CN115158076A - Metering error evaluation method, device and computer readable storage medium - Google Patents
Metering error evaluation method, device and computer readable storage medium Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
- B60L53/60—Monitoring or controlling charging stations
- B60L53/62—Monitoring or controlling charging stations in response to charging parameters, e.g. current, voltage or electrical charge
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
- B60L53/60—Monitoring or controlling charging stations
- B60L53/66—Data transfer between charging stations and vehicles
- B60L53/665—Methods related to measuring, billing or payment
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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Abstract
The invention discloses a metering error evaluation method, a metering error evaluation device and a computer readable storage medium. Wherein, the method comprises the following steps: acquiring multiple groups of variable data and multiple charging quantity readings corresponding to multiple standard charging piles when the electric automobile is charged by utilizing the multiple standard charging piles within a preset time range; determining an actual charge amount corresponding to the plurality of charge amount readings; determining a charging energy relationship between the variable quantity and the actual charge quantity based on the plurality of sets of variable data and the corresponding actual charge quantity; acquiring variable data of a charging pile to be tested and a reading value of the charging quantity of the charging pile to be tested, wherein the charging pile to be tested is used for charging the electric automobile; determining the actual charging amount of the charging pile to be tested based on the relation between the variable data of the charging pile to be tested and the charging energy; and determining the metering error of the charging pile to be tested based on the actual charging quantity of the charging pile to be tested and the reading value of the charging quantity of the charging pile to be tested. The invention solves the technical problems of low working efficiency and high cost consumption of metering error verification for the charging pile.
Description
Technical Field
The invention relates to the field of metering error evaluation, in particular to a metering error evaluation method, a metering error evaluation device and a computer readable storage medium.
Background
In the correlation technique, when carrying out the error measurement aassessment and examination to filling electric pile, if adopt every field of the stake of waiting to charge to carry out the mode completion examination of error measurement aassessment, it is inefficient, with high costs, if adopt long-range examination, need to fill electric pile and reform transform, with high costs.
Therefore, in the related art, the technical problems of low working efficiency and high cost consumption of metering error verification for the charging pile exist.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a metering error evaluation method and device and a computer readable storage medium, which at least solve the technical problems of low working efficiency and high cost of metering error verification for a charging pile.
According to an aspect of an embodiment of the present invention, there is provided a metrology error evaluation method, including: acquiring multiple groups of variable data and multiple charging quantity readings corresponding to multiple standard charging piles when the electric automobile is charged by utilizing the multiple standard charging piles within a preset time range; determining an actual charge amount corresponding to the plurality of charge amount readings; determining a charging energy relationship between the variable quantity and the actual charge quantity based on the plurality of sets of variable data and the corresponding actual charge quantity; acquiring variable data of a charging pile to be tested and a reading value of the charging quantity of the charging pile to be tested, wherein the charging pile to be tested is used for charging the electric automobile; determining the actual charging amount of the charging pile to be tested based on the variable data of the charging pile to be tested and the charging energy relation; and determining the metering error of the charging pile to be tested based on the actual charging quantity of the charging pile to be tested and the reading value of the charging quantity of the charging pile to be tested.
Optionally, determining an actual charge amount corresponding to the plurality of charge amount readings includes: respectively acquiring standard charging pile metering errors corresponding to the plurality of standard charging piles; and respectively determining actual charging quantities corresponding to the plurality of charging quantity reading values based on the standard charging pile metering errors corresponding to the plurality of standard charging piles and the corresponding plurality of charging quantity reading values.
Optionally, determining a charging energy relationship between the variable quantity and the actual charging amount based on the multiple sets of variable data and the corresponding actual charging amount includes: and taking the multiple groups of variable data and the corresponding actual charging amount as sample data, and performing machine training on the initial relation model to obtain a target relation model, wherein model parameters of the target relation model represent a charging energy relation.
Optionally, the method further includes: obtaining test data for testing a target relational model, wherein the test data comprises: testing the reading value of the charging quantity, the metering error and the test variable data; inputting the test variable data into a target relation model to obtain a first actual charging amount corresponding to the test variable data; obtaining a second actual charging amount based on the reading value of the testing charging amount and the testing metering error; acquiring a difference value between a first actual charge amount and a second actual charge amount; in the event that the difference exceeds a predetermined difference threshold, the target relationship model is updated.
Optionally, the method further includes: and under the condition that the metering error exceeds the preset metering error range, calibrating the charging pile to be tested.
Optionally, the variable data includes at least one of: charging pile output voltage, charging pile output current, charging time, battery state of charge, battery highest temperature and battery lowest temperature.
According to another aspect of the embodiments of the present invention, there is also provided a metering error evaluation apparatus including: the first acquisition module is used for acquiring multiple groups of variable data and multiple charging quantity readings corresponding to the multiple standard charging piles when the electric automobile is charged by the multiple standard charging piles within a preset time range; a first determination module for determining an actual charge amount corresponding to the plurality of charge amount readings; a second determining module, configured to determine a charging energy relationship between the variable quantity and the actual charging amount based on the multiple sets of variable data and the corresponding actual charging amount; the second acquisition module is used for acquiring variable data of the charging pile to be detected and the reading value of the charging quantity of the charging pile to be detected, wherein the charging pile to be detected is used for charging the electric automobile; the third determining module is used for determining the actual charging amount of the charging pile to be tested based on the variable data of the charging pile to be tested and the charging energy relation; and the fourth determination module is used for determining the metering error of the charging pile to be detected based on the actual charging amount of the charging pile to be detected and the charging amount reading value of the charging pile to be detected.
Optionally, the first determining module includes: the acquisition unit is used for respectively acquiring standard charging pile metering errors corresponding to the plurality of standard charging piles; and the determining unit is used for respectively determining the actual charging quantity corresponding to the plurality of charging quantity reading values based on the standard charging pile metering errors corresponding to the plurality of standard charging piles and the corresponding plurality of charging quantity reading values.
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, which includes a stored program, wherein when the program runs, the apparatus where the computer-readable storage medium is located is controlled to execute any one of the above metering error evaluation methods.
According to another aspect of the embodiments of the present invention, there is also provided a computer device, including: a memory and a processor, the memory storing a computer program; a processor for executing a computer program stored in the memory, the computer program when executed causing the processor to perform any of the above-described metrology error evaluation methods.
In the embodiment of the invention, based on the principle of magnitude transmission, because the standard charging pile is verified, and meanwhile, the metering error of the standard charging pile is known and meets the metering standard, the relationship between the actual charging quantity of the charging pile and various variable data during the charging period, namely the charging energy relationship in the embodiment, can be determined based on the charging data by acquiring various charging data, such as multiple groups of variable data, the reading value of the charging quantity, the metering error and the like when the electric vehicle charges on the standard charging pile, and then the actual charging quantity of the charging pile to be tested in the charging process can be determined by using the variable data of the electric vehicle charging on the charging pile to be tested according to the charging energy relationship, and the metering error of the charging pile to be tested can be directly determined by comparing the actual charging quantity with the reading value of the charging quantity of the charging pile to be tested, that the electric vehicle charged on the standard charging pile serves as a measurer, and the metering error of the electric vehicle on the charging pile to be tested can be accurately measured by using the charging data, so that a part of the standard charging pile can be evaluated in a large scale, and the metering error of the charging pile to solve the technical problem of the metering error.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of a metrology error evaluation method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating an implementation of a magnitude-transfer model to evaluate metering performance of a charging pile in accordance with an alternative embodiment of the present invention;
fig. 3 is a block diagram of a metering error evaluation apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Description of the terms
The quantity value transmission is a process of unifying all levels of measurement standards by the highest national standard and unifying the working measuring instruments by all levels of measurement standards to realize accurate and consistent quantity values.
The battery state of charge, the percentage of the number of charges actually existing in the energy storage medium (unit is Anshi) in the energy storage medium corresponding to the rated energy storage capacity (unit is Anshi) in the electrochemical energy storage process. I.e., the ratio of the remaining capacity of a battery after it has been used for a period of time or left unused for an extended period of time to its capacity in its fully charged state, expressed as a percentage.
In a Deep Neural Network (DNN) model, the Neural network layers inside the DNN can be divided into three types, an input layer, a hidden layer and an output layer.
In accordance with an embodiment of the present invention, there is provided a method embodiment of metrology error evaluation, it being noted that the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer executable instructions and that, although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
FIG. 1 is a flow chart of a metrology error evaluation method according to an embodiment of the present invention, as shown in FIG. 1, the method comprising the steps of:
step S102, acquiring multiple groups of variable data and multiple charging quantity readings corresponding to multiple standard charging piles when the electric automobile is charged by utilizing the multiple standard charging piles within a preset time range;
a step S104 of determining an actual charge amount corresponding to the plurality of charge amount readings;
step S106, determining a charging energy relation between the variable quantity and the actual charging quantity based on the multiple groups of variable data and the corresponding actual charging quantity;
step S108, acquiring variable data of a charging pile to be tested and a reading value of the charging quantity of the charging pile to be tested, wherein the charging pile to be tested is used for charging the electric automobile;
step S110, determining the actual charging amount of the charging pile to be tested based on the relation between the variable data of the charging pile to be tested and the charging energy;
and step S112, determining the metering error of the charging pile to be tested based on the actual charging quantity of the charging pile to be tested and the reading value of the charging quantity of the charging pile to be tested.
Through the steps, the principle of magnitude transmission can be based, and since the standard charging pile is verified, and meanwhile, the metering error of the standard charging pile is known and meets the metering standard, the relationship between the actual charging quantity of the charging pile and various variable data in the charging period can be determined based on the charging data, namely the charging energy relationship in the embodiment, according to the charging energy relationship, the actual charging quantity of the charging pile to be detected in the charging process can be determined by using the variable data of the electric vehicle charging on the charging pile to be detected, and the metering error of the charging pile to be detected can be directly determined by comparing the actual charging quantity with the variable data of the charging pile to be detected, namely, the electric vehicle charged through the standard charging pile serves as a measurer, the metering error measurement of the charging pile to be detected can be accurately completed through the charging data of the electric vehicle on the charging pile to be detected, so that the technical effect of large-scale evaluation of the metering error of the remaining charging pile to be detected can be achieved by verifying a part of the standard, and the problem of high metering error of the charging pile to be solved.
It should be noted that when various variable data of the electric vehicle during charging on the standard charging pile or the charging pile to be tested are acquired, data acquisition can be performed from a background through an electric vehicle-mounted system or a sensor, and the acquired data can also generate a timestamp or a classification identifier to perform efficient and ordered storage and management.
As an alternative embodiment, determining an actual charge amount corresponding to a plurality of charge amount readings includes: respectively acquiring standard charging pile metering errors corresponding to the plurality of standard charging piles; and respectively determining the actual charging quantity corresponding to the plurality of charging quantity reading values based on the standard charging pile metering errors corresponding to the plurality of standard charging piles and the plurality of corresponding charging quantity reading values. In this embodiment, the standard charging pile is calibrated, the metering error of the standard charging pile is known and meets the metering standard, and the actual charging amount of the standard charging pile in the charging process can be determined by means of difference or addition based on the charging amount reading value and the metering error of the standard charging pile.
As an alternative embodiment, determining the charging energy relationship between the variable quantity and the actual charging quantity based on the plurality of sets of variable data and the corresponding actual charging quantity includes: and taking the multiple groups of variable data and the corresponding actual charging amount as sample data, and performing machine training on the initial relation model to obtain a target relation model, wherein model parameters of the target relation model represent a charging energy relation. After the variable data and the actual charging amount corresponding to each standard charging pile in the charging process are acquired, a target relation model can be obtained by constructing the model and training the model by using the data, namely, the relation between various variable data and the actual charging amount of the charging pile in the charging process is determined.
As an alternative embodiment, the method further includes: obtaining test data for testing a target relational model, wherein the test data comprises: testing the reading value of the charging quantity, the metering error and the test variable data; inputting the test variable data into the target relation model to obtain a first actual charging amount corresponding to the test variable data; obtaining a second actual charging amount based on the reading value of the testing charging amount and the testing metering error; acquiring a difference value between the first actual amount of charge and the second actual amount of charge; in case the difference exceeds a predetermined difference threshold, the target relationship model is updated. After the target relation model is determined, test data for model testing can be further obtained, the accuracy and the precision of the target relation model in the process of calculating the actual charging amount according to the variable data can be determined by obtaining the difference value between the first actual charging amount determined by the target relation model and the second actual charging amount determined based on the test data, the target relation model can be further updated according to the calculation result of the target relation model and the error precision requirement, a more accurate actual charging amount calculation result is obtained, and the accuracy of measuring error evaluation of the charging pile to be tested is further improved.
As an optional embodiment, the method further includes: and under the condition that the metering error exceeds the preset metering error range, calibrating the charging pile to be tested. If the metering error is within the preset metering error range, the charging pile to be tested can be regarded as standard, the metering error of the charging pile to be tested can be directly determined in a mode of collecting charging data of the electric vehicle through the method, the operation site of the charging pile to be tested is not required to be reached, the charging pile to be tested with the metering error exceeding the preset metering error range is only required to be calibrated according to the evaluation result of the metering error, and the efficiency of calibrating the metering error of the charging pile can be greatly improved.
As an alternative embodiment, the variable data comprises at least one of: charging pile output voltage, charging pile output current, charging time, battery state of charge, battery highest temperature and battery lowest temperature.
It should be noted that, when the variable data of the charging pile in the charging process is collected by using the electric vehicle, in order to ensure validity and accuracy of the collected data, the charging data of the electric vehicle during the period of stable aging degree during the electric measurement of the battery and the battery management system of the electric vehicle may be only obtained, that is, the data collection may be performed within 1% of the design life of the battery of the electric vehicle.
Based on the above embodiments and alternative embodiments, the present invention proposes an alternative implementation, which is described below.
Electric automobile fills electric pile in the operation and uses, can appear because metering error is too big and cause economic loss. However, in the related art, calibration is usually performed on the operation site of the charging pile, and due to the characteristics of complex operation environment, large quantity, wide distribution range and the like, calibration work is easily affected by external environments such as weather and the like, so that efficiency is low, and huge manpower, material resources and financial resources are consumed. When the remote charging pile detection is carried out, the method needs to add a metering module in the production process of the charging pile, and needs to carry out hardware transformation on the charging pile which is put into use, so that the construction and operation cost of the charging pile can be greatly improved.
In view of the above technical problems, an optional embodiment of the present invention provides a remote, efficient and intelligent metering error calibration method suitable for a dc charging pile. The method comprises the steps of firstly selecting a batch of charging piles with metering errors meeting the metering standard as standard charging piles by utilizing a 'magnitude transmission' principle, and establishing a functional relation among charging process variables, charging electric energy and the metering error values by acquiring charging process data of the electric automobile on the standard charging piles. The electric automobile charged on the standard charging pile can be regarded as a measurer, when the electric automobile is charged on other non-standard charging piles, the functional relation between the charging process and the electric quantity value is established again, a charging pile metering performance verification model is established based on a deep learning algorithm, and the metering error of the charging pile to be measured is evaluated.
The method is described below.
The charging process of the electric automobile is a process of converting electric energy output by the charging pile into chemical energy of an electric automobile battery. In this process, the electrical energy is characterized on the pile side and the vehicle side by different parameters: the measurement reading of the electric quantity is shown on the pile side, and the measurement reading of the change of the charging voltage, the charging current and the State of Charge (SOC) of the battery is shown on the vehicle side.
Fig. 2 is a schematic flow chart illustrating an implementation process of evaluating the metering performance of the charging pile by using the quantity transfer model according to the alternative embodiment of the present invention, as shown in fig. 2, the method includes the following steps:
firstly, collecting transaction data in a charging process, and acquiring charging electric energy information and voltage, current, SOC (system on chip) and charging time information in the charging process. The relationship between the electric energy E generated when the charging pile is charged and the voltage u (t), the current i (t) and the charging time t in the charging process can be expressed by the following formula:
further, the amount of change in the state of charge SOC of the battery can be calculated by the following equation:
wherein, the delta SOC is the percentage value change of the ratio of the residual electric quantity to the full electric quantity of the rechargeable automobile battery in the time period from t1 to t2, and is usually 0-100 or more; e is charging electric energy in a time period from t1 to t 2; t1, t2 are charge start and end times, respectively, Δ t = t 2 -t 1 The charging time is; c is the rated capacity of the battery; u (t) is the voltage during charging in units of V; i (t) is current in units of A; eta is the charge conversion efficiency.
Since the charging capacity, the charging voltage, the charging current, and the SOC are different expressions of the charging power at the same time, it can be assumed that a functional relationship f between the charging capacity and the charging voltage, the charging current, the SOC, the charging time, and the like is stable for the electric vehicle in a certain Battery and Battery Management System (BMS) measurement circuit aging period, that is, a calculation relationship of the power in an actual situation can be represented as:
E c ＝f[u(t)，i(t)，SOC，Δt，…]
when the electric automobile is in n charging piles (hereinafter referred to as P) which are subjected to metrological verification s (n), where n is the number of charging piles), the calculated electric energy value may be represented as:
E c (n)＝f]u(t)，i(t)，SOC，Δt，...]
and the electric energy reading value on the corresponding charging pile can be represented as:
E r (n)＝[1+δ(n)]·E c (n)
in the formula, delta (n) represents the metering error of the charging pile; e r (n) represents the electric energy indicating value on the charging pile in the charging process; e c (n) represents the electric energy value obtained by calculation of the function f, and E is used for charging the electric automobile in the standard pile charging pile (the standard calibrating apparatus is adopted to measure | delta (n) | < 1%) c (n)＝E r (n)。
By P s Indicating the charging energy of the standard pile, P s (n) represents an amount of electric energy consumed in which the nth charging post completes one charging. To P s (n) adopting field metrological verification work to obtain an error delta (n) value; collecting and reading BMS communication messages in the charging process to obtain E r (n), E (n), u (t), i (t), SOC, Δ t. The vehicle passes through n charging piles P which are subjected to metrological verification in D days s (n) chargingThereafter, the functional relationship f (in this case, the data analysis will be performed by using a deep learning algorithm) can be determined by analyzing a large amount of data obtained, wherein D represents 1% of the design life of the battery, and the function f is also stable during the period when the aging degree of the battery and the BMS electrical measurement device is considered to be stable.
When the vehicle is charged with m measured charging piles (hereinafter referred to as P) in D days t (m), where m is the number of piles), the calculated electric energy can be expressed as follows:
E c (m)＝f[u(t)，i(t)，SOC，Δt，...]
the electric energy measurement reading of charging pile is:
E r (m)＝[1+δ(m)]·E c (m)
due to the above formula in E r (n), E (n), u (t), i (t), SOC, Δ t, etc. are all directly readable measurements, E r (n) available P s The functional relation f obtained by the (n) pile is calculated, so that P can be calculated t (m) working error δ (m).
In conclusion, the battery of the electric automobile in a certain BMS measuring circuit aging period is used as a measuring container and is arranged on the standard pile P s The upper charging is used as a standard scale to calculate the pile P to be measured in a contrast way t Is thus at P s And P t To achieve "magnitude transfer" of electrical energy.
According to the optional implementation mode of the invention, only a few charging piles need to be selected and calibrated, and the metering errors of all the charging piles in operation can be calculated through the charging transmission of the electric automobile, so that the calibration cost of the charging piles is greatly reduced. Meanwhile, based on the quantity value transmission principle, the established pile-vehicle-pile evaluation model can directly reflect the measurement difference between the standard pile and the measured pile, greatly improve the error precision and make up the defects of a neural network model. In addition, as the charging transaction data of the electric automobile gradually increases over time, the algorithm can realize repeated calculation of the metering error of the charging pile at regular intervals, the charging data of a plurality of different electric automobiles is used for evaluating the same tested pile, and the accuracy of the error evaluation result is greatly improved.
According to an embodiment of the present invention, there is further provided a metering error evaluation apparatus, and fig. 3 is a block diagram of a configuration of the metering error evaluation apparatus according to the embodiment of the present invention, as shown in fig. 3, the apparatus includes: the device includes a first obtaining module 31, a first determining module 32, a second determining module 33, a second obtaining module 34, a third determining module 35, and a fourth determining module 36, which are described below.
The first obtaining module 31 is configured to obtain multiple sets of variable data and multiple charging amount readings corresponding to multiple standard charging piles when the electric vehicle is charged by the multiple standard charging piles within a preset time range; a first determining module 32, connected to the first acquiring module 31, for determining an actual charge amount corresponding to a plurality of charge amount readings; a second determining module 33, connected to the first determining module 32, for determining a charging energy relationship between the variable quantity and the actual charging quantity based on multiple sets of variable data and corresponding actual charging quantities; a second obtaining module 34, connected to the second determining module 33, for obtaining variable data of the charging pile to be tested and a reading value of the charging quantity of the charging pile to be tested, where the electric vehicle is charged by using the charging pile to be tested; a third determining module 35, connected to the second obtaining module 34, for determining an actual charging amount of the charging pile to be tested based on the relationship between the variable data of the charging pile to be tested and the charging energy; and the fourth determining module 36 is connected to the third determining module 35, and configured to determine a metering error of the charging pile to be measured based on the actual charging amount of the charging pile to be measured and the reading value of the charging amount of the charging pile to be measured.
As an alternative embodiment, the first determining module 32 includes: the acquisition unit is used for respectively acquiring standard charging pile metering errors corresponding to the plurality of standard charging piles; and the determining unit is used for respectively determining the actual charging quantity corresponding to the plurality of charging quantity reading values based on the standard charging pile metering errors corresponding to the plurality of standard charging piles and the corresponding plurality of charging quantity reading values.
According to an embodiment of the present invention, there is also provided a computer-readable storage medium including a stored program, where the program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform any one of the above-mentioned metering error estimation methods.
According to an embodiment of the present invention, there is also provided a computer apparatus including: a memory and a processor, the memory storing a computer program; a processor for executing a computer program stored in the memory, the computer program when executed causing the processor to perform any of the above-described metrology error evaluation methods
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and amendments can be made without departing from the principle of the present invention, and these modifications and amendments should also be considered as the protection scope of the present invention.
Claims (10)
1. A method of metrology error evaluation, comprising:
acquiring multiple groups of variable data and multiple charging quantity readings corresponding to multiple standard charging piles when an electric automobile is charged by utilizing the multiple standard charging piles within a preset time range;
determining an actual charge amount corresponding to the plurality of charge amount readings;
determining a charging energy relationship between the variable quantity and the actual charge quantity based on the plurality of sets of variable data and the corresponding actual charge quantity;
acquiring variable data of a charging pile to be tested and a reading value of the charging quantity of the charging pile to be tested, wherein the charging pile to be tested is used for charging the electric automobile;
determining the actual charging amount of the charging pile to be tested based on the variable data of the charging pile to be tested and the charging energy relation;
and determining the metering error of the charging pile to be tested based on the actual charging quantity of the charging pile to be tested and the reading value of the charging quantity of the charging pile to be tested.
2. The method of claim 1, wherein the determining an actual charge amount corresponding to the plurality of charge amount readings comprises:
respectively acquiring standard charging pile metering errors corresponding to the plurality of standard charging piles;
and respectively determining actual charging quantities corresponding to the plurality of charging quantity reading values based on the standard charging pile metering errors corresponding to the plurality of standard charging piles and the plurality of corresponding charging quantity reading values.
3. The method of claim 1, wherein determining a charging energy relationship between a variable quantity and an actual charge quantity based on the plurality of sets of variable data and corresponding actual charge quantities comprises:
and taking the multiple groups of variable data and the corresponding actual charging amount as sample data, and performing machine training on an initial relation model to obtain a target relation model, wherein model parameters of the target relation model represent the charging energy relation.
4. The method of claim 3, further comprising:
obtaining test data for testing the target relationship model, wherein the test data comprises: testing the reading value of the charging quantity, the metering error and the test variable data;
inputting the test variable data into the target relation model to obtain a first actual charging amount corresponding to the test variable data;
obtaining a second actual charging quantity based on the reading value of the testing charging quantity and the testing metering error;
acquiring a difference value between the first actual amount of charge and the second actual amount of charge;
updating the target relationship model if the difference exceeds a predetermined difference threshold.
5. The method of claim 1, further comprising:
and under the condition that the metering error exceeds a preset metering error range, verifying the charging pile to be tested.
6. The method of any one of claims 1 to 5, wherein the variable data comprises at least one of:
charging pile output voltage, charging pile output current, charging time, battery state of charge, battery highest temperature and battery lowest temperature.
7. A metering error evaluation apparatus, comprising:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring multiple groups of variable data and multiple charging quantity readings corresponding to multiple standard charging piles when the electric automobile is charged by utilizing the multiple standard charging piles within a preset time range;
a first determination module configured to determine an actual charge amount corresponding to the plurality of charge amount readings;
a second determining module, configured to determine a charging energy relationship between a variable quantity and an actual charging amount based on the multiple sets of variable data and the corresponding actual charging amount;
the second acquisition module is used for acquiring variable data of the charging pile to be detected and the reading value of the charging quantity of the charging pile to be detected, wherein the charging pile to be detected is used for charging the electric automobile;
the third determination module is used for determining the actual charging amount of the charging pile to be detected based on the variable data of the charging pile to be detected and the charging energy relation;
and the fourth determination module is used for determining the metering error of the charging pile to be detected based on the actual charging quantity of the charging pile to be detected and the reading value of the charging quantity of the charging pile to be detected.
8. The apparatus of claim 7, wherein the first determining module comprises:
the acquisition unit is used for respectively acquiring the standard charging pile metering errors corresponding to the plurality of standard charging piles;
and the determining unit is used for respectively determining actual charging quantities corresponding to the plurality of charging quantity reading values on the basis of the standard charging pile metering errors corresponding to the plurality of standard charging piles and the plurality of corresponding charging quantity reading values.
9. A computer-readable storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the metrology error evaluation method of any one of claims 1 to 6.
10. A computer device, comprising: a memory and a processor, wherein the processor is capable of,
the memory stores a computer program;
the processor for executing a computer program stored in the memory, the computer program when executed causing the processor to perform the metrology error evaluation method of any one of claims 1 to 6.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115542235A (en) * | 2022-11-07 | 2022-12-30 | 北京志翔科技股份有限公司 | Method, device and equipment for determining metering error of charging gun and storage medium |
| CN116184058A (en) * | 2022-11-09 | 2023-05-30 | 南昌市新海通实业有限公司 | Charging pile metering detection method and device based on Internet of things |
| CN117372006A (en) * | 2023-12-08 | 2024-01-09 | 乐山市计量测试所 | Charging method and system for electric bicycle charging pile |
-
2022
- 2022-07-19 CN CN202210848986.2A patent/CN115158076A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115542235A (en) * | 2022-11-07 | 2022-12-30 | 北京志翔科技股份有限公司 | Method, device and equipment for determining metering error of charging gun and storage medium |
| CN116184058A (en) * | 2022-11-09 | 2023-05-30 | 南昌市新海通实业有限公司 | Charging pile metering detection method and device based on Internet of things |
| CN116184058B (en) * | 2022-11-09 | 2023-11-21 | 南昌市新海通实业有限公司 | Charging pile metering detection method and device based on Internet of things |
| CN117372006A (en) * | 2023-12-08 | 2024-01-09 | 乐山市计量测试所 | Charging method and system for electric bicycle charging pile |
| CN117372006B (en) * | 2023-12-08 | 2024-02-06 | 乐山市计量测试所 | Charging method and system for electric bicycle charging pile |
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