CN113715880A - High-speed maglev train auxiliary driving method, system and equipment based on battery model calculation - Google Patents
High-speed maglev train auxiliary driving method, system and equipment based on battery model calculation Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/04—Automatic systems, e.g. controlled by train; Change-over to manual control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L1/00—Supplying electric power to auxiliary equipment of vehicles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
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- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
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Abstract
The invention provides a high-speed maglev train auxiliary driving method based on battery model calculation, which analyzes the electric quantity of a storage battery according to a new scheduling timetable and a storage battery model after judging that a train is in an abnormal parking state, instead of charging the storage battery blindly, demonstrates the scheme and feasibility of continuous driving, charges when the electric quantity is insufficient, switches to a manual driving mode by taking the storage battery as a core after judging that the train can be continuously driven, effectively guides an auxiliary driver to drive until the train reaches the next auxiliary parking area, and can remotely check auxiliary driving data, thereby effectively reducing the train test maintenance cost.
Description
Technical Field
The invention relates to the technical field of train auxiliary driving, in particular to a method, a system and equipment for high-speed maglev train auxiliary driving based on battery model calculation.
Background
The high-speed maglev train adopts a maglev technology, the speed per hour is more than 400km easily due to no wheel-rail friction, the development direction of the rail transit in the future is formed, in order to ensure that the high-speed maglev train runs at high speed and safely, the running plan is adjusted at any time according to the conditions of vehicles and lines in running, various emergencies in running are processed quickly, and the running control must finish various functions, particularly safety related functions, correctly, so that in the system design stage, a scheme for fully demonstrating the transportation organization and recovery after system failure is necessary.
The vehicle-mounted storage battery is one of important devices for providing energy for suspension and guide equipment when a high-speed maglev train runs, the high-speed maglev train can stop in a current auxiliary parking area after triggering emergency stop due to faults, protection and the like in the running process, the train can run in a maintenance running mode when running again in order to guarantee safety, the electric quantity of the vehicle-mounted storage battery is changed to be crucial when the high-speed maglev train is maintained and run between the auxiliary parking areas, if the distance between the auxiliary parking areas is too far away, the vehicle-mounted storage battery is insufficient in electric quantity to cause a vehicle-falling accident, therefore, before the maintenance running, the storage battery of the train is required to have sufficient electric quantity to ensure that the train can run smoothly to the next auxiliary parking area, the prior art either increases the capacity of the storage battery or directly charges the storage battery before the maintenance running, in any way, the test and maintenance cost of the train is increased, so that it is necessary to develop a method for effectively guiding the auxiliary driving of the train by taking a storage battery as a core after the emergency stop of the train.
Disclosure of Invention
The invention aims to provide a method, a system and equipment for assisting in driving a high-speed maglev train based on battery model calculation, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a high-speed maglev train auxiliary driving method based on battery model calculation comprises the following steps:
s1, constructing a running organization capability test platform, and sending train running data to the running organization capability test platform by a vehicle-mounted running control system (VSC);
s2, the operation organization capability test platform carries out simulation synchronization according to the received data, establishes a storage battery model and a traction energy-saving model, and analyzes the data models of the vehicle-mounted storage battery and the traction energy-saving module in the operation process of the train in real time according to the vehicle state information;
s3, judging the running state of the train by a vehicle-mounted running control system (VSC) according to the analysis result, starting an auxiliary driving module in the running organization capability test platform and importing a new scheduling schedule when judging that the train is in an abnormal parking state;
s4, the operation organization ability test platform analyzes the electric quantity according to the new scheduling schedule and the storage battery model, analyzes the scheme and the feasibility of the continuous driving when the train is switched to the manual driving mode, and judges whether the continuous driving is possible;
s5, when the electric quantity is low and the vehicle cannot run, calculating the charging time, when the vehicle can run continuously, the auxiliary driving module switches to a manual driving mode by analyzing the relation between the storage battery module and the vehicle, the speed, the energy consumption and other models, and guides an auxiliary driver to drive to the next auxiliary parking area;
and S6, operating the organization capability test platform to acquire auxiliary driving information, packaging the data information, performing data transmission through network communication, and sending the data information to an android terminal for display.
Preferably, the train operation data in step S1 includes clock information, speed information, and IPC status.
Preferably, the building of the battery model in step S2 specifically includes the following steps:
s201, designing a discharge model according to the clock interval in the clock information;
s202, designing a charging model according to the speed information;
and S203, designing battery capacity management according to the designed charge and discharge model.
Preferably, the specific step of analyzing the electric quantity of the battery model in step S4 is:
s401, constructing an energy balance equation of the high-speed magnetic-levitation train in the maintenance operation process:
Wlig+Wbat＝Wxf+Wdx+Wsb
in the formula, WligIs the output energy of the on-board linear generator, WbatFor the consumption of energy of on-board batteries, WxfFor the consumption of energy in the levitation apparatus, WdxAnd WsbThe consumed energy of the guiding equipment is the consumed energy of the vehicle-mounted electrical equipment;
s402, calculating the output energy of the vehicle-mounted linear generator according to the running speed of the train, wherein the calculation formula is as follows:
in the formula, a, b and c are coefficients, twhThe train running time is;
s403, calculating the electric quantity consumed by the vehicle-mounted storage battery, wherein the calculation formula is as follows:
in the formula, QbatFor the consumption of electric power, P, of the on-board batteryxfFor the consumption of power by levitating apparatus, PdxConsumption of power for steering devices, PsbFor power consumption of vehicle-mounted electrical equipment, UbatIs the voltage of an on-board battery, where Pxf、PdxAnd PsbObtaining a numerical value through a real vehicle test;
s404, the consumed electric quantity Q of the vehicle-mounted storage battery is calculatedbatAnd comparing the electric quantity with the electric quantity of the actual vehicle-mounted storage battery, and judging the scheme and feasibility of continuous driving.
Preferably, the train running time twhCalculating according to the train maintenance operation speed curve, the distance from the next auxiliary parking area and the train schedule, wherein the calculation process of the maintenance operation speed comprises the steps of firstly inputting the maintenance operation speed of the train and the distance between the auxiliary parking areasAnd finally, judging whether the minimum distance is smaller than the distance between the auxiliary parking areas, if so, outputting a maintenance operation vehicle speed curve, and if not, outputting a limit vehicle speed.
Preferably, the communication mode between the running organization capability test platform and the android terminal is UDP communication transmission.
Preferably, the android terminal is internally provided with a user login function, no data information exists in a normal state, and only when the vehicle is abnormally parked, data information for guiding a trainee to assist driving is available after the vehicle is logged in an appointed account.
The invention also provides a high-speed maglev train auxiliary driving system based on battery model calculation, which comprises:
the simulation construction testing module is used for constructing an operation organization capability testing platform and enabling a vehicle-mounted driving control system (VSC) to send train operation data to the operation organization capability testing platform;
the running organization capability test module is used for controlling the running organization capability test platform to carry out simulation synchronization according to the received data, establishing a storage battery model and a traction energy-saving model, and analyzing a vehicle-mounted storage battery and a traction energy-saving module data model in the running process of the train in real time according to the vehicle state information;
the train state judgment module is used for enabling a vehicle-mounted running control system (VSC) to judge the running state of the train according to the analysis result, starting an auxiliary driving module in the running organization capability test platform when the train is judged to be in an abnormal parking state, and importing a new scheduling timetable;
the storage battery electric quantity analysis module is used for enabling the operation organization capability test platform to analyze the electric quantity of the operation organization capability test platform according to the new scheduling timetable and the storage battery model, analyzing the scheme and feasibility of continuous running when the train is switched to the manual driving mode, and judging whether the train can be continuously run or not;
the driving guidance auxiliary module is used for calculating charging time when the vehicle cannot run due to low electric quantity, and when the vehicle can continue to run, the auxiliary driving module is switched to a manual driving mode by analyzing the relation between the storage battery module and the models of the vehicle, speed, energy consumption and the like, and guides an auxiliary driver to drive to a next auxiliary parking area; and
and the data transmission module is used for enabling the running organization capability test platform to acquire the auxiliary driving information, packaging the data information, transmitting the data information through network communication, and sending the data information to the android terminal for displaying.
The invention also provides a high-speed maglev train auxiliary driving device based on battery model calculation, wherein the auxiliary driving device comprises a memory, a processor, a bus, a communication module and an auxiliary driving program which is stored on the memory and runs on the processor, the memory, the processor, the communication module and a vehicle-mounted running control system (VSC) in the train are electrically connected through the bus, and the auxiliary driving program is configured to realize the steps of the auxiliary driving method.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, after the train is judged to be in an abnormal parking state, the electric quantity of the storage battery is analyzed according to the new scheduling timetable and the storage battery model, the storage battery is not charged blindly, but a scheme and feasibility of continuous driving are demonstrated, the charging is carried out when the electric quantity is insufficient, and after the train can be judged to be continuously driven, the train is switched to a manual driving mode by taking the storage battery as a core, an auxiliary driver is effectively guided to drive until the train reaches the next auxiliary parking area, and the auxiliary driving data can be remotely checked, so that the train testing and maintenance cost is effectively reduced.
Drawings
Fig. 1 is a schematic flow chart of an auxiliary driving method for a high-speed magnetic-levitation train according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an auxiliary driving system of a high-speed magnetic-levitation train according to an embodiment of the present invention;
FIG. 3 is a schematic view of the operation flow of the vehicle-mounted operation control system according to the embodiment of the invention;
FIG. 4 is a schematic flow chart of the operation of the organizational ability test platform according to the embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a flow of analyzing the electric quantity of the battery model according to the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
referring to fig. 1 to 5, the present invention provides a technical solution:
a high-speed maglev train auxiliary driving method based on battery model calculation comprises the following steps:
and S1, constructing a running organization capability test platform, and sending train running data to the running organization capability test platform by a vehicle-mounted running control system (VSC).
The train operation data comprises clock information, speed information and IPC states, and a vehicle-mounted operation control system (VSC) is technical equipment for supervising, controlling and adjusting states of train operation speed, a braking mode and the like according to objective conditions and actual conditions of train operation on a line, and can detect various kinds of train operation data in real time.
And S2, the operation organization capability test platform carries out simulation synchronization according to the received data, establishes a storage battery model and a traction energy-saving model, and analyzes the data models of the vehicle-mounted storage battery and the traction energy-saving module in the operation process of the train in real time according to the vehicle state information.
The method for establishing the storage battery model specifically comprises the following steps:
s201, designing a discharge model according to the clock interval in the clock information;
s202, designing a charging model according to the speed information;
and S203, designing battery capacity management according to the designed charge and discharge model.
The battery capacity management is mainly based on battery data (including battery voltage, current, temperature, etc.), and the state of the battery is judged according to the data, and the battery is intelligently managed according to a certain management method, so as to achieve the purpose of most effectively using the battery capacity.
And S3, judging the running state of the train by the vehicle-mounted running control system (VSC) according to the analysis result, and starting an auxiliary driving module in the running organization capability test platform and importing a new scheduling schedule when the train is judged to be in an abnormal parking state.
When a new scheduling schedule is imported, a dispatcher imports the new scheduling schedule through a schedule import module in a vehicle-mounted running control system (VSC).
And S4, analyzing the electric quantity of the running organization capability test platform according to the new scheduling schedule and the storage battery model, analyzing the scheme and the feasibility of continuous running when the train is switched to the manual driving mode, and judging whether the train can be continuously run.
The specific steps of analyzing the electric quantity of the storage battery model are as follows:
s401, constructing an energy balance equation of the high-speed magnetic-levitation train in the maintenance operation process:
Wlig+Wbat＝Wxf+Wdx+Wsb
in the formula, WligIs the output energy of the on-board linear generator, WbatFor the consumption of energy of on-board batteries, WxfFor the consumption of energy in the levitation apparatus, WdxAnd WsbThe consumed energy of the guiding equipment is the consumed energy of the vehicle-mounted electrical equipment;
s402, calculating the output energy of the vehicle-mounted linear generator according to the running speed of the train, wherein the calculation formula is as follows:
in the formula, a, b and c are coefficients, twhThe train running time is;
s403, calculating the electric quantity consumed by the vehicle-mounted storage battery, wherein the calculation formula is as follows:
in the formula, QbatFor the consumption of electric power, P, of the on-board batteryxfFor the consumption of power by levitating apparatus, PdxConsumption of power for steering devices, PsbFor power consumption of vehicle-mounted electrical equipment, UbatIs the voltage of an on-board battery, where Pxf、PdxAnd PsbObtaining a numerical value through a real vehicle test;
s404, the consumed electric quantity Q of the vehicle-mounted storage battery is calculatedbatAnd comparing the electric quantity with the electric quantity of the actual vehicle-mounted storage battery, and judging the scheme and feasibility of continuous driving.
The train running time twhCalculating according to the train maintenance operation speed curve, the distance from the next auxiliary parking area and the train schedule, wherein the maintenance operation speed curve is twhThe integral of the speed is the distance from the next auxiliary parking area, the train schedule can also display the running time of the train, and needs to be considered comprehensively, the calculation flow of the maintenance running speed is that firstly the maintenance running speed of the train and the distance between the auxiliary parking areas are input, then the acceleration distance and the eddy current braking distance are calculated according to the maintenance running speed, and the sum of the acceleration distance and the eddy current braking distance is used as the minimum distance, and finally whether the minimum distance is smaller than the distance between the auxiliary parking areas is judged, if so, a maintenance running speed curve is output, if not, a limit speed is output, and the consumed electric quantity Q of the vehicle-mounted storage battery isbatJudging that the electric quantity is insufficient when the electric quantity is less than the electric quantity of the actual vehicle-mounted storage battery, and continuing to drive after charging is needed, wherein the consumed electric quantity Q of the vehicle-mounted storage batterybatAnd when the electric quantity of the battery is larger than the electric quantity of the actual vehicle-mounted storage battery, the manual driving mode can be started for driving.
And S5, when the vehicle cannot run due to low electric quantity, calculating the charging time, and when the vehicle can continue to run, switching the auxiliary driving module to a manual driving mode by analyzing the relation between the storage battery module and the vehicle, the speed, the energy consumption and other models, and guiding an auxiliary driver to drive to the next auxiliary parking area.
The charging time is calculated according to the charging power, the current capacity of the storage battery and the minimum capacity required for driving to the next auxiliary parking area.
And S6, operating the organization capability test platform to acquire auxiliary driving information, packaging the data information, performing data transmission through network communication, and sending the data information to an android terminal for display.
The communication mode between the operation organization capability test platform and the android terminal is UDP communication transmission, the android terminal is internally provided with a user login function, no data information exists in a normal state, only when abnormal parking is performed, the data information for guiding a trainman to assist driving is logged in a designated account, and the data of the assisted driving can be remotely checked through the android terminal, so that the train test maintenance cost is effectively reduced.
The invention also provides a high-speed maglev train auxiliary driving system based on battery model calculation, which comprises:
the simulation construction testing module is used for constructing an operation organization capability testing platform and enabling a vehicle-mounted driving control system (VSC) to send train operation data to the operation organization capability testing platform;
the running organization capability test module is used for controlling the running organization capability test platform to carry out simulation synchronization according to the received data, establishing a storage battery model and a traction energy-saving model, and analyzing a vehicle-mounted storage battery and a traction energy-saving module data model in the running process of the train in real time according to the vehicle state information;
the train state judgment module is used for enabling a vehicle-mounted running control system (VSC) to judge the running state of the train according to the analysis result, starting an auxiliary driving module in the running organization capability test platform when the train is judged to be in an abnormal parking state, and importing a new scheduling timetable;
the storage battery electric quantity analysis module is used for enabling the operation organization capability test platform to analyze the electric quantity of the operation organization capability test platform according to the new scheduling timetable and the storage battery model, analyzing the scheme and feasibility of continuous running when the train is switched to the manual driving mode, and judging whether the train can be continuously run or not;
the driving guidance auxiliary module is used for calculating charging time when the vehicle cannot run due to low electric quantity, and when the vehicle can continue to run, the auxiliary driving module is switched to a manual driving mode by analyzing the relation between the storage battery module and the models of the vehicle, speed, energy consumption and the like, and guides an auxiliary driver to drive to a next auxiliary parking area; and
and the data transmission module is used for enabling the running organization capability test platform to acquire the auxiliary driving information, packaging the data information, transmitting the data information through network communication, and sending the data information to the android terminal for displaying.
The invention also provides a high-speed maglev train auxiliary driving device based on battery model calculation, wherein the auxiliary driving device comprises a memory, a processor, a bus, a communication module and an auxiliary driving program which is stored on the memory and runs on the processor, the memory, the processor, the communication module and a vehicle-mounted running control system (VSC) in the train are electrically connected through the bus, and the auxiliary driving program is configured to realize the steps of the auxiliary driving method.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A high-speed maglev train auxiliary driving method based on battery model calculation is characterized by comprising the following steps:
s1, constructing a running organization capability test platform, and sending train running data to the running organization capability test platform by a vehicle-mounted running control system (VSC);
s2, the operation organization capability test platform carries out simulation synchronization according to the received data, establishes a storage battery model and a traction energy-saving model, and analyzes the data models of the vehicle-mounted storage battery and the traction energy-saving module in the operation process of the train in real time according to the vehicle state information;
s3, judging the running state of the train by a vehicle-mounted running control system (VSC) according to the analysis result, starting an auxiliary driving module in the running organization capability test platform and importing a new scheduling schedule when judging that the train is in an abnormal parking state;
s4, the operation organization ability test platform analyzes the electric quantity according to the new scheduling schedule and the storage battery model, analyzes the scheme and the feasibility of the continuous driving when the train is switched to the manual driving mode, and judges whether the continuous driving is possible;
s5, when the electric quantity is low and the vehicle cannot run, calculating the charging time, when the vehicle can run continuously, the auxiliary driving module switches to a manual driving mode by analyzing the relation between the storage battery module and the vehicle, the speed, the energy consumption and other models, and guides an auxiliary driver to drive to the next auxiliary parking area;
and S6, operating the organization capability test platform to acquire auxiliary driving information, packaging the data information, performing data transmission through network communication, and sending the data information to an android terminal for display.
2. The high-speed maglev train auxiliary driving method based on battery model calculation as claimed in claim 1, wherein: the train operation data in the step S1 includes clock information, speed information, and IPC status.
3. The high-speed maglev train auxiliary driving method based on battery model calculation as claimed in claim 2, wherein: the building of the battery model in step S2 specifically includes the following steps:
s201, designing a discharge model according to the clock interval in the clock information;
s202, designing a charging model according to the speed information;
and S203, designing battery capacity management according to the designed charge and discharge model.
4. The high-speed maglev train auxiliary driving method based on battery model calculation as claimed in claim 1, wherein: the specific steps of analyzing the electric quantity of the battery model in the step S4 are as follows:
s401, constructing an energy balance equation of the high-speed magnetic-levitation train in the maintenance operation process:
Wlig+Wbat＝Wxf+Wdx+Wsb
in the formula, WligIs the output energy of the on-board linear generator, WbatFor the consumption of energy of on-board batteries, WxfFor the consumption of energy in the levitation apparatus, WdxAnd WsbThe consumed energy of the guiding equipment is the consumed energy of the vehicle-mounted electrical equipment;
s402, calculating the output energy of the vehicle-mounted linear generator according to the running speed of the train, wherein the calculation formula is as follows:
in the formula, a, b and c are coefficients, twhThe train running time is;
s403, calculating the electric quantity consumed by the vehicle-mounted storage battery, wherein the calculation formula is as follows:
in the formula, QbatFor the consumption of electric power, P, of the on-board batteryxfFor the consumption of power by levitating apparatus, PdxConsumption of power for steering devices, PsbFor power consumption of vehicle-mounted electrical equipment, UbatIs the voltage of an on-board battery, where Pxf、PdxAnd PsbObtaining a numerical value through a real vehicle test;
s404, the consumed electric quantity Q of the vehicle-mounted storage battery is calculatedbatComparing with the actual electric quantity of the vehicle-mounted storage battery, and judging to continue runningDriving scheme and feasibility.
5. The high-speed maglev train auxiliary driving method based on battery model calculation as claimed in claim 4, wherein: the train running time twhThe method comprises the steps of firstly inputting the maintenance operation speed of the train and the distance between the train and the auxiliary parking area, then calculating according to the maintenance operation speed to obtain the acceleration distance and the eddy current braking distance, taking the sum of the acceleration distance and the eddy current braking distance as the minimum distance, finally judging whether the minimum distance is smaller than the distance between the auxiliary parking areas, if so, outputting a maintenance operation speed curve, and if not, outputting the limit speed.
6. The high-speed maglev train auxiliary driving method based on battery model calculation as claimed in claim 1, wherein: and the communication mode between the running organization capability test platform and the android terminal adopts UDP communication transmission.
7. The high-speed maglev train auxiliary driving method based on battery model calculation as claimed in claim 1, wherein: the android terminal is internally provided with a user login function, no data information exists in a normal state, and only when the android terminal is in abnormal parking, data information for guiding a trainee to assist in driving is available after the android terminal logs in an appointed account.
8. The utility model provides a high-speed maglev train aided driving system based on battery model calculates which characterized in that includes:
the simulation construction testing module is used for constructing an operation organization capability testing platform and enabling a vehicle-mounted driving control system (VSC) to send train operation data to the operation organization capability testing platform;
the running organization capability test module is used for controlling the running organization capability test platform to carry out simulation synchronization according to the received data, establishing a storage battery model and a traction energy-saving model, and analyzing a vehicle-mounted storage battery and a traction energy-saving module data model in the running process of the train in real time according to the vehicle state information;
the train state judgment module is used for enabling a vehicle-mounted running control system (VSC) to judge the running state of the train according to the analysis result, starting an auxiliary driving module in the running organization capability test platform when the train is judged to be in an abnormal parking state, and importing a new scheduling timetable;
the storage battery electric quantity analysis module is used for enabling the operation organization capability test platform to analyze the electric quantity of the operation organization capability test platform according to the new scheduling timetable and the storage battery model, analyzing the scheme and feasibility of continuous running when the train is switched to the manual driving mode, and judging whether the train can be continuously run or not;
the driving guidance auxiliary module is used for calculating charging time when the vehicle cannot run due to low electric quantity, and when the vehicle can continue to run, the auxiliary driving module is switched to a manual driving mode by analyzing the relation between the storage battery module and the models of the vehicle, speed, energy consumption and the like, and guides an auxiliary driver to drive to a next auxiliary parking area; and
and the data transmission module is used for enabling the running organization capability test platform to acquire the auxiliary driving information, packaging the data information, transmitting the data information through network communication, and sending the data information to the android terminal for displaying.
9. The utility model provides a high-speed maglev train auxiliary driving equipment based on battery model calculates which characterized in that: the driving assistance device comprises a memory, a processor, a bus, a communication module and a driving assistance program stored on the memory and running on the processor, wherein the memory, the processor, the communication module and a vehicle-mounted operation control system (VSC) inside the train are electrically connected through the bus, and the driving assistance program is configured to realize the steps of the driving assistance method according to any one of claims 1 to 7.
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