A subway-based air conditioning air supply control method

Abstract

The present application belongs to the technical field of subway air conditioning air supply, and particularly relates to a subway-based air conditioning air supply control method. The present application effectively solves the local overcooling or overheating problem existing in the traditional subway air conditioning air supply system by accurately sensing and dynamically adjusting the thermal comfort of passengers in different areas of the car, realizes individualized and intelligent air supply control by real-time data collection through multi-source sensing devices and combining historical preference information and real-time environmental parameters, significantly improves the riding comfort of passengers, and simultaneously, the present application adopts the combination of partition control and feedback regulation, not only optimizes the energy utilization efficiency, but also reduces the experience decline problem caused by regulation lag, in addition, the introduction of the compensation regulation mechanism further enhances the stability and adaptability of the air supply result, can quickly respond and adjust to the best state under complex environment, and effectively improves the riding comfort of passengers.

Description

Technical Field

[0001] This invention belongs to the field of subway air supply regulation technology, specifically relating to a subway-based air conditioning air supply control method. Background Technology

[0002] As a common mode of transportation for daily travel, the comfort of the subway car environment directly affects the travel experience of passengers. Especially in hot or cold weather, the air supply effect of the air conditioning system becomes a key factor affecting thermal comfort. Therefore, air supply control for subway cars is essential. With the development of information technology, subway air conditioning systems are gradually evolving from fixed modes to intelligent and personalized adjustments. Before being put into use, the control strategy often needs to be simulated and tested in the field to ensure the stability and adaptability of the system under different passenger flow densities, seasonal temperature differences, and operating periods. Digital twin technology provides corresponding technical support for this. By constructing a digital twin car model to simulate various subway load conditions, sufficient simulation verification can be carried out before the optimized subway air supply strategy is officially put into application.

[0003] Existing subway car air conditioning control technologies largely rely on global temperature feedback or fixed-period adjustment strategies, lacking responsiveness to differences in passenger spatial distribution and individual thermal comfort needs. This can easily lead to localized overcooling or overheating, resulting in energy waste and a decline in the passenger experience. Furthermore, the lack of integration of historical preference data and real-time sensing information for collaborative optimization results in significant control lag, making it difficult to achieve personalized and dynamic air supply control. Consequently, passenger thermal comfort experiences vary considerably, especially during peak hours in densely populated areas. Therefore, this invention provides a simulation-based subway air conditioning control method to address the aforementioned problems. Summary of the Invention

[0004] The purpose of this invention is to provide a subway-based air conditioning control method that can perceive and dynamically adjust the thermal comfort of passengers in different areas of the carriage, thereby improving passenger comfort.

[0005] The specific technical solution adopted by this invention is as follows:

[0006] A method for controlling air supply to an air conditioner in a subway system, comprising:

[0007] The passenger distribution data and temperature field data in the carriage are collected in real time by pre-deployed multi-source sensing devices, and the distribution location of the air supply grilles in the carriage is obtained and synchronously mapped to the three-dimensional simulation model. Then, the air supply control zone is divided according to the coverage area of ​​each air supply grille.

[0008] Based on the fusion analysis of passenger distribution and temperature field data, the thermal comfort index of each air supply control zone is calculated, and the wind speed of the corresponding air supply grille is dynamically adjusted according to the thermal comfort index of each zone.

[0009] The control feedback period is constructed based on the wind speed adjustment node of the air supply grille, and the response effect of air supply adjustment is evaluated based on the thermal comfort index within the control feedback period.

[0010] Obtain the preferred thermal comfort temperature under similar historical conditions, as well as the corresponding air supply parameters, and integrate the preferred thermal comfort temperature and air supply parameters into benchmark reference data;

[0011] The baseline reference data is compared with the current thermal comfort index, a deviation adjustment signal is output, and the wind speed of the air supply grille is adjusted to compensate for the deviation adjustment signal to determine the final target wind speed.

[0012] In a preferred embodiment, the step of obtaining the distribution location of the air supply grilles inside the vehicle compartment and dividing the air supply control zones according to the coverage area of ​​each air supply grille includes:

[0013] Based on the installation position and air delivery angle of the air supply grilles, the effective range of each air supply grille is determined. The effective range is positively correlated with the wind speed and negatively correlated with the temperature difference between the inside and outside of the vehicle.

[0014] Identify the effective range of overlapping areas and mark the relative position of the overlapping areas from each air supply grille;

[0015] The air supply grille with the closest relative position in the intersection area is selected as the main control unit, and the air supply grille with the second closest position is selected as the auxiliary adjustment unit;

[0016] The areas covered by the effective range of the main control unit and the auxiliary adjustment unit are divided into independent air supply control zones.

[0017] The effective range of non-overlapping areas is directly divided into independent air supply control zones.

[0018] In a preferred embodiment, the step of calculating the thermal comfort index of each air supply control zone based on the fusion analysis of passenger distribution and temperature field data includes:

[0019] The system collects passenger positions in the carriage in real time, divides temperature sampling areas based on passenger positions, and collects temperature field data within the temperature sampling areas in real time.

[0020] The density of people in each temperature sampling area is determined based on the distribution of passenger locations, and the average perceived temperature of each temperature sampling area is determined by combining the temperature field data.

[0021] The current ambient temperature is obtained, and the heat exchange rate is determined based on the difference between the ambient temperature and the average perceived temperature. The thermal comfort index of each temperature sampling area is calculated by combining the heat exchange rate with the personnel density.

[0022] Among them, the thermal comfort index is negatively correlated with the heat exchange rate and positively correlated with the population density.

[0023] In a preferred embodiment, the step of dynamically adjusting the airflow speed of the corresponding air supply grille according to the thermal comfort index of each zone includes:

[0024] Obtain the thermal comfort index and comfort threshold for each air supply control zone, and calculate the deviation between the thermal comfort index and the comfort threshold.

[0025] Obtain the initial wind speed of the air supply grille, calculate the adjustment coefficient of the initial wind speed based on the deviation, and then multiply the initial wind speed with the adjustment coefficient to obtain the adjusted target wind speed.

[0026] When there are overlapping areas in the temperature sampling area, a control command to adjust to the target wind speed is sent to the corresponding air supply grid of the main control unit.

[0027] If the target wind speed exceeds the wind speed limit of the corresponding air supply grille of the main control unit, the wind speed of the main control unit will be set to the upper limit value, and a compensation command will be sent to the corresponding air supply grille of the auxiliary adjustment unit simultaneously.

[0028] The compensation instruction includes the wind speed value that the auxiliary adjustment unit needs to increase. The wind speed value is determined based on the overlap ratio between the remaining deviation of the main control unit and the effective range of the auxiliary adjustment unit.

[0029] In a preferred embodiment, the step of constructing a control feedback period based on the wind speed adjustment node of the air supply grille, and evaluating the response effect of the air supply adjustment according to the thermal comfort index within the control feedback period, includes:

[0030] The physical delay time for the air supply grille to adjust the wind speed is obtained, and the start time of the wind speed adjustment is determined by combining the control command transmission cycle.

[0031] Based on the start time, a control feedback period with a preset feedback window length is constructed, and the thermal comfort index change sequence of each temperature sampling area during the period is collected in real time.

[0032] The trend value of thermal comfort index is determined based on the change sequence of thermal comfort index, and the air supply adjustment response is deemed effective when the trend value is negative and lower than the preset response threshold.

[0033] If the trend value is positive or the absolute value is greater than or equal to the response threshold, it indicates that the air supply regulation response is invalid or there is an over-adjustment phenomenon, and the regulation coefficient is recalculated and a second wind speed adjustment is performed.

[0034] In the case of over-adjustment, the air supply intensity of the auxiliary adjustment unit is reduced first to suppress the over-adjustment trend. If the response is ineffective, the adjustment coefficient of the main control unit is recalculated, and adjustment commands are sent to the main control unit and the auxiliary adjustment unit again based on the updated adjustment coefficient.

[0035] In a preferred embodiment, the step of obtaining the preferred thermal comfort temperature under historical similar environments includes:

[0036] Obtain the current environmental parameters and the current subway operating period, and retrieve historical operating records that match the current environmental parameters and operating period from the subway historical operating database;

[0037] Extract the corresponding carriage supply temperature and user feedback rating based on the matched historical operation records.

[0038] The user feedback rating is compared with the preset satisfaction rating, and the corresponding carriage supply temperature is clustered for user feedback ratings that are higher than the user feedback rating. Several carriage supply temperature clusters under the high satisfaction range are obtained, and the mean of the carriage supply temperature cluster is selected as the thermal comfort preference temperature.

[0039] In a preferred embodiment, the step of fusing the thermal comfort preference temperature with the air supply parameters into reference data includes:

[0040] Extract the air supply parameters corresponding to the thermal comfort preference temperature from the historical operation records. The air supply parameters include air supply temperature, air supply velocity, and air supply duration.

[0041] The thermal comfort preference temperature and the corresponding air supply parameters are vectorized and mapped to obtain the thermal comfort preference temperature vector and the air supply parameter vector, respectively.

[0042] The thermal comfort preference temperature vector and the air supply parameter vector are linearly weighted and fused in a multi-dimensional space, and the result is output as a benchmark reference data.

[0043] In a preferred embodiment, the step of comparing the benchmark reference data with the current thermal comfort index, outputting a deviation adjustment signal, and compensating for the wind speed of the air supply grille based on the deviation adjustment signal to determine the final target wind speed includes:

[0044] The current thermal comfort index is sampled in real time and converted into a current thermal comfort vector. The similarity between the current thermal comfort vector and the thermal comfort preference temperature vector in the benchmark reference data is calculated, and the similarity deviation value is output.

[0045] The similarity deviation value is compared with the preset comfort threshold;

[0046] If the similarity deviation value is greater than or equal to the comfort threshold, it indicates that the current cabin environment meets the thermal comfort requirements and there is no need to adjust the airflow speed of the air supply grille.

[0047] If the similarity deviation value is less than the comfort threshold, it indicates that the current cabin environment does not meet the thermal comfort requirements. The difference between the current thermal comfort index and the preferred comfort temperature is calculated and recorded as the parameter to be adjusted.

[0048] The parameters to be controlled are input into the fuzzy logic controller, which generates a wind speed compensation amount by combining it with the current air supply speed, and then adds it to the current wind speed of the air supply grille to obtain the final target wind speed.

[0049] The present invention also provides a subway-based air conditioning supply control system, which uses the above-mentioned subway-based air conditioning supply control method, including:

[0050] The carriage partitioning module is used to collect passenger distribution data and temperature field data in the carriage in real time through pre-deployed multi-source sensing devices, obtain the distribution location of the air supply grilles in the carriage, and divide the air supply control zones according to the coverage area of ​​each air supply grille.

[0051] The wind speed adjustment module is used to calculate the thermal comfort index of each air supply control zone based on the fusion analysis of passenger distribution and temperature field data, and then dynamically adjust the wind speed of the corresponding air supply grille according to the thermal comfort index of each zone.

[0052] The feedback evaluation module is used to construct the control feedback period based on the wind speed adjustment node of the air supply grille, and evaluate the response effect of the air supply adjustment according to the thermal comfort index within the control feedback period.

[0053] The reference data acquisition module is used to acquire the preferred thermal comfort temperature under the same historical environment, as well as the air supply parameters corresponding to the preferred thermal comfort temperature, and to integrate the preferred thermal comfort temperature and the air supply parameters into benchmark reference data.

[0054] The compensation and adjustment module is used to compare the baseline reference data with the current thermal comfort index, output the deviation adjustment signal, and adjust the wind speed of the air supply grille according to the deviation adjustment signal to determine the final target wind speed.

[0055] And, an electronic device, the electronic device comprising:

[0056] At least one processor;

[0057] and a memory communicatively connected to the at least one processor;

[0058] The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the aforementioned subway-based air conditioning supply control method.

[0059] The technical effects achieved by this invention are as follows:

[0060] This invention effectively solves the problem of localized overcooling or overheating in traditional subway air conditioning systems by accurately sensing and dynamically adjusting the thermal comfort of passengers in different areas of the carriage. Through real-time data collection using multi-source sensing devices, combined with historical preference information and real-time environmental parameters, personalized and intelligent air supply control is achieved, significantly improving passenger comfort. Furthermore, this invention employs a combination of zoned control and feedback adjustment, which not only optimizes energy efficiency but also reduces the decline in experience caused by control lag. In addition, the introduction of a compensation adjustment mechanism further enhances the stability and adaptability of the air supply results, enabling rapid response and adjustment to the optimal state in complex environments, thus effectively improving passenger comfort. Attached Figure Description

[0061] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0062] Figure 2 This is a schematic diagram of the system modules of the present invention;

[0063] Figure 3 This is a schematic diagram of the electronic device structure of the present invention. Detailed Implementation

[0064] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0065] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0066] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0067] Please see Figure 1As shown, the present invention provides a method for controlling the air supply of air conditioning in a subway system, comprising:

[0068] S1. Real-time collection of passenger distribution data and temperature field data in the carriage through pre-deployed multi-source sensing devices, acquisition of the distribution location of air supply grilles in the carriage, and synchronous mapping to the three-dimensional simulation model, and then division of air supply control zones according to the coverage area of ​​each air supply grille.

[0069] In step S1, during subway operation, the thermal environment inside the carriage is significantly affected by passenger density, external temperature, and operating section. To ensure passenger comfort, precise control of air supply in different areas of the carriage is crucial. In this embodiment, multi-source sensing devices, including infrared sensors, thermal imaging cameras, and temperature sensor arrays, are pre-deployed inside the carriage to collect real-time passenger distribution density and temperature field information in different areas of the carriage, providing data support for subsequent air supply adjustment. Simultaneously, based on the actual distribution location of the air supply grilles, the carriage is divided into multiple independent air supply control zones to ensure independent control of air supply in each area. The steps of obtaining the distribution location of the air supply grilles in the carriage and dividing the air supply control zones according to the coverage area of ​​each grille include:

[0070] Based on the installation position and air delivery angle of the air supply grilles, the effective range of each air supply grille is determined. The effective range is positively correlated with the wind speed and negatively correlated with the temperature difference between the inside and outside of the vehicle.

[0071] Identify the effective range of overlapping areas and mark the relative position of the overlapping areas from each air supply grille;

[0072] The air supply grille with the closest relative position in the intersection area is selected as the main control unit, and the air supply grille with the second closest position is selected as the auxiliary adjustment unit;

[0073] The areas covered by the effective range of the main control unit and the auxiliary adjustment unit are divided into independent air supply control zones.

[0074] The effective range of non-overlapping areas is directly divided into independent air supply control zones;

[0075] Specifically, when dividing the air supply control zones, the effective range of the air supply grilles must first be determined. Determining the effective range depends not only on the installation location and air supply angle of the grilles but also on the temperature difference between the inside and outside of the carriage. Generally, higher wind speeds result in a larger effective range, while a greater temperature difference reduces the effective range. Adjustments need to be made based on the train's operating conditions to ensure dynamic adaptability in the division of each air supply control zone. In practice, the effective ranges of adjacent air supply grilles may overlap, forming intersecting areas. When identifying these intersecting areas, the overlapping portions of multiple air supply grille ranges are automatically marked, and the relationship between the intersecting areas and each individual air supply grille is further determined. The relative positions of the air supply grilles are used to clearly define the division of labor between the main control unit and the auxiliary adjustment unit, ensuring efficient coordination during air supply adjustment. Specifically, the air supply grille located at the center of the intersection area and closest to the main control unit is set as the main control unit, while the next closest air supply grille serves as the auxiliary adjustment unit. The two work together to optimize the thermal comfort of the area. Of course, multiple next closest air supply grilles can also be set as auxiliary adjustment units to enhance control redundancy and response accuracy. Especially when passengers are densely distributed during peak hours, this can effectively avoid local overcooling or overheating. For effective areas without intersections, they will be directly divided into independent air supply control zones. This zoning method simplifies the control logic and avoids control conflicts caused by overlapping areas.

[0076] S2. Based on the fusion analysis of passenger distribution and temperature field data, calculate the thermal comfort index of each air supply control zone, and then dynamically adjust the wind speed of the corresponding air supply grille according to the thermal comfort index of each zone.

[0077] In step S2, during train operation, passenger distribution density and body surface temperature data are collected in real time using in-car camera monitoring equipment and infrared thermal imaging system. The collected data is then fused to determine the thermal comfort index for each air supply control zone. The airflow speed of the corresponding air supply grilles is then adjusted based on the thermal comfort index of each zone to ensure that thermal comfort in each area remains within the optimal range, thereby improving passenger comfort. The step of calculating the thermal comfort index for each air supply control zone based on the fusion analysis of passenger distribution and temperature field data includes:

[0078] The system collects passenger positions in the carriage in real time, divides temperature sampling areas based on passenger positions, and collects temperature field data within the temperature sampling areas in real time.

[0079] The density of people in each temperature sampling area is determined based on the distribution of passenger locations, and the average perceived temperature of each temperature sampling area is determined by combining the temperature field data.

[0080] The current ambient temperature is obtained, and the heat exchange rate is determined based on the difference between the ambient temperature and the average perceived temperature. The thermal comfort index of each temperature sampling area is calculated by combining the heat exchange rate with the personnel density.

[0081] Among them, the thermal comfort index is negatively correlated with the heat exchange rate and positively correlated with the population density;

[0082] Specifically, when calculating the thermal comfort index of each air supply control zone, it is first necessary to clarify the division method of the temperature sampling area. This is typically based on the seating layout, standing area, and coverage area of ​​the air supply grilles within the passenger compartment. For example, each row of seats and the area within 0.5 meters in front and behind it can be designated as a temperature sampling area. The standing area is dynamically divided per square meter to ensure the precision of data collection. Each temperature sampling area serves as an independent analysis unit, more accurately reflecting changes in the local thermal environment. After obtaining the passenger location distribution, the passenger density is calculated by statistically analyzing the number of passengers within the area. Combined with temperature field data, further analysis can be performed... The average perceived temperature of the corresponding area is determined in one step. The average perceived temperature is not only affected by the ambient temperature, but also closely related to the passengers' body surface temperature and activity status. For example, during peak hours, due to the dense passenger flow, the body surface temperature has a more significant impact on the thermal environment of the area. Based on this, the thermal comfort index can be quantified more accurately. The thermal comfort index is calculated as α × (1 / heat exchange rate) + β × passenger density, where α and β are weighting coefficients that are dynamically adjusted according to the season, time of day, and overall load of the carriage. For example, during the high-temperature period in summer, the value of α is appropriately increased to strengthen the weight of heat dissipation demand, while in winter, the value of β is increased to take into account the heat preservation needs of densely populated areas.

[0083] Secondly, the steps for dynamically adjusting the airflow speed of the corresponding air supply grilles based on the thermal comfort index of each zone include:

[0084] Obtain the thermal comfort index and comfort threshold for each air supply control zone, and calculate the deviation between the thermal comfort index and the comfort threshold.

[0085] Obtain the initial wind speed of the air supply grille, calculate the adjustment coefficient of the initial wind speed based on the deviation, and then multiply the initial wind speed with the adjustment coefficient to obtain the adjusted target wind speed.

[0086] When there are overlapping areas in the temperature sampling area, a control command to adjust to the target wind speed is sent to the corresponding air supply grid of the main control unit.

[0087] If the target wind speed exceeds the wind speed limit of the corresponding air supply grille of the main control unit, the wind speed of the main control unit will be set to the upper limit value, and a compensation command will be sent to the corresponding air supply grille of the auxiliary adjustment unit simultaneously.

[0088] The compensation instruction includes the wind speed value that the auxiliary adjustment unit needs to increase. The wind speed value is determined based on the overlap ratio between the remaining deviation of the main control unit and the effective range of the auxiliary adjustment unit.

[0089] In the above process, when adjusting the airflow speed of the air supply grilles, the thermal comfort index and its corresponding comfort threshold for each air supply control zone are first obtained. The comfort threshold is used to determine whether the current thermal environment is within an acceptable range. It is usually set based on actual operating experience, such as 24±1.5℃ for summer and 20±1.5℃ for winter. Then, the deviation between the thermal comfort index and the comfort threshold for each zone is calculated. If the deviation is zero, it indicates that the current thermal environment has reached an ideal state, and there is no need to adjust the airflow speed of the air supply grilles. If the deviation is not zero, the process is considered complete. The airflow speed of the air supply grille needs to be dynamically adjusted based on the magnitude of the deviation. In actual operation, it is first determined whether there are overlapping areas between the temperature sampling zones. For independent air supply control zones without overlapping areas, the adjustment can be completed by directly sending the target airflow speed adjustment command to the corresponding air supply grille. However, for zones with overlapping areas, it is necessary to further distinguish the division of labor between the main control unit and the auxiliary adjustment unit to ensure the efficiency and accuracy of the control process. During the airflow speed adjustment process, the initial airflow speed adjustment coefficient is determined by comprehensively considering the deviation, the coverage area of ​​the air supply grille, and changes in environmental parameters inside and outside the vehicle. Furthermore, the adjustment coefficient is calculated using the formula: Adjustment Coefficient = 1 + k × (Deviation / Comfort Threshold), where k is the adjustment sensitivity coefficient, which can be dynamically configured according to actual operating needs. For example, during peak hours or when the external ambient temperature fluctuates drastically, the value of k can be appropriately increased to enhance the system's response speed, while during off-peak hours or when the environment is stable, the value of k can be decreased to reduce unnecessary energy consumption. In addition, when the target wind speed exceeds the wind speed limit of the corresponding air supply grille of the main control unit, a compensation mechanism will be automatically activated. Specifically, the wind speed of the main control unit will be set to its upper limit value, and simultaneously... A compensation command is sent to the auxiliary adjustment unit. The wind speed increase value in the compensation command is determined by the following formula: Compensated wind speed value = Residual deviation × Overlap ratio + Wind direction offset compensation amount. The wind direction offset compensation amount is used to offset the effective wind speed attenuation caused by mutual interference of air supply directions. The residual deviation amount is the deviation that the main control unit has not completely eliminated after reaching the upper limit. The overlap ratio is the ratio of the effective range of the auxiliary adjustment unit to the area of ​​the intersection area. Through this coordinated control method, the occurrence of local overcooling or overheating can be effectively avoided, while ensuring the overall thermal environment balance of the carriage.

[0090] S3. Construct a control feedback period based on the wind speed adjustment node of the air supply grille, and evaluate the response effect of air supply adjustment based on the thermal comfort index within the control feedback period.

[0091] In step S3, during the air supply adjustment process, to ensure the effectiveness of the adjustment, a control feedback period is constructed based on the wind speed adjustment node of the air supply grille. The length of this period is dynamically set according to the thermal inertia of the vehicle compartment and the ventilation response delay characteristics, typically 90 to 150 seconds. Then, real-time thermal comfort indicators of each temperature sampling area are continuously collected during the control feedback period. Based on this, the actual effect of the air supply adjustment is evaluated, thereby determining whether the adjustment process has achieved the expected goal. The steps of constructing the control feedback period based on the wind speed adjustment node of the air supply grille and evaluating the response effect of the air supply adjustment based on the thermal comfort indicators within the control feedback period include:

[0092] The physical delay time for the air supply grille to adjust the wind speed is obtained, and the start time of the wind speed adjustment is determined by combining the control command transmission cycle.

[0093] Based on the start time, a control feedback period with a preset feedback window length is constructed, and the thermal comfort index change sequence of each temperature sampling area during the period is collected in real time.

[0094] The trend value of thermal comfort index is determined based on the change sequence of thermal comfort index, and the air supply adjustment response is deemed effective when the trend value is negative and lower than the preset response threshold.

[0095] If the trend value is positive or the absolute value is greater than or equal to the response threshold, it indicates that the air supply regulation response is invalid or there is an over-adjustment phenomenon, and the regulation coefficient is recalculated and a second wind speed adjustment is performed.

[0096] In the case of over-adjustment, the air supply intensity of the auxiliary adjustment unit is reduced first to suppress the over-adjustment trend. If the response is invalid, the adjustment coefficient of the main control unit is recalculated, and the adjustment command is sent to the main control unit and the auxiliary adjustment unit again based on the updated adjustment coefficient.

[0097] Specifically, when evaluating the response effect of air supply adjustment, it is first necessary to obtain the physical delay time of the air supply grille executing wind speed adjustment. The physical delay time generally varies depending on the equipment performance and installation location, usually fluctuating between 5 and 15 seconds. At the same time, combined with the control command transmission cycle, the start time of wind speed adjustment can be determined, thus providing a time benchmark for the construction of the subsequent control feedback period. The length of the control feedback period is dynamically set according to the thermal inertia of the carriage and the ventilation response delay characteristics, usually within the range of 90 to 150 seconds, to ensure that the evaluation process can fully reflect the actual effect of air supply adjustment. During this period, the change sequence of thermal comfort indexes in each temperature sampling area will be collected in real time, and the trend values ​​of these data will be analyzed to determine whether the adjustment effect has achieved the expected goal. If the trend value is negative and below the preset response threshold, it indicates that the air supply adjustment response is effective. Conversely, if the trend value is positive or the absolute value is greater than or equal to the response threshold, there may be over-adjustment or ineffective response. For over-adjustment, the air supply intensity of the auxiliary adjustment unit will be reduced first to suppress the over-adjustment trend and restore the thermal environment balance. For ineffective response, the adjustment coefficient of the main control unit will be recalculated, and adjustment instructions will be sent to the main control unit and auxiliary adjustment unit again based on the updated adjustment coefficient. This achieves dynamic optimization and control, thereby further improving the thermal comfort experience of passengers.

[0098] S4. Obtain the preferred thermal comfort temperature under similar historical conditions, as well as the corresponding air supply parameters, and integrate the preferred thermal comfort temperature and air supply parameters into benchmark reference data.

[0099] In step S4, to ensure that the adjustment results are more closely aligned with the cabin environment, this embodiment prioritizes acquiring the preferred thermal comfort temperature and its corresponding air supply parameters under historical similar environments. This data is then used as a benchmark for subsequent adjustment strategy optimization, thereby improving the system's response accuracy and personalized adaptation capabilities to passenger thermal comfort. The step of acquiring the preferred thermal comfort temperature under historical similar environments includes:

[0100] Obtain the current environmental parameters and the current subway operating period, and retrieve historical operating records that match the current environmental parameters and operating period from the subway historical operating database;

[0101] Extract the corresponding carriage supply temperature and user feedback rating based on the matched historical operation records.

[0102] The user feedback rating is compared with the preset satisfaction rating, and the corresponding carriage supply temperature is clustered for the user feedback rating that is higher than the user feedback rating to obtain several carriage supply temperature clusters under the high satisfaction range. The mean of the carriage supply temperature cluster is selected as the thermal comfort preference temperature.

[0103] Specifically, when determining the preferred thermal comfort temperature, the system first collects real-time environmental parameters, including the temperature and humidity inside and outside the carriage, as well as information on the subway's operating hours. This data is then matched against records in the subway's historical operation database. The matching process can employ algorithms such as multi-dimensional similarity to prioritize historical records that most closely match the current environmental parameters and operating hours. For example, during hot summer periods with high carriage occupancy, historical data under similar conditions is prioritized to ensure the extracted carriage temperature has high reference value. After obtaining the carriage temperature, the data is further filtered and optimized by incorporating user feedback ratings, which are derived from passenger feedback. Actual experience evaluations are typically collected through mobile applications or station terminal devices. Higher scores indicate that the thermal comfort of the corresponding carriage temperature meets passenger needs. By performing cluster analysis on the carriage supply temperatures within the high satisfaction range, the preferred thermal comfort temperatures under different environmental conditions can be effectively identified. Cluster analysis can use the K-means algorithm or hierarchical clustering method to group similar carriage supply temperatures together and calculate the mean of each group as the preferred thermal comfort temperature. In addition, to improve the dynamic adaptability of the benchmark reference data, the historical database is updated regularly according to seasonal changes and operational needs, and the preferred thermal comfort temperature is recalculated to ensure that it always matches the actual operating scenario.

[0104] Secondly, the steps for integrating thermal comfort preference temperature with air supply parameters into benchmark reference data include:

[0105] Extract the air supply parameters corresponding to the thermal comfort preference temperature from the historical operation records. The air supply parameters include air supply temperature, air supply velocity, and air supply duration.

[0106] The thermal comfort preference temperature and the corresponding air supply parameters are vectorized and mapped to obtain the thermal comfort preference temperature vector and the air supply parameter vector, respectively.

[0107] The thermal comfort preference temperature vector and the air supply parameter vector are linearly weighted and fused in a multi-dimensional space, and the result is output as a benchmark reference data.

[0108] In the process described above, when determining the benchmark reference data, the air supply parameters corresponding to the thermal comfort preference temperature are first extracted from historical operating records. These parameters include air supply temperature, air supply velocity, and air supply duration. This allows for a clearer understanding of the optimal air supply configuration for different thermal comfort preference temperatures. During this process, the thermal comfort preference temperature and the corresponding air supply parameters are vectorized to form a thermal comfort preference temperature vector and an air supply parameter vector. These vectors are then fused in a multi-dimensional space using a linear weighting method. The weighting coefficients are dynamically adjusted based on actual operational needs and environmental conditions to ensure that the fusion result accurately reflects the actual thermal environment requirements of the passenger compartment. Finally, the fused data is output as benchmark reference data to guide subsequent optimization of the air supply adjustment strategy.

[0109] S5. Compare the benchmark reference data with the current thermal comfort index, output the deviation adjustment signal, and adjust the wind speed of the air supply grille according to the deviation adjustment signal to determine the final target wind speed.

[0110] In step S5, after the baseline reference data is output, it is dynamically compared with the real-time collected thermal comfort index inside the carriage to determine the degree of deviation between the current thermal environment of the carriage and the ideal state. If a deviation exists, a deviation adjustment signal is output to compensate for and adjust the air supply grille, thereby providing a more comfortable riding environment for passengers inside the carriage. The steps of comparing the baseline reference data with the current thermal comfort index, outputting a deviation adjustment signal, and compensating for and adjusting the wind speed of the air supply grille according to the deviation adjustment signal to determine the final target wind speed include:

[0111] The current thermal comfort index is sampled in real time and converted into a current thermal comfort vector. The similarity between the current thermal comfort vector and the thermal comfort preference temperature vector in the benchmark reference data is calculated, and the similarity deviation value is output.

[0112] The similarity deviation value is compared with the preset comfort threshold;

[0113] If the similarity deviation value is greater than or equal to the comfort threshold, it indicates that the current cabin environment meets the thermal comfort requirements and there is no need to adjust the airflow speed of the air supply grille.

[0114] If the similarity deviation value is less than the comfort threshold, it indicates that the current cabin environment does not meet the thermal comfort requirements. The difference between the current thermal comfort index and the preferred comfort temperature is calculated and recorded as the parameter to be adjusted.

[0115] The parameters to be controlled are input into the fuzzy logic controller, which generates a wind speed compensation amount by combining it with the current air supply speed, and then adds it to the current wind speed of the air supply grille to obtain the final target wind speed.

[0116] Specifically, when determining the final target wind speed of the air supply grille, the current thermal comfort index needs to be sampled in real time and converted into a current thermal comfort vector. This vector is then used to calculate the similarity with the thermal comfort preference temperature vector in the benchmark reference data. The calculated similarity deviation value directly reflects the difference between the current thermal environment of the passenger compartment and the ideal state. The similarity deviation value can be measured using metrics such as cosine similarity or Euclidean distance. If the similarity deviation value is greater than or equal to the preset comfort threshold, it indicates that the current thermal environment in the passenger compartment has met the comfort requirements of the passengers, and there is no need to adjust the wind speed of the air supply grille. External adjustment; however, if the similarity deviation value is less than the comfort threshold, it indicates that the current cabin environment fails to meet the thermal comfort requirements. At this time, the difference between the current thermal comfort index and the thermal comfort preference temperature will be automatically calculated and recorded as the parameter to be adjusted. Subsequently, the parameter to be adjusted is input into the fuzzy logic controller, which generates the corresponding wind speed compensation amount in combination with the actual wind speed of the current air supply grille. The fuzzy logic controller can dynamically adjust the control strategy according to the input parameters to ensure that the calculation of the compensation amount meets the actual needs. Finally, the generated wind speed compensation amount is superimposed on the current wind speed of the air supply grille to determine the final target wind speed of the air supply grille.

[0117] Please see Figure 2 A subway-based air conditioning supply control system, using the aforementioned subway-based air conditioning supply control method, includes:

[0118] The carriage partitioning module is used to collect passenger distribution data and temperature field data in the carriage in real time through pre-deployed multi-source sensing devices, obtain the distribution location of the air supply grilles in the carriage, and divide the air supply control zones according to the coverage area of ​​each air supply grille.

[0119] The wind speed adjustment module is used to calculate the thermal comfort index of each air supply control zone based on the fusion analysis of passenger distribution and temperature field data, and then dynamically adjust the wind speed of the corresponding air supply grille according to the thermal comfort index of each zone.

[0120] The feedback evaluation module is used to construct the control feedback period based on the wind speed adjustment node of the air supply grille, and evaluate the response effect of the air supply adjustment according to the thermal comfort index within the control feedback period.

[0121] The reference data acquisition module is used to acquire the preferred thermal comfort temperature under the same historical environment, as well as the air supply parameters corresponding to the preferred thermal comfort temperature, and to integrate the preferred thermal comfort temperature and the air supply parameters into benchmark reference data.

[0122] The compensation and adjustment module is used to compare the baseline reference data with the current thermal comfort index, output the deviation adjustment signal, and adjust the wind speed of the air supply grille according to the deviation adjustment signal to determine the final target wind speed.

[0123] The execution process of the above control system corresponds exactly to the steps of the aforementioned control method, so it will not be repeated here.

[0124] Please see Figure 3 An electronic device, comprising:

[0125] At least one processor;

[0126] and memory that is communicatively connected to at least one processor;

[0127] The memory stores a computer program that can be executed by at least one processor, which enables the at least one processor to execute the aforementioned subway-based air conditioning supply control method.

[0128] The processor of the aforementioned electronic device can be at least one central processing unit (CPU) or graphics processing unit (GPU) to execute computer program instructions stored in the memory, thereby achieving accurate perception and dynamic control of the thermal environment inside the vehicle. The memory can be random access memory (RAM), read-only memory (ROM), or flash memory, used to store sensor-collected data, control algorithm parameters, and historical operation records, supporting real-time access and analysis by the processor to ensure the efficient and stable operation of the air conditioning ventilation control system. In addition, the electronic device may also include an arithmetic unit, input devices, and output devices. The arithmetic unit is responsible for performing wind speed calculation, data fusion, and control logic operations. The input devices are used to receive sensor data and user instructions, and the output devices transmit control signals to the air supply grille actuator to achieve intelligent adjustment of the air conditioning ventilation.

[0129] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A simulation-based method for controlling the air supply of subway air conditioning, characterized in that: include: The passenger distribution data and temperature field data in the carriage are collected in real time by pre-deployed multi-source sensing devices, and the distribution location of the air supply grilles in the carriage is obtained and synchronously mapped to the three-dimensional simulation model. Then, the air supply control zone is divided according to the coverage area of ​​each air supply grille. Based on the fusion analysis of passenger distribution and temperature field data, the thermal comfort index of each air supply control zone is calculated, and the wind speed of the corresponding air supply grille is dynamically adjusted according to the thermal comfort index of each zone. The control feedback period is constructed based on the wind speed adjustment node of the air supply grille, and the response effect of air supply adjustment is evaluated based on the thermal comfort index within the control feedback period. Obtain the preferred thermal comfort temperature under similar historical conditions, as well as the corresponding air supply parameters, and integrate the preferred thermal comfort temperature and air supply parameters into benchmark reference data; The baseline reference data is compared with the current thermal comfort index, a deviation adjustment signal is output, and the wind speed of the air supply grille is adjusted to compensate for the deviation adjustment signal to determine the final target wind speed.

2. The air supply control method for air conditioning in a subway system according to claim 1, characterized in that: The step of obtaining the distribution location of the air supply grilles inside the vehicle compartment and dividing the air supply control zones according to the coverage area of ​​each air supply grille includes: Based on the installation position and air delivery angle of the air supply grilles, the effective range of each air supply grille is determined. The effective range is positively correlated with the wind speed and negatively correlated with the temperature difference between the inside and outside of the vehicle. Identify the effective range of overlapping areas and mark the relative position of the overlapping areas from each air supply grille; The air supply grille with the closest relative position in the intersection area is selected as the main control unit, and the air supply grille with the second closest position is selected as the auxiliary adjustment unit; The areas covered by the effective range of the main control unit and the auxiliary adjustment unit are divided into independent air supply control zones. The effective range of non-overlapping areas is directly divided into independent air supply control zones.

3. The air supply control method for air conditioning in a subway system according to claim 1, characterized in that: The steps for calculating the thermal comfort index of each air supply control zone based on the fusion analysis of passenger distribution and temperature field data include: The system collects passenger positions in the carriage in real time, divides temperature sampling areas based on passenger positions, and collects temperature field data within the temperature sampling areas in real time. The density of people in each temperature sampling area is determined based on the distribution of passenger locations, and the average perceived temperature of each temperature sampling area is determined by combining the temperature field data. The current ambient temperature is obtained, and the heat exchange rate is determined based on the difference between the ambient temperature and the average perceived temperature. The thermal comfort index of each temperature sampling area is calculated by combining the heat exchange rate with the personnel density. Among them, the thermal comfort index is negatively correlated with the heat exchange rate and positively correlated with the population density.

4. The air supply control method for air conditioning in a subway system according to claim 1, characterized in that: The step of dynamically adjusting the airflow speed of the corresponding air supply grille according to the thermal comfort index of each zone includes: Obtain the thermal comfort index and comfort threshold for each air supply control zone, and calculate the deviation between the thermal comfort index and the comfort threshold. Obtain the initial wind speed of the air supply grille, calculate the adjustment coefficient of the initial wind speed based on the deviation, and then multiply the initial wind speed with the adjustment coefficient to obtain the adjusted target wind speed. When there are overlapping areas in the temperature sampling area, a control command to adjust to the target wind speed is sent to the corresponding air supply grid of the main control unit. If the target wind speed exceeds the wind speed limit of the corresponding air supply grille of the main control unit, the wind speed of the main control unit will be set to the upper limit value, and a compensation command will be sent to the corresponding air supply grille of the auxiliary adjustment unit simultaneously. The compensation instruction includes the wind speed value that the auxiliary adjustment unit needs to increase. The wind speed value is determined based on the overlap ratio between the remaining deviation of the main control unit and the effective range of the auxiliary adjustment unit.

5. The air supply control method for air conditioning in a subway system according to claim 1, characterized in that: The step of constructing a control feedback period based on the wind speed adjustment node of the air supply grille, and evaluating the response effect of the air supply adjustment based on the thermal comfort index within the control feedback period, includes: The physical delay time for the air supply grille to adjust the wind speed is obtained, and the start time of the wind speed adjustment is determined by combining the control command transmission cycle. Based on the start time, a control feedback period with a preset feedback window length is constructed, and the thermal comfort index change sequence of each temperature sampling area during the period is collected in real time. The trend value of thermal comfort index is determined based on the change sequence of thermal comfort index, and the air supply adjustment response is deemed effective when the trend value is negative and lower than the preset response threshold. If the trend value is positive or the absolute value is greater than or equal to the response threshold, it indicates that the air supply regulation response is invalid or there is an over-adjustment phenomenon, and the regulation coefficient is recalculated and a second wind speed adjustment is performed. In the case of over-adjustment, the air supply intensity of the auxiliary adjustment unit is reduced first to suppress the over-adjustment trend. If the response is ineffective, the adjustment coefficient of the main control unit is recalculated, and adjustment commands are sent to the main control unit and the auxiliary adjustment unit again based on the updated adjustment coefficient.

6. The air supply control method for air conditioning in a subway system according to claim 1, characterized in that: The step of obtaining the preferred thermal comfort temperature under historical similar environments includes: Obtain the current environmental parameters and the current subway operating period, and retrieve historical operating records that match the current environmental parameters and operating period from the subway historical operating database; Extract the corresponding carriage supply temperature and user feedback rating based on the matched historical operation records. The user feedback rating is compared with the preset satisfaction rating, and the corresponding carriage supply temperature is clustered for user feedback ratings that are higher than the user feedback rating. Several carriage supply temperature clusters under the high satisfaction range are obtained, and the mean of the carriage supply temperature cluster is selected as the thermal comfort preference temperature.

7. The air supply control method for air conditioning in a subway system according to claim 1, characterized in that: The step of integrating thermal comfort preference temperature with air supply parameters into benchmark reference data includes: Extract the air supply parameters corresponding to the thermal comfort preference temperature from the historical operation records. The air supply parameters include air supply temperature, air supply velocity, and air supply duration. The thermal comfort preference temperature and the corresponding air supply parameters are vectorized and mapped to obtain the thermal comfort preference temperature vector and the air supply parameter vector, respectively. The thermal comfort preference temperature vector and the air supply parameter vector are linearly weighted and fused in a multi-dimensional space, and the result is output as a benchmark reference data.

8. The air supply control method for air conditioning in a subway system according to claim 1, characterized in that: The steps of comparing the benchmark reference data with the current thermal comfort index, outputting a deviation adjustment signal, and compensating for the wind speed of the air supply grille based on the deviation adjustment signal to determine the final target wind speed include: The current thermal comfort index is sampled in real time and converted into a current thermal comfort vector. The similarity between the current thermal comfort vector and the thermal comfort preference temperature vector in the benchmark reference data is calculated, and the similarity deviation value is output. The similarity deviation value is compared with the preset comfort threshold; If the similarity deviation value is greater than or equal to the comfort threshold, it indicates that the current cabin environment meets the thermal comfort requirements and there is no need to adjust the airflow speed of the air supply grille. If the similarity deviation value is less than the comfort threshold, it indicates that the current cabin environment does not meet the thermal comfort requirements. The difference between the current thermal comfort index and the preferred comfort temperature is calculated and recorded as the parameter to be adjusted. The parameters to be controlled are input into the fuzzy logic controller, which generates a wind speed compensation amount by combining it with the current air supply speed, and then adds it to the current wind speed of the air supply grille to obtain the final target wind speed.

9. A subway-based air conditioning supply control system, characterized in that: The subway-based air conditioning supply control method according to any one of claims 1 to 8 includes: The carriage partitioning module is used to collect passenger distribution data and temperature field data in the carriage in real time through pre-deployed multi-source sensing devices, obtain the distribution location of the air supply grilles in the carriage, and divide the air supply control zones according to the coverage area of ​​each air supply grille. The wind speed adjustment module is used to calculate the thermal comfort index of each air supply control zone based on the fusion analysis of passenger distribution and temperature field data, and then dynamically adjust the wind speed of the corresponding air supply grille according to the thermal comfort index of each zone. The feedback evaluation module is used to construct the control feedback period based on the wind speed adjustment node of the air supply grille, and evaluate the response effect of the air supply adjustment according to the thermal comfort index within the control feedback period. The reference data acquisition module is used to acquire the preferred thermal comfort temperature under the same historical environment, as well as the air supply parameters corresponding to the preferred thermal comfort temperature, and to integrate the preferred thermal comfort temperature and the air supply parameters into benchmark reference data. The compensation and adjustment module is used to compare the baseline reference data with the current thermal comfort index, output the deviation adjustment signal, and adjust the wind speed of the air supply grille according to the deviation adjustment signal to determine the final target wind speed.

10. An electronic device, characterized in that: The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the subway-based air conditioning supply control method according to any one of claims 1 to 8.

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