Energy intelligent control method and system for refrigeration detection laboratory

Abstract

The application discloses an energy intelligent control method and system for a refrigeration detection laboratory, relates to the technical field of energy control, collects temperature, humidity, pressure, fog delivery parameters and refrigeration equipment operation parameters, calculates humidity content and wet air enthalpy, peels off enthalpy and humidity changes caused by refrigeration actions, forms refrigeration enthalpy and humidity residual and a fog delivery action sequence; analyzes fog evaporation delay, constructs a micro-fog latent cooling phase track body, and combines a historical phase track carrier to form a phase track mass migration tensor; distributes latent cooling winding mass to current and subsequent sampling time periods, generates a latent cooling refrigeration proportion spectrum and a proportion corrected dynamic refrigeration amount; respectively deduces an original refrigeration operation track and a latent cooling proportion operation track, and outputs a latent cooling proportion execution instruction, a residual proportion continuation instruction or an original refrigeration track execution instruction after comprehensive evaluation. The application can identify micro-fog evaporation and residual latent cooling actions after fog delivery stops, and inhibit repeated refrigeration and temperature and humidity fluctuations.

Description

Technical Field

[0001] This invention relates to the field of energy control technology, specifically to an intelligent energy control method and system for a refrigeration testing laboratory. Background Technology

[0002] Existing refrigeration testing laboratories typically calculate dynamic cooling capacity based on the deviation between the actual temperature and the target temperature, and then adjust the compressor operating frequency and electronic expansion valve opening. Ultrasonic humidification equipment, on the other hand, independently adjusts the oscillation frequency and airflow speed based on the deviation between the actual humidity and the target humidity. These control methods usually treat cooling and humidification separately, failing to continuously analyze the time delay between mist generation, transport, and evaporation heat absorption, and also failing to identify the latent cooling share of mist still in the air after mist delivery stops. Therefore, the dynamic cooling capacity calculation easily over-includes cooling already undertaken by mist evaporation, making it difficult to allocate the latent cooling effect of mist to the current and subsequent sampling periods.

[0003] The aforementioned shortcomings mainly stem from the fact that the micro-mist evaporation process and the real-time operating status of the ultrasonic humidification equipment are not completely synchronized. After the micro-mist is delivered into the laboratory by air, it undergoes a process of transport, suspension, and evaporation. Even if the ultrasonic oscillation frequency has dropped to zero, the previously formed micro-mist may still continue to absorb heat from the air. If the compressor's cooling capacity is still configured according to the real-time temperature deviation, it may result in repeated use of cooling capacity, causing the laboratory temperature to be lower than the target temperature, and causing repeated fluctuations in actual humidity, compressor operating frequency, and electronic expansion valve opening. At the same time, the latent cooling effect of the mist tail stage is not continuously utilized, which will also cause frequent compressor adjustments and increased cooling energy consumption. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an intelligent energy control method and system for a refrigeration testing laboratory, solving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: an energy intelligent control system for a refrigeration testing laboratory, comprising an enthalpy-humidity scale sequencing module, a micro-mist latent cooling phase track weaving module, a phase track quality migration preliminary evaluation module, a latent cooling quota spectrum generation module, and a quota trajectory comprehensive evaluation execution module;

[0006] The enthalpy and humidity scale sequencing module collects actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening and dynamic cooling capacity, calculates moisture content HS and enthalpy value ZHD of humid air, and forms the enthalpy and humidity residue of de-cooling and fog delivery action sequence after scale conversion and refrigeration action projection stripping.

[0007] The micro-mist latent cooling phase track weaving module obtains the fog delivery evaporation delay position based on the fog delivery action sequence and the enthalpy moisture residue of the decooling, constructs a three-dimensional state point P, and calculates the latent cooling winding mass to form the micro-mist latent cooling phase track body B.

[0008] The phase track quality migration preliminary assessment module will conduct a preliminary assessment of the micro-mist latent cooling phase track body B and the historical phase track quality centroid, and form a phase track quality migration tensor.

[0009] The latent cooling occupancy spectrum generation module allocates the latent cooling winding mass to the current and subsequent sampling periods based on the phase track mass migration tensor, forming the latent cooling occupancy spectrum C, and obtains the dynamic cooling capacity RQ after occupancy correction;

[0010] The quota trajectory comprehensive evaluation and execution module respectively deduce the dynamic cooling capacity operation trajectory and the dynamic cooling capacity RQ operation trajectory after quota correction, and outputs the latent cooling quota execution command, the residual quota continuation command and the original cooling trajectory execution command after comprehensive evaluation.

[0011] Preferably, the enthalpy-humidity scale sequencing module includes an enthalpy-humidity simultaneous conversion unit and a cooling trace stripping unit;

[0012] The enthalpy-humidity conversion unit reads the actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening degree, and dynamic cooling capacity according to a fixed sampling period.

[0013] When the collection times of various data are inconsistent, the sampling time is made up by matching two adjacent sampling values ​​to form a synchronous energy collection group, and the moisture content HS and the enthalpy of moist air ZHD are calculated and obtained, as follows:

[0014] ;

[0015] ;

[0016] In the formula, This represents a decimal value derived from the actual humidity. This represents the saturated water vapor pressure at the current actual temperature;

[0017] The moisture content (HS), enthalpy of moist air (ZHD), and energy acquisition group at the same time are normalized to eliminate the dimensions of the data. The normalized moisture content (HS), enthalpy of moist air (ZHD), compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity are arranged according to the sampling order to form an enthalpy-humidity cooling sequence.

[0018] The processed ultrasonic oscillation frequency and air delivery speed are arranged in the same sampling order to form a complete sequence of fog delivery actions.

[0019] The cooling trace stripping unit reads the enthalpy-humidity cooling sequence and the fog delivery action sequence, calculates the change in moisture content (HS) and the change in enthalpy of moist air (ZHD) between adjacent sampling locations, and forms the enthalpy-humidity change sequence.

[0020] The changes in moisture content (HS) and enthalpy of moist air (ZHD) were obtained by measuring the difference in moisture content (HS) and the difference in enthalpy of moist air (ZHD) between adjacent sampling locations, respectively.

[0021] The compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity are read from the current sampling position, the previous sampling position, and the two previous sampling positions respectively to form a cooling action trace;

[0022] The repeated actions carried in the refrigeration action trace are removed one by one, so that the compressor operating frequency change, electronic expansion valve opening change and dynamic refrigeration capacity change each retain their independent function;

[0023] By projecting the enthalpy-humidity change sequence using the independent action component, the amount of enthalpy-humidity change caused by the cooling action can be obtained;

[0024] Subtract the enthalpy and humidity change caused by the refrigeration action from the enthalpy and humidity change sequence to form the enthalpy and humidity residue after refrigeration.

[0025] The enthalpy-humidity residue after cooling is obtained by the difference between the change in moisture content (HS) and the change in enthalpy (ZHD) of moist air at the current sampling location and the enthalpy-humidity change explained by the cooling action trace.

[0026] The enthalpy-humidity residue after cooling includes the moisture content (HS residue) and the enthalpy value (ZHD residue) of moist air;

[0027] The enthalpy and humidity residue of the refrigeration system retains enthalpy and humidity changes that cannot be explained by the compressor operating frequency, electronic expansion valve opening, and dynamic refrigeration capacity, which are then used for subsequent extraction of micro-mist evaporation.

[0028] The ultrasonic oscillation frequency and the air delivery speed in the entire fog delivery sequence are multiplied to obtain the continuous fog delivery effect. The changes between these two values ​​at adjacent sampling positions are then read to characterize the transitions in fog generation intensity and fog delivery intensity, respectively. The continuous fog delivery effect, the transitions in fog generation intensity and fog delivery intensity, and the sampling order are arranged together to form the fog delivery sequence.

[0029] Preferably, the micro-mist latent cooling phase track weaving module includes a fog delivery delay traction analysis unit and a latent cooling phase track winding weaving unit;

[0030] The fog delivery delay traction analysis unit reads the fog delivery action sequence and the moisture content (HS residual) and humid air enthalpy (ZHD residual) in the decooling enthalpy moisture residual;

[0031] The positive component formed by the increase in water vapor content is retained in the moisture content (HS) residue, and the negative component formed by the decrease in air enthalpy is retained in the moisture air enthalpy (ZHD) residue;

[0032] The two components are combined according to the sampling order to form an evaporative endothermic response sequence;

[0033] Several consecutive delay positions are set within a fixed period: for each selected delay position, the fog delivery sequence is shifted backward by the corresponding number of samples and then overlapped with the evaporation endothermic response sequence.

[0034] Based on their respective data distributions, the shifted fog delivery effect and evaporative heat absorption response are divided into several equal-frequency intervals. The proportion of both data points falling into each interval combination is statistically analyzed, and the time-series traction Ir at the current delay position is calculated using the following formula:

[0035] ;

[0036] In the formula, This indicates the proportion of the combined occurrence of the shifted fog delivery effect falling into the a-th equal-frequency interval and the evaporative endothermic response falling into the b-th equal-frequency interval. and These represent the proportions of each data point falling within the current interval, and r represents the delay position;

[0037] The acquired temporal traction quantity Ir is converted into delay allocation weights, and the fog delivery evaporation delay position re is formed by the weighted center of each delay position, as shown in the formula: ;

[0038] In the formula, Represents an exponential function;

[0039] Among them, the use of weighted center can retain the multiple delays formed by the same batch of micro-mist after direct evaporation, suspension evaporation and surface residence evaporation, without forcibly classifying all micro-mist into a single sampling location;

[0040] Then, according to the delay allocation weights at each delay position, the moved fog delivery action sequence is weighted and superimposed to form a fog delivery traction sequence.

[0041] Each sampled value in the fog delivery traction sequence represents the evaporation traction share that the previous fog delivery action still retains at the current sampling position. After the ultrasonic oscillation frequency returns to zero, as long as the previous fog delivery action still falls into the subsequent sampling positions along the delay allocation weight, the fog delivery traction sequence continues to retain values, so that the micro-mist evaporation process after fog cessation can be included in the latent cooling winding quality calculation;

[0042] Preferably, the latent cooling phase track winding braiding unit reads the fog delivery evaporation delay position, fog delivery traction sequence, and the moisture content (HS) and humid air enthalpy (ZHD) residual in the decooling enthalpy moisture residue.

[0043] When the fog evaporation delay position falls between two sampling positions, the residual moisture content HS is linearly interpolated based on the distance between the two sampling positions and the fog evaporation delay position to obtain the residual moisture content HS at the delay position. A three-dimensional state point P is then constructed for each sampling position, as shown in the following formula:

[0044] ;

[0045] In the formula, Pk represents the three-dimensional state point formed at the k-th sampling position. This represents the residual moisture content (HS) at the k-th sampling location. This represents the residual enthalpy of moist air (ZHD) at the k-th sampling location. express ;

[0046] Among them, the first dimension of the three-dimensional state point P records the current change in water vapor content, the second dimension records the process of air enthalpy decrease, and the third dimension records the amount of expansion of the current moisture content HS residual relative to the fog evaporation delay position.

[0047] Connect each 3D state point P according to the sampling order. To eliminate the interference of the coordinate origin selection on the winding result, four 3D state points are read continuously. The first 3D state point is taken as the current winding base point. Subtract the winding base point from the remaining three 3D state points to form three state transition vectors. Calculate the directed volume Vk enclosed by the three state transition vectors, as shown in the following formula:

[0048] ;

[0049] In the formula, Vk specifically represents the directional winding volume at the k-th sampling position. The positive or negative sign of Vk indicates the winding direction, reflecting the rotation order of the moisture content HS, the enthalpy of moist air ZHD, and the delay unfolding amount in the current sampling process. This indicates the degree of spatial expansion formed after the current state trajectory deviates from unidirectional change. This represents the three-dimensional state point formed at the (k-1)th sampling position. This represents the three-dimensional state point formed at the (k-2)th sampling position. Let represent the three-dimensional state point formed at the (k-3)th sampling position, and det represent the determinant of the third-order matrix composed of the three state transition vectors;

[0050] Read the fog delivery traction amount Gk at the current sampling position, multiply the absolute value of the directed winding volume by the fog delivery traction amount to form the latent cooling winding mass Mk at the current sampling position, as shown in the formula: ;

[0051] The method for obtaining the fog delivery traction amount Gk is as follows:

[0052] Arrange the samples in the sampling order to form a fog delivery traction sequence, read the value of the kth sampling position in the fog delivery traction sequence, and record it as Gk;

[0053] Gk represents the degree to which the mist delivery action still pulls at the k-th sampling position. When the ultrasonic humidification system is running, Gk includes the pull share left by the current mist delivery action and the previous mist delivery action. After the ultrasonic humidification system stops running, if the previously delivered micro-mist is still in the process of being transported, suspended, or evaporated, the mist delivery pull sequence still retains a value at the k-th sampling position, so Gk will not immediately return to zero.

[0054] Arrange the three-dimensional state points P, latent cooling winding mass Mk, winding direction, fog delivery traction amount Gk, and fog delivery evaporation delay position according to the sampling order to form the micro-fog latent cooling phase track B.

[0055] Preferably, the phase track quality migration preliminary assessment module includes a historical phase track parallel bearing unit and a phase track quality migration preliminary assessment unit;

[0056] The historical phase track co-processing unit reads the historical micro-mist latent cold phase track bodies formed during multiple historical humidification processes; each historical micro-mist latent cold phase track body contains a three-dimensional state point P, latent cold winding mass, winding direction, fog delivery traction amount, and sampling order.

[0057] Because the runtime, ultrasonic oscillation frequency, and air delivery speed of each historical humidification process are different, they cannot be directly stacked according to the sampling position; the fog delivery process position Sk is calculated based on the fog delivery traction amount at each sampling position, as shown in the following formula:

[0058] ;

[0059] In the formula, Sk represents the fog delivery process position of the kth sampling position, with a value ranging from zero to one; Gq represents the fog delivery traction amount of the qth sampling position in the fog delivery traction sequence; N represents the total number of sampling positions contained in the current historical micro-fog latent cooling phase track.

[0060] The fog delivery process position indicates the proportion of fog delivery traction that has been released up to the current sampling position. Different historical humidification processes, even if their durations differ, can be uniformly treated according to a fog delivery process position of zero to one.

[0061] Read the number of sampling locations contained in the entire historical micro-mist latent cooling phase track, and take the historical humidification process with the fewest sampling locations as the unified division basis to form several continuous bearing locations within the range of zero to one mist delivery process.

[0062] For each historical micro-fog latent cooling phase track, read the position of the fog delivery process where each latent cooling winding mass is located;

[0063] When the current fog delivery process position falls between two adjacent support positions, the current latent cooling winding mass is divided into two support positions according to its distance from the two support positions, and the total latent cooling winding mass after division remains unchanged.

[0064] The three-dimensional state point P and the winding direction are not directly averaged, but are weighted according to the latent cooling winding mass entering the same bearing position, and the three-dimensional state position and main winding direction of the current bearing position are calculated.

[0065] Thus, each historical micro-fog latent cooling phase track body is converted into a set of historical phase track carrier plates located on a unified fog delivery process;

[0066] Each historical phase track carrier piece is reversed from the unified carrier position to the original fog delivery process position, and the spatial deviation between the restored three-dimensional state point and the original three-dimensional state point is calculated.

[0067] The spatial deviation is obtained as follows:

[0068] The three-dimensional state points of each bearing position in the historical phase track bearing plate are redistributed to the corresponding historical sampling positions according to their original fog delivery process positions. The restored three-dimensional state points and the original three-dimensional state points are read one by one, and the differences between the two three-dimensional state points in the three directions of residual moisture content (HS), residual enthalpy of moist air (ZHD), and delayed expansion are calculated respectively. The square root of the sum of the squares of the three differences is used to obtain the spatial distance of the current historical sampling position. Then, the spatial distances of all historical sampling positions in the same historical phase track bearing plate are averaged to obtain the spatial deviation of the current historical phase track bearing plate.

[0069] Spatial deviation is used to allocate the participation share of the current historical phase track carrier piece: the more concentrated the spatial deviation, the larger the participation share; the more dispersed the spatial deviation, the smaller the participation share.

[0070] According to the participation share, each historical phase track carrier piece is collected, and the historical three-dimensional state position, historical carrier mass and historical main winding direction are formed at each carrier position, and finally the historical phase track carrier body is formed.

[0071] Preferably, the phase track quality migration preliminary assessment unit reads the current micro-mist latent cooling phase track body B and the historical phase track carrier body;

[0072] Based on the current fog delivery traction in the micro-fog latent cooling phase track body B, and according to the processing method in the historical phase track co-path bearing unit, calculate the fog delivery process position of each three-dimensional state point P.

[0073] Each three-dimensional state point P in the current micro-mist latent cooling phase orbit body B is combined with each bearing position in the historical phase orbit bearing body to form a migration grid, and the migration cost of each migration grid is calculated. The formula is as follows:

[0074] ;

[0075] In the formula, This represents the g-th historical three-dimensional state position in the historical phase track carrier, Sg represents the fog delivery process position of the historical carrier position, dk represents the current winding direction, and dr represents the historical main winding direction. Represents the weights for 3D state position transitions. Indicates the migration weight of the fog delivery process. This indicates the weight of the roll-up direction migration, and ;

[0076] , and The method of obtaining it is:

[0077] First, read the historical phase track carrier and the historical micro-mist latent cold phase track bodies used to form the historical phase track carrier, and then read the carrier position of each historical three-dimensional state point P that it migrated into one by one.

[0078] For each historical 3D state point P, calculate the spatial distance between it and the historical 3D state position of the incoming carrier position, and form a 3D state position deviation sequence from all spatial distances; calculate the interval between the fog delivery process position of the current historical 3D state point P and the fog delivery process position of the incoming carrier position, and form a fog delivery process deviation sequence from all intervals; read the winding direction of the current historical 3D state point P and the historical main winding direction of the incoming carrier position, record zero when the directions are the same and one when the directions are opposite, and form a winding direction deviation sequence from all records.

[0079] The medians of the three-dimensional state position deviation sequence, the fog delivery process deviation sequence, and the winding direction deviation sequence are read respectively. Then, the absolute difference between each value in each sequence and its own median is calculated, and the median of the absolute difference is calculated to form the three-dimensional state position discrete quantity, the fog delivery process discrete quantity, and the winding direction discrete quantity in turn.

[0080] The reciprocals of the three discrete quantities are taken respectively, so that the processing portions with more concentrated changes in historical records receive a larger share of participation, while the processing portions with more dispersed changes receive a smaller share of participation. Before the reciprocal calculation, the same small correction amount is added to the three discrete quantities. The small correction amount is one-thousandth of the smallest positive value among the three discrete quantities, and is only used to prevent calculation when the discrete quantity is zero.

[0081] Finally, divide each of the three reciprocals by the sum of the three reciprocals to obtain the three-dimensional state position transition weights. Fog delivery process migration weight and winding direction migration weight Make the sum of the three weights equal to one.

[0082] After obtaining the migration cost of all migration cells, the migration cost is converted into an initial migration share. The smaller the migration cost, the larger the initial migration share obtained by the current migration cell; the larger the migration cost, the smaller the initial migration share obtained by the current migration cell. These two adjustments are then repeatedly performed.

[0083] The first adjustment is based on each portion of the latent cooling winding mass in the current micro-mist latent cooling phase track body B, so that the sum of the current latent cooling winding mass allocated to each historical bearing position is equal to the current latent cooling winding mass.

[0084] The second adjustment uses the historical load mass of each historical phase track carrier as a benchmark to ensure that the latent cold winding mass moved into the current load position is distributed on the same scale as the historical load mass.

[0085] The two adjustments are performed alternately until the migration share obtained in two consecutive rounds no longer changes numerically, forming the migration allocation result of the latent cold winding mass between the current three-dimensional state point P and the historical bearing position. A preliminary assessment is then performed on the current micro-mist latent cold phase track body B. This assessment does not output a simple category, but instead retains the specific migration process of each latent cold winding mass, including:

[0086] The original sampling location where the current latent cooling winding quality is located;

[0087] The historical bearing position of the current latent cooling winding mass migration;

[0088] The migration proportion allocated to each historical location;

[0089] The migration span between the original fog delivery process location and the new fog delivery process location;

[0090] The directional transfer amount formed when the current winding direction moves into the historical main winding direction;

[0091] The residual mass that falls after the bearing position at the end of the historical phase track carrier.

[0092] The above migration information is arranged according to three dimensions: "current sampling location - historical carrying location - migration attribute" to obtain the phase track quality migration tensor.

[0093] Preferably, the latent cooling refrigeration quotient spectrum generation module includes a latent cooling mass temporal expansion unit and a latent cooling quotient conversion unit;

[0094] The latent cooling mass time-position expansion unit reads each latent cooling winding mass in the micro-mist latent cooling phase track body B, as well as the original sampling position, migration bearing position, migration ratio and migration span recorded in the phase track mass migration tensor. Starting from the current sampling period, it sequentially forms the current time position and several subsequent time positions according to a fixed period.

[0095] Then, the bearing position in the historical phase track carrier is converted into a time position;

[0096] Among them, the latently cooled winding mass whose relocation position is after the original position is allocated to the subsequent time position, while the latently cooled winding mass whose relocation position is before the original position is retained at the current time position.

[0097] Based on the migration ratio in the phase-track mass migration tensor, each portion of latent cold winding mass is allocated to different time positions to form latent cold accumulation. The formula is: ;

[0098] In the formula, Specifically, this represents the latent cold accumulation amount in the (k+a)th sampling period, where 'a' represents the number of sampling periods extending backward relative to the current sampling period, and 'mki' represents the i-th latent cold winding mass in the micro-mist latent cold phase track. This represents the proportion of the i-th latently cooled winding mass that has migrated to the r-th time position;

[0099] The migration ratio is obtained as follows:

[0100] First, read the migration cost between each portion of the latent cold winding mass and each historical bearing position in the phase track mass migration tensor. The smaller the migration cost, the more suitable the current latent cold winding mass is for migrating to the current historical bearing position, and therefore a larger migration share is allocated; the larger the migration cost, the smaller the migration share is allocated.

[0101] Each migration cost is reverse-converted to obtain a larger initial migration share for a smaller migration cost, and then the initial migration shares of the same latent cold winding mass at each historical bearing position are added together.

[0102] Finally, the initial migration share of each historical bearing location is divided by the sum of the above shares to obtain the migration ratio of the current latently cooled winding mass to the current historical bearing location. After processing, the sum of the migration ratios of the same latently cooled winding mass allocated to each historical bearing location is 1;

[0103] When the historical bearing position is after the current fog delivery process position, the current migration ratio is used to allocate the latent cooling winding mass to subsequent sampling periods; when the historical bearing position is at the same position as or before the current fog delivery process position, the current migration ratio is used to retain the latent cooling winding mass in the current sampling period.

[0104] When the sum of the migration proportions of a latently cooled winding mass allocated to each time position is less than one, the unallocated latently cooled winding mass will continue to be delivered along the current migration span.

[0105] When the assigned position exceeds the end of the fog delivery period, the excess portion is recorded as the residual latent cold accumulation amount; the latent cold accumulation amount, residual latent cold accumulation amount, and migration span at each time position are combined to form the latent cold time position expansion sequence.

[0106] Preferably, the latent cooling occupancy conversion unit reads the latent cooling time-position unfolding sequence and dynamic cooling capacity;

[0107] The dynamic cooling capacity follows the cooling demand calculated by the central intelligent control unit based on the actual temperature and the target temperature, and is arranged according to the time position in the latent cooling time position unfolding sequence;

[0108] The system reads the latent cold accumulation during historical humidification processes, as well as the cooling capacity reduction due to heat absorption by micro-mist evaporation during the same sampling period. It repeatedly adjusts the conversion coefficient to make the cooling capacity reduction calculated from historical latent cold accumulation close to the historical data, thus obtaining the correct conversion coefficient. The latent cooling ration for each sampling period is calculated using the following formula:

[0109] ;

[0110] In the formula, This represents the proportion of dynamic cooling capacity undertaken by micro-mist evaporation heat absorption during the (k+a)th sampling period (the value is between zero and one). Represents an exponential function;

[0111] The latent cooling refrigeration quota, the location of the residual latent cooling accumulation, and the location of the fog delivery evaporation delay in each sampling period are arranged in chronological order to form the latent cooling refrigeration quota spectrum C.

[0112] Read the latent cooling quotient in the latent cooling quotient spectrum C one by one, and calculate it with the dynamic cooling capacity in the same sampling period to obtain the quotient-corrected dynamic cooling capacity RQ, as shown in the following formula:

[0113] ;

[0114] In the formula, This represents the dynamic cooling capacity during the (k+a)th sampling period.

[0115] Preferably, the quota trajectory comprehensive evaluation execution module includes a dual-track replay unit and a quota trajectory adjudication unit;

[0116] The homogeneous dual-track replay unit reads the latent cooling spectral density C, dynamic cooling capacity, and dynamic cooling capacity RQ after spectral correction.

[0117] From historical continuous sampling records, extract the actual temperature and humidity of the previous sampling period, the dynamic cooling capacity, compressor operating frequency and electronic expansion valve opening of the current sampling period, and the actual temperature and humidity of the next sampling period to form state transition samples; based on each state transition sample, obtain the short-term effect relationship between changes in cooling capacity and changes in control actions on temperature and humidity in the next sampling period.

[0118] Using the current actual temperature and humidity as common starting conditions, and assuming that the pressure value and the fog delivery process remain unchanged, two trajectory reenactments are performed:

[0119] The first method uses the dynamic cooling capacity within the coverage period of the latent cooling spectral C to calculate the actual temperature, actual humidity, compressor operating frequency, and electronic expansion valve opening hourly, forming the original refrigeration operation trajectory.

[0120] The second method uses the dynamic cooling capacity after quota correction within the same time period, and retains the cooling share undertaken by micro-mist evaporation in each sampling period according to the latent cooling quota spectrum C, forming the latent cooling quota operation trajectory.

[0121] The quota trajectory command unit calculates the comprehensive trajectory cost J of the two operating trajectories based on the original refrigeration operating trajectory and the latent cooling quota operating trajectory, as follows:

[0122] ;

[0123] In the formula, Indicates temperature deviation. Indicates humidity deviation. This indicates the change in the compressor's operating frequency. This indicates the change in the opening degree of the electronic expansion valve. and These represent the weighting of the compressor operating frequency and the weighting of the electronic expansion valve opening, respectively.

[0124] The temperature deviation is obtained by reading the original refrigeration operation trajectory and the latent cooling capacity operation trajectory for each sampling period, subtracting the target temperature from each, and recording the difference as the temperature deviation of the current operation trajectory in the current sampling period. A positive difference indicates that the calculated temperature is higher than the target temperature, and a negative difference indicates that the calculated temperature is lower than the target temperature.

[0125] The humidity deviation is obtained by reading the humidity calculated for each of the two operating trajectories at each sampling time period, subtracting the target humidity from each, and recording the difference as the humidity deviation of the current operating trajectory at the current sampling time period. The difference is retained in both positive and negative directions, and is subsequently squared for use in the comprehensive trajectory evaluation.

[0126] The compressor operating frequency weight ηf is obtained by reading the compressor operating frequency change, electronic expansion valve opening change, actual temperature change and actual humidity change in adjacent sampling periods in the historical operation record; firstly, the duplicate part of the compressor operating frequency change that changes synchronously with the electronic expansion valve opening is removed; then, the effect of the remaining compressor operating frequency change on the subsequent temperature and humidity changes is calculated; and the effect of all historical sampling periods is accumulated to form the total compressor action effect.

[0127] The method for obtaining the electronic expansion valve opening weight ηa is as follows: remove the repeated part that changes synchronously with the compressor operating frequency from the electronic expansion valve opening change, then count the effect of the remaining electronic expansion valve opening change on subsequent temperature and humidity changes, and sum up the effect of all historical sampling periods to form the total action of the electronic expansion valve.

[0128] Finally, using the sum of the total action of the compressor and the total action of the electronic expansion valve as the allocation benchmark, the proportions of the two are calculated respectively, and the compressor operating frequency weight ηf and the electronic expansion valve opening weight ηa are obtained in sequence, and the sum of the two weights is equal to one.

[0129] A final comprehensive evaluation will be performed on the original refrigeration operation trajectory and the latent cooling capacity operation trajectory:

[0130] When the comprehensive trajectory cost of the pre-cooling rated operating trajectory is less than the original refrigeration operating trajectory, a pre-cooling rated execution command is output to control the number of compressor heads, compressor operating frequency and electronic expansion valve opening to operate according to the rated corrected dynamic cooling capacity RQ.

[0131] When the latent cooling occupancy spectrum C extends to the sampling period after the ultrasonic oscillation frequency returns to zero, the remaining occupancy continuation instruction is output based on the latent cooling occupancy execution instruction, and the latent cooling occupancy that has not yet ended in the latent cooling occupancy spectrum C is continued to be called until the remaining latent cooling accumulation is exhausted.

[0132] When the comprehensive trajectory cost of the original refrigeration operation trajectory is not greater than the latent cooling capacity of the operation trajectory, the original refrigeration trajectory execution command is output to control the number of compressor heads, compressor operating frequency and electronic expansion valve opening according to the dynamic cooling capacity DQ.

[0133] A smart energy control method for a refrigeration testing laboratory includes the following steps:

[0134] Step 1: The enthalpy and humidity scale sequence module collects the actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening and dynamic cooling capacity, calculates the moisture content HS and the enthalpy value of humid air ZHD, and after scale conversion and cooling action projection stripping, forms the enthalpy and humidity residue of the de-cooling and the fog delivery action sequence.

[0135] Step 2: The micro-mist latent cooling phase track weaving module obtains the fog delivery evaporation delay position based on the fog delivery action sequence and the enthalpy moisture residue of the decooling, constructs a three-dimensional state point P, and calculates the latent cooling winding mass to form the micro-mist latent cooling phase track body B.

[0136] Step 3: The Phase Track Quality Migration Preliminary Assessment Module conducts a preliminary assessment of the micro-mist latent cooling phase track body B and the historical phase track quality centroid, forming the phase track quality migration tensor.

[0137] Step 4: The latent cooling occupancy spectrum generation module allocates the latent cooling winding mass to the current and subsequent sampling periods based on the phase track mass migration tensor, forming the latent cooling occupancy spectrum C, and obtains the dynamic cooling capacity RQ after occupancy correction.

[0138] Step 5: The quota trajectory comprehensive evaluation execution module respectively deduces the dynamic cooling capacity operation trajectory and the dynamic cooling capacity RQ operation trajectory after quota correction. After comprehensive evaluation, it outputs the latent cooling quota execution command, the residual quota continuation command and the original cooling trajectory execution command.

[0139] This invention provides an intelligent energy control method and system for a refrigeration testing laboratory, which has the following beneficial effects:

[0140] (1) During system operation, the current latent cooling winding mass is transferred and registered with the historical latent cooling phase track of the micro-mist through the phase track mass migration tensor, and the latent cooling winding mass is allocated to the current and subsequent sampling periods to form the latent cooling occupancy spectrum C. Based on the latent cooling occupancy spectrum C, the dynamic cooling capacity is deducted to obtain the occupancy-corrected dynamic cooling capacity RQ, so that the cooling share already undertaken by micro-mist evaporation is no longer redistributed to the compressor. This helps to suppress situations where the laboratory temperature is lower than the target temperature, humidity changes repeatedly, and the compressor operating frequency and electronic expansion valve opening are frequently adjusted.

[0141] (2) Normalize the moisture content (HS), enthalpy of moist air (ZHD), and various energy operation data, and construct an enthalpy-humidity refrigeration sequence and a mist delivery sequence according to a unified sampling order. After this processing, data with different units and numerical ranges can participate in subsequent processing within the same computational scale, preventing the pressure value, operating frequency, valve opening, and other parameters from having an unbalanced impact on the analysis results due to differences in numerical ranges, while preserving the change order of refrigeration and mist delivery actions on the time axis.

[0142] (3) The common distribution of fog delivery effect and evaporation endothermic response is statistically analyzed using the equal frequency interval, and the dependence of the two at different delay positions is described by the time-series traction quantity. The current processing does not limit the fog delivery effect and evaporation endothermic response quantity to be linearly changing, and can retain the nonlinear traction characteristics between ultrasonic oscillation frequency, air delivery speed and enthalpy-moisture residue; then, multiple fog delivery action sequences after movement are weighted and superimposed to form a fog delivery traction sequence, so that the early fog delivery action can still retain the corresponding traction share at the subsequent sampling position, which is suitable for describing the micro-mist delivery, suspension and evaporation process that continues to exist after fog delivery stops.

[0143] (4) When the fog delivery process position falls between two adjacent bearing positions, the latent cold winding mass is split according to the position distance, while maintaining the total latent cold winding mass before and after the split unchanged; at the same time, the latent cold winding mass entering the same bearing position is used as the calculation weight for the three-dimensional state position and winding direction. The current processing can prevent ordinary averaging from weakening the trajectory part of the latent cold winding mass concentration, and can also retain the actual participation share of different winding directions in historical operation, so that the historical three-dimensional state position, historical bearing mass and historical main winding direction can reflect the change law of the latent cold state of the fog with the fog delivery process. Attached Figure Description

[0144] Figure 1 This is a schematic diagram of the energy intelligent control system for a refrigeration testing laboratory according to the present invention.

[0145] Figure 2 This is a schematic diagram illustrating the steps of an intelligent energy control method for a refrigeration testing laboratory according to the present invention. Detailed Implementation

[0146] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0147] Example 1

[0148] This invention provides an intelligent energy control system for a refrigeration testing laboratory. Please refer to [link / reference]. Figure 1 It includes an enthalpy-humidity scale sequencing module, a micro-mist latent cooling phase track weaving module, a phase track quality migration preliminary evaluation module, a latent cooling quota spectrum generation module, and a quota trajectory comprehensive evaluation execution module;

[0149] The enthalpy and humidity scale sequencing module collects actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening and dynamic cooling capacity, calculates moisture content HS and enthalpy value ZHD of humid air, and forms the enthalpy and humidity residue of de-cooling and fog delivery action sequence after scale conversion and refrigeration action projection stripping.

[0150] The micro-mist latent cooling phase track weaving module obtains the fog delivery evaporation delay position based on the fog delivery action sequence and the enthalpy moisture residue of the decooling, constructs a three-dimensional state point P, and calculates the latent cooling winding mass to form the micro-mist latent cooling phase track body B.

[0151] The phase track quality migration preliminary assessment module will conduct a preliminary assessment of the micro-mist latent cooling phase track body B and the historical phase track quality centroid, and form a phase track quality migration tensor.

[0152] The latent cooling occupancy spectrum generation module allocates the latent cooling winding mass to the current and subsequent sampling periods based on the phase track mass migration tensor, forming the latent cooling occupancy spectrum C, and obtains the dynamic cooling capacity RQ after occupancy correction;

[0153] The quota trajectory comprehensive evaluation and execution module respectively deduce the dynamic cooling capacity operation trajectory and the dynamic cooling capacity RQ operation trajectory after quota correction, and outputs the latent cooling quota execution command, the residual quota continuation command and the original cooling trajectory execution command after comprehensive evaluation.

[0154] In this embodiment, the enthalpy-humidity scale sequencing module converts actual temperature, actual humidity, pressure values, and refrigeration equipment operating data into enthalpy-humidity change results under a unified sampling order. Furthermore, the effects of compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity on enthalpy-humidity changes are stripped away using refrigeration action projection, resulting in a de-refrigeration enthalpy-humidity residual. This allows the changes in moisture content and air thermal state caused by micro-mist evaporation to be separated from the refrigeration equipment's action, solving the problem of existing control methods that mix refrigeration action with micro-mist latent cooling action in calculations, and establishing a data foundation for subsequent calculations of the latent cooling share.

[0155] By analyzing the time delay between the generation, transport, and evaporation heat absorption of micro-mist through the mist delivery sequence and the residual enthalpy of evaporation, and constructing a micro-mist latent cooling phase trajectory using three-dimensional state points, latent cooling winding mass, and mist delivery traction, this method not only describes the latent cooling effect of micro-mist during the operation of ultrasonic humidifiers but also preserves the residual latent cooling effect formed by the continued transport, suspension, and evaporation of previously generated micro-mist after the ultrasonic oscillation frequency returns to zero. This overcomes the inadequacy of judging the micro-mist effect period solely based on the real-time operating status of the humidifier.

[0156] The dynamic cooling capacity operation trajectory and the dynamic cooling capacity RQ operation trajectory after quota correction were respectively derived and compared by comprehensively considering temperature deviation, humidity deviation, and changes in refrigeration equipment operation. Based on the comparison results, the latent cooling quota execution command, the residual quota continuation command, or the original refrigeration trajectory execution command are output. When the latent cooling effect of the micro-mist is suitable for meeting the refrigeration demand, the refrigeration control mode after quota correction is adopted. When the mist delivery stops but the residual latent cooling has not ended, the latent cooling quota continues to be carried out. When the latent cooling quota is not suitable for the current operating conditions, the original refrigeration trajectory is restored. This helps to control the temperature and humidity fluctuations in the laboratory and reduce the energy consumption caused by repeated refrigeration.

[0157] Example 2

[0158] Please refer to Figure 1 Specifically: the enthalpy-humidity scale sequencing module includes an enthalpy-humidity simultaneous conversion unit and a cooling trace stripping unit;

[0159] The enthalpy-humidity conversion unit reads the actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening degree, and dynamic cooling capacity according to a fixed sampling period.

[0160] When the collection times of various data are inconsistent, the sampling time is made up by matching two adjacent sampling values ​​to form a synchronous energy collection group, and the moisture content HS and the enthalpy of moist air ZHD are calculated and obtained, as follows:

[0161] ;

[0162] ;

[0163] In the formula, This represents a decimal value derived from the actual humidity. This represents the saturated water vapor pressure at the current actual temperature;

[0164] The moisture content (HS), enthalpy of moist air (ZHD), and energy acquisition group at the same time are normalized to eliminate the dimensions of the data. The normalized moisture content (HS), enthalpy of moist air (ZHD), compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity are arranged according to the sampling order to form an enthalpy-humidity cooling sequence.

[0165] The processed ultrasonic oscillation frequency and air delivery speed are arranged in the same sampling order to form a complete sequence of fog delivery actions.

[0166] The cooling trace stripping unit reads the enthalpy-humidity cooling sequence and the fog delivery action sequence, calculates the change in moisture content (HS) and the change in enthalpy of moist air (ZHD) between adjacent sampling locations, and forms the enthalpy-humidity change sequence.

[0167] The compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity are read from the current sampling position, the previous sampling position, and the two previous sampling positions respectively to form a cooling action trace;

[0168] The repeated actions carried in the refrigeration action trace are removed one by one, so that the compressor operating frequency change, electronic expansion valve opening change and dynamic refrigeration capacity change each retain their independent function;

[0169] By projecting the enthalpy-humidity change sequence using the independent action component, the amount of enthalpy-humidity change caused by the cooling action can be obtained;

[0170] Subtract the enthalpy and humidity change caused by the refrigeration action from the enthalpy and humidity change sequence to form the enthalpy and humidity residue after refrigeration.

[0171] The enthalpy-humidity residue after cooling is obtained by the difference between the change in moisture content (HS) and the change in enthalpy (ZHD) of moist air at the current sampling location and the enthalpy-humidity change explained by the cooling action trace.

[0172] The enthalpy-humidity residue after cooling includes the moisture content (HS residue) and the enthalpy value (ZHD residue) of moist air;

[0173] Multiply the ultrasonic oscillation frequency and the air delivery speed in the entire fog delivery sequence to obtain the continuous fog delivery effect; then read the changes between the two at adjacent sampling positions to characterize the transition in fog generation intensity and the transition in fog delivery intensity, respectively; arrange the continuous fog delivery effect, the transition in fog generation intensity, the transition in fog delivery intensity, and the sampling order together to form the fog delivery action sequence.

[0174] In this embodiment, actual temperature, actual humidity, pressure, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity are simultaneously processed according to a fixed sampling period. Adjacent sampling values ​​are used to fill in data from different sampling times, ensuring that the operating data from different sensors and control devices fall into a unified sampling location. Based on the actual temperature, humidity, and pressure values, the moisture content (HS) and enthalpy of moist air (ZHD) are calculated, converting temperature and humidity states into air moisture content and thermal state parameters, facilitating the analysis of enthalpy and humidity changes caused by micro-mist entering the laboratory.

[0175] Based on the compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity at the current sampling location, the previous sampling location, and the two sampling locations prior to that, a cooling action trace is constructed, and the repeated variations between each cooling action are subtracted. By projecting the independent effects of each cooling action onto the enthalpy-humidity change sequence, the effects caused by compressor refrigeration and electronic expansion valve regulation can be separated from the changes in moisture content (HS) and enthalpy of moist air (ZHD). The residual moisture content (HS) and enthalpy of moist air (ZHD) are obtained, providing an independent data basis for identifying the enthalpy-humidity response caused by micro-mist evaporation and overcoming the problem of mixed calculation of refrigeration and latent cooling effects of micro-mist.

[0176] The product of the ultrasonic oscillation frequency and the air delivery speed was used as the continuous mist delivery effect. Combining the changes in both between adjacent sampling locations, the transitions in mist generation intensity and mist delivery intensity were recorded separately. This mist delivery sequence not only records the continuous operating status of the ultrasonic humidifier during each sampling period but also records the changes in action during mist delivery startup, adjustment, and shutdown. This provides a basis for subsequent analysis of the time delay between mist generation, delivery, and evaporative heat absorption, as well as for identifying the residual latent cooling effect after mist delivery stops.

[0177] Example 3

[0178] Please refer to Figure 1 Specifically: the micro-mist latent cooling phase track weaving module includes a fog delivery delay traction analysis unit and a latent cooling phase track winding weaving unit;

[0179] The fog delivery delay traction analysis unit reads the fog delivery action sequence and the moisture content (HS residual) and humid air enthalpy (ZHD residual) in the decooling enthalpy moisture residual;

[0180] The positive component formed by the increase in water vapor content is retained in the moisture content (HS) residue, and the negative component formed by the decrease in air enthalpy is retained in the moisture air enthalpy (ZHD) residue;

[0181] The two components are combined according to the sampling order to form an evaporative endothermic response sequence;

[0182] Several consecutive delay positions are set within a fixed period: for each selected delay position, the fog delivery sequence is shifted backward by the corresponding number of samples and then overlapped with the evaporation endothermic response sequence.

[0183] Based on their respective data distributions, the shifted fog delivery effect and evaporative heat absorption response are divided into several equal-frequency intervals. The proportion of both data points falling into each interval combination is statistically analyzed, and the time-series traction Ir at the current delay position is calculated using the following formula:

[0184] ;

[0185] In the formula, This indicates the proportion of the combined occurrence of the shifted fog delivery effect falling into the a-th equal-frequency interval and the evaporative endothermic response falling into the b-th equal-frequency interval. and These represent the proportions of each data point falling within the current interval, and r represents the delay position;

[0186] The acquired temporal traction quantity Ir is converted into delay allocation weights, and the fog delivery evaporation delay position re is formed by the weighted center of each delay position, as shown in the formula: ;

[0187] In the formula, Represents an exponential function;

[0188] Then, according to the delay allocation weights at each delay position, the moved fog delivery action sequence is weighted and superimposed to form a fog delivery traction sequence.

[0189] The latent cooling phase track winding braiding unit reads the fog delivery evaporation delay position, fog delivery traction sequence, and the moisture content (HS) and humid air enthalpy (ZHD) residual in the decooling enthalpy moisture residue.

[0190] When the fog evaporation delay position falls between two sampling positions, the residual moisture content HS is linearly interpolated based on the distance between the two sampling positions and the fog evaporation delay position to obtain the residual moisture content HS at the delay position. A three-dimensional state point P is then constructed for each sampling position, as shown in the following formula:

[0191] ;

[0192] In the formula, Pk represents the three-dimensional state point formed at the k-th sampling position. This represents the residual moisture content (HS) at the k-th sampling location. This represents the residual enthalpy of moist air (ZHD) at the k-th sampling location. express ;

[0193] Connect the three-dimensional state points P according to the sampling order, and calculate the directed volume Vk enclosed by the three state transition vectors, as shown in the following formula:

[0194] ;

[0195] In the formula, Vk specifically represents the directed winding volume at the k-th sampling position. This represents the three-dimensional state point formed at the (k-1)th sampling position. This represents the three-dimensional state point formed at the (k-2)th sampling position. Let represent the three-dimensional state point formed at the (k-3)th sampling position, and det represent the determinant of the third-order matrix composed of the three state transition vectors;

[0196] Read the fog delivery traction amount Gk at the current sampling position, multiply the absolute value of the directed winding volume by the fog delivery traction amount to form the latent cooling winding mass Mk at the current sampling position, as shown in the formula: ;

[0197] Arrange the three-dimensional state points P, latent cooling winding mass Mk, winding direction, fog delivery traction amount Gk, and fog delivery evaporation delay position according to the sampling order to form the micro-fog latent cooling phase track B.

[0198] In this embodiment, by shifting the mist delivery sequence to multiple consecutive delayed positions and performing overlap analysis with the evaporation endothermic response sequence, the temporal traction between the mist delivery effect and the enthalpy-humidity response can be extracted from multiple possible mist delivery-evaporation intervals. Then, the mist delivery-evaporation delay positions are formed using the assigned weights of each delay position. Compared to determining the mist delivery period solely based on the current start / stop status of the ultrasonic humidifier, this current processing can characterize the temporal misalignment between mist generation, air delivery, and the evaporation response, establishing a temporal basis for identifying the delayed latent cooling effect.

[0199] A three-dimensional state point P is constructed using the current residual moisture content (HS), the reverse component of the residual enthalpy of moist air (ZHD), and the change in residual moisture content (HS) within the fog evaporation delay range. These three-dimensional state points are then connected according to the sampling order to form the spatial evolution trajectory of the micro-fog latent cooling state. The directed volume enclosed by three continuous state migration vectors can simultaneously reflect the degree of joint change and the direction of rotation between moisture content change, enthalpy change, and moisture content expansion within the delay range. This overcomes the problem of difficulty in distinguishing between short-term fluctuations and continuous evaporation responses when describing the micro-fog latent cooling process based solely on a single temperature or humidity change.

[0200] The absolute value of the directional winding volume is multiplied by the fog delivery traction amount at the current sampling position to form the latent cooling winding mass. The three-dimensional state point P, the latent cooling winding mass, the winding direction, the fog delivery traction amount, and the fog delivery evaporation delay position are then combined in the sampling order to form the micro-mist latent cooling phase track body B. The current result retains the spatial expansion of the micro-mist latent cooling state while limiting the current expansion to be formed by the fog delivery traction, allowing the latent cooling effect to be continuously recorded according to the sampling position. This provides a unified data carrier for the subsequent migration, evaluation, and allocation of the latent cooling winding mass and historical phase track bearing state to the current and subsequent sampling periods.

[0201] Example 4

[0202] Please refer to Figure 1 Specifically: the phase track quality migration preliminary assessment module includes the historical phase track parallel bearing unit and the phase track quality migration preliminary assessment unit;

[0203] The historical phase track co-processing unit reads the historical micro-mist latent cold phase track bodies formed during multiple historical humidification processes; each historical micro-mist latent cold phase track body contains a three-dimensional state point P, latent cold winding mass, winding direction, fog delivery traction amount, and sampling order.

[0204] The fog delivery process position Sk is calculated based on the fog delivery traction amount at each sampling location, using the following formula:

[0205] ;

[0206] In the formula, Sk specifically represents the fog delivery process position of the kth sampling position, Gq represents the fog delivery traction amount of the qth sampling position in the fog delivery traction sequence, and N represents the total number of sampling positions contained in the current historical micro-fog latent cooling phase track.

[0207] Read the number of sampling locations contained in the entire historical micro-mist latent cooling phase track, and take the historical humidification process with the fewest sampling locations as the unified division basis to form several continuous bearing locations within the range of zero to one mist delivery process.

[0208] For each historical micro-fog latent cooling phase track, read the position of the fog delivery process where each latent cooling winding mass is located;

[0209] When the current fog delivery process position falls between two adjacent support positions, the current latent cooling winding mass is divided into two support positions according to its distance from the two support positions, and the total latent cooling winding mass after division remains unchanged.

[0210] The three-dimensional state point P and the winding direction are not directly averaged, but are weighted according to the latent cooling winding mass entering the same bearing position, and the three-dimensional state position and main winding direction of the current bearing position are calculated.

[0211] Thus, each historical micro-fog latent cooling phase track body is converted into a set of historical phase track carrier plates located on a unified fog delivery process;

[0212] Each historical phase track carrier piece is reversed from the unified carrier position to the original fog delivery process position, and the spatial deviation between the restored three-dimensional state point and the original three-dimensional state point is calculated.

[0213] According to the participation share, each historical phase track carrier piece is collected, and the historical three-dimensional state position, historical carrier mass and historical main winding direction are formed at each carrier position, and finally the historical phase track carrier body is formed.

[0214] The preliminary assessment unit for phase track quality migration reads the current micro-mist latent cooling phase track body B and the historical phase track carrier body;

[0215] Based on the current fog delivery traction in the micro-fog latent cooling phase track body B, and according to the processing method in the historical phase track co-path bearing unit, calculate the fog delivery process position of each three-dimensional state point P.

[0216] Each three-dimensional state point P in the current micro-mist latent cooling phase orbit body B is combined with each bearing position in the historical phase orbit bearing body to form a migration grid, and the migration cost of each migration grid is calculated. The formula is as follows:

[0217] ;

[0218] In the formula, This represents the g-th historical three-dimensional state position in the historical phase track carrier, Sg represents the fog delivery process position of the historical carrier position, dk represents the current winding direction, and dr represents the historical main winding direction. Represents the weights for 3D state position transitions. Indicates the migration weight of the fog delivery process. This indicates the weight of the roll-up direction migration, and ;

[0219] After obtaining the migration cost for all migration cells, convert the migration cost into the initial migration share, and repeatedly perform two adjustments:

[0220] The first adjustment is based on each portion of the latent cooling winding mass in the current micro-mist latent cooling phase track body B, so that the sum of the current latent cooling winding mass allocated to each historical bearing position is equal to the current latent cooling winding mass.

[0221] The second adjustment uses the historical load mass of each historical phase track carrier as a benchmark to ensure that the latent cold winding mass moved into the current load position is distributed on the same scale as the historical load mass.

[0222] The two adjustments are performed alternately until the migration share obtained in two consecutive rounds no longer changes numerically, forming the migration distribution result of the latent cold winding mass between the current three-dimensional state point P and the historical bearing position, and performing a preliminary evaluation on the current micro-mist latent cold phase track body B to obtain the phase track mass migration tensor.

[0223] In this embodiment, based on the cumulative proportion of fog delivery traction, historical micro-mist latent cooling phase tracks with different durations, sampling numbers, and fog delivery intensities are converted into a unified fog delivery process ranging from zero to one. Compared to directly superimposing historical trajectories according to sampling times, the current processing uses the actual progress of the fog delivery process as the bearing benchmark, which can eliminate the misalignment in duration and sampling position of different historical humidification processes. This allows the three-dimensional state point P and the latent cooling winding mass at the same fog delivery process stage to enter the same bearing position, facilitating the extraction of the common state structure in the historical micro-mist latent cooling process.

[0224] The historical phase track carrier plates under the unified fog delivery process are reversed and restored to their original fog delivery process positions. The participation share of each historical phase track carrier plate is allocated according to the spatial deviation between the restored three-dimensional state point and the original three-dimensional state point. Historical phase track carrier plates with smaller deviations after restoration receive a larger participation share, while historical phase track carrier plates with larger deviations receive a smaller participation share. This can suppress the interference of occasional temperature and humidity fluctuations, abnormal fog delivery actions, or single operational deviations on the historical phase track carrier, allowing the historical phase track carrier to retain a relatively stable latent cooling winding structure.

[0225] The current 3D state point P is combined with each historical bearing position to form a migration grid. The migration cost is calculated by comprehensively considering the differences in 3D state positions, the span of the fog delivery process, and the change in winding direction. Then, through two alternating adjustments, each current latent cooling winding mass is fully allocated, while ensuring that the migration mass received by each historical bearing position is adapted to the historical bearing mass. The resulting phase track mass migration tensor can record the original sampling position, the incoming bearing position, the migration ratio, and the migration span of each latent cooling winding mass. This provides a time-position basis for subsequently allocating the latent cooling effect of the micro-fog to the current and subsequent sampling periods, and addresses the problem that existing control methods cannot continuously utilize the latent cooling effect of the fog delivery tail.

[0226] Example 5

[0227] Please refer to Figure 1 Specifically: the latent cooling refrigeration quotient spectrum generation module includes a latent cooling mass temporal expansion unit and a latent cooling quotient conversion unit;

[0228] The latent cooling mass time-position expansion unit reads each latent cooling winding mass in the micro-mist latent cooling phase track body B, as well as the original sampling position, migration bearing position, migration ratio and migration span recorded in the phase track mass migration tensor. Starting from the current sampling period, it sequentially forms the current time position and several subsequent time positions according to a fixed period.

[0229] Then, the bearing position in the historical phase track carrier is converted into a time position;

[0230] Based on the migration ratio in the phase-track mass migration tensor, each portion of latent cold winding mass is allocated to different time positions to form latent cold accumulation. The formula is: ;

[0231] In the formula, Specifically, this represents the latent cold accumulation amount in the (k+a)th sampling period, where 'a' represents the number of sampling periods extending backward relative to the current sampling period, and 'mki' represents the i-th latent cold winding mass in the micro-mist latent cold phase track. This represents the proportion of the i-th latently cooled winding mass that has migrated to the r-th time position;

[0232] When the sum of the migration proportions of a latently cooled winding mass allocated to each time position is less than one, the unallocated latently cooled winding mass will continue to be delivered along the current migration span.

[0233] When the assigned position exceeds the end of the fog delivery period, the excess portion is recorded as the residual latent cold accumulation amount; the latent cold accumulation amount, residual latent cold accumulation amount, and migration span at each time position are combined to form the latent cold time position expansion sequence.

[0234] The latent cooling occupancy conversion unit reads the latent cooling time-position expansion sequence and dynamic cooling capacity;

[0235] The system reads the latent cold accumulation during historical humidification processes, as well as the cooling capacity reduction due to heat absorption by micro-mist evaporation during the same sampling period. It repeatedly adjusts the conversion coefficient to make the cooling capacity reduction calculated from historical latent cold accumulation close to the historical data, thus obtaining the correct conversion coefficient. The latent cooling ration for each sampling period is calculated using the following formula:

[0236] ;

[0237] In the formula, This represents the proportion of dynamic cooling capacity undertaken by heat absorption through micro-mist evaporation during the (k+a)th sampling period. Represents an exponential function;

[0238] The latent cooling refrigeration quota, the location of the residual latent cooling accumulation, and the location of the fog delivery evaporation delay in each sampling period are arranged in chronological order to form the latent cooling refrigeration quota spectrum C.

[0239] Read the latent cooling quotient in the latent cooling quotient spectrum C one by one, and calculate it with the dynamic cooling capacity in the same sampling period to obtain the quotient-corrected dynamic cooling capacity RQ, as shown in the following formula:

[0240] ;

[0241] In the formula, This represents the dynamic cooling capacity during the (k+a)th sampling period.

[0242] The quota trajectory comprehensive evaluation execution module includes a dual-track simulation unit and a quota trajectory adjudication unit;

[0243] The homogeneous dual-track replay unit reads the latent cooling spectral density C, dynamic cooling capacity, and dynamic cooling capacity RQ after spectral correction.

[0244] From historical continuous sampling records, extract the actual temperature and humidity of the previous sampling period, the dynamic cooling capacity, compressor operating frequency and electronic expansion valve opening of the current sampling period, and the actual temperature and humidity of the next sampling period to form state transition samples; based on each state transition sample, obtain the short-term effect relationship between changes in cooling capacity and changes in control actions on temperature and humidity in the next sampling period.

[0245] Using the current actual temperature and humidity as common starting conditions, and assuming that the pressure value and the fog delivery process remain unchanged, two trajectory reenactments are performed:

[0246] The first method uses the dynamic cooling capacity within the coverage period of the latent cooling spectral C to calculate the actual temperature, actual humidity, compressor operating frequency, and electronic expansion valve opening hourly, forming the original refrigeration operation trajectory.

[0247] The second method uses the dynamic cooling capacity after quota correction within the same time period, and retains the cooling share undertaken by micro-mist evaporation in each sampling period according to the latent cooling quota spectrum C, forming the latent cooling quota operation trajectory.

[0248] The quota trajectory command unit calculates the comprehensive trajectory cost J of the two operating trajectories based on the original refrigeration operating trajectory and the latent cooling quota operating trajectory, as follows:

[0249] ;

[0250] In the formula, Indicates temperature deviation. Indicates humidity deviation. This indicates the change in the compressor's operating frequency. This indicates the change in the opening degree of the electronic expansion valve. and These represent the weighting of the compressor operating frequency and the weighting of the electronic expansion valve opening, respectively.

[0251] A final comprehensive evaluation will be performed on the original refrigeration operation trajectory and the latent cooling capacity operation trajectory:

[0252] When the overall trajectory cost of the latent cooling occupancy operation trajectory is less than that of the original refrigeration operation trajectory, the latent cooling occupancy execution command is output.

[0253] When the latent cooling occupancy spectrum C extends to the sampling period after the ultrasonic oscillation frequency returns to zero, the remaining occupancy continuation instruction is output based on the latent cooling occupancy execution instruction, and the latent cooling occupancy that has not yet ended in the latent cooling occupancy spectrum C is continued to be called until the remaining latent cooling accumulation is exhausted.

[0254] When the overall trajectory cost of the original refrigeration operation trajectory is not greater than the latent cooling quota operation trajectory, the original refrigeration trajectory execution command is output.

[0255] In this embodiment, based on the original sampling position, the incoming bearing position, the migration ratio, and the migration span recorded in the phase track mass migration tensor, each portion of latent cold winding mass is unfolded to the current and subsequent sampling periods, forming a latent cold time-position unfolding sequence. Compared to the method of processing the effect of micro-mist only based on the current operating status of the ultrasonic humidifier, the current processing can record the delayed release process of the latent cold effect of micro-mist on the time axis, and record the latent cold winding mass that continues to evaporate and absorb heat after the mist delivery ends as the residual latent cold accumulation amount, solving the problem of omission of residual effect caused by the termination of latent cold calculation when the mist delivery stops.

[0256] A conversion coefficient is obtained based on the relationship between historical latent cold accumulation and the share of cooling decline in dynamic cooling capacity. The latent cold accumulation in each sampling period is converted into a latent cold cooling quota, forming a latent cold cooling quota spectrum C. The latent cold cooling quota gradually approaches saturation as the latent cold accumulation increases, which limits the latent cold cooling quota to between zero and one, preventing the converted result from exceeding the current dynamic cooling capacity when the latent cold accumulation is large. Then, the cooling share undertaken by micro-mist evaporation is deducted from the dynamic cooling capacity to obtain the quota-corrected dynamic cooling capacity RQ, so that the latent cold effect of micro-mist and the cooling effect of compressors undertake the cooling demand separately according to the sampling period, preventing the same cooling effect from being counted repeatedly.

[0257] Using the same actual temperature, humidity, pressure, and mist delivery process as common starting conditions, the operating trajectory is reenacted using both dynamic cooling capacity and the pre-calculated dynamic cooling capacity RQ, resulting in the original refrigeration operating trajectory and the latent cooling pre-calculated operating trajectory. The two operating trajectories employ the same state transition relationship and simulation duration, limiting the trajectory differences to the introduction of the latent cooling pre-calculated capacity. Furthermore, the comprehensive trajectory cost is calculated by combining temperature deviation, humidity deviation, compressor operating frequency changes, and electronic expansion valve opening changes. This ensures that the selection of the refrigeration trajectory considers not only temperature and humidity deviations but also the operational impact of frequent changes in refrigeration equipment operation.

[0258] Based on the combined trajectory cost of the two operating trajectories, the system outputs either a latent cooling capacity execution command or the original refrigeration trajectory execution command. When the ultrasonic oscillation frequency returns to zero but the remaining latent cooling capacity has not yet been exhausted, a residual capacity continuation command is output. The current command mode allows operation according to the dynamically adjusted refrigeration capacity when the latent cooling capacity trajectory is suitable for the current temperature and humidity conditions. During the residual evaporation phase, the remaining latent cooling capacity is deducted. When the latent cooling capacity trajectory is unsuitable for the current operating conditions, the original refrigeration operating trajectory is used. This helps suppress temperatures below the target temperature, repeated humidity changes, frequent adjustments to the compressor operating frequency and electronic expansion valve opening, and reduces energy consumption from repeated refrigeration.

[0259] Example 6

[0260] Please refer to Figure 2 Specifically: An intelligent energy control method for a refrigeration testing laboratory, comprising the following steps:

[0261] Step 1: The enthalpy and humidity scale sequence module collects the actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening and dynamic cooling capacity, calculates the moisture content HS and the enthalpy value of humid air ZHD, and after scale conversion and cooling action projection stripping, forms the enthalpy and humidity residue of the de-cooling and the fog delivery action sequence.

[0262] Step 2: The micro-mist latent cooling phase track weaving module obtains the fog delivery evaporation delay position based on the fog delivery action sequence and the enthalpy moisture residue of the decooling, constructs a three-dimensional state point P, and calculates the latent cooling winding mass to form the micro-mist latent cooling phase track body B.

[0263] Step 3: The Phase Track Quality Migration Preliminary Assessment Module conducts a preliminary assessment of the micro-mist latent cooling phase track body B and the historical phase track quality centroid, forming the phase track quality migration tensor.

[0264] Step 4: The latent cooling occupancy spectrum generation module allocates the latent cooling winding mass to the current and subsequent sampling periods based on the phase track mass migration tensor, forming the latent cooling occupancy spectrum C, and obtains the dynamic cooling capacity RQ after occupancy correction.

[0265] Step 5: The quota trajectory comprehensive evaluation execution module respectively deduces the dynamic cooling capacity operation trajectory and the dynamic cooling capacity RQ operation trajectory after quota correction. After comprehensive evaluation, it outputs the latent cooling quota execution command, the residual quota continuation command and the original cooling trajectory execution command.

[0266] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended technical solutions and their equivalents.

Claims

1. An intelligent energy control system for a refrigeration testing laboratory, characterized in that: It includes an enthalpy-humidity scale sequencing module, a micro-mist latent cooling phase track weaving module, a phase track quality migration preliminary evaluation module, a latent cooling quota spectrum generation module, and a quota trajectory comprehensive evaluation execution module; The enthalpy and humidity scale sequencing module collects actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening and dynamic cooling capacity, calculates moisture content HS and enthalpy value ZHD of humid air, and forms the enthalpy and humidity residue of de-cooling and fog delivery action sequence after scale conversion and refrigeration action projection stripping. The micro-mist latent cooling phase track weaving module obtains the fog delivery evaporation delay position based on the fog delivery action sequence and the enthalpy moisture residue of the decooling, constructs a three-dimensional state point P, and calculates the latent cooling winding mass to form the micro-mist latent cooling phase track body B. The phase track quality migration preliminary assessment module will conduct a preliminary assessment of the micro-mist latent cooling phase track body B and the historical phase track quality centroid, and form a phase track quality migration tensor. The latent cooling occupancy spectrum generation module allocates the latent cooling winding mass to the current and subsequent sampling periods based on the phase track mass migration tensor, forming the latent cooling occupancy spectrum C, and obtains the dynamic cooling capacity RQ after occupancy correction; The quota trajectory comprehensive evaluation and execution module respectively deduce the dynamic cooling capacity operation trajectory and the dynamic cooling capacity RQ operation trajectory after quota correction, and outputs the latent cooling quota execution command, the residual quota continuation command and the original cooling trajectory execution command after comprehensive evaluation.

2. The energy intelligent control system for a refrigeration testing laboratory according to claim 1, characterized in that: The enthalpy-humidity scale sequencing module includes an enthalpy-humidity simultaneous conversion unit and a cooling trace stripping unit; The enthalpy-humidity conversion unit reads the actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening degree, and dynamic cooling capacity according to a fixed sampling period. When the collection times of various data are inconsistent, the sampling time is made up by matching two adjacent sampling values ​​to form a synchronous energy collection group, and the moisture content HS and the enthalpy of moist air ZHD are calculated and obtained, as follows: ； ； In the formula, This represents a decimal value derived from the actual humidity. This represents the saturated water vapor pressure at the current actual temperature; The moisture content (HS), enthalpy of moist air (ZHD), and energy acquisition group at the same time are normalized to eliminate the dimensions of the data. The normalized moisture content (HS), enthalpy of moist air (ZHD), compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity are arranged according to the sampling order to form an enthalpy-humidity cooling sequence. The processed ultrasonic oscillation frequency and air delivery speed are arranged in the same sampling order to form a complete sequence of fog delivery actions. The cooling trace stripping unit reads the enthalpy-humidity cooling sequence and the fog delivery action sequence, calculates the change in moisture content (HS) and the change in enthalpy of moist air (ZHD) between adjacent sampling locations, and forms the enthalpy-humidity change sequence. The compressor operating frequency, electronic expansion valve opening, and dynamic cooling capacity are read from the current sampling position, the previous sampling position, and the two previous sampling positions respectively to form a cooling action trace; The repeated actions carried in the refrigeration action trace are removed one by one, so that the compressor operating frequency change, electronic expansion valve opening change and dynamic refrigeration capacity change each retain their independent function; By projecting the enthalpy-humidity change sequence using the independent action component, the amount of enthalpy-humidity change caused by the cooling action can be obtained; Subtract the enthalpy and humidity change caused by the refrigeration action from the enthalpy and humidity change sequence to form the enthalpy and humidity residue after refrigeration. The enthalpy-humidity residue after cooling is obtained by the difference between the change in moisture content (HS) and the change in enthalpy (ZHD) of moist air at the current sampling location and the enthalpy-humidity change explained by the cooling action trace. The enthalpy-humidity residue after cooling includes the moisture content (HS residue) and the enthalpy value (ZHD residue) of moist air; Multiply the ultrasonic oscillation frequency and the air delivery speed in the entire fog delivery sequence to obtain the continuous fog delivery effect; then read the changes between the two at adjacent sampling positions to characterize the transition in fog generation intensity and the transition in fog delivery intensity, respectively; arrange the continuous fog delivery effect, the transition in fog generation intensity, the transition in fog delivery intensity, and the sampling order together to form the fog delivery action sequence.

3. The energy intelligent control system for a refrigeration testing laboratory according to claim 2, characterized in that: The micro-mist latent cooling phase track braiding module includes a fog delivery delay traction analysis unit and a latent cooling phase track winding braiding unit; The fog delivery delay traction analysis unit reads the fog delivery action sequence and the moisture content (HS residual) and humid air enthalpy (ZHD residual) in the decooling enthalpy moisture residual; The positive component formed by the increase in water vapor content is retained in the moisture content (HS) residue, and the negative component formed by the decrease in air enthalpy is retained in the moisture air enthalpy (ZHD) residue; The two components are combined according to the sampling order to form an evaporative endothermic response sequence; Several consecutive delay positions are set within a fixed period: for each selected delay position, the fog delivery sequence is shifted backward by the corresponding number of samples and then overlapped with the evaporation endothermic response sequence. Based on their respective data distributions, the shifted fog delivery effect and evaporative heat absorption response are divided into several equal-frequency intervals. The proportion of both data points falling into each interval combination is statistically analyzed, and the time-series traction Ir at the current delay position is calculated using the following formula: ； In the formula, This indicates the proportion of the combined occurrence of the shifted fog delivery effect falling into the a-th equal-frequency interval and the evaporative endothermic response falling into the b-th equal-frequency interval. and These represent the proportions of each data point falling within the current interval, and r represents the delay position; The acquired temporal traction quantity Ir is converted into delay allocation weights, and the fog delivery evaporation delay position re is formed by the weighted center of each delay position, as shown in the formula: ; In the formula, Represents an exponential function; Then, according to the delay allocation weights at each delay position, the moved fog delivery action sequence is weighted and superimposed to form a fog delivery traction sequence.

4. The energy intelligent control system for a refrigeration testing laboratory according to claim 3, characterized in that: The latent cooling phase track winding braiding unit reads the fog delivery evaporation delay position, fog delivery traction sequence, and the moisture content (HS) and humid air enthalpy (ZHD) residual in the decooling enthalpy moisture residue. When the fog evaporation delay position falls between two sampling positions, the residual moisture content HS is linearly interpolated based on the distance between the two sampling positions and the fog evaporation delay position to obtain the residual moisture content HS at the delay position. A three-dimensional state point P is then constructed for each sampling position, as shown in the following formula: ； In the formula, Pk represents the three-dimensional state point formed at the k-th sampling position. This represents the residual moisture content (HS) at the k-th sampling location. This represents the residual enthalpy of moist air (ZHD) at the k-th sampling location. express ; Connect the three-dimensional state points P according to the sampling order, and calculate the directed volume Vk enclosed by the three state transition vectors, as shown in the following formula: ； In the formula, Vk specifically represents the directed winding volume at the k-th sampling position. This represents the three-dimensional state point formed at the (k-1)th sampling position. This represents the three-dimensional state point formed at the (k-2)th sampling position. Let represent the three-dimensional state point formed at the (k-3)th sampling position, and det represent the determinant of the third-order matrix composed of the three state transition vectors; Read the fog delivery traction amount Gk at the current sampling position, multiply the absolute value of the directed winding volume by the fog delivery traction amount to form the latent cooling winding mass Mk at the current sampling position, as shown in the formula: ; Arrange the three-dimensional state points P, latent cooling winding mass Mk, winding direction, fog delivery traction amount Gk, and fog delivery evaporation delay position according to the sampling order to form the micro-fog latent cooling phase track B.

5. The energy intelligent control system for a refrigeration testing laboratory according to claim 4, characterized in that: The phase track quality migration preliminary assessment module includes the historical phase track parallel bearing unit and the phase track quality migration preliminary assessment unit; The historical phase track co-processing unit reads the historical micro-mist latent cold phase track bodies formed during multiple historical humidification processes; each historical micro-mist latent cold phase track body contains a three-dimensional state point P, latent cold winding mass, winding direction, fog delivery traction amount, and sampling order. The fog delivery process position Sk is calculated based on the fog delivery traction amount at each sampling location, using the following formula: ； In the formula, Sk specifically represents the fog delivery process position of the kth sampling position, Gq represents the fog delivery traction amount of the qth sampling position in the fog delivery traction sequence, and N represents the total number of sampling positions contained in the current historical micro-fog latent cooling phase track. Read the number of sampling locations contained in the entire historical micro-mist latent cooling phase track, and take the historical humidification process with the fewest sampling locations as the unified division basis to form several continuous bearing locations within the range of zero to one mist delivery process. For each historical micro-fog latent cooling phase track, read the position of the fog delivery process where each latent cooling winding mass is located; When the current fog delivery process position falls between two adjacent support positions, the current latent cooling winding mass is divided into two support positions according to its distance from the two support positions, and the total latent cooling winding mass after division remains unchanged. The three-dimensional state point P and the winding direction are not directly averaged, but are weighted according to the latent cooling winding mass entering the same bearing position, and the three-dimensional state position and main winding direction of the current bearing position are calculated. Thus, each historical micro-fog latent cooling phase track body is converted into a set of historical phase track carrier plates located on a unified fog delivery process; Each historical phase track carrier piece is reversed from the unified carrier position to the original fog delivery process position, and the spatial deviation between the restored three-dimensional state point and the original three-dimensional state point is calculated. According to the participation share, each historical phase track carrier piece is collected, and the historical three-dimensional state position, historical carrier mass and historical main winding direction are formed at each carrier position, and finally the historical phase track carrier body is formed.

6. The energy intelligent control system for a refrigeration testing laboratory according to claim 5, characterized in that: The preliminary assessment unit for phase track quality migration reads the current micro-mist latent cooling phase track body B and the historical phase track carrier body; Based on the current fog delivery traction in the micro-fog latent cooling phase track body B, and according to the processing method in the historical phase track co-path bearing unit, calculate the fog delivery process position of each three-dimensional state point P. Each three-dimensional state point P in the current micro-mist latent cooling phase orbit body B is combined with each bearing position in the historical phase orbit bearing body to form a migration grid, and the migration cost of each migration grid is calculated. The formula is as follows: ； In the formula, This represents the g-th historical three-dimensional state position in the historical phase track carrier, Sg represents the fog delivery process position of the historical carrier position, dk represents the current winding direction, and dr represents the historical main winding direction. Represents the weights for 3D state position transitions. Indicates the migration weight of the fog delivery process. This indicates the weight of the roll-up direction migration, and ; After obtaining the migration cost for all migration cells, convert the migration cost into the initial migration share, and repeatedly perform two adjustments: The first adjustment is based on each portion of the latent cooling winding mass in the current micro-mist latent cooling phase track body B, so that the sum of the current latent cooling winding mass allocated to each historical bearing position is equal to the current latent cooling winding mass. The second adjustment uses the historical load mass of each historical phase track carrier as a benchmark to ensure that the latent cold winding mass moved into the current load position is distributed on the same scale as the historical load mass. The two adjustments are performed alternately until the migration share obtained in two consecutive rounds no longer changes numerically, forming the migration distribution result of the latent cold winding mass between the current three-dimensional state point P and the historical bearing position, and performing a preliminary evaluation on the current micro-mist latent cold phase track body B to obtain the phase track mass migration tensor.

7. The energy intelligent control system for a refrigeration testing laboratory according to claim 6, characterized in that: The latent cooling refrigeration quotient spectrum generation module includes a latent cooling mass temporal expansion unit and a latent cooling quotient conversion unit; The latent cooling mass time-position expansion unit reads each latent cooling winding mass in the micro-mist latent cooling phase track body B, as well as the original sampling position, migration bearing position, migration ratio and migration span recorded in the phase track mass migration tensor. Starting from the current sampling period, it sequentially forms the current time position and several subsequent time positions according to a fixed period. Then, the bearing position in the historical phase track carrier is converted into a time position; Based on the migration ratio in the phase-track mass migration tensor, each portion of latent cold winding mass is allocated to different time positions to form latent cold accumulation. The formula is: ; In the formula, Specifically, this represents the latent cold accumulation amount in the (k+a)th sampling period, where 'a' represents the number of sampling periods extending backward relative to the current sampling period, and 'mki' represents the i-th latent cold winding mass in the micro-mist latent cold phase track. This represents the proportion of the i-th latently cooled winding mass that has migrated to the r-th time position; When the sum of the migration proportions of a latently cooled winding mass allocated to each time position is less than one, the unallocated latently cooled winding mass will continue to be delivered along the current migration span. When the assigned position exceeds the end of the fog delivery period, the excess portion is recorded as the residual latent cold accumulation amount; the latent cold accumulation amount, residual latent cold accumulation amount, and migration span at each time position are combined to form the latent cold time position expansion sequence.

8. The energy intelligent control system for a refrigeration testing laboratory according to claim 7, characterized in that: The latent cooling occupancy conversion unit reads the latent cooling time-position expansion sequence and dynamic cooling capacity; The system reads the latent cold accumulation during historical humidification processes, as well as the cooling capacity reduction due to heat absorption by micro-mist evaporation during the same sampling period. It repeatedly adjusts the conversion coefficient to make the cooling capacity reduction calculated from historical latent cold accumulation close to the historical data, thus obtaining the correct conversion coefficient. The latent cooling ration for each sampling period is calculated using the following formula: ； In the formula, This represents the proportion of dynamic cooling capacity undertaken by heat absorption through micro-mist evaporation during the (k+a)th sampling period. Represents an exponential function; The latent cooling refrigeration quota, the location of the residual latent cooling accumulation, and the location of the fog delivery evaporation delay in each sampling period are arranged in chronological order to form the latent cooling refrigeration quota spectrum C. Read the latent cooling quotient in the latent cooling quotient spectrum C one by one, and calculate it with the dynamic cooling capacity in the same sampling period to obtain the quotient-corrected dynamic cooling capacity RQ, as shown in the following formula: ； In the formula, This represents the dynamic cooling capacity during the (k+a)th sampling period.

9. The energy intelligent control system for a refrigeration testing laboratory according to claim 8, characterized in that: The quota trajectory comprehensive evaluation execution module includes a dual-track simulation unit and a quota trajectory adjudication unit; The homogeneous dual-track replay unit reads the latent cooling spectral density C, dynamic cooling capacity, and dynamic cooling capacity RQ after spectral correction. From historical continuous sampling records, extract the actual temperature and humidity of the previous sampling period, the dynamic cooling capacity of the current sampling period, the compressor operating frequency and the electronic expansion valve opening, as well as the actual temperature and humidity of the next sampling period to form a state transition sample. Based on the state transition samples, the short-term effects of changes in cooling capacity and control actions on temperature and humidity in the next sampling period are obtained; Using the current actual temperature and humidity as common starting conditions, and assuming that the pressure value and the fog delivery process remain unchanged, two trajectory reenactments are performed: The first method uses the dynamic cooling capacity within the coverage period of the latent cooling spectral C to calculate the actual temperature, actual humidity, compressor operating frequency, and electronic expansion valve opening hourly, forming the original refrigeration operation trajectory. The second method uses the dynamic cooling capacity after quota correction within the same time period, and retains the cooling share undertaken by micro-mist evaporation in each sampling period according to the latent cooling quota spectrum C, forming the latent cooling quota operation trajectory. The quota trajectory command unit calculates the comprehensive trajectory cost J of the two operating trajectories based on the original refrigeration operating trajectory and the latent cooling quota operating trajectory, as follows: ； In the formula, Indicates temperature deviation. Indicates humidity deviation. This indicates the change in the compressor's operating frequency. This indicates the change in the opening degree of the electronic expansion valve. and These represent the weighting of the compressor operating frequency and the weighting of the electronic expansion valve opening, respectively. A final comprehensive evaluation will be performed on the original refrigeration operation trajectory and the latent cooling capacity operation trajectory: When the overall trajectory cost of the latent cooling occupancy operation trajectory is less than that of the original refrigeration operation trajectory, the latent cooling occupancy execution command is output. When the latent cooling occupancy spectrum C extends to the sampling period after the ultrasonic oscillation frequency returns to zero, the remaining occupancy continuation instruction is output based on the latent cooling occupancy execution instruction, and the latent cooling occupancy that has not yet ended in the latent cooling occupancy spectrum C is continued to be called until the remaining latent cooling accumulation is exhausted. When the overall trajectory cost of the original refrigeration operation trajectory is not greater than the latent cooling quota operation trajectory, the original refrigeration trajectory execution command is output.

10. An intelligent energy control method for a refrigeration testing laboratory, applied to the intelligent energy control system for a refrigeration testing laboratory as described in any one of claims 1 to 9, characterized in that: Includes the following steps: Step 1: The enthalpy and humidity scale sequence module collects the actual temperature T, actual humidity, pressure value Pa, ultrasonic oscillation frequency, air delivery speed, compressor operating frequency, electronic expansion valve opening and dynamic cooling capacity, calculates the moisture content HS and the enthalpy value of humid air ZHD, and after scale conversion and cooling action projection stripping, forms the enthalpy and humidity residue of the de-cooling and the fog delivery action sequence. Step 2: The micro-mist latent cooling phase track weaving module obtains the fog delivery evaporation delay position based on the fog delivery action sequence and the enthalpy moisture residue of the decooling, constructs a three-dimensional state point P, and calculates the latent cooling winding mass to form the micro-mist latent cooling phase track body B. Step 3: The Phase Track Quality Migration Preliminary Assessment Module conducts a preliminary assessment of the micro-mist latent cooling phase track body B and the historical phase track quality centroid, forming the phase track quality migration tensor. Step 4: The latent cooling occupancy spectrum generation module allocates the latent cooling winding mass to the current and subsequent sampling periods based on the phase track mass migration tensor, forming the latent cooling occupancy spectrum C, and obtains the dynamic cooling capacity RQ after occupancy correction. Step 5: The quota trajectory comprehensive evaluation execution module respectively deduces the dynamic cooling capacity operation trajectory and the dynamic cooling capacity RQ operation trajectory after quota correction. After comprehensive evaluation, it outputs the latent cooling quota execution command, the residual quota continuation command and the original cooling trajectory execution command.

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