CN109109913A - A kind of information processing method for Rail Transit System efficiency organization of driving - Google Patents
A kind of information processing method for Rail Transit System efficiency organization of driving 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
- B61L27/10—Operations, e.g. scheduling or time tables
- B61L27/16—Trackside optimisation of vehicle or train operation
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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
- B61L27/40—Handling position reports or trackside vehicle data
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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Abstract
The present invention relates to a kind of information processing methods for Rail Transit System efficiency organization of driving, comprising: step S1: using the train continuous in time three times dispatched a car as a basic driving organizational unit；Step S2: train behavior difference model is established；Step S3: goal behavior curve is calculated in the train behavior difference model based on foundation；Step S4: the poly- scattered rule respectively stood on the line according to goal behavior curve and passenger determines in each unit the interval time of train, the interval time of basic driving organizational unit and train in station down time；Step S5: the interval time of the interval time of train, basic driving organizational unit are exported in the basic driving organizational unit that step S1 is determined and each unit that step S4 is determined, and train, in station down time, auxiliary establishment takes into account passenger transport demand, energy-saving and train operation agility route map of train.Compared with prior art, the present invention has many advantages, such as substantially energy saving, reduction energy consumption.
Description
Technical field
The present invention relates to a kind of rail traffic dispatching techniques, drive a vehicle more particularly, to one kind for Rail Transit System efficiency
The information processing method of tissue.
Background technique
For urban track traffic, " efficiency " is mainly reflected in energy-saving and train operation two sides of agility
Face.The method for improving " efficiency " of driving and organization of driving's tissue mainly has excellent based on operating condition in theoretical research and in practice
Change the group of combined energy-saving train operation, time-table optimization and the recycling of regenerative electric energy and above-mentioned three kinds of methods
It closes and utilizes.
It is the switching point by optimizing each operating condition of train, mainly based on the energy-saving train operation of operation optimization combination
It is by extending the train coasting time, to achieve the purpose that electric energy and reduction energy consumption are saved in train operation, it is quick to sacrifice
Property be cost, it is difficult to realize energy conservation it is compatible with agility.Therefore, energy-saving train operation and organization of driving, regenerative electric energy utilize
Combine closely, be the inexorable trend of City Rail Transit System " efficiency promotion " research, and hot fields studied now.
Ning etc. proposes a kind of headway time interval Controlling model that the train arrival time is adjusted by change train operation curve, trip
Visitor is average to be greatly reduced in station waiting time and energy consumption in train journey；Jia etc. devise it is a kind of based on time-table optimization
Train efficiency control strategy, for passenger transport demand have probabilistic subway line non-transport peak period column control with
Organization of driving；Huang etc. is with City Rail Transit System energy-saving train operation and enhances the quality of passenger service as target, proposes one
Kind passenger flow supersaturated condition Train timetable Optimized model, it is directly sharp in regenerative electric energy by the adjustment of headway time interval
With between the Passenger Travel time acquirement it is balanced, thus reach City Rail Transit System operation biobjective scheduling；Infantry etc.
Control strategy progress unified planning to bicycle energy conservation and the collaboration of more vehicles using regenerative electric energy, simulating, verifying optimization train time
The energy-saving effect of table；Su etc. proposes that a kind of train target of avoidable frequent switching operating status based on ATO control principle is bent
Line optimization method, to improve city rail train efficiency；Feng etc. is to the passenger train under train length and driving power constraint
Energy conservation object curve is thoroughly discussed, and the improvement and raising of passenger organization and train running scheme are facilitated.Yang etc. will
The energy-efficient operation reserve of train is attributed to three time-table optimization, energy-efficient driving and comprehensive optimization method aspects.
The above research achievement is to the green of High Speed Train in China, the development of energy-saving and environmental protection is pushed, and constantly improve China is at a high speed
Train operation efficiency is horizontal, has great importance.But " energy saving research ", also mainly around train coasting and regeneration electricity
Can recycling, using expansion, although many scholars combine it with time-table optimization, so that train is in energy-saving run
Meanwhile also increasing in agility, since the short limitation train excellent performance of City Rail Transit System distance between sites plays
Defect there is no very good solutions, the promotion of actually " efficiency " still have huge space have it is to be excavated.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind to be used for rail traffic
The information processing method of system energy efficiency organization of driving.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of information processing method for Rail Transit System efficiency organization of driving, comprising:
Step S1: using the train continuous in time three times dispatched a car as a basic driving organizational unit, train is equal three times
From the starting station, wherein a train only stops odd stations and terminus, and No. one time train only stops even stations and terminus,
It stops at another every station of secondary train；
Step S2: train behavior difference model is established；
Step S3: goal behavior curve is calculated in the train behavior difference model based on foundation；
Step S4: the poly- scattered rule respectively stood on the line according to goal behavior curve and passenger determines train in each unit
Interval time, basic driving organizational unit interval time and train in station down time；
Step S5: in each unit that the output step S1 basic driving organizational unit determined and step S4 are determined between train
Every time, the interval time of basic driving organizational unit and train in station down time, auxiliary establishment takes into account passenger transport and needs
It asks, energy-saving and train operation agility route map of train.
The sequence of three trains in any basic driving organizational unit arbitrarily sorts.
The difference model of train includes constant moment of force area difference model, invariable power area difference model, nature in the step S2
Characteristic area difference model, cruise area's difference model, coasting area difference model and regenerative braking area difference model, air damping area；
Constant moment of force area difference model are as follows:
Wherein: m is train gross mass (including train self weight and passenger's total weight), and v (k), v (k+1) are train in kth, k
The sampling speed of service in+1 sampling period, T are sampling period, FAFor train in the tractive force in constant moment of force area, W (k) is train
The suffered resistance within k-th of sampling period；
Invariable power area difference model are as follows:
Wherein: P is the invariable power of train；
Natural characteristic area difference model are as follows:
Wherein: M is train natural characteristic constant；
Cruise area difference model are as follows:
- v (k)=0 v (k+1)
Coasting area difference model are as follows:
Regenerative braking area difference model are as follows:
Wherein: the brake force that B (k) is taken within k-th of sampling period by train, fDEIt (k) is train braking force constant.
Air damping area difference model are as follows:
Wherein: Bairbraking(k) brake force taken within k-th of sampling period by train.
The step S3 is specifically included:
Step S31: the optimal energy consumption E of City Rail Transit SystemOptimalInitialization, i.e. EOptimal=EC, wherein ECIt is to make
For the total energy consumption of the City Rail Transit System of current optimization object；
Step S32: the operation energy consumption E of the l articles route i-th train is calculatedLine(l),Train(i)；
Wherein: nl,iIt is the section quantity of the l articles route i-th train operation, j is the l articles route i-th train operation
The number in section, Fl,i,jIt is i-th train operation tractive force suffered when the l articles route, j-th of section, Bl,i,jI-th column
Vehicle runs on brake force suffered when the l articles route, j-th of section, and ds indicates the differential of distance, tA,tB,tC,tC*,tD,tE,tF,
tOIt respectively indicates train and runs constant moment of force area, invariable power area, natural characteristic area, cruise area, coasting area, regenerative braking in each section
The time in each stage in area, air damping area etc. divides；
Step S33: the operation energy consumption E of the l articles all train of route is calculatedLine(l)；
Wherein: nlIt is the quantity of the l articles all running train of route；
Step S34: the energy consumption in train journey E of entire City Rail Transit System is calculatedAllTrains。
Wherein: n is the number of, lines of City Rail Transit System；
Step S35: compare EAllTrainsWith EOptimalIf EAllTrains< EOptimal, then EOptimal=EAllTrains, otherwise protect
Hold EOptimalIt is constant；
Step S36: return step S31 until cycle-index reaches setting number；
Step S37: to obtain optimal energy consumption EOptimalWhen train behavior curve be goal behavior curve.
In the step S32, the resistance W (k) of each section of train each operation phase is by datum drag and additional drag group
At.Specific train resistance w based on datum drag0Are as follows:
w0=a+bv+cv2
Wherein, a, b, c are constant, and v is train real time execution speed.The additional drag of ramp and bend can be by rail traffic
The relevant regulations that the traction of department calculates regulation are converted.
Tractive force F in the step S3, in constant moment of force area, invariable power area, natural characteristic areal,i,jAccording to train behavior
Difference model and newtonian motion law are calculated；
The tractive force F in cruise areal,i,jIt is equal with train running resistance numerical value；
Brake force Bl,i,jAccording to train behaviour control demand, the difference model and newtonian motion law of train behavior are utilized
It is calculated.
Compared with prior art, the invention has the following advantages:
1) on the basis of taking into account passenger's accessibility transportation demand, it is short brilliant to train is made full use of that distance between sites are alleviated
The limitation of performance, while substantially energy saving, reduction energy consumption, significantly improve the agility of train operation, overcome pure dependence
Train coasting length of time is controlled to reach train operation energy conservation or improve train operation agility, but it is compatible to cannot achieve the two
Defect.
2) by establishing specific difference model, the accuracy of calculating is improved.
Detailed description of the invention
Fig. 1 is key step flow diagram of the invention；
Fig. 2 (a)~Fig. 2 (e) is train operation in energy consumption-time graph schematic diagram of 2.0km block section between stations；
Fig. 3 (a)~Fig. 3 (e) is train operation in energy consumption-time graph schematic diagram of 4.0km block section between stations；
Fig. 4 (a) and Fig. 4 (b) is the establishment schematic diagram of route map of train.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with technical solution of the present invention
Premised on implemented, the detailed implementation method and specific operation process are given, but protection scope of the present invention is not limited to
Following embodiments.
A kind of information processing method for Rail Transit System efficiency organization of driving, as shown in Figure 1, comprising:
Step S1: using the train continuous in time three times dispatched a car as a basic driving organizational unit, train is equal three times
From the starting station, wherein a train only stops odd stations and terminus, and No. one time train only stops even stations and terminus,
It stops at another every station of secondary train；The sequence of three trains in any basic driving organizational unit arbitrarily sorts, totally 6 kinds of combinations
Mode: 1. train 1-- train 2-- train 3；2. train 1-- train 3-- train 2；3. train 2-- train 1-- train 3；4. train
2-- train 3-- train 1；5. train 3-- train 1-- train 2；6. train 3-- train 2-- train 1.It can be according to the actual situation
Select any one combination.
Fig. 2 (a)~Fig. 2 (e) and Fig. 3 (a)~Fig. 3 (e) simulate respectively train operation in 2.0km standard block section between stations with
The block section between stations situation of 4.0km, it can be found that the operation energy consumption overwhelming majority generation of train subtracts in train Accelerating running and braking
Speed two stages of operation, and the stage energy consumption then very little that travels at the uniform speed in train cruise area, the coasting stage, train was then without power consumption.
And when train speed raising, it can be found that energy consumption in train journey increases, and the standard block section between stations of 2.0km are due to apart from too short, limit
Made the performance of train excellent performance, i.e. the maximum operational speed of train cannot be fully utilized, thus train operation
It agility and energy-saving is greatly constrained.
Step S2: establishing train behavior difference model, and wherein the difference model of train includes constant moment of force area difference model, perseverance
Power area difference model, natural characteristic area difference model, cruise area's difference model, coasting area difference model and regenerative braking area are poor
Sub-model, air damping area；
Constant moment of force area difference model are as follows:
Wherein: m is train gross mass (including train self weight and passenger's total weight), and v (k), v (k+1) are train in kth, k
The sampling speed of service in+1 sampling period, T are sampling period, FAFor train in the tractive force in constant moment of force area, W (k) is train
The suffered resistance within k-th of sampling period；
Invariable power area difference model are as follows:
Wherein: P is the invariable power of train；
Natural characteristic area difference model are as follows:
Wherein: M is train natural characteristic constant；
Cruise area's difference model are as follows:
- v (k)=0 v (k+1)
Coasting area difference model are as follows:
Regenerative braking area difference model are as follows:
Wherein: the brake force that B (k) is taken within k-th of sampling period by train, fDEIt (k) is train braking force constant.
Air damping area difference model are as follows:
Wherein: Bairbraking(k) brake force taken within k-th of sampling period by train.
Step S3: the train behavior difference model based on foundation, which is calculated, can make that train is safe and efficient, energy-saving run
Goal behavior curve, specifically include:
Step S31: the optimal energy consumption E of City Rail Transit SystemOptimalInitialization, i.e. EOptimal=EC, wherein ECIt is to make
For the total energy consumption of the City Rail Transit System of current optimization object；
Step S32: the operation energy consumption E of the l articles route i-th train is calculatedLine(l),Train(i)；
Wherein: nl,iIt is the section quantity of the l articles route i-th train operation, j is the l articles route i-th train operation
The number in section, Fl,i,jIt is i-th train operation tractive force suffered when the l articles route, j-th of section, Bl,i,jI-th column
Vehicle runs on brake force suffered when the l articles route, j-th of section, and ds indicates the differential of distance, tA,tB,tC,tC*,tD,tE,tF,
tOIt respectively indicates train and runs constant moment of force area, invariable power area, natural characteristic area, cruise area, coasting area, regenerative braking in each section
The time in each stage in area, air damping area etc. divides；
Wherein, the resistance W (k) of each section of train each operation phase is made of datum drag and additional drag.Basic resistance
Power can be according to following specific train resistance w0Calculation formula:
w0=a+bv+cv2
It is calculated according to the weight of train (including train self weight and passenger's total weight).In formula, a, b, c are constant, and v is column
Vehicle real time execution speed.The additional drag of ramp and bend can by rail traffic department traction calculate regulation relevant regulations into
Row conversion.
Tractive force F in constant moment of force area, invariable power area, natural characteristic areal,i,jAccording to the difference model of train behavior and ox
The kinematics law that pauses is calculated；
The tractive force F in cruise areal,i,jIt is equal with train running resistance numerical value；
Brake force Bl,i,jAccording to train behaviour control demand, the difference model and newtonian motion law of train behavior are utilized
It is calculated.
Step S33: the operation energy consumption E of the l articles all train of route is calculatedLine(l)；
Wherein: nlIt is the quantity of the l articles all running train of route；
Step S34: the energy consumption in train journey E of entire City Rail Transit System is calculatedAllTrains。
Wherein: n is the number of, lines of City Rail Transit System；
Step S35: compare EAllTrainsWith EOptimalIf EAllTrains< EOptimal, then EOptimal=EAllTrains, otherwise protect
Hold EOptimalIt is constant；
Step S36: return step S31 until cycle-index reaches setting number；
Step S37: to obtain optimal energy consumption EOptimalWhen train behavior curve be goal behavior curve.
, can be with linear superposition since energy consumption belongs to scalar, we can imitate for the train operation situation of a route
Very, the correctness and feasibility of above-mentioned algorithm, and the effect implemented are verified.It might as well assume that a level tangent track has 40 vehicles
It stands, each station is at a distance of 2.0km, the setting by step 1 to Train1, Tain2 and Train3, under the conditions of can emulating friction speed
The runing time and energy consumption of Train1, Tain2 and Train3 various combination.Table 1 is basic under the conditions of energy-saving train operation
The tourist on train time of organization of driving's unit and energy consumption.So-called energy-saving train operation condition is run for train interval
Microscopic behavior for, i.e., by the optimization of train operation operating condition switching time point, to achieve the purpose that energy-saving train operation.
Table 1
The runing time that can be seen that Train1, Tain2 and Train3 from the Unit 1-3 in table 1 it is total compared to
Train1, Tain2 and Train3 take traditional organization of driving's scheme of each station parking, maximum operational speed 80km/h, Unit
1, which reduces 10.18%, Unit 2, which reduces 14.75%, Unit 3, reduces 18.14%；In terms of energy consumption, Unit 1 is reduced
36.49%, Unit 2, which reduces 27.97%, Unit 3, reduces 16.13%.Train energy-saving and fast express agency have obtained very
Good realization overcomes the simple technological deficiency that this cannot take into account by the optimization of train microscopic behavior, at the same time, Train3
Maximum operational speed 80km/h and each station is all stopped, and the transportation demand that passenger reaches respective destination has been taken into account well, overcome
Train1, Train2 every station parking passenger have to the deficiency that selects to get off in the neighboring station of oneself point of destination.
Step S4: the poly- scattered rule respectively stood on the line according to goal behavior curve and passenger determines train in each unit
Interval time, basic driving organizational unit interval time and train in station down time；
Step S5: in each unit that the output step S1 basic driving organizational unit determined and step S4 are determined between train
Every time, the interval time of basic driving organizational unit and train in station down time, auxiliary establishment takes into account passenger transport and needs
It asks, energy-saving and train operation agility route map of train.
It is assumed that headway time interval tTrainInterval=120s, train dwelling time tDwellTime=30s, route station number
Measure ns=40.Wherein, tTrainIntervalIt indicates continuously to reach terminal train from the headway time interval at the starting station with them
The minimum value of interval time, tDwellTimeIndicate the time that train dwelling passenger stop point needs, tUnitIntervalIndicate basic driving
Minimum headway time interval between organizational unit.
Fig. 4 (a) and figure (b) emulate the train that the drawing various combination maximum operational speed of Train1,2,3 is 80km/h
Operation figure, from safety considerations, tTrainInterval、tUnitIntervalFollowing condition must be met:
T in formulaSwitchbackFor train reciprocal time.
Claims (6)
1. a kind of information processing method for Rail Transit System efficiency organization of driving characterized by comprising
Step S1: using the train continuous in time three times dispatched a car as a basic driving organizational unit, train is from the beginning three times
It sets out at hair station, wherein a train only stops odd stations and terminus, and No. one time train only stops even stations and terminus, another
It stops at the secondary every station of train；
Step S2: train behavior difference model is established；
Step S3: goal behavior curve is calculated in the train behavior difference model based on foundation；
Step S4: the poly- scattered rule respectively stood on the line according to goal behavior curve and passenger determines in each unit between train
Every time, the interval time of basic driving organizational unit and train in station down time；
Step S5: in each unit that the basic driving organizational unit and step S4 that output step S1 is determined determine when the interval of train
Between, the interval time of basic driving organizational unit and train in station down time, auxiliary establishment take into account passenger transport demand,
Energy-saving and train operation agility route map of train.
2. a kind of information processing method for Rail Transit System efficiency organization of driving according to claim 1, special
Sign is that the sequence of three trains in any basic driving organizational unit arbitrarily sorts.
3. a kind of information processing method for Rail Transit System efficiency organization of driving according to claim 1, special
Sign is that the difference model of train includes constant moment of force area difference model, invariable power area difference model, naturally spy in the step S2
Property area difference model, cruise area's difference model, coasting area difference model and regenerative braking area difference model, air damping area；
Constant moment of force area difference model are as follows:
Wherein: m is train gross mass (including train self weight and passenger's total weight), and v (k), v (k+1) are train in kth, k+1
The sampling speed of service in sampling period, T are sampling period, FAFor train in the tractive force in constant moment of force area, W (k) is train in kth
Suffered resistance in a sampling period；
Invariable power area difference model are as follows:
Wherein: P is the invariable power of train；
Natural characteristic area difference model are as follows:
Wherein: M is train natural characteristic constant；
Cruise area difference model are as follows:
- v (k)=0 v (k+1)
Coasting area difference model are as follows:
Regenerative braking area difference model are as follows:
Wherein: the brake force that B (k) is taken within k-th of sampling period by train, fDEIt (k) is train braking force constant.
Air damping area difference model are as follows:
Wherein: Bairbraking(k) brake force taken within k-th of sampling period by train.
4. a kind of information processing method for Rail Transit System efficiency organization of driving according to claim 3, special
Sign is that the step S3 is specifically included:
Step S31: the optimal energy consumption E of City Rail Transit SystemOptimalInitialization, i.e. EOptimal=EC, wherein ECIt is as working as
The total energy consumption of the City Rail Transit System of preceding optimization object；
Step S32: the operation energy consumption E of the l articles route i-th train is calculatedLine(l),Train(i)；
Wherein: nl,iIt is the section quantity of the l articles route i-th train operation, j is the l articles route i-th train running interval
Number, Fl,i,jIt is i-th train operation tractive force suffered when the l articles route, j-th of section, Bl,i,jI-th train fortune
Row brake force suffered when the l articles route, j-th of section, ds indicate the differential of distance, tA,tB,tC,tC*,tD,tE,tF,tOPoint
Not Biao Shi train each section run constant moment of force area, invariable power area, natural characteristic area, cruise area, coasting area, regenerative braking area,
The time in each stage in air damping area etc. divides；
Step S33: the operation energy consumption E of the l articles all train of route is calculatedLine(l)；
Wherein: nlIt is the quantity of the l articles all running train of route；
Step S34: the energy consumption in train journey E of entire City Rail Transit System is calculatedAllTrains。
Wherein: n is the number of, lines of City Rail Transit System；
Step S35: compare EAllTrainsWith EOptimalIf EAllTrains< EOptimal, then EOptimal=EAllTrains, otherwise keep
EOptimalIt is constant；
Step S36: return step S31 until cycle-index reaches setting number；
Step S37: to obtain optimal energy consumption EOptimalWhen train behavior curve be goal behavior curve.
5. a kind of information processing method for Rail Transit System efficiency organization of driving according to claim 4, special
Sign is, in the step S32, the resistance W (k) of each section of train each operation phase is by datum drag and additional drag group
At wherein specific train resistance w based on datum drag0Are as follows:
w0=a+bv+cv2
Wherein, a, b, c are constant, and v is train real time execution speed.
6. a kind of information processing method for Rail Transit System efficiency organization of driving according to claim 4, special
Sign is, the tractive force F in the step S3, in constant moment of force area, invariable power area, natural characteristic areal,i,jAccording to train behavior
Difference model and newtonian motion law are calculated；
The tractive force F in cruise areal,i,jIt is equal with train running resistance numerical value；
Brake force Bl,i,jAccording to train behaviour control demand, calculated using the difference model and newtonian motion law of train behavior
It obtains.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110544010A (en) * | 2019-07-30 | 2019-12-06 | 同济大学 | Identification method of key elements influencing global efficiency emergence of rail transit system |
| CN111806241A (en) * | 2020-06-28 | 2020-10-23 | 同济大学 | Method for determining regenerative electric energy recovery space of rail transit train |
| CN111824093A (en) * | 2020-07-30 | 2020-10-27 | 中车株洲电力机车有限公司 | Rail transit vehicle parking control method and system |
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| CN104260759A (en) * | 2014-10-08 | 2015-01-07 | 北京交通大学 | Method and system for optimizing energy conservation of urban rail transit |
| CN106651009A (en) * | 2016-11-23 | 2017-05-10 | 北京交通大学 | Energy-saving and optimized control method for random multi-train collaboration of urban rail transit |
| EP3219573A1 (en) * | 2016-03-16 | 2017-09-20 | Hitachi, Ltd. | Train driving assistance system |
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| CN103963805A (en) * | 2014-04-25 | 2014-08-06 | 北京交通大学 | Energy-saving method of train operation of urban mass transit |
| CN104260759A (en) * | 2014-10-08 | 2015-01-07 | 北京交通大学 | Method and system for optimizing energy conservation of urban rail transit |
| EP3219573A1 (en) * | 2016-03-16 | 2017-09-20 | Hitachi, Ltd. | Train driving assistance system |
| CN106651009A (en) * | 2016-11-23 | 2017-05-10 | 北京交通大学 | Energy-saving and optimized control method for random multi-train collaboration of urban rail transit |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110544010A (en) * | 2019-07-30 | 2019-12-06 | 同济大学 | Identification method of key elements influencing global efficiency emergence of rail transit system |
| CN110544010B (en) * | 2019-07-30 | 2023-04-07 | 同济大学 | Identification method of key elements influencing global efficiency emergence of rail transit system |
| CN111806241A (en) * | 2020-06-28 | 2020-10-23 | 同济大学 | Method for determining regenerative electric energy recovery space of rail transit train |
| CN111824093A (en) * | 2020-07-30 | 2020-10-27 | 中车株洲电力机车有限公司 | Rail transit vehicle parking control method and system |
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| CN109109913B (en) | 2019-11-05 |
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