Device Performance Evaluation Method and Apparatus, Storage Medium, and Terminal

Abstract

The present invention discloses a device performance evaluation method, device, storage medium, and terminal, which relate to the technical field of intelligent power consumption and metering. The main purpose is to solve the problem that the performance of the indoor charging behavior identification device for electric vehicles cannot be evaluated. It mainly includes obtaining first measurement data and second measurement data, where the first measurement data is the actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is the load parameters measured by the device to be evaluated according to each preset charging stage; determining the identification difference degree between the first measurement data and the second measurement data; correcting the identification difference degree based on a penalty coefficient and a superimposed electrical appliance weight coefficient to determine the performance evaluation result of the device to be evaluated. It is mainly used for the performance evaluation of the indoor charging behavior identification device for electric vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent power consumption and metering, and particularly to a method and device for evaluating equipment performance, a storage medium, and a terminal. Background Art

[0002] An electric vehicle, also known as a "battery car", is a pure electric vehicle powered by a battery (electric battery) and driven by an electric motor (DC, AC, series excitation, shunt excitation). Electric vehicles have the advantages of low operation and maintenance costs, environmental protection, and convenient parking. However, due to the weak safety awareness of residents and the lack of community supervision means, users continuously charge the battery cars indoors at night for a long time, which may cause overcharging of the battery, resulting in heat swelling, spontaneous combustion or explosion, and electrical fires.

[0003] In order to supervise the indoor charging behavior of electric vehicles, some enterprises have launched devices that can identify the indoor charging behavior of electric vehicles. Such devices collect the current and voltage data at the incoming line end of the electricity meter of power users and use non-intrusive load identification technology to accurately identify the indoor charging behavior of electric vehicles. However, there is currently no evaluation method for evaluating the performance of devices for identifying the indoor charging behavior of electric vehicles, so it is impossible to meet the need to know the device performance status and carry out technical improvements based on the device performance status. Summary of the Invention

[0004] In view of this, the present invention provides a method and device for evaluating equipment performance, a storage medium, and a terminal, mainly aiming to solve the problem that the performance of devices for identifying the indoor charging behavior of electric vehicles cannot be evaluated.

[0005] According to one aspect of the present invention, a method for evaluating equipment performance is provided, including:

[0006] Obtaining first measurement data and second measurement data, where the first measurement data is the actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is the load parameters measured by the device to be evaluated according to each preset charging stage;

[0007] Determining the identification difference degree between the first measurement data and the second measurement data;

[0008] Based on a penalty coefficient and a superimposed electrical appliance weight coefficient, correcting the identification difference degree to determine the performance evaluation result of the device to be evaluated.

[0009] Further, the preset charging stages include a first charging amount stage, a second charging amount stage, a third charging amount stage, a constant current stage, a constant voltage stage, and a trickle charging stage;

[0010] Among them, the charging amount in the third charging amount stage is greater than the charging amount in the second charging amount stage, and the charging amount in the second charging amount stage is greater than the charging amount in the first charging amount stage.

[0011] Further, before obtaining the first measurement data and the second measurement data, the method further includes:

[0012] Obtain load parameter information, where the load parameter information includes electrical appliance type, start time, stop time, and power consumption;

[0013] Use the standard device to measure the actual values of the start time, the stop time, and the power consumption in each preset charging stage, and obtain the preset value of the electrical appliance type. Determine the first measurement data based on the actual values of the start time, the stop time, the power consumption, and the preset value of the electrical appliance type;

[0014] Use the device to be evaluated to measure the measured values of the electrical appliance type, the start time, the stop time, and the power consumption in each preset charging stage, and obtain the second measurement data.

[0015] Further, the using the device to be evaluated to measure the measured value of the electrical appliance type in each preset charging stage includes:

[0016] When the device to be evaluated detects that the charging electrical appliance is an electric vehicle, determine that the measured value of the electrical appliance type is 1;

[0017] When the device to be evaluated detects that the charging electrical appliance is not an electric vehicle, determine that the measured value of the electrical appliance type is 0.

[0018] Further, the correcting the identification difference degree based on the penalty coefficient and the superimposed electrical appliance weight coefficient to determine the performance evaluation result of the device to be evaluated includes:

[0019] Calculate the product of the identification difference degree in each preset charging stage and the reciprocal of the corresponding penalty coefficient, and calculate the identification accuracy based on the result of the product;

[0020] Determine the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient, where the superimposed electrical appliance weight coefficient is determined according to the superimposed electrical appliance types and the number of electrical appliances.

[0021] Further, the determining the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient includes:

[0022] Obtain a performance value by calculating the product of the identification accuracy and the superimposed electrical appliance weight coefficient;

[0023] Match the performance value with a preset performance comparison parameter to determine the performance evaluation result of the device to be evaluated.

[0024] Further, the determining the identification difference degree between the first measurement data and the second measurement data includes:

[0025] Determine a first measurement vector corresponding to the first measurement data and a second measurement vector corresponding to the second measurement data;

[0026] Determine the identification difference degree by calculating the similarity between the first measurement vector and the second measurement vector.

[0027] According to another aspect of the present invention, there is provided a device performance evaluation apparatus, including:

[0028] An acquisition module, configured to acquire first measurement data and second measurement data, where the first measurement data is actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is load parameters measured by the device to be evaluated according to each preset charging stage;

[0029] A first determination module, configured to determine the identification difference degree between the first measurement data and the second measurement data;

[0030] A second determination module, configured to correct the identification difference degree based on a penalty coefficient and a superimposed electrical appliance weight coefficient to determine the performance evaluation result of the device to be evaluated.

[0031] Further, the acquisition module is specifically configured to the preset charging stage includes a first charging amount stage, a second charging amount stage, a third charging amount stage, a constant current stage, a constant voltage stage, and a trickle charging stage;

[0032] Wherein, the charging amount in the third charging amount stage is greater than the charging amount in the second charging amount stage, and the charging amount in the second charging amount stage is greater than the charging amount in the first charging amount stage.

[0033] Further, the apparatus further includes: a first measurement module, a second measurement module

[0034] The acquisition module: is further configured to acquire load parameter information, where the load parameter information includes electrical appliance type, start time, stop time, and power consumption;

[0035] The first measurement module: is used to measure the start time, the stop time, and the actual value of the power consumption in each preset charging stage by using the standard device, and obtain the preset value of the electrical appliance type, and determine the first measurement data based on the start time, the stop time, the actual value of the power consumption, and the preset value of the electrical appliance type;

[0036] The second measurement module: is used to measure the measured values of the electrical appliance type, the start time, the stop time, and the power consumption in each preset charging stage by using the device to be evaluated, and obtain the second measurement data.

[0037] Further, the second measurement module includes:

[0038] The first determination unit: is used to determine that the measured value of the electrical appliance type is 1 when the device to be evaluated detects that the charging electrical appliance is an electric vehicle;

[0039] The second determination unit: is used to determine that the measured value of the electrical appliance type is 0 when the device to be evaluated detects that the charging electrical appliance is not an electric vehicle.

[0040] Further, the second determination module includes:

[0041] The first calculation unit: is used to calculate the product of the identification difference degree in each preset charging stage and the reciprocal of the corresponding penalty coefficient, and calculate the identification accuracy based on the result of the product;

[0042] The second calculation unit: is used to determine the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient, where the superimposed electrical appliance weight coefficient is determined according to the superimposed electrical appliance type and the number of electrical appliances.

[0043] Further, the second calculation unit is specifically used for:

[0044] Obtaining a performance value by calculating the product of the identification accuracy and the superimposed electrical appliance weight coefficient;

[0045] Matching the performance value with a preset performance comparison parameter to determine the performance evaluation result of the device to be evaluated.

[0046] Further, the first determination module includes:

[0047] The third determination unit: is used to determine the first measurement vector corresponding to the first measurement data and the second measurement vector corresponding to the second measurement data;

[0048] A fourth determination unit, configured to determine an identification difference degree by calculating a similarity between the first measurement vector and the second measurement vector.

[0049] According to another aspect of the present invention, there is provided a storage medium storing at least one executable instruction, and the executable instruction causes a processor to perform operations corresponding to the above device performance evaluation method.

[0050] According to still another aspect of the present invention, there is provided a terminal including: a processor, a memory, a communication interface, and a communication bus, and the processor, the memory, and the communication interface complete communication with each other through the communication bus;

[0051] The memory is configured to store at least one executable instruction, and the executable instruction causes the processor to perform operations corresponding to the above device performance evaluation method.

[0052] By means of the above technical solutions, the technical solutions provided by the embodiments of the present invention have at least the following advantages:

[0053] The present invention provides a device performance evaluation method, device, storage medium, and terminal. In the embodiments of the present invention, first measurement data and second measurement data are obtained, where the first measurement data is actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is load parameters measured by a device to be evaluated according to each preset charging stage; an identification difference degree between the first measurement data and the second measurement data is determined; the identification difference degree is corrected based on a penalty coefficient and a superimposed electrical appliance weight coefficient to determine a performance evaluation result of the device to be evaluated, filling a blank in the field of device performance evaluation for indoor charging behavior identification of electric vehicles. At the same time, the accuracy of device performance evaluation is ensured, so as to meet the need to know the performance level of the device for indoor charging behavior identification of electric vehicles and to technically improve the device performance based on the identification device performance level.

[0054] The above description is only an overview of the technical solutions of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are specifically described below. Brief Description of the Drawings

[0055] By reading the detailed description of the preferred embodiments below, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0056] Figure 1Shows a flowchart of a device performance evaluation method provided by an embodiment of the present invention;

[0057] Figure 2 Shows a flowchart of another device performance evaluation method provided by an embodiment of the present invention;

[0058] Figure 3 Shows a schematic diagram of a preset charging stage division method provided by an embodiment of the present invention;

[0059] Figure 4 Shows a block diagram of the composition of another device performance evaluation device provided by an embodiment of the present invention;

[0060] Figure 5 Shows a schematic diagram of the structure of a terminal provided by an embodiment of the present invention. Detailed implementation manners

[0061] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0062] In view of the problem that there is currently no evaluation method for identifying the performance of electric vehicle indoor charging behavior identification devices, which cannot meet the need to know the performance status of the devices and to improve and enhance the device performance. An embodiment of the present invention provides a device performance evaluation method, as Figure 1 shown, the method includes:

[0063] 101. Obtain first measurement data and second measurement data.

[0064] In an embodiment of the present invention, the object of performance evaluation is a device for identifying electric vehicle indoor charging behavior. Since such a device discriminates the charging behavior of an electric vehicle battery based on the characteristics of the load parameters in each stage of the electric vehicle battery charging process, the evaluation of the device performance is the evaluation of the accuracy of the load parameter measurement of the device in each charging stage. Therefore, when evaluating the performance of the device to be evaluated, it is necessary to obtain the load parameters measured by the device to be evaluated in each preset charging stage, that is, the second measurement data, and the actual load parameters used as reference data, that is, the first measurement data. The actual load parameters are measured by a standard device, and the standard device here can be a precision instrument such as an oscillograph dedicated to measuring load parameters. The embodiment of the present invention does not make specific limitations.

[0065] It should be noted that the first measurement data and the second measurement data are load parameters measured according to different preset charging stages. For example, when there are three preset charging stages of 20% - 40% of the charge amount, 40% - 60% of the charge amount, and 60% - 80% of the charge amount, the first measurement data includes the load parameters of 20% - 40% of the charge amount, 40% - 60% of the charge amount, and 60% - 80% of the charge amount collected by the oscillograph; the second measurement data includes the load parameters of 20% - 40% of the charge amount, 40% - 60% of the charge amount, and 60% - 80% of the charge amount measured by the device to be evaluated. In the embodiments of the present invention, no specific limitation is made to the above numerical segments, and they can be set according to the configuration of technicians. Since the measurement difficulty of the load parameters in different charging stages of the electric vehicle battery is different. Therefore, based on the load parameters measured by the device to be evaluated in different charging stages as the basis for evaluating the device performance, it can more comprehensively and accurately reflect the performance of the device to be evaluated, thereby improving the accuracy of the device performance evaluation.

[0066] 102. Determine the identification difference degree between the first measurement data and the second measurement data.

[0067] In the embodiments of the present invention, in order to evaluate the performance of the indoor charging behavior identification device for electric vehicles, a scenario of indoor charging of electric vehicles is simulated. The electric vehicle battery or the electric vehicle battery and other types of household appliances, such as variable frequency air conditioners, rice cookers, and electric water heaters, can be connected only to the load end of the electric meter, and the load parameters are measured by the standard device and the device to be evaluated respectively. The result measured by the standard device is used as the actual load parameter to judge the accuracy of the load parameter measurement value displayed by the device to be evaluated. In addition, it is also possible to choose not to connect the electric vehicle battery to the load end of the electric meter to test whether the device to be evaluated will give false alarms.

[0068] In the embodiments of the present invention, since the load parameters measured by the device to be evaluated are the data basis for the device to be evaluated to identify the charging behavior of the electric vehicle, in order to determine the performance of the device to be evaluated, it is necessary to calculate the identification difference degree between the load parameters measured by the device to be evaluated and the actual load parameters measured by the standard device in each preset charging stage according to the obtained first measurement data and second measurement data, so as to determine the measurement accuracy of the load parameters of the device to be evaluated for each preset charging stage. The smaller the difference degree between the load parameters of each preset charging stage measured by the device to be evaluated and the actual load parameters measured by the standard device, the more accurately the device to be evaluated can obtain the characteristics of the load parameters of each preset charging stage, and thus more accurately identify whether the electric vehicle battery is included in the electrical appliances generating the electrical load.

[0069] It should be noted that in the process of calculating the identification difference degree between the first measurement data and the second measurement data, the identification difference degree between the measured load parameter and the actual load parameter is calculated for each preset charging stage respectively. Since the power change characteristics are different in different preset charging stages, the identification difference degree for each preset charging stage can be used to more accurately evaluate the identification ability of the device to be evaluated, thereby effectively improving the accuracy of device performance evaluation.

[0070] 103. Modify the identification difference degree based on the penalty coefficient and the determined superposition electrical appliance weight coefficient, and determine the performance evaluation result of the device to be evaluated.

[0071] In the embodiment of the present invention, in order to further accurately evaluate the performance of the device to be evaluated, the identification difference degrees of each preset charging stage obtained are modified by using the penalty coefficient to correct the influence of different identification difficulties in different preset charging stages on the identification difference degree, and the correction result of the penalty coefficient is corrected by using the superposition electrical appliance weight coefficient to cope with the situation that there are other types of electrical appliances in addition to the electric vehicle battery in the electrical load. For example, if the load parameters measured by the device to be evaluated include the load parameters corresponding to the variable-frequency air conditioner and the electric vehicle battery, the variable-frequency air conditioner is the superposition electrical appliance, and the weight coefficient corresponding to the variable-frequency air conditioner needs to be used to correct the identification difference degree. Further, according to the identification difference degree corrected by the penalty coefficient and the superposition electrical appliance weight coefficient, the performance evaluation result of the device to be evaluated is determined.

[0072] It should be noted that the penalty coefficient can be custom-set for different charging stages. Based on the different identification difficulties in different charging stages, adding corresponding weight coefficients (penalty coefficients) to the identification difference degrees of each charging stage can improve the accuracy of the evaluation of the identification ability of the device to be evaluated. In addition, in the actual application scenario, it is impossible to rule out the simultaneous use of other types of electrical equipment and the electric vehicle battery. Adding the superposition electrical appliance weight coefficient can compensate for the influence of other types of electrical equipment on the identification accuracy of the identification device, thereby further improving the accuracy of the evaluation of the identification ability of the device to be evaluated.

[0073] In an embodiment of the present invention, for further illustration and limitation, the preset charging stage in step 101 includes:

[0074] The first charge amount stage, the second charge amount stage, the third charge amount stage, the constant current stage, the constant voltage stage, and the trickle charge stage; wherein, the charge amount in the third charge amount stage is greater than the charge amount in the second charge amount stage, and the charge amount in the second charge amount stage is greater than the charge amount in the first charge amount stage.

[0075] In the embodiments of the present invention, in order to more accurately evaluate the performance of the indoor charging behavior identification device for electric vehicles, the battery charging process is pre-divided into multiple charging stages, and the device to be evaluated is evaluated according to the measurement data of the load parameters in each charging stage. The preset charging stages at least include a first charging amount stage, a second charging amount stage, a third charging amount stage, a constant current stage, a constant voltage stage, and a trickle stage. Among them, the constant current stage, the constant voltage stage, and the trickle stage are three representative stages in the process of electric vehicle battery charging where the power changes with the charging time, and these three stages cover the whole process of electric vehicle battery charging; the first charging amount stage, the second charging amount stage, and the third charging amount stage are set according to specific device performance evaluation requirements. The charging amount of the third charging amount stage is greater than that of the second charging amount stage, and the charging amount of the second charging amount stage is greater than that of the first charging amount stage. Among them, the lower limit charging amount of the first charging amount stage can be 0%, or 10%, 20%, etc., and the upper limit charging amount of the charging amount of the third charging amount stage can be 100%, or 90%, 80%, etc., and the charging amount ranges of each charging amount stage can be equal or unequal. For example, the first charging amount stage is 10% - 30%, the second charging amount stage is 30% - 50%, and the third charging amount stage is 50% - 80%. The embodiments of the present invention do not make specific limitations. In a charging stage division method in a specific application scenario, as Figure 3 shown, the preset charging stages include a constant current stage, a constant voltage stage, a trickle stage, and three charging amount stages of 20% - 40%, 40% - 60%, and 60% - 80%.

[0076] It should be noted that on the basis of dividing the charging stages according to the characteristics of the power change with the charging time, dividing the charging stages according to the charging amount of the electric vehicle battery can obtain the change situation of the load parameters during the charging process from another angle. In addition, through a more detailed division of the charging stages and increasing redundant load parameters, more sufficient data references can be provided for subsequent data analysis and calculation, thereby effectively improving the accuracy of device performance evaluation.

[0077] In an embodiment of the present invention, for further illustration and limitation, as Figure 2 shown, the device performance evaluation method includes:

[0078] 201. Obtain load parameter information.

[0079] 202. Use the standard device to measure the start time, the stop time, and the actual value of the power consumption in each preset charging stage, and obtain the preset value of the electrical appliance type. Based on the start time, the stop time, the actual value of the power consumption, and the preset value of the electrical appliance type, determine the first measurement data.

[0080] 203. Use the device to be evaluated to measure the measured values of the electrical appliance type, start time, stop time, and power consumption in each preset charging stage, and obtain second measurement data.

[0081] In an embodiment of the present invention, in order to evaluate the performance of the device to be evaluated, it is necessary to set corresponding load parameter information according to the load parameter basis and recognition result for identifying the indoor charging behavior of electric vehicles by the current device. The load parameter information represents the type of load parameters that need to be used as the basis for device evaluation, and at least includes the electrical appliance type, start time, stop time, and power consumption. For example, if the device to be evaluated identifies the indoor charging behavior of electric vehicles based on the start time, stop time, and power consumption, and outputs a judgment result on the type of load electrical appliance, the set load parameter information includes the electrical appliance type, start time, stop time, and power consumption. Further, based on the type of load parameters that need to be collected indicated by the collected load parameter information, use a standard device to collect the actual data of the load parameters, and use the device to be evaluated to collect the measured data of the load parameters. Since in the process of using a standard device to measure the load parameters in each preset stage, the standard device can only collect the data of the load parameters and does not have the ability to identify the load electrical appliance, the actual value of the electrical appliance type in the first measurement data needs to be set according to the current actual load situation. For example, if the actual load electrical appliance includes an electric vehicle, the preset value of the electrical appliance type is 1; if the actual load electrical appliance does not include an electric vehicle, the preset value of the electrical appliance type is 0.

[0082] In an embodiment of the present invention, for further illustration and limitation, the measurement of the measured value of the electrical appliance type in each preset charging stage by using the device to be evaluated in step 203 includes:

[0083] When the device to be evaluated detects that the charging electrical appliance is an electric vehicle, determine that the measured value of the electrical appliance type is 1; when the device to be evaluated detects that the charging electrical appliance is not an electric vehicle, determine that the measured value of the electrical appliance type is 0.

[0084] In an embodiment of the present invention, the electrical appliance type is the recognition result of the device to be evaluated. If the device to be evaluated recognizes that the current electrical load includes an electric vehicle battery, assign the measured value of the electrical appliance type to 1; if the recognition result of the device to be evaluated indicates that the current electrical load does not include an electric vehicle battery, assign the measured value of the electrical appliance type to 0.

[0085] 204. Obtain the first measurement data and the second measurement data.

[0086] 205. Determine a first measurement vector corresponding to the first measurement data and a second measurement vector corresponding to the second measurement data.

[0087] 206. Determine the identification difference degree by calculating the similarity between the first measurement vector and the second measurement vector.

[0088] In the embodiments of the present invention, in order to evaluate the accuracy of the load parameters measured by the device to be evaluated, the first measurement data and the second measurement data need to be respectively represented in vector form, and the similarity is calculated based on the first measurement vector and the second measurement vector. The calculation of the similarity can use similarity calculation methods such as Mahalanobis distance, cosine similarity, and Euclidean distance, and the embodiments of the present invention do not make specific limitations. Taking the Mahalanobis distance as an example below, the process of calculating the similarity between the first measurement vector and the second measurement vector is described in detail, specifically including:

[0089] 1) Convert the obtained actual values of the electrical appliance type, start time, stop time, and power consumption into vector form, and represent them as y1, y2, y3, and y4 in sequence. Convert the measured values of the electrical appliance type, start time, stop time, and power consumption into vector form, and represent them as x1, x2, x3, and x4 in sequence. Then the first measurement vector is represented as y = (y1, y2, y3, y4) 2 , and the second measurement vector is represented as x = (x1, x2, x3, x4) T ;

[0090] 2) Calculate the mean vectors of the first measurement vector and the second measurement vector. The formula is:

[0091]

[0092] 3) Calculate the expectations E(y) of the first measurement vector y and E(x) of the second measurement vector x respectively. The formula is:

[0093]

[0094] 4) Calculate the covariance according to the expectations of the first measurement vector and the second measurement vector. The formula is:

[0095] Cov(x, y) = E((x - E(x))(y - E(y))) (4);

[0096] Then the covariance matrix is:

[0097]

[0098] The inverse covariance matrix is: ∑ -1 = ((Cov(x, y)) 4×4 ) -1 (6);

[0099] 5) Calculate the Mahalanobis distance D(x) between the first measurement vector and the second measurement vector. The formula is as follows:

[0100] Furthermore, determine the identification difference degree R according to the Mahalanobis distance D(x). The value range of R is [0, 1]. When D(x) is greater than 1, the value of R is 1; when D(x) is less than 0, the value of R is 0.

[0101] 207. Calculate the product of the identification difference degree of each of the preset charging stages and the reciprocal of the corresponding penalty coefficient, and calculate the identification accuracy based on the result of the product.

[0102] In the embodiment of the present invention, since the identification difficulty of each preset charging stage for the electric vehicle is different, the penalty coefficient is used to attach corresponding weights to the identification difference degrees of each preset charging stage to achieve a punitive correction of the identification difference degrees. Among them, the penalty coefficient is customarily set according to the identification difficulty of each preset charging stage based on test experience, and is denoted as α. According to the identification difference degree R of each preset charging stage and the penalty coefficient α of the corresponding preset charging stage, calculate the initial identification accuracy of each preset charging stage, denoted as T. The formula is as follows:

[0103] According to the initial identification accuracies of each preset charging stage, use the trimmed mean method to calculate the final identification accuracy T0, that is, ignore the maximum value and the minimum value in the initial identification accuracies, and calculate the average value of the remaining initial identification accuracies as the final identification accuracy T0.

[0104] It should be noted that by attaching corresponding weights to the identification difference degrees of each preset charging stage through the penalty coefficient, the differences in the identification difficulties of different preset charging stages for the electric vehicle are fully considered, avoiding the influence of the different identification difficulties of different preset charging stages on the accuracy of equipment evaluation, and further improving the accuracy of the identification accuracy by processing the initial identification accuracies of each preset charging stage through the trimmed mean method, thereby effectively improving the accuracy of equipment performance evaluation.

[0105] 208. Determine the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient.

[0106] In an embodiment of the present invention, for further illustration and limitation, determining the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient in step 208 includes: obtaining a performance value by calculating the product of the identification accuracy and the superimposed electrical appliance weight coefficient; and determining the performance evaluation result of the device to be evaluated according to the matching between the performance value and a preset performance comparison parameter.

[0107] In an embodiment of the present invention, since in an actual application scenario, there is a situation where multiple electrical appliances are used in a superimposed manner in the indoor electrical load of electricity users, therefore, the superimposed electrical appliance weight coefficient C is used to further correct the obtained identification accuracy T0 to obtain a performance value, denoted as S. The formula is: S = CT0 (9); where the value range of the performance value is [0, 100], the superimposed electrical appliance weight coefficient C is the sum of the weight coefficients corresponding to the types of electrical appliances used in superimposition with the electric vehicle battery in the same time period, and the weight coefficient corresponding to each type of electrical appliance is customarily set based on the test experience of the power change during the operation of different household electrical appliances. For example, if the electrical appliance used in superimposition is a variable-frequency air conditioner and the weight coefficient of the variable-frequency air conditioner is 1.1, then the superimposed electrical appliance weight coefficient is 1.1. Another example is that the electrical appliances used in superimposition are a variable-frequency air conditioner and a washing machine, the weight coefficient of the variable-frequency air conditioner is 1.1, and the weight coefficient of the washing machine is 1.2, then the superimposed electrical appliance weight coefficient is 2.3. When there are no electrical appliances used in superimposition, the superimposed electrical appliance weight coefficient is 1.

[0108] Furthermore, in order to make the device performance evaluation result more standardized and clear, an identification ability level for the indoor charging behavior of electric vehicles is set, that is, the identification ability of the indoor charging behavior identification device for electric vehicles is divided into several levels, and each level corresponds to a different performance index range. For example, a performance value of 90 - 100 corresponds to an excellent identification ability level, and a performance value of 80 - 90 corresponds to a good identification ability level. If the calculated performance value of the device to be evaluated is 87, then the performance evaluation result of the device is determined to be good.

[0109] It should be noted that by further correcting the identification accuracy through the superimposed electrical appliance weight coefficient, the situation where there are multiple electrical appliances in the electrical load in the actual application scenario is included in the evaluation scope, ensuring that the performance of the device to be evaluated can still be accurately evaluated when there is not only one electrical load of the electric vehicle, thus ensuring the comprehensiveness of the performance evaluation of the device to be evaluated. At the same time, the applicable range of the evaluation method is greatly expanded, and the applicability of the evaluation method is improved.

[0110] In the embodiments of the present invention, for further illustration and limitation, a method for evaluating the performance of a device in a certain actual application scenario is described. Among them, the charging stage includes a constant current stage, a constant voltage stage, a trickle charging stage, and six charging stages of 20% - 40% of the charging amount, 40% - 60% of the charging amount, and 60% - 80% of the charging amount; the load parameter information includes the type of electrical appliance, start time, stop time, and power consumption; there is only an electric vehicle in the electrical load without other superimposed electrical appliances, specifically including:

[0111] 1. Obtain the actual values of the load parameters in each charging stage recorded by the oscillograph, as shown in Table (1), and the measured values of the load parameters output by the device to be evaluated in each charging stage, as shown in Table (2).

[0112] Table (1):

[0113]

[0114]

[0115] Table (2):

[0116]

[0117] 2. Calculate the identification difference degree R in each charging stage according to the actual values and measured values of the load parameters, as shown in Table (3).

[0118] Table (3):

[0119] Charging stage Recognition difference degree R Constant current 0.0112 Constant voltage 0.0468 Trickle 0.0833 Charge amount 20%-40% 0.0295 Charge amount 40%-60% 0.0664 Charge amount 60%-80% 0.1185

[0120] 3. Obtain the penalty coefficient corresponding to each charging stage, as shown in Table (4), and calculate the accuracy T according to the identification difference degree R and the penalty coefficient α in each charging stage, as shown in Table (5).

[0121] Table (4):

[0122]

[0123]

[0124] Table (5):

[0125] Charging stage Accuracy T Constant current 89.89 Constant voltage 88.26 Trickle 86.48 Charge amount 20%-40% 89.04 Charge amount 40%-60% 87.25 Charge amount 60%-80% 83.95

[0126] 4. Calculate the comprehensive accuracy T0 by using the trimmed mean method.

[0127] 5. Obtain the superposition electrical appliance weight coefficient as shown in Table (6), and calculate the performance value S according to the superposition electrical appliance weight coefficient C: S = C × T0 = 1 × 87.76 = 87.76.

[0128] Table (6):

[0129] Superimposed electrical appliance types C Frequency conversion air conditioner 1.1 Rice cooker 1.15 Electric water heater 1.18 Washing machine 1.2 None 1.0

[0130] 6. Obtain the identification ability level as shown in Table (7), match according to the performance value S and the identification ability level, and determine that the performance level of the evaluated electric vehicle indoor charging behavior identification device is good.

[0131] Table (7):

[0132]

[0133]

[0134] The present invention provides a method for evaluating the performance of a device. In the embodiments of the present invention, by obtaining first measurement data and second measurement data, the first measurement data is the actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is the load parameters measured by the device to be evaluated according to each preset charging stage; determining the identification difference degree between the first measurement data and the second measurement data; correcting the identification difference degree based on a penalty coefficient and a superposition electrical appliance weight coefficient to determine the performance evaluation result of the device to be evaluated, filling the blank in the field of performance evaluation of electric vehicle indoor charging behavior identification devices. At the same time, it ensures the accuracy of device performance evaluation, thereby meeting the need to know the performance level of electric vehicle indoor charging behavior identification devices and technically improving the device performance based on the performance level of the identification device.

[0135] Further, as an implementation of the above Figure 1 method, the embodiments of the present invention provide a device performance evaluation device, as Figure 4 shown, the device includes:

[0136] An acquisition module 31, configured to acquire first measurement data and second measurement data, where the first measurement data is the actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is the load parameters measured by the device to be evaluated according to each preset charging stage;

[0137] A first determination module 32, configured to determine the identification difference degree between the first measurement data and the second measurement data;

[0138] A second determination module 33, configured to correct the identification difference degree based on a penalty coefficient and a superposition electrical appliance weight coefficient to determine the performance evaluation result of the device to be evaluated.

[0139] Further, the obtaining module is specifically configured such that the preset charging stage includes a first charge amount stage, a second charge amount stage, a third charge amount stage, a constant current stage, a constant voltage stage, and a trickle charge stage;

[0140] Wherein, the charge amount in the third charge amount stage is greater than the charge amount in the second charge amount stage, and the charge amount in the second charge amount stage is greater than the charge amount in the first charge amount stage.

[0141] Further, the device further includes: a first measurement module and a second measurement module

[0142] The obtaining module: is further configured to obtain load parameter information, where the load parameter information includes electrical appliance type, start time, stop time, and power consumption;

[0143] The first measurement module: is configured to measure the actual values of the start time, the stop time, and the power consumption in each of the preset charging stages by using the standard device, and obtain a preset value of the electrical appliance type, and determine first measurement data based on the actual values of the start time, the stop time, the power consumption, and the preset value of the electrical appliance type;

[0144] The second measurement module: is configured to measure the measured values of the electrical appliance type, the start time, the stop time, and the power consumption in each of the preset charging stages by using the device to be evaluated, and obtain second measurement data.

[0145] Further, the second measurement module includes:

[0146] A first determination unit, configured to determine that the measured value of the electrical appliance type is 1 when the device to be evaluated detects that the charging electrical appliance is an electric vehicle;

[0147] A second determination unit, configured to determine that the measured value of the electrical appliance type is 0 when the device to be evaluated detects that the charging electrical appliance is not an electric vehicle.

[0148] Further, the second determination module includes:

[0149] A first calculation unit, configured to calculate the product of the identification difference degree in each of the preset charging stages and the reciprocal of the corresponding penalty coefficient, and calculate the identification accuracy based on the result of the product;

[0150] A second calculation unit, configured to determine the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient, where the superimposed electrical appliance weight coefficient is determined according to the superimposed electrical appliance types and the number of electrical appliances.

[0151] Further, the second calculation unit is specifically configured to:

[0152] Obtain a performance value by calculating the product of the identification accuracy and the superimposed electrical appliance weight coefficient;

[0153] Match the performance value with a preset performance comparison parameter to determine the performance evaluation result of the device to be evaluated.

[0154] Further, the first determination module includes:

[0155] A third determination unit for determining a first measurement vector corresponding to the first measurement data and a second measurement vector corresponding to the second measurement data;

[0156] A fourth determination unit for determining an identification difference degree by calculating the similarity between the first measurement vector and the second measurement vector.

[0157] The present invention provides a device performance evaluation apparatus. In an embodiment of the present invention, by obtaining first measurement data and second measurement data, where the first measurement data is the actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is the load parameters measured by the device to be evaluated according to each preset charging stage; determining the identification difference degree between the first measurement data and the second measurement data; correcting the identification difference degree based on a penalty coefficient and a superimposed electrical appliance weight coefficient to determine the performance evaluation result of the device to be evaluated, filling the blank in the field of device performance evaluation for electric vehicle indoor charging behavior identification. At the same time, it ensures the accuracy of device performance evaluation, thereby meeting the requirement of knowing the performance level of the electric vehicle indoor charging behavior identification device and technically improving the device performance based on the identification device performance level.

[0158] According to an embodiment of the present invention, a storage medium is provided, and the storage medium stores at least one executable instruction, and the computer executable instruction can execute the data query method in any of the above method embodiments.

[0159] Figure 5 FIG. shows a schematic structural diagram of a terminal according to an embodiment of the present invention. The specific implementation of the terminal is not limited in the specific embodiments of the present invention.

[0160] As Figure 5 shown, the terminal may include: a processor 402, a communication interface 404, a memory 406, and a communication bus 408.

[0161] Among them: The processor 402, the communication interface 404, and the memory 406 communicate with each other through the communication bus 408.

[0162] The communication interface 404 is used to communicate with network elements of other devices such as clients or other servers.

[0163] The processor 402 is used to execute the program 410, and specifically can execute the relevant steps in the embodiment of the above device performance evaluation method.

[0164] Specifically, the program 410 may include program code, and the program code includes computer operation instructions.

[0165] The processor 402 may be a central processing unit (CPU), or a specific integrated circuit (ASIC) (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention. One or more processors included in the terminal may be of the same type of processor, such as one or more CPUs; or may be of different types of processors, such as one or more CPUs and one or more ASICs.

[0166] The memory 406 is used to store the program 410. The memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0167] The program 410 is specifically used to cause the processor 402 to perform the following operations:

[0168] Obtain first measurement data and second measurement data, where the first measurement data is the actual load parameter measured by the standard device according to each preset charging stage, and the second measurement data is the load parameter measured by the device to be evaluated according to each preset charging stage;

[0169] Determine the identification difference degree between the first measurement data and the second measurement data;

[0170] Based on the penalty coefficient and the superimposed electrical appliance weight coefficient, correct the identification difference degree, and determine the performance evaluation result of the device to be evaluated.

[0171] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. Optionally, they can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a sequence different from that here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module for implementation. In this way, the present invention is not limited to any specific combination of hardware and software.

[0172] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for evaluating device performance, characterized in that, Including: Obtain first measurement data and second measurement data, where the first measurement data is the actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is the load parameters measured by a device to be evaluated according to each preset charging stage. The preset charging stages include a first charge amount stage, a second charge amount stage, a third charge amount stage, a constant current stage, a constant voltage stage, and a trickle charge stage; Determine the identification difference degree between the first measurement data and the second measurement data, including: determining a first measurement vector corresponding to the first measurement data and a second measurement vector corresponding to the second measurement data; determining the identification difference degree by calculating the similarity between the first measurement vector and the second measurement vector; Based on a penalty coefficient and a superimposed electrical appliance weight coefficient, correct the identification difference degree to determine the performance evaluation result of the device to be evaluated, specifically including: Calculate the product of the identification difference degree of each preset charging stage and the reciprocal of the corresponding penalty coefficient, and calculate the initial identification accuracy of each preset charging stage based on the result of the product, and calculate the final identification accuracy according to the initial identification accuracies of each preset charging stage; determine the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient; where the superimposed electrical appliance weight coefficient is determined according to the type and quantity of superimposed electrical appliances.

2. The method according to claim 1, wherein The charge amount in the third charge amount stage is greater than the charge amount in the second charge amount stage, and the charge amount in the second charge amount stage is greater than the charge amount in the first charge amount stage.

3. The method according to claim 1, wherein Before obtaining the first measurement data and the second measurement data, the method further includes: Obtain load parameter information, where the load parameter information includes electrical appliance type, start time, stop time, and power consumption; Use the standard device to measure the actual values of the start time, the stop time, and the power consumption in each preset charging stage, and obtain the preset value of the electrical appliance type, and determine the first measurement data based on the actual values of the start time, the stop time, the power consumption, and the preset value of the electrical appliance type; Use the device to be evaluated to measure the measured values of the electrical appliance type, the start time, the stop time, and the power consumption in each preset charging stage to obtain the second measurement data.

4. The method according to claim 3, characterized in that, The measurement of the measured value of the electrical appliance type in each preset charging stage by using the device to be evaluated includes: When the device to be evaluated detects that the charging electrical appliance is an electric vehicle, determine that the measured value of the electrical appliance type is 1; When the device to be evaluated detects that the charging electrical appliance is not an electric vehicle, determine that the measured value of the electrical appliance type is 0.

5. The method according to claim 1, wherein The determination of the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient includes: Obtain a performance value by calculating the product of the identification accuracy and the superimposed electrical appliance weight coefficient; Match the performance value with a preset performance comparison parameter to determine the performance evaluation result of the device to be evaluated.

6. An apparatus for evaluating device performance, characterized in that, Including: An acquisition module, configured to acquire first measurement data and second measurement data, where the first measurement data is the actual load parameters measured by a standard device according to each preset charging stage, and the second measurement data is the load parameters measured by a device to be evaluated according to each preset charging stage. The preset charging stages include a first charge amount stage, a second charge amount stage, a third charge amount stage, a constant current stage, a constant voltage stage, and a trickle charge stage; A first determination module, configured to determine the identification difference degree between the first measurement data and the second measurement data, including: determining a first measurement vector corresponding to the first measurement data and a second measurement vector corresponding to the second measurement data; determining the identification difference degree by calculating the similarity between the first measurement vector and the second measurement vector; A second determination module, configured to correct the identification difference degree based on a penalty coefficient and a superimposed electrical appliance weight coefficient, and determine the performance evaluation result of the device to be evaluated, specifically including: Calculating the product of the identification difference degree of each preset charging stage and the reciprocal of the corresponding penalty coefficient, and calculating the initial identification accuracy of each preset charging stage based on the result of the product, and calculating the final identification accuracy according to the initial identification accuracies of each preset charging stage; determining the performance evaluation result of the device to be evaluated according to the identification accuracy and the superimposed electrical appliance weight coefficient; where the superimposed electrical appliance weight coefficient is determined according to the types and quantities of superimposed electrical appliances.

7. A storage medium, in which at least one executable instruction is stored, and the executable instruction causes a processor to perform operations corresponding to the device performance evaluation method according to any one of claims 1-5.

8. A terminal, comprising: A processor, a memory, a communication interface, and a communication bus, where the processor, the memory, and the communication interface complete communication with each other through the communication bus; The memory is used to store at least one executable instruction, and the executable instruction causes the processor to perform operations corresponding to the device performance evaluation method according to any one of claims 1-5.

Images