Locomotive adhesion utilization control method, device, medium and control equipment

Abstract

The application discloses a locomotive adhesion utilization control method, device, medium and control equipment. The method comprises the following steps: collecting the angular velocity of a locomotive wheel, calculating the acceleration of the wheel according to the angular velocity; performing filtering processing on the acceleration; acquiring the motor torque of the wheel, calculating the acceleration differential critical value according to the motor torque; and adjusting the motor torque of the wheel if the filtered acceleration is greater than the acceleration differential critical value. The application can improve the accuracy of adhesion utilization control.

Description

Technical Field

[0001] This invention relates to the field of locomotive control technology, and in particular to a locomotive adhesion control method, device, medium and control equipment. Background Technology

[0002] In wheel-rail transportation, the adhesion between the locomotive's driving wheels and the rails is the static friction between the wheels and rails, and it is also the ultimate driving force for the locomotive's operation. Locomotive adhesion is achieved through creep within the wheel-rail contact surface, the specific process of which is as follows: Figure 1 For small longitudinal forces (provided by the driving force, which is the product of torque T and wheel radius R), creep can occur due to the Hertzian contact zone (in...). Figure 1 The contact area (which can be considered the total contact area between the wheel and the road surface) is provided by a small relative sliding along the trailing edge of the adhesive zone (compressive / tensile elastic deformation zone) and the sliding zone (contact area). As the longitudinal force increases, the sliding zone gradually expands from the trailing edge to the leading edge; when the adhesive zone at the leading edge disappears (i.e., the entire contact area is a sliding zone), the adhesive force F reaches the limiting Coulomb friction. When the driving force exceeds the limiting Coulomb friction, the excess driving force will release energy through wheel idling acceleration, rapidly increasing the sliding speed v, causing wear on the wheel-rail surface and generating more frictional heat, leading to a longer cooling and hardening process on the wheel-rail surface material. This process, in turn, affects the limiting Coulomb friction, so as the sliding speed increases, the effective usable adhesive force decreases rapidly. It can be seen that as the sliding speed increases, the adhesive force rises to its maximum value and then decreases, as... Figure 2 The figure shows the adhesion characteristic curve.

[0003] With the development of high-speed and heavy-haul railway transportation in recent years, locomotive traction has been continuously improved. However, the full utilization of locomotive effective traction is actually limited by the maximum usable adhesion level between the wheel and rail. When the locomotive traction exceeds the maximum value of adhesion between the wheel and rail, wheel spin occurs, causing a rapid decrease in transmittable traction. Furthermore, locomotive wheel spin can cause serious problems such as excessive rail wear, wheel rim overheating exceeding the limit temperature, motor speed exceeding the maximum allowable value, and wheel tread abrasion and increased braking distance during braking. To ensure the safe and reliable operation of locomotives and to fully utilize the maximum possible traction and braking force, achieving optimal adhesion control for electric locomotives is imperative.

[0004] Current adhesion control systems employ various techniques. Some use simple corrective (re-adhesion) control technology, which can quickly reduce traction when wheel spins. Others introduce creep control to achieve active adhesion control. The speed difference Δv in creep control is slightly larger than the value corresponding to the maximum adhesion force. However, since this is the descending region (unstable region) of the adhesion characteristic curve, it may cause destructive frictional vibrations. Furthermore, the adhesion characteristic curve is dynamically changing, and there is no clear relationship between the maximum adhesion force and the creep speed, thus it cannot be very effective. Some systems use direct adhesion control, but the calculation of adhesion force introduces wheel circumferential acceleration noise, resulting in large errors and consequently large control errors. Summary of the Invention

[0005] The technical problem to be solved by the present invention is that the adhesion control error is large and the control accuracy is low in the prior art.

[0006] To solve the above-mentioned technical problems, the present invention provides a locomotive adhesion control method, device, medium and control equipment.

[0007] A locomotive adhesion control method includes:

[0008] The angular velocity of the locomotive wheels is collected, and the acceleration of the wheels is calculated based on the angular velocity.

[0009] The acceleration is filtered.

[0010] Obtain the motor torque of the wheel, and calculate the critical value of the differential acceleration based on the motor torque;

[0011] If the acceleration after filtering is greater than the differential critical value of acceleration, then the motor torque of the wheel is adjusted.

[0012] In one embodiment, calculating the wheel acceleration based on the angular velocity includes:

[0013] Convert the angular velocity into linear velocity;

[0014] The acceleration of the wheel is calculated based on the linear velocity.

[0015] In one embodiment, filtering the acceleration includes:

[0016] The acceleration is optimally estimated using a Kalman filter to obtain the optimal acceleration estimate.

[0017] In one embodiment, after performing optimal estimation of the acceleration using a Kalman filter to obtain the optimal acceleration estimate, the method further includes:

[0018] The optimal acceleration estimate is smoothed using a Kalman smoother to obtain a smoothed acceleration.

[0019] In one embodiment, the step of calculating the critical value of the differential acceleration based on the motor torque includes:

[0020]

[0021]

[0022] Among them, T m The torque of the motor is... The rate of change of motor torque. The preset moment of inertia; This is the critical value of the differential acceleration.

[0023] In one embodiment, adjusting the motor torque of the wheel includes:

[0024] Reduce the motor torque of the wheel until the filtered acceleration is less than or equal to the critical value of the differential acceleration.

[0025] A locomotive adhesion control device includes:

[0026] The speed acquisition module is used to collect the angular velocity of the locomotive wheels and calculate the acceleration of the wheels based on the angular velocity.

[0027] An acceleration optimization module is used to filter the acceleration.

[0028] The critical value acquisition module is used to acquire the motor torque of the wheel and calculate the critical value of the differential acceleration based on the motor torque;

[0029] The adhesion adjustment module is used to adjust the motor torque of the wheel when the acceleration after filtering is greater than the differential critical value of acceleration.

[0030] In one embodiment, the acceleration optimization module uses a Kalman filter to perform optimal estimation of the acceleration, thereby obtaining an optimal acceleration estimate.

[0031] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0032] The angular velocity of the locomotive wheels is collected, and the acceleration of the wheels is calculated based on the angular velocity.

[0033] The acceleration is filtered.

[0034] Obtain the motor torque of the wheel, and calculate the critical value of the differential acceleration based on the motor torque;

[0035] If the acceleration after filtering is greater than the differential critical value of acceleration, then the motor torque of the wheel is adjusted.

[0036] A control device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to perform the following steps:

[0037] The angular velocity of the locomotive wheels is collected, and the acceleration of the wheels is calculated based on the angular velocity.

[0038] The acceleration is filtered.

[0039] Obtain the motor torque of the wheel, and calculate the critical value of the differential acceleration based on the motor torque;

[0040] If the acceleration after filtering is greater than the differential critical value of acceleration, then the motor torque of the wheel is adjusted.

[0041] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0042] By comparing the acceleration and differential critical value of the vehicle wheels with the filtered acceleration and differential critical value, the motor torque of the wheels is adjusted when the filtered acceleration exceeds the differential critical value, thus achieving active adhesion utilization control with good control effect. Moreover, because the acceleration is filtered, the influence of noise can be reduced and the accuracy of acceleration can be improved. Therefore, the accuracy of comparison and analysis based on the filtered acceleration is higher, thereby improving the accuracy of adhesion utilization control. Attached Figure Description

[0043] The scope of this disclosure can be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The accompanying drawings are:

[0044] Figure 1 A schematic diagram showing the generation of tangential force at the locomotive wheel-rail contact surface is shown.

[0045] Figure 2 This is a schematic diagram of the adhesion characteristic curve of the locomotive;

[0046] Figure 3 Here is a block diagram of the existing adhesive force direct control system;

[0047] Figure 4 This is a rendering of an existing direct adhesion control system;

[0048] Figure 5This is another rendering of the existing adhesive direct control system;

[0049] Figure 6 This is another rendering of an existing adhesive direct control system;

[0050] Figure 7 This is a flowchart illustrating a locomotive adhesion control method in one embodiment;

[0051] Figure 8 This is a block diagram of a control system for a locomotive adhesion control method in one embodiment;

[0052] Figure 9 An illustration of the effect of applying a locomotive adhesion control method;

[0053] Figure 10 Another effect diagram of the application of locomotive adhesion control method;

[0054] Figure 11 This is another effect diagram of the application of locomotive adhesion control method;

[0055] Figure 12 This is a structural block diagram of a locomotive adhesion control device in one embodiment. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the present invention clearer, the implementation method of the present invention will be described in detail below with reference to the accompanying drawings and embodiments, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0057] The adhesion characteristics reflected by the adhesion coefficient and creep speed of locomotive wheels and rails are as follows: as the creep speed increases, the locomotive adhesion coefficient rises to its maximum value and then decreases, as shown in the adhesion characteristic curve. Figure 2 As shown, the adhesion coefficient-creep characteristic curve of the locomotive wheel and rail can be represented as follows:

[0058] When the creep velocity is Δ At that time, the coefficient of adhesion Equal to the maximum adhesion coefficient When the driving force is greater than the maximum available adhesive force, Δ >△ However, the adhesive force actually decreases. According to wheel-rail dynamics, the creep velocity is:

[0059] (1)

[0060] in, As the driving force, For usable adhesive force, where The normal pressure exerted by the wheel on the rail surface; The moment of inertia of the wheel; Let be the wheel diameter. Ignoring the effect of wheel friction torque, it can be seen that when the available adhesive force decreases, It will increase further. When the creep speed... At this time, the wheel-rail interaction point enters the unstable region, resulting in wheel spin and slippage.

[0061] The adhesive force direct control system used in the prior art, such as Figure 3 As shown. Among them, the dimension-reduced observer for adhesion:

[0062] Since the adhesive force and its differential value cannot be directly measured, a method for estimating the adhesive force and its differential value is derived through a specially designed dimension reduction observer.

[0063] locomotive motor interference torque and its differential value The design process of the dimension-reduced closed-loop state observer is as follows:

[0064] Step 1:

[0065] Since the wheel is a rotating body, according to the equations of motion for rotating bodies, we can obtain:

[0066] (2)

[0067] Among them, there are For the rotational friction torque term, For coefficients, Let be the angular velocity of the wheel circumference. Assume the transmission ratio is... Based on the transmission ratio, the relationship between the torque and moment of inertia between the wheel circumference and the motor rotor can be derived:

[0068] (3)

[0069] (4)

[0070] From equation (4), we can derive the mechanical equation for the electric motor:

[0071] (5)

[0072] Among them are: .

[0073] Step 2:

[0074] According to the mechanical equation of an electric motor:

[0075] (6)

[0076] Step 3:

[0077] By motor rotor speed Interference torque and its differential value Linear state-space equations for state variables:

[0078] = (7)

[0079] (8)

[0080] in, Input variables for system control; Output variables for the system.

[0081] From the above formula, we can assume:

[0082] , , , (9)

[0083] It can be simplified to:

[0084] (10)

[0085] Step 4:

[0086] (11)

[0087] in,

[0088] (12)

[0089] Step 5:

[0090] (13)

[0091] in

[0092] Step 6:

[0093] (15)

[0094] Step 7:

[0095] (16)

[0096] (17)

[0097] Step 8:

[0098] (18)

[0099] in:

[0100] (19)

[0101] Step 9:

[0102] (20)

[0103] in:

[0104] (twenty one)

[0105] Step 10:

[0106] (twenty two)

[0107] = (twenty three)

[0108] in:

[0109] (twenty four)

[0110] Step 11:

[0111]

[0112] (25)

[0113] (26)

[0114] Step 12:

[0115] The locomotive motor interference torque was obtained. and its differential value The dimension-reduced closed-loop state observer is as follows:

[0116] = + (27)

[0117] (28)

[0118] Regarding the control law for the direct adhesive control system:

[0119] Using the observer obtained in step 12, the control law of the direct adhesive control system is derived as shown in formula (29):

[0120] (29)

[0121] The control effect of existing adhesive direct control systems is as follows: Figure 4 , Figure 5 and Figure 6As shown, it meets the basic requirements for adhesive control, but it has the following drawbacks:

[0122] (1) Adhesive force direct control system: Due to the design considerations of the control system, the calculation of adhesive force introduces wheel circumference acceleration noise, resulting in large errors. Even with the use of a low-pass filter, it will lead to inaccurate judgment of idling and coasting, and the adjustment of the control quantity will lag behind the response of the controlled object, or even cause a complete reversal.

[0123] (2) The control error is large, and the locomotive exhibits unstable wheel speed and obvious vibration. For lines such as long slopes and small curve radii, the locomotive is prone to speed loss due to unstable traction.

[0124] Based on this, the present invention provides a locomotive adhesion utilization control method.

[0125] In one embodiment, such as Figure 7 As shown, a locomotive adhesion control method includes the following steps:

[0126] S110: Collects the angular velocity of the locomotive wheels and calculates the wheel acceleration based on the angular velocity.

[0127] Angular velocity can be obtained through a velocity sensor. Specifically, angular velocity can be the angular velocity of the wheel axle, and correspondingly, wheel axle acceleration can be calculated from the angular velocity of the wheel axle.

[0128] The locomotive includes multiple wheels, and each wheel can correspond to an adhesion utilization control system hardware platform that applies the locomotive adhesion utilization control method. Therefore, in step S110, the angular velocity of one wheel is collected, and the acceleration of that wheel is calculated. The adhesion utilization control system hardware platform collects the angular velocities of the other wheels and calculates their accelerations. For example, the HXD1C locomotive uses an axle control method, where one MCC board (adhesion utilization control system hardware platform) collects the velocity of that axle and calculates its acceleration.

[0129] S130: Filters the acceleration.

[0130] S150: Obtain the motor torque of the wheel and calculate the critical value of the differential acceleration based on the motor torque.

[0131] S170: If the acceleration after filtering is greater than the critical value of the differential acceleration, then adjust the motor torque of the wheel.

[0132] Specifically, adjusting the motor torque of the wheel can be done by adjusting the motor torque of the wheel in a way that reduces the filtered acceleration, until the filtered acceleration is less than or equal to the critical value of the differential acceleration. Further, if the filtered acceleration is less than or equal to the critical value of the differential acceleration, the process can return to step S110, thereby cyclically comparing and analyzing the acceleration and the critical value of the differential acceleration to perform adhesion utilization control.

[0133] The aforementioned locomotive adhesion utilization control method compares the acceleration and differential critical value of the locomotive wheels with the filtered acceleration and differential critical value. When the filtered acceleration exceeds the differential critical value, the motor torque of the wheels is adjusted to achieve active adhesion utilization control, resulting in good control performance. Moreover, because the acceleration is filtered, the influence of noise can be reduced, and the accuracy of acceleration can be improved. Therefore, the accuracy of the comparative analysis based on the filtered acceleration is higher, thereby improving the accuracy of adhesion utilization control.

[0134] In one embodiment, the step of calculating the wheel acceleration based on the angular velocity in S110 includes: converting the angular velocity into linear velocity; and calculating the wheel acceleration based on the linear velocity.

[0135] Among them, acceleration can be calculated based on linear velocity using the following formula: Calculated.

[0136] In one embodiment, step S130 of filtering the acceleration includes: performing optimal estimation on the acceleration using a Kalman filter to obtain the optimal acceleration estimate.

[0137] In actual locomotive operation, the wheel-rail relationship is a highly time-varying and complex system, and the wheel-rail characteristic curve is not constant. Furthermore, due to factors such as vibration and electromagnetic interference in the locomotive's operating environment, the linear velocity collected by the speed sensor contains a significant amount of noise. Directly applying the speed sensor signal to locomotive adhesion control can lead to serious distortions in slip and coasting detection, and control failures. To obtain effective signals from the speed sensor, a Kalman filter is applied to optimally estimate the acceleration, thus filtering the acceleration and improving data accuracy.

[0138] In one embodiment, after using a Kalman filter to perform optimal estimation of the acceleration and obtaining the optimal acceleration estimate, the method further includes: using a Kalman smoother to smooth the optimal acceleration estimate and obtain a smoothed acceleration.

[0139] Further smoothing filtering after the optimal estimation yields better results and more accurate acceleration data.

[0140] For example, you can first establish a wheel circumference acceleration model, then perform online Kalman estimation of the wheel circumference acceleration, and then perform smoothing filtering.

[0141] The acceleration model is as follows:

[0142]

[0143]

[0144] The explanation is as follows:

[0145] : System state at time k; : The state observed at time k;

[0146] System noise at time k-1; : Noise observed at time k;

[0147] : Transfer matrix of the dynamic system at time k-1; : Observation model matrix at time k

[0148] The Kalman filter mainly consists of two processes: Prediction and Update. The specific formulas are as follows:

[0149] Prediction:

[0150]

[0151]

[0152] Update:

[0153]

[0154]

[0155]

[0156]

[0157] The explanation is as follows:

[0158] and The mean and covariance of the state space predicted at time k; and The mean and covariance of the state space estimated at time k; The observation difference at time k; Estimate the prediction covariance at time k; This represents the filter gain.

[0159] The specific formula for the Kalman_RTS smoother is as follows:

[0160]

[0161]

[0162]

[0163]

[0164]

[0165] The explanation is as follows:

[0166] and The smoother estimate of the sampled values ​​and covariance at time k; and The filter estimate of the sampled value and covariance at time k; and The filter estimate of the sampled value and covariance at time k+1; Let k be the smoother gain at time k.

[0167] In one embodiment, step S150, which calculates the critical value of the differential acceleration based on the motor torque, includes:

[0168]

[0169]

[0170] Among them, T m For motor torque, The rate of change of motor torque. The preset moment of inertia; This is the critical value for the differential of acceleration. The moment of inertia is the moment of inertia of the motor, wheelset, and its accessories referred to the wheelset.

[0171] Adhesion control based on acceleration derivative is adopted, and its basic control principle is as follows:

[0172] Equations of motion for the electric motor:

[0173] (30)

[0174] Based on (30), we can derive (31):

[0175] (31)

[0176] (31) Both sides are simultaneously adjusted Differentiate:

[0177] (32)

[0178] Pick At the same time, remember , Substituting it into equation (32) yields:

[0179] (33)

[0180] In locomotive adhesion control, it is desirable for the locomotive adhesion to operate slightly to the left of the peak point of its adhesion characteristic curve (maximum adhesion coefficient / maximum adhesion force). At this point, ( Substituting this into equation (33), we get:

[0181] (34)

[0182] (35)

[0183] The meaning of the above symbols: For locomotive speed; For locomotive weight; The moment of inertia of the motor, wheelset, and their accessories referred to the wheelset; This refers to the motor torque; r is the locomotive running resistance; r is the locomotive wheelset radius; The transmission ratio; The circumferential angular velocity of the locomotive wheel; For adhesion.

[0184] To ensure the locomotive operates slightly to the left of the adhesion peak and that the adhesion force is slightly less than the maximum adhesion force, the differential acceleration of the locomotive wheels must satisfy formula (35). Therefore, the following formula is adopted: As the differential critical value of acceleration, by comparing the acceleration with the differential critical value of acceleration, when the acceleration is greater than the differential critical value of acceleration, the motor torque of the wheel is adjusted to reduce the acceleration, with the locomotive wheel working to the left of the adhesion peak point as the target, to achieve optimal adhesion utilization control.

[0185] In one embodiment, adjusting the motor torque of the wheel in step S170 includes: reducing the motor torque of the wheel until the filtered acceleration is less than or equal to the differential critical value of acceleration.

[0186] Reduce the motor torque of the wheels and aim to make the locomotive wheels work to the left of the adhesion peak point to achieve optimal adhesion utilization control.

[0187] It should be understood that, although Figure 7 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 7 At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0188] like Figure 8 The diagram shows the control system block diagram of the locomotive adhesion utilization control method based on acceleration derivative of this invention. The actual control effect of the locomotive adhesion utilization control method based on acceleration derivative of this invention is as follows: Figure 9 , Figure 10 and Figure 11 As shown, practical application on the HXD1C locomotive demonstrates advantages such as accurate and timely judgment of slippage trends, smooth locomotive traction, and low wheelset creep speed. Long-term, large-scale testing of HXD1C locomotives on long gradients and lines with small curve radii has proven the effectiveness of the adhesion control scheme based on acceleration derivatives.

[0189] This invention uses the Kalman algorithm to identify the wheelset acceleration signal in real time, obtaining the optimal linear estimate of the wheelset acceleration. Based on this, RTS monotonicity processing is performed to obtain a smooth acceleration signal, completely solving the problem of noise interference in the acceleration signal. The advantages of this invention are derived through reasoning as follows:

[0190] (36)

[0191] (37)

[0192] Formula 36 provides the control law for the direct adhesive force control system. The calculation of adhesive force directly introduces the differential of acceleration. The speed differential calculated based on the real-time locomotive speed signal has high noise. Based on this, it is very difficult to directly judge the trend of adhesive force change, and it loses its application value under harsh track conditions.

[0193] Equation 37 gives the control law of the locomotive adhesion utilization algorithm based on acceleration derivative of the present invention. The calculated wheelset acceleration is estimated online in real time through Kalman filter to obtain an acceleration signal with excellent monotonicity. Based on this, the acceleration derivative adhesion utilization control has good control performance.

[0194] In one embodiment, a locomotive adhesion control device is provided, such as... Figure 12 As shown, the device includes a velocity acquisition module 110, an acceleration optimization module 130, a critical value acquisition module 150, and an adhesion utilization adjustment module 170.

[0195] The speed acquisition module 110 is used to collect the angular velocity of the locomotive wheels and calculate the acceleration of the wheels based on the angular velocity; the acceleration optimization module 130 is used to filter the acceleration; the critical value acquisition module 150 is used to acquire the motor torque of the wheels and calculate the differential critical value of acceleration based on the motor torque; the adhesion utilization adjustment module 170 is used to adjust the motor torque of the wheels when the acceleration after filtering is greater than the differential critical value of acceleration.

[0196] The aforementioned locomotive adhesion utilization control device compares the acceleration and differential critical value of the locomotive wheels with the filtered acceleration and differential critical value. When the filtered acceleration exceeds the differential critical value, the motor torque of the wheel is adjusted to achieve active adhesion utilization control with good control effect. Moreover, because the acceleration is filtered, the influence of noise can be reduced and the accuracy of acceleration can be improved. Therefore, the accuracy of comparison and analysis based on the filtered acceleration is higher, thereby improving the accuracy of adhesion utilization control.

[0197] In one embodiment, the acceleration optimization module 130 uses a Kalman filter to perform optimal estimation of the acceleration to obtain the optimal acceleration estimate.

[0198] In one embodiment, the acceleration optimization module 130 further employs a Kalman smoother to smooth the optimal acceleration estimate, thereby obtaining a smoothed acceleration.

[0199] Specific limitations regarding the locomotive adhesion utilization control device can be found in the limitations of the locomotive adhesion utilization control method described above, and will not be repeated here. Each module in the aforementioned locomotive adhesion utilization control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in the control device, or stored in software in the memory of the control device, so that the processor can call and execute the operations corresponding to each module. It should be noted that the module division in this embodiment is illustrative and only represents a logical functional division; other division methods may be used in actual implementation.

[0200] In one embodiment, a control device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the methods in the above embodiments.

[0201] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the methods described in the above embodiments.

[0202] The aforementioned control device and computer-readable storage medium, since they can implement the steps of the methods in the above embodiments, similarly improve the accuracy of adhesion utilization control.

[0203] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0204] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0205] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A locomotive adhesion control method, characterized in that, include: The angular velocity of the locomotive wheels is collected, and the acceleration of the wheels is calculated based on the angular velocity. The acceleration is filtered. Obtain the motor torque of the wheel, and calculate the critical value of the differential acceleration based on the motor torque; If the derivative of the filtered acceleration is greater than the critical value of the derivative of acceleration, then the motor torque of the wheel is adjusted. The filtering process for the acceleration includes: The acceleration is optimally estimated using a Kalman filter to obtain the optimal acceleration estimate. The step of performing optimal estimation of the acceleration using a Kalman filter to obtain the optimal acceleration estimate further includes: The optimal acceleration estimate is smoothed using a Kalman smoother to obtain a smoothed acceleration. The Kalman smoother is a Kalman RTS smoother, which performs smoothing using the following formula: in, and The smoother estimate of the sampled values ​​and covariance at time k; and The filter estimate of the sampled value and covariance at time k; and The filter estimate of the sampled value and covariance at time k+1; Let k be the smoother gain at time k; Let k be the dynamic system transfer matrix at time k; The system noise at time k; The adjustment of the motor torque of the wheel includes: Reduce the motor torque of the wheel until the differential of the filtered acceleration is less than or equal to the critical value of the differential of acceleration.

2. The method according to claim 1, characterized in that, The calculation of the wheel acceleration based on the angular velocity includes: Convert the angular velocity into linear velocity; The acceleration of the wheel is calculated based on the linear velocity.

3. The method according to claim 1, characterized in that, The calculation of the differential critical value of acceleration based on the motor torque includes: Among them, T m The torque of the motor is... The rate of change of motor torque. The preset moment of inertia; This is the critical value of the differential acceleration.

4. A locomotive adhesion control device, characterized in that, include: The speed acquisition module is used to collect the angular velocity of the locomotive wheels and calculate the acceleration of the wheels based on the angular velocity. An acceleration optimization module is used to filter the acceleration. The critical value acquisition module is used to acquire the motor torque of the wheel and calculate the critical value of the differential acceleration based on the motor torque; The adhesion adjustment module is used to adjust the motor torque of the wheel when the derivative of the filtered acceleration is greater than the critical value of the derivative of acceleration. The acceleration optimization module is used for: The acceleration is optimally estimated using a Kalman filter to obtain the optimal acceleration estimate. The acceleration optimization module is further configured to: The optimal acceleration estimate is smoothed using a Kalman smoother to obtain a smoothed acceleration. The Kalman smoother is a Kalman RTS smoother, which performs smoothing using the following formula: in, and The smoother estimate of the sampled values ​​and covariance at time k; and The filter estimate of the sampled value and covariance at time k; and The filter estimate of the sampled value and covariance at time k+1; Let k be the smoother gain at time k; Let k be the dynamic system transfer matrix at time k; The system noise at time k; The adhesion adjustment module is used for: Reduce the motor torque of the wheel until the differential of the filtered acceleration is less than or equal to the critical value of the differential of acceleration.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

6. A control device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

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