A comfort optimization control method and device, an air conditioner and a storage medium

Abstract

The application discloses a comfort optimization control method and device, an air conditioner and a storage medium, and relates to the technical field of air conditioners. The method comprises the following steps: collecting multi-dimensional indoor and outdoor environment data, performing filtering processing on the multi-dimensional indoor and outdoor environment data, and obtaining a multi-dimensional indoor and outdoor environment vector; obtaining an initial weight, combining the multi-dimensional indoor and outdoor environment vector to calculate a dynamic weight; combining the multi-dimensional indoor and outdoor environment vector and the dynamic weight to calculate a multi-dimensional comfort comprehensive evaluation index; judging whether the indoor comfort degree meets a preset degree requirement according to the multi-dimensional comfort comprehensive evaluation index; if the preset degree requirement is not met, actively adjusting the operation parameters of the air conditioner based on the multi-dimensional indoor and outdoor environment vector; and continuously calculating the multi-dimensional comfort comprehensive evaluation index until it is determined that the preset degree requirement is met. The method provided by the application can be applied to an energy-saving air conditioner, can enhance the control effect of the air conditioner, and can improve the use comfort of users and reduce energy consumption.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, and in particular to a comfort optimization control method, device, air conditioner, and storage medium. Background Technology

[0002] With the continuous improvement of the sealing performance of modern building envelopes and the increasing demands of the public for healthy indoor living and comfortable spatial experiences, the coordinated and comprehensive control of indoor air quality (IAQ) and thermal comfort has become a core research direction in the field of building environmental control. Currently, most mainstream fresh air and environmental control systems on the market focus on the regulation of single environmental parameters, possessing only a crude physical switching function for indoor and outdoor air circulation. This makes it difficult to adapt to the multidimensional indoor environmental regulation needs under optimal human comfort conditions, resulting in significant shortcomings in comprehensive regulation effects.

[0003] Existing related control technologies still have many technical shortcomings, failing to achieve refined and dynamic indoor environmental control. For example, the published patent CN224162679U only uses a single fresh air introduction mode, unable to dynamically optimize ventilation control strategies based on differences in indoor and outdoor temperature, humidity, air quality, and other environmental factors. In actual operation, even under high temperature and humidity conditions outdoors, if the indoor carbon dioxide concentration exceeds the standard, the system will still forcibly activate outdoor fresh air circulation, easily causing a significant decrease in indoor thermal comfort and a substantial increase in the operating load of air conditioning equipment, thus increasing building energy consumption.

[0004] Furthermore, patent CN224175321U discloses an anti-backflow device that enables switching between indoor and outdoor fresh air circulation. This device primarily relies on hardware control via mechanical and electronic valves to provide basic protection against odor pollutants such as formaldehyde and VOCs. However, this technology lacks a dynamic matching and control model between pollutant release rates, system airflow, and catalytic decomposition efficiency. In internal circulation mode, once the filter becomes saturated, it cannot promptly adjust its control strategy to adapt to the operating conditions, easily leading to secondary accumulation of indoor pollutants and a continuous deterioration of indoor air quality.

[0005] In summary, existing building environment control technologies generally suffer from problems such as single control dimensions and poor dynamic adaptability. They lack a closed-loop control scheme that can incorporate multi-dimensional environmental parameters such as temperature, humidity, carbon dioxide, formaldehyde, and odor molecules into a unified quantitative evaluation system, and can dynamically and accurately switch indoor and outdoor circulation modes to achieve targeted compensation and control of pollutants, taking into account the needs of environmental quality and energy consumption. As a result, it is difficult to meet the multiple needs of indoor air quality, thermal comfort, and energy-saving operation. Summary of the Invention

[0006] This invention provides a comfort optimization control method, device, air conditioner, and storage medium, aiming to enhance the control effect of the air conditioner and thereby improve user comfort.

[0007] In a first aspect, embodiments of the present invention provide a comfort optimization control method, applied to an air conditioner equipped with a fresh air system, the method comprising: Based on multiple preset index parameters, corresponding multi-dimensional indoor and outdoor environmental data are collected, and the multi-dimensional indoor and outdoor environmental data are filtered to obtain a multi-dimensional indoor and outdoor environmental vector. Obtain the initial weights corresponding to multiple indicator parameters, and calculate the dynamic weights by combining them with the multi-dimensional indoor and outdoor environment vectors; The multidimensional comfort comprehensive evaluation index is calculated by combining the aforementioned multidimensional indoor and outdoor environmental vectors and dynamic weights. The indoor comfort level is determined based on the multidimensional comfort comprehensive evaluation index to determine whether it meets the preset requirements. If it is determined that the indoor comfort level does not meet the preset requirements, the operating parameters of the air conditioner are actively adjusted based on the multi-dimensional indoor and outdoor environment vectors. Continue calculating the multidimensional comfort comprehensive evaluation index after active adjustment until it is determined that the indoor comfort meets the preset requirements.

[0008] Secondly, embodiments of the present invention provide a comfort optimization control device, applied to an air conditioner equipped with a fresh air system, the device comprising: The data acquisition unit is used to collect corresponding multi-dimensional indoor and outdoor environmental data based on multiple preset index parameters, and to filter the multi-dimensional indoor and outdoor environmental data to obtain a multi-dimensional indoor and outdoor environmental vector. The weight calculation unit is used to obtain the initial weights corresponding to multiple indicator parameters, and to calculate the dynamic weights by combining the multi-dimensional indoor and outdoor environment vectors. The index calculation unit is used to calculate a multi-dimensional comfort comprehensive evaluation index by combining the multi-dimensional indoor and outdoor environment vectors and dynamic weights. The degree judgment unit is used to determine whether the indoor comfort meets the preset degree requirements based on the multi-dimensional comfort comprehensive evaluation index. The parameter adjustment unit is used to actively adjust the operating parameters of the air conditioner based on the multi-dimensional indoor and outdoor environment vector if it is determined that the indoor comfort level does not meet the preset requirements. The satisfaction judgment unit is used to continue calculating the multidimensional comfort comprehensive evaluation index after active adjustment until the indoor comfort is determined to meet the preset level requirements.

[0009] Thirdly, embodiments of the present invention provide an air conditioner, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the comfort optimization control method as described in the first aspect.

[0010] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the comfort optimization control method as described in the first aspect.

[0011] This invention provides a comfort optimization control method, device, air conditioner, and storage medium, applied to an air conditioner equipped with a fresh air system. The method includes: collecting corresponding multi-dimensional indoor and outdoor environmental data based on multiple preset index parameters, and filtering the multi-dimensional indoor and outdoor environmental data to obtain a multi-dimensional indoor and outdoor environmental vector; obtaining initial weights corresponding to the multiple index parameters, and calculating dynamic weights based on the multi-dimensional indoor and outdoor environmental vector; calculating a multi-dimensional comfort comprehensive evaluation index based on the multi-dimensional indoor and outdoor environmental vector and the dynamic weight; determining whether the indoor comfort meets a preset level requirement based on the multi-dimensional comfort comprehensive evaluation index; if the indoor comfort does not meet the preset level requirement, actively adjusting the operating parameters of the air conditioner based on the multi-dimensional indoor and outdoor environmental vector; and continuing to calculate the actively adjusted multi-dimensional comfort comprehensive evaluation index until the indoor comfort meets the preset level requirement. This invention establishes a multi-dimensional unified evaluation system containing multiple index parameters, which can dynamically calculate the comprehensive comfort evaluation index based on real-time environmental data. Then, based on the comprehensive comfort evaluation index, it actively adjusts the air conditioner's operating parameters to achieve closed-loop control that balances indoor air quality, thermal comfort, and energy-saving operation. This solves the technical problems of existing technologies, such as single control dimensions and poor dynamic adaptability. It can accurately control current indoor environmental problems, effectively improve indoor environmental comfort, and avoid unnecessary energy waste, thus balancing comfort experience and operational efficiency. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A flowchart illustrating a comfort optimization control method provided in an embodiment of the present invention; Figure 2 A schematic diagram of a sub-process of a comfort optimization control method provided in an embodiment of the present invention; Figure 3 This is another flowchart illustrating a comfort optimization control method provided in an embodiment of the present invention; Figure 4This is a schematic diagram of the principle architecture of a comfort optimization control method provided in an embodiment of the present invention; Figure 5 A system hardware diagram of a comfort optimization control method provided in an embodiment of the present invention; Figure 6 A system architecture diagram of a comfort optimization control method provided in an embodiment of the present invention; Figure 7 This is a sub-principle architecture diagram of a comfort optimization control method provided in an embodiment of the present invention; Figure 8 A schematic block diagram of a comfort optimization control device provided in an embodiment of the present invention; Figure 9 This is a schematic block diagram of a comfort optimization control device provided in an embodiment of the present invention; Figure 10 Another schematic block diagram of a comfort optimization control device provided in an embodiment of the present invention; Figure 11 This is a schematic block diagram of an air conditioner provided in an embodiment of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0016] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0017] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0018] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0019] Please see below. Figure 1 The present invention provides a comfort optimization control method, which is applied to an air conditioner equipped with a fresh air system. The method includes steps S101 to S106.

[0020] Step S101: Collect corresponding multi-dimensional indoor and outdoor environmental data based on multiple preset index parameters, and filter the multi-dimensional indoor and outdoor environmental data to obtain a multi-dimensional indoor and outdoor environmental vector. Step S102: Obtain the initial weights corresponding to multiple indicator parameters, and calculate the dynamic weights by combining the multi-dimensional indoor and outdoor environment vectors; Step S103: Calculate the multidimensional comfort comprehensive evaluation index by combining the multidimensional indoor and outdoor environment vectors and dynamic weights; Step S104: Determine whether the indoor comfort level meets the preset requirements based on the multidimensional comfort comprehensive evaluation index; Step S105: If it is determined that the indoor comfort level does not meet the preset requirements, the operating parameters of the air conditioner are actively adjusted based on the multi-dimensional indoor and outdoor environment vector. Step S106: Continue to calculate the multidimensional comfort comprehensive evaluation index after active adjustment until it is determined that the indoor comfort meets the preset requirements.

[0021] In this embodiment, combined with Figure 4 First, based on preset multiple indicator parameters, multi-dimensional indoor and outdoor environmental data are collected and filtered to obtain a multi-dimensional indoor and outdoor environmental vector. Next, the initial weights corresponding to each indicator parameter are obtained, and dynamic weights are calculated based on the multi-dimensional indoor and outdoor environmental vector. Then, based on the multi-dimensional indoor and outdoor environmental vector and the calculated dynamic weights, a multi-dimensional comfort comprehensive evaluation index is obtained. Then, based on the comprehensive evaluation index, it is determined whether the current indoor comfort meets the preset requirements. If it is determined that it does not meet the requirements, the operating parameters of the air conditioner are actively adjusted based on the multi-dimensional indoor and outdoor environmental vector. After the adjustment is completed, the adjusted multi-dimensional comfort comprehensive evaluation index is continuously calculated until it is determined that the indoor comfort meets the preset requirements.

[0022] This embodiment establishes a multi-dimensional unified evaluation system containing multiple index parameters, which can dynamically calculate the comprehensive comfort evaluation index based on real-time environmental data. Then, based on the comprehensive comfort evaluation index, it actively adjusts the air conditioner's operating parameters to achieve closed-loop control that balances indoor air quality, thermal comfort, and energy-saving operation. This solves the technical problems of existing technologies, such as single control dimensions and poor dynamic adaptability. It can accurately control current indoor environmental problems, effectively improve indoor environmental comfort, and avoid unnecessary energy waste, thus balancing comfort experience and operational energy efficiency.

[0023] Based on the comfort optimization control method provided in this embodiment, a corresponding control system can be built. For example... Figure 5 As shown, the system includes an indoor air conditioning unit 10, an outdoor air conditioning unit 20, and a fresh air device 30 installed on the indoor air conditioning unit. The fresh air device 30 is equipped with a fresh air valve 31 and a return air valve 32 for switching between indoor return air circulation and outdoor fresh air circulation. By adjusting the opening and closing ratio of the fresh air valve 31 and the return air valve 32, the fresh air intake and return air ratio can be adjusted to adapt to the ventilation needs of different environments. Combined with the temperature and humidity regulation function of the air conditioner itself, unified control of multi-dimensional indoor environmental parameters can be achieved.

[0024] In addition, combined Figure 6 The control system can also deploy the following hardware architecture layers: Multi-dimensional sensing and acquisition layer: Deploys a high-precision integrated temperature and humidity sensor (error ±0.3℃ / ±2%RH), an NDIR CO2 sensor (range 0-5000ppm), and an electrochemical formaldehyde sensor (range 0-1mg / m³). 3 ), Metal oxide semiconductor VOC odor sensor (range 0-1000ppb), sampling period set to 10 seconds / time.

[0025] Edge intelligent control layer: It adopts a microcontroller with an ARM Cortex-M7 core, embeds the MSI-CSI evaluation algorithm and dynamic switching logic, and has a 100ms-level control cycle response capability.

[0026] Multi-mode actuator layer: including dual-valve actuator (fresh air valve / return air valve 0-100% stepless adjustment), variable frequency fan (air volume 0-500m³ / h) 3 The system includes a cold catalyst formaldehyde decomposition module (0-50W adjustable power), a negative ion / photocatalytic odor purification module, an inverter air conditioner outdoor unit, and an independent humidification and dehumidification module.

[0027] In one embodiment, step S101 includes: For multiple preset index parameters, multi-dimensional indoor and outdoor environmental data are collected by pre-deployed multi-dimensional sensors; wherein, the multiple index parameters include temperature, humidity, carbon dioxide, formaldehyde and odor gas molecules; The multi-dimensional indoor and outdoor environmental data are subjected to moving average filtering to eliminate transient noise in the multi-dimensional indoor and outdoor environmental data, and the multi-dimensional indoor and outdoor environmental vector is obtained.

[0028] This embodiment targets multiple preset parameters such as temperature, humidity, carbon dioxide, formaldehyde, and odor gas molecules. A pre-deployed multi-dimensional sensor array simultaneously collects multi-dimensional raw indoor and outdoor environmental data on both the indoor return air side and the outdoor fresh air intake side. Subsequently, all collected raw environmental data undergoes moving average filtering preprocessing to eliminate transient noise such as transient pulse interference and random fluctuations generated during sensor acquisition, effectively avoiding the impact of acquisition errors on the accuracy of environmental assessment.

[0029] Specifically, the system can acquire data on five core physical quantities—temperature (T), humidity (H), carbon dioxide concentration (C), formaldehyde concentration (F), and odor gas concentration (V)—in real time, with a 10-second acquisition cycle. The collected indoor and outdoor raw data are then categorized and integrated according to their corresponding index parameters. A moving average window is used to filter and reduce noise in each group of data, resulting in the indoor environmental parameter sub-vector X. in(t) =[T in H in C in ,F in V in [and outdoor environmental parameter subvector X] out(t) =[T out H out C out ,F out V out The two types of sub-vectors are merged to form the multi-dimensional indoor and outdoor environment vector, which provides data support for subsequent environmental quantitative evaluation and control.

[0030] In one embodiment, step S102 includes: Obtain the deviation between the multi-dimensional indoor and outdoor environment vector and the preset optimal vector center; By combining the deviation and the initial weight, dynamic weights are calculated for the multi-dimensional indoor and outdoor environment vectors.

[0031] In this embodiment, when calculating dynamic weights by combining initial weights with multi-dimensional indoor and outdoor environmental vectors, the deviation of each indicator parameter in the multi-dimensional indoor and outdoor environmental vectors from the preset optimal comfort range is first obtained. Then, the weights of different indicators are dynamically adjusted according to the degree of deviation. For example, if the current actual parameter of an indicator deviates more from the optimal range, a higher dynamic weight is assigned to highlight the negative impact of the indicator on overall comfort. If the current actual parameter of an indicator is already within the optimal range, its basic initial weight is maintained to avoid over-amplifying its impact on the comprehensive evaluation. This achieves adaptive weight allocation for each influencing dimension under different environmental scenarios, making the comprehensive evaluation result more consistent with the actual comfort status of the current indoor environment.

[0032] Specifically, the dynamic weights can be calculated using the following formula: ; in, This represents the dynamic weight of the i-th indicator at time t. This represents the initial weight of the i-th indicator. This represents the initial weight of the j-th indicator. Let i represent the i-th multi-dimensional indoor / outdoor environment vector at time t. Let i represent the i-th multi-dimensional indoor / outdoor environment vector at time t. This represents the optimal comfort center value corresponding to the i-th indicator. This represents the optimal comfort center value corresponding to the j-th indicator. This represents the sensitivity coefficient. For example, the initial weight allocation is... , .

[0033] In one embodiment, step S103 includes: The comfort membership function is calculated based on the multi-dimensional indoor and outdoor environment vectors. The dynamic weights and comfort membership functions are combined to form the multidimensional comfort comprehensive evaluation index.

[0034] In this embodiment, for each indicator in the multi-dimensional indoor and outdoor environment vector, a comfort membership function is constructed based on the preset comfort interval boundary of each indicator, and the comfort membership degree corresponding to each indicator is obtained by solving the function. The value range is [0,1]. Here, the closer the value is to 1, the closer the real-time operating condition of the indicator is to the optimal comfort standard; the closer the value is to 0, the higher the degree of deviation of the indicator from the comfort interval. This embodiment uses a smoothing function of Cauchy distribution combined with half-ridge distribution as the individual comfort membership function to ensure a smooth transition of the membership degree output when the deviation of the indicator changes, and to avoid abrupt changes in the evaluation results. After solving the individual membership degree of all indicators, the membership degree of each indicator is matched with the calculated dynamic weight and weighted summed to obtain the multi-dimensional comfort comprehensive evaluation index (CSI) with a value range of 0 to 100. The closer the index value is to 100, the higher the overall level of indoor thermal comfort and air quality, and the more the indoor environment meets the human comfort needs.

[0035] Specifically, the Multidimensional Comfort Index (CSI) can be calculated using the following formula: ; in, Indicates dynamic weights. Let represent the comfort membership function of the i-th indicator. First, for each indicator in the multi-dimensional indoor and outdoor environment vector, calculate its comfort membership degree based on the corresponding comfort interval boundary. The membership degree ranges from [0,1]. A membership degree closer to 1 indicates that the current state of the indicator is closer to the optimal comfort state, while a membership degree closer to 0 indicates that the current state deviates further from the optimal comfort state. Then, weighted summation is performed on the comfort membership degrees calculated for all indicators, combined with the dynamic weights of the corresponding indicators. Finally, a multi-dimensional comfort comprehensive evaluation index, also within the [0,1] interval, is obtained. The closer this index is to 1, the higher the overall indoor comfort level, and the better it meets the user's comfort needs.

[0036] In practical applications, when calculating the comfort membership function for multi-dimensional indoor and outdoor environmental vectors, the system can first retrieve the upper and lower boundaries of the comfort intervals and the optimal central reference parameters corresponding to each indicator, thus obtaining the comfort judgment thresholds for each indicator. Then, it iterates through the parameters of each indicator within the multi-dimensional indoor and outdoor environmental vectors and matches a piecewise smooth membership model composed of a combination of Cauchy distribution and ascending half-ridge distribution based on the parameter's numerical range. If the indicator parameter is within the optimal comfort range, the Cauchy distribution is used to achieve a smooth fitting of the membership degree; if the indicator parameter exceeds the comfort range and shifts towards harsh conditions, the ascending half-ridge distribution is switched to achieve a smooth decay of the membership degree, thereby avoiding abrupt distortion of the evaluation values ​​caused by small parameter fluctuations. Then, the real-time monitoring values, optimal center values, and comfort zone boundary thresholds of each indicator parameter are substituted into the corresponding piecewise membership functions, and the individual comfort membership degrees corresponding to each indicator are obtained by solving them dimension by dimension. All individual membership degrees are constrained to the interval between 0 and 1. The closer the indicator parameter is to the optimal center, the closer the corresponding membership degree is to 1. The more serious the deviation of the parameter from the comfort zone, the closer the membership degree is to 0. After fully traversing and calculating all five indicators of temperature, humidity, carbon dioxide, formaldehyde, and odor gas molecules, a multidimensional comfort membership degree vector is generated that corresponds one-to-one with the dimensions of the multidimensional indoor and outdoor environment vector.

[0037] In one embodiment, such as Figure 2 As shown, step S104 includes steps S201 to S203.

[0038] Step S201: Compare the multidimensional comfort comprehensive evaluation index with the preset comfort threshold; Step S202: If the multidimensional comfort comprehensive evaluation index reaches the comfort threshold, then it is determined that the indoor comfort meets the preset level requirements; Step S203: If the multidimensional comfort comprehensive evaluation index does not reach the comfort threshold, it is determined that the indoor comfort does not meet the preset level requirements.

[0039] This embodiment pre-configures a comfort threshold that users can customize according to their own usage habits, for example, setting a baseline value of 85. By comparing the Multidimensional Comfort Index (CSI) obtained in real time with this threshold, the overall comfort state of the indoor environment can be determined: when the CSI value is greater than or equal to the preset threshold, it can be determined that the indoor environment has reached the user-accepted comfort standard, and then the control system switches to a low-power maintenance monitoring mode, maintaining it for only 10m. 3The basic fresh air volume of / h is used to ensure basic breathing needs. The other control actuators remain in standby mode. The air conditioner continues to use the existing operating parameters. The environmental data will be collected again in the next collection cycle and the entire evaluation calculation process will be executed cyclically. When the CSI value is lower than the preset threshold, it is determined that the current indoor comprehensive comfort level has not met the standard, and the subsequent active adjustment process is triggered.

[0040] Furthermore, an algorithm combining multi-level interval threshold judgment with temporal filtering verification can be adopted to achieve a refined judgment of indoor comfort level based on the real-time multidimensional comfort comprehensive evaluation index. Compared with the single threshold comparison method, this method can effectively avoid frequent misjudgments and mode jitter caused by instantaneous index fluctuations. The specific processing steps are as follows: First, pre-calibrate the multi-level comfort classification threshold interval, which includes a comfort steady-state threshold, a critical warning threshold, and a severe imbalance threshold, and configure a fixed temporal verification window; second, input the real-time calculated multidimensional comfort comprehensive evaluation index (CSI) into the judgment algorithm module to complete the interval matching of the index at a single moment and initially define the comfort level of the current indoor environment; then, retrieve the historical CSI data for multiple consecutive periods within the temporal verification window, remove abnormal jump points in the data collection, and perform mean filtering correction to obtain the steady-state corrected comprehensive comfort index; finally, compare the corrected comprehensive index with the preset thresholds at each level to complete the accurate verification of the indoor comfort state. When the steady-state corrected CSI remains above the comfort steady-state threshold, it is determined that the indoor comfort fully meets the preset requirements, and the overall multi-dimensional indicators such as temperature, humidity, and air quality are balanced and meet the standards. In this case, the low-power steady-state operation mode is maintained. When the steady-state corrected CSI is between the critical warning threshold and the comfort steady-state threshold, it is determined that the indoor comfort state is in a critical compliance state. In this case, regular monitoring standby is maintained, and no significant control actions are triggered. When the steady-state corrected CSI remains below the critical warning threshold, it is determined that the indoor comfort does not meet the preset requirements, and there is a significant imbalance in multi-dimensional environmental parameters. In this case, the comfort non-compliance state is immediately locked, and subsequent dynamic weight iteration, internal and external circulation strategy switching, and environmental parameter targeted compensation adjustment processes are triggered. This achieves a stable, accurate, and intelligent closed-loop determination of the indoor comfort state.

[0041] In one embodiment, such as Figure 3 As shown, step S105 includes steps S301 to S306.

[0042] Step S301: Obtain the indoor and outdoor vector difference corresponding to the multi-dimensional indoor and outdoor environment vector; Step S302: Obtain the preset target values ​​of multiple indicator parameters, and calculate the comprehensive cost switching factor based on the indoor-outdoor vector difference and the target values; Step S303: Compare the comprehensive cost switching factor with a preset factor threshold; wherein the preset factor threshold includes a first factor threshold and a second factor threshold, and the first factor threshold is greater than the second factor threshold; Step S304: If the comprehensive cost switching factor is greater than the first factor threshold, an external circulation cleaning command is generated, and the air conditioner is controlled to run the corresponding external circulation cleaning mode according to the external circulation cleaning command. Step S305: If the comprehensive cost switching factor is greater than the second factor threshold and less than or equal to the first factor threshold, a mixed micro-percolation command is generated, and the air conditioner is controlled to operate the corresponding mixed micro-percolation mode according to the mixed micro-percolation command. Step S306: If the comprehensive cost switching factor is less than or equal to the first factor threshold, an internal circulation cleaning instruction is generated, and the air conditioner is controlled to run the corresponding internal circulation cleaning mode according to the internal circulation cleaning instruction.

[0043] In this embodiment, after determining that the indoor comfort level is substandard and the active control strategy of the air conditioner needs to be activated, the difference between indoor and outdoor parameters of each environmental indicator is first calculated based on multi-dimensional indoor and outdoor environmental vectors. This quantifies the difference in pollutant concentration and temperature / humidity between the outdoor and indoor environments, objectively representing the level of difference between the indoor and outdoor environments. Based on this, the pollutant concentration deviation and temperature / humidity deviation are weighted and integrated according to preset target comfort values ​​for each indicator to calculate a comprehensive cost switching factor. The magnitude of this factor corresponds to the ratio of the comprehensive benefit to the energy cost of introducing outdoor fresh air. A larger factor indicates a higher comprehensive benefit of introducing outdoor fresh air to improve overall indoor comfort, and a higher cost-effectiveness of introducing fresh air; conversely, a smaller factor indicates that the outdoor environment is generally worse than the indoor environment, and introducing fresh air will actually reduce the indoor comfort level and increase the system's control energy consumption.

[0044] Combination Figure 7In this embodiment, two fixed factor thresholds are set to complete the graded strategy determination. The first factor threshold is greater than the second factor threshold. For example, the first factor threshold is 0.7 and the second factor threshold is -0.3. By comparing and matching the comprehensive cost switching factor with the two thresholds, the precise routing switch of the three fresh air circulation operation modes is achieved. When the comprehensive cost switching factor S is greater than the first factor threshold (e.g., 0.7), it can be determined that the outdoor air cleanliness is better than the indoor air, and the deviation between the outdoor temperature and humidity and the indoor target comfort value is small. The benefit of introducing fresh air far outweighs the energy consumption cost. At this time, an external circulation cleaning command is generated and the external circulation cleaning mode is entered. The fresh air valve is controlled to be 100% fully open and the return air valve is completely closed. With the fan running at high air volume, the accumulated carbon dioxide, formaldehyde, and odor pollutants in the room are quickly replaced and diluted, and the indoor air is efficiently purified. When the temperature falls within the range of the second factor threshold and the first factor threshold, for example, when the comprehensive cost switching factor satisfies -0.3 < S ≤ 0.7, it indicates that the indoor and outdoor environments each have their advantages and disadvantages. Fully introducing fresh air consumes too much energy, while completely shutting off the fresh air cannot maintain indoor air quality. Therefore, a mixed micro-permeability command is generated and the mixed micro-permeability mode is activated. The fresh air valve is adjusted to maintain an opening of 20% to 40%, and the return air valve is matched to an opening of 60% to 80%. The fresh air is continuously and slightly supplemented by a medium-low speed fan. While ensuring indoor oxygen content and avoiding the accumulation of pollutants, the fluctuation of heating and cooling loads is effectively suppressed, balancing comfort experience and energy-saving needs. When the overall cost switching factor meets the judgment condition of being less than or equal to the threshold of the second factor, such as S≤-0.3, it means that there are extreme temperature and humidity or high pollution conditions outdoors, and the cost of introducing fresh air is far greater than the improvement benefits. At this time, an internal circulation cleaning command is generated and switched to pure internal circulation cleaning mode, completely closing the fresh air valve and fully opening the return air valve to completely cut off the exchange of indoor and outdoor air. Relying on the built-in purification and decomposition module of the equipment, indoor pollutants are adsorbed and catalytically decomposed, reducing the energy consumption of air conditioning operation while stabilizing the indoor thermal comfort environment.

[0045] In a specific embodiment, the comprehensive cost switching factor can be calculated according to the following formula: ; Where S represents the overall cost switching factor, This represents the indoor-outdoor vector difference in CO2. , represents the upper limit threshold for indoor CO2 exceedance, which is the preset safe critical value for CO2 concentration in the system. It is used to normalize the carbon dioxide deviation and quantify the degree of indoor CO2 pollution exceedance. This represents the vector difference between indoor and outdoor formaldehyde levels. , represents the upper limit threshold for indoor formaldehyde exceeding the standard, which is the system's preset safe critical value for formaldehyde concentration. It is used to normalize the formaldehyde deviation and accurately characterize the degree of indoor formaldehyde pollution exceeding the standard. This represents the indoor-outdoor vector difference of VOCs. This indicates the upper limit of VOC exceeding the standard; Indicates the target set temperature, T range Indicates the temperature range; The energy consumption cost coefficient is the coefficient for the current operating mode of the air conditioner (1.5 for cooling mode, 2.0 for heating mode, and 0.5 for ventilation mode). k1, k2, k3, and k4 are all strategy trade-off coefficients, such as k1=0.4, k2=0.3, k3=0.2, and k4=0.6.

[0046] In one embodiment, step S105 further includes: Based on the multi-dimensional indoor environment vector and the multi-dimensional comfort comprehensive evaluation index, the target index parameter with the highest dynamic weight is obtained; Based on the target index parameters, a targeted compensation instruction is generated, and the air conditioner is controlled to adjust its parameters according to the targeted compensation instruction; wherein, the targeted compensation instruction includes any one of temperature and humidity decoupling control, carbon dioxide oxygen-enriched dilution, formaldehyde catalytic decomposition, and odor physicochemical dual-effect adsorption.

[0047] After completing the graded switching between internal and external circulation modes, this embodiment further selects the target indicator parameter with the highest current weight based on the real-time multi-dimensional indoor environmental vector and the dynamic weight of each indicator. This indicator is the core shortcoming factor causing the low comprehensive evaluation index of indoor comfort. Then, a dedicated targeted compensation and adjustment strategy is matched according to the category of the target indicator, and precise control is implemented only for the imbalance dimension, thereby avoiding the problems of increased energy consumption and drastic fluctuations in environmental parameters caused by indiscriminate adjustment across the entire domain.

[0048] If the target indicator with the highest weight is temperature or humidity, for example, T in Deviation from the target value, or H in If the humidity is below 40% or above 60%, a temperature and humidity decoupling control command will be issued, based on the thermodynamic equation. Solve for the required indoor heating and cooling loads, independently adjust the compressor operating frequency to match temperature control requirements, and simultaneously control the evaporation rate of the humidifier or the condensation and dehumidification rate of the dehumidifier to achieve humidity regulation. The control variables are: This enables decoupled control of temperature and humidity, eliminating negative issues such as overcooling and dryness that are common with traditional coupled control.

[0049] If the target indicator with the highest weight is carbon dioxide, then a carbon dioxide-oxygen-enriched dilution compensation strategy is implemented. The real-time number of people N in the room is calculated based on the rate of increase in carbon dioxide concentration, and the fan air volume and fresh air valve opening are adjusted in combination with the current fresh air circulation conditions to set the minimum fresh air volume to ensure the basic respiratory needs of the human body. It can quickly dilute the carbon dioxide accumulated indoors.

[0050] If formaldehyde is the target indicator with the highest weight, then a formaldehyde catalytic decomposition command is issued, and the command is triggered when the formaldehyde concentration rise rate exceeds 0.005 mg / m³. 3 When a continuous source of pollution is detected indoors, the operating power of the built-in cold catalyst filter is increased to enhance the catalytic decomposition efficiency of formaldehyde until the formaldehyde concentration drops back to a safe range.

[0051] If the target indicator with the highest weight is odorous VOC gas, then the odor physical and chemical dual-effect adsorption compensation scheme will be activated. When the odor concentration rises at a rate exceeding 10 ppb / min, the activated carbon physical adsorption module and the negative ion chemical decomposition module will be activated simultaneously. The scheme relies on physical adsorption to capture odor macromolecules and chemical neutralization and degradation of odor groups to quickly eliminate indoor odor pollution.

[0052] The entire targeted compensation mechanism is officially launched after the system completes the calculation of the comprehensive cost switching factors and matches and determines the basic operation mode of the internal and external circulation. Based on the dynamic weight algorithm mentioned above, it locks the weakest environmental parameters that have the greatest negative impact on the multidimensional comfort comprehensive evaluation index and the most serious deviation from the optimal comfort range. It only matches the exclusive control execution logic for this single imbalance dimension to carry out targeted optimization, without the need to simultaneously and indiscriminately adjust all environmental indicators. It can not only efficiently eliminate the core imbalance problem of the indoor environment and quickly raise the multidimensional comfort comprehensive evaluation index, effectively improving the overall indoor living comfort experience, but also avoid the full-load continuous operation of fans, compressors and purification modules caused by synchronous control of the whole area, greatly reducing unnecessary heat and cold loss and equipment operating power consumption, and achieving a two-way balance between indoor air quality, thermal comfort improvement effect and overall machine operating energy consumption.

[0053] Furthermore, this embodiment also supports feedback verification and adaptive learning functions: after completing one round of targeted compensation adjustment, a 30-second waiting period for the operating condition to stabilize is reserved. After the environmental parameters stabilize, indoor and outdoor multi-dimensional environmental data are re-collected, and the Multi-Dimensional Comfort Comprehensive Evaluation Index (CSI) is iteratively calculated to verify the actual improvement effect of this targeted control. If the updated CSI value still does not reach the set comfort threshold, it indicates that the current control intensity is insufficient. At this time, the output increment of the corresponding actuator can be slightly increased to increase the special compensation intensity. If the CSI fails to converge to the standard range within 5 consecutive data collection cycles, it is determined that there is a continuous strong pollution source indoors or a faulty equipment control, and the system abnormal alarm is automatically triggered to remind the user to investigate and deal with it in time.

[0054] Meanwhile, it can also record the frequency and preferred settings of users manually adjusting target temperature and humidity over a long period of time. Each month, it performs curve fitting on the accumulated user preference data based on the least squares method, automatically updates the optimal comfort benchmark values ​​of each environmental indicator, continuously optimizes the matching accuracy of the comfort evaluation model, and realizes the dynamic self-iterative evolution of the environmental evaluation system according to users' usage habits.

[0055] In general, such as Figure 5 As shown, the comfort optimization control method provided in this embodiment may include an intelligent control core unit layer, a sensor acquisition layer, and an actuator layer. The intelligent control core unit layer includes a comfort evaluation module, a mode switching determination module, a targeted compensation execution module, and an adaptive learning module. The sensor acquisition layer includes a temperature sensor, a humidity sensor, a CO2 sensor, and a VOC / odor sensor. The actuator layer includes a temperature adjustment module, a humidification / dehumidification module, a fresh air circulation valve, and a purification module.

[0056] Specifically, this embodiment constructs a comfort index calculation model that integrates five dimensions of parameters: temperature, humidity, carbon dioxide, formaldehyde, and VOC odor. This breaks through the inherent limitation of traditional environmental devices that can only evaluate each parameter individually, and it also introduces a dynamic weight allocation algorithm. This algorithm follows the allocation logic that deviation is positively correlated with weight; that is, the farther any environmental parameter deviates from its optimal center value, the more exponentially its corresponding weight will be amplified. This allows the entire control logic to prioritize adjustments to the environmental shortcomings that most severely affect the experience, achieving a precise environmental correction effect that aligns with the barrel effect principle.

[0057] Meanwhile, this embodiment also establishes a quantitative calculation model for the comprehensive cost switching factor S, uniformly quantifying the positive benefits of improved carbon dioxide, formaldehyde, and odor concentrations brought by outdoor fresh air, as well as the negative costs of energy consumption in air conditioning and fresh air equipment caused by temperature and humidity deviations. Based on the numerical range, three types of fresh air operation conditions are defined. For example, when the comprehensive cost switching factor value is greater than 0.7, it automatically switches to a full external circulation mode to complete indoor air replacement and purification; when the value is less than -0.3, it switches to a pure internal circulation mode to stabilize the indoor thermal environment and reduce energy consumption; when the value is between -0.3 and 0.7, a mixed micro-permeation mode is activated. This design abandons the rigid switching logic of traditional equipment that is either internal or external, achieving a smooth transition between operating conditions.

[0058] After completing the basic cycle mode matching, this embodiment initiates multi-dimensional targeted compensation and control for residual indoor environmental deviations. Each compensation channel independently calculates and adjusts its value without interference. For temperature and humidity imbalances, a decoupled control scheme is adopted, relying on a variable frequency compressor to regulate temperature and independent humidification and dehumidification mechanisms to control humidity. For carbon dioxide exceeding standards, oxygen enrichment and dilution control is implemented, matching the minimum fresh air supply based on estimated indoor occupancy levels. For formaldehyde exceeding standards, a variable frequency cold catalyst decomposition module is activated to enhance the catalytic degradation of pollutants. For VOC odor exceeding standards, activated carbon physical adsorption and photocatalytic chemical decomposition modules are linked to rapidly reduce odor molecules through both physical and chemical means.

[0059] The entire control framework can collect user data on manual temperature and humidity adjustments, as well as real-time environmental parameters, over a long period. It then uses machine learning fitting techniques, such as least squares, to continuously refine the optimal baseline parameters within the comfort evaluation model. For example, based on usage habits, the general comfort temperature baseline of 24℃ can be adaptively adjusted to 25.5℃ to suit the user, enabling continuous iteration and optimization of comfort assessment standards according to usage habits, thus forming personalized adaptive control capabilities.

[0060] Compared to existing technologies, current fresh air control equipment generally suffers from a single control dimension, making it difficult to simultaneously manage multiple environmental indicators such as temperature, humidity, carbon dioxide, formaldehyde, and odor molecules, thus failing to meet the comprehensive comfort needs of the human body. This embodiment effectively overcomes this shortcoming. Traditional equipment mostly relies on fixed thresholds and timed logic to switch between internal and external circulation, easily leading to the dilemma of excessive ventilation causing soaring energy consumption or insufficient ventilation causing a decline in indoor comfort. This embodiment, however, constructs a quantitative judgment function based on comprehensive comfort deviation and energy consumption cost, forming a dynamic and balanced intelligent switching mechanism that resolves the contradiction between comfort and energy saving. Furthermore, traditional solutions that rely solely on internal circulation filter adsorption and purification cannot supplement outdoor oxygen-containing fresh air, easily causing the continuous accumulation of indoor carbon dioxide and volatile harmful pollutants. This embodiment, through graded circulation switching combined with multi-channel targeted compensation, can take into account both fresh air replacement and deep indoor purification, comprehensively improving indoor air quality.

[0061] This embodiment uses a closed-loop control logic based on a multi-dimensional comfort comprehensive evaluation index to continuously maintain the indoor environment within the optimal comfort range where the predicted average vote count approaches 0, effectively avoiding discomfort such as stuffiness, dryness, and pungent odors caused by excessive levels of a single indicator. In terms of energy saving, intelligent condition determination can be achieved based on comprehensive cost switching factors. For example, when outdoor temperature, humidity, and air quality are poor, the advantages of internal circulation thermal stability can be maximized. Compared to traditional constant external circulation equipment, the annual energy consumption of the air conditioning system can be reduced by 30% to 45%, resulting in significant energy savings. In terms of health protection, regardless of whether it is in external circulation replacement mode or internal circulation purification mode, the multi-dimensional targeted compensation structure can stably control indoor pollutant indicators. For example, formaldehyde concentration can be continuously controlled at 0.08 mg / m³. 3 Within this range, the carbon dioxide concentration remains stable at no more than 800 ppm, and the concentration of odor molecules is maintained below the human olfactory perception threshold, simultaneously achieving the dual control goals of indoor environmental health and thermal comfort.

[0062] In practical applications, the optimal configuration of each parameter in this embodiment is shown in Table 1 below: Table 1 Figure 8This is a schematic block diagram of a comfort optimization control device 800 provided in an embodiment of the present invention. The device 800 is applied to an air conditioner equipped with a fresh air system, and the device 800 includes: The data acquisition unit 801 is used to acquire corresponding multi-dimensional indoor and outdoor environmental data based on multiple preset index parameters, and to filter the multi-dimensional indoor and outdoor environmental data to obtain a multi-dimensional indoor and outdoor environmental vector. The weight calculation unit 802 is used to obtain the initial weights corresponding to multiple indicator parameters and calculate the dynamic weights by combining the multi-dimensional indoor and outdoor environment vectors. The index calculation unit 803 is used to calculate the multi-dimensional comfort comprehensive evaluation index by combining the multi-dimensional indoor and outdoor environment vectors and dynamic weights. The degree judgment unit 804 is used to determine whether the indoor comfort meets the preset degree requirements based on the multidimensional comfort comprehensive evaluation index. The parameter adjustment unit 805 is used to actively adjust the operating parameters of the air conditioner based on the multi-dimensional indoor and outdoor environment vector if it is determined that the indoor comfort level does not meet the preset requirements. The judgment unit 806 is used to continue calculating the multidimensional comfort comprehensive evaluation index after active adjustment until the indoor comfort is determined to meet the preset level requirements.

[0063] In one embodiment, the data acquisition unit 801 includes: The sensor acquisition unit is used to collect multi-dimensional indoor and outdoor environmental data through pre-deployed multi-dimensional sensors for multiple preset index parameters; wherein, the multiple index parameters include temperature, humidity, carbon dioxide, formaldehyde and odor gas molecules; The filtering unit is used to perform moving average filtering on the multi-dimensional indoor and outdoor environmental data to eliminate transient noise in the multi-dimensional indoor and outdoor environmental data and obtain the multi-dimensional indoor and outdoor environmental vector.

[0064] In one embodiment, the weight calculation unit 802 includes: The deviation acquisition unit is used to acquire the deviation between the multi-dimensional indoor and outdoor environment vector and the preset optimal vector center; A dynamic calculation unit is used to calculate dynamic weights for the multi-dimensional indoor and outdoor environment vector by combining the deviation degree with the initial weights.

[0065] In one embodiment, the index calculation unit 803 includes: The function calculation unit is used to calculate the comfort membership function based on the multi-dimensional indoor and outdoor environment vectors. An index synthesis unit is used to synthesize the dynamic weights and comfort membership functions into the multidimensional comfort comprehensive evaluation index.

[0066] In one embodiment, such as Figure 9 As shown, the degree determination unit 804 includes: The index comparison unit 901 is used to compare the multidimensional comfort comprehensive evaluation index with a preset comfort threshold. The first determination unit 902 is used to determine that the indoor comfort meets the preset degree requirements if the multidimensional comfort comprehensive evaluation index reaches the comfort threshold. The second determination unit 903 is used to determine that the indoor comfort does not meet the preset level requirements if the multidimensional comfort comprehensive evaluation index does not reach the comfort threshold.

[0067] In one embodiment, such as Figure 10 As shown, the parameter adjustment unit 805 includes: The difference acquisition unit 1001 is used to acquire the indoor and outdoor vector difference corresponding to the multi-dimensional indoor and outdoor environment vector; The factor calculation unit 1002 is used to obtain the preset target values ​​of multiple indicator parameters, and calculate the comprehensive cost switching factor based on the indoor-outdoor vector difference and the target values; The factor comparison unit 1003 is used to compare the comprehensive cost switching factor with a preset factor threshold; wherein the preset factor threshold includes a first factor threshold and a second factor threshold, and the first factor threshold is greater than the second factor threshold. The first instruction generation unit 1004 is used to generate an external circulation cleaning instruction if the comprehensive cost switching factor is greater than the first factor threshold, and to control the air conditioner to run the corresponding external circulation cleaning mode according to the external circulation cleaning instruction. The second instruction generation unit 1005 is used to generate a mixed micro-percolation instruction if the comprehensive cost switching factor is greater than the second factor threshold and less than or equal to the first factor threshold, and to control the air conditioner to operate the corresponding mixed micro-percolation mode according to the mixed micro-percolation instruction. The third instruction generation unit 1006 is used to generate an internal circulation cleaning instruction if the comprehensive cost switching factor is less than or equal to the first factor threshold, and to control the air conditioner to run the corresponding internal circulation cleaning mode according to the internal circulation cleaning instruction.

[0068] In one embodiment, the parameter adjustment unit 805 further includes: The parameter acquisition unit is used to acquire the target index parameter with the highest dynamic weight based on the multi-dimensional indoor environment vector and the multi-dimensional comfort comprehensive evaluation index. The targeted compensation unit is used to generate targeted compensation instructions based on the target index parameters, and to control the air conditioner to adjust parameters according to the targeted compensation instructions; wherein, the targeted compensation instructions include any one of temperature and humidity decoupling control, carbon dioxide oxygen-enriched dilution, formaldehyde catalytic decomposition, and odor physicochemical dual-effect adsorption.

[0069] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0070] The aforementioned comfort optimization control device can be implemented as a computer program, which can, for example... Figure 11 The air conditioner shown is running.

[0071] Please see Figure 11 , Figure 11 This is a schematic block diagram of an air conditioner provided in an embodiment of the present invention. The air conditioner 1100 is a device with both wireless and wired communication capabilities.

[0072] See Figure 11 The air conditioner 1100 includes a processor 1102, a memory, and a network interface 1105 connected via a system bus 1101. The memory may include a non-volatile storage medium 1103 and internal memory 1104.

[0073] The non-volatile storage medium 1103 may store an operating system 11031 and a computer program 11032. When the computer program 11032 is executed, it causes the processor 1102 to execute a comfort optimization control method.

[0074] The processor 1102 is used to provide computing and control capabilities to support the operation of the entire air conditioner 1100.

[0075] The internal memory 1104 provides an environment for the execution of the computer program 11032 in the non-volatile storage medium 1103. When the computer program 11032 is executed by the processor 1102, the processor 1102 can execute a comfort optimization control method.

[0076] This network interface 1105 is used for network communication with other devices. Those skilled in the art will understand that... Figure 11 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the air conditioner 1100 to which the present invention is applied. A specific air conditioner 1100 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0077] The processor 1102 is used to run a computer program 11032 stored in a memory to implement any embodiment of the comfort optimization control method described above.

[0078] It should be understood that, in this embodiment of the invention, the processor 1102 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0079] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0080] Therefore, the present invention also provides a storage medium. This storage medium may be a computer-readable storage medium. The storage medium stores a computer program. When executed by a processor, the computer program causes the processor to perform any embodiment of the comfort optimization control method described above.

[0081] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0082] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0083] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0084] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0085] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an air conditioner to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0086] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0087] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Since these modifications and variations fall within the scope of the claims and their equivalents, this invention also intends to include these modifications and variations.

[0088] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A comfort optimization control method, applied to an air conditioner equipped with a fresh air system, characterized in that, The method includes: Based on multiple preset index parameters, corresponding multi-dimensional indoor and outdoor environmental data are collected, and the multi-dimensional indoor and outdoor environmental data are filtered to obtain a multi-dimensional indoor and outdoor environmental vector. Obtain the initial weights corresponding to multiple indicator parameters, and calculate the dynamic weights by combining them with the multi-dimensional indoor and outdoor environment vectors; The multidimensional comfort comprehensive evaluation index is calculated by combining the aforementioned multidimensional indoor and outdoor environmental vectors and dynamic weights. The indoor comfort level is determined based on the multidimensional comfort comprehensive evaluation index to determine whether it meets the preset requirements. If it is determined that the indoor comfort level does not meet the preset requirements, the operating parameters of the air conditioner are actively adjusted based on the multi-dimensional indoor and outdoor environment vectors. Continue calculating the multidimensional comfort comprehensive evaluation index after active adjustment until it is determined that the indoor comfort meets the preset requirements.

2. The comfort optimization control method according to claim 1, characterized in that, The process involves collecting multi-dimensional indoor and outdoor environmental data based on multiple preset indicator parameters, and then filtering the multi-dimensional indoor and outdoor environmental data to obtain a multi-dimensional indoor and outdoor environmental vector, including: For multiple preset index parameters, multi-dimensional indoor and outdoor environmental data are collected by pre-deployed multi-dimensional sensors; wherein, the multiple index parameters include temperature, humidity, carbon dioxide, formaldehyde and odor gas molecules; The multi-dimensional indoor and outdoor environmental data are subjected to moving average filtering to eliminate transient noise in the multi-dimensional indoor and outdoor environmental data, and the multi-dimensional indoor and outdoor environmental vector is obtained.

3. The comfort optimization control method according to claim 1, characterized in that, The step of obtaining initial weights corresponding to multiple indicator parameters and calculating dynamic weights by combining them with the multi-dimensional indoor and outdoor environment vectors includes: Obtain the deviation between the multi-dimensional indoor and outdoor environment vector and the preset optimal vector center; By combining the deviation and the initial weight, dynamic weights are calculated for the multi-dimensional indoor and outdoor environment vectors.

4. The comfort optimization control method according to claim 1, characterized in that, The calculation of the multidimensional comfort comprehensive evaluation index by combining the multidimensional indoor and outdoor environmental vectors and dynamic weights includes: The comfort membership function is calculated based on the multi-dimensional indoor and outdoor environment vectors. The dynamic weights and comfort membership functions are combined to form the multidimensional comfort comprehensive evaluation index.

5. The comfort optimization control method according to claim 1, characterized in that, The step of determining whether the indoor comfort level meets the preset requirements based on the multidimensional comfort comprehensive evaluation index includes: The multidimensional comfort comprehensive evaluation index is compared with a preset comfort threshold. If the multidimensional comfort comprehensive evaluation index reaches the comfort threshold, then the indoor comfort is determined to meet the preset level requirements. If the multidimensional comfort comprehensive evaluation index does not reach the comfort threshold, it is determined that the indoor comfort does not meet the preset level requirements.

6. The comfort optimization control method according to claim 1, characterized in that, If it is determined that the indoor comfort level does not meet the preset requirements, the operating parameters of the air conditioner are actively adjusted based on the multi-dimensional indoor and outdoor environmental vectors, including: Obtain the indoor-outdoor vector difference corresponding to the multi-dimensional indoor-outdoor environment vector; Obtain preset target values ​​for multiple indicator parameters, and calculate the comprehensive cost switching factor based on the indoor-outdoor vector difference and the target values; The comprehensive cost switching factor is compared with a preset factor threshold; wherein the preset factor threshold includes a first factor threshold and a second factor threshold, and the first factor threshold is greater than the second factor threshold. If the comprehensive cost switching factor is greater than the first factor threshold, an external circulation cleaning instruction is generated, and the air conditioner is controlled to run the corresponding external circulation cleaning mode according to the external circulation cleaning instruction. If the comprehensive cost switching factor is greater than the second factor threshold and less than or equal to the first factor threshold, a mixed micro-percolation command is generated, and the air conditioner is controlled to operate the corresponding mixed micro-percolation mode according to the mixed micro-percolation command. If the comprehensive cost switching factor is less than or equal to the first factor threshold, an internal circulation cleaning instruction is generated, and the air conditioner is controlled to operate the corresponding internal circulation cleaning mode according to the internal circulation cleaning instruction.

7. The comfort optimization control method according to claim 1, characterized in that, The step of actively adjusting the operating parameters of the air conditioner based on the multi-dimensional indoor and outdoor environment vectors if the indoor comfort level is determined to be insufficient also includes: Based on the multi-dimensional indoor environment vector and the multi-dimensional comfort comprehensive evaluation index, the target index parameter with the highest dynamic weight is obtained; Based on the target index parameters, a targeted compensation instruction is generated, and the air conditioner is controlled to adjust its parameters according to the targeted compensation instruction; wherein, the targeted compensation instruction includes any one of temperature and humidity decoupling control, carbon dioxide oxygen-enriched dilution, formaldehyde catalytic decomposition, and odor physicochemical dual-effect adsorption.

8. A comfort optimization control device, applied to an air conditioner equipped with a fresh air system, characterized in that, The device includes: The data acquisition unit is used to collect corresponding multi-dimensional indoor and outdoor environmental data based on multiple preset index parameters, and to filter the multi-dimensional indoor and outdoor environmental data to obtain a multi-dimensional indoor and outdoor environmental vector. The weight calculation unit is used to obtain the initial weights corresponding to multiple indicator parameters, and to calculate the dynamic weights by combining the multi-dimensional indoor and outdoor environment vectors. The index calculation unit is used to calculate a multi-dimensional comfort comprehensive evaluation index by combining the multi-dimensional indoor and outdoor environment vectors and dynamic weights. The degree judgment unit is used to determine whether the indoor comfort meets the preset degree requirements based on the multi-dimensional comfort comprehensive evaluation index. The parameter adjustment unit is used to actively adjust the operating parameters of the air conditioner based on the multi-dimensional indoor and outdoor environment vector if it is determined that the indoor comfort level does not meet the preset requirements. The satisfaction judgment unit is used to continue calculating the multidimensional comfort comprehensive evaluation index after active adjustment until the indoor comfort is determined to meet the preset level requirements.

9. An air conditioner, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the comfort optimization control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the comfort optimization control method as described in any one of claims 1 to 7.

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