CN116714611B - Train control method, vehicle-mounted controller, train and storage medium - Google Patents
Train control method, vehicle-mounted controller, train and storage medium Download PDFInfo
- Publication number
- CN116714611B CN116714611B CN202310981964.8A CN202310981964A CN116714611B CN 116714611 B CN116714611 B CN 116714611B CN 202310981964 A CN202310981964 A CN 202310981964A CN 116714611 B CN116714611 B CN 116714611B
- Authority
- CN
- China
- Prior art keywords
- proportion
- environmental data
- limiting
- train
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 74
- 230000007613 environmental effect Effects 0.000 claims abstract description 248
- 238000013507 mapping Methods 0.000 claims description 76
- 238000012937 correction Methods 0.000 claims description 19
- 238000004590 computer program Methods 0.000 claims description 12
- 238000005259 measurement Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006698 induction Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000000725 suspension Substances 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61C—LOCOMOTIVES; MOTOR RAILCARS
- B61C17/00—Arrangement or disposition of parts; Details or accessories not otherwise provided for; Use of control gear and control systems
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/72—Electric energy management in electromobility
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Train Traffic Observation, Control, And Security (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses a train control method, a vehicle-mounted controller, a train and a storage medium, wherein the train control method comprises the following steps: acquiring first environmental data of a train; when the first environmental data meets traction limiting conditions, determining a target limiting proportion according to the first environmental data; and limiting the target traction force of the train based on the target limiting proportion. The method can realize that when the first environmental data meets the traction limiting condition, the traction limitation is carried out by utilizing the target limiting proportion determined by the first environmental data, and the influence of noise generated in the running process of the train on the normal life of people can be effectively reduced.
Description
Technical Field
The invention relates to the technical field of rail transit, in particular to a train control method, a vehicle-mounted controller, a train and a storage medium.
Background
Rail traffic refers to a type of transportation means or transportation system in which an operating vehicle needs to travel on a specific track, and with the diversification development of train and railway technologies, rail traffic is of an increasing type, and is not only transported over long-distance land, but also widely applied to urban public transportation in short and medium distances. Common rail transit is the traditional railway (common railway, inter-city railway and urban railway), subway, light rail and tramcar, and also the novel rail transit such as magnetic suspension rail system, monorail system and cloud bar.
When a train runs, due to different frictional force between the train and the track, environmental humidity, environmental wind speed and other environmental factors, larger noise is generated in the running process of the train, adverse effects are caused on living environments of surrounding residents, and a train control method is needed to reduce the noise in the running process of the train.
Disclosure of Invention
The embodiment of the invention provides a train control method, a vehicle-mounted controller, a train and a storage medium, which are used for solving the problem that the normal life of people is influenced due to large noise generated in the running process of the train.
A train control method comprising:
acquiring first environmental data of a train;
when the first environmental data meets traction limiting conditions, determining a target limiting proportion according to the first environmental data;
and limiting the target traction force of the train based on the target limiting proportion.
Preferably, after the acquiring the first environmental data of the train, the train control method further includes:
and controlling the running of the train according to the target traction force of the train when the first environmental data does not meet the traction force limiting condition.
Preferably, the first environmental data includes a current system time and a current train position;
The traction limiting condition is that the current system time is within a preset rest period and the current train position is within a residential area.
Preferably, the first environmental data further includes a current environmental humidity;
the traction limiting condition is that the current system time is in a preset rest time period, the current train position is in a residential area, and the current environmental humidity is larger than a preset humidity threshold.
Preferably, when the first environmental data meets the traction force limiting condition, determining the target limiting proportion according to the first environmental data includes:
acquiring second environmental data of the train when the first environmental data meets traction limiting conditions;
and determining a target limiting proportion according to the first environment data and the second environment data.
Preferably, the determining the target limit proportion according to the first environment data and the second environment data includes:
determining a first limiting proportion corresponding to the first environmental data according to the first environmental data;
and determining a target limiting proportion according to the second environment data and the first limiting proportion.
Preferably, the first environmental data includes a current system time and a current train position;
The determining, according to the first environmental data, a first limitation proportion corresponding to the first environmental data includes:
determining a time limit proportion corresponding to the current system time according to the mapping relation between the current system time and the time limit proportion;
determining a position limiting proportion corresponding to the current train position according to the mapping relation between the actual measured distance and the distance limiting proportion between the current train position and the residential area;
and determining a first limiting proportion according to the time limiting proportion and the position limiting proportion.
Preferably, the first environmental data includes a current system time, a current train position, and a current environmental humidity;
the determining, according to the first environmental data, a first limitation proportion corresponding to the first environmental data includes:
determining a time limit proportion corresponding to the current system time according to the mapping relation between the current system time and the time limit proportion;
determining a position limiting proportion corresponding to the current train position according to the mapping relation between the actual measured distance and the distance limiting proportion between the current train position and the residential area;
determining a humidity limiting proportion corresponding to the current environment humidity according to the mapping relation between the current environment humidity and the humidity limiting proportion;
And determining a first limiting proportion according to the time limiting proportion, the position limiting proportion and the humidity limiting proportion.
Preferably, the determining a target restriction ratio according to the second environmental data and the first restriction ratio includes:
determining a target correction coefficient according to the second environmental data;
and correcting the first limiting proportion by adopting the target correction coefficient, and determining a target limiting proportion.
Preferably, the determining a target restriction ratio according to the second environmental data and the first restriction ratio includes:
determining a second limiting proportion corresponding to the second environment data according to the second environment data;
and determining a target limiting proportion according to the second limiting proportion and the first limiting proportion.
Preferably, the second environmental data comprises measured sound loudness;
the determining, according to the second environmental data, a second limiting proportion corresponding to the second environmental data includes:
and determining a loudness limiting proportion corresponding to the measured sound loudness according to the mapping relation between the measured sound loudness and the loudness limiting proportion, and determining the loudness limiting proportion as a second limiting proportion corresponding to the second environment data.
Preferably, the second environmental data includes measured sound frequency;
the determining, according to the second environmental data, a second limiting proportion corresponding to the second environmental data includes:
and determining a frequency limit proportion corresponding to the measured sound frequency according to the mapping relation between the measured sound frequency and the frequency limit proportion, and determining the frequency limit proportion as a second limit proportion corresponding to the second environment data.
Preferably, the second environmental data includes measured sound loudness and measured sound frequency;
the determining, according to the second environmental data, a second limiting proportion corresponding to the second environmental data includes:
determining a loudness limiting proportion corresponding to the measured sound loudness according to the mapping relation between the measured sound loudness and the loudness limiting proportion;
determining a frequency limit proportion corresponding to the measured sound frequency according to the mapping relation between the measured sound frequency and the frequency limit proportion;
and determining a second limiting proportion corresponding to the second environment data according to the loudness limiting proportion and the frequency limiting proportion.
Preferably, after the second environmental data of the train is acquired, the train control method further includes:
Judging whether the second environmental data meets a noise interference condition or not;
if the second environmental data meets the noise interference condition, executing the step of determining a target limiting proportion according to the first environmental data and the second environmental data;
and if the second environmental data does not meet the noise interference condition, executing the step of determining a target limiting proportion according to the first environmental data.
Preferably, the second environmental data comprises measured sound loudness and/or measured sound frequency;
the noise interference condition is that the measured sound loudness is greater than a preset loudness threshold and/or the measured sound frequency is less than a preset frequency threshold.
Preferably, the first environmental data is environmental data collected during the running process of the train, and/or the second environmental data is environmental data collected during the running process of the train.
The vehicle-mounted controller comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the train control method when executing the computer program.
A train includes a vehicle-mounted controller.
A computer readable storage medium storing a computer program which when executed by a processor implements the train control method described above.
According to the train control method, the train control device, the vehicle-mounted controller and the storage medium, when the first environmental data meet the traction limiting conditions, the traction limiting requirements are determined to exist, the corresponding target limiting proportion is determined according to the first environmental data, the target traction of the train is limited by the target limiting proportion, and the influence of noise generated in the running process of the train on normal life of people can be effectively reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments of the present invention will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for controlling a train in accordance with an embodiment of the present invention;
FIG. 2 is a flowchart of step S102 in FIG. 1;
FIG. 3 is a flowchart of step S202 in FIG. 2;
FIG. 4 is a flowchart of step S301 in FIG. 3;
fig. 5 is another flowchart of step S301 in fig. 3;
FIG. 6 is a flowchart of step S302 in FIG. 3;
Fig. 7 is another flowchart of step S302 in fig. 3;
fig. 8 is a flowchart of step S701 in fig. 7;
fig. 9 is a flowchart after step S201 in fig. 2;
FIG. 10 is a diagram of a time constraint ratio mapping table according to an embodiment of the present invention;
FIG. 11 is a schematic diagram of a humidity limit ratio mapping table according to an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. 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.
The train control method provided by the embodiment of the invention can be applied to a train of a rail transit system, and is particularly applied to a vehicle-mounted controller loaded on the train, wherein the vehicle-mounted controller can be a controller special for controlling the train or can be a controller integrated with other functions.
In one embodiment, as shown in fig. 1, a train control method is provided, and the method is described by taking an on-board controller loaded on a train as an example, and includes the following steps:
S101: acquiring first environmental data of a train;
s102: when the first environmental data meets traction limiting conditions, determining a target limiting proportion according to the first environmental data;
s103: and limiting the target traction force of the train based on the target limiting proportion.
The first environmental data is data which is acquired in real time and reflects the environment where the train is located, and is environmental data matched with traction limiting conditions. The first environmental data herein includes, but is not limited to, current system time, current train position, current environmental humidity, current environmental wind speed, etc. data that may affect normal life of people on the train passing area.
The traction force limiting condition refers to a preset condition for evaluating whether traction force limitation is required or not. Generally, the traction limit condition is a condition that is generally set based on whether or not passing of a train has a great influence on normal life of a person. The target limiting proportion is a limiting proportion determined according to the environmental data, is a limiting proportion for finally controlling the train to limit the traction force, and can be understood as a proportion for limiting the target traction force of the train for normal running, and the limiting proportion has a value range of (0, 1).
The target traction force is the traction force required to be provided for controlling the train to run normally, and the traction force required to be provided for controlling the train to run normally can be understood under the condition that environmental data is not considered.
As an example, in step S101, the vehicle-mounted controller may obtain, according to a traction limitation condition preset by the system, first environmental data of the train matched with the traction limitation condition through an induction device or other hardware device loaded on the train, so as to evaluate the extent of influence of the train passing on life of people based on the first environmental data. For example, when the traction force limiting condition environmental humidity reaches a preset threshold value, first environmental data of the current environmental humidity of the train is required to be acquired.
As an example, in step S102, after acquiring the first environmental data, the vehicle-mounted controller compares the first environmental data with a preset traction limitation condition; when the first environmental data meets traction force limiting conditions, it is determined that the passing of the train can cause great influence on normal life of people, for example, noise generated by the passing of the train can cause great influence on normal rest of people, and at the moment, the first environmental data is required to be analyzed and processed to determine corresponding target limiting proportion.
As an example, in step S103, the on-board controller may limit the target traction force during the train operation based on the target limit proportion after determining the target limit proportion according to the first environmental data. For example, when the target traction force of the train running normally is F1 and the target limiting proportion is Km, the target traction force F1 may be limited by using the target limiting proportion Km, the product of the target traction force F1 and the target limiting proportion is determined as a new target traction force F1 '=f1×km, and the train running is controlled based on the new target traction force F1', so as to reduce the running speed of the train, further reduce the noise generated in the running process of the train, and avoid affecting the normal life of people.
In this embodiment, when the first environmental data meets the traction force limitation condition, it is determined that there is a traction force limitation demand, and only the corresponding target limitation proportion is determined according to the first environmental data, and the target limitation proportion is used to limit the target traction force of the train, so that the influence of noise generated in the running process of the train on the normal life of people can be effectively reduced.
In an embodiment, after step S101, that is, after acquiring the first environmental data of the train, the train control method further includes:
And controlling the running of the train according to the target traction force of the train when the first environmental data meets the condition that the traction force limiting condition is not met.
As an example, when the first environmental data does not meet the traction force limitation condition, the noise generated by the running of the train is considered to have a smaller influence on the normal life of people, and at this time, the train can be controlled to run normally according to the target traction force without traction force limitation, so as to meet the travel requirement of the passengers and reduce the travel time of the passengers.
In one embodiment, the first environmental data includes a current system time and a current train location;
the traction force limiting condition is that the current system time is within a preset rest period and the current train position is within a residential area.
The current system time refers to the system time at the current moment. The preset rest period refers to a period of time preset for evaluating whether a person is at rest, and for example, may be set to 8:00-20:00.
the current train position refers to a position of the train at the current moment, and the current train position can be determined by positioning through a vehicle-mounted positioning system (such as a GPS positioning system and a Beidou positioning system) arranged on the train. The residential area refers to the area where people are living as determined by the electronic map.
As an example, after acquiring the two first environmental data of the current system time and the current train position, the vehicle-mounted controller determines whether the current system time is within a preset rest period, and determines whether the current train position is within a residential area, and if the current system time is within the preset rest period and the current train position is within the residential area, it is determined that the train passes through the residential area within the preset rest period, and noise generated by the train may have a great influence on normal rest of people, so that it is determined that traction limitation conditions are met, traction limitation needs to be performed on the train, so that noise generated in the running process of the train is reduced, and normal rest of people is further ensured.
In the example, whether the traction limiting condition is met is evaluated by combining the current system time, traction limitation is carried out when noise influences normal rest of people, and noise in the running process of a train is reduced; the travel requirement of the passengers can be met to the greatest extent on the premise that the noise does not influence normal rest of the people, so that the travel time of the passengers is reduced. Whether the traction limiting condition is met or not is evaluated by combining the current train position, traction limiting is carried out when the train passes through the residential area, and noise in the running process of the train is reduced; the traction force is not limited when the train does not pass through the residential area, so that the running speed of the train can be ensured, and the travel time of passengers is saved.
In an embodiment, the first environmental data further comprises a current environmental humidity;
the traction limiting condition is that the current system time is in a preset rest time period, the current train position is in a residential area, and the current environmental humidity is greater than a preset humidity threshold.
The current environmental humidity refers to the humidity of the environment where the train is located, which is detected at the current moment. The preset humidity threshold is a preset humidity threshold for evaluating whether traction limitation is required.
As an example, after three first environmental data of the current system time, the current train position and the current environmental humidity are acquired, the vehicle-mounted controller judges whether the current system time is within a preset rest time period, judges whether the current train position is within a residential area, and judges that the current environmental humidity is greater than a preset humidity threshold; in the preset rest time period of the current system time, the current train position is in the residential area, and when the current environmental humidity is greater than the preset humidity threshold value, the train is considered to pass through the residential area in the preset rest time period, noise generated by the train can possibly cause great influence on normal rest of people, and the current environmental humidity is great, the friction coefficient between wheels and the track is great, the train can possibly generate great noise, therefore, the traction limiting condition is considered to be met, the traction limiting is needed to be carried out on the train, so that the noise generated in the running process of the train is reduced, and the normal rest of people is further ensured.
In the example, whether the traction limiting condition is met is evaluated by combining the current system time, traction limitation is carried out when noise influences normal rest of people, and noise in the running process of a train is reduced; the travel requirement of the passengers can be met to the greatest extent on the premise that the noise does not influence normal rest of the people, so that the travel time of the passengers is reduced. Whether the traction limiting condition is met or not is evaluated by combining the current train position, traction limiting is carried out when the train passes through the residential area, and noise in the running process of the train is reduced; the traction force is not limited when the train does not pass through the residential area, so that the running speed of the train can be ensured, and the travel time of passengers is saved. And the noise condition in the running process of the train is determined based on the analysis of the current environmental humidity, and traction force limitation is carried out under the condition that the analysis determines that the noise is large, so that the noise generated in the running process of the train is reduced, and the normal rest of people is further ensured.
In one embodiment, as shown in fig. 2, step S102, that is, when the first environmental data satisfies the traction force limitation condition, determines the target limitation ratio according to the first environmental data includes:
s201: acquiring second environmental data of the train when the first environmental data meets traction limiting conditions;
S202: and determining a target limiting proportion according to the first environment data and the second environment data.
The second environmental data is collected after the index force limiting condition is determined to be met, and the second environmental data is different from the first environmental data, and specifically may be actually measured sound data for reflecting the environmental noise condition.
As an example, in step S201, after acquiring the first environmental data, the vehicle-mounted controller compares the first environmental data with a preset traction limitation condition; when the first environmental data meets traction force limiting conditions, the passing of the train is considered to have a great influence on normal life of people, for example, noise generated by the passing of the train can have a great influence on normal rest of people, and at the moment, the second environmental data of the train can be acquired through sensing equipment or other hardware equipment loaded on the train.
As an example, in step S202, after acquiring the first environmental data and the second environmental data, the vehicle-mounted controller may analyze the first environmental data and the second environmental data to determine a target limitation ratio matched with the first environmental data and the second environmental data, so as to limit the traction force of the train running based on the target limitation ratio. For example, when the target traction force of the train running normally is F1 and the target limiting proportion is Km, the target traction force F1 may be limited by using the target limiting proportion Km, the product of the target traction force F1 and the target limiting proportion is determined as a new target traction force F1 '=f1×km, and the train running is controlled based on the new target traction force F1', so as to reduce the running speed of the train, further reduce the noise generated in the running process of the train, and avoid affecting the normal life of people.
In this embodiment, when the first environmental data meets the traction force limitation condition, the second environmental data of the train needs to be acquired, so that the operand of acquiring the environmental data can be reduced, and the operation resource can be saved; according to the first environmental data and the second environmental data, the corresponding target limiting proportion is determined, so that the determined target limiting proportion not only meets the traction limiting requirement corresponding to the first environmental data, but also meets the traction limiting requirement corresponding to the second environmental data, traction limitation on the train based on the target limiting proportion is ensured, and the influence of noise generated in the running process of the train on normal life of people can be effectively reduced.
In one embodiment, as shown in fig. 3, step S202, that is, determining the target limit proportion according to the first environment data and the second environment data, includes:
s301: determining a first limiting proportion according to the first environment data;
s302: and determining a target limiting proportion according to the second environment data and the first limiting proportion.
The first limiting proportion refers to a limiting proportion determined according to the first environment data.
As an example, in step S301, the data, including, but not limited to, the current system time, the current train position, the current environmental humidity, the current environmental wind speed, etc., that may affect the normal life of people in the passing area of the train, may be obtained by the vehicle-mounted controller, and when the corresponding first limitation proportion is required to be determined according to the first environmental data, a preset mapping table or mapping curve representing the mapping relationship may be queried respectively according to at least two types of first environmental data, so as to determine the limitation proportion corresponding to each type of first environmental data; and then, comprehensively analyzing the limiting proportion corresponding to the at least two types of first environment data, including but not limited to weighting and minimum processing, so that the obtained first limiting proportion can meet the traction limiting requirement required by the at least two types of first environment data.
As an example, in step S302, after acquiring the second environmental data and the first limiting proportion, the vehicle-mounted controller may determine a correction coefficient with a numerical range between 0 and 1 according to the second environmental data, for example, may quickly determine a corresponding correction coefficient based on the second environmental data and a preset noise-correction coefficient mapping relationship; and then correcting the first limiting proportion by using the correction coefficient to obtain a corrected target limiting proportion, wherein the target limiting proportion can be the product of the first limiting proportion and the correction coefficient so as to correct the first limiting proportion by using the second environment data, so that the corrected target limiting proportion is not only related to the first environment data but also related to the second environment data, and the traction limiting requirements of different conditions can be met. Or, the vehicle-mounted controller may also analyze and determine whether the second environmental data is noise according to the collected second environmental data, and when the second environmental data is noise, determine a second limiting proportion corresponding to the second environmental data; and then comprehensively analyzing the second limit proportion and the first limit proportion, and determining a smaller value or a weighted processing result of the second limit proportion and the first limit proportion as a target limit proportion, so that the target limit proportion is related to the first environment data and the second environment data, and can meet traction force limit requirements of different situations.
In the embodiment, a first limiting proportion is determined according to the first environmental data, so that the determined first limiting proportion is matched with the current environment of the train, and the required traction limiting requirement is met; according to the second environment data and the first limit proportion, the corresponding target limit proportion is comprehensively analyzed and determined, so that the target limit proportion is not only related to the first environment data but also related to the second environment data, and the traction force limit requirements of different conditions can be met; the traction force of the train is limited based on the target limiting proportion, so that the running speed of the train can be effectively reduced, further, the noise generated in the running process of the train is reduced, and the influence on normal life of people is avoided.
In one embodiment, the first environmental data includes a current system time and a current train location;
as shown in fig. 4, step S301, that is, determining a first restriction proportion according to the first environment data, includes:
s401: determining a time limit proportion corresponding to the current system time according to the mapping relation between the current system time and the time limit proportion;
s402: determining a position limiting proportion corresponding to the current train position according to the mapping relation between the actual measured distance and the distance limiting proportion between the current train position and the residential area;
S403: the first restriction ratio is determined based on the time restriction ratio and the position restriction ratio.
The time limit proportion mapping relation is a preset mapping relation used for reflecting the mapping relation between the system time and the limit proportion.
As an example, in step S401, after acquiring the current system time, the vehicle-mounted controller may use the mapping relationship between the current system time and the preset time limit proportion, and may specifically determine the limit proportion corresponding to the current system time based on the mapping table or the mapping curve of the mapping relationship between the current system time and the characteristic time limit proportion, and determine the limit proportion corresponding to the current system time as the time limit proportion corresponding to the current system time. For example, at the current system time 21:00, the time limit proportion mapping table shown in fig. 10 is queried to determine that the corresponding time limit proportion is 50%, so as to achieve the purpose of limiting the traction force in the preset rest time period.
The distance limiting proportion mapping relation is a preset mapping relation used for reflecting the mapping relation between different distances and limiting proportions.
As an example, in step S402, after acquiring the current train position, the vehicle-mounted controller may calculate, in real time, an actual measurement distance between the current train position and the residential area, where the actual measurement distance may be a distance between the current train position and a periphery of the residential area near one side of the train, and may be understood as a minimum distance between the current train position and the residential area. Then, the vehicle-mounted controller can determine a limiting proportion corresponding to the measured distance based on the measured distance and a preset distance limiting proportion mapping relation, specifically can determine a position limiting proportion corresponding to the current train position based on a mapping table or a mapping curve of the distance limiting proportion mapping relation represented by the measured distance query. Generally, the smaller the measured distance is, the larger the influence of the train passing on the normal rest of people in the residential area is, so that the smaller the corresponding position limiting proportion is, and the influence of the noise generated by the train passing on the normal life of people in the residential area is reduced as much as possible.
As an example, in step S403, after determining the time limit proportion and the position limit proportion, the in-vehicle controller may perform comprehensive analysis on the time limit proportion and the position limit proportion to determine the first limit proportion. For example, the time limit proportion and the position limit proportion may be subjected to weighting processing, and the result of the weighting processing may be determined as the first limit proportion; the time limit proportion and the position limit proportion can be compared, and the smaller value of the time limit proportion and the position limit proportion is determined to be the first limit proportion, so that the determined first limit proportion can simultaneously meet the traction force limit requirement required by the current system time and the current train position, and the influence of noise generated after the traction force limit of the train on the rest of people in a residential area is reduced.
In this embodiment, according to the current system time and the current train position, the table is respectively checked, the time limit proportion and the position limit proportion are rapidly determined, the time limit proportion and the position limit proportion are comprehensively analyzed, and the first limit proportion is determined, so that the first limit proportion can simultaneously meet the traction force limit requirements required by the current system time and the current train position, and the influence of noise generated after the traction force limit of the train on the rest of people in the residential area is reduced.
In one embodiment, as shown in fig. 5, step S301, that is, determining a first restriction ratio according to the first environment data, includes:
s501: determining a time limit proportion corresponding to the current system time according to the mapping relation between the current system time and the time limit proportion;
s502: determining a position limiting proportion corresponding to the current train position according to the mapping relation between the actual measured distance and the distance limiting proportion between the current train position and the residential area;
s503: determining a humidity limiting proportion corresponding to the current ambient humidity according to the mapping relation between the current ambient humidity and the humidity limiting proportion;
s504: the first limiting ratio is determined based on the time limiting ratio, the position limiting ratio, and the humidity limiting ratio.
Step S501 is the same as step S401, step S502 is the same as step S402, and the description is omitted herein to avoid repetition.
The mapping relation of the humidity limiting proportion is preset and used for reflecting the mapping relation between different environmental humidity and limiting proportion. Generally, the greater the ambient humidity, the greater the coefficient of friction between the wheels and the track, the greater the noise generated by the train, and the smaller the limit ratio determined in order to reduce the noise effect.
As an example, in step S503, after acquiring the current ambient humidity, the vehicle-mounted controller may utilize the mapping relationship between the current ambient humidity and the preset humidity limit proportion, and specifically may determine the limit proportion corresponding to the current ambient humidity based on the mapping table and the mapping curve of the mapping relationship between the current ambient humidity and the current ambient humidity, and determine the limit proportion as the humidity limit proportion corresponding to the current ambient humidity. For example, when the current ambient humidity is 15%, the humidity limit proportion mapping table shown in fig. 11 is queried to determine that the corresponding humidity limit proportion is 90%, so as to achieve the purpose of limiting the traction according to the current ambient humidity.
As an example, in step S504, after determining the time limit proportion, the position limit proportion, and the humidity limit proportion, the vehicle-mounted controller may perform comprehensive analysis on the time limit proportion, the position limit proportion, and the humidity limit proportion, to determine the first limit proportion. For example, the time limit proportion, the position limit proportion, and the humidity limit proportion may be weighted, and the weighted result may be determined as the first limit proportion; or comparing the time limit proportion, the position limit proportion and the humidity limit proportion, and determining the minimum value of the time limit proportion, the position limit proportion and the humidity limit proportion as a first limit proportion, so that the determined first limit proportion can simultaneously meet the traction force limit requirements required by the current system time, the current train position and the current environment humidity, and the influence of noise generated after the traction force limit of the train on the rest of people in a residential area is reduced.
In the embodiment, table lookup is performed according to the current system time, the current train position and the current environment humidity respectively, and the time limit proportion, the position limit proportion and the humidity limit proportion are rapidly determined; and then comprehensively analyzing the time limit proportion, the position limit proportion and the humidity limit proportion, and determining a first limit proportion, so that the first limit proportion can simultaneously meet the traction force limit requirements required by the current system time, the current train position and the current environment humidity, and the influence of noise generated after the traction force limit of the train on the rest of people in a residential area is reduced.
In one embodiment, as shown in fig. 6, step S302, that is, determining the target restriction ratio according to the second environment data and the first restriction ratio, includes:
s601: determining a target correction coefficient according to the second environmental data;
s602: and correcting the first limiting proportion by adopting a target correction coefficient, and determining the target limiting proportion.
As an example, in step S601, after acquiring the second environmental data, the vehicle-mounted controller may query a preset mapping table or mapping function according to the second environmental data, and determine a target correction coefficient corresponding to the second environmental data. The target correction factor is understood here to be a correction factor that matches the second environmental data in a preset mapping table or mapping function.
As an example, in step S601, after acquiring the target correction coefficient, the in-vehicle controller may correct the first limitation ratio determined by the first environment data using the target correction coefficient to determine a corrected target limitation ratio. In this example, the product of the target correction coefficient and the first restriction proportion may be determined as the target restriction proportion.
In this embodiment, the corresponding target correction coefficient is determined according to the second environmental data, then the first limitation proportion is corrected by the target correction coefficient, and the target limitation proportion is determined, so as to achieve the purpose of correcting the first limitation proportion determined by the first environmental data by using the second environmental data, so that the first limitation proportion can meet the traction force limitation requirements corresponding to the first environmental data and the second environmental data, and the influence of noise generated after the traction force limitation of the train on the rest of people in the residential area is reduced.
In one embodiment, as shown in fig. 7, step S302, that is, determining the target restriction ratio according to the second environment data and the first restriction ratio, includes:
s701: determining a second limiting proportion corresponding to the second environmental data according to the second environmental data;
s702: the target restriction ratio is determined based on the second restriction ratio and the first restriction ratio.
As an example, in step S701, the second environmental data obtained by the vehicle-mounted controller includes at least one noise feature of the measured sound loudness and the measured sound frequency, and the feature limitation ratio corresponding to the at least one noise feature may be determined based on the at least one noise feature by looking up a table or querying a preset mapping function, respectively; and comprehensively analyzing according to the characteristic limiting proportion corresponding to the at least one noise characteristic, and determining a corresponding second limiting proportion corresponding to the second environment data so that the determined second limiting proportion meets traction force limiting requirements corresponding to the at least one noise characteristic.
As an example, in step S702, after acquiring the second limit proportion and the first limit proportion, the vehicle-mounted controller may perform comprehensive analysis on the second limit proportion and the first limit proportion to determine the target limit proportion. For example, the second limiting proportion and the first limiting proportion may be weighted, the weighted result may be determined as a target limiting proportion, or the second limiting proportion and the first limiting proportion may be compared, and a smaller value of the second limiting proportion and the first limiting proportion may be determined as a target limiting proportion, so that the determined target limiting proportion may meet traction force limiting requirements corresponding to different sound data and different environment data.
In this embodiment, the corresponding second limiting proportion is determined according to the second environmental data, and then the second limiting proportion and the first limiting proportion are comprehensively analyzed to determine the target limiting proportion, so that the target limiting proportion can simultaneously meet the traction limiting requirements required by the second environmental data and the first environmental data, and the influence of noise generated after the traction limitation of the train on the rest of people in the residential area is reduced.
In one embodiment, the second environmental data includes measured sound loudness;
step S701, namely determining a second limitation ratio corresponding to the second environmental data according to the second environmental data, includes:
and determining a loudness limiting proportion corresponding to the measured sound loudness according to the mapping relation between the measured sound loudness and the loudness limiting proportion, and determining the loudness limiting proportion as a second limiting proportion corresponding to the second environment data.
The loudness limiting proportion mapping relation is a preset mapping relation used for reflecting the mapping relation between the loudness of the sound and the limiting proportion. Generally, when the sound loudness is greater than a preset loudness threshold (such as 50 dB), the greater the sound loudness is, the greater the interference of the sound loudness to normal rest of people is, the smaller the proportion of traction limitation is required, so that the running speed of the train is reduced after the traction limitation is carried out, the noise generated in the running process of the train is further reduced, and the normal rest of people is ensured.
As an example, when the obtained second environmental data includes the measured sound loudness, the vehicle-mounted controller may determine, according to the measured sound loudness and a preset loudness limitation proportion mapping relationship, a loudness limitation proportion corresponding to the measured sound loudness according to a mapping table or a mapping curve of the measured sound loudness query specific loudness limitation proportion mapping relationship. In this example, when the measured sound loudness is not greater than the preset loudness threshold 55dB in the noise interference condition, the measured sound loudness collected in real time can be considered to be smaller, and interference to normal rest of people can not be caused, and at this time, the default limiting proportion 1 can be determined as the loudness limiting proportion, so that the target traction force of normal running of the train can not be limited. Conversely, when the measured sound loudness is greater than the preset loudness threshold value 55dB in the noise interference condition, the loudness limitation proportion corresponding to the measured sound loudness can be determined based on the measured sound loudness inquiry loudness limitation proportion mapping relation, for example, when the measured sound loudness is 55dB-65dB, the look-up table can determine that the loudness limitation proportion is 0.9; when the measured sound loudness is 65-75dB, the table look-up can determine that the loudness limiting proportion is 0.8.
In this example, when the received second environmental data only includes the noise feature of the measured sound loudness, the vehicle-mounted controller may determine the loudness limitation proportion determined based on the look-up table of the second environmental data as the target limitation proportion, so that the finally determined target limitation proportion is related to the measured sound loudness acquired in real time, and meets the traction limitation requirement corresponding to the measured sound loudness.
In one embodiment, the second environmental data includes measured sound frequencies;
step S701, namely determining a second limitation ratio corresponding to the second environmental data according to the second environmental data, includes:
according to the mapping relation between the actually measured sound frequency and the frequency limitation proportion, determining the frequency limitation proportion corresponding to the actually measured sound frequency, and determining the frequency limitation proportion as a second limitation proportion corresponding to second environment data.
The frequency limit proportion mapping relation is a preset mapping relation used for reflecting the mapping relation between the sound frequency and the limit proportion. Generally, when the actually measured sound frequency is smaller than a preset frequency threshold (such as 500 Hz), the smaller the sound frequency is, the more sharp the noise is, the larger the interference of the actually measured sound frequency to normal rest of people is, the smaller the proportion of traction force limitation is needed, so that the running speed of the train is reduced after the traction force limitation, the noise generated in the running process of the train is further reduced, and the normal rest of people is ensured.
As an example, when the obtained second environmental data includes the measured sound frequency, the vehicle-mounted controller may determine, according to the measured sound frequency and a preset frequency limitation ratio mapping relationship, a frequency limitation ratio corresponding to the measured sound frequency according to a mapping table or a mapping curve of the measured sound frequency query and characteristic frequency limitation ratio mapping relationship. In this example, when the measured sound frequency is greater than the preset frequency threshold 500Hz in the noise interference condition, the measured sound frequency collected in real time can be considered to be smaller, and no interference is caused to normal rest of people, at this time, the default limiting proportion 1 can be determined as the frequency limiting proportion, so that the target traction force of the normal running of the train can not be limited. Conversely, when the measured sound frequency is not greater than the preset frequency threshold 55dB in the noise interference condition, the frequency limitation proportion corresponding to the measured sound frequency can be determined based on the frequency limitation proportion mapping relation of the measured sound frequency, for example, when the measured sound frequency is 450Hz-500Hz, the frequency limitation proportion can be determined to be 0.9 by table lookup; when the measured sound frequency is 400Hz-450Hz, the table look-up can determine that the frequency limit ratio is 0.8.
In this example, when the received second environmental data only includes the noise feature of the measured sound frequency, the vehicle-mounted controller may determine the frequency limitation ratio determined based on the table look-up of the second environmental data as the target limitation ratio, so that the finally determined target limitation ratio is related to the measured sound frequency acquired in real time, and meets the traction limitation requirement corresponding to the measured sound frequency.
In one embodiment, the second environmental data includes measured sound loudness and measured sound frequency;
as shown in fig. 8, step S701, that is, determining, according to the second environment data, a second limitation ratio corresponding to the second environment data includes:
s801: according to the mapping relation between the actual measured sound loudness and the loudness limiting proportion, determining the loudness limiting proportion corresponding to the actual measured sound loudness;
s802: determining the frequency limiting proportion corresponding to the measured sound frequency according to the mapping relation between the measured sound frequency and the frequency limiting proportion;
s803: and determining a second limiting proportion corresponding to the second environment data according to the loudness limiting proportion and the frequency limiting proportion.
Step S802 and step S803 are the same as the above embodiments, and are described herein for brevity.
As an example, in step S803, after acquiring the loudness limiting proportion and the frequency limiting proportion, the in-vehicle controller may perform comprehensive analysis on the loudness limiting proportion and the frequency limiting proportion to determine the second limiting proportion. For example, the loudness limitation proportion and the frequency limitation proportion may be weighted, and the result of the weighting process is determined as a second limitation proportion; or, the loudness limiting proportion and the frequency limiting proportion can be compared, and the smaller value of the loudness limiting proportion and the frequency limiting proportion is determined as a second limiting proportion, so that the determined second limiting proportion can simultaneously meet the traction limiting requirements required by the actual measured sound loudness and the actual measured sound frequency, and the influence of noise generated after the traction limitation of the train on the rest of people in the residential area is reduced.
In this embodiment, according to the practical sound loudness and the practical sound frequency, the loudness limiting proportion and the frequency limiting proportion can be rapidly determined by looking up a table respectively; and comprehensively analyzing the loudness limiting proportion and the frequency limiting proportion, so that the second limiting proportion determined by comprehensive analysis can simultaneously meet the traction limiting requirements required by the measured sound loudness and the measured sound frequency, and the influence of noise generated after the traction limitation of the train on the rest of people in the residential area is reduced.
In an embodiment, as shown in fig. 9, after step S201, that is, after acquiring the second environmental data of the train, the train control method further includes:
s901: judging whether the second environmental data meets noise interference conditions or not;
s902: if the second environmental data meets the noise interference condition, determining a target limiting proportion according to the second environmental data and the first limiting proportion;
s903: and if the second environment data does not meet the noise interference condition, determining the first limiting proportion as a target limiting proportion.
The noise interference condition is a preset problem of evaluating whether sound data can cause interference to life of people.
As an example, in step S901, after acquiring the second environmental data of the train, the vehicle-mounted controller needs to compare the second environmental data with a preset noise interference condition, so as to determine whether the second environmental data will interfere with normal life of people according to the comparison result.
As an example, in step S902, when the second environmental data meets the noise interference condition, the vehicle-mounted controller may determine that the second environmental data may cause interference to normal life of the person, and at this time, traction limitation needs to be performed in combination with the second environmental data, so that determining the target limitation ratio according to the second environmental data and the first limitation ratio may be performed, that is, step S302 is performed.
As an example, in step S903, when the second environmental data does not meet the noise interference condition, the vehicle-mounted controller may determine that the second environmental data does not interfere with the normal life of the person, and at this time, the vehicle-mounted controller may directly determine the first limitation ratio determined according to the first environmental data as the target limitation ratio without performing traction limitation in combination with the second environmental data.
In this embodiment, according to whether the second environmental data meets the noise interference condition, it is determined whether the traction limitation needs to be performed in combination with the second environmental data, so as to ensure that the finally determined target limitation proportion meets different traction limitation requirements.
In an embodiment, the second environmental data comprises measured sound loudness and/or measured sound frequency;
the noise disturbance condition is that the measured sound loudness is greater than a preset loudness threshold and/or the measured sound frequency is less than a preset frequency threshold.
The measured sound loudness is the loudness of the sound measured in real time. The preset loudness threshold is a preset threshold for evaluating whether the loudness meets noise criteria, and may be set to 55dB, for example. The measured sound frequency is the frequency of the noise measured in real time. The preset frequency threshold is a threshold set in advance for evaluating whether the frequency reaches a noise standard that is considered to affect the life of a person. Generally, a sound having a frequency between 20-500Hz is determined as a low frequency noise in the human ear range, i.e., an irregular sound emitted by vibrating 20-500 times in 1 second is called a low frequency noise, which affects normal rest of people, and thus 500Hz may be determined as a preset frequency threshold.
As an example, the second environmental data obtained by the vehicle-mounted controller includes an actual measurement sound loudness, the actual measurement sound loudness may be compared with a preset loudness threshold, if the actual measurement sound loudness is greater than the preset loudness threshold, the actual measurement sound loudness collected in real time may be determined to be greater, and interference is caused to normal rest of people, so that it may be determined that the second environmental data satisfies the noise interference condition.
As an example, the second environmental data obtained by the vehicle-mounted controller includes an actual measurement sound frequency, the loudness of the actual measurement sound may be compared with a preset frequency threshold, and if the actual measurement sound frequency is smaller than the preset frequency threshold, the actual measurement sound frequency collected in real time may be considered to cause greater interference to normal rest of people, so that it may be determined that the actual measurement sound frequency satisfies the noise interference condition.
As an example, when the second environmental data obtained by the vehicle-mounted controller includes the measured sound loudness and the measured sound frequency, if the measured sound loudness is greater than the preset loudness threshold and the measured sound frequency is less than the preset frequency threshold, the second environmental data collected in real time may be considered to cause interference to normal rest of people, so that it may be determined that the second environmental data satisfies the noise interference condition.
In an embodiment, the first environmental data is environmental data collected during the running of the train, and/or the second environmental data is environmental data collected during the running of the train.
As an example, the first environmental data may be environmental data collected during a train running process, or the second environmental data may be environmental data collected during a train running process, or both the first environmental data and the second environmental data may be environmental data collected during a train running process, so that instantaneity of the first environmental data and/or the second environmental data collected during a train control process may be ensured, so that instantaneity of traction limitation is performed based on the first environmental data and the second environmental data.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
In an embodiment, a vehicle-mounted controller is provided, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor executes the computer program to implement the method for controlling a train in the above embodiment, for example, S101-S103 shown in fig. 1, or S2-S9, and the repetition is avoided.
In an embodiment, a computer readable storage medium is provided, and a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the method for controlling a train in the above embodiment is implemented, for example, S101-S103 shown in fig. 1, or S2-S9, which are not repeated herein.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
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 technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (18)
1. A train control method, comprising:
acquiring first environmental data of a train, wherein the first environmental data comprises current system time and current train position;
When the first environmental data meets traction force limiting conditions, determining a target limiting proportion according to the first environmental data, wherein the traction force limiting conditions are that the current system time is in a preset rest time period and the current train position is in a residential area;
and limiting the target traction force of the train based on the target limiting proportion.
2. The train control method according to claim 1, wherein after the first environmental data of the train is acquired, the train control method further comprises:
and controlling the running of the train according to the target traction force of the train when the first environmental data does not meet the traction force limiting condition.
3. The train control method of claim 1, wherein the first environmental data further comprises a current environmental humidity;
the traction limiting condition is that the current system time is in a preset rest time period, the current train position is in a residential area, and the current environmental humidity is larger than a preset humidity threshold.
4. The train control method according to claim 1, wherein the determining a target limit ratio based on the first environmental data when the first environmental data satisfies a traction force limit condition includes:
Acquiring second environmental data of the train when the first environmental data meets traction limiting conditions;
and determining a target limiting proportion according to the first environment data and the second environment data.
5. The train control method of claim 4, wherein determining a target limit ratio based on the first environmental data and the second environmental data comprises:
determining a first limiting proportion corresponding to the first environmental data according to the first environmental data;
and determining a target limiting proportion according to the second environment data and the first limiting proportion.
6. The train control method according to claim 5, wherein the first environmental data includes a current system time and a current train position;
the determining, according to the first environmental data, a first limitation proportion corresponding to the first environmental data includes:
determining a time limit proportion corresponding to the current system time according to the mapping relation between the current system time and the time limit proportion;
determining a position limiting proportion corresponding to the current train position according to the mapping relation between the actual measured distance and the distance limiting proportion between the current train position and the residential area;
And determining a first limiting proportion according to the time limiting proportion and the position limiting proportion.
7. The train control method according to claim 5, wherein the first environmental data includes a current system time, a current train position, and a current environmental humidity;
the determining, according to the first environmental data, a first limitation proportion corresponding to the first environmental data includes:
determining a time limit proportion corresponding to the current system time according to the mapping relation between the current system time and the time limit proportion;
determining a position limiting proportion corresponding to the current train position according to the mapping relation between the actual measured distance and the distance limiting proportion between the current train position and the residential area;
determining a humidity limiting proportion corresponding to the current environment humidity according to the mapping relation between the current environment humidity and the humidity limiting proportion;
and determining a first limiting proportion according to the time limiting proportion, the position limiting proportion and the humidity limiting proportion.
8. The train control method according to claim 5, wherein the determining a target limit ratio based on the second environmental data and the first limit ratio includes:
Determining a target correction coefficient according to the second environmental data;
and correcting the first limiting proportion by adopting the target correction coefficient, and determining a target limiting proportion.
9. The train control method according to claim 5, wherein the determining a target limit ratio based on the second environmental data and the first limit ratio includes:
determining a second limiting proportion corresponding to the second environment data according to the second environment data;
and determining a target limiting proportion according to the second limiting proportion and the first limiting proportion.
10. The train control method of claim 9 wherein the second environmental data includes measured loudness of sound;
the determining, according to the second environmental data, a second limiting proportion corresponding to the second environmental data includes:
and determining a loudness limiting proportion corresponding to the measured sound loudness according to the mapping relation between the measured sound loudness and the loudness limiting proportion, and determining the loudness limiting proportion as a second limiting proportion corresponding to the second environment data.
11. The train control method of claim 9 wherein the second environmental data includes measured sound frequencies;
The determining, according to the second environmental data, a second limiting proportion corresponding to the second environmental data includes:
and determining a frequency limit proportion corresponding to the measured sound frequency according to the mapping relation between the measured sound frequency and the frequency limit proportion, and determining the frequency limit proportion as a second limit proportion corresponding to the second environment data.
12. The train control method of claim 9 wherein the second environmental data includes measured sound loudness and measured sound frequency;
the determining a second limiting proportion according to the second environment data comprises the following steps:
determining a loudness limiting proportion corresponding to the measured sound loudness according to the mapping relation between the measured sound loudness and the loudness limiting proportion;
determining a frequency limit proportion corresponding to the measured sound frequency according to the mapping relation between the measured sound frequency and the frequency limit proportion;
and determining a second limiting proportion corresponding to the second environment data according to the loudness limiting proportion and the frequency limiting proportion.
13. The train control method according to claim 4, wherein after acquiring the second environmental data of the train when the first environmental data satisfies a traction force limitation condition, the train control method further comprises:
Judging whether the second environmental data meets a noise interference condition or not;
if the second environmental data meets the noise interference condition, executing the step of determining a target limiting proportion according to the first environmental data and the second environmental data;
and if the second environmental data does not meet the noise interference condition, executing the step of determining a target limiting proportion according to the first environmental data.
14. The train control method according to claim 13, wherein the second environmental data includes measured sound loudness and/or measured sound frequency;
the noise interference condition is that the measured sound loudness is greater than a preset loudness threshold and/or the measured sound frequency is less than a preset frequency threshold.
15. The train control method according to claim 4, wherein the first environmental data is environmental data collected during a train running process, and/or the second environmental data is environmental data collected during a train running process.
16. An on-board controller comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the train control method according to any one of claims 1 to 15 when executing the computer program.
17. A train comprising the on-board controller of claim 16.
18. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the train control method according to any one of claims 1 to 15.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310981964.8A CN116714611B (en) | 2023-08-07 | 2023-08-07 | Train control method, vehicle-mounted controller, train and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310981964.8A CN116714611B (en) | 2023-08-07 | 2023-08-07 | Train control method, vehicle-mounted controller, train and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116714611A CN116714611A (en) | 2023-09-08 |
| CN116714611B true CN116714611B (en) | 2023-11-14 |
Family
ID=87871903
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310981964.8A Active CN116714611B (en) | 2023-08-07 | 2023-08-07 | Train control method, vehicle-mounted controller, train and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116714611B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11355082A (en) * | 1998-06-04 | 1999-12-24 | Yahata Denki Sangyo Kk | Noise followup control announcing device for railroad vehicle |
| WO2012098024A1 (en) * | 2011-01-17 | 2012-07-26 | Siemens Aktiengesellschaft | Method for operating a track-bound vehicle |
| CN103707904A (en) * | 2013-12-05 | 2014-04-09 | 北京交控科技有限公司 | Temporary speed limiting method and temporary speed limiting system in urban rail transit CBTC (communication based train control system) mode |
| KR20160146111A (en) * | 2015-06-11 | 2016-12-21 | 주식회사 피지오닉스 | Self-recognition Monitoring system of Interlayer noise and Interior Noise |
| CN116238549A (en) * | 2023-04-27 | 2023-06-09 | 湖南工业大学 | Adhesion control system of electric locomotive |
-
2023
- 2023-08-07 CN CN202310981964.8A patent/CN116714611B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11355082A (en) * | 1998-06-04 | 1999-12-24 | Yahata Denki Sangyo Kk | Noise followup control announcing device for railroad vehicle |
| WO2012098024A1 (en) * | 2011-01-17 | 2012-07-26 | Siemens Aktiengesellschaft | Method for operating a track-bound vehicle |
| CN103707904A (en) * | 2013-12-05 | 2014-04-09 | 北京交控科技有限公司 | Temporary speed limiting method and temporary speed limiting system in urban rail transit CBTC (communication based train control system) mode |
| KR20160146111A (en) * | 2015-06-11 | 2016-12-21 | 주식회사 피지오닉스 | Self-recognition Monitoring system of Interlayer noise and Interior Noise |
| CN116238549A (en) * | 2023-04-27 | 2023-06-09 | 湖南工业大学 | Adhesion control system of electric locomotive |
Non-Patent Citations (4)
| Title |
|---|
| 地铁列车运行时间仿真分析;陈喜红, 李敏玲, 柳晓峰;电力机车与城轨车辆(04);正文第1.6.3节 * |
| 提速及高速列车影响环境噪声的评价分析及噪声防治;王伯福;中国铁道科学(01);全文 * |
| 王伯福.提速及高速列车影响环境噪声的评价分析及噪声防治.中国铁道科学.1998,(01),全文. * |
| 陈喜红,李敏玲,柳晓峰.地铁列车运行时间仿真分析.电力机车与城轨车辆.2003,(04),正文第1.6.3节. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116714611A (en) | 2023-09-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20200406911A1 (en) | Self-Driving Safety Evaluation Method, Apparatus, and System | |
| CN106627579B (en) | Coordination testing in vehicle fleet | |
| JP5596691B2 (en) | Operation method of driving evaluation system | |
| US20190158581A1 (en) | System and method for balancing processing of sensor-based data and signals in a vehicle | |
| KR20180077623A (en) | Hybrid vehicle and method of predicting driving pattern | |
| WO2014196115A1 (en) | Method for presenting result of determination of whether vehicle is stopped, device for determining whether vehicle is stopped, and system for determining whether vehicle is stopped | |
| Hu et al. | Autonomous vehicle’s impact on traffic: Empirical evidence from waymo open dataset and implications from modelling | |
| CN109800984B (en) | Driving level evaluation method, driving level evaluation device, computer device, and storage medium | |
| US8144032B2 (en) | Method of checking the quality of traffic disturbance reporting processes | |
| US10571290B2 (en) | Method and system for vehicle speed profile generation | |
| US20230164615A1 (en) | Systems and methods for assessing vehicle data transmission capabilities | |
| CN111612378A (en) | Potential collision risk prediction method and device and computer equipment | |
| Schulz et al. | Future role of cost–benefit analysis in intelligent transport system‐research | |
| CN116714611B (en) | Train control method, vehicle-mounted controller, train and storage medium | |
| US11428680B2 (en) | Train emission compliance system | |
| DE102020104301A1 (en) | Method and control unit for operating a noise suppression unit of a vehicle | |
| Alam et al. | Validation of the road traffic noise prediction model rls-90 in an urban area | |
| US20220292521A1 (en) | Computer-Assisted Method for Generating Training Data for a Neural Network for Predicting a Concentration of Pollutants | |
| CN110458475B (en) | Urban rail transit overhead line planning method and device based on acoustic environment | |
| CN115204755B (en) | Service area access rate measuring method and device, electronic equipment and readable storage medium | |
| CN113609592B (en) | Method, system and related components for fast prediction of aerodynamic noise of long marshalling train | |
| US20230031251A1 (en) | Vehicle lateral dynamics estimation using telemetry data | |
| CN114572180A (en) | Vehicle brake diagnosis method, device, electronic apparatus, and medium | |
| CN112254804A (en) | Sound source judgment method and device, computer equipment and storage medium | |
| Jedh et al. | Improvement and Evaluation of Resilience of Adaptive Cruise Control Against Spoofing Attacks Using Intrusion Detection System |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |