A rail transit vehicle traction system energy efficiency testing method and system

Abstract

The present invention discloses a method and system for testing the energy efficiency of a rail transit vehicle traction system with high test accuracy. The method comprises: obtaining an original line data table; dividing the original line data table into multiple candidate short trips and calculating characteristic parameters of each candidate short trip; screening and obtaining a standard short trip based on the characteristic parameters; sequentially splicing the standard short trips to obtain an overall V-F distribution probability; calculating the vehicle speed-traction force distribution probability X1 of a short trip combination to be tested based on the standard short trips; performing a non-parametric test on X1 and the overall V-F distribution probability to obtain a test value P1; selecting the short trip combination to be tested corresponding to the minimum P1 value as the dynamic typical operating condition of the entire vehicle, then obtaining the steady-state typical operating condition of the entire vehicle, and then converting it into a dynamic / steady-state test condition of the traction system; and then operating the tested traction system according to the dynamic / steady-state test condition to obtain the corresponding traction system energy efficiency value. The present invention has the advantages of high test accuracy.

Description

Technical Field

[0001] The present invention mainly relates to the field of rail transit technology, and in particular to a method and system for testing the energy efficiency of a rail transit vehicle traction system. Background Art

[0002] When categorizing railway energy consumption, train operation accounts for over 80% of total railway energy consumption, with the traction system accounting for over 70%-85% of this. Therefore, the efficiency of the traction system and its components significantly impacts the energy consumption of the entire rolling stock, and further influences the overall energy consumption of the railway system. Consequently, continuously improving the energy efficiency of rail transit vehicle traction systems and guiding companies and products towards higher energy efficiency levels are crucial for energy conservation and emission reduction across the industry. Energy efficiency assessment of railway equipment is a crucial tool for its high-quality development.

[0003] Currently, the energy efficiency evaluation of rail transit vehicle traction systems and components is primarily conducted in accordance with standards such as GB / T 25117, GB / T 25122, and GB / T 25123. GB / T 25117 stipulates that when conducting combined tests on the traction system, efficiency tests must be conducted simultaneously with the torque characteristics test of the traction motor in the hot state. Furthermore, energy consumption tests under the line operating curve are required to verify the traction system energy consumption values ​​under the line operating curve specified in the test specifications. Relevant component standards such as GB / T 25122 and GB / T 25123 require that each component be tested for efficiency at its rated point. Currently, the overall energy efficiency evaluation of the traction system is based on these efficiency test values.

[0004] However, when locomotives operate over long distances, the power and speed of the traction system and its components are not at the rated point or within the envelope. Actual test results show that the efficiency of the traction system varies significantly at different operating points. Therefore, for energy efficiency evaluation of traction systems over long distances and under multiple operating conditions, the efficiency test results at the rated point cannot accurately represent the energy efficiency of the traction system during actual operation. Furthermore, the operating conditions of different lines vary significantly, and the "energy consumption test under the line operation curve" is not comparable horizontally because it is based on different line data.

[0005] The traction system is the primary energy conversion unit in rail transit vehicles and the key to achieving electric drive. Its energy utilization efficiency directly impacts the energy efficiency of rolling stock. Researching traction system energy efficiency calculation methods based on actual line operation data is crucial for guiding the energy-saving and emission-reduction design of related products, evaluating energy efficiency levels, and ultimately improving the energy efficiency of the entire rail transit vehicle fleet. Summary of the Invention

[0006] The technical problem to be solved by the present invention is: in response to the technical problems existing in the prior art, the present invention provides a method and system for testing the energy efficiency of a rail transit vehicle traction system with high testing accuracy.

[0007] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0008] A method for testing the energy efficiency of a rail transit vehicle traction system comprises the following steps:

[0009] Obtain the speed / traction-time operation history data of a predetermined number of vehicles and splice them in chronological order to form an original route data table of speed / traction-time;

[0010] Divide the original route data table of each vehicle into K candidate short trips and calculate the characteristic parameters of each candidate short trip;

[0011] Screening the candidate short strokes to obtain a standard short stroke according to the characteristic parameters of the candidate short strokes;

[0012] The standard short trips of each vehicle after screening are spliced ​​in sequence, and the number of vehicle VF distributions is counted. After weighting the number of VF distributions of each vehicle, the overall VF distribution is obtained and converted into the overall VF distribution probability;

[0013] Divide the standard short trip into n equal parts according to the cumulative frequency distribution to form n short trip packages; extract short trips from each of the n short trip packages to form several short trip combinations to be tested; then calculate the speed-traction distribution probability X1 of the short trip combinations to be tested;

[0014] A non-parametric test is performed on the speed-traction distribution probability X1 of the short-trip combination to be tested and the overall VF distribution probability to obtain the test value P1; the short-trip combination with the smallest P1 is selected as the optimal short-trip combination under the n value;

[0015] When n is different, the short-stroke combination to be tested corresponding to the smallest P1 value is selected as the dynamic typical working condition of the whole vehicle; then the steady-state typical working condition of the whole vehicle is obtained based on the dynamic typical working condition of the whole vehicle or the overall VF distribution;

[0016] Convert the typical dynamic working condition of the whole vehicle into the dynamic test working condition of the traction system; convert the typical steady-state working condition of the whole vehicle into the steady-state test working condition of the traction system;

[0017] The traction system under test is operated according to the dynamic test condition of the traction system or the steady-state test condition of the traction system to obtain the corresponding energy efficiency value of the traction system under test.

[0018] Preferably, the specific process of dividing the original route data table of each vehicle into K candidate short trips is:

[0019] Take the partial derivative of the speed-time distribution of the original route data table to obtain the acceleration data a;

[0020] Taking |a| < 0 and V = 0 as the split point, the original route data table of each vehicle is divided into K candidate short trips.

[0021] Preferably, the characteristic parameters include maximum speed Vmax, average speed Vm, average running speed Vmr, running time T, maximum acceleration a in the acceleration section, max and the minimum deceleration a in the deceleration stage min One or more of .

[0022] Preferably, after obtaining the standard short stroke, the data sufficiency is judged, and the specific process is as follows:

[0023] Define the stability of the characteristic values ​​of different train sampling data as A1, A2, A3...An, and define the average stability of each characteristic value as A, then

[0024]

[0025]

[0026] is the cumulative average of the characteristic values ​​of the sampled data of the jth vehicle;

[0027] Define the significance level α. If |A| < α for m consecutive times, it can be determined that the data volume is saturated.

[0028] Preferably, the specific process of obtaining the typical steady-state operating condition of the vehicle according to the overall VF distribution is as follows:

[0029] 1) Treat the overall VF distribution as one class and perform binary K-means to split it into two;

[0030] 2) Calculate the distance between the two newly obtained centroids and the variance of the two classes;

[0031] 3) Select the class with the largest variance among all classes and continue to perform binary K-means to split it into two;

[0032] 4) Repeat steps 2-3) until the absolute value of the difference between the distance between the two newly obtained centroids and the distance between the centroids obtained in the previous split is less than a% of the average distance between the centroids obtained in each split;

[0033] 5) Output the result obtained by the N-4th split as the typical steady-state operating condition of the vehicle.

[0034] Preferably, the specific process of converting the typical dynamic working condition of the whole vehicle into the dynamic test working condition of the traction system is as follows:

[0035] Based on the vehicle speed-time and traction force-time corresponding to the typical dynamic working conditions of the vehicle, combined with the wheel diameter and gearbox ratio parameters, the speed-time and torque-time distributions of the traction system are obtained, which are used as the dynamic test conditions of the traction system.

[0036] Preferably, the specific process of converting the steady-state typical working condition of the whole vehicle into the steady-state test working condition of the traction system is as follows:

[0037] The operating parameters of the traction motor are calculated based on the vehicle speed and traction force corresponding to the typical steady-state operating conditions of the vehicle, combined with the wheel diameter and gearbox ratio parameters, and used as the steady-state test conditions of the traction system.

[0038] Preferably, the specific process of obtaining the energy efficiency value corresponding to the tested traction system is as follows:

[0039] The traction system under test is operated according to the traction system dynamic test conditions, and the input side electric power E1 and the output side mechanical power accumulated energy E2 are tested simultaneously. The energy efficiency value of the traction system under test is η1 = E2 / E1*100%;

[0040] According to the steady-state test conditions of the traction system, the input side electric power P at different speeds and torque points is tested. 1i , mechanical power P 2i , and the corresponding point cluster weight κ i , calculate the test traction energy efficiency value

[0041] The present invention also discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described above are executed.

[0042] The present invention further discloses a rail transit vehicle traction system energy efficiency test system, comprising a memory and a processor connected to each other, wherein a computer program is stored on the memory, and when the computer program is run by the processor, the steps of the above method are executed.

[0043] Compared with the prior art, the advantages of the present invention are:

[0044] The rail transit vehicle traction system energy efficiency test method of the present invention achieves the summary of its typical operating curve based on the actual operating data of domestic locomotive and vehicle traction systems. The test conditions are consistent with the actual on-site operating conditions and the test curves are consistent, thereby ensuring test accuracy and achieving comparability of test results.

[0045] The energy efficiency testing method for the traction system of a rail transit vehicle of the present invention solves the problems that the existing energy efficiency calculation methods for the traction systems and components of railway locomotives and vehicles are greatly different from the actual operating conditions, and the calculation results are not horizontally comparable. The present invention can provide a basis for the energy-saving design of the traction systems and components of railway locomotives and vehicles and guide the energy-saving design direction of the traction systems and components of railway locomotives and vehicles. It can further serve as an important basis for relevant competent departments to evaluate and rate the energy-saving effects of equipment, and promote further energy conservation and emission reduction in the railway industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flowchart of the construction of the vehicle traction system energy efficiency dynamic test working condition in an embodiment of the present invention.

[0047] Figure 2 This is a flowchart of the construction of a steady-state test condition for energy efficiency of a vehicle traction system in an embodiment of the present invention.

[0048] Figure 3 This is a flow chart of a vehicle traction system energy efficiency testing method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0050] like Figure 1-3 As shown, the energy efficiency testing method of the rail transit vehicle traction system according to the embodiment of the present invention specifically includes the following steps:

[0051] 1. Acquisition of route data: Based on the route or depot configuration of the relevant vehicle models, a certain number of rolling stock are selected as carriers as needed, and the "vehicle speed / traction-time" (V / Ft) operation history data of each vehicle is obtained. The data is then spliced ​​in chronological order to form the "original route data table" of "vehicle speed / traction-time";

[0052] 2. Short trip division: Take the partial derivative of the “vehicle speed-time” (Vt) distribution of the “original route data table” Obtain acceleration data a; using |a| < 0 and V = 0 as the split point, divide the "original route data table" of each vehicle into K short trips;

[0053] 3. Calculation of short-stroke characteristic parameters: Define and calculate the characteristic parameters of each short-stroke, mainly including: maximum speed / Vmax, average speed / Vm, average running speed / Vmr, running time / T, maximum acceleration in acceleration section / a max , Minimum deceleration in deceleration stage / a min wait;

[0054] 4. Short trip selection: Based on the actual operating characteristics of the vehicle, according to characteristic parameters such as average speed / Vm, average operating speed / Vmr, and operating time / T, short trips that are consistent with the overall route or vehicle operating characteristics are selected to obtain the "standard short trip";

[0055] 5. Data sufficiency judgment: define the stability of n parameters such as average running speed, acceleration time ratio, inertia time ratio, running time, and average traction force in the running range as A1, A2, A3...An, and define the average value of the stability of these characteristic values ​​as A, then

[0056]

[0057]

[0058] in: is the cumulative average of the characteristic values ​​of the sampled data of the jth vehicle;

[0059] Define the significance level α. If |A| < α for 5 consecutive times (customizable), it can be determined that the data volume is saturated and the data is sufficient.

[0060] 6. Calculation of weighted coefficients for each line: Calculate the weighted coefficient λ for each line based on the vehicle density of each line. i ;

[0061] 7. Overall "VF" distribution probability statistics: The "standard short trip" after screening of each vehicle is spliced ​​together in sequence, and the number of vehicles with "VF" distribution is counted; the "VF" distribution number of each vehicle is weighted according to the weighting coefficient calculated in step 6 to obtain the overall "VF" distribution, and then converted into the overall "VF" distribution probability;

[0062] 8. Determine the number of short-stroke combinations: Sort the operating times of all "standard short-stroke" operations by length and calculate the cumulative frequency distribution. Divide the cumulative frequency distribution into n equal parts. In each equally divided interval, find the x point corresponding to the 50% percentile accumulation of that interval. The duration of the x point serves as the basis for selecting the interval database and is summed up. The summed results for different n values ​​(2, 3, 4, etc.) represent the expected operating time for the specified standard operating condition under different n values. Select the n value corresponding to the acceptable operating time and proceed according to steps 9-11 below.

[0063] 9. Short-trip combination: Based on the number n of short-trip combinations, the "standard short-trip" is divided into n equal parts according to the cumulative frequency distribution to form n "short-trip packages". Using the Cartesian product method, short trips are sequentially extracted from the n "short-trip packages" to form several "short-trip combinations to be tested";

[0064] 10. Short-trip combination "VF" distribution probability statistics: Calculate the "vehicle speed-traction force" distribution probability X1 of the "short-trip combination to be tested" obtained in step 9;

[0065] 11. Non-parametric test: Perform a non-parametric test on the "vehicle speed-traction force" distribution probability X1 of the "short-trip combination to be tested" and the overall "VF" distribution probability to obtain the test value P1; select the short-trip combination with the smallest P1 as the optimal short-trip combination for the n value;

[0066] 12. Formation of the vehicle's typical dynamic operating condition: When n is different, the "short-stroke combination to be tested" corresponding to the smallest P1 value is selected as the vehicle's "typical dynamic operating condition";

[0067] The above typical dynamic working conditions of the whole vehicle can be used as a test of the relevant energy consumption of the whole vehicle;

[0068] 13. Formation of typical steady-state operating conditions of the vehicle: The formation of typical steady-state operating conditions of the vehicle is obtained through the following two methods:

[0069] a) Cluster analysis of typical vehicle dynamic operating conditions to obtain discrete steady-state test points;

[0070] b) Perform cluster analysis on the overall line “VF” to obtain steady-state test points.

[0071] Both of the above methods can obtain steady-state test conditions and can verify each other. In addition to the different data sources, the overall clustering process of the above two methods is consistent. The specific method b) is introduced as follows:

[0072] 1) Treat the overall “VF” distribution as one class and perform binary K-means to split it into two;

[0073] 2) Calculate the distance between the two newly obtained centroids and the variance of the two classes;

[0074] 3) Select the class with the largest variance among all classes and continue to perform binary K-means to split it into two;

[0075] 4) Repeat steps 2-3) until the absolute value of the difference between the distance between the two newly obtained centroids and the distance between the centroids obtained in the previous split is less than 5% of the average distance between the centroids obtained in each split (adjust according to needs);

[0076] 5) Output the result obtained by the N-4th split as the typical steady-state operating condition of the vehicle.

[0077] 14. Conversion of traction system typical operating conditions: Based on the "vehicle speed-time" (Vt) and "traction force-time" (Pt) corresponding to the "vehicle dynamic typical operating conditions," combined with parameters such as wheel diameter and transmission ratio, the traction system's "speed-time" (nt) and "torque-time" (Tt) distributions are calculated and used as the "traction system dynamic test operating conditions."

[0078] The vehicle speed, traction force, wheel diameter, gearbox ratio and other parameters corresponding to the "typical steady-state vehicle operating condition" are converted into the operating parameters of the traction motor to serve as the "steady-state test operating condition of the traction system";

[0079] Of course, in other embodiments, the operating data of the traction motor may be directly used to perform operating condition fitting.

[0080] 15. Calculation of energy efficiency value: Run the traction system under test according to the "traction system dynamic test operating conditions" and simultaneously test the input side electric power E1 and the output side mechanical power accumulated energy E2. The energy efficiency value of the traction system under test η1 = E2 / E1*100%;

[0081] Or according to the "traction system steady-state test operating conditions", test the input side electric power P at different speeds and torque points. 1i and mechanical power P 2i , and the corresponding point cluster weight κ i , calculate the test traction energy efficiency value

[0082] After actual measurement and verification, the deviation between the steady-state energy efficiency test value and the dynamic energy efficiency test value is within an acceptable range.

[0083] The rail transit vehicle traction system energy efficiency test method of the present invention achieves the summary of its typical operation curve based on the actual operation data of domestic locomotive and vehicle traction systems. The test conditions are consistent with the actual operation conditions on site and the test curves are consistent, thereby achieving comparability of test results.

[0084] The energy efficiency testing method for the traction system of a rail transit vehicle of the present invention solves the problems that the existing energy efficiency calculation methods for the traction systems and components of railway locomotives and vehicles are greatly different from the actual operating conditions, and the calculation results are not horizontally comparable. The present invention can provide a basis for the energy-saving design of the traction systems and components of railway locomotives and vehicles and guide the energy-saving design direction of the traction systems and components of railway locomotives and vehicles. It can further serve as an important basis for relevant competent departments to evaluate and rate the energy-saving effects of equipment, and promote further energy conservation and emission reduction in the railway industry.

[0085] An embodiment of the present invention also discloses a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program performs the steps of the above-described method. An embodiment of the present invention further discloses a rail transit vehicle traction system energy efficiency testing system, comprising an interconnected memory and a processor. The memory has a computer program stored thereon. When executed by the processor, the computer program performs the steps of the above-described method. The medium and system of the present invention correspond to the above-described testing method and similarly possess the advantages described for the above-described testing method.

[0086] The present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned method embodiment. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable storage media include: any entity or device that can carry computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. The memory is used to store computer programs and / or modules, and the processor implements various functions by running or executing computer programs and / or modules stored in the memory, and calling data stored in the memory. The memory may include high-speed random access memory and non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0087] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for testing the energy efficiency of a rail transit vehicle traction system, characterized in that: Including steps: Obtain the speed / traction-time operation history data of a predetermined number of vehicles and splice them in chronological order to form an original route data table of speed / traction-time; Divide the original route data table of each vehicle into K candidate short trips and calculate the characteristic parameters of each candidate short trip; Screening the candidate short strokes to obtain a standard short stroke according to the characteristic parameters of the candidate short strokes; The standard short trips of each vehicle after screening are spliced ​​in sequence, and the number of vehicle VF distributions is counted. After weighting the number of VF distributions of each vehicle, the overall VF distribution is obtained and converted into the overall VF distribution probability; Divide the standard short trip into n equal parts according to the cumulative frequency distribution to form n short trip packages; extract short trips from each of the n short trip packages to form several short trip combinations to be tested; then calculate the speed-traction distribution probability X1 of the short trip combinations to be tested; A non-parametric test is performed on the speed-traction distribution probability X1 of the short-trip combination to be tested and the overall VF distribution probability to obtain the test value P1; the short-trip combination with the smallest P1 is selected as the optimal short-trip combination under the n value; When n is different, the short-stroke combination to be tested corresponding to the smallest P1 value is selected as the dynamic typical working condition of the whole vehicle; then the steady-state typical working condition of the whole vehicle is obtained based on the dynamic typical working condition of the whole vehicle or the overall VF distribution; Convert the typical dynamic working condition of the whole vehicle into the dynamic test working condition of the traction system; convert the typical steady-state working condition of the whole vehicle into the steady-state test working condition of the traction system; Operate the tested traction system according to the dynamic test condition or the steady-state test condition of the traction system to obtain the corresponding energy efficiency value of the tested traction system; The specific process of obtaining the energy efficiency value corresponding to the tested traction system is as follows: Operate the tested traction system according to the dynamic test conditions of the traction system and test the input side electric power simultaneously , output side mechanical power accumulated energy , then the energy efficiency value of the tested traction system is ; According to the steady-state test conditions of the traction system, test the input side electric power at different speeds and torque points , mechanical power , and the weights obtained by clustering the corresponding points , calculate the test traction energy efficiency value .

2. The rail transit vehicle traction system energy efficiency testing method according to claim 1, characterized in that: The specific process of dividing each vehicle's original route data table into K candidate short trips is: Take the partial derivative of the speed-time distribution of the original route data table to obtain the acceleration data a; Taking |a|<0 and V=0 as the split point, the original route data table of each vehicle is divided into K candidate short trips.

3. The method for testing energy efficiency of a rail transit vehicle traction system according to claim 1, characterized in that: The characteristic parameters include maximum speed Vmax, average speed Vm, average running speed Vmr, running time T, maximum acceleration of acceleration section a max and the minimum deceleration a in the deceleration stage min One or more of .

4. The method for testing energy efficiency of a rail transit vehicle traction system according to claim 1, 2 or 3, wherein: After obtaining the standard short stroke, the data sufficiency is judged. The specific process is as follows: Define the stability of the characteristic values ​​of different train sampling data as A1, A2, A3...An, and define the average stability of each characteristic value as A, then is the cumulative average of the characteristic values ​​of the sampled data of the jth vehicle; Define the significance level α. If |A| < α for m consecutive times, the data volume is considered to be saturated.

5. The method for testing energy efficiency of a rail transit vehicle traction system according to claim 1, 2 or 3, characterized in that: The specific process of obtaining the typical steady-state operating condition of the vehicle based on the overall VF distribution is as follows: 1) Treat the overall VF distribution as one class and perform a binary K-means to split it into two; 2) Calculate the distance between the two newly obtained centroids and the variance of the two classes; 3) Select the class with the largest variance among all classes and continue to perform binary K-means to split it into two; 4) Repeat steps 2-3) until the absolute value of the difference between the distance between the two newly obtained centroids and the distance between the centroids obtained in the previous split is less than a% of the average distance between the centroids obtained in each split; 5) Output the result obtained by the N-4th split as the typical steady-state operating condition of the vehicle.

6. The method for testing energy efficiency of a rail transit vehicle traction system according to claim 1, 2 or 3, wherein: The specific process of converting the typical dynamic working conditions of the vehicle into the dynamic test conditions of the traction system is as follows: Based on the vehicle speed-time and traction force-time corresponding to the typical dynamic working conditions of the vehicle, combined with the wheel diameter and gearbox ratio parameters, the speed-time and torque-time distributions of the traction system are obtained, which are used as the dynamic test conditions of the traction system.

7. The method for testing energy efficiency of a rail transit vehicle traction system according to claim 1, 2 or 3, characterized in that: The specific process of converting the typical steady-state working condition of the vehicle into the steady-state test working condition of the traction system is as follows: The operating parameters of the traction motor are calculated based on the vehicle speed and traction force corresponding to the typical steady-state operating conditions of the vehicle, combined with the wheel diameter and gearbox ratio parameters, and used as the steady-state test conditions of the traction system.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

9. A rail transit vehicle traction system energy efficiency test system, comprising a memory and a processor connected to each other, wherein a computer program is stored in the memory, characterized in that: When the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

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