A train energy-saving optimization operation method considering train traction transmission system efficiency

Abstract

The application provides a train energy-saving optimization operation method considering train traction transmission system efficiency, comprising the following steps: S1: obtaining line section data to be optimized, including train information, locomotive information, line data, line speed limit and timetable data; S2: performing operation optimization without considering train transmission system efficiency for the line range to be optimized, to obtain train optimization operation curve; S3: judging whether other gentle slopes exist in the optimization curve; if yes, entering S5; if no, the optimization process ends; S4: calculating operation time to be adjusted according to replacement adjustment process; S5: replacing part of traction working conditions on other gentle slopes; S6: judging whether the overall operation time meets the constraint; if yes, the optimization process ends; if no, returning to S4. The energy-saving operation optimization model considering transmission efficiency of the application can more truly describe the actual situation of train operation, and the energy consumption calculation is also more true and reliable.

Description

TECHNICAL FIELD

[0001] The field of the present application relates to train operation control optimization, in particular to providing a train energy-saving optimization control method considering train traction drive system efficiency. TECHNICAL BACKGROUND

[0002] Railway operation consumes a large amount of energy, and nearly 68-73% of the total energy consumption is used for traction energy consumption. The energy received by the train from the catenary during operation cannot be completely converted into wheel mechanical energy, and there is a loss in between, and the loss size does not remain constant. In the actual long-distance operation of the train across multiple stations, there is often a situation that the train runs at a low speed or the train traction level is low. Under this condition, the train drive efficiency is much lower than that when the train runs at high speed and high load. Therefore, the train drive efficiency rule should be studied according to the actual situation, and the drive efficiency should be considered in the train control energy-saving optimization problem. Through reasonable control optimization, the energy consumption and loss required in the train traction process can be effectively reduced, and the purpose of energy saving is achieved from the electric energy absorbed by the train.

[0003] In the current research considering the energy loss of the train traction drive system, the drive efficiency is described as a constant or a function of the train running speed, which cannot completely describe the relationship between the drive efficiency and the train running speed and the train traction force, and there is a cumulative deviation in the energy consumption calculation of the optimization result. Or an actual nonlinear model of the traction drive system is established to completely describe the influence of various factors on the train drive efficiency. According to this model, it is difficult to perform train control energy-saving optimization, it is impossible to solve the train control energy-saving optimization problem considering the drive efficiency from the theoretical level by using the analytical method, and it is necessary to use heuristic algorithms for solving. The problem scale is large, the solving difficulty is large, and the solving speed is slow.

[0004] In the prior art, Wang Qingyuan. Simulation research on optimal energy-saving control of high-speed train considering regenerative braking energy utilization [J]. China Railway Science, 2015, 36(1): 96-103. This paper establishes a train energy-saving control kinematic model based on high-speed train, considers the utilization rate of train regenerative energy, analyzes the optimal working condition set and working condition conversion condition of train energy-saving operation by using the maximum value principle (PMP), proposes an energy-saving optimization control algorithm that meets the energy-saving operation of high-speed train on time, and uses actual cases for simulation verification.

[0005] Novak, H., V., M, 2021. Energy-efficient Model Predictive Train Traction Control with incorporated Traction System Efficiency[J]. IEEE Transactions on Intelligent Transportation Systems, 2020. 3046416. This paper considers the detailed model of train motor, takes the train transmission efficiency as a constant in optimization, and adopts a double-layer optimization structure to optimize train energy saving.

[0006] In the above two prior arts, the train transmission efficiency is constant, which does not conform to the actual running process in which the efficiency changes with the train running speed and the size of the traction force. The optimization results obtained are only applicable to the special case where the transmission efficiency is the same as the set value.

[0007] In addition, Song, Y., Song, W., 2016. A Novel Dual Speed-Curve optimization Based Approach for Energy-Saving Operation of High-Speed Trains. IEEE Transactions on Intelligent Transportation Systems, 17(6), 1564-1577. In this paper, a kinematic model of high-speed train considering traction characteristics and regenerative braking is established, the train transmission efficiency is considered as a function of train running speed, and is considered in the train kinematic model, and a double-layer optimization mode of offline global optimization and online local optimization is adopted to realize the energy-saving optimization control of high-speed train. In this technology, the influencing factors of train transmission efficiency are not considered, the influence of traction force on train transmission efficiency is not considered, and the genetic algorithm is difficult to obtain the global optimal solution as a solving method.

[0008] Zhao, X., Ke, B., Lian, K., 2018. Optimization of Train Speed Curve for Energy Saving Using Efficient and Accurate Electric Traction Models on the Mass Rapid Transit System. IEEE Transactions on Transportation Electrification, 4(4), 922-935. In this paper, accurate train traction power supply network and train operation model is established, the train operation energy saving problem is considered from the power supply side, and particle swarm algorithm is used for optimization solution. The train traction transmission system loss model in this technology is a nonlinear model established according to the actual situation, which cannot be directly solved by analytical method, and the problem scale is large, the solution difficulty is large, and the solution speed is slow. SUMMARY

[0009] In view of the above technical problems, the present application provides a train energy-saving optimization operation calculation method, which realizes the optimization of train working condition switching sequence according to the line slope condition under the condition of considering the train transmission efficiency and meeting the running time limit, improves the transmission system efficiency in the train running process, and reduces the electric energy consumption of train traction.

[0010] The terms to be explained are:

[0011] Train traction transmission system: a hardware system that converts electrical energy into mechanical energy to drive the train, and can convert mechanical energy into electrical energy to feed back to the power grid when the train brakes.

[0012] Train transmission efficiency: In the process of converting electrical energy into mechanical energy or converting mechanical energy into electrical energy by the traction transmission system, there is energy loss, and the electrical energy cannot be completely converted into mechanical energy. The train transmission efficiency refers to the ratio between the mechanical energy output by the traction transmission system and the electrical energy input.

[0013] Working condition sequence: full power traction, full power braking, coasting, constant speed and other operation modes.

[0014] The specific technical solutions are:

[0015] A train energy-saving optimization operation method considering the efficiency of train traction transmission system, comprising the following steps:

[0016] S1: Obtain the data of the line section to be optimized, including train information, locomotive information, line data, line speed limit and timetable data;

[0017] S2: The train operation curve is obtained by optimizing the train operation without considering the train transmission system efficiency for the range of the line to be optimized.

[0018] The specific sub-steps are as follows:

[0019] S2.1: The shortest running time of the train is calculated; it is judged whether the shortest running time is lower than the time constraint; if it is lower, the subsequent optimization process is entered; if it is higher, the optimization process is directly ended;

[0020] S2.2: According to the time constraint and the slope partition, the constant speed area is divided, the constant speed areas are connected, and the train optimization curve is obtained;

[0021] S2.3: It is judged whether the running time after optimization meets the constraint; if it does not meet the constraint, S2.2 is entered;

[0022] S3: It is judged whether there is other flat slope in the optimization curve; if there is, S5 is entered; if there is not, the optimization process is ended;

[0023] S4: The running time that needs to be adjusted is calculated according to the replacement adjustment process;

[0024] S5: The part of the traction working condition on the other flat slope is replaced;

[0025] S6: It is judged whether the overall running time meets the constraint; if it meets the constraint, the optimization process is ended; if it does not meet the constraint, S4 is returned.

[0026] S5 specifically includes the following sub-steps:

[0027] S5.1: The preset running distance S of the replacement interval is obtained FP，lim and the constant speed v c before replacement;

[0028] S5.2: The upper limit speed v s after replacement and the number of full traction-idling n after replacement are initialized;

[0029] S5.3: According to v s and n, the lower speed v x after replacement and the running distance S FP after replacement are calculated by substituting into the formula; the calculation formula is:

[0030] (1-θ e )F(v s )+(θ f -1)F(v x )=0

[0031]

[0032] In the formula, Let e ​​be the accompanying variable at the inflection point e of the full-traction-inertia process;

[0033] The accompanying variable at the inertia-to-full traction inflection point f;

[0034] Let be the integral constant of segment ae;

[0035] c ef =c ae +(1-θ e )F(v s ) represents the integral constant of segment ef;

[0036] c fd =c ae The constant of integration for segment fd;

[0037] S5.4: Determine the running distance S of the current replacement pair FP Is it consistent with the preset running distance S? FP，lim If they are the same, the replacement process stops; otherwise, proceed to step S5.5.

[0038] S5.5: Based on the running distance S of the current replacement pair FP Adjust the upper limit of running speed v s The adjusted upper limit running speed v s Substitute into S5.3.

[0039] Compared with the prior art, the beneficial effects of the technical solution of the present invention are as follows:

[0040] 1) The energy-saving operation optimization model that takes transmission efficiency into account more realistically describes the actual operation of the train.

[0041] 2) After considering transmission efficiency, train energy-saving optimization operation can be carried out. Even in sections with low transmission efficiency, energy-saving and efficient operation can be achieved, saving traction energy consumption from the power supply side and achieving the goal of saving electricity. At the same time, the energy consumption calculation is more realistic and reliable. Attached Figure Description

[0042] Figure 1 This invention provides an energy-saving optimized train handling curve under conditions without special track constraints.

[0043] Figure 2 This is the train transmission efficiency distribution of the present invention;

[0044] Figure 3 This is a schematic diagram of the process of the present invention;

[0045] Figure 4 This is a schematic diagram of step 2 of the present invention;

[0046] Figure 5This is a schematic diagram illustrating how the present invention replaces some traction maneuvers in other gentle slopes with full traction-coasting.

[0047] Figure 6 This is a flowchart illustrating the specific steps of the replacement calculation in this invention. Detailed Implementation

[0048] This invention employs the principle of maximizing efficiency without considering the train's traction drive system:

[0049] Train operation model:

[0050]

[0051]

[0052] Among them, u t u b These are the control coefficients for the train's traction and braking forces, satisfying u t ∈[0,1],u b ∈[0,1]and u t ·u b =0, F(v) refers to the maximum traction force per unit mass of the train, B(v) is the maximum braking force per unit mass of the train, w(v) is the train running resistance, and g r (x) is the external ramp resistance.

[0053] In addition, train operating speed and time must meet speed limits and overall time limits.

[0054] v(0)=0,v(X)=0,v(x)≤v lim (x)

[0055] t(X)-t(0)=T

[0056] Among them, v lim (x) is the maximum allowed speed, and T is the given total running time.

[0057] Based on the train operation model, the Hamiltonian function is constructed as follows:

[0058]

[0059] Among them, u t u b These are the control coefficients for the train's traction and braking forces, satisfying u t ∈[0,1],u b ∈[0,1]and u t ·u b=0, F(v) refers to the maximum traction force per unit mass of the train, B(v) is the maximum braking force per unit mass of the train, w(v) refers to the train running resistance, and g(x) is the external slope resistance.

[0060] The accompanying variables λ1=λ1(x) and λ2=λ2(x) are solutions to the accompanying equation:

[0061]

[0062]

[0063] Where M is the complementary relaxation factor. Define a new adjoint variable. The Hamiltonian function is transformed into:

[0064]

[0065] Therefore, the optimal control condition for the train can be obtained:

[0066]

[0067] The accompanying variable λ1 is related to the total train running time during the calculation process and determines the optimal speed in the constant speed section during operation. Based on the above analysis results, the train energy-saving optimization control curve under no special track conditions is as follows: Figure 1 As shown:

[0068] The following derivation process is the process protected by this patent.

[0069] (1) Train transmission efficiency

[0070] Train transmission efficiency is related to train speed and traction class, and the corresponding relationship is expressed as follows:

[0071]

[0072] The specific patterns are as follows:

[0073] When the train speed is low, v ≤ v down Regardless of the traction class of the train, the train transmission efficiency is relatively low, i.e., η = η down .

[0074] When the train traction level is low, u t ≤u t，down Regardless of the train's operating speed, the train's transmission efficiency is relatively low, i.e., η = η down .

[0075] When the train speed is greater than a small value v > v down The train's traction level exceeds a certain range. t ≥u t，upOr the train class is greater than a smaller value u t >u t，down When the train's speed exceeds a certain range, v≥v up The train transmission efficiency is relatively high, η = η up .

[0076] Train transmission efficiency distribution as follows Figure 2 As shown.

[0077] (2) Application of the maximum value principle after considering train transmission efficiency

[0078] Considering transmission efficiency, the Hamiltonian function is constructed as follows:

[0079]

[0080] Where the adjoint variables λ1=λ1(x) and λ2=λ2(x) are solutions to the adjoint equation:

[0081]

[0082]

[0083] Where M is the complementary relaxation factor. Define a new adjoint variable. The Hamiltonian function is transformed into:

[0084]

[0085] The operating condition sequence can be represented as:

[0086]

[0087] (3) Replacement of restricted traction conditions

[0088] Limited traction conditions occur when the gradient is small and the additional resistance of the track is low. The train needs to apply a traction force less than the maximum traction force to maintain a constant speed; that is, the applied traction force is: 0 < F(v). c ) < F max The associated variable takes the value θ = 1. However, according to the efficiency law of the train transmission system in (2), on slopes with small additional resistance, the long-term use of a lower traction level u < u t，min Maintaining a constant speed will result in lower transmission efficiency, which is detrimental to energy-saving train operation. Therefore, the additional resistance on a gradient is -w(v). c )<g r <u t，min F(v c )-w(v cIn cases where partial traction conditions are replaced with a full traction-coasting pair, the efficiency of the transmission system can be improved. Such slopes are referred to as other gentle slopes, where the traction level is u≥u. t，min A slope that maintains a constant speed is a restricted gentle slope.

[0089] Based on the endpoint state constraints and the changing patterns of accompanying variables for other gentle slopes, the replacement full-traction-coasting pair must start and end with full-force traction. Therefore, the replacement operation must consist of at least one full-traction-coasting-full-traction process. Simultaneously, during the replacement process, the speed at the endpoint must equal the constant speed before replacement, and the endpoint positions must be the start and end points of other gentle slopes, meaning the running distance remains unchanged after replacement.

[0090] Therefore, the process of this embodiment is as follows: Figure 3 As shown, the method is as follows:

[0091] S1: Obtain basic data: train weight (M), train traction / braking characteristics, line speed limit (v) lim Total running time limit (T) lim ).

[0092] S2: Without considering the transmission efficiency of the train traction system, energy-saving optimization of train operation is performed based on PMP, and the accompanying variable λ1 is calculated. The specific steps are as follows: Figure 4 As shown:

[0093] S2.1: Calculate the running time of the train at its maximum capacity. Based on the track gradient, speed limit, and train traction / braking characteristics, draw the train's running curves under the control modes of full traction, constant speed, and full braking, and calculate the running time.

[0094] S2.2: Determine the relationship between the maximum capacity running time and the total time constraint. If the maximum capacity running time is shorter than the given total time constraint, proceed to S2.3; otherwise, terminate the optimization process directly.

[0095] S2.3: Calculate λ1, v c v d The accompanying variables λ1 and the optimal constant speed for traction / braking v c v d There is a one-to-one correspondence between them, and v c v d This will affect the total train travel time. If v has not appeared in the current calculations... c It can be initialized according to the following formula:

[0096]

[0097] λ1,ν can be calculated using the following formula. d :

[0098] λ1+v c 2 F0(v c ) = 0

[0099]

[0100] v c To achieve the optimal constant speed for traction, v d The optimal constant speed for electric braking is given by F0, where F0 is the unit basic resistance and α is the regenerative energy utilization rate.

[0101] S2.4: Combined with speed limit, v c v d The track gradients are classified. Based on the relationship between the additional resistance and the restraining force of the track, the track gradients are divided into steep uphill slopes, steep downhill slopes, gentle uphill slopes, gentle downhill slopes, and regenerative energy-saving slopes.

[0102] S2.5: Organize the constant speed sections in the ramp zoning table. Insert constant speed sections at the beginning and end of the constant speed intervals at the end of the zoning list.

[0103] S2.6: Connection of constant speed zones. Based on the operating condition switching conditions and actual situation, the constant speed zones are connected end to end to form a global train operation optimization curve.

[0104] S2.7: Calculate the total train running time and compare it with the total time constraint. If the constraint is not met, proceed to S2.8 for readjustment; if it is met, end the optimization process and obtain the train energy-saving optimized control curve and the global adjoint variable λ1.

[0105] S2.8: Adjust v according to runtime and time constraints. c If the runtime is less than the time constraint, then increase v. c If the runtime exceeds the time constraint, then decrease v. c Return the adjustment results to S2.3.

[0106] S3: Identify the gentle slopes that require partial traction, i.e., the gentle uphill slopes in S2.4. If other gentle slopes exist within the gentle uphill slopes, proceed to S5; otherwise, end the optimization calculation.

[0107] S4: Calculate the required adjustment of running time based on the replacement adjustment of the full traction-lazy pair. The change in the overall running time due to the full traction-lazy pair calculated based on the position constraints requires adjusting the running time of the non-replacement intervals to ensure the overall running time meets the constraints. If the overall running time exceeds the time constraint, shorten the overall running time; if the overall running time is less than the time constraint, increase the overall running time.

[0108] S5: Based on the relationship between operating speed and speed limit, replace some traction control in other gentle slopes with full traction-coasting pairs. The diagram after replacement is shown below. Figure 5 As shown:

[0109] The specific steps for replacement calculation are as follows: Figure 6 As shown.

[0110] S5.1: Obtain the preset running distance S of the replacement interval FP，lim and the constant speed v before replacement c .

[0111] S5.2: Initialize and replace the upper limit speed v s And the number of fully traction-lazy logarithms after replacement, n.

[0112] S5.3: According to v s Substitute n into the formula to calculate the lower linear velocity v. x and the running distance S after replacement FP The calculation formula is:

[0113] (1-θ e )F(v s )+(θ f -1)F(v x ) = 0

[0114]

[0115] In the formula, Let e ​​be the accompanying variable at the inflection point e of the full-traction-inertia process.

[0116] Let f be the accompanying variable at the inertial-to-full traction inflection point.

[0117] Let be the integral constant of segment ae.

[0118] c ef =c ae +(1-θ e )F(v s ) is the integral constant of segment ef.

[0119] c fd =c ae is the integration constant for segment fd.

[0120] S5.4: Determine the running distance S of the current replacement pair FP Is it consistent with the preset running distance S? FP，lim If they are the same, the replacement process stops; otherwise, proceed to S5.5.

[0121] S5.5: Based on the running distance S of the current replacement pair FPAdjust the upper limit of running speed v s The adjusted upper limit running speed v s Substitute into S5.3.

[0122] S6: Determine whether the overall train travel time meets the constraints. If it does, the optimization calculation ends; otherwise, return to S4.

[0123] Based on the above optimization algorithm, the output results are the train control sequence and the optimized train operation curve.

Claims

1. A train energy-saving optimization operation method considering the efficiency of the train traction drive system, characterized in that, Includes the following steps: S1: Obtain data on the section of the line to be optimized, including train information, locomotive information, line data, line speed limits, and timetable data; S2: Perform operation optimization on the range of lines to be optimized without considering the efficiency of the train transmission system to obtain the optimized train operation curve; S3: Determine if there are other gentle slopes in the optimization curve; if so, proceed to S5; otherwise, the optimization process ends. Additional resistance of ramps In some cases, replacing some traction conditions with a full traction-coasting pair configuration improves transmission system efficiency; such slopes are called other gentle slopes. This refers to the maximum traction force per unit mass of the train. This refers to the resistance of train operation. It is the external slope resistance; S4: Calculate the required runtime adjustment based on the replacement and adjustment process; S5: Replace some of the traction conditions on other gentle slopes; S5 specifically includes the following sub-steps: S5.1: Obtain the preset running distance of the replacement interval and constant speed before replacement ; S5.2: Initialize replacement upper limit speed And the logarithm of full pull-lazy movement after replacement ; S5.3: According to and Substitute into the formula to calculate the lower linear velocity. and the distance after replacement The calculation formula is: ； ； In the formula, Let e ​​be the accompanying variable at the inflection point e of the full-traction-inertia process; The accompanying variable at the inertia-to-full traction inflection point f; for The integral constant of the segment; for Segmental integral constant; This refers to the maximum traction force per unit mass of the train. This refers to the resistance of train operation. It is the external slope resistance; S5.4: Determine the running distance of the current replacement pair Is it consistent with the preset running distance? If they are the same, the replacement process stops; otherwise, proceed to step S5.

5. S5.5: Based on the running distance of the current replacement pair Adjust the maximum running speed ; Adjust the upper limit running speed Substitute into S5.3; S6: Determine whether the overall running time meets the constraints; if it does, the optimization process ends; otherwise, return to S4.

2. The train energy-saving optimization operation method considering the efficiency of the train traction drive system according to claim 1, characterized in that, S2 specifically includes the following sub-steps: S2.1: Calculate the shortest train running time; determine whether the shortest running time is lower than the time constraint. If it is lower, proceed to the subsequent optimization process; if it is higher, end the optimization process directly. S2.2: Based on time constraints and gradient zones, divide the constant speed zone, connect the constant speed zones, and obtain the train optimization curve; S2.3: Determine whether the optimized running time meets the constraints. If not, proceed to S2.2.

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