Optimized adhesion control method, system, device and medium for creep rate tracking control

Abstract

The application discloses an optimization adhesion control method and system based on creep ratio tracking control, equipment and medium, and relates to the technical field of vehicle control. The actual locomotive wheel speed and the actual vehicle speed of a target vehicle are obtained. The actual creep ratio of the target vehicle is determined based on the actual locomotive wheel speed and the actual vehicle speed. The wheel radius, torque, rotational inertia and adhesion force of the target vehicle are obtained. The target creep ratio of the target vehicle is determined based on the wheel radius, torque, rotational inertia and adhesion force and the actual vehicle speed. The torque adjustment parameter of the target vehicle for eliminating the error between the actual creep ratio and the target creep ratio is determined based on the target creep ratio and the actual creep ratio, so that the torque of the target vehicle is adjusted based on the torque adjustment parameter. The torque adjustment parameter is determined based on the target creep ratio and the actual creep ratio, the torque of the target vehicle is adjusted based on the torque adjustment parameter, the target vehicle can reach the target creep ratio, and the maximum adhesion force can be exerted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, more particularly, to an optimization adhesion control method and system for creep rate tracking control, an electronic device and a computer readable storage medium. BACKGROUND

[0002] Currently, the metro vehicle requires to ensure the effective traction performance of the vehicle under various track conditions, especially under the adverse track conditions caused by the decrease of the adhesion coefficient between the wheel and the rail due to the external factors such as rain and snow weather, oil stains / coverings on the track, etc. The metro vehicle usually adopts an electric locomotive to provide running power by a traction motor, and the traction performance depends on the adhesion between the wheel and the rail. The decrease of the adhesion coefficient between the wheel and the rail will cause the metro vehicle to appear the phenomenon of idling and sliding, and eventually cause the wheel and rail to be scratched, worn, and even derailed, etc. Therefore, a high-performance adhesion control strategy is designed in the train traction control system to prevent the metro vehicle from idling and sliding in time, so that the adhesion working point of the train is near the maximum adhesion coefficient.

[0003] Adhesion control is an indispensable part of the control of the wheel-rail contact type rail vehicle in the field of rail transit, and the adhesion control includes the dual functions of performance control and safety protection. The adhesion control requires higher and higher in improving the traction force between the wheel and the rail and obtaining higher stability. In order to achieve a better adhesion control effect and improve the adhesion control performance, it is necessary to ensure that the adhesion between the wheel and the rail is always exerted near the optimal adhesion point.

[0004] In summary, how to ensure that the vehicle exerts the maximum adhesion force is a problem to be solved by the technical personnel in the field. SUMMARY

[0005] The purpose of the present application is to provide an optimization adhesion control method for creep rate tracking control, which can solve the technical problem of how to ensure that the vehicle exerts the maximum adhesion force to a certain extent. The present application also provides an optimization adhesion control system for creep rate tracking control, an electronic device and a computer readable storage medium.

[0006] In order to achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] An optimization adhesion control method for creep rate tracking control, comprising:

[0008] obtaining the actual locomotive wheel speed and the actual vehicle speed of a target vehicle;

[0009] determining the actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed;

[0010] obtaining the wheel radius, torque, moment of inertia and adhesion force of the target vehicle;

[0011] determining a target creep ratio of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion force and the actual vehicle speed;

[0012] determining a torque adjustment parameter of the target vehicle for eliminating an error between the actual creep ratio and the target creep ratio based on the target creep ratio and the actual creep ratio, so as to adjust the torque of the target vehicle based on the torque adjustment parameter.

[0013] Preferably, the actual creep ratio of the target vehicle is determined based on the actual locomotive wheel speed and the actual vehicle speed, comprising:

[0014] the actual creep ratio of the target vehicle is determined based on the actual locomotive wheel speed and the actual vehicle speed by a first operation formula;

[0015] the first operation formula comprises:

[0016]

[0017] wherein, n1 represents the actual creep ratio; v w represents the actual locomotive wheel speed; v represents the actual vehicle speed.

[0018] Preferably, the target creep ratio of the target vehicle is determined based on the wheel radius, the torque, the moment of inertia, the adhesion force and the actual vehicle speed, comprising:

[0019] the target creep ratio of the target vehicle is determined based on the wheel radius, the torque, the moment of inertia, the adhesion force and the actual vehicle speed by a second operation formula;

[0020] the second operation formula comprises:

[0021]

[0022] wherein, n2 represents the target creep ratio; r represents the wheel radius; T1 represents the torque; J represents the moment of inertia; F ad represents the adhesion force; v represents the actual vehicle speed; t represents time.

[0023] Preferably, the torque adjustment parameter of the target vehicle for eliminating the error between the actual creep ratio and the target creep ratio is determined based on the target creep ratio and the actual creep ratio, comprising:

[0024] obtaining a vehicle acceleration of the target vehicle;

[0025] determining a target creep speed of the target vehicle based on the target creep ratio.

[0026] determining an error value between the target slip ratio and the actual slip ratio;

[0027] determining a rate of change of the target slip speed over time;

[0028] inputting the vehicle acceleration, the target slip speed, the error value and the rate of change into a pre-trained BP neural network model;

[0029] receiving the torque adjustment parameter of the target vehicle output by the BP neural network model to eliminate the error between the actual slip ratio and the target slip ratio.

[0030] Preferably, the torque adjustment parameter includes an integral coefficient and a proportional coefficient of a PI controller.

[0031] Preferably, after determining the torque adjustment parameter of the target vehicle to eliminate the error between the actual slip ratio and the target slip ratio based on the target slip ratio and the actual slip ratio, the method further comprises:

[0032] determining a target torque of the target vehicle through the PI controller.

[0033] Preferably, the determining a target torque of the target vehicle through the PI controller comprises:

[0034] determining the target torque of the target vehicle through the PI controller through a third operation formula;

[0035] The third operation formula comprises:

[0036] T(k) = T(k-1) + k p (e(k) - e(k-1) + k i e(k));

[0037] wherein T(k) represents the target torque at time k; T(k-1) represents the target torque at time (k-1); k p represents the proportional coefficient; k i represents the integral coefficient; e(k) represents the error value at time k; e(k-1) represents the error value at time (k-1).

[0038] An optimized adhesion control system for slip ratio tracking control, comprising:

[0039] a first acquisition module configured to acquire an actual locomotive wheel speed and an actual vehicle speed of a target vehicle;

[0040] a first determining module, configured to determine an actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed;

[0041] A second acquisition module is used to obtain the wheel radius, torque, moment of inertia, and adhesion of the target vehicle;

[0042] a second determining module, configured to determine a target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion, and the actual vehicle speed;

[0043] The third determination module is configured to determine, based on the target creep rate and the actual creep rate, a torque adjustment parameter of the target vehicle that eliminates an error between the actual creep rate and the target creep rate, so as to adjust the torque of the target vehicle based on the torque adjustment parameter.

[0044] An electronic device, comprising:

[0045] memory for storing computer programs;

[0046] A processor is configured to implement the steps of any of the above-mentioned methods for optimizing adhesion control of creep rate tracking control when executing the computer program.

[0047] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned methods for optimizing adhesion control of creep rate tracking control.

[0048] The present application provides an optimized adhesion control method for creep rate tracking control, which comprises obtaining the actual locomotive wheel speed and actual vehicle speed of a target vehicle; determining the actual creep rate of the target vehicle based on the actual locomotive wheel speed and actual vehicle speed; obtaining the wheel radius, torque, moment of inertia, and adhesion of the target vehicle; determining a target creep rate of the target vehicle based on the wheel radius, torque, moment of inertia, adhesion, and actual vehicle speed; and determining a torque adjustment parameter for the target vehicle based on the target creep rate and actual creep rate to eliminate the error between the actual creep rate and the target creep rate, thereby adjusting the torque of the target vehicle based on the torque adjustment parameter. In the present application, the actual creep rate of the target vehicle is determined based on the actual locomotive wheel speed and actual vehicle speed, the target creep rate of the target vehicle is determined based on the wheel radius, torque, moment of inertia, adhesion, and actual vehicle speed, and finally, the torque adjustment parameter for the target vehicle based on the target creep rate and actual creep rate to eliminate the error between the actual creep rate and the target creep rate is determined. Subsequent adjustment of the torque of the target vehicle based on the torque adjustment parameter can ensure that the target vehicle reaches the target creep rate and maximizes adhesion. The optimized adhesion control system, electronic device and computer-readable storage medium for creep rate tracking control provided in this application also solve corresponding technical problems. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the provided drawings.

[0050] Figure 1 The first flow chart of the optimization adhesion control method of the creep rate tracking control provided by the embodiments of the present application.

[0051] Figure 2 The second flow chart of the optimization adhesion control method of the creep rate tracking control provided by the embodiments of the present application.

[0052] Figure 3 The structural schematic diagram of the BP neural network model.

[0053] Figure 4 The system block diagram of the present application.

[0054] Figure 5 The structural schematic diagram of the optimization adhesion control system of the creep rate tracking control provided by the embodiments of the present application.

[0055] Figure 6 The structural schematic diagram of the electronic device provided by the embodiments of the present application.

[0056] Figure 7 Another structural schematic diagram of the electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0057] The technical solutions of the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0058] Please refer to Figure 1 , Figure 1 The first flow chart of the optimization adhesion control method of the creep rate tracking control provided by the embodiments of the present application.

[0059] The optimization adhesion control method of the creep rate tracking control provided by the embodiments of the present application can include the following steps:

[0060] Step S101: obtaining the actual locomotive wheel speed and the actual vehicle speed of the target vehicle.

[0061] Step S102: determining the actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed.

[0062] In actual application, the actual locomotive wheel speed and the actual vehicle speed of the target vehicle can be acquired first, and the actual creep rate of the target vehicle is determined based on the actual locomotive wheel speed and the actual vehicle speed, so as to adjust the torque of the vehicle by using the actual creep rate subsequently.

[0063] In specific application scenarios, the actual vehicle speed of the vehicle can be acquired by means of the VCU (Vehicle control unit, central control unit), which is not limited herein.

[0064] In specific application scenarios, in the process of determining the actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed, the actual creep rate of the target vehicle can be determined based on the actual locomotive wheel speed and the actual vehicle speed by using a first calculation formula; the first calculation formula comprises:

[0065]

[0066] wherein, n1 represents the actual creep rate; v w represents the actual locomotive wheel speed; and v represents the actual vehicle speed.

[0067] Step S103: acquiring the wheel radius, the torque, the moment of inertia, and the adhesion force of the target vehicle.

[0068] Step S104: determining the target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion force, and the actual vehicle speed.

[0069] In actual application, after the actual creep rate of the target vehicle is determined, the wheel radius, the torque, the moment of inertia, and the adhesion force of the target vehicle are acquired; the target creep rate of the target vehicle is determined based on the wheel radius, the torque, the moment of inertia, the adhesion force, and the actual vehicle speed, so as to determine the torque adjustment information of the vehicle by comparing the actual creep rate and the target creep rate. It should be noted that the moment of inertia refers to the moment of inertia of the wheelset and the motor converted to the wheelset side; and the torque refers to the torque of the motor acting on the wheelset.

[0070] In specific application scenarios, in the process of determining the target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion force, and the actual vehicle speed, the target creep rate of the target vehicle can be determined based on the wheel radius, the torque, the moment of inertia, the adhesion force, and the transmission ratio of the gearbox by using a second calculation formula; the second calculation formula comprises:

[0071]

[0072] Wherein, n2 represents the target slip ratio; r represents the wheel radius; T1 represents the torque; J represents the moment of inertia; F ad represents the adhesion; v represents the actual vehicle speed; t represents the time.

[0073] It should be noted that the motor rotation equation is:

[0074] Wherein, J m is the moment of inertia of the wheelset converted to the traction motor side; ω m is the angular speed of the traction motor; T m is the electromagnetic torque of the traction motor; T L is the load torque of the motor;

[0075] The load torque TL is: T L = F ad × r / R g ; wherein, R g represents the gear ratio of the gearbox;

[0076] Then And ω1 = ω m / R g, ω1 represents the angular speed of the wheelset;

[0077] Therefore, the relationship between the slip ratio and the motor torque can be obtained:

[0078]

[0079] Step S105: Based on the target slip ratio and the actual slip ratio, determine the torque adjustment parameter of the target vehicle for eliminating the error between the actual slip ratio and the target slip ratio, so as to adjust the torque of the target vehicle based on the torque adjustment parameter.

[0080] In actual application, after determining the actual slip ratio and the target slip ratio, the torque adjustment parameter of the target vehicle for eliminating the error between the actual slip ratio and the target slip ratio can be determined based on the target slip ratio and the actual slip ratio, so as to adjust the torque of the target vehicle based on the torque adjustment parameter.

[0081] The application provides an optimization adhesion control method of creep rate tracking control, actual locomotive wheel speed and actual vehicle speed of a target vehicle are obtained, actual creep rate of the target vehicle is determined based on the actual locomotive wheel speed and the actual vehicle speed, wheel radius, torque, moment of inertia and adhesion force of the target vehicle are obtained, target creep rate of the target vehicle is determined based on the wheel radius, the torque, the moment of inertia, the adhesion force and the actual vehicle speed, torque adjustment parameters of the target vehicle for eliminating errors between the actual creep rate and the target creep rate are determined based on the target creep rate and the actual creep rate, and the torque of the target vehicle is adjusted based on the torque adjustment parameters.

[0082] Please refer to Figure 2 , Figure 2 A second flowchart of the optimization adhesion control method of creep rate tracking control provided by the embodiment of the application is provided.

[0083] The optimization adhesion control method of creep rate tracking control provided by the embodiment of the application can include the following steps:

[0084] Step S201: obtaining actual locomotive wheel speed and actual vehicle speed of a target vehicle.

[0085] Step S202: determining actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed.

[0086] Step S203: obtaining wheel radius, torque, moment of inertia and adhesion force of the target vehicle.

[0087] Step S204: determining target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion force and the actual vehicle speed.

[0088] Step S205: obtaining vehicle acceleration of the target vehicle.

[0089] Step S206: determining target creep speed of the target vehicle based on the target creep rate.

[0090] Step S207: determining error value between the target creep rate and the actual creep rate.

[0091] Step S208: determining change rate of the target creep speed with time.

[0092] Step S209: input the vehicle acceleration, the target creep speed, the error value and the change rate into the pre-trained BP neural network model.

[0093] Step S210: receive the torque adjustment parameter of the target vehicle output by the BP neural network model to eliminate the error between the actual creep rate and the target creep rate, so as to adjust the torque of the target vehicle based on the torque adjustment parameter.

[0094] In actual application, in the process of determining the torque adjustment parameter of the target vehicle for eliminating the error between the actual creep rate and the target creep rate based on the target creep rate and the actual creep rate, the vehicle acceleration a of the target vehicle can be obtained; the target creep speed vs of the target vehicle is determined based on the target creep rate, that is, the target creep speed of the target vehicle is determined based on the target creep rate through the first operation formula; the error value e between the target creep rate and the actual creep rate is determined; the change rate dvs / dt of the target creep speed with time is determined; the vehicle acceleration, the target creep speed, the error value and the change rate are input into the pre-trained BP (back propagation) neural network model; and the torque adjustment parameter of the target vehicle output by the BP neural network model for eliminating the error between the actual creep rate and the target creep rate is received.

[0095] In a specific application scenario, the structure of the BP neural network model can be determined according to actual needs, for example, as shown in FIG. 1, assuming that i, j, m are respectively the number of input layer, hidden layer and output layer neurons, the input and output of the hidden layer are: Figure 3

[0096]

[0097] The input and output of the output layer are:

[0098]

[0099] The activation function can be represents the input of the hidden layer j; represents the corresponding weight value between the input layer i and the hidden layer j; represents the output of the input layer i; represents the output of the hidden layer j; sigmoid represents the activation function; represents the input of the output layer m; represents the corresponding weight value between the hidden layer j and the output layer m; represents the output of the output layer m; k p represents the proportional coefficient; k i represents the integral coefficient; represents the first output value of the output layer m; ​represents a second output value of the output layer m.

[0100] In actual applications, considering that the torque of the vehicle can be adjusted by means of a PI (proportional integral) controller, the torque adjustment parameter can include an integral coefficient and a proportional coefficient of the PI controller.

[0101] In a specific application scenario, after determining the torque adjustment parameter of the target vehicle for eliminating the error between the actual creep rate and the target creep rate based on the target creep rate and the actual creep rate, the target torque of the target vehicle can be determined by means of a PI controller.

[0102] In a specific application scenario, in the process of determining the target torque of the target vehicle by means of a PI controller, the target torque of the target vehicle can be determined by means of a PI controller by means of a third operation formula; the third operation formula includes:

[0103] T(k)=T(k-1)+k p (e(k)-e(k-1)+k i e(k));

[0104] wherein T(k) represents the target torque at time k; T(k-1) represents the target torque at time (k-1); k p represents a proportional coefficient; k i represents an integral coefficient; e(k) represents an error value at time k; and w(k-1) represents an error value at time (k-1). At this time, the system block diagram of the present application can be as shown in Figure 4 .

[0105] Please refer to Figure 5 , Figure 5 a structure schematic diagram of an optimized adhesion control system of creep rate tracking control provided by the embodiment of the present application.

[0106] The optimized adhesion control system of creep rate tracking control provided by the embodiment of the present application can include:

[0107] The first acquisition module 101 is configured to acquire the actual locomotive wheel speed and the actual vehicle speed of the target vehicle.

[0108] The first determination module 102 is configured to determine the actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed.

[0109] The second acquisition module 103 is configured to acquire the wheel radius, the torque, the moment of inertia, and the adhesion force of the target vehicle.

[0110] The second determination module 104 is configured to determine the target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion force, and the actual vehicle speed.

[0111] The third determining module 105 is configured to determine a torque adjustment parameter of the target vehicle for eliminating an error between the actual creep rate and the target creep rate based on the target creep rate and the actual creep rate, so as to adjust the torque of the target vehicle based on the torque adjustment parameter.

[0112] The first determining module can be specifically configured to determine the actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed by using a first calculation formula.

[0113] The first calculation formula comprises:

[0114]

[0115] wherein, n1 represents the actual creep rate; v w represents the actual locomotive wheel speed; and v represents the actual vehicle speed.

[0116] The second determining module can be specifically configured to determine the target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion force and the actual vehicle speed by using a second calculation formula.

[0117] The second calculation formula comprises:

[0118]

[0119] wherein, n2 represents the target creep rate; r represents the wheel radius; T1 represents the torque; J represents the moment of inertia; F ad represents the adhesion force; v represents the actual vehicle speed; and t represents time.

[0120] The third determining module can be specifically configured to obtain the vehicle acceleration of the target vehicle, determine the target creep speed of the target vehicle based on the target creep rate, determine an error value between the target creep rate and the actual creep rate, determine a change rate of the target creep speed with time, input the vehicle acceleration, the target creep speed, the error value and the change rate into a pre-trained BP neural network model, and receive a torque adjustment parameter of the target vehicle for eliminating the error between the actual creep rate and the target creep rate output by the BP neural network model.

[0121] The torque adjustment parameter comprises an integral coefficient and a proportional coefficient of a PI controller.

[0122] The optimization adhesion control system for creep rate tracking control can further comprise:

[0123] The fourth determining module is configured to determine the target torque of the target vehicle by the PI controller after the third determining module determines the torque adjustment parameter of the target vehicle for eliminating the error between the actual creep rate and the target creep rate.

[0124] The fourth determining module can be specifically configured to determine the target torque of the target vehicle by the PI controller through the third operation formula.

[0125] The third operation formula comprises:

[0126] T(k) = T(k-1) + k p (e(k) - e(k-1) + k i e(k));

[0127] wherein T(k) represents the target torque at the k time; T(k-1) represents the target torque at the (k-1) time; k p represents a proportional coefficient; k i represents an integral coefficient; e(k) represents the error value at the k time; and e(k-1) represents the error value at the (k-1) time.

[0128] The present application also provides an electronic device and a computer readable storage medium, both of which have the corresponding effects of the optimization adhesion control method of the creep rate tracking control provided by the embodiments of the present application. Please refer to Figure 6 , Figure 6 The present application provides a structural schematic diagram of an electronic device.

[0129] The electronic device provided by the embodiments of the present application comprises a memory 201 and a processor 202, the memory 201 stores a computer program, and the processor 202 implements the steps of the optimization adhesion control method of the creep rate tracking control when executing the computer program.

[0130] Please refer to Figure 7The electronic device provided in another embodiment of the present application can further include: an input port 203 connected to the processor 202, configured to transmit an external input command to the processor 202; a display unit 204 connected to the processor 202, configured to display the processing result of the processor 202 to the outside world; and a communication module 205 connected to the processor 202, configured to realize the communication between the electronic device and the outside world. The display unit 204 can be a display panel, a laser scanning display, or the like. The communication mode adopted by the communication module 205 includes but is not limited to Mobile High-Definition Link (MHL), Universal Serial Bus (USB), High-Definition Multimedia Interface (HDMI), wireless connection: WIreless Fidelity (WiFi), Bluetooth communication technology, low-power Bluetooth communication technology, and IEEE 802.11s-based communication technology.

[0131] The computer readable storage medium provided in the embodiment of the present application stores a computer program, and the computer program is executed by the processor to realize the steps of the optimization adhesion control method of the creep rate tracking control described in any one of the above embodiments.

[0132] The computer readable storage medium involved in the present application includes a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a compact disc read-only memory (CD-ROM), or any other form of storage medium known in the technical field.

[0133] The descriptions of the related parts in the optimization adhesion control system of the creep rate tracking control, the electronic device, and the computer readable storage medium provided in the embodiments of the present application can be referred to the detailed descriptions of the corresponding parts in the optimization adhesion control method of the creep rate tracking control provided in the embodiments of the present application, which will not be described here again. In addition, the parts in the above technical solutions provided in the embodiments of the present application that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail, so as to avoid excessive description.

[0134] It is also to be noted that, as used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a component" can include a combination of two or more components, and the term "an element" can include comparable reference to a plurality of elements. Additionally, the term "or" as used herein means any one member of a logical disjunction (i.e., it is equivalent to "or" and "or else") and not a logical exclusion. Also, the terms "comprise," "comprising," "include," "including," and the like mean "including but not limited to." Furthermore, the terms "first," "second," "third," etc. are used merely as labels, and are not intended to impose numerical requirements on their objects.

[0135] The above description of disclosed embodiments provides examples, and is not intended to be limiting. Numerous modifications of the embodiments, as defined herein, will be apparent to those skilled in the art, and will be encompassed within the spirit of the present application. Accordingly, the scope of the present application is to be limited only by the modified claims below.

Claims

1. An optimized adhesion control method for creep rate tracking control, characterized in that: include: Obtain the actual locomotive wheel speed and actual vehicle speed of the target vehicle; determining an actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed; Obtaining the wheel radius, torque, moment of inertia, and adhesion of the target vehicle; determining a target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion, and the actual vehicle speed; determining, based on the target creep rate and the actual creep rate, a torque adjustment parameter of the target vehicle that eliminates an error between the actual creep rate and the target creep rate, and adjusting the torque of the target vehicle based on the torque adjustment parameter; Wherein, determining the target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion force, and the actual vehicle speed includes: determining the target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion, and the actual vehicle speed using a second calculation formula; The second operation formula includes: ； in, represents the target creep rate; represents the wheel radius; represents the torque; represents the moment of inertia; represents the adhesion force; Indicates the actual vehicle speed; Indicates time; Wherein, determining the torque adjustment parameter of the target vehicle to eliminate the error between the actual creep rate and the target creep rate based on the target creep rate and the actual creep rate includes: Obtaining the vehicle acceleration of the target vehicle; determining a target creep speed of the target vehicle based on the target creep rate; determining an error value between the target creep rate and the actual creep rate; determining a rate of change of the target creep velocity over time; Inputting the vehicle acceleration, the target creep speed, the error value and the change rate into a pre-trained BP neural network model; The torque adjustment parameter of the target vehicle output by the BP neural network model is received to eliminate the error between the actual creep rate and the target creep rate.

2. The method according to claim 1, characterized in that The determining the actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed includes: determining the actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed using a first calculation formula; The first operation formula includes: ； in, represents the actual creep rate; represents the actual locomotive wheel speed; Indicates the actual vehicle speed.

3. The method according to any one of claims 1 to 2, characterized in that The torque adjustment parameters include an integral coefficient and a proportional coefficient of a PI controller.

4. The method according to claim 3, characterized in that After determining the torque adjustment parameter of the target vehicle that eliminates the error between the actual creep rate and the target creep rate based on the target creep rate and the actual creep rate, the method further includes: The target torque of the target vehicle is determined by the PI controller.

5. The method according to claim 4, characterized in that Determining the target torque of the target vehicle by the PI controller includes: Determining the target torque of the target vehicle by the PI controller through a third operation formula; The third operation formula includes: ； in, express The target torque at the time; express The target torque at the time; represents the proportionality coefficient; represents the integral coefficient; express The error value at the time; express The error value at the moment.

6. An optimized adhesion control system for creep rate tracking control, characterized in that: include: The first acquisition module is used to obtain the actual wheel speed and actual vehicle speed of the target vehicle; a first determining module, configured to determine an actual creep rate of the target vehicle based on the actual locomotive wheel speed and the actual vehicle speed; A second acquisition module is used to obtain the wheel radius, torque, moment of inertia, and adhesion of the target vehicle; a second determining module, configured to determine a target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion, and the actual vehicle speed; a third determining module, configured to determine, based on the target creep rate and the actual creep rate, a torque adjustment parameter of the target vehicle that eliminates an error between the actual creep rate and the target creep rate, so as to adjust the torque of the target vehicle based on the torque adjustment parameter; The second determining module is configured to determine the target creep rate of the target vehicle based on the wheel radius, the torque, the moment of inertia, the adhesion, and the actual vehicle speed using a second calculation formula; The second operation formula includes: ； in, represents the target creep rate; represents the wheel radius; represents the torque; represents the moment of inertia; represents the adhesion force; Indicates the actual vehicle speed; Indicates time; Among them, the third determination module is used to: obtain the vehicle acceleration of the target vehicle; determine the target creep speed of the target vehicle based on the target creep rate; determine the error value between the target creep rate and the actual creep rate; determine the rate of change of the target creep speed over time; input the vehicle acceleration, the target creep speed, the error value and the rate of change into a pre-trained BP neural network model; receive the torque adjustment parameter of the target vehicle output by the BP neural network model to eliminate the error between the actual creep rate and the target creep rate.

7. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the optimized adhesion control method for creep rate tracking control according to any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the optimized adhesion control method for creep rate tracking control according to any one of claims 1 to 5.

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