Charging pile group error characteristic control method and device based on statistical test, equipment and medium

Abstract

The invention provides a charging pile group error characteristic control method and device based on statistical test, equipment and a medium. The method comprises the following steps: S101, calculating a virtual verification standard value in a charging pile group metering guarantee scheme; s102, calculating process parameters of a virtual checking standard in the charging pile group metering guarantee scheme based on the virtual checking standard value; s103, controlling the error characteristics of the charging pile group according to the process parameters of the virtual verification standard; in the control process, if it is found that all pile errors of the charging pile group exceed the control limit, process parameters of the virtual checking standard in the charging pile group metering guarantee scheme are corrected. The method has the advantages that the error characteristic of the charging pile group is monitored, the error of each pile of the charging pile group is monitored, the effectiveness of the virtual verification standard is ensured, and the verification efficiency of the charging piles is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile verification process control, and in particular to a method, device, equipment and medium for controlling error characteristics of a charging pile group. Background Art

[0002] At present, the number of new energy electric vehicles is growing, and the operation and service of electric vehicle charging facilities are receiving increasing attention, which is mainly reflected in the measurement accuracy and charging safety of charging facilities. The accuracy of charging facility measurement directly determines the fairness and reliability of charging trade settlement, and ultimately determines whether the electric vehicle industry can develop healthily.

[0003] The metrological assurance program (MAP) refers to the quality assurance program of the metrological process. The program can quantitatively determine the total measurement uncertainty (including random error and systematic error components) of the metrological process relative to the national benchmark or other specified standards, and verify whether the total uncertainty meets the user's requirements. The metrological assurance program system refers to a management system that ensures the quality of the metrological process through a series of planned and systematic activities so that the metrological results can meet the predetermined requirements. Its advantages are: Improve measurement quality: Through a closed-loop feedback mechanism, the entire measurement process is comprehensively assessed to ensure the accuracy and consistency of value transfer.

[0004] Reduce costs: Simplifying the application of metrology assurance solutions can reduce implementation costs while maintaining measurement quality.

[0005] Enhanced traceability: Establish a complete metrology chain to ensure that metrology results can be traced back to national or international standards.

[0006] However, the existing charging pile calibration is divided into manual calibration and data-driven calibration methods. Manual calibration faces problems such as high cost, low efficiency, heavy tasks, and shortage of personnel. It is not suitable for the calibration of massive charging piles. The use of data-driven calibration is an effective way to improve the efficiency of massive charging pile calibration. At present, data-driven calibration methods include energy conservation-based methods and vehicle-pile data interaction methods, but these methods still follow the traditional single calibration ideas and use the error calculation algorithm as a virtual measuring instrument. It is impossible to continuously monitor the error change trend of the charging pile group and it is difficult to effectively ensure that the error characteristics of the charging piles are continuously controlled in daily use.

[0007] Therefore, how to monitor the error characteristics of a charging pile group, monitor the errors of each pile in the charging pile group, ensure the effectiveness of the virtual verification standard, and improve the efficiency of charging pile calibration has become a technical problem that needs to be solved urgently. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a control method, device, equipment and medium for the error characteristics of a charging pile group. Based on the metering assurance scheme system, the energy measurement data of the total meter of the charging station and the energy measurement data of each pile in the pile group in the station are used to establish a virtual verification standard value based on energy conservation, and then calculate the process parameters, including the mean value within the group. , within-group standard deviation , mean between groups A c , standard deviation between groups S B , combined standard deviation S P , forming a virtual verification standard model; by calculating the mean within the group and within-group standard deviation , perform t-test and F-test, control the error characteristics of the charging pile group, determine whether the charging piles need to be manually verified and calibrated, and update the control process of the charging pile group of the measurement assurance solution system through manual verification of sampling plans or built-in standard modules.

[0009] In a first aspect, the present invention provides a method for controlling error characteristics of a charging pile group based on statistical testing, comprising the following steps: S101. Calculate the virtual verification standard value in the charging pile group metering assurance plan, and the calculation method is: ; Where, the subscript k represents the kth calculation, where k ≥ 2; A i is a matrix β No. i elements, representing the error coefficient of the solution of the i-th charging pile; the matrix β Refers to the error coefficient matrix of each charging pile in the charging pile group. β The calculation formula is: ; In the formula, the superscript T Represents matrix transpose; matrix E and E t They are: , ; Among them, the matrix E t Medium Element E tx The total energy meter of the charging station is x Readings at a moment; ε 0 is the fixed loss in the charging station; 1 N×1 is a matrix with N rows and 1 column and all 1s; the matrix E Medium Element Exi For the charging station i Pile No. x Readings at a moment; η i For the i The AC-DC conversion efficiency of a pile is: η i =1; one measurement contains N moments, x=1, 2, ...N; Each moment measures n Data of piles i=1,2,…n ; Among them, the number of moments N> the number of charging piles n; S102, based on the virtual verification standard value, calculate the process parameters of the virtual verification standard in the charging pile group metering assurance scheme, the charging pile group is divided into J charging pile groups, for the jth group of charging piles, 1≤j≤J, then the process parameters of the virtual verification standard in the charging pile group metering assurance scheme include the group mean , within-group standard deviation , mean between groups A c , standard deviation between groups S B , combined standard deviation S P； The mean value of the jth group of charging piles is The calculation method is: ; Where M is the number of measurements within the group, 2≤M≤k; is the verification standard approval value obtained by the kth measurement of the jth group of charging piles, and the calculation method is: ; The standard deviation of the jth group of charging piles The calculation method is: ; A gross error test is conducted on the approved values ​​of each verification standard. The gross error test formula is: ; In the formula, is the critical value of the Grubbs criterion; if the gross error test formula is established, a set of measurement data is formed, otherwise, it should be eliminated and additional data should be measured; Mean between groups A c The calculation method is: ; Where, J is the number of measurement groups; Standard deviation between groups S B The calculation method is: ; Pooled Standard Deviation S P The calculation method is: ; S103, controlling the error characteristics of the charging pile group according to the process parameters of the virtual verification standard; during the control process, if it is found that the errors of all piles in the charging pile group exceed the control limit, correcting the process parameters of the virtual verification standard in the charging pile group measurement assurance scheme; The charging pile group is divided into J charging pile groups. For the jth group of charging piles, 1≤j≤J. Then the method for controlling the error characteristics of the charging pile group by the process parameters of the virtual verification standard includes: (1) When a new measurement is added, it is recorded as Group k Measurements, , 1≤ k ≤M, calculate the standard value of this virtual verification ; ; When M measurements are accumulated, the gross error test is performed and a set of measurement data is formed; (2) Calculate the mean within the group and within-group standard deviation : ; ; (3) Conduct t-test and F-test: ; ; In the formula, t p (P-1) represents the critical value of the t distribution with a confidence probability of P and a degree of freedom of P-1; It means that at the significance level α, the degrees of freedom are The critical value of the F distribution; If and only if the two equations in (3) are satisfied, it is considered that the errors of all the charging piles in the charging pile group do not exceed the control limit, that is, they meet the normal use requirements; otherwise, it is considered that the error of at least one charging pile in the charging pile group exceeds the tolerance, triggering the correction process: ; ; In the formula, A 2 (M) and D 4 (M) is given by querying the calculated control limit factor table.

[0010] Furthermore, the correction process includes: Manually calibrate T charging piles in the charging pile group or install standard power modules, and measure these T piles M times to obtain the error calibration value of T piles as d yz ,y=1,2,…,T, 1≤T <N;z=1,2,…,M, Calculate its mean A c' and standard deviation S c ': ; ; If the t statistic ,and S c '≤ S c , then the process parameters of the virtual verification standard are under control and do not need to be corrected; otherwise, A c for A c '.

[0011] In a second aspect, the present invention provides a charging pile group error characteristic control device based on statistical testing, comprising: The simulation verification standard value calculation module is used to calculate the virtual verification standard value in the charging pile group measurement assurance scheme. The calculation method of the virtual verification standard value in the charging pile group measurement assurance scheme is: ; Where, the subscript k represents the kth calculation, where k ≥ 2; A i is a matrix β No. i elements, representing the error coefficient of the solution of the i-th charging pile; the matrix β Refers to the error coefficient matrix of each charging pile in the charging pile group. β The calculation formula is: ; In the formula, the superscript T Represents matrix transpose; matrix E and E t They are: , ; Among them, the matrix E t Medium Element E tx The total energy meter of the charging station is x Readings at a moment; ε 0 is the fixed loss in the charging station; 1 N×1 is a matrix with N rows and 1 column and all 1s; the matrix E Medium Element E xi For the charging station i Pile No. x Readings at a moment; η i For the i The AC-DC conversion efficiency of a pile is: ηi =1; one measurement contains N moments, x=1, 2, ...N; Each moment measures n Data of piles i=1,2,…n ; Among them, the number of moments N> the number of charging piles n; The process parameter calculation module is used to calculate the process parameters of the virtual verification standard in the charging pile group metering assurance scheme based on the virtual verification standard value. The charging pile group is divided into J charging pile groups. For the jth group of charging piles, 1≤j≤J, then the process parameters of the virtual verification standard in the charging pile group metering assurance scheme include the group mean , within-group standard deviation , mean between groups A c , standard deviation between groups S B , combined standard deviation S P ; The mean value of the jth group of charging piles is The calculation method is: ; Where M is the number of measurements within the group, 2≤M≤k; is the verification standard approval value obtained by the kth measurement of the jth group of charging piles, and the calculation method is: ; The standard deviation of the jth group of charging piles The calculation method is: ; A gross error test is performed on the approved values ​​of each verification standard. The gross error test formula is: ; In the formula, is the critical value of the Grubbs criterion; if the gross error test formula is established, a set of measurement data is formed, otherwise, it should be eliminated and additional data should be measured; Mean between groups A c The calculation method is: ; Where, J is the number of measurement groups; Standard deviation between groups S B The calculation method is: ; An error characteristic control and correction module is used to control the error characteristics of the charging pile group according to the process parameters of the virtual verification standard; during the control process, if it is found that the errors of all piles in the charging pile group exceed the control limit, the process parameters of the virtual verification standard in the charging pile group measurement assurance plan are corrected; The method for controlling the error characteristics of a charging pile group by using the process parameters of the virtual verification standard includes: (1) When a new measurement is added, it is recorded as Group k Measurements, , 1≤ k ≤M, calculate the standard value of this virtual verification ; ; When M measurements are accumulated, the gross error test is performed and a set of measurement data is formed; (2) Calculate the mean within the group and within-group standard deviation : ; ; (3) Conduct t-test and F-test: ; ; In the formula, t p (P-1) represents the critical value of the t distribution with a confidence probability of P and a degree of freedom of P-1; It means that at the significance level α, the degrees of freedom are The critical value of the F distribution; If and only if the two equations in (3) are satisfied, it is considered that the errors of all the charging piles in the charging pile group do not exceed the control limit, that is, they meet the normal use requirements; otherwise, it is considered that the error of at least one charging pile in the charging pile group exceeds the tolerance, and the correction process is triggered: ; ; In the formula, A 2 (M) and D 4 (M) is given by querying the calculated control limit factor table.

[0012] Furthermore, the revision process includes: Manually calibrate T charging piles in the charging pile group or install standard power modules, and measure these T piles M times to obtain the error calibration value of T piles as d yz ,y=1,2,…,T, 1≤T <N;z=1,2,…,M, Calculate its mean A c ' and standard deviation S c ': ; ; If the t statistic ,and S c '≤ S c , then the process parameters of the virtual verification standard are under control and do not need to be corrected; otherwise, A c for Ac '.

[0013] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0015] One or more technical solutions provided by the present invention have at least the following technical effects or advantages: introducing the idea of ​​the metering assurance scheme into the metering verification of the charging pile group, using the electric energy measurement data of the charging station master meter and the electric energy measurement data of each pile in the pile group in the station, and establishing the virtual verification standard value according to the law of energy conservation, calculating the process parameters of the virtual verification standard, forming a virtual verification standard model, monitoring the error characteristics of the charging pile group, continuously monitoring the errors of each pile in the pile group through closed-loop control, and updating the control process of the charging pile group of the metering assurance scheme system through manual verification by sampling scheme or installation of standard modules, thereby ensuring the effectiveness of the virtual verification standard and improving the efficiency of charging pile verification.

[0016] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with embodiments with reference to the accompanying drawings.

[0018] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 It is a schematic diagram of the device module of the present invention; Figure 3 It is a schematic diagram of the device of the present invention; Figure 4 Schematic diagram of the medium of the present invention. DETAILED DESCRIPTION

[0019] The embodiment of the present application provides a charging pile group error characteristic control method, device, equipment and medium based on statistical inspection. The overall idea is as follows: based on the metering assurance scheme system, using the total meter power measurement data of the charging station and the power measurement data of each pile in the pile group in the station, the energy conservation is used to establish a virtual verification standard value, and then calculate the process parameters, including the group mean , within-group standard deviation , mean between groups Ac , standard deviation between groups S B , combined standard deviation S P , forming a virtual verification standard model; by calculating the mean within the group and within-group standard deviation , perform t-test and F-test, control the error characteristics of the charging pile group, determine whether the charging piles need to be manually verified and calibrated, and update the control process of the charging pile group of the measurement assurance solution system through manual verification of sampling plans or built-in standard modules to ensure the continued effectiveness of error control.

[0020] Embodiment 1 This embodiment provides a charging pile group error characteristic control method based on statistical testing, such as Figure 1 As shown, the following steps are included: S101. Based on the law of conservation of energy, a virtual verification standard value in a charging pile group metering assurance scheme is calculated. The calculation method of the virtual verification standard value in the charging pile group metering assurance scheme is: ; Where, the subscript k represents the kth calculation, where k ≥ 2; A i is a matrix β No. i elements, representing the error coefficient of the solution of the i-th charging pile; the matrix β Refers to the error coefficient matrix of each charging pile in the charging pile group. β The calculation formula is: ; In the formula, the superscript T Represents matrix transpose; matrix E and E t They are: , ; Among them, the matrix E t Medium Element E tx The total energy meter of the charging station is x Readings at a moment; ε 0 is the fixed loss in the charging station; 1 N×1 is a matrix with N rows and 1 column and all 1s; the matrix E Medium Element E xi For the charging station i Pile No. x Readings at a moment; η i For the iThe AC-DC conversion efficiency of a pile is: η i =1; one measurement contains N moments, x=1, 2, ...N; Each moment measures n Data of piles i=1,2,…n ; Among them, the number of moments N> the number of charging piles n; The overall error characteristics of the charging pile group are dynamically captured through matrix operations, avoiding reliance on data at a single moment and significantly improving the robustness of the error model.

[0021] S102, based on the virtual verification standard value, calculate the process parameters of the virtual verification standard in the charging pile group metering assurance scheme, the charging pile group is divided into J charging pile groups, for the jth group of charging piles, 1≤j≤J, then the process parameters of the virtual verification standard in the charging pile group metering assurance scheme include the group mean , within-group standard deviation , mean between groups A c , standard deviation between groups S B , combined standard deviation S P ; The mean value of the jth group of charging piles is The calculation method is: ; Where M is the number of measurements within the group, 2≤M≤k; is the verification standard approval value obtained by the kth measurement of the jth group of charging piles, and the calculation method is: ; The standard deviation of the jth group of charging piles The calculation method is: ; A gross error test is conducted on the approved values ​​of each verification standard. The gross error test formula is: ; In the formula, is the critical value of the Grubbs criterion; if the gross error test formula is established, a set of measurement data is formed, otherwise, it should be eliminated and additional data should be measured; Mean between groups A c The calculation method is: ; Where, J is the number of measurement groups; Standard deviation between groups S B The calculation method is: ; Pooled Standard Deviation S P The calculation method is: ; Through the sliding window statistics method, the process parameters are dynamically updated to ensure that the model adapts to the long-term operation changes of the charging pile group (such as equipment aging or environmental fluctuations).

[0022] S103. Control the error characteristics of the charging pile group according to the process parameters of the virtual verification standard. During the control process, if it is found that the errors of all piles in the charging pile group exceed the control limit, correct the process parameters of the virtual verification standard in the metering assurance scheme of the charging pile group.

[0023] The charging pile group is divided into J charging pile groups. For the jth group of charging piles, 1≤j≤J. Then the method for the process parameters of the virtual verification standard to perform process control on the error characteristics of the charging pile group is: (1) When a new measurement is added, the measurement range is all groups, recorded as Group k Measurements, , 1≤ k ≤M, calculate the standard value of this virtual verification ; ; When M measurements are accumulated, the gross error test is performed and a set of measurement data is formed; (2) Calculate the mean within the group and within-group standard deviation : ; ; (3) Conduct t-test and F-test: ; ; Where, t p (P-1) represents the critical value of the t distribution with a confidence probability of P and a degree of freedom of P-1; It means that at the significance level α, the degrees of freedom are The critical value of the F distribution; If and only if the two equations in (3) are satisfied, it is considered that the errors of all the charging piles in the charging pile group do not exceed the control limit, that is, they meet the normal use requirements; otherwise, it is considered that the error of at least one charging pile in the charging pile group exceeds the tolerance, triggering the correction process: ; ; In the formula, A 2 (M) and D 4 (M) is given by querying the calculated control limit factor table.

[0024] The correction process includes: Manually calibrate T charging piles in the charging pile group or install standard power modules, and measure these T piles M times to obtain the error calibration value of T piles as dyz ,y=1,2,…,T, 1≤T <N;z=1,2,…,M, Calculate its mean A c ' and standard deviation S c ': ; ; If the t statistic ,and S c '≤ S c , then the process parameters of the virtual verification standard are under control and do not need to be corrected; otherwise, A c for A c '.

[0025] Therefore, the model parameters can be corrected in real time through closed-loop feedback, and the error control error rate can be reduced to less than 0.5%.

[0026] Embodiment 2 Based on the same inventive concept, the present application also provides a device corresponding to the method in Example 1, see Example 2 for details. Figure 2 As shown, in this embodiment, a charging pile group error characteristic control device based on statistical inspection is provided, including: The simulation verification standard value calculation module is used to calculate the virtual verification standard value in the charging pile group measurement assurance scheme. The calculation method of the virtual verification standard value in the charging pile group measurement assurance scheme is: ; Where, the subscript k represents the kth calculation, where k ≥ 2; A i is a matrix β No. i elements, representing the error coefficient of the solution of the i-th charging pile; the matrix β Refers to the error coefficient matrix of each charging pile in the charging pile group. β The calculation formula is: ; In the formula, the superscript T Represents matrix transpose; matrix E and E t They are: , ; Among them, the matrix E t Medium Element E tx The total energy meter of the charging station is x Readings at a moment; ε 0 is the fixed loss in the charging station; 1 N×1 is a matrix with N rows and 1 column and all 1s; the matrix E Medium Element E xi For the charging station i Pile No. x Readings at a moment; η i For the i The AC-DC conversion efficiency of a pile is: η i =1; one measurement contains N moments, x=1, 2, ...N; Each moment measures n Data of piles i=1,2,…n ; Among them, the number of moments N> the number of charging piles n; The process parameter calculation module is used to calculate the process parameters of the virtual verification standard in the charging pile group metering assurance scheme based on the virtual verification standard value. The charging pile group is divided into J charging pile groups. For the jth group of charging piles, 1≤j≤J, then the process parameters of the virtual verification standard in the charging pile group metering assurance scheme include the group mean , within-group standard deviation , mean between groups A c , standard deviation between groups S B , combined standard deviation S P ; The mean value of the jth group of charging piles is The calculation method is: ; Where M is the number of measurements within the group, 2≤M≤k; is the verification standard approval value obtained by the kth measurement of the jth group of charging piles, and the calculation method is: ; The standard deviation of the jth group of charging piles The calculation method is: ; A gross error test is performed on the approved values ​​of each verification standard. The gross error test formula is: ; In the formula, is the critical value of the Grubbs criterion; if the gross error test formula is established, a set of measurement data is formed, otherwise, it should be eliminated and additional data should be measured; Mean between groups A c The calculation method is: ; Where, J is the number of measurement groups; Standard deviation between groupsS B The calculation method is: ; Pooled Standard Deviation S P The calculation method is: ; The error characteristic control and correction module is used to control the error characteristics of the charging pile group according to the process parameters of the virtual verification standard; during the control process, if it is found that the errors of all piles in the charging pile group exceed the control limit, the process parameters of the virtual verification standard in the charging pile group measurement assurance plan are corrected.

[0027] The method for controlling the error characteristics of the charging pile group by the process parameters of the virtual verification standard is as follows: (1) When a new measurement is added, it is recorded as Group k Measurements, , 1≤ k ≤M, calculate the standard value of this virtual verification ; ; When M measurements are accumulated, the gross error test is performed and a set of measurement data is formed; (2) Calculate the mean within the group and within-group standard deviation : ; ; (3) Conduct t-test and F-test: ; ; Where, t p (P-1) represents the critical value of the t distribution with a confidence probability of P and a degree of freedom of P-1; It means that at the significance level α, the degrees of freedom are The critical value of the F distribution; If and only if the two equations in (3) are satisfied, it is considered that the errors of all the charging piles in the charging pile group do not exceed the control limit, that is, they meet the normal use requirements; otherwise, it is considered that the error of at least one of the charging piles in the charging pile group exceeds the tolerance, triggering the correction process: ; ; In the formula, A 2 (M) and D 4 (M) is given by querying the calculated control limit factor table.

[0028] The correction process includes: Manually calibrate T charging piles in the charging pile group or install standard power modules, and measure these T piles M times to obtain the error calibration value of T piles as dyz ,y=1,2,…,T, 1≤T <N;z=1,2,…,M, Calculate its mean A c ' and standard deviation S c ': ; ; If the t statistic ,and S c '≤ S c , then the process parameters of the virtual verification standard are under control and do not need to be corrected; otherwise, A c for A c '.

[0029] Therefore, the model parameters can be corrected in real time through closed-loop feedback, and the error control error rate can be reduced to less than 0.5%.

[0030] Embodiment 3 Based on the same inventive concept, this application provides an electronic device embodiment corresponding to the first embodiment, see the third embodiment for details. Figure 3 As shown, this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, any implementation method in Embodiment 1 can be implemented.

[0031] Since the electronic device introduced in this embodiment is a device used to implement the method in the first embodiment of the present application, based on the method introduced in the first embodiment of the present application, a person skilled in the art can understand the specific implementation of the electronic device of the present embodiment and its various variations, so how the electronic device implements the method in the embodiment of the present application is not described in detail here. As long as a person skilled in the art implements the device used by the method in the embodiment of the present application, it belongs to the scope of protection of the present application.

[0032] Embodiment 4 Based on the same inventive concept, this application provides a storage medium corresponding to the first embodiment, see the fourth embodiment for details. Figure 4 As shown, this embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, any implementation method in the first embodiment can be implemented.

[0033] The technical solution provided in the embodiments of the present application has at least the following technical effects or advantages: introducing the idea of ​​the metering assurance scheme into the metering calibration of the charging pile group, using the electric energy measurement data of the charging station master meter and the electric energy measurement data of each pile in the pile group in the station, and establishing a virtual verification standard value based on the law of energy conservation, calculating the process parameters of the virtual verification standard, forming a virtual verification standard model, monitoring the error characteristics of the charging pile group, continuously monitoring the errors of each pile in the pile group through closed-loop control, and updating the control process of the charging pile group of the metering assurance scheme system through manual calibration by sampling scheme or installation of standard modules, thereby ensuring the effectiveness of the virtual verification standard and improving the efficiency of charging pile calibration.

[0034] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may 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.) containing computer-usable program code.

[0035] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes 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 a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0036] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0037] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0038] Although the specific implementation modes of the present invention are described above, those skilled in the art should understand that the specific implementation modes described are only illustrative and are not intended to limit the scope of the present invention. Equivalent modifications and changes made by those skilled in the art in accordance with the spirit of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. A charging pile group error characteristic control method based on statistical test, characterized by: The following steps are involved: S101. Calculate the virtual verification standard value in the charging pile group metering assurance plan, and the calculation method is: ; Where, the subscript k represents the kth calculation, where k ≥ 2; A i is a matrix β No. i elements, representing the solution error coefficient of the i-th charging pile; matrix β Refers to the error coefficient matrix of each charging pile in the charging pile group. β The calculation formula is: ; In the formula, the superscript T Represents matrix transpose; matrix E and E t They are: , ; Among them, the matrix E t Medium Element E tx The total energy meter of the charging station is x Readings at a moment; ε 0 is the fixed loss in the charging station; 1 N×1 is a matrix with N rows and 1 column and all 1s; the matrix E Medium Element E xi For the charging station i Pile No. x Readings at a moment; η i For the i The AC-DC conversion efficiency of a pile is: η i =1; one measurement contains N moments, x=1, 2, ...N; Each moment measures n Data of piles i=1,2,…n ; Among them, the number of moments N> the number of charging piles n; S102, based on the virtual verification standard value, calculating the process parameters of the virtual verification standard in the charging pile group metering assurance scheme, the charging pile group is divided into J charging pile groups, for the jth group of charging piles, 1≤j≤J, then the process parameters of the virtual verification standard in the charging pile group metering assurance scheme include the group mean , within-group standard deviation , mean between groups A c , standard deviation between groups S B , combined standard deviation S P ; The mean value of the jth group of charging piles is The calculation method is: ; Where M is the number of measurements within the group, 2≤M≤k; is the verification standard approval value obtained by the kth measurement of the jth group of charging piles, and the calculation method is: ; The standard deviation of the jth group of charging piles The calculation method is: ; A gross error test is performed on the approved values ​​of each verification standard. The gross error test formula is: ; In the formula, is the critical value of the Grubbs criterion; if the gross error test formula is established, a set of measurement data is formed, otherwise, it should be eliminated and additional data should be measured; Mean between groups A c The calculation method is: ; Where, J is the number of measurement groups; Standard deviation between groups S B The calculation method is: ; Pooled Standard Deviation S P The calculation method is: ; S103, controlling the error characteristics of the charging pile group according to the process parameters of the virtual verification standard; during the control process, if it is found that the errors of all piles in the charging pile group exceed the control limit, correcting the process parameters of the virtual verification standard in the charging pile group measurement assurance scheme; The method for controlling the error characteristics of the charging pile group according to the process parameters of the virtual verification standard includes: (1) When a new measurement is added, it is recorded as Group k Measurements, , 1≤ k ≤M, calculate the standard value of this virtual verification ; ; When M measurements are accumulated, the gross error test is performed and a set of measurement data is formed; (2) Calculate the mean within the group and within-group standard deviation : ; ; (3) Conduct t-test and F-test: ; ; Where, t p (P-1) represents the critical value of the t distribution with a confidence probability of P and a degree of freedom of P-1; It means that at the significance level α, the degrees of freedom are The critical value of the F distribution; If and only if the two equations in (3) are satisfied, it is considered that the errors of all the piles in the charging pile group do not exceed the control limit, that is, they meet the normal use requirements; otherwise, it is considered that the error of at least one pile in the charging pile group exceeds the tolerance, triggering the correction process.

2. The method according to claim 1, characterized in that: The correction process in step S103 includes: Manually calibrate T charging piles in the charging pile group or install standard power modules, and measure these T piles M times to obtain the error calibration value of T piles as d yz ,y=1,2,…,T, 1≤T <N;z=1,2,…,M, Calculate its mean A c ' and standard deviation S c ': ; ; If the t statistic ,and S c '≤ S c , then the process parameters of the virtual verification standard are under control and do not need to be corrected; otherwise, A c for A c '.

3. A charging pile group error characteristic control device based on statistical inspection, characterized in that: include: The simulation verification standard value calculation module is used to calculate the virtual verification standard value in the charging pile group measurement assurance scheme. The calculation method of the virtual verification standard value in the charging pile group measurement assurance scheme is: ; Where, the subscript k represents the kth calculation, where k ≥ 2; A i is a matrix β No. i elements, representing the solution error coefficient of the i-th charging pile; matrix β Refers to the error coefficient matrix of each charging pile in the charging pile group. β The calculation formula is: ; In the formula, the superscript T Represents matrix transpose; matrix E and E t They are: , ; Among them, the matrix E t Medium Element E tx The total energy meter of the charging station is x Readings at a moment; ε 0 is the fixed loss in the charging station; 1 N×1 is a matrix with N rows and 1 column and all 1s; the matrix E Medium Element E xi For the charging station i Pile No. x Readings at a moment; η i For the i The AC-DC conversion efficiency of a pile is: η i =1; one measurement contains N moments, x=1, 2, ...N; Each moment measures n Data of piles i=1,2,…n ; Among them, the number of moments N> the number of charging piles n; The process parameter calculation module is used to calculate the process parameters of the virtual verification standard in the charging pile group metering assurance scheme based on the virtual verification standard value. The charging pile group is divided into J charging pile groups. For the jth group of charging piles, 1≤j≤J, then the process parameters of the virtual verification standard in the charging pile group metering assurance scheme include the group mean , within-group standard deviation , mean between groups A c , standard deviation between groups S B , combined standard deviation S P ; The mean value of the jth group of charging piles is The calculation method is: ; Where M is the number of measurements within the group, 2≤M≤k; is the verification standard approval value obtained by the kth measurement of the jth group of charging piles, and the calculation method is: ; The standard deviation of the jth group of charging piles The calculation method is: ; A gross error test is performed on the approved values ​​of each verification standard. The gross error test formula is: ; In the formula, is the critical value of the Grubbs criterion; if the gross error test formula is established, a set of measurement data is formed, otherwise, it should be eliminated and additional data should be measured; Mean between groups A c The calculation method is: ; Where, J is the number of measurement groups; Standard deviation between groups S B The calculation method is: ; Pooled Standard Deviation S P The calculation method is: ; An error characteristic control and correction module is used to control the error characteristics of the charging pile group according to the process parameters of the virtual verification standard; during the control process, if it is found that the errors of all piles in the charging pile group exceed the control limit, the process parameters of the virtual verification standard in the charging pile group measurement assurance plan are corrected; The method for controlling the error characteristics of the charging pile group according to the process parameters of the virtual verification standard includes: (1) When a new measurement is added, it is recorded as Group k Measurements, , 1≤ k ≤M, calculate the standard value of this virtual verification ; ; When M measurements are accumulated, the gross error test is performed and a set of measurement data is formed; (2) Calculate the mean within the group and within-group standard deviation : ; ; (3) Conduct t-test and F-test: ; ; Where, t p (P-1) represents the critical value of the t distribution with a confidence probability of P and a degree of freedom of P-1; It means that at the significance level α, the degrees of freedom are The critical value of the F distribution; If and only if the two equations in (3) are satisfied, it is considered that the errors of all the piles in the charging pile group do not exceed the control limit, that is, they meet the normal use requirements; otherwise, it is considered that the error of at least one pile in the charging pile group exceeds the tolerance, triggering the correction process.

4. The device according to claim 3, characterized in that: The correction process includes: Manually calibrate T charging piles in the charging pile group or install standard power modules, and measure these T piles M times to obtain the error calibration value of T piles as d yz ,y=1,2,…,T, 1≤T <N;z=1,2,…,M, Calculate its mean A c ' and standard deviation S c ': ; ; If the t statistic ,and S c '≤ S c , then the process parameters of the virtual verification standard are under control and do not need to be corrected; otherwise, A c for A c '.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to claim 1 or 2 is implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to claim 1 or 2 is implemented.

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