CN116279601A - Prediction method, device and product for endurance mileage of railway vehicle - Google Patents

Abstract

The embodiment of the application provides a method, a device and a product for predicting the endurance mileage of a railway vehicle, wherein the railway vehicle comprises: traction engine and traction battery; the traction storage battery is used for supplying power to the traction engine so that the traction engine drives the railway vehicle to run; the method comprises the following steps: under the condition that the rail vehicle is detected to be in a starting state, obtaining the information of the residual electric quantity of the traction storage battery in real time; acquiring traction parameters of the traction engine in real time; acquiring operation interval parameters corresponding to the operation interval of the railway vehicle in real time; and obtaining the endurance mileage predicted value of the railway vehicle in real time according to the residual electric quantity information, the traction force parameter and the running interval parameter. According to the embodiment of the application, the characteristic that the railway vehicle runs on a fixed line is fully utilized, and the endurance mileage is accurately and in real time predicted based on the traction parameters and the running interval parameters of the electric railway vehicle obtained in real time.

Description

Method, device and product for predicting cruising range of rail vehicles

technical field

The embodiments of the present application relate to the technical field of rail transit, and in particular to a method for predicting the cruising range of a rail vehicle, a device for predicting the cruising range of a rail vehicle, a rail vehicle, a computer-readable storage medium, and an electronic device.

Background technique

The locomotive using battery as the power source has the characteristics of environmental protection and low noise. Compared with the internal combustion locomotive using traditional energy, it has a more positive effect on environmental protection. The current rail vehicles have introduced traction batteries to provide energy for the traction engines, so that rail vehicles can run on the track relying on battery power. However, limited by the power density and volume of the battery, the battery life of electric rail vehicles at this stage is still insufficient. Accurately estimating whether the power is sufficient to reach the destination smoothly or return to the base safely will not only cause anxiety for the staff, but also cause serious safety hazards in the online operations of the staff.

Contents of the invention

The embodiment of the present application provides a method for predicting the mileage of a rail vehicle, a device for predicting the mileage of a rail vehicle, a rail vehicle, a computer-readable storage medium, and an electronic device, aiming to Traction parameters and operating interval parameters of electric rail vehicles, accurate and real-time prediction of cruising range.

In one aspect, an embodiment of the present application provides a method for predicting the cruising range of a rail vehicle, the rail vehicle comprising: a traction engine and a traction battery; the traction battery is used to supply power to the traction engine so that the A traction engine drives the rail vehicle; the method includes:

When it is detected that the rail vehicle is in the starting state, obtain the remaining power information of the traction storage battery in real time;

Obtaining the traction parameters of the traction engine in real time;

Obtaining in real time the operating interval parameters corresponding to the operating interval of the rail vehicle;

According to the remaining power information, the traction force parameter and the operating interval parameter, the predicted value of the cruising range of the rail vehicle is obtained in real time.

Optionally, the step of obtaining the operating interval parameters corresponding to the operating intervals of the rail vehicle in real time includes:

In the case of detecting that the rail vehicle is in a starting state, acquiring the current position information of the rail vehicle in real time;

Obtaining the destination location information of the rail vehicle in real time;

generating the operating interval of the rail vehicle according to the current location information and the destination location information of the rail vehicle;

The operating interval parameters corresponding to the operating intervals of the rail vehicle are acquired in real time.

Optionally, the operating interval parameters include at least one of the following: slope information of the operating interval, and speed limit information of the operating interval.

Optionally, according to the remaining power information, the traction force parameter and the operating interval parameter, the predicted value of the cruising range of the rail vehicle is obtained in real time, including:

Inputting the remaining power information, the traction force parameter and the operating interval parameter obtained in real time into a prediction model, and obtaining a predicted mileage value of the rail vehicle in real time;

Wherein, the prediction model is obtained by inputting a preset number of samples of remaining power information, sample traction force parameters and sample operating interval parameters into the initial neural network model for training.

Optionally, the method also includes:

After the rail vehicle travels the first preset mileage in the operating interval, the actual power consumption of the rail vehicle traveling in the first preset mileage is obtained;

Obtaining the predicted power consumption of the rail vehicle within the first preset mileage according to the traction force parameters of the traction engine and the operating interval parameters of the rail vehicle within the first preset mileage;

Comparing the actual power consumption and the predicted power consumption of the rail vehicle traveling within the first preset mileage, correcting the predicted mileage value of the rail vehicle in the remaining operating interval.

Optionally, the method also includes:

Obtaining the total weight of the rail vehicle when it is detected that the rail vehicle is in a starting state;

According to the total weight of the rail vehicle, the traction parameters and the parameters of the operation interval, the predicted speed curve of the rail vehicle traveling in the operation interval is obtained;

According to the remaining power information, the traction force parameter, the operating interval parameter and the predicted speed curve, the predicted value of the cruising range of the rail vehicle is obtained in real time.

In yet another aspect, an embodiment of the present application provides a device for predicting the cruising range of a rail vehicle. The rail vehicle includes: a traction engine and a traction battery; the traction battery can supply power to the traction engine, so that the traction engine Drive the rail vehicle to travel; the device includes:

a power meter unit, configured to obtain information about the remaining power of the traction battery;

a traction force parameter acquisition unit, configured to acquire the traction force parameter of the traction engine in real time when the rail vehicle is detected to be in a starting state;

An operating interval parameter acquisition unit is used to obtain operating interval parameters corresponding to the operating interval of the rail vehicle in real time;

A prediction unit, configured to obtain a predicted value of the cruising range of the rail vehicle in real time according to the remaining power information, the traction force parameter and the operating interval parameter.

In yet another aspect, another embodiment of the present application provides a rail vehicle, comprising:

traction engine;

a traction battery for powering the traction engine so that the traction engine drives the rail vehicle;

A prediction device, configured to implement the steps in the method of any one of the above-mentioned embodiments of the present application.

In yet another aspect, another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps in the method of any one of the above-mentioned embodiments of the present application are implemented.

In yet another aspect, another embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor is executed, any of the above-mentioned embodiments of the present application are implemented. steps in the method.

Compared with the prior art, the advantages of the present application are:

Utilizing the characteristics of rail vehicles running on fixed lines, the remaining power information, traction parameters and operating interval parameters of electric rail vehicles can be obtained in real time, and the cruising range of electric rail vehicles can be accurately and real-time predicted based on the line that the locomotive will run subsequently. It is beneficial to avoid the situation that the rail vehicle breaks down on the running line due to insufficient power of the rail vehicle, reduces the anxiety of the staff, and reduces the safety hazards of the staff who ride the electric rail vehicle for online operations.

Description of drawings

The accompanying drawings are for reference and description only, and are not intended to limit the protection scope of the present application. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Apparently, the described embodiments are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

Fig. 1 shows the flow chart of the steps of a method for predicting the cruising range of a rail vehicle in an embodiment provided by the application;

Fig. 2 shows a schematic flow chart of another method for predicting the cruising range of a rail vehicle in an embodiment provided by the present application;

Fig. 3 shows a structural block diagram of an apparatus for predicting the mileage of a rail vehicle in an embodiment provided by the present application.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

In the field of rail transit technology, the introduction of battery traction power supply has brought about cost reduction and is also conducive to environmental protection. However, the disadvantages of batteries as a power source are also obvious. The battery life is limited. Once a rail vehicle (also known as a locomotive) running on the track loses power, it will not only be difficult to reach the destination or return to the base safely, but will also affect the entire track system. scheduling and security. However, in the prior art, the mileage estimation of electric rail vehicles is only the power consumption speed, and the accuracy is very low, and the estimated mileage is far from the actual one. The inventor considers that the running interval of rail vehicles is usually in a fixed environment, and the efficiency of battery power conversion is also relatively stable, and proposes to make full use of the characteristics of rail vehicles running on fixed lines, by collecting data on locomotive running lines, and predicting the locomotives that will be running in the future. The line is used as the benchmark, combined with a variety of parameters to accurately predict the cruising range of electric rail vehicles, with good real-time performance and high accuracy.

In view of this, the embodiment of the present application provides a method for predicting the cruising range of a rail vehicle, a device for predicting the cruising range of a rail vehicle, a rail vehicle, a computer-readable storage medium, and an electronic device, which acquire real-time The remaining power information, traction parameters and operating interval parameters of rail vehicles can accurately and real-time predict the cruising range of rail vehicles.

Embodiments of the present application will be described below in conjunction with the accompanying drawings.

Referring to FIG. 1 , FIG. 1 shows a flow chart of the steps of a method for predicting the mileage of a rail vehicle in an embodiment provided by the present application. As shown in Figure 1, the embodiment of the present application provides a method for predicting the mileage of a rail vehicle, which can be applied to a rail vehicle powered by battery traction and running on a laid track, and the rail vehicle includes: a traction engine and traction batteries. The traction battery is used to supply power to the traction engine, so that the traction engine drives the rail vehicle to travel.

Specifically, the traction battery may include any of the following: lead-acid battery, nickel-metal hydride battery, sodium-sulfur battery, secondary lithium battery, air battery, and ternary lithium battery.

The methods include:

Step S301, when it is detected that the rail vehicle is in the starting state, obtain the remaining power information (State Of Charge, SOC state information) of the traction battery in real time.

Wherein, the remaining power information of the traction battery may be expressed as a percentage of the total power or as a remaining charge.

Among them, the remaining power information of the traction battery can be obtained by the battery management system in the rail vehicle starting self-check after the rail vehicle is started, and then can be obtained by the locomotive control system from the battery management system.

Step S302, acquiring tractive force parameters of the traction engine in real time.

Wherein, the traction force parameter may at least include a traction direction and a traction force magnitude. Wherein, the traction force may be in any one of ton (t), cattle (N) or kilogram (Kg) as a unit. Exemplarily, the pulling effort parameter may include pulling tons.

Wherein, the traction parameter can be provided by a monitoring system on the rail vehicle. The monitoring system can establish a communication connection with the engine control unit, and obtain the traction parameters of the rail vehicle from the engine control unit.

Step S303, obtaining in real time operating interval parameters corresponding to the operating intervals of the rail vehicle.

Wherein, the operating interval parameters can be collected according to the geographical information and related regulatory information of the operating intervals in the rail system, and can be pre-stored in the locomotive control system of the rail vehicle or in a server that establishes remote communication with the rail vehicle.

Considering that the power of the traction engine mainly affects the power consumption speed of the battery, and both the ramp and the vehicle speed affect the engine power, the ramp and speed limit in the operating range will affect the battery life. For this reason, in an optional implementation manner, the operating interval parameters include at least one of the following: slope information of the operating interval, and speed limit information of the operating interval.

For example, assuming that a certain section of the mileage in the operating interval is an uphill section, and the speed is kept constant, the power consumed by the traction engine in this section increases, the traction force increases, and the battery consumption speed increases, so the cruising range is reduced; In the case that the power consumed by the engine remains unchanged, the speed of the rail vehicle in this section will decrease, the battery power consumption time will increase, and the cruising range will also be reduced.

Taking a lead-acid battery as an example, the activity of the battery is easily affected by the ambient temperature. Therefore, the temperature in the area where the operating range is located may also affect the cruising range. For this reason, in an optional implementation manner, the operating interval parameters may further include: ambient temperature information of the operating interval.

Step S304, according to the remaining power information, the traction force parameter and the operating interval parameter, obtain the predicted cruising range of the rail vehicle in real time.

Specifically, the neural network model can be used to train the prediction model to obtain the prediction model, and the remaining power information, the traction force parameter and the operating interval parameter can be input to obtain the cruising range prediction value of the rail vehicle.

In some optional embodiments, the locomotive control system may perform prediction calculation to obtain the predicted value of the cruising range of the rail vehicle.

In some other optional embodiments, in order to reduce the cost and increase the sample size of the model so that the model can be fully trained during use, the locomotive control system can send the remaining power information, the traction parameters and the operating interval parameters to To the computing server that establishes a remote communication connection with it, the computing server can be provided with a well-trained prediction model, and the computing server can predict the cruising range of multiple rail vehicles in the entire rail system.

Wherein, the higher the remaining power is, the larger the predicted value of the cruising range may be. The greater the tractive effort, the lower the range prediction value of the rail vehicle can be. The steeper the slope or the lower the ambient temperature or the lower the speed limit in the operating interval parameters, the smaller the predicted value of the cruising range can be.

Through the above-mentioned embodiments, making full use of the characteristics of rail vehicles running on fixed lines, real-time acquisition of remaining power information, traction parameters and operating interval parameters of electric rail vehicles, based on the line that the locomotive will run subsequently, accurately and real-time prediction of electric track The cruising range of the vehicle is conducive to avoiding the breakdown of the rail vehicle on the running line due to insufficient power of the rail vehicle, reducing the anxiety of the staff, and reducing the safety hazards of the staff driving the electric rail vehicle for online operations.

The running interval can be updated in real time according to the current position of the rail vehicle. For this reason, in an optional implementation manner, the present application also provides a method for obtaining operating interval parameters, including:

Step S401 , acquiring the current location information of the rail vehicle in real time when it is detected that the rail vehicle is in a starting state.

Wherein, the current position information can be provided by the monitoring system on the rail vehicle. The monitoring system can establish a communication connection with the preset positioning system, and obtain the current position information of the rail vehicle from the preset positioning system. The preset positioning system may be Beidou satellite positioning system or GPS positioning system.

Step S402, acquiring destination location information of the rail vehicle in real time.

Step S403, generating the running section of the rail vehicle according to the current location information of the rail vehicle and the destination location information.

Step S404, acquiring in real time operating interval parameters corresponding to the operating intervals of the rail vehicle.

In some optional embodiments, the present application considers using a neural network model to make predictions, so as to improve prediction accuracy. For this reason, in an optional embodiment, the application also provides a method for obtaining the predicted value of the cruising range of the rail vehicle, including:

The remaining power information, the traction parameters and the operating interval parameters obtained in real time are input into a prediction model to obtain a predicted value of the cruising range of the rail vehicle in real time.

Wherein, the prediction model is obtained by inputting a preset number of samples of remaining power information, sample traction force parameters and sample operating interval parameters into the initial neural network model for training.

Since the predicted value can only be infinitely close to the actual situation, in order to improve the accuracy of the prediction, the embodiment of the present application also considers using the actual power consumption to correct the predicted value of the cruising range of the rail vehicle. For this reason, in an optional embodiment, the present application also provides a method for correcting the predicted value of the cruising range of the rail vehicle, including:

Step S501, after the rail vehicle travels a first preset mileage in an operating section, obtain the actual power consumption of the rail vehicle traveling within the first preset mileage.

Step S502, according to the traction force parameters of the traction engine and the operating range parameters of the rail vehicle within the first preset mileage, the predicted power consumption of the rail vehicle within the first preset mileage is obtained.

Step S503, comparing the actual power consumption and the predicted power consumption of the rail vehicle traveling within the first preset mileage, and correcting the predicted value of the cruising range of the rail vehicle in the remaining operating interval .

Although the traction parameter can already reflect the power consumption of the battery to a certain extent, the weight of the rail vehicle also affects the running speed of the rail vehicle in the set operating interval. Although there may be a speed limit in the operating interval, the weight of the rail vehicle Obviously, it is still possible to affect the length of time that the rail vehicle travels in the set operating interval, so the weight of the rail vehicle may also affect the cruising range prediction value of the rail vehicle. For this reason, in an optional embodiment, the present application also provides another method for obtaining the predicted cruising range of a rail vehicle, including:

Step S601, if it is detected that the rail vehicle is in the starting state, obtain the total weight of the rail vehicle.

Step S602, according to the total weight of the rail vehicle, the traction force parameter and the operation interval parameter, obtain the predicted speed curve of the rail vehicle traveling in the operation interval.

Step S603, according to the remaining power information, the traction force parameter, the operating interval parameter and the predicted speed curve, obtain the predicted cruising range of the rail vehicle in real time.

Referring to FIG. 2 , FIG. 2 shows a schematic flowchart of another method for predicting the cruising range of a rail vehicle in an embodiment provided by the present application. As shown in Figure 2, in some optional embodiments, the embodiment of the present application also provides another method for predicting the mileage of a rail vehicle, wherein the rail vehicle also includes: a traction battery management system, a locomotive monitoring system, and locomotive control system. Methods include:

Step S701, after the rail vehicle is started, the traction battery management system self-checks the traction battery SOC status information and sends it to the locomotive control system.

Step S702, obtaining the weight, traction force parameters and running interval of the rail vehicle from the locomotive monitoring system.

Wherein, the traction parameter and the running interval may also be obtained by the driver through the locomotive monitoring system input.

Step S703, the locomotive control system estimates the cruising range of the locomotive in the current state according to the weight of the rail vehicle, traction force parameters, operating range and SOC state information of the traction battery.

Step S704, after the rail vehicle has been running for a period of time, the monitoring system and the battery management system can also collect real-time location information, speed, traction battery discharge current and SOC status information of the locomotive to correct the cruising range of the rail vehicle.

Referring to FIG. 3 , FIG. 3 shows a structural block diagram of an apparatus for predicting the mileage of a rail vehicle in an embodiment provided by the present application. As shown in Figure 3, based on the same inventive concept, the embodiment of the present application also provides a prediction system for the mileage of a rail vehicle, and the device includes:

The power metering unit 801 is configured to obtain information about the remaining power of the traction battery.

The traction force parameter acquisition unit 802 is configured to acquire the traction force parameter of the traction engine in real time when it is detected that the rail vehicle is in a starting state.

The operating interval parameter acquisition unit 803 is configured to acquire operating interval parameters corresponding to the operating interval of the rail vehicle in real time.

The predicting unit 804 is configured to obtain the predicted value of the cruising range of the rail vehicle in real time according to the remaining power information, the tractive force parameter and the operating interval parameter.

Based on the same inventive concept, another embodiment of the present application provides a rail vehicle, including:

Traction engine.

The traction battery is used to supply power to the traction engine, so that the traction engine drives the rail vehicle to travel.

A prediction device, configured to implement the steps in the method of any one of the above-mentioned embodiments of the present application.

Based on the same inventive concept, another embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps in the method of any of the above-mentioned embodiments of the present application are implemented.

Based on the same inventive concept, another embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes, any of the above-mentioned embodiments of the present application is realized steps in the method.

As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for related parts, please refer to the part of the description of the method embodiment.

Each embodiment in this specification is described in a progressive manner, each embodiment focuses on the difference from other embodiments, and the same and similar parts of each embodiment can be referred to each other.

Those skilled in the art should understand that the embodiments of the embodiments of the present application may be provided as methods, devices, or computer program products. Therefore, the embodiment of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

Embodiments of the present application are described with reference to flowcharts and/or block diagrams of methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor or processor of other programmable data processing terminal equipment to produce a machine such that instructions executed by the computer or processor of other programmable data processing terminal equipment Produce means for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the The instruction means implements the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded into a computer or other programmable data processing terminal equipment, so that a series of operational steps are performed on the computer or other programmable terminal equipment to produce computer-implemented processing, thereby The instructions executed above provide steps for implementing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

While the preferred embodiments of the embodiments of the present application have been described, additional changes and modifications can be made to these embodiments by those skilled in the art once the basic inventive concept is understood. Therefore, the appended claims are intended to be interpreted to cover the preferred embodiment and all changes and modifications that fall within the scope of the embodiments of the application.

Finally, it should also be noted that in this text, relational terms such as first and second etc. are only used to distinguish one entity or operation from another, and do not necessarily require or imply that these entities or operations, any such actual relationship or order exists. Furthermore, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or terminal equipment comprising a set of elements includes not only those elements, but also includes elements not expressly listed. other elements identified, or also include elements inherent in such a process, method, article, or terminal equipment. Without further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article or terminal device comprising the element.

Claims (10)

1. The method for predicting the endurance mileage of the railway vehicle is characterized in that the railway vehicle comprises the following steps: traction engine and traction battery; the traction storage battery is used for supplying power to the traction engine so that the traction engine drives the railway vehicle to run; the method comprises the following steps:

under the condition that the rail vehicle is detected to be in a starting state, obtaining the information of the residual electric quantity of the traction storage battery in real time;

acquiring traction parameters of the traction engine in real time;

acquiring operation interval parameters corresponding to the operation interval of the railway vehicle in real time;

and obtaining the endurance mileage predicted value of the railway vehicle in real time according to the residual electric quantity information, the traction force parameter and the running interval parameter.

2. The method for predicting the range of a railway vehicle according to claim 1, wherein the step of acquiring in real time an operation interval parameter corresponding to the operation interval of the railway vehicle comprises:

the method comprises the steps that under the condition that the fact that the railway vehicle is in a starting state is detected, current position information of the railway vehicle is obtained in real time;

acquiring destination position information of the railway vehicle in real time;

generating the running interval of the railway vehicle according to the current position information and the destination position information of the railway vehicle;

and acquiring an operation interval parameter corresponding to the operation interval of the railway vehicle in real time.

3. The method of claim 1, wherein the operating interval parameters include at least one of: slope information of the operation interval and speed limit information of the operation interval.

4. The method for predicting the range of the railway vehicle according to claim 1, wherein obtaining the range prediction value of the railway vehicle in real time according to the remaining power information, the traction parameter and the operation interval parameter comprises:

inputting the residual electric quantity information, the traction force parameter and the running interval parameter which are acquired in real time into a prediction model, and acquiring a range predicted value of the railway vehicle in real time;

the prediction model is obtained by inputting preset quantity of sample residual electric quantity information, sample traction force parameters and sample operation interval parameters into an initial neural network model for training.

5. The method for predicting range of a rail vehicle of claim 1, further comprising:

after the rail vehicle runs a first preset mileage in an operation interval, obtaining the actual power consumption of the rail vehicle running in the first preset mileage;

obtaining the predicted electricity consumption of the railway vehicle in the first preset mileage according to the traction parameters of the traction engine and the running interval parameters of the railway vehicle in the first preset mileage;

and comparing the actual power consumption of the railway vehicle running in the first preset mileage with the predicted power consumption, and correcting the predicted value of the endurance mileage of the railway vehicle in the residual running interval.

6. The method for predicting range of a rail vehicle of claim 1, further comprising:

under the condition that the rail vehicle is detected to be in a starting state, acquiring the total weight of the rail vehicle;

obtaining a predicted speed curve of the rail vehicle running in the running interval according to the total weight of the rail vehicle, the traction force parameter and the running interval parameter;

and obtaining the predicted value of the endurance mileage of the railway vehicle in real time according to the residual electric quantity information, the traction force parameter, the running interval parameter and the predicted speed curve.

7. A prediction apparatus for a range of a railway vehicle, wherein the railway vehicle comprises: traction engine and traction battery; the traction storage battery can supply power to the traction engine so that the traction engine drives the railway vehicle to run; the device comprises:

the electricity metering unit is used for obtaining the information of the residual electric quantity of the traction storage battery;

the traction parameter acquisition unit is used for acquiring traction parameters of the traction engine in real time under the condition that the railway vehicle is detected to be in a starting state;

an operation interval parameter obtaining unit, configured to obtain an operation interval parameter corresponding to an operation interval of the rail vehicle in real time;

and the prediction unit is used for obtaining the endurance mileage predicted value of the railway vehicle in real time according to the residual electric quantity information, the traction force parameter and the running interval parameter.

8. A rail vehicle, comprising:

a traction engine;

a traction battery for powering the traction engine so that the traction engine drives the rail vehicle to travel;

prediction means for implementing the steps in the method according to any one of claims 1 to 6.

9. A computer readable storage medium, characterized in that a computer program is stored thereon, which program, when being executed by a processor, realizes the steps in the method according to any of claims 1 to 6.

10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executed implementing the steps in the method of any one of claims 1 to 6.

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