A performance evaluation method, device, medium and equipment of a new energy vehicle air conditioner

Abstract

The application provides a performance evaluation method and device of a new energy automobile air conditioner, medium and equipment, parameter data of a new energy automobile to be evaluated is collected; a plurality of working condition subsets are obtained based on vehicle operation parameters and environmental state parameters; a plurality of evaluation indexes are calculated based on the vehicle operation parameters, environmental state parameters and corresponding air conditioner operation parameters of each working condition subset; and the evaluation result of the air conditioner performance is comprehensively determined based on the plurality of evaluation indexes; that is, the vehicle operation parameters, air conditioner operation parameters and environmental state parameters of the new energy automobile to be evaluated in the running process are actually collected, each group of parameters is clustered to obtain a plurality of working condition subsets, a plurality of evaluation indexes of the air conditioner performance of each working condition subset are calculated, and then the air conditioner performance of the new energy automobile to be evaluated is comprehensively determined, the air conditioner performance is evaluated in multiple dimensions in combination with the parameters of the actual running of the vehicle, and the accuracy of the air conditioner performance evaluation is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy vehicle air conditioner evaluation, and particularly relates to a performance evaluation method, device, medium and equipment for a new energy vehicle air conditioner. BACKGROUND

[0002] With the emphasis on environmental protection and the transformation of energy structure worldwide, new energy vehicles have developed rapidly. The air conditioning system of a new energy vehicle is a key component for adjusting the vehicle environment, and its performance directly affects the comfort and cruising range of the vehicle. Therefore, the performance of the air conditioning system needs to be evaluated when the new energy vehicle is designed. However, the existing evaluation methods are mostly carried out in specific experimental environments, and the working conditions are single, which cannot truly reflect the complex road conditions, weather and different habits of drivers in the actual driving process, and the performance requirements of the air conditioner and the running state of the air conditioner. Therefore, a method for accurately evaluating the performance of a new energy vehicle air conditioner is needed. SUMMARY

[0003] To solve the above technical problems, the present application is proposed. Embodiments of the present application provide a performance evaluation method, device, medium and equipment for a new energy vehicle air conditioner.

[0004] According to one aspect of the present application, a performance evaluation method for a new energy vehicle air conditioner is provided, including: collecting parameter data of a new energy vehicle to be evaluated; wherein the parameter data includes vehicle operating parameters of the new energy vehicle to be evaluated when running, air conditioner operating parameters of an air conditioner carried by the new energy vehicle to be evaluated when running, and environmental state parameters of an environment in which the new energy vehicle to be evaluated is located; clustering to obtain a plurality of working condition subsets based on the vehicle operating parameters and the environmental state parameters; wherein each working condition subset represents a vehicle operating parameter and an environmental state parameter; calculating a plurality of evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operating parameters, the environmental state parameters and the corresponding air conditioner operating parameters of each working condition subset; and comprehensively determining an evaluation result of the air conditioner performance of the new energy vehicle to be evaluated based on the plurality of evaluation indexes.

[0005] In an embodiment, the clustering to obtain a plurality of working condition subsets based on the vehicle operating parameters and the environmental state parameters includes: randomly selecting k data points as initial cluster center points; wherein, kFor the number of working condition subsets, the data points are data vectors composed of a vehicle operating parameter and an environmental state parameter; a clustering distance between each of the initial cluster center points and the remaining data points is calculated; the remaining data points are assigned to the cluster corresponding to the initial cluster center point with the closest clustering distance; a deviation distance between the average value of all data points in each cluster and the corresponding initial cluster center point is calculated; if the deviation distance is greater than a preset deviation threshold, the average value is taken as a new cluster center point; all data points are clustered again based on the new cluster center point to obtain new clusters, until the deviation distance between the average value of the data points in all clusters and the cluster center point is less than or equal to the deviation threshold.

[0006] In an embodiment, the evaluation index includes air conditioner energy consumption; wherein the calculation of the multiple evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operating parameter, the environmental state parameter and the corresponding air conditioner operating parameter of each working condition subset includes: the air conditioner operating time is calculated based on the environmental state parameter and the vehicle operating parameter; the air conditioner energy consumption is calculated based on the air conditioner operating time and the air conditioner operating parameter.

[0007] In an embodiment, the evaluation index includes air conditioner energy consumption fluctuation degree; wherein the calculation of the multiple evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operating parameter, the environmental state parameter and the corresponding air conditioner operating parameter of each working condition subset includes: the initial parameter is set based on the average value of the air conditioner energy consumption in multiple historical periods; the air conditioner energy consumption in future multiple periods is iteratively predicted based on the initial parameter; the air conditioner energy consumption fluctuation degree is calculated based on the air conditioner energy consumption in the historical period and the air conditioner energy consumption in the future multiple periods.

[0008] In an embodiment, the evaluation index includes air conditioner fuel consumption; wherein the calculation of the multiple evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operating parameter, the environmental state parameter and the corresponding air conditioner operating parameter of each working condition subset includes: the first fuel consumption under the condition of closing the air conditioner is measured based on the vehicle operating parameter and the environmental state parameter; the second fuel consumption under the condition of opening the air conditioner is measured based on the vehicle operating parameter, the environmental state parameter and the air conditioner operating parameter; the air conditioner fuel consumption is calculated based on the first fuel consumption and the second fuel consumption.

[0009] In an embodiment, the comprehensive determination of the evaluation result of the air conditioner performance of the new energy vehicle to be evaluated based on the multiple evaluation indexes includes: the multiple evaluation indexes are weighted to obtain the evaluation result of the air conditioner performance of the new energy vehicle to be evaluated.

[0010] In an embodiment, the determining the evaluation result of the air conditioning performance of the new energy vehicle to be evaluated based on the plurality of evaluation indexes comprises: determining the evaluation result of the air conditioning performance of the new energy vehicle to be evaluated based on the plurality of evaluation indexes and corresponding target indexes, wherein the target indexes are generated based on the vehicle operating parameters, the environmental state parameters and the air conditioning operating parameters.

[0011] According to another aspect of the present application, a performance evaluation device for a new energy vehicle air conditioner is provided, comprising: a parameter data acquisition module configured to acquire parameter data of a new energy vehicle to be evaluated, wherein the parameter data comprises vehicle operating parameters of the new energy vehicle to be evaluated when in operation, air conditioning operating parameters of an air conditioner carried by the new energy vehicle to be evaluated when in operation, and environmental state parameters of an environment in which the new energy vehicle to be evaluated is located; a working condition subset clustering module configured to cluster a plurality of working condition subsets based on the vehicle operating parameters and the environmental state parameters, wherein each working condition subset represents a vehicle operating parameter and an environmental state parameter; an evaluation index calculation module configured to calculate a plurality of evaluation indexes of the air conditioning performance of the new energy vehicle to be evaluated based on the vehicle operating parameters, the environmental state parameters and corresponding air conditioning operating parameters of each working condition subset; and an evaluation result determination module configured to determine an evaluation result of the air conditioning performance of the new energy vehicle to be evaluated based on the plurality of evaluation indexes.

[0012] According to another aspect of the present application, a computer readable storage medium is provided, wherein the storage medium stores a computer program for executing any of the above-mentioned methods.

[0013] According to another aspect of the present application, an electronic device is provided, comprising: a processor; a memory configured to store instructions executable by the processor; and the processor configured to execute any of the above-mentioned methods.

[0014] The application provides a performance evaluation method and device of a new energy vehicle air conditioner, a medium and equipment. BRIEF DESCRIPTION OF DRAWINGS

[0015] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description thereof taken in conjunction with the accompanying drawings, in which:

[0016] Figure 1 FIG. 1 is a flowchart of a performance evaluation method of a new energy vehicle air conditioner according to an example embodiment of the present application.

[0017] Figure 2 FIG. 2 is a structural diagram of a performance evaluation device of a new energy vehicle air conditioner according to an example embodiment of the present application.

[0018] Figure 3 FIG. 3 is a structural diagram of an electronic device according to an example embodiment of the present application. DETAILED DESCRIPTION

[0019] Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be understood that the described embodiments are merely a part of the embodiments of the present application, but not the whole embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein.

[0020] Figure 1is a flowchart of a performance evaluation method of a new energy vehicle air conditioner provided by an exemplary embodiment of the present application. As shown in Figure 1 the performance evaluation method of the new energy vehicle air conditioner includes the following steps:

[0021] Step 110: Collecting parameter data of the new energy vehicle to be evaluated.

[0022] Among them, the parameter data includes vehicle operating parameters of the new energy vehicle to be evaluated when running, air conditioner operating parameters of the air conditioner carried by the new energy vehicle to be evaluated when running, and environmental state parameters of the environment where the new energy vehicle to be evaluated is located. Specifically, the present application installs a plurality of sensors and measuring devices on the new energy vehicle to be evaluated, including but not limited to an indoor temperature sensor, a humidity sensor, an air conditioner outlet air speed sensor, an outdoor environment temperature sensor, a vehicle speed sensor, a battery management system data acquisition interface, a thermal sensor, a 3D surface area measuring instrument, etc. These sensors periodically collect (for example, collect once every 5 seconds) various parameters of the vehicle and the driver and passengers during the vehicle running process, covering air conditioner operating parameters, vehicle driving state, environmental condition parameters, and driver and passenger thermal comfort related parameters, and transmit the data to the vehicle-mounted data storage unit.

[0023] Step 120: Clustering to obtain a plurality of working condition subsets based on the vehicle operating parameters and the environmental state parameters.

[0024] Among them, each working condition subset represents a vehicle operating parameter and an environmental state parameter. The present application uses a vehicle-mounted communication module to upload the collected data to a cloud data center regularly (for example, upload once every 10 minutes), ensuring the timeliness and integrity of the data. At the same time, a data verification mechanism is set up in the cloud data center to preliminarily screen the uploaded data, eliminate incorrect or abnormal data, and ensure the data quality for subsequent analysis. A big data analysis platform for processing new energy vehicle data is built in the cloud data center, which adopts a distributed storage and computing architecture to cope with the storage and operation needs of massive data. The platform has multiple data analysis algorithm models built-in, including a clustering analysis algorithm for classifying and aggregating the collected data according to different road conditions (such as urban roads, highways, and rural roads), seasons, and regions to mine the potential rules of air conditioner energy consumption under different working conditions; a time series analysis model for tracking the change trend of air conditioner energy consumption of the same vehicle in different time periods to assist in discovering possible performance degradation problems of the air conditioning system; and an adaptive learning rate optimization algorithm for detecting and learning the usage habits of the driver and passengers for the air conditioner, thereby realizing precise adjustment of the indoor temperature and reducing energy consumption loss.

[0025] Step 130: Calculating a plurality of evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operating parameters, the environmental state parameters, and the corresponding air conditioner operating parameters of each working condition subset.

[0026] According to the clustering analysis result of the big data analysis platform, the application selects representative working condition combinations, covering different road conditions, seasons, temperature intervals, and air conditioning setting modes, etc. In the simulation test environment, according to the selected working condition combinations, high-precision measuring instruments are used to measure the real-time parameters of the air conditioning system of the new energy vehicle under test under each working condition, and combined with the running time of the new energy vehicle under test, multiple evaluation indexes of the evaluation of the air conditioning performance are accurately calculated. At the same time, in order to ensure the accuracy of the test, the simulation test environment is equipped with temperature and humidity adjusting equipment similar to the actual environment, loading devices simulating road driving resistance, etc.

[0027] Step 140: Based on multiple evaluation indexes, the evaluation result of the air conditioning performance of the new energy vehicle under test is comprehensively determined.

[0028] Based on the big data analysis result and the simulation test data, the application constructs an energy consumption evaluation system for new energy vehicle air conditioning, which evaluates the air conditioning system of the new energy vehicle under test from multiple dimensions:

[0029] The energy saving dimension compares the proportion of air conditioning energy consumption and total vehicle energy consumption under different vehicle models and different working conditions, as well as the energy consumption corresponding to unit refrigeration / heat, evaluates the energy utilization efficiency of the air conditioning system, determines whether it meets the standard energy saving requirement and whether it contains intelligent energy saving function, etc.

[0030] The comfort dimension combines the actual adjustment effect of key indicators such as indoor temperature, humidity, noise, and air quality to evaluate the performance of the air conditioning system in providing a comfortable driving environment.

[0031] The adaptability dimension considers whether the air conditioning system can quickly respond under extreme weather conditions (such as high temperature, severe cold, low pressure, and no oxygen, etc.) and complex road conditions to meet the basic use requirements of the vehicle.

[0032] The reliability dimension tracks the abnormal fluctuation of air conditioning energy consumption according to time series analysis, judges whether the air conditioning system has potential fault hidden dangers, evaluates the performance, safety, and maintainability of the air conditioning system during long-term operation, and evaluates the running reliability of the air conditioning system.

[0033] The application provides a performance evaluation method of a new energy automobile air conditioner. Parameter data of a new energy automobile to be evaluated is collected. The parameter data includes vehicle operation parameters of the new energy automobile to be evaluated when the new energy automobile to be evaluated is running, air conditioner operation parameters of an air conditioner carried by the new energy automobile to be evaluated when the air conditioner is running, and environmental state parameters of an environment in which the new energy automobile to be evaluated is located. A plurality of working condition subsets are obtained by clustering based on the vehicle operation parameters and the environmental state parameters. Each working condition subset represents one vehicle operation parameter and one environmental state parameter. A plurality of evaluation indexes of the air conditioner performance of the new energy automobile to be evaluated are calculated based on the vehicle operation parameters, the environmental state parameters and the corresponding air conditioner operation parameters of each working condition subset. An evaluation result of the air conditioner performance of the new energy automobile to be evaluated is comprehensively determined based on the plurality of evaluation indexes. That is, the vehicle operation parameters, the air conditioner operation parameters and the environmental state parameters of the new energy automobile to be evaluated during the running process are actually collected, each group of parameters is clustered to obtain a plurality of working condition subsets, a plurality of evaluation indexes of the air conditioner performance are calculated for each working condition subset, and then the air conditioner performance of the new energy automobile to be evaluated is comprehensively determined. The air conditioner performance of the new energy automobile to be evaluated is evaluated in multiple dimensions in combination with the actual running parameters of the vehicle, so that the accuracy of the air conditioner performance evaluation of the new energy automobile to be evaluated is improved.

[0034] In an embodiment, the specific implementation of the step 120 can be: any selected k data points are taken as initial cluster center points; wherein, k is the number of working condition subsets, and the data points are data vectors composed of one vehicle operation parameter and one environmental state parameter; the clustering distances between the remaining data points and each initial cluster center point are calculated; the remaining data points are distributed to the clusters corresponding to the initial cluster center points with the nearest clustering distances; the deviation distances between the average values of all data points in each cluster and the corresponding initial cluster center points are calculated; if the deviation distance is greater than a preset deviation threshold, the average value is taken as a new cluster center point; all data points are clustered again based on the new cluster center points to obtain new clusters, until the deviation distance between the average value of the data points in all clusters and the cluster center point is less than or equal to the deviation threshold.

[0035] Specifically, the application first determines the number of clusters to be clustered (i.e., the number of working condition subsets to be finally generated k ), and then selects k data points in the collected data points as initial cluster center points, and the i cluster is recorded as C i , 1≤ i ≤ k, calculate clustering distances of the remaining data points (data points not assigned to the clusters) to the cluster center points of each cluster, and assign the remaining data points to the cluster with the nearest clustering distance to the cluster center point according to the nearest principle, and after the assignment of all the remaining data points is completed, the target function value with the cluster center point of each cluster and the average value of all data points in each cluster as the target is calculated respectively, specifically, the target function is: , wherein, J is the target function value, x is a data point, and the present application respectively calculates is the cluster center point of the first i cluster and the average value of all data points in the first i cluster to obtain the corresponding target function, and calculates the difference (i.e. deviation distance) between the target functions, if the deviation distance is large (i.e. greater than a preset deviation threshold), the average value is taken as a new cluster center point to reassign the data points to obtain new clusters, by continuously adjusting the cluster center point, until the deviation distance is less than or equal to the deviation threshold, the iteration update is stopped, i.e. the clustering is completed. The typical working conditions obtained by clustering include:

[0036] Table 1: Typical working condition subset

[0037]

[0038] In an embodiment, the evaluation index includes air conditioner energy consumption; wherein the specific implementation of the above step 130 can be: based on the environmental state parameters and the vehicle running parameters, the air conditioner running time is calculated; based on the air conditioner running time and the air conditioner running parameters, the air conditioner energy consumption is calculated.

[0039] The present application calculates the running time of the air conditioner according to the environmental state parameters and the vehicle running parameters, and then calculates the air conditioner energy consumption according to the air conditioner running time and the air conditioner running parameters. Specifically, the calculation formula of the air conditioner running time is as follows:

[0040] ;

[0041] , wherein, is the running time of the air conditioner system in the first i hour of a day (corresponding to one hour from the first i time to the first i +1 time), is the total duration of the to-be-evaluated new energy vehicle running throughout the day, is the proportion of travel of the to-be-evaluated new energy vehicle in the first i hour, is a representation of human thermal comfort at the first i time, which refers to the dissatisfaction rate of the human body to the environmental temperature in the first i hour.

[0042] ;

[0043] wherein, ;

[0044] ; ;

[0045] ;

[0046] ;

[0047] ;

[0048] wherein, PMV is the average reaction of the human body to the current ambient temperature, L is the heat load of the human body, M is the energy metabolic rate of the human body, W is the mechanical work done by the human body, P a is the actual output power of the air conditioner driving motor, is the air temperature around the human body, is the ratio of the clothing surface area to the naked body surface area, h c is the clothing surface heat transfer coefficient, is the clothing surface temperature, is the average radiation temperature in the vehicle, V is the air flow rate around the human body, is the clothing thermal resistance, clo = 0.155, is the relative humidity.

[0049] The calculation formula of the air conditioner energy consumption is as follows:

[0050] ;

[0051] wherein, is the energy consumption value of the air conditioning system within a day, is the output power of the air conditioning system within the i th hour.

[0052] In an embodiment, the evaluation index includes the air conditioner energy consumption fluctuation degree; wherein the specific implementation manner of the step 130 can be: setting an initial parameter based on the air conditioner energy consumption average value within a plurality of historical periods; iteratively predicting the air conditioner energy consumption within a plurality of future periods based on the initial parameter; and calculating the air conditioner energy consumption fluctuation degree based on the air conditioner energy consumption within the historical periods and the air conditioner energy consumption within the plurality of future periods.

[0053] This application predicts air conditioning energy consumption for future periods based on previous periods' energy consumption, thereby forecasting the degree of fluctuation in air conditioning energy consumption. This allows for early detection of abnormal fluctuations in energy consumption and provides advance warnings or appropriate measures when such fluctuations occur. Specifically, initial parameters are set based on the average energy consumption over multiple historical periods, including an initial energy consumption level. S 0. Initial energy consumption trend value b 0 and initial seasonal factor I 0, and set the data smoothing coefficient. α (0≤) α ≤1) Trend smoothing coefficient β (0≤) β ≤1) and seasonal smoothing coefficient gamma (0≤) gamma ≤1); Based on the initial energy consumption level, initial energy consumption trend, initial seasonal factor, data smoothing coefficient, trend smoothing coefficient, and seasonal smoothing coefficient, the air conditioning energy consumption in the future multiple periods is predicted through iteration. The specific prediction formula is as follows:

[0054]

[0055] in, S t For time t The energy consumption level value (i.e., the value corresponding to the energy consumption range). Y t For time t The actual observed value (i.e. the value obtained by the sensor). I t-L For the seasonal factor at the same time in the previous cycle, L For seasonal cycles (e.g., spring, summer, autumn, winter). b t For time t The energy consumption trend value (i.e., the rate of change of energy consumption at that point in time). I t For time t Seasonal factors, F t+m For the future m The predicted value at the same time after one cycle.

[0056] In one embodiment, the evaluation index includes air conditioning fuel consumption; wherein, the specific implementation of step 130 above may be as follows: based on vehicle operating parameters and environmental state parameters, a first fuel consumption under the condition of air conditioning off is measured; based on vehicle operating parameters, environmental state parameters and air conditioning operating parameters, a second fuel consumption under the condition of air conditioning on is measured; based on the first fuel consumption and the second fuel consumption, the air conditioning fuel consumption is calculated.

[0057] The first fuel consumption under the condition of closing the air conditioner and the second fuel consumption under the condition of opening the air conditioner are measured according to the vehicle operating parameters and the environmental state parameters, and the air conditioner fuel consumption is calculated according to the first fuel consumption and the second fuel consumption, wherein the air conditioner fuel consumption = the second fuel consumption - the first fuel consumption. After the air conditioner fuel consumption is calculated, the size between the target fuel consumption and the air conditioner fuel consumption is compared to determine whether the air conditioner fuel consumption of the new energy vehicle to be tested meets the standard, wherein the target fuel consumption , CM is the total vehicle preparation mass. Moreover, the application also calculates the fuel consumption of the air conditioner under various fuel uses according to the fuel type of the new energy vehicle to be tested, and converts it into the consumption of liquid fuels such as diesel, gasoline or methanol. The consumption of gaseous fuels such as natural gas and hydrogen is converted into the consumption of liquid fuels by the following formula:

[0058] ;

[0059] wherein, Q 1 is the consumption of liquid fuels converted from the consumption of gaseous fuels, P is the gas pressure, V gas is the gas volume, M is the molar volume of the gas, R is the ideal gas constant, R = 8.314 J / (mol·K), T is the gas temperature, is the liquid density.

[0060] The electric consumption is converted into the consumption of liquid fuels by the following formula:

[0061] ;

[0062] wherein, Q 2 is the consumption of liquid fuels converted from the electric consumption, E is the electric energy consumption of the vehicle, is the energy factor of the fuel, r p is the refinery efficiency, t p is the delivery and filling efficiency, i ch is the charging efficiency, which is 100% when the electric energy is obtained from the power grid, i tr is the line loss rate, is the proportion of thermal power generation, s ge is the power supply efficiency,T E Standard coal consumption for thermal power generation. T C The carbon dioxide emission factor for fuel coal. T F Carbon dioxide emission factor for fuel. This is the conversion factor between fuel coal and standard coal.

[0063] In one embodiment, step 140 can be implemented by determining the evaluation result of the air conditioning performance of the new energy vehicle to be evaluated based on multiple evaluation indicators and corresponding target indicators; wherein the target indicators are generated based on vehicle operating parameters, environmental state parameters and air conditioning operating parameters.

[0064] Specifically, this application obtains the score for each evaluation indicator by comparing the differences between individual evaluation indicators and their corresponding target indicators, and determines the evaluation result of the air conditioning performance of the new energy vehicle to be evaluated based on the scores of all evaluation indicators. The target indicators can be obtained by inputting relevant parameters of the new energy vehicle to be evaluated into a neural network model to directly obtain the optimal indicators (i.e., target indicators) of the air conditioning in the corresponding scenario. Relevant parameters may include: driving habits (e.g., temperature setting, wind speed preference), environmental parameters (e.g., temperature and humidity, solar radiation), and vehicle status (e.g., speed, acceleration), thereby obtaining the optimal air conditioning control strategy and corresponding target indicators adapted to the new energy vehicle to be evaluated. For example, in high-speed conditions (vehicle speed > 80 km / h), the compressor load is reduced by using windward cooling; in congested conditions (vehicle speed < 30 km / h), an intermittent air supply mode is activated, and the energy-saving mode is switched 5 minutes in advance based on the predicted arrival time to avoid ineffective cooling; special road sections such as tunnels and uphill sections are identified in real time by fusion of GPS and high-precision maps; the wind speed is automatically reduced and the internal circulation ratio is increased before entering a tunnel; when climbing a hill, the engine thermal management system is linked to use waste heat to assist heating and improve the energy efficiency ratio.

[0065] The training methods for neural network models include:

[0066] First, set initial metrics, and then introduce activation functions to map the initial metrics to each convolutional layer, calculating the corresponding feature results layer by layer. The feature results of the layer are as follows: , For the first The feature results of the layer, For the first The convolution function of the layer, For the first The weight matrix of the layer, For the first The bias vector of the layer; calculate the error between the predicted result and the actual result. , N is the number of samples, h is the true value (real result) of the sample, is the predicted result; the loss function is calculated , is the regularization coefficient, is the weight parameter; the iterative gradient is calculated based on the loss function , is the gradient at the moment t , is the learning rate, is the loss value of the i-th sample; the weight matrix and the bias vector are updated, and the update formula of the bias vector is as follows: i , is the bias vector at the moment , t is the derivative of the error with respect to the bias vector; the model is updated based on the updated weight matrix and bias vector, and the above calculation is repeated until the loss function is less than the preset value or the number of iterations reaches the set value. In an embodiment, the specific implementation of the above step 140 can be: weighting multiple evaluation indexes to obtain the evaluation result of the air conditioning performance of the new energy vehicle to be evaluated.

[0067] After the multiple evaluation indexes (or scores of the evaluation indexes) are calculated, the application weights the multiple evaluation indexes to obtain the evaluation result of the air conditioning performance of the new energy vehicle to be evaluated. For example, the calculation formula of the comprehensive score of the air conditioning performance of the new energy vehicle to be evaluated is:

[0068]

[0069] ;

[0070] wherein, S is the total score of the air conditioning performance of the new energy vehicle to be evaluated, A, B, C, D respectively correspond to the energy saving evaluation index score, the comfort evaluation index score, the adaptability evaluation index score, and the reliability evaluation index score, 、 、 、 respectively are the weight coefficients of each evaluation index, may be 0.2, may be 0.2, may be 0.3, may be 0.3.

[0071] Specifically, the air conditioning performance evaluation indexes of the new energy vehicle to be evaluated can include: ​

[0072] Table 2 Air Conditioner Performance Evaluation Indicators

[0073]

[0074] Figure 2 This is a schematic diagram of the structure of a performance evaluation device for a new energy vehicle air conditioner provided in an exemplary embodiment of this application. Figure 2 As shown, the performance evaluation device 20 for the air conditioning of a new energy vehicle includes: a parameter data acquisition module 21, used to collect parameter data of the new energy vehicle to be evaluated; wherein, the parameter data includes vehicle operating parameters of the new energy vehicle to be evaluated during operation, air conditioning operating parameters of the air conditioning installed in the new energy vehicle to be evaluated during operation, and environmental state parameters of the environment in which the new energy vehicle to be evaluated is located; a working condition subset clustering module 22, used to cluster multiple working condition subsets based on vehicle operating parameters and environmental state parameters; wherein, each working condition subset represents a vehicle operating parameter and an environmental state parameter; an evaluation index calculation module 23, used to calculate multiple evaluation indexes of the air conditioning performance of the new energy vehicle to be evaluated based on the vehicle operating parameters, environmental state parameters, and corresponding air conditioning operating parameters of each working condition subset; and an evaluation result determination module 24, used to comprehensively determine the evaluation result of the air conditioning performance of the new energy vehicle to be evaluated based on multiple evaluation indexes.

[0075] This application provides a performance evaluation device for a new energy vehicle air conditioner. The device collects parameter data from the new energy vehicle under test via a parameter data acquisition module 21. This parameter data includes vehicle operating parameters, air conditioner operating parameters, and environmental state parameters of the environment in which the new energy vehicle is located. A working condition subset clustering module 22 clusters multiple working condition subsets based on the vehicle operating parameters and environmental state parameters. Each working condition subset represents a vehicle operating parameter and an environmental state parameter. An evaluation index calculation module 23 calculates the evaluation index based on the vehicle operating parameters and environmental state parameters of each working condition subset. The system calculates multiple evaluation indicators for the air conditioning performance of the new energy vehicle under test based on the data and corresponding air conditioning operating parameters. The evaluation result determination module 24 comprehensively determines the evaluation result of the air conditioning performance of the new energy vehicle under test based on multiple evaluation indicators. Specifically, it collects the vehicle operating parameters, air conditioning operating parameters, and environmental state parameters of the new energy vehicle under test during operation, and clusters each set of parameters to obtain multiple operating condition subsets. For each operating condition subset, it calculates multiple evaluation indicators for its air conditioning performance, and then comprehensively determines the air conditioning performance of the new energy vehicle under test. It combines the parameters of actual vehicle operation to conduct a multi-dimensional evaluation of its air conditioning performance in order to improve the accuracy of its air conditioning performance evaluation.

[0076] In one embodiment, the above-mentioned working condition subset clustering module 22 can be further configured to: arbitrarily select ka data point as an initial cluster center point; wherein k is the number of working condition subsets, and the data point is a data vector composed of a vehicle operating parameter and an environmental state parameter; a clustering distance between each remaining data point and each initial cluster center point is calculated; the remaining data points are assigned to a cluster corresponding to the initial cluster center point with the closest clustering distance; a deviation distance between the average value of all data points in each cluster and the corresponding initial cluster center point is calculated; if the deviation distance is greater than a preset deviation threshold, the average value is taken as a new cluster center point; all data points are clustered again based on the new cluster center points to obtain new clusters, until the deviation distance between the average value of the data points in all clusters and the cluster center point is less than or equal to the deviation threshold.

[0077] In an embodiment, the evaluation index includes air conditioner energy consumption; wherein the evaluation index calculation module 23 can be further configured to: calculate the air conditioner running time based on the environmental state parameter and the vehicle operating parameter; and calculate the air conditioner energy consumption based on the air conditioner running time and the air conditioner operating parameter.

[0078] In an embodiment, the evaluation index includes air conditioner energy consumption fluctuation; wherein the evaluation index calculation module 23 can be further configured to: set an initial parameter based on the average value of the air conditioner energy consumption in a plurality of historical periods; iteratively predict the air conditioner energy consumption in a plurality of future periods based on the initial parameter; and calculate the air conditioner energy consumption fluctuation based on the air conditioner energy consumption in the historical periods and the air conditioner energy consumption in the plurality of future periods.

[0079] In an embodiment, the evaluation index includes air conditioner fuel consumption; wherein the evaluation index calculation module 23 can be further configured to: measure a first fuel consumption under the condition of closing the air conditioner based on the vehicle operating parameter and the environmental state parameter; measure a second fuel consumption under the condition of opening the air conditioner based on the vehicle operating parameter, the environmental state parameter, and the air conditioner operating parameter; and calculate the air conditioner fuel consumption based on the first fuel consumption and the second fuel consumption.

[0080] In an embodiment, the evaluation result determination module 24 can be further configured to: weight a plurality of evaluation indexes to obtain the evaluation result of the air conditioner performance of the new energy vehicle to be evaluated.

[0081] In an embodiment, the evaluation result determination module 24 can be further configured to: determine the evaluation result of the air conditioner performance of the new energy vehicle to be evaluated based on a plurality of evaluation indexes and corresponding target indexes; wherein the target index is generated based on the vehicle operating parameter, the environmental state parameter, and the air conditioner operating parameter.

[0082] In the following, reference is made to Figure 3An electronic device according to embodiments of the present application will be described. The electronic device can be either one or both of the first and second devices, or a stand-alone device independent of them, which can communicate with the first and second devices to receive the acquired input signals therefrom.

[0083] Figure 3 A block diagram of an electronic device according to embodiments of the present application is illustrated.

[0084] As Figure 3 shown, the electronic device 10 includes one or more processors 11 and a memory 12.

[0085] The processor 11 can be a central processing unit (CPU) or other form of processing unit having data processing and / or instruction executing capabilities, and can control other components in the electronic device 10 to perform desired functions.

[0086] The memory 12 can include one or more computer program products, which can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory, for example, can include random access memory (RAM), cache memory, and / or the like. The non-volatile memory, for example, can include read only memory (ROM), hard disk, flash memory, and / or the like. One or more computer program instructions can be stored on the computer-readable storage media, which the processor 11 can execute to implement the methods of the embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, and the like can also be stored in the computer-readable storage media.

[0087] In one example, the electronic device 10 can further include input and output means 13 and 14, which are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0088] When the electronic device is a stand-alone device, the input means 13 can be a communication network connector for receiving the acquired input signals from the first and second devices.

[0089] In addition, the input means 13 can further include, for example, a keyboard, a mouse, and the like.

[0090] The output means 14 can output various information including the determined distance information, direction information, and the like to the outside. The output means 14 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0091] Of course, to simplify, Figure 3Only some of the components of the electronic device 10 related to the present application are shown, and components such as a bus, an input / output interface, and the like are omitted. In addition to these, the electronic device 10 can include any other appropriate components according to the specific application.

[0092] In addition to the method and the device described above, an embodiment of the present application can be a computer program product, which includes computer program instructions that when executed by a processor cause the processor to perform steps of the methods according to various embodiments of the present application described in the above "Exemplary Methods" section of this specification.

[0093] The computer program product can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++, etc., and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server.

[0094] In addition, an embodiment of the present application can be a computer readable storage medium, which stores computer program instructions, which when executed by a processor cause the processor to perform steps of the methods according to various embodiments of the present application described in the above "Exemplary Methods" section of this specification.

[0095] The computer readable storage medium can be any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include the following: an electrical connection having one or more wires, a portable disc, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0096] The above describes the basic principles of the present application in combination with specific embodiments, but it needs to be pointed out that the advantages, benefits, effects and the like mentioned in the present application are only examples and are not limiting, and these advantages, benefits, effects and the like cannot be considered as necessary for each embodiment of the present application. In addition, the above specific details disclosed are only for the purpose of example and understanding, and are not limiting, and the above details do not limit the present application to be necessarily implemented with the above specific details.

[0097] The block diagrams of the devices, apparatuses, equipment, systems involved in the present application are only illustrative examples and are not intended to require or imply the connection, arrangement, configuration shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, systems can be connected, arranged, configured in any manner. Words such as "include", "contain", "have" and the like are open-ended words, mean "including but not limited to", and can be used interchangeably. The words "or" and "and" used herein mean the word "and / or", and can be used interchangeably unless the context clearly indicates otherwise. The word "such as" used herein means the phrase "such as but not limited to", and can be used interchangeably.

[0098] It also needs to be pointed out that in the devices, equipment and methods of the present application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions of the present application.

[0099] The above description of the disclosed aspects is provided so that any person skilled in the art can make or use the present application. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but is intended to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0100] The above description has been given for the purpose of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A performance evaluation method of a new energy vehicle air conditioner, characterized in that, The method comprises the following steps: Collecting parameter data of a new energy vehicle to be evaluated, wherein the parameter data comprises vehicle operation parameters of the new energy vehicle to be evaluated when the new energy vehicle to be evaluated is running, air conditioner operation parameters of an air conditioner carried by the new energy vehicle to be evaluated when the air conditioner is running, and environmental state parameters of an environment in which the new energy vehicle to be evaluated is located; Based on the vehicle operation parameters and the environmental state parameters, a plurality of working condition subsets are clustered, wherein each working condition subset represents a vehicle operation parameter and an environmental state parameter; Based on the vehicle operation parameters, the environmental state parameters and the corresponding air conditioner operation parameters of each working condition subset, a plurality of evaluation indexes of air conditioner performance of the new energy vehicle to be evaluated are calculated; Based on the plurality of evaluation indexes, an evaluation result of the air conditioner performance of the new energy vehicle to be evaluated is comprehensively determined; The evaluation indexes comprise air conditioner energy consumption, wherein the calculation of the plurality of evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operation parameters, the environmental state parameters and the corresponding air conditioner operation parameters of each working condition subset comprises: Based on the environmental state parameters and the vehicle operation parameters, air conditioner running time is calculated; Based on the air conditioner running time and the air conditioner operation parameters, the air conditioner energy consumption is calculated; The calculation formula of the air conditioner running time is as follows: ； wherein, is the running time of the air conditioning system in the first i hour of the day (corresponding to the time period from the i time to the time +1 hour), i is the total running time of the new energy vehicle to be evaluated throughout the day, is the proportion of travel of the new energy vehicle to be evaluated in the first hour, i is the representation of human thermal comfort at the time, which refers to the dissatisfaction rate of the human body to the ambient temperature in the first hour. i i ​​ 2. The performance evaluation method of the new energy vehicle air conditioner according to claim 1, characterized in that, The clustering of the plurality of working condition subsets based on the vehicle operation parameters and the environmental state parameters comprises: arbitrarily selected k a data point as an initial cluster center point; wherein, k is the number of working condition subsets, and the data point is a data vector composed of a vehicle operating parameter and an environmental state parameter; The clustering distance between the remaining data points and each initial cluster center point is calculated; The remaining data points are assigned to the cluster corresponding to the initial cluster center point with the closest clustering distance; The deviation distance between the average value of all data points in each cluster and the corresponding initial cluster center point is calculated; If the deviation distance is greater than a preset deviation threshold, the average value is taken as a new cluster center point; Based on the new cluster center point, all data points are clustered again to obtain new clusters, until the deviation distance between the average value of the data points in all clusters and the cluster center point is less than or equal to the deviation threshold.

3. The performance evaluation method of the new energy vehicle air conditioner according to claim 1, characterized in that, The evaluation indexes comprise air conditioner energy consumption fluctuation degree, wherein the calculation of the plurality of evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operation parameters, the environmental state parameters and the corresponding air conditioner operation parameters of each working condition subset comprises: An initial parameter is set based on the average value of the air conditioner energy consumption in a plurality of historical periods; The air conditioner energy consumption in a plurality of future periods is iteratively predicted based on the initial parameter; Based on the air conditioner energy consumption in the historical periods and the air conditioner energy consumption in the future plurality of periods, the air conditioner energy consumption fluctuation degree is calculated.

4. The performance evaluation method of the new energy vehicle air conditioner according to claim 1, characterized in that, The evaluation indexes comprise air conditioner fuel consumption, wherein the calculation of the plurality of evaluation indexes of the air conditioner performance of the new energy vehicle to be evaluated based on the vehicle operation parameters, the environmental state parameters and the corresponding air conditioner operation parameters of each working condition subset comprises: A first fuel consumption under the condition of closing the air conditioner is measured based on the vehicle operation parameters and the environmental state parameters; A second fuel consumption under the condition of opening the air conditioner is measured based on the vehicle operation parameters, the environmental state parameters and the air conditioner operation parameters; The air conditioner fuel consumption is calculated based on the first fuel consumption and the second fuel consumption.

5. The performance evaluation method of the new energy vehicle air conditioner according to claim 1, characterized in that, The evaluation result of the air conditioner performance of the new energy vehicle under test is determined based on the plurality of evaluation indexes. The evaluation result of the air conditioner performance of the new energy vehicle under test is determined based on the plurality of evaluation indexes.

6. The performance evaluation method of the new energy vehicle air conditioner according to claim 1, characterized in that, The evaluation result of the air conditioner performance of the new energy vehicle under test is determined based on the plurality of evaluation indexes. The evaluation result of the air conditioner performance of the new energy vehicle under test is determined based on the plurality of evaluation indexes and corresponding target indexes, wherein the target indexes are generated based on the vehicle operating parameters, the environmental state parameters and the air conditioner operating parameters.

7. A performance evaluation device for a new energy vehicle air conditioner, characterized in that, The evaluation result of the air conditioner performance of the new energy vehicle under test is determined based on the plurality of evaluation indexes and corresponding target indexes, wherein the target indexes are generated based on the vehicle operating parameters, the environmental state parameters and the air conditioner operating parameters. The parameter data acquisition module is configured to acquire parameter data of the new energy vehicle under test, wherein the parameter data includes vehicle operating parameters of the new energy vehicle under test when in operation, air conditioner operating parameters of an air conditioner carried by the new energy vehicle under test when in operation, and environmental state parameters of an environment in which the new energy vehicle under test is located. The working condition subset clustering module is configured to cluster a plurality of working condition subsets based on the vehicle operating parameters and the environmental state parameters, wherein each working condition subset represents a vehicle operating parameter and an environmental state parameter. The evaluation index calculation module is configured to calculate a plurality of evaluation indexes of the air conditioner performance of the new energy vehicle under test based on the vehicle operating parameters, the environmental state parameters and corresponding air conditioner operating parameters of each working condition subset. The evaluation index calculation module is configured to calculate a plurality of evaluation indexes of the air conditioner performance of the new energy vehicle under test based on the vehicle operating parameters, the environmental state parameters and corresponding air conditioner operating parameters of each working condition subset. The evaluation index calculation module is configured to calculate a plurality of evaluation indexes of the air conditioner performance of the new energy vehicle under test based on the vehicle operating parameters, the environmental state parameters and corresponding air conditioner operating parameters of each working condition subset. The evaluation index calculation module is configured to calculate a plurality of evaluation indexes of the air conditioner performance of the new energy vehicle under test based on the vehicle operating parameters, the environmental state parameters and corresponding air conditioner operating parameters of each working condition subset. The air conditioner operating time is calculated based on the environmental state parameters and the vehicle operating parameters. The air conditioner operating time is calculated based on the environmental state parameters and the vehicle operating parameters. ； wherein, is the running time of the air conditioning system in the first i hour of the day (corresponding to one hour from the i time to the i +1 time), is the total running time of the new energy vehicle to be evaluated throughout the day, is the proportion of travel of the new energy vehicle to be evaluated in the first i hour, is the representation of human thermal comfort at the i time, indicating the dissatisfaction rate of the human body to the ambient temperature in the first i hour.

8. A computer-readable storage medium, characterized in that, The air conditioner operating time is calculated based on the environmental state parameters and the vehicle operating parameters.

9. An electronic device, comprising: The storage medium stores a computer program, and the computer program is used to execute the method of any one of claims 1-6. The processor; The memory is configured to store instructions executable by the processor. The processor is configured to execute the method of any one of claims 1-6.

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