CN111267913B - Energy-saving running method for urban rail transit train - Google Patents
Energy-saving running method for urban rail transit train Download PDFInfo
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Abstract
An energy-saving running method for urban rail transit train includes carrying out off-line ATO interval simulation running according to real line environment of train running, iteratively searching target regulation speed to obtain distance-speed curves of different operation levels with different running time, setting multiple time regulation points with running data stored in them on train running interval according to distance-speed curves of each operation level planned off-line, running train on running interval on line, and when time regulation point is passed, on-line regulating target regulation speed of train according to running data in time regulation point and distance-speed curves of each operation level planned off-line to make train run alternatively in idle mode without applying power or resistance and recovery mode applying power or resistance. The invention not only has obvious energy-saving effect, but also can automatically match with the changed ATS operation time constraint and meet the punctuation requirement.
Description
Technical Field
The invention relates to the field of urban rail transit, in particular to an energy-saving running method for an urban rail transit train.
Background
The urban rail transit line has the characteristics of short station spacing and large passenger flow volume, the requirement on the point aligning rate is very high, in addition, in the operation cost of the urban rail transit train, the proportion of the traction energy consumption almost reaches half, and the reduction of the traction energy consumption of the train is an urgent requirement.
Because the optimization calculation of the energy-saving operation curve is very time-consuming, the Train usually stores the offline energy-saving operation curves of different operation levels in advance, and selects the corresponding operation mode curve according to the running time constraint of the ATS (Automatic Train Supervision). However, in the actual Operation process, due to the line emergency and the adjustment of the ATS Operation plan, the off-line optimization energy-saving curve directly stored in the off-line optimization energy-saving curve cannot meet the real-time Operation time requirement, and it is required that an ATO (Automatic Train Operation) control system of the Train can adjust the Operation mode timely to achieve the two goals of quasi-point arrival and energy-saving Operation.
Disclosure of Invention
The invention provides an energy-saving operation method for an urban rail transit train, which not only has a remarkable energy-saving effect, but also can automatically match with the changed ATS operation time constraint and meet the punctuation requirement.
In order to achieve the purpose, the invention provides an energy-saving running method of an urban rail transit train, which comprises the following steps:
performing offline ATO interval simulation operation according to a real line environment of train operation, iteratively searching for a target adjustment speed, obtaining distance-speed curves of various operation grades with different operation times, and setting a plurality of time adjustment points storing operation data on a train operation interval according to the distance-speed curves of various operation grades planned offline;
the train runs on line in the running interval, and when the time adjusting point passes, the target adjusting speed of the train is adjusted on line according to the running data in the time adjusting point and the distance-speed curves of each operation grade planned off line, so that the train runs alternately in an idle mode without applying power or resistance and a recovery mode with applying power or resistance.
The distance-speed curve of the operation grade comprises: a tight travel distance-speed curve, and at least two energy-saving distance-speed curves;
the compact running distance-speed curve is a distance-speed curve obtained by completing the interval running of the simulated train in the shortest time;
the energy-saving distance-speed curve is obtained by using the running time of the simulated train at different operation grades as a constraint and carrying out iterative search on the target adjustment speed of the simulated train.
The method for iteratively searching the target adjustment speed of the simulated train comprises the following steps:
setting the lower limit value of the initial search range of the target adjustment speed as 0, setting the upper limit value as the speed peak value of the compact running distance-speed curve, and taking the average value of the initial search range as the initial value of the target adjustment speed;
the simulation train carries out ATO interval simulation operation according to the current target adjustment speed, if the time used for the operation is longer than the expected operation time of the current operation grade, the lower limit value of the search range of the target adjustment speed is adjusted, and the average value of the adjusted search range is used as the updated target adjustment speed;
and the simulation train carries out ATO interval simulation operation according to the updated target adjustment speed until the operation time is less than or equal to the expected operation time of the current operation grade, and then the iteration is stopped to obtain an energy-saving distance-speed curve of the current operation grade.
The expected operation time of the operation level is as follows:
desired_time＝tight_running_time×(1+time_percent)
wherein, the light _ running _ time is the running time of the compact running distance-speed curve, and the time _ percentage is the time relaxation scale factor of different operation levels.
The time adjustment points include: a remaining time check point and a migration parameter update point;
the remaining time checkpoint comprises: the remaining time, the target adjustment speed and the lazy line strategy attribute; the lazy strategy attributes are divided into a lazy prohibiting strategy, a lazy allowing strategy and a lazy forcing strategy; setting a coasting prohibition strategy in an area with the gradient exceeding a positive and negative gradient threshold value and a constant speed cruise area; setting an idle-permitting strategy in a region with the gradient within a positive and negative gradient threshold range; when a train enters a platform area, a forced coasting strategy is set;
the wandering parameter update point comprises: positive and negative gradient thresholds of the running interval, upper and lower limit values of the speed adjustment threshold and the minimum coasting speed.
The method for adjusting the target adjusting speed of the train on line comprises the following steps: the train runs on line, when the train passes through a remaining time check point, the remaining time is calculated, the coasting strategy attribute is judged, and the target adjustment speed is updated on line according to the energy-saving distance-speed curves of all operation levels; when the train passes through the migration parameter updating point, the positive and negative gradient threshold values are updated, the upper and lower limit values of the target adjusting speed are calculated and updated, and the minimum speed allowing coasting is updated.
The recovery method comprises the following steps: a traction recovery operation mode and a braking recovery operation mode;
when the train runs on an uphill slope, the train runs on line under traction, when the speed of the train is higher than the upper limit of the target adjustment speed, the train starts running in an idling mode, and when the speed of the train is lower than the lower limit of the target adjustment speed, the train starts running in a traction recovery running mode;
when the train runs downhill, the train is subjected to braking power to run on line, when the speed of the train is less than the lower limit of the target adjusting speed, the train starts to run in an idling mode, and when the speed of the train is greater than the upper limit of the target adjusting speed, the train starts to run in a braking recovery running mode.
When ascending, the method for calculating and updating the upper and lower limit values of the target adjusting speed comprises the following steps:
start_coast_limit＝time_regu_speed+upper_speed_margin
stop_coast_limit＝time_regu_speed-lower_speed_margin
wherein, time _ regular _ speed is a target adjusting speed, start _ coast _ limit is a target adjusting speed upper limit value, stop _ coast _ limit is a target adjusting speed lower limit value, upper _ speed _ margin is a speed adjusting threshold upper limit value, and lower _ speed _ margin is a speed adjusting threshold lower limit value;
when the vehicle runs downhill, the method for calculating and updating the upper and lower limit values of the target adjusting speed comprises the following steps:
start_coast_limit＝time_regu_speed-lower_speed_margin
stop_coast_limit＝time_regu_speed+upper_speed_margin
wherein, time _ regular _ speed is a target adjusting speed, start _ coast _ limit is a target adjusting speed lower limit value, stop _ coast _ limit is a target adjusting speed upper limit value, upper _ speed _ margin is a speed adjusting threshold upper limit value, and lower _ speed _ margin is a speed adjusting threshold lower limit value.
The target adjusting speed calculating method in the traction recovery operation process comprises the following steps:
time_regu_speed[k]＝time_regu_speed[k-1]+Γtraction×ΔT
wherein time _ regular _ speed represents a target adjustment speed, ΓtractionThe traction acceleration threshold value in the traction recovery stage is shown, delta T is the simulation control period of an ATO interval, and subscript indexes k and k-1 respectively represent numerical values of the period and the last period;
the target adjusting speed calculating method in the braking recovery operation process comprises the following steps:
time_regu_speed[k]＝time_regu_speed[k-1]+Γbrake×ΔT
wherein time _ regular _ speed represents a target adjustment speed, ΓbrakeThe braking acceleration threshold value in the braking recovery stage is shown, delta T is the simulation control period of the ATO interval, and subscript indexes k and k-1 respectively represent numerical values of the period and the last period.
In the process of coasting operation, the method for updating the target adjustment speed on line comprises the following steps:
xp＝speed_dev_profile[p].remaining_time
yp＝speed_dev_profile[p].regu_speed
xp+1＝speed_dev_profile[p+1].remaining_time
yp+1＝speed_dev_profile[p+1].regu_speed
wherein, time _ regu _ speed is the target regulation speed, remaining _ time represents the time remaining when the train is at the current location, speed _ dev _ profile [ p ]]A distance-speed curve, speed _ dev _ profile [ p +1 ], representing the current position corresponding to the operating class p]Distance-speed curve, x, representing the current position corresponding to the operating class p +1pRepresenting the remaining time of the operating class p, ypTarget adjustment speed, x, representing operation level pp+1Representing the remaining time, y, of the operating class p +1p+1Indicating the target adjustment speed for the operation level p + 1.
When the train passes through the remaining time check point, calculating an estimated error of the arrival time, and if the estimated error of the arrival time is smaller than a set threshold, adopting an idle running mode;
the method for estimating the error of the arrival time comprises the following steps:
where Δ v is the difference between the current speed train _ speed and the entering coasting speed start _ coast _ limit of the train, and Γ iscoastIs the resultant acceleration, Γ, of the gradient and resistance experienced by the train when coastingbrakeIs the brake acceleration threshold.
Compared with the prior art, the invention has the following advantages:
1. by adopting a means of combining offline planning and online optimization, the ATO energy-saving operation strategy based on the speed migration mode can be rapidly operated in real time in vehicle-mounted embedded software.
2. When distance-speed curves of different operation grades are planned off line, the distance-speed curves are obtained through interval ATO interval simulation, a very accurate simulation model is established for real slope scene constraint and a train, and the positive and negative errors between the simulation running time and the actual measurement time of the interval ATO interval are not more than 1 s.
4. The method is particularly suitable for a running chart recovery scene after an ATS operation plan is interfered, the distance-speed curve can be adjusted in real time according to the latest ATS instruction when the train runs in an interval, the high precision point rate is still achieved, the positive and negative errors are not more than 1s, and good energy-saving effect and comfort level can be achieved when the train runs.
Drawings
Fig. 1 is a flowchart of an energy-saving operation method for an urban rail transit train in an embodiment of the present invention.
Fig. 2 is a schematic diagram of an energy-saving operation method for an urban rail transit train in an embodiment of the invention.
Fig. 3 is a flowchart of a method for obtaining an energy-saving distance-speed curve for each operation level through off-line simulation in an embodiment of the present invention.
Fig. 4 is a schematic diagram of policy switching between lazy enable and lazy disable in an embodiment of the present invention.
FIG. 5 is a schematic diagram of a velocity cruise control in an embodiment of the present invention.
Fig. 6 is a schematic diagram illustrating that the upper and lower limit values of the target adjustment speed are inverted during the switching process from the traction scene to the braking scene in the embodiment of the present invention.
FIG. 7 is a schematic diagram of a coasting strategy with a target adjusted speed change in an embodiment of the present invention.
FIG. 8 is a schematic diagram of calculating a target adjustment speed based on a remaining time checkpoint online optimization in an embodiment of the present invention.
Detailed Description
The preferred embodiment of the present invention will be described in detail below with reference to fig. 1 to 8.
In view of energy conservation, the train coasting is a relatively energy-saving control mode, when the station travel time is sufficient, a proper coasting strategy can be adopted to achieve the purpose of energy conservation, and meanwhile, in order to enable the train to arrive at a targeted point, the target speed needs to be dynamically adjusted in real time on the basis of an offline planning distance-speed curve.
As shown in fig. 1, in an embodiment of the present invention, an energy-saving operation method for an urban rail transit train is provided, which includes the following steps:
step S1, establishing a simulation train model according to the real line environment of train operation, performing ATO interval simulation operation off line, iteratively searching target adjustment speed, and obtaining distance-speed curves of each operation grade;
step S2, setting a plurality of time adjustment points storing operation data on a train operation interval according to the distance-speed curve of each operation grade planned off-line, and adjusting the operation speed and the operation state of the train in real time;
and step S3, performing online operation of the train in a speed traveling and controlling manner, and performing online optimization according to the operation data in the time adjusting point and the distance-speed curves of each operation grade planned offline when the time adjusting point passes, so as to adjust the operation speed and the operation state of the train in real time.
As shown in fig. 2, a simulation model is established for a real line environment and a train, a time adjustment point is introduced to depict a distance-speed curve of each operation level in an off-line planning process, and an operation mode is adjusted timely based on the time adjustment point in an on-line operation optimization process, so that accurate point arrival and energy-saving operation are realized.
In the operation process of the urban rail transit train, the ATO controls the train in an interval under the ATP safety protection, the train is folded and returned to a station, the stop curve of the ATO is different from the stop curve of a positive line due to the influence of a protection section, and the stop curve of the ATO of the returning station is interfered by the ATP emergency braking trigger curve. In consideration of the real scene constraints and the delay response characteristic of a train traction braking system, a real slope scene and a train are subjected to simulation modeling, so that an offline planned distance-speed curve is close to an ATO distance-speed curve in a real environment, the reality reference significance is achieved, and the quasi-point rate of ATO energy-saving time adjustment during online operation can be ensured.
In step S1, the dynamic response model of the simulated train model may be described by a first-order time delay model, as shown in formula (1):
where R(s) is the input control level, Y(s) is the output acceleration, K is the steady state gain, T is the system response time, and τ is the system net delay. The steady state gain K in the simulation train model is a static parameter and is used for describing the steady state mapping relation between different traction braking forces and the train acceleration, and T and tau in the simulation train model are dynamic process parameters.
In step S1, an ATO interval simulation is used to plan a distance-speed curve for 4 operation classes offline, where operation class 1 is a tight operation distance-speed curve, the remaining 3 operation classes are energy-saving distance-speed curves, the 3 operation classes correspond to an early peak time, a late peak time, and a flat peak time, respectively, and the total operation time of different operation classes is different.
The tight running distance-speed curve is also obtained by ATO section simulation running, that is, a distance-speed curve obtained by a simulation Train completing section running in the shortest time under ATP (Automatic Train Protection) safety Protection.
The energy-saving distance-speed curve offline planning of each operation level is a series of iterative search processes carried out through ATO interval simulation operation, half of the speed peak value in the compact operation distance-speed curve is used as the initial value of the target adjustment speed, and the target adjustment speed meeting the given operation time constraint is iteratively searched out to form an energy-saving distance-speed curve.
As shown in fig. 3, the method for obtaining the energy-saving distance-speed curve of each operation level by off-line simulation includes the following steps:
s1.1, initializing ATO (automatic train operation) interval simulation, loading line data (including safety speed limit and line gradient of different operation intervals), a simulated train model and initial parameters of a first migration parameter updating point, and setting time relaxation scale factors time _ percent of different operation levels;
considering a range of time margins, usually on a tight run-time basis, the time relaxation scaling factors time _ percent for different operating classes are typically set to 10%, 15%, and 20%;
s1.2, controlling the train by the simulation train according to a tight running distance-speed curve to obtain tight running time (namely time required for running the whole course at the tight running speed), and calculating expected running time desired _ time under different operation levels according to the set time relaxation scale factor and the tight running time, wherein the calculation formula is shown as (2):
desired_time＝tight_running_time×(1+time_percent) (2)
wherein the light _ running _ time is a compact running time, and the time _ percentage is a time relaxation scale factor;
s1.3, recording the highest speed in the compact running distance-speed curve as Vmax, setting the initial search range of the target adjustment speed to be 0-Vmax, and taking the average value of the initial search range as the initial value of the target adjustment speed;
s1.4, the simulation train operates according to the target adjustment speed calculated in each iteration, if the current operation time meets the operation time constraint under the given operation level (the condition that the operation time constraint is met means that the actual operation time is equal to the expected operation time or the error time does not exceed the allowed range), the iterative search process under the current operation level is quitted, and if the search range of the target adjustment speed is smaller than the set threshold value, the iterative search process under the current operation level is also quitted;
and S1.5, performing iterative search, comparing the time used by the current operation with the expected operation time, and iteratively calculating the next search range and the target adjustment speed.
The iterative search process comprises the following steps: and the simulation train carries out ATO interval simulation operation according to the current target adjustment speed, if the time used for the operation is longer than the expected operation time, the lower limit value of the search range of the target adjustment speed is adjusted, the updated average value of the search range is used as a new target adjustment speed, the simulation train carries out ATO interval simulation operation according to the new target adjustment speed, and the iteration is stopped until the time used for the operation is less than or equal to the expected operation time, so that an energy-saving distance-speed curve is obtained.
The distance-speed curves of different operation grades are different, the interval running time is different, the traction braking working conditions are also different, and each iterative search in the offline planning process is an ATO interval energy-saving simulation running process based on a speed traveling vehicle control mode. In an embodiment of the present invention, the search range of the initially set target adjustment speed is (0,80), the target adjustment speed takes an intermediate value of 40kph, if the ATO interval simulation operation time is greater than the expected operation time, that indicates that the target adjustment speed 40kph used in the current search is lower, the next search range becomes (40,80), the new target adjustment speed takes an intermediate value of 60kph, and then the ATO interval simulation operation is performed, and the process is repeated. And setting a threshold value to avoid endless loop, and exiting the endless loop when the search range of the target adjustment speed is smaller than the set threshold value.
In step S2, after energy-saving distance-speed curves of different operation levels are planned offline, a series of time adjustment points are arranged on the energy-saving distance-speed curves and the compact running distance-speed curves, and the time adjustment points are set to better follow the offline planned compact running distance-speed curves and energy-saving distance-speed curves and perform speed adjustment according to the expected running time.
Considering that the energy-saving distance-speed curves of different operation levels overlap when the train is dispatched from the platform and finally stops in the area, the time adjustment is not needed in the platform area, and the time adjustment point can not be set.
The time adjustment points are of two types: one is a remaining time check point, and the other is a migration parameter update point; the residual time check point comprises residual time, target adjustment speed and lazy line strategy attributes, and is mainly used for achieving the aim of quasi point arrival through speed adjustment, wherein the lazy line strategy attributes are divided into three situations of lazy line forbidding, lazy line allowing and lazy line forcing; the wandering parameter updating point comprises a slope scene (positive and negative slope thresholds), an upper limit value and a lower limit value of a speed adjusting threshold, and a minimum coasting speed (the condition that the train coasts slowly and slowly at a very low speed in a section to influence the operation efficiency of a line) so as to be suitable for the energy-saving purpose under different line type scenes.
Considering that the gradient of some areas in the urban railway line is larger, in order to avoid frequent working condition switching of trains, a coasting prohibition strategy is set for the large-gradient line area and the constant-speed cruise area, and when the gradient of the line is within the range of the allowed positive and negative gradient threshold values, the coasting permission strategy is set. Fig. 4 shows the coasting strategy of the train in different route sections, considering the performance difference of different trains on the whole route and the load change in different operation periods, if the coasting strategy is still adopted when the train enters a large-gradient area, the phenomenon that the distance-speed curve deviates greatly from the offline planning distance-speed curve is likely to occur, and in the subsequent operation process, in order to ensure a standard point, large traction is output, but the energy consumption is higher, so that the coasting strategy is forbidden, that is, the cruising strategy is adopted when the train enters the large-gradient area. And setting a forced coasting strategy when the train is about to enter the platform area.
In the step S3, the train runs on line in a speed traveling and vehicle controlling manner, when a remaining time check point passes, the remaining time is calculated, the target adjustment speed is updated by performing online optimization according to the energy-saving distance-speed curves of each operation level, and the coasting strategy is judged; when the traveling parameter updating point is passed, updating the positive and negative gradient threshold values, updating the upper and lower limit values of the calculated target adjusting speed, and updating the minimum speed allowing coasting;
in step S3, the speed traveling control mode is to perform ATO control within the upper and lower limits of the target adjustment speed, and the speed traveling control process includes alternately operating in a coasting mode without applying power and a speed recovery mode with applying power, wherein the recovery process is divided into a traction recovery process and a braking recovery process.
As shown in fig. 5, taking a traction scenario as an example, a train starts at a maximum acceleration, an idling mode is adopted after reaching a target adjustment speed upper limit, when the train enters a traction recovery stage when the train speed exceeds a speed fluctuation range allowed by the idling, and then the idling mode and the traction mode are alternately adopted for controlling the train to stop at a maximum deceleration.
Taking the traction scene of the slope as an example, when the wandering parameter update point is passed, defining the speed of entering the coasting as the upper limit of the target adjustment speed, the speed of exiting the coasting as the lower limit of the target adjustment speed, and the calculation formula is shown as (3),
here, time _ regular _ speed is a target adjustment speed, start _ coast _ limit is a target adjustment speed upper limit (speed to enter the coasting), stop _ coast _ limit is a target adjustment speed lower limit (speed to exit the coasting), upper _ speed _ margin is a speed adjustment threshold upper limit (preset), and lower _ speed _ margin is a speed adjustment threshold lower limit (preset). Still taking the traction scene as an example, the condition that the train enters the coasting is that the speed of the train is greater than the upper limit of the target adjustment speed, and the condition that the train exits the coasting and enters the traction recovery process is that the speed of the train is less than the lower limit of the target adjustment speed.
If the train is in a downhill braking scene, the process of braking recovery is entered after the coasting process is exited. In order to ensure comfort, the braking acceleration threshold value and the traction acceleration threshold value in the recovery process need to be considered when the braking recovery process or the traction recovery process is started. As shown in fig. 6, the train enters a braking situation from a traction situation, and the upper and lower limit values of the target regulation speed are reversed during the switching of the braking situation.
If the train is in a downhill scene, the speed of the train is faster and faster in the coasting state, so that the speed entering coasting is defined as a target adjustment speed lower limit, and the speed exiting coasting is defined as a target adjustment speed upper limit, and the calculation formula is as follows:
here, time _ regular _ speed is a target adjustment speed, start _ coast _ limit is a target adjustment speed lower limit (speed to enter the coasting), stop _ coast _ limit is a target adjustment speed upper limit (speed to exit the coasting), upper _ speed _ margin is a speed adjustment threshold upper limit (preset), and lower _ speed _ margin is a speed adjustment threshold lower limit (preset).
Still taking the traction scenario as an example, at the time of entering the traction recovery process, the initial value of the target adjustment speed time _ regu _ speed is equal to the target adjustment speed lower limit stop _ coast _ limit, and then calculated according to the formula (4), during the traction recovery process, the train speed will increase, and when the train speed exceeds the target adjustment speed upper limit start _ coast _ limit, the coasting process is entered again. The target regulation speed calculation formula in the traction recovery process is shown as (5),
time_regu_speed[k]＝time_regu_speed[k-1]+Γtraction×ΔT (5)
where time _ regu _ speed represents the target trim speed, subscript indices k, k-1 represent the values of the present and upper cycles, respectively, and ΓtractionThe traction acceleration threshold value is in the traction recovery stage, and delta T is the simulation control period of the ATO interval.
Taking a braking scene as an example, the initial value of the target adjusting speed time _ regu _ speed is equal to the target adjusting speed upper limit stop _ coast _ limit, and then the train speed is reduced in the braking recovery process according to the formula (6), and when the train speed is smaller than the target adjusting speed lower limit start _ coast _ limit, the coasting process is started again. The target regulation speed during the brake resumption calculation formula is shown in (6),
time_regu_speed[k]＝time_regu_speed[k-1]+Γbrake×ΔT (6)
where time _ regu _ speed represents the target trim speed, subscript indices k, k-1 represent the values of the present and upper cycles, respectively, and ΓbrakeThe braking acceleration threshold value is the braking acceleration threshold value in the braking recovery stage, and delta T is the simulation control period of the ATO interval.
Fig. 7 shows an energy-saving strategy in a transition process when a target adjustment speed changes in an online operation process, in an actual operation process of a train, due to train performance difference or ATS operation plan adjustment, in order to meet a criterion requirement, the target adjustment speed needs to be adjusted, in the transition process of the target adjustment speed, if an estimated error of arrival time is within an operation allowable range, the energy-saving strategy is preferentially considered, and a coasting strategy is adopted instead of a braking strategy to enter a new target adjustment speed region. When the remaining time check point passes, the arrival time estimation error is calculated, as shown in (7),
where Δ v is the difference between the current speed train _ speed and the entering coasting speed start _ coast _ limit of the train, and Γ iscoastIs the resultant acceleration, Γ, of the gradient and resistance to which the train is subjected in the coasting statebrakeIs the brake acceleration threshold and tolerance _ time is the estimated error of the arrival time allowed by the operation.
In step S3, in order to meet the operating requirements of punctual arrival and energy saving, the train needs to update the migration parameters and calculate a new target adjustment speed on line according to the remaining time during the on-line operation process. Fig. 8 illustrates a target speed adjustment process when a train passes through a checkpoint type of time remaining therein. When the train runs through the remaining time check point, the remaining time of the current position of the train is calculated in real time according to the latest ATS instruction, and online optimization is performed in different operation grade curves planned offline according to the train speed to obtain a new target adjustment speed.
The remaining time is calculated as shown in equation (8),
remaining_time＝desired_time-cost_time (8)
wherein remaining _ time is the remaining time, i.e., the time required for the train to complete the remaining distance of the section, desired _ time is the expected running time of the section, and cost _ time is the time taken for the train to travel from the station to the current location.
Under special conditions, if the remaining time is exactly equal to the remaining time corresponding to the operation level p, the train is located at the operation level p; if the remaining time is exactly equal to the remaining time corresponding to the operation level p +1, the train is located at the operation level p + 1; typically, the speed profile of the train is between the operation classes p and p + 1.
When coasting, the target adjustment speed time _ regular _ speed calculation process is as shown in equation (9),
wherein remaining _ time represents the remaining time of the train at the current position, speed _ dev _ profile [ p [ ]]A distance-speed curve, speed _ dev _ profile [ p +1 ], representing the current position corresponding to the operating class p]A distance-speed curve representing the current position corresponding to the operation level p +1, the distance-speed curve of the operation level p and the operation level p +1 is searched according to the remaining time remaining _ time of the current position, xpRepresenting the remaining time of the operating class p, ypTarget adjustment speed, x, representing operation level pp+1Representing the remaining time, y, of the operating class p +1p+1Indicating the target adjustment speed for the operation level p + 1.
The operation level speed curves planned off-line are arranged from high to low according to the target adjustment speed, and the running-out intervals have more time consumption as the speed is lower, so that the remaining time of each operation level is changed from less to more. When the train runs through a remaining time check point, calculating the remaining time, and then circularly traversing an operation grade speed curve planned offline, wherein under a special condition, the remaining time is exactly equal to the remaining time corresponding to an operation grade p, so that the interpolation calculation of a formula (9) is not needed, and the target adjustment speed is directly equal to the target adjustment speed corresponding to the operation grade p; if the remaining time is longer than the remaining time corresponding to the operation level p and shorter than the remaining time corresponding to the operation level p +1, it indicates that the actual speed curve of the train is required to be between the operation level p and the operation level p +1 if the punctuality requirement is to be met, and then the formula (9) is required to calculate the real-time target adjustment speed through interpolation.
Compared with the prior art, the invention has the following advantages:
1. by adopting a means of combining offline planning and online optimization, the ATO energy-saving operation strategy based on the speed migration mode can be rapidly operated in real time in vehicle-mounted embedded software.
2. When distance-speed curves of different operation grades are planned off line, the distance-speed curves are obtained through interval ATO interval simulation, a very accurate simulation model is established for real slope scene constraint and a train, and the positive and negative errors between the simulation running time and the actual measurement time of the interval ATO interval are not more than 1 s.
4. The method is particularly suitable for a running chart recovery scene after an ATS operation plan is interfered, the distance-speed curve can be adjusted in real time according to the latest ATS instruction when the train runs in an interval, the high precision point rate is still achieved, the positive and negative errors are not more than 1s, and good energy-saving effect and comfort level can be achieved when the train runs.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.
Claims (9)
1. An energy-saving operation method for an urban rail transit train is characterized by comprising the following steps:
performing offline ATO interval simulation operation according to a real line environment of train operation, iteratively searching for a target adjustment speed, obtaining distance-speed curves of various operation grades with different operation times, and setting a plurality of time adjustment points storing operation data on a train operation interval according to the distance-speed curves of various operation grades planned offline;
the method comprises the steps that a train runs on line in a speed traveling control mode in a running interval, when a time adjusting point passes, the target adjusting speed of the train is adjusted on line according to running data in the time adjusting point and distance-speed curves of various operation levels planned in an off-line mode, the speed traveling control mode is that ATO control is carried out on the train within the upper limit value and the lower limit value of the target adjusting speed, the speed traveling control process comprises alternately running in an idle mode without applying power and a speed recovery mode with applying power, and the recovery process is divided into a traction recovery process and a brake recovery process;
the time adjustment points include: a remaining time check point and a migration parameter update point;
the remaining time checkpoint comprises: the remaining time, the target adjustment speed and the lazy line strategy attribute; the lazy strategy attributes are divided into a lazy prohibiting strategy, a lazy allowing strategy and a lazy forcing strategy; setting a coasting prohibition strategy in an area with the gradient exceeding a positive and negative gradient threshold value and a constant speed cruise area; setting an idle-permitting strategy in a region with the gradient within a positive and negative gradient threshold range; when a train enters a platform area, a forced coasting strategy is set;
the wandering parameter update point comprises: positive and negative gradient threshold values of a running interval, upper and lower limit values of a target adjusting speed and a minimum coasting speed;
the method for adjusting the target adjusting speed of the train on line comprises the following steps: the train runs on line, when the train passes through a remaining time check point, the remaining time is calculated, the coasting strategy attribute is judged, and the target adjustment speed is updated on line according to the energy-saving distance-speed curves of all operation levels; when the train passes through the migration parameter updating point, the positive and negative gradient threshold values are updated, the upper and lower limit values of the target adjusting speed are calculated and updated, and the minimum speed allowing coasting is updated.
2. The energy-saving operation method of an urban rail transit train according to claim 1, wherein the distance-speed curve of the operation level comprises: a tight travel distance-speed curve, and at least two energy-saving distance-speed curves;
the compact running distance-speed curve is a distance-speed curve obtained by completing the interval running of the simulated train in the shortest time;
the energy-saving distance-speed curve is obtained by using the running time of the simulated train at different operation grades as a constraint and carrying out iterative search on the target adjustment speed of the simulated train.
3. The energy-saving operation method of an urban rail transit train according to claim 2, wherein the method for iteratively searching for the target regulation speed of the simulated train comprises:
setting the lower limit value of the initial search range of the target adjustment speed as 0, setting the upper limit value as the speed peak value of the compact running distance-speed curve, and taking the average value of the initial search range as the initial value of the target adjustment speed;
the simulation train carries out ATO interval simulation operation according to the current target adjustment speed, if the time used for the operation is longer than the expected operation time of the current operation grade, the lower limit value of the search range of the target adjustment speed is adjusted, and the average value of the adjusted search range is used as the updated target adjustment speed;
and the simulation train carries out ATO interval simulation operation according to the updated target adjustment speed until the operation time is less than or equal to the expected operation time of the current operation grade, and then the iteration is stopped to obtain an energy-saving distance-speed curve of the current operation grade.
4. The energy-saving operation method for urban rail transit trains according to claim 3, wherein the expected operation time of the operation level is:
desired_time＝tight_running_time×(1+time_percent)
wherein, the light _ running _ time is the running time of the compact running distance-speed curve, and the time _ percentage is the time relaxation scale factor of different operation levels.
5. The energy-saving operation method of an urban rail transit train according to claim 1, wherein the recovery means comprises: a traction recovery operation mode and a braking recovery operation mode;
when the train runs on an uphill slope, the train runs on line under traction, when the speed of the train is higher than the upper limit of the target adjustment speed, the train starts running in an idling mode, and when the speed of the train is lower than the lower limit of the target adjustment speed, the train starts running in a traction recovery running mode;
when the train runs downhill, the train is subjected to braking power to run on line, when the speed of the train is less than the lower limit of the target adjusting speed, the train starts to run in an idling mode, and when the speed of the train is greater than the upper limit of the target adjusting speed, the train starts to run in a braking recovery running mode.
6. The energy-saving operation method of an urban rail transit train according to claim 5, wherein the method for calculating and updating the upper and lower limit values of the target regulation speed during uphill comprises:
start_coast_limit＝time_regu_speed+upper_speed_margin
stop_coast_limit＝time_regu_speed-lower_speed_margin
wherein, time _ regular _ speed is a target adjusting speed, start _ coast _ limit is a target adjusting speed upper limit value, stop _ coast _ limit is a target adjusting speed lower limit value, upper _ speed _ margin is a speed adjusting threshold upper limit value, and lower _ speed _ margin is a speed adjusting threshold lower limit value;
when the vehicle runs downhill, the method for calculating and updating the upper and lower limit values of the target adjusting speed comprises the following steps:
start_coast_limit＝time_regu_speed-lower_speed_margin
stop_coast_limit＝time_regu_speed+upper_speed_margin
wherein, time _ regular _ speed is a target adjusting speed, start _ coast _ limit is a target adjusting speed lower limit value, stop _ coast _ limit is a target adjusting speed upper limit value, upper _ speed _ margin is a speed adjusting threshold upper limit value, and lower _ speed _ margin is a speed adjusting threshold lower limit value.
7. The energy-saving operation method of an urban rail transit train according to claim 6, wherein the target regulation speed calculation method in the traction recovery operation process comprises:
time_regu_speed[k]＝time_regu_speed[k-1]+Γtraction×ΔT
wherein time _ regular _ speed represents a target adjustment speed, ΓtractionThe traction acceleration threshold value in the traction recovery stage is shown, delta T is the simulation control period of an ATO interval, and subscript indexes k and k-1 respectively represent numerical values of the period and the last period;
the target adjusting speed calculating method in the braking recovery operation process comprises the following steps:
time_regu_speed[k]＝time_regu_speed[k-1]+Γbrake×ΔT
wherein time _ regular _ speed represents a target adjustment speed, ΓbrakeThe braking acceleration threshold value in the braking recovery stage is shown, delta T is the simulation control period of the ATO interval, and subscript indexes k and k-1 respectively represent numerical values of the period and the last period.
8. The energy-saving operation method of an urban rail transit train according to claim 7, wherein in the coasting operation process, the method for updating the target regulation speed on line comprises:
xp＝speed_dev_profile[p].remaining_time
yp＝speed_dev_profile[p].regu_speed
xp+1＝speed_dev_profile[p+1].remaining_time
yp+1＝speed_dev_profile[p+1].regu_speed
wherein time _ regular _ speed is a target regulation speed, remaining _ time represents a remaining time of the train at a current position, speed _ dev _ profile [ p ]]A distance-speed curve, speed _ dev _ profile [ p +1 ], representing the current position corresponding to the operating class p]Distance-speed curve, x, representing the current position corresponding to the operating class p +1pRepresenting the remaining time of the operating class p, ypTarget adjustment speed, x, representing operation level pp+1Representing the remaining time, y, of the operating class p +1p+1Indicating the target adjustment speed for the operation level p + 1.
9. The energy-saving operation method of the urban rail transit train according to claim 8, wherein when the train passes through the remaining time check point, an arrival time estimation error is calculated, and if the arrival time estimation error is less than a set threshold, an idling operation mode is adopted;
the method for estimating the error of the arrival time comprises the following steps:
where Δ v is the difference between the current speed train _ speed and the entering coasting speed start _ coast _ limit of the train, and Γ iscoastIs the resultant acceleration, Γ, of the gradient and resistance experienced by the train when coastingbrakeIs the brake acceleration threshold.
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