CN112158237A - Deep fusion system integrating TCMS and ATO functions and train - Google Patents
Deep fusion system integrating TCMS and ATO functions and train Download PDFInfo
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- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
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Abstract
The embodiment of the invention provides a deep fusion system integrating TCMS and ATO functions and a train, wherein the TCMS and ATO functions are integrated in the same system, and compared with the situation that the TCMS and ATO transmit data through buses respectively, the integrated deep fusion system can reduce the occupancy rate of a bus MVB to a certain extent and improve the data transmission performance due to certain coincidence of the data transmitted by the TCMS and ATO. Meanwhile, a speed prediction module and a speed comparison module are provided in the depth fusion system, the real-time speed of the train is predicted, the predicted speed is compared with the real-time speed determined by the speed sensor, whether the real-time speed determined by the speed sensor is accurate or not is judged in time, corresponding measures are taken in time under the condition that the real-time speed determined by the speed sensor is inaccurate, and the train control precision is improved.
Description
Technical Field
The invention relates to the technical field of automatic train driving, in particular to a deep fusion system integrating TCMS and ATO functions and a train.
Background
An automatic train operation subsystem ATO in a communication-based train operation control system CBTC is key equipment for ensuring automatic train operation, and a train control and management system TCMS is key for controlling a train network to control and manage each subsystem of a train. In the prior art, distributed systems are used, which connect subsystems to TCMS systems by bus technology, such as ATP/ATO (automatic driving and protection on board), passenger information systems, broadcast systems, traction systems, brake systems, door systems, air conditioning systems, etc., which have a lot of data communication during the start-up and on-line of the train, which results in a high occupancy of the MVB bus of the vehicle. Meanwhile, a large number of physical interfaces and logical relations in software are loaded on the core host of each system. These device interfaces also mean that a large number of cabling is required, a large amount of installation space is occupied, and the large number of wiring connections results in increased vehicle weight and increased commissioning and maintenance efforts.
Therefore, in the existing train control system, the subsystems of the train are independent from each other, and the data of each subsystem are transmitted through the bus MVB, so that the occupancy rate of the MVB is high, the data transmission performance is affected, and whether the real-time speed determined according to the speed sensor on the wheel is accurate cannot be judged.
Disclosure of Invention
The embodiment of the invention provides a deep fusion system integrating TCMS and ATO functions and a train, which are used for solving the problems that in the existing train control system, all subsystems of the train are mutually independent, data of all subsystems are transmitted through a bus MVB, so that the occupancy rate of the MVB is very high, the data transmission performance is influenced, and whether the real-time speed determined according to a speed sensor on a wheel is accurate cannot be judged.
In view of the above technical problems, in a first aspect, an embodiment of the present invention provides a deep fusion system integrating TCMS and ATO functions, including an operation module in the TCMS for determining a train speed, a control module in the ATO for controlling a train speed, a speed prediction module and a speed comparison module;
the operation module is used for determining the real-time speed of the train at the moment according to the received wheel rotating speed; the wheel rotating speed is obtained by a speed sensor arranged on a train wheel; the current time is the time when the wheel rotating speed is received at this time;
the speed prediction module is used for predicting the speed of the train at the next moment according to the real-time speed of the train at the current moment to obtain a predicted speed; the next time is the time when the operation module receives the wheel rotating speed next time;
the speed comparison module is used for comparing the predicted speed with the real-time speed of the train at the next moment determined by the operation module to obtain a comparison result, and outputting a control instruction to the control module according to the comparison result;
and the control module is used for controlling the speed of the train according to the control instruction.
Optionally, the predicting the speed of the train at the next time according to the real-time speed of the train at the current time to obtain a predicted speed includes:
acquiring the acting force exerted on the train determined according to the target speed curve of the train at each moment from the current moment to the next moment; the acting force is traction force or braking force;
and calculating the speed of the train at the next moment according to the real-time speed of the train at the moment, the acting force, the first mass of the train when the train is unloaded and the second mass of the passengers when the train is fully loaded, and taking the speed of the train at the next moment as the predicted speed.
Optionally, the calculating a speed of the train at the next time as the predicted speed according to the real-time speed of the train at the current time, the acting force, the first mass of the train when the train is empty, and the second mass of the passengers when the train is full includes:
according to the formula
Calculating the predicted speed;
wherein, VpreRepresenting said predicted speed, t0Indicates the time t of this timeeIndicating the next time, F (t) between this time and the next timeAt time t, the force applied to the train, m, is determined from the target speed profile of the trainAWORepresenting the first mass of the train when it is empty, mfullRepresenting the second mass of passengers when the train is fully loaded.
Optionally, the outputting a control instruction to the control module according to the comparison result includes:
if the comparison result is that the absolute value of the difference between the predicted speed and the real-time speed at the next moment is smaller than or equal to a preset difference, the control instruction is to control the speed of the train according to the real-time speed at the next moment;
and if the comparison result is that the absolute value of the difference between the predicted speed and the real-time speed at the next moment is greater than the preset difference, the control instruction is to quit the ATO vehicle control and switch to manual vehicle control.
Optionally, the method further comprises:
if the control instruction is to control the speed of the train according to the real-time speed at the next moment, controlling the train to decelerate when the real-time speed at the next moment is greater than the speed corresponding to the next moment in the target speed curve of the train, and controlling the train to accelerate when the real-time speed at the next moment is less than the speed corresponding to the next moment in the target speed curve of the train.
Optionally, the determining the real-time speed of the train at the current time according to the wheel speed received this time includes:
and determining the real-time speed of the train at the moment according to the wheel radius of the train stored in advance and the wheel rotating speed received at the moment.
Optionally, the computing module receives the wheel speed via a bus MVB.
Optionally, the operation module, the control module, the speed prediction module and the speed comparison module are integrated in the same board card.
In a second aspect, an embodiment of the present invention provides a train, which includes any one of the above deep fusion systems integrating TCMS and ATO functions.
The embodiment of the invention provides a deep fusion system integrating TCMS and ATO functions and a train, wherein the TCMS and ATO functions are integrated in the same system, and compared with the situation that the TCMS and ATO transmit data through buses respectively, the integrated deep fusion system can reduce the occupancy rate of a bus MVB to a certain extent and improve the data transmission performance due to certain coincidence of the data transmitted by the TCMS and ATO. Meanwhile, a speed prediction module and a speed comparison module are provided in the depth fusion system, the real-time speed of the train is predicted, the predicted speed is compared with the real-time speed determined by the speed sensor, whether the real-time speed determined by the speed sensor is accurate or not is judged in time, corresponding measures are taken in time under the condition that the real-time speed determined by the speed sensor is inaccurate, and the train control precision is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a block diagram of a deep fusion system integrating TCMS and ATO functions according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a hardware module for fusing an ATO and a VCU in a TCMS according to another embodiment of the present invention;
fig. 3 is a schematic diagram of the structure of the software framework of the AIMP platform with the fusion of ATO and TCMS functions according to another embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Among the functions of the vehicle ATO, the automatic speed regulation is the most core and complex function. The acceleration of the train is adjusted in real time according to the working condition of the running speed of the train, so that the train can automatically and stably run under the permission of the safety protection of ATP. Automatic speed regulation requires some parameters of the train operating state: the actual running speed of the train, the running state of the train, the full load rate of the train and the like. Under the safety protection of the ATP, the ATO calculates the sensed real-time speed parameter of the train and then regulates and controls the parameter to be close to the recommended speed of the ATP, and can output a braking command when the speed of the train is too high and appropriately output a traction signal to improve the running speed of the train when the speed is too low, so that the line operation efficiency is improved. In a vehicle-mounted TCMS system, the main functions of the system control subsystems such as air conditioners, traction, brakes, car doors and the like on a train, most state signals of the train are collected in a bus/Ethernet mode and are delivered to core equipment VCU of the TCMS system for processing, and the signal parts are overlapped with ATO car control signals, so that the two signals can be integrated on a host machine, and the purposes of saving the installation space of train equipment, saving interfaces and the like are achieved.
Fig. 1 is a structural block diagram of a deep fusion system integrating TCMS and ATO functions provided in this embodiment, and referring to fig. 1, the deep fusion system integrating TCMS and ATO functions includes an operation module 101 for determining a train speed in a TCMS, a control module 102 for controlling a train speed in an ATO, a speed prediction module 103, and a speed comparison module 104;
the operation module 101 is configured to determine a real-time speed of the train at the current time according to the wheel rotation speed received this time; the wheel rotating speed is obtained by a speed sensor arranged on a train wheel; the current time is the time when the wheel rotating speed is received at this time;
the speed prediction module 103 is configured to predict the speed of the train at the next time according to the real-time speed of the train at the current time, so as to obtain a predicted speed; the next time is the time when the operation module receives the wheel rotating speed next time;
the speed comparison module 104 is configured to compare the predicted speed with a real-time speed of the train determined by the operation module at a next time to obtain a comparison result, and output a control instruction to the control module according to the comparison result;
the control module 102 is configured to control the speed of the train according to the control instruction.
The time interval between the present time and the next time is usually a set value, and is, for example, 2 s.
In the existing train control system, a TCMS and an ATO are two independent subsystems, the ATO generally acquires data such as train speed from the TCMS, the data is transmitted to the ATO from the TCMS through a bus MVB, and the ATO controls the operation of a train according to the data acquired from the TCMS. In this embodiment, the TCMS and ATO functions are integrated into the same system, that is, the deep fusion system, and the data transmitted by the deep fusion system can be used for the TCMS function and the ATO function integrated therein at the same time, so that the data transmission between the TCMS and the ATO is omitted, the data transmission load on the bus MVB is reduced, and the data transmission performance in each train control system is improved.
On the other hand, in this embodiment, still include speed prediction module and speed comparison module, speed prediction module can predict the speed of train at next moment based on another dimension, through carrying out the comparison with the real-time speed of predicting speed and next moment, can judge whether there is great error to the real-time speed of next moment, in time take corresponding treatment when there is great error in the real-time speed of next moment, avoid leading to controlling the car control process to appear the problem because of the error that the real-time speed of next moment exists.
The embodiment provides a deep fusion system integrating TCMS and ATO functions, wherein the TCMS and ATO functions are integrated in the same system, and compared with the case that the TCMS and ATO transmit data through buses respectively, the integrated deep fusion system can reduce the occupancy rate of the bus MVB to a certain extent and improve the performance of data transmission due to the fact that the data transmitted by the TCMS and ATO have certain coincidence. Meanwhile, a speed prediction module and a speed comparison module are provided in the depth fusion system, the real-time speed of the train is predicted, the predicted speed is compared with the real-time speed determined by the speed sensor, whether the real-time speed determined by the speed sensor is accurate or not is judged in time, corresponding measures are taken in time under the condition that the real-time speed determined by the speed sensor is inaccurate, and the train control precision is improved.
Further, on the basis of the above embodiment, the predicting the speed of the train at the next time according to the real-time speed of the train at the current time to obtain the predicted speed includes:
acquiring the acting force exerted on the train determined according to the target speed curve of the train at each moment from the current moment to the next moment; the acting force is traction force or braking force;
and calculating the speed of the train at the next moment according to the real-time speed of the train at the moment, the acting force, the first mass of the train when the train is unloaded and the second mass of the passengers when the train is fully loaded, and taking the speed of the train at the next moment as the predicted speed.
The target speed curve of the train is a train control curve of the train, and generally speaking, the train control process needs to make the speed of the train as close as possible to the speed in the target speed curve. The target speed profile is typically determined based on the destination to which the train is to arrive, the stopping location of the train, and the like. In the process of controlling the train according to the target speed curve, the magnitude of the traction force or the braking force applied to the train is actually determined according to the target speed curve, and both the process and the determination process of the target speed curve belong to the prior art, and are not described herein again.
Generally, if the current train is in a running phase, the force exerted on the train determined from the target speed profile of the train is the tractive effort. And if the current train is in a braking stage, determining the acting force exerted on the train according to the target speed curve of the train as a braking force. Therefore, the deep fusion system integrating the TCMS and the ATO functions, which is provided by the application, can be used for controlling the traction force output by the traction system and also can be used for controlling the braking force output by the braking system.
Further, in addition to the above embodiments, the calculating a speed of the train at the next time as the predicted speed according to the real-time speed of the train at the current time, the acting force, the first mass of the train when the train is empty, and the second mass of the passengers when the train is full includes:
according to the formula
Calculating the predicted speed;
wherein, VpreRepresenting said predicted speed, t0Indicates the time t of this timeeShowing the next time, F (t) showing the force exerted on the train determined from the target speed curve of the train at time t between the current time and the next time, mAWORepresenting the first mass of the train when it is empty, mfullRepresenting the second mass of passengers when the train is fully loaded.
It will be appreciated that,
the acceleration of the train is shown.
In the embodiment, a formula for calculating the predicted speed is provided, and the speed of the train at the next moment can be quickly calculated through the formula, so that the speed of the train at the next moment is predicted.
Further, on the basis of the foregoing embodiments, the outputting a control instruction to the control module according to the comparison result includes:
if the comparison result is that the absolute value of the difference between the predicted speed and the real-time speed at the next moment is smaller than or equal to a preset difference, the control instruction is to control the speed of the train according to the real-time speed at the next moment;
and if the comparison result is that the absolute value of the difference between the predicted speed and the real-time speed at the next moment is greater than the preset difference, the control instruction is to quit the ATO vehicle control and switch to manual vehicle control.
Further, on the basis of the above embodiments, the method further includes:
if the control instruction is to control the speed of the train according to the real-time speed at the next moment, controlling the train to decelerate when the real-time speed at the next moment is greater than the speed corresponding to the next moment in the target speed curve of the train, and controlling the train to accelerate when the real-time speed at the next moment is less than the speed corresponding to the next moment in the target speed curve of the train.
The predetermined difference may be set manually, typically to a small value.
When the predicted speed of the next moment is obtained through the comparison result and is closer to the real-time speed of the next moment, the vehicle can be controlled according to the real-time speed of the next moment. When the predicted speed at the next moment is far different from the real-time speed at the next moment, the speed sensor on the wheel may have a fault, the transmission process of the wheel rotating speed transmitted to the deep fusion system by the speed sensor may have a fault, and the ATO vehicle control is quitted at the moment, so that the vehicle control fault caused by inaccurate speed determination of the train can be avoided, and the safety of the vehicle control process is improved.
Further, in addition to the above embodiments, the determining the real-time speed of the train at the current time according to the wheel rotation speed received this time includes:
and determining the real-time speed of the train at the moment according to the wheel radius of the train stored in advance and the wheel rotating speed received at the moment.
For example, if the unit of the wheel rotation speed is rpm/sec, the real-time speed of the fixed train at the current time can be obtained by multiplying the wheel rotation speed by the product of pi and 2 r. Wherein r is the radius of the wheel.
It can be understood that the real-time speed of the train at the next time is calculated in the same manner as the real-time speed at the present time.
In this embodiment, the calculation of the real-time speed of the train at the present time is realized by the radius of the wheel and the wheel rotation speed measured by the speed sensor.
Specifically, regarding the control process of train speed, in the deep fusion of ATO and TCMS, the two are mainly reflected in the functional relationship: the train control function of the TCMS and the train control function of the ATO are partially crossed, for example, in the control of a train traction system, the ATO needs to regulate the speed of the train by controlling the traction system, the TCMS needs to receive relevant data (such as traction force, wheel diameter value and the like) of the train from the traction system so as to monitor parameters of the whole train, and in the function, the TCMS needs to communicate with and regulate a train subsystem, so that the train traction control function of the ATO can be controlled by the TCMS system.
When the conventional ATO judges the speed of a train, the information of the speed of the train needs to be acquired, the signal needs to be acquired from a wheel diameter speed sensor of the train, is converted into a train bus MVB signal and then is transmitted to a core operation unit VCU of a TCMS, the current speed of the train is calculated after the data processing of the VCU, and then the parameter is transmitted to an ATO system through a train bus. The bus data transmission needs to be performed for many times, and a large number of interfaces are needed for transmitting and processing the data between the devices, which is not beneficial to the development of the train control software and has low real-time performance.
In the ATO and TCMS integrated host, at this time, the ATO train traction control function is integrated into the TCMS, and the approach for the ATO system to acquire the train speed may be: the acceleration of the train can be calculated after calculation of parameters which can be obtained by a traction system (or a brake) before the train runs, such as a traction force value, the train initial weight AW0 of an auxiliary system, the full load ratio and the like. The calculation process may include:
and a is the acceleration of the train.
After the TCMS completes calculation, the speed of the train can be immediately estimated, and the speed of the train can be compared with the speed of the train transmitted by the wheel sensor at intervals, so that the reliability of the speed data of the train is improved. And parameters such as traction force, train full load rate, real-time weight and the like received by the TCMS can be reused in the TCMS, so that an ATO data interface is reduced, the train control time delay of the ATO system can be reduced, the stability of train control is improved, a certain predicting capability can be provided for the future train speed, and the ATO system can give an early warning and can be regulated and controlled in time.
Further, on the basis of the above embodiments, the computing module receives the wheel rotation speed through a bus MVB.
Fig. 2 is a schematic diagram of a hardware module based on fusion of ATO and VCU in TCMS provided in this embodiment, referring to fig. 2, after the ATO and the TCMS are fused, the ATO and the TCMS that are originally on two independent hosts are integrated in the same module, and the two hosts respectively transmit data from a bus, as shown in fig. 2, after the ATO and the TCMS are integrated in the same module, only the module transmits data through the bus (not shown in fig. 2), because some identical data of the ATO and the TCMS need to be transmitted through the bus, the duplicated data after being integrated in the same module need not be transmitted twice on the bus, and only need to be transmitted to the integrated module (i.e., the deep fusion system in this application) once, and occupation of duplicated data on the bus MVB can be reduced, thereby optimizing a data transmission process.
Further, on the basis of the above embodiments, the operation module, the control module, the speed prediction module, and the speed comparison module are integrated in the same board card.
In this embodiment, the operation module, the control module, the speed prediction module and the speed comparison module are integrated in the same board card, on one hand, the data transmission accuracy can be improved due to the fact that the data transmission delay inside the board card is small, and on the other hand, the integration of the same board card saves space and improves the integration level compared with the case that the ATO and the TCMS are respectively integrated in different board cards.
Fig. 3 is a schematic diagram of an AIMP platform software framework structure with integrated ATO and TCMS functions provided in this embodiment, where platform software application bears most functions of a TCMS and an ATO system, an integrated host interacts with external information such as a train bus through an interface layer, a platform service layer is a specific function list that can be implemented by the integrated host, and an operating system and hardware bear normal driving operation of functions of hardware devices of the integrated host. In the ATO and TCMS deep fusion host, the data interfaces of the ATO and the TCMS can be shared, the complex data transmission between the two systems is not needed to increase the data load of a train bus, the interface cable between the hosts is reduced, and the communication time delay of the vehicle control is reduced. For the software development of VCU and ATO systems of TCMS, due to the overlapping of interfaces, a lot of data can be directly called, the difficulty and time of software development are reduced, and the subsequent development of other functions is facilitated.
The embodiment provides a train, which comprises the deep fusion system integrating the TCMS and the ATO functions.
The embodiment provides a train, which includes the deep fusion system integrating the TCMS and ATO functions provided in the above embodiment, and the deep fusion system integrating the TCMS and the ATO functions integrates the TCMS and the ATO functions in the same system, and compared with the case that the TCMS and the ATO transmit data through buses respectively, because data transmitted by the TCMS and the ATO have a certain coincidence, the integrated deep fusion system can reduce the occupancy rate of a bus MVB to a certain extent, and improve the performance of data transmission. Meanwhile, a speed prediction module and a speed comparison module are provided in the depth fusion system, the real-time speed of the train is predicted, the predicted speed is compared with the real-time speed determined by the speed sensor, whether the real-time speed determined by the speed sensor is accurate or not is judged in time, corresponding measures are taken in time under the condition that the real-time speed determined by the speed sensor is inaccurate, and the train control precision is improved.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A deep fusion system integrating TCMS and ATO functions is characterized by comprising an operation module used for determining the speed of a train in the TCMS, a control module used for controlling the speed of the train in the ATO, a speed prediction module and a speed comparison module;
the operation module is used for determining the real-time speed of the train at the moment according to the received wheel rotating speed; the wheel rotating speed is obtained by a speed sensor arranged on a train wheel; the current time is the time when the wheel rotating speed is received at this time;
the speed prediction module is used for predicting the speed of the train at the next moment according to the real-time speed of the train at the current moment to obtain a predicted speed; the next time is the time when the operation module receives the wheel rotating speed next time;
the speed comparison module is used for comparing the predicted speed with the real-time speed of the train at the next moment determined by the operation module to obtain a comparison result, and outputting a control instruction to the control module according to the comparison result;
and the control module is used for controlling the speed of the train according to the control instruction.
2. The TCMS and ATO function integrated deep fusion system of claim 1, wherein the predicting the speed of the train at the next time according to the real-time speed of the train at the current time to obtain the predicted speed comprises:
acquiring the acting force exerted on the train determined according to the target speed curve of the train at each moment from the current moment to the next moment; the acting force is traction force or braking force;
and calculating the speed of the train at the next moment according to the real-time speed of the train at the moment, the acting force, the first mass of the train when the train is unloaded and the second mass of the passengers when the train is fully loaded, and taking the speed of the train at the next moment as the predicted speed.
3. The integrated TCMS and ATO deep fusion system of claim 2 wherein said calculating a speed of said train at said next time as said predicted speed based on said real-time speed of said train at said present time, said force, a first mass of said train when said train is empty, and a second mass of said passengers when said train is full comprises:
according to the formula
Calculating the predicted speed;
wherein, VpreRepresenting said predicted speed, t0Indicates the time t of this timeeShowing the next time, F (t) showing the force exerted on the train determined from the target speed curve of the train at time t between the current time and the next time, mAWORepresenting the first mass of the train when it is empty, mfullRepresenting the second mass of passengers when the train is fully loaded.
4. The integrated TCMS and ATO deep fusion system of claim 1 wherein said outputting control instructions to said control module based on said comparison comprises:
if the comparison result is that the absolute value of the difference between the predicted speed and the real-time speed at the next moment is smaller than or equal to a preset difference, the control instruction is to control the speed of the train according to the real-time speed at the next moment;
and if the comparison result is that the absolute value of the difference between the predicted speed and the real-time speed at the next moment is greater than the preset difference, the control instruction is to quit the ATO vehicle control and switch to manual vehicle control.
5. The integrated TCMS and ATO functional deep fusion system of claim 4, further comprising:
if the control instruction is to control the speed of the train according to the real-time speed at the next moment, controlling the train to decelerate when the real-time speed at the next moment is greater than the speed corresponding to the next moment in the target speed curve of the train, and controlling the train to accelerate when the real-time speed at the next moment is less than the speed corresponding to the next moment in the target speed curve of the train.
6. The TCMS and ATO function integrated deep fusion system as claimed in claim 1, wherein the determining the real-time speed of the train at the current time according to the wheel rotation speed received this time comprises:
and determining the real-time speed of the train at the moment according to the wheel radius of the train stored in advance and the wheel rotating speed received at the moment.
7. The integrated TCMS and ATO deep fusion system of claim 1 wherein the computing module receives the wheel speed via a bus MVB.
8. The integrated TCMS and ATO deep fusion system of claim 1 wherein the computing module, the control module, the speed prediction module and the speed comparison module are integrated into the same board.
9. A train comprising the integrated TCMS and ATO deep fusion system of any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011015329.7A CN112158237B (en) | 2020-09-24 | 2020-09-24 | Deep fusion system integrating TCMS and ATO functions and train |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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