Control method of air conditioning system, air conditioning system and medium

Abstract

The invention relates to the technical field of air conditioner control, particularly provides a control method of an air conditioner system, the air conditioner system and a medium, and aims at solving the problems that in the prior art, the hardware cost is high, and rapid temperature control and operation energy efficiency cannot be considered at the same time. In order to achieve the purpose, the control method of the air conditioning system comprises the steps that system input parameters of the air conditioning system are obtained; the system input parameters comprise the set temperature of the air conditioning system and the indoor environment temperature; determining an operation mode of the air conditioning system based on the system input parameters; wherein the operation mode comprises a rapid approaching mode or an energy efficiency optimization mode; in the rapid approaching mode, the air conditioning system is controlled to adjust the indoor environment temperature to a preset range corresponding to the set temperature; in the energy efficiency optimization mode, the air conditioning system is controlled to achieve optimal energy efficiency ratio operation on the premise that the indoor environment temperature is kept within the preset range; determining target operation parameters of the air conditioning system based on the operation mode of the air conditioning system; and controlling the air conditioning system to operate based on the target operation parameters.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air conditioner control, and specifically provides an air conditioner system control method, an air conditioner system and a medium. BACKGROUND

[0002] Current household variable frequency air conditioner systems generally use compressor control based on PID algorithm, outdoor fan control based on condensing temperature, and electronic expansion valve control based on superheat. However, the prior art has the following main defects: first, the existing control strategy takes temperature regulation as the primary goal, and energy efficiency optimization is in a passive position. When the temperature tends to the set value, the system only performs simple adjustments such as compressor frequency reduction, and lacks the cooperation of multiple actuators to actively pursue the optimal energy efficiency operating point. In addition, to achieve precise superheat control, the system usually needs to be equipped with expensive pressure sensors, which not only increases the hardware cost and structural complexity of the system, but also affects the market competitiveness of the product to some extent. Second, the compressor, outdoor fan and electronic expansion valve use independent control loops, forming an isolated control architecture, ignoring the coupling characteristics between actuators, and unable to achieve system-level optimization.

[0003] Correspondingly, there is a need in the art for a new air conditioner control scheme to solve the above problems. SUMMARY

[0004] In order to overcome the above defects, the present application is proposed to provide a solution or at least partially solve the technical problems of high hardware cost and inability to balance fast temperature control and high operating energy efficiency of the existing air conditioner system control technology.

[0005] In a first aspect, the present application provides an air conditioner system control method, which comprises: obtaining system input parameters of an air conditioner system; the system input parameters include a set temperature and an indoor environment temperature of the air conditioner system; determining an operating mode of the air conditioner system based on the system input parameters; wherein the operating mode includes a fast approach mode or an energy efficiency optimization mode; in the fast approach mode, controlling the air conditioner system to adjust the indoor environment temperature to a preset range corresponding to the set temperature; in the energy efficiency optimization mode, controlling the air conditioner system to achieve optimal energy efficiency ratio operation under the premise of maintaining the indoor environment temperature within the preset range; determining target operating parameters of the air conditioner system based on the operating mode of the air conditioner system; and controlling the air conditioner system to operate based on the target operating parameters.

[0006] In a technical solution of the control method of the air conditioning system, the determination of the operation mode of the air conditioning system based on the system input parameters comprises: determining a real-time temperature difference based on the absolute value of the difference between the indoor environment temperature and the set temperature; determining whether the real-time temperature difference is less than a preset switching threshold; if yes, the operation mode of the air conditioning system is the energy efficiency optimization mode; if no, the operation mode of the air conditioning system is the fast approaching mode.

[0007] In a technical solution of the control method of the air conditioning system, the system input parameters further comprise an outdoor environment temperature, an outdoor coil temperature and a compressor discharge temperature; the target operation parameter comprises a first target operation parameter; the determination of the target operation parameter of the air conditioning system based on the operation mode of the air conditioning system comprises: in the fast approaching mode, determining the first target operation parameter of the air conditioning system based on the outdoor environment temperature, the outdoor coil temperature and the compressor discharge temperature.

[0008] In a technical solution of the control method of the air conditioning system, the first target operation parameter comprises a compressor frequency, an outdoor fan rotating speed and an electronic expansion valve opening degree of the air conditioning system; the determination of the first target operation parameter of the air conditioning system based on the outdoor environment temperature, the outdoor coil temperature and the compressor discharge temperature comprises: determining the compressor frequency by using a fuzzy self-adaptive PID controller based on the indoor environment temperature, the set temperature and the outdoor environment temperature; determining the outdoor fan rotating speed by using a PI controller based on the outdoor environment temperature and the outdoor coil temperature; determining a virtual superheat degree based on the outdoor coil temperature and the compressor discharge temperature; determining the electronic expansion valve opening degree by using a PI controller based on the virtual superheat degree.

[0009] In a technical solution of the control method of the air conditioning system, the target operation parameter comprises a second target operation parameter; the determination of the target operation parameter of the air conditioning system based on the operation mode of the air conditioning system comprises: in the energy efficiency optimization mode, determining the second target operation parameter based on a preset energy efficiency optimization model and the system input parameters.

[0010] In one of the technical solutions of the control method of the air conditioning system, the system input parameters further include an outdoor environment temperature; and the determining of the second target operation parameter based on the preset energy efficiency optimization model and the system input parameters comprises: in each control cycle of the energy efficiency optimization mode, the following optimization steps are performed: obtaining an operation parameter at a current time, the operation parameter including a compressor frequency, an outdoor fan speed, and an electronic expansion valve opening degree; based on the operation parameter at the current time, generating a plurality of candidate operation parameter combinations containing data perturbation; each candidate operation parameter combination includes a candidate compressor frequency, a candidate outdoor fan speed, and a candidate electronic expansion valve opening degree; inputting each candidate operation parameter combination and the outdoor environment temperature into the preset energy efficiency optimization model to obtain an estimated energy efficiency ratio corresponding to each candidate operation parameter combination; comparing the estimated energy efficiency ratios corresponding to all the candidate operation parameter combinations, and selecting a candidate operation parameter combination with the highest estimated energy efficiency ratio as the second target operation parameter of the current control cycle; and the second target operation parameter includes the compressor frequency, the outdoor fan speed, and the electronic expansion valve opening degree of the air conditioning system.

[0011] In one of the technical solutions of the control method of the air conditioning system, the preset energy efficiency optimization model is a relationship mapping model of an estimated energy efficiency ratio and a compressor frequency, an outdoor fan speed, an electronic expansion valve opening degree, and an outdoor environment temperature.

[0012] In one of the technical solutions of the control method of the air conditioning system, the method further comprises: in the process of determining the second target operation parameter, determining a real-time temperature difference based on an absolute value of a difference between the indoor environment temperature and the set temperature; and if the real-time temperature difference is greater than a preset temperature threshold, determining a compressor frequency as the second target operation parameter based on the indoor environment temperature, the set temperature, and the outdoor environment temperature by using a fuzzy self-adaptive PID controller to stabilize fluctuations of the indoor environment temperature.

[0013] In a second aspect, the application provides an air conditioning system, comprising a processor and a memory, the memory being adapted to store a plurality of program codes, the program codes being adapted to be loaded and run by the processor to execute the control method of the air conditioning system in any one of the technical solutions of the control method of the air conditioning system.

[0014] In a third aspect, a computer readable storage medium is provided, the computer readable storage medium having a plurality of program codes stored therein, the program codes being adapted to be loaded and run by a processor to execute the control method of the air conditioning system in any one of the technical solutions of the control method of the air conditioning system.

[0015] The one or more technical solutions of the application have at least one or more of the following beneficial effects:

[0016] The control method of the air conditioning system according to the present application comprises: obtaining system input parameters of the air conditioning system; the system input parameters comprise a set temperature and an indoor environment temperature of the air conditioning system; determining an operation mode of the air conditioning system based on the system input parameters; wherein the operation mode comprises a fast approaching mode or an energy efficiency optimization mode; in the fast approaching mode, controlling the air conditioning system to adjust the indoor environment temperature to a preset range corresponding to the set temperature; in the energy efficiency optimization mode, controlling the air conditioning system to realize optimal energy efficiency ratio operation on the premise of maintaining the indoor environment temperature in the preset range; determining target operation parameters of the air conditioning system based on the operation mode of the air conditioning system; and controlling the air conditioning system to operate based on the target operation parameters. The present application intelligently switches the air conditioning system in the fast approaching mode or the energy efficiency optimization mode through system input parameters, realizes intelligent switching and segmented control of the operation mode, and thus, the response capability of fast temperature adjustment and the energy saving effect during stable operation are taken into account without increasing hardware cost. BRIEF DESCRIPTION OF DRAWINGS

[0017] The preferred embodiments of the present application will be described below with reference to the accompanying drawings, in which:

[0018] Figure 1 is a main step flow diagram of the control method of the air conditioning system according to an embodiment of the present application;

[0019] Figure 2 is a detailed step flow diagram of the fast approaching mode according to an embodiment of the present application;

[0020] Figure 3 is a detailed step flow diagram of the energy efficiency optimization mode according to an embodiment of the present application;

[0021] Figure 4 is a main structure block diagram of the air conditioning system according to an embodiment of the present application.

[0022] LIST OF REFERENCE NUMERALS

[0023] 11: memory; 12: processor. DETAILED DESCRIPTION

[0024] Some embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present application, and are not intended to limit the protection scope of the present application.

[0025] In the description of the present application, "module", "processor" can include hardware, software or a combination of both. A module can include hardware circuit, various suitable sensors, communication port, memory, and can also include software part such as program code, and can be a combination of software and hardware. The processor can be a central processor, microprocessor, image processor, digital signal processor or any other suitable processor. The processor has data and / or signal processing function. The processor can be implemented in software, hardware or a combination of both. The non-transitory computer readable storage medium includes any suitable medium that can store program code, such as magnetic disk, hard disk, optical disk, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B or both A and B. The term "at least one of A or B" or "at least one of A and B" has similar meaning as "A and / or B", and can include only A, only B or both A and B. The singular form of the term "one", "this" can also include plural forms.

[0026] The existing compressor control based on PID algorithm, outdoor fan control based on condensing temperature and electronic expansion valve control based on superheat degree have the following main defects: first, the existing control strategy takes temperature regulation as the primary goal, and energy efficiency optimization is in a passive position. When the temperature approaches the set value, the system only performs simple adjustments such as compressor frequency reduction, and lacks the cooperation of multiple actuators to actively pursue the optimal energy efficiency operating point. In addition, to achieve precise superheat control, the system usually needs to configure expensive pressure sensors, which not only increases the hardware cost and structural complexity of the system, but also affects the market competitiveness of the product to some extent. Second, the compressor, outdoor fan and electronic expansion valve use independent control loops, forming an isolated control architecture, ignoring the coupling characteristics between actuators, and unable to achieve system-level optimization.

[0027] To this end, the application provides a control method of an air conditioning system, comprising: acquiring system input parameters of the air conditioning system; the system input parameters comprising a set temperature and an indoor environment temperature of the air conditioning system; determining an operation mode of the air conditioning system based on the system input parameters; wherein the operation mode comprises a fast approaching mode or an energy efficiency optimization mode; in the fast approaching mode, controlling the air conditioning system to adjust the indoor environment temperature to a preset range corresponding to the set temperature; in the energy efficiency optimization mode, controlling the air conditioning system to realize optimal energy efficiency ratio operation on the premise that the indoor environment temperature is maintained within the preset range; determining target operation parameters of the air conditioning system based on the operation mode of the air conditioning system; and controlling the air conditioning system to operate based on the target operation parameters. The application switches the air conditioning system between the fast approaching mode and the energy efficiency optimization mode through the system input parameters, realizes intelligent switching and segmented control of the operation mode, and thus takes into account the response capability of fast temperature adjustment and the energy saving effect during stable operation without increasing hardware cost.

[0028] Referring to the drawings Figure 1 , Figure 1 is a main step flow diagram of a control method of an air conditioning system according to an embodiment of the application. As shown in Figure 1 , the control method of the air conditioning system in the embodiment mainly comprises the following steps S101-S104.

[0029] Step S101: acquiring system input parameters of the air conditioning system; the system input parameters comprising a set temperature and an indoor environment temperature of the air conditioning system.

[0030] In the embodiment, the system input parameters are detectable signals of the air conditioning system, specifically comprising a set temperature set by a user and an indoor environment temperature detected in real time by a temperature sensor.

[0031] Step S102: determining an operation mode of the air conditioning system based on the system input parameters; wherein the operation mode comprises a fast approaching mode or an energy efficiency optimization mode; in the fast approaching mode, controlling the air conditioning system to adjust the indoor environment temperature to a preset range corresponding to the set temperature; in the energy efficiency optimization mode, controlling the air conditioning system to realize optimal energy efficiency ratio operation on the premise that the indoor environment temperature is maintained within the preset range.

[0032] In the embodiment, the operation mode of the air conditioning system is determined according to the system input parameters, in the fast approaching mode, the air conditioning system is controlled to quickly adjust the indoor environment temperature to a range close to the set temperature, and in the energy efficiency optimization mode, the indoor environment temperature is already within a range close to the set temperature, and the air conditioning system is controlled to operate with the optimal energy efficiency ratio as the target.

[0033] Step S103: determining a target operation parameter of the air conditioning system based on the operation mode of the air conditioning system.

[0034] In this embodiment, the target operation parameter of the air conditioning system is determined based on the determined operation mode of the air conditioning system.

[0035] Step S104: controlling the air conditioning system to operate based on the target operation parameter.

[0036] Based on the above steps S101-S104, the system input parameters including the set temperature and the indoor environment temperature are obtained, and the operation mode is dynamically decided based on these parameters: when the fast approach mode is enabled, the indoor environment temperature is adjusted to the target preset range; when the energy efficiency optimization mode is switched to, the optimal energy efficiency ratio of the system is pursued under the premise of maintaining the stability of the indoor environment temperature. The air conditioning system is controlled to switch between the fast approach mode and the energy efficiency optimization mode through the system input parameters, realizing the intelligent switching and segmented control of the operation mode, so as to balance the response ability of fast temperature adjustment and the energy saving effect in stable operation without increasing the hardware cost.

[0037] The above steps S102 and S103 will be further described below.

[0038] For step S102, in one embodiment, the determining of the operation mode of the air conditioning system based on the system input parameters comprises: determining a real-time temperature difference based on the absolute value of the difference between the indoor environment temperature and the set temperature; judging whether the real-time temperature difference is less than a preset switching threshold; if yes, the operation mode of the air conditioning system is the energy efficiency optimization mode; if no, the operation mode of the air conditioning system is the fast approach mode.

[0039] Specifically, the real-time temperature difference is calculated based on the absolute value of the difference between the indoor environment temperature and the set temperature, and the calculation formula is:

[0040]

[0041] In the formula, is the real-time temperature difference, is the indoor environment temperature, is the set temperature.

[0042] It is judged whether the real-time temperature difference is less than the preset switching threshold. In one specific example, the preset switching threshold can be set to 2.0°C.

[0043] When the real-time temperature difference is less than the preset switching threshold, the operation mode of the air conditioning system is set to an energy efficiency optimization mode, at this time, the indoor environment temperature is close to the set temperature, the current indoor environment temperature tends to be stable, and the system is operated with the optimal energy efficiency ratio as the target to achieve the purpose of saving energy.

[0044] When the real-time temperature difference is greater than or equal to the preset switching threshold, the operation mode of the air conditioning system is set to a fast approaching mode, that is, when the indoor environment temperature is far from the set temperature, the system preferentially performs fast cooling or heating to make the indoor environment temperature rapidly approach the set temperature.

[0045] The threshold judgment mechanism ensures that the system can provide strong power when the user most needs fast temperature adjustment, and automatically switches to energy-saving operation after the temperature is stable (i.e., the indoor environment temperature approaches the set temperature), thereby intelligently balancing the response speed and operation energy efficiency of the air conditioning system.

[0046] For step S103, in an embodiment, the system input parameters further include an outdoor environment temperature, an outdoor coil temperature and a compressor discharge temperature; the target operation parameter includes a first target operation parameter; and the determining the target operation parameter of the air conditioning system based on the operation mode of the air conditioning system includes: in the fast approaching mode, determining the first target operation parameter of the air conditioning system based on the outdoor environment temperature, the outdoor coil temperature and the compressor discharge temperature.

[0047] Referring to FIG. 1, an embodiment of the air conditioning system according to the present application is shown. Figure 2 , Figure 2 FIG. 2 is a detailed step flow diagram of the fast approaching mode according to an embodiment of the present application.

[0048] In an embodiment, the first target operation parameter includes a compressor frequency, an outdoor fan speed and an electronic expansion valve opening degree of the air conditioning system; and the determining the first target operation parameter of the air conditioning system based on the outdoor environment temperature, the outdoor coil temperature and the compressor discharge temperature includes: determining the compressor frequency by using a fuzzy self-adaptive PID controller based on the indoor environment temperature, the set temperature and the outdoor environment temperature; determining the outdoor fan speed by using a PI controller based on the outdoor environment temperature and the outdoor coil temperature; determining a virtual superheat degree based on the outdoor coil temperature and the compressor discharge temperature; and determining the electronic expansion valve opening degree by using a PI controller based on the virtual superheat degree.

[0049] Specifically, in the fast approaching mode, the compressor frequency, the outdoor fan speed and the electronic expansion valve opening degree of the air conditioning system are respectively determined based on the outdoor environment temperature, the outdoor coil temperature and the compressor discharge temperature as the first target operation parameter.

[0050] Specifically, based on the indoor environment temperature, the set temperature and the outdoor environment temperature, a fuzzy self-adaptive PID controller is adopted to determine the compressor frequency, the fuzzy self-adaptive PID controller comprising a fuzzy inference machine for adaptively outputting a fuzzy correction amount and a PID controller for determining the compressor frequency based on the fuzzy correction amount; and the determination of the compressor frequency specifically comprises the following steps:

[0051] Step one: define system input and output variables

[0052] System input:

[0053] Real-time temperature difference (ΔT): based on the indoor environment temperature , the set temperature Determine the real-time temperature difference:

[0054]

[0055] Temperature difference change rate (dΔT), reflecting the temperature change trend, the calculation formula is:

[0056]

[0057] In the formula, is the temperature difference change rate, ΔT(k) is the current real-time temperature difference, is the real-time temperature difference sampled last time.

[0058] Outdoor environment temperature (T_out): an environmental variable for system protection and performance optimization.

[0059] System output:

[0060] Compressor frequency (F_comp_target): the control instruction finally output to the frequency converter.

[0061] PID parameter online correction amount (ΔKp, ΔKi, ΔKd): the parameter adjustment amount output by the fuzzy inference machine.

[0062] Step two: fuzzification (Fuzzification)

[0063] Convert the accurate input amount (ΔT, dΔT) into a fuzzy language value, and define a fuzzy set.

[0064] For ΔT: it can be defined as {negative big (NB), negative small (NS), zero (ZO), positive small (PS), positive big (PB)}. For example: when ΔT=-2°C (the indoor environment temperature is much lower than the set temperature), it can be classified as "negative big (NB)".

[0065] For dΔT: can be defined as {negative big (NB), negative small (NS), zero (ZO), positive small (PS), positive big (PB)}. For example: when dΔT is a large positive value, it means that the temperature is rapidly deviating from the set value.

[0066] For ΔKp, ΔKi, ΔKd: also need to define its fuzzy set, such as {negative big (NB), negative medium (NM), negative small (NS), zero (ZO), positive small (PS), positive medium (PM), positive big (PB)}.

[0067] Set a membership function for each fuzzy set, such as using a triangular membership function to calculate the degree to which each input value belongs to each fuzzy language variable (between 0 and 1).

[0068] Step three: establish a fuzzy rule base (Fuzzy Rule Base)

[0069] Based on expert experience, establish fuzzy rules in the form of IF-THEN to dynamically adjust PID parameters. For example, the fuzzy rules are shown in Table 1.

[0070] Table 1

[0071] Rule No. IF (condition) THEN (conclusion) - parameter adjustment strategy Control logic explanation 1 ΔT is PB AND dΔT is ZO ΔKp is PB, ΔKi is NB, ΔKd is PS Temperature difference is large and stable, increase P action to respond quickly, weaken I action to prevent integral saturation, and appropriately strengthen D action to stabilize the system. 2 ΔT is PS AND dΔT is NS ΔKp is PS, ΔKi is NM, ΔKd is ZO Temperature difference is small and decreasing, appropriately increase P action, weaken I action, and keep D action. 3 ΔT is ZO AND dΔT is ZO ΔKp is ZO, ΔKi is ZO, ΔKd is ZO Target temperature has been reached and is stable, keep current PID parameters to maintain stable operation. 4 ΔT is NS AND dΔT is PS ΔKp is NS, ΔKi is PS, ΔKd is NB Room temperature is slightly higher than the set value and has a rising trend, reduce P action to prevent overshoot, strengthen I action to eliminate static error, and strengthen D action to suppress the rising trend.

[0072] Step four: fuzzy inference (Fuzzy Inference)

[0073] According to the fuzzy values of input ΔT and dΔT and the above fuzzy rules, the fuzzy results of output variables (ΔKp, ΔKi, ΔKd) are calculated by the fuzzy inference machine.

[0074] Step five: defuzzification (Defuzzification)

[0075] The fuzzy results of output variables (ΔKp, ΔKi, ΔKd) obtained by the fuzzy inference machine are converted back to accurate numerical values, and finally the accurate correction amount corresponding to the output variables is obtained.

[0076] Step six: PID parameter online adjustment and frequency calculation

[0077] PID parameter adaptive adjustment: add the accurate correction amount obtained after defuzzification to the initial PID parameters:

[0078]

[0079]

[0080]

[0081] Where, Kp_initial, Ki_initial, Kd_initial are initial PID parameters.

[0082] Calculate the base frequency (F_base): using the online adjusted PID parameters (Kp, Ki, Kd) 、 、 , calculate the base frequency F_base by standard PID algorithm. .

[0083]

[0084] F_base is an adaptive frequency value positively related to ΔT.

[0085] Step 7: Introduce the outdoor ambient temperature (T_out) for final correction

[0086] This is a key step for system protection, dynamically limit the upper limit of frequency by outdoor ambient temperature (T_out).

[0087] Define the outdoor ambient temperature correction rule:

[0088] If T_out ≤ T_low_threshold (e.g. 25°C), then the upper limit of frequency F_max = F_max_rated (rated maximum value).

[0089] If T_low_threshold (e.g. 25°C) < T_out < T_high_threshold (e.g. 45°C), then F_max linearly or regularly decreases.

[0090] If T_out ≥ T_high_threshold (e.g. 45°C), then F_max = F_max_derated (derated protection value, e.g. 80% of rated value).

[0091] Final frequency limit:

[0092]

[0093] Where, is the compressor frequency.

[0094] This means that no matter how high the base frequency F_base calculated by fuzzy adaptive PID is, the final output of the compressor frequency will not exceed the highest safety frequency F_max determined by the current outdoor ambient temperature T_out.

[0095] A minimum running frequency F_min can also be set in advance for lower limit protection, to ensure that the compressor does not start and stop frequently. Then the final compressor frequency is:

[0096]

[0097] Based on outdoor ambient temperature and outdoor coil temperature, a PI controller is used to determine the outdoor fan speed, with the goal of providing optimal heat dissipation for the condenser of the air conditioning system, ensuring that the system can maintain appropriate condensing pressure during high load operation, while reducing fan speed to save energy during low load. Specifically, the following steps are included:

[0098] Step 1: Collect real-time data

[0099] Read T_out (outdoor ambient temperature) and T_cond (outdoor coil temperature).

[0100] Step 2: Calculate target condensing temperature

[0101] The target condensing temperature increases linearly with the outdoor ambient temperature to adapt to changes in heat dissipation conditions. According to the preset linear relationship, the target condensing temperature T_cond_target is obtained using the current outdoor ambient temperature. The preset linear relationship can be:

[0102] When T_out ≤ T_low (e.g. 20°C): T_cond_target = 45°C (T_cond_target_min);

[0103] When T_out ≥ T_high (e.g. 40°C): T_cond_target = 55°C (T_cond_target_max);

[0104] When T_low (e.g. 20°C) < T_out < T_high (e.g. 40°C): T_cond_target is linearly interpolated between 45°C and 55°C. The calculation formula is:

[0105]

[0106] Step 3: Calculate control error

[0107]

[0108] Where error is the deviation value of the outdoor coil temperature from the target condensing temperature, which is the input of the PI controller; T_cond is the outdoor coil temperature; T_cond_target is the target condensing temperature.

[0109] Then, the PI controller is used to adjust the outdoor fan speed according to the deviation error between the outdoor coil temperature T_cond and the target condensing temperature T_cond_target. If the outdoor coil temperature is higher than the target condensing temperature, the outdoor fan speed will be increased; otherwise, the outdoor fan speed will be decreased.

[0110] Step four: PI controller calculation

[0111] Proportional term (P term):

[0112]

[0113] Integral term (I term):

[0114] where, is the integral time constant.

[0115] PI total output:

[0116]

[0117] Step five: Anti-integral saturation processing and speed limiting

[0118] This is a critical step to prevent the outdoor fan speed N_fan_out from losing control after reaching the limit speed due to the ineffective accumulation of the integral term. The implementation method is: only when the outdoor fan speed N_fan_out does not reach the upper or lower limit, the integral term is allowed to accumulate.

[0119] if (N_fan_out > N_max) and (error > 0): the fan has reached the highest speed but is still overheating, stop positive integration

[0120] integral = integral or do not perform integral accumulation

[0121] else if (N_fan_out < N_min) and (error < 0): the fan has reached the lowest speed but is still too cold, stop negative integration

[0122] integral = integral or do not perform integral accumulation

[0123] Step six: determine the outdoor fan speed command

[0124] Use the PI output as the basic command for the outdoor fan speed: N_fan_out_command = PI_output

[0125] Limiting processing: limit the command within a safe range.

[0126] if N_fan_out_command > N_max: N_fan_out = N_max

[0127] else if N_fan_out_command < N_min: N_fan_out = N_min

[0128] else: N_fan_out = N_fan_out_command

[0129] Step Seven: Output the control signal

[0130] The calculated final outdoor fan speed N_fan_out is applied to the outdoor fan through a driver (e.g. a frequency converter).

[0131] Step Eight: Prepare for the next cycle

[0132] Store the current error as the previous error: previous_error = error (This variable is not necessary in the standard positional PI formula, but is used in the incremental PI).

[0133] Step Nine: Wait for the next control cycle and repeat from Step One.

[0134] Determine the virtual superheat based on the outdoor coil temperature and the compressor discharge temperature; use a PI controller to determine the electronic expansion valve opening based on the virtual superheat, including:

[0135] In this embodiment, based on no additional hardware of pressure sensor, through other easily measured temperature parameters (outdoor coil temperature and compressor discharge temperature) in the system, an estimated value is indirectly calculated to represent the system superheat state using the following formula to determine the virtual superheat:

[0136]

[0137] In the formula, SH_virtual is the virtual superheat, Tdischarge is the compressor discharge temperature, Tcoil is the outdoor coil temperature, and k1 and k2 are coefficients calibrated through experiments, related to the characteristics of the refrigerant and the structure of the system. K1 can range from 1 to 3, and K2 can range from 8 to 16.

[0138] Then, using a PI controller, the virtual superheat SH_virtual is stabilized within a pre-set safe superheat range (e.g. 5-7°C), ensuring system safety and evaporator utilization. Determining the electronic expansion valve opening based on the estimated virtual superheat includes the following steps:

[0139] Calculation error:

[0140]

[0141] where, Error is the error of virtual superheat and target superheat, Target superheat, i.e. the safe superheat range (e.g. 5-7°C).

[0142] If SH_virtual > SH_set, the error Error is negative, indicating that the superheat is too high, the evaporator utilization is insufficient, and the electronic expansion valve needs to be opened.

[0143] If SH_virtual < SH_set, the error Error is positive, indicating that the superheat is too low, there is a risk of liquid hammer, and the electronic expansion valve needs to be closed.

[0144] The proportion P is responsible for fast response, and the calculation formula is:

[0145]

[0146] It is proportional to the size of the error, the larger the error, the stronger the adjustment.

[0147] The integral I is responsible for eliminating steady-state error and achieving precise control, and the calculation formula is:

[0148]

[0149] The cumulative historical error, as long as the error exists, the integral output will change constantly until the error is zero.

[0150] PI total output:

[0151]

[0152] Send the output PI_Output of the PI controller (usually a pulse signal or digital command) to the stepper motor of the electronic expansion valve. If PI_Output is positive, the controller will control the electronic expansion valve to rotate in the opening direction by the corresponding number of steps. If PI_Output is negative, the controller will control the electronic expansion valve to rotate in the closing direction by the corresponding number of steps.

[0153] The change of the opening of the electronic expansion valve will change the refrigerant flow, and then affect the compressor discharge temperature and the outdoor coil temperature, thereby causing the virtual superheat to change. The system continuously monitors these temperatures, recalculates the virtual superheat at the next control cycle, forms a closed-loop feedback, and finally stabilizes the virtual superheat near the target superheat. Through closed-loop control, the system can automatically adapt to load changes and maintain the superheat in a preset safe interval, thereby realizing stable, efficient and safe operation.

[0154] In one embodiment, the target operating parameter includes a second target operating parameter; and the determining of the target operating parameter of the air conditioning system based on the operating mode of the air conditioning system comprises: in the energy efficiency optimization mode, determining the second target operating parameter based on a preset energy efficiency optimization model and the system input parameter.

[0155] In one embodiment, the preset energy efficiency optimization model is a mapping model of the estimated energy efficiency ratio and the compressor frequency, the outdoor fan speed, the opening of the electronic expansion valve, and the outdoor environment temperature.

[0156] Specifically, when the air conditioning system switches from the fast approach mode to the energy efficiency optimization mode, the system enters the energy efficiency optimization state seeking the "optimal solution" from the high energy consumption state.

[0157] The preset energy efficiency optimization model is constructed based on the following steps:

[0158] The calculation formula of the energy efficiency ratio of the system is:

[0159]

[0160] In the formula, COP is the energy efficiency ratio, P_comp is the operating power of the compressor, P_fan_out is the operating power of the outdoor fan, and Cooling_Capacity is the refrigerating capacity. Since the refrigerating capacity and power cannot be directly measured, the above formula is converted into a model based on measurable data:

[0161]

[0162] In the formula, F_comp is the compressor frequency; N_fan_out is the outdoor fan speed; Open_EEV is the opening of the electronic expansion valve (step number); and T_out is the outdoor environment temperature.

[0163] The specific form of the function is a binary polynomial, the coefficients of which are fitted and calibrated through a large amount of experimental data, and are pre-embedded in the memory of the controller as an energy efficiency optimization model for real-time calculation of the energy efficiency ratio COP. The expression of the energy efficiency optimization model is as follows (only an example, the actual coefficients need to be experimentally calibrated):

[0164]

[0165] COP_est is the estimated COP.

[0166] Then, in each control cycle (e.g. 10s), the compressor frequency, the outdoor fan speed, and the electronic expansion valve opening are finely adjusted, the trend of the estimated COP is observed, and the optimal working point is autonomously tracked through an iterative algorithm similar to "hill climbing" in the dynamic changes.

[0167] Referring to the accompanying drawings Figure 3 , Figure 3 is a detailed step flowchart of the energy efficiency optimization mode according to an embodiment of the present application.

[0168] In an embodiment, the system input parameters further include an outdoor environment temperature; and the determining the second target operating parameter based on the preset energy efficiency optimization model and the system input parameters comprises: in each control cycle of the energy efficiency optimization mode, performing the following optimization steps: obtaining operating parameters at the current time, the operating parameters including a compressor frequency, an outdoor fan speed, and an electronic expansion valve opening; generating a plurality of candidate operating parameter combinations containing data perturbations based on the operating parameters at the current time; wherein each candidate operating parameter combination includes a candidate compressor frequency, a candidate outdoor fan speed, and a candidate electronic expansion valve opening; inputting each candidate operating parameter combination and the outdoor environment temperature into the preset energy efficiency optimization model to obtain an estimated COP corresponding to each candidate operating parameter combination; comparing the estimated COPs corresponding to all the candidate operating parameter combinations, and selecting a candidate operating parameter combination with the highest estimated COP as the second target operating parameter of the current control cycle; and the second target operating parameter includes the compressor frequency, the outdoor fan speed, and the electronic expansion valve opening of the air conditioning system.

[0169] Specifically, the step of determining the second target operating parameter is as follows:

[0170] Micro-perturbation: in each control cycle, a set of candidate operating parameter combinations containing micro-perturbations are generated around the operating parameter combination (compressor frequency F_comp, outdoor fan speed N_fan_out, electronic expansion valve opening Open_EEV) at the current time, for example: compressor frequency ± 1 Hz, outdoor fan speed ± 10 rpm, and electronic expansion valve opening ± 5 steps.

[0171] Predictive evaluation: each candidate operating parameter combination is inputted into the energy efficiency optimization model together with the current outdoor environment temperature T_out, and the estimated COP corresponding to each candidate operating parameter combination is calculated.

[0172] Decision and execution: from the estimated energy efficiency ratios of all candidate operating parameter combinations, the candidate operating parameter combination with the highest estimated energy efficiency ratio is selected as the second target operating parameter of the current period, and is issued to each actuator.

[0173] Loop iteration: the system continues to repeat this prediction-decision-execution process, so as to automatically track and maintain the optimal energy efficiency operating point dynamically drifting due to changes in outdoor ambient temperature.

[0174] In one embodiment, the method further comprises: in the process of determining the second target operating parameter, determining a real-time temperature difference based on the absolute value of the difference between the indoor ambient temperature and the set temperature; if the real-time temperature difference is greater than a preset temperature threshold, determining the compressor frequency as the second target operating parameter based on the indoor ambient temperature, the set temperature and the outdoor ambient temperature, using a fuzzy adaptive PID controller, to stabilize the indoor ambient temperature fluctuation.

[0175] Specifically, while the system is running in the energy efficiency optimization mode, it continues to calculate and monitor the absolute value of the difference between the indoor ambient temperature and the set temperature, i.e. the real-time temperature difference (ΔT), and monitor the fluctuation trend of the indoor ambient temperature. Once the system monitors that the real-time temperature difference ΔT is greater than a preset temperature threshold (e.g. 0.5°C), it determines that the current temperature fluctuation has exceeded the comfort range. At this time, the system will immediately suspend the current energy efficiency optimization process and intervene. In the intervention state, the system will call a fuzzy adaptive PID controller based on the indoor ambient temperature, the set temperature and the outdoor ambient temperature, quickly calculate and output a compressor frequency with temperature stabilization as the priority target. By fine-tuning the compressor power, the temperature fluctuation is quickly suppressed and the indoor ambient temperature is stabilized.

[0176] When the system successfully stabilizes the indoor ambient temperature and monitors that the real-time temperature difference ΔT is less than or equal to a preset return threshold (e.g. 0.2°C), it indicates that the temperature state has recovered to stability. At this time, the system will automatically exit the intervention state and re-enter the process of determining the highest estimated energy efficiency ratio by the "hill climbing algorithm" before, to continue to pursue the optimal energy efficiency ratio.

[0177] By introducing the temperature stability judgment and priority control strategy in the energy efficiency optimization mode, dynamic multi-objective optimization is realized. It ensures that the control strategy can intelligently and smoothly switch between energy efficiency priority and temperature stability priority, thus perfectly balancing energy saving effect and user comfort in actual operation.

[0178] It should be noted that although the above embodiments describe the steps in a specific order, those skilled in the art can understand that, in order to achieve the effects of the present application, the different steps do not have to be executed in such an order, and they can be executed simultaneously (in parallel) or in other orders, and these changes are within the protection scope of the present application.

[0179] Those skilled in the art can understand that all or part of the processes in the method of the above embodiment can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer readable storage medium. When the processor executes the computer program, the steps of the above various method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable storage medium can include any entity or device, medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal and software distribution medium, etc. that can carry the computer program code.

[0180] Further, the present application also provides an air conditioning system. In an air conditioning system embodiment according to the present application, the air conditioning system includes a processor and a memory. The memory can be configured to store a program for executing the control method of the air conditioning system of the above method embodiments, and the processor can be configured to execute the program in the memory, which includes but is not limited to the program for executing the control method of the air conditioning system of the above method embodiments. For ease of illustration, only the parts related to the embodiments of the present application are shown, and the specific technical details not disclosed are referred to the method part of the embodiments of the present application. The air conditioning system can be an air conditioning system formed by various electronic devices. Refer to the exemplary air conditioning system shown in FIG. 1. Figure 4 , Figure 4 The memory 11 and the processor 12 are communicatively connected through a bus, as shown exemplarily in FIG. 1.

[0181] Further, the present application also provides a computer readable storage medium. In a computer readable storage medium embodiment according to the present application, the computer readable storage medium can be configured to store a program for executing the control method of the air conditioning system of the above method embodiments, which can be loaded and run by the processor to implement the control method of the above air conditioning system. For ease of illustration, only the parts related to the embodiments of the present application are shown, and the specific technical details not disclosed are referred to the method part of the embodiments of the present application. The computer readable storage medium can be a memory device formed by various electronic devices, and optionally, the computer readable storage medium in the embodiments of the present application is a non-transitory computer readable storage medium.

[0182] Further, it should be understood that, since the setting of each module is only for illustrating the functional units of the device of the present application, the physical device corresponding to the module can be the processor itself, or a part of the software in the processor, a part of the hardware, or a part of the combination of the software and the hardware. Therefore, the number of each module in the figure is only illustrative.

[0183] Those skilled in the art can understand that each module in the device can be adaptively split or combined. Such splitting or combining of the specific module does not cause the technical solution to deviate from the principles of the present application, and therefore, the technical solution after splitting or combining will fall within the protection scope of the present application.

[0184] So far, the technical solution of the present application has been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without deviating from the principles of the present application, and the technical solution after the changes or replacements will fall within the protection scope of the present application.

Claims

1. A control method for an air conditioning system, characterized in that, The method includes: Obtain the system input parameters of the air conditioning system; the system input parameters include the set temperature of the air conditioning system and the indoor ambient temperature. Based on the system input parameters, the operating mode of the air conditioning system is determined; wherein, the operating mode includes a rapid approach mode or an energy efficiency optimization mode; in the rapid approach mode, the air conditioning system is controlled to adjust the indoor ambient temperature to a preset range corresponding to the set temperature; in the energy efficiency optimization mode, the air conditioning system is controlled to achieve optimal energy efficiency ratio operation while maintaining the indoor ambient temperature within the preset range; Based on the operating mode of the air conditioning system, the target operating parameters of the air conditioning system are determined; The air conditioning system is controlled to operate based on the target operating parameters.

2. The control method for the air conditioning system according to claim 1, characterized in that, Determining the operating mode of the air conditioning system based on the system input parameters includes: The real-time temperature difference is determined based on the absolute value of the difference between the indoor ambient temperature and the set temperature. Determine whether the real-time temperature difference is less than a preset switching threshold; If so, the operating mode of the air conditioning system is energy efficiency optimization mode; If not, then the operating mode of the air conditioning system is the rapid approach mode.

3. The control method for the air conditioning system according to claim 1, characterized in that, The system input parameters also include outdoor ambient temperature, outdoor coil temperature, and compressor discharge temperature; The target operating parameters include a first target operating parameter; determining the target operating parameters of the air conditioning system based on the operating mode of the air conditioning system includes: In the rapid approach mode, the first target operating parameters of the air conditioning system are determined based on the outdoor ambient temperature, the outdoor coil temperature, and the compressor exhaust temperature.

4. The control method for the air conditioning system according to claim 3, characterized in that, The first target operating parameters include the compressor frequency, outdoor fan speed, and electronic expansion valve opening of the air conditioning system; determining the first target operating parameters of the air conditioning system based on the outdoor ambient temperature, the outdoor coil temperature, and the compressor discharge temperature includes: Based on the indoor ambient temperature, the set temperature, and the outdoor ambient temperature, a fuzzy adaptive PID controller is used to determine the compressor frequency; Based on the outdoor ambient temperature and the outdoor coil temperature, a PI controller is used to determine the speed of the outdoor fan; The virtual superheat is determined based on the outdoor coil temperature and the compressor discharge temperature; the opening degree of the electronic expansion valve is determined based on the virtual superheat using a PI controller.

5. The control method for an air conditioning system according to claim 1, characterized in that, The target operating parameters include a second target operating parameter; determining the target operating parameters of the air conditioning system based on the operating mode of the air conditioning system includes: In the energy efficiency optimization mode, the second target operating parameters are determined based on the preset energy efficiency optimization model and the system input parameters.

6. The control method for an air conditioning system according to claim 5, characterized in that, The system input parameters also include outdoor ambient temperature; determining the second target operating parameters based on the preset energy efficiency optimization model and the system input parameters includes: In each control cycle of the energy efficiency optimization mode, the following optimization steps are performed: Obtain the operating parameters at the current moment, including compressor frequency, external fan speed, and electronic expansion valve opening. Based on the operating parameters at the current moment, multiple candidate operating parameter combinations containing data perturbations are generated; wherein, each candidate operating parameter combination includes candidate compressor frequency, candidate external fan speed and candidate electronic expansion valve opening; Each candidate combination of operating parameters and the outdoor ambient temperature are input into a preset energy efficiency optimization model to obtain the estimated energy efficiency ratio corresponding to each candidate combination of operating parameters. Compare the estimated energy efficiency ratios corresponding to all the candidate operating parameter combinations, and select the candidate operating parameter combination with the highest estimated energy efficiency ratio as the second target operating parameter for the current control cycle; the second target operating parameter includes the compressor frequency, outdoor fan speed and electronic expansion valve opening of the air conditioning system.

7. The control method for an air conditioning system according to claim 6, characterized in that, The preset energy efficiency optimization model is a mapping model that estimates the relationship between the energy efficiency ratio and the compressor frequency, the external fan speed, the electronic expansion valve opening degree, and the outdoor ambient temperature.

8. The control method for an air conditioning system according to claim 6, characterized in that, The method further includes: In determining the second target operating parameters, the real-time temperature difference is determined based on the absolute value of the difference between the indoor ambient temperature and the set temperature. If the real-time temperature difference is greater than the preset temperature threshold, a fuzzy adaptive PID controller is used to determine the compressor frequency based on the indoor ambient temperature, the set temperature, and the outdoor ambient temperature, as a second target operating parameter to stabilize indoor ambient temperature fluctuations.

9. An air conditioning system, comprising a processor and a memory, the memory being adapted to store multiple lines of program code, characterized in that, The program code is adapted to be loaded and run by the processor to perform the control method of the air conditioning system according to any one of claims 1 to 8.

10. A computer-readable storage medium storing a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by a processor to perform the control method of the air conditioning system according to any one of claims 1 to 8.

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