CN108725519A - A kind of route map of train optimization method reducing operation energy consumption - Google Patents
A kind of route map of train optimization method reducing operation energy consumption Download PDFInfo
- Publication number
- CN108725519A CN108725519A CN201810076618.4A CN201810076618A CN108725519A CN 108725519 A CN108725519 A CN 108725519A CN 201810076618 A CN201810076618 A CN 201810076618A CN 108725519 A CN108725519 A CN 108725519A
- Authority
- CN
- China
- Prior art keywords
- train
- time
- braking
- regenerative braking
- section
- 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
Links
Classifications
-
- 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
- B61L27/14—Following schedules
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L7/00—Electrodynamic brake systems for vehicles in general
- B60L7/10—Dynamic electric regenerative braking
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
- B61L27/04—Automatic systems, e.g. controlled by train; Change-over to manual control
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses a kind of route map of train optimization methods reducing operation energy consumption, belong to urban track traffic service chart optimisation technique field.The method is specific as follows：Determine the speed separation v of regenerative braking and mechanical brakingmin；Calculate the overlapping time O (h, x) of train traction and regenerative braking；Calculate regenerative braking energy utilization rate α；Calculate the electric energy that train i is consumed in section (n, n+1)Calculate the regenerative braking energy that train i is utilized in section (n, n+1)The gross energy E (h, x) that train consumes in the process of running is calculated, the model with the total operation energy consumption of all trains in constrained all fronts is obtained.The method of the invention can be used for optimizing route map of train, improve the utilization rate of regenerative braking energy, reduce total operation energy consumption.
Description
Technical field
The present invention relates to a kind of route map of train optimization methods reducing operation energy consumption, and in particular to a kind of raising regeneration system
The Train optimization method of kinetic energy efficiency belongs to urban track traffic service chart optimisation technique neck
Domain.
Background technology
In recent years, urban track traffic is fast-developing, and quick, comfortable service is provided for passenger, but with network
The expansion of scale, operating mileage increase, and run energy consumption rapid development, and operation cost is substantially improved.Improve the profit of regenerative braking energy
It is the effective means for reducing operation energy consumption with rate.Wherein, by optimizing route map of train, the real-time profit of regenerative braking energy is realized
With being the method that current cost is minimum, operation is the easiest.
At this stage, the research of related route map of train optimization has had certain accumulation in theory.It is most of about drop
The research of low operation energy consumption, without the operational process of detailed analysis train, it is believed that train is all made using regeneration in the deboost phase
Flowing mode.Leading to optimum results and actual conditions, there are certain deviations, cannot accurately reflect the energy of City Rail Transit System
The saving situation of consumption and cost.
Invention content
The purpose of the present invention is to provide a kind of route map of train optimization method reducing operation energy consumption, specially one kind carries
The city railway train service chart optimization method of high regenerative braking energy utilization rate.The method is used for optimizing route map of train, drops
Low operation energy consumption and operation cost.
The purpose of the present invention is realized by following technical scheme：
A kind of Train optimization method, steps are as follows for the method：
Step 1, the speed separation v of regenerative braking and mechanical braking is determinedmin；
Train is divided into three phases in the operational process of section：Traction, coasting and braking, train make first in the deboost phase
With regenerative braking mode, mechanical braking mode, mechanical braking stage is used to be generated without regenerative braking energy when speed is relatively low, base area
Iron runs nearest one month historical data, determines the speed separation v of regenerative braking and mechanical brakingmin；
Step 2, the overlapping time O (h, x) of train traction and regenerative braking is calculated；
According to train operation feature, arriving and leaving moment and dwell time, departure interval and the section run time of train are determined
Relationship；
When train i is drawn, and train i+1 is braked, train i is located at this section (n, n+1), and train i+1 is located at (n-1, n)
The overlapping time O of this section, train traction and braking1(h, x) is divided into four kinds of situations：The traction stage of train i has terminated, row
Vehicle i+1 not yet starts the regenerative braking stage；Train i is in the traction stage, and train i+1 is in the regenerative braking stage, and train i is opened
At the time of beginning to start regenerative braking earlier than train i+1 at the time of traction；Train i is in the traction stage, and train i+1 is in regeneration and makes
The dynamic stage, and train i starts to be later than train i+1 at the time of traction at the time of start regenerative braking；The traction stage of train i is not yet
Start, the regenerative braking stage of train i+1 has terminated；
When train i is braked, and train i+1 is drawn, two vehicles are located at this section (n, n+1), train traction and braking simultaneously
Overlapping time O2(h, x) is divided into four kinds of situations：The traction stage of train i+1 has terminated, and train i not yet starts regenerative braking rank
Section；Train i+1 is in the traction stage, and train i is in the regenerative braking stage, and train i+1 at the time of start traction earlier than train i
At the time of starting braking；Train i+1 is in the traction stage, and train i is in the deboost phase, and at the time of train i+1 starts traction
At the time of being later than train i and start regenerative braking；The traction stage of train i+1 not yet starts, and the regenerative braking stage of train i has tied
Beam；
When train i is drawn, and train i+1 is braked, two parking stalls are likely to be at different power supply sections in different sections,
When two trains are in the same power supply section and n ≠ 1, the value of λ (n-1, n) takes 1；When two trains are in different power supply sections
When, the value of λ (n-1, n) takes 0；
The overlapping time of all train tractions and braking includes O on circuit1(h, x) and O2The sum of (h, x)；
Wherein, i indicates train index, i.e. i=1,2 ..., I；I is train quantity；N indicates that station indexes, i.e. n=1,
2,…,N；N is station quantity；xnFor the dwell time at the stations n；tnFor the run time of section (n, n+1)；H is the departure interval；For the acceleration time of section (n, n+1)；For the braking time of section (n, n+1)；B is the mechanical braking stage
Acceleration；At the time of station n being left for train i；For train i get to the station n at the time of；
Step 3, regenerative braking energy utilization rate α is calculated；
The ratio of the overlapping time of train traction and braking and regenerative braking time are the utilization rate of regenerative braking energy, are indicated
The producing level of regenerative braking energy；
Step 4, the electric energy that train i is consumed in section (n, n+1) is calculated
For train i in section (n, n+1) interior running under power, the traction stage is approximately that constant force traction and invariable power draw two
Stage, empirically determined electric energy are converted into the conversion ratio η of kinetic energy1, determined according to Newton's second law and to be consumed in the section
Electric energy；
Wherein, PaFor specified traction power；FaFor maximum drawbar pull；M is train weight；W is unit resistance；
Step 5, the regenerative braking energy that train i is utilized in section (n, n+1) is calculated
For train i when section (n, n+1) inside brake is run, the regenerative braking stage is approximately invariable power braking and constant force braking
Two stages, mechanical braking stage do not generate regenerative braking energy, and empirically determined kinetic energy is converted into the conversion ratio η of electric energy2, root
The regenerative braking energy generated in the section is determined according to Newton's second law, according to regenerative braking energy utilization rate, is determined in the section
The regenerative braking energy utilized；
Wherein, PbFor rated brake horse-power；FbFor maximum braking force；
Step 6, the gross energy E (h, x) that train consumes in the process of running is calculated；
The gross energy that train consumes in the process of running is all trains in the traction energy consumption in all sections and utilizes again
The difference of raw Brake Energy；
Allow departure interval, dwell time and run time to have fluctuation, obtains always transporting with all trains in constrained all fronts
The model of row energy consumption：
Wherein, Z is set of integers, lhAnd uhThe respectively permitted minimum value of departing time interval and maximum value, lnAnd unPoint
It Wei not dwell time permitted minimum value and maximum value.lTAnd uTThe respectively permitted minimum value of run time and maximum value.
The total operation energy consumption model of all trains in the constrained all fronts of band can by many existing ripe algorithms into
Row solves, such as genetic algorithm can be realized as the solution to the model.
Advantageous effect
The present invention is used for optimizing route map of train, improves the utilization rate of regenerative braking energy, reduces total operation energy consumption, and have
Following advantage：(1) adjustment route map of train reduces the operation energy consumption and operation cost of operator；(2) model is simple, is easy to manage
Solution and calculating, application are stronger.(3) heuritic approach is used, using computer simulation, calculating speed is fast.
Description of the drawings
Fig. 1 is the overlapping time schematic diagram of the train traction and braking of the method for the invention；
In Fig. 1,At the time of station n being left for train i,For train i get to the station n at the time of,For train i from
The stations n rear haulage is opened at the time of terminate,At the time of to start braking before the stations train i arrival n, vminIndicate that regenerative braking terminates machine
The speed that tool braking starts, dash area indicate the overlapping time of front and back two train tractions and braking；
Fig. 2 is the traction power-time diagram of the method for the invention；
Fig. 3 is the braking power-time diagram of the method for the invention.
Specific implementation mode
The present invention is described in detail in the following with reference to the drawings and specific embodiments, but not limited to this.
The present invention provides a kind of route map of train optimization method reducing operation energy consumption, founding mathematical models (carry
The total operation energy consumption of all trains in all fronts of constraint), the dwell time for adjusting the departure interval and each standing, improve regenerative braking energy
Utilization rate reduces total energy consumption.
In the method for the invention, according to the operation data of subway operator, the current of toll line is obtained first
The title of timetable, station indicates with numbering, as shown in table 1 below.
Table 1 current time table
Assuming that the run time in each section, acceleration time and braking time are constant, each section run time, acceleration time
It is as shown in table 2 below with braking time.
2 each section run time of table, acceleration time and braking time
Departure interval h under current time table is 134s, and train quantity I is 20 row, and station quantity N is 14, train matter
Amount M is 286 600kg, specified traction power PaFor 3250kW, rated brake horse-power PbFor 4 300kW, maximum drawbar pull FaFor
312.87kN maximum braking force FbIt is 0.08N/kg, the speed of regenerative braking and mechanical braking for 258.40kN, unit resistance w
Separation vminAcceleration b for 8m/s, mechanical braking stage is 1m/s2, electric energy is converted into the conversion ratio η of kinetic energy1It is 0.7, moves
The conversion ratio η of electric energy can be converted into2It is 0.8.
According to the mathematical model that the present invention establishes, the total energy consumption under current time table is calculated.
Step 1, the speed separation v of regenerative braking and mechanical braking is determinedmin；
Train is divided into three phases in the operational process of section：Traction, coasting and braking, train make first in the deboost phase
With regenerative braking mode, mechanical braking mode, mechanical braking stage is used to be generated without regenerative braking energy when speed is relatively low, base area
The historical data of iron operation determines the speed separation v of regenerative braking and mechanical brakingmin；
Step 2, the overlapping time O (h, x) of train traction and braking is calculated；
According to train operation feature, arriving and leaving moment and dwell time, departure interval and the section run time of train are determined
Relationship；
As shown in Figure 1, when train i tractions, when train i+1 is braked, train i is located at this section (n, n+1), train i+1
Positioned at this section (n-1, n), the overlapping time O of train traction and braking1(h, x) is divided into four kinds of situations：The traction rank of train i
Section has terminated, and train i+1 not yet starts the regenerative braking stage；Train i is in the traction stage, and train i+1 is in regenerative braking rank
Section, and train i is at the time of start traction at the time of start regenerative braking earlier than train i+1；Train i is in traction stage, train i
+ 1 is in the regenerative braking stage, and at the time of train i starts to be later than train i+1 at the time of traction and start regenerative braking；Train i's
The traction stage not yet starts, and the regenerative braking stage of train i+1 has terminated；
When train i is braked, and train i+1 is drawn, two vehicles are located at this section (n, n+1), train traction and braking simultaneously
Overlapping time O2(h, x) is divided into four kinds of situations：The traction stage of train i+1 has terminated, and train i not yet starts regenerative braking rank
Section；Train i+1 is in the traction stage, and train i is in the regenerative braking stage, and train i+1 at the time of start traction earlier than train i
At the time of starting braking；Train i+1 is in the traction stage, and train i is in the deboost phase, and at the time of train i+1 starts traction
At the time of being later than train i and start regenerative braking；The traction stage of train i+1 not yet starts, and the regenerative braking stage of train i has tied
Beam；
When train i is drawn, and train i+1 is braked, two parking stalls are likely to be at different power supply sections in different sections,
When two trains are in the same power supply section and n ≠ 1, the value of λ (n-1, n) takes 1；When two trains are in different power supply sections
When, the value of λ (n-1, n) takes 0；
The overlapping time of all train tractions and braking includes O on circuit1(h, x) and O2The sum of (h, x)；
According to the speed separation v of regenerative braking and mechanical braking that step 1 determinesmin, substitute into dwell time xn, dispatch a car
It is spaced h, section (n, n+1) run time tn, section (n, the n+1) acceleration timeSection (n, n+1) braking timeThe acceleration b in mechanical braking stage, determines the overlapping time of all train tractions and braking on circuit.
Step 3, regenerative braking energy utilization rate α is calculated；
The ratio of the overlapping time of train traction and braking and regenerative braking time are the utilization rate of regenerative braking energy, are indicated
The producing level of regenerative braking energy；
According to the speed separation v of regenerative braking and mechanical braking that step 1 determinesminThe train traction determined with step 2
With the overlapping time of braking, the braking time of section (n, n+1) is substituted intoWith the acceleration b in mechanical braking stage, determine again
Raw Brake Energy utilization rate.
Step 4, the electric energy that train i is consumed in section (n, n+1) is calculated
As shown in Fig. 2, train i, in section (n, n+1) interior running under power, the traction stage can be approximately constant force traction and perseverance
Power draws two stages, and empirically determined electric energy is converted into the conversion ratio η of kinetic energy1, being determined according to Newton's second law should
The electric energy consumed in section；
Substitute into specified traction power Pa, maximum drawbar pull Fa, train weight M, unit resistance w and electric energy are converted into kinetic energy
Conversion ratio η1, determine the electric energy that train i is consumed in section (n, n+1).
Step 5, the regenerative braking energy that train i is utilized in section (n, n+1) is calculated
As shown in figure 3, train i is when section (n, n+1) inside brake is run, the deboost phase can be approximately invariable power braking and
Constant force is braked two stages, and the mechanical braking stage does not generate regenerative braking energy, and empirically determined kinetic energy is converted into turning for electric energy
Rate η2, the regenerative braking energy generated in the section is determined according to Newton's second law, according to regenerative braking energy utilization rate, is determined
The regenerative braking energy utilized in the section；
According to the regenerative braking energy utilization rate that step 3 determines, rated brake horse-power P is substituted intob, maximum braking force Fb, train matter
M is measured, unit resistance w and kinetic energy are converted into the conversion ratio η of electric energy2, determine the regeneration system that train i is utilized in section (n, n+1)
Kinetic energy.
Step 6, the gross energy E (h, x) that train consumes in the process of running is calculated；
The gross energy that train consumes in the process of running is all trains in the traction energy consumption in all sections and utilizes again
The difference of raw Brake Energy；
According to above-mentioned each data and the model that proposes through the invention, the utilization rate of regenerative braking energy is under current time table
10.71%, total operation energy consumption is 3576.65kW.h.
Using heuritic approach-genetic algorithm adjustment departure interval and dwell time, optimizes route map of train, improve again
The utilization rate of raw Brake Energy, reduces total energy consumption, is as follows：
Step 1 chromosome coding
N number of decision variable is shared in the embodiment of the present invention, with a chromosome Yk=(y1,y2,y3,......yN) replace mould
One feasible solution (h, x of type1,x2,x3,......xN-1), a gene of chromosome corresponds to a decision of corresponding position
Variable.Meanwhile by each genetic transformation of chromosome be binary-coded representation.
Step 2 initialization population
Population scale pop_size is set, the pop_size chromosome Y for meeting constraints are randomly generatedk=(y1,y2,
y3,......yN)。
Step 3 fitness evaluation
We select object function E (h, x) to be used as fitness function in the embodiment of the present invention, it should be noted that heredity
Algorithm commonly used to solve object function maximum value, but need to solve in the present embodiment be object function minimum value,
So being handled object function to obtain fitness function Eval (Y)=A-E (h, x), A is a sufficiently large constant, is made
The value for obtaining fitness function is always positive value.
Step 4 selects
Calculate that method selects pop_size outstanding chromosomes and enters next-generation population using roulette.According to each chromosome
Adaptive value calculates the probability P of each chromosomek, chromosome probability is updated, is enabled
K=1,2 ..., pop_size, it is random generate a c ∈ (0,1] real number c, c ∈ (P will be metk-1,Pk] chromosome YkChoosing
It selects out.
Step 5 is intersected
Define crossover probability Pc, a real number r ∈ (0,1) is generated at random, if r < Pc, choosing two chromosomes will intersect
Gene after point swaps, otherwise without intersecting.If newly generated chromosome meets constraints, with new dyeing
Body replaces original chromosome；Otherwise, it is constant to retain original chromosome.
Step 6 makes a variation
Define mutation probability Pm, a real number s ∈ (0,1) is randomly generated, if s < Pm, select one it is binary-coded
Chromosome is into row variation, otherwise without variation.If newly generated chromosome meets constraints, replaced with new chromosome
Chromosome originally；Otherwise, it is constant to retain original chromosome.
Iterations max_generation is defined, step 3-6 is repeated, until reaching iterations max_
generation。
According to model proposed by the present invention, departure interval and dwell time, dispatching a car after optimization are adjusted using genetic algorithm
Between be divided into 136s, table is as shown in table 3 below at the time of after optimization：
Table at the time of after the optimization of table 3
The utilization rate of table at the time of according to after optimization, regenerative braking energy is 22.32%, and total operation energy consumption is
3420.34kW.h.Compared with current time table, the utilization rate of the regenerative braking energy of table improves (22.32- at the time of after optimization
10.71)/10.71=108.40%, total operation energy consumption reduce (3 576.65-3420.34)/3576.65=4.37%, this
Illustrate that a kind of route map of train optimization method reducing operation energy consumption proposed by the present invention has preferable effect.
It these are only the preferred embodiment of the present invention, be not intended to restrict the invention, for those skilled in the art
For member, the invention may be variously modified and varied.Any modification made by all within the spirits and principles of the present invention,
Equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of Train optimization method, which is characterized in that steps are as follows for the method：
Step 1, the speed separation v of regenerative braking and mechanical braking is determinedmin；
Step 2, the overlapping time O (h, x) of train traction and regenerative braking is calculated；
Step 3, regenerative braking energy utilization rate α is calculated；
Step 4, the electric energy that train i is consumed in section (n, n+1) is calculated
Step 5, the regenerative braking energy that train i is utilized in section (n, n+1) is calculated
Step 6, the gross energy E (h, x) that train consumes in the process of running is calculated, is obtained total with all trains in constrained all fronts
The model of operation energy consumption.
2. a kind of Train optimization method according to claim 1, which is characterized in that the step
Rapid 1 medium velocity separation determines that method is as follows：
Train is divided into three phases in the operational process of section：Traction, coasting and braking, train use again first in the deboost phase
Raw mode of braking uses mechanical braking mode, mechanical braking stage to generate without regenerative braking energy, transported according to subway when speed is relatively low
The historical data of battalion determines the speed separation v of regenerative braking and mechanical brakingmin。
3. a kind of Train optimization method according to claim 2, which is characterized in that described to go through
The metro operation data that history data are nearest one month.
4. a kind of Train optimization method according to claim 1, which is characterized in that the step
Overlapping time O (h, x) computational methods are as follows in rapid 2：
According to train operation feature, the pass of the arriving and leaving moment and dwell time, departure interval and section run time of train are determined
System；
When train i is drawn, when train i+1 braking, train i is located at this section (n, n+1), train i+1 be located at (n-1, n) this
Section calculates the overlapping time O of train traction and braking1(h,x)；
When train i is braked, and train i+1 is drawn, two vehicles are located at this section (n, n+1) simultaneously, calculate train traction and braking
Overlapping time O2(h,x)；
When train i is drawn, when train i+1 braking, two parking stalls in different sections, when two trains in the same power supply section and
When n ≠ 1, the value of λ (n-1, n) takes 1；When two trains are in different power supply sections, the value of λ (n-1, n) takes 0；
The overlapping time of all train tractions and braking includes O on circuit1(h, x) and O2The sum of (h, x)；
Wherein, i indicates train index, i.e. i=1,2 ..., I；I is train quantity；N indicates station index, i.e. n=1,2 ..., N；
N is station quantity；xnFor the dwell time at the stations n；tnFor the run time of section (n, n+1)；H is the departure interval；For train i
At the time of leaving station n；For train i get to the station n at the time of.
5. a kind of Train optimization method according to claim 4, which is characterized in that the row
Vehicle is drawn and the overlapping time O of braking1(h, x) is divided into four kinds of situations：The first, the traction stage of train i has terminated, train i+
1 not yet starts the regenerative braking stage；Second, train i is in the traction stage, and train i+1 is in regenerative braking stage, and train
At the time of i starts to start regenerative braking earlier than train i+1 at the time of traction；The third, train i is in traction stage, train i+1
In the regenerative braking stage, and train i starts to be later than train i+1 at the time of traction at the time of start regenerative braking；4th kind, row
The traction stage of vehicle i not yet starts, and the regenerative braking stage of train i+1 has terminated；Then have：
Wherein,For the acceleration time of section (n, n+1)；For the braking time of section (n-1, n)；B is that machinery is made
The acceleration in dynamic stage.
6. a kind of Train optimization method according to claim 4, which is characterized in that the row
Vehicle is drawn and the overlapping time O of braking2(h, x) is divided into four kinds of situations：The first, the traction stage of train i+1 has terminated, train
I not yet starts the regenerative braking stage；Second, train i+1 is in the traction stage, and train i is in regenerative braking stage, and train
At the time of starting braking earlier than train i at the time of i+1 starts traction；The third, train i+1 is in the traction stage, and train i is in
Deboost phase, and at the time of train i+1 starts to be later than train i at the time of traction and start regenerative braking；4th kind, train i+1's
The traction stage not yet starts, and the regenerative braking stage of train i has terminated；Then have：
Wherein,For the acceleration time of section (n, n+1)；For the braking time of section (n, n+1)；B is that machinery is made
The acceleration in dynamic stage.
7. a kind of Train optimization method according to claim 1, which is characterized in that the step
It is specific as follows that regenerative braking energy utilization rate α is calculated in rapid 3：
The ratio of the overlapping time of train traction and braking and regenerative braking time are the utilization rate of regenerative braking energy, indicate regeneration
The producing level of Brake Energy；
Wherein,For the braking time of section (n, n+1)；B is the acceleration in mechanical braking stage.
8. a kind of Train optimization method according to claim 1, which is characterized in that the step
The electric energy that train i is consumed in section (n, n+1) is calculated in rapid 4It is specific as follows：
For train i in section (n, n+1) interior running under power, the traction stage is approximately that constant force traction and invariable power draw two ranks
Section, empirically determined electric energy are converted into the conversion ratio η of kinetic energy1, the electricity consumed in the section is determined according to Newton's second law
Energy；
Wherein, PaFor specified traction power；FaFor maximum drawbar pull；M is train weight；W is unit resistance；For section
The acceleration time of (n, n+1).
9. a kind of Train optimization method according to claim 1, which is characterized in that the step
The regenerative braking energy that train i is utilized in section (n, n+1) is calculated in rapid 5It is specific as follows：
For train i when section (n, n+1) inside brake is run, the regenerative braking stage is approximately that invariable power braking and constant force brake two
Stage, mechanical braking stage do not generate regenerative braking energy, and empirically determined kinetic energy is converted into the conversion ratio η of electric energy2, according to ox
The second law that pauses determines the regenerative braking energy generated in the section, according to regenerative braking energy utilization rate, determines in the section and utilizes
Regenerative braking energy；
Wherein, PbFor rated brake horse-power；FbFor maximum braking force；For the braking time of section (n, n+1)；M is train
Quality；W is unit resistance.
10. a kind of Train optimization method according to claim 1, which is characterized in that described
It is specific as follows that the gross energy E (h, x) that train consumes in the process of running is calculated in step 6：
It in all sections traction energy consumption and the regeneration system that utilizes that the gross energy that train consumes in the process of running, which is all trains,
The difference of kinetic energy；
Allow departure interval, dwell time and run time to have fluctuation, obtains always running energy with all trains in constrained all fronts
The model of consumption：
Wherein, Z is set of integers, lhAnd uhThe respectively permitted minimum value of departing time interval and maximum value, lnAnd unRespectively
Dwell time permitted minimum value and maximum value.lTAnd uTThe respectively permitted minimum value of run time and maximum value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810076618.4A CN108725519A (en) | 2018-01-26 | 2018-01-26 | A kind of route map of train optimization method reducing operation energy consumption |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810076618.4A CN108725519A (en) | 2018-01-26 | 2018-01-26 | A kind of route map of train optimization method reducing operation energy consumption |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108725519A true CN108725519A (en) | 2018-11-02 |
Family
ID=63940495
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810076618.4A Pending CN108725519A (en) | 2018-01-26 | 2018-01-26 | A kind of route map of train optimization method reducing operation energy consumption |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108725519A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111114596A (en) * | 2019-12-26 | 2020-05-08 | 西南交通大学 | Multi-train speed curve collaborative optimization method considering network loss |
| CN111806241A (en) * | 2020-06-28 | 2020-10-23 | 同济大学 | Method for determining regenerative electric energy recovery space of rail transit train |
| CN112590867A (en) * | 2020-12-21 | 2021-04-02 | 中车青岛四方车辆研究所有限公司 | Urban rail train group speed optimization method and system based on vehicle-to-vehicle communication |
| CN113442731A (en) * | 2021-08-31 | 2021-09-28 | 通号城市轨道交通技术有限公司 | Intelligent train control method and device based on regenerative braking energy and electronic equipment |
| CN114954572A (en) * | 2022-06-14 | 2022-08-30 | 通号城市轨道交通技术有限公司 | Automatic train dispatching method and device based on traction energy consumption statistics |
| CN115991101A (en) * | 2023-03-23 | 2023-04-21 | 卡斯柯信号(北京)有限公司 | Train braking mode conversion method and device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103390111A (en) * | 2013-07-29 | 2013-11-13 | 北京交通大学 | Calculation method oriented to single-train running energy consumption of urban rail transit |
| CN104401370A (en) * | 2014-10-21 | 2015-03-11 | 北京交通大学 | Energy-saving optimization method for cooperative control on multiple trains |
| CN105083338A (en) * | 2015-08-25 | 2015-11-25 | 北京交通大学 | Train operation control method for maximumly utilizing renewable energy |
| CN106672027A (en) * | 2017-01-06 | 2017-05-17 | 广州地铁集团有限公司 | Urban rail transit ATS energy-saving time table compilation method |
-
2018
- 2018-01-26 CN CN201810076618.4A patent/CN108725519A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103390111A (en) * | 2013-07-29 | 2013-11-13 | 北京交通大学 | Calculation method oriented to single-train running energy consumption of urban rail transit |
| CN104401370A (en) * | 2014-10-21 | 2015-03-11 | 北京交通大学 | Energy-saving optimization method for cooperative control on multiple trains |
| CN105083338A (en) * | 2015-08-25 | 2015-11-25 | 北京交通大学 | Train operation control method for maximumly utilizing renewable energy |
| CN106672027A (en) * | 2017-01-06 | 2017-05-17 | 广州地铁集团有限公司 | Urban rail transit ATS energy-saving time table compilation method |
Non-Patent Citations (2)
| Title |
|---|
| 丁奕: "基于列车节能的时刻表制定方法研究", 《中国优秀硕士学位论文全文数据库，工程科技II辑》 * |
| 冯佳: "考虑节能目标的城市轨道交通列车运行行为优化研究", 《中国博士学位论文全文数据库 工程科技II辑》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111114596A (en) * | 2019-12-26 | 2020-05-08 | 西南交通大学 | Multi-train speed curve collaborative optimization method considering network loss |
| CN111114596B (en) * | 2019-12-26 | 2021-05-11 | 西南交通大学 | Multi-train speed curve collaborative optimization method considering network loss |
| CN111806241A (en) * | 2020-06-28 | 2020-10-23 | 同济大学 | Method for determining regenerative electric energy recovery space of rail transit train |
| CN111806241B (en) * | 2020-06-28 | 2022-02-18 | 同济大学 | Method for determining regenerative electric energy recovery space of rail transit train |
| CN112590867A (en) * | 2020-12-21 | 2021-04-02 | 中车青岛四方车辆研究所有限公司 | Urban rail train group speed optimization method and system based on vehicle-to-vehicle communication |
| CN112590867B (en) * | 2020-12-21 | 2022-05-27 | 中车青岛四方车辆研究所有限公司 | Urban rail train group speed optimization method and system based on vehicle-to-vehicle communication |
| CN113442731A (en) * | 2021-08-31 | 2021-09-28 | 通号城市轨道交通技术有限公司 | Intelligent train control method and device based on regenerative braking energy and electronic equipment |
| CN114954572A (en) * | 2022-06-14 | 2022-08-30 | 通号城市轨道交通技术有限公司 | Automatic train dispatching method and device based on traction energy consumption statistics |
| CN114954572B (en) * | 2022-06-14 | 2024-04-19 | 通号城市轨道交通技术有限公司 | Automatic train dispatching method and device based on traction energy consumption statistics |
| CN115991101A (en) * | 2023-03-23 | 2023-04-21 | 卡斯柯信号(北京)有限公司 | Train braking mode conversion method and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108725519A (en) | A kind of route map of train optimization method reducing operation energy consumption | |
| Zhao et al. | An integrated metro operation optimization to minimize energy consumption | |
| CN109815536B (en) | Urban rail transit energy-saving timetable and operation curve optimization method | |
| CN109657845B (en) | Urban rail transit train timetable optimization system for time-varying passenger flow | |
| Zhou et al. | Integrated optimization on train control and timetable to minimize net energy consumption of metro lines | |
| CN105460048B (en) | Comprehensive energy-saving control method and method integrating optimized manipulation and traffic scheduling for urban rail transit | |
| CN105930937B (en) | A kind of train operation scheduling Integrated Optimization considering subway speed line | |
| CN102360401B (en) | Method for designing urban rail transit energy-saving run chart based on genetic algorithm | |
| CN107704950A (en) | A kind of city rail train figure optimization method based on trip requirements and energy saving of system | |
| CN102495934B (en) | Design method for railway transport drawing power balanced run chart based on particle swarm algorithm | |
| CN107368920A (en) | A kind of off-peak period multi-train movement energy conservation optimizing method | |
| CN112633598A (en) | Comprehensive energy-saving optimization method for speed curve and timetable of urban rail transit train | |
| CN108883784A (en) | The method and train driver consulting system of drive advice are provided to train driver | |
| He et al. | Optimal control of metro energy conservation based on regenerative braking: A complex model study of trajectory and overlap time | |
| CN109583125A (en) | A kind of optimization method improving subway train regenerative braking energy utilization rate | |
| CN111680413B (en) | Tramcar timing energy-saving operation optimization method and system based on double-layer algorithm | |
| CN114298510A (en) | Time schedule and speed curve optimization method based on NSPSO algorithm | |
| CN108985662A (en) | A kind of train operation optimization method based on parallel immunity particle cluster algorithm | |
| CN109109913A (en) | A kind of information processing method for Rail Transit System efficiency organization of driving | |
| Zhao et al. | Driving strategy optimization and field test on an urban rail transit system | |
| Chuang et al. | Design of optimal coasting speed for saving social cost in mass rapid transit systems | |
| CN116307590A (en) | Electric bus charging scheduling method based on charging station dispatching strategy | |
| CN111523235A (en) | Energy-saving slope optimization method under combined condition of fast and slow vehicles | |
| Sharov et al. | The Irkutsk transportation master plan solutions for public transport system development | |
| Yildiz et al. | Traction energy optimization considering comfort parameter: A case study in Istanbul metro line |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181102 |