CN110795834B - Urban rail train energy consumption optimization method with intermittent power supply - Google Patents
Urban rail train energy consumption optimization method with intermittent power supply Download PDFInfo
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Abstract
The invention discloses an energy consumption optimization method for an urban rail train with intermittent power supply. The method is based on an improved time approximation search algorithm and comprises the following steps: step 1, carrying out stress analysis on an urban rail train and establishing a train dynamic model; step 2, performing algorithm construction on the train dynamic model, and judging whether the current acceleration needs to be adjusted or not according to the current operation condition of the train; step 3, calculating the energy consumption of the urban rail train according to the train running time, the running position, the working condition and the state SOC of the energy storage equipment; and 4, under the condition of limiting the running time and the running distance, establishing a time approximation search algorithm optimization model by analyzing the timing energy-saving optimization model, and realizing the optimization of the urban rail train energy consumption of intermittent power supply. The invention has the advantages of high convergence rate, good energy-saving effect and strong applicability.
Description
Technical Field
The invention belongs to an energy management optimization technology of an urban rail train, and particularly relates to an energy consumption optimization method of an urban rail train with intermittent power supply.
Background
As a zero-emission pollution-free green vehicle, the urban electric car can be used as an effective supplement for subways in the aspects of environmental protection, comfort level and transportation capacity, and is receiving more and more attention from people. Urban rail trains have great advantages in energy conservation and environmental protection, but the current situations of high concentration of energy utilization and low energy utilization rate are still not negligible.
The energy consumption cost of the urban rail transit train brings huge pressure to urban development. Therefore, the energy consumption influence factors of the urban rail transit train are analyzed, the breakthrough point for energy conservation and optimization is found, and the method has practical significance for reducing transportation cost, improving energy utilization rate and improving economic benefit and sustainable development.
At the present stage, research on an energy consumption optimization method of an urban rail train with intermittent power supply has been advanced to a certain extent. However, most of researches on reducing the running energy consumption are directed to the braking stage, energy is recovered by adopting a regenerative braking mode, and the running process of the train is not analyzed in detail. And the mode of recovering the running energy consumption by the regenerative braking of the train has lower recovery rate, so that the optimized result has deviation from the actual condition, and the energy consumption and cost saving condition of the urban rail transit cannot be accurately reflected.
Disclosure of Invention
The invention aims to provide an urban rail train energy consumption optimization method for intermittent power supply with good practicability and high convergence rate, so that the energy utilization rate is improved.
The technical solution for realizing the purpose of the invention is as follows: an urban rail train energy consumption optimization method with intermittent power supply comprises the following steps:
and 4, under the condition of limiting the running time and the running distance, establishing a time approximation search algorithm optimization model by analyzing the timing energy-saving optimization model, and realizing the optimization of the urban rail train energy consumption of intermittent power supply.
Further, the step 1 of performing stress analysis on the urban rail train to establish a train dynamics model specifically comprises the following steps:
step 1.1, firstly, obtaining the traction force F of the train at any moment by adopting an urban rail train traction characteristic curve:
in the formula, mu f Is the train tractive power coefficient, mu f ∈[0，1](ii) a v is the speed of the urban rail train; e t Is the nominal voltage of the super capacitor, F max The traction force of a constant power area of the train;
speed, V, of power change point of train max Is the maximum speed;
step 1.2, calculating the common braking force B, the emergency braking force B and the basic resistance w of the urban rail train 0 Additional resistance w j And a starting resistance w q ：
w 0 ＝a 1 +b 1 v+c 1 v 2 (3)
w q ＝A q (5)
In the formula, mu b Is the braking force coefficient of the urban rail train,
is coefficient of friction, ∑ K h For the total brake shoe force of the train, mu b ∈[0，1]；a 1 ，b 1 ，c 1 The coefficient is a basic resistance formula coefficient and is determined by the self characteristics of the vehicle; w is a i Is unit ramp resistance, w p Resistance generated for the number of passengers, w r Is the resistance per unit curve, w w R is the radius of the curve; tau is the air resistance coefficient, S is the windward area, rho is the air density,
as a relative velocity, A q Is a constant;
step 1.3, taking the intermittent power supply urban rail train as a quality point chain, and calculating average addition ramp resistance w according to the length of the urban rail train j ：
Wherein L is the train length; i.e. i i 、l i The thousands and the length of the ith ramp covered by the train are respectively; r i ，l ri Respectively the radius and the length of the ith curve covered by the urban rail train; x is the position corresponding to the train;
step 1.4, solving the dynamic model of the urban rail train, and when the train is started:
wherein M is the total mass of the train, g is the gravity acceleration, v is the running speed of the urban rail train 1 For upper starting speed, C is the resultant force of the train unit, F, w q 、w j 、w 0 Traction force, starting resistance, additional resistance and basic resistance which are obtained respectively;
when the urban rail train is respectively in a normal traction working condition, an idle working condition and a braking working condition:
acceleration a of urban rail train 0 Relationship to the resultant force of units:
wherein gamma is a rotation mass coefficient, is related to the urban rail train and is a constant value of 0.06.
Further, the step 2 of performing algorithm construction on the train dynamics model, and judging whether the current acceleration needs to be adjusted according to the current operation condition of the train comprises the specific steps of:
step 2.1, judging whether the current acceleration needs to be adjusted according to the current running working condition of the train:
firstly, when the train is in the traction working condition, the train traction force F is calculated according to the current running condition T ：
In the formula, F T Is the tractive force of the current operating condition, C is the resultant force of the train unit, w q 、w j 、w 0 Respectively a starting resistance, an additional resistance and a basic resistance, wherein M is the train mass, and g is the gravity acceleration;
judging whether the train can provide the traction force according to the train traction characteristic curve: if so, calculating the traction force use coefficient mu f (ii) a Otherwise, according to the maximum traction of the train, recalculating the acceleration:
in the formula, F max The maximum traction of the train at the current speed;
when the train is in the idle working condition, calculating the corresponding acceleration of the train:
a＝-(w j +w 0 )g (13)
thirdly, when the train is in the braking working condition, the corresponding braking force B of the train is used T ：
Judging whether the train can provide the braking force according to the train braking characteristic curve: if it is possible to do so,the braking force usage coefficient mu is calculated b (ii) a Otherwise, according to the maximum braking force of the train, recalculating the acceleration:
in the formula, B max The maximum braking force of the train at the current speed;
step 2.2, calculating the running distance of the train according to the adjusted acceleration:
a＝a 0 +Δ a ×Δ t ，a≤A (17)
in the formula, a is the acceleration corresponding to each simulation time unit; a is 0 The acceleration at the previous moment; delta of a To impact limit; delta t Is the simulation time unit size; a is the maximum acceleration;
in the formula, s is the current train running distance; s 0 The distance of train operation until the last simulation moment; v' and v are respectively the unit end speed and the starting speed at the current simulation moment.
Further, in step 3, the energy consumption of the urban rail train is calculated according to the train running time, the running position, the working condition and the state SOC of the energy storage device, and the formula is as follows:
in the formula, E is total train operation energy consumption, I (v) is traction current, delta t is simulation time unit step length, U is energy storage equipment nominal voltage, and P is a For auxiliary power consumption, eta sc When it is simulatedInter-cell discharge efficiency.
Further, the establishing of the time approximation search algorithm optimization model in the step 4 realizes the optimization of the urban rail train energy consumption of the intermittent power supply, and the specific steps are as follows:
step 4.1, in a starting stage, the train runs at the maximum traction acceleration, and runs at a constant speed at a speed limit value when the speed is increased to the maximum interval speed limit value; if the speed limit value of the next section is lower than that of the current section, the train is braked by the maximum braking force, so that the train runs to the next section in a deceleration way, and the speed is just the speed limit value of the next section; if the speed limit value of the next section is higher than that of the current section, the train runs at the starting point of the next section with the maximum traction acceleration until reaching the speed limit; when the train is about to arrive at the station, the train operates at the maximum traction force in a deceleration mode until the train stops, and the minimum operation time T is obtained min ；
Step 4.2, searching a speed limit transition section from the tail end of the operation line in the opposite direction: if no such segment exists, go to step 4.4; if the section exists, the operation is switched to the idling working condition from the starting point of the section, and if the speed is increased in the idling process, the train is braked to enable the operation speed to exceed the limit; if the speed is reduced, the intersection point of the coasting curve and the original braking curve is used as a new working condition conversion point; if no intersection point exists, the coasting speed is reduced to the size of the speed limit value, and then the vehicle travels to the next speed limit interval at a constant speed;
4.3, increasing the running time of the train by delta T compared with the original running time every time of adjusting the running mode, when the formula (20) is satisfied, taking the middle position of the section for segmenting again, starting from the middle position of the section, and returning to the step 4.2; when equation (21) is satisfied, the optimization terminates; if the equations (20) and (21) are not satisfied, the starting point of the line is moved forward by one segment, and the step 4.2 is returned to:
where k is the number of adjustment conditions, Δ T (i) For increased operation time after the ith adjustment of the operating conditions, T 0 Delta is the acceptable error limit value for the train running time;
step 4.4, searching from the last section forward in sequence, and searching when the traction force F is searched b (x) When the working condition of the train is 0, the train is turned into the idle running, and the step 4.2 is returned; if the coasting speed is reduced to 0 and the train does not arrive at the station yet, abandoning the working condition conversion of the section, keeping the original working condition and entering the step 4.5;
step 4.5, if the coasting switching is completed in all the braking sections, the total running time of the train is longer than the given time T 0 And then, reversely searching from the tail end of the line, converting from the train traction acceleration section to a cruising working condition, taking the intersection point of the cruising curve and the original coasting curve as a new coasting point, and converting to the step 4.3: if the total train running time is not more than the given time T 0 And obtaining the optimized operation condition.
Compared with the prior art, the invention has the remarkable advantages that: (1) a traction calculation model is established under the complex working condition of the urban rail train, and a corresponding algorithm is designed to solve the model, so that the convergence speed is high, and the method is accurate and reliable; (2) energy consumption calculation models under different working conditions are deduced, and finally, a time approximation search algorithm is adopted to establish an urban rail train timing energy-saving control strategy to obtain the optimal operation working condition.
Drawings
Fig. 1 is a flow chart of the urban rail train energy consumption optimization method for intermittent power supply.
Fig. 2 is a time-saving control mode speed-distance curve diagram of an urban rail train.
Fig. 3 is a schematic diagram of two modes of an urban rail train in a running section.
Fig. 4 is a flow chart of a method for calculating the timing energy saving of the urban rail train.
FIG. 5 is a diagram of energy consumption simulation in south-Guangzhou tower east section of a great bridge of Hunde train on urban rail.
FIG. 6 is a diagram of the energy consumption simulation of the urban rail train win-win bushou tower section.
FIG. 7 is a graph comparing simulated energy consumption to actual energy consumption.
Detailed Description
With reference to fig. 1, the method for optimizing the energy consumption of the intermittent power supply urban rail train comprises the following steps:
and 4, under the condition of limiting the running time and the running distance, establishing a time approximation search algorithm optimization model by analyzing the timing energy-saving optimization model, and realizing the optimization of the urban rail train energy consumption of intermittent power supply.
Further, the step 1 of performing stress analysis on the urban rail train to establish a train dynamics model specifically comprises the following steps:
step 1.1, firstly, obtaining the traction force F of the train at any moment by adopting an urban rail train traction characteristic curve:
in the formula, mu f Is the train tractive power coefficient, mu f ∈[0，1](ii) a v is the speed of the urban rail train; e t Is the nominal voltage of the super capacitor, F max The traction force of a constant power area of the train;
speed, V, of power change point of train max Is the maximum speed;
step 1.2, calculating the common braking force B, the emergency braking force B and the basic resistance w of the urban rail train 0 Additional resistance w j And starting resistance w q ：
w 0 ＝a 1 +b 1 v+c 1 v 2 (3)
w q ＝A q (5)
In the formula, mu b Is the braking force coefficient of the urban rail train,
coefficient of friction, sigma K h For the total brake shoe force of the train, mu b ∈[0，1]；a 1 ，b 1 ，c 1 The coefficient is a basic resistance formula coefficient and is determined by the self characteristics of the vehicle; w is a i Is unit ramp resistance, w p Resistance generated for the number of passengers, w r Is the resistance of the unit curve, w w R is the radius of the curve; tau is the air resistance coefficient, S is the windward area, rho is the air density,
as a relative velocity, A q Is constant, as summarized by experience, for example, 8 for a steam locomotive;
step 1.3, regarding the intermittent power supply urban rail train as a quality point chain, and calculating average added ramp resistance w according to the length of the urban rail train j ：
Wherein L is the train length; i.e. i i 、l i Respectively is the thousandth number and the length of the ith ramp covered by the train; r i ，l ri Respectively the radius and the length of the ith curve covered by the urban rail train; x is the position corresponding to the train;
step 1.4, solving the dynamic model of the urban rail train, and when the train is started:
wherein M is the total mass of the train, g is the gravity acceleration, v is the running speed of the urban rail train, v 1 For upper starting speed, C is the resultant force of the train unit, F, w q 、w j 、w 0 Traction force, starting resistance, additional resistance and basic resistance which are obtained respectively;
when the urban rail train is respectively in a normal traction working condition, an idle working condition and a braking working condition:
urban rail train acceleration a 0 Relationship to the resultant force of units:
wherein gamma is a rotation mass coefficient, is related to the urban rail train and is a constant value of 0.06.
Further, the step 2 of performing algorithm construction on the train dynamics model, and judging whether the current acceleration needs to be adjusted according to the current operation condition of the train comprises the specific steps of:
step 2.1, judging whether the current acceleration needs to be adjusted according to the current running working condition of the train:
firstly, when the train is in a traction working condition, the traction force F of the train is calculated according to the current running condition T ：
In the formula, F T The tractive effort for the current operating condition, C isResultant force of train unit, w q 、w j 、w 0 Respectively starting resistance, additional resistance and basic resistance, wherein M is train mass, and g is gravity acceleration;
judging whether the train can provide the traction force according to the train traction characteristic curve: if so, calculating the traction force use coefficient mu f (ii) a Otherwise, according to the maximum traction of the train, recalculating the acceleration:
in the formula, F max The maximum traction of the train at the current speed;
secondly, when the train is in the idle working condition, calculating the corresponding acceleration of the train:
a＝-(w j +w 0 ) g (13)
thirdly, when the train is in the braking working condition, the corresponding braking force B of the train is used T ：
Judging whether the train can provide the braking force according to the train braking characteristic curve: if so, calculating the braking force usage coefficient mu b (ii) a Otherwise, according to the maximum braking force of the train, recalculating the acceleration:
in the formula, B max Is as followsMaximum braking force of the front speed train;
step 2.2, calculating the running distance of the train according to the adjusted acceleration:
a＝a 0 +Δ a ×Δ t ，a≤A (17)
in the formula, a is the acceleration corresponding to each simulation time unit; a is 0 The acceleration at the previous moment; delta of a To impact limit; delta of t Is the simulation time unit size; a is the maximum acceleration;
in the formula, s is the running distance of the current train; s 0 The distance of train operation until the last simulation moment; v' and v are respectively the unit end speed and the starting speed at the current simulation moment.
Further, the energy consumption calculation of the urban rail train is carried out according to the train running time, the running position, the working condition and the state SOC of the energy storage equipment in the step 3, and the formula is as follows:
in the formula, E is total train operation energy consumption, I (v) is traction current, delta t is simulation time unit step length, U is energy storage equipment nominal voltage, and P is a For auxiliary power consumption, eta sc Discharge efficiency in a simulated time unit.
Further, the establishing of the time approximation search algorithm optimization model in the step 4 realizes the optimization of the urban rail train energy consumption of the intermittent power supply, and the specific steps are as follows:
step 4.1, in a starting stage, the train runs at the maximum traction acceleration, and runs at a constant speed at a speed limit value when the speed is increased to the maximum interval speed limit value; if the speed limit value of the next section is lower than that of the current section, the train is braked by the maximum braking force, so that the train is decelerated to the next section, and the speed is just the speed limit value of the next section; if it is notIf the speed limit value of the next section is higher than that of the current section, the train runs at the starting point of the next section with the maximum traction force in an accelerating way until the speed limit is reached; when the train is about to arrive at the station, the train is decelerated at the maximum traction force until the train stops, and the minimum operation time T is obtained min As shown in fig. 2;
step 4.2, searching a speed limit transition section from the tail end of the operation line in the opposite direction: if no such segment exists, go to step 4.4; if the section exists, the operation is switched to the coasting working condition from the starting point of the section, and if the speed is increased in the coasting process, the train is braked to enable the operation speed to exceed the limit; if the speed is reduced, the intersection point of the coasting curve and the original braking curve is used as a new working condition conversion point; if no intersection point exists, the coasting speed is reduced to the size of the speed limit value, and then the vehicle travels to the next speed limit interval at a constant speed;
4.3, increasing the running time of the train by delta T compared with the original running time every time of adjusting the running mode, when the formula (20) is satisfied, taking the middle position of the section for segmenting again, starting from the middle position of the section, and returning to the step 4.2; when equation (21) is satisfied, the optimization terminates; if the equations (20) and (21) are not satisfied, the starting point direction of the line is moved forward by one section, and the step 4.2 is returned to:
where k is the number of adjustment conditions, Δ T (i) For increased operation time after the ith adjustment of the operating conditions, T 0 Delta is the acceptable error limit value for the train running time;
step 4.4, searching forward from the last section in sequence, and searching for traction force F when the traction force F is searched b (x) When the working condition of the train is 0, the train is turned into the idle running, and the step 4.2 is returned; if the idling speed is reduced to 0 and the train does not arrive at the station, giving up the working condition conversion of the section, keeping the original working condition, and entering the step 4.5;
step (ii) of4.5, if all the braking sections finish the coasting switching, the total train running time is longer than the given time T 0 And then, reversely searching from the tail end of the line, converting from the train traction acceleration section to a cruising working condition, taking the intersection point of the cruising curve and the original coasting curve as a new coasting point, and converting to the step 4.3: if the total train running time is not more than the given time T 0 And obtaining the optimized operation condition.
The present invention will be described in further detail with reference to the accompanying drawings.
Examples
An important principle of train operation energy-saving operation is to avoid train braking as much as possible and to make the train operate at a constant speed as much as possible. Theoretically, two operation modes are mostly adopted for trains between stations, wherein the mode 1 is S 1 ～S 2 In cruise mode, mode 2 uses a combination of traction and coasting, as shown in FIG. 3.
The invention provides a method for optimizing an urban rail train section in sections, which searches a section to be optimized through practical approximation and adjusts the train operation condition, thereby realizing the aim of train energy conservation. With reference to fig. 4, the method for calculating the timing energy saving of the urban rail train is as follows:
step 1: firstly, the train runs in all intervals in a fastest mode, namely a time-saving control mode, and the minimum running time T is obtained min 。
Step 2: searching a transition section from a high speed limit to a low speed limit from the tail end of the line to the starting point direction, and starting from the starting point of the section, converting the train into an idle working condition;
if no such section exists, jump to step 5.
And step 3: in the coasting process, if the speed rises, the train is braked to meet the speed limit requirement;
if the speed is reduced, the intersection point of the coasting speed curve and the original braking speed curve is used as a new working condition conversion point.
If no intersection point exists, the coasting speed is reduced to the speed limit size of the next stage, and the vehicle runs to the next speed limit interval at a constant speed.
And 4, step 4: and updating the train speed curve every time the running mode is adjusted, wherein the running time of the train is increased by delta T compared with the original running time.
When the formula (20) is satisfied, taking the middle position of the segment to segment again, and returning to the step 2 from the middle new segmentation position;
when equation (21) is satisfied, the optimization process terminates;
if the equations (20) and (21) are not satisfied, the starting point direction of the line is moved forward by one section, and the step 2 is returned;
and 5: and searching from the last section after the whole line is segmented.
When f (x) is found to be 0, the train operation condition is changed from the section to the coasting, and the process goes to step 2.
The difference is that when the coasting speed is reduced to 0 and the train does not arrive at the station yet, the conversion of the working condition of the section is abandoned, the running under the original working condition is kept, and the step 6 is carried out.
Step 6: when all braking sections have completed the coasting change, the total train running time is still greater than the given time T 0 Then, starting from the end of the whole line, searching towards the starting point direction, and sequentially pulling and accelerating from the train (satisfying F) t (x) And (4) starting a section where F (x) is greater than or equal to 0 and F (x) is equal to 0), switching to a cruising working condition, taking an intersection point of a cruising speed curve and an original coasting curve as a new coasting point, and switching to the step 4.
By the time approximation search algorithm, the optimal operation condition of the train under the timing condition can be obtained. The optimization method has the advantages of high convergence rate and obvious energy-saving effect.
The method is used for optimizing the running energy consumption of the urban rail train based on the time approximation search algorithm, and the experiment is carried out by utilizing simulation data obtained by a computer simulation model established by MATLAB: as shown in Table l, the average acceleration of the urban rail train is not less than 0.6m/s 2 The deceleration is more than or equal to 1.1m/s 2 The maximum tractive effort is at 120 kN.
Table 1 shows the basic parameters of Guangzhou Haizhu area modern urban rail train
| Rated voltage | 750V |
| Full charge voltage of energy storage device | 900V |
| Capacity of energy storage device | 9.5KWh |
| Auxiliary power of vehicle | 64KW |
| Mean starting acceleration | ≥1.0m/s 2 |
| Average acceleration | ≥0.6m/s 2 |
| Deceleration rate | ≥1.1m/s 2 |
| Limit of impact | ≥0.75m/s 2 |
| Maximum speed | 70km/h |
| Maximum tractive effort | 120KN |
The Guangzhou Zhuhai tramcar THZ1 line is used as a research object, vehicle line data is selected for simulation experiments, modeling is carried out through input data, an optimal working condition conversion point is searched for each station-station operation interval through a time approximation search algorithm, and then energy consumption simulation of each station-station interval is carried out. Taking the south-east section of hunter bridge, guangzhou townto as an example, the energy consumption-distance curve and the speed-distance curve in the section are respectively shown in fig. 5 and fig. 6. The energy consumption simulation curve graph of a part of sections obtained through the experiment is shown in fig. 7, compared with the actual line energy consumption, the urban rail train energy consumption simulation curve graph has the advantages that the traction energy consumption is reduced while the indexes of safe operation, accurate parking, punctuality and comfort level of the urban rail train are guaranteed, the working condition point of the model is optimized through the time approximation search algorithm, the energy-saving effect is obvious, and the practicability is high.
Claims (4)
1. An urban rail train energy consumption optimization method with intermittent power supply is characterized by comprising the following steps:
step 1, carrying out stress analysis on an urban rail train and establishing a train dynamic model;
step 2, performing algorithm construction on the train dynamic model, and judging whether the current acceleration needs to be adjusted or not according to the current operation condition of the train;
step 3, calculating the energy consumption of the urban rail train according to the train running time, the running position, the working condition and the state SOC of the energy storage equipment;
step 4, under the condition of limiting the running time and the running distance, establishing a time approximation search algorithm optimization model by analyzing the timing energy-saving optimization model, and realizing the optimization of the urban rail train energy consumption of intermittent power supply;
step 1, performing stress analysis on the urban rail train, and establishing a train dynamics model, wherein the stress analysis specifically comprises the following steps:
step 1.1, firstly, obtaining the traction force F of the train at any moment by adopting an urban rail train traction characteristic curve:
in the formula, mu f Is the train tractive power coefficient, mu f ∈[0，1](ii) a v is the speed of the urban rail train; e t Is the nominal voltage of the super capacitor, F max The traction force of a constant power area of the train;
speed, V, of power change point of train max Is the maximum speed;
step 1.2, calculating the common braking force B, the emergency braking force B and the basic resistance w of the urban rail train 0 Additional resistance w j And a starting resistance w q ：
w 0 ＝a 1 +b 1 v+c 1 v 2 (3)
w q ＝A q (5)
In the formula, mu b Is the braking force coefficient of the urban rail train,
is coefficient of friction, ∑ K h The train total brake shoe force, mu b ∈[0，1]；a 1 ，b 1 ，c 1 The coefficient is a basic resistance formula coefficient and is determined by the self characteristics of the vehicle; w is a i Is unit ramp resistance, w p Resistance generated for the number of passengers, w r Is the resistance per unit curve, w w R is the radius of the curve; tau is the air resistance coefficient, S is the windward area, rho is the air density,
as a relative velocity, A q Is a constant;
step 1.3, regarding the intermittent power supply urban rail train as qualityPoint chain, calculating average added ramp resistance w according to the length of urban rail train j ：
Wherein L is the train length; i.e. i i 、l i The thousands and the length of the ith ramp covered by the train are respectively; r is i ，l ri Respectively the radius and the length of the ith curve covered by the urban rail train; x is the position corresponding to the train;
step 1.4, solving a dynamic model of the urban rail train, and when the train is started:
s.t v≤v 1
wherein M is the total mass of the train, g is the gravity acceleration, v is the running speed of the urban rail train 1 For upper starting speed, C is the resultant force of the train unit, F, w q 、w j 、w 0 Traction force, starting resistance, additional resistance and basic resistance which are obtained respectively;
when the urban rail train is respectively in a normal traction working condition, an idle working condition and a braking working condition:
acceleration a of urban rail train 0 Relationship to the resultant force of units:
wherein gamma is a rotation mass coefficient, is related to the urban rail train and is a constant value of 0.06.
2. The method for optimizing the energy consumption of the intermittently powered urban rail train according to claim 1, wherein the step 2 of performing algorithm construction on a train dynamics model and judging whether the current acceleration needs to be adjusted according to the current running condition of the train comprises the following specific steps:
step 2.1, judging whether the current acceleration needs to be adjusted according to the current running working condition of the train:
firstly, when the train is in the traction working condition, the train traction force F is calculated according to the current running condition T ：
In the formula, F T Is the tractive force of the current operating condition, C is the unit resultant force of the train, w q 、w j 、w 0 Respectively a starting resistance, an additional resistance and a basic resistance, wherein M is the train mass, and g is the gravity acceleration;
judging whether the train can provide the traction force according to the train traction characteristic curve: if so, calculating the train traction coefficient mu f (ii) a Otherwise, according to the maximum traction of the train, recalculating the acceleration:
in the formula, F max The maximum traction of the train at the current speed;
secondly, when the train is in the idle working condition, calculating the corresponding acceleration of the train:
a＝-(w j +w 0 )g (13)
thirdly, when the train is in the braking working condition, the corresponding braking force B of the train is used T ：
Judging whether the train can provide the braking force according to the train braking characteristic curve: if so, calculating the braking force usage coefficient mu b (ii) a Otherwise, according to the maximum braking force of the train, recalculating the acceleration:
in the formula, B max The maximum braking force of the train at the current speed;
step 2.2, calculating the running distance of the train according to the adjusted acceleration:
a＝a 0 +Δ a ×Δ t ，a≤A (17)
in the formula, a is the acceleration corresponding to each simulation time unit; a is 0 The acceleration at the previous moment; delta of a To impact limit; delta t Is the simulation time unit size; a is the maximum acceleration;
in the formula, s is the running distance of the current train; s 0 The distance of train operation until the last simulation moment; v' and v are the unit end speed and the initial speed at the current simulation time respectively.
3. The method for optimizing the energy consumption of the intermittently powered urban rail train according to claim 1, wherein the energy consumption of the urban rail train is calculated according to the train running time, the running position, the working condition and the state SOC of the energy storage device in the step 3, and the formula is as follows:
in the formula, E is total train operation energy consumption, I (v) is traction current, delta t is simulation time unit step length, U is energy storage equipment nominal voltage, and P is a For auxiliary power consumption, eta sc Discharge efficiency in a simulated time unit.
4. The method for optimizing the energy consumption of the intermittently powered urban rail train according to claim 1, wherein the establishing of the time-approximating search algorithm optimization model in the step 4 realizes the optimization of the energy consumption of the intermittently powered urban rail train, and the method comprises the following specific steps:
step 4.1, in a starting stage, the train runs at the maximum traction acceleration, and runs at a constant speed at a speed limit value when the speed is increased to the maximum interval speed limit value; if the speed limit value of the next section is lower than that of the current section, the train is braked by the maximum braking force, so that the train is decelerated to the next section, and the speed is just the speed limit value of the next section; if the speed limit value of the next section is higher than that of the current section, the train runs at the starting point of the next section in the maximum traction acceleration mode until the speed limit is reached; when the train is about to arrive at the station, the train is decelerated at the maximum traction force until the train stops, and the minimum operation time T is obtained min ；
Step 4.2, searching a speed limit transition section from the tail end of the operation line in the opposite direction: if no such segment exists, go to step 4.4; if the section exists, the operation is switched to the coasting working condition from the starting point of the section, and if the speed is increased in the coasting process, the train is braked to enable the operation speed to exceed the limit; if the speed is reduced, the intersection point of the coasting curve and the original braking curve is used as a new working condition conversion point; if no intersection point exists, the coasting speed is reduced to the size of the speed limit value, and then the vehicle travels to the next speed limit interval at a constant speed;
4.3, increasing the running time of the train by delta T compared with the original running time every time of adjusting the running mode, when the formula (20) is satisfied, taking the middle position of the section for segmenting again, starting from the middle position of the section, and returning to the step 4.2; when equation (21) is satisfied, the optimization terminates; if the equations (20) and (21) are not satisfied, the starting point direction of the line is moved forward by one section, and the step 4.2 is returned to:
where k is the number of adjustment conditions, Δ T (i) For increased operation time after the ith adjustment of operating conditions, T 0 Delta is the acceptable error limit value for the train running time;
step 4.4, searching forward from the last section in sequence, and searching for traction force F when the traction force F is searched b (x) When the working condition of the train is 0, the train is turned into the idle running, and the step 4.2 is returned; if the idling speed is reduced to 0 and the train does not arrive at the station, giving up the working condition conversion of the section, keeping the original working condition, and entering the step 4.5;
step 4.5, if the coasting switching is completed in all the braking sections, the total running time of the train is longer than the given time T 0 And then, reversely searching from the tail end of the line, converting from the train traction acceleration section to a cruising working condition, taking the intersection point of the cruising curve and the original coasting curve as a new coasting point, and converting to the step 4.3: if the total train running time is not more than the given time T 0 And obtaining the optimized operation condition.
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