Locomotive speed measurement adjustment device

Abstract

A locomotive speed measurement adjustment device, when satellite positioning speed measurement is effective, satellite positioning speed measurement data is used to set the wheel / vehicle speed ratio adjustment model parameters and the locomotive radar speed adjustment model parameters; when satellite positioning speed measurement is not effective, the previous model parameters are used to calculate new model parameters; and then the model parameters are used to calculate the locomotive speed. Meanwhile, the automatic judgment of whether the locomotive is in the variable speed motion state is performed on the satellite positioning data transmission time, that is, the optimization calculation of the number of delay interval periods, so as to obtain the accurate number of delay interval periods, and further ensure the accuracy and reliability of the aforementioned locomotive speed calculation.

Description

Technical Field

[0001] This invention belongs to the field of locomotive traction control technology, and in particular relates to a locomotive speed measurement and adjustment device. Background Technology

[0002] Due to creep, especially wheel slippage, the locomotive wheelset speed does not match the actual locomotive speed. Furthermore, when determining whether wheel slippage has occurred and calculating creep rate and creep degree, it is necessary to measure both the locomotive wheelset speed and the locomotive speed separately; the wheelset speed cannot be used to represent the locomotive speed. Locomotive speed is commonly measured using radar or satellite positioning. Satellite positioning speed measurement uses satellite positioning to track the locomotive's speed and position in real time, transmitting this information to the locomotive control unit for processing to obtain the final locomotive speed. Satellite positioning speed measurement can overcome errors caused by wheel slippage and wheel slippage, but its accuracy is greatly affected by weather and terrain, and it cannot achieve 100% speed measurement. There is also data transmission delay, which varies depending on distance and ionospheric conditions, affecting the real-time performance of speed measurements. Radar speed measuring devices are generally installed under the locomotive, with the radar antenna at a certain angle to the ground. The radar waves are emitted in the direction of the vehicle. When the vehicle moves relative to the ground, the received radar waves will experience a frequency shift. This shift is determined based on the radar wavelength, frequency shift amount, and angle. By calculating data such as radar installation height, the locomotive speed can be obtained; however, the included angle... Data such as radar installation height may fluctuate over time, and the road conditions for locomotives are not consistent, so the radar installation height may also change with the road conditions, which will affect the accuracy of radar speed measurement.

[0003] Train operation relies on the interaction between wheels and rails. Only when effective adhesion between wheels and rails is ensured can the power of the traction motor be further utilized. Wheel-rail adhesion characteristics are related not only to the traction locomotive itself and the wheel and rail materials, but also to a series of uncertain factors that change with time and space, such as track conditions and rail surface cleanliness. If the traction force during locomotive operation exceeds the available adhesion between wheels and rails, the excess traction force will accelerate wheel spinning, rapidly increasing the relative sliding speed and quickly reducing the available adhesion. This will cause wear and even damage to the wheels and rails, increasing railway maintenance costs and threatening the safe operation of the locomotive. Because locomotive operating conditions are highly variable, changes in driver operation or deterioration of track conditions during traction can lead to slippage that cannot be completely avoided. Currently, domestic AC / DC locomotives mainly employ a combined correction method for slippage and anti-skid control. This method first assesses wheel acceleration; if acceleration exceeds a certain threshold, it indicates severe slippage, and the driving torque of the moving wheels is rapidly and deeply reduced, thus decreasing the locomotive's traction. If wheel acceleration does not exceed the threshold, creep speed is assessed; if creep speed exceeds the threshold, the driving torque is adjusted significantly; otherwise, it is considered normal operation. The current combined correction method uses two or more individual threshold conditions to determine slippage. When slippage has not occurred, it cannot comprehensively assess the risk of slippage; when slippage has already occurred, it cannot comprehensively assess the degree of slippage. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by providing a locomotive speed measurement and adjustment device, comprising a speed adjustment calculation unit, a locomotive wheel rotation speed acquisition unit, a locomotive radar speed acquisition unit, and an onboard satellite positioning system speed acquisition unit; the locomotive wheel rotation speed acquisition unit periodically acquires the locomotive wheel rotation speed V from axle 1 to axle n. j (h), the locomotive radar speed acquisition unit periodically acquires the locomotive radar speed W(h), and the vehicle-mounted satellite positioning system speed acquisition unit periodically acquires the vehicle-mounted satellite positioning system speed U(k) and positioning status information X(k); the period for acquiring the vehicle-mounted satellite positioning system speed and positioning status information is T. U The period for collecting the locomotive radar speed and locomotive wheel rotation speed is T. V T U Greater than T V The value of j is one from 1 to n, where n is the number of axles of the locomotive.

[0005] The locomotive speed V and the creep rate of change x from axle 1 to axle n were obtained by iterative calculation. j2 The method is:

[0006] Step 1: Read the vehicle-mounted satellite positioning system speed U(k) and positioning status information X(k) at the time of the kth iteration calculation.

[0007] Step 2: Read the locomotive wheel rotation speeds V from axle 1 to axle n, which were collected at the synchronous acquisition time point of the vehicle-mounted satellite positioning system speed U(k). j (k) and locomotive radar speed W(k).

[0008] Step 3: Determine if the vehicle-mounted satellite positioning system speed is valid; if the vehicle-mounted satellite positioning system speed is valid, proceed to step 4; if the vehicle-mounted satellite positioning system speed is invalid, proceed to step 5.

[0009] Step 4, according to the formula

[0010]

[0011] Setting the current radar velocity ratio coefficient P W (k) and the wheel / vehicle speed adjustment coefficient P for current axle 1 to axle n j (k); Let the radar velocity adjustment coefficient P W equals P w (k), proceed to step 6.

[0012] Step 5: Calculate and adjust the parameters of the locomotive radar speed adjustment model, that is, for m points (k-1, P... w (k-1)), (k-2,P W (k-2)), ..., (km,P) W (km) is used to perform linear fitting to obtain the first-order fitting line for the radar velocity ratio. Points (k, P) on the first-order fitting line for the radar velocity ratio are taken. W * The value P on (k) W * (k) represents the current radar velocity ratio coefficient P. W (k). Let the radar speed adjustment coefficient P W equals P W (k), according to formula

[0013]

[0014] Calculate the radar synchronization adjustment speed W * (k). According to formula

[0015]

[0016] Adjust the wheel / vehicle speed adjustment coefficient P for the current axle 1 to axle n j (k); Proceed to step 6.

[0017] Step 6, according to the formula

[0018]

[0019] Calculate the current locomotive speed V C (h) Take the locomotive speed V as the current locomotive speed V c (h).

[0020] For m points (k, P) on axis j j (k)), (k-1,P j (k-1)), ..., (k-m+1, P j (k-m+1)) is used to perform linear fitting to obtain the first-order fitting line of the axle j wheel / vehicle speed ratio coefficient. The point (k, U) on the first-order fitting line of the axle j wheel / vehicle speed adjustment coefficient is taken. j The value of (k)U j (k) is the wheel / vehicle speed ratio coefficient U of axle j. j (k); m is greater than or equal to 3. According to the formula...

[0021]

[0022] Calculate the rate of change of creep of axis j x j2 .

[0023] The τth locomotive radar speed acquisition time before the sampling time of the vehicle-mounted satellite positioning system speed U(k) is the synchronous acquisition time point of the vehicle-mounted satellite positioning system speed U(k), where τ is the number of delay interval periods. The number of delay interval periods τ is the acquisition period T converted from the time lag between the acquisition time of the vehicle-mounted satellite positioning system speed and the acquisition time of the locomotive wheel rotation speed and the locomotive radar speed. V The multiple value. The method to obtain the number of delay interval periods τ is to satisfy the following condition:

[0024] When the vehicle's speed is valid in the most recent m1 consecutive judgments of the onboard satellite positioning system, the number of delay interval periods τ is calculated; where β(ki) is the locomotive acceleration change rate in the most recent m1 times, β(ki) when i equals 0 is the locomotive acceleration change rate β(k) at the current moment; β(ki) when i equals 1 to m1-1 are the locomotive acceleration change rates obtained when calculating the number of delay interval periods in the previous m1-1 times; ε is the acceleration change threshold greater than 0. The locomotive acceleration change rate is calculated according to the formula...

[0025]

[0026] The calculation is performed; where α(k) is the most recently collected locomotive acceleration, and α(k-1) is the previously collected locomotive acceleration; the locomotive acceleration is calculated according to the formula...

[0027]

[0028] The calculation is performed; where U(k-1) is the speed of the vehicle-mounted satellite positioning system in the previous acquisition of U(k). Let the parameter to be optimized be the number of delay intervals, τ. * and radar speed adjustment coefficient p w * The number of delay intervals is τ. * At that time, the locomotive radar speed acquired at the synchronous acquisition time point corresponding to U(ki) is W. * (ki), the minimum optimization objective function is

[0029]

[0030] Take the number of delay intervals τ that satisfy the optimal value Q. * Let τ be the number of delay interval periods; * The value range is greater than 0 and less than 2 / T V integers, p W * The value range is greater than or equal to 0.8 and less than or equal to 1.2; m1 is greater than or equal to 10.

[0031] The vehicle-mounted satellite positioning system speed is valid when the positioning status in the positioning status information X(k) is valid and the number of satellites using the positioning status information X(k) to calculate the location is greater than or equal to δ. Otherwise, the vehicle-mounted satellite positioning system speed is invalid. The value of δ is required to be greater than or equal to 4.

[0032] creep change rate x j2 Used for controlling the traction force of locomotive wheelset slippage, the method is as follows:

[0033]

[0034] Calculate the idling risk value E of axis j j ;where x j1 Let θ1 be the inter-axis velocity difference of axis j, θ2 be the inter-axis velocity difference threshold, θ2 be the creep rate of change threshold, and γ1 and γ2 be nonlinear weighted exponential factors, with γ1≥1 and γ2≥1.

[0035] Regarding the rotational speed V of the locomotive wheels j The n values ​​of (h) are compared, and the minimum value is taken as the minimum rotational speed of the locomotive wheel V0(h), and the inter-axle speed difference x of axle j is taken as the minimum value of the locomotive wheel rotational speed V0(h). j1 According to the formula

[0036] x j1 =V j (h)-V0(h)

[0037] Perform the calculation.

[0038] The condition for determining the idling of locomotive wheelset j is that when E j If ≥1, it is determined that the locomotive wheelset of axle j has idled; the traction control process for axle j idling is as follows:

[0039] Process I, the process of decreasing traction force during idling; from the idling risk value E j Starting from a value greater than or equal to 1 and continuously increasing, up to the idling risk value E. j The control ratio of traction force for shaft j to idling ends when the continuous increase changes to the beginning of decrease. j With the load reduction slope d of shaft j jd φ at the end of process I j The value is the minimum maintenance value φ jL .

[0040] Process II, the process of maintaining the minimum idling traction value; starting from the end of Process I, the idling risk value E j The control stops when the value decreases to less than 1. j Equal to the minimum maintenance value φ jL .

[0041] Process III, the traction recovery process during idling; starting from the end of Process II, until φ j Increase to a value equal to 1 and then stop, controlling φ. j To restore the slope d ju It begins to grow.

[0042] Among them, the idle traction control ratio φ j φ is the ratio between the locomotive traction force output by the idling traction force control module and the locomotive traction force input to the locomotive, and 0 ≤ φ. j ≤1. The unloading slope d of axis j jd The size is determined by the axle speed difference load reduction factor e. j Control, according to formula

[0043]

[0044] Calculate the speed difference load reduction factor e j Where γ0 is the speed difference load reduction control factor, and 1≤γ0≤2. The load reduction slope d of shaft j. jd According to the formula

[0045]

[0046] Perform the calculation, where d H d is the upper limit of the load reduction slope. L e is the lower limit of the load reduction slope. m The limit value for the speed difference load reduction factor is given, and e is also given. m =3γ0.

[0047] Locomotive speed V is used for upper limit control of locomotive traction force. The method is as follows:

[0048]

[0049] The upper limit of the locomotive traction force on axle j is controlled, wherein P jμ Calculate the adhesive weight, μ, for axis j. k It calculates the coefficient of adhesion; F j1 It is the locomotive traction force of axle j before the upper limit and amplitude control; F j2 ξ is the locomotive traction force of axle j after upper limit and amplitude control; ξ is the wheel-rail adhesion coefficient control parameter. According to the formula...

[0050]

[0051] The calculated adhesion coefficient μ is obtained. k Where a1, a2, a3, a4, and a5 are empirical formula parameters for calculating the adhesion coefficient. According to the formula...

[0052]

[0053] To determine the control parameter ξ for the wheel-rail adhesion coefficient, where R m The maximum rainfall limit is defined as 2 mm / h to 2.5 mm / h; C 11 For real-time rainfall, the output range is 0 to R. m C 12 b3 is the rail surface dryness / humidity, with an output range of 0 to 1, where 0 indicates the rail surface is completely dry and 1 indicates the rail surface is completely wet; b4 is the adhesion coefficient rainfall control parameter, with a value range of 0.25≤b3≤0.4; b4 is the adhesion coefficient rail surface control parameter, with a value range of 0.7≤b4≤0.9.

[0054] The sampled locomotive wheel rotation speed is filtered to obtain the collected locomotive wheel rotation speed; the sampled locomotive radar speed is filtered to obtain the collected locomotive radar speed; the sampled vehicle-mounted satellite positioning system speed is filtered to obtain the collected vehicle-mounted satellite positioning system speed. Before collecting the first vehicle-mounted satellite positioning system speed, let...

[0055]

[0056] Where i = 1, 2, ..., m-1; j = 1, 2, ..., n.

[0057] The beneficial effects of this invention are as follows: When satellite positioning speed measurement is effective, the wheel / vehicle speed ratio adjustment model parameters and locomotive radar speed adjustment model parameters are adjusted and calculated using satellite positioning speed measurement data; when satellite positioning speed measurement is ineffective, new locomotive radar speed adjustment model parameters are calculated from the previously adjusted locomotive radar speed adjustment model parameters according to a given expression, or by using a first-order fitting straight line method. The adjusted radar speed adjustment model parameters are then used to adjust and calculate the wheel / vehicle speed ratio adjustment model parameters. Finally, based on the wheel / vehicle speed ratio adjustment model, the locomotive speed and various locomotive speed-related quantities such as the rate of change of creep in each axle, creep, and inter-axle speed difference are calculated. This method combines the advantages of high accuracy of satellite positioning speed measurement and good real-time performance of radar speed measurement, as well as its ability to operate normally for long periods, thus improving the accuracy and reliability of measuring various locomotive speed-related quantities. The locomotive speed adjustment method also employs a method to determine whether the locomotive is in a speed-changing state. If it is, it collects information from radar speed measurement, satellite positioning speed measurement, and locomotive wheelset speed measurement after the locomotive's speed change, and optimizes the satellite positioning data transmission time, i.e., the number of delay intervals, to obtain an accurate real-time satellite positioning data transmission delay time (i.e., the number of delay intervals). This further ensures the accuracy and reliability of the speed data calculated by the aforementioned locomotive speed adjustment method. Besides locomotive speed, the main factors affecting the adhesion coefficient include the condition of the rail surface and the surrounding environment. Rain affects the adhesion coefficient, but heavy rain (including torrential rain exceeding heavy rain) cleans the rail surface, and its impact on the adhesion coefficient is smaller than that of light rain. When there is no rain, the wetter the rail surface, the greater the impact on the adhesion coefficient. The adhesion coefficient control parameter adjustment model, based on the input real-time rainfall and rail surface dryness / wetness, considers their combined effects and directly calculates the adhesion coefficient control parameters using a given method. These parameters are then used to tune the adhesion coefficient empirical calculation model parameters, reflecting the influence of locomotive speed. This allows the system to adaptively adjust the adhesion coefficient based on actual road condition data such as real-time rainfall and rail surface dryness / wetness during locomotive operation. Furthermore, with the joint adjustment of the adhesion coefficient control parameter adjustment model, the system can, based on the empirical formula for calculating the adhesion coefficient derived from extensive experimental data, take into account the actual operating section and changing road conditions. This ensures that the locomotive's maximum traction limit can change in real-time with changes in road conditions, traction is performed as much as possible without wheelset slippage.When adhesion conditions worsen, even with upper limit and width restrictions, the locomotive traction force (wheel circumferential tangential force) on the wheel axle still exceeds the wheel-rail adhesion force, making wheelset slippage unavoidable. To quickly restore normal locomotive traction, this invention employs a nonlinear mathematical model to calculate the slippage risk value. It integrates multiple individual threshold judgment conditions for traditional wheelset slippage and weighted judgment conditions when none of the individual threshold conditions are met into a single whole, simplifying the judgment criteria. Even when none of the individual threshold conditions are met, it quantifies and weights multiple factors to achieve a comprehensive judgment, making slippage judgment more comprehensive and accurate. The selection of the nonlinear mathematical model minimizes the possibility of misjudgment by the weighted judgment conditions when none of the individual threshold conditions are met. Furthermore, the magnitude of the weighted judgment conditions and the relative magnitude of each weighted item can be set and adjusted through parameters, making this nonlinear mathematical model-normalized locomotive wheelset slippage judgment method applicable to different locomotive types and operating conditions. Attached Figure Description

[0058] Figure 1 A schematic diagram of the adhesion control system for an electric locomotive;

[0059] Figure 2 A flowchart illustrating the method for calculating and adjusting the control parameters of the adhesion coefficient;

[0060] Figure 3 This is a schematic diagram of the idle traction control module for axle 1 when the locomotive wheelset experiences idle.

[0061] Figure 4 The load reduction factor e1 for the speed difference of shaft 1 and x 11 A schematic diagram illustrating the relationship between / θ1;

[0062] Figure 5 A schematic diagram of the locomotive speed measurement and adjustment module;

[0063] Figure 6 Flowchart of locomotive speed adjustment method;

[0064] Figure 7 A schematic diagram of an embodiment of the first-order fitting line for the radar velocity ratio coefficient;

[0065] Figure 8 A schematic diagram of an example of a first-order fitting line for the wheel / vehicle speed ratio coefficient;

[0066] Figure 9 A flowchart for calculating the number of delay intervals;

[0067] Figure 10 A schematic diagram showing the speed acquisition delay, locomotive acceleration, and locomotive acceleration change rate of the vehicle-mounted satellite positioning system;

[0068] Figure 11 A schematic diagram showing the time points at which the locomotive wheel rotation speed and locomotive radar speed are synchronously collected, representing the speed of the vehicle-mounted satellite positioning system. Detailed Implementation

[0069] The present invention will be further described below with reference to the accompanying drawings.

[0070] An electric locomotive is an electric locomotive capable of n-axle controlled traction. Figure 1 A schematic diagram of the electric locomotive adhesion control system structure for implementing electric locomotive adhesion control methods is shown, including an adhesion coefficient control parameter adjustment model 10, a traction force limiting self-tuning module 11, an idle traction force control module 12, a locomotive speed measurement and adjustment module 13, and a rainfall and rail surface monitoring module 14. The empirical calculation model for the adhesion coefficient is...

[0071]

[0072] In equation (1), V is the locomotive speed, μ k This is for calculating the adhesion coefficient. a1, a2, a3, and a4 are empirical formula parameters for calculating the adhesion coefficient. For domestically produced axle-controlled electric locomotives HXD1C, HXD1D, HXD2, HXD3, and SS4, a1 = 0.24, a2 = 12, a3 = 100, and a4 = 8, respectively. The locomotive speed V is measured in km / h.

[0073] The input to the traction force limiting self-tuning module is F. 11 To F n1 The output of the traction force limiting self-tuning module is F, along with locomotive speed V and adhesion coefficient control parameters ξ. 12 To F n2 The traction force limiting self-tuning module uses both adhesion coefficient control parameters and an empirical calculation model of the adhesion coefficient to jointly control the upper limit and amplitude of the locomotive traction force.

[0074]

[0075] In equation (2), j is one from 1 to n; P jμ ξ represents the calculated adhesive weight of axle j, i.e., the wheel load of axle j. For a given locomotive model, the wheel load of the axle is a fixed value; ξ represents the adhesive coefficient control parameter output by the adhesion coefficient control parameter adjustment model; F j1 That is, F 11 To F n1 One of them is the locomotive traction force of axle j, which is the input of the traction force limiting self-tuning module. That is, the locomotive traction force allocated to axle j after the axle-controlled traction system performs multi-axle inter-axle coordination; F j2 That is, F 12 To F n2One of them is the locomotive traction force output by the traction force limiting self-tuning module. jμ and the traction force F of each locomotive j1 F j2 F j3 The unit is kN; when needed, the traction force of each locomotive can also be converted into torque. The upper limit of the locomotive traction force of axles 1 to n is controlled according to equation (2).

[0076] Figure 1 In this embodiment, the rainfall and track surface monitoring module includes a rainfall measurement unit and a track surface image acquisition and recognition unit. 11 Real-time rainfall measured and output by the rainfall measurement unit, in mm / 24h or mm / h. Maximum rainfall limit R. m The value range is 48mm / 24h to 60mm / 24h, or 2mm / h to 2.5mm / h. For example, if R is taken... m The rainfall threshold C0 is 2.2 mm / h. The range of C0 is 2.4 mm / 24h to 4.8 mm / 24h, or 0.1 mm / h to 0.2 mm / h, a relatively small measurable value. For example, C0 can be set to 0.1 mm / h. The rainfall measurement unit can use one of the following methods to measure rainfall: infrared scattering rainfall measurement, image visual rainfall measurement, or electrostatic hourly rainfall measurement, or a combination of two or more methods to improve measurement accuracy. When the real-time rainfall exceeds the maximum rainfall limit R... m At that time, the real-time rainfall C was taken. 11 =R m The rainfall measurement unit measures real-time rainfall and outputs it using conventional techniques in the field.

[0077] The track surface image acquisition and recognition unit acquires real-time images of the track surface, processes and recognizes these images, and outputs the current track surface humidity (C). 12 C 12 The range is 0% to 100%, or 0% to 1.0%, where 0 indicates the rail surface is completely dry, and 100% indicates the rail surface is completely wet. The rail surface image acquisition and recognition unit acquires real-time rail surface images and performs recognition processing, outputting the current rail dryness / wetness using conventional image processing techniques.

[0078] Figure 2 The model for adjusting the adhesion coefficient control parameters is based on the real-time rainfall C during locomotive operation. 11 and track surface dryness C 12 The flowchart for determining the control parameter ξ of the wheel-rail adhesion coefficient is as follows:

[0079] First, based on real-time rainfall C 11 Calculate the first adhesion coefficient control parameter value ξ1.

[0080]

[0081] Second, based on the track surface dryness C 12 Calculate the value of the second adhesion coefficient control parameter ξ2.

[0082] ξ2=1+C 12 (b2-1) (4)

[0083] Third, based on real-time rainfall C 11 The size of the adhesion coefficient control parameter ξ is determined by its magnitude.

[0084]

[0085] In equations (3) and (4), b1 is the lower threshold of the adhesion coefficient control parameter, and its value ranges from 0.2 to 0.35, for example, b1 is 0.3. b2 is the middle threshold of the adhesion coefficient control parameter, and its value ranges from 0.7 to 0.85, for example, b2 is 0.8. During heavy rainfall, the value of the adhesion coefficient control parameter ξ is controlled by the real-time rainfall; during light rainfall, the value of the adhesion coefficient control parameter ξ is controlled by the dryness or wetness of the rail surface.

[0086] Based on the real-time rainfall C during locomotive operation 11 and track surface dryness C 12 The control parameter ξ for the wheel-rail adhesion coefficient can also be determined according to the formula.

[0087]

[0088] The calculation is performed using the following parameters: b3 is the adhesion coefficient rainfall control parameter, with a value range of 0.25 ≤ b3 ≤ 0.4 (e.g., b3 = 0.35); b4 is the adhesion coefficient rail surface control parameter, with a value range of 0.7 ≤ b4 ≤ 0.9 (e.g., b4 = 0.8). The value of the adhesion coefficient control parameter ξ is simultaneously controlled by the real-time rainfall and the rail surface dryness / wetness. A smaller value for b3 indicates that the rainfall magnitude has a greater impact on the value of the adhesion coefficient control parameter ξ.

[0089] The wheel-rail adhesion coefficient control parameter ξ is the same for shafts 1 to n.

[0090] The locomotive wheel idle traction control module, i.e., the locomotive wheelset idle traction control device, receives the locomotive traction force F from axle 1 to axle n as input. 12 To F n2 , and C 21 To C 2n The output is the locomotive traction force F from shaft 1 to shaft n, after idling judgment and load reduction control. 13 To F n3The idling traction control module uses an established nonlinear mathematical model to calculate the idling risk value, E, for axle j. j According to the formula

[0091]

[0092] Perform the calculation. In equation (7), x j1 Let θ be the inter-axis velocity difference on axis j, and θ1 be the inter-axis velocity difference threshold; x j2 Let θj be the rate of change of creep friction on axis j, and θ2 be the threshold for the rate of change of creep friction. γ1 and γ2 are nonlinear weighting exponential factors, and γ1 ≥ 1 and γ2 ≥ 1. The inter-axis velocity difference xj j1 , creep change rate x j2 All are non-negative values. The condition for determining the idling of the locomotive wheelset on axle j is that when E... j If the value is ≥1, then the locomotive wheelset of axle j is judged to be spinning freely. Combining equation (7) and the free spin judgment condition, the free spin judgment logic obtained by decomposition is: there are 3 situations (or one of the 3 conditions must be met) that the locomotive wheelset of axle j is spinning freely, namely, ① when the speed difference between the axles is x j1 ① When it is greater than or equal to the threshold θ1; ② Or, when the rate of change of creep x j2 ③ When the inter-axis velocity difference x is greater than or equal to the threshold θ2; j1 Less than the threshold θ1 and the rate of change of creep x j2 Less than the threshold θ2 and the idling risk value E j When greater than or equal to 1. The first two conditions ① and ② are individual threshold conditions, meaning that each individual condition satisfies x. j1 When ≥θ1, or when a single term satisfies x j2 When ≥θ2, E is satisfied. j A value greater than or equal to 1 satisfies the condition for the idle judgment. Condition ③ is a weighted judgment condition when none of the individual threshold conditions are met. The larger the values ​​of γ1 and γ2, the greater the influence of the individual threshold judgment, and the smaller the effect of the weighted judgment of condition ③. When both γ1 and γ2 are sufficiently large, the main body of the idle judgment logic is the individual threshold conditions ① and ②, and the effect of condition ③ is very small or almost non-existent. For example, when γ1 and γ2 are both equal to 100, even if x... j1 / θ1、x j2 / θ2 is equal to 0.99, and the idling risk value E j Only 0.555, E j Since it is also less than 1, it cannot meet the condition for judging idle spinning, and the weighted judgment has almost no effect. The smaller the values ​​of both γ1 and γ2 are, the greater the effect of the weighting of condition ③. For example, when both γ1 and γ2 are 1, if x j1 / θ1、x j2 If / θ2 is equal to 0.59, then E jThe value equals 1.01, which already satisfies the idling judgment condition; when γ1 and γ2 are both 1, if x j1 / θ1 equals 0.8, x j2 / θ2 equals 0.33, then E j The value equals 1.004, which already satisfies the idling judgment condition; when γ1 and γ2 are both 2, if x j1 If / θ1 equals 0.8, then x j2 When / θ2 equals 0.72, E j The value equals 0.986, which does not meet the condition for idling; when both γ1 and γ2 are 2, if x j1 If / θ1 equals 0.8, then x j2 When / θ2 needs to be equal to 0.73, E j A value equal to 1.002 is required to satisfy the idling judgment condition. The relative magnitudes of the nonlinear weighting exponential factors γ1 and γ2 are used to determine the relative influence between weighting terms and do not affect the judgment condition for each individual term exceeding the threshold. The larger the value of either γ1 or γ2, the smaller the weighting effect of the corresponding judgment term; conversely, the smaller the value of either γ1 or γ2, the larger the weighting effect of the corresponding judgment term. For example, if γ1 is small and γ2 is large, then the idling risk value E in condition ③ will be large. j In the calculation, x j1 The role of the term / θ1 in the weighted calculation is greater than that of the term x. j2 / θ2 is large, but the effect of the single threshold conditions ① and ② remains unchanged. As long as either ① or ② reaches or exceeds the threshold, the idling judgment condition is still satisfied.

[0093] The risk value E of idling on axis j j Or according to the formula

[0094]

[0095] Perform the calculation. In equation (8), x j1 θ1 is the inter-axis velocity difference threshold; x j2 x is the rate of change of creep, θ2 is the threshold for the rate of change of creep; j3 Let θ be the creep coefficient, and θ3 be the creep threshold; γ1, γ2, and γ3 are nonlinear weighting exponential factors, and γ1≥1, γ2≥1, and γ3≥1. The inter-axis velocity difference x j1 , creep change rate x j2 Creepiness x j3 All are non-negative values. The condition for determining the idling of the locomotive wheelset on axle j is that when E... j If the value is ≥1, then the locomotive wheelset of axle j is judged to be spinning freely. Combining equation (8) and the free spin judgment condition, the free spin judgment logic obtained by decomposition is: there are 4 situations (or one of the 4 conditions must be met) that the locomotive wheelset of axle j is spinning freely, namely, ① when the speed difference between the axles is x j1① When it is greater than or equal to the threshold θ1; ② Or, when the rate of change of creep x j2 ③ When the creep coefficient is greater than or equal to the threshold θ2; or, when the creep coefficient x j3 When the speed difference between axes is greater than or equal to the threshold θ3; ④ Or, when the speed difference between axes is greater than or equal to the threshold θ3. j1 Less than the threshold θ1 and the rate of change of creep x j2 Less than the threshold θ2 and the creep x j3 Less than the threshold θ3 and the idling risk value E j When greater than or equal to 1. The first three conditions ①②③ are individual threshold conditions, meaning each condition satisfies x. j1 When ≥θ1, or when a single term satisfies x j2 When ≥θ2, or when a single term satisfies x j3 When ≥θ3, E is satisfied. j A value greater than or equal to 1 satisfies the condition for the idle judgment. Condition ④ is a weighted judgment condition when none of the individual threshold conditions are met; the larger the values ​​of γ1, γ2, and γ3, the greater the influence of the individual threshold judgment, and the smaller the effect of the weighted judgment; when γ1, γ2, and γ3 are sufficiently large, the main body of the idle judgment logic is the individual threshold conditions ①②③, and the effect of condition ④ is very small, or almost non-existent; for example, when γ1, γ2, and γ3 are all equal to 100, even if x j1 / θ1、x j2 / θ2、x j3 / θ3 is equal to 0.99, and the idling risk value E j Only 0.833, E j Since the values ​​are also less than 1, the condition for idling cannot be met, and the weighted judgment has almost no effect. When the values ​​of γ1, γ2, and γ3 are small, the weighting effect of condition ④ is greater. For example, when γ1, γ2, and γ3 are all 1, if x j1 / θ1、x j2 / θ2 is equal to 0.59, x j3 When / θ3 equals 0, E j It is also equal to 1.01, which satisfies the idling judgment condition; when γ1, γ2, and γ3 are all 2, if x j1 / θ1 equals 0.8, x j2 If / θ² equals 0, then x j3 When / θ3 needs to be equal to 0.73, E j The condition for idling is satisfied only when x equals 1.002; when γ1, γ2, and γ3 are all 2, if x j1 / θ1 equals 0.7, x j2 If / θ² equals 0.7, then x j3 When / θ3 equals 0.54, E j The value equals 0.996, which does not meet the condition for idling; when γ1, γ2, and γ3 are all 2, if x j1 / θ1 equals 0.7, x j2 If / θ² equals 0.7, then x j3 When / θ3 equals 0.55, E j A value equal to 1.006 is required to satisfy the idling judgment condition. The relative magnitudes of the nonlinear weighting exponential factors γ1, γ2, and γ3 are used to determine the relative influence between weighting terms and do not affect the judgment condition for each individual term exceeding the threshold. The larger the value of any one of γ1, γ2, and γ3, the smaller the weighting effect of the corresponding judgment term; conversely, the smaller the value of any one of γ1, γ2, and γ3, the larger the weighting effect of the corresponding judgment term. For example, if γ1 is small and γ2 and γ3 are large, then the idling risk value E in condition ④ will be high. j In the calculation, x j1 The role of the term / θ1 in the weighted calculation is greater than that of the term x. j2 / θ2、x j3 / θ3 are all large, but the effects of individual threshold conditions ①②③ remain unchanged. As long as any one of ①②③ reaches or exceeds the threshold, the idling judgment condition is still satisfied.

[0096] The aforementioned values ​​for θ1 range from 0.05 m / s to 0.4 m / s; θ2 ranges from 0.0001 m / s to 0.005 m / s; and θ3 ranges from 0.005 m / s to 0.05 m / s. The threshold values ​​θ1, θ2, and θ3 for axes 1 to n are the same. j1 x j2 x j3 The units are the same as those of θ1, θ2, and θ3, respectively. The value of j is one from 1 to n. The idling risk value of axle 1 to axle n of the locomotive is calculated according to formula (7) and judged separately; or, the idling risk value of axle 1 to axle n is calculated according to formula (8) and judged separately.

[0097] The electric locomotive wheelset traction control device determines when wheel slip occurs on axle j and reduces the traction control ratio φ. j This is used to reduce the traction force of locomotive J on axle and achieve idling traction force control. Figure 3 This is a schematic diagram of the traction control for axle 1 in the traction control module when the locomotive wheelset experiences idling. φ1 represents the traction control ratio for axle 1, and d... 1d Let d be the unloading slope of shaft 1. 1u The recovery slope of axis 1. Idle traction control ratio φ j The locomotive traction force F output by the idling traction control module is axle j. j3 With the input axle j locomotive traction force F j2 The ratio between them satisfies

[0098] F j3 =φ j ·Fj2 0≤φ j ≤1 (9)

[0099] The relationship. Figure 3 Before t1, the idling risk value E1 is less than 1, the locomotive wheelset of axle 1 does not idle, the idling traction control ratio φ1 is equal to 1, and the idling traction control module does not implement idling traction control for axle 1. The value of j is one from 1 to n. In the idling traction control module, axles 1 to n are calculated according to equation (9). The idling traction control process for axle j is as follows:

[0100] Process I, the process of decreasing traction force during idling; from the idling risk value E j Starting from a value greater than or equal to 1 and continuously increasing, up to the idling risk value E. j The control ratio of traction force for shaft j to idling ends when the continuous increase changes to the beginning of decrease. j With the load reduction slope d of shaft j jd Decrease; φ at the end of process I j The value is the minimum maintenance value φ jL . Figure 3 In the example, process I starts at time t1 and ends at time t2; the idling traction control module controls φ1 to reduce the load at an inclination d. 1d The value of φ1 at the end of process I begins to decrease and is the minimum maintenance value φ. 1L The minimum sustaining value φ for axis j. jL Not less than 0.

[0101] Process II, the process of maintaining the minimum idling traction value; starting from the end of Process I, the idling risk value E j The process continues until the value decreases to less than 1, at which point the idling traction control module controls φ. j Equal to the minimum maintenance value φ jL . Figure 3 In this process, process II begins at time t2 and ends at time t3.

[0102] Process III, the traction recovery process during idling; starting from the end of Process II, until φ j The process ends when the value increases to 1, and the idling traction control module controls φ. j To restore the slope d ju It begins to grow. Figure 3 In this process, process III begins at time t3 and ends at time t4.

[0103] When the risk value of idling is E j When the value increases from less than 1 to greater than or equal to 1, it satisfies the risk value E of idling. j The condition is that the value is greater than or equal to 1 and continues to increase. When the φ of axis j... j It equals 1, and its idling risk value E jWhen the value is consistently less than 1, the idle traction control module does not perform idle traction control on shaft j.

[0104] The rate of load reduction of the locomotive's traction force on axle j is determined by the load reduction slope d. jd Control; inter-shaft speed difference x j1 The smaller the load reduction slope d jd The smaller the value, the greater the inter-axis velocity difference x. j1 The larger the slope d, the more unloading slope d jd The larger the value, the greater the load reduction slope d of shaft j. jd The magnitude is determined by the speed difference load reduction factor e of shaft j. j Control, according to formula

[0105]

[0106] Calculate the speed difference load reduction factor e j Where γ0 is the speed difference load reduction control factor, and 1≤γ0≤2; the same speed difference load reduction control factor value is taken from shaft 1 to shaft n. Figure 4 The load reduction factor e1 for the speed difference of shaft 1 when γ0 equals 1 and x 11 A schematic diagram of the relationship between / θ1, e m The limit value for the speed difference load reduction factor is x. 11 When / θ1 approaches ∞, the speed difference load reduction factor value, atan() in equations (7), (8), and (10) is the arctangent function, therefore we have Speed ​​difference load reduction factor limit e from shaft 1 to shaft n m equal.

[0107] The unloading slope d of shaft j jd According to the formula

[0108]

[0109] Perform the calculation, where d H d is the upper limit of the load reduction slope. L d is the lower limit of the load reduction slope. H and d L The values ​​are all selected between 0.3 / s and 2 / s, and d H ≥d L For example, choose d H =0.9, d L =0.4; when d is selected H =d L When the load reduction slope d1 = d L The load reduction factor e does not change with the speed difference. j It changes with the change. Axes 1 to n take the same upper limit value of the load reduction slope d. H and the lower limit of the load reduction slope d L .

[0110] unloading slope d jd The value represents the control φ j The rate of decrease. For example, the unloading slope d 1d When the descent rate is chosen to be 0.5 / s, then 1 s The time will be reduced by 50%, which can be 1 s Time reduced from 100% to 50%, or 1 s Time φ1 decreases from 80% to 30%, and so on. Recovery slope d ju The rate of ascent is selected between 0.05 / s and 0.5 / s, for example, the recovery slope d. 1u When the rate of ascent is chosen to be 0.2 / s, then 1 s The time will increase φ1 by 20%, which can be 1 s Time φ1 increases from 40% to 60%, or 1 s The time is increased from 50% to 70%, and so on. The same recovery slope is taken from axis 1 to axis n.

[0111] The two terms in equation (7), the three terms in equation (8), and each term in equation (10) include the following:

[0112]

[0113] Function terms of the form shown, where ρ represents x j1 / θ1、x j2 / θ2、x j3 / θ3, the basic shape of this formal function is as follows Figure 4 As shown, when the threshold is not exceeded (i.e., 0 ≤ ρ < 1), the slope of the curve increases with the increase of ρ. This means that the closer the relevant value is to the corresponding threshold, the greater the impact of its change on the function term. For example, with x... j1 Taking θ1 as an example, x j1 The closer to θ1, the better x j1 Even a small change in can cause a large change in e0. This characteristic of the function amplifies the value to be judged near the threshold (i.e., x). j1 x j2 x j3 The effect of the change is more sensitive near the threshold; conversely, when the value to be judged is far from the threshold, the sensitivity is reduced to avoid the possibility of misjudgment of the weighted judgment condition when none of the individual threshold conditions are met. In equations (7) and (8), the larger the values ​​of γ1, γ2, and γ3, the greater the change in the slope of the curve when 0≤ρ<1, the more sensitive it is near the threshold and the less sensitive it is far from the threshold.

[0114] In equation (12), when ρ≥1, the slope of the curve decreases as ρ increases, and when ρ approaches ∞, e0=3, meaning that the more the relevant value exceeds the corresponding threshold, the smaller the impact of its value change on the function term, eventually tending towards a limit value. For the function in equation (10) as a whole, when ρ≥0, x… j1 The closer to θ1, the more x j1 Changes cause e j The higher the sensitivity to change; x j1 The closer to θ1, the more x j1 Changes cause e j The lower the sensitivity to changes, the more sensitive the unloading slope d becomes. jd Also x j1 The closer x is to θ1, the better. j1 Changes in the unloading slope d jd The greater the impact of the change, and the more ρ approaches ∞, the better. j There is a limit value; theoretically, even if x... j1 Exceeding θ1 by a large margin, the unloading slope d jd The reduction of is also finite.

[0115] The nonlinear mathematical models (7) and (8) for calculating the risk of wheel spin both include terms for the speed difference between axles and the rate of change of creep. The rate of change of creep is the speed at which creep changes; the larger the value, the faster the creep increases, and the higher the risk of wheel spin. When wheelsets of a multi-axle locomotive spin, there is usually a sequence. A large speed difference between axles indicates that the axle has already spin, or that the risk of spinning is high. The magnitude of the speed difference between axles directly reflects the degree of danger of wheel spin or the extent to which wheel spin has already occurred. Equation (8) also includes a creep term. Creep is the relative difference between the speed of the locomotive wheelset and the speed of the locomotive. Its value also reflects how far the locomotive wheelset is from spinning or the extent to which it has already spun. However, creep is a relative value related to the speed of the locomotive, and its effect is greater at low speeds than at high speeds. The speed difference between axles is an absolute value, and its effect is greater at high speeds. When calculating the risk value of idling, you can choose either formula (7) or formula (8) as needed. When choosing formula (8), since the effects of the speed difference between shafts and the creep are similar, it should be taken into consideration when determining the size of γ1 and γ3.

[0116] The nonlinear mathematical model for calculating the risk value of wheel slip, namely Equation (7) or Equation (8), and the corresponding wheel slip judgment conditions, integrate the traditional single-threshold judgment conditions for wheel slip of multiple wheelsets and the weighted judgment conditions when none of the single-threshold conditions are met into a whole, simplifying the judgment basis. Furthermore, when none of the single-threshold conditions are met, multiple factors are quantified and weighted to achieve a comprehensive judgment of multiple factors, making the wheel slip judgment more comprehensive and accurate. The selection of the nonlinear mathematical model can minimize the possibility of misjudgment by the weighted judgment conditions when none of the single-threshold conditions are met. At the same time, the magnitude of the weighted judgment conditions can be set and adjusted by parameters, and the relative magnitude of each weighted term can also be set and adjusted by parameters, making the wheel slip judgment method of the locomotive wheelsets normalized by this nonlinear mathematical model applicable to different locomotive types and operating conditions.

[0117] Currently, commonly used combined correction methods in China employ a fixed torque unloading strategy regardless of the degree of idling, failing to consider the wheel-rail adhesion state during unloading. This leads to several problems: first, insufficient unloading depth results in incomplete suppression of idling; second, excessive unloading depth causes locomotive traction loss; and third, unloading only stops when acceleration or creep rate falls below a set threshold, potentially resulting in excessive unloading depth. The idling traction control module of this invention controls idling traction based on an idling risk value that incorporates multi-factor comprehensive judgment. Both the degree and process of locomotive traction reduction are controlled by the idling risk value, reflecting the wheel-rail adhesion state. This effectively avoids situations where insufficient unloading depth leads to incomplete suppression of idling, or excessive unloading depth results in locomotive traction loss. Unloading stops when the idling risk value changes from increasing to decreasing, further mitigating the consequences of excessive unloading depth. The non-linear characteristics of the idling risk value allow judgments with higher risks to have a more significant control effect. When a wheel pair on a certain axle is determined to be spinning, the rate of traction load reduction on that axle is non-linearly controlled by the magnitude of the speed difference between the axles. A larger speed difference results in a faster reduction rate, allowing wheel pairs that started spinning earlier to reduce load faster than other axles. This non-linear control of the traction load reduction rate based on the speed difference ensures high control sensitivity near the speed difference threshold, improving the control effect on wheel pairs with severe spinning and thus enhancing overall spinning control. The magnitude of the non-linear influencing factor on the traction load reduction rate based on the speed difference can be adjusted by setting parameters to adapt to different situations and achieve optimal results.

[0118] Figure 5 This diagram illustrates the structure of a locomotive speed measurement and adjustment module, or more specifically, a locomotive speed measurement and adjustment device, for implementing a locomotive speed adjustment method. The locomotive wheel rotation speed acquisition unit 101 periodically acquires the locomotive wheel rotation speed V. j(h), that is, the locomotive wheel rotation speed V1(h) to V from axle 1 to axle n. n (h), the acquisition cycle time is T V The locomotive wheel rotation speed acquisition unit 101 outputs the acquired locomotive wheel rotation speed V from axle 1 to axle n. j (h), that is, V1(h) to V n (h)(including V1(k) to V n (k) is the speed adjustment calculation unit 104, where n is the number of axles on the locomotive. For example, for an 8-axle locomotive, n equals 8; for a 6-axle locomotive, n equals 6. The locomotive radar speed acquisition unit 103 periodically acquires the locomotive radar speed W(h), with an acquisition period of T. V The locomotive radar speed acquisition unit 103 outputs the acquired locomotive radar speed W(h) (including W(k)) to the speed adjustment calculation unit 104; the vehicle-mounted satellite positioning system speed acquisition unit 102 periodically acquires and outputs the vehicle-mounted satellite positioning system speed U(k) and positioning status information X(k) to the speed adjustment calculation unit 104; the speed adjustment calculation unit 104 adjusts and calculates the wheel / vehicle speed ratio adjustment model parameters and the locomotive radar speed adjustment model parameters based on the input information, and outputs the locomotive speed, creep, creep rate of change, and inter-axle speed difference. Specifically, the combination switch SW1 in the speed adjustment calculation unit 104 is controlled by the positioning status information X(k) input from terminal 5; when it is determined that the vehicle-mounted satellite positioning system speed is valid based on X(k), terminal 1 of the combination switch SW1 is connected to terminals 2 and 3, and the parameters of the wheel / vehicle speed ratio adjustment model and the locomotive radar speed adjustment model are adjusted by the vehicle-mounted satellite positioning system speed U(k); terminal 4 is left floating, and the radar synchronization adjustment speed W output by the locomotive radar speed adjustment model is... * (k) Not used at this time, i.e., W * (k) has no effect at this time. When it is determined that the vehicle-mounted satellite positioning system speed is invalid based on X(k), terminal 4 of control SW1 is connected to terminal 2. The locomotive radar speed adjustment model recursively derives the parameters of the locomotive radar speed adjustment model according to the given method. The locomotive radar speed adjustment model adjusts the locomotive radar speed value W(k) at the synchronous acquisition time point in the locomotive radar speed value W(h) to obtain the radar synchronous adjustment speed W. * (k), speed W is adjusted synchronously by radar. * (k) To tune the parameters of the wheel / vehicle speed ratio adjustment model; terminals 1 and 3 are left unconnected, meaning the onboard satellite positioning system speed U(k) is not used (or is invalid), and the parameters of the locomotive radar speed adjustment model are not tuned by external signals. The wheel / vehicle speed ratio adjustment model is based on the input locomotive wheel rotation speed V1(h) to V n(h) The locomotive radar speed W(k) is adjusted and calculated, and the locomotive speed V is output to the traction force limiting self-tuning module and the locomotive speed correlation quantity C is output to the idle traction force control module. 2j C 21 To C 2n When the idling risk value is calculated according to formula (7), the locomotive speed-related quantity C 2j Including the inter-axis speed difference x j1 , creep rate of change xj2; when the idling risk value is calculated according to formula (8), the locomotive speed related quantity C 2j Including the inter-axis speed difference x j1 , creep change rate xj2, creep x j3 Inter-axis speed difference x j1 Including x 11 To x n1 The rate of change in creep sludge, xj2, includes x 12 To x n2 Creepiness x j3 Including x 13 To x n3 . Figure 5 The combination switch SW1 in the diagram is a schematic switch, which means that the direction of the signal flow is controlled according to X(k). In digital control, it is usually implemented by program branching.

[0119] In this embodiment of the locomotive speed measurement and adjustment device, the acquisition period T of the locomotive wheel rotation speed acquisition unit is... V The acquisition period T of the vehicle-mounted satellite positioning system's speed acquisition unit is 32ms. U For 1 second, m equals 4. The output locomotive wheel rotation speed V1(h) is calculated to V... nWhen the locomotive wheel rotation speed W(h) and the locomotive radar speed W(h) are measured, the corresponding speed acquisition unit has already performed corresponding filtering processing in the speed sampling and data processing stages according to the specific situation. For example, if the locomotive wheel rotation speed is sampled using a pulse speed sensor (encoder), the jitter interference of the pulse edge and the high-frequency interference in the pulse transmission process are filtered out accordingly. If the locomotive wheel rotation speed and the locomotive radar speed directly output analog or digital quantities, low-pass filtering, smoothing filtering, Kalman filtering, and other filtering methods can be used alone or in combination to filter out high-frequency interference, random interference, white noise interference, etc. The vehicle-mounted satellite positioning system speed acquisition unit includes one or more GNSS (Global Navigation Satellite System) receiving terminals, such as GPS, BeiDou, Galileo, and GLONASS system receiving terminals, and a corresponding receiving and processing module. The receiving and processing module receives information such as the number of satellites currently calculating the position, ground velocity (vehicle-mounted satellite positioning system speed), and the validity of the positioning status from one or more receiving terminals. Alternatively, it may also receive information such as longitude, latitude, UTC time, and altitude from one or more receiving terminals and calculate the vehicle-mounted satellite positioning system speed accordingly. The technical means employed in the locomotive wheel rotation speed acquisition unit, locomotive radar speed acquisition unit, and vehicle-mounted satellite positioning system speed acquisition unit are conventional techniques in this field.

[0120] Figure 6 This document presents a flowchart illustrating the locomotive speed adjustment method, which involves tuning and calculating the wheel / vehicle speed ratio adjustment model parameters and locomotive radar speed adjustment model parameters for the locomotive speed measurement and adjustment module, as well as calculating the wheel / vehicle speed ratio coefficient and various locomotive speed-related quantities. The iterative calculation cycle is the same as the acquisition cycle of the vehicle-mounted satellite positioning system speed acquisition unit. The specific steps for each iterative calculation are as follows:

[0121] Step 1, read the calculation results of the kth iteration (equivalent to kT). U The data from the vehicle-mounted satellite positioning system at the sampling time includes the vehicle-mounted satellite positioning system speed U(k) and positioning status information X(k);

[0122] Step 2: Read the locomotive wheel rotation speeds V from axle 1 to axle n, which were collected at the synchronous acquisition time point of the vehicle-mounted satellite positioning system speed U(k). j (k) and locomotive radar speed W(k), V j (k) refers to the rotational speed of the locomotive wheels from axle 1 to axle n, V1(k) to V n (k);

[0123] Step 3: Determine if the vehicle-mounted satellite positioning system speed is valid; if the vehicle-mounted satellite positioning system speed is valid, proceed to step 4; if the vehicle-mounted satellite positioning system speed is invalid, proceed to step 5.

[0124] Step 4: Adjust the model parameters based on the wheel / vehicle speed ratio and the locomotive radar speed, i.e., according to formula...

[0125] Setting the current radar velocity ratio coefficient P W (k) and the wheel / vehicle speed adjustment coefficient P for current axle 1 to axle n j (k); Let the radar velocity adjustment coefficient P w equals P W (k), proceed to step 6;

[0126] Step 5: Calculate and adjust the locomotive radar speed model parameters, that is, for m points (k-1, P... W (k-1)), (k-2,P W (k-2)), ..., (km,P) W (km) is used to perform linear fitting to obtain the first-order fitting line for the radar velocity ratio. Points (k, P) on the first-order fitting line for the radar velocity ratio are taken. W * The value P on (k) w * (k) represents the current radar velocity ratio coefficient P. w (k). Let the radar speed adjustment coefficient P w equals P W (k), according to formula

[0127] Calculate the radar synchronization adjustment speed W * (k); according to W * (k) Adjust the wheel / vehicle speed ratio model parameters, i.e., according to the formula

[0128]

[0129] Adjust the wheel / vehicle speed adjustment coefficient P for the current axle 1 to axle n j (k); Proceed to step 6;

[0130] Step 6, calculate the wheel / vehicle speed ratio coefficient U. j (k) Calculate the speed-related quantities for each locomotive. Calculate the adjustment wheel / car speed ratio coefficient U. j (k) There are 2 implementation examples; calculate the wheel / vehicle speed ratio coefficient U. j Example 1 of (k), according to formula

[0131] Calculate the wheel / vehicle speed ratio coefficient U for the current axle 1 to axle n. j (k). Calculate the wheel / vehicle speed ratio coefficient U. j (k) Example 2, for m points (k, P) on axis j j (k)), (k-1,P j (k-1)), ..., (k-m+1, P j (k-m+1)) is used to perform linear fitting to obtain the first-order fitting line of the axle j wheel / vehicle speed ratio coefficient. The point (k, U) on the first-order fitting line of the axle j wheel / vehicle speed adjustment coefficient is taken. j The value of (k)U j (k) is the wheel / vehicle speed ratio coefficient U of axle j. j (k); Fitting was completed for axes 1 to n respectively.

[0132] In the example, m equals 4. Figure 7 This is a schematic diagram of an embodiment of the first-order fitting line for the radar velocity ratio coefficient. Figure 7 In the middle, the four "+" points from left to right represent points (k-4, P). W (k-4)), (k-3,P w (k-3)), (k-2,P) W (k-2)), (k-1,P W (k-1)), the point "o" on the first-order fitting line of the radar velocity ratio coefficient is the point (k, P). w * (k)). Figure 8 A schematic diagram of the first-order fitting line of the wheel / vehicle speed ratio coefficient of axle 1 when j equals 1. Figure 8 In the diagram, the four "+" points from left to right are (k-3,P1(k-3)), (k-2,P1(k-2)), (k-1,P1(k-1)), and (k,P1(k)), respectively. The point "o" on the first-order fitted line of the wheel / vehicle speed ratio coefficient is (k,U1(k)). Figure 7 , Figure 8 For illustrative purposes, the coefficient values ​​of the four "+" points are not actual data. To make the illustration clearer, the errors are intentionally marked as larger, and the slope of the first-order fitted line is also intentionally marked as larger.

[0133] The positioning status information X(k) includes whether the positioning status is valid or invalid, and the number of satellites currently using the position calculation. In step 3 of the locomotive speed adjustment method, the method for determining whether the vehicle-mounted satellite positioning system speed is valid is as follows: if the positioning status in the positioning status information X(k) is valid, the vehicle-mounted satellite positioning system speed is valid; otherwise, the vehicle-mounted satellite positioning system speed is invalid. Alternatively, the method for determining whether the vehicle-mounted satellite positioning system speed is valid is as follows: if the positioning status in both positioning status information X(k) and X(k-1) is valid, the vehicle-mounted satellite positioning system speed is valid; otherwise, the vehicle-mounted satellite positioning system speed is invalid. Another method for determining whether the vehicle-mounted satellite positioning system speed is valid is as follows: if the positioning status in the positioning status information X(k) is valid, and the number of satellites currently using the position calculation in the positioning status information X(k) is greater than or equal to δ, the vehicle-mounted satellite positioning system speed is valid; otherwise, the vehicle-mounted satellite positioning system speed is invalid. One method to determine the validity of the vehicle-mounted satellite positioning system speed is as follows: The vehicle-mounted satellite positioning system speed is valid when both the positioning status information X(k) and X(k-1) show valid positioning, and the number of satellites currently calculating the location in both X(k) and X(k-1) is greater than or equal to δ. Otherwise, the vehicle-mounted satellite positioning system speed is invalid. X(k-1) is the vehicle-mounted satellite positioning system data read at time k-1 during the previous iteration calculation. In this embodiment, the vehicle-mounted satellite positioning system speed acquisition unit includes a GPS system receiving terminal and a corresponding receiving and processing module. When the method for determining the validity of the vehicle-mounted satellite positioning system speed uses the latter two of the aforementioned four methods, and the number of satellites currently calculating the location in the positioning status information X(k) is required, δ should be greater than or equal to 4, with a preferred value of 5.

[0134] P in steps 4-6 j (k), or P when i equals 0 j (ki) represents the wheel / vehicle speed adjustment coefficient for axle j. For example, P1(k) represents the current wheel / vehicle speed adjustment coefficient for axle 1. P is the wheel / vehicle speed adjustment coefficient for axle j when i is equal to 1, 2, ..., m-1. j (k-1), P j (k-2), ..., P j (k-m+1) represents the wheel / vehicle speed adjustment coefficient for axle j obtained during the first m-1 iterations. P in steps 4-5... w (k), or P when i equals 0 w (ki) represents the current radar velocity ratio coefficient. P is defined as follows: when i equals 1, 2, ..., 4. W (k-1), P W (k-2), ..., P W(km), representing the radar velocity ratio coefficients obtained in the first m iterations. In step 6, U j (k) is the wheel / vehicle speed ratio coefficient of axle j. For example, U2(k) is the wheel / vehicle speed ratio coefficient of axle 2.

[0135] Step 6: Calculate the wheel / vehicle speed ratio coefficient U V In Example 1 of (k), μ V (k), μ V (k-1), ..., μ V (k-m+1) is related to P j (k), P j (k-1), ..., P j The corresponding variable weighting coefficients (k-m+1) satisfy the equation

[0136] The relationship between μ and μ, from largest to smallest. V (k), μ v (k-1), ..., μ V The value is taken from (k-m+1), for example, if m equals 4, μ V (k), μ V (k-1), μ V (k-2), μ V (k-3) can be equal to 0.4, 0.3, 0.2, 0.1, or 0.55, 0.27, 0.13, 0.05, etc. Different values ​​of j do not affect the magnitude of the variation weighting coefficient.

[0137] In step 6, the locomotive speed-related quantities include the locomotive speed V and the creep coefficient x from axle 1 to axle n. j3 , creep change rate x j2 Inter-axis speed difference x j1 Current locomotive speed V C (h) According to formula

[0138] Perform calculations, calculation period and sampling period T V Same. V j (h), V j (k), W(h), W(k), U(k), W * (k), V C The unit of (h) is m / s; T V T U The unit is seconds (s). The locomotive speed V is taken as the current locomotive speed V. C (h), the unit of locomotive speed V is km / h. After converting the unit m / s to km / h, the value of locomotive speed V is equal to Vh. c 3.6 times the (h) value.

[0139] U j (k) reflects the ratio between the locomotive wheelset speed and the locomotive speed of axle j, therefore the creep of axle j is x. j3 It can be done according to the formula

[0140]

[0141] Perform calculations, calculation period and sampling period T U Same. Or, according to the formula.

[0142] Calculate the current creep x of axis j j3 (h), calculation period and sampling period T V Same, take the creep degree x j3 Equal to current creep x j3 (h).

[0143] The rate of change of creep of axis j x j2 According to the formula

[0144] Perform calculations, calculation period and sampling period T U Same. U j (k-1) is the wheel / vehicle speed ratio coefficient of axle j obtained from the previous iterative calculation using the locomotive speed adjustment method. Alternatively, according to formula...

[0145] Calculate the current rate of change of creep x of axis j j2 Calculation period and sampling period T V Same. x j3 (h-1) represents the previous sampling period T. V The current creep of axis j is obtained when calculating creep.

[0146] The wheel / vehicle speed ratio adjustment model in the speed adjustment calculation unit receives the locomotive wheel rotation speeds V1(h) from axle 1 to axle n. n (h) after V j The n values ​​of (h) are compared, that is, the values ​​of V1(h) to V are compared. n The n values ​​of (h) are compared, and the minimum value is taken as the minimum rotational speed of the locomotive wheel V0(h), and the inter-axle speed difference x of axle j is taken as the minimum value of the locomotive wheel rotational speed V0(h). j1 according to

[0147] x j1 =V j (h)-V0(h) (23)

[0148] Perform calculations, calculation period and sampling period T VSame. As defined, the speed difference between axles where the minimum rotational speed V0(h) of a locomotive wheel is located is equal to 0.

[0149] The creep coefficient x is calculated using equation (19). j3 At the same time, the creep rate of change x is calculated using equation (21). j2 The creep coefficient x is calculated using equation (20). j3 At the same time, the creep rate of change x is calculated using equation (22). j2 In the locomotive speed adjustment method, the value of j in each step ranges from 1 to n. For example, V j (k) represents the locomotive wheel rotation speed V1(k) to V n (k); Wheel / vehicle speed adjustment coefficient P from axle 1 to axle n j (k), wheel / vehicle speed ratio coefficient U j (k), and x j1 x j2 x j3 Each is calculated (tuned) or fitted separately.

[0150] Figure 9 The flowchart illustrates a method for calculating the number of delay interval cycles in an embodiment of a locomotive speed measurement and adjustment device. The calculation cycle is the same as the acquisition cycle of the speed acquisition unit in the vehicle-mounted satellite positioning system. This calculation can be performed before or after the iterative calculation of the locomotive speed adjustment method. Specifically:

[0151] Step ①: Obtain the current time, i.e., time k (i.e., kT). U The rate of change of locomotive acceleration β(k) at the sampling time;

[0152] Step ②: Determine whether the conditions for calculating the number of delay interval periods are met. The equation is satisfied.

[0153] If the relationship is such that the vehicle's satellite positioning system speed has been valid for the most recent m1 consecutive checks, proceed to step ③; otherwise, exit; m1 is greater than or equal to 10. The acceleration change threshold ε can be selected based on the locomotive's acceleration capability and can be determined experimentally. The value of ε can be determined by... to Choose from within the range of values. This represents the average acceleration of the locomotive during startup. In the embodiment, T... U Given a time interval of 1 second and m1 equals 20, the average acceleration of a locomotive from 0 to 200 meters can typically reach 0.4 m / s². 2Then, the value of ε can be selected in the range of 0.4 to 2.4. For example, ε can be taken as 1.2. In equation (24), β(ki) when i equals 0 is the locomotive acceleration change rate β(k) at the current moment; β(ki) when i equals 1 is the locomotive acceleration change rate obtained when calculating the number of delay interval cycles in the previous calculation (i.e., iteratively calculating the wheel / vehicle speed ratio coefficient); and so on, β(ki) when i equals 1 to m1-1 are the locomotive acceleration change rates obtained when calculating the number of delay interval cycles in the previous m1-1 calculations. The most recent consecutive m1 judgments that the vehicle-mounted satellite positioning system speed is valid refers to the following Figure 6 In the iterative calculation of the locomotive speed adjustment method, in the most recent consecutive m1 iterations, step 3 determined that the speed of the on-board satellite positioning system was valid.

[0154] Step ③: Obtain the number of hysteresis intervals τ. The method is to set the parameter to be optimized as the number of hysteresis intervals τ. * and radar speed proportionality coefficient p W * ;τ * The value of is selected within the range that ensures the delay interval is no greater than 2 seconds, i.e., greater than 0 and less than 2 / T. V Integer; in the example, T V Equals 32ms, or 0.032s; 2 / T V Equals 62.5, therefore τ * The value of p is greater than 0 and less than or equal to 62. W * The value range is greater than or equal to 0.8 and less than or equal to 1.2. The parameter p to be optimized is... W * Only used in this optimization process. The number of delay interval periods is τ. * At that time, the locomotive radar speed acquired at the synchronous acquisition time point corresponding to U(ki) is W. * (ki), the locomotive wheel rotation speed V of each axle collected at the synchronous acquisition time point. j (ki), the minimum optimization objective function is

[0155]

[0156] Optimization can employ various algorithms such as genetic algorithms and particle swarm optimization, selecting the number of delay intervals τ that satisfies the optimal (minimum) value Q. * Let τ be the number of delay intervals.

[0157] In step ①, obtain kT U The method for calculating the locomotive acceleration change rate β(k) at the sampling time is as follows:

[0158] The calculation is performed, where α(k) is the currently collected locomotive acceleration, and α(k-1) is the locomotive acceleration collected in the previous instance. In this embodiment, the currently collected locomotive acceleration α(k) is calculated according to the formula...

[0159] The calculation is performed, where U(k) is the currently acquired vehicle satellite positioning system speed, and U(k-1) is the previously acquired vehicle satellite positioning system speed. The locomotive acceleration α(k) can also be measured using an accelerometer. The unit of α(k) is m / s². 2 The unit of β(k) is m / s. 3 .

[0160] Figure 10 This diagram illustrates the speed acquisition delay, locomotive acceleration, and rate of change of locomotive acceleration for the vehicle-mounted satellite positioning system. Here, V1(t) is the rotational speed of the locomotive wheel at axle 1 after V1(h) is made continuous; W(t) is the locomotive radar speed after W(h) is made continuous; and U(t) is the speed of the vehicle-mounted satellite positioning system after U(k) is made continuous. τ The lag time between the vehicle-mounted satellite positioning system's speed acquisition time and the locomotive wheel rotation speed acquisition time is given by point k-7; points k-7 to k represent the various sampling times (k-7)T for the vehicle-mounted satellite positioning system's speed. U To kT U α(k) and β(k) are the locomotive acceleration and the rate of change of locomotive acceleration, respectively.

[0161] Figure 11 This diagram illustrates the time points for synchronous acquisition of locomotive radar speed for the vehicle-mounted satellite positioning system, where the sampling time (i.e., kT) is the sampling time of U(k). U The current time in which the locomotive speed measurement and adjustment device iteratively calculates the locomotive speed adjustment method is represented. The sampling times of W(h-τ), W(h-τ+1), ..., W(h-3), W(h-2), W(h-1), W(h), etc., are the sampling times of the locomotive radar speed. For example, the time of W(h) is its sampling time hT. V Due to ionospheric delay and other factors, the acquisition of locomotive speed (including speed from the onboard satellite positioning system and speed from the locomotive radar) and the rotational speed of each axle of the locomotive is delayed by T compared to the acquisition of locomotive wheel rotational speed and locomotive radar speed at the same moment. τ The delay interval τ is the number of acquisition periods relative to the locomotive wheel rotation speed acquisition period T. V The number of cycles, i.e., the number of hysteresis interval cycles τ, is the acquisition period T converted from the time lag between the acquisition time of the vehicle-mounted satellite positioning system's speed and the acquisition time of the locomotive wheel rotation speed and the locomotive radar speed. V Multiple values. Figure 11 In the middle, the sampling time (h-τ)T where W(h-τ) is located V Let U(k) be the time point for synchronous acquisition of the vehicle-mounted satellite positioning system speed U(k). The locomotive radar speed W(h-τ) acquired at this point is denoted as W(k). Specifically, the τ-th locomotive radar speed acquisition time before the sampling time of the vehicle-mounted satellite positioning system speed U(k), which is also the time point for acquiring the locomotive wheel rotation speed, is the synchronous acquisition time point of U(k). The acquisition period and time of the locomotive radar speed and the locomotive wheel rotation speed are the same, and the mutual delay between them is negligible. Therefore, the sampling times of the locomotive radar speeds W(h-τ), W(h-τ+1), ..., W(h-3), W(h-2), W(h-1), and W(h) are respectively related to the locomotive wheel rotation speed V of each axle. j (h-τ), V j (h-τ+1), ..., V j (h-3), V j (h-2), V j (h-1), V j The sampling times of (h) are the same, V j The sampling time (h-τ)T at which (h-τ) occurs. V At the same sampling time of W(h-τ), the locomotive wheel rotation speed V collected at this point j (h-τ) is V j (k).

[0162] Similarly, with Figure 11 For example, when performing the optimization calculation of the number of delay interval periods τ, if τ * If W(h-1) equals 1, then the sampling point where W(h-1) is located is its corresponding synchronous acquisition time point, and its V j * (k) equals V j (h-1), W * (k) equals W(h-1); if τ * If V equals 2, then V j The sampling point (h-2) is its corresponding synchronous acquisition time point, and its V j * (k) equals V j (h-2), W * (k) equals W(h-2); and so on. Note that, for example, τ * Equal to 1, V j * (k) equals V j (h-1), while V j * (k-1) is not V j(h-2); In this embodiment, the vehicle-mounted satellite positioning system samples the speed once, and the locomotive wheel rotation speed is sampled an average of 31.25 times. Therefore, if τ * Equal to 1, V j * (k) equals V j (h-1), then V j * (k-1) could be V j (h-32), or V j (h-33).

[0163] In the aforementioned locomotive speed measurement and adjustment device for implementing locomotive speed adjustment, when satellite positioning speed measurement is effective, the parameters of the wheel / vehicle speed ratio adjustment model and the locomotive radar speed adjustment model are adjusted and calculated using the satellite positioning speed measurement data. When satellite positioning speed measurement is ineffective, new locomotive radar speed adjustment model parameters are calculated from the previously adjusted locomotive radar speed adjustment model parameters according to a given expression or by using a first-order fitting straight line method. The adjusted radar speed adjustment model parameters are then used to adjust and calculate the wheel / vehicle speed ratio adjustment model parameters. Finally, based on the wheel / vehicle speed ratio adjustment model, the locomotive speed and various locomotive speed-related quantities such as the rate of change of creep of each axle, creep, and inter-axle speed difference are calculated. This method combines the advantages of high accuracy of satellite positioning speed measurement and good real-time performance of radar speed measurement, as well as the ability to operate normally for long periods, thus improving the accuracy and reliability of measuring various locomotive speed-related quantities. The locomotive speed adjustment method also uses the judgment of whether the locomotive is in a speed change state. If it is in a speed change state, the information obtained from radar speed measurement, satellite positioning speed measurement, and locomotive wheelset speed measurement after the locomotive speed change is collected and the satellite positioning data transmission time, i.e. the number of delay intervals, is optimized to obtain the accurate real-time satellite positioning data transmission delay time (i.e. the number of delay intervals). This further ensures the accuracy and reliability of the speed data calculated by the aforementioned locomotive speed adjustment method.

Claims

1. A locomotive speed measuring and adjusting device, characterized in that, It includes a speed adjustment calculation unit, a locomotive wheel rotation speed acquisition unit, a locomotive radar speed acquisition unit, and an onboard satellite positioning system speed acquisition unit; the locomotive wheel rotation speed acquisition unit periodically acquires the locomotive wheel rotation speed V from axle 1 to axle n. j (h), the locomotive radar speed acquisition unit periodically acquires the locomotive radar speed W(h), and the vehicle-mounted satellite positioning system speed acquisition unit periodically acquires the vehicle-mounted satellite positioning system speed U(k) and positioning status information X(k); the period for acquiring the vehicle-mounted satellite positioning system speed and positioning status information is T. U The period for collecting the locomotive radar speed and locomotive wheel rotation speed is T. V T U Greater than T V The value of j is one from 1 to n, where n is the number of axles of the locomotive. The locomotive speed V and the creep rate of change x from axle 1 to axle n were obtained by iterative calculation. j2 The method is: Step 1: Read the vehicle-mounted satellite positioning system speed U(k) and positioning status information x(k) at the time of the kth iteration calculation; Step 2: Read the locomotive wheel rotation speeds V from axle 1 to axle n, which were collected at the synchronous acquisition time point of the vehicle-mounted satellite positioning system speed U(k). j (k) and locomotive radar speed W(k); Step 3: Determine if the vehicle-mounted satellite positioning system speed is valid; if it is determined that the vehicle-mounted satellite positioning system speed is valid, proceed to step 4. If the vehicle-mounted satellite positioning system is determined to be ineffective, proceed to step 5; Step 4, according to the formula Setting the current radar velocity ratio coefficient P W (k) and the wheel / vehicle speed adjustment coefficient P for current axle 1 to axle n j (k); Let the radar velocity adjustment coefficient P W equals P W (k), proceed to step 6; Step 5: Calculate and adjust the parameters of the locomotive radar speed adjustment model, that is, for m points (k-1, P... W (k-1)), (k-2,P W (k-2)), ..., (km,P) W (km) is used to perform linear fitting to obtain the first-order fitting line for the radar velocity ratio. Points (k, P) on the first-order fitting line for the radar velocity ratio are taken. W * The value P on (k) W * (k) represents the current radar velocity ratio coefficient P. W (k); Let the radar velocity adjustment coefficient P W equals P W (k), according to formula Calculate the radar synchronization adjustment speed W * (k); according to formula Adjust the wheel / vehicle speed adjustment coefficient P for the current axle 1 to axle n j (k); Proceed to step 6; Step 6, according to the formula Calculate the current locomotive speed V C (h) Take the locomotive speed V as the current locomotive speed V C (h); For m points (k, P) on axis j j (k)), (k-1,P j (k-1)), ..., (k-m+1, P j (k-m+1)) is used to perform linear fitting to obtain the first-order fitting line of the axle j wheel / vehicle speed ratio coefficient. The point (k, U) on the first-order fitting line of the axle j wheel / vehicle speed adjustment coefficient is taken. j The value of (k)U j (k) is the wheel / vehicle speed ratio coefficient U of axle j. j (k); m is greater than or equal to 3; According to the formula Calculate the rate of change of creep of axis j x j2 .

2. The locomotive speed measuring and adjusting device as described in claim 1, characterized in that, The τth locomotive radar speed acquisition time before the sampling time of the vehicle-mounted satellite positioning system speed U(k) is the synchronous acquisition time point of the vehicle-mounted satellite positioning system speed U(k), where τ is the number of delay interval periods. The number of delay interval periods τ is the acquisition period T converted from the time lag between the acquisition time of the vehicle-mounted satellite positioning system speed and the acquisition time of the locomotive wheel rotation speed and the locomotive radar speed. V The multiple value; the method to obtain the number of delay interval periods τ is to satisfy the following: When the vehicle's satellite positioning system speed is valid for the most recent m1 consecutive determinations, the delay interval period τ is calculated; where β(ki) is the locomotive acceleration change rate for the most recent m1 times, β(ki) when i equals 0 is the locomotive acceleration change rate β(k) at the current moment; β(ki) when i equals 1 to m1-1 are the locomotive acceleration change rates obtained when calculating the delay interval period for the previous m1-1 times; ε is the acceleration change threshold greater than 0; the locomotive acceleration change rate is calculated according to the formula... The calculation is performed; where α(k) is the most recently collected locomotive acceleration, and α(k-1) is the previously collected locomotive acceleration; the locomotive acceleration is calculated according to the formula... Calculations are performed; where U(k-1) is the speed of the vehicle-mounted satellite positioning system in the previous acquisition of U(k); Let the parameter to be optimized be the number of delay intervals, τ. * and radar speed adjustment coefficient p W * The number of delay intervals is τ. * At that time, the locomotive radar speed acquired at the synchronous acquisition time point corresponding to U(ki) is W. * (ki), the minimum optimization objective function is Take the number of delay intervals τ that satisfy the optimal value Q. * Let τ be the number of delay interval periods; τ * The value range is greater than 0 and less than 2 / T V integers, p W * The value range is greater than or equal to 0.8 and less than or equal to 1.2; m1 is greater than or equal to 10.

3. The locomotive speed measurement and adjustment device as described in claim 2, characterized in that, The vehicle-mounted satellite positioning system speed is valid when the positioning status in the positioning status information X(k) is valid and the number of satellites using the positioning status information X(k) to calculate the location is greater than or equal to δ. Otherwise, the vehicle-mounted satellite positioning system speed is invalid. The value of δ is required to be greater than or equal to 4.

4. The locomotive speed measuring and adjusting device as described in claim 3, characterized in that, creep change rate x j2 Used for controlling the traction force of locomotive wheelset slippage; the method is as follows: according to formula... Calculate the idling risk value E of axis j j ; where x j1 Let θ1 be the inter-axis velocity difference of axis j, θ2 be the inter-axis velocity difference threshold, θ2 be the creep rate of change threshold, and γ1 and γ2 be nonlinear weighting exponential factors, with γ1≥1 and γ2≥1. Regarding the rotational speed V of the locomotive wheels j The n values ​​of (h) are compared, and the minimum value is taken as the minimum rotational speed of the locomotive wheel V0(h), and the inter-axle speed difference x of axle j is taken as the minimum value of the locomotive wheel rotational speed V0(h). j1 According to the formula x j1 =V j (h)-V0(h) Perform calculations; The condition for determining the idling of locomotive wheelset j is that when E j If the value is ≥1, it is determined that the locomotive wheelset of axle j has idled; the traction control process for axle j idling is as follows: Process I, the process of decreasing traction force during idling; from the idling risk value R j Starting from a value greater than or equal to 1 and continuously increasing, up to the idling risk value R. j The control ratio of traction force to shaft j during idle traction force ends when the continuous increase begins to decrease. j With the load reduction slope d of shaft j jd φ at the end of process I j The value is the minimum maintenance value φ jL ; Process II, the process of maintaining the minimum idling traction value; starting from the end of Process I, the idling risk value E j The control stops when the value decreases to less than 1. j Equal to the minimum maintenance value φ jL ; Process III, the traction recovery process during idling; starting from the end of Process II, until φ j Increase to a value equal to 1 and then stop, controlling φ. j To restore the slope d ju It begins to increase; Among them, the idle traction control ratio φ j φ is the ratio between the locomotive traction force output by the idling traction force control module and the locomotive traction force input to the locomotive, and 0 ≤ φ. j ≤1; The unloading slope d of shaft j jd The size is determined by the axle speed difference load reduction factor e. j Control, according to formula Calculate the speed difference load reduction factor e j Where γ0 is the speed difference load reduction control factor, and 1≤γ0≤2; the load reduction slope d of shaft j jd According to the formula Perform the calculation, where d H d is the upper limit of the load reduction slope. L e is the lower limit of the load reduction slope. m The limit value for the speed difference load reduction factor is given, and e is also given. m =3 γ 0.

5. The locomotive speed measuring and adjusting device as described in claim 4, characterized in that, Locomotive speed V is used for upper limit control of locomotive traction force. The method is as follows: The upper limit of the locomotive traction force on axle j is controlled, wherein P jμ Calculate the adhesive weight, μ, for axis j. k It calculates the coefficient of adhesion; F j1 It is the locomotive traction force of axle j before the upper limit and amplitude control; F j2 It is the locomotive traction force of axle j after the upper limit and amplitude control; ξ is the wheel-rail adhesion coefficient control parameter; According to the formula The calculated adhesion coefficient μ is obtained. k Where a1, a2, a3, a4, and a5 are empirical formula parameters for calculating the adhesion coefficient; according to the formula... To determine the control parameter ξ for the wheel-rail adhesion coefficient, where R m The maximum rainfall limit is defined as 2 mm / h to 2.5 mm / h; C 11 For real-time rainfall, the output range is 0 to R. m C 12 b3 is the rail surface dryness / humidity, with an output range of 0 to 1, where 0 indicates the rail surface is completely dry and 1 indicates the rail surface is completely wet; b4 is the adhesion coefficient rainfall control parameter, with a value range of 0.25≤b3≤0.4; b4 is the adhesion coefficient rail surface control parameter, with a value range of 0.7≤b4≤0.9.

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