Train emergency self-walking energy consumption distribution optimization method and device

Abstract

The invention provides a train emergency self-walking energy consumption distribution optimization method and device, and relates to the technical field of train operation energy-saving optimization. The method comprises the steps that a working condition section of train operation is determined, and available regenerative braking energy is determined according to the surplus capacity of train vehicle-mounted energy storage equipment, the maximum value of train vehicle-mounted energy storage energy, regenerative braking power of a braking section and electric power of an auxiliary system; the working condition section comprises a traction section and a braking section; if it is determined that the regenerative braking power is larger than or equal to the auxiliary system electric power of the braking section and it is determined that residual energy exists according to the regenerative braking energy, the auxiliary system electric power of the working condition section is adjusted; and recalculating the train operation energy consumption according to the adjusted auxiliary system electric power of the working condition section to obtain the optimized train operation energy consumption. The device executes the method. According to the method and device provided by the embodiment of the invention, the utilization efficiency of the emergency self-walking energy consumption of the train can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy-saving optimization for train operation, and particularly relates to a method and device for optimizing the energy consumption distribution of emergency self-propulsion of trains. Background Art

[0002] During the operation of EMUs, sometimes the catenary power failure may occur due to factors such as bad weather, high-voltage cable detachment, catenary fault, power supply system fault, etc., resulting in the loss of train power and affecting the normal daily operation of trains. When this fault occurs in an EMU, it is likely to cause a series of impacts. For example, due to the power failure of the train, potential safety hazards may occur in the carriages due to problems such as high temperature and lack of oxygen. EMUs with on-vehicle energy storage devices have a certain emergency self-propulsion ability in the state without catenary. However, due to the limitations of the installation space of the EMU and the energy density of the on-vehicle energy storage device, the battery capacity of the on-vehicle energy storage device is limited. At the same time, when the EMU is in an emergency operation state, the on-vehicle energy storage device not only needs to provide the energy required by the traction drive system, but also needs to provide the electric energy required by auxiliary systems such as lighting, ventilation, air conditioning, and oxygen generator. During the emergency self-propulsion process of the train, different energy distribution strategies will largely determine the final energy consumption result of the train and the comfort of passengers during emergency self-propulsion. An effective energy distribution strategy can improve the success rate of emergency self-propulsion on the line and ensure the safe operation of the train. Therefore, studying and determining a reasonable energy optimization scheme for train self-propulsion has important research value and engineering significance. Traditional methods for emergency self-propulsion of trains often ignore the utilization of regenerative braking energy, resulting in increased train energy consumption and decreased endurance. Summary of the Invention

[0003] Aiming at the problems in the prior art, an embodiment of the present invention provides a method and device for optimizing the energy consumption distribution of emergency self-propulsion of trains, which can at least partially solve the problems existing in the prior art.

[0004] On the one hand, the present invention proposes a method for optimizing the energy consumption distribution of emergency self-propulsion of trains, including:

[0005] Determine the working condition section of train operation, and determine the regenerative braking energy that can be utilized according to the remaining capacity of the train on-vehicle energy storage device, the maximum value of the train on-vehicle energy storage energy, the regenerative braking power in the braking section, and the power consumption of the auxiliary system; the working condition section includes a traction section and the braking section;

[0006] If it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then adjust the power consumption of the auxiliary system in the working condition section;

[0007] Recalculate the train operation energy consumption according to the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption.

[0008] Among them, determining the recoverable regenerative braking energy according to the remaining capacity of the on-train energy storage device, the maximum on-train energy storage capacity, the regenerative braking power in the braking section, and the power consumption of the auxiliary system includes:

[0009] Calculating the recoverable regenerative braking energy according to the following formula:

[0010]

[0011] Among them, F d v k η d represents the regenerative braking power in the braking section, P aux is the power consumption of the auxiliary system in the braking section, E sc is the remaining capacity of the on-train energy storage device, E sc_max is the maximum on-train energy storage capacity, F d is the braking force of the train, v k is the speed of the train at the discretized position s k when, η d is the overall vehicle electromechanical efficiency under the train braking condition, t k is the running time of the train at the discretized position s k when, P charge is the charging power of the on-train energy storage device.

[0012] Among them, adjusting the power consumption of the auxiliary system in the working condition section includes:

[0013] If it is determined that the working condition section is the traction section, then adjust the power consumption of the auxiliary system corresponding to the traction section to the first preset power threshold according to the traction force at the discretized position where the train is located;

[0014] If it is determined that the working condition section is the braking section, then adjust the power consumption of the auxiliary system corresponding to the braking section to the second preset power threshold according to the braking force at the discretized position where the train is located; the second preset power threshold is greater than the first preset power threshold.

[0015] Among them, recalculating the train running energy consumption according to the adjusted power consumption of the auxiliary system in the working condition section includes:

[0016] Taking the adjusted power consumption of the auxiliary system in the working condition section as the model variable parameter of the pre-established train running energy consumption calculation discretization model, and recalculating the train running energy consumption.

[0017] Among them, after the step of obtaining the optimized train running energy consumption, the train emergency self-propelled energy consumption distribution optimization method further includes:

[0018] Calculate the maximum length of time that the train can wait at a stop based on the optimized train operation energy consumption, the auxiliary power during train stop waiting, and the maximum value of the on-train energy storage of the train.

[0019] Among them, calculating the maximum length of time that the train can wait at a stop based on the optimized train operation energy consumption, the auxiliary power during train stop waiting, and the maximum value of the on-train energy storage of the train includes:

[0020] Subtract the optimized train operation energy consumption from the maximum value of the on-train energy storage of the train to obtain the energy consumption during train stop waiting;

[0021] Take the ratio of the energy consumption during train stop waiting to the auxiliary power during train stop waiting as the maximum length of time that the train can wait at a stop.

[0022] On the one hand, the present invention proposes a device for optimizing the energy consumption distribution of emergency self-propelled trains, including:

[0023] A determination unit, configured to determine the working condition section of the train operation, and determine the recoverable regenerative braking energy according to the remaining capacity of the on-train energy storage device of the train, the maximum value of the on-train energy storage of the train, the regenerative braking power and the auxiliary system power consumption in the braking section; the working condition section includes a traction section and the braking section;

[0024] An adjustment unit, configured to adjust the auxiliary system power consumption in the working condition section if it is determined that the regenerative braking power is greater than or equal to the auxiliary system power consumption in the braking section and there is remaining energy according to the regenerative braking energy;

[0025] An optimization unit, configured to recalculate the train operation energy consumption according to the adjusted auxiliary system power consumption in the working condition section to obtain the optimized train operation energy consumption.

[0026] On the other hand, an embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following method is implemented:

[0027] Determine the working condition section of the train operation, and determine the recoverable regenerative braking energy according to the remaining capacity of the on-train energy storage device of the train, the maximum value of the on-train energy storage of the train, the regenerative braking power and the auxiliary system power consumption in the braking section; the working condition section includes a traction section and the braking section;

[0028] If it is determined that the regenerative braking power is greater than or equal to the auxiliary system power consumption in the braking section and there is remaining energy according to the regenerative braking energy, then adjust the auxiliary system power consumption in the working condition section;

[0029] Recalculate the train operation energy consumption according to the auxiliary system power consumption of the adjusted working condition section to obtain the optimized train operation energy consumption.

[0030] An embodiment of the present invention provides a computer-readable storage medium, including:

[0031] The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following method is implemented:

[0032] Determine the working condition section of the train operation, and determine the available regenerative braking energy according to the remaining capacity of the train on-board energy storage device, the maximum value of the train on-board energy storage energy, the regenerative braking power and the auxiliary system power consumption in the braking section; the working condition section includes a traction section and the braking section;

[0033] If it is determined that the regenerative braking power is greater than or equal to the auxiliary system power consumption in the braking section, and there is remaining energy determined according to the regenerative braking energy, then adjust the auxiliary system power consumption of the working condition section;

[0034] Recalculate the train operation energy consumption according to the auxiliary system power consumption of the adjusted working condition section to obtain the optimized train operation energy consumption.

[0035] An embodiment of the present invention further provides a computer program product, the computer program product includes a computer program, and when the computer program is executed by a processor, the following method is implemented:

[0036] Determine the working condition section of the train operation, and determine the available regenerative braking energy according to the remaining capacity of the train on-board energy storage device, the maximum value of the train on-board energy storage energy, the regenerative braking power and the auxiliary system power consumption in the braking section; the working condition section includes a traction section and the braking section;

[0037] If it is determined that the regenerative braking power is greater than or equal to the auxiliary system power consumption in the braking section, and there is remaining energy determined according to the regenerative braking energy, then adjust the auxiliary system power consumption of the working condition section;

[0038] Recalculate the train operation energy consumption according to the auxiliary system power consumption of the adjusted working condition section to obtain the optimized train operation energy consumption.

[0039] The train emergency self - running energy consumption allocation optimization method and device provided by the embodiments of the present invention determine the operating condition sections of the train, and determine the recoverable regenerative braking energy according to the remaining capacity of the train on - vehicle energy storage device, the maximum value of the train on - vehicle energy storage, the regenerative braking power and the auxiliary system power consumption in the braking section; the operating condition sections include the traction section and the braking section; if it is determined that the regenerative braking power is greater than or equal to the auxiliary system power consumption in the braking section, and there is remaining energy determined according to the regenerative braking energy, then the auxiliary system power consumption in the operating condition section is adjusted; the train running energy consumption is recalculated according to the adjusted auxiliary system power consumption in the operating condition section to obtain the optimized train running energy consumption, which can improve the utilization efficiency of the train emergency self - running energy consumption. Description of the Drawings

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings. In the drawings:

[0041] Figure 1 is a flowchart of the train emergency self - running energy consumption allocation optimization method provided by an embodiment of the present invention.

[0042] Figure 2 is a flowchart of the train emergency self - running energy consumption allocation optimization method provided by another embodiment of the present invention.

[0043] Figure 3 is a flowchart of the train emergency self - running energy consumption allocation optimization method provided by another embodiment of the present invention.

[0044] Figure 4 is a schematic diagram for explaining difficult sections provided by an embodiment of the present invention.

[0045] Figure 5 is a flowchart of the train emergency self - running energy consumption allocation optimization method provided by another embodiment of the present invention.

[0046] Figure 6 is a flowchart of the train emergency self - running energy consumption allocation optimization method provided by another embodiment of the present invention.

[0047] Figure 7 is a flowchart of the train emergency self - running energy consumption allocation optimization method provided by another embodiment of the present invention.

[0048] Figure 8 is a schematic structural diagram of the train emergency self - running energy consumption allocation optimization device provided by an embodiment of the present invention.

[0049] Figure 9 Schematic diagram of the physical structure of the computer device provided by the embodiment of the present invention. Detailed implementation manners

[0050] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer and more understandable, the following further describes the embodiments of the present invention in detail with reference to the accompanying drawings. Herein, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but not to limit the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily.

[0051] To better illustrate the method of the present invention, the relevant content is described as follows:

[0052] Establish the objective function:

[0053]

[0054] Wherein, J e is the train operation energy consumption, S sta and S end respectively represent the starting position and the ending position of the train operation section, s is the train operation distance, F t is the train traction force, F d is the train braking force, η t is the overall vehicle electromechanical efficiency under the train traction condition, η d is the overall vehicle electromechanical efficiency under the train braking condition, α is the utilization rate of the regenerative braking energy, P aux is the power consumption of the auxiliary system, and T is the total operation time of the train's emergency self-propulsion.

[0055] Construct the train kinematic equation:

[0056]

[0057] Wherein: v is the train operation speed, s is the train operation distance, t is the train operation time, γ is the train rotary mass coefficient, M is the train mass, F t is the train traction force, F d is the train braking force, W0 is the basic train operation resistance, W j is the train additional resistance.

[0058] Wherein:

[0059] W0 = a + bv + cv 2 (3)

[0060] W0 = w0 × Mg × 10 -3 (4)

[0061] Among them, W0 is the basic running resistance of the train, w0 is the unit running resistance of the train, g is the acceleration due to gravity, a, b, and c are empirical coefficients selected according to the vehicle type; v is the running speed of the train.

[0062]

[0063] Among them, W j is the additional resistance of the train, θ is the value of the line gradient, c r is the curve resistance coefficient, and R is the curve radius.

[0064] Model discretization:

[0065] To solve the optimization problem, the model is discretized with the same distance Δs, which can be divided into steps, and each position can be vectorized and represented as s k , where k = 1, 2…N, then the discrete expression of the objective function can be expressed as:

[0066]

[0067] The dynamic model of the train can be written in the following discrete form:

[0068]

[0069] The regenerative braking energy flow constraint includes the following constraints:

[0070] Speed limit constraint:

[0071] For safe operation, the running speed can be less than the speed protection. The magnitude of the speed limit changes with the distance. So the speed limit when the train is at position s k is expressed as:

[0072] v min ≤v k ≤v lim,k (8)

[0073] Among them, v k is the speed of the train when it is at position s k , v min is the lower limit of the speed limit, and v lim,k is the upper limit of the speed limit when the train is at position s k .

[0074] Traction and electric braking constraints:

[0075] The traction force and electric braking force of the locomotive have the same characteristics, and they are related to the running speed. Due to the characteristics of the adhesive and the engine, the traction force is a non-linear expression of the speed. To describe this limitation, it is transformed into the following inequality constraint by the linear approximation method:

[0076] 0 ≤ F t,k ≤ min{a t1 + b t1 v k , a t2 + b t2 v k , F t,max} (9)

[0077] Among them, F t,k is the traction force of the train at position s k , a t1 is the first linear approximation coefficient of the constant torque region of the train traction force characteristic, b t1 is the second linear approximation coefficient of the constant torque region of the train traction force characteristic, a t2 is the first linear approximation coefficient of the constant power region of the train traction force characteristic, b t2 is the second linear approximation coefficient of the constant power region of the train traction force characteristic, F t,max is the rated maximum traction force of the train.

[0078] Similarly, for the electric braking force, the inequality constraint is:

[0079] F d,max ≤ F d,k ≤ min{a d1 + b d1 v k , a d2 + b d2 v k} (10)

[0080] Among them, F d,k is the braking force of the train at position s k , a d1 is the first linear approximation coefficient of the constant torque region of the train braking force characteristic, b d1 is the second linear approximation coefficient of the constant torque region of the train braking force characteristic, a d2 is the first linear approximation coefficient of the constant power region of the train braking force characteristic, b d2 is the second linear approximation coefficient of the constant power region of the train braking force characteristic, F d,max is the rated maximum braking force of the train.

[0081] In order to avoid the simultaneous existence of traction and electric braking in the optimization problem, there is:

[0082] F t,k · F d,k = 0 (11)

[0083] On-vehicle energy storage capacity power constraint:

[0084]

[0085] Among them, P discharge is the discharge power of the vehicle-mounted energy storage system, P tr is the wheel circumference power of the train, P aux is the power consumption of the auxiliary system, η loss is the power loss of the power supply system, P discharge_max is the maximum discharge power of the vehicle-mounted energy storage system, E sc_max is the maximum capacity of the train's vehicle-mounted energy storage device, E wait is the energy consumption of the train during parking and waiting.

[0086] Therefore, due to the above vehicle capacity power constraints, which will restrict the train's traction and braking performance, the following formula can be obtained:

[0087]

[0088] Among them, C T is the output force that can be provided in the constant torque region of the traction characteristic, P rate is the rated maximum traction power of the train.

[0089] Energy consumption constraint for regenerative braking energy:

[0090] The regenerative braking energy recovered during train braking is preferentially supplied to the energy consumption of the train's auxiliary system. When the regenerative braking power is less than the auxiliary power, the regenerative braking energy provides the energy required by the auxiliary electrical appliances. When the regenerative braking power is greater than the auxiliary power, the regenerative braking energy provides all the energy required by the auxiliary electrical appliances and the remaining energy is fed back to the vehicle-mounted energy storage device. When the vehicle-mounted energy storage device is fully charged, the remaining energy is dissipated through the braking resistor. The part used by the auxiliary electrical appliances and the part fed back to the vehicle-mounted energy storage device is the available regenerative braking energy, which can be expressed as:

[0091]

[0092] Among them, F d v k η d represents the regenerative braking power in the braking section, P aux is the power consumption of the auxiliary system in the braking section, E sc is the remaining capacity of the train's vehicle-mounted energy storage device, E sc_max is the maximum value of the train's vehicle-mounted energy storage energy, F d is the braking force of the train, v k The train is at the discretized position s k at the speed, η d is the overall vehicle electromechanical efficiency under the train braking condition, t k The train is at the discretized position s k at the train running time, P charge is the charging power of the train's vehicle-mounted energy storage device.

[0093] Auxiliary power distribution:

[0094] Based on the switching positions and condition holding times of the train traction and braking conditions under the train operation strategy, adjust the power of the auxiliary system within the holding time windows of the traction and braking conditions during the whole process of emergency running. The auxiliary power operates at a low power P1 within the traction condition time window and at a high power P2 within the braking condition time window (P2 > P1) to improve the passenger riding comfort. The formula is as follows:

[0095]

[0096] Calculation of parking waiting time:

[0097] Based on the total energy consumption of the train emergency operation obtained after power distribution, that is, the optimized train operation energy consumption J e ', the remaining battery capacity, that is, the train energy available for the parking waiting stage, can be solved, and the longest duration that the train can park and wait can be calculated and determined as follows:

[0098] E wait = E sc_max - J e '(17)

[0099] After the train makes an emergency stop, the on-board energy storage device only supplies power to the train auxiliary system. By dividing the maximum remaining energy E wait of the battery by the train parking waiting auxiliary power P0, the longest parking waiting time T0 before the train starts running can be calculated. The formula is as follows:

[0100]

[0101] Based on the above inferences, the problem is transformed into a multi-stage optimal problem and solved by dynamic programming.

[0102] Figure 1 is a schematic flow chart of the train emergency self-running energy consumption distribution optimization method provided by an embodiment of the present invention. As Figure 1 shown, the train emergency self-running energy consumption distribution optimization method provided by the embodiment of the present invention includes:

[0103] Step R1: Determine the condition sections of the train operation. Based on the remaining capacity of the train on-board energy storage device, the maximum value of the train on-board energy storage energy, the regenerative braking power in the braking section, and the power consumption of the auxiliary system, determine the available regenerative braking energy; the condition sections include the traction section and the braking section.

[0104] Step R2: If it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is surplus energy determined according to the regenerative braking energy, then adjust the power consumption of the auxiliary system in the working condition section.

[0105] Step R3: Recalculate the train operation energy consumption according to the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption.

[0106] In the above step R1, the device determines the working condition section of the train operation. According to the remaining capacity of the train on-board energy storage device, the maximum value of the train on-board energy storage energy, the regenerative braking power and the power consumption of the auxiliary system in the braking section, it determines the available regenerative braking energy; the working condition section includes the traction section and the braking section. The device can be a computer device that executes this method. In the technical solution of this application, the acquisition, storage, use, processing, etc. of data all comply with relevant regulations. The determining the available regenerative braking energy according to the remaining capacity of the train on-board energy storage device, the maximum value of the train on-board energy storage energy, the regenerative braking power and the power consumption of the auxiliary system in the braking section includes:

[0107] Calculate the available regenerative braking energy according to the following formula:

[0108]

[0109] where, F d v k η d represents the regenerative braking power in the braking section, P aux is the power consumption of the auxiliary system in the braking section, E sc is the remaining capacity of the train on-board energy storage device, E sc_max is the maximum value of the train on-board energy storage energy, F d is the train braking force, v k is the speed of the train at the discrete position s k when, η d is the overall vehicle electromechanical efficiency in the train braking condition, t k is the train operation time when the train is at the discrete position s k when, P charge is the charging power of the train on-board energy storage device.

[0110] As Figure 2 shown, the following steps can also be included before this step:

[0111] S1: Obtain train data at the moment of power failure (train weight, train rotary mass coefficient, train traction / braking characteristics, on-vehicle energy storage device characteristics, etc.), line data (ramps, curves, facilities, speed limits, tunnels, and split phases), and emergency self-propulsion related data (emergency operation target speed, emergency traction characteristics, emergency electric braking characteristics, emergency auxiliary power, regenerative braking energy utilization rate, battery output power, battery efficiency, etc.).

[0112] S2: Reduce the solution space, and determine whether the train can reach the rescue point according to the train characteristics and line conditions; if it cannot reach, record the energy consumption as 0 and jump to S7, if it can reach, then enter step S3.

[0113] As Figure 3 shown, the specific description is as follows:

[0114] S2.1: Calculate the forward and reverse running curves of the train on the specified line, and record the energy consumption and train running state parameters during the forward and reverse running processes;

[0115] S2.2: Determine whether there are characteristic difficulties (i.e., sections with capacity difficulties) according to the energy consumption during the train operation process and the train running state parameters. As Figure 3 shown, if there are difficult sections, then execute S2.3, indicating that the train cannot reach the rescue point and needs to wait for rescue in place, record the energy consumption as 0, and jump to S7; if there are no difficult sections, then execute S2.4, indicating that the train can reach, and enter step S3. The difficult sections are as Figure 4 shown.

[0116] S3: Calculate the energy-saving speed curve of the train under the condition of the auxiliary system power consumption, and the train operation sequence (operating condition sequence) and the corresponding energy consumption can also be obtained. As Figure 5 shown, the description is as follows:

[0117] S3.1: Establish the train motion model and optimization model according to equations (1)-(7).

[0118] S3.2: Use dynamic programming to solve the optimal energy-saving speed curve and operating condition sequence that meet the constraints with the minimum energy consumption as the goal according to the bundle conditions corresponding to equations (8)-(14).

[0119] S3.3: Calculate and store the actual running time and energy consumption of the train with the obtained optimal energy-saving speed curve.

[0120] S4: Determine the train operation conditions according to the train energy-saving speed curve, train operation sequence, and corresponding energy consumption obtained in step S3, and calculate the traction section, braking section, and the corresponding operating condition holding time according to the train operation conditions. That is, determine the operating condition section of the train operation.

[0121] S5: Adjust the energy consumption according to the regenerative braking energy recovery and utilization situation in the braking section. AsFigure 6 As shown below, the specific description is as follows:

[0122] S5.1: Calculate the regenerative braking energy in each braking section according to Equation (15), i.e., E eb,k .

[0123] In the above step R2, if the device determines that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section and there is remaining energy according to the regenerative braking energy, the power consumption of the auxiliary system in the working condition section is adjusted. Continuing with S5.1, the specific description is as follows:

[0124] S5.2: If it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section and there is remaining energy, then perform the subsequent step S6; otherwise, perform S5.3.

[0125] S5.3: In line with the actual regenerative braking energy usage, the train operation energy consumption remains unchanged. That is, the subsequent method steps are no longer executed.

[0126] The adjustment of the power consumption of the auxiliary system in the working condition section includes:

[0127] If it is determined that the working condition section is the traction section, then adjust the power consumption of the auxiliary system corresponding to the traction section to the first preset power threshold according to the traction force at the discretized position where the train is located;

[0128] If it is determined that the working condition section is the braking section, then adjust the power consumption of the auxiliary system corresponding to the braking section to the second preset power threshold according to the braking force at the discretized position where the train is located; the second preset power threshold is greater than the first preset power threshold. The first preset power threshold is P1, and the second preset power threshold is P2. The specific adjustment method is as shown in Equation (16).

[0129] As Figure 7 shown, the adjustment of the auxiliary power in the traction section and the braking section in S6 and the recalculation of the train energy consumption are specifically described as follows:

[0130] S6.1: Load the working condition section of the train operation.

[0131] S6.2: Determine whether this section is the traction section. If so, then execute step S6.3; otherwise, execute step S6.4.

[0132] S6.3: Adjust the auxiliary power in each traction working condition time window to P1 according to Equation (16), and execute step S6.6.

[0133] S6.4: Determine whether this section is the braking section. If so, then execute step S6.5; otherwise, execute step S6.6.

[0134] S6.5: Adjust the auxiliary power within the time window of each braking condition to P2 according to Equation (16), and execute step S6.6.

[0135] In the above step R3, the device recalculates the train operation energy consumption based on the adjusted auxiliary system power consumption of the working condition section, and obtains the optimized train operation energy consumption. The recalculating the train operation energy consumption based on the adjusted auxiliary system power consumption of the working condition section includes:

[0136] Taking the adjusted auxiliary system power consumption of the working condition section as the model variable parameter of the pre-established discretization model for calculating train operation energy consumption, and recalculating the train operation energy consumption.

[0137] As Figure 7 shown, continuing the above steps, it further includes:

[0138] S6.6: Substitute P calculated through Equation (16) aux into Equation (6) to calculate the optimized train operation energy consumption J e '.

[0139] After the step of obtaining the optimized train operation energy consumption, the train emergency self-propelled energy consumption allocation optimization method further includes:

[0140] Calculating the longest duration that the train can park and wait according to the optimized train operation energy consumption, the train parking waiting auxiliary power, and the maximum value of the train on-board energy storage.

[0141] The calculating the longest duration that the train can park and wait according to the optimized train operation energy consumption, the train parking waiting auxiliary power, and the maximum value of the train on-board energy storage includes:

[0142] Subtracting the optimized train operation energy consumption from the maximum value of the train on-board energy storage to obtain the train parking waiting energy consumption;

[0143] Taking the ratio of the train parking waiting energy consumption to the train parking waiting auxiliary power as the longest duration that the train can park and wait. The longest duration that the train can park and wait is the parking waiting time as Figure 2 shown. The specific description is as follows:

[0144] S7: Calculate the train parking waiting energy consumption E wait according to Equation (17). Calculate the longest duration T0 that the train can park and wait according to Equation (18).

[0145] S8: Output the optimization result.

[0146] The train emergency self - running energy consumption distribution optimization method provided by the embodiments of the present invention aims to address the above - mentioned deficiencies in the prior art. It provides an energy distribution method for the traction system and auxiliary system during the train operation by adding the constraint of the regenerative braking energy flow, optimizes the train operation strategy, improves the energy utilization efficiency, extends the emergency self - running distance, and accurately estimates the parking waiting time, so as to obtain an optimized train speed curve to meet the requirements of efficient and comfortable operation on the premise of the train arriving at the rescue point smoothly, and solves the deficiencies of the existing train emergency self - running energy consumption optimization methods.

[0147] The train emergency self - running energy consumption distribution optimization method provided by the embodiments of the present invention, compared with the previous operation optimization work for train emergency self - running, fully considers the utilization of regenerative braking energy during the emergency running process, realizes the optimized distribution of train energy consumption while achieving energy - saving operation of the train, thereby improving the passenger riding comfort. The present invention considers the regenerative braking energy feedback constraint and the passenger comfort index of train operation, adds the regenerative braking energy constraint to adjust the real - time energy consumption of the train auxiliary system, and designs a train emergency self - running energy consumption distribution optimization method considering regenerative braking, which improves the energy utilization efficiency, extends the emergency self - running distance, and improves the rescue success rate.

[0148] The train emergency self - running energy consumption distribution optimization method provided by the embodiments of the present invention determines the working condition sections of the train operation. According to the remaining capacity of the train on - vehicle energy storage device, the maximum value of the train on - vehicle energy storage, the regenerative braking power in the braking section, and the power consumption of the auxiliary system, it determines the available regenerative braking energy; the working condition sections include the traction section and the braking section; if it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then the power consumption of the auxiliary system in the working condition section is adjusted; the train operation energy consumption is recalculated according to the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption, which can improve the energy utilization efficiency of the train emergency self - running.

[0149] Further, the determining the available regenerative braking energy according to the remaining capacity of the train on - vehicle energy storage device, the maximum value of the train on - vehicle energy storage, the regenerative braking power in the braking section, and the power consumption of the auxiliary system includes:

[0150] The available regenerative braking energy is calculated according to the following formula:

[0151]

[0152] where F d v k η d represents the regenerative braking power in the braking section, P auxThe power consumption of the auxiliary system for the braking section, E sc The remaining capacity of the on-train energy storage device of the train, E sc_max The maximum value of the on-train energy storage energy of the train, F d The braking force of the train, v k The train is at the discretized position s k The speed at this time, η d The overall vehicle electromechanical efficiency under the braking condition of the train, t k The train is at the discretized position s k The running time of the train at this time, P charge The charging power of the on-train energy storage device of the train. It can be described with reference to the above embodiments and will not be elaborated here.

[0153] Further, the adjustment of the power consumption of the auxiliary system for the working condition section includes:

[0154] If it is determined that the working condition section is the traction section, then adjust the power consumption of the auxiliary system corresponding to the traction section to the first preset power threshold according to the traction force at the discretized position where the train is located; it can be described with reference to the above embodiments and will not be elaborated here.

[0155] If it is determined that the working condition section is the braking section, then adjust the power consumption of the auxiliary system corresponding to the braking section to the second preset power threshold according to the braking force at the discretized position where the train is located; the second preset power threshold is greater than the first preset power threshold. It can be described with reference to the above embodiments and will not be elaborated here.

[0156] Further, the recalculation of the train running energy consumption according to the adjusted power consumption of the auxiliary system for the working condition section includes:

[0157] Take the adjusted power consumption of the auxiliary system for the working condition section as the model variable parameter of the pre-established train running energy consumption calculation discretization model, and recalculate the train running energy consumption. It can be described with reference to the above embodiments and will not be elaborated here.

[0158] Further, after the step of obtaining the optimized train running energy consumption, the train emergency self-propelled energy consumption allocation optimization method further includes:

[0159] Calculate the longest duration that the train can park and wait according to the optimized train running energy consumption, the auxiliary power for train parking and waiting, and the maximum value of the on-train energy storage energy of the train. It can be described with reference to the above embodiments and will not be elaborated here.

[0160] Further, the calculation of the longest duration that the train can park and wait according to the optimized train running energy consumption, the auxiliary power for train parking and waiting, and the maximum value of the on-train energy storage energy of the train includes:

[0161] Subtract the maximum value of the on-train energy storage of the train from the optimized train operation energy consumption to obtain the train parking waiting energy consumption. For details, reference can be made to the above embodiments and will not be elaborated here.

[0162] Take the ratio of the train parking waiting energy consumption to the auxiliary power during train parking waiting as the maximum allowable parking waiting duration of the train. For details, reference can be made to the above embodiments and will not be elaborated here.

[0163] Figure 8 It is a schematic structural diagram of a train emergency self-propelled energy consumption allocation optimization device provided by an embodiment of the present invention. As Figure 8 shown, the train emergency self-propelled energy consumption allocation optimization device provided by the embodiment of the present invention includes a determination unit 801, an adjustment unit 802, and an optimization unit 803, where:

[0164] The determination unit 801 is configured to determine the working condition section of the train operation, and determine the available regenerative braking energy according to the remaining capacity of the on-train energy storage device of the train, the maximum value of the on-train energy storage of the train, the regenerative braking power and the auxiliary system power consumption in the braking section; the working condition section includes a traction section and the braking section; the adjustment unit 802 is configured to adjust the auxiliary system power consumption in the working condition section if it is determined that the regenerative braking power is greater than or equal to the auxiliary system power consumption in the braking section and there is remaining energy according to the regenerative braking energy; the optimization unit 803 is configured to recalculate the train operation energy consumption according to the adjusted auxiliary system power consumption in the working condition section to obtain the optimized train operation energy consumption.

[0165] Specifically, the determination unit 801 in the device is configured to determine the working condition section of the train operation, and determine the available regenerative braking energy according to the remaining capacity of the on-train energy storage device of the train, the maximum value of the on-train energy storage of the train, the regenerative braking power and the auxiliary system power consumption in the braking section; the working condition section includes a traction section and the braking section; the adjustment unit 802 is configured to adjust the auxiliary system power consumption in the working condition section if it is determined that the regenerative braking power is greater than or equal to the auxiliary system power consumption in the braking section and there is remaining energy according to the regenerative braking energy; the optimization unit 803 is configured to recalculate the train operation energy consumption according to the adjusted auxiliary system power consumption in the working condition section to obtain the optimized train operation energy consumption.

[0166] The train emergency self - running energy consumption allocation optimization device provided by the embodiment of the present invention determines the working condition section of the train operation, and determines the recoverable regenerative braking energy according to the remaining capacity of the train on - vehicle energy storage device, the maximum value of the train on - vehicle energy storage energy, the regenerative braking power in the braking section and the power consumption of the auxiliary system; the working condition section includes the traction section and the braking section; if it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then the power consumption of the auxiliary system in the working condition section is adjusted; the train operation energy consumption is recalculated according to the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption, which can improve the utilization efficiency of the train emergency self - running energy consumption.

[0167] The embodiment of the train emergency self - running energy consumption allocation optimization device provided by the embodiment of the present invention can be specifically used to execute the processing flow of the above - mentioned method embodiments, and its functions will not be elaborated here, and reference can be made to the detailed description of the above - mentioned method embodiments.

[0168] Figure 9 It is a schematic diagram of the physical structure of the computer device provided by the embodiment of the present invention. As Figure 9 shown, the computer device includes: a memory 901, a processor 902, and a computer program stored on the memory 901 and executable on the processor 902. When the processor 902 executes the computer program, the following method is implemented:

[0169] Determine the working condition section of the train operation, and determine the recoverable regenerative braking energy according to the remaining capacity of the train on - vehicle energy storage device, the maximum value of the train on - vehicle energy storage energy, the regenerative braking power in the braking section and the power consumption of the auxiliary system; the working condition section includes the traction section and the braking section;

[0170] If it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then the power consumption of the auxiliary system in the working condition section is adjusted;

[0171] Recalculate the train operation energy consumption according to the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption.

[0172] This embodiment discloses a computer program product, which includes a computer program. When the computer program is executed by a processor, the following method is implemented:

[0173] Determine the working condition section of the train operation, and determine the recoverable regenerative braking energy according to the remaining capacity of the train on - vehicle energy storage device, the maximum value of the train on - vehicle energy storage energy, the regenerative braking power in the braking section and the power consumption of the auxiliary system; the working condition section includes the traction section and the braking section;

[0174] If it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then adjust the power consumption of the auxiliary system in the working condition section;

[0175] Recalculate the train operation energy consumption based on the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption.

[0176] This embodiment provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the following method is implemented:

[0177] Determine the working condition section of the train operation, and determine the available regenerative braking energy according to the remaining capacity of the train on-board energy storage device, the maximum value of the train on-board energy storage energy, and the regenerative braking power and the power consumption of the auxiliary system in the braking section; the working condition section includes the traction section and the braking section;

[0178] If it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then adjust the power consumption of the auxiliary system in the working condition section;

[0179] Recalculate the train operation energy consumption based on the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption.

[0180] Compared with the technical solutions in the prior art, the train emergency self-propelled energy consumption allocation optimization method provided by this embodiment of the present invention determines the working condition section of the train operation, determines the available regenerative braking energy according to the remaining capacity of the train on-board energy storage device, the maximum value of the train on-board energy storage energy, and the regenerative braking power and the power consumption of the auxiliary system in the braking section; the working condition section includes the traction section and the braking section; if it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then adjust the power consumption of the auxiliary system in the working condition section; recalculate the train operation energy consumption based on the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption, which can improve the utilization efficiency of the train emergency self-propelled energy consumption.

[0181] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0182] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or the combination of flows and / or blocks.

[0183] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or the combination of flows and / or blocks.

[0184] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or the combination of flows and / or blocks.

[0185] In the description of this specification, the descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0186] The specific embodiments described above further elaborate on the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. An optimization method for the energy consumption distribution of a train's emergency self-propulsion, characterized in that, Including: Determine the working condition section of train operation, and determine the available regenerative braking energy according to the remaining capacity of the train's on-vehicle energy storage device, the maximum value of the train's on-vehicle stored energy, the regenerative braking power in the braking section, and the power consumption of the auxiliary system; the working condition section includes a traction section and the braking section; If it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy, then adjust the power consumption of the auxiliary system in the working condition section; Recalculate the train operation energy consumption according to the adjusted power consumption of the auxiliary system in the working condition section to obtain the optimized train operation energy consumption.

2. The train emergency self-propelled energy consumption allocation optimization method according to claim 1, characterized in that The determining the available regenerative braking energy according to the remaining capacity of the train's on-vehicle energy storage device, the maximum value of the train's on-vehicle stored energy, the regenerative braking power in the braking section, and the power consumption of the auxiliary system includes: Calculate the available regenerative braking energy according to the following formula: Among them, F d v k η d represents the regenerative braking power of the braking section, P aux is the power consumption of the auxiliary system in the braking section, E sc is the remaining capacity of the on-train energy storage device of the train, E sc_max is the maximum value of the on-train energy storage energy of the train, F d is the braking force of the train, v k The train is at the discretized position s k The speed at this time, v d is the overall vehicle electromechanical efficiency under the braking condition of the train, t k The train is at the discretized position s k The running time of the train at this time, P charge is the charging power of the on-train energy storage device of the train.

3. The optimized method for energy consumption distribution of train emergency self-propulsion according to claim 1, characterized in that The adjusting the power consumption of the auxiliary system in the working condition section includes: If it is determined that the working condition section is the traction section, then adjust the power consumption of the auxiliary system corresponding to the traction section to a first preset power threshold according to the traction force at the discretized position where the train is located; If it is determined that the working condition section is the braking section, then adjust the power consumption of the auxiliary system corresponding to the braking section to a second preset power threshold according to the braking force at the discretized position where the train is located; the second preset power threshold is greater than the first preset power threshold.

4. The emergency self-propelled energy consumption allocation optimization method for trains according to claim 1, wherein The recalculating the train operation energy consumption according to the adjusted power consumption of the auxiliary system in the working condition section includes: Use the adjusted power consumption of the auxiliary system in the working condition section as the model variable parameter of the pre-established train operation energy consumption calculation discretization model, and recalculate the train operation energy consumption.

5. The train emergency self-propelled energy consumption allocation optimization method according to any one of claims 1 to 4, characterized in that, After the step of obtaining the optimized train operation energy consumption, the train emergency self-propelled energy consumption allocation optimization method further includes: Calculate the longest duration that the train can park and wait according to the optimized train operation energy consumption, the train parking waiting auxiliary power, and the maximum value of the train's on-vehicle stored energy.

6. The train emergency self-propelled energy consumption allocation optimization method according to claim 5, characterized in that The calculating the longest duration that the train can park and wait according to the optimized train operation energy consumption, the train parking waiting auxiliary power, and the maximum value of the train's on-vehicle stored energy includes: Subtract the optimized train operation energy consumption from the maximum value of the train's on-vehicle stored energy to obtain the train parking waiting energy consumption; Use the ratio of the train parking waiting energy consumption to the train parking waiting auxiliary power as the longest duration that the train can park and wait.

7. An energy consumption distribution optimization device for emergency self-propelled trains, characterized in that, Including: A determining unit for determining the working condition section of train operation, and determining the available regenerative braking energy according to the remaining capacity of the train's on-vehicle energy storage device, the maximum value of the train's on-vehicle stored energy, the regenerative braking power in the braking section, and the power consumption of the auxiliary system; the working condition section includes a traction section and the braking section; An adjusting unit for adjusting the power consumption of the auxiliary system in the working condition section if it is determined that the regenerative braking power is greater than or equal to the power consumption of the auxiliary system in the braking section, and there is remaining energy determined according to the regenerative braking energy; An optimization unit is configured to recalculate the train operation energy consumption according to the auxiliary system power consumption in the adjusted operating condition section, so as to obtain the optimized train operation energy consumption.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that, The computer program product includes a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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