Data processing method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a data processing method and device, equipment, a storage medium and a program product. The method comprises the following steps: receiving in-vehicle environment data collected by an average thermal sensation index (PMV) measuring device; acquiring a human body metabolic rate and clothing thermal resistance set for the current test; according to the in-vehicle environment data, the human body metabolic rate and the clothes thermal resistance, determining a corresponding PMV value; the PMV value and the in-vehicle environment data are displayed, the in-vehicle environment factors and the user factors are considered, the accurate PMV value can be obtained, the two parameters of the human body metabolic rate and the clothes thermal resistance are adjusted according to the test requirements, different parameters are set for different users, the test requirements of different scenes are met, and the test efficiency is improved. And finally, the data is displayed, so that a tester can more intuitively display the data.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a data processing method, device, equipment, storage medium and program product. Background Art

[0002] In recent years, the automobile industry has developed rapidly. Vehicle air conditioning is an indispensable device for improving riding comfort, and it plays a major role in creating a thermal environment in the car. Vehicle air conditioning is generally controlled manually or automatically. Manual control is for users to manually adjust the air flow parameters of the air conditioner according to their needs. Automatic control is to detect parameters such as temperature and humidity in the car through sensors, and feed these parameters back to the vehicle's control system. The control system adjusts the air flow parameters of the air conditioner according to the parameters, thereby achieving automatic control.

[0003] The Predicted Mean Vote (PMV) is an evaluation index that characterizes the thermal response of the human body. Its value range is -3 to +3, corresponding to the cold and hot sensations of the human body. In the above automatic control method, the PMV value is used as the temperature and humidity control parameters of the vehicle to meet the user's comfort needs. In the existing vehicle air conditioning test and evaluation methods, the factors that affect user comfort mainly include temperature, humidity, etc., and only environmental factors are considered, and the PMV results obtained are not accurate enough. Summary of the invention

[0004] The embodiments of the present application provide a data processing method, apparatus, device, storage medium and program product to solve the problem that only environmental factors are considered in the evaluation of in-vehicle air conditioning testing, resulting in inaccurate test results.

[0005] In a first aspect, an embodiment of the present application provides a data processing method, including:

[0006] Receiving in-vehicle environment data collected by a PMV measuring device for measuring the average thermal sensation index;

[0007] Get the human metabolic rate and clothing thermal resistance for the current test setup;

[0008] Determining a corresponding PMV value according to the in-vehicle environment data, the human metabolic rate, and the clothing thermal resistance;

[0009] The PMV value and the in-vehicle environment data are displayed, wherein the in-vehicle environment data at least includes one or more of an air temperature value, a humidity value, a radiation temperature value, and a wind speed value.

[0010] In a possible implementation, the human metabolic rate and clothing thermal resistance for the current test setting are obtained in the following manner:

[0011] Displaying the user's human metabolic rate corresponding to at least one age group and clothing thermal resistance corresponding to at least one season;

[0012] In response to the parameter setting request, a human metabolic rate and clothing thermal resistance for the current test setting are obtained.

[0013] In a possible implementation, the method further includes:

[0014] If any of the air temperature value, humidity value, radiation temperature value or wind speed value in the in-vehicle environment data is missing, the missing data is supplemented.

[0015] In a possible implementation, the method further includes:

[0016] If any of the air temperature value, humidity value, radiation temperature value or wind speed value in the vehicle interior environment data is missing, determining the number of missing data;

[0017] If the missing times reaches the preset times, and the missing data is the air temperature value, a data missing prompt message is generated and the calculation of the PMV value is stopped;

[0018] If the number of missing times reaches a preset number, and the missing data is a humidity value, a radiation temperature value, or a wind speed value, the missing data is supplemented.

[0019] In a possible implementation, the completing the missing data includes:

[0020] Get the data closest in time to the missing data, and use the data closest in time to complete the missing data.

[0021] In a possible implementation manner, determining the corresponding PMV value according to the air temperature value, humidity value, radiation temperature value, wind speed value, human metabolic rate and clothing thermal resistance includes:

[0022] Calculating a metabolic rate conversion coefficient according to the human body metabolic rate, and calculating a sweat evaporation rate according to the metabolic rate conversion coefficient;

[0023] Calculate heat transfer according to the air temperature value, clothing surface temperature value and thermal conductivity, and calculate human body surface area according to the radiation temperature value;

[0024] Calculating a corresponding PMV value according to the metabolic rate conversion coefficient, the sweat evaporation rate, the heat transfer and the human body surface area;

[0025] Among them, the thermal conductivity coefficient is determined by the air temperature value and the radiation temperature value; the clothing surface temperature value is determined by the radiation temperature value, the metabolic conversion coefficient, the radiation multiplier correction value and the clothing insulation value; the radiation multiplier correction value is determined by the wind speed value and the air speed value correction coefficient; the clothing insulation value is determined by the clothing thermal resistance.

[0026] In a possible implementation manner, the displaying the PMV value and the in-vehicle environment data includes:

[0027] displaying a temperature value curve graph in a first area in the user interface, the temperature value curve graph including the temperature value;

[0028] Displaying a humidity graph, a radiation temperature graph, and a wind speed graph in a second area of ​​the user interface, the humidity graph including the humidity value, the radiation temperature graph including the radiation temperature value, and the wind speed graph including the wind speed value;

[0029] A PMV graph is displayed in a third area in the user interface, the PMV graph including the PMV value.

[0030] In a second aspect, an embodiment of the present application provides a data processing device, including:

[0031] A data receiving module, used for receiving the in-vehicle environment data collected by the mean thermal sensation index PMV measuring device;

[0032] A parameter setting module, used to obtain the human metabolic rate and clothing thermal resistance for the current test setting;

[0033] A data calculation module, used to determine a corresponding PMV value according to the in-vehicle environment data, the human metabolic rate and the clothing thermal resistance;

[0034] The data display module is used to display the PMV value and the in-vehicle environmental data, wherein the in-vehicle environmental data at least includes one or more of air temperature value, humidity value, radiation temperature value and wind speed value.

[0035] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0036] The memory stores computer-executable instructions;

[0037] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0038] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0039] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0040] The data processing method, device, equipment, storage medium and program product provided in the embodiments of the present application receive the in-vehicle environment data collected by the PMV measuring device, and the in-vehicle environment data at least includes one or more of air temperature value, humidity value, radiation temperature value and wind speed value, obtain the human metabolic rate and clothing thermal resistance set for the current test, calculate the corresponding PMV value according to the in-vehicle environment data, human metabolic rate and clothing thermal resistance obtained above, and display the PMV value and the in-vehicle environment data. During the test, not only the in-vehicle environment factors but also the user's own factors are considered, and a more accurate PMV value can be obtained. Moreover, the two parameters of human metabolic rate and clothing thermal resistance are adjusted according to the test requirements, and different parameters are set for different users to meet the test requirements of different scenarios. Finally, the data is displayed so that the test personnel can view the corresponding data more intuitively. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0042] Figure 1 A schematic diagram of a scenario of the data processing method provided in this application;

[0043] Figure 2 Schematic diagram of the data processing method provided for this application Figure 1 ;

[0044] Figure 3 Schematic diagram of the data processing method provided for this application Figure 2 ;

[0045] Figure 4 Schematic diagram of the structure of the electronic device for the data processing method provided in this application Figure 1 ;

[0046] Figure 5 Schematic diagram of the structure of the electronic device for the data processing method provided in this application Figure 2 ;

[0047] Figure 6A schematic diagram of a user interface for the data processing method provided in this application;

[0048] Figure 7 A schematic diagram of the structure of the data processing device provided by this application;

[0049] Figure 8 Structural diagram of the electronic device provided for this application Figure 3 .

[0050] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0051] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0052] Figure 1 A schematic diagram of a scenario of the data processing method provided in this application, such as Figure 1 As shown, the specific application scenarios of the present application include: a PMV measuring device 101 and a host computer 102, the PMV measuring device 101 reports the collected in-vehicle environment data to the host computer 102, the in-vehicle environment data at least includes one or more of air temperature value, humidity value, radiation temperature value and wind speed value, the host computer 102 obtains the air temperature value, humidity value, radiation temperature value and wind speed value from the in-vehicle environment data; the host computer 102 obtains the human metabolic rate and clothing thermal resistance set for the current test; the host computer 102 determines the corresponding PMV value according to the air temperature value, humidity value, radiation temperature value and wind speed value, human metabolic rate and clothing thermal resistance; the host computer 102 displays the PMV value and the in-vehicle environment data. During the test, not only the in-vehicle environment factors but also the user's own factors are considered, and a more accurate PMV value can be obtained, and the two parameters of human metabolic rate and clothing thermal resistance are adjusted according to the test requirements, and different parameters are set for different users to meet the test requirements of different scenarios, and finally the data is displayed so that the test personnel can view the corresponding data more intuitively.

[0053] Combining the above scenarios, it can be seen that in the prior art, only environmental factors are considered in the in-vehicle air conditioning test and evaluation, resulting in inaccurate test results.

[0054] The data processing method provided in the present application receives the in-vehicle environment data collected by the PMV measuring device, and the in-vehicle environment data includes at least one or more of air temperature value, humidity value, radiation temperature value and wind speed value, obtains the human metabolic rate and clothing thermal resistance set for the current test, calculates the corresponding PMV value according to the above-obtained data, and displays the PMV value and the in-vehicle environment data. During the test, not only the in-vehicle environment factors but also the user's own factors are considered, and a more accurate PMV value can be obtained. Moreover, the two parameters of human metabolic rate and clothing thermal resistance are adjusted according to the test requirements, and different parameters are set for different users to meet the test requirements of different scenarios. Finally, the data is displayed so that the test personnel can view the corresponding data more intuitively.

[0055] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0056] Figure 2 Schematic diagram of the data processing method provided for this application Figure 1 ,like Figure 2 As shown, the method includes:

[0057] Step 201: receiving in-vehicle environment data collected by a PMV measuring device.

[0058] Among them, the Predicted Mean Vote (PMV) is an evaluation index that characterizes the thermal response of the human body. Its value range is -3 to +3, corresponding to the cold and hot sensations of the human body, respectively. Environmental factors that affect PMV include temperature, humidity, wind speed, and radiation temperature.

[0059] The executor of this embodiment is an electronic device, the PMV measuring device is a wireless PMV measuring device, the electronic device is wirelessly connected to the PMV measuring device, the PMV measuring device includes a temperature and humidity sensor, a wind speed sensor and a radiation temperature sensor, the temperature and humidity sensor is used to collect air temperature and humidity values, the wind speed sensor is used to collect wind speed values ​​in the environment, and the radiation temperature sensor is used to collect radiation temperature values.

[0060] Specifically, during the test process, the PMV measuring device actively reports the collected in-vehicle environment data to the electronic device at preset intervals. The in-vehicle environment data includes at least one or more of air temperature, humidity, radiation temperature and wind speed values. Because the time node of each sensor data may be slightly different, and each sensor is set to the same data transmission frequency, due to some reasons, such as problems with the data transmission frequency caused by low battery level, when calculating the PMV value, in order to be more accurate, the air temperature, humidity, radiation temperature and wind speed values ​​corresponding to the same time are obtained from the in-vehicle environment data.

[0061] Step 202, obtaining the human body metabolic rate and clothing thermal resistance for the current test setting.

[0062] In this embodiment, the human metabolic rate and clothing thermal resistance set for the current test are obtained. The human metabolic rate sets multiple human metabolic rates based on different age groups for testing, and the clothing thermal resistance sets multiple clothing thermal resistances based on different seasons for testing. The test user can set different parameters for the current test as needed.

[0063] Step 203, determining the corresponding PMV value according to the in-vehicle environment data, the human metabolic rate and the thermal resistance of clothing.

[0064] In this embodiment, the PMV value corresponding to the same time is calculated based on the air temperature value, humidity value, radiation temperature value, wind speed value, human metabolic rate and clothing thermal resistance. Specifically, the metabolic rate conversion coefficient, sweat evaporation rate, heat transfer and human body surface area are calculated based on the air temperature value, humidity value, radiation temperature value, wind speed value, human metabolic rate and clothing thermal resistance, and then the PMV value corresponding to the same time is calculated based on the metabolic rate conversion coefficient, sweat evaporation rate, heat transfer and human body surface area.

[0065] Step 204, displaying the PMV value and the in-vehicle environment data.

[0066] In this embodiment, the PMV value and the in-vehicle environment data are displayed. Optionally, the PMV value and the in-vehicle environment data are displayed in the form of a curve graph, so that the tester can view the data more intuitively.

[0067] The data processing method provided in the embodiment of the present application receives the in-vehicle environment data collected by the PMV measuring device, and the in-vehicle environment data includes at least one or more of air temperature value, humidity value, radiation temperature value and wind speed value, obtains the human metabolic rate and clothing thermal resistance set for the current test, calculates the PMV value corresponding to the same time according to the above-obtained data, and displays the PMV value and the in-vehicle environment data. During the test, not only the in-vehicle environment factors but also the user's own factors are considered, and a more accurate PMV value can be obtained. Moreover, the two parameters of human metabolic rate and clothing thermal resistance are adjusted according to the test requirements, and different parameters are set for different users to meet the test requirements of different scenarios. Finally, the data is displayed so that the test personnel can view the corresponding data more intuitively.

[0068] Figure 3 Schematic diagram of the data processing method provided for this application Figure 2 ,like Figure 3 As shown, in this embodiment Figure 2 Based on the embodiment, the data processing method is described in detail, and the method includes:

[0069] Step 301, receiving the in-vehicle environment data collected by the mean thermal sensation index PMV measuring device.

[0070] The executor of this embodiment is an electronic device, the PMV measuring device is a wireless PMV measuring device, the electronic device is wirelessly connected to the PMV measuring device, the PMV measuring device includes a temperature and humidity sensor, a wind speed sensor and a radiation temperature sensor, the temperature and humidity sensor is used to collect air temperature and humidity values, the wind speed sensor is used to collect wind speed values ​​in the environment, and the radiation temperature sensor is used to collect radiation temperature values.

[0071] Specifically, the PMV measuring device reports the collected in-vehicle environmental data to the electronic device at preset intervals. The in-vehicle environmental data includes at least one or more of air temperature, humidity, radiation temperature and wind speed values. Because the time node of each sensor data may be slightly different, and each sensor is set to the same data transmission frequency, due to some reasons, such as problems with the data transmission frequency caused by low battery level, when calculating the PMV value, in order to be more accurate, the air temperature, humidity, radiation temperature and wind speed values ​​corresponding to the same time are obtained from the in-vehicle environmental data.

[0072] See also Figure 4The electronic device includes: a data receiving module, a data synchronization module, an abnormality detection module, a data calculation module, a parameter setting module, a data display module, a data storage module and a renaming module, wherein the data receiving module is respectively connected to the data synchronization module and the average thermal sensation index PMV measuring device; the data synchronization module is respectively connected to the abnormality detection module and the data calculation module; the data calculation module is respectively connected to the parameter setting module and the data display module; the data display module is respectively connected to the renaming module and the data storage module. The renaming module is used to name the data corresponding to each sensor to distinguish them.

[0073] Among them, the in-vehicle environment data collected by the PMV device is sent wirelessly to the data receiving module, and the data receiving module is used to receive the in-vehicle environment data collected by the PMV device; the data receiving module is also used to send the in-vehicle environment data to the data synchronization module, and the data synchronization module is used to obtain the air temperature value, humidity value, radiation temperature value and wind speed value corresponding to the same time from the in-vehicle environment data; the data synchronization module sends the acquired air temperature value, humidity value, radiation temperature value and wind speed value corresponding to the same time to the data calculation module, and the data calculation module performs calculations.

[0074] See also Figure 5 The data receiving module also includes a ZigBee receiving module and a decoding module. The ZigBee receiving module receives the in-vehicle environment data reported by the PMV device. ZigBee supports conflict avoidance carrier multi-path listening technology, which reduces network conflicts and data packet loss and improves communication efficiency and security. The ZigBee receiving module sends the in-vehicle environment data to the decoding module, which is used to decode the in-vehicle environment data to obtain air temperature, humidity, radiation temperature and wind speed values, and send them to the data synchronization module.

[0075] Continue to see Figure 5 The data synchronization module also includes a timer and a collection module. Within the timer, such as 1 second, the collection module of the synchronization module collects the sensor data transmitted by the decoding module. If there is repeated collection, only the latest data of the channel is retained. If there is data missing, it is handled by the anomaly detection module. If there is no anomaly, the data is directly updated by the data synchronization module. If there is an anomaly, the data is processed by the anomaly detection module before the data is updated.

[0076] Optionally, the method further comprises:

[0077] If any of the air temperature value, humidity value, radiation temperature value or wind speed value in the in-vehicle environment data is missing, the missing data is supplemented.

[0078] In this embodiment, if any data corresponding to the same time in the in-vehicle environment data is missing, the missing data is supplemented. For details, see Figure 4 If the abnormality detection module detects that any data in the in-vehicle environment data is missing, it will send a missing prompt to the data synchronization module. Data synchronization is also used to complete the missing data. If the abnormality detection module detects that any data in the in-vehicle environment data is missing, the missing number of the missing data will be increased by one.

[0079] Optionally, the method further comprises:

[0080] If any of the air temperature value, humidity value, radiation temperature value or wind speed value in the in-vehicle environment data is missing, the number of times the missing data is missing is determined; if the number of missing times reaches the preset number of times, and the missing data is the air temperature value, a data missing prompt message is generated and the calculation of the PMV value is stopped; if the number of missing times reaches the preset number of times, and the missing data is the humidity value, radiation temperature value or wind speed value, the missing data is completed.

[0081] In this embodiment, if any of the air temperature value, humidity value, radiation temperature value or wind speed value corresponding to the same time in the in-vehicle environment data is missing, the number of times the missing data is missing is determined, and the number of times the missing data is missing is compared with a preset number, wherein the preset number is set according to actual conditions, such as being set to three times. If the number of times the missing data is missing reaches three times, and the missing data is the air temperature value, a data missing prompt message is generated and the calculation of the PMV value is stopped; if the number of times the missing data is missing reaches three times, and the missing data is the humidity value, radiation temperature value or wind speed value, a value can be assigned to continue the calculation, i.e., the missing data is completed.

[0082] Specifically, the anomaly detection module is used to determine the number of missing data. If the number of missing data reaches a preset number and the missing data is an air temperature value, the anomaly detection module generates a data missing prompt message, stops calculating the PMV value, and sends the data missing prompt message to the data display module. The data display module is used to display the data missing prompt message to promptly notify the test user when an abnormal situation is detected; if the number of missing data reaches a preset number and the missing data is a humidity value, a radiation temperature value, or a wind speed value, the anomaly detection module notifies the data synchronization module, and the data synchronization module completes the missing data.

[0083] Continue to see Figure 5 The anomaly detection module includes an anomaly counter, a data verification module, and an anomaly handling module. The anomaly counter is used to accumulate the number of missing data. The data verification module is used to determine the number of missing data and compare the number of missing data with the preset number. The anomaly handling module is used to generate data missing prompt information.

[0084] Optionally, complete the missing data, including:

[0085] Get the data closest in time to the missing data, and use the data closest in time to complete the missing data.

[0086] In this embodiment, the PMV measuring device reports at preset intervals, and the preset time can be set to 1s. When supplementing the missing data, the data with the latest time distance can be selected, and the missing data can be supplemented with the data with the closest time distance, so as to reduce the error of the PMV value. Specifically, the data synchronization module is used to obtain the data with the closest time distance to the missing data, and the missing data can be supplemented with the data with the closest time distance. By detecting abnormal situations, the missing data can be supplemented in time.

[0087] Step 302, obtaining the human body metabolic rate and clothing thermal resistance for the current test setting.

[0088] In this embodiment, the human metabolic rate and clothing thermal resistance set for the current test are obtained. The human metabolic rate sets multiple human metabolic rates based on different age groups for testing, and the clothing thermal resistance sets multiple clothing thermal resistances based on different seasons for testing. The test user can set different parameters for the current test as needed.

[0089] See also Figure 4 The parameter setting module is used to obtain the human metabolic rate and clothing thermal resistance for the current test setting. The parameter setting module sends the obtained human metabolic rate and clothing thermal resistance for the current test setting to the data calculation module. The data calculation module calculates the PMV value corresponding to the same time based on the air temperature value, humidity value, radiation temperature value, wind speed value, human metabolic rate and clothing thermal resistance.

[0090] Optionally, obtain the human metabolic rate and clothing thermal resistance for the current test setup by:

[0091] Display the human metabolic rate of the user corresponding to at least one age group and the clothing thermal resistance corresponding to at least one season; in response to a parameter setting request, obtain the human metabolic rate and clothing thermal resistance for the current test setting.

[0092] Specifically, the human metabolic rate of users corresponding to at least one age group and the clothing thermal resistance corresponding to at least one season are saved in advance, the human metabolic rate of users corresponding to at least one age group and the clothing thermal resistance corresponding to at least one season are displayed, the test user sets the human metabolic rate and clothing thermal resistance required for the current test according to the test requirements, responds to the user's parameter setting request in the user interface, parses the request, and obtains the human metabolic rate and clothing thermal resistance set for the current test. Moreover, the tester can directly set the clothing thermal resistance and human metabolic rate, which simplifies the setting process of clothing thermal resistance and human metabolic rate, and improves the usability of the software.

[0093] See Table 1, which shows the pre-saved human metabolic rates. Different ages and genders have corresponding human metabolic rates. The test user selects the corresponding metabolic rate from the pre-saved human metabolic rates according to the test requirements, that is, sets the human metabolic rate required for the current test.

[0094] Table 1 Classification of human metabolic rate

[0095] age male female 11～15 1.44 1.37 16～20 1.32 1.26 20～30 1.16 1.1 31～40 1.17 1.11 40～50 1.13 1.08 ＞51 1.1 1.04

[0096] See Table 2, which shows the pre-saved clothing thermal resistance. Corresponding clothing thermal resistance is set for different seasons or indoors or outdoors. The test user selects the corresponding clothing thermal resistance from the pre-saved clothing thermal resistance according to the test requirements, that is, sets the clothing thermal resistance required for the current test.

[0097] Table 2 Clothing thermal resistance classification table

[0098]

[0099]

[0100] It should be noted that the human metabolic rate and clothing thermal resistance are not limited to the data in Table 1 and Table 2 above, but may also be other suitable data.

[0101] Step 303, determining the corresponding PMV value according to the in-vehicle environment data, the human metabolic rate and the thermal resistance of clothing.

[0102] In this embodiment, the corresponding PMV value is calculated based on the in-vehicle environment data, the human metabolic rate and the thermal resistance of clothing. Specifically, the metabolic rate conversion coefficient, sweat evaporation rate, heat transfer and human body surface area are calculated based on the air temperature value, humidity value, radiation temperature value and wind speed value, the human metabolic rate and the thermal resistance of clothing. Then, based on the metabolic rate conversion coefficient, sweat evaporation rate, heat transfer and human body surface area, the corresponding PMV value at the same time is calculated.

[0103] In a possible implementation, the corresponding PMV value is determined according to the in-vehicle environment data, the human metabolic rate, and the thermal resistance of clothing, including:

[0104] The metabolic rate conversion coefficient is calculated according to the human metabolic rate, and the sweat evaporation rate is calculated according to the metabolic rate conversion coefficient; the heat transfer is calculated according to the air temperature value, the clothing surface temperature value and the thermal conductivity coefficient, and the human body surface area is calculated according to the radiation temperature value; the corresponding PMV value is calculated according to the metabolic rate conversion coefficient, the sweat evaporation rate, the heat transfer and the human body surface area; among which, the thermal conductivity coefficient is determined by the air temperature value and the radiation temperature value; the clothing surface temperature value is determined by the radiation temperature value, the metabolic conversion coefficient, the radiation multiplier correction value and the clothing insulation value; the radiation multiplier correction value is determined by the wind speed value and the air speed value correction coefficient; the clothing insulation value is determined by the thermal resistance of the clothing.

[0105] In this embodiment, the human metabolic rate for the current test setting is substituted into the formula to calculate the metabolic rate conversion coefficient, and the formula is expressed as:

[0106] m f =m1×58.2 Formula (1)

[0107] Among them, m f is the metabolic rate conversion coefficient, and m1 is the human metabolic rate.

[0108] Specifically, the metabolic rate conversion coefficient is substituted into the formula to calculate the sweat evaporation rate, which is expressed as:

[0109] s r =0.42×(m f -58.15) Formula (2)

[0110] Among them, s r is the sweat evaporation rate, m f is the metabolic rate conversion factor.

[0111] Specifically, the air temperature value, the clothing surface temperature value and the thermal conductivity coefficient are substituted into the formula to calculate the heat transfer, which is expressed as:

[0112] h f =h t ×(t c -t a ) Formula (3)

[0113] Among them, h f is the heat transfer, h t is the thermal conductivity, t c is the clothing surface temperature, t a is the air temperature value.

[0114] Furthermore, the radiation temperature is substituted into the formula to calculate the human body surface area, which is expressed as:

[0115] s a=0.202×t r 0.725 Formula (4)

[0116] Among them, s a is the human body surface area, t r is the radiation temperature.

[0117] Furthermore, the metabolic rate conversion coefficient, sweat evaporation rate, heat transfer and human body surface area are substituted into the formula to calculate the PMV value corresponding to the same time. The formula is expressed as:

[0118]

[0119] Where, P is the PMV value, m f is the metabolic rate conversion coefficient, s r is the sweat evaporation rate, h f is the heat transfer, s a is the human body surface area.

[0120] Specifically, the heat transfer coefficient is determined by the air temperature value and the radiation temperature value. Substituting the air temperature value and the radiation temperature value into the formula to calculate the heat transfer coefficient, the formula is expressed as:

[0121] h t =2.38×|t a -t r | 0.25 Formula (6)

[0122] Among them, h t is the thermal conductivity, t a is the air temperature, t r is the radiation temperature value.

[0123] Specifically, the clothing surface temperature value is determined by the radiation temperature value, the metabolic conversion coefficient, the radiation multiplier correction value and the clothing insulation value. The radiation temperature value, the metabolic conversion coefficient, the radiation multiplier correction value and the clothing insulation value are substituted into the formula to calculate the clothing surface temperature value. The formula is expressed as follows:

[0124] t c =t r +0.067×m f -r c -0.1×i c Formula (7)

[0125] Among them, tc is the surface temperature of the clothing, t r is the radiation temperature value, m f is the metabolic rate conversion coefficient, r c is the radiation multiplier correction value, i c Thermal insulation value of clothing.

[0126] Specifically, the radiation multiplier correction value is determined by the wind speed value and the air speed value correction coefficient. The wind speed value and the air speed value correction coefficient are substituted into the formula to calculate the air speed value correction coefficient. The formula is expressed as follows:

[0127] r c =3.96×a s 0.5 -a f Formula (8)

[0128] Among them, r c is the radiation multiplier correction value, a s is the wind speed value, a f is the correction factor for air velocity value.

[0129] Specifically, the air speed correction coefficient is determined by the wind speed value. The wind speed value is substituted into the formula to calculate the air speed correction coefficient. The formula is expressed as:

[0130]

[0131] Among them, a f is the correction factor of air velocity, a s is the wind speed value.

[0132] Specifically, the thermal insulation value of clothing is determined by the thermal resistance of clothing. Specifically, the thermal resistance of clothing in the current test setting is substituted into the formula to calculate the thermal insulation conversion coefficient of clothing, which is expressed as:

[0133] c f =c×0.155 Formula (10)

[0134] Among them, c f is the clothing insulation conversion coefficient, and c is the clothing thermal resistance.

[0135] Furthermore, the clothing insulation conversion coefficient is substituted into the formula to calculate the clothing insulation value, which is expressed as:

[0136] i c =0.155×c f Formula (11)

[0137] Among them, i c is the thermal insulation value of clothing, c f Conversion factor for clothing insulation.

[0138] Step 304, display a temperature value graph in the first area of ​​the user interface; display a humidity graph, a radiation temperature graph and a wind speed graph in the second area of ​​the user interface, the humidity graph including humidity values; display a PMV graph in the third area of ​​the user interface; the temperature value graph includes temperature values; the humidity graph includes humidity values, the radiation temperature graph includes radiation temperature values, the wind speed graph includes wind speed values; the PMV graph includes PMV values.

[0139] In this embodiment, the PMV value and the in-vehicle environment data are displayed. Optionally, the PMV value and the in-vehicle environment data are displayed in the form of a curve graph, so that the tester can view the data more intuitively.

[0140] Specifically, the data calculation module sends the PMV value to the data display module, which is used to display the PMV value and the in-vehicle environment data. The data display module is connected to the data storage module, which is used to store the calculated PMV value.

[0141] See also Figure 6 The user interface includes a first area, a second area and a third area. A temperature value curve graph is displayed in the first area. The temperature value curve graph includes the temperature values ​​obtained above and the temperature values ​​previously reported by the PMV measuring device. For example, the temperature value is reported at every preset time interval, the preset time is 1s, and the temperature curve graph includes multiple temperature values ​​at preset time intervals.

[0142] Specifically, a humidity graph is displayed in the second area, the humidity graph includes the humidity values ​​obtained above and the humidity values ​​previously reported by the PMV measuring device, and the humidity graph includes multiple humidity values ​​at preset time intervals; a radiation temperature graph is displayed in the second area, the radiation temperature graph includes the radiation temperature values ​​obtained above and the radiation temperature values ​​previously reported by the PMV measuring device, and the radiation temperature graph includes multiple radiation temperature values ​​at preset time intervals; a wind speed graph is displayed in the second area, including the wind speed values ​​obtained above and the wind speed values ​​previously reported by the PMV measuring device, and the wind speed graph includes multiple wind speed values ​​at preset time intervals, and different graphs are distinguished by legends, graph colors, and graph names.

[0143] Specifically, a PMV curve graph is displayed in the third area, the PMV curve graph includes the above-calculated PMV value and the previously calculated PMV value, and the PMV curve graph includes multiple PMV values ​​at preset time intervals. In addition, the user interface also includes a fourth area, in which control buttons are displayed, and the control buttons are used to control the overall process and set parameters.

[0144] The data processing method provided by the embodiment of the present application not only considers the environmental factors in the vehicle but also the user's own factors during the test, and can obtain a relatively accurate PMV value. Moreover, the two parameters of human metabolic rate and clothing thermal resistance are adjusted according to the test requirements, and different parameters are set for different users to meet the test requirements of different scenarios. Finally, the data is displayed so that the test personnel can view the corresponding data more intuitively. By detecting abnormal situations, the missing data can be supplemented in time. Moreover, the test personnel can directly set the clothing thermal resistance and human metabolic rate, which simplifies the setting process of clothing thermal resistance and human metabolic rate, and improves the ease of use of the software.

[0145] Figure 7 A schematic diagram of the structure of the data processing device provided in this application, such as Figure 7 As shown, the data processing device 70 provided in this embodiment includes:

[0146] The data receiving module 701 is used to receive the in-vehicle environment data collected by the PMV measuring device. The parameter setting module 702 is used to obtain the human metabolic rate and clothing thermal resistance for the current test setting. The data calculation module 703 is used to determine the corresponding PMV value based on the in-vehicle environment data, the human metabolic rate and the clothing thermal resistance. The data display module 704 is used to display the PMV value and the in-vehicle environment data, and the in-vehicle environment data at least includes one or more of the air temperature value, the humidity value, the radiation temperature value and the wind speed value.

[0147] In a possible implementation, the data display module 704 is further configured to display the human metabolic rate of the user corresponding to at least one age group and the clothing thermal resistance corresponding to at least one season. The parameter setting module 702 is further configured to obtain the human metabolic rate and clothing thermal resistance for the current test setting in response to a parameter setting request.

[0148] In a possible implementation, it also includes: a data synchronization module.

[0149] The data synchronization module is used to complete the missing data if any of the air temperature value, humidity value, radiation temperature value or wind speed value in the in-vehicle environment data is missing.

[0150] In a possible implementation, the data processing device further includes: an anomaly detection module.

[0151] The abnormality detection module is used to determine the number of missing data if any of the air temperature value, humidity value, radiation temperature value or wind speed value in the in-vehicle environment data is missing. The abnormality detection module is also used to generate a data missing prompt message and stop calculating the PMV value if the number of missing data reaches a preset number and the missing data is the air temperature value; the data synchronization module 702 is also used to complete the missing data if the number of missing data reaches a preset number and the missing data is the humidity value, radiation temperature value or wind speed value.

[0152] In a possible implementation, the data synchronization module is further used to obtain data that is closest in time to the missing data, and use the data that is closest in time to complete the missing data.

[0153] In a possible implementation, the data calculation module 703 is also used to calculate the metabolic rate conversion coefficient according to the human metabolic rate, and calculate the sweat evaporation rate according to the metabolic rate conversion coefficient; calculate the heat transfer according to the air temperature value, the clothing surface temperature value and the thermal conductivity coefficient, and calculate the human body surface area according to the radiation temperature value; calculate the corresponding PMV value according to the metabolic rate conversion coefficient, the sweat evaporation rate, the heat transfer and the human body surface area; wherein the thermal conductivity coefficient is determined by the air temperature value and the radiation temperature value; the clothing surface temperature value is determined by the radiation temperature value, the metabolic conversion coefficient, the radiation multiplier correction value and the clothing insulation value; the radiation multiplier correction value is determined by the wind speed value and the air speed value correction coefficient; the clothing insulation value is determined by the clothing thermal resistance.

[0154] In one possible implementation, the data display module 704 is also used to display a temperature value curve graph in the first area of ​​the user interface, the temperature value curve graph includes temperature values; to display a humidity curve graph, a radiation temperature curve graph and a wind speed curve graph in the second area of ​​the user interface, the humidity curve graph includes humidity values, the radiation temperature curve graph includes radiation temperature values, and the wind speed curve graph includes wind speed values; and to display a PMV curve graph in the third area of ​​the user interface, the PMV curve graph includes PMV values.

[0155] The data processing device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be described in detail here.

[0156] Figure 8 This is a schematic diagram of the structure of the electronic device provided in this application. Figure 8 As shown, the electronic device 80 provided in this embodiment includes: at least one processor 801 and a memory 802. Optionally, the device 80 also includes a communication component 803. The processor 801, the memory 802 and the communication component 803 are connected via a bus 804.

[0157] In a specific implementation process, at least one processor 801 executes the computer-executable instructions stored in the memory 802, so that at least one processor 801 executes the above method.

[0158] The specific implementation process of the processor 801 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0159] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0160] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0161] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0162] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0163] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0164] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0165] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0166] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0167] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0168] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0169] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0170] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0171] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A data processing method, characterized in that: include: Receiving in-vehicle environment data collected by a PMV measuring device for measuring the average thermal sensation index; Get the human metabolic rate and clothing thermal resistance for the current test setup; Determining a corresponding PMV value according to the in-vehicle environment data, the human metabolic rate, and the clothing thermal resistance; The PMV value and the in-vehicle environment data are displayed, wherein the in-vehicle environment data at least includes one or more of an air temperature value, a humidity value, a radiation temperature value, and a wind speed value.

2. The method according to claim 1, characterized in that Obtain the human metabolic rate and clothing thermal resistance for the current test setup by: Displaying the user's human metabolic rate corresponding to at least one age group and clothing thermal resistance corresponding to at least one season; In response to the parameter setting request, a human metabolic rate and clothing thermal resistance for the current test setting are obtained.

3. The method according to claim 1, characterized in that Also includes: If any of the air temperature value, humidity value, radiation temperature value or wind speed value in the in-vehicle environment data is missing, the missing data is supplemented.

4. The method according to claim 1, characterized in that: Also includes: If any of the air temperature value, humidity value, radiation temperature value or wind speed value in the vehicle interior environment data is missing, determining the number of missing data; If the missing times reaches the preset times, and the missing data is the air temperature value, a data missing prompt message is generated and the calculation of the PMV value is stopped; If the number of missing times reaches a preset number, and the missing data is a humidity value, a radiation temperature value, or a wind speed value, the missing data is supplemented.

5. The method according to claim 3 or 4, characterized in that: The method of completing the missing data includes: Get the data closest in time to the missing data, and use the data closest in time to complete the missing data.

6. The method according to any one of claims 1 to 4, characterized in that: The determining of the corresponding PMV value according to the in-vehicle environment data, the human metabolic rate and the clothing thermal resistance includes: Calculating a metabolic rate conversion coefficient according to the human body metabolic rate, and calculating a sweat evaporation rate according to the metabolic rate conversion coefficient; Calculate heat transfer according to the air temperature value, clothing surface temperature value and thermal conductivity, and calculate human body surface area according to the radiation temperature value; Calculating a corresponding PMV value according to the metabolic rate conversion coefficient, the sweat evaporation rate, the heat transfer and the human body surface area; Among them, the thermal conductivity coefficient is determined by the air temperature value and the radiation temperature value; the clothing surface temperature value is determined by the radiation temperature value, the metabolic conversion coefficient, the radiation multiplier correction value and the clothing insulation value; the radiation multiplier correction value is determined by the wind speed value and the air speed value correction coefficient; the clothing insulation value is determined by the clothing thermal resistance.

7. The method according to any one of claims 1 to 4, characterized in that: The displaying of the PMV value and the in-vehicle environment data includes: displaying a temperature value curve graph in a first area in the user interface, the temperature value curve graph including the temperature value; Displaying a humidity graph, a radiation temperature graph, and a wind speed graph in a second area of ​​the user interface, the humidity graph including the humidity value, the radiation temperature graph including the radiation temperature value, and the wind speed graph including the wind speed value; A PMV graph is displayed in a third area in the user interface, the PMV graph including the PMV value.

8. A data processing device, characterized in that: include: A data receiving module, used for receiving the in-vehicle environment data collected by the mean thermal sensation index PMV measuring device; A parameter setting module, used to obtain the human metabolic rate and clothing thermal resistance for the current test setting; A data calculation module, used to determine a corresponding PMV value according to the in-vehicle environment data, the human metabolic rate and the clothing thermal resistance; The data display module is used to display the PMV value and the in-vehicle environmental data, wherein the in-vehicle environmental data at least includes one or more of air temperature value, humidity value, radiation temperature value and wind speed value.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

11. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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