CN109109913B - 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 PDF

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CN109109913B
CN109109913B CN201810833980.1A CN201810833980A CN109109913B CN 109109913 B CN109109913 B CN 109109913B CN 201810833980 A CN201810833980 A CN 201810833980A CN 109109913 B CN109109913 B CN 109109913B
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train
difference model
area
rail transit
transit system
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CN109109913A (en
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潘登
夏易君
赵立婷
陈泽君
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Tongji University
CRRC Changchun Railway Vehicles Co Ltd
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/10Operations, e.g. scheduling or time tables
    • B61L27/16Trackside optimisation of vehicle or train operation
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/40Handling position reports or trackside vehicle data
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive 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
    • G05B13/042Adaptive 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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  • Mechanical Engineering (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Train Traffic Observation, Control, And Security (AREA)

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

A kind of information processing method for Rail Transit System efficiency organization of driving
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, Lai Tigao 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 are poor Sub-model;
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,tO It 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, train resistance W (k) suffered within k-th of sampling period is by datum drag and additional drag Composition.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 difference model;
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,tO It 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, train resistance W (k) suffered within k-th of sampling period is made of datum drag and additional drag.Substantially Resistance 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 difference Model;
Constant moment of force area difference model are as follows:
Wherein: m is train gross mass, and v (k), v (k+1) are train in kth, the sampling speed of service in k+1 sampling period, T For sampling period, FAFor train in the tractive force in constant moment of force area, W (k) is train resistance suffered 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.
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,tORespectively Indicate that train runs constant moment of force area, invariable power area, natural characteristic area, cruise area, coasting area, regenerative braking area, sky in each section The time that gas brakes each stage in area 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, train resistance W (k) suffered within k-th of sampling period is by datum drag and additional drag It forms, 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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