CN117565927A - Intelligent dormancy wakeup control method for full-automatic unmanned vehicle - Google Patents

Abstract

The invention discloses an intelligent dormancy awakening method for an automatic unmanned vehicle, which comprises the following steps of: after the wake-up power-up is received, the TCMS is powered up and performs self-checking, meanwhile, the expert system WTS collects all system data from the bus, the comprehensive state of the vehicle and the comprehensive state of the train network quality are estimated and fed back to the TCMS, when the TCMS reports the self-checking result, the self-checking is continued, and if the TCMS fails to report the self-checking, the wake-up flow of the vehicle is ended; the signal system ATC sends a high-voltage test instruction, the vehicle network control system automatically completes the inspection item of the high-voltage test after receiving the instruction, the vehicle automatically rises the bow and inspects the high-voltage part of the vehicle after the 1500V voltage is connected, if the vehicle network control system TCMS reports the failure of the high-voltage self-inspection, the vehicle wake-up flow is ended; the vehicle and the signal system are matched to carry out the combined self-check, and after the combined self-check is successful, the automatic unmanned vehicle is enabled to enter the wake-up state from the dormant state.

Description

Intelligent dormancy wakeup control method for full-automatic unmanned vehicle

Technical Field

The invention belongs to the field of full-automatic products, and relates to an intelligent dormancy wakeup control method for a full-automatic unmanned vehicle.

Background

The unmanned subway vehicle is widely applied worldwide, so that the operation safety, service quality and economy of a rail transit system are improved; china is in a preliminary development stage in the aspects of unmanned subway technical research and application. Comprehensive technology. The degree of maturity of the vehicle's cooperation with the signaling system is very important.

From an automation point of view: the unmanned rail transit system aims at improving the operation safety and service quality of rail transit and improving economy, and fully utilizes modern electronic, electric, mechanical and information technologies to form a new generation of urban rail transit system with high automation level. Within the IEC standard, five levels of automation levels GOA0-GOA4 are defined, where GOA 3/GOA 4 is what we say unmanned, because it does not require the driver, removes the driver's control of the vehicle, and the vehicle's control is completely handed to the automation system.

Unmanned has the advantages that firstly, the safety is higher, the automatic control and diagnosis are realized, and the manual operation errors are reduced; the system has higher redundancy and rich functions of remote recovery, bypass, isolation and the like; in addition, the operation quality and the flexible operation schedule can be improved; the standard point has higher transportation efficiency; the higher automation level provides more humanized service functions; the economy is good, and the configuration quantity of trains can be reduced; less labor investment; the energy consumption level is low. The unmanned subway is opened and mature in various countries and regions of the world, and has relatively mature application performance.

Technical solution of the prior art

The existing sleep-wake-up method of the unmanned subway vehicle is low in intelligent degree, and the real-time state of the vehicle is checked mainly through power-on self-detection, vehicle static test, vehicle high-voltage test, dynamic test and the like of all subsystems of the traditional vehicle after power-on, so that the vehicle is wakened up to enter a standby state; through pre-dormancy, including battery voltage detection, total wind pressure detection, air conditioner state detection etc., confirm that the vehicle can carry out dormancy and carry out the dormancy action of vehicle, realize the dormancy of vehicle. In a word, the current vehicle is mainly finished according to the real-time state information of the vehicle, and the vehicle is finished by frequently interacting the vehicle state information with the vehicle signal system and the signal system.

Disadvantages of the prior art

(1) The interaction between the vehicle dormancy wakeup logic and the signal system in the prior art is too frequent, a test instruction is initiated by the signal system, state information is fed back to the signal system after the vehicle is executed, the signal system gradually controls the vehicle dormancy wakeup steps, and each step has the maximum test tolerance time, if the test tolerance time is exceeded, the test is unsuccessful, and the signal system can automatically judge dormancy wakeup failure. The frequent interaction causes the sleep and wake-up time of the vehicle to be increased, the standby time of the vehicle to be greatly increased, and the operation efficiency of the vehicle is reduced.

(2) The existing dormancy awakening process of the vehicle lacks attention to early warning information of a key system of the vehicle and historical alarm information of the key system, so that the vehicle ignores the early warning of the key system and the historical alarm information continues to awaken successfully, and the failure of the positive line operation possibly causes late or offline of the vehicle, and the running index of the vehicle is reduced.

(3) The existing vehicle cannot detect the central system (train network control system) of the train in real time, and the network control system has the abnormal conditions such as interference, packet loss, wrong needle and the like, which can cause the conditions such as false sending and missed sending of the vehicle control command, so that the control function of the vehicle is abnormal or invalid, the vehicle is caused to run in front, even the vehicle is off line, and the running index of the vehicle is seriously influenced.

Disclosure of Invention

In order to solve the problems, the invention adopts the following technical scheme: an intelligent dormancy awakening method for an automatic unmanned vehicle comprises the following steps:

the method comprises the steps that S1, after wake-up power-up is received, a TCMS (vehicle network control system) powers up and performs self-checking, other subsystems perform power-up self-checking work at the same time, meanwhile, an expert system WTS collects system data from a bus, the comprehensive state of a vehicle and the comprehensive state of train network quality are evaluated and fed back to the TCMS, the self-checking result reported to a signal system ATC is determined by the TCMS, and when the TCMS reports the self-checking result, self-checking is continued, S2 is performed, if the TCMS reports self-checking failure, the vehicle wake-up flow is ended;

s2, after the signal system ATC feeds back and receives a self-checking result of the vehicle network control system TCMS, the signal system ATC sends a high-voltage testing instruction, the vehicle network control system automatically completes a checking item of the high-voltage testing after receiving the instruction, the vehicle automatically rises to check a high-voltage part of the vehicle after 1500V voltage is accessed, when the vehicle network control system TCMS reports the high-voltage self-checking success, the self-checking process is continued, S3 is carried out, if the vehicle network control system TCMS reports the high-voltage self-checking failure, the vehicle awakening process is ended;

and S3, after the signal system ATC receives success of high-voltage self-checking fed back by the vehicle network control system TCMS, the vehicle and the signal system cooperate to carry out joint self-checking, and after the joint self-checking is successful, the vehicle enters a standby working condition, so that the automatic unmanned vehicle enters a wake-up state from a dormant state.

Further: the other subsystems perform power-on self-checking work simultaneously, wherein the power-on self-checking work comprises traction, assistance, braking, a vehicle door, a bow net, a walking part, a fire alarm, a charger, an air conditioner, a passenger information system, a vehicle door state, a vehicle bypass button state and a vehicle key switch state.

Further: the high-voltage part inspection comprises input and output inspection of a traction/auxiliary system, air blowing and air tightness inspection of an air compressor, inspection of a charger and inspection of mechanical braking.

Further: the vehicle and the signal system are matched to perform joint self-checking including switching an activation end, emergency braking self-checking, opening and closing a door and peristaltic testing.

Further: also included is sleep process control, comprising the following processes:

the train runs to a dormancy wakeup area in a FAM mode and stops at the dormancy wakeup station in an aligned mode;

the communication channel is established, a signal system ATC sends a dormancy request, a vehicle TCMS system replies an ATC dormancy request confirmation after receiving the dormancy request signal, at the moment, the ATC sends a dormancy command to a vehicle TCMS, the TCMS feeds back the dormancy command confirmation to the ATC and simultaneously carries out preparation before dormancy of the vehicle, the preparation comprises detection of a total wind state, a storage battery state, a stop air compressor, an air conditioner, a vehicle key fault, vehicle comprehensive state evaluation combining an expert system and comprehensive state of network quality, after all dormancy conditions of the vehicle are met, the TCMS sends dormancy preparation completion to the ATC, and the ATC sends a vehicle outage instruction and is responsible for executing outage of the vehicle.

Further: the process adopted for evaluating the comprehensive state of the vehicle is as follows:

the comprehensive evaluation value of the whole vehicle C is obtained through the calculation of the health degree of the single vehicle subsystem, the calculation of the health degree of the whole vehicle subsystem and the comprehensive evaluation calculation of the whole vehicle, and the specific steps are as follows.

Calculating the health degree of a single vehicle subsystem:

wherein: a1 is a bicycle subsystem score (0-100), X is an evaluation dimension, and Y is a weight proportion of a subsystem;

and (3) calculating the health degree of the whole vehicle subsystem:

B1＝(A1+A2+A3…)/N；

wherein: b1 is the score (0-100) of the whole vehicle subsystem, ai is the score of the ith vehicle-saving system, and N is the number of the vehicle-saving system;

and (3) calculating comprehensive score of the whole vehicle:

C＝B1*P1+B2*P2+…+Bn*Pn；

wherein: c is the actual vehicle comprehensive score (0-100), bn is the whole vehicle subsystem score, and Pn is the weight proportion of the whole vehicle system.

Further: the comprehensive state of the train network quality automatically obtains an analysis result of each device/port by collecting the MVB network communication messages 30S-180S and the waveform data of one macro period for a period of time and analyzing the data according to the configuration parameters to generate an analysis report;

and through collecting communication messages and physical waveforms of the train MVB network, carrying out omnibearing analysis on the train network from a communication physical layer, a link layer and a network layer, and outputting a train network quality analysis report.

The invention provides a full-automatic unmanned vehicle intelligent dormancy awakening control method, which is used for grasping the problems of vehicles in the dormancy awakening process through the centralized investigation of dormancy awakening logics of a plurality of existing unmanned subways. Controlled by the method to enable

(1) The interaction between the vehicle dormancy wakeup logic and the signal system is simple, the TCMS intelligently controls the vehicle self-checking test, the efficiency is greatly improved, the servicing time of the vehicle is greatly shortened, and the operation efficiency of the vehicle is improved.

(2) The method has the advantages that the early warning information of the key system of the vehicle and the analysis of the historical warning information of the key system are added to the dormancy awakening process of the vehicle, so that the problem that the vehicle is late or offline due to the fact that the normal operation is possibly failed is effectively avoided, and the running index of the vehicle is improved.

(3) The central system (train network control system) of the train is detected in real time, and the network control system has the abnormal conditions of interference, packet loss, wrong needle and the like, so that the vehicle can be prevented from being normally awakened under the condition of poor network quality, and the conditions of false transmission, missed transmission and the like of vehicle control instructions are avoided, thereby causing abnormal or invalid control functions of the vehicle, causing failure of normal running of the vehicle, and even off-line running of the vehicle, and further ensuring the running safety of the vehicle.

The method has the following advantages:

(1) The intelligent vehicle dormancy and change-over control method simplifies the interaction flow, improves the awakening efficiency, and mainly awakens the vehicle to be controlled and detected autonomously, and has the following characteristics compared with the traditional awakening method:

1) The interaction process is concise, and the autonomous detection and control capability of the vehicle is high, so that the vehicle wake-up failure caused by data loss due to frequent interaction between the vehicle and the signal system is reduced, and the operation efficiency of the vehicle is directly affected.

2) The vehicle wake-up control flow is highly intelligent, and the vehicle autonomously decides the self-checking project according to the preset sequence after receiving the signal system instruction, so that the repetition of the signal system is reduced, the wake-up time of the vehicle is shortened, the vehicle can quickly enter the standby working condition, and the operation efficiency of the vehicle is improved.

3) The vehicle wake-up condition fully considers various conditions of vehicle driving safety, such as a state of a vehicle breaker, a bypass switch state, a key relay state, a cabinet door state and the like. And after all conditions are met, wake-up operation can be performed.

(2) And the expert system performs diagnosis and application of the subsystem, applies big data analysis to perform comprehensive health assessment on the vehicle, and performs dormancy wakeup control on the vehicle according to an assessment result.

(3) And the expert system analyzes and applies the train control bus, evaluates the communication quality of the rail train MVB network and positions communication faults, and performs vehicle dormancy awakening control according to the evaluation result.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive effort to a person skilled in the art.

FIG. 1 is a topology of a network control system of an unmanned vehicle;

FIG. 2 is a wake-up flow diagram;

FIG. 3 is a sleep flow diagram;

FIG. 4 is a graph of health value versus impact factor;

fig. 5 is a network report test chart.

Detailed Description

It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other, and the present invention will be described in detail below with reference to the drawings and the embodiments.

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.

The relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise. Meanwhile, it should be clear that the dimensions of the respective parts shown in the drawings are not drawn in actual scale for convenience of description. Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate. In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.

In the description of the present invention, it should be understood that the azimuth or positional relationships indicated by the azimuth terms such as "front, rear, upper, lower, left, right", "lateral, vertical, horizontal", and "top, bottom", etc., are generally based on the azimuth or positional relationships shown in the drawings, merely to facilitate description of the present invention and simplify the description, and these azimuth terms do not indicate and imply that the apparatus or elements referred to must have a specific azimuth or be constructed and operated in a specific azimuth, and thus should not be construed as limiting the scope of protection of the present invention: the orientation word "inner and outer" refers to inner and outer relative to the contour of the respective component itself.

Spatially relative terms, such as "above … …," "above … …," "upper surface at … …," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial location relative to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "above" or "over" other devices or structures would then be oriented "below" or "beneath" the other devices or structures. Thus, the exemplary term "above … …" may include both orientations of "above … …" and "below … …". The device may also be positioned in other different ways (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.

In addition, the terms "first", "second", etc. are used to define the components, and are only for convenience of distinguishing the corresponding components, and the terms have no special meaning unless otherwise stated, and therefore should not be construed as limiting the scope of the present invention.

FIG. 1 is a topology of a network control system of an unmanned vehicle, with an orange portion of the diagram being a network control system device;

(1) Each Tc car has a train control unit (CCU) that are redundant to each other. The main CCU is responsible for control of the vehicle, monitoring and diagnosis of vehicle equipment;

(2) Two human-machine interface units (HMI), one for each Tc car, are located separately, responsible for displaying the status of the equipment and guiding the driver and passengers.

(3) Each carriage is provided with a RIOM module which is connected with a vehicle bus through an MVB interface, so that the main signals of the 110V control circuit are collected and controlled, and signals such as analog signals or digital signals of a driver controller, a steering handle and the like are collected and controlled. The Tc1 and Tc2 cars each have two RIOM modules for redundant acquisition of critical train signals.

(4) Each section of vehicle is provided with a repeater, each repeater comprises two repeater modules which are redundant with each other, and when one repeater fails, the other repeater relays and transmits the original A path or B path without influencing the receiving of each subsystem to the signals. The repeater divides the train network into a train bus and a vehicle bus, amplifies and regenerates signals transmitted in the MVB line, and ensures the reliable transmission distance of the bus;

(6) An accident backup recording device (ERD) is arranged on the M1 vehicle and used for providing independent accident backup recording devices, continuously recording key train information, meeting the requirements of accident impact, vibration, extrusion, water resistance, fire resistance and the like and analyzing major accidents of the train.

(7) Other subsystems are connected to the TCMS through an MVB bus or RIOM, and subsystem component failures do not affect the normal operation of the MVB vehicle bus. The interfaces between the subsystem and the vehicle bus are redundant, and the normal operation of the train is not affected by the failure of a single interface.

(8) The subsystem is connected with the Ethernet switch of each section of the train through an Ethernet interface and an Ethernet cable, and constructs a train maintenance Ethernet local area network together for remote debugging, updating, data downloading and the like of the equipment. Meanwhile, the local area network provides a reliable and high-speed data transmission path for data collection of a train system.

FIG. 2 is a wake-up flow diagram;

and a reliable and high-speed data transmission path is provided for data collection of a train system.

In the figure, ATC is a signal system, WTS is a vehicle expert system, and the intelligent dormancy wakeup control method is mainly realized by matching a network control system, the signal system and the expert system. The wake-up implementation process is as shown:

an intelligent dormancy awakening method for an automatic unmanned vehicle comprises the following steps:

the TCMS collects network data of all subsystems of the vehicle and hardware data of the vehicle through MVB and ETH buses, and performs wake-up operation on the vehicle by combining related control instructions sent by a signal system (ATC);

the method comprises the steps that S1, a TCMS (train control system) is powered on and performs self-checking after a vehicle receives wake-up power-on, other subsystems perform power-on self-checking work simultaneously, wherein the work comprises traction, assistance, braking, a vehicle door, a bow net, a running part, a fire alarm, a charger, an air conditioner, a passenger information system, a vehicle cabinet door state, a vehicle bypass button state, a vehicle key switch state and the like;

s2, after the vehicle network control system TCMS feeds back the success of self-checking to the signal system ATC, the signal system ATC sends a high-voltage test instruction, after the vehicle network control system receives the instruction, all inspection items of the part are automatically completed, the vehicle automatically rises to perform high-voltage part inspection of the vehicle after 1500V voltage is accessed, the inspection comprises input and output inspection of a traction/auxiliary system, air blowing and air tightness inspection of an air compressor, inspection of a charger, mechanical brake inspection and the like, if the vehicle network control system TCMS reports that the high-voltage self-checking is successful, the self-checking process is continued, and if the vehicle network control system TCMS reports that the high-voltage self-checking is failed, the vehicle awakening process is ended;

and S3, after the high-voltage self-test is successfully fed back to the signal system ATC by the vehicle network control system TCMS, the vehicle and the signal system cooperate to carry out combined self-test, including switching an activation end, carrying out emergency braking self-test, opening and closing a door, carrying out peristaltic test and the like. After the combined self-checking is successful, the vehicle enters a standby working condition, and can be started at any time to be put into operation.

FIG. 3 is a sleep flow diagram;

an intelligent dormancy method of an automatic unmanned vehicle comprises the following steps:

the train runs to a dormancy wakeup area in a FAM mode and stops at the dormancy wakeup station in an aligned mode;

the communication channel is established, the ATC sends a sleep request, the vehicle TCMS system replies the ATC sleep request confirmation after receiving the sleep request signal, at the moment, the ATC sends a sleep command to the vehicle TCMS, the TCMS feeds back the sleep command confirmation to the ATC and simultaneously carries out preparation before the vehicle is in sleep, the preparation comprises detection of a total wind state, a storage battery state, a stop air compressor, an air conditioner, a vehicle key fault, comprehensive vehicle state evaluation combining an expert system, comprehensive network quality state and the like, after all the sleep conditions of the vehicle are met, the TCMS sends a sleep preparation completion to the ATC, and the ATC sends a vehicle power-off instruction and is responsible for executing power off of the vehicle.

The implementation structure of the intelligent dormancy wakeup control method is shown in figure 1, and all components are connected through an MVB bus and an ETH bus. The working process is as follows:

a. the various subsystems of the vehicle (blue part) interact data with the TCMS control system of the vehicle (orange part) via the MVB bus and the ethernet bus.

And b, performing a control flow of dormancy wakeup by the TCMS according to the system state fed back by each subsystem. As in fig. 2 and 3.

c. The vehicle expert system (WTS) determines whether the vehicle can sleep and wake smoothly by comprehensively judging the states of key system components through data analysis of each system as a precondition for sleep and wake of the vehicle.

d. The bus analysis module in the vehicle expert system (WTS) analyzes the quality of the MVB bus, diagnoses abnormal conditions such as interference, packet loss, error needle and the like, and feeds back the diagnosis result to the vehicle TCMS control system as a precondition of vehicle dormancy awakening to determine whether the vehicle can be successfully dormancy awakened.

And e, completing the vehicle dormancy wakeup control flow by the TCMS control system according to the time sequence shown in the figures 2 and 3.

(2) The invention relates to a full-automatic unmanned vehicle intelligent dormancy wakeup control method, which is mainly realized by a TCMS system and an expert system (WTS), wherein the TCMS system mainly aims at controlling the flow of vehicle dormancy wakeup according to the figures 2 and 3 and carrying out data interaction with a signal system (ATC); the expert system mainly comprises two parts, wherein one part is fault information, early warning information and life prediction information of key components of the real-time diagnosis subsystem, the other part is quality of the real-time diagnosis control bus, the two parts of information are transmitted to the TCMS system, and the TCMS comprehensively judges whether dormancy wakeup is continued or not.

Further, the expert system intelligently evaluates the comprehensive state of the subsystem and directly participates in the dormancy wakeup control process as follows:

the vehicle expert system performs comprehensive diagnosis on vehicle data, intelligently decides whether the vehicle is in dormancy and wakes up according to the diagnosis result, and ensures the driving safety of the vehicle.

The vehicle expert system provides data support for vehicle health status assessment from the bottom layer to the top layer step by step (vehicle level assessment data comes from a system level, and system level assessment data is provided by other business systems), and factors affecting the system level health status include train status information, fault class information, status monitoring information and the like. The vehicle-level impact factors consist of systems (or parts of the accent systems) that participate at the system level. FIG. 4 is a graph of health value versus impact factor;

the expert system supports the relation between the data item points and the influence factors according to a certain data editing rule, and when a plurality of data item points are needed to support a certain influence factor or calculation cannot be completed in a single function system, health degree weighted calculation is carried out after data editing (secondary data calculation) is carried out after the data item points are imported.

The result of the calculation is the content of the final factor calculation input item.

The system status is digitally presented in conjunction with the health score value. According to the system scores, the system is divided into five grades, and the grade judgment value is adjustable. And when the health degree is good, the vehicle is allowed to sleep and wake up, otherwise, human intervention is needed to check the vehicle.

Health degree	Grade
		>90	Good state
90-75	Operation observation
		75-65	Maintain operation
65-55	Influence on driving
		<55	Potential safety hazard

The vehicle expert system calculates influence factors on vehicle awakening and dormancy according to the data of the vehicle subsystem, finally evaluates the health degree of the vehicle through weighted calculation, reports the diagnosis result to the TCMS system through the vehicle bus, and decides the vehicle awakening from dormancy according to the health degree through the TCMS system. The vehicle health degree does not allow the TCMS to wake up the vehicle when the potential safety hazard and the driving influence are two stages. The method greatly reduces the failure rate of the vehicle on-line and improves the operation service level of the vehicle.

The process adopted for evaluating the comprehensive state of the vehicle is as follows:

the comprehensive evaluation value of the whole vehicle C is obtained through the calculation of the health degree of the single vehicle subsystem, the calculation of the health degree of the whole vehicle subsystem and the comprehensive evaluation calculation of the whole vehicle, and the specific steps are as follows.

(1) Calculating the health degree of a single vehicle subsystem:

wherein: a1 is a bicycle subsystem score (0-100), X is an evaluation dimension, and Y is a weight ratio of the subsystem as follows:

(2) And (3) calculating the health degree of the whole vehicle subsystem:

B1＝(A1+A2+A3…)/N；

wherein: b1 is the score (0-100) of the whole vehicle subsystem, ai is the score of the ith vehicle-saving system, and N is the number of the vehicle-saving system;

(3) And (3) calculating comprehensive score of the whole vehicle:

C＝B1*P1+B2*P2+…+Bn*Pn；

wherein: c is the actual vehicle comprehensive score (0-100), bn is the whole vehicle subsystem score, pn is the weight ratio of the whole vehicle system as follows:

b (evaluation dimension)	P (subsystem weight ratio)
		Traction system	0.1
Braking system	0.1
		Auxiliary system	0.1
Vehicle door system	0.1
		Air conditioning system	0.1
Passenger information system	0.1
		Fire alarm detection system	0.1
Walking part overhauling system	0.05
		Obstacle overhauling system	0.05
Train control system	0.15
		Storage battery monitoring system	0.02
Bow net monitoring system	0.03

Further, the expert system intelligently diagnoses and controls the bus quality and directly participates in dormancy wakeup control, and the specific process is as follows:

the vehicle-mounted expert diagnosis system intelligently diagnoses the bus quality, reports the result to the TCMS, and the TCMS decides whether to wake the vehicle to sleep or not.

And the vehicle-mounted expert diagnosis system evaluates the communication quality of the train MVB network. After the operation starts to analyze on the software, the device automatically collects the MVB network communication message (30S-180S) and the waveform data of one macro period for a period of time, analyzes the data according to the configuration parameters, automatically obtains the analysis result of each device/port, and generates an analysis report. Fig. 5 is a network report test chart.

The vehicle-mounted expert diagnosis system evaluates the communication quality of the rail train MVB network and locates communication faults, and the product carries out omnibearing analysis on the train network from a communication physical layer, a link layer and a network layer by collecting communication messages and physical waveforms of the train MVB network and outputs a train network quality analysis report. When the train network fails, the expert system can quickly diagnose the occurrence position and possible reasons of the failure.

And the TCMS controls the dormancy wakeup of the vehicle according to the diagnosis result, for example, the vehicle is not allowed to wake up when the error rate is more than 15 percent, and the vehicle is not allowed to sleep when the error rate is more than 25 percent. The method can reduce the off-line faults of the vehicle caused by the network quality problem and improve the running efficiency of the vehicle.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the 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 scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (7)

1. An intelligent dormancy awakening method for an automatic unmanned vehicle is characterized by comprising the following steps of: the method comprises the following steps:

the method comprises the steps that S1, after wake-up power-up is received, a TCMS (vehicle network control system) powers up and performs self-checking, other subsystems perform power-up self-checking work at the same time, meanwhile, an expert system WTS collects system data from a bus, the comprehensive state of a vehicle and the comprehensive state of train network quality are evaluated and fed back to the TCMS, the self-checking result reported to a signal system ATC is determined by the TCMS, and when the TCMS reports the self-checking result, self-checking is continued, S2 is performed, if the TCMS reports self-checking failure, the vehicle wake-up flow is ended;

s2, after the signal system ATC feeds back and receives a self-checking result of the vehicle network control system TCMS, the signal system ATC sends a high-voltage testing instruction, the vehicle network control system automatically completes a checking item of the high-voltage testing after receiving the instruction, the vehicle automatically rises to check a high-voltage part of the vehicle after 1500V voltage is accessed, when the vehicle network control system TCMS reports the high-voltage self-checking success, the self-checking process is continued, S3 is carried out, if the vehicle network control system TCMS reports the high-voltage self-checking failure, the vehicle awakening process is ended;

and S3, after the signal system ATC receives success of high-voltage self-checking fed back by the vehicle network control system TCMS, the vehicle and the signal system cooperate to carry out joint self-checking, and after the joint self-checking is successful, the vehicle enters a standby working condition, so that the automatic unmanned vehicle enters a wake-up state from a dormant state.

2. The intelligent dormancy wakeup method of an automatic unmanned vehicle according to claim 1, wherein: the other subsystems perform power-on self-checking work simultaneously, wherein the power-on self-checking work comprises traction, assistance, braking, a vehicle door, a bow net, a walking part, a fire alarm, a charger, an air conditioner, a passenger information system, a vehicle door state, a vehicle bypass button state and a vehicle key switch state.

3. The intelligent dormancy wakeup method of an automatic unmanned vehicle according to claim 1, wherein: the high-voltage part inspection comprises input and output inspection of a traction/auxiliary system, air blowing and air tightness inspection of an air compressor, inspection of a charger and inspection of mechanical braking.

4. The intelligent dormancy wakeup method of an automatic unmanned vehicle according to claim 1, wherein: the vehicle and the signal system are matched to perform joint self-checking including switching an activation end, emergency braking self-checking, opening and closing a door and peristaltic testing.

5. The intelligent dormancy wakeup method of an automatic unmanned vehicle according to claim 1, wherein: also included is sleep process control, comprising the following processes:

the train runs to a dormancy wakeup area in a FAM mode and stops at the dormancy wakeup station in an aligned mode;

the communication channel is established, a signal system ATC sends a dormancy request, a vehicle TCMS system replies an ATC dormancy request confirmation after receiving the dormancy request signal, at the moment, the ATC sends a dormancy command to a vehicle TCMS, the TCMS feeds back the dormancy command confirmation to the ATC and simultaneously carries out preparation before dormancy of the vehicle, the preparation comprises detection of a total wind state, a storage battery state, a stop air compressor, an air conditioner, a vehicle key fault, vehicle comprehensive state evaluation combining an expert system and comprehensive state of network quality, after all dormancy conditions of the vehicle are met, the TCMS sends dormancy preparation completion to the ATC, and the ATC sends a vehicle outage instruction and is responsible for executing outage of the vehicle.

6. The intelligent dormancy wakeup method of an automatic unmanned vehicle according to claim 1, wherein: the process adopted for evaluating the comprehensive state of the vehicle is as follows:

the comprehensive evaluation value of the whole vehicle C is obtained through the calculation of the health degree of the single vehicle subsystem, the calculation of the health degree of the whole vehicle subsystem and the comprehensive evaluation calculation of the whole vehicle, and the specific steps are as follows.

Calculating the health degree of a single vehicle subsystem:

wherein: a1 is a bicycle subsystem score (0-100), X is an evaluation dimension, and Y is a weight proportion of a subsystem;

and (3) calculating the health degree of the whole vehicle subsystem:

B1＝(A1+A2+A3…)/N；

wherein: b1 is the score (0-100) of the whole vehicle subsystem, ai is the score of the ith vehicle-saving system, and N is the number of the vehicle-saving system;

and (3) calculating comprehensive score of the whole vehicle:

C＝B1*P1+B2*P2+…+Bn*Pn；

wherein: c is the actual vehicle comprehensive score (0-100), bn is the whole vehicle subsystem score, and Pn is the weight proportion of the whole vehicle system.

7. The intelligent dormancy wakeup method of an automatic unmanned vehicle according to claim 1, wherein: the comprehensive state of the train network quality automatically obtains an analysis result of each device/port by collecting the MVB network communication messages 30S-180S and the waveform data of one macro period for a period of time and analyzing the data according to the configuration parameters to generate an analysis report;

and through collecting communication messages and physical waveforms of the train MVB network, carrying out omnibearing analysis on the train network from a communication physical layer, a link layer and a network layer, and outputting a train network quality analysis report.