Charging station electric energy variable data processing method and system

Abstract

The application provides a charging station electric energy variable data processing method and system, relates to the technical field of data processing, and comprises the following steps: performing difference processing on adjacent power measurement values in a power measurement sequence to obtain a power change amount sequence; determining a stage boundary according to the power change amount sequence, and dividing a charging process into multiple charging stages; generating stage sampling control parameters for each charging stage; performing stage sampling in each charging stage to obtain electric energy variable sampling data; performing piecewise electric energy calculation on the power corresponding to each sampling time interval in each charging stage, and performing intra-stage accumulation on the piecewise electric energy to obtain stage electric energy; and performing summary processing on the stage electric energy to generate a charging electric energy result corresponding to the charging process; and the application improves the autonomy and accuracy of charging station electric energy variable data processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a charging station electric energy variable data processing method and system. BACKGROUND

[0002] With the popularization of electric vehicles, as an important node of electric energy transaction and energy management, the measurement and processing technology of electric energy parameters of charging stations has gradually matured. In the prior art, for the electric energy variable data of the charging station, an electric energy metering device arranged in the charging pile or the power distribution circuit is usually used to periodically sample the voltage, current, active power and electric energy and the like, and generate corresponding electric energy data records according to a preset time interval. Such technology generally based on an electric energy meter or a collection terminal stores or uploads the collected original measurement values according to a fixed sampling period, and performs statistics, settlement or operation analysis on the electric energy variable data in a background system, for example, for application scenarios such as billing settlement, electric energy consumption statistics or load monitoring.

[0003] However, in the actual charging station operation environment, the above-mentioned method of processing electric energy variable data based on fixed period sampling directly has technical defects in specific scenarios. In a direct current fast charging station, the charging process usually includes multiple stages such as starting, constant current, constant voltage and ending, and the current and power change amplitude and rate of change of each stage are significantly different. When a uniform and fixed sampling period (such as sampling once per second or per minute) is used to process electric energy variables, in the charging starting or power mutation stage, the sampling points may not cover the key time interval of the rapid power change, resulting in a deviation between the segmented electric energy calculated by the background system according to the discrete sampling data and the electric energy actually output by the charging device. For example, when performing time-of-use electricity price settlement for a single fast charging order, if the instantaneous power change in the high-power stage is not accurately reflected, the electric energy in the corresponding period may be underestimated or overestimated, thereby affecting the accuracy of the billing result and further affecting the electric energy settlement credibility between the operator and the user. SUMMARY

[0004] The purpose of the present application is to provide a charging station electric energy variable data processing method and system, which aims to solve the problems mentioned in the background.

[0005] To solve the above technical problems, the technical solutions of the present application are as follows:

[0006] In a first aspect, a charging station electric energy variable data processing method is provided, which comprises:

[0007] obtaining continuous measurement values of voltage, current and power of a charging device in a charging process, and forming a power measurement sequence in order of sampling time;

[0008] differencing the adjacent power measurement values in the power measurement sequence to obtain a power change amount sequence;

[0009] comparing the power change amounts in the power change amount sequence one by one to generate a change trend determination result, identifying a time section with a consistent trend continuously according to the change trend determination result, determining a stage boundary through double verification of a change amplitude and stability of the time section, and dividing the charging process into multiple charging stages with different power change characteristics;

[0010] For each charging stage, the power change amount in the stage is extracted and distribution characteristic data is obtained, the stage power change activity level is determined according to the distribution discreteness and change frequency of the power change amount, the stage sampling control parameter is generated after calculation correction and boundary constraint verification according to the matching of the sampling control target and the rule set according to the activity level, and the stage sampling control parameter at least includes an electric energy variable sampling time interval;

[0011] In each charging stage, according to the corresponding stage sampling control parameter, the voltage, current and power are sampled in stages to obtain the electric energy variable sampling data corresponding to the charging stage;

[0012] In each charging stage, according to the electric energy variable sampling data, the power corresponding to each sampling time interval in the stage is calculated in stages, and the stage electric energy is obtained by accumulating the electric energy in stages.

[0013] The stage electric energy is summarized to generate a charging electric energy result corresponding to the charging process.

[0014] Preferably, the power change amounts in the power change amount sequence are compared one by one to generate a change trend determination result, a time section with a consistent trend continuously is identified according to the change trend determination result, a stage boundary is determined through double verification of a change amplitude and stability of the time section, and the charging process is divided into multiple charging stages with different power change characteristics, including:

[0015] The power change amounts in the power change amount sequence are compared one by one to generate a change trend determination result for representing the power change trend;

[0016] According to the change trend determination result, a time section with a consistent trend of the continuous power change amount is identified to generate power change trend section data;

[0017] The power change trend section data is judged in terms of change amplitude and continuous stability, and when the power change trend section is changed from a section satisfying a preset stability determination condition to a section satisfying a preset change determination condition, the corresponding time position is determined as the stage boundary data.

[0018] According to the stage boundary data, the charging process is segmented to generate a plurality of charging stage data which are distinguished from each other in time dimension and have different power change characteristics.

[0019] Preferably, for each charging stage, the power change amount in the stage is extracted and the distribution characteristic data is obtained by statistics, the stage power change activity level is determined in combination with the distribution discreteness and change frequency of the power change amount, the stage sampling control parameter is generated after calculation correction and boundary constraint verification according to the matching of the sampling control target and the rule set, including:

[0020] The corresponding power change amount in each charging stage is extracted to generate stage power change amount data;

[0021] The stage power change amount data is statistically processed to obtain distribution characteristic data for representing the concentration degree of the power change amount in time dimension;

[0022] According to the distribution characteristic data, the stage power change activity level data is generated in combination with the distribution discreteness and change frequency of the power change amount;

[0023] According to the stage power change activity level data, the stage sampling control parameter data is generated after the calculation correction and boundary constraint verification according to the matching of the sampling control target and the rule set;

[0024] The stage sampling control parameter data is associated with the corresponding charging stage as the control basis for voltage, current and power sampling in the charging stage.

[0025] Preferably, in each charging stage, according to the electric energy variable sampling data, the power corresponding to each sampling time interval in the stage is calculated in segments, and the segmented electric energy is accumulated in the stage to obtain the stage electric energy corresponding to each charging stage, including:

[0026] The electric energy variable sampling data corresponding to each charging stage is obtained, and the electric energy variable sampling data is sorted in the order of sampling time to generate stage sampling sequence data;

[0027] According to the sampling time corresponding to adjacent sampling points in the stage sampling sequence data, the sampling time interval data formed between the adjacent sampling points is determined;

[0028] For each sampling time interval data, the power measurement value corresponding to the starting position of the sampling time interval is obtained to generate sampling time interval power representation data;

[0029] According to the sampling time interval power representation data and the duration of the corresponding sampling time interval, the interval electric energy data corresponding to the sampling time interval is determined;

[0030] According to the sampling time sequence, the interval energy data corresponding to each sampling time interval in the same charging phase is accumulated to generate the phase energy data corresponding to the charging phase.

[0031] Preferably, the power change trend section data is subjected to dual judgment of change amplitude and duration stability, and when the power change trend section is changed from a section satisfying the preset stability judgment condition to a section satisfying the preset change judgment condition, the corresponding time position is determined as the phase boundary data, including:

[0032] According to the power change trend section data, the corresponding power change amount in each power change trend section is extracted to generate section power change amount set data;

[0033] According to the section power change amount set data, the change amplitude in each power change trend section is subjected to statistical processing to generate section change amplitude representation data representing the power change amplitude level in the power change trend section;

[0034] According to the section change amplitude representation data, the stable duration of the power change amplitude in the power change trend section is evaluated to generate section stability representation data representing the stability of the power change trend section;

[0035] The section stability representation data is compared with the preset stability judgment condition, and when the section stability representation data satisfies the preset stability judgment condition, stable section identification data is generated;

[0036] The section change amplitude representation data is compared with the preset change judgment condition, and when the section change amplitude representation data satisfies the preset change judgment condition, change section identification data is generated;

[0037] The continuity relationship of the stable section identification data and the change section identification data in time sequence is checked, and when it is detected that the stable section identification data continuously appears in time dimension and the change section identification data continuously appears subsequently, the junction time position of the stable section and the change section is determined;

[0038] The junction time position is output as the phase boundary data representing the change of the power change state.

[0039] Preferably, according to the distribution feature data, the distribution discreteness and the change frequency of the power change amount are combined to generate phase power change activity level data, including:

[0040] According to the distribution feature data, the time distribution state of the power change amount in the charging phase is analyzed to generate distribution discreteness representation data representing the distribution discrete degree of the power change amount;

[0041] According to the distribution discreteness characterization data, the change frequency of the power change amount in the charging stage is evaluated and processed to generate change frequency characterization data for characterizing the frequency of power change;

[0042] According to the distribution discreteness characterization data and the change frequency characterization data, active state combination data for characterizing the active state of power change is constructed, wherein the active state combination data is used to reflect the joint state of power change in the two dimensions of time distribution and change frequency;

[0043] The active state combination data is subjected to state mapping processing to map the active state combination data to a preset active degree category, and the active degree category of the power change corresponding to the charging stage is determined;

[0044] According to the determined power change active degree category, stage power change active level data corresponding to the charging stage is generated.

[0045] Preferably, according to the stage power change active level data, the sampling control target is matched with the rule set, and after calculation correction and boundary constraint verification, the electric energy variable sampling time interval is determined, and stage sampling control parameter data is generated, including:

[0046] According to the stage power change active level data, the sampling control target corresponding to the charging stage is determined, and the sampling control target is used to characterize the balance requirement between the sampling accuracy of the electric energy variable and the consumption of the sampling resource;

[0047] According to the sampling control target, the sampling control rules corresponding to different power change active levels are subjected to screening processing to generate a sampling control rule set matched with the current charging stage;

[0048] According to the sampling control rule set, the electric energy variable sampling time interval is calculated and corrected to generate candidate sampling time interval data that meets the sampling control target;

[0049] The candidate sampling time interval data is subjected to boundary constraint verification processing to generate electric energy variable sampling time interval data that meets the preset sampling time constraint condition;

[0050] The electric energy variable sampling time interval data is output as stage sampling control parameter data, and the stage sampling control parameter data is used to control the sampling process of voltage, current and power in the charging stage.

[0051] In a second aspect, a charging station electric energy variable data processing system, the system comprising:

[0052] The measurement data acquisition module is configured to acquire continuous measurement values of voltage, current and power of the charging device in the charging process, and form a power measurement sequence in the order of sampling time;

[0053] The power change amount generation module is configured to perform difference processing on adjacent power measurement values in the power measurement sequence to obtain a power change amount sequence.

[0054] The charging phase division module is configured to compare the power change amounts in the power change amount sequence one by one, generate a change trend judgment result, identify a time section with consistent continuous trend according to the change trend judgment result, determine the phase boundary through double verification of the time section change amplitude and stability, and divide the charging process into multiple charging phases with different power change characteristics.

[0055] The sampling control parameter generation module is configured to extract the power change amount in each charging phase and obtain distribution characteristic data, determine the phase power change activity level according to the distribution discreteness and change frequency of the power change amount, match the sampling control target and rule set according to the activity level, and generate the phase sampling control parameter after calculation correction and boundary constraint verification.

[0056] The phased sampling module is configured to perform phased sampling on the voltage, current and power according to the corresponding phase sampling control parameter in each charging phase to obtain the electric energy variable sampling data of the corresponding charging phase.

[0057] The phase electric energy amount calculation module is configured to perform phase-by-phase electric energy amount calculation on the power corresponding to each sampling time interval in the phase according to the electric energy variable sampling data in each charging phase, and accumulate the phase-by-phase electric energy to obtain the phase electric energy amount corresponding to each charging phase.

[0058] The electric energy amount summary module is configured to summarize the phase electric energy amounts to generate the charging electric energy result corresponding to the charging process.

[0059] The above-mentioned scheme of the present application at least has the following beneficial effects:

[0060] Firstly, by continuously acquiring the measurement values of voltage, current and power in the charging process and forming a power measurement sequence in the order of sampling time, the power change state with time in the charging process can be continuously recorded. On this basis, difference processing is performed on adjacent power measurement values in the power measurement sequence to obtain a power change amount sequence, thereby converting the power data reflecting only the instantaneous state into a data form capable of representing the power change trend and change amplitude, providing basic data support for identifying the power change state in the charging process, and avoiding the information missing problem caused by relying only on fixed time point sampling data for processing.

[0061] Secondly, by traversing and comparing the power change amounts in the power change amount sequence one by one, a change trend determination result is generated, and a time section with consistent continuous trend is identified according to the change trend determination result. On this basis, by double-checking the change amplitude and continuous stability of the time section, the stage boundary where the power change state changes is determined, so as to divide the charging process into multiple charging stages with different power change characteristics. This stage division method no longer regards the charging process as a single and homogeneous time section, but carries out stage processing according to the actual evolution process of the power change state, which provides clear time boundaries for subsequent differential data processing for different charging stages.

[0062] Further, in different charging stages, the power change amount in the stage is extracted and statistically processed to obtain distribution characteristic data for representing the power change distribution state, and the distribution dispersion and change frequency of the power change amount are combined to determine the stage power change activity level. On this basis, the corresponding sampling control target and rule set are matched according to the activity level, and the stage sampling control parameter is generated after calculation correction and boundary constraint checking, so that the sampling time interval of voltage, current and power can be adjusted according to the power change activity level in the charging stage, thereby avoiding the problems of insufficient sampling in the frequent power change stage and redundant sampling in the smooth power change stage.

[0063] On the basis of stage sampling, the power variable sampling data is obtained in each charging stage according to the corresponding stage sampling control parameter, and the power is calculated in each section according to the sampling time interval, and then the calculation is accumulated in the stage, so that the calculation process of the electric energy is consistent with the sampling time interval. This sectional calculation method can accurately reflect the actual contribution of power change to electric energy in different charging stages, and reduce the calculation deviation introduced by the change of sampling time interval.

[0064] Finally, the stage electric energy obtained in each charging stage is summarized to generate the charging electric energy result corresponding to the entire charging process, so that the final electric energy data can more truly reflect the electric energy output of the charging device in the complete charging process. In the charging application scene with obvious power change, the above processing method is beneficial to reduce the deviation between the stage electric energy and the actual output electric energy, thereby providing a reliable data basis for subsequent applications such as electric energy statistics and metering analysis. BRIEF DESCRIPTION OF DRAWINGS

[0065] Figure 1 is the flow chart of the charging station electric energy variable data processing method provided by the embodiment of the application. DETAILED DESCRIPTION

[0066] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be thoroughly understood and fully conveyed to those skilled in the art.

[0067] As shown in Figure 1 Embodiments of the present application propose a charging station electric energy variable data processing method, the method comprising:

[0068] Obtaining continuous measurement values of voltage, current and power of the charging device during the charging process, and forming a power measurement sequence according to the sampling time sequence;

[0069] Differencing adjacent power measurement values in the power measurement sequence to obtain a power change amount sequence;

[0070] Comparing the power change amounts in the power change amount sequence one by one to generate a change trend judgment result, identifying a time section with consistent continuous trend according to the change trend judgment result, determining the phase boundary through the dual verification of the time section change amplitude and stability, and dividing the charging process into multiple charging phases with different power change characteristics;

[0071] For each charging phase, extracting the power change amount in the phase and obtaining distribution characteristic data, determining the phase power change activity level in combination with the distribution discreteness and change frequency of the power change amount, matching the sampling control target and rule set according to the activity level, generating the phase sampling control parameter after calculation correction and boundary constraint verification, and the phase sampling control parameter at least includes the electric energy variable sampling time interval;

[0072] In each charging phase, according to the corresponding phase sampling control parameter, the voltage, current and power are sampled in stages to obtain the electric energy variable sampling data of the corresponding charging phase;

[0073] In each charging phase, according to the electric energy variable sampling data, the power corresponding to each sampling time interval in the phase is calculated in stages, and the power energy is accumulated in the phase to obtain the phase electric energy corresponding to each charging phase;

[0074] The phase electric energy is processed to obtain the charging electric energy result corresponding to the charging process.

[0075] In the embodiment of the present application, by continuously acquiring the measurement values of voltage, current and power during the charging process, and forming a power measurement sequence in the order of sampling time, the state of power change with time during the charging process can be continuously recorded. On this basis, the adjacent power measurement values are processed by difference, and the power change amount sequence is obtained, so as to convert the original power measurement data into a data form reflecting the power change trend and change amplitude, thereby providing basic data support for subsequent analysis of the power change state during the charging process.

[0076] Further, by comparing the power change amounts in the power change amount sequence one by one, a change trend determination result is generated, and a time section with consistent continuous trend is identified based on the change trend determination result. On this basis, by double-checking the change amplitude and continuous stability of the time section, the stage boundary where the power change state changes is determined, so as to divide the charging process into multiple charging stages with different power change characteristics. This way makes the division of charging stages based on the overall evolution process of power change, rather than the instantaneous change at a single time point, which is conducive to accurately reflecting the power change characteristics in different stages of the charging process.

[0077] In different charging stages, by extracting the power change amount in the stage and performing statistical processing, distribution characteristic data for characterizing the power change distribution state is obtained, and the stage power change activity level is determined in combination with the distribution dispersion and change frequency of the power change amount. On this basis, the corresponding sampling control target and rule set are matched according to the activity level, and the stage sampling control parameter is generated through calculation correction and boundary constraint checking, so that the sampling time interval of voltage, current and power can adapt to the power change activity level of the charging stage, thereby avoiding the problems of insufficient sampling in the frequent power change stage or redundant sampling in the flat power change stage.

[0078] On the basis of stage sampling, the electrical energy variable sampling data obtained in each charging stage is calculated in segments according to the corresponding power in the sampling time interval, and the stage electrical energy corresponding to each charging stage is obtained by accumulating in the stage. Since the sampling time interval has been adjusted according to the stage power change characteristics, this segmented calculation method can more accurately reflect the actual contribution of power change to electrical energy in different charging stages. Subsequently, the stage electrical energy obtained in each charging stage is processed to generate the charging electrical energy result corresponding to the entire charging process, so that the final electrical energy result is more consistent with the actual energy output of the charging device.

[0079] For example, in a charging station comprising a direct current fast charging device, the charging process of a vehicle usually experiences a power rapid rising stage, a power relatively stable stage and a power gradually decreasing stage in sequence. Through the above method, in the stage with relatively intense power change, a shorter sampling time interval is generated according to the stage power change activity level to obtain more intensive power sampling data; in the stage with relatively gentle power change, a longer sampling time interval is generated to reduce unnecessary sampling. The stage electric energy collected based on different charging stages is calculated respectively and summarized, and the obtained charging electric energy result can more accurately reflect the energy output condition of the vehicle in the whole charging process, facilitating subsequent electric energy statistics, analysis or related application processing.

[0080] In a preferred embodiment of the present application, the stage electric energies are summarized to generate a charging electric energy result corresponding to the charging process, specifically including:

[0081] After the calculation of the stage electric energies corresponding to each charging stage is completed, the stage electric energies are sorted according to the time sequence of the charging process, and the sequence of the stage electric energies in the whole charging process is determined. Subsequently, the stage electric energies belonging to the same charging process are sequentially accumulated to form a charging electric energy result reflecting the energy output condition of the whole charging process. In the summarizing process, the stage electric energies can be read as independent data units, and written into the summary result after reading is completed, so as to avoid data confusion between different stages. Through the above method, the charging electric energy result corresponding to a complete charging process of the charging device can be obtained on the basis of retaining the calculation result of the stage electric energy, for subsequent use.

[0082] In a preferred embodiment of the present application, the power change amounts in the power change amount sequence are compared one by one to generate a change trend determination result, the time section with consistent continuous trend is identified according to the change trend determination result, the stage boundary is determined through the dual verification of the change amplitude and stability of the time section, the charging process is divided into multiple charging stages with different power change characteristics, including:

[0083] The power change amounts in the power change amount sequence are compared one by one to generate a change trend determination result for characterizing the power change trend;

[0084] According to the change trend determination result, the time section with consistent continuous trend of multiple power change amounts is identified to generate power change trend section data;

[0085] The power change trend section data is judged in terms of change amplitude and duration stability, and when the power change trend section changes from a section satisfying the preset stable judgment condition to a section satisfying the preset change judgment condition, the corresponding time position is determined as the stage boundary data;

[0086] According to the stage boundary data, the charging process is segmented to generate a plurality of charging stage data which are distinguished from each other in time dimension and have different power change characteristics.

[0087] In the embodiment of the application, the power change trend in time dimension can be determined by processing the power change amount in the power change amount sequence one by one and comparing the current power change amount with the previous power change amount, and the change trend judgment result for representing the power change trend is generated. The processing method can clearly express the evolution process of the power change in the form of the trend judgment result, thereby avoiding the instability caused by relying on a single power change amount value for judgment.

[0088] On this basis, according to the change trend judgment result, the case that a plurality of power change amounts have consistent change trends is identified, and the corresponding time range is merged into a continuous power change trend section. By organizing the discrete change trend judgment results into time-continuous trend sections, the power change state can be described in a segmented form, thereby providing a clear time structure for subsequent overall judgment of the power change state.

[0089] Further, by judging the power change trend section in terms of change amplitude and duration stability, the preset stable judgment condition and the preset change judgment condition are introduced to identify the transition process of the power change state from stability to change. When the power change trend section changes from a section satisfying the preset stable judgment condition to a section satisfying the preset change judgment condition, the corresponding time position is determined as the stage boundary data. The double-checking method makes the determination of the stage boundary based on the overall characteristics of the trend section, effectively reducing the possibility of stage misjudgment caused by short-time abnormal fluctuation or noise change.

[0090] Finally, according to the determined stage boundary data, the charging process is segmented, so that the entire charging process is divided into a plurality of charging stages which are distinguished from each other in time dimension and have different power change characteristics. Through the above processing, the charging stage division result can more truly reflect the actual evolution process of the power change state in the charging process, and provide a clear and reliable stage basis for subsequent stage-based sampling control and stage electric energy calculation.

[0091] In a preferred embodiment of the present application, the power change amounts in the power change amount sequence are processed one by one, and the current power change amount is compared with the previous power change amount to generate a change trend determination result for representing the power change trend, specifically including:

[0092] After obtaining the power change amount sequence, according to the arrangement order of the power change amounts in time, the second power change amount in the sequence is selected as a group of comparison data, and the current power change amount and the previous power change amount adjacent in time are selected as a group of comparison data. By comparing the size relationship between the current power change amount and the previous power change amount, it is determined whether the power change is enhanced, weakened or basically kept consistent at this time position, and the determination result is recorded as a change trend determination result. The above traversal and comparison processing is continuously executed until all power change amounts in the power change amount sequence are determined, so as to obtain a group of change trend determination results arranged in time sequence, for reflecting the evolution of the power change trend in the entire charging process.

[0093] In a preferred embodiment of the present application, according to the change trend determination result, a time section with consistent change trend of the continuous multiple power change amounts is identified, and power change trend section data is generated, specifically including:

[0094] After obtaining the change trend determination result, the change trend determination result is scanned according to the time sequence. When it is detected that the adjacent multiple change trend determination results keep consistent in the change direction, the corresponding power change amounts are merged into the same time section in the time dimension, and the start time position and the end time position of the section are recorded. If the change trend is detected to change in the scanning process, the identification of the current time section is ended, and the identification of the new time section is started. Through the above-mentioned manner, the originally discrete change trend determination results are converted into several time-continuous power change trend sections, so that the power change trend can be expressed in the form of section.

[0095] In a preferred embodiment of the present application, according to the stage boundary data, the charging process is segmented to generate multiple charging stage data which are distinguished from each other in the time dimension and have different power change characteristics, specifically including:

[0096] After the phase boundary data is determined, the phase boundary data is taken as a time segmentation point to divide the time axis of the entire charging process. Specifically, the starting time of the charging process is taken as the starting point of the first time period, the time interval between adjacent two phase boundaries is taken as an independent charging phase, and the time interval between the last phase boundary and the ending time of the charging process is taken as the last charging phase. Subsequently, a corresponding time range identifier is assigned to each charging phase, and the power measurement value, the power change amount and related data in the time range are classified into the corresponding charging phase, thereby forming a plurality of charging phase data which are independent in time and different in power change characteristics.

[0097] In a preferred embodiment of the present application, for each charging phase, the power change amount in the phase is extracted and distribution characteristic data is obtained by statistics, the phase power change activity level is determined in combination with the distribution discreteness and change frequency of the power change amount, the sampling control target and rule set are matched according to the activity level, and the phase sampling control parameter is generated after calculation correction and boundary constraint verification, including:

[0098] The corresponding power change amount in each charging phase is extracted to generate phase power change amount data;

[0099] The phase power change amount data is statistically processed to obtain distribution characteristic data for representing the concentration degree of the power change amount in the time dimension;

[0100] According to the distribution characteristic data, the phase power change activity level data is generated in combination with the distribution discreteness and change frequency of the power change amount;

[0101] According to the phase power change activity level data, the sampling control target and rule set are matched to determine the electric energy variable sampling time interval after calculation correction and boundary constraint verification, and the phase sampling control parameter data is generated;

[0102] The phase sampling control parameter data is associated with the corresponding charging phase to serve as the control basis for voltage, current and power sampling in the charging phase.

[0103] In the embodiment of the present application, the corresponding power change amount in each charging phase is extracted to form phase power change amount data, and the distribution characteristic data for representing the distribution state of the power change amount in the time dimension is obtained by statistically processing the phase power change amount data. The distribution characteristic data can reflect the concentration degree of the power change amount in the charging phase and provide a basis for analyzing the overall characteristics of the power change in the phase.

[0104] On this basis, the activity degree of the power change is determined by combining the distribution discreteness and the change frequency of the power change in the charging stage, and a stage power change activity level corresponding to the charging stage is generated. By introducing the two dimensions of distribution discreteness and change frequency, the determination of the activity degree of the power change is no longer dependent on a single statistical result, but is based on the comprehensive performance of the power change in time distribution and occurrence frequency, so that different charging stages have clear and stable distinguishing basis in the power change characteristics.

[0105] Further, according to the stage power change activity level, a corresponding sampling control target and rule set are matched, and after calculation correction and boundary constraint verification, a power variable sampling time interval corresponding to the charging stage is determined, and a stage sampling control parameter is generated. Since the sampling control parameter is directly derived from the actual activity state of the power change in the stage, the sampling behavior of voltage, current and power can be adjusted according to the power change characteristics of different charging stages, so as to avoid adopting a unified sampling strategy for all charging stages, ensure the continuity of sampling, and make the sampling density consistent with the power change degree in the stage, thereby improving the matching degree between the power variable sampling process and the actual charging process.

[0106] In a preferred embodiment of the present application, the stage power change data is statistically processed to obtain distribution characteristic data for representing the concentration degree of the power change in the time dimension, specifically including:

[0107] After obtaining the stage power change data corresponding to a certain charging stage, the data is first arranged according to the time sequence of the power change in the charging stage. Then, the distribution of the power change at different time positions is statistically analyzed by taking the time range of the charging stage as the statistical interval, for example, whether the power change is concentrated in a few time sections or more evenly distributed in the entire time range. Through the above statistical processing, distribution characteristic data reflecting the concentration or dispersion degree of the power change in the time dimension is generated, which is used to describe the overall distribution state of the power change in the charging stage.

[0108] In a preferred embodiment of the present application, according to the stage power change activity level data, a sampling control target and rule set are matched, and after calculation correction and boundary constraint verification, a power variable sampling time interval is determined to generate stage sampling control parameter data, specifically including:

[0109] After obtaining the active level data of the stage power change corresponding to a certain charging stage, the active level is input as the basis of sampling control. According to the correspondence between the preset level and the sampling time interval, the sampling time interval of the electric energy variable applicable to the charging stage is determined. When the power change active level represents that the power change in the stage is relatively frequent, a relatively short sampling time interval is selected; when the power change active level represents that the power change in the stage is relatively flat, a relatively long sampling time interval is selected. Then, the determined sampling time interval is output as the stage sampling control parameter data and is stored in association with the corresponding charging stage for subsequent stage sampling process calling.

[0110] In a preferred embodiment of the present application, in each charging stage, according to the electric energy variable sampling data, the power corresponding to each sampling time interval in the stage is calculated in stages, and the segmented electric energy is accumulated in the stage to obtain the stage electric energy corresponding to each charging stage, including:

[0111] Obtain the electric energy variable sampling data corresponding to each charging stage, and sort the electric energy variable sampling data in the order of sampling time to generate stage sampling sequence data;

[0112] According to the sampling time corresponding to adjacent sampling points in the stage sampling sequence data, determine the sampling time interval data formed between the adjacent sampling points;

[0113] For each sampling time interval data, obtain the power measurement value corresponding to the starting position of the sampling time interval to generate sampling time interval power representation data;

[0114] According to the sampling time interval power representation data and the duration of the corresponding sampling time interval, determine the interval electric energy data corresponding to the sampling time interval;

[0115] According to the sampling time sequence, the interval electric energy data corresponding to each sampling time interval in the same charging stage is accumulated to generate the stage electric energy data corresponding to the charging stage.

[0116] In the embodiment of the present application, by arranging the power sampling data collected in each charging stage according to the sampling time sequence, the sampling time interval formed between adjacent sampling points can be determined, and the power measurement value and the corresponding time interval are corresponded. On this basis, the power energy is calculated in segments with the sampling time interval as the unit, and the accumulation processing is performed in the stage, so that the calculation process of the power energy can reflect the actual situation of the power change with time. Since the sampling time interval is derived from the stage sampling control, this segmented calculation method can adapt to the power energy calculation requirements under different sampling time intervals, and avoid introducing calculation deviation due to the change of sampling interval. Through the above processing, the stage power energy corresponding to each charging stage can accurately reflect the energy output in the stage, and provide a reliable data basis for the subsequent power energy aggregation.

[0117] In a preferred embodiment of the present application, according to the sampling time interval power characteristic data and the duration of the corresponding sampling time interval, the interval power energy data corresponding to the sampling time interval is determined, which specifically includes:

[0118] After determining the sampling time interval power characteristic data, the power characteristic data and its corresponding sampling time interval are associated. Specifically, the power change in the sampling time interval is combined with the time length of the sampling time interval to reflect the energy output in the time interval. By quantitatively describing the duration of the power characteristic data in the time interval, the interval power energy data corresponding to the sampling time interval is generated, so that each sampling time interval has corresponding power energy results.

[0119] In a preferred embodiment of the present application, according to the sampling time sequence, the interval power energy data corresponding to each sampling time interval in the same charging stage is accumulated to generate the stage power energy data corresponding to the charging stage, which specifically includes:

[0120] After obtaining the interval power energy data corresponding to all sampling time intervals in the same charging stage, first, the interval power energy data is arranged according to the order of the sampling time interval on the time axis. Then, starting from the initial sampling time interval of the charging stage, the interval power energy data corresponding to the subsequent sampling time interval is sequentially accumulated until the accumulation of all sampling time intervals in the charging stage is completed. Through the above sequential accumulation method, the stage power energy data reflecting the overall energy output of the charging stage is generated, and the stage power energy data is used as the input of the subsequent power energy aggregation processing.

[0121] In a preferred embodiment of the present application, the power variation trend section data is judged in terms of both variation amplitude and stability, and when the power variation trend section changes from a section satisfying the preset stability judgment condition to a section satisfying the preset variation judgment condition, the corresponding time position is determined as the stage boundary data, including:

[0122] According to the power variation trend section data, the power variation amount in each power variation trend section is extracted to generate section power variation amount set data;

[0123] According to the section power variation amount set data, the variation amplitude in each power variation trend section is statistically processed to generate section variation amplitude representation data representing the power variation amplitude level in the power variation trend section;

[0124] According to the section variation amplitude representation data, the stable duration of the power variation amplitude in the power variation trend section is evaluated to generate section stability representation data representing the stability of the power variation trend section;

[0125] The section stability representation data is compared with the preset stability judgment condition, and when the section stability representation data satisfies the preset stability judgment condition, stable section identification data is generated;

[0126] The section variation amplitude representation data is compared with the preset variation judgment condition, and when the section variation amplitude representation data satisfies the preset variation judgment condition, variation section identification data is generated;

[0127] The continuity relationship of the stable section identification data and the variation section identification data in time sequence is checked, and when it is detected that the stable section identification data continuously appears in the time dimension and the variation section identification data continuously appears subsequently, the junction time position of the stable section and the variation section is determined;

[0128] The junction time position is output as the stage boundary data representing the change of the power variation state.

[0129] In the embodiments of the present application, by further processing the power change amount at the level of the power change trend section, the trend information originally only reflecting the change direction is refined into section characteristic data capable of representing the change amplitude level and stable duration state. Based on the statistical results of the change amplitude in the section, whether the power change remains stable within a period of time is evaluated, and different change states are distinguished in combination with the stable determination condition and the change determination condition. On this basis, the verification of the continuous relationship in time sequence between the stable section and the change section is introduced, so that the determination of the stage boundary not only depends on the single change amplitude judgment, but is established on the overall process of "stable duration followed by obvious change". This processing method can reduce the misjudgment caused by transient power fluctuation, make the determined stage boundary more consistent with the real turning point of the power change state in the charging process, and thus improve the rationality of the charging stage division.

[0130] In a preferred embodiment of the present application, according to the section power change amount set data, the change amplitude statistical processing in the section is performed on each power change trend section to generate section change amplitude characteristic data for representing the power change amplitude level in the power change trend section, specifically including:

[0131] After obtaining the section power change amount set data corresponding to a power change trend section, first, the set data is sorted according to the time sequence of the power change amount in the section. Then, all the power change amounts in the power change trend section are analyzed as a whole to determine the overall fluctuation level of the power change amounts in the section. For example, by comparing the differences between the power change amounts in the section, it can be judged whether the power change is concentrated in a small range of fluctuation or in a large range of change. Through the above-mentioned statistical processing in the section, the section change amplitude characteristic data capable of reflecting the overall change amplitude level of the power change trend section is generated, which is used for subsequent stability and change state judgment.

[0132] In a preferred embodiment of the present application, according to the section change amplitude characteristic data, the stable duration of the power change amplitude in the power change trend section is evaluated and processed to generate section stability characteristic data for representing the stability of the power change trend section, specifically including:

[0133] After obtaining the segment variation amplitude characterization data, the data is taken as basic information reflecting the strength of power variation within the segment. Subsequently, the continuity of the power variation trend segment in the time dimension is analyzed to determine whether the power variation amplitude within the segment remains at a relatively consistent level for a period of continuous time. If the segment variation amplitude characterization data changes little at multiple continuous time positions within the power variation trend segment, it is determined that the power variation within the segment has the characteristics of continuous stability, and corresponding segment stability characterization data is generated. Through the above evaluation process, the stability of the power variation not only reflects the variation at a single time point, but also embodies the continuous characteristics of the variation amplitude in time.

[0134] In a preferred embodiment of the present application, the setting method of the preset stability determination condition and the preset variation determination condition specifically includes:

[0135] During the system initialization or running configuration phase, the typical value range of the power variation amplitude is analyzed according to the rated power range of the charging device, historical operation data, and common fluctuation characteristics of the power variation. On this basis, the preset stability determination condition for characterizing the power variation in a flat state is set, so that when the segment stability characterization data indicates that the power variation amplitude continuously appears within the condition range, the power variation trend segment can be determined as a stable segment. At the same time, the preset variation determination condition for characterizing the significant enhancement of the power variation is set, so that when the segment variation amplitude characterization data meets the condition, the corresponding power variation trend segment can be determined as a variation segment. By respectively setting the stability determination condition and the variation determination condition and reserving a distinguishing space between the two, it is possible to avoid frequent switching between stable segments and variation segments due to small fluctuations or accidental changes, thereby improving the reliability of the phase boundary identification process.

[0136] In a preferred embodiment of the present application, the continuity relationship of the stable segment identification data and the variation segment identification data in the time sequence is checked, and when it is detected that the stable segment identification data continuously appears in the time dimension and the variation segment identification data continuously appears subsequently, the boundary time position of the stable segment and the variation segment is determined, specifically including:

[0137] After obtaining the stable section identification data and the change section identification data, the identification data is checked one by one according to the arrangement order of the power change trend section on the time axis. First, the stable section identification data arranged continuously in time is identified, and the end time position of the continuous stable section is recorded. Then, it is judged whether the continuous change section identification data appears immediately after the end time position. If the above time sequence relationship is detected, the junction point between the stable section end time position and the change section start time position is determined as the time position at which the power change state changes. Through the continuity checking method, the short-term abnormal fluctuation can be avoided from being misjudged as a stage boundary, and the finally determined stage boundary is more consistent with the actual process of the power change state changing from stable to change in the charging process.

[0138] In a preferred embodiment of the present application, according to the distribution characteristic data, the distribution discreteness of the power change amount and the change frequency are combined to generate stage power change activity level data, including:

[0139] According to the distribution characteristic data, the time distribution state of the power change amount in the charging stage is analyzed and processed to generate distribution discreteness representation data representing the distribution discrete degree of the power change amount;

[0140] According to the distribution discreteness representation data, the change frequency of the power change amount in the charging stage is evaluated and processed to generate change frequency representation data representing the power change frequency;

[0141] According to the distribution discreteness representation data and the change frequency representation data, active state combination data representing the power change active state is constructed, wherein the active state combination data is used to reflect the joint state of the power change in the two dimensions of time distribution and change frequency;

[0142] The active state combination data is subjected to state mapping processing to map the active state combination data to a preset active degree category, and the power change activity degree category corresponding to the charging stage is determined;

[0143] According to the determined power change activity degree category, stage power change activity level data corresponding to the charging stage is generated.

[0144] In the embodiment of the present application, by analyzing the time distribution state of the power change in the charging stage, the power change is expanded from a single numerical characteristic to a description form of two dimensions of distribution discreteness and change frequency, so that the power change state in the stage can be described from multiple angles. On this basis, the discrete data and the change frequency data are combined to form active state combination data reflecting the joint state of the power change, and are converted into an explicit activity level category through state mapping. This processing process avoids directly judging the activity level with a single statistical result, so that the generation of the activity level has a clear data source and processing path, so that the difference in power change activity of different charging stages can be stably and repeatedly identified, providing a reliable basis for subsequent sampling control.

[0145] In a preferred embodiment of the present application, according to the distribution characteristic data, the time distribution state of the power change in the charging stage is analyzed and processed to generate distribution discreteness data for representing the distribution discreteness of the power change, specifically including:

[0146] After obtaining the distribution characteristic data corresponding to a certain charging stage, first, the overall range of the charging stage in the time dimension is determined. Then, the power change in the stage is arranged according to the time position of its occurrence, and whether the power change is concentrated in a few time sections or dispersed in the entire charging stage is observed. Through the analysis of the distribution state of the power change on the time axis, the distribution discreteness data reflecting the concentration or dispersion degree of the power change in the charging stage is generated, which is used to describe the discrete characteristics of the power change in the time dimension.

[0147] In a preferred embodiment of the present application, according to the distribution discreteness data, the change frequency of the power change in the charging stage is evaluated and processed to generate change frequency data for representing the frequency of the power change, specifically including:

[0148] After obtaining the distribution discreteness data, the number of occurrences of the power change in the charging stage and its occurrence rhythm in the time dimension are further analyzed. Specifically, the occurrence of the power change exceeding the preset change judgment condition in the charging stage can be counted, and combined with the distribution of the changes in time, it is judged whether the power change occurs multiple times in a short time or only at a few time points. Through the above evaluation processing, the change frequency data for representing whether the power change in the charging stage occurs frequently is generated.

[0149] In a preferred embodiment of the present application, the distribution discreteness characterization data and the frequency variation characterization data are used to construct active state combination data for characterizing the power variation active state, wherein the active state combination data is used to reflect the joint state of the power variation in the time distribution and the variation frequency, and specifically includes:

[0150] After obtaining the distribution discreteness characterization data and the frequency variation characterization data respectively, the two types of data are combined as two independent dimensions for describing the power variation state. Specifically, the distribution discreteness characterization data and the frequency variation characterization data can be associatedly stored to form a combination data structure for reflecting the power variation time distribution characteristics and the variation frequency simultaneously. Through the combination processing, the power variation state is no longer described by a single feature, but can be expressed in the form of a joint state, providing a basis for subsequent determination of the active degree category.

[0151] In a preferred embodiment of the present application, the active state combination data is subjected to state mapping processing to map the active state combination data to a preset active degree category, and to determine the power variation active degree category corresponding to the charging phase, and specifically includes:

[0152] After the active state combination data is constructed, it is used as input data and compared with a preset active degree mapping rule. The mapping rule is used to specify the power variation active degree category corresponding to different distribution discreteness and variation frequency combinations. Through the determination of the active state combination data, it is mapped to a specific active degree category, thereby completing the conversion from continuous state description to discrete category description, so that the power variation active degree can be expressed in the form of an explicit category.

[0153] In a preferred embodiment of the present application, the power variation active level data corresponding to the charging phase is generated according to the determined power variation active degree category, and specifically includes:

[0154] After the power variation active degree category corresponding to the charging phase is determined, the category is used as the final characterization result of the power variation state of the charging phase. Subsequently, the active degree category is converted into phase power variation active level data consistent with the internal use rules of the system, and is associatedly stored with the corresponding charging phase. In this way, each charging phase has a clear and unique power variation active level, which is used in the subsequent generation process of the sampling control parameter.

[0155] In a preferred embodiment of the present application, the setting method of the active degree category specifically includes:

[0156] In the system configuration stage, at least two power change activity level categories are set in advance according to the power change characteristics of the charging device and the common modes of power change in actual operation, for distinguishing between the relatively flat stage of power change and the relatively frequent stage of power change. Further, multiple activity level categories can be divided according to different combinations of the discrete degree of power change amount in time distribution and the change frequency, so that the different activity level categories have clear distinction in power change characteristics. The activity level categories set in the above manner can cover the common power change states in the charging process, and provide clear and executable basis for subsequent generation of sampling control parameters according to the activity level categories.

[0157] In a preferred embodiment of the present application, according to the stage power change activity level data, the sampling control target is matched with the rule set, and after calculation correction and boundary constraint verification, the electric energy variable sampling time interval is determined to generate stage sampling control parameter data, including:

[0158] According to the stage power change activity level data, the sampling control target corresponding to the charging stage is determined, and the sampling control target is used to represent the balance requirement between the electric energy variable sampling accuracy and the sampling resource consumption;

[0159] According to the sampling control target, the sampling control rules corresponding to different power change activity levels are screened and processed to generate a sampling control rule set matched with the current charging stage;

[0160] According to the sampling control rule set, the electric energy variable sampling time interval is calculated and corrected to generate candidate sampling time interval data meeting the sampling control target;

[0161] The boundary constraint verification is performed on the candidate sampling time interval data to generate electric energy variable sampling time interval data meeting the preset sampling time constraint condition;

[0162] The electric energy variable sampling time interval data is output as stage sampling control parameter data, and the stage sampling control parameter data is used to control the sampling process of voltage, current and power in the charging stage.

[0163] In the embodiment of the present application, by introducing the determination process of the sampling control target, the generation of the electric energy variable sampling time interval is no longer dependent on the power change activity level itself, but is processed in combination with the balance relationship between the sampling accuracy requirement and the sampling resource consumption. On this basis, according to the sampling control target, a plurality of sampling control rules are screened to form a rule set matched with the characteristics of the current charging stage, and the sampling time interval is calculated and corrected accordingly. Subsequently, through boundary constraint verification, it is ensured that the generated sampling time interval meets the preset time range requirement. The processing mechanism makes the determination process of the sampling time interval have clear control logic and constraint conditions, so that the sampling control parameters can adapt to the power change characteristics of different charging stages, and improve the executability and stability of the staged sampling in actual application.

[0164] In a preferred embodiment of the present application, according to the stage power change activity level data, the sampling control target corresponding to the charging stage is determined, which is used to represent the balance requirement between the electric energy variable sampling accuracy and the sampling resource consumption, specifically including:

[0165] After obtaining the stage power change activity level data corresponding to a certain charging stage, the activity level is taken as input information reflecting the power change state in the stage. According to the activity level, the attention degree of the charging stage to the power change details in the sampling process is determined. When the activity level represents that the power change in the stage is relatively frequent, the sampling control target is set to preferentially ensure the continuous reflection of the power change process; when the activity level represents that the power change in the stage is relatively flat, the sampling control target is set to reduce the sampling times on the premise of meeting the basic measurement requirement. Through the above-mentioned manner, the sampling control target matched with the power change characteristics of the charging stage is formed.

[0166] In a preferred embodiment of the present application, according to the sampling control target, the sampling control rules corresponding to different power change activity levels are screened and processed to generate a sampling control rule set matched with the current charging stage, specifically including:

[0167] In the system, a plurality of groups of sampling control rules are pre-stored, and each group of sampling control rules corresponds to one power change activity level or activity level interval. When the sampling control target is determined, the rules conforming to the sampling control target are selected from the sampling control rules, and the rules not conforming to the current sampling control target are excluded. Through the screening processing, a sampling control rule set only containing the sampling control rules matched with the power change characteristics of the current charging stage is formed, which provides clear rule basis for the generation of the subsequent sampling time interval.

[0168] In a preferred embodiment of the present application, the sampling time interval of the electric energy variable is calculated and corrected according to the set of sampling control rules, and candidate sampling time interval data meeting the sampling control target is generated, which specifically includes:

[0169] After obtaining the set of sampling control rules, the sampling time interval of the electric energy variable is preliminarily determined according to the sampling strategy defined in the set of rules. The preliminarily determined sampling time interval is used to reflect the time interval requirement of voltage, current and power sampling under the current sampling control target. Then, the preliminarily determined sampling time interval is corrected according to the actual situation of power change in the charging phase, for example, the sampling time interval is appropriately shortened when the power change appears a short-time enhancement trend. Through the above processing, candidate sampling time interval data matching the power change state of the current charging phase is generated.

[0170] In a preferred embodiment of the present application, the candidate sampling time interval data is subjected to boundary constraint verification processing to generate electric energy variable sampling time interval data meeting the preset sampling time constraint condition, which specifically includes:

[0171] After generating the candidate sampling time interval data, the data is compared with the preset sampling time constraint condition. If the candidate sampling time interval is within the range defined by the sampling time constraint condition, the candidate sampling time interval is directly used as the final sampling time interval; if the candidate sampling time interval exceeds the range defined by the sampling time constraint condition, it is adjusted to fall within the allowed sampling time range. Through the above boundary constraint verification processing, it is ensured that the finally determined sampling time interval meets both the sampling control target and the requirements of system operation and measurement stability.

[0172] In a preferred embodiment of the present application, the electric energy variable sampling time interval data is output as phase sampling control parameter data, and the phase sampling control parameter data is used to control the sampling process of voltage, current and power in the charging phase, which specifically includes:

[0173] After determining the final electric energy variable sampling time interval data, the sampling time interval is output as phase sampling control parameter data and is stored in association with the corresponding charging phase. When sampling voltage, current and power in the charging phase, the sampling operation is performed according to the sampling time interval indicated in the phase sampling control parameter data, so that the sampling process maintains consistent control mode throughout the charging phase. Through this way, it is ensured that the sampling control parameter can be actually applied to the electric energy variable sampling process in the charging phase.

[0174] In a preferred embodiment of the present application, the setting method of the preset sampling time constraint condition specifically includes:

[0175] In the system configuration phase, according to the measured capacity of the charging device, the data processing capacity and the typical characteristics of power change in the charging process, the reasonable value range of the sampling time interval of the electric energy variable is set. The sampling time constraint condition is used to limit the minimum allowable value and the maximum allowable value of the sampling time interval, wherein the minimum allowable value is used to avoid too high sampling frequency leading to too heavy data processing burden, and the maximum allowable value is used to avoid too long sampling interval missing power change information. By setting the above sampling time constraint condition, the adjustment process of the sampling time interval is always carried out within a controllable range, thereby ensuring the executability and stability of the sampling process.

[0176] Embodiments of the present application also provide a charging station electric energy variable data processing system, which comprises:

[0177] A measurement data acquisition module is configured to acquire continuous measurement values of voltage, current and power of the charging device in the charging process, and form a power measurement sequence in the order of sampling time;

[0178] A power change amount generation module is configured to perform difference processing on adjacent power measurement values in the power measurement sequence to obtain a power change amount sequence;

[0179] A charging phase division module is configured to compare the power change amounts in the power change amount sequence one by one, generate a change trend judgment result, identify a time section with consistent continuous trend according to the change trend judgment result, determine the phase boundary through double verification of the time section change amplitude and stability, and divide the charging process into multiple charging phases with different power change characteristics;

[0180] A sampling control parameter generation module is configured to extract the power change amounts in each charging phase and obtain distribution characteristic data, determine the power change activity level of the phase according to the distribution discreteness and change frequency of the power change amounts, match the sampling control target and rule set according to the activity level, generate the phase sampling control parameter after calculation correction and boundary constraint verification, and the phase sampling control parameter at least includes the electric energy variable sampling time interval;

[0181] A phased sampling module is configured to perform phased sampling on the voltage, current and power according to the corresponding phase sampling control parameter in each charging phase to obtain the electric energy variable sampling data of the corresponding charging phase;

[0182] A phase electric energy amount calculation module is configured to calculate the phase electric energy amount in each charging phase according to the electric energy variable sampling data, and accumulate the phase electric energy amount to obtain the phase electric energy amount corresponding to each charging phase;

[0183] An electric energy summarizing module is configured to summarize the electric energy of each stage to generate a charging electric energy result corresponding to the charging process.

[0184] It should be noted that the system is a system corresponding to the above method, and all the implementation manners in the above method embodiments are applicable to this embodiment and can also achieve the same technical effects.

[0185] Embodiments of the present application also provide a computing device, comprising a processor, a memory storing a computer program, the computer program being executed by the processor to perform the method described above. All the implementation manners in the above method embodiments are applicable to this embodiment and can also achieve the same technical effects.

[0186] Embodiments of the present application also provide a computer readable storage medium storing instructions, when the instructions are executed on a computer, the computer executes the method described above. All the implementation manners in the above method embodiments are applicable to this embodiment and can also achieve the same technical effects.

[0187] The above is the preferred embodiment of the present application, it should be noted that for those skilled in the art, without departing from the principles of the present application, can make a number of improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A method for processing electrical energy variable data in charging stations, characterized in that, The method includes: Acquire continuous measurements of voltage, current, and power of the charging device during the charging process, and form a power measurement sequence according to the sampling time order; By performing difference processing on adjacent power measurement values ​​in the power measurement sequence, a power change sequence is obtained; The power change in the power change sequence is traversed and compared one by one to generate a trend determination result. Based on the trend determination result, time segments with consistent trends are identified. The stage boundary is determined by dual verification of the change amplitude and stability of the time segment, and the charging process is divided into multiple charging stages with different power change characteristics. For each charging stage, the power change within the stage is extracted and the distribution characteristic data is statistically obtained. The activity level of power change in the stage is determined by combining the distribution discreteness and change frequency of the power change. The sampling control target and rule set are matched according to the activity level. After calculation correction and boundary constraint verification, the stage sampling control parameters are generated. The stage sampling control parameters include at least the energy variable sampling time interval. In each charging stage, voltage, current and power are sampled in stages according to the corresponding stage sampling control parameters to obtain the energy variable sampling data of the corresponding charging stage. Within each charging stage, based on the energy variable sampling data, the power corresponding to each sampling time interval within the stage is calculated segment by segment of energy, and the segment of energy is accumulated within the stage to obtain the stage energy corresponding to each charging stage. The electrical energy at each stage is summarized and processed to generate the charging electrical energy result corresponding to the charging process.

2. The charging station energy variable data processing method according to claim 1, characterized in that, Based on the power change sequence, the power changes in the sequence are iterated and compared one by one to generate a trend determination result. Based on the trend determination result, time segments with consistent trends are identified. The stage boundaries are determined through dual verification of the amplitude and stability of the time segment changes, dividing the charging process into multiple charging stages with different power change characteristics, including: The power change values ​​in the power change value sequence are traversed one by one, and the current power change value is compared with the previous power change value to generate a trend determination result that characterizes the power change trend. Based on the trend determination results, identify time intervals in which multiple consecutive power changes have the same trend, and generate power change trend interval data. The power change trend segment data is judged by both the change magnitude and the continuous stability. When the power change trend segment changes from a segment whose change magnitude meets the preset stability judgment condition to a segment whose change magnitude meets the preset change judgment condition, the corresponding time position is determined as the stage boundary data. Based on the stage boundary data, the charging process is segmented to generate multiple charging stage data that are distinct from each other in the time dimension and have different power change characteristics.

3. The charging station energy variable data processing method according to claim 1, characterized in that, For each charging stage, the power change within that stage is extracted and its distribution characteristics are statistically analyzed. The activity level of the power change in that stage is determined by combining the dispersion and frequency of the power change distribution. Based on this activity level, a set of sampling control objectives and rules is matched. After calculation, correction, and boundary constraint verification, stage sampling control parameters are generated, including: Extract the power change in each charging stage to generate stage power change data. Statistical processing of the power change data in each stage yields distribution characteristic data that characterizes the degree of concentration of power change over time. Based on the distribution characteristic data, combined with the distribution dispersion and frequency of power change, stage power change activity level data is generated. Based on the stage power change activity level data, the sampling control target and rule set are matched, and the sampling time interval of the power variable is determined after calculation correction and boundary constraint verification to generate stage sampling control parameter data. The stage sampling control parameter data is correlated with the corresponding charging stage, and used as the basis for the control of voltage, current and power sampling within that charging stage.

4. The method for processing electrical energy variable data in charging stations according to claim 1, characterized in that, Within each charging stage, based on the sampled data of electrical energy variables, the power corresponding to each sampling time interval within the stage is calculated segment by segment of electrical energy, and the segmented electrical energy is accumulated within the stage to obtain the stage electrical energy corresponding to each charging stage, including: Acquire the energy variable sampling data corresponding to each charging stage, and sort the energy variable sampling data according to the sampling time order to generate stage sampling sequence data; Based on the sampling time corresponding to adjacent sampling points in the phased sampling sequence data, determine the sampling time interval data formed between adjacent sampling points; For each sampling time interval, obtain the power measurement value corresponding to the starting position of the sampling time interval, and generate power characterization data for the sampling time interval; Based on the power characterization data of the sampling time interval and the duration of the corresponding sampling time interval, determine the interval electrical energy data corresponding to the sampling time interval; According to the sampling time sequence, the interval electrical energy data corresponding to each sampling time interval within the same charging stage are accumulated to generate the stage electrical energy data corresponding to that charging stage.

5. The method for processing electrical energy variable data in charging stations according to claim 2, characterized in that, The power change trend data is evaluated using both the magnitude of change and the stability of the change. When a power change trend segment changes from a segment whose magnitude meets a preset stability criterion to a segment whose magnitude meets a preset change criterion, the corresponding time position is determined as the stage boundary data, including: Based on the power change trend segment data, extract the corresponding power change amount within each power change trend segment to generate segment power change set data. Based on the power change data set of the segment, statistical processing of the change amplitude within each power change trend segment is performed to generate segment change amplitude characterization data to represent the power change amplitude level within the power change trend segment. Based on the segment variation amplitude characterization data, the stability and continuity of the power variation amplitude within the power variation trend segment are evaluated and processed to generate segment stability characterization data for characterizing the stability of the power variation trend segment. The stability characterization data of the section is compared with the preset stability judgment conditions. When the stability characterization data of the section meets the preset stability judgment conditions, stable section identification data is generated. The segment change amplitude representation data is compared with the preset change judgment conditions. When the segment change amplitude representation data meets the preset change judgment conditions, the changed segment identification data is generated. The continuity of stable segment identifier data and changed segment identifier data in time sequence is verified. When stable segment identifier data appears continuously in time dimension and then changed segment identifier data appears continuously, the boundary time position between stable segment and changed segment is determined. The boundary time position is output as stage boundary data to characterize the change in power state.

6. The method for processing electrical energy variable data in charging stations according to claim 3, characterized in that, Based on the distribution characteristic data, combined with the dispersion and frequency of power change, stage power change activity level data is generated, including: Based on the distribution characteristic data, the time distribution of power change during the charging phase is analyzed and processed to generate distribution discreteness characterization data to characterize the degree of dispersion of power change distribution. Based on the discreteness characterization data, the frequency of power change during the charging phase is evaluated and processed to generate frequency characterization data to characterize the frequency of power change. Based on the discreteness characterization data and the frequency characterization data, active state combination data is constructed to characterize the active state of power change, wherein the active state combination data is used to reflect the joint state of power change in two dimensions: time distribution and frequency of change. The active state combination data is processed by state mapping, and the active state combination data is mapped to a preset activity level category to determine the power change activity level category corresponding to the charging stage. Based on the determined category of power change activity, generate stage power change activity level data corresponding to the charging stage.

7. The method for processing electrical energy variable data in charging stations according to claim 3, characterized in that, Based on the stage power change activity level data, the sampling control target and rule set are matched, and after calculation correction and boundary constraint verification, the energy variable sampling time interval is determined, generating stage sampling control parameter data, including: Based on the power change activity level data of the stage, the sampling control target corresponding to the charging stage is determined. The sampling control target is used to characterize the balance requirement between the sampling accuracy of the power variable and the consumption of sampling resources. Based on the sampling control objective, the sampling control rules corresponding to different power change activity levels are filtered to generate a set of sampling control rules that match the current charging stage. Based on the set of sampling control rules, the sampling time interval of electrical energy variables is calculated and corrected to generate candidate sampling time interval data that meet the sampling control objectives; Boundary constraint verification is performed on the candidate sampling time interval data to generate energy variable sampling time interval data that meets the preset sampling time constraint conditions; The sampling time interval data of the electrical energy variable is output as stage sampling control parameter data, and the stage sampling control parameter data is used to control the sampling process of voltage, current and power within the charging stage.

8. A charging station energy variable data processing system, characterized in that, The system, used in any one of claims 1 to 7, comprises: The measurement data acquisition module is used to acquire continuous measurement values ​​of voltage, current and power of the charging device during the charging process, and form a power measurement sequence according to the sampling time order; The power change generation module is used to perform difference processing on adjacent power measurement values ​​in the power measurement sequence to obtain the power change sequence. The charging stage segmentation module is used to traverse and compare the power change in the power change sequence one by one, generate the trend determination result, identify the time segment with a consistent trend based on the trend determination result, determine the stage boundary through the dual verification of the change amplitude and stability of the time segment, and divide the charging process into multiple charging stages with different power change characteristics. The sampling control parameter generation module is used to extract the power change within each charging stage and statistically obtain the distribution characteristic data. It determines the power change activity level of the stage by combining the distribution discreteness and change frequency of the power change. Based on the activity level, it matches the sampling control target and rule set, and generates the stage sampling control parameters after calculation correction and boundary constraint verification. The stage sampling control parameters include at least the energy variable sampling time interval. The phased sampling module is used to sample voltage, current and power in stages according to the corresponding phased sampling control parameters in each charging stage, so as to obtain the energy variable sampling data of the corresponding charging stage. The stage energy calculation module is used to calculate the energy of each segment of power corresponding to each sampling time interval within each charging stage based on the energy variable sampling data, and to accumulate the energy of each segment within the stage to obtain the stage energy corresponding to each charging stage. The electrical energy aggregation module is used to aggregate and process the electrical energy at each stage to generate the charging electrical energy result corresponding to the charging process.

9. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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