78 results about "Adhesion coefficient" patented technology

Disclosed herein are an adhesion coefficient determination method and apparatus, and a vehicle, a medium and a program product. The method comprises: acquiring sensor data collected by at least one sensor of a vehicle; on the basis of the sensor data, determining travelling information of the vehicle, wherein the travelling information comprises at least one of the following: a slip rate, longitudinal stiffness, a tire longitudinal force, a tire lateral force, a tire vertical load, a front-axle lateral force and a rack force; on the basis of the travelling information, or the sensor data and the travelling information, determining at least one reference adhesion coefficient and a confidence level of each reference adhesion coefficient, wherein the at least one reference adhesion coefficient comprises at least one of the following: a steady-state adhesion coefficient, a dynamic adhesion coefficient, a longitudinal adhesion coefficient and a lateral adhesion coefficient; and on the basis of the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient, determining a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient. The method in the embodiments of the present application improves the accuracy of adhesion coefficient determination.

The invention relates to the technical field of vehicle dynamics, and discloses an adhesion coefficient determination method and device and electronic equipment. The method comprises the steps that the wheel end torque, the wheel angular acceleration, the wheel slip rate and the wheel vertical load of the vehicle are obtained; determining a first longitudinal force of each wheel based on the wheel end torque and the wheel angular acceleration; determining a basic adhesion coefficient of each wheel based on the first longitudinal force and the wheel vertical load; determining a second longitudinal force of each wheel based on the wheel slip rate and a tire model corresponding to the wheel; if the basic adhesion coefficient is smaller than a preset adhesion coefficient threshold value, the second longitudinal force is adopted to correct the basic adhesion coefficient, and the target adhesion coefficient of each wheel is obtained. According to the method, the attachment state of each wheel can be known in time, potential safety hazards caused by inaccurate calculation of the attachment coefficient are reduced, and the driving safety of the vehicle is improved.

The invention discloses a dynamic adhesion coefficient correction evaluation method and system based on multi-source data fusion, and belongs to the field of vehicle electronic control, and the method comprises the following steps: S1, carrying out the data collection of a multi-source sensor; s2, calculating a slip rate based on data collected by a wheel speed sensor, calculating a dynamic compensation factor based on data collected by a suspension load sensor, correcting a centroid offset error based on data collected by an inertial sensor, and triggering segmented compensation based on data collected by a brake disc temperature sensor; s3, calculating a basic adhesion coefficient based on the slip rate; s4, correcting the basic adhesion coefficient based on the dynamic compensation factor and the corrected centroid offset; and S5, the basic braking force and the basic torque distributed by the ESC system are corrected. By adopting the dynamic adhesion coefficient correction evaluation method and system based on multi-source data fusion, high-precision correction of the dynamic adhesion coefficient and intelligent adjustment of the braking force are realized through multi-source sensor data fusion and ESC system integrated design.

The invention relates to a vehicle braking method based on a road adhesion coefficient, and the method comprises the steps: 1, carrying out the real vehicle data collection, and punching a uniform timestamp through a clock source; 2, uniformly converting all the collected data into a vehicle coordinate system; 3, inputting the collected data into a preset deep learning regression model to obtain a predicted value of an attachment coefficient, generating a typical attachment coefficient representing the type of road, and adding the typical attachment coefficient into a preset road attachment coefficient query table; 4, the current road type is recognized, the corresponding typical attachment coefficient is called from the road attachment coefficient query table, the vehicle following distance is adjusted, and the braking deceleration is formulated; 5, analyzing to obtain the maximum adhesion potential of the current road surface; and 6, the original road adhesion coefficient is corrected, and the final braking deceleration is assigned to the current road so that the vehicle can conduct deceleration braking according to the assigned value.

The invention provides a vehicle anti-skid control method and device. The method comprises the following steps: perceiving and identifying the pavement type of a pavement in front of a vehicle, and determining the perceiving adhesion coefficient of each wheel; estimating based on the dynamic model, and determining the utilization adhesion coefficient of each wheel; according to the perception adhesion coefficient and the utilization adhesion coefficient of each wheel, determining an anti-skid control use adhesion coefficient of each wheel; under the condition that the anti-skid flag bit is activated, according to the anti-skid control use adhesion coefficient of each wheel, a first-time torque reduction target torque value of the vehicle is determined; and based on the first-time torque reduction target torque value, anti-skid control is conducted on the vehicle.

The invention discloses a vehicle torque control method and device and related equipment. The method comprises the steps that the utilization adhesion coefficient and the slip rate of target wheels of a vehicle in a preset first time period and the feedback torque of the target wheels are obtained, and the target wheels comprise at least one wheel driven by a target motor; the utilization adhesion coefficient and the slip rate of the target wheel are fitted, and the longitudinal rigidity of the vehicle is determined; performing torque operation on the longitudinal stiffness to obtain a feed-forward torque of the target wheel; and determining the sum of the feedforward torque and the feedback torque as a target motor torque, and controlling the target motor to output the target motor torque, the target motor being a motor corresponding to the target wheel.

A method and device (50) for determining a longitudinal adhesion coefficient, a vehicle (60), a medium and a program product. The method comprises: determining a longitudinal adhesion coefficient of each wheel on the basis of first wheel information and a plurality of scenario adhesion coefficients of each wheel, the first wheel information comprising a longitudinal stiffness, a slip rate, and a nominal longitudinal force (S201); on the basis of the longitudinal adhesion coefficients of a plurality of wheels, determining a first longitudinal adhesion coefficient and a first confidence of a vehicle in a low adhesion state, and a second longitudinal adhesion coefficient and a second confidence of the vehicle in a high adhesion state (S202); and determining a longitudinal adhesion coefficient of the vehicle on the basis of the first longitudinal adhesion coefficient, the first confidence, the second longitudinal adhesion coefficient and the second confidence (S203), thereby improving the accuracy of determining the longitudinal adhesion coefficient of the vehicle.

The invention relates to the field of vehicles, in particular to a vehicle control method, a vehicle, electronic equipment and a computer readable storage medium. The method comprises the steps of obtaining image data of a front road of a vehicle, and calculating an adhesion coefficient of the front road according to the image data; under the condition that the adhesion coefficient represents that the front road is a low-adhesion road, matching the adhesion coefficient with a plurality of preset coefficient intervals to obtain a target coefficient interval where the adhesion coefficient is located and a target anti-skid mode corresponding to the target coefficient interval; wherein each preset coefficient interval corresponds to one preset anti-skid mode, and the smaller the minimum value of the preset coefficient interval is, the larger the torque adjusting degree of the preset anti-skid mode corresponding to the preset coefficient interval on the vehicle is; and switching the current driving mode of the vehicle to the target anti-skid mode. According to the method, the low attachment state of the front road can be recognized, and the control strategy of the vehicle is automatically adjusted according to different low attachment degrees, so that the driving stability and safety of the vehicle under the complex road condition are improved.

The invention discloses an electric vehicle lane changing path planning method and system suitable for a variable adhesion coefficient road surface, and relates to the technical field of electric vehicle unmanned driving. The method comprises the following steps: receiving road adhesion information of a to-be-changed area and information of surrounding obstacle vehicles; introducing concepts of lane changing time and offset rate to define different lane changing paths, and generating a basic lane changing path cluster based on a quintic Bezier curve; proposing a path stability criterion in a curvature form and a lane changing time form based on a vehicle stability domain; generating a stable lane changing path cluster containing a symmetric path and an asymmetric path by using a path stability criterion and road surface attachment information; and generating a lane changing path meeting optimal comfort, stability, safety and efficiency based on an approximate ideal solution sorting algorithm. According to the method, the change of the road surface attachment information in the future lane changing area is considered, the stability of the vehicle during lane changing under the road surface with the variable attachment coefficient is ensured by using the asymmetric lane changing path, and the lane changing safety of the vehicle is improved.

This application relates to the field of vehicle control technology and discloses a predictive control method and system based on road surface adhesion coefficient. In this method, a cloud server acquires real-time information uploaded by vehicles on the road. The cloud server can combine the real-time information with historical information from each grid to form a road surface adhesion coefficient matrix. The cloud server sends the road surface adhesion coefficient matrix to the vehicle. Based on the road surface adhesion coefficient matrix, the vehicle's current position, and navigation path, the vehicle determines the predicted road surface adhesion coefficient value in its current direction of travel. Based on the predicted road surface adhesion coefficient value, the vehicle calculates the upper limit of its regenerative braking capacity and / or the upper limit of its driving torque, and then controls the vehicle accordingly. The beneficial effect is improved vehicle control efficiency on low-adhesion roads.

The invention discloses a pavement adhesion coefficient identification method, electronic equipment, a vehicle and a storage medium, relates to the technical field of pavement identification, and aims to solve the problem of low accuracy of a pavement adhesion coefficient. The road adhesion coefficient identification method comprises the following steps: acquiring a road type identification result of a road in front of a vehicle, wherein the road type is obtained by identifying a road image of the road in front of the vehicle shot by unmanned aerial vehicle equipment flying in front of the vehicle; determining a visual estimation value of a road adhesion coefficient of a road in front of the vehicle based on the road type recognition result and a preset corresponding relation; wherein the preset corresponding relation is used for indicating pavement adhesion coefficients corresponding to different pavement types; and determining the road adhesion coefficient of the road in front of the vehicle based on the visual estimation value of the road adhesion coefficient.

This invention discloses a method and system for dynamic distribution of axle control power in urban rail vehicles based on real-time adhesion estimation. The method includes: acquiring real-time operating state data of the vehicle; calculating the dynamic vertical load of each axle during braking by combining the vehicle's longitudinal dynamics model; constructing an extended state observer and using it to estimate the wheel-rail adhesion and wheel-rail contact state parameters of each axle in real time, and calculating the theoretical maximum available adhesion coefficient accordingly; applying an asymmetric rate of change constraint to the theoretical maximum available adhesion coefficient to obtain the safe adhesion limit for constraint; constructing a multi-objective optimization function for braking force distribution, including a braking force tracking error objective and an adhesion utilization rate objective, and weighting the two objectives using adaptive weighting coefficients; and solving the multi-objective optimization function to obtain the optimal braking force for each axle. This invention can significantly improve the adhesion utilization rate and active safety performance of urban rail vehicles under complex road conditions, effectively preventing wheel slippage.

The embodiment of the invention provides a train detection system, the train detection system comprises a detection device and a processing module, the detection device comprises a first mounting seat, a second mounting seat, a first sensor, a second sensor, a sliding part and an elastic guide rod, one side of the first mounting seat comprises a mounting plate, and the elastic guide rod is connected with the mounting plate; the second mounting seat is connected with one end, away from the first mounting plate, of the elastic guide rod; the sliding part is arranged on one side, back to the elastic guide rod, of the second mounting seat; the first sensor and the second sensor are arranged between the second mounting seat and the sliding part; one side, back to the mounting plate, of the first mounting seat is connected with the bottom of the train; the first sensor and the second sensor are connected with the processing module. Through the train detection system, the adhesion coefficient can be determined in real time, and the accuracy of the adhesion coefficient is improved.

The application discloses a kind of anti-cracking performance evaluation method and computer equipment for asphalt stress absorbing layer, it is related to pavement engineering technical field, the method includes: stress absorbing layer test piece is carried out oblique shear test, and index information in the process of oblique shear test is collected, the index information includes shear angle, stress load, vertical displacement, lateral displacement, interlayer dislocation displacement and stress absorbing layer adhesion force;According to the index information, the interlayer adhesion coefficient and interlayer stress absorbing coefficient of the stress absorbing layer test piece are calculated;According to the interlayer adhesion coefficient and interlayer stress absorbing coefficient, the anti-cracking performance of the stress absorbing layer test piece is evaluated.The application can introduce the interlayer adhesion coefficient and interlayer stress absorbing coefficient of stress absorbing layer test piece, and accurately evaluate the anti-cracking performance of asphalt stress absorbing layer.

This invention discloses a dynamic adhesion coefficient correction and evaluation method and system based on multi-source data fusion, belonging to the field of vehicle electronic control. The method includes the following steps: S1, multi-source sensor data acquisition; S2, calculating the slip ratio based on wheel speed sensor data, calculating the dynamic compensation factor based on suspension load sensor data, correcting the center of gravity offset error based on inertial sensor data, and triggering segmented compensation based on brake disc temperature sensor data; S3, calculating the base adhesion coefficient based on the slip ratio; S4, correcting the base adhesion coefficient based on the dynamic compensation factor and the corrected center of gravity offset; S5, correcting the base braking force and base torque allocated by the ESC system. By employing the above-mentioned dynamic adhesion coefficient correction and evaluation method and system based on multi-source data fusion and integrated design with the ESC system, high-precision correction of the dynamic adhesion coefficient and intelligent adjustment of the braking force are achieved.

A locomotive traction force upper limit limiting method, according to the environmental temperature, weather state and track object state, the adhesion coefficient is adaptively adjusted by using the direct reasoning calculation method to obtain the adhesion coefficient setting value, so that the maximum traction force limit of the locomotive can change in real time with the change of the road section road condition, and the locomotive traction is performed as much as possible without wheel pair idling. When the wheel pair idling cannot be avoided, the non-linear mathematical expression is used to calculate the idling risk value according to the creep rate change rate and the creep degree, to judge whether the wheel pair of the locomotive idles, and to decide whether to perform the idling traction force control on the locomotive traction force after the upper limit limiting control according to the idling judgment result, to realize the comprehensive judgment of multiple factors, so that the idling judgment and the idling traction force control are more comprehensive and accurate.

This application provides a method for controlling a vehicle and a vehicle in the field of vehicle control technology. The method incorporates environmental perception data, which considers the environmental sensitivity of adhesion coefficient recovery under complex operating conditions. A first feature is introduced, which directly relates to the physical root cause of adhesion coefficient changes. A second feature reflects the actual fluctuation trajectory of the adhesion coefficient between the tire and the road surface, taking into account the temporal dynamics of the adhesion coefficient under complex operating conditions. After determining the prediction result, the first feature provides physical justification for the adhesion coefficient prediction process, and the third feature provides an adjustment basis for the prediction process, thus accurately determining the adhesion coefficient after the vehicle exits a flooded road section. When the target adhesion coefficient at the current time point recovers to a normal state, the power output limitation is lifted, and the drive torque corresponding to the normal state is output. This enables precise vehicle control, avoiding the risk of slippage due to premature power recovery and eliminating the degradation in experience caused by conservative control.

The invention provides a pavement actual adhesion coefficient estimation method and device based on a tire slippage state and a storage medium, and relates to the technical field of vehicle motion control. According to the method, dynamics basic parameters during normal driving of a vehicle are collected, vertical loads and transverse and longitudinal forces of a front axle and a rear axle are calculated, after the longitudinal force is calibrated by adopting a correction coefficient, an adhesion coefficient is calculated and utilized in combination with the vertical loads, a complex tire model and a camera are not needed, the calculation force requirement is reduced, the transverse and longitudinal force coupling working condition is adapted, and the adaptability of a complex road surface is improved; tracking and utilizing the maximum value of the adhesion coefficient through a stepped memory storage mechanism, storing an effective peak value for a long time, performing gradient forgetting, and providing a stable reference basis; then, vehicle dynamic parameters during tire slippage are collected, and the flag bit activation state is determined; and finally, when the flag bit is activated, outputting a memory adhesion coefficient as an actual pavement adhesion coefficient, so that the output is more fit with a real pavement, and the transverse and longitudinal stability of the vehicle and the torque vector control accuracy are improved.

The invention relates to the technical field of vehicle algorithms, and discloses a wheel adhesion coefficient determination method and system and electronic equipment. According to the method, a weight corresponding relation between vehicle driving data and algorithm weights is established through algorithm errors of driving force algorithms under different vehicle driving data, a current weight is matched according to current driving data of a target vehicle and the weight corresponding relation, and a plurality of driving force algorithms are adopted to perform weighted calculation according to the current weight. Compared with a method for estimating the adhesion coefficient through a single driving force algorithm, the method has the advantages that the multiple driving force algorithms are combined to jointly act on the wheel driving force, the reference coverage range of the adhesion coefficient is expanded, and the adhesion coefficient can be determined through the obtained wheel driving force. And the weight of the driving force algorithm is dynamically adjusted according to the vehicle driving data, so that the influence of algorithm errors on the adhesion coefficient is reduced, and the estimation accuracy of the adhesion coefficient is improved from two aspects.

Specifically, the present invention is a method for testing the relationship between adhesion coefficient and slip rate based on a large-slip wheel-rail test bench. Specifically, S1 applies or places a third medium on the track; S2 controls the first clutch and the second clutch to mesh the first gear set and the second gear set and the second gear set and the third gear set, starts the wheel speed motor to drive the pure roller and the sliding wheel to rotate, and pulls the frame to the target speed; S3 controls the extension and contraction of the cylinder to apply different axle loads; S4 controls the speed of the vehicle speed motor and the wheel speed motor to generate slip rates of different waveforms; S5 collects wheel-rail adhesion coefficient and slip rate data under different working conditions, plots the adhesion coefficient versus slip rate and the adhesion coefficient versus time curves, and finally obtains the wheel-rail adhesion characteristics and change laws under different working conditions. Advantages of the present invention: It realizes tests with greater slip and different waveform slip rates, studies adhesion characteristics under large-slip working conditions; and simulates the dynamic changes and quantitative research of the amount of the third medium under real rail surface conditions.

The invention discloses a method for testing a dry ground adhesion coefficient of an automobile tire. The method comprises the following steps: determining a test speed range; the tractor runs in the test road section at the first output power, and the surface temperature of tires and the speed of the tractor are detected; calculating a dynamic adhesive force coefficient, correcting the dynamic adhesive force coefficient, and recording the corrected dynamic adhesive force coefficient as a standard dynamic adhesive force coefficient; determining a correction coefficient; acquiring the surface roughness of the road surface on the driving path of the to-be-tested tire on the trailer, and the longitudinal force and the transverse force borne by the trailer; and calculating the standard dynamic adhesion coefficient of the tire to be tested, and correcting the standard dynamic adhesion coefficient by using the correction coefficient to obtain the dry ground adhesion coefficient of the tire. According to the method, the corresponding relation between the real-time roughness and the correction coefficient is established, the adhesive force deviation caused by pavement roughness changes is compensated in a targeted mode, and the high-precision requirements of tire basic performance evaluation and road safety monitoring can be met.

The present application relates to a kind of based on eddy current brake adhesion brake force enhancement method and system, comprising the following steps: when high-speed train implements emergency brake, linear eddy current brake is connected into excitation current and enters working state;On the basis of cooperating longitudinal non-adhesion brake force generated by linear eddy current brake, the surplus of maximum axle load and actual axle load is controlled excitation current to make vertical suction force in safe range, simultaneously using the vertical suction force generated, combined with the adhesion coefficient calculation obtains the increased high-speed train adhesion force available domain;Additional adhesion force available is fed back to adhesion brake system to improve adhesion brake force, and the braking effect of high-speed train is improved;With longitudinal non-adhesion brake force generated by linear eddy current brake, further realize the efficient matching use of brake force and adhesion force under multiple working conditions.The present application can be applied to any kind of linear eddy current brake, further improves total brake force on the basis of original high-speed train brake system, and improves brake efficiency.

A battery drop simulation method including: generating, by at least one processor, a three-dimensional model including an adhesive member for a battery; receiving, by the at least one processor, information associated with the three-dimensional model; estimating, by the at least one processor, an adhesion coefficient of the adhesive member based on the information associated with the three-dimensional model; performing, by the at least one processor, a drop simulation of the three-dimensional model based on the information associated with the three-dimensional model, the adhesion coefficient, and drop condition information; and outputting, by the at least one processor, a drop simulation result of the drop simulation. The drop simulation result includes information about whether or not the adhesive member is separated due to a drop.

A method and device (50) for determining a longitudinal adhesion coefficient, a vehicle (60), a medium and a program product. The method comprises: determining a longitudinal adhesion coefficient of each wheel on the basis of first wheel information and a plurality of scenario adhesion coefficients of each wheel, the first wheel information comprising a longitudinal stiffness, a slip rate, and a nominal longitudinal force (S201); on the basis of the longitudinal adhesion coefficients of a plurality of wheels, determining a first longitudinal adhesion coefficient and a first confidence of a vehicle in a low adhesion state, and a second longitudinal adhesion coefficient and a second confidence of the vehicle in a high adhesion state (S202); and determining a longitudinal adhesion coefficient of the vehicle on the basis of the first longitudinal adhesion coefficient, the first confidence, the second longitudinal adhesion coefficient and the second confidence (S203), thereby improving the accuracy of determining the longitudinal adhesion coefficient of the vehicle.

This application discloses a method, device, equipment, and medium for rail vehicle operation control based on onboard edge computing, relating to the field of vehicle operation control technology. The method includes: acquiring pre-collected historical operation-related data of the rail vehicle; the historical operation-related data includes vehicle operation parameters, environmental monitoring parameters, and real-time track surface images; preprocessing the historical operation-related data and dividing it according to track surface conditions to construct a target training dataset; training an initial adhesion coefficient estimation model using the target training dataset to obtain a trained adhesion coefficient estimation model, and then performing trimming and fine-tuning to obtain a target adhesion coefficient estimation model; deploying the target adhesion coefficient estimation model on the onboard edge device of the target rail vehicle, so that the onboard edge device can use the target adhesion coefficient estimation model to estimate the wheel-rail adhesion coefficient of the target rail vehicle, and perform operation control of the target wheel-rail vehicle based on the target wheel-rail adhesion coefficient.

The invention relates to a vehicle control method and device, a vehicle, a storage medium and a program product, and belongs to the technical field of vehicles. Determining an estimated adhesion coefficient of the road according to the road information; taking the larger one of the estimated adhesion coefficient and the utilization adhesion coefficient of the wheels of the vehicle as a target adhesion coefficient corresponding to the wheels; and determining the upper limit value of the energy recovery torque of the vehicle according to the target adhesion coefficient of the wheels. Thus, the upper limit value suitable for the energy recovery torque of the current vehicle can be dynamically determined, wheel locking caused by the large energy recovery torque is avoided, and the stability of the vehicle is guaranteed.

A vehicle slip control method and a related apparatus, which relate to the technical field of vehicles. The method comprises: acquiring first information; on the basis of the first information, acquiring a target active force to be output by a suspension of a vehicle; and controlling the suspension to output the target active force. The first information comprises the type of a slip road surface that the vehicle is about to pass on a first road section ahead of the vehicle, and friction coefficients between different types of slip road surfaces and the wheels of the vehicle are different. The target active force comprises a downward force that acts on one or more wheels of the vehicle and is directed toward the ground. By means of the present solution, vehicle slippage can be effectively suppressed on a road surface having a low adhesion coefficient.

The application provides a multi-sensor-based road friction dynamic inversion Internet of Things system and method, and relates to the field of vehicle road safety. The system comprises a management platform, a vehicle-road cooperation network and a plurality of vehicle terminals. The method is executed by the system, and the method comprises: by each vehicle terminal, determining the adhesion coefficient of the wheel and the road surface contact based on multi-dimensional mechanical data; determining the confidence of the adhesion coefficient based on the wheel slip rate; by the management platform, acquiring the vehicle driving information of the vehicle terminal, the adhesion coefficient corresponding to the wheel and the confidence of the adhesion coefficient; based on the vehicle driving information of each vehicle terminal, the plurality of adhesion coefficients and the plurality of confidences, determining the fusion adhesion coefficient corresponding to the grid area and transmitting to the vehicle terminal; and by the vehicle terminal, determining the target driving speed of the vehicle based on the fusion adhesion coefficient, and driving the vehicle to the target driving speed within the target time. The application can provide reliable road surface state data support for automatic driving and intelligent traffic.

The present application relates to a method for predicting the optimal slip ratio of a vehicle for non-standard road surfaces, which includes: determining the current slip ratio and the current utilization adhesion coefficient of the host vehicle through a first formula and a second formula respectively, where the utilization adhesion coefficient is used to characterize the utilization degree of the adhesion coefficient between the vehicle wheels and the ground, and there is a corresponding relationship between the slip ratio and the utilization adhesion coefficient; based on the current utilization adhesion coefficient, calculating the first predicted optimal slip ratio of the host vehicle through a first equation; determining the second predicted optimal slip ratio according to the extreme point of the second equation; and determining the current optimal slip ratio of the host vehicle according to the first predicted optimal slip ratio and the second predicted optimal slip ratio. It solves the problem that the current optimal slip ratio calculation method has a certain lag and is difficult to provide support for real-time control.

The present invention relates to a device for improving the adhesion coefficient of a rail vehicle. The device comprises a rail vehicle wheel, a cleaning device, and a rail on which the rail vehicle travels. The rail vehicle wheel is coupled to the cleaning device so that the cleaning device acts on the wheel when required. The cleaning device is arranged and designed to at least reduce moisture adhering to the wheel rolling surface before the wheel rolling surface contacts the rail, thereby improving the adhesion coefficient in the contact area between the wheel rolling surface and the rail.