CN115329160A - Global optimal energy-saving speed curve generation method for high-speed train - Google Patents
Global optimal energy-saving speed curve generation method for high-speed train Download PDFInfo
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Abstract
The invention discloses a global optimal energy-saving speed curve generation method for a high-speed train, which comprises the steps of obtaining high-speed train data, line data and interval operation data; iteratively calculating a corresponding maximum operation capacity curve based on the line speed limit value, and searching the lower limit of the range of the optimal speed limit value; iteratively calculating a corresponding longest coasting energy-saving optimized speed curve based on the line speed limit value, and searching the upper limit of the range where the optimal speed limit value is located; calculating a feasible coasting energy-saving optimization speed curve with the running time meeting the set running time under each speed limit value according to the lower limit and the upper limit of the range of the optimal speed limit value; and selecting the feasible coasting energy-saving optimization speed curve with the minimum energy consumption from all the feasible coasting energy-saving optimization speed curves to obtain a global energy-saving optimal speed curve. The invention can greatly reduce the average time of one iteration and reduce the search range, thereby reducing the iteration times, improving the search efficiency and further reducing the energy consumption.
Description
Technical Field
The invention relates to the technical field of generation of a reference speed curve of a high-speed train, in particular to a global optimal energy-saving speed curve generation method of the high-speed train.
Background
The energy consumption of traction in the high-speed train accounts for about 70 percent of the total energy consumption of the high-speed train railway, and the high-speed train has larger energy-saving space. Therefore, under the constraint conditions of train operation safety and punctuality, the generation algorithm of the global energy-saving optimal speed curve of the high-speed train is researched with the aim of minimizing the traction energy consumption, a reference speed curve and an operation prompt can be provided for a driver, and the train traction energy consumption is reduced. This work is of great significance.
Most of the existing energy-saving optimized speed curve generation algorithms for high-speed trains adopt an optimization strategy for increasing coasting, that is, coasting is inserted into a maximum capacity curve as far as possible under the conditions of given lines, train dynamics parameters and target running time and allowance time, namely the difference between set interval running time and the time required by the maximum running capacity curve, so as to achieve the purpose of energy conservation. However, the global optimum is not fully considered in the existing algorithm, that is, when the surplus time is long, a group of feasible solutions exist, and the running time of the speed curve at different target constant speeds all meets a group of lazy energy-saving optimized speed curves with set running time, and an energy-saving speed curve with the minimum energy consumption exists in the group of feasible solutions, that is, the global energy-saving optimum speed curve.
In conclusion, the energy-saving optimal speed curve generation algorithm for the high-speed train has important significance for reducing train traction energy consumption and realizing train energy-saving operation. However, existing speed curve generation algorithms do not consider global optima to be sufficient.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a global optimal energy-saving speed curve generation method for a high-speed train, which integrates an idling energy-saving optimization strategy and a line speed limit adjustment strategy.
In order to achieve the purpose of the invention, the invention adopts the technical scheme that:
a global optimal energy-saving speed curve generation method for a high-speed train comprises the following steps:
s1, acquiring high-speed train data, line data and interval running data;
s2, iteratively calculating a corresponding maximum operation capacity curve based on the line speed limit values, and searching the corresponding line speed limit values in the maximum operation capacity curve when the operation time meets the set operation time, wherein the line speed limit values serve as the lower limit of the range of the optimal speed limit value;
s3, iteratively calculating a corresponding longest coasting energy-saving optimization speed curve based on the line speed limit values, and searching the corresponding line speed limit value when the running time in the longest coasting energy-saving optimization speed curve meets the set running time, wherein the line speed limit value is used as the upper limit of the range where the optimal speed limit value is located;
s4, calculating a feasible coasting energy-saving optimization speed curve with the running time meeting the set running time under each speed limit value according to the lower limit and the upper limit of the range of the optimal speed limit value;
and S5, selecting the feasible coasting energy-saving optimization speed curve with the minimum energy consumption from all the feasible coasting energy-saving optimization speed curves to obtain a global energy-saving optimal speed curve.
Alternatively, in step S1,
the high-speed train data specifically includes: vehicle length, load mass, rotating mass coefficient, rotating adhesion coefficient, auxiliary power, transmission efficiency, regeneration efficiency, traction characteristic, braking characteristic, deceleration characteristic;
the line data specifically includes: the method comprises the following steps of (1) limiting speed of a line, gradient of a ramp, radius of a curve, length of the curve, length of a tunnel, kilometer posts of station positions, electric split-phase kilometer posts and whether long or short chains exist;
the interval operation data specifically includes: a start station, a terminal station, a scheduled departure time, a scheduled arrival time.
Optionally, step S2 specifically includes the following sub-steps:
s21, taking the initial line speed limit value as the upper limit of an iteration interval, taking the lowest speed limit value allowed by the line as the lower limit of the iteration interval, and selecting one line speed limit value from the upper limit and the lower limit of the iteration interval as the initial iteration speed limit value;
s22, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating a maximum operation capacity curve and corresponding operation time of the high-speed train under the line speed limit condition;
s23, judging whether the running time corresponding to the maximum running capacity curve is equal to the set running time or not;
if yes, jumping to step S26;
otherwise, jumping to step S24;
s24, determining a next iteration speed limit value according to a difference value between the running time corresponding to the maximum running capacity curve and the set running time;
s25, judging whether the determined next iteration speed limit value exceeds the upper limit and the lower limit of the iteration interval;
if yes, ending the process;
otherwise, returning to the step S22;
and S26, outputting the iteration speed limit value at the moment as the lower limit of the range of the optimal speed limit value.
Optionally, the step S22 of calculating the maximum operation capacity curve of the high-speed train under the line speed limit condition specifically includes:
constructing a high-speed train operation model, and obtaining an optimal control working condition of the high-speed train according to the constraint conditions that the operation speed and the operation time of the high-speed train meet the speed limit and the overall time limit;
and taking the iteration speed limit value at the moment as a new line speed limit value, accelerating to the line speed limit value by adopting a full-force traction working condition under the line speed limit condition, maintaining a constant speed by adopting a partial traction working condition and a partial braking working condition, braking in advance when a low speed limit or a stop is met in the front, reversely calculating a speed-position curve according to the full-force braking working condition, intersecting with the constant speed part, and finally generating a maximum running capacity curve of the high-speed train.
Optionally, step S3 specifically includes the following sub-steps:
s31, taking the initial line speed limit value as the upper limit of an iteration interval, taking the lower limit of the range where the optimal speed limit value obtained in the step S2 is located as the lower limit of the iteration interval, and selecting one line speed limit value from the upper limit and the lower limit of the iteration interval as the initial iteration speed limit value;
s32, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating the longest coasting energy-saving optimized speed curve and the corresponding running time of the high-speed train under the line speed limit condition;
s33, judging whether the running time corresponding to the longest coasting energy-saving optimization speed curve is equal to the set running time or not;
if yes, jumping to step S36;
otherwise, jumping to step S34;
s34, determining a next iteration speed limit value according to a difference value between the running time corresponding to the longest coasting energy-saving optimization speed curve and the set running time;
s35, judging whether the determined next iteration speed limit value exceeds the upper limit and the lower limit of the iteration interval;
if yes, ending the process;
otherwise, returning to step S32;
and S36, outputting the iteration speed limit value at the moment as the upper limit of the range of the optimal speed limit value.
Optionally, the step S32 of calculating the longest coasting energy-saving optimized speed curve of the high-speed train under the line speed-limiting condition specifically includes:
replacing the braking working condition sections after traction with the coasting working condition based on the maximum operation capacity curve calculated in the step S2, wherein the replacement condition is that the speed-position curve under the replaced coasting working condition is connected with the original curve and the coasting working condition curve in each replaced section is as long as possible;
and (4) completely replacing all the traction braking conditions meeting the replacement conditions to obtain the longest coasting energy-saving optimized speed curve of the high-speed train.
Optionally, step S4 specifically includes the following steps:
s41, taking the optimal speed limit value range determined according to the lower limit of the range where the optimal speed limit value obtained in the step S2 is located and the upper limit of the range where the optimal speed limit value obtained in the step S3 is located as a search interval, setting an iteration step length according to the solving precision, and taking the lower limit of the range where the optimal speed limit value is located as an initial iteration speed limit value;
s42, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating an idle energy-saving optimized speed curve and corresponding running time of the high-speed train under the line speed limit condition;
s43, judging whether the running time corresponding to the coasting energy-saving optimization speed curve is equal to the set running time or not;
if yes, jumping to step S44;
otherwise, jumping to step S45;
s44, saving the coasting energy-saving optimization speed curve corresponding to the iteration speed limit value at the moment as a feasible solution;
s45, determining the next iteration speed limit value according to the iteration speed limit value and the iteration step length at the moment;
s46, judging whether the determined next iteration speed limit value exceeds a search interval;
if yes, ending the process;
otherwise, return to step S42.
Optionally, the step S42 of calculating the coasting energy-saving optimized speed curve of the high-speed train under the line speed-limiting condition specifically includes:
s421, replacing the braking working condition section after traction with an idling working condition based on the maximum operation capacity curve calculated in the step S2;
s422, the allowance time is calculated according to the maximum operation capacity curve and the set operation time,
s423, judging whether the allowance time is less than or equal to zero;
if so, taking the maximum operation capacity curve as an idling energy-saving optimized speed curve;
otherwise, jumping to step S425;
s424, judging whether the set running time is larger than the longest coasting time under the current speed limit;
if so, taking the longest coasting energy-saving optimization speed curve calculated in the step S3 as a coasting energy-saving optimization speed curve;
otherwise, jumping to step S425;
and S425, determining the length of the coasting working condition in each section which is replaced by the coasting working condition according to the surplus time, and taking the speed-position curve after replacement as a coasting energy-saving optimized speed curve.
The invention has the following beneficial effects:
(1) The invention realizes feasible solution of the coasting energy-saving optimization speed curve in the full speed domain under the condition that the curve running time is equal to a set running time and a group of different line speed limits is met by integrating the coasting energy-saving optimization strategy and the speed limit adjustment strategy, and outputs the speed curve with the minimum energy consumption, namely the global energy-saving optimal speed curve, thereby further reducing the energy consumption.
(2) According to the invention, the upper limit of the feasible speed-limiting interval is quickly determined by calculating the maximum capacity curve in iteration, and the lower limit of the feasible speed-limiting interval is quickly determined by calculating the longest coasting energy-saving optimization speed curve in iteration, so that the calculation times of the coasting energy-saving optimization curve which is time-consuming due to the need of allocating coasting intervals are greatly reduced, the average time for performing one iteration is greatly reduced, the search range is also reduced, the iteration times are reduced, and the search efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a method for generating a global optimal energy-saving speed curve of a high-speed train according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
As shown in fig. 1, an embodiment of the present invention provides a method for generating a global optimal energy-saving speed curve of a high-speed train, including the following steps:
s1, acquiring high-speed train data, line data and interval operation data;
in an alternative embodiment of the present invention, step S1 of the present invention requires obtaining basic data for energy-saving speed curve generation, including high-speed train data, route data, and section operation data.
The high-speed train data specifically comprises the following steps: vehicle length, load mass, coefficient of rotary adhesion, auxiliary power, transmission efficiency, regeneration efficiency, traction characteristics, braking characteristics, deceleration characteristics;
the line data specifically includes: the method comprises the following steps of (1) limiting speed of a line, gradient of a ramp, radius of a curve, length of the curve, length of a tunnel, kilometer posts of station positions, electric split-phase kilometer posts and whether long or short chains exist;
the interval operation data specifically includes: a start station, a terminal station, a scheduled departure time, a scheduled arrival time.
S2, iteratively calculating a corresponding maximum operation capacity curve based on the line speed limit values, and searching the corresponding line speed limit values when the operation time in the maximum operation capacity curve meets the set operation time to serve as the lower limit of the range of the optimal speed limit value;
in an optional embodiment of the present invention, step S2 of the present invention searches for a lower limit of the feasible speed limit value range, that is, calculates a corresponding maximum operation capacity curve by continuously changing the speed limit value, and searches for a speed limit value when the maximum capacity curve operation time satisfies the set operation time, as the feasible speed limit value range, that is, the lower limit of the range where the optimal speed limit value is located.
In an optional embodiment of the present invention, step S2 of the present invention specifically includes the following substeps S21 to S26:
s21, taking the initial line speed limit value as the upper limit of an iteration interval, taking the lowest speed limit value allowed by a line as the lower limit of the iteration interval, and selecting a line speed limit value between the upper limit and the lower limit of the iteration interval as an initial iteration speed limit value, so that the initialization of the iteration interval and the initial iteration speed limit value is realized;
s22, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating a maximum operation capacity curve and corresponding operation time of the high-speed train under the line speed limit condition;
in an optional embodiment of the present invention, the step S22 of calculating the maximum operation capacity curve of the high-speed train under the line speed limit condition specifically includes the following substeps S221 to S222:
s221, constructing a high-speed train operation model, and obtaining an optimal control working condition of the high-speed train according to the constraint condition that the operation speed and the operation time of the high-speed train meet the speed limit and the overall time limit;
in step S221, the method of constructing a high-speed train operation model includes:
wherein u is t ，u b Control coefficients of train traction and braking force respectively, and satisfy u t ∈[0，1]，u b ∈[0，1]And u is t ·u b =0, F (v) refers to the maximum traction force of the train under unit mass, B (v) refers to the maximum braking force of the train under unit mass, w (v) refers to the running resistance of the train, g r (x) Is the external ramp resistance, v is the train operating speed, x is the train position, and t is the operating time.
The constraint conditions that the running speed and time of the high-speed train need to meet the speed limit and the overall time limit are as follows:
v(0)＝0，v(X)＝0，v(x)≤v lim (x)
t(X)-t(0)＝T
wherein v is lim (x) Is the maximum allowable speed, T is the given overall operating time, and X is the operating end position.
According to the train operation model, constructing a Hamiltonian:
accompanying variable lambda 1 ＝λ 1 (x)，λ 2 ＝λ 2 (x) Is the solution of the adjoint equation
Wherein M is a complementary relaxation factor.
Defining new companion variables
The Hamiltonian is converted into
Thereby obtaining the optimal control working condition of the train, as shown in table 1.
TABLE 1
S222, taking the iteration speed limit value at the moment as a new line speed limit value, accelerating to the line speed limit value by adopting a full-force traction working condition under the line speed limit condition, maintaining a constant speed by adopting a partial traction working condition and a partial braking working condition, braking in advance when a low speed limit or a stop is met in the front, reversely calculating a speed-position curve according to the full-force braking working condition, intersecting with the constant speed part, and finally generating a maximum running capacity curve of the high-speed train.
In step S222, under a given speed limit, the present invention solves to obtain a maximum operational capacity curve of the high-speed train according to the line condition, train characteristics and target constraints under a full-force traction condition, a constant-speed condition (including constant-speed partial traction and constant-speed partial braking), and a full-force braking condition sequence. The curve consumes the least time and consumes the most energy under the speed limit.
Finally, the invention calculates the operation time of the maximum operation capacity curve of the high-speed train, and the calculation formula is as follows:
s23, judging whether the running time corresponding to the maximum running capacity curve is equal to the set running time or not; the set running time is specifically interval running time specified by the running time schedule;
if yes, jumping to step S26;
otherwise, jumping to step S24;
s24, determining a next iteration speed limit value according to a difference value between the running time corresponding to the maximum running capacity curve and the set running time;
specifically, iteration methods such as a bisection method and a steepest descent method can be adopted, and a next iteration speed limit value is determined according to a difference value between the running time corresponding to the maximum running capacity curve and the set running time;
s25, judging whether the determined next iteration speed limit value exceeds the upper limit and the lower limit of the iteration interval;
if yes, ending the process;
otherwise, returning to the step S22;
and S26, outputting the iteration speed limit value at the moment as the lower limit of the range of the optimal speed limit value.
S3, iteratively calculating a corresponding longest coasting energy-saving optimization speed curve based on the line speed limit values, and searching the corresponding line speed limit value when the running time in the longest coasting energy-saving optimization speed curve meets the set running time, wherein the line speed limit value is used as the upper limit of the range where the optimal speed limit value is located;
in an optional embodiment of the present invention, step S3 of the present invention searches for an upper limit of a feasible speed limit range, that is, searches for a speed limit when an operating time of the energy-saving optimized speed curve satisfies a set operating time by continuously changing the speed limit and then calculating a longest coasting energy-saving optimized speed curve, and takes the speed limit as the feasible speed limit range, that is, an upper limit of a range where an optimal speed limit is located.
In an optional embodiment of the present invention, step S3 of the present invention specifically includes the following sub-steps:
s31, taking the initial line speed limit value as the upper limit of an iteration interval, taking the lower limit of the range where the optimal speed limit value obtained in the step S2 is located as the lower limit of the iteration interval, and selecting one line speed limit value from the upper limit and the lower limit of the iteration interval as the initial iteration speed limit value, so that the initialization of the iteration interval and the initial iteration speed limit value is realized;
s32, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating the longest coasting energy-saving optimized speed curve of the high-speed train under the line speed limit condition and the corresponding running time;
in an optional embodiment of the present invention, the step S32 of calculating the longest coasting energy-saving optimized speed curve of the high-speed train under the line speed-limiting condition in the present invention specifically includes:
replacing the braking working condition sections after traction with the coasting working condition based on the maximum operation capacity curve calculated in the step S2, wherein the replacement condition is that the speed-position curve under the replaced coasting working condition is connected with the original curve and the coasting working condition curve in each replaced section is as long as possible, namely the longest replacement length under the condition of connecting the original curve can be ensured;
and (4) completely replacing all the traction braking conditions meeting the replacement conditions to obtain the longest coasting energy-saving optimized speed curve of the high-speed train.
The running time is increased when the coasting working condition is replaced each time until all the traction rear braking working conditions meeting the conditions are replaced, the speed-position curve at the moment is the longest coasting energy-saving optimized speed curve, and the energy consumption of the curve is minimum and the time consumption is longest under the speed limit.
S33, judging whether the running time corresponding to the longest coasting energy-saving optimization speed curve is equal to the set running time or not;
if yes, jumping to step S36;
otherwise, jumping to step S34;
s34, determining a next iteration speed limit value according to a difference value between the running time corresponding to the longest coasting energy-saving optimization speed curve and the set running time;
specifically, iteration methods such as a bisection method and a steepest descent method can be adopted, and the next iteration speed limit value is determined according to the difference value between the running time corresponding to the longest coasting energy-saving optimization speed curve and the set running time;
s35, judging whether the determined next iteration speed limit value exceeds the upper limit and the lower limit of the iteration interval;
if yes, ending the process;
otherwise, returning to step S32;
and S36, outputting the iteration speed limit value at the moment as the upper limit of the range of the optimal speed limit value.
S4, calculating a feasible coasting energy-saving optimization speed curve with the running time meeting the set running time under each speed limit value according to the lower limit and the upper limit of the range of the optimal speed limit value;
in an optional embodiment of the present invention, step S4 of the present invention obtains all feasible coasting energy-saving optimized speed curves, that is, by setting an appropriate step size, a feasible coasting energy-saving optimized speed curve whose running time of each speed-limiting speed curve meets a set running time is calculated in a feasible speed-limiting value range determined by the lower limit of the feasible speed-limiting value range obtained in step S2 and the upper limit of the feasible speed-limiting value range obtained in step S3.
Step S4 of the present invention specifically includes the following steps:
s41, taking the optimal speed limit value range determined according to the lower limit of the range where the optimal speed limit value obtained in the step S2 is located and the upper limit of the range where the optimal speed limit value obtained in the step S3 is located as a search interval, setting an iteration step length according to the solving precision, and taking the lower limit of the range where the optimal speed limit value is located as an initial iteration speed limit value;
specifically, the feasible limit range determined by the lower limit of the feasible speed limit range obtained in the step S2 and the upper limit of the feasible speed limit range obtained in the step S3 is used as a search interval, an iteration step length is set according to the solving precision, the iteration step length of the normal solving precision is 1km/h, the high-precision iteration step length is set to 0.1km/h, and the lower limit of the feasible speed limit range is used as an initial iteration speed limit value, so that the search interval, the initial iteration speed limit value and the iteration step length are determined.
S42, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating a coasting energy-saving optimized speed curve and corresponding running time of the high-speed train under the line speed limit condition;
in an optional embodiment of the present invention, the step S42 of calculating the coasting energy-saving optimized speed curve of the high-speed train under the line speed-limiting condition in the present invention specifically includes:
s421, replacing the braking working condition section after traction with an idling working condition based on the maximum operation capacity curve calculated in the step S2;
s422, calculating the allowance time according to the maximum operation capacity curve and the set operation time,
s423, judging whether the allowance time is less than or equal to zero;
if so, taking the maximum operation capacity curve as an idling energy-saving optimized speed curve;
otherwise, jumping to step S425;
s424, judging whether the set running time is larger than the longest coasting time under the current speed limit;
if so, taking the longest coasting energy-saving optimization speed curve calculated in the step S3 as a coasting energy-saving optimization speed curve;
otherwise, jumping to step S425;
and S425, determining the length of the coasting working condition in each section which is replaced by the coasting working condition according to the allowance time, and taking the replaced speed-position curve as a coasting energy-saving optimized speed curve.
Specifically, the coasting energy saving optimization speed curve herein refers to a speed curve between the maximum capacity curve and the longest coasting energy saving optimization speed curve at a given speed limit.
The invention firstly obtains the maximum capacity curve and the longest coasting energy-saving optimized speed curve under the given speed limit, still replaces the braking working condition after traction in the maximum capacity curve with the coasting working condition, a plurality of replaceable coasting working condition curves are arranged in the same section, the lengths of the curves are decreased gradually, and the curves can be connected with the original maximum capacity curve. It is known that the larger the coasting proportion is, the lower the energy consumption is and the longer the time is, but the different length coasting curves of different sections have different energy efficiency ratios (energy consumption per unit time). According to the invention, the allowance time is distributed, so that the energy efficiency ratio of the coasting working condition curve in each braking working condition section after traction is the highest, and the corresponding speed curve is the coasting energy-saving optimized speed curve.
If the allowance time is less than or equal to 0, the coasting energy-saving optimized speed curve is the maximum operation curve; if the set time T0 is larger than the longest coasting time required under the current speed limit, the coasting energy-saving optimized speed curve is the longest coasting running curve; otherwise, the length of the coasting condition in each zone that can be replaced with the coasting condition is determined based on the slack time.
S43, judging whether the running time corresponding to the coasting energy-saving optimization speed curve is equal to the set running time or not;
if yes, jumping to step S44;
otherwise, jumping to step S45;
s44, saving the coasting energy-saving optimization speed curve corresponding to the iteration speed limit value at the moment as a feasible solution;
s45, determining the next iteration speed limit value according to the iteration speed limit value and the iteration step length at the moment;
specifically, the invention determines the next iteration speed limit value by adding the iteration step length to the iteration speed limit value at the moment.
S46, judging whether the determined next iteration speed limit value exceeds a search interval;
if yes, ending the process;
otherwise, it returns to step S42.
And S5, selecting the feasible coasting energy-saving optimization speed curve with the minimum energy consumption from all the feasible coasting energy-saving optimization speed curves to obtain a global energy-saving optimal speed curve.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.
Claims (8)
1. A global optimal energy-saving speed curve generation method for a high-speed train is characterized by comprising the following steps:
s1, acquiring high-speed train data, line data and interval operation data;
s2, iteratively calculating a corresponding maximum operation capacity curve based on the line speed limit values, and searching the corresponding line speed limit values when the operation time in the maximum operation capacity curve meets the set operation time to serve as the lower limit of the range of the optimal speed limit value;
s3, iteratively calculating a corresponding longest coasting energy-saving optimization speed curve based on the line speed limit values, and searching the corresponding line speed limit value when the running time in the longest coasting energy-saving optimization speed curve meets the set running time, wherein the line speed limit value is used as the upper limit of the range where the optimal speed limit value is located;
s4, calculating a feasible coasting energy-saving optimization speed curve with the running time meeting the set running time under each speed limit value according to the lower limit and the upper limit of the range of the optimal speed limit value;
and S5, selecting the feasible coasting energy-saving optimization speed curve with the minimum energy consumption from all the feasible coasting energy-saving optimization speed curves to obtain a global energy-saving optimal speed curve.
2. The method for generating the global optimal energy-saving speed curve of the high-speed train according to claim 1, wherein in step S1,
the high-speed train data specifically includes: vehicle length, load mass, rotating mass coefficient, rotating adhesion coefficient, auxiliary power, transmission efficiency, regeneration efficiency, traction characteristic, braking characteristic, deceleration characteristic;
the line data specifically includes: the method comprises the following steps of (1) limiting speed of a line, gradient of a ramp, radius of a curve, length of the curve, length of a tunnel, kilometer posts of station positions, electric split-phase kilometer posts and whether long or short chains exist;
the interval operation data specifically includes: a start station, a terminal station, a scheduled departure time, a scheduled arrival time.
3. The method for generating the global optimal energy-saving speed curve of the high-speed train according to claim 1, wherein the step S2 specifically comprises the following substeps:
s21, taking the initial line speed limit value as the upper limit of an iteration interval, taking the lowest speed limit value allowed by a line as the lower limit of the iteration interval, and selecting one line speed limit value from the upper limit and the lower limit of the iteration interval as the initial iteration speed limit value;
s22, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating a maximum operation capacity curve and corresponding operation time of the high-speed train under the line speed limit condition;
s23, judging whether the running time corresponding to the maximum running capacity curve is equal to the set running time or not;
if yes, jumping to step S26;
otherwise, jumping to step S24;
s24, determining a next iteration speed limit value according to a difference value between the running time corresponding to the maximum running capacity curve and the set running time;
s25, judging whether the determined next iteration speed limit value exceeds the upper limit and the lower limit of the iteration interval;
if yes, ending the process;
otherwise, returning to the step S22;
and S26, outputting the iteration speed limit value at the moment as the lower limit of the range of the optimal speed limit value.
4. The method for generating the global optimal energy-saving speed curve of the high-speed train according to claim 3, wherein the step S22 of calculating the maximum operation capacity curve of the high-speed train under the line speed limit condition specifically comprises the following steps:
constructing a high-speed train operation model, and obtaining the optimal control working condition of the high-speed train according to the constraint conditions that the operation speed and the operation time of the high-speed train meet the speed limit and the overall time limit;
and taking the iteration speed limit value at the moment as a new line speed limit value, accelerating to the line speed limit value by adopting a full-force traction working condition under the line speed limit condition, maintaining a constant speed by adopting a partial traction working condition and a partial braking working condition, braking in advance when a low speed limit or a stop is met in the front, reversely calculating a speed-position curve according to the full-force braking working condition, and intersecting with the constant speed part to finally generate a maximum operation capacity curve of the high-speed train.
5. The method for generating the global optimal energy-saving speed curve of the high-speed train according to claim 1, wherein the step S3 specifically comprises the following substeps:
s31, taking the initial line speed limit value as the upper limit of an iteration interval, taking the lower limit of the range where the optimal speed limit value obtained in the step S2 is located as the lower limit of the iteration interval, and selecting one line speed limit value from the upper limit and the lower limit of the iteration interval as the initial iteration speed limit value;
s32, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating the longest coasting energy-saving optimized speed curve of the high-speed train under the line speed limit condition and the corresponding running time;
s33, judging whether the running time corresponding to the longest coasting energy-saving optimization speed curve is equal to the set running time or not;
if yes, jumping to step S36;
otherwise, jumping to step S34;
s34, determining a next iteration speed limit value according to a difference value between the running time corresponding to the longest coasting energy-saving optimization speed curve and the set running time;
s35, judging whether the determined next iteration speed limit value exceeds the upper limit and the lower limit of the iteration interval;
if yes, ending the process;
otherwise, returning to step S32;
and S36, outputting the iteration speed limit value at the moment as the upper limit of the range of the optimal speed limit value.
6. The method for generating the global optimal energy-saving speed curve of the high-speed train according to claim 5, wherein the step S32 of calculating the longest coasting energy-saving optimized speed curve of the high-speed train under the line speed limit condition specifically comprises:
replacing the braking working condition sections after traction with the coasting working condition based on the maximum operation capacity curve calculated in the step S2, wherein the replacement condition is that the speed-position curve under the replaced coasting working condition is connected with the original curve and the coasting working condition curve in each replaced section is as long as possible;
and (4) completely replacing all traction braking conditions meeting the replacement condition to obtain the longest coasting energy-saving optimized speed curve of the high-speed train.
7. The method for generating the global optimal energy-saving speed curve of the high-speed train according to claim 1, wherein the step S4 specifically comprises the following steps:
s41, taking the optimal speed limit value range determined according to the lower limit of the range where the optimal speed limit value obtained in the step S2 is located and the upper limit of the range where the optimal speed limit value obtained in the step S3 is located as a search interval, setting an iteration step length according to the solving precision, and taking the lower limit of the range where the optimal speed limit value is located as an initial iteration speed limit value;
s42, taking the iteration speed limit value at the moment as a new line speed limit value, and calculating an idle energy-saving optimized speed curve and corresponding running time of the high-speed train under the line speed limit condition;
s43, judging whether the running time corresponding to the coasting energy-saving optimization speed curve is equal to the set running time or not;
if yes, jumping to step S44;
otherwise, jumping to step S45;
s44, saving the coasting energy-saving optimization speed curve corresponding to the iteration speed limit value at the moment as a feasible solution;
s45, determining the next iteration speed limit value according to the iteration speed limit value and the iteration step length at the moment;
s46, judging whether the determined next iteration speed limit value exceeds a search interval;
if yes, ending the process;
otherwise, it returns to step S42.
8. The method for generating the global optimal energy-saving speed curve of the high-speed train according to claim 7, wherein the step S42 of calculating the coasting energy-saving optimized speed curve of the high-speed train under the line speed-limiting condition specifically comprises:
s421, replacing the braking working condition section after traction with an idling working condition based on the maximum operation capacity curve calculated in the step S2;
s422, the allowance time is calculated according to the maximum operation capacity curve and the set operation time,
s423, judging whether the allowance time is less than or equal to zero;
if so, taking the maximum operation capacity curve as an idling energy-saving optimized speed curve;
otherwise, jumping to step S425;
s424, judging whether the set running time is larger than the longest coasting time required under the current speed limit;
if so, taking the longest coasting energy-saving optimization speed curve calculated in the step S3 as a coasting energy-saving optimization speed curve;
otherwise, jumping to step S425;
and S425, determining the length of the coasting working condition in each section which is replaced by the coasting working condition according to the allowance time, and taking the replaced speed-position curve as a coasting energy-saving optimized speed curve.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116890800A (en) * | 2023-09-11 | 2023-10-17 | 成都交控轨道科技有限公司 | Train emergency braking triggering speed calculation method and system |
| CN117261974A (en) * | 2023-11-17 | 2023-12-22 | 北京全路通信信号研究设计院集团有限公司 | Calculation mode speed limit value calculation algorithm and system based on dichotomy |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116890800A (en) * | 2023-09-11 | 2023-10-17 | 成都交控轨道科技有限公司 | Train emergency braking triggering speed calculation method and system |
| CN116890800B (en) * | 2023-09-11 | 2024-01-19 | 成都交控轨道科技有限公司 | Train emergency braking triggering speed calculation method and system |
| CN117261974A (en) * | 2023-11-17 | 2023-12-22 | 北京全路通信信号研究设计院集团有限公司 | Calculation mode speed limit value calculation algorithm and system based on dichotomy |
| CN117261974B (en) * | 2023-11-17 | 2024-02-09 | 北京全路通信信号研究设计院集团有限公司 | Calculation mode speed limit value calculation algorithm and system based on dichotomy |
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