Control method and system capable of automatically adjusting fresh air volume of room

Abstract

The invention relates to the technical field of air volume control, and discloses a control method and system capable of automatically adjusting the fresh air volume of a room, and the method comprises the steps: obtaining and storing the in-room condition time historical data of the room, extracting a room condition change condition set based on the environment parameters and the variable quantity, and building a condition-attached in-room rate prediction model; in each control period, the number of indoor personnel and environment parameters are collected, and in combination with personnel change categories, the current attached condition in-room rate is obtained through the prediction model; and calculating the basic fresh air volume and the corrected fresh air volume, synthesizing the basic fresh air volume and the corrected fresh air volume to obtain the target fresh air volume, generating an execution instruction, and storing and updating the periodic data. Through data-driven historical behavior pattern learning and real-time multi-parameter fusion prediction, balance between timeliness and stability of fresh air volume setting is achieved, and the problem of slow control response or frequent fluctuation caused by personnel discrete change and environment feedback lag is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of air volume control, and more particularly, to an automatic adjustable fresh air volume control method and system for a room. Background Art

[0002] The fresh air system dilutes carbon dioxide, fine particulate matter, volatile organic compounds, odors, etc. by introducing outdoor air into the room and exhausting some indoor air, and cooperates with temperature and humidity regulation to a certain extent. It has been widely used in residential and small indoor spaces. The setting of the fresh air volume usually needs to balance air quality, comfort and energy consumption. Therefore, the rationality of the control strategy directly affects the user experience and operating cost.

[0003] The existing room fresh air volume control methods mainly include: fixed air volume operation, multi-stage operation, timed operation, and regulation operation based on sensor feedback. In the method based on sensor feedback, the common practice is to use carbon dioxide concentration or fine particulate matter concentration as the main control quantity, and use threshold control or proportional control to adjust the fan speed and valve opening; there are also solutions that use human presence detection, number estimation, door and window opening and closing states, etc. as auxiliary information for linkage control.

[0004] The above methods are relatively simple in engineering implementation, but often face multi-source uncertain factors in the home scenario: on the one hand, the environmental parameters themselves have measurement noise, drift and sampling delay, and indicators such as carbon dioxide have obvious lag characteristics; on the other hand, activities such as opening and closing doors and windows, cooking, smoking, cleaning, etc. will introduce short-term strong disturbances, making the environmental parameters show non-stationary fluctuations; at the same time, the residential space volume is small and the change range of the number of people is limited, resulting in discrete jumps rather than continuous changes in the number-related signals over time. Summary of the Invention

[0005] In view of this, the present invention proposes an automatic adjustable fresh air volume control method and system for a room, aiming to solve the problem that in small space scenarios such as homes, where the entry and exit of people are discrete events, the feedback of environmental parameters is lagging and vulnerable to transient disturbances such as opening and closing doors and windows and daily activities, it is difficult for the existing fresh air control methods to achieve the timeliness and stability of fresh air volume setting under limited observation conditions, and it is easy to出现新风量调整滞后或频繁波动的问题。

[0006] On the one hand, the present invention proposes an automatic adjustable fresh air volume control method for a room, including: Obtain and store the time history data of the occupancy status of the room; based on the environmental parameters and the change amount of environmental parameters in the time history data of the occupancy status, extract the set of room condition change conditions; Based on each room condition change condition in the set of room condition change conditions, the total number of samples that meet the room condition change conditions is counted, and the number of samples that are occupied is counted. The conditional occupancy rate is calculated based on the number of occupied samples and the total number of samples. An occupancy rate prediction model is established based on the room condition change conditions and the conditional occupancy rate. The number of people in the room and environmental parameters are collected in each control cycle, and the change of the environmental parameters relative to the environmental parameters in the previous control cycle is calculated. The difference between the number of people indoors in the current control cycle and the number of people indoors in the previous control cycle is calculated to obtain the personnel number difference value. The personnel number change category is determined based on the personnel number difference value. Based on the environmental parameters and changes in environmental parameters during the current control cycle, the current room condition change conditions are determined. These current room condition change conditions are then input into the occupancy rate prediction model to obtain the conditional occupancy rate for the target control cycle. The basic fresh air volume is determined based on the number of people in the room and the environmental parameters. The corrected fresh air volume is determined based on the conditional occupancy rate and the category of changes in the number of people. The basic fresh air volume and the corrected fresh air volume are then combined to form the target fresh air volume. An execution parameter set is generated based on the target fresh air volume. Control commands are output to the fan according to the execution parameter set. The collected data of the target control cycle, the current room status change conditions, the conditional occupancy rate, the target fresh air volume, and the execution parameter set are stored in the occupancy status time history data.

[0007] Furthermore, when extracting the set of room condition change conditions based on the environmental parameters and changes in environmental parameters in the historical data of room conditions over time, the following steps are included: The historical values ​​of each environmental parameter in the indoor condition time history data are sorted, and the historical values ​​are divided into at least two value intervals according to the number of samples to obtain the value interval boundary of the corresponding environmental parameter; the changes of the environmental parameters are sorted, and the changes of the environmental parameters are divided into at least two change intervals according to the number of samples to obtain the change interval boundary of the corresponding environmental parameter. For each time sample in the historical data of room conditions, the value range identifier of the time sample is determined according to the value range boundary of the corresponding environmental parameter, and the change range identifier of the time sample is determined according to the change range boundary of the corresponding environmental parameter. The value range identifier and change range identifier of each environmental parameter are combined to form the room condition change conditions. The room condition change conditions are deduplicated, and the number of times each room condition change condition appears in the in-room time history data after deduplication is counted. When the number of times any room condition change condition appears is less than a first number, the value range or change range corresponding to at least one environmental parameter in the room condition change condition is merged with the adjacent range, and a new room condition change condition is formed. The counting and merging are repeated to obtain a set of room condition change conditions.

[0008] Furthermore, when collecting the number of people in the room and environmental parameters in each control cycle, and calculating the change in environmental parameters relative to the previous control cycle, the process includes: Within the control period, multiple sampled values ​​of the same environmental parameter are acquired at a first sampling interval; the multiple sampled values ​​are sorted, and several sampled values ​​at the smallest and largest ends of the sorted values ​​are removed. The average value of the remaining sampled values ​​is determined as the periodic value of the environmental parameter for the control period. When the change in the number of people is classified as either a change in entering or leaving the room, the first sampling interval is adjusted to the second sampling interval, and the multiple sampling values ​​are reacquired and the periodic values ​​of the environmental parameters are redefined within the control cycle. The change in environmental parameters is obtained by subtracting the periodic value of the environmental parameters in the current control cycle from the periodic value of the environmental parameters in the previous control cycle. The control cycle duration is fixed, and the adjustment of the first sampling interval and the second sampling interval does not change the control cycle duration.

[0009] Furthermore, when establishing an occupancy rate prediction model based on changes in room conditions and additional conditions, the following are included: Establish a room condition change condition index table. Each record in the room condition change condition index table contains a room condition change condition, the total number of samples corresponding to the room condition change condition, the number of occupied samples corresponding to the room condition change condition, and the conditional occupancy rate calculated from the number of occupied samples and the total number of samples. Within each control cycle, the current room status change conditions are matched with the room status change condition index table. When a match is successful, the conditional occupancy rate corresponding to the matched record is read. If a match fails, the current room status change conditions are reconstructed according to a preset priority order and then matched again. The preset priority order includes deleting the environmental parameter change range identifier first, then deleting the environmental parameter value range identifier, and merging adjacent environmental parameter value ranges or adjacent environmental parameter change ranges after deletion. Each reconstruction is followed by a match until a match is successful or the maximum number of reconstructions is reached. If a match is still not found after reaching the maximum number of reconstruction attempts, read the conditional occupancy rate corresponding to the record that appears most frequently in the room condition change condition index table.

[0010] Furthermore, when determining the basic fresh air volume based on the number of people indoors and environmental parameters, the following should be considered: Obtain basic room parameters, which are derived from user input parameter tables or building information parameter tables. These parameters include room area, room volume, and room purpose. Determine the fresh air volume per person based on the basic room parameters. Multiply the number of people in the room by the fresh air volume per person to obtain the required fresh air volume per person. For each environmental parameter, read the target value of the environmental parameter; calculate the deviation between the environmental parameter and the target value of the environmental parameter; determine the fresh air volume increment value corresponding to the environmental parameter based on the area where the deviation falls in the multi-segment mapping table. The multi-segment mapping table is a monotonically non-decreasing mapping relationship between the fresh air volume increment value and the deviation value. The incremental values ​​of fresh air volume corresponding to environmental parameters are combined to obtain the environmental fresh air volume demand value. The basic fresh air volume is obtained by combining the fresh air volume requirements of the number of people and the fresh air volume requirements of the environment. Boundary constraints are imposed on the basic fresh air volume, which include being greater than or equal to the minimum fresh air volume and less than or equal to the maximum fresh air volume; the rate of change constraint is imposed on the basic fresh air volume, which includes the change in the basic fresh air volume between adjacent control cycles not exceeding the limit value.

[0011] Furthermore, when determining the corrected fresh air volume based on the conditional occupancy rate and the category of personnel number changes, the following steps are included: Read the category of personnel quantity change and read the correction mode parameter set, which includes the correction coefficient for entering the room, the correction coefficient for leaving the room, and the correction coefficient for no change. When the category of personnel quantity change is entering the room, select the correction coefficient for entering the room; when the category of personnel quantity change is leaving the room, select the correction coefficient for leaving the room; when the category of personnel quantity change is no change, select the correction coefficient for no change. The probability weight value is determined based on the conditional occupancy rate, and the corrected fresh air volume is obtained by multiplying the probability weight value by the correction coefficient. The corrected fresh air volume is subject to a limiting constraint, which includes ensuring that the corrected fresh air volume does not exceed a predetermined percentage of the basic fresh air volume, and the corrected fresh air volume is determined accordingly.

[0012] Furthermore, when combining the basic fresh air volume and the corrected fresh air volume into the target fresh air volume, it includes: Calculate the combined value of the base fresh air volume and the corrected fresh air volume; Compare the composite value with the minimum fresh air volume and take the value that is greater than or equal to the minimum fresh air volume; compare the composite value with the maximum fresh air volume and take the value that is less than or equal to the maximum fresh air volume. When the change in the number of people is classified as an entry change, the first upward limit rule is used to limit the target fresh air volume; when the change in the number of people is classified as an exit change, the first downward limit rule is used to limit the target fresh air volume; when the change in the number of people is classified as no change, the second limit rule is used to limit the target fresh air volume. The first upward limit rule, the first downward limit rule, and the second limit rule respectively limit the maximum increase, maximum decrease, and maximum change of the target fresh air volume in adjacent control cycles, thereby determining the target fresh air volume.

[0013] Furthermore, when generating the set of execution parameters based on the target fresh air volume, it includes: Obtain the fan operating characteristic table, which records the correspondence between fresh air volume and fan speed, and the correspondence between fresh air valve opening and fresh air volume; Based on the target fresh air volume, the matching range is found in the fan operating characteristic table to obtain the fan speed setting value and the fresh air valve opening setting value; At least one of the fan speed setpoint and the fresh air valve opening setpoint is selected as the set of execution parameters, and the set of execution parameters is constrained. The constraint process includes speed limit, valve opening limit, and adjacent control cycle change rate limit. If the set of execution parameters does not meet the speed limit or valve opening limit, the set of execution parameters is adjusted to the corresponding limit boundary value. The set of execution parameters is output to the fan or fresh air valve to form control commands.

[0014] Furthermore, when storing the collected data of the target control cycle, current room condition changes, conditional occupancy rate, target fresh air volume, and set of execution parameters into the historical data of occupancy time, this includes: Time alignment is performed on the collected data for the target control cycle. Time alignment includes mapping the number of people indoors, environmental parameters, and changes in environmental parameters to the same control cycle timestamp. The current room status change conditions, conditional occupancy rate, target fresh air volume, and set of execution parameters are associated with the control cycle timestamp and stored to form a control cycle record. The control cycle records are subjected to integrity verification, which includes field missing verification and value range verification. If the integrity verification passes, the in-room status time history data is written. If the integrity verification fails, the control cycle record is deleted and replaced with the previous control cycle record. Capacity management is performed on historical data of in-room conditions. Capacity management includes deleting the earliest record according to the time window or downsampling historical records according to the sampling interval.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: By storing and managing the historical data of room occupancy time, and extracting the set of room condition change conditions based on environmental parameters and changes in environmental parameters, the present invention obtains the conditional occupancy rate by statistically analyzing the number of occupant samples and the total number of samples under the room condition change conditions, and establishes an occupancy rate prediction model. This enables the current room condition change conditions to be determined based on the current environmental parameters and changes in environmental parameters within the control cycle, and the conditional occupancy rate for the target control cycle to be obtained. At the same time, within each control cycle, the basic fresh air volume and the corrected fresh air volume are calculated by combining the number of people in the room, environmental parameters, and the type of change in the number of people, and are combined into the target fresh air volume. The target fresh air volume is then converted into an execution parameter set to output control commands, and the control cycle data is written back to the historical data of room occupancy time. This provides a traceable historical data basis for the fresh air volume setting process and forms a continuous accumulation and iterative update mechanism for control cycle data.

[0016] On the other hand, this application also provides an automatic room fresh air volume control system for implementing the above-mentioned automatic room fresh air volume control method, including: The historical data acquisition module is configured to acquire and store historical data on the room's in-room status over time; and to extract a set of room status change conditions based on the environmental parameters and changes in those environmental parameters in the historical data on the room's in-room status over time. In the occupancy rate statistical modeling module, it is configured to count the total number of samples that meet the room condition change conditions according to each room condition change condition in the set of room condition change conditions, and count the number of samples that are occupied. The conditional occupancy rate is calculated based on the number of occupied samples and the total number of samples. An occupancy rate prediction model is established based on the room condition change conditions and the conditional occupancy rate. The control cycle acquisition module is configured to acquire the number of people in the room and environmental parameters in each control cycle, and calculate the change of the environmental parameters relative to the environmental parameters in the previous control cycle. The personnel change determination module is configured to calculate the difference between the number of indoor personnel in the current control cycle and the number of indoor personnel in the previous control cycle to obtain the personnel number difference value, and determine the personnel number change category based on the personnel number difference value; In the room rate inference output module, it is configured to determine the current room condition change conditions based on the environmental parameters and the change of environmental parameters in the current control cycle, and input the current room condition change conditions into the room rate prediction model to obtain the conditional room rate for the target control cycle. The target air volume generation module is configured to determine a basic fresh air volume based on the number of people in the room and the environmental parameters, determine a corrected fresh air volume based on the conditional occupancy rate and the category of changes in the number of people, and combine the basic fresh air volume and the corrected fresh air volume into a target fresh air volume. The execution parameter storage module is configured to generate an execution parameter set based on the target fresh air volume, output control commands to the fan according to the execution parameter set, and store the collected data of the target control cycle, the current room status change conditions, the conditional occupancy rate, the target fresh air volume, and the execution parameter set into the occupancy status time history data.

[0017] It is understandable that the above-mentioned method and system for automatically adjusting the fresh air volume in a room have the same beneficial effects, and will not be elaborated further here. Attached Figure Description

[0018] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart of a method for automatically adjusting room fresh air volume control provided by an embodiment of the present invention; Figure 2 This is a functional block diagram of a room fresh air volume control system that can automatically adjust the room's air volume, provided as an embodiment of the present invention. Detailed Implementation

[0019] Exemplary embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0020] See Figure 1 As shown, this application proposes a method for automatically adjusting the fresh air volume control of a room, comprising: S1: Acquire and store the historical data of the room's in-room status over time; based on the environmental parameters and changes in environmental parameters in the historical data of the room's in-room status over time, extract the set of conditions for changes in the room's status; S2: Based on each room condition change condition in the set of room condition change conditions, count the total number of samples that meet the room condition change conditions, and count the number of samples that are occupied. Calculate the conditional occupancy rate based on the number of occupied samples and the total number of samples. Establish an occupancy rate prediction model based on the room condition change conditions and the conditional occupancy rate. S3: Collect the number of people in the room and environmental parameters in each control cycle, and calculate the change in environmental parameters relative to the previous control cycle. S4: Calculate the difference between the number of indoor personnel in the current control cycle and the number of indoor personnel in the previous control cycle to obtain the personnel number difference value, and determine the personnel number change category based on the personnel number difference value; S5: Based on the environmental parameters and changes in environmental parameters during the current control cycle, determine the current room condition change conditions, input the current room condition change conditions into the occupancy rate prediction model, and obtain the conditional occupancy rate for the target control cycle. S6: Determine the basic fresh air volume based on the number of people in the room and environmental parameters, determine the corrected fresh air volume based on the conditional occupancy rate and the category of changes in the number of people, and combine the basic fresh air volume and the corrected fresh air volume into the target fresh air volume; S7: Generates a set of execution parameters based on the target fresh air volume, outputs control commands to the fan according to the set of execution parameters, and stores the collected data of the target control cycle, the current room condition change conditions, the conditional occupancy rate, the target fresh air volume, and the set of execution parameters in the occupancy time history data.

[0021] Specifically, the indoor status time history data is a collection of historical samples recorded in chronological order. Each historical sample includes the sampling time, indoor status marker, number of people indoors, carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. The indoor status marker is used to distinguish between occupied and unoccupied states, and the number of people indoors is the number of people detected at that sampling time.

[0022] The change in environmental parameters is the difference between the periodic values ​​of environmental parameters in adjacent control cycles. The periodic value of environmental parameters is a representative value obtained by averaging the remaining sampled values ​​after sorting multiple sampled values ​​of the same environmental parameter within the control cycle, removing several sampled values ​​at the minimum and maximum ends, and so on. The change in environmental parameters is used to reflect the direction and magnitude of change of environmental parameters between adjacent control cycles.

[0023] The set of room condition change conditions is a set of condition categories extracted and summarized from historical data on room conditions over time. The room condition change conditions are formed by combining the identifiers of carbon dioxide concentration ranges, temperature ranges, humidity ranges, fine particulate matter concentration ranges, carbon dioxide concentration change ranges, temperature change ranges, humidity change ranges, and fine particulate matter concentration change ranges. The range identifiers are determined by dividing the ranges according to the sample size after sorting the historical values ​​of the corresponding environmental parameters. The change range identifiers are determined by dividing the change ranges according to the sample size after sorting the changes in the corresponding environmental parameters. After generating room condition change conditions for each historical sample, duplicates are removed and the frequency of occurrence is counted. Room condition change conditions with fewer than the first occurrence number are re-formed by merging adjacent ranges or adjacent change ranges. This process of repeated counting and merging yields the set of room condition change conditions.

[0024] The conditional occupancy rate is the proportion of rooms occupied under given changes in room conditions. The conditional occupancy rate is calculated from the total number of samples that meet the room condition change conditions and the number of samples that are occupied. The occupancy rate prediction model is a mapping structure from room condition change conditions to the conditional occupancy rate. The mapping structure is implemented using a room condition change condition index table, which records the room condition change conditions, the total number of samples, the number of occupied samples, and the calculated conditional occupancy rate.

[0025] Within each control cycle, the number of people indoors, carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration are collected, and the changes in carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration are calculated. The difference in the number of people is the difference between the number of people indoors in the current control cycle and the number of people indoors in the previous control cycle. The category of change in the number of people is determined based on the difference in the number of people: change upon entering the room, change upon leaving the room, or no change. The current room condition change conditions are obtained by combining the carbon dioxide concentration, temperature, humidity, fine particulate matter concentration and corresponding changes in the current control period, according to the boundary of the value interval and the boundary of the change interval. The current room condition change conditions are input into the occupancy rate prediction model, and the index table is matched to obtain the conditional occupancy rate of the target control period. If the matching fails, the current room condition change conditions are reconstructed according to the preset priority order. The preset priority order is to first delete the environmental parameter change interval identifier, then delete the environmental parameter value interval identifier, and then merge adjacent environmental parameter value intervals or merge adjacent environmental parameter change intervals. Each reconstruction is performed once, until the matching is successful or the maximum number of reconstructions is reached. If the maximum number of reconstructions is reached and the matching still fails, the conditional occupancy rate corresponding to the record with the highest occurrence in the index table is read.

[0026] The basic fresh air volume is the fresh air volume value determined based on the number of people in the room and environmental parameters. The basic fresh air volume is calculated by determining the fresh air volume per person through the basic room parameters, then calculating the fresh air volume requirement per person, and determining the incremental fresh air volume value based on the deviation of the target value of environmental parameters and a multi-segment mapping table. The fresh air volume requirement per person and the environmental fresh air volume requirement are then combined to obtain the target fresh air volume. The corrected fresh air volume is the fresh air volume value determined based on the conditional occupancy rate and the category of changes in the number of people. The corrected fresh air volume is obtained by multiplying the probability weight value determined by the conditional occupancy rate with the corresponding correction coefficient in the correction mode parameter set, including the inbound correction coefficient, the outbound correction coefficient, and the unchanged correction coefficient, and then applying amplitude constraints. The basic fresh air volume and the corrected fresh air volume are combined to obtain the target fresh air volume.

[0027] The execution parameter set is the set of parameters after converting the target fresh air volume into executable parameters for the fan. The execution parameter set is formed by looking up the fan speed setpoint and fresh air valve opening setpoint from the fan operating characteristic table and then subjecting them to amplitude and rate of change constraints. Control commands are output to the fan according to the execution parameter set, and the collected data of the target control cycle, the current room status change conditions, the conditional occupancy rate, the target fresh air volume, and the execution parameter set are stored in the occupancy time history data. The storage includes time alignment, associated storage, integrity verification, and capacity management. Capacity management is achieved by deleting the earliest record according to the time window and by downsampling the historical records according to the sampling interval.

[0028] In some embodiments of this application, when extracting a set of room condition change conditions based on environmental parameters and changes in environmental parameters in historical data of room conditions over time, the following steps are included: The historical values ​​of each environmental parameter in the indoor condition time history data are sorted and divided into at least two value intervals according to the sample size to obtain the value interval boundary of the corresponding environmental parameter; the changes of the environmental parameters are sorted and divided into at least two change intervals according to the sample size to obtain the change interval boundary of the corresponding environmental parameter. For each time sample in the historical data of room conditions, the value range identifier of the time sample is determined according to the value range boundary of the corresponding environmental parameter, and the change range identifier of the time sample is determined according to the change range boundary of the corresponding environmental parameter. The value range identifier and change range identifier of each environmental parameter are combined to form the room condition change conditions. The room condition change conditions are deduplicated, and the occurrence frequency of each room condition change condition in the historical data of room condition time is counted. When the occurrence frequency of any room condition change condition is less than the first number, the value range or change range corresponding to at least one environmental parameter in the room condition change condition is merged with the adjacent range, and a new room condition change condition is formed. The counting and merging are repeated to obtain the set of room condition change conditions.

[0029] Specifically, the environmental parameters in the historical data of indoor conditions include carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. The changes in these environmental parameters are the changes in carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. Historical value sequences are compiled for each of these parameters. Each historical value sequence is then sorted from smallest to largest, and the sorted sequences are divided into several continuous intervals according to the sample size. This ensures that the number of samples within each interval meets a predetermined distribution rule, and the endpoints of the intervals correspond to the interval boundaries. Regarding carbon dioxide concentration... The changes in temperature, humidity, and fine particulate matter concentration are summarized to obtain a change sequence. Each change sequence is sorted from smallest to largest, and the sorted change sequence is divided into several continuous intervals according to the number of samples. The number of samples contained in each change interval meets the predetermined number allocation rules, and the interval endpoints correspond to the change interval boundaries. When there are the same values ​​or the same changes in the sorted sequence, resulting in the repetition of interval endpoints, the adjacent intervals of the repetitive endpoints are merged into the same continuous interval, and the interval boundaries are updated, thereby ensuring that the value interval boundaries and change interval boundaries are a monotonically increasing set of boundaries.

[0030] For each time sample in the historical data of indoor conditions, the carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration are compared with the corresponding value interval boundaries to determine the carbon dioxide concentration value interval identifier, temperature value interval identifier, humidity value interval identifier, and fine particulate matter concentration value interval identifier. Then, the changes in carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration are compared with the corresponding change interval boundaries to determine the carbon dioxide concentration change interval identifier, temperature change interval identifier, humidity change interval identifier, and fine particulate matter concentration change interval identifier. These eight interval identifiers are combined in a fixed order to form the room condition change conditions. The combination method is to form ordered tuples or encoded strings using the interval identifiers, so that each time sample generates a unique room condition change condition representation.

[0031] For all time-based samples of room condition change conditions, a deduplication operation is performed. The deduplication method involves establishing a mapping table between room condition change conditions and count values. For each occurrence of the same room condition change condition, the count value is incremented by one, resulting in the deduplicated set of room condition change conditions and the number of times each room condition change condition appears in the historical data of room conditions over time. When the number of occurrences is less than a predetermined threshold, the room condition change conditions are merged by merging either the value interval or the change interval. The value interval merging is performed by combining one of the following intervals: carbon dioxide concentration, temperature, humidity, or fine particulate matter concentration. Each value interval is merged with adjacent value intervals and the value interval boundaries are updated. The change intervals are merged by merging one of the change intervals of carbon dioxide concentration, temperature, humidity and fine particulate matter concentration with an adjacent change interval and updating the change interval boundaries. After merging, the interval identifiers of the affected time samples are re-determined and recombined to form room condition change conditions. The deduplication and counting are performed again. The merging, deduplication and counting process is repeated until the occurrence frequency of each room condition change condition meets the first quantity constraint. Finally, the set of room condition change conditions used for subsequent statistical analysis of conditional occupancy rate is obtained.

[0032] In some embodiments of this application, when collecting the number of people in the room and environmental parameters in each control cycle, and calculating the change in environmental parameters relative to the previous control cycle, the process includes: Within the control period, multiple sampled values ​​of the same environmental parameter are obtained at the first sampling interval; the multiple sampled values ​​are sorted, and several sampled values ​​at the smallest and largest ends of the sorted values ​​are removed. The average value of the remaining sampled values ​​is determined as the periodic value of the environmental parameter in the control period. When the change in the number of people is classified as either a change in entering or leaving the room, the first sampling interval is adjusted to the second sampling interval, and multiple sampling values ​​are reacquired within the control period and the periodic values ​​of environmental parameters are redefined. The change in environmental parameters is obtained by subtracting the periodic value of the environmental parameters in the current control cycle from the periodic value of the environmental parameters in the previous control cycle. The control cycle duration is fixed, and the adjustment of the first sampling interval and the second sampling interval does not change the control cycle duration.

[0033] Specifically, the control cycle is the basic time window for fresh air control. The duration of the control cycle is set to a fixed duration during the system initialization phase and remains unchanged during operation. At the beginning of each control cycle, the system enters the sampling phase of the target control cycle, collecting data on the number of people indoors, carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. The number of people indoors is recorded by reading the number of people detected within the control cycle and forming a record of the number of people in the current control cycle. The carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration are sampled multiple times at a first sampling interval. The first sampling interval is the time interval between two adjacent samples within the same control cycle. The number of samples within the same control cycle is determined by the control cycle duration and the first sampling interval.

[0034] The multiple sampled values ​​obtained for each environmental parameter are sorted. The sampled values ​​at the smallest end of the sorting represent transient low-value disturbances during the sampling process, and the sampled values ​​at the largest end of the sorting represent transient high-value disturbances during the sampling process. After removing the sampled values ​​at the smallest and largest ends, the remaining sampled values ​​are retained and averaged to obtain the environmental parameter periodic value corresponding to the target control period. The environmental parameter periodic value is used as the representative value of the target control period and enters the subsequent process of determining the room condition change conditions. After obtaining the indoor personnel count records for the target control period, the system calculates the personnel count difference by combining it with the indoor personnel count records from the previous control period, and determines the category of personnel count change accordingly. When the personnel count change category is an entry change or an exit change, the system switches the sampling strategy for the target control period to the second sampling interval, which is shorter than the first sampling interval, thus increasing the number of sampled values ​​acquired within the control period. After switching to the second sampling interval, the system resamples the carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration multiple times within the target control period, and repeats the sorting, elimination of interfering values ​​at both ends, and averaging of the remaining sampled values ​​for each environmental parameter to obtain the periodic values ​​of the environmental parameters for the target control period. The control period duration remains unchanged, and the adjustment of the sampling interval only changes the number of samples and the sampling density within the control period, without changing the start and end boundaries of the control period.

[0035] The changes in environmental parameters are calculated at the end of the target control cycle. The calculation method is to subtract the environmental parameter cycle value of the previous control cycle from the environmental parameter cycle value of the current control cycle to obtain the changes in carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration, respectively. The environmental parameter cycle value of the previous control cycle is read from the historical record and associated with the timestamp of the previous control cycle. The environmental parameter cycle value of the current control cycle is associated with the timestamp of the current control cycle, thereby ensuring that the changes in environmental parameters correspond to the differential results of adjacent control cycles.

[0036] The above-mentioned data acquisition, aggregation, and differential processing methods enable each control cycle to output a set of stable environmental parameter periodic values ​​and a set of corresponding environmental parameter changes, which serve as input data for subsequent determination of current room condition changes, indexing of occupancy rate prediction models, calculation of basic fresh air volume, and correction of fresh air volume.

[0037] In some embodiments of this application, when establishing an occupancy rate prediction model based on room condition changes and additional conditions, the following are included: Establish a room condition change condition index table. Each record in the room condition change condition index table contains a room condition change condition, the total number of samples corresponding to the room condition change condition, the number of occupied samples corresponding to the room condition change condition, and the conditional occupancy rate calculated from the number of occupied samples and the total number of samples. Within each control cycle, the current room status change conditions are matched with the room status change condition index table. When a match is successful, the conditional occupancy rate corresponding to the matched record is read. If a match fails, the current room status change conditions are reconstructed according to a preset priority order and then matched again. The preset priority order includes deleting the environmental parameter change range identifier first, then deleting the environmental parameter value range identifier, and merging adjacent environmental parameter value ranges or adjacent environmental parameter change ranges after deletion. Each reconstruction is followed by a match until a match is successful or the maximum number of reconstructions is reached. If a match is still not found after reaching the maximum number of reconstruction attempts, read the conditional occupancy rate corresponding to the record that appears most frequently in the room condition change condition index table.

[0038] Specifically, the occupancy rate prediction model is implemented in the form of a room condition change condition index table. This index table is generated and stored in memory during the model building phase. The key of the index table is the room condition change condition, and the values ​​are the total number of samples corresponding to the same room condition change condition, the number of occupied samples, and the calculated conditional occupancy rate. The room condition change conditions are formed by combining carbon dioxide concentration range identifiers, temperature range identifiers, humidity range identifiers, fine particulate matter concentration range identifiers, carbon dioxide concentration change range identifiers, temperature change range identifiers, humidity change range identifiers, and fine particulate matter concentration change range identifiers in a fixed order, thus ensuring that different records in the index table have a consistent data structure.

[0039] When the index table is created, corresponding room status change conditions are generated for each historical sample in the historical data of room status time, and records with the same room status change conditions are located in the index table, and the total number of corresponding samples is incremented once; when the room status of a historical sample is marked as occupied, the number of occupied samples is incremented once; after all historical samples have been accumulated, the ratio of the number of occupied samples to the total number of samples is calculated for each record in the index table to obtain the conditional room status rate corresponding to the record, and the conditional room status rate is written into the index table record. After the index table is generated, it is saved as the room status prediction model.

[0040] After determining the current room status change conditions within each control cycle, the system uses these conditions as the search key to perform a key-value equivalence match on the index table. If a match is successful, the system directly reads the conditional occupancy rate from the matched record and outputs it as the conditional occupancy rate for the target control cycle. If a match fails, it means there is no record in the index table that perfectly matches the current room status change conditions. The system then enters a reconstructed matching process. This process expands the matchable range by gradually reducing the granularity of the room status change conditions, and an index table match is performed immediately after each reconstruction.

[0041] The preset priority sequence includes three stages: The first stage deletes environmental parameter change range identifiers in the following order: carbon dioxide concentration change range identifiers, temperature change range identifiers, humidity change range identifiers, and fine particulate matter concentration change range identifiers. The second stage deletes environmental parameter value range identifiers in the following order: carbon dioxide concentration value range identifiers, temperature value range identifiers, humidity value range identifiers, and fine particulate matter concentration range identifiers. The third stage performs range merging and reconstruction, which includes merging adjacent environmental parameter value ranges and merging adjacent environmental parameter change ranges. The merging method is to extend the range boundary corresponding to the selected environmental parameter outward to the adjacent range boundary and redetermine the range identifiers, and then recombine them in a fixed order to form the room condition change conditions.

[0042] The maximum number of reconstruction attempts is the upper limit for the reconstruction matching process. This maximum number is set during system initialization, for example, ten times. The reconstruction count begins from the first deletion or merge operation. Each successful deletion or merge and subsequent matching increments the reconstruction count. If the maximum number of reconstruction attempts is reached without a match, the system reads the conditional in-room rate corresponding to the most frequently occurring record in the index table as the conditional in-room rate output for the target control period. The record with the most frequent occurrences is determined by maximizing the total number of samples. Through the process of index table matching, reconstruction matching, and rollback reading, the in-room rate prediction model outputs the conditional in-room rate within the control period, maintaining the continuity of the calculation process even when the index table does not cover certain conditions.

[0043] In some embodiments of this application, determining the basic fresh air volume based on the number of people indoors and environmental parameters includes: Obtain basic room parameters, which are derived from user input parameter tables or building information parameter tables. These parameters include room area, room volume, and room purpose. Determine the fresh air volume per person based on the basic room parameters. Multiply the number of people in the room by the fresh air volume per person to obtain the required fresh air volume per person. For each environmental parameter, read the target value of the environmental parameter; calculate the deviation between the environmental parameter and the target value of the environmental parameter; determine the fresh air volume increment value corresponding to the environmental parameter based on the area where the deviation falls in the multi-segment mapping table. The multi-segment mapping table is a monotonically non-decreasing mapping relationship between the fresh air volume increment value and the deviation value. The incremental values ​​of fresh air volume corresponding to environmental parameters are combined to obtain the environmental fresh air volume demand value. The basic fresh air volume is obtained by combining the fresh air volume requirements of the number of people and the fresh air volume requirements of the environment. Boundary constraints are imposed on the basic fresh air volume, which include being greater than or equal to the minimum fresh air volume and less than or equal to the maximum fresh air volume; the rate of change constraint is imposed on the basic fresh air volume, which includes the change in the basic fresh air volume between adjacent control cycles not exceeding the limit value.

[0044] Specifically, basic room parameters are written into the user input parameter table or building information parameter table during system deployment or initial activation. The user input parameter table stores room area, room volume, and room usage manually entered by the user, while the building information parameter table stores room area, room volume, and room usage imported from the building information model or property delivery data. After the control cycle begins, the basic room parameters are read, and the unit-person fresh air volume rule table is used to find the unit-person fresh air volume value based on the room usage. The unit-person fresh air volume rule table is a mapping table between room usage and unit-person fresh air volume values. For example, the unit-person fresh air volume rule table is based on room usage... The fresh air volume per person is set as follows: 30 cubic meters per hour per person when the room is used as a bedroom, 40 cubic meters per hour per person when the room is used as a living room, and 35 cubic meters per hour per person when the room is used as a study. When the room is used as a living room and there are 2 people in the room, the fresh air volume requirement is 80 cubic meters per hour. Different fresh air volume values ​​per person are corresponding to the room's use as a bedroom, living room, and study. The fresh air volume requirement per person is obtained by multiplying the number of people in the room by the fresh air volume per person value. The fresh air volume requirement per person value represents the ventilation demand based on the number of people.

[0045] The environmental parameters are carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. The target values ​​of the environmental parameters are the target values ​​of carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. The target values ​​of the environmental parameters are written into the target parameter table during the system initialization phase and read during the operation phase. For each environmental parameter, the deviation between the environmental parameter and the corresponding target value is calculated. The deviation is the difference between the environmental parameter and the target value.

[0046] The multi-segment mapping table is a correspondence table between deviation value intervals and fresh air volume increment values. The multi-segment mapping table is divided into multiple continuous deviation intervals according to the deviation value from small to large, and a fresh air volume increment value is configured for each deviation interval, so that the larger the deviation interval, the larger or equal the corresponding fresh air volume increment value. The corresponding fresh air volume increment value is read according to the deviation interval in which the deviation value falls, thereby obtaining the fresh air volume increment values ​​for carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration, respectively.

[0047] The environmental fresh air volume requirement is obtained by synthesizing the incremental values ​​of fresh air volume for carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. The synthesis method is either the maximum value method or the summation method. The maximum value method selects the maximum value among the four fresh air volume increments as the environmental fresh air volume requirement value, while the summation method sums the four fresh air volume increments as the environmental fresh air volume requirement value. The basic fresh air volume is obtained by synthesizing the fresh air volume requirement value for the number of people with the environmental fresh air volume requirement value. The synthesis method is either the maximum value method or the summation method. The maximum value method selects the maximum value among the fresh air volume requirement value for the number of people and the environmental fresh air volume requirement value as the basic fresh air volume, while the summation method sums the fresh air volume requirement value for the number of people and the environmental fresh air volume requirement value as the basic fresh air volume.

[0048] After the basic fresh air volume is obtained, boundary constraints are applied. These constraints are achieved by comparing the basic fresh air volume with the minimum fresh air volume and taking the larger value, and by comparing the basic fresh air volume with the maximum fresh air volume and taking the smaller value. The minimum and maximum fresh air volumes are configured in the equipment parameter table and read during operation. The basic fresh air volume also undergoes a rate of change constraint. This constraint is achieved by calculating the difference between the basic fresh air volume of the current control cycle and the basic fresh air volume of the previous control cycle and comparing it with a limit value. If the difference exceeds the limit value, the basic fresh air volume of the current control cycle is adjusted to the basic fresh air volume of the previous control cycle plus or minus the limit value. The limit value is configured in the control strategy parameter table. For example, the limit value is set to ensure that the change in each control cycle does not exceed a predetermined air volume value.

[0049] The above process outputs the basic fresh air volume after boundary constraints and rate of change constraints in each control cycle, providing input for subsequent fresh air volume correction calculation and target fresh air volume synthesis.

[0050] In some embodiments of this application, when determining the corrected fresh air volume based on the conditional room rate and the category of changes in the number of people, the following methods are included: Read the category of personnel quantity change and read the correction mode parameter set, which includes the correction coefficient for entering the room, the correction coefficient for leaving the room, and the correction coefficient for no change. When the category of personnel quantity change is entering the room, select the correction coefficient for entering the room; when the category of personnel quantity change is leaving the room, select the correction coefficient for leaving the room; when the category of personnel quantity change is no change, select the correction coefficient for no change. The probability weight value is determined based on the conditional occupancy rate, and the corrected fresh air volume is obtained by multiplying the probability weight value by the correction coefficient. The corrected fresh air volume is subject to a limiting constraint, which includes ensuring that the corrected fresh air volume does not exceed a predetermined percentage of the basic fresh air volume, and the corrected fresh air volume is determined accordingly.

[0051] Specifically, the category of personnel quantity change is determined by the difference between the number of indoor personnel in the current control cycle and the number of indoor personnel in the previous control cycle. A difference greater than zero corresponds to an entry change, a difference less than zero corresponds to an exit change, and a difference equal to zero corresponds to no change. After the start of the control cycle, the category of personnel quantity change is read, and the set of correction mode parameters is read from the control strategy parameter table. The set of correction mode parameters is configured with entry correction coefficient, exit correction coefficient, and no change correction coefficient according to the category of personnel quantity change. The entry correction coefficient, exit correction coefficient, and no change correction coefficient are numerical parameters and are written during the system initialization phase. The entry correction coefficient is used for correction calculation in the case of entry change, the exit correction coefficient is used for correction calculation in the case of exit change, and the no change correction coefficient is used for correction calculation in the case of no change. After reading the category of personnel quantity change, the entry correction coefficient is selected for entry change, the exit correction coefficient is selected for exit change, and the no change correction coefficient is selected for no change.

[0052] The conditional in-room rate is the probability value output by the in-room rate prediction model, and its value ranges from zero to one. The probability weight value is determined by the conditional in-room rate, and it is a weight parameter obtained by segmenting the conditional in-room rate. The segment boundaries of the segmentation mapping are determined by the distribution of the conditional in-room rate in the historical data of in-room status over time. The segmentation method is to divide the data into several probability intervals according to the number of samples and assign a weight value to each probability interval. Different probability weight values ​​correspond to different probability intervals for the conditional in-room rate, and a larger probability weight value corresponds to a conditional in-room rate falling into a larger probability interval. The configuration of the probability weight values ​​is written into the weight parameter table and read during the runtime phase. For example, the conditional ventricular rate values ​​obtained from historical ventricular condition time data are sorted by sample size and divided into four probability intervals. The boundaries of the four probability intervals correspond to the 25th, 50th, and 75th percentile values, respectively. Probability interval 1 is from 0 to 25th percentile, probability interval 2 is from 25th to 50th percentile, probability interval 3 is from 50th to 75th percentile, and probability interval 4 is from 75th percentile to 1. Probability weight values ​​are assigned to the four probability intervals: 0.25 for probability interval 1, 0.5 for probability interval 2, 0.75 for probability interval 3, and 1 for probability interval 4. When the conditional ventricular rate falls into probability interval 3, the probability weight value is 0.75; when the conditional ventricular rate falls into probability interval 4, the probability weight value is 1.

[0053] After determining the probability weight value, the probability weight value is multiplied by the selected correction coefficient to obtain the corrected fresh air volume. When the inflow changes, the probability weight value is multiplied by the inflow correction coefficient to obtain the corrected fresh air volume; when the outflow changes, the probability weight value is multiplied by the outflow correction coefficient to obtain the corrected fresh air volume; when it does not change, the probability weight value is multiplied by the unchanged correction coefficient to obtain the corrected fresh air volume. The sign of the corrected fresh air volume is determined by the sign of the correction coefficient. A positive value for the inflow correction coefficient results in a positive corrected fresh air volume, a negative value for the outflow correction coefficient results in a negative corrected fresh air volume, and a zero value for the unchanged correction coefficient results in a zero corrected fresh air volume. The sign of the correction coefficient is configured in the control strategy parameter table. After the corrected fresh air volume is obtained, a limiting constraint is applied. The limiting constraint is achieved by comparing the absolute value of the corrected fresh air volume with the limiting value obtained by multiplying the basic fresh air volume by a predetermined ratio. The predetermined ratio is configured in the control strategy parameter table, for example, the predetermined ratio is set to 30%. When the absolute value of the corrected fresh air volume exceeds the limiting value, the corrected fresh air volume is adjusted to the positive or negative value corresponding to the limiting value. When the absolute value of the corrected fresh air volume does not exceed the limiting value, the corrected fresh air volume remains unchanged, thus obtaining the limited corrected fresh air volume, which is used as the input for synthesizing the target fresh air volume.

[0054] In some embodiments of this application, when combining the basic fresh air volume and the modified fresh air volume to form the target fresh air volume, the following methods are included: Calculate the combined value of the base fresh air volume and the corrected fresh air volume; Compare the composite value with the minimum fresh air volume and take the value that is greater than or equal to the minimum fresh air volume; compare the composite value with the maximum fresh air volume and take the value that is less than or equal to the maximum fresh air volume. When the change in the number of people is classified as an entry change, the first upward limit rule is used to limit the target fresh air volume; when the change in the number of people is classified as an exit change, the first downward limit rule is used to limit the target fresh air volume; when the change in the number of people is classified as no change, the second limit rule is used to limit the target fresh air volume. The first upward limit rule, the first downward limit rule, and the second limit rule respectively limit the maximum increase, maximum decrease, and maximum change of the target fresh air volume in adjacent control cycles, thereby determining the target fresh air volume.

[0055] Specifically, the basic fresh air volume is the basic ventilation volume obtained based on the number of people in the room and environmental parameters. The corrected fresh air volume is the correction amount obtained based on the conditional occupancy rate and the category of personnel number changes. Within the control cycle, the basic fresh air volume is first calculated and the corrected fresh air volume is added to obtain the composite value. After the composite value is calculated, air volume boundary processing is performed. The boundary processing uses the minimum and maximum fresh air volumes configured in the equipment parameter table. The minimum fresh air volume is the fresh air volume corresponding to the lowest stable operating speed of the fan or the fresh air volume corresponding to the minimum controllable opening of the fresh air valve. The maximum fresh air volume is the fresh air volume corresponding to the rated speed of the fan or the fresh air volume corresponding to the maximum opening of the fresh air valve. The boundary processing process is to compare the composite value with the minimum fresh air volume and take the larger value, and then compare it with the maximum fresh air volume and take the smaller value, thus obtaining the air volume value after boundary processing.

[0056] After boundary processing, the air volume value enters the limiting rule processing. The limiting rule processing takes the change in target fresh air volume in adjacent control cycles as the constraint object. The target fresh air volume of the previous control cycle is read from the historical data of the indoor status time and associated with the timestamp of the previous control cycle. The change in target fresh air volume is obtained by subtracting the target fresh air volume of the previous control cycle from the air volume value after boundary processing. When the change in the number of people is a change in entering the room, the first upward limiting rule is used; when the change in the number of people is a change in leaving the room, the first downward limiting rule is used; and when the change in the number of people is no change, the second limiting rule is used. The content of the three types of limiting rules is to set different upward limiting values, downward limiting values, and change limiting values ​​for the change in target fresh air volume, and to perform truncation processing according to the positive sign and absolute value of the change in target fresh air volume.

[0057] The maximum rise amount of the first rise limit rule is used to limit the rise rate of the target fresh air volume under the condition of changes in the incoming air volume. The maximum rise amount is determined during the system initialization phase and written into the control strategy parameter table. The determination of the maximum rise amount is based on one or more of the following: fan speed rise slope limit, fan noise limit, and valve opening change limit. The fan speed rise slope limit is determined by the allowable change in speed per unit time of the fan driver. The valve opening change limit is determined by the allowable change in opening per unit time of the valve actuator. The fan noise limit is determined by the correspondence between the noise level set by the user and the fan speed range. The maximum rise amount is obtained by converting the slope limit or opening limit into the allowable increase in fresh air volume within the control cycle. For example, if the fan driver is allowed to increase its speed by no more than a predetermined speed value per minute, and the control cycle is set to a predetermined duration, the maximum rise amount is the allowable increase in fresh air volume within the predetermined duration.

[0058] The maximum decrease in the first descent limit rule is used to limit the rate at which the target fresh air volume decreases under the condition of changes in the room. The maximum decrease is determined during the system initialization phase and written into the control strategy parameter table. The determination of the maximum decrease is based on one or more of the minimum fan hold-up time limit and the air quality maintenance strategy limit: the minimum fan hold-up time limit is determined by the fan frequent start-stop protection requirements, and the air quality maintenance strategy limit is determined by the correspondence between the indoor carbon dioxide concentration drop time and the control cycle; the maximum decrease is obtained by converting the minimum hold-up time limit or the drop-down time limit into the allowable reduction of fresh air volume within the control cycle. For example, if the minimum hold-up time limit requires the air volume to drop from a high level to a low level to cover multiple control cycles, then the maximum decrease is obtained by dividing the difference between the high-level air volume and the low-level air volume by the number of multiple control cycles. The maximum change amount of the second limiting rule is used to limit the fluctuation range of the target fresh air volume when the personnel number change category is unchanged. The maximum change amount is determined during the system initialization phase and written into the control strategy parameter table. The determination of the maximum change amount is based on one or more of the following: sensor noise amplitude, natural fluctuation amplitude of environmental parameters, and equipment adjustment stability requirements. The sensor noise amplitude is obtained by statistically analyzing the short-time variance or historical fluctuation range of the environmental parameter periodic values. The natural fluctuation amplitude of environmental parameters is obtained by statistically analyzing historical data during periods without personnel changes. The equipment adjustment stability requirements are determined by limiting the frequent changes in fan speed. The maximum change amount is obtained by directly configuring the allowable air volume fluctuation range. For example, the maximum change amount is set to ensure that the target fresh air volume change does not exceed the predetermined air volume value in each control cycle.

[0059] The limit rule execution process is as follows: In the case of changes in the inbound air volume, when the change in the target fresh air volume is greater than the maximum increase, the target fresh air volume of the current control cycle is adjusted to the target fresh air volume of the previous control cycle plus the maximum increase; in the case of changes in the outbound air volume, when the change in the target fresh air volume is less than the opposite of the maximum decrease, the target fresh air volume of the current control cycle is adjusted to the target fresh air volume of the previous control cycle minus the maximum decrease; in the case of no change, when the absolute value of the change in the target fresh air volume is greater than the maximum change, the target fresh air volume of the current control cycle is adjusted to the target fresh air volume of the previous control cycle plus or minus the maximum change; when the corresponding conditions are not met, the air volume value after boundary processing remains unchanged.

[0060] After completing the amplitude limiting rule processing, the target fresh air volume for the current control cycle is obtained, and the target fresh air volume for the current control cycle is used as the input parameter for generating the execution parameter set. At the same time, the maximum rise, maximum fall, and maximum change are saved in the system as configurable parameters in the control strategy parameter table.

[0061] In some embodiments of this application, generating the set of execution parameters based on the target fresh air volume includes: Obtain the fan operating characteristic table, which records the correspondence between fresh air volume and fan speed, and the correspondence between fresh air valve opening and fresh air volume; Based on the target fresh air volume, the matching range is found in the fan operating characteristic table to obtain the fan speed setting value and the fresh air valve opening setting value; At least one of the fan speed setpoint and the fresh air valve opening setpoint is selected as the set of execution parameters, and the set of execution parameters is constrained. The constraint process includes speed limit, valve opening limit, and adjacent control cycle change rate limit. If the set of execution parameters does not meet the speed limit or valve opening limit, the set of execution parameters is adjusted to the corresponding limit boundary value. The set of execution parameters is output to the fan or fresh air valve to form control commands.

[0062] Specifically, the fan operating characteristic table is generated and written into the equipment parameter table during the equipment installation and commissioning phase. The fan operating characteristic table obtains the correspondence between fresh air volume and fan speed by calibrating the actual fresh air volume of the fan under different speed setting values, and obtains the correspondence between fresh air valve opening and fresh air volume by calibrating the actual fresh air volume of the fresh air valve under different opening setting values. The fan operating characteristic table is stored in a segmented form, and the segment boundaries are determined by the fresh air volume values ​​of the calibration points. Each segment records the fan speed setting value range and the fresh air valve opening setting value range under the fresh air volume range. The fan speed setting value range and the fresh air valve opening setting value range are calculated from adjacent calibration points by linear interpolation or segmented constant value method.

[0063] After obtaining the target fresh air volume, compare the target fresh air volume with the segment boundaries of the fan operating characteristic table to locate the fresh air volume range into which the target fresh air volume falls, and read the fan speed setting value and fresh air valve opening setting value corresponding to the fresh air volume range; when the target fresh air volume falls between two calibration points, perform interpolation on the fan speed setting value corresponding to the two calibration points to obtain the fan speed setting value, and perform interpolation on the fresh air valve opening setting value corresponding to the two calibration points to obtain the fresh air valve opening setting value.

[0064] In this embodiment, the execution parameter set includes the fan speed setpoint and the fresh air valve opening setpoint. After the execution parameter set is generated, constraint processing is performed. The constraint processing uses the minimum fan speed, maximum fan speed, minimum fresh air valve opening, and maximum fresh air valve opening from the equipment parameter table to apply speed limiting to the fan speed setpoint and valve opening limiting to the fresh air valve opening setpoint. The constraint processing also uses the fan speed setpoint and the fresh air valve opening setpoint from the previous control cycle to calculate the speed change and opening change in adjacent control cycles, respectively, and compares them with the change rate limit parameter. When the speed change exceeds the speed change rate limit, the fan speed setpoint is adjusted to the change rate limit boundary; when the opening change exceeds the opening change rate limit, the fresh air valve opening setpoint is adjusted to the change rate limit boundary. The change rate limit parameter is configured in the control strategy parameter table. For example, the speed change rate limit is set to ensure that the speed change does not exceed a predetermined speed value in each control cycle, and the opening change rate limit is set to ensure that the opening change does not exceed a predetermined opening value in each control cycle. After the amplitude and rate of change constraints are completed, the fan speed setpoint is converted into a speed control quantity that the fan driver can recognize, and the fresh air valve opening setpoint is converted into an opening control quantity that the valve actuator can recognize. The fan driver control quantity and the fresh air valve actuator control quantity are output as control commands to the fan and the fresh air valve. After the control commands are output, the acquisition and calculation process of the next control cycle begins.

[0065] In some embodiments of this application, storing the collected data of the target control cycle, the current room condition change conditions, the conditional occupancy rate, the target fresh air volume, and the set of execution parameters into the occupancy time history data includes: Time alignment is performed on the collected data for the target control cycle. Time alignment includes mapping the number of people indoors, environmental parameters, and changes in environmental parameters to the same control cycle timestamp. The current room status changes, conditional occupancy rate, target fresh air volume, and set of execution parameters are associated with the control cycle timestamp and stored to form a control cycle record. The control cycle records are subjected to integrity verification, which includes field missing verification and value range verification. If the integrity verification passes, the in-room status time history data is written. If the integrity verification fails, the control cycle record is deleted and replaced with the previous control cycle record. Capacity management is performed on historical data of in-room conditions. Capacity management includes deleting the earliest record according to the time window or downsampling historical records according to the sampling interval.

[0066] Specifically, the data collected during the target control cycle is aggregated into a single record to be written at the end of the control cycle. This data includes the number of people indoors, carbon dioxide concentration, temperature, humidity, fine particulate matter concentration, changes in carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration. Time alignment is performed at the end of the control cycle, using the control cycle timestamp as a unified time reference. The control cycle timestamp is either the start or end time of the control cycle and is fixed during system initialization. The number of people indoors is taken from the last person count within the control cycle or the median of the person counts within the control cycle. Carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration are taken from the calculated periodic values ​​of environmental parameters within the control cycle. Changes in carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration are taken from the difference between the current control cycle's environmental parameter periodic value and the previous control cycle's environmental parameter periodic value. All of the above collected data is mapped to the control cycle timestamp to form time-aligned collected data.

[0067] The associated storage is executed after time alignment. It uses the control cycle timestamp as the primary key field and writes the current room status change conditions, conditional occupancy rate, target fresh air volume, and execution parameter set fields into the same control cycle record. The current room status change conditions are stored as an interval identifier sequence or coded string, the conditional occupancy rate is stored as a probability value, the target fresh air volume is stored as the air volume setpoint, and the execution parameter set is stored as the fan speed setpoint and the fresh air valve opening setpoint. Integrity verification is performed before the control cycle record is written. Field missing verification checks whether the control cycle record contains the control cycle timestamp, number of people in the room, carbon dioxide concentration, temperature, humidity, fine particulate matter concentration, carbon dioxide concentration change, temperature change, humidity change, fine particulate matter concentration change, current room status change conditions, conditional occupancy rate, target fresh air volume, and execution parameter set. If any field is missing, the verification fails. Numerical range verification checks whether the number of people in the room is a non-negative integer, the carbon dioxide concentration is a non-negative number, the temperature is within the predetermined temperature range, the humidity is between zero and one hundred, the fine particulate matter concentration is non-negative, and the conditional occupancy rate is within the predetermined temperature range. If the room rate is between zero and one, the target fresh air volume is between the minimum and maximum fresh air volume, the fan speed setting is between the minimum and maximum fan speed, and the fresh air valve opening setting is between the minimum and maximum fresh air valve opening, any deviation from these ranges will result in a failed verification. If the integrity verification passes, the control cycle record will be appended to the in-room status time history data and the index will be updated synchronously. If the integrity verification fails, the control cycle record will be deleted, and the previous control cycle record will be read. The previous control cycle record will be copied as a replacement record, and the control cycle timestamp of the replacement record will be updated to the target control cycle timestamp before being written to the in-room status time history data.

[0068] Capacity management is executed after the write operation is complete. When capacity management uses a time window deletion method, the time window is a preset duration. The system iterates through the control cycle timestamps in the historical data of in-room status time, deleting the earliest record whose control cycle timestamp is earlier than the start of the time window until all records are within the time window. When capacity management uses a downsampling method, the downsampling interval is a preset interval. The system filters historical records according to the control cycle timestamp, retaining records that meet the control cycle timestamp interval of the preset interval and deleting the rest, thereby controlling the number of records in the historical data of in-room status time. The above process of time alignment, associated storage, integrity verification, and capacity management ensures that each control cycle forms a structurally consistent control cycle record and guarantees the availability and maintainability of the historical data of in-room status time.

[0069] In another preferred embodiment based on the above embodiments, see [reference] Figure 2 As shown, this embodiment provides a control system for automatically adjusting the fresh air volume in a room, including: The historical data acquisition module is configured to acquire and store historical data on the room's in-room status over time; and to extract a set of conditions for changes in room status based on the environmental parameters and changes in those parameters in the historical data. In the occupancy rate statistical modeling module, it is configured to count the total number of samples that meet the room condition change conditions according to the set of room condition change conditions, and count the number of samples that are occupied. The conditional occupancy rate is calculated based on the number of occupied samples and the total number of samples. An occupancy rate prediction model is established based on the room condition change conditions and the conditional occupancy rate. The control cycle acquisition module is configured to acquire the number of people in the room and environmental parameters in each control cycle, and calculate the change in environmental parameters relative to the previous control cycle. The personnel change determination module is configured to calculate the difference between the number of indoor personnel in the current control cycle and the number of indoor personnel in the previous control cycle to obtain the personnel number difference value, and determine the personnel number change category based on the personnel number difference value; In the room rate inference output module, it is configured to determine the current room condition change conditions based on the environmental parameters and the change of environmental parameters in the current control cycle, and input the current room condition change conditions into the room rate prediction model to obtain the conditional room rate of the target control cycle. The target air volume generation module is configured to determine the basic fresh air volume based on the number of people in the room and environmental parameters, determine the corrected fresh air volume based on the conditional occupancy rate and the category of changes in the number of people, and combine the basic fresh air volume and the corrected fresh air volume into the target fresh air volume. The execution parameter storage module is configured to generate an execution parameter set based on the target fresh air volume, output control commands to the fan according to the execution parameter set, and store the collected data of the target control cycle, the current room condition change conditions, the conditional occupancy rate, the target fresh air volume, and the execution parameter set into the occupancy time history data.

[0070] Understandably, modular division enables structured processing of the room fresh air volume control process: the historical data acquisition module writes the room presence status, number of people in the room, environmental parameters, and changes in environmental parameters within the control cycle into the historical data of room presence status in chronological order, and forms a set of room presence change conditions based on the historical data, providing a unified condition space for subsequent statistical modeling; the room presence rate statistical modeling module counts samples from historical samples based on the set of room presence change conditions and calculates the conditional room presence rate, establishing a mapping relationship from room presence change conditions to the conditional room presence rate, enabling the room presence rate prediction model to output the corresponding conditional room presence rate within the control cycle; the control cycle acquisition module collects data on the number of people in the room, carbon dioxide concentration, temperature, humidity, and fine particulate matter concentration within a fixed control cycle and forms periodic values ​​of environmental parameters, while calculating the changes in environmental parameters between adjacent control cycles, ensuring periodic consistency of environmental parameter input; the number of people change judgment module calculates the difference in the number of people in the room between adjacent control cycles and determines the category of number of people change, enabling subsequent control calculations to... The system distinguishes between three scenarios: changes in room entry, changes in room exit, and no change. The room presence rate inference output module determines the current room status change conditions based on the environmental parameters and changes in these parameters during the current control cycle. It then obtains the conditional room presence rate for the target control cycle through the room presence rate prediction model, ensuring the availability of room presence rate information within the control cycle. The target air volume generation module calculates and synthesizes the basic fresh air volume and the corrected fresh air volume separately. The basic fresh air volume is determined by the number of people in the room and environmental parameters, while the corrected fresh air volume is determined by the conditional room presence rate and the category of personnel number changes, thus clarifying the composition of the target fresh air volume. The execution parameter storage module converts the target fresh air volume into a set of executable parameters, such as the fan speed setpoint and the fresh air valve opening setpoint, and outputs control commands. Simultaneously, it writes back the collected data for the target control cycle, the current room status change conditions, the conditional room presence rate, the target fresh air volume, and the execution parameter set to the historical data of the room presence time, forming a continuously accumulated control cycle record. This supports statistical updates and parameter maintenance for subsequent control cycles, and maintains the availability and consistency of historical data through capacity management and integrity verification.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for automatically adjusting the fresh air volume in a room, characterized in that, include: Acquire and store historical data on the room's in-room status over time; based on the environmental parameters and changes in these parameters in the historical data, extract a set of conditions for changes in the room's status. Based on each room condition change condition in the set of room condition change conditions, the total number of samples that meet the room condition change conditions is counted, and the number of samples that are occupied is counted. The conditional occupancy rate is calculated based on the number of occupied samples and the total number of samples. An occupancy rate prediction model is established based on the room condition change conditions and the conditional occupancy rate. The number of people in the room and environmental parameters are collected in each control cycle, and the change of the environmental parameters relative to the environmental parameters in the previous control cycle is calculated. The difference between the number of people indoors in the current control cycle and the number of people indoors in the previous control cycle is calculated to obtain the personnel number difference value. The personnel number change category is determined based on the personnel number difference value. Based on the environmental parameters and changes in environmental parameters during the current control cycle, the current room condition change conditions are determined. These current room condition change conditions are then input into the occupancy rate prediction model to obtain the conditional occupancy rate for the target control cycle. The basic fresh air volume is determined based on the number of people in the room and the environmental parameters. The corrected fresh air volume is determined based on the conditional occupancy rate and the category of changes in the number of people. The basic fresh air volume and the corrected fresh air volume are then combined to form the target fresh air volume. An execution parameter set is generated based on the target fresh air volume. Control commands are output to the fan according to the execution parameter set. The collected data of the target control cycle, the current room status change conditions, the conditional occupancy rate, the target fresh air volume, and the execution parameter set are stored in the occupancy status time history data.

2. The method for automatically adjusting room fresh air volume control according to claim 1, characterized in that, When extracting the set of room condition change conditions based on the environmental parameters and changes in environmental parameters in the historical data of room conditions over time, the following are included: The historical values ​​of each environmental parameter in the indoor condition time history data are sorted, and the historical values ​​are divided into at least two value intervals according to the number of samples to obtain the value interval boundary of the corresponding environmental parameter; the changes of the environmental parameters are sorted, and the changes of the environmental parameters are divided into at least two change intervals according to the number of samples to obtain the change interval boundary of the corresponding environmental parameter. For each time sample in the historical data of room conditions, the value range identifier of the time sample is determined according to the value range boundary of the corresponding environmental parameter, and the change range identifier of the time sample is determined according to the change range boundary of the corresponding environmental parameter. The value range identifier and change range identifier of each environmental parameter are combined to form the room condition change conditions. The room condition change conditions are deduplicated, and the number of times each room condition change condition appears in the in-room time history data after deduplication is counted. When the number of times any room condition change condition appears is less than a first number, the value range or change range corresponding to at least one environmental parameter in the room condition change condition is merged with the adjacent range, and a new room condition change condition is formed. The counting and merging are repeated to obtain a set of room condition change conditions.

3. The method for automatically adjusting room fresh air volume control according to claim 2, characterized in that, When collecting the number of people in the room and environmental parameters in each control cycle, and calculating the change in environmental parameters relative to the previous control cycle, the following steps are included: Within the control period, multiple sampled values ​​of the same environmental parameter are acquired at a first sampling interval; the multiple sampled values ​​are sorted, and several sampled values ​​at the smallest and largest ends of the sorted values ​​are removed. The average value of the remaining sampled values ​​is determined as the periodic value of the environmental parameter for the control period. When the change in the number of people is classified as either a change in entering or leaving the room, the first sampling interval is adjusted to the second sampling interval, and the multiple sampling values ​​are reacquired and the periodic values ​​of the environmental parameters are redefined within the control cycle. The change in environmental parameters is obtained by subtracting the periodic value of the environmental parameters in the current control cycle from the periodic value of the environmental parameters in the previous control cycle. The control cycle duration is fixed, and the adjustment of the first sampling interval and the second sampling interval does not change the control cycle duration.

4. The method for automatically adjusting room fresh air volume control according to claim 3, characterized in that, When establishing an occupancy rate prediction model based on changes in room conditions and additional conditions, the following should be included: Establish a room condition change condition index table. Each record in the room condition change condition index table contains a room condition change condition, the total number of samples corresponding to the room condition change condition, the number of occupied samples corresponding to the room condition change condition, and the conditional occupancy rate calculated from the number of occupied samples and the total number of samples. Within each control cycle, the current room status change conditions are matched with the room status change condition index table. When a match is successful, the conditional occupancy rate corresponding to the matched record is read. If a match fails, the current room status change conditions are reconstructed according to a preset priority order and then matched again. The preset priority order includes deleting the environmental parameter change range identifier first, then deleting the environmental parameter value range identifier, and merging adjacent environmental parameter value ranges or adjacent environmental parameter change ranges after deletion. Each reconstruction is followed by a match until a match is successful or the maximum number of reconstructions is reached. If a match is still not found after reaching the maximum number of reconstruction attempts, read the conditional occupancy rate corresponding to the record that appears most frequently in the room condition change condition index table.

5. The method for automatically adjusting room fresh air volume control according to claim 4, characterized in that, When determining the basic fresh air volume based on the number of people indoors and environmental parameters, the following should be included: Obtain basic room parameters, which are derived from user input parameter tables or building information parameter tables. These parameters include room area, room volume, and room purpose. Determine the fresh air volume per person based on the basic room parameters. Multiply the number of people in the room by the fresh air volume per person to obtain the required fresh air volume per person. For each environmental parameter, read the target value of the environmental parameter; calculate the deviation between the environmental parameter and the target value of the environmental parameter; determine the fresh air volume increment value corresponding to the environmental parameter based on the area where the deviation falls in the multi-segment mapping table. The multi-segment mapping table is a monotonically non-decreasing mapping relationship between the fresh air volume increment value and the deviation value. The incremental values ​​of fresh air volume corresponding to environmental parameters are combined to obtain the environmental fresh air volume demand value. The basic fresh air volume is obtained by combining the fresh air volume requirements of the number of people and the fresh air volume requirements of the environment. Boundary constraints are imposed on the basic fresh air volume, which include being greater than or equal to the minimum fresh air volume and less than or equal to the maximum fresh air volume; the rate of change constraint is imposed on the basic fresh air volume, which includes the change in the basic fresh air volume between adjacent control cycles not exceeding the limit value.

6. The method for automatically adjusting room fresh air volume control according to claim 5, characterized in that, When determining the corrected fresh air volume based on the conditional occupancy rate and the category of personnel number changes, the following are included: Read the category of personnel quantity change and read the correction mode parameter set, which includes the correction coefficient for entering the room, the correction coefficient for leaving the room, and the correction coefficient for no change. When the category of personnel quantity change is entering the room, select the correction coefficient for entering the room; when the category of personnel quantity change is leaving the room, select the correction coefficient for leaving the room; when the category of personnel quantity change is no change, select the correction coefficient for no change. The probability weight value is determined based on the conditional occupancy rate, and the corrected fresh air volume is obtained by multiplying the probability weight value by the correction coefficient. The corrected fresh air volume is subject to a limiting constraint, which includes ensuring that the corrected fresh air volume does not exceed a predetermined percentage of the basic fresh air volume, and the corrected fresh air volume is determined accordingly.

7. The method for automatically adjusting room fresh air volume control according to claim 6, characterized in that, When combining the base fresh air volume and the corrected fresh air volume to form the target fresh air volume, the following are included: Calculate the combined value of the base fresh air volume and the corrected fresh air volume; Compare the composite value with the minimum fresh air volume and take the value that is greater than or equal to the minimum fresh air volume; compare the composite value with the maximum fresh air volume and take the value that is less than or equal to the maximum fresh air volume. When the change in the number of people is classified as an entry change, the first upward limit rule is used to limit the target fresh air volume; when the change in the number of people is classified as an exit change, the first downward limit rule is used to limit the target fresh air volume; when the change in the number of people is classified as no change, the second limit rule is used to limit the target fresh air volume. The first upward limit rule, the first downward limit rule, and the second limit rule respectively limit the maximum increase, maximum decrease, and maximum change of the target fresh air volume in adjacent control cycles, thereby determining the target fresh air volume.

8. The method for automatically adjusting room fresh air volume control according to claim 7, characterized in that, When generating the set of execution parameters based on the target fresh air volume, it includes: Obtain the fan operating characteristic table, which records the correspondence between fresh air volume and fan speed, and the correspondence between fresh air valve opening and fresh air volume; Based on the target fresh air volume, the matching range is found in the fan operating characteristic table to obtain the fan speed setting value and the fresh air valve opening setting value; At least one of the fan speed setpoint and the fresh air valve opening setpoint is selected as the set of execution parameters, and the set of execution parameters is constrained. The constraint process includes speed limit, valve opening limit, and adjacent control cycle change rate limit. If the set of execution parameters does not meet the speed limit or valve opening limit, the set of execution parameters is adjusted to the corresponding limit boundary value. The set of execution parameters is output to the fan or fresh air valve to form control commands.

9. The method for automatically adjusting room fresh air volume control according to claim 8, characterized in that, When storing the data collected during the target control cycle, current room condition changes, conditional occupancy rate, target fresh air volume, and set of execution parameters into the historical data of occupancy time, this includes: Time alignment is performed on the collected data for the target control cycle. Time alignment includes mapping the number of people indoors, environmental parameters, and changes in environmental parameters to the same control cycle timestamp. The current room status change conditions, conditional occupancy rate, target fresh air volume, and set of execution parameters are associated with the control cycle timestamp and stored to form a control cycle record. The control cycle records are subjected to integrity verification, which includes field missing verification and value range verification. If the integrity verification passes, the in-room status time history data is written. If the integrity verification fails, the control cycle record is deleted and replaced with the previous control cycle record. Capacity management is performed on historical data of in-room conditions. Capacity management includes deleting the earliest record according to the time window or downsampling the historical records according to the sampling interval.

10. An automatically adjustable room fresh air volume control system, used to implement the automatically adjustable room fresh air volume control method as described in any one of claims 1-9, characterized in that, include: The historical data acquisition module is configured to acquire and store historical data on the room's in-room status over time; and to extract a set of room status change conditions based on the environmental parameters and changes in those environmental parameters in the historical data on the room's in-room status over time. In the occupancy rate statistical modeling module, it is configured to count the total number of samples that meet the room condition change conditions according to each room condition change condition in the set of room condition change conditions, and count the number of samples that are occupied. The conditional occupancy rate is calculated based on the number of occupied samples and the total number of samples. An occupancy rate prediction model is established based on the room condition change conditions and the conditional occupancy rate. The control cycle acquisition module is configured to acquire the number of people in the room and environmental parameters in each control cycle, and calculate the change of the environmental parameters relative to the environmental parameters in the previous control cycle. The personnel change determination module is configured to calculate the difference between the number of indoor personnel in the current control cycle and the number of indoor personnel in the previous control cycle to obtain the personnel number difference value, and determine the personnel number change category based on the personnel number difference value; In the room rate inference output module, it is configured to determine the current room condition change conditions based on the environmental parameters and the change of environmental parameters in the current control cycle, and input the current room condition change conditions into the room rate prediction model to obtain the conditional room rate for the target control cycle. The target air volume generation module is configured to determine a basic fresh air volume based on the number of people in the room and the environmental parameters, determine a corrected fresh air volume based on the conditional occupancy rate and the category of changes in the number of people, and combine the basic fresh air volume and the corrected fresh air volume into a target fresh air volume. The execution parameter storage module is configured to generate an execution parameter set based on the target fresh air volume, output control commands to the fan according to the execution parameter set, and store the collected data of the target control cycle, the current room status change conditions, the conditional occupancy rate, the target fresh air volume, and the execution parameter set into the occupancy status time history data.

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