Six-axle locomotive axle load transfer optimization method, system, equipment and medium

Abstract

The invention relates to the field of locomotives, and provides a six-axle locomotive axle load transfer optimization method, system and device and a medium, and the method comprises the steps: obtaining design parameters of a locomotive, and selecting a design variable and a corresponding initial value from the design parameters; establishing a locomotive axle load transfer mechanical model of a locomotive body and front and rear bogies, and taking the model as a balance condition; selecting an optimized locomotive adhesion utilization rate as a target function, selecting a constraint condition comprising the balance condition, and solving to obtain an optimized value of a design variable corresponding to the optimized locomotive adhesion utilization rate; the optimized value of the design variable is substituted into the locomotive axle load transfer mechanical model, optimized axle load distribution is obtained, the optimized adhesion utilization rate and traction force are obtained through calculation, the six-axle locomotive is designed according to the optimized adhesion utilization rate, and the traction force is applied to all axles of the six-axle locomotive in the movement process. The idling risk of the locomotive is reduced through axle load transfer optimization, the traction performance of the train is improved, and the speed fluctuation of the train is reduced.

Description

Technical Field

[0001] The present invention relates to the field of locomotives, and in particular to a method, system, equipment and medium for optimizing axle weight transfer of a six-axle locomotive. Background Art

[0002] With the development of economy and society, railway transportation is facing greater freight demand, which requires the development of heavy-duty locomotives with greater power and traction. When the locomotive is pulling a freight train, it provides forward traction for the freight train behind it, while it is subjected to a backward horizontal force. This horizontal force and the traction provided by the wheel-rail to the locomotive will generate torque, causing some axle loads to be reduced, thereby affecting the traction and reducing the locomotive adhesion utilization rate.

[0003] The adhesion control and related design of locomotives are included in two stages. The first stage is the optimization of axle load transfer in the locomotive design stage, which requires adjusting the locomotive design parameters, improving the axle load transfer, and increasing the static adhesion utilization rate. The second stage is the online real-time adjustment of traction during the operation of the locomotive to improve adhesion utilization and idling, which mainly includes re-adhesion control and optimized adhesion control.

[0004] Axle load transfer refers to the phenomenon that the vertical load on each axle changes due to the traction force during the traction process of the locomotive. This change reduces the adhesion utilization of the locomotive, which may cause scratches on the track structure and shorten its service life.

[0005] The best adhesion performance of a single wheelset does not mean the best overall performance of the locomotive. In order to ensure that the system still has good overall traction performance when a wheelset fails, it is necessary to coordinate the power of other wheelsets. After a wheelset fails, the purpose of multi-wheelset adhesion coordinated control is achieved by comprehensively coordinating other normal wheelsets.

[0006] The existing adhesion control first-stage axle load transfer optimization technology is based on an optimization algorithm. The objective function is to maximize the traction force. The constraint equation uses the theoretical mechanics method to list the equilibrium equation. The design variable is the traction force of each axle. Therefore, the axle load transfer can only be improved by changing the traction force. However, the existing locomotive axle load transfer adjustment technology does not include factors such as the traction rod angle, wheelbase, and fixed distance into the design variables. Therefore, it is impossible to provide a solution for adjusting the axle load transfer through the traction rod angle, wheelbase, and fixed distance. The existing locomotive axle load transfer adjustment technology cannot take into account various different numbers of secondary support forms. The existing locomotive axle load transfer adjustment technology cannot take into account various different motor layout forms of secondary support forms.

[0007] The method used in the second stage of existing adhesion control for multi-wheel-set adhesion coordinated control does not fully consider the mechanical characteristics of the locomotive, and often fails to comprehensively consider the adhesion status of all wheelsets, seriously affecting the traction of the locomotive.

[0008] Therefore, it is necessary to optimize the axle load transfer during the locomotive design process in the first stage of adhesion control. In actual design and production, axle load transfer involves multiple factors such as locomotive spacing, traction rod inclination, suspension stiffness, etc. Involving the interaction and influence between multiple factors, it is necessary to comprehensively consider various factors in the optimization process and conduct complex mechanical analysis and calculations. At the same time, in the second stage of adhesion control, multi-wheel pair adhesion coordinated control needs to combine the locomotive traction mechanical characteristics to control the traction force, while ensuring adhesion and improving the traction of the locomotive. Summary of the invention

[0009] Based on the above purpose, the present invention proposes a six-axle locomotive axle weight transfer optimization method, comprising: Obtaining design parameters of the locomotive, and selecting design variables and corresponding initial values ​​from the design parameters; Establish the mechanical model of locomotive axle load transfer for the car body, front and rear bogies, and use it as the balance condition; Selecting the optimized locomotive adhesion utilization rate as the objective function, selecting the constraint conditions including the balance condition, and solving to obtain the optimized value of the design variable corresponding to the optimized locomotive adhesion utilization rate; The optimized values ​​of the design variables are substituted into the locomotive axle load transfer mechanical model to obtain the optimized axle load distribution and calculate the optimized adhesion utilization and traction force. The six-axle locomotive is designed according to the optimized adhesion utilization rate, and the traction force is applied to each axle of the six-axle locomotive during movement.

[0010] In some embodiments, the design parameters include axle weight, wheelbase, gauge, drawbar angle, coupler height, tow point height, and towing force; Design variables are design parameters that can be changed.

[0011] In some embodiments, the steps of establishing a mechanical model of locomotive axle load transfer between the vehicle body and the front and rear bogies include: Establish corresponding vertical force balance models and moment balance models for the car body, front bogie and rear bogie respectively; Establish the physical model of primary and secondary suspension; Establish a model for increasing and decreasing load on each axis.

[0012] In some embodiments, the steps of establishing the primary and secondary suspension physical models include: Obtain the vertical displacement corresponding to the primary suspension and the secondary suspension; Obtain the primary and secondary stiffness corresponding to the car body and bogie; According to Hooke's law, the physical models of primary and secondary suspension are established.

[0013] In some embodiments, the step of establishing a load increase and decrease model for each axis includes: Calculate the vertical load of each axis under static conditions according to the motor layout; According to the physical models of the primary and secondary suspensions and the vertical loads, a model for increasing and decreasing the load on each axle is established.

[0014] In some embodiments, the step of selecting the optimal locomotive adhesion utilization as the objective function includes: Select the axle with the lowest adhesion utilization rate from the wheel axles as the minimum axle; Maximizing the adhesion utilization of the smallest axis is taken as the optimization goal; Construct an objective function based on the optimization goal.

[0015] In some embodiments, the constraints also include the load increase and decrease range of the traction force of each axle, the adhesion coefficient range, and the design variable range.

[0016] The present invention proposes a six-axle locomotive axle weight transfer optimization system, comprising: An acquisition unit configured to acquire the traction force adopted by the idle shaft adhesion controller and the traction force of the non-idle shaft; A modeling unit configured to establish a mechanical model of a vehicle body, front and rear bogies for locomotive axle load transfer and as a balance condition; An optimization unit is configured to select an optimized locomotive adhesion utilization rate as an objective function, select a constraint condition including the balance condition, and solve to obtain an optimized value of a design variable corresponding to the optimized locomotive adhesion utilization rate; The implementation unit is configured to substitute the optimization scheme of the traction force of each axle into the locomotive axle weight transfer mechanical model to obtain the optimized axle weight distribution, and calculate the optimized adhesion utilization and traction force, design the six-axle locomotive according to the optimized adhesion utilization, and apply traction force to each axle of the six-axle locomotive during movement.

[0017] The present invention provides a computer device, comprising: At least one processor; and a memory storing a computer program executable on the processor, wherein the processor executes the steps of the method for optimizing axle load transfer of a six-axle locomotive when executing the program.

[0018] The present invention proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the axle weight transfer optimization method for a six-axle locomotive are executed.

[0019] The present invention has at least the following beneficial technical effects: The present invention proposes a six-axle locomotive axle weight transfer optimization method, system, equipment and medium, the method comprising: The design parameters of the locomotive are obtained, and design variables and corresponding initial values ​​are selected from the design parameters; a mechanical model of locomotive axle weight transfer of the car body, front and rear bogies is established, and used as a balance condition; the optimized locomotive adhesion utilization is selected as the objective function, and the constraint conditions including the balance condition are selected to solve the optimized values ​​of the design variables corresponding to the optimized locomotive adhesion utilization; the optimized values ​​of the design variables are substituted into the locomotive axle weight transfer mechanical model to obtain the optimized axle weight distribution, and the optimized adhesion utilization and traction are calculated, and a six-axle locomotive is designed according to the optimized adhesion utilization, and traction is applied to each axle of the six-axle locomotive during movement.

[0020] The present invention designs an axle weight adjustment algorithm that can incorporate factors such as traction rod deflection angle, wheelbase, and fixed distance into the design variables, selects an objective function suitable for actual production, and derives an optimization constraint equation suitable for different motor layouts and different numbers of secondary supports. Through the optimization of axle weight transfer, it is more reasonable, reduces the risk of locomotive idling, improves the traction performance of the train, reduces the speed fluctuation of the train, and improves the comfort of the train. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other embodiments can be obtained based on these drawings without paying creative work.

[0022] Figure 1 A flow chart of a six-axle locomotive axle weight transfer optimization method provided by the present invention; Figure 2 A module diagram of an axle load transfer optimization system for a six-axle locomotive provided by the present invention; Figure 3 A diagram of the stress state of a locomotive during traction in the prior art of an embodiment of a six-axle locomotive axle weight transfer optimization method provided by the present invention; Figure 4 A design flow chart of an embodiment of a six-axle locomotive axle load transfer optimization method provided by the present invention; Figure 5 A force state diagram of a locomotive during traction according to an embodiment of a six-axle locomotive axle load transfer optimization method provided by the present invention; Figure 6 A design and motion flow chart of an embodiment of a six-axle locomotive axle load transfer optimization method provided by the present invention; Figure 7 A schematic diagram of the structure of an embodiment of a computer device provided by the present invention; Figure 8 A schematic diagram of the structure of an embodiment of a computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0024] It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are for distinguishing two non-identical entities with the same name or non-identical parameters. It can be seen that "first" and "second" are only for the convenience of expression and should not be understood as limitations on the embodiments of the present invention. The subsequent embodiments will not explain this one by one.

[0025] The present invention proposes a method for optimizing the axle load transfer of a six-axle locomotive. Figure 1 and Figure 4 ,include: S1: Obtain design parameters of the locomotive, and select design variables and corresponding initial values ​​from the design parameters; S2: Establish the mechanical model of locomotive axle load transfer for the car body, front and rear bogies, and use it as the balance condition; S3: Selecting the optimized locomotive adhesion utilization rate as the objective function, selecting the constraint conditions including the equilibrium condition, and solving to obtain the optimized values ​​of the design variables corresponding to the optimized locomotive adhesion utilization rate; S4: Substituting the optimized values ​​of the design variables into the locomotive axle load transfer mechanical model to obtain an optimized axle load distribution, and calculating an optimized adhesion utilization rate based on the optimized axle load distribution.

[0026] The present invention designs an axle weight adjustment algorithm that can incorporate factors such as traction rod deflection angle, wheelbase, and fixed distance into the design variables, selects an objective function suitable for actual production, and derives an optimization constraint equation suitable for different motor layouts and different numbers of secondary supports. In the locomotive design stage, the axle weight transfer optimization is made more reasonable, the risk of locomotive idling is reduced, the traction performance of the train is improved, the speed fluctuation of the train is reduced, and the comfort of the train is improved.

[0027] The locomotive operation adhesion control stage of the present invention is similar to the axle load transfer design stage. The design variables are the traction of each axle of the locomotive. The traction of the idle axle is provided by the adhesion controller, and the traction of other axles is provided by the optimization algorithm. The traction is selected as the design variable, the traction of the idle axle adhesion controller is used as the input, the traction optimization value is substituted into the axle load transfer mechanical model, and the traction is applied. Based on the optimized traction distribution, while ensuring that idling does not occur, the overall traction output is improved.

[0028] When a train is running on the track, due to the surface condition of the tread rails, dynamic load and other factors, the locomotive may idle in the traction state, causing scratches on the rails. Reasonable axle weight distribution can reduce the wear of the wheels on the rails and extend the service life of the rails. By optimizing the traction force distribution through multi-wheel pair adhesion coordinated control, the traction force of the whole machine can be improved and the longitudinal impulse and noise of the train can be reduced.

[0029] In some embodiments, see Figure 1 and Figure 4 , the design parameters include axle weight, wheelbase, fixed distance, drawbar angle, coupler height, towing point height and traction; Design variables are design parameters that can be changed.

[0030] Clarify the main design parameters of the locomotive, such as axle weight, wheelbase, fixed distance, drawbar angle, coupler height, traction point height, and traction force. Clarify the design parameters that can be changed, select the design variables, and set the initial values ​​of these design variables.

[0031] Axle weight can ensure that the locomotive has sufficient traction when starting, accelerating and climbing, and improve the traction efficiency of the locomotive. By adjusting the axle weight, the wear of the wheels on the track can be reduced, extending the service life of the track.

[0032] A properly set wheelbase helps maintain the stability of the locomotive, especially when driving at high speeds and passing through curves. A reasonable choice of wheelbase can affect the locomotive's traction performance and curve passing performance, and improve the locomotive's lateral stability and adhesion utilization.

[0033] The fixed distance (i.e. the distance between the two bogies) directly affects the critical speed of the locomotive. A longer fixed distance can enhance the locomotive's ability to resist the nodding torque and improve the locomotive's adhesion utilization rate.

[0034] The adjustment of the drawbar angle can affect the locomotive axle load transfer performance. A drawbar angle greater than 5° will significantly reduce the adhesion utilization rate.

[0035] The height of the coupler is also an important factor affecting the axle load transfer. Generally speaking, the closer the coupler height is to the traction point height, the less axle load transfer there is. Therefore, if conditions permit, choose the coupler height reasonably.

[0036] The adjustment of the traction point height directly affects the bogie nodding torque. A lower traction point height can significantly improve the adhesion utilization rate.

[0037] Sufficient traction can ensure that the locomotive has a faster response speed when starting and accelerating, and improve the acceleration performance of the locomotive. The traction can ensure that the locomotive has sufficient power when climbing a slope, and improve the locomotive's climbing ability.

[0038] From multiple design parameters, variable ones are selected as design variables, and the design variables are optimized. By adjusting design variables such as traction force and wheelbase, the traction performance of the locomotive can be optimized so that it can perform well under various working conditions, which helps the locomotive to start, accelerate and climb faster and more smoothly, thereby improving operating efficiency.

[0039] In some embodiments, see Figure 1 and Figure 4 The steps of establishing the mechanical model of locomotive axle load transfer for the car body and front and rear bogies include: Establish corresponding vertical force balance models and moment balance models for the car body, front bogie and rear bogie respectively; Establish the physical model of primary and secondary suspension; Establish a model for increasing and decreasing load on each axis.

[0040] The formulas for establishing the vertical force balance equation and moment balance equation for the car body and front and rear bogies are as follows: The vertical force equation of the vehicle body is:

[0041] Body moment equation:

[0042] Front bogie vertical force equation:

[0043] Front bogie moment equation:

[0044] The vertical force equation of the rear bogie is:

[0045] Rear bogie moment equation:

[0046] Among them, Fsi is the secondary spring vertical force, Fpi is the primary spring vertical force, and Fti is the traction force of each axis. is the coupler force; Arrange markings for secondary springs, Arrange the markings for the motor, , , Take 1, , , Take -1. arrive Take 1. L si L is the longitudinal distance between the secondary spring and the center of the vehicle body, tiis the longitudinal distance between the primary spring and the center of the bogie. β is the inclination angle of the traction rod; L m It is the longitudinal distance between the motor suspension rod hanging point on the frame and the wheelset. Rw is the wheel diameter. and They are the heights from the vehicle body end of the coupler and the drawbar to the vehicle body center; It is the longitudinal distance from the vehicle body end of the drawbar to the vehicle body center; It is the longitudinal distance from the end of the drawbar frame to the center of the frame.

[0047] The vertical force balance model can accurately analyze the vertical loads on the car body, front bogie and rear bogie, and clearly express the vertical force conditions of the car body, front bogie and rear bogie. The balance equation takes into account the different secondary suspension and motor layout conditions, supporting the subsequent optimization calculation analysis.

[0048] The moment balance model can accurately calculate the moments borne by the car body, front bogie and rear bogie, clearly expressing the moments borne and the interactions between them. The balance equation also supports the subsequent optimization calculation analysis.

[0049] In some embodiments, see Figure 1 and Figure 4 ,The steps to establish the physical model of primary and secondary suspension include: Obtain the vertical displacement corresponding to the primary suspension and the secondary suspension; Obtain the primary and secondary stiffness corresponding to the car body and bogie; According to Hooke's law, the physical models of primary and secondary suspension are established.

[0050] The formula is as follows:

[0051]

[0052] in, is the vertical displacement of the i-th secondary spring of the vehicle body, is the vertical displacement of the i-th secondary spring of the front bogie. is the vertical displacement of the i-th primary spring of the front bogie. k s is the vertical stiffness of the secondary spring, k p is the vertical stiffness of the primary spring.

[0053] The primary and secondary suspension physical models can accurately reflect the dynamic response of the vehicle under different working conditions, iterate and optimize various parameters of the suspension system to find the best design solution, thereby improving the performance and reliability of the suspension system.

[0054] In some embodiments, see Figure 1 and Figure 4 , the steps of establishing the load increase and decrease model of each axis include: Calculate the vertical load of each axis under static conditions according to the motor layout; According to the physical models of the primary and secondary suspensions and the vertical loads, a model for increasing and decreasing the load on each axle is established.

[0055] The formula for establishing the load increase and decrease equation for each axis based on the motor layout is as follows:

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062] Among them, F mi is the motor boom force, is the axle load transfer caused by the motor boom force.

[0063] By accurately calculating the increase or decrease in load on each axle, the vehicle's traction and braking systems can be optimized to ensure that the forces on each axle are balanced during starting, acceleration, climbing, and braking, thereby improving the vehicle's traction efficiency. The model for increasing or decreasing load on each axle can reflect the dynamic response of the vehicle under different working conditions. By adjusting components such as the suspension system and bogies, the traction of the locomotive can be optimized and the occurrence of problems such as idling can be reduced.

[0064] In some embodiments, see Figure 1 and Figure 4 , the steps of selecting the optimized locomotive adhesion utilization as the objective function include: Select the axle with the lowest adhesion utilization rate from the wheel axles as the minimum axle; Maximizing the adhesion utilization of the smallest axis is taken as the optimization goal; Construct an objective function based on the optimization goal.

[0065] The formula for selecting the objective function is as follows:

[0066]

[0067] Among them U iis the adhesion utilization rate of each axle, and P0 is the static axle weight. Optimizing the adhesion utilization rate of the locomotive means that the friction between the wheel and the rail can be used more effectively, thereby improving the traction performance of the locomotive, helping the locomotive to show stronger power performance under conditions such as starting, acceleration, and climbing, shortening the operating time and improving transportation efficiency. Optimizing the adhesion utilization rate of the locomotive helps to reduce the energy consumption of the locomotive during operation, thereby achieving the purpose of energy saving. In addition, due to the improvement of the locomotive traction performance, the additional energy consumption and operating costs caused by insufficient traction can be reduced.

[0068] According to the optimized adhesion utilization, the stiffness and damping parameters of the suspension system are adjusted to balance the vertical loads of each axle, reduce axle weight transfer, and thus improve adhesion utilization.

[0069] The adhesion control problem during the dynamic operation of the locomotive can be solved from many aspects. Microcomputer control technology can be introduced to accurately control the amount of sand spread and the running speed of the locomotive to improve the sand spreading efficiency and sand utilization rate. Choose better quality sand materials to replace the original materials to increase the friction coefficient between the wheelset and the rail. This patent adopts multi-wheel pair adhesion collaborative control, combined with the adhesion controller to obtain the traction of the idling axle and the non-idling axle, and uses the optimization algorithm to reduce the traction of the idling axle to suppress idling while improving the traction of other non-idling axles, thereby ensuring the stable output of the traction of the locomotive.

[0070] In some embodiments, see Figure 1 and Figure 4 The constraints also include the load increase and decrease range of traction force of each axle, the adhesion coefficient range, and the design variable range.

[0071] Constraints include equality constraints to select the locomotive axle load transfer mechanical model, and inequality constraints to add the load increase and decrease range of each axle traction force. Adhesion coefficient range, select the design variable range.

[0072] By introducing the locomotive axle load transfer mechanical model as an equation constraint, we can ensure that the optimization process strictly follows the physical laws and avoid generating solutions that do not conform to the actual situation. The mechanical model can reflect the force conditions of the locomotive during operation and ensure that the axle load transfer is within a reasonable range, thereby ensuring the comfort and stability of the locomotive.

[0073] Inequality constraints can limit the range of load increase and decrease of the traction force of each axle, ensuring that the locomotive does not exceed its design limit during operation and avoid damage to the locomotive. By setting the inequality constraint of the adhesion coefficient range, it can ensure that the locomotive fully utilizes the adhesion between the wheel and rail during operation and improve the traction efficiency performance.

[0074] By reasonably selecting the range of design variables, the search space of the optimization process can be limited and the optimization efficiency can be improved. The actual operation conditions and needs of the locomotive should be comprehensively considered to ensure that the optimization results are practical and feasible.

[0075] The present invention proposes a six-axle locomotive axle load transfer optimization system, please refer to Figure 2 ,include: An acquisition unit 100 is configured to acquire design parameters of the locomotive, and select design variables and corresponding initial values ​​from the design parameters; A modeling unit 200 is configured to establish a mechanical model of a vehicle body, front and rear bogies for locomotive axle load transfer, and use it as a balance condition; The optimization unit 300 is configured to select the optimized locomotive adhesion utilization rate as the objective function, select the constraint conditions including the balance condition, and solve to obtain the optimized value of the design variable corresponding to the optimized locomotive adhesion utilization rate; The implementation unit 400 is configured to substitute the optimized value of the design variable into the locomotive axle load transfer mechanical model to obtain the optimized axle load distribution, and calculate the optimized adhesion utilization and traction force, design the six-axle locomotive according to the optimized adhesion utilization, and apply traction force to each axle of the six-axle locomotive during movement.

[0076] In some embodiments, see Figure 3 and Figure 5 , The prior art is Figure 3 By using the optimization algorithm and the stress state of the vehicle, the optimal traction force of each axle under the influence of axle load transfer can be obtained, and the axle load transfer can be improved by changing the traction force.

[0077] Different from this, the present invention is as follows Figure 5 The stress state shown in Figure 5 In the six-axle locomotive shown, more locomotive parameters can be incorporated into the design variables for the locomotive axle weight adjustment optimization, which can provide more optional schemes for the locomotive axle weight adjustment. It is suitable for various forms of six-axle locomotives and can calculate the axle weight transfer optimization schemes for locomotives with different numbers of secondary supports and different motor arrangements.

[0078] In some embodiments, see Figure 6 The present invention has made improvements in two directions for the six-axle locomotive. One is to optimize the axle load transfer in the design stage: Obtaining design parameters of the locomotive, and selecting design variables and corresponding initial values ​​from the design parameters; Establish the mechanical model of locomotive axle load transfer for the car body, front and rear bogies, and use it as the balance condition; Selecting the optimized locomotive adhesion utilization rate as the magic table function, selecting the constraint conditions including the balance condition, and solving to obtain the optimized value of the design variable corresponding to the optimized locomotive adhesion utilization rate; The optimized values ​​of the design variables are substituted into the axle load transfer mechanical model to obtain an optimized axle load distribution, and an optimized adhesion utilization rate is calculated based on the optimized axle load distribution.

[0079] The second is the operation phase, which is based on the first phase to carry out multi-wheel adhesion coordinated control, mainly used to adjust the traction during the movement of the locomotive; The idle shaft adhesion controller takes the rate gravity as input and selects the rate gravity as the design variable. Establish the mechanical model of locomotive axle load transfer for the car body, front and rear bogies, and use it as the balance condition Select the optimized locomotive adhesion utilization rate as the magic table surplus, select the constraint conditions including the balance condition, and solve to obtain the optimized value of the design variable corresponding to the optimized locomotive adhesion utilization rate The traction optimization scheme is substituted into the axle load transfer mechanical model, and the rate gravity scheme is applied.

[0080] By designing the axle weight distribution between the axles, it is possible to ensure that each wheel is under appropriate pressure to prevent some wheels from spinning due to excessive pressure. Increasing the contact area and friction between the wheel and the track improves the adhesion between the wheel and the track and reduces the risk of spinning. Reducing wheel slip and spinning enables the traction motor to transmit power more effectively, thereby improving the efficiency of the traction motor.

[0081] By precisely adjusting the locomotive's traction, it ensures that the locomotive can move forward faster when starting, accelerating and climbing, and will not lose power due to wheel slippage. It can prevent wheel slippage, thereby improving the locomotive's stability and controllability, and ensuring that the locomotive can run safely and smoothly.

[0082] Based on the same inventive concept, according to another aspect of the present invention, Figure 7 As shown, an embodiment of the present invention further provides a computer device 30, which includes a processor 310 and a memory 320. The memory 320 stores a computer program 321 that can be run on the processor. When the processor 310 executes the program, the steps of the above method are performed.

[0083] Based on the same inventive concept, according to another aspect of the present invention, Figure 8 As shown, an embodiment of the present invention further provides a computer-readable storage medium 40, which stores a computer program 410 for executing the above method when executed by a processor.

[0084] The embodiment of the present invention may also include a corresponding computer device. The computer device includes a memory, at least one processor, and a computer program stored in the memory and executable on the processor, and the processor executes any one of the above methods when executing the program.

[0085] The memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules in the embodiments of the present application. The processor executes various functional applications and data processing of the device by running the non-volatile software programs, instructions and modules stored in the memory, that is, implementing the above method.

[0086] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the device, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In an embodiment, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the local module via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0087] Finally, it should be noted that a person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium of the program can be a disk, an optical disk, a read-only storage memory (ROM) or a random access memory (RAM), etc. The above-mentioned computer program embodiments can achieve the same or similar effects as the corresponding above-mentioned arbitrary method embodiments.

[0088] It will also be appreciated by those skilled in the art that various exemplary logic blocks, modules, circuits and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software or a combination of the two. In order to clearly illustrate this interchangeability of hardware and software, a general description has been given to the functions of various schematic components, blocks, modules, circuits and steps. Whether this function is implemented as software or hardware depends on specific applications and the design constraints imposed on the entire system. Those skilled in the art can implement the function in various ways for each specific application, but this implementation decision should not be interpreted as causing a departure from the disclosed scope of the embodiments of the present invention.

[0089] The above are exemplary embodiments disclosed in the present invention, but it should be noted that various changes and modifications may be made without departing from the scope of the embodiments disclosed in the present invention as defined in the claims. The functions, steps and / or actions of the method claims according to the disclosed embodiments described herein do not need to be performed in any particular order. The serial numbers of the embodiments disclosed in the above embodiments of the present invention are for description only and do not represent the advantages and disadvantages of the embodiments. In addition, although the elements disclosed in the embodiments of the present invention may be described or required in individual form, they may also be understood as multiple unless explicitly limited to the singular.

[0090] It should be understood that, as used herein, the singular forms "a", "an" are intended to include the plural forms as well, unless the context clearly supports an exception. It should also be understood that, as used herein, "and / or" refers to any and all possible combinations including one or more of the associated listed items.

[0091] A person skilled in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the disclosure of the embodiments of the present invention (including the claims) is limited to these examples; under the concept of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other changes in different aspects of the above embodiments of the present invention, which are not provided in detail for the sake of simplicity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.

Claims

1. A six-axle locomotive axle load transfer optimization method, characterized in that: include: Obtaining design parameters of the locomotive, and selecting design variables and corresponding initial values ​​from the design parameters; Establish the mechanical model of locomotive axle load transfer for the car body, front and rear bogies, and use it as the balance condition; Selecting the optimized locomotive adhesion utilization rate as the objective function, selecting the constraint conditions including the balance condition, and solving to obtain the optimized value of the design variable corresponding to the optimized locomotive adhesion utilization rate; The optimized values ​​of the design variables are substituted into the locomotive axle load transfer mechanical model to obtain the optimized axle load distribution and calculate the optimized adhesion utilization and traction force. The six-axle locomotive is designed according to the optimized adhesion utilization rate, and the traction force is applied to each axle of the six-axle locomotive during movement.

2. The method for optimizing axle load transfer of a six-axle locomotive according to claim 1, characterized in that: Design parameters include axle weight, wheelbase, gauge, drawbar angle, coupler height, towing point height and traction; Design variables are design parameters that can be changed.

3. The method for optimizing axle load transfer of a six-axle locomotive according to claim 1, characterized in that: The steps of establishing the mechanical model of the car body, front and rear bogies for locomotive axle load transfer include: Establish corresponding vertical force balance models and moment balance models for the car body, front bogie and rear bogie respectively; Establish the physical model of primary and secondary suspension; Establish a model for increasing and decreasing load on each axis.

4. The method for optimizing axle load transfer of a six-axle locomotive according to claim 3, characterized in that: The steps to establish the primary and secondary suspension physical models include: Obtain the vertical displacement corresponding to the primary suspension and the secondary suspension; Obtain the primary and secondary stiffness corresponding to the car body and bogie; The physical models of primary and secondary suspension are established according to Hooke's law.

5. The method for optimizing axle load transfer of a six-axle locomotive according to claim 3, characterized in that: The steps to establish the load increase and decrease model for each axis include: Calculate the vertical load of each axis under static conditions according to the motor layout; According to the physical models of the primary and secondary suspensions and the vertical loads, a model for increasing and decreasing the load on each axle is established.

6. The method for optimizing axle load transfer of a six-axle locomotive according to claim 1, characterized in that: The steps of selecting the optimal locomotive adhesion utilization as the objective function include: Select the axle with the lowest adhesion utilization rate from the wheel axles as the minimum axle; Maximizing the adhesion utilization of the smallest axis is taken as the optimization goal; Construct an objective function based on the optimization goal.

7. The method for optimizing axle load transfer of a six-axle locomotive according to claim 1, characterized in that: The constraints also include the load increase and decrease range of the traction force of each axle, the adhesion coefficient range, and the design variable range.

8. A six-axle locomotive axle load transfer optimization system, characterized in that: include: an acquisition unit configured to acquire design parameters of the locomotive, and select design variables and corresponding initial values ​​from the design parameters; A modeling unit configured to establish a mechanical model of a vehicle body, front and rear bogies for locomotive axle load transfer and as a balance condition; An optimization unit is configured to select an optimized locomotive adhesion utilization rate as an objective function, select a constraint condition including the balance condition, and solve to obtain an optimized value of a design variable corresponding to the optimized locomotive adhesion utilization rate; The implementation unit is configured to substitute the optimized values ​​of the design variables into the locomotive axle load transfer mechanical model to obtain the optimized axle load distribution and calculate the optimized adhesion utilization and traction force, design the six-axle locomotive according to the optimized adhesion utilization, and apply traction force to each axle of the six-axle locomotive during movement.

9. A computer device comprising: at least one processor; and a memory storing a computer program executable on the processor, wherein the processor executes the steps of a six-axle locomotive axle weight transfer optimization method as described in any one of claims 1 to 7 when executing the program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the axle load transfer optimization method for a six-axle locomotive are performed as described in any one of claims 1 to 7.

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