An air conditioner intelligent control method, system, storage medium and program product

Abstract

An air conditioner intelligent control method, system, storage medium and program product, in the method, it is judged whether there is no shielding air conditioner in the preset range of key area; if there is, it is determined to output air conditioner; the output parameter of the output air conditioner is determined, and the first instruction is sent to the output air conditioner; if there is not, respectively determine the conveying air duct of each air conditioner in the preset range of air conditioner wind conveying to the key area; the target operating parameter of each air conditioner is obtained; the target operating power of the air conditioner is calculated according to the target operating parameter; the corresponding recommended score is calculated by using weighted average algorithm according to the final air direction of each conveying air duct and the target operating power of each air conditioner; the optimal output air conditioner with the highest recommended score is determined, and the second instruction is sent to the optimal output air conditioner to make the output air conditioner run according to the corresponding target operating parameter. For improving the accuracy of air conditioner control by controlling the operating parameters of air conditioner, and then adjusting the environmental parameters of key area to target parameters.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of air conditioning system control, and particularly relates to an air conditioner intelligent control method and system, a storage medium and a program product. BACKGROUND

[0002] With the wide application of air conditioners in large buildings and industrial sites, the precision control of air conditioner air becomes particularly important. In special scenarios such as biological laboratories and article storage rooms, the precision requirements for parameters such as temperature, humidity, and flow rate in the air environment are extremely high. However, traditional air conditioning systems mostly use a single water pump or multiple water pumps with the same operating frequency to circulate refrigerant medium. Due to the large interval between the operating frequency adjustment gears of the water pump during operation, the circulation flow control in the pipeline is not accurate enough, and the demand of high-precision scenarios cannot be met.

[0003] In the related technology, the operating parameters of the air conditioner output air conditioner air are obtained, and the operating frequency of a first chilled water pump in an operating state is obtained. The operating parameters are compared with target parameters to determine a deviation parameter. The deviation parameter and the operating frequency are used to determine a to-be-adjusted frequency. The operating state of a second chilled water pump in a resting state and the first chilled water pump is controlled according to the to-be-adjusted frequency, so that the deviation parameter is 0.

[0004] The above technical solution compares the operating parameters of the air conditioner with the target parameters to determine the deviation parameter, and then controls the operating frequency to make the deviation parameter 0. However, in special scenarios, if only the parameters output by the air conditioner are the same as the target parameters, since the air sent by the air conditioner needs a certain time to reach the key area, and during this period, it may also encounter blockage or other problems, the environmental parameters in the key area may not be the same as the target parameters, which may reduce the accuracy of air conditioner control. SUMMARY

[0005] The application provides an air conditioner intelligent control method and system, a storage medium and a program product, which are used to improve the accuracy of air conditioner control by controlling the operating parameters of the air conditioner, and then adjust the environmental parameters in the key area to the target parameters.

[0006] In a first aspect, the application provides an air conditioner intelligent control method, which determines whether a non-shielded air conditioner is located in a preset range of a key area. The non-shielded air conditioner is an air conditioner without objects between the air conditioner and the key area.

[0007] If the non-shielded air conditioner exists, the output air conditioner in the non-shielded air conditioner closest to the key area is determined.

[0008] The output parameters of the output air conditioner are determined according to the target parameters, and a first instruction is sent to the output air conditioner to make the output air conditioner operate according to the output parameters.

[0009] If not, determine the delivery air duct of each air conditioner in the preset range for delivering air conditioner air to the key area, the delivery air duct including delivery length, number of barriers, barrier heat conduction parameter and final air direction;

[0010] Input the target parameter, delivery length, number of barriers and barrier heat conduction parameter into an air conditioner operating parameter calculation function to obtain the target operating parameter of each air conditioner;

[0011] Calculate the target operating power of the air conditioner according to the target operating parameter;

[0012] Calculate the corresponding recommended score using a weighted average algorithm according to the final air direction of each delivery air duct and the target operating power of each air conditioner;

[0013] Determine the optimal output air conditioner with the highest recommended score and send a second instruction to the optimal output air conditioner to make the output air conditioner operate according to the corresponding target operating parameter.

[0014] By adopting the above technical solution, first, the method determines whether there is an unobstructed air conditioner in the preset range of the key area. If there is, the air conditioner closest to the key area is selected as the output air conditioner, and the output parameter of the output air conditioner is directly determined according to the target parameter. Since there is no object between the unobstructed air conditioner and the key area, the cold air can be directly delivered, and the heat transfer efficiency is the highest, so the unobstructed air conditioner is selected to minimize the loss of cold energy and reduce energy consumption. Secondly, if there is no unobstructed air conditioner, the method analyzes the delivery air duct of each air conditioner in the preset range, including delivery length, number of barriers and parameters, air direction, etc. The target operating parameter and power of each air conditioner are obtained by combining the target parameter through the air conditioner operating parameter calculation function, and the corresponding recommended score is calculated using a weighted average algorithm. This process takes into account the influence of the blockage of the air duct on the refrigeration effect and energy consumption, and through mathematical modeling, the optimal output air conditioner selection and control scheme are obtained. Compared with simply selecting the nearest air conditioner or average output, this method can achieve fine intelligent control in complex scenarios while meeting temperature requirements and minimizing energy consumption. By controlling the operating parameters of the air conditioner, the accuracy of air conditioner control is improved, and the environmental parameters of the key area are adjusted to the target parameters.

[0015] In combination with some embodiments of the first aspect, in some embodiments, determining whether there is an unobstructed air conditioner in the preset range of the key area specifically includes:

[0016] Obtain a three-dimensional map of the preset range of the key area;

[0017] Determine a plurality of air conditioners in the three-dimensional map;

[0018] Connect each air conditioner with the center point of the key area in the three-dimensional graph to obtain a plurality of connection lines;

[0019] Determine whether there is an object on each connection line;

[0020] If there is an object, the air conditioner corresponding to the connection line is not a non-shielded air conditioner;

[0021] If there is no object, the air conditioner corresponding to the connection line is a non-shielded air conditioner.

[0022] By adopting the above technical scheme, through the information expression of the three-dimensional space, the spatial layout and the shielding relationship are intuitively reflected, and reliable data basis is provided for subsequent judgment. Three-dimensional modeling makes the originally abstract spatial information intuitive and visual, which helps to improve the rationality and accuracy of decision-making. The simple algorithm of connection line judgment avoids complex space collision detection and other operations, while ensuring the accuracy of judgment, improving the calculation efficiency. Especially in the scene of multiple air conditioners and complex layout, this method can quickly filter out non-shielded air conditioners, saving time for generating optimization solutions. The clear non-shielded determination provides a direct basis for the output of the optimal air conditioner. The geometric analysis result based on the three-dimensional model has high reliability. Once it is determined that there is a non-shielded air conditioner, the optimal solution can be directly locked, unnecessary calculation and analysis are avoided, and the advantages in efficiency and effect are very obvious. Even in a dynamically changing environment, this method is still applicable. As long as the three-dimensional graph is updated in real time, the change of the non-shielded condition can be determined at any time, and the output strategy can be quickly responded and adjusted in time. This dynamic adaptive ability further expands the application space of the intelligent control method.

[0023] In combination with some embodiments of the first aspect, in some embodiments, if there is no object, the delivery air duct of each air conditioner in the preset range for delivering air conditioner wind to the key area is determined respectively, specifically including:

[0024] When the connection line contacts the object, the direction of the connection line is changed to pass through the center point to obtain the delivery air duct. The included angle between the new connection line after changing the direction and the connection line vector is not greater than 90 degrees. The connection line vector is a vector with the air conditioner as the origin and the center point of the key area as the direction;

[0025] Record the delivery length, the number of barriers passed through, and the final wind direction of the delivery air duct;

[0026] Determine the barriers passed through according to the delivery air duct and the three-dimensional graph;

[0027] Determine the barrier heat conduction parameter of each barrier passed through according to the barrier passed through.

[0028] By adopting the technical scheme, a physical model of temperature dynamic change is established, and the scientificity of parameter estimation is improved. The function comprehensively considers many factors such as initial temperature, target temperature, air heat loss, air duct length, shelter attribute and the like from the perspective of heat transfer and attenuation, forms a complete temperature change description, makes the analysis and prediction of air conditioner parameters closer to the actual situation, and avoids the randomness of empirical estimation. Through the form of mathematical function, the quantitative description of the relationship between parameters is realized, and the calculation accuracy is enhanced. Each parameter in the function is expressed in a clear mathematical symbol and is connected through integration, summation and product operations to form a close logical system. According to strict numerical calculation of input conditions, accurate quantitative results can be obtained, and compared with qualitative analysis, the error is smaller and the reliability is higher. High-order mathematical tools such as Green function are introduced, and the model is given stronger expression ability. The Green function is an important method for solving non-homogeneous partial differential equations and can describe complex initial-boundary value problems. In the function, heat propagation is converted into a non-homogeneous partial differential equation, and an analytical solution is obtained through the Green function, so that the model can handle more complex heat transport scenarios and expand the application range of intelligent control.

[0029] In combination with some embodiments of the first aspect, in some embodiments, the target operating power of the air conditioner is calculated according to the target operating parameters, specifically comprising:

[0030] The operating current and operating voltage of the air conditioner are determined according to the target operating parameters;

[0031] The target operating power of the air conditioner is calculated according to the operating current and operating voltage.

[0032] By adopting the technical scheme, the dual weight setting enhances the comprehensiveness of the evaluation. In the calculation of the recommended score, the method comprehensively considers two key factors of the final air direction of the air supply duct and the target running power. On the one hand, the air direction weight reflects the accuracy of air supply, the smaller the included angle, the more concentrated the air direction, and the higher the score; on the other hand, the power weight reflects the economy of energy consumption, the smaller the power, the better the energy-saving effect, and the higher the score. The introduction of the dual weight enables the evaluation process to consider both the air supply quality and the energy efficiency, avoids the limitation brought by a single standard, and improves the reliability of the evaluation result. The zoning weighting strategy improves the sensitivity of the evaluation. In the determination of the air direction weight, the method divides different intervals according to the included angle, and the air direction in the interval is given the same weight value. The zoning weighting processing greatly improves the sensitivity of the evaluation to the change of the air direction. When the air direction changes slightly, if it crosses the interval boundary, the weight value will change in steps, thereby affecting the final recommended score. This sensitive characteristic is beneficial to timely discovering and responding to the fluctuation of the air direction, so that the control decision can be dynamically optimized according to the real-time feedback of the air direction, and the adaptability of the system is improved. The weighted average calculation method considers both qualitative and quantitative analysis. The air direction weight represents the qualitative judgment of the conveying effect, and the power weight provides quantitative measurement of energy consumption. By inputting the two types of weights into the weighted calculation function, the qualitative and quantitative analysis are combined through mathematical operation to obtain a quantitative recommended score.

[0033] In combination with some embodiments of the first aspect, in some embodiments, the corresponding recommended score is calculated according to the final air direction of each air supply duct and the target running power of each air conditioner using a weighted average algorithm, specifically including:

[0034] The final air direction of each air supply duct is determined as a first weight or a second weight, the final air direction being the first weight when the included angle between the final air direction and the connecting line vector is located in a first interval, and the final air direction being the second weight when the included angle between the final air direction and the connecting line vector is located in a second interval;

[0035] Each target running power is determined as a third weight or a fourth weight, the target running power being the third weight when the target running power is located in a preset first power interval, and the target running power being the fourth weight when the target running power is located in a preset second power interval;

[0036] The first weight or the second weight, the third weight or the fourth weight is input into a weighted calculation function to obtain the recommended score.

[0037] By adopting the technical scheme, the form of the function makes the calculation process clear and easy to implement. The core step of calculating the recommended score is condensed into a simple mathematical formula, which clearly represents the elements such as wind direction angle, wind direction weight, target power, power weight, etc. with explicit symbols and connects them together through simple algebraic operations. This formalized expression converts the complex calculation logic into a standard mathematical problem, making the implementation of score calculation simple and intuitive, reducing programming complexity and improving calculation efficiency. Mathematical modeling enhances the interpretability and traceability of the calculation process. Through the mathematical function, the influence of wind direction and power on the recommended score is quantified. The smaller the wind direction angle, the higher the wind direction weight, and the higher the recommended score; the smaller the power, the higher the power weight, and the higher the recommended score. This quantitative relationship clearly illustrates the internal logic of score calculation, making the evaluation results more transparent and reliable. When analyzing and explaining the recommended results, the calculation process can be easily traced back to identify the main influencing factors and provide reference for decision optimization. The weighted summation strategy embodies the concept of comprehensive evaluation. In the function, the product of the wind direction weight and the angle reflects the score of the wind direction factor, and the product of the power weight and the target power reflects the score of the energy consumption factor. Adding the two scores together, a comprehensive score that takes into account both wind direction and power is obtained. This weighted summation calculation strategy reflects the comprehensive trade-off of multiple target factors, avoiding bias and one-sidedness, making the evaluation results more comprehensive and balanced. At the same time, this linear combination form is easy to understand and analyze, leaving room for adjustment and optimization.

[0038] In some embodiments in combination with the first aspect, in some embodiments, the weighted calculation function is:

[0039] M = θ·A + P A ·B

[0040] In the formula, M is the recommended score, θ is the angle between the final wind direction and the connecting line vector, A is the first weight or the second weight, P A is the target operating power, and B is the third weight or the fourth weight.

[0041] By adopting the above technical scheme, the recommended score is calculated using the weighted calculation function, making the calculated result more accurate and providing a parameter basis for subsequent selection of the optimal air conditioner.

[0042] In a second aspect, the embodiments of the present application provide an air conditioner intelligent control system, which comprises one or more processors and a memory; the memory is coupled with the one or more processors, and the memory is used to store computer program code, the computer program code comprising computer instructions, and the one or more processors invoke the computer instructions to enable the system to execute the method described in the first aspect and any possible implementation manner of the first aspect.

[0043] In a third aspect, the embodiments of the present application provide a computer readable storage medium, including instructions, when the instructions are run on a system, causing the system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0044] In a fourth aspect, the embodiments of the present application provide a computer program product, characterized by, when the computer program product is run on a system, causing the system to perform the method described in any possible implementation manner of the first aspect.

[0045] The one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0046] 1. The present application provides an intelligent control method for air conditioners. First, the method determines whether there is an unobstructed air conditioner in the preset range of the key area. If there is, the air conditioner closest to the key area is selected as the output air conditioner, and the output parameters of the output air conditioner are directly determined according to the target parameters. Since there is no object between the unobstructed air conditioner and the key area, the cold air can be directly delivered, and the heat transfer efficiency is the highest, so the use of the unobstructed air conditioner can maximize the reduction of cold energy loss and reduce energy consumption. Secondly, if there is no unobstructed air conditioner, the method will analyze the delivery air duct of each air conditioner in the preset range, including the delivery length, the number and parameters of the obstacles, the wind direction, etc. Combined with the target parameters, the target operating parameters and power of each air conditioner are obtained through the air conditioner operating parameter calculation function, and the corresponding recommended score is calculated by the weighted average algorithm. This process takes into account the influence of the air duct obstruction on the cooling effect and energy consumption, and through mathematical modeling, the optimal output air conditioner selection and control scheme are obtained by comparative analysis. Compared with simply selecting the nearest air conditioner or average output, this method can achieve fine intelligent control in complex scenarios, while meeting the temperature demand and minimizing energy consumption. The method is used to control the operating parameters of the air conditioner, improve the accuracy of air conditioner control, and then adjust the environmental parameters of the key area to the target parameters.

[0047] 2、The application provides an air conditioner intelligent control method, which intuitively reflects the space layout and shielding relationship through the information expression of three-dimensional space, and provides a reliable data basis for subsequent judgment. Three-dimensional modeling makes the originally abstract space information intuitive and visual, which helps to improve the rationality and accuracy of decision-making. The simple algorithm of connection judgment avoids complex space collision detection and other operations, improves the calculation efficiency while ensuring the accuracy of judgment. Especially in the scene of multiple air conditioners and complex layout, this method can quickly filter out the unshielded air conditioner, saving time for the generation of optimization scheme. The clear unshielded judgment provides a direct basis for the optimal output air conditioner. The geometric analysis result based on the three-dimensional model has high reliability. Once it is determined that there is an unshielded air conditioner, the optimal solution can be directly locked, unnecessary calculation and analysis are avoided, and the advantages in efficiency and effect are very obvious. Even in a dynamically changing environment, this method is still applicable. As long as the three-dimensional graph is updated in real time, the change of unshielded condition can be judged at any time, and the output strategy can be quickly responded and timely adjusted. This dynamic adaptability further expands the application space of the intelligent control method.

[0048] 3、The application provides an air conditioner intelligent control method, which directly links the target operating parameter with the electrical parameter, enhancing the operability of control. The running state of the air conditioner is finally reflected in the change of current and voltage, and both of these two parameters can be directly measured and adjusted. By introducing the electrical parameter as an intermediate bridge, the conversion between the target parameter and the execution action is more explicit and convenient, which is conducive to improving the accuracy and response speed of control. Power as a comprehensive index comprehensively reflects the energy consumption of air conditioner operation. The product of current and voltage is power, and the size of power directly indicates the power consumption level of the air conditioner. By calculating the target power, the energy consumption after executing the control strategy can be estimated, providing an important basis for energy-saving optimization. At the same time, power is also closely related to the refrigeration effect. The greater the power, the stronger the refrigeration capacity. Therefore, the introduction of the power index enables the control strategy to balance between energy saving and comfort. The idea of step-by-step calculation improves the efficiency and accuracy of solving the target power. First, the current and voltage values suitable for the target operating parameter are determined, and then the power is calculated by substituting the values into the formula. This decomposition makes each step more single and explicit, avoiding the complexity of one-step calculation and improving the calculation efficiency. At the same time, the matching of current and voltage can be quickly realized by table lookup and other methods, reducing unnecessary operations and ensuring the accuracy of the calculation result. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 is a flowchart of an air conditioner intelligent control method in an embodiment of the application.

[0050] Figure 2 is another flowchart of an air conditioner intelligent control method in an embodiment of the application.

[0051] Figure 3 is a physical device structure schematic diagram of an intelligent control system of an air conditioner provided by an embodiment of the present application. DETAILED DESCRIPTION

[0052] The terms used in the following embodiments of the present application are only for the purpose of describing the specific embodiments and are not intended to be limiting of the present application. As used in the specification and the appended claims of the present application, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or," as used in the present application, refers to any or all possible combinations of one or more of the associated listed items.

[0053] Hereinafter, the terms "first" and "second" are used only for the purpose of description and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0054] An application scenario of an embodiment of the present application is described below:

[0055] In the modern medical field, precise environmental control has become an indispensable part of many high-end medical facilities. For example, in the operating room of a certain large hospital, in order to ensure the safety and success rate of the operation process, the requirements for parameters such as temperature, humidity, cleanliness, etc. in the room are extremely strict. The temperature in the operating room usually needs to be maintained between 22-25℃, the relative humidity needs to be controlled between 50%-60%, and the number of suspended particles in the air needs to reach the standard of hundred-level cleanliness.

[0056] However, due to the complexity of the layout in the operating room, the precise control of environmental parameters faces many challenges. First, there are many devices in the operating room, such as surgical lamps, anesthetizing machines, electrocardiogram monitors, etc. The operation of these devices will generate a large amount of heat, which will interfere with the stability of the indoor temperature. Second, the personnel in the operating room frequently enter and exit, and the opening and closing of the door will cause the exchange of indoor and outdoor air, affecting the constancy of indoor humidity and cleanliness. In addition, the surgical area also has special requirements for air flow rate, too high flow rate will increase the risk of wound infection, and too low flow rate will also be difficult to meet the demand of air purification.

[0057] In the face of such complex environmental control requirements, traditional air conditioning systems are not up to the task. These systems often use a single temperature control strategy, which cannot take into account humidity and cleanliness adjustments. At the same time, the air supply mode of traditional air conditioning is difficult to adapt to the special layout of the operating room, which is prone to air flow dead angles and temperature gradients, affecting the environmental stability of the operating area.

[0058] More importantly, the precise control of the operating room environment parameters cannot rely solely on the parameter detection at the air conditioner outlet. Due to the distance between the outlet and the operating area, air is affected by equipment, personnel, and other factors during transmission, resulting in a deviation between the actual parameters of the operating area and the detection values at the outlet. This deviation can pose serious medical risks, such as slight changes in temperature affecting the patient's body temperature regulation, and slight fluctuations in humidity interfering with the normal use of surgical instruments. To solve the above technical problems, the present application provides an intelligent air conditioning control method for improving the accuracy of air conditioning control by controlling the operating parameters of the air conditioner, and then adjusting the environmental parameters of the key area to the target parameters.

[0059] The following will be combined Figure 1 , an intelligent air conditioning control method in the embodiment of the present application is described:

[0060] Please refer to Figure 1 , a flowchart of an intelligent air conditioning control method in the embodiment of the present application.

[0061] S101, determine whether there is an unobstructed air conditioner located in the preset range of the key area;

[0062] The system determines whether there is an unobstructed air conditioner located in the preset range of the key area, and the unobstructed air conditioner is an air conditioner that does not exist between the key area and the object. Specifically, it will be described in another embodiment below, which will not be repeated here.

[0063] S102, determine the output air conditioner in the unobstructed air conditioner closest to the key area;

[0064] If there is, determine the output air conditioner in the unobstructed air conditioner closest to the key area.

[0065] On the basis of determining the unobstructed air conditioner, the system further selects the air conditioner closest to the key area from it as the output air conditioner. The purpose of this step is to find the air conditioner that can send air to the key area in the shortest distance and most direct way.

[0066] The distance between the air conditioner and the key area is an important factor affecting the air supply effect. The shorter the distance, the less energy loss of the air conditioner air during transmission, the higher the speed and stability of the air supply. In addition, the closest air conditioner also means that its outlet is closest to the horizontal line connecting the key area, and the transmission path of the air conditioner air is the most direct and least affected by air disturbance.

[0067] Continuing with the above example of the operating room, after determining that air conditioner C is an unobstructed air conditioner, the system begins to calculate the distance between it and the operating table. Through the calculation of spatial coordinates, it is found that air conditioner C is located directly above the operating table, with a vertical distance of 2 meters, which is the shortest among the three air conditioners. Therefore, the system determines air conditioner C as the optimal output air conditioner and focuses on controlling its outlet parameters to achieve precise adjustment of the environment around the operating table.

[0068] S103, determining the output parameters of the output air conditioner according to the target parameters, and sending a first instruction to the output air conditioner to make the output air conditioner run according to the output parameters;

[0069] After determining the optimal output air conditioner, the system begins to determine the specific working parameters of the output air conditioner according to the preset target parameters. The target parameters usually include temperature, humidity, cleanliness, etc. environmental indicators, which are set according to the specific needs of the key area. The task of the system is to adjust the running state of the output air conditioner so that the output air conditioner can adjust the environmental parameters of the key area to the target value.

[0070] This process involves complex parameter matching and conversion. The system needs to consider factors such as the performance parameters of the air conditioner, the spatial relationship between the output air conditioner and the key area, etc. through a series of calculations and optimizations to obtain the best output parameter combination. These parameters may include air conditioner outlet temperature, air speed, air direction, etc., which are key factors affecting the environment of the key area.

[0071] Taking the operating room as an example, assume that the target temperature of the area around the operating table is 22℃ and the target humidity is 55%. The system first obtains the performance parameters of air conditioner C, such as refrigerating capacity, air supply capacity, etc. Then, combined with the distance, height difference, etc. spatial parameters between air conditioner C and the operating table, through heat transfer and fluid mechanics calculations, the optimal outlet parameters of air conditioner C are obtained: temperature 20℃, air speed 1.5m / s, and the angle between the air direction and the center line of the operating table is 30 degrees.

[0072] After determining the output parameters, the system sends control instructions to air conditioner C to adjust its compressor power, fan speed, etc. running parameters, so that it works according to the optimal parameters calculated. Under the continuous output of air conditioner C, the environmental parameters around the operating table will gradually approach and stabilize at the target value, achieving precise control of the key area.

[0073] S104, respectively determine the delivery air duct of each air conditioner in the preset range to deliver air conditioner air to the key area, the delivery air duct includes delivery length, number of barriers, barrier heat conduction parameter and final air direction.

[0074] If not, respectively determine the delivery air duct of each air conditioner in the preset range to deliver air conditioner air to the key area, the delivery air duct includes delivery length, number of barriers, barrier heat conduction parameter and final air direction. Specifically: when the connecting line contacts the object, change the direction of the connecting line to pass through the center point to obtain the delivery air duct, the angle between the new connecting line after changing the direction and the connecting line vector is not greater than 90 degrees, and the connecting line vector is a vector with the air conditioner as the origin and the center point of the key area as the direction.

[0075] Record the delivery length, number of barriers and final air direction of the delivery air duct;

[0076] Determine the barrier according to the delivery air duct and the three-dimensional map;

[0077] Determine the barrier heat conduction parameter of each barrier according to the barrier.

[0078] In the case of only one output air conditioner, the control of the system is relatively simple and direct. But in practical application, due to the complexity of indoor environment, often need multiple air conditioners to work together to realize the environmental control of the key area. This requires the system to consider the air supply of all air conditioners in the preset range, and determine the optimal delivery air duct for each air conditioner.

[0079] Delivery air duct refers to the air flow path between the air outlet of the air conditioner and the key area. It not only includes the straight-line distance, but also involves barriers in the air duct, air direction change and other factors. These factors will affect the transmission efficiency and effect of air conditioner air. Therefore, the system needs to analyze the indoor layout and spatial relationship to plan the optimal air supply path for each air conditioner.

[0080] Take a large server room as an example, there are multiple server racks in the room, which need strict temperature and humidity control for stable operation. The system sets the area where the racks are located as the key area, and sets a preset range with this as the center. Within this range, there are A, B and C three air conditioners.

[0081] The system first obtains the three-dimensional model of the server room, and then calculates the connecting line between each air conditioner and the key area. By analyzing the position relationship between the connecting line and the server racks and other barriers, the system finds that the connecting line of air conditioner A will pass through a rack, the connecting line of air conditioner B will not be directly blocked, but will be disturbed by the server rack cooling air, and the connecting line of air conditioner C is relatively open and not blocked and disturbed.

[0082] According to these analysis results, the system generates a delivery air duct model for each air conditioner. The air duct of air conditioner A needs to bypass the blocking rack, and the air direction will change twice by 90 degrees; the air duct of air conditioner B is straight, but it will be affected by the rack cooling air near the key area; the air duct of air conditioner C is basically coincident with the connecting line, the air direction is stable, and the transmission efficiency is the highest.

[0083] The system records the length, air direction change times, and the number of encountered obstructions in the air duct model. These parameters will be important inputs for subsequent calculations to assess the air supply effect and energy consumption level of each air conditioner.

[0084] S105, input the target parameters, delivery length, number of obstructions encountered, and heat conduction parameters of the obstructions into the air conditioner operation parameter calculation function to obtain the target operation parameters of each air conditioner;

[0085] The system inputs the target parameters, delivery length, number of obstructions encountered, and heat conduction parameters of the obstructions into the air conditioner operation parameter calculation function to obtain the target operation parameters of each air conditioner.

[0086] After determining the delivery air duct of each air conditioner, the system needs to further calculate the optimal operation parameters of each air conditioner to achieve precise control of the key area environment. This process needs to consider various factors such as target environmental parameters and air duct characteristics, and through complex mathematical models and algorithms, a customized control scheme is obtained.

[0087] The system first inputs the preset target environmental parameters such as temperature, humidity, and cleanliness into the calculation model. These parameters are the basis for evaluating control effectiveness, and the system needs to adjust the operation state of the air conditioner to make the actual environmental parameters of the key area as close as possible to the target value.

[0088] Secondly, the system inputs the characteristic parameters of each delivery air duct, such as air duct length, number of encountered obstructions, and heat conduction performance of obstructions, into the model. These parameters reflect the energy loss and attenuation of air conditioner air during transmission. The longer the air duct and the more obstructions, the lower the temperature and wind speed of air conditioner air when it reaches the key area, and the control effect will be affected.

[0089] The system substitutes these input parameters into a complex air conditioner operation parameter calculation function. This function is based on physical principles such as thermodynamics and fluid mechanics to establish a mathematical model of air conditioner air transmission and heat exchange. By solving this model, the system can obtain the optimal operation parameters of each air conditioner, such as compressor power, fan speed, and air outlet temperature.

[0090] Taking the server room of the previous step as an example, assume that the target temperature is 22℃ and the target humidity is 55%. The system inputs these target values, along with the air duct parameters of air conditioners A, B, and C, into the calculation function. After complex iterative calculations, the system obtains the following results:

[0091] Air conditioner A: Due to the long air duct and obstructions, the compressor power needs to be increased by 20%, the fan speed needs to be increased by 30%, and the outlet air temperature needs to be reduced to 18℃, in order to reach the target temperature at the end of the air duct.

[0092] Air conditioner B: Due to the interference of rack cooling air in the air duct, the fan speed needs to be increased by 15%, and the outlet air temperature needs to be appropriately increased to 24℃ to offset the influence of the cooling air.

[0093] Air conditioner C: Since the air duct conditions are optimal, it only needs to run according to the standard parameters to meet the target requirements.

[0094] S106, calculate the target running power of the air conditioner according to the target running parameters;

[0095] The system calculates the target running power of the air conditioner according to the target running parameters. Specifically, the running current and running voltage of the air conditioner are determined according to the target running parameters.

[0096] The target running power of the air conditioner is calculated based on the running current and running voltage.

[0097] In this step, the system needs to calculate the target running power of each air conditioner according to the target running parameters obtained earlier. The target running power refers to the power size that the air conditioner should run in order to achieve the expected cooling / heating effect. This calculation process can be divided into two parts:

[0098] First, the system determines the running current and running voltage of the air conditioner according to the target running parameters. The running current and voltage of the air conditioner are two key factors that affect its power. The target running parameters include information such as target temperature, air speed, mode, etc. The system can calculate appropriate current and voltage values based on these parameters and the characteristics of the air conditioner itself, such as compressor power, fan power, etc. This process needs to consider multiple factors such as the energy efficiency ratio of the air conditioner, the type of refrigerant, etc., to balance the relationship between cooling / heating demand and energy consumption.

[0099] Secondly, after obtaining the running current and voltage, the system can calculate the target running power accordingly. The formula for calculating electric power is: P (power) = I (current) x U (voltage), with the unit being watts (W) or kilowatts (kW). For example, if a air conditioner has a running current of 5 amperes and a running voltage of 220 volts, its running power is 1100 watts, i.e. 1.1 kilowatts. The system will perform this calculation process for each air conditioner, ultimately obtaining a set of target running power data.

[0100] As a specific example: Suppose there are 3 air conditioners in an office area, according to environmental needs and equipment characteristics, the system calculates their target running parameters as follows:

[0101] Air conditioner A: target temperature 25℃, medium speed, dehumidification mode, running current 3A, running voltage 220V

[0102] Air conditioner B: target temperature 26℃, high speed, cooling mode, running current 4A, running voltage 220V

[0103] Air conditioner C: target temperature 24℃, low speed, air supply mode, running current 2A, running voltage 220V

[0104] According to the electric power calculation formula, the target running power of the three air conditioners can be obtained as follows:

[0105] Air conditioner A: 3A x 220V = 660W = 0.66kW

[0106] Air conditioner B: 4A x 220V = 880W = 0.88kW

[0107] Air conditioner C: 2A x 220V = 440W = 0.44kW

[0108] In this way, the system obtains the target running power corresponding to each air conditioner. These power data will provide an important basis for subsequent intelligent decision-making, helping the system to reduce energy consumption as much as possible while meeting cooling / heating needs, and improving the overall efficiency of the air conditioning system. At the same time, the system can also dynamically adjust the running power of the air conditioner according to real-time electricity prices, equipment health, and other external factors, to further optimize energy use.

[0109] S107, according to the final air direction of each air supply duct and the target running power of each air conditioner, a weighted average algorithm is used to calculate the corresponding recommended score;

[0110] The system calculates the corresponding recommended score using a weighted average algorithm according to the final air direction of each delivery air duct and the target operating power of each air conditioner. Specifically, the final air direction of each delivery air duct is determined as a first weight or a second weight. When the included angle between the final air direction and the connecting line vector is in the first interval, the final air direction is the first weight. When the included angle between the final air direction and the connecting line vector is in the second interval, the final air direction is the second weight.

[0111] The target operating power of each air conditioner is determined as a third weight or a fourth weight. When the target operating power is in a preset first power interval, the target operating power is the third weight. When the target operating power is in a preset second power interval, the target operating power is the fourth weight.

[0112] The first weight or the second weight, the third weight or the fourth weight is input into a weighted calculation function to obtain the recommended score. The weighted calculation function is:

[0113] M = θ·A + P A ·B

[0114] In the formula, M is the recommended score, θ is the included angle between the final air direction and the connecting line vector, A is the first weight or the second weight, P A is the target operating power, and B is the third weight or the fourth weight.

[0115] After calculating the target operating power of each air conditioner, the system needs to further evaluate their contribution to the target area environmental control in order to select the optimal output air conditioner. This evaluation process can be realized by calculating the recommended score. The calculation of the recommended score needs to consider two key factors: the final air direction of the delivery air duct and the target operating power of the air conditioner.

[0116] Regarding the final air direction of the delivery air duct, the system first classifies it and assigns weights. The closeness of the air direction to the ideal air direction (i.e. the direction of the connecting line vector) determines the influence effect of the air duct on the target area. The system sets two included angle intervals. When the included angle between the final air direction and the connecting line vector falls into the first interval, it is considered that the air duct can better send cold air to the target position, so a higher weight (first weight) is assigned. Conversely, if the included angle falls into the second interval, it means that the guiding effect of the air duct is poor, so a lower weight (second weight) is assigned. This classification and weight mechanism can objectively evaluate the air guiding performance of different delivery air ducts.

[0117] As for the target operating power of the air conditioner, the system adopts a similar classification weighting method. According to the size of the air conditioner power, it is divided into two preset power intervals. The air conditioner in the first power interval represents its refrigeration / heating capacity is stronger, which can provide more significant temperature control effect for the target area, so it is given a higher weight (the third weight); the air conditioner in the second power interval represents the temperature control effect is relatively weak, and is given a lower weight (the fourth weight).

[0118] Again, taking the 3 air conditioners in the office area as an example, suppose the system sets the following classification standards and weights according to the actual situation:

[0119] Wind direction weight: when the included angle is less than 30°, the first weight (A=5) is given; when the included angle is greater than or equal to 30°, the second weight (A=2) is given

[0120] Power weight: when the power is greater than 0.7kW, the third weight (B=3) is given; when the power is less than or equal to 0.7kW, the fourth weight (B=1) is given

[0121] Suppose the calculated final wind direction of the 3 air supply ducts is 25°, 40°, and 15°, respectively, and the included angle with the connecting line vector is 25°, 40°, and 15°, respectively, then the corresponding recommended score is calculated as follows:

[0122] Air conditioner A: M=25×5+0.66×1=125.66

[0123] Air conditioner B: M=40×2+0.88×3=82.64

[0124] Air conditioner C: M=15×5+0.44×1=75.44

[0125] S108, determine the optimal output air conditioner with the highest recommended score, and send a second instruction to the optimal output air conditioner to operate according to the corresponding target operating parameters.

[0126] After obtaining the recommended score of each air conditioner, the system will make the final decision to select the optimal output air conditioner and control it to operate according to the target operating parameters. This step aims to achieve intelligent and refined air conditioner control to achieve ideal temperature effect and energy efficiency level.

[0127] Firstly, the system will compare the recommended scores of each air conditioner to find out one or more air conditioners with the highest score. The highest recommended score means that the air conditioner is evaluated as the most suitable device to undertake the target area environmental regulation task after considering the air supply performance and refrigeration / heating capacity. This selection method can fully utilize the characteristics and advantages of each air conditioner, avoid blind average allocation or fixed collocation, and thus improve the efficiency and flexibility of the entire air conditioning system.

[0128] If there are multiple air conditioners with the same highest score, the system also needs to make a selection among them. One common way to handle this is to further compare the performance of these air conditioners in individual indicators, such as operating power, energy efficiency ratio, health degree, etc., to select the best one. Another way is to consider the location and interconnection of each air conditioner in the network topology, and select the one that works best with other air conditioners. If necessary, the system can also enable multiple highest-score air conditioners to work together to serve the target area. These measures help optimize the selection and arrangement of air conditioners in detail.

[0129] After determining the optimal output air conditioner, the system will send it operating instructions, requiring it to work strictly according to the target operating parameters (such as temperature, wind speed, mode, etc.) calculated earlier. These parameters are carefully set after considering environmental needs, device characteristics, energy consumption budget, etc., and represent the optimal control strategy under the current state. After receiving the instructions, the air conditioner's embedded controller will be responsible for parsing the instruction content, adjusting the working state of components such as compressors and fans, and monitoring the running effect in real time through temperature, humidity, etc. sensors, and if necessary, will also report status data to form a closed-loop feedback control.

[0130] The above embodiment has the following beneficial effects:

[0131] First, the method determines whether there is an unobstructed air conditioner in the preset range of the key area. If there is, the unobstructed air conditioner closest to the key area is selected as the output air conditioner, and the output parameters of the output air conditioner are directly determined according to the target parameters. Since there is no obstruction between the unobstructed air conditioner and the key area, the cold air can be directly delivered, and the heat transfer efficiency is the highest, so the priority selection can maximize the reduction of cold loss and energy consumption. Secondly, if there is no unobstructed air conditioner, the method analyzes the delivery air duct of each air conditioner in the preset range, including the delivery length, the number and parameters of the obstructions, the wind direction, etc., and combines the target parameters to obtain the target operating parameters and power of each air conditioner through the air conditioner operating parameter calculation function, and calculates the corresponding recommended score using the weighted average algorithm. This process takes into account the impact of the obstruction of the air duct on the cooling effect and energy consumption, and through mathematical modeling, the optimal output air conditioner selection and control scheme are obtained. Compared with simply selecting the nearest air conditioner or average output, this method can achieve fine and intelligent control in complex scenarios, while meeting the temperature demand and minimizing energy consumption. The method is used to control the operating parameters of the air conditioner, improve the accuracy of air conditioner control, and then adjust the environmental parameters of the key area to the target parameters.

[0132] The scientificity of parameter estimation is improved. The function considers many factors such as initial temperature, target temperature, air heat loss, air duct length, and shelter properties from the perspective of heat transfer and attenuation, forming a complete description of temperature change, making the analysis and prediction of air conditioning parameters more close to the actual situation, and avoiding the randomness of empirical estimation. Through the form of mathematical function, the quantitative description of the relationship between parameters is realized, and the accuracy of calculation is enhanced. The parameters in the function are expressed in clear mathematical symbols and connected through integration, summation, and multiplication, forming a tight logical system. According to the strict numerical calculation of input conditions, accurate quantitative results can be obtained, with smaller error and higher reliability compared to qualitative analysis. High-order mathematical tools such as Green's function are introduced, giving the model stronger expression ability. Green's function is an important method for solving non-homogeneous partial differential equations and can describe complex initial and boundary value problems. In this function, heat propagation is transformed into a non-homogeneous partial differential equation, and an analytical solution is obtained through Green's function, making the model capable of handling more complex heat transport scenarios and expanding the application scope of intelligent control.

[0133] The target operating parameters are directly linked to electrical parameters, enhancing the operability of control. The running state of the air conditioner is ultimately reflected in the changes of current and voltage, which can be directly measured and adjusted. By introducing electrical parameters as an intermediate bridge, the conversion between target parameters and execution actions is more explicit and convenient, which helps to improve the accuracy and response speed of control. Power is a comprehensive indicator that reflects the energy consumption of air conditioner operation. The product of current and voltage is power, and the size of power directly indicates the power consumption level of the air conditioner. By calculating the target power, the energy consumption after implementing the control strategy can be estimated, providing an important basis for energy optimization. At the same time, power is also closely related to the refrigeration effect, and the greater the power, the stronger the refrigeration capacity. Therefore, the introduction of the power index enables the control strategy to balance between energy saving and comfort. The step-by-step calculation idea improves the efficiency and accuracy of solving the target power. First, determine the current and voltage values that match the target operating parameters, and then substitute them into the formula to calculate the power. This decomposition makes each step more single and clear, avoiding the complexity of one-step calculation and improving the calculation efficiency. At the same time, the matching of current and voltage can be quickly realized through table lookup, reducing unnecessary operations and ensuring the accuracy of the calculation results.

[0134] The setting of dual weights enhances the comprehensiveness of the evaluation. In calculating the recommended score, the method considers two key factors: the final wind direction of the delivery air duct and the target operating power. On the one hand, the wind direction weight reflects the accuracy of air supply. The smaller the included angle, the more concentrated the wind direction, and the higher the score. On the other hand, the power weight embodies the economy of energy consumption. The smaller the power, the better the energy-saving effect, and the higher the score. The introduction of dual weights makes the evaluation process take into account both air supply quality and energy efficiency, avoiding the limitations of a single standard and improving the reliability of the evaluation results. The zoning weighting strategy improves the sensitivity of the evaluation. In determining the wind direction weight, the method divides different intervals according to the size of the included angle, and the wind direction within the interval is given the same weight value. This zoning weighting processing greatly improves the sensitivity of the evaluation to changes in wind direction. When the wind direction changes slightly, if it crosses the interval boundary, the weight value will change in a stepwise manner, affecting the final recommended score. This sensitive characteristic is beneficial for timely discovering and responding to fluctuations in wind direction, enabling control decisions to be dynamically optimized based on real-time feedback of wind direction, thereby improving the adaptability of the system. The weighted average calculation method takes into account both qualitative and quantitative analysis. The wind direction weight represents a qualitative judgment of the delivery effect, while the power weight provides a quantitative measure of energy consumption. By inputting both types of weights into the weighted calculation function and combining qualitative and quantitative analysis through mathematical operations, a quantitative recommended score is obtained.

[0135] The form of the function makes the calculation process clear and easy to implement. The core steps of calculating the recommended score are condensed into a concise mathematical formula, which clearly represents the elements such as wind direction angle, wind direction weight, target power, power weight, etc. with explicit symbols and connects them together through simple algebraic operations. This formalized expression converts the complex calculation logic into a standard mathematical problem, making the implementation of score calculation simple and intuitive, reducing programming complexity and improving calculation efficiency. Mathematical modeling enhances the interpretability and traceability of the calculation process. Through the mathematical function, the influence of wind direction and power on the recommended score is quantified. The smaller the wind direction angle, the higher the wind direction weight, and the higher the recommended score; the smaller the power, the higher the power weight, and the higher the recommended score. This quantitative relationship clearly illustrates the internal logic of score calculation, making the evaluation results more transparent and credible. When analyzing and explaining the recommended results, the calculation process can be easily traced back to identify the main influencing factors and provide reference for decision optimization. The weighted summation strategy embodies the concept of comprehensive evaluation. In the function, the product of the wind direction weight and the angle reflects the score of the wind direction factor, and the product of the power weight and the target power reflects the score of the energy consumption factor. Adding the two scores together, we get the comprehensive score considering both wind direction and power. This weighted summation calculation strategy reflects the comprehensive trade-off of multiple target factors, avoiding bias and one-sidedness, making the evaluation results more comprehensive and balanced. At the same time, this linear combination form is easy to understand and analyze, leaving room for adjustment and optimization.

[0136] Using the weighted calculation function to calculate the recommended score makes the calculated results more accurate, providing parameter basis for subsequent selection of the optimal air conditioner.

[0137] The following describes step S101 in the above embodiment in conjunction with another embodiment. The following describes step S101 in the above embodiment in conjunction with another embodiment. Figure 2 Another air conditioner intelligent control method in the embodiments of the present application is described.

[0138] Please refer to Figure 2 Another flowchart of the air conditioner intelligent control method in the embodiments of the present application is shown.

[0139] S201, obtaining a three-dimensional graph of a preset range of a key area;

[0140] Before performing air conditioner intelligent control, the system first needs to obtain a three-dimensional digital model of the target environment, i.e. a three-dimensional graph of the preset range of the key area. This step aims to provide necessary spatial information and geometric parameters for subsequent air conditioner selection and optimization.

[0141] Specifically, the system can obtain or construct this three-dimensional map in various ways. One commonly used method is to use three-dimensional scanning technology, such as laser scanning or structured light scanning, to conduct all-around scanning and collection of the target area, obtaining high-precision point cloud data. Then, through professional three-dimensional modeling software, the point cloud data is converted into a three-dimensional model containing complete geometric and topological information. This method has high precision and strong reality, and can accurately reproduce key elements such as the shape, size and layout of the room.

[0142] Another method is to directly use the design drawings or BIM (Building Information Modeling) model of the target area. Modern architectural design generally uses three-dimensional CAD or BIM software for design and management, and these digital design models contain rich geometric and attribute information that can be directly used for air conditioning control systems. Compared with the scanning method, this method saves the step of on-site collection, but the accuracy of the model depends on the quality of the design drawings and the degree of conformity with the completed state.

[0143] S202, determining a plurality of air conditioners in the three-dimensional map;

[0144] After obtaining the three-dimensional map of the key area, the system needs to identify and locate all air conditioning equipment in it. This step aims to clearly define the specific location and orientation of each air conditioner in space, providing necessary boundary conditions for subsequent airflow simulation and equipment selection.

[0145] Specifically, the system first searches and identifies the three-dimensional model of the air conditioner in the three-dimensional map. In the digital management of modern buildings, all equipment and facilities are usually integrated into the overall model of the building in the form of three-dimensional models, forming a complete BIM system. Therefore, the system can directly extract and call the pre-drawn three-dimensional model of the air conditioner from the BIM database and place it accurately in the corresponding position in the three-dimensional scene.

[0146] If the three-dimensional map does not contain the air conditioner model, the system can also determine the position of the air conditioner through other ways. One method is to use computer vision technology to perform semantic segmentation and object detection on the three-dimensional map to automatically identify the outline and position of the air conditioner in the map. Another method is manual annotation, that is, the system administrator manually selects and marks the installation position and direction of each air conditioner in the three-dimensional map.

[0147] S203, connecting each air conditioner with the center point of the key area in the three-dimensional map to obtain a plurality of connection lines;

[0148] After determining the positions of the key area and the air conditioner, the system needs to analyze the spatial relationship between each air conditioner and the target area to evaluate its impact on the regional environment. One intuitive analysis method is to connect each air conditioner with the center point of the key area in the three-dimensional map to obtain a plurality of connection lines, and use them to depict the geometric relationship between the air conditioner and the area.

[0149] Specifically, the system first needs to determine the center point of the key area in the three-dimensional graph. This can be achieved by calculating the geometric center of the area bounding box, that is, taking the maximum and minimum coordinate values of the area in the x, y, z three directions respectively, and then calculating the average value to get a center point coordinate in three-dimensional space. This point represents the geometric center of the entire key area, which is usually also the target point of temperature control.

[0150] Then, the system generates a straight line connecting the two points in the three-dimensional graph, with the center of the air outlet of each air conditioner as the starting point and the center of the key area as the ending point. This connecting line intuitively expresses the spatial relationship between the air conditioner and the key area, embodying the approximate path of the cold air from the air outlet to the target area. The length of the connecting line reflects the distance between the air conditioner and the area, and the direction of the connecting line reflects the direction of the air conditioner.

[0151] The system repeats the above steps for each air conditioner, and eventually obtains several connecting lines. Each connecting line uniquely corresponds to an air conditioner, representing the geometric relationship between the air conditioner and the key area. By observing and analyzing the spatial distribution of these connecting lines, the system can preliminarily judge which air conditioners have a closer relationship with the target area, and their sent cold air may have a greater impact on the temperature of the area.

[0152] S204, judge whether there is an object on each connecting line;

[0153] After obtaining several connecting lines connecting the air conditioner and the key area, the system needs to further judge whether there are obstacles on each connecting line. This step aims to comprehensively evaluate the ventilation path between the air conditioner and the target area, considering the blocking and shielding effect of obstacles, to more accurately predict the actual delivery of cold air.

[0154] Specifically, the system needs to traverse all object models (such as walls, furniture, equipment, etc.) in the three-dimensional graph for each connecting line, and check one by one whether they intersect with the connecting line. This can be achieved by using the ray intersection algorithm in computational geometry. That is, the connecting line is regarded as a ray, and the orthogonal operation is performed with the surface mesh of each object model to determine whether the ray passes through the surface of the object.

[0155] If a connecting line intersects with a certain object model, it means that the object is located on the ventilation path between the air conditioner and the key area, and it has a certain blocking or shielding effect on the propagation of cold air. The system will record all the obstacle information on this connecting line, including the type, size, material, intersection position with the connecting line, etc. These information will be used for subsequent ventilation effect prediction and air supply strategy optimization.

[0156] If a connection line does not intersect with any object, it means that there is a direct and unobstructed ventilation path between the air conditioner and the focus area. Cold air can propagate along the path in a straight line without being affected by objects. In this case, the influence of the air conditioner on the temperature of the target area is relatively more significant and direct. The system will mark such unobstructed air conditioners as optional priority control objects.

[0157] S205, the air conditioner corresponding to the connection line is not an unobstructed air conditioner;

[0158] If there is an object, the air conditioner corresponding to the connection line is not an unobstructed air conditioner

[0159] S206, the air conditioner corresponding to the connection line is an unobstructed air conditioner.

[0160] If there is no object, the air conditioner corresponding to the connection line is an unobstructed air conditioner

[0161] The above embodiment has the following beneficial effects:

[0162] It intuitively reflects the spatial layout and shielding relationship, providing a reliable data foundation for subsequent judgments. Three-dimensional modeling makes abstract spatial information intuitive and visual, helping to improve the rationality and accuracy of decision-making. The simple algorithm of connection line judgment avoids complex spatial collision detection operations, ensuring the accuracy of the judgment while improving the calculation efficiency. Especially in the scene of multiple air conditioners and complex layout, this method can quickly filter out unobstructed air conditioners, saving time for generating optimization solutions. The clear unobstructed determination provides a direct basis for the preferred output air conditioner. The geometric analysis results based on the three-dimensional model have high reliability. Once it is determined that there is an unobstructed air conditioner, the optimal solution can be directly locked, eliminating unnecessary calculation and analysis, and the advantages in efficiency and effect are very obvious. Even in a dynamically changing environment, this method is still applicable. As long as the three-dimensional graph is updated in real time, the changes in unobstructed conditions can be judged at any time, and the output strategy can be quickly responded and adjusted in a timely manner. This dynamic adaptability further expands the application space of the intelligent control method.

[0163] The system in the embodiment of the present application will be described from the perspective of hardware processing. Please refer to Figure 3 , which is a schematic diagram of the entity device structure of an air conditioner intelligent control system provided by the embodiment of the present application.

[0164] It should be noted that, Figure 3 The structure of the system shown is only an example and should not impose any limitations on the functions and use range of the embodiment of the present application.

[0165] As Figure 3As shown, the system includes a central processing unit (CPU) 301 which can perform various appropriate actions and processes, such as executing the methods in the above-described embodiments, according to programs stored in a read-only memory (ROM) 302 or loaded from a storage section 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for operation of the system are also stored. The CPU 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0166] Connected to the I / O interface 305 are an input section 306 including a camera, an infrared sensor, and the like; an output section 307 including a liquid crystal display (LCD) and a speaker, and the like; the storage section 308 including a hard disk, and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as necessary. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 310 as necessary, so that a computer program read therefrom is installed into the storage section 308 as necessary.

[0167] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing a computer program for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present application are performed.

[0168] It should be noted that the computer-readable medium in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer-readable signal medium can include a data signal carrying computer-readable computer programs in a baseband or as a part of a carrier wave. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above.

[0169] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In the flowcharts or block diagrams, each block can represent a module, a program segment or a part of code containing one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different orders than that shown in the drawings. For example, two blocks indicated in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0170] As another aspect, the present application also provides a computer readable storage medium, which can be included in the system described in the above embodiments, or can exist independently without being assembled into the system. The above storage medium carries one or more computer programs, which, when executed by a processor of a system, enable the system to implement the method provided in the above embodiments.

[0171] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still make modifications to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0172] In the above embodiments, according to the context, the term "when" can be interpreted as meaning "if" or "after" or "in response to determining" or "in response to detecting". Similarly, according to the context, the phrase "upon determining" or "if detecting (the stated condition or event)" can be interpreted as meaning "if determining" or "in response to determining" or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)".

[0173] In the above embodiments, all or some of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or some of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or some of the processes or functions described in the embodiments of the present application are generated. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium, or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (such as floppy disk, hard disk, magnetic tape), optical media (such as DVD), or semiconductor media (such as solid state disk) and the like.

[0174] Those skilled in the art can understand that all or part of the processes in the above-mentioned method embodiments can be implemented by a computer program instructing relevant hardware to complete, the program can be stored in a computer readable storage medium, and the program can include the processes of the above-mentioned method embodiments when executed. The aforementioned storage medium includes ROM or random storage memory RAM, magnetic disc or optical disc and various storage code medium.

Claims

1. An air conditioner intelligent control method, characterized by, The method comprises the following steps: determining whether there is an unobstructed air conditioner in the preset range of the key area, wherein the unobstructed air conditioner is an air conditioner without objects between the air conditioner and the key area; if there is, determining the output air conditioner closest to the key area among the unobstructed air conditioners; determining the output parameter of the output air conditioner according to the target parameter, and sending a first instruction to the output air conditioner to make the output air conditioner operate according to the output parameter; if there is not, determining the conveying air duct of each air conditioner in the preset range for conveying air conditioner air to the key area, wherein the conveying air duct comprises conveying length, number of obstructions, obstruction thermal conductivity parameter and final air direction; inputting the target parameter, conveying length, number of obstructions and obstruction thermal conductivity parameter into an air conditioner operating parameter calculation function to obtain the target operating parameter of each air conditioner; calculating the target operating power of each air conditioner according to the target operating parameter; calculating the corresponding recommendation score using a weighted average algorithm according to the final air direction of each conveying air duct and the target operating power of each air conditioner; determining the optimal output air conditioner with the highest recommendation score, and sending a second instruction to the optimal output air conditioner to make the output air conditioner operate according to the corresponding target operating parameter.

2. The method of claim 1, wherein, The method for determining whether there is an unobstructed air conditioner in the preset range of the key area comprises the following steps: obtaining a three-dimensional map of the preset range of the key area; determining a plurality of air conditioners in the three-dimensional map; connecting each air conditioner with the center point of the key area in the three-dimensional map to obtain a plurality of connection lines; determining whether there is an object on each connection line; if there is an object, the air conditioner corresponding to the connection line is not the unobstructed air conditioner; if there is no object, the air conditioner corresponding to the connection line is the unobstructed air conditioner.

3. The method of claim 2, wherein, If there is not, the method for determining the conveying air duct of each air conditioner in the preset range for conveying air conditioner air to the key area comprises the following steps: when the connection line is in contact with the object, changing the direction of the connection line to pass through the center point to obtain a conveying air duct, the angle between the new connection line after changing the direction and the connection line vector is not greater than 90 degrees, and the connection line vector is a vector with the air conditioner as the origin and the center point of the key area as the direction; recording the conveying length, number of obstructions and final air direction of the conveying air duct; determining the obstructions according to the conveying air duct and the three-dimensional map; determining the obstruction thermal conductivity parameter of each obstruction according to the obstructions.

4. The method of claim 1, wherein, The method for calculating the target operating power of each air conditioner according to the target operating parameter comprises the following steps: determining the operating current and operating voltage of the air conditioner according to the target operating parameter; calculating the target operating power of the air conditioner according to the operating current and operating voltage.

5. The method of claim 3, wherein, The method for calculating the corresponding recommendation score using a weighted average algorithm according to the final air direction of each conveying air duct and the target operating power of each air conditioner comprises the following steps: determining a final wind direction of each of the delivery air ducts as a first weight or a second weight, the final wind direction being the first weight when an included angle between the final wind direction and the connecting line vector is in a first interval, and the final wind direction being the second weight when the included angle between the final wind direction and the connecting line vector is in a second interval; determining a target operating power of each of the delivery air ducts as a third weight or a fourth weight, the target operating power being the third weight when the target operating power is in a preset first power interval, and the target operating power being the fourth weight when the target operating power is in a preset second power interval; inputting the first weight or the second weight and the third weight or the fourth weight into a weighted calculation function to obtain the recommendation score.

6. The method of claim 5, wherein, The weighted calculation function is: ； In the formula, the is the recommended score, the is the angle between the final wind direction and the connecting line vector, the is the first weight or the second weight, the is the target operating power, the is the third weight or the fourth weight.

7. An intelligent control system for an air conditioner, characterized by comprising: The system comprises: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is configured to store computer program code, the computer program code comprises computer instructions, and the one or more processors invoke the computer instructions to enable the system to perform the method according to any one of claims 1-6.

8. A computer-readable storage medium comprising instructions, characterized in that, The instructions enable the system to perform the method according to any one of claims 1-6 when the instructions run on the system.

9. A computer program product, characterised in that, The computer program product enables the system to perform the method according to any one of claims 1-6 when the computer program product runs on the system.

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