a plurality of road condition value intervals according to the adhesion degree between the wheel and rail, determine that the road condition index is within at least one road condition value interval, and obtain the current adhesion state between the wheel and rail.

[0021] In some embodiments, the membership function construction module is further configured to set multiple membership degrees in the membership function corresponding to each influencing factor, and the membership degrees correspond one-to-one to the judgment numerical intervals; wherein, in the membership function corresponding to an influencing factor, each membership degree corresponds to a unique judgment numerical interval.

[0022] In some embodiments, the road condition index acquisition module is further configured to, for any influencing factor, substitute the real-time value of the influencing factor into the corresponding membership function, and calculate multiple single factor evaluation values based on the membership degree and the judgment value interval;

[0023] Integrate the multiple single factor evaluation values corresponding to each influencing factor to form an evaluation matrix;

[0024] The weight information corresponding to multiple influencing factors is formed into a weight set, and the weight set and the evaluation matrix are weighted and summed to obtain the road condition index.

[0025] Compared with related technologies, the embodiments of the present application provide a method and system for evaluating the adhesion state between a vehicle and a rail. By integrating various types of influencing factors, using membership functions and weighted summation methods, and utilizing fuzzy mathematical models for calculation, comprehensive and objective road condition values are obtained, thereby obtaining the real-time adhesion state between the wheel and the rail. This solves the problem of low monitoring capability of the adhesion state between the wheel and the rail, and enables real-time monitoring of the adhesion state between the wheel and the rail.

[0026] The details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0028] Figure 1 is a flow chart of a method for evaluating the adhesion state between a vehicle wheel and rail according to an embodiment of the present application;

[0029] Figure 2 is a flow chart of a method for evaluating the adhesion state between a vehicle wheel and rail according to an embodiment of the present application;

[0030] Figure 3 4 is a structural block diagram of a vehicle wheel-rail adhesion state evaluation system according to an embodiment of the present application.

[0031] In the picture:

[0032] 301. Construct a membership function module; 302. Obtain a road condition index module; 303. Determine an adhesion state module. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is described and illustrated below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely used to explain this application and are not intended to limit this application. Based on the embodiments provided in this application, all other embodiments obtained by those of ordinary skill in the art without making any creative efforts are within the scope of protection of this application.

[0034] Obviously, the drawings described below are merely examples or embodiments of the present application. Those skilled in the art can, without inventive effort, apply the present application to other similar scenarios based on these drawings. Furthermore, it is also understood that, although the effort involved in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, changes in design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as an insufficiency of the content disclosed in this application.

[0035] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it refer to independent or alternative embodiments that are mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments unless there is a conflict.

[0036] Unless otherwise defined, the technical or scientific terms used in this application should have the ordinary meaning understood by a person of ordinary skill in the technical field to which this application belongs. The words "one", "a", "the" and the like used in this application do not indicate a limit on quantity and may indicate the singular or plural. The terms "include", "comprise", "have" and any variations thereof used in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units that are inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The word "multiple" used in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0037] Adhesion is a railway-specific term describing the relationship between wheel and rail. Macroscopically, it manifests as the force transmitted tangentially across the wheel-rail contact surface, acting as resistance to wheel rotation. The maximum adhesion value is proportional to the axle load, and this ratio is known as the adhesion coefficient. Wheel-rail adhesion is a key fundamental scientific issue in railway transportation.

[0038] Adhesion between the wheel and rail is the fundamental basis for generating braking and traction on rail vehicles. Under normal circumstances, vehicle control systems utilize adhesion to achieve traction or braking. However, once maximum adhesion between the wheel and rail is reached, further increasing the driving or braking force will cause relative sliding between the wheel and rail, destroying the adhesion and resulting in both rolling and sliding between the wheel and rail. At this point, the rail's reaction force on the wheel changes from static friction to sliding friction, rapidly decreasing in magnitude and causing the wheel's rotational speed to increase rapidly. If the applied force is driving, the wheel will spin. If the applied force is braking, the wheel will slide or even lock. Both spinning and sliding can cause scratches on the wheel tread and rail surface, and sliding increases braking distance, compromising driving safety. Therefore, these conditions should be avoided as much as possible. Good adhesion at the wheel-rail interface is the fundamental guarantee for safe and high-quality train operation.

[0039] As an open system, the wheel-rail system is subject to various natural environmental factors, such as humidity, temperature, water, wind, sand, and even iron oxides. All of these environmental factors affect the adhesion state at the wheel-rail interface. Adhesion states can vary at different locations along a track, and even at the same location, they can fluctuate with the weather. Therefore, real-time monitoring and assessment of rail adhesion is essential.

[0040] Existing technologies have largely focused on the exploration and utilization of the adhesion coefficient, which determines the maximum braking force a braking system can apply. Accurately measuring the adhesion coefficient is a complex task, requiring extensive road testing on trains equipped with specialized equipment. Braking forces are applied in various sections to induce slip between the wheel and rail. Accurately determining wheel deceleration at the initial moment of slip allows the adhesion coefficient to be calculated, ultimately yielding a formula or data range for calculating the adhesion coefficient. Limited by the capabilities of the braking system, it is impossible to accurately determine the maximum adhesion coefficient between the wheel and rail in real time.

[0041] Although theoretically the braking anti-skid system can obtain the vehicle deceleration at the moment of slipping and roughly calculate the current adhesion coefficient, the adhesion coefficient between the wheel and rail will change significantly as subsequent wheels pass by, so it cannot be used as a reference for subsequent vehicles. However, for the vehicle operation system, a comprehensive assessment of the adhesion situation of a section of track over a certain period of time is required.

[0042] To solve the above problems, this embodiment provides a method for evaluating the adhesion state between a vehicle wheel and rail. Figure 1 FIG. 1 is a flow chart of a method for evaluating the adhesion state between a vehicle wheel and rail according to an embodiment of the present application. Figure 1 As shown, the process includes the following steps:

[0043] Membership function construction step S101: setting multiple judgment value intervals corresponding to at least one type of influencing factor under various road conditions, and constructing a membership function corresponding to the at least one type of influencing factor based on the multiple judgment value intervals. The influencing factor is a factor that affects the adhesion state of the wheel-rail contact interface.

[0044] Obtaining the road condition index step S102: setting the weight information corresponding to each influencing factor, when the vehicle axle is detected to slip for the first time, obtaining the real-time value of at least one type of influencing factor, substituting the real-time value of each influencing factor into the corresponding membership function to obtain the evaluation matrix, performing a weighted sum calculation on the evaluation matrix and the weight information corresponding to each influencing factor to obtain the road condition index.

[0045] Adhesion state determination step S103: setting a plurality of road condition value intervals according to the degree of wheel-rail adhesion, determining whether the road condition index is within at least one road condition value interval, and obtaining the current wheel-rail adhesion state.

[0046] For different types of influencing factors, judgment value intervals are set under various road conditions, and corresponding membership functions are constructed to quantify the relationship between influencing factors and road conditions.

[0047] By systematically constructing membership functions, obtaining road condition indicators, and judging adhesion status, we can comprehensively consider multiple influencing factors, accurately assess the adhesion status between the vehicle wheel and rail, provide effective protection for the safety and stability of vehicle operation, and avoid safety accidents caused by misjudgment of adhesion status.

[0048] Starting from the real-time numerical values of influencing factors, real-time monitoring and evaluation can be achieved, thereby improving the accuracy of evaluation results.

[0049] In some embodiments, multiple membership degrees are set in the membership function corresponding to each influencing factor, and the membership degrees correspond to the judgment value intervals one by one. In the membership function corresponding to an influencing factor, each membership degree corresponds to a unique judgment value interval.

[0050] When constructing the membership function, a specific membership degree is assigned to each judgment value interval. When the real-time value of the influencing factor is substituted, the corresponding membership degree can be determined based on the judgment value interval in which it is located. Through this clear correspondence, a more accurate description and analysis of the influencing factors can be achieved.

[0051] In the membership function, membership degrees are set to correspond one-to-one with the judgment value intervals, and each membership degree corresponds to a unique judgment value interval, which makes the logic of the membership function clearer and more accurate, improves the accuracy of the quantitative analysis of influencing factors, and thus improves the accuracy and reliability of the adhesion state assessment.

[0052] In some embodiments, for any influencing factor, the real-time value of the influencing factor is substituted into the corresponding membership function, and multiple single factor evaluation values are calculated based on the membership degree and the judgment value interval.

[0053] Integrate multiple single factor evaluation values corresponding to each influencing factor to form an evaluation matrix.

[0054] The weight information corresponding to multiple influencing factors is formed into a weight set, and the weight set and the evaluation matrix are weighted and summed to obtain the road condition index.

[0055] For each influencing factor, its real-time value is substituted into the membership function to obtain multiple single-factor evaluation values. Each single-factor evaluation value reflects the degree of influence of the influencing factor on the road condition from different dimensions at the same time.

[0056] The single-factor evaluation values of all influencing factors at the same time, calculated using their corresponding membership functions, are integrated into an evaluation matrix. The weight information is then combined into a weighted set. Using a weighted summation method using matrix operations, each factor and its weight is comprehensively considered to arrive at the final road condition index. Each row of the evaluation matrix corresponds to multiple single-factor evaluation values of any influencing factor calculated using the membership functions at the same time.

[0057] By calculating the single-factor evaluation value, forming an evaluation matrix and performing weighted summation with the weight set, it is possible to fully integrate the information of multiple influencing factors and comprehensively and systematically evaluate the road conditions. Compared with single-factor analysis, this greatly improves the scientificity and comprehensiveness of adhesion state evaluation.

[0058] In some embodiments, the influencing factors include vehicle deceleration, and the current moment and current vehicle speed are periodically recorded. The ratio of the difference between the current vehicle speeds corresponding to two adjacent moments and the difference between the two adjacent moments is calculated to obtain the vehicle deceleration.

[0059] The current moment and the corresponding vehicle speed are recorded at regular intervals. The vehicle deceleration is calculated by calculating the ratio of the difference in vehicle speed between two adjacent moments to the time difference. When evaluating the adhesion state, this deceleration value is substituted into the corresponding membership function for analysis and calculation to reflect its impact on road condition indicators.

[0060] Taking vehicle deceleration as an influencing factor, by periodically recording vehicle speed and calculating deceleration, it is possible to reflect the speed changes during vehicle operation in real time, provide dynamic and critical reference information for adhesion state assessment, and help to promptly detect vehicle operation abnormalities.

[0061] In some embodiments, the influencing factor includes a speed difference, and the vehicle speed and the axle speed at the same moment are obtained, and the difference between the vehicle speed and the axle speed is calculated to obtain the speed difference.

[0062] The vehicle speed and axle speed at the same moment are obtained, and the difference between the two is calculated to obtain the speed difference. During the adhesion state assessment process, the speed difference is substituted into the corresponding membership function and combined with other influencing factors to comprehensively calculate the road condition index to determine the adhesion state between the wheel and rail.

[0063] Using speed difference as an influencing factor, it directly reflects the difference between the overall vehicle movement and the axle movement, and can intuitively determine whether the axle has slip abnormalities, providing key clues for adhesion status assessment and improving the timeliness and accuracy of the assessment.

[0064] In some embodiments, the influencing factors include the number of sliding axles, and the number of vehicle axles in a sliding state at a moment is obtained to obtain the number of sliding axles.

[0065] The number of vehicle axles in a sliding state at a given moment is counted to obtain the sliding axle count. When evaluating the adhesion state, the sliding axle count is substituted into the corresponding membership function and combined with other influencing factors in a weighted summation calculation to derive a road condition index and determine the adhesion state.

[0066] Including the number of sliding axles as an influencing factor can help grasp the scale of vehicle axle sliding from an overall perspective, help analyze the severity and prevalence of vehicle adhesion, and provide a strong basis for taking appropriate countermeasures.

[0067] In some embodiments, the influencing factors include the coasting duration, and the moment when the vehicle axle starts to be in the coasting state, any moment when it is still in the coasting state, and / or the moment when the vehicle axle leaves the coasting state are obtained. If the vehicle axle is still in the coasting state, the time from the moment when the vehicle axle starts to be in the coasting state to the moment when it is in the coasting state is the coasting duration. If the vehicle axle is not in the coasting state, the time from the moment when the vehicle axle starts to be in the coasting state to the moment when the vehicle axle leaves the coasting state is the coasting duration.

[0068] The moment when the vehicle axle starts to slide, is still sliding, or stops sliding is recorded, and the sliding duration is calculated based on the current state of the vehicle axle. When evaluating the adhesion state, the sliding duration is substituted into the corresponding membership function and combined with other influencing factors to calculate the road condition index, thereby determining the adhesion state between the wheel and rail.

[0069] Taking the coasting duration as an influencing factor can deeply analyze the duration of vehicle axle coasting, distinguish the different effects of short-term and long-term coasting on the adhesion state, provide more comprehensive and detailed information for adhesion state assessment, and improve the accuracy and pertinence of the assessment.

[0070] Influencing factors include but are not limited to: vehicle deceleration, maximum coasting time, maximum speed difference and number of coasting axles.

[0071] Multiple influencing factors can be determined according to different vehicle types, the weight value of each influencing factor can be determined, and multiple membership functions can be designed according to actual application requirements.

[0072] This application enables real-time monitoring and evaluation, rather than a post-test evaluation, reducing damage to vehicles and tracks. The results obtained by this application are more accurate and detailed, and can be combined with other technologies such as positioning to accurately determine the adhesion state of the train immediately before it began to slide or idle after a braking or traction command. Changes in the track surface condition can also be determined by comparing the results of the front and rear axles of the vehicle, or the results of the preceding and following vehicles.

[0073] In practical applications, all factors that affect the evaluation of the track surface state are first selected to form a factor set. The factor set can be recorded as U = {u1, u2, ..., u m}. Among them, u i is the i-th influencing factor. m is the total number of factors. The influencing factors include vehicle deceleration, maximum coasting time, maximum speed difference, and number of coasting axes.

[0074] The vehicle's anti-skid system collects and calculates the signals of the wheel axle speed and the vehicle body speed, and can obtain the real-time values of the wheel axle speed and the vehicle body speed.

[0075] The calculation formula for vehicle deceleration is: Where t1 is the first moment. t2 is the second moment. v1 is the vehicle speed at the first moment. v2 is the vehicle speed at the second moment. The speed difference is the difference between the vehicle speed and the axle speed at the same moment.

[0076] The maximum speed difference is the maximum value of the speed difference between the start of a coasting event and the moment the coasting has not yet ceased during the vehicle's driving process. Alternatively, the maximum speed difference is the maximum value of the speed difference between the moment the first coasting event begins and the moment the coasting has ceased during the vehicle's driving process.

[0077] The maximum sliding duration is the duration from the moment sliding appears to the moment sliding does not disappear or the moment sliding disappears.

[0078] The number of sliding axles is the number of axles that are sliding at a certain moment.

[0079] When a vehicle is coasting, the wheel's axle speed is lower than the actual train speed, causing the wheel to slide relative to the track. Different systems use different criteria for determining "coasting," but most often rely on vehicle deceleration and speed differential. Specifically, a vehicle is considered coasting when both the speed differential is greater than the set speed differential value v0 and the deceleration is greater than the set deceleration value a0.

[0080] Secondly, a weight set is established, and for each influencing factor u i Assign a unique weight a i (i=1,2,…,m). In this application, the weight of vehicle deceleration is set to a1=0.5, the weight of maximum coasting time is set to a2=0.2, the weight of maximum speed difference is set to a3=0.2, and the weight of the number of coasting axes is set to a4=0.1. The weights a corresponding to each influencing factor are i It forms a weight set, which is recorded as: A = (a1, a2, a3, a4).

[0081] Again, based on the suitability of road conditions, a judgment set is established, as shown in the following table.

[0082]

[0083] The judgment set is recorded as V = {v1, v2, ..., v m Each parameter in the table is given an initial value based on system characteristics and designer experience. It can then be adjusted based on the evaluation results and the braking distance during the anti-skid process. Fuzzy comprehensive evaluation comprehensively considers the impact of all factors on the wheel-rail adhesion state and finds the most satisfactory result from the evaluation set.

[0084] If a research object cannot be determined to conform to a certain concept, it indicates that there is no decisive relationship between the object and the concept, which is a violation of the law of the excluded middle. In the study of fuzziness, fuzzy set theory grasps the objective meaning of the generalized law of the excluded middle, the affiliation relationship, and the degree of event membership. It can reflect the constraints and connections between objects and fuzzy concepts.

[0085] This application sets the membership function through trapezoidal distribution. The membership functions corresponding to the four influencing factors are as follows:

[0086] The membership function of vehicle deceleration is:

[0087] Among them, x1 is the real-time value of the vehicle deceleration during driving.

[0088] The membership function of the maximum sliding time is:

[0089] Among them, x2 is the real-time value of the maximum coasting time during driving.

[0090] The membership function of the maximum speed difference is:

[0091] Among them, x3 is the real-time value of the maximum speed difference during driving.

[0092] The membership function of the number of sliding axes is:

[0093] Among them, x4 is the real-time value of the number of sliding axes during driving.

[0094] Secondly, fuzzy judgment is performed on the influencing factors. i When making a judgment, the element V in the judgment set V j The degree of membership is denoted as r ij , reflecting factor u i and the element V in the judgment set V j The correlation strength, r ij It can be obtained by calculating the membership function mentioned above.

[0095] The single factor evaluation matrix is formed as follows:

[0096] The single factor evaluation matrix R can be regarded as a fuzzy relationship between the factor set U and the evaluation set V. i It represents the set of multiple single factor evaluation values of the i-th influencing factor calculated by the membership function at a certain moment.

[0097] In order to conduct comprehensive fuzzy evaluation, the weighted summation method is adopted, which can scientifically reflect the influence of all factors on the evaluation object. Therefore, the fuzzy evaluation can be expressed as:

[0098]

[0099] This gives the road condition index according to The value of can be used to evaluate the road condition more objectively. i Represents the unique weight corresponding to the i-th influencing factor. in It represents the nth single factor evaluation value of the i-th influencing factor at a certain moment.

[0100] Multiple road condition value ranges can be set according to the degree of adhesion between the wheel and rail, as shown in the following table:

[0101]

[0102]

[0103] The above road condition value ranges can be applied to different systems, with different judgment value ranges set according to system performance, and multiple value ranges can be set. The parameters in each road condition value range can be adjusted based on the braking distance during the anti-skid process. In application, the shorter the braking distance at the same initial speed, the more reasonable the parameter settings.

[0104] like Figure 2As shown, this embodiment also provides a method for assessing the wheel-rail adhesion state of a vehicle. During vehicle travel, the vehicle's braking control system applies a braking command to the vehicle, and the anti-skid system begins real-time monitoring of wheel axle slip. When a wheel axle first slips, the real-time values of the vehicle's deceleration, maximum speed difference, slip duration, and number of slipping axles are calculated and substituted into their corresponding membership functions to obtain multiple membership degrees. The multiple membership degrees for each of the vehicle's deceleration, maximum speed difference, slip duration, and number of slipping axles are integrated into a single-factor evaluation matrix. Weights are assigned to the vehicle's deceleration, maximum speed difference, slip duration, and number of slipping axles to form a weighted set. A weighted summation is performed on the weighted set and the single-factor evaluation matrix to obtain a road condition index. Based on the road condition value range, the calculated road condition index is determined to fall within the road condition value range, thereby determining the wheel-rail adhesion state corresponding to the road condition value range. Based on the wheel-rail adhesion state, corresponding improvement measures can be implemented, including adhesion enhancement measures by the vehicle control system or changes to the brake system's control algorithm.

[0105] It provides real-time rail surface status information to the vehicle control system. Combined with other systems like sand spreading, it helps achieve optimal adhesion, reduce tread abrasions and wheel flange wear, and increase wheel flange service life. By integrating multiple rail surface status data, it can provide a basis for establishing reasonable rail surface maintenance cycles and setting driver warnings, ensuring driving safety.

[0106] This embodiment also provides a vehicle wheel-rail adhesion state assessment system. Figure 3 is a structural block diagram of a vehicle wheel-rail adhesion state evaluation system according to an embodiment of the present application, such as Figure 3 As shown, the system includes:

[0107] The membership function construction module 301 is configured to set multiple judgment value intervals corresponding to at least one type of influencing factor under various road conditions, and construct a membership function corresponding to the at least one type of influencing factor based on the multiple judgment value intervals. The influencing factor is a factor that affects the adhesion state of the wheel-rail contact interface.

[0108] The road condition index acquisition module 302 is configured to set weight information corresponding to each influencing factor. When the vehicle axle is detected to slip for the first time, the real-time value of at least one type of influencing factor is obtained, and the real-time value of each influencing factor is substituted into the corresponding membership function to obtain an evaluation matrix. The evaluation matrix and the weight information corresponding to each influencing factor are weighted and summed to obtain the road condition index.

[0109] The adhesion state determination module 303 is configured to set a plurality of road condition value intervals according to the degree of wheel-rail adhesion, determine whether the road condition index is within at least one road condition value interval, and obtain the current wheel-rail adhesion state.

[0110] The membership function construction module 301 is responsible for setting the judgment value interval and constructing the membership function. When axle slip is detected, the road condition index acquisition module 302 obtains the real-time values of the influencing factors and calculates the road condition index by combining the membership function and weight information. The adhesion state determination module 303 determines the road condition index based on the preset road condition value interval and determines the wheel-rail adhesion state.

[0111] By constructing the membership function module 301, the road condition index acquisition module 302, and the adhesion state judgment module 303, the functions of the vehicle wheel-rail adhesion state assessment system are implemented in a modular manner, making the system structure clear, easy to maintain and expand, and ensuring the accuracy and efficiency of the adhesion state assessment.

[0112] In some embodiments, the membership function construction module 301 is further configured to set multiple membership degrees in the membership function corresponding to each influencing factor, and the membership degrees correspond to the judgment value intervals one by one. In the membership function corresponding to an influencing factor, each membership degree corresponds to a unique judgment value interval.

[0113] In the process of constructing the membership function, the membership function construction module 301 strictly sets a one-to-one correspondence between multiple membership degrees and judgment value intervals, and ensures that each membership degree corresponds to a unique judgment value interval, laying the foundation for the subsequent road condition index module 302 to accurately calculate the single factor evaluation value.

[0114] The membership function construction module 301 further refines the correspondence between the membership degree and the judgment value interval, making the membership function construction more rigorous and standardized, enhancing the accuracy of the system's analysis of influencing factors, and thus improving the reliability of the entire evaluation system and the credibility of the evaluation results.

[0115] In some embodiments, the road condition index acquisition module is further configured to, for any influencing factor, substitute the real-time numerical value of the influencing factor into the corresponding membership function and, based on the membership degree and the judgment value interval, calculate multiple single-factor evaluation values. The multiple single-factor evaluation values corresponding to each influencing factor are integrated to form an evaluation matrix. The weight information corresponding to the multiple influencing factors is formed into a weight set, and the weight set and the evaluation matrix are weighted and summed to obtain the road condition index.

[0116] The road condition index acquisition module first calculates the single factor evaluation value for each influencing factor, then forms an evaluation matrix, and forms a weight set with the weight information. Finally, the road condition index is obtained through weighted summation operation, providing an accurate evaluation basis for the adhesion state judgment module 303.

[0117] The road condition index acquisition module further refines the calculation process. By calculating single-factor evaluation values, evaluation matrices, and weight sets, it more accurately integrates information on various influencing factors, improving the accuracy of road condition index calculations and, in turn, enhancing the accuracy and reliability of the vehicle wheel-rail adhesion state assessment system.

[0118] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0119] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for evaluating the adhesion state between a vehicle wheel and rail, characterized in that: include: The step of constructing a membership function includes setting a plurality of judgment value intervals corresponding to at least one type of influencing factor under a plurality of road conditions, and constructing a membership function corresponding to the at least one type of influencing factor based on the plurality of judgment value intervals; the influencing factor is a factor that affects the adhesion state of the wheel-rail contact interface; Obtaining road condition index: setting weight information corresponding to each influencing factor, obtaining the real-time value of at least one type of influencing factor when the vehicle axle is detected to slip for the first time, substituting the real-time value of each influencing factor into the corresponding membership function to obtain an evaluation matrix, and performing a weighted sum calculation on the evaluation matrix and the weight information corresponding to each influencing factor to obtain the road condition index; Adhesion state determination step: setting a plurality of road condition value intervals according to the degree of adhesion between the wheel and the rail, determining that the road condition index is within at least one road condition value interval, and obtaining the current wheel-rail adhesion state.

2. The method for evaluating the vehicle wheel-rail adhesion state according to claim 1, wherein: In the membership function corresponding to each influencing factor, multiple membership degrees are set, and the membership degrees correspond to the judgment value intervals one by one; wherein, in the membership function corresponding to one influencing factor, each membership degree corresponds to a unique judgment value interval.

3. The method for evaluating the vehicle wheel-rail adhesion state according to claim 2, wherein: For any influencing factor, the real-time value of the influencing factor is substituted into the corresponding membership function, and multiple single factor evaluation values are calculated based on the membership degree and the judgment value interval; Integrate the multiple single factor evaluation values corresponding to each influencing factor to form an evaluation matrix; The weight information corresponding to multiple influencing factors is formed into a weight set, and the weight set and the evaluation matrix are weighted and summed to obtain the road condition index.

4. The method for evaluating the vehicle wheel-rail adhesion state according to claim 1, wherein: The influencing factors include vehicle deceleration. The current time and current vehicle speed are recorded periodically. The ratio of the difference between the current vehicle speeds at two adjacent time points and the difference between the two adjacent time points is calculated to obtain the vehicle deceleration. The membership function corresponding to the vehicle deceleration is: Among them, x1 is the real-time value of the vehicle deceleration during the vehicle driving process.

5. The method for evaluating the vehicle wheel-rail adhesion state according to claim 1, wherein: The influencing factors include speed difference. The vehicle speed and axle speed at the same time are obtained, and the difference between the vehicle speed and the axle speed is calculated to obtain the speed difference. The membership function corresponding to the speed difference is: x3 is the real-time value of the speed difference during vehicle driving.

6. The method for evaluating the vehicle wheel-rail adhesion state according to claim 1, wherein: The influencing factors include the number of sliding axles. The number of vehicle axles in the sliding state at a certain moment is obtained to obtain the number of sliding axles. The membership function corresponding to the number of sliding axles is: Among them, x4 is the real-time value of the number of sliding axes during vehicle driving.

7. The method for evaluating the vehicle wheel-rail adhesion state according to claim 1, wherein: The influencing factors include the coasting duration. The moment when the vehicle axle starts to coast, any moment when it is still in the coasting state, and / or the moment when the vehicle axle leaves the coasting state are obtained. If the vehicle axle is still in the coasting state, the duration from the moment when the vehicle axle starts to coast to the moment when it is in the coasting state is the coasting duration. If the vehicle axle is not in the coasting state, the duration from the moment when the vehicle axle starts to coast to the moment when the vehicle axle leaves the coasting state is the coasting duration. The membership function corresponding to the coasting duration is: Among them, x2 is the real-time value of the coasting time during driving.

8. A vehicle wheel-rail adhesion state assessment system, characterized in that: include: a membership function construction module configured to set multiple judgment value intervals corresponding to at least one type of influencing factor under multiple road conditions, and construct a membership function corresponding to the at least one type of influencing factor based on the multiple judgment value intervals; the influencing factor is a factor that affects the adhesion state of the wheel-rail contact interface; A road condition index acquisition module is configured to set weight information corresponding to each influencing factor, obtain a real-time value of at least one type of influencing factor when the vehicle axle first slips, substitute the real-time value of each influencing factor into the corresponding membership function to obtain an evaluation matrix, and perform a weighted sum calculation on the evaluation matrix and the weight information corresponding to each influencing factor to obtain a road condition index; The adhesion state determination module is configured to set a plurality of road condition value intervals according to the adhesion degree between the wheel and rail, determine that the road condition index is within at least one road condition value interval, and obtain the current adhesion state between the wheel and rail.

9. The vehicle wheel-rail adhesion state evaluation system according to claim 8, characterized in that: The membership function construction module is further configured to set multiple membership degrees in the membership function corresponding to each influencing factor, and the membership degrees correspond one-to-one to the judgment value intervals; wherein, in the membership function corresponding to an influencing factor, each membership degree corresponds to a unique judgment value interval.

10. The vehicle wheel-rail adhesion state evaluation system according to claim 9, characterized in that: The road condition index acquisition module is further configured to, for any influencing factor, substitute the real-time value of the influencing factor into the corresponding membership function, and calculate multiple single factor evaluation values based on the membership degree and the judgment value interval; Integrate the multiple single factor evaluation values corresponding to each influencing factor to form an evaluation matrix; The weight information corresponding to multiple influencing factors is formed into a weight set, and the weight set and the evaluation matrix are weighted and summed to obtain the road condition index.

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