CN115203816A - Train energy-saving optimized operation method considering train traction transmission system efficiency - Google Patents

Train energy-saving optimized operation method considering train traction transmission system efficiency Download PDF

Info

Publication number
CN115203816A
CN115203816A CN202210540361.XA CN202210540361A CN115203816A CN 115203816 A CN115203816 A CN 115203816A CN 202210540361 A CN202210540361 A CN 202210540361A CN 115203816 A CN115203816 A CN 115203816A
Authority
CN
China
Prior art keywords
train
traction
optimized
energy
speed
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210540361.XA
Other languages
Chinese (zh)
Inventor
王青元
张子佩
孙鹏飞
程军舒
饶煜
唐海川
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southwest Jiaotong University
Original Assignee
Southwest Jiaotong University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Southwest Jiaotong University filed Critical Southwest Jiaotong University
Priority to CN202210540361.XA priority Critical patent/CN115203816A/en
Publication of CN115203816A publication Critical patent/CN115203816A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/15—Vehicle, aircraft or watercraft design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/06—Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Geometry (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Automation & Control Theory (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The invention provides a train energy-saving optimized operation method considering train traction transmission system efficiency, which comprises the following steps: s1: acquiring data of a section to be optimized of a line, wherein the data comprises train information, locomotive information, line data, line speed limit and timetable data; s2: performing operation optimization without considering the efficiency of a train transmission system aiming at the range of the line to be optimized to obtain an optimized operation curve of the train; s3: judging whether other gentle slopes exist in the optimized curve; if the existence exists, entering S5, and if the existence does not exist, ending the optimization process; s4: calculating the running time required to be adjusted according to the replacement adjustment process; s5: replacing part of traction conditions on other gentle slopes; s6: judging whether the overall operation time meets the constraint; if yes, the optimization process is ended, and if not, the step returns to S4. The energy-saving operation optimization model considering the transmission efficiency more truly describes the actual running condition of the train, and meanwhile, the energy consumption calculation is more true and reliable.

Description

Train energy-saving optimized operation method considering train traction transmission system efficiency
Technical Field
The invention relates to train operation optimization, in particular to a train energy-saving optimization operation method considering train traction transmission system efficiency (transmission efficiency for short) under the condition of considering train traction transmission system efficiency.
Technical Field
The railway operation has huge energy consumption, and approximately 68-73% of total energy consumption is used for traction energy consumption. In the running process, the energy received by the train from the overhead contact system cannot be completely converted into mechanical energy around the wheel, the loss exists in the middle, and the loss is not constant. In the actual long-distance multi-station-crossing running process of a train, the running speed of the train is lower or the traction level of the train is lower, and under the condition, the transmission efficiency of the train is far lower than that of the high-speed high-load running, so that the train transmission efficiency rule should be researched according to the actual situation, and the transmission efficiency is considered in the problem of train operation energy-saving optimization. Through reasonable operation and optimization, the energy consumption and the loss required in the train traction process can be effectively reduced, and the purpose of energy conservation is achieved from the electric energy absorbed by the train.
In the current research considering train traction transmission system energy loss, the transmission efficiency is described as a constant or a function of train running speed, the relation between the transmission efficiency and the train running speed and the train traction cannot be completely expressed, and the energy consumption calculation of an optimization result has accumulated deviation; or a practical nonlinear model of the traction transmission system is established, the influence of each factor on the train transmission efficiency is completely described, the train operation energy-saving optimization is difficult to carry out according to the model, the train operation energy-saving optimization problem considering the transmission efficiency cannot be solved from a theoretical level by using an analytic method, a heuristic algorithm has to be used for solving, the problem solving scale is large, the difficulty in solving is large, and the solving speed is low.
In the prior art, rongqingyuan is an energy-saving optimal control simulation research on a high-speed train considering the utilization of regenerative braking energy [ J ] China railway science 2015,36 (1): 96-103. The paper establishes a train energy-saving control kinematic model based on the high-speed train, considers the utilization rate of the regenerative energy of the train, analyzes an optimal working condition set and working condition conversion conditions of the energy-saving operation of the train by applying a maximum value principle (PMP), provides an energy-saving optimal control algorithm meeting the quasi-point energy-saving operation of the high-speed train, and adopts a practical case for simulation verification.
Novak,H.,
Figure BDA0003647932180000011
V.,
Figure BDA0003647932180000012
M,2021.Energy-efficient Model Predictive Train Traction Control with incorporated Traction System Efficiency[J]IEEE Transactions on Intelligent transfer Systems,2020.3046416, the paper considers a detail model of a train motor, considers train transmission efficiency as a constant during optimization, and adopts a double-layer optimization structure to optimize train energy conservation.
In the two prior arts, the train transmission efficiency is constant, which is not in accordance with the situation that the efficiency changes with the train running speed and the traction force in the actual running process, and the obtained optimization result is only suitable for the special situation that the transmission efficiency is the same as the set value.
In addition, song, Y, song, W, 2016.A Novel double Speed-current optimization Based application for Energy-conserving Operation of High-Speed trains on Intelligent Transportation Systems,17 (6), 1564-1577. In the paper, a High-Speed train kinematics model considering traction characteristics and regenerative braking is established, train transmission efficiency is regarded as a function of train running Speed, the train kinematics model is considered, and a double-layer optimization mode of off-line global optimization and on-line local optimization is adopted to realize Energy-Saving optimization control of the High-Speed train. Influence factors related to train transmission efficiency in the technology are not considered sufficiently, influence of traction on the train transmission efficiency is not considered, and a genetic algorithm is adopted as a solving mode to solve a global optimal solution difficultly.
Zhao, x, ke, b, lian, k, 2018.Optimization of Train Speed Saving Using efficiency and Accurate Electric Traction Models on the Mass Rapid Transit system, ieee Transactions on transmission Electric configuration, 4 (4), 922-935. In this paper, accurate Train Traction power supply network and Train operation Models are established, train operation Energy Saving problems are considered from the power supply side, and a particle swarm algorithm is used for optimization solution. The loss model of the train traction transmission system in the technology is a nonlinear model which is completely built according to actual conditions, an analytic method cannot be directly utilized, the problem solving scale is large, the solving difficulty is large, and the solving speed is low.
Disclosure of Invention
Aiming at the technical problem, the invention provides a calculation method for train energy-saving optimization operation, which is used for optimizing a train working condition switching sequence according to a line ramp condition under the condition of meeting the running time limit and considering the train transmission efficiency, so that the efficiency of a transmission system in the running process of a train is improved, and the electric energy consumed by train traction is reduced.
The terms to be interpreted are:
train traction drive system: the electric energy is converted into mechanical energy to draw the train to run, and the mechanical energy can be converted into the electric energy to feed back to a hardware system of a power grid when the train is braked.
The train transmission efficiency is as follows: in the process that the traction transmission system converts electric energy into mechanical energy or converts mechanical energy into electric energy, energy loss exists, the electric energy cannot be completely converted into the mechanical energy, and the train transmission efficiency refers to the ratio of the mechanical energy output by the traction transmission system to the electric energy input.
The working condition sequence is as follows: full traction, full braking, coasting, constant speed, and the like.
The specific technical scheme is as follows:
a train energy-saving optimized operation method considering train traction transmission system efficiency comprises the following steps:
s1: acquiring data of a section to be optimized of a line, wherein the data comprises train information, locomotive information, line data, line speed limit and schedule data;
s2: and performing operation optimization without considering the efficiency of the train transmission system aiming at the range of the line to be optimized to obtain an optimized train operation curve.
The specific substeps are as follows:
s2.1: calculating the shortest running time of the train; judging whether the shortest running time is lower than a time constraint, if so, entering a subsequent optimization process, and if so, directly ending the optimization process;
s2.2: dividing constant-speed areas according to time constraints and ramp partitions, and connecting the constant-speed areas to obtain a train optimization curve;
s2.3: judging whether the optimized running time meets the constraint, if not, entering S2.2;
s3: judging whether other gentle slopes exist in the optimized curve; if the existence exists, entering S5, and if the existence does not exist, ending the optimization process;
s4: calculating the running time required to be adjusted according to the replacement adjustment process;
s5: replacing part of traction working conditions on other gentle slopes;
s6: judging whether the overall operation time meets the constraint; if yes, the optimization process is ended, and if not, the step returns to S4.
S5 specifically comprises the following substeps:
s5.1: acquiring a preset running distance S of a replacement interval FP，lim And constant speed v before replacement c ；
S5.2: initializing the replacement upper limit speed v s And the total pull-coasting logarithm after replacement n;
s5.3: according to v s And n, substituting into formula to calculate the linear velocity v x And a post-replacement running distance S FP (ii) a The calculation formula is as follows:
(1-θ e )F(v s )+(θ f -1)F(v x )＝0
Figure BDA0003647932180000031
in the formula (I), the compound is shown in the specification,
Figure BDA0003647932180000032
is the accompanying variable at the turning point e of the all-traction-coasting;
Figure BDA0003647932180000033
is an accompanying variable at the turning point f of the coasting and the full traction;
Figure BDA0003647932180000034
is the integral constant of ae section;
c ef ＝c ae +(1-θ e )F(v s ) Is the ef section integration constant;
c fd ＝c ae is the integration constant of fd section;
s5.4: judging the running distance S of the current replacement pair FP Whether to reach the preset running distance S FP，lim If the two are the same, the replacement process is stopped, and if the two are not the same, the S5.5 is started;
s5.5: according to the running distance S of the current replacement pair FP Adjusting the upper limit operating speed v s (ii) a Will adjust the upper limit running speed v s Substituting into S5.3.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
1) The energy-saving operation optimization model considering the transmission efficiency more truly describes the actual condition of train operation.
2) The train energy-saving optimization operation is carried out after the transmission efficiency is considered, the energy-saving and high-efficiency operation can be realized in a section with lower transmission efficiency, the traction energy consumption is saved from the power supply side, the purpose of saving electric energy is realized, and meanwhile, the energy consumption calculation is more real and reliable.
Drawings
FIG. 1 is a train energy-saving optimized operation curve without special line condition constraint
FIG. 2 is a train transmission efficiency profile of the present invention;
FIG. 3 is a schematic flow diagram of the present invention;
FIG. 4 is a schematic flow chart of step 2 of the present invention;
FIG. 5 is a schematic diagram of the present invention after replacing the partial tow maneuver in other gentle ramps with a full power tow-coast pair;
FIG. 6 is a flowchart illustrating alternative computing steps according to the present invention.
Detailed Description
The invention adopts the maximum principle without considering the efficiency of a train traction transmission system:
a train operation model:
Figure BDA0003647932180000041
Figure BDA0003647932180000042
wherein u is t ，u b The control coefficients of the traction force and the braking force of the train respectively satisfy u t ∈[0，1]，u b ∈[0，1]And u is t ·u b =0,F (v) maximum tractive effort per unit mass of train, B (v) maximum braking effort per unit mass of train, w (v) train operating resistance, g r (x) Is the external ramp resistance.
In addition to this, train operating speed and time need to meet speed and overall time constraints
v(0)＝0，v(X)＝0，v(x)≤v lim (x)
t(X)-t(0)＝T
Wherein v is lim (x) Is the maximum allowable speed and T is the given overall run time.
According to the train operation model, constructing a Hamiltonian:
Figure BDA0003647932180000043
wherein u is t ，u b The control coefficients of the traction force and the braking force of the train respectively satisfy u t ∈[0，1]，u b ∈[0，1]And u is t ·u b =0, f (v) is the maximum tractive force per unit mass of the train, B (v) is the maximum braking force per unit mass of the train, w (v) is the train running resistance, g, (x) is the external ramp resistance.
Accompanying variable lambda 1 ＝λ 1 (x)，λ 2 ＝λ 2 (x) Is a solution to the companion equation:
Figure BDA0003647932180000051
Figure BDA0003647932180000052
wherein M is a complementary relaxation factor. Defining new companion variables
Figure BDA0003647932180000053
The Hamiltonian is converted to:
Figure BDA0003647932180000054
therefore, the optimal control working condition of the train can be obtained:
Figure BDA0003647932180000055
the accompanying variable lambda 1 is related to the total running time of the train in the calculation process, and the optimal speed of the constant-speed section in the running process is determined. According to the analysis results, the train energy-saving optimized operation curve without special line condition constraint is shown in figure 1:
the following derivation process is the patent protection process.
(1) Train transmission efficiency
The train transmission efficiency is related to the train running speed and the train traction level, and the corresponding relation is expressed as follows:
Figure BDA0003647932180000056
the specific rule is as follows:
v is less than or equal to v when the running speed of the train is lower down The train transmission efficiency is low no matter the size of the traction level of the train, i.e. eta = eta down 。
When train traction level is low u t ≤u t，down The train transmission efficiency is low no matter the running speed of the train, i.e. eta = eta down 。
When the train running speed is greater than a smaller value v > v down The train traction level exceeds a certain range u t ≥u t，up Or the train level is greater than a small value u t ＞u t，down When the train running speed exceeds a certain range v is more than or equal to v up Higher train transmission efficiency eta = eta up 。
The train transmission efficiency distribution is shown in fig. 2.
(2) Maximum principle application after considering train transmission efficiency
After transmission efficiency is considered, a Hamiltonian is constructed:
Figure BDA0003647932180000061
wherein the accompanying variable lambda 1 ＝λ 1 (x)，λ 2 ＝λ 2 (x) Is a solution to the companion equation:
Figure BDA0003647932180000062
Figure BDA0003647932180000063
wherein M is a complementary relaxation factor. Defining new companion variables
Figure BDA0003647932180000064
The Hamiltonian is converted to:
Figure BDA0003647932180000065
the sequence of operating conditions may be expressed as:
Figure BDA0003647932180000066
(3) Limited partial traction condition replacement
The limited part traction working condition occurs in the slope with smaller gradient, the additional resistance of the line is smaller, and the train needs to apply part traction force smaller than the maximum traction force to keep constant speed, namely the applied traction force is as follows: f (v) is more than 0 c )＜F max The value of its accompanying variable θ =1. However, according to the efficiency law of the train transmission system in (2), on the slope with less additional resistance, the lower traction level u < u is used for a long time t，min Maintaining a constant speed will result in a less efficient transmission and a less energy efficient train operation, and therefore, the additional ramp drag-w (v) c )＜g r ＜u t，min F(v c )-w(v c ) Under the condition of (1), partial traction working conditions are replaced by a full traction-idle running pair mode so as to improve the efficiency of the transmission system. Such ramps are referred to as other gentle ramps, with the other imposed traction levels u ≧ u t，min The ramp that maintains the constant speed is a limited gentle ramp.
According to the end point state constraint conditions of other gentle ramps and the change rule of the accompanying variables, the replaced full traction-coasting pair is always started by full traction and ended by full traction, so that the replacement working condition is at least a full traction-coasting-full traction process. Meanwhile, in the replacement process, the speed of the end point is equal to the constant speed before replacement, the position of the end point is the starting point and the end point of other gentle slopes, and the running distance after replacement is kept unchanged.
Therefore, the flow of this embodiment is shown in fig. 3, and the method includes:
s1: acquiring basic data: train weight (M), train traction/braking characteristics, line speed limit (v) lim ) Total run time limit (T) lim )。
S2: train operation energy-saving optimization is carried out according to PMP under the condition that the transmission efficiency of a train traction system is not considered, and an accompanying variable lambda is obtained through calculation 1 The specific steps are shown in fig. 4:
s2.1: and calculating the running time of the maximum capacity running of the train. And drawing a running curve of the train according to the operating modes of full-force traction, constant speed and full-force braking according to the fluctuation and speed limit of the line ramp and the train traction/braking characteristics, and calculating the running time.
S2.2: and judging the constraint relation between the maximum capacity running time and the total time. If the maximum capacity runtime is shorter than the given total time constraint, S2.3 is entered, otherwise the optimization process is ended directly.
S2.3: calculating lambda 1 ，v c ，v d . Accompanying variable lambda 1 And traction/braking optimum constant speed v c ，v d There is a one-to-one correspondence between, and v c ，v d The total train operating time will be affected. If v is not present in the current calculation c Initialization may be according to the following:
Figure BDA0003647932180000071
λ can be calculated according to 1 ，ν d ：
λ 1 +v c 2 F 0 (v c )＝0
Figure BDA0003647932180000072
v c Optimum constant speed v for traction d Optimum constant speed for electric braking, F 0 As unit basic resistance, and alpha as regenerative energy utilization rate
S2.4: binding rate limiting, v c ，v d And dividing the interval ramp. According to the relationship between the additional resistance and the drag force of the line, the line ramp is divided into a large uphill slope, a large downhill slope, a moderate uphill slope, a moderate downhill slope and a regenerative energy-saving ramp.
S2.5: and clearing the constant-speed sections in the ramp partition table. And respectively inserting a constant speed interval starting point constant speed area and an interval end point constant speed area at the end of the partition list.
S2.6: the constant velocity zone is connected. And connecting the constant-speed areas end to end according to the working condition switching condition and the actual condition to form a global train operation optimization curve.
S2.7: the total train running time is calculated and compared to the total time constraint. If the constraint is not met, the method enters S2.8, readjusts, and if the constraint is met, the optimization process is ended to obtain a train energy-saving optimization operation curve and a global adjoint variable lambda 1 。
S2.8: adjusting v according to run time and time constraints c . If the runtime is below the time constraint, then increase v c If the run time is above the time constraint, then v is reduced c . The adjustment result is returned to S2.3.
S3: a gentle ramp, i.e. a gentle uphill slope in S2.4, is identified that requires the implementation of a partial traction condition. If there are other gentle slopes in the gentle uphill, the process proceeds to S5, and if not, the optimization calculation is ended.
S4: the runtime to be adjusted is calculated based on the alternate adjustment of the all-pull-coast pair. The total pull-idle pairs calculated according to the position constraints allow the overall operation time to change, and the operation time of the non-replacement interval needs to be adjusted, so that the overall operation time meets the constraints. If the overall runtime is greater than the time constraint, the overall runtime is shortened, and if the overall time is less than the time constraint, the overall runtime is increased.
S5: and replacing partial traction operation in other gentle slopes by full-force traction-coasting pairs according to the relation between the running speed and the speed limit. The schematic diagram after replacement is shown in FIG. 5:
the specific steps of the replacement calculation are shown in fig. 6.
S5.1: obtaining a preset running distance S of a replacement interval FP，lim And constant speed v before replacement c 。
S5.2: initializing the replacement upper limit speed v s And a total pull-coast logarithm after replacement n.
S5.3: according to v s And n, substituting into formula to calculate the lower linear velocity v x And a post-replacement running distance S FP . The calculation formula is as follows:
(1-θ e )F(v s )+(θ f -1)F(v x )＝0
Figure BDA0003647932180000081
in the formula (I), the compound is shown in the specification,
Figure BDA0003647932180000082
is the accompanying variable at turning point e of the all pull-coast.
Figure BDA0003647932180000083
Is the accompanying variable at the coasting-total traction turning point f.
Figure BDA0003647932180000084
Is the integration constant of ae segments.
c ef ＝c ae +(1-θ e )F(v s ) Is the ef section integration constant.
c fd ＝c ae Is the integration constant for the fd segment.
S5.4: judging the running distance S of the current replacement pair FP Whether to reach the preset running distance S FP，lim If the two are the same, the replacement process is stopped, otherwise, S5.5 is entered.
S5.5: according to the running distance of the current replacement pairFrom S FP Adjusting the upper limit operating speed v s . Will adjust the upper limit running speed v s Substituting into S5.3.
S6: and judging whether the overall running time of the train meets the constraint, if so, finishing the optimization calculation, and if not, returning to S4.
According to the optimization algorithm, the output result is a train operation sequence and a train optimization operation curve.

Claims (3)

1. A train energy-saving optimized operation method considering train traction transmission system efficiency is characterized by comprising the following steps:
s1: acquiring data of a section to be optimized of a line, wherein the data comprises train information, locomotive information, line data, line speed limit and timetable data;
s2: performing operation optimization without considering the efficiency of a train transmission system aiming at the range of the line to be optimized to obtain an optimized operation curve of the train;
s3: judging whether other gentle slopes exist in the optimized curve; if the existence exists, entering S5, and if the existence does not exist, ending the optimization process;
s4: calculating the running time required to be adjusted according to the replacement adjustment process;
s5: replacing part of traction working conditions on other gentle slopes;
s6: judging whether the overall operation time meets the constraint; if yes, the optimization process is ended, and if not, the step returns to S4.
2. The train energy-saving optimized operation method considering train traction drive system efficiency according to claim 1, wherein S2 comprises the following sub-steps:
s2.1: calculating the shortest running time of the train; judging whether the shortest running time is lower than the time constraint, if so, entering a subsequent optimization process, and if so, directly ending the optimization process;
s2.2: dividing constant-speed areas according to time constraints and ramp partitions, and connecting the constant-speed areas to obtain a train optimization curve;
s2.3: and judging whether the optimized running time meets the constraint or not, and if not, entering S2.2.
3. The train energy-saving optimized operation method considering train traction drive system efficiency according to claim 1, wherein S5 comprises the following sub-steps:
s5.1: acquiring a preset running distance S of a replacement interval FP，lim And constant speed v before replacement c ；
S5.2: initializing the replacement upper limit speed v s And a total pull-coast logarithm after replacement n;
s5.3: according to v s And n, substituting into formula to calculate the lower linear velocity v x And a post-replacement running distance S FP (ii) a The calculation formula is as follows:
(1-θ e )F(v s )+(θ f -1)F(v x )＝0
Figure FDA0003647932170000011
in the formula (I), the compound is shown in the specification,
Figure FDA0003647932170000012
is the accompanying variable at the turning point e of the all-traction-coasting;
Figure FDA0003647932170000013
is an accompanying variable at the turning point f of the coasting and the full traction;
Figure FDA0003647932170000021
is the integral constant of ae section;
c ef ＝c ae +(1-θ e )F(v s ) Is the ef section integration constant;
c fd ＝c ae is the integration constant of fd section;
s5.4: determining a current replacementRunning distance S of pairs FP Whether to reach the preset running distance S FP，lim If the two are the same, the replacement process is stopped, and if the two are not the same, the S5.5 is started;
s5.5: according to the running distance S of the current replacement pair FP Adjusting the upper limit operating speed v s (ii) a Will adjust the upper limit running speed v s Substituting into S5.3.
CN202210540361.XA 2022-05-17 2022-05-17 Train energy-saving optimized operation method considering train traction transmission system efficiency Pending CN115203816A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210540361.XA CN115203816A (en) 2022-05-17 2022-05-17 Train energy-saving optimized operation method considering train traction transmission system efficiency

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210540361.XA CN115203816A (en) 2022-05-17 2022-05-17 Train energy-saving optimized operation method considering train traction transmission system efficiency

Publications (1)

Publication Number Publication Date
CN115203816A true CN115203816A (en) 2022-10-18

Family

ID=83574483

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210540361.XA Pending CN115203816A (en) 2022-05-17 2022-05-17 Train energy-saving optimized operation method considering train traction transmission system efficiency

Country Status (1)

Country Link
CN (1) CN115203816A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116062004A (en) * 2023-03-23 2023-05-05 西南交通大学 Energy-saving speed curve adjustment method considering train control force smoothness
CN117112987A (en) * 2023-09-08 2023-11-24 西南交通大学 Method for solving optimal train operation curve based on maximum principle

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116062004A (en) * 2023-03-23 2023-05-05 西南交通大学 Energy-saving speed curve adjustment method considering train control force smoothness
CN116062004B (en) * 2023-03-23 2024-07-23 西南交通大学 Energy-saving speed curve adjustment method considering train control force smoothness
CN117112987A (en) * 2023-09-08 2023-11-24 西南交通大学 Method for solving optimal train operation curve based on maximum principle

Similar Documents

Publication Publication Date Title
CN115203816A (en) Train energy-saving optimized operation method considering train traction transmission system efficiency
CN109815536B (en) Urban rail transit energy-saving timetable and operation curve optimization method
CN109783890B (en) Heavy-load train operation curve multi-objective optimization method based on coupler and draft gear model
CN102951165B (en) Rail train electric energy saving operation control method
CN110795834B (en) Urban rail train energy consumption optimization method with intermittent power supply
CN104590333A (en) Railway train intelligent operation optimization control system
CN107704975A (en) Subway train energy-saving run optimization method and system based on biogeography algorithm
Li et al. Energy-constraint operation strategy for high-speed railway
Calderaro et al. An algorithm to optimize speed profiles of the metro vehicles for minimizing energy consumption
CN109398426B (en) Energy-saving driving strategy optimization method based on discrete ant colony algorithm under timing condition
CN109703593B (en) Comprehensive optimization method for whole-district operation of contact-net-free tramcar
CN111409673A (en) Train quasi-point energy-saving operation method based on dynamic programming algorithm
CN111580391B (en) Motor train unit traction torque control method based on model prediction
CN106740998B (en) The energy saving control methods of urban track traffic CBTC system onboards ATO
CN115221717A (en) Operation curve rolling optimization method for reducing longitudinal impulse of heavy-duty train
CN109376437A (en) A kind of vehicle-mounted energy storage optimal control method of new energy based on multi-objective genetic algorithm
Zhang et al. Pareto multi-objective optimization of metro train energy-saving operation using improved NSGA-II algorithms
Zhou et al. Real-time energy-efficient optimal control of high-speed electric train
Ding et al. Simulation algorithm for energy-efficient train control under moving block system
CN110356396A (en) A method of considering the electric car speed instantaneous optimization of road grade
Wang et al. Analysis of energy consumption characteristics based on simulation and traction calculation model for the crh electric motor train units
CN114597951B (en) Optimization method for energy-saving operation of electric automobile participating in alternating-current urban rail power supply system
Li et al. Train energy-efficient operation with stochastic resistance coefficient
Ke et al. Model of traction system and speed control for single train of Taipei mass rapid transit system
Jin et al. Operation Optimal Control of Urban Rail Train Based on Multi-Objective Particle Swarm Optimization.

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination