Control method and system for measuring the capacity of air-conditioning users under working conditions based on big data

Abstract

The present invention discloses a control method and system for measuring the performance of air conditioners under user operating conditions based on big data. The method includes: establishing an air conditioner performance database, filtering, verifying, and querying the air conditioner performance database to output the final indoor temperature value that the air conditioner can achieve under set conditions; and operating the air conditioner based on the obtained final indoor temperature value. Based on the air conditioner status data reported to the cloud by individual air conditioners, the present invention sorts and extracts the data content of key fields during each air conditioner startup cycle, and classifies and processes the data to obtain the minimum or maximum temperature that can be achieved in the room under different conditions. The obtained value is regarded as the cooling or heating capacity of the air conditioner in the user's home under various operating conditions, and is used to formulate a more optimal cooling strategy for the air conditioner, thereby improving its operating efficiency.

Description

Technical Field

[0001] The present invention relates to the field of air conditioning control technology, and in particular to a control method and system for measuring the performance of air conditioning users under working conditions based on big data. Background Art

[0002] Standalone air conditioners are installed in millions of homes. Their operation in the summer is affected by numerous factors, including the outdoor temperature, room orientation, window layout, wall insulation thickness, user-set fan speed, and user-set gear position. Consequently, their actual operation varies greatly, and the final temperature to which indoor temperatures can be lowered also varies. From a professional perspective, it's possible to calculate the required cooling capacity of a standalone air conditioner by statistically analyzing the various influencing factors within its environment and then using a formula to determine whether the air conditioner can reach the set temperature. However, accurate data on these factors is often not available, making it impossible to calculate the exact cooling capacity. Summary of the Invention

[0003] The purpose of the present invention is to provide a control method and system for measuring the performance of air conditioners under user working conditions based on big data, so as to solve the technical problems in the prior art that all influencing factor data of a single air conditioner cannot be fully obtained, resulting in the inability to accurately calculate the cooling capacity of the air conditioner and the inability to confirm whether the set temperature can be reached.

[0004] The present invention solves the above problems through the following technical solutions:

[0005] The control method based on big data to measure the performance of air conditioner users under working conditions includes:

[0006] Step S1: Establishing an air conditioning capacity database:

[0007] When the air conditioner is turned on, the historical operation data of the air conditioner is judged one by one. If the indoor temperature in the key field of the air conditioner is the same for n consecutive times, and n ≥ 3, the key field content described in the data is recorded. In this way, each data judgment is completed every time the air conditioner is turned on, and all the key field contents at the corresponding time that meet the conditions are recorded and stored in the database to form the air conditioner capacity database;

[0008] Step S2: Screening and filtering the air conditioning capacity database:

[0009] Perform secondary processing on the data in the air conditioning capacity database, retaining the data with only the lowest or highest indoor temperature difference in the key fields of the air conditioning as the final indoor temperature value that the single air conditioning can achieve under the set conditions;

[0010] Step S3: Verify the air conditioning capacity database:

[0011] Verify the filtered air conditioning capacity database to remove interference data that cannot reflect the air conditioning cooling capacity;

[0012] Step S4: query the air conditioning capacity database:

[0013] Automatically match the key field content of the air conditioner and output the corresponding final indoor temperature value that the air conditioner can reach under the set conditions in the air conditioner capacity database;

[0014] Step S5: operate the air conditioner according to the final indoor temperature value obtained.

[0015] As a further improvement, in step S1, each data in the air conditioner startup data is arranged in ascending order of timestamp.

[0016] As a further improvement, the key fields include: outdoor temperature, user-set wind speed level, user-set mode, current time, user-set temperature, air conditioning equipment number and indoor temperature.

[0017] As a further improvement, in step S3, the verification content of the air-conditioning capacity database includes the outdoor temperature and the wind speed level set by the user.

[0018] As a further improvement, in step S4, the automatically matched air-conditioning key field content at least includes the air-conditioning equipment number, outdoor temperature, current time, user-set wind speed level and user-set temperature.

[0019] As a further improvement, in step S4, the user-set wind speed level and the user-set temperature are input through the air conditioner remote controller.

[0020] As a further improvement, the final indoor temperature value is displayed on an air-conditioning remote controller or an air-conditioning panel so that the user can modify the content of the air-conditioning key field.

[0021] As a further improvement, in step S5, the air conditioner is operated according to the final indoor temperature value obtained, and the specific method is as follows:

[0022] When the air conditioner cannot reach the user-set temperature, that is, in cooling mode, the user-set temperature value is less than the final indoor temperature value, the air conditioner will operate according to the final indoor temperature value; in heating mode, the user-set temperature value is greater than the final indoor temperature value, the air conditioner will operate according to the final indoor temperature value;

[0023] When the air conditioner can reach the user-set temperature, that is, in cooling mode, the user-set temperature value ≥ the final indoor temperature value, the air conditioner will operate according to the user-set temperature; in heating mode, the user-set temperature value ≤ the final indoor temperature value, the air conditioner will operate according to the user-set temperature.

[0024] At the same time, the present invention also solves the above problems through the following technical solutions:

[0025] A control system for measuring the performance of air conditioners under user operating conditions based on big data includes: an air conditioner data processor, a big data platform, and an air conditioner remote control. The air conditioner data processor communicates with the big data platform and the air conditioner remote control, and obtains the historical operating data of the air conditioner stored in the big data platform through the air conditioner data processor to establish an air conditioner performance database; and the established air conditioner performance database is screened, filtered, verified, and queried to obtain a final indoor temperature value, and the key field content of the air conditioner operation is adjusted according to the obtained final indoor temperature value, so that the air conditioner can realize the control method for measuring the performance of air conditioners under user operating conditions based on big data as described above.

[0026] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0027] The present invention is based on the air-conditioning status data reported to the cloud by a single air-conditioner, and sorts and extracts the key field data content in each power-on cycle of the air-conditioner, including outdoor temperature, user-set wind speed level, user-set mode, current time, and user-set temperature, and obtains the classified processing. The lowest temperature value or the highest temperature value that can be reached in the room under different outdoor temperatures, wind speed levels, time periods, and indoor set temperatures is obtained, which is regarded as the cooling or heating capacity of the air-conditioner in the user's home under various working conditions, and is stored in a database in the form of multi-dimensional data. By inputting the current environment data into the database at subsequent power-on, the temperature value that the air-conditioner can finally reach can be obtained, which is used to formulate a better cooling strategy for the air-conditioner and improve the working efficiency of the air-conditioner. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of the control method for measuring the capacity of air-conditioning users under working conditions based on big data of the present invention;

[0029] Figure 2 This is a block diagram of a control system for measuring the performance of air-conditioning users under working conditions based on big data according to the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below in conjunction with the drawings in the preferred embodiments of the present application. In the drawings, the same or similar reference numerals throughout represent the same or similar parts or parts with the same or similar functions. The described embodiments are part of the embodiments of the present application, not all of the embodiments. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain the present application, and should not be understood as limitations on the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0031] In the description of this application, it should be noted that, unless expressly provided and limited otherwise, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or display that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or displays.

[0032] The following will be combined Figure 1-2 , a control method and system for measuring the performance of air conditioner users under working conditions based on big data according to an embodiment of the present application are described in detail. It is worth noting that the following embodiments are only used to explain the present application and do not constitute a limitation of the present application.

[0033] Example 1:

[0034] Combined with attachment Figure 1 As shown in FIG, the control method for measuring the capacity of air conditioner users under working conditions based on big data specifically includes the following steps:

[0035] Step S1: Establishing an air conditioning capacity database:

[0036] When the air conditioner is turned on, the historical operating data of the air conditioner is judged one by one. If the indoor temperature in the key field of the air conditioner is the same for n consecutive times, and n ≥ 3, the key field content described at that moment is recorded. In this way, the judgment of each data at each startup is completed, and all the key field contents at the corresponding moments that meet the conditions are recorded and stored in the database to form an air conditioner capacity database.

[0037] In this embodiment, after a single air conditioner is installed in a household, based on the user's usage habits, after the air conditioner is turned on and off multiple times, the cloud can obtain a large amount of historical operating data of the air conditioner's operating status. The cloud stores the historical operating data of the air conditioner in a memory for retrieval the next time the air conditioner is turned on; and each data in the air conditioner startup data is arranged in ascending order by timestamp to facilitate data-by-data judgment.

[0038] Optionally, key fields include: outdoor temperature, user-set wind speed level, user-set mode, current time, user-set temperature, air conditioning equipment number and indoor temperature, etc.

[0039] Step S2: Screening and filtering the air conditioning capacity database:

[0040] Perform secondary processing on the data in the air conditioning capacity database established in step S1, retaining the data in the air conditioning key field that only has different indoor temperatures and the lowest or highest data as the final indoor temperature value that the single air conditioner can achieve under the set conditions;

[0041] Specifically, in this embodiment, the data stored in the air-conditioning capacity database is processed secondary to match the user-set wind speed level, user-set temperature, and outdoor temperature contained in the air-conditioning capacity database with a fixed air-conditioning equipment number in the cooling mode. Usually, there are multiple different indoor temperatures, and only the lowest indoor temperature is retained, and other indoor temperature values ​​under the same conditions are deleted. In theory, this indoor temperature value is regarded as the final indoor temperature value that can be reached by the single air-conditioner under the conditions of the corresponding user-set wind speed level, corresponding outdoor temperature, and corresponding user-set temperature, reflecting the cooling capacity of the single air-conditioner.

[0042] The following is an example using Table 1: Under the same conditions, there are three different indoor temperature values. Only the data corresponding to the indoor temperature of 18°C ​​is retained, and the other two data are deleted.

[0043]

[0044]

[0045] Table 1 Database filtering diagram

[0046] Step S3: Verify the air conditioning capacity database:

[0047] Verify the air conditioning capacity database after filtering in step S2 to remove interference data that cannot reflect the air conditioning cooling capacity;

[0048] Specifically, in this embodiment, the air conditioning capacity database after processing in step S2 still has problems such as insufficient data collection under certain working conditions and unstable working conditions caused by users opening doors and windows. In this case, it cannot reflect the actual cooling capacity of the air conditioner and needs to be verified and eliminated according to normal logic. The verification content includes outdoor temperature, user-set wind speed level, etc.

[0049] The following is an example of Table 2: As shown in the following table, the outdoor temperature can reach the set temperature of 18°C ​​at both 31°C and 33°C, but it cannot reach 18°C ​​at 32°C, which is obviously not in line with common sense. Therefore, the corresponding data is deleted.

[0050]

[0051] Table 2 Database verification diagram

[0052] Step S4: query the air conditioning capacity database:

[0053] Automatically match key air conditioning field contents such as air conditioning equipment number, outdoor temperature, indoor temperature, user-set temperature, user-set wind speed level, and user-set mode, and output the corresponding final indoor temperature value in the air conditioning capability database;

[0054] Specifically, in this embodiment, after the air conditioning equipment number, outdoor temperature, current time, user-set wind speed level and user-set temperature fixed value are input through the air conditioning remote control, the corresponding indoor temperature value in the air conditioning capability database is automatically output, which can be displayed on the air conditioning remote control or on the air conditioning panel for the user to observe whether it meets the user's needs, so as to modify the content of the air conditioning key fields for the user to make adjustments.

[0055] The following is an example using Table 3: When the air conditioner number D3N8006 is input, the outdoor temperature is 31°C, the set wind speed is 1, and the indoor set temperature is 18°C, the output indoor temperature of 18°C ​​represents the temperature value that the indoor temperature can reach under the environmental conditions.

[0056] Air Conditioner Number Outdoor temperature Set wind speed Indoor temperature Indoor set temperature Is it daytime D3N8006 31℃ 1 18℃ 18℃ yes D3N8006 33℃ 1 18℃ 18℃ yes D3N8006 34℃ 1 18.3℃ 18℃ yes D3N8006 35℃ 1 18.2℃ 18℃ yes D3N8006 36℃ 1 18.1℃ 18℃ yes

[0057] Table 3. Database table data after processing

[0058] Step S5: operate the air conditioner according to the final indoor temperature value obtained in step S4.

[0059] When the air conditioner cannot reach the user-set temperature, that is, in cooling mode, the user-set temperature value is less than the final indoor temperature value, the air conditioner will operate according to the final indoor temperature value; in heating mode, the user-set temperature value is greater than the final indoor temperature value, the air conditioner will operate according to the final indoor temperature value;

[0060] When the air conditioner can reach the user-set temperature, that is, in cooling mode, the user-set temperature value ≥ the final indoor temperature value, the air conditioner will operate according to the user-set temperature; in heating mode, the user-set temperature value ≤ the final indoor temperature value, the air conditioner will operate according to the user-set temperature.

[0061] For example: when the air conditioner cannot reach the temperature set by the user, such as the set temperature in cooling mode is 16℃, the final indoor temperature value can only reach 20℃. The frequency of the air conditioner compressor will always be at the highest speed, and the energy consumption will be relatively high. If the air conditioner knows that it can only reach 20℃ in the end, it will run according to the set temperature of 20℃. When it is about to reach 20℃, the frequency of the compressor will be gradually reduced, thus achieving energy saving.

[0062] When the air conditioner can reach the user-set temperature, for example, the user-set temperature is 20℃, the final indoor temperature value can also reach 20℃. The air conditioner itself will reach 20℃ as quickly as possible before starting to reduce the compressor frequency. Because the frequency reduction timing is too late, the actual indoor temperature will usually drop to lower than the set temperature, such as 19℃. When we know that the air conditioner can reach 20℃ in this environment, we can start to reduce the frequency when the indoor temperature reaches 21℃, and finally reach 20℃ smoothly, thus achieving energy saving.

[0063] This invention utilizes a network of air conditioners, with individual units reporting real-time operating status data to a big data platform. This data can then be processed using cloud-based algorithms to achieve various functional optimization requirements, providing a robust technical environment for product optimization. By predicting the expected indoor temperature each time the air conditioner is turned on, a more optimal cooling process can be developed, ensuring rapid room cooling while maximizing energy savings, bringing significant practical value to users.

[0064] Example 2:

[0065] Refer to Figure 2 A control system for measuring the performance of air conditioners under user operating conditions based on big data is used to implement the control method for measuring the performance of air conditioners under user operating conditions based on big data as described in Example 1, comprising: an air conditioner data processor, a big data platform, an air conditioner remote control, and a control panel, wherein the air conditioner data processor communicates with the big data platform and the air conditioner remote control; the air conditioner data processor obtains historical operating data of the air conditioner stored in the big data platform to establish an air conditioner performance database; and the established air conditioner performance database is screened, filtered, verified, and queried to obtain a final indoor temperature value, and the key field content of the air conditioner operation is adjusted according to the obtained final indoor temperature value, so that the air conditioner can reach a preset temperature value, thereby achieving better cooling efficiency control and realizing efficient operation of the air conditioner.

[0066] In the specific implementation process, the indoor temperature in the air conditioning key field is the same for n consecutive times, and the relatively stable temperature of the indoor temperature is taken, that is, there is no temperature change for 3 consecutive minutes. Of course, it can also be a time interval in which there is no temperature change at other times.

[0067] Under the same external environment, which specifically includes the outdoor temperature, user-set fan speed, user-set temperature, and whether it is daytime, only the lowest indoor temperature value is retained, and the corresponding data of other indoor temperature values ​​under this environment are deleted. Of course, since the air conditioner has both cooling and heating modes, the temperature can also be retained at the highest indoor temperature value to control the heating capacity in heating mode.

[0068] Although the present invention is described herein with reference to illustrative embodiments of the present invention, the above embodiments are merely preferred embodiments of the present invention, and the embodiments of the present invention are not limited to the above embodiments. It should be understood that those skilled in the art can design many other modifications and implementations, which will fall within the scope and spirit of the principles disclosed in this application.

Claims

1. A control method for measuring the capacity of air-conditioning users under working conditions based on big data, characterized in that: include: Step S1: Establishing an air conditioning capacity database: When the air conditioner is turned on, the historical operating data of the air conditioner is judged one by one. If the indoor temperature in the key field of the air conditioner is the same for n consecutive times, and n ≥ 3, the key field content described in the data is recorded. In this way, each data judgment is completed every time the air conditioner is turned on, and all the key field contents at the corresponding time that meet the conditions are recorded and stored in the database to form an air conditioner capacity database; the key fields include: outdoor temperature, user-set wind speed level, user-set mode, current time, user-set temperature, air conditioner device number and indoor temperature; Step S2: Screening and filtering the air conditioning capacity database: Perform secondary processing on the data in the air conditioning capacity database, retaining the data with only the lowest or highest indoor temperature difference in the key fields of the air conditioning as the final indoor temperature value that the single air conditioning can achieve under the set conditions; Step S3: Verify the air conditioning capacity database: Verify the filtered air conditioning capacity database to remove interference data that cannot reflect the air conditioning cooling capacity; Step S4: query the air conditioning capacity database: Automatically match the content of key fields of the air conditioner and output the final indoor temperature value that the air conditioner can reach under the set conditions in the air conditioner capability database; the content of the key fields of the air conditioner that are automatically matched includes at least the air conditioner equipment number, outdoor temperature, current time, user-set wind speed level and user-set temperature; Step S5: operating the air conditioner according to the final indoor temperature value obtained; the specific method is: When the air conditioner cannot reach the user-set temperature, that is, in cooling mode, the user-set temperature value is less than the final indoor temperature value, the air conditioner will operate according to the final indoor temperature value; in heating mode, the user-set temperature value is greater than the final indoor temperature value, the air conditioner will operate according to the final indoor temperature value; When the air conditioner can reach the user-set temperature, that is, in cooling mode, the user-set temperature value ≥ the final indoor temperature value, the air conditioner will operate according to the user-set temperature; in heating mode, the user-set temperature value ≤ the final indoor temperature value, the air conditioner will operate according to the user-set temperature.

2. The control method for measuring the performance of air-conditioning users under working conditions based on big data according to claim 1 is characterized in that: In step S1, each data in the air conditioner startup data is arranged in ascending order of timestamp.

3. The control method for measuring the performance of air-conditioning users under working conditions based on big data according to claim 1 is characterized in that: In step S3, the verification content of the air conditioning capacity database includes the outdoor temperature and the wind speed level set by the user.

4. The control method for measuring the performance of air-conditioning users under working conditions based on big data according to claim 1 is characterized in that: In step S4, the user-set wind speed level and the user-set temperature are input via the air conditioner remote controller.

5. The control method for measuring the performance of air conditioner users under working conditions based on big data according to any one of claims 1 to 4, characterized in that: The final indoor temperature value is displayed on the air conditioner remote controller or the air conditioner panel so that the user can modify the content of the key field of the air conditioner.

6. A control system based on big data to measure the capacity of air-conditioning users under working conditions, characterized by: include: An air conditioner data processor, a big data platform, and an air conditioner remote control. The air conditioner data processor communicates with the big data platform and the air conditioner remote control. The air conditioner data processor obtains historical operating data of the air conditioner stored in the big data platform to establish an air conditioner capability database. The established air conditioning capacity database is screened, filtered, verified and queried to obtain the final indoor temperature value, and the key field content of the air conditioning operation is adjusted according to the obtained final indoor temperature value, so that the air conditioner can realize the control method of measuring the capacity of the air conditioner under the working conditions based on big data as described in any one of claims 1-5.

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