Efficiency-increasing and energy-saving control method and device for train

Abstract

The invention provides an efficiency-increasing and energy-saving control method and device for a train, and the method comprises the steps: responding to an operation instruction, and obtaining the running state of the train, the demand level of the whole train and the efficiency parameter of a traction system; the operation state comprises an operation speed and an operation condition; selecting a target optimization model corresponding to the operation condition from preset optimization models; constructing a constraint model by combining the number of power units of the train based on the demand level of the whole train; performing torque optimal distribution calculation by taking the optimization of the target optimization model as a target and combining the constraint model, the whole vehicle demand level, the operation speed and the traction system efficiency parameter to obtain an optimal distribution result; and controlling a power unit of the train, and outputting a corresponding torque according to an optimal distribution result. On the premise that the whole vehicle torque requirement is met, optimization is carried out with the optimal efficiency as the target based on traction system efficiency parameters, torque optimization distribution is carried out on all power units, the whole vehicle operation efficiency is improved, and energy conservation and consumption reduction of a train are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of train efficiency and energy saving technology, and in particular to a train efficiency and energy saving control method and device. BACKGROUND

[0002] In recent years, with the vigorous development of rail transit vehicles, intelligent rail trains and the like in China, trains are moving towards a more green and efficient direction. Train power has developed from centralized driving of the vehicle head to common driving of multiple power units, with significantly enhanced power, and modular design improving the redundancy and reliability of the train.

[0003] In the traditional method, the energy saving control of the train is focused on the research of ATO (Automatic Train Operation) train automatic control, and the running time and running speed of the train are dynamically planned by weighting combination of safety, punctuality and energy saving rate and the like, and each power unit module adopts fixed proportion torque distribution.

[0004] Due to the nonlinear relationship between the traction system efficiency and the motor torque and speed, at the same speed, the efficiency of the traction system will be different due to factors such as motor efficiency map when different torque distributions. The traditional fixed proportion torque distribution method cannot make the whole vehicle obtain the optimal traction efficiency. SUMMARY

[0005] The present application provides a train efficiency and energy saving control method and device for obtaining an optimal torque optimization distribution strategy in the premise of meeting the torque demand of the whole vehicle, so as to realize energy saving and consumption reduction of the train.

[0006] In a first aspect, the present application provides a train efficiency and energy saving control method, comprising: In response to an operation instruction, obtaining the running state, the whole vehicle demand level and the traction system efficiency parameter of the train; the running state includes running speed and running condition; From a preset optimization model, selecting a target optimization model corresponding to the running condition; Based on the whole vehicle demand level, combining the number of power units of the train, a constraint model is constructed; Taking the optimal target optimization model as the target, combining the constraint model, the whole vehicle demand level, the running speed and the traction system efficiency parameter, torque optimization distribution calculation is performed to obtain an optimization distribution result; Controlling the power unit of the train to output corresponding torque according to the optimization distribution result.

[0007] Optionally, the operating conditions include: a traction condition and a regenerative braking condition; the optimization model includes: a traction condition optimization model and a regenerative braking condition optimization model; and selecting, from preset optimization models, a target optimization model corresponding to the operating condition includes: if the operating condition is the traction condition, selecting the traction condition optimization model as the target optimization model; if the operating condition is the regenerative braking condition, selecting the regenerative braking condition optimization model as the target optimization model.

[0008] Optionally, the traction condition optimization model is: ; or ; the regenerative braking condition optimization model is: ; or ; the constraint model is: ; wherein, is the motor active power, is the traction loss power, is a proportional coefficient, is the i-th power unit, is the gear position allocated to the i-th power unit, is the shaft end speed of the power unit output shaft, is the transmission ratio, is the gear box transmission efficiency of the i-th power unit when the speed and torque are is the four-quadrant rectifier efficiency of the i-th power unit when the speed and torque are for a direct current power supply system, there is no four-quadrant rectifier link, so the conversion efficiency is 1.0; for an alternating current power supply system, according to the number of multiple four-quadrant operations, different phase angles are used for carrier phase shift control, is the motor efficiency of the i-th power unit when the speed and torque are is the number of power units, is the motor feedback power, is the braking loss power, is the vehicle gear position.

[0009] ​​​​​​​Optionally, the target optimization model is optimized, combined with the constraint model, the vehicle demand gear, the running speed and the traction system efficiency parameter, torque optimization distribution calculation is performed, and an optimization distribution result is obtained, including: The target optimization model is optimized, combined with the constraint model, the vehicle demand gear, the running speed and the traction system efficiency parameter, online optimization is performed, and a plurality of gear distribution results are obtained. From all the gear distribution results, the gear distribution result with the optimal efficiency is selected as the optimization distribution result.

[0010] Optionally, the target optimization model is optimized, combined with the constraint model, the vehicle demand gear, the running speed and the traction system efficiency parameter, torque optimization distribution calculation is performed, and an optimization distribution result is obtained, including: The target optimization model is optimized, combined with the constraint model and the traction system efficiency parameter, offline calculation is performed, and a mapping relationship between vehicle speed, vehicle gear and power unit gear is established. According to the train speed, the corresponding real-time vehicle speed is calculated, and combined with the vehicle demand gear, the gear distribution result with the optimal efficiency is determined from the mapping relationship as the optimization distribution result.

[0011] Optionally, the target optimization model is optimized, combined with the constraint model, the vehicle demand gear, the running speed and the traction system efficiency parameter, torque optimization distribution calculation is performed, and an optimization distribution result is obtained, including: According to the constraint model and the vehicle gear demand, the minimum number of power units meeting the vehicle gear demand is confirmed; The vehicle gear demand is evenly distributed according to the minimum number of power units, and the optimization distribution result is obtained.

[0012] Optionally, after the step of controlling the power unit of the train to output corresponding torque according to the optimization distribution result, the method further includes: The power unit with torque distribution of 0 adopts weak magnetic standby and / or shutdown mode to reduce standby power consumption.

[0013] Optionally, the power unit with torque distribution of 0 adopts weak magnetic standby and / or shutdown mode to reduce standby power consumption, including: When there is the power unit with torque distribution of 0, it is judged whether the number of the power unit with torque distribution of 0 is greater than 1 group; If not, the power unit is maintained in weak magnetic standby; If yes, at least one group of the power unit is maintained in weak magnetic standby, and the other power units are shut down.

[0014] Secondly, the present invention provides a train efficiency-enhancing and energy-saving control device, comprising: The response module is used to respond to operation commands and acquire the train's operating status, overall vehicle demand level, and traction system efficiency parameters; the operating status includes operating speed and operating conditions. The optimization model selection module is used to select the target optimization model corresponding to the operating condition from the preset optimization models; The constraint model construction module is used to construct a constraint model based on the overall vehicle demand level and the number of power units of the train. The allocation result determination module is used to perform torque optimization allocation calculation with the target optimization model as the objective, combined with the constraint model, the vehicle demand level, the operating speed and the traction system efficiency parameters, to obtain the optimized allocation result; The output module is used to control the power unit of the train and output the corresponding torque according to the optimized allocation result.

[0015] Optionally, the operating conditions include: traction conditions and regenerative braking conditions; the optimization model includes: a traction condition optimization model and a regenerative braking condition optimization model; the optimization model selection module includes: The first selection submodule is used to select the traction condition optimization model as the target optimization model if the operating condition is the traction condition. The second selection submodule is used to select the regenerative braking condition optimization model as the target optimization model if the operating condition is the regenerative braking condition.

[0016] Optionally, the traction condition optimization model is: ; or ; The optimization model for regenerative braking is as follows: ; or ; The constraint model is as follows: ; in, The active power of the motor. For traction power loss, This is the proportionality coefficient. For the first One power unit, To be allocated to the The level of each power unit The output shaft speed of the power unit is the shaft end speed. The transmission ratio is... For the first Each power unit operates at a speed and torque of Gearbox transmission efficiency at that time For the first Each power unit operates at a speed and torque of The efficiency of the four-quadrant rectifier is calculated as follows: For DC power supply systems, which do not have a four-quadrant rectifier stage, the conversion efficiency is taken as 1.0. For AC power supply systems, different phase shift angles are used for carrier phase shift control based on the number of multiple four-quadrant rectifiers operating. For the first Each power unit operates at a speed and torque of Motor efficiency at that time For the number of power units, For motor feedback power, For braking power loss, This is at the vehicle level.

[0017] Optionally, the allocation result determination module includes: The online optimization submodule is used to perform online optimization with the target optimization model as the goal, combined with the constraint model, the vehicle demand level, the operating speed and the traction system efficiency parameters, to obtain multiple level allocation results. The first allocation result determination submodule is used to select the most efficient allocation result from all the allocation results as the optimized allocation result.

[0018] Optionally, the allocation result determination module includes: The mapping relationship determination submodule is used to establish the mapping relationship between vehicle speed, vehicle level and power unit level by taking the optimization model as the target as the goal, combining the constraint model and the traction system efficiency parameters for offline calculation; The second allocation result determination submodule is used to calculate the corresponding real-time vehicle rotation speed based on the train speed, and combine it with the overall vehicle demand level to determine the most efficient level allocation result from the mapping relationship as the optimized allocation result.

[0019] Optionally, with the optimization of the target model as the objective, and in conjunction with the constraint model, the vehicle demand level, and the operating speed, torque optimization allocation calculation is performed to obtain the optimized allocation result, including: The minimum number of power units determination submodule is used to determine the minimum number of power units that meet the vehicle level requirements based on the constraint model and the vehicle level requirements. The allocation submodule is used to evenly distribute the vehicle-level requirements with the minimum number of power units to obtain the optimized allocation result.

[0020] Optionally, further comprising: An energy consumption control module is configured to adopt a weak magnetic standby and / or shutdown mode for the power unit with torque allocation of 0, so as to reduce standby energy consumption.

[0021] Optionally, the energy consumption control module comprises: A judgment sub-module is configured to judge whether the number of the power units with torque allocation of 0 is greater than one group when the power unit with torque allocation of 0 exists; if not, the power unit is maintained in a weak magnetic standby mode; if yes, at least one group of the power units is maintained in a weak magnetic standby mode, and other power units are shut down.

[0022] In a third aspect, the present application provides an electronic device comprising a processor and a memory, wherein the memory stores computer readable instructions, and when the computer readable instructions are executed by the processor, the steps in the method provided in the first aspect are executed.

[0023] In a fourth aspect, the present application provides a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the method provided in the first aspect are executed.

[0024] In a fifth aspect, the present application provides a computer program product comprising a computer program, and when the computer program is executed by a processor, the steps in the method provided in the first aspect are executed.

[0025] From the above technical solutions, the present application has the following advantages: The present application provides a train efficiency and energy saving control method and device, which comprises the following steps: in response to an operation instruction, obtaining the running state, the whole vehicle demand level and the traction system efficiency parameter of a train; the running state comprises running speed and running condition; selecting a target optimization model corresponding to the running condition from a preset optimization model; constructing a constraint model based on the whole vehicle demand level and in combination with the number of power units of the train; taking the optimal target optimization model as the target, combining the constraint model, the whole vehicle demand level, the running speed and the traction system efficiency parameter, performing torque optimization distribution calculation to obtain an optimization distribution result; and controlling the power unit of the train to output corresponding torque according to the optimization distribution result. Under the premise of meeting the whole vehicle torque demand, the efficiency optimal target is sought based on the traction system efficiency parameter, the torque of each power unit is optimized and distributed, the whole vehicle running efficiency is improved, and the energy saving and consumption reduction of the train are realized. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0027] Figure 1 A flow chart of a train energy-saving control method according to an embodiment of the present application; Figure 2 A flow chart of a train energy-saving control method according to an embodiment of the present application; Figure 3 A central control unit structure diagram of a train energy-saving control method according to an embodiment of the present application; Figure 4 A structure block diagram of a train energy-saving control device according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiments of the present application provide a train energy-saving control method and device, which is used to obtain an optimal torque distribution strategy under the premise of meeting the torque demand of the whole train, so as to realize energy saving and consumption reduction of the train.

[0029] In order to make the objectives, features and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the following described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0030] Embodiment one Please refer to Figure 1 , Figure 1 A flow chart of a train energy-saving control method according to an embodiment of the present application, the method comprises: Step S101, in response to an operation instruction, obtaining a running state of a train, a whole vehicle demand level and a traction system efficiency parameter; the running state comprises a running speed and a running condition; In the embodiments of the present application, the running state covers the running speed and the running condition, and the running condition comprises a traction condition and a regenerative braking condition. The traction system efficiency parameter comprises efficiency map diagrams of a motor, a transmission mechanism and the like, and reflects the efficiency characteristics under different conditions.

[0031] Step S102, selecting a target optimization model corresponding to the running condition from a preset optimization model; In the embodiment of the present application, according to the running condition information obtained in step S101, a corresponding target optimization model is selected from a pre-set optimization model library. For example, if the running condition is acceleration traction, an optimization model suitable for the acceleration traction condition is selected.

[0032] In step S103, a constraint model is constructed based on the vehicle demand level and the number of power units of the train. In the embodiment of the present application, the torque output range of the power unit is specified by the constraint model, and within the maximum capacity range of the motor, the power unit is prevented from being overloaded or insufficiently output. At the same time, the coordinated work between the power units is also considered to ensure the load balancing of each power unit, thereby improving the reliability and stability of the train.

[0033] In step S104, a torque optimization distribution calculation is performed to obtain an optimization distribution result, with the target optimization model optimization as the target, in combination with the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameters. In the embodiment of the present application, the target optimization model selected in step S102 is optimized as the target, and a mathematical optimization algorithm is used to calculate, in combination with the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameters, to find the solution that optimizes the target optimization model, thereby obtaining the optimization distribution result.

[0034] In step S105, the power unit of the train is controlled to output corresponding torque according to the optimization distribution result.

[0035] In the embodiment of the present application, a control instruction is generated according to the optimization distribution result obtained in step S104. After receiving the instruction, the controller of the power unit adjusts the working state of the power unit and outputs corresponding torque. At the same time, the power unit feeds back the actual output torque information to the control system of the train, so that the control system can monitor the running condition of the power unit in real time and ensure that the torque output meets the optimization distribution result.

[0036] This invention provides a train efficiency-enhancing and energy-saving control method, comprising: responding to an operation command to acquire the train's operating status, overall vehicle demand level, and traction system efficiency parameters; the operating status includes operating speed and operating condition; selecting a target optimization model corresponding to the operating condition from a preset optimization model; constructing a constraint model based on the overall vehicle demand level and the number of power units in the train; performing torque optimization allocation calculation with the target optimization model as the objective, combined with the constraint model, the overall vehicle demand level, the operating speed, and the traction system efficiency parameters, to obtain an optimization allocation result; and controlling the train's power units to output corresponding torque according to the optimization allocation result. Under the premise of meeting the overall vehicle torque demand, based on the traction system efficiency parameters, optimization is performed with the goal of optimal efficiency, and torque optimization allocation is performed on each power unit to improve the overall vehicle operating efficiency and achieve energy saving and consumption reduction for the train.

[0037] Example 2 Please see Figure 2 , Figure 2 This is a flowchart illustrating a second embodiment of the train efficiency-enhancing and energy-saving control method of the present invention. The steps include: Step S201: In response to the operation command, obtain the train's operating status, overall vehicle demand level, and traction system efficiency parameters; the operating status includes operating speed and operating conditions; the operating conditions include traction conditions and regenerative braking conditions. In this embodiment, the train's operating speed is measured using a speed sensor based on principles such as electromagnetic induction. The operating condition is determined in response to the train driver's instructions by monitoring the status of the train's traction and braking systems. For example, the direction of the motor current and the action of the braking device are used to determine whether it is a traction condition or a regenerative braking condition. The traction system efficiency parameters are stored in the train's database. These parameters are obtained through extensive experiments and tests during the train design and commissioning phases.

[0038] In practice, the overall vehicle demand level is determined by the driver's operating instructions, and it is the demand level for the overall traction or braking strength of the train.

[0039] Step S202: Select the target optimization model corresponding to the operating condition from the preset optimization models; the optimization models include: traction condition optimization model and regenerative braking condition optimization model; Traditional torque distribution methods are The first power unit adopts a proportional torque distribution, the second... The torque and stage of each power unit are as follows: , .

[0040] The embodiments of this application optimize torque allocation based on efficiency. For traction conditions, optimal efficiency means minimizing the motor's active power or traction power loss, thus achieving... The maximum traction condition optimization model is as follows: ; or ; For regenerative braking, optimal efficiency means inputting the same torque and speed to the traction system, i.e., inputting the same mechanical power. This allows the motor to regenerate power. To achieve maximum efficiency, or minimum braking power loss, the following parameters are used: The maximum regenerative braking condition optimization model is as follows: ; or ; in, The active power of the motor. For traction power loss, This is the proportionality coefficient. For the first One power unit, To be allocated to the The level of each power unit The output shaft speed of the power unit is the shaft end speed. The transmission ratio is... For the first Each power unit operates at a speed and torque of Gearbox transmission efficiency at that time For the first Each power unit operates at a speed and torque of The efficiency of a four-quadrant rectifier is calculated as follows: For DC power supply systems, where there is no four-quadrant rectifier stage, the conversion efficiency is taken as 1.0; for AC power supply systems, depending on the number of multiple four-quadrant rectifiers operating, different phase shift angles are used for carrier phase shift control to reduce grid-side harmonics, thereby reducing harmonic losses and switching losses, and improving efficiency. For the first Each power unit operates at a speed and torque of Motor efficiency at that time For the number of power units, For motor feedback power, This refers to the power loss during braking.

[0041] Step S203: Based on the overall vehicle demand level and the number of power units of the train, construct a constraint model; The constraint model is as follows: ; wherein, is the vehicle level.

[0042] In the embodiments of the present application, it is assumed that the vehicle has power units, the level of the vehicle and the torque demand are , , , the level and torque allocated to the i-th power unit, , the value of i is 1~N, , since the level and torque are in a linear relationship, the proportional coefficient is taken as , , ., Step S204, taking the target optimization model optimal as the target, combining the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameter, torque optimization distribution calculation is carried out to obtain the optimization distribution result; The traditional torque distribution method is to adopt equal proportion torque average distribution for power units, the torque of the i-th power unit and the level are respectively: , , And the torque optimization distribution of the present application is carried out with efficiency as the optimal. For the traction working condition, the significance of efficiency optimization is to make the motor active power minimum, so as to realize In an optional embodiment, taking the target optimization model optimal as the target, combining the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameter, online optimization is carried out to obtain multiple level distribution results; From all the level distribution results, the level distribution result with the optimal efficiency is selected as the optimization distribution result.

[0043] In an optional embodiment, taking the target optimization model optimal as the target, combining the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameter, torque optimization distribution calculation is carried out to obtain the optimization distribution result, including: Taking the target optimization model optimal as the target, combining the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameter, online optimization is carried out to obtain multiple level distribution results; From all the level distribution results, the level distribution result with the optimal efficiency is selected as the optimization distribution result.

[0044] ​In an optional embodiment, the target optimization model is optimized, the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameter are combined, torque optimization distribution calculation is performed, and an optimization distribution result is obtained, including: The target optimization model is optimized, the constraint model and the traction system efficiency parameter are combined, offline calculation is performed, and a mapping relationship between the vehicle speed, the vehicle level and the power unit level is established. According to the train speed, the corresponding real-time vehicle speed is calculated, and the optimization distribution result is determined as the most efficient level distribution result from the mapping relationship in combination with the vehicle demand level.

[0045] In an optional embodiment, the target optimization model is optimized, the constraint model, the vehicle demand level, the running speed and the traction system efficiency parameter are combined, torque optimization distribution calculation is performed, and an optimization distribution result is obtained, including: According to the constraint model and the vehicle level demand, the minimum number of power units that meet the vehicle level demand is determined; The vehicle level demand is evenly distributed according to the minimum number of power units, and the optimization distribution result is obtained.

[0046] In the application embodiment, torque optimization distribution calculation can be performed in the following three ways to obtain the optimization distribution result, respectively: (1) Online optimization method: Real-time train running state and vehicle demand level are used to calculate torque distribution by using optimization algorithm to obtain the most efficient level distribution result. This method can adapt to real-time changes in the train running process, including changes in the number of power units due to reorganization or failure.

[0047] (2) Offline optimization method: When the computing resources are tight, offline optimization calculation can be used. One method is to obtain the optimal level distribution table of the vehicle speed and the vehicle level demand, and then use linear interpolation method to obtain real-time level distribution; another method is to fit the optimal level distribution and the relationship between the vehicle speed and the vehicle level demand, and then obtain real-time level distribution.

[0048] (3) Simplified distribution method: According to the torque optimization distribution characteristics, a similar simplified distribution method is used, that is, the total level demand is evenly distributed by the minimum number of power units. For example, for a system of 1 / power unit, the total level demand is reduced by 1 / power unit is put into operation, and the remaining power unit is evenly distributed.

[0049] Step S205, controlling the power unit of the train to output corresponding torque according to the optimal allocation result.

[0050] In the embodiment of the present application, according to the optimal allocation result, the whole vehicle system sends control instructions to each power unit, so that it outputs torque allocated to it, thereby realizing efficient operation of the train traction system. For the power unit whose torque allocation is zero, the combination of field weakening standby and shutdown is adopted, which can reduce standby loss and maintain the ability to respond to torque demand in time.

[0051] The composition structure diagram of the whole vehicle system is shown in Figure 3 CCU1 and CCU2 are central control units (Central Control Uint), and TCU1-TCU N are traction control units (Traction Control Uint). The central control unit is used for train-level control and communication, and is usually arranged in the two head cars of the vehicle, receives the operation instructions of the driver, and displays the working state of each vehicle-mounted subsystem. The traction control unit is a vehicle-level power control unit, which receives the traction braking instructions and gear size from the CCU, and feeds back the actual working state information.

[0052] Step S206, for the power unit whose torque allocation is 0, the field weakening standby and / or shutdown mode is adopted to reduce standby power consumption.

[0053] Specifically, when there is a power unit whose torque allocation is 0, it is judged whether the number of the power unit whose torque allocation is 0 is greater than 1 group; if not, the power unit is maintained in field weakening standby; if yes, at least one group of the power unit is maintained in field weakening standby, and the other power units are shut down.

[0054] The train efficiency control method provided by the embodiment of the present application comprises: in response to an operation instruction, obtaining the running state, the whole vehicle demand gear position and the traction system efficiency parameter of a train; the running state comprises running speed and running working condition; from a preset optimization model, selecting a target optimization model corresponding to the running working condition; based on the whole vehicle demand gear position, combining the number of power units of the train, constructing a constraint model; taking the optimization of the target optimization model as the target, combining the constraint model, the whole vehicle demand gear position, the running speed and the traction system efficiency parameter, performing torque optimization allocation calculation through one of online optimization or offline optimization or simplified allocation mode, to obtain an optimal allocation result; controlling the power unit of the train to output corresponding torque according to the optimal allocation result. Under the premise of meeting the whole vehicle torque demand, based on the traction system efficiency parameter, taking the efficiency optimization as the target to perform optimization, the torque of each power unit is optimized and allocated, so as to improve the running efficiency of the whole vehicle and realize the energy saving and consumption reduction of the train.

[0055] Embodiment three Please refer to Figure 4 , Figure 4 A structural block diagram of an embodiment of a train synergistic energy-saving control device of the present application is shown in FIG. 1. The device comprises: A response module 301, configured to obtain the running state, the whole-vehicle demand level, and the traction system efficiency parameter of the train in response to an operation instruction; the running state comprises the running speed and the running condition; An optimization model selection module 302, configured to select the target optimization model corresponding to the running condition from the preset optimization models; A constraint model construction module 303, configured to construct the constraint model based on the whole-vehicle demand level and in combination with the number of power units of the train; An allocation result determination module 304, configured to perform torque optimization allocation calculation in combination with the constraint model, the whole-vehicle demand level, the running speed, and the traction system efficiency parameter, with the target optimization model optimization as the target, to obtain the optimization allocation result; An output module 305, configured to control the power units of the train to output corresponding torque according to the optimization allocation result.

[0056] In an optional embodiment, the running condition comprises the traction condition and the regenerative braking condition; the optimization model comprises the traction condition optimization model and the regenerative braking condition optimization model; and the optimization model selection module 302 comprises: A first selection sub-module, configured to select the traction condition optimization model as the target optimization model if the running condition is the traction condition; A second selection sub-module, configured to select the regenerative braking condition optimization model as the target optimization model if the running condition is the regenerative braking condition.

[0057] In an optional embodiment, the traction condition optimization model is: ; or ; The regenerative braking condition optimization model is: ; or ; The constraint model is: ; wherein, is the active power of the motor, is the traction loss power, is the proportional coefficient, is the i-th a power unit, a gear position allocated to the a power unit, a rotational speed of a shaft end of a power unit output shaft, a transmission ratio, a gear position allocated to the a gear box transmission efficiency of the power unit when the rotational speed and the torque are a gear position allocated to the power unit when the rotational speed and the torque are a four-quadrant rectifier efficiency of the power unit when the rotational speed and the torque are power unit when the rotational speed and the torque are a motor efficiency of the a number of power units, a motor feedback power, a braking loss power, a vehicle gear position.

[0058] In an optional embodiment, the allocation result determination module 304 comprises: an online optimization sub-module, configured to perform online optimization in combination with the constraint model, the vehicle demand gear position, the running speed and the traction system efficiency parameter, to obtain a plurality of gear position allocation results, with the target optimization model optimum as a target; a first allocation result determination sub-module, configured to select the gear position allocation result with the optimal efficiency from all the gear position allocation results as the optimal allocation result.

[0059] In an optional embodiment, the allocation result determination module 304 comprises: a mapping relationship determination sub-module, configured to perform offline calculation in combination with the constraint model and the traction system efficiency parameter, to establish a mapping relationship among the vehicle speed, the vehicle gear position and the power unit gear position, with the target optimization model optimum as a target; a second allocation result determination sub-module, configured to calculate a corresponding real-time vehicle speed according to the train speed, and to determine the gear position allocation result with the optimal efficiency from the mapping relationship as the optimal allocation result in combination with the vehicle demand gear position.

[0060] In an optional embodiment, the allocation result determination module 304 comprises: A minimum power unit quantity determination sub-module is configured to determine a minimum power unit quantity satisfying the vehicle level gear requirement according to the constraint model and the vehicle level gear requirement; A distribution sub-module is configured to evenly distribute the vehicle level gear requirement by the minimum power unit quantity to obtain the optimal distribution result.

[0061] In an optional embodiment, the method further comprises: An energy consumption control module is configured to adopt a weak magnetic standby and / or shutdown mode for the power unit with torque distribution of 0 to reduce standby energy consumption.

[0062] In an optional embodiment, the energy consumption control module comprises: A judgment sub-module is configured to judge whether the quantity of the power unit with torque distribution of 0 is greater than one group when the power unit with torque distribution of 0 exists; if not, the power unit maintains the weak magnetic standby; if yes, at least one group of the power unit maintains the weak magnetic standby and the other power units are shut down.

[0063] Embodiment four The embodiment of the present application further provides an electronic device comprising a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to make the processor execute the steps of the train efficiency and energy saving control method of any embodiment.

[0064] Embodiment five The embodiment of the present application further provides a computer storage medium storing a computer program, and the computer program is executed by the processor to realize the steps of the train efficiency and energy saving control method of any embodiment.

[0065] Embodiment six The embodiment of the present application further provides a computer program product storing a computer program, and the computer program is executed by the processor to realize the steps of the train efficiency and energy saving control method of any embodiment.

[0066] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0067] In several embodiments provided in the present application, it should be understood that the disclosed methods, devices, electronic devices and storage media can be implemented in other ways. For example, the above-described device embodiments are only illustrative, and the division of the units is only a logical function division. In actual implementation, another division manner can be used, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0068] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place or distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0069] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0070] When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a readable storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned readable storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0071] The above-described embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalent replacements; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of synergistic energy saving control of a train, characterized by, The method comprises the following steps: in response to an operation instruction, obtaining a running state, a whole-vehicle demand level, and a traction system efficiency parameter of a train; the running state comprises a running speed and a running condition; from a preset optimization model, selecting a target optimization model corresponding to the running condition; based on the whole-vehicle demand level, combining the number of power units of the train, and constructing a constraint model; taking the optimization of the target optimization model as a target, combining the constraint model, the whole-vehicle demand level, the running speed, and the traction system efficiency parameter, performing torque optimization and distribution calculation to obtain an optimization distribution result; controlling the power units of the train to output corresponding torque according to the optimization distribution result.

2. The train synergistic energy-saving control method according to claim 1, characterized by, the running condition comprises a traction condition and a regenerative braking condition; the optimization model comprises a traction condition optimization model and a regenerative braking condition optimization model; from the preset optimization model, the target optimization model corresponding to the running condition is selected, which comprises: if the running condition is the traction condition, the traction condition optimization model is selected as the target optimization model; if the running condition is the regenerative braking condition, the regenerative braking condition optimization model is selected as the target optimization model.

3. The train synergistic energy-saving control method according to claim 2, characterized by, the traction condition optimization model is: ； or ; the regenerative braking condition optimization model is: ； or ; the constraint model is: ； in, The active power of the motor. For traction power loss, This is the proportionality coefficient. For the first One power unit, To be allocated to the The level of each power unit The output shaft speed of the power unit is the shaft end speed. The transmission ratio is... For the first Each power unit operates at a speed and torque of Gearbox transmission efficiency at that time For the first Each power unit operates at a speed and torque of The efficiency of the four-quadrant rectifier is calculated as follows: For DC power supply systems, which do not have a four-quadrant rectifier stage, the conversion efficiency is taken as 1.

0. For AC power supply systems, different phase shift angles are used for carrier phase shift control based on the number of multiple four-quadrant rectifiers operating. For the first Each power unit operates at a speed and torque of Motor efficiency at that time For the number of power units, For motor feedback power, For braking power loss, This is at the vehicle level.

4. The train synergistic energy-saving control method according to claim 2, characterized by, taking the optimization of the target optimization model as a target, combining the constraint model, the whole-vehicle demand level, the running speed, and the traction system efficiency parameter, performing torque optimization and distribution calculation to obtain an optimization distribution result, which comprises: taking the optimization of the target optimization model as a target, combining the constraint model, the whole-vehicle demand level, the running speed, and the traction system efficiency parameter, performing online optimization to obtain a plurality of level distribution results; from all the level distribution results, the level distribution result with the optimal efficiency is selected as the optimization distribution result.

5. The train synergistic energy saving control method according to claim 2, wherein taking the optimization of the target optimization model as a target, combining the constraint model, the whole-vehicle demand level, the running speed, and the traction system efficiency parameter, performing torque optimization and distribution calculation to obtain an optimization distribution result, which comprises: taking the optimization of the target optimization model as a target, combining the constraint model and the traction system efficiency parameter, performing offline calculation to establish a mapping relationship among vehicle speed, whole-vehicle level, and power unit level; according to the train speed, calculating a corresponding real-time vehicle speed, and combining the whole-vehicle demand level to determine the level distribution result with the optimal efficiency from the mapping relationship as the optimization distribution result.

6. The train synergistic energy-saving control method according to claim 2, wherein taking the optimization of the target optimization model as a target, combining the constraint model, the whole-vehicle demand level, and the running speed, performing torque optimization and distribution calculation to obtain an optimization distribution result, which comprises: according to the constraint model and the whole-vehicle level demand, confirming the minimum number of power units that meet the whole-vehicle level demand; performing average distribution on the whole-vehicle level demand by using the minimum number of power units to obtain the optimization distribution result.

7. The train synergistic energy-saving control method according to claim 1, wherein after the step of controlling the power units of the train to output corresponding torque according to the optimization distribution result, the method further comprises the following steps: The power unit with torque distribution of 0 adopts a weak magnetic standby and / or shutdown mode to reduce standby energy consumption.

8. The train synergistic energy-saving control method according to claim 7, wherein The power unit with torque distribution of 0 adopts a weak magnetic standby and / or shutdown mode to reduce standby energy consumption, comprising: When there is the power unit with torque distribution of 0, it is determined whether the number of the power unit with torque distribution of 0 is greater than one group; If not, the power unit maintains weak magnetic standby; If yes, at least one group of the power unit maintains weak magnetic standby, and the other power units are shut down.

9. A train energy saving control device, characterized by comprising: Comprising: A response module is configured to obtain a running state, a whole vehicle demand level, and a traction system efficiency parameter of a train in response to an operation instruction; the running state comprises a running speed and a running condition; An optimization model selection module is configured to select a target optimization model corresponding to the running condition from preset optimization models; A constraint model construction module is configured to construct a constraint model based on the whole vehicle demand level and in combination with a number of power units of the train; An allocation result determination module is configured to perform torque optimization allocation calculation in combination with the constraint model, the whole vehicle demand level, the running speed, and the traction system efficiency parameter, to obtain an optimization allocation result, with the target optimization model being optimal; An output module is configured to control the power units of the train to output corresponding torques according to the optimization allocation result.

10. An electronic device, comprising: The computer program is executed by the processor to implement the method of any one of claims 1-8.

11. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1-8.

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