Energy-saving control method and device for industrial low-temperature air conditioner

Abstract

The application relates to the technical field of heat exchange device control, in particular to an energy-saving control method and device for an industrial low-temperature air conditioner, which comprises the following steps: analyzing the correlation between an equivalent refrigeration load and the temperature on the air outlet side of an evaporator, combining the difference between the instantaneous temperature and the average temperature of the application area of the low-temperature air conditioner, constructing a first self-adaptive compensation factor, and correcting the proportional gain of a PID controller; analyzing the difference between the equivalent refrigeration loads at all adjacent moments, constructing a second self-adaptive compensation factor, and correcting the integral gain of the PID controller; and generating a control instruction of the low-temperature air conditioner based on the corrected proportional gain and integral gain, so as to dynamically regulate and control the temperature of the low-temperature air conditioner. The application dynamically corrects the PID parameters based on the load and temperature response characteristics, solves the problems of frosting, overshooting and high energy consumption caused by traditional control, and improves the energy-saving control effect and operation stability of the industrial low-temperature air conditioner.

Description

Technical Field

[0001] This application relates to the field of heat exchange device control technology, specifically to an energy-saving control method and device for industrial low-temperature air conditioning. Background Technology

[0002] Industrial cryogenic air conditioning systems are refrigeration systems that use a compressor and a cooling fan working together to achieve rapid cooling through refrigerant phase change. They are primarily used to create low-temperature working environments around zero degrees Celsius. In applications such as precision manufacturing, where the processing causes temperature fluctuations, cryogenic air conditioning systems need to be precisely adjusted in real time according to the target temperature to meet stringent process requirements.

[0003] While existing control algorithms (such as PID controllers) can quickly adjust parameters such as compressor load, refrigerant flow, and fan speed based on the error between the current temperature and the target temperature, they rely solely on temperature difference as the single control standard. In pursuit of rapid cooling, traditional PID control often leads to low-temperature air conditioners frequently operating at high loads. This not only increases energy consumption but also induces evaporator frosting. Frosting significantly weakens the heat exchange capacity and circulation of the low-temperature air conditioner, resulting in a lower-than-expected actual adjustment effect. Consequently, the system is forced to further increase its load, falling into a vicious cycle of "high load - low heat exchange - high energy consumption," thus reducing the operational stability and energy-saving control effect of industrial low-temperature air conditioners. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide an energy-saving control method and device for industrial low-temperature air conditioning, the specific technical solution of which is as follows: In a first aspect, embodiments of this application provide an energy-saving control method for industrial low-temperature air conditioning, the method comprising the following steps: Real-time data collection of the equivalent cooling load, evaporator outlet temperature, and temperature of the low-temperature air conditioning application area in the industrial environment; The low-temperature air conditioning control process is divided into multiple continuous control cycles. The correlation between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle is analyzed to determine the heat exchange efficiency mismatch of the low-temperature air conditioning in the current control cycle. In combination with the difference between the instantaneous temperature and the average temperature of the low-temperature air conditioning application area in the current control cycle, the first adaptive compensation factor is constructed to correct the proportional gain of the PID controller in the next control cycle. Within the current control cycle, the difference in equivalent cooling load between all adjacent time points is analyzed to construct a second adaptive compensation factor, which corrects the integral gain of the PID controller in the next control cycle. Control commands for the cryogenic air conditioner are generated based on the corrected proportional gain and integral gain to dynamically regulate the temperature of the cryogenic air conditioner.

[0005] Preferably, the equivalent cooling load of the low-temperature air conditioner at time t. The expression is: In the formula, , These represent the operating load of the compressor and the operating load of the cooling fan in the low-temperature air conditioner at time t, which are collected in real time by the sensor. , These represent the preset first weight factor and the preset second weight factor, respectively. and .

[0006] Preferably, the heat exchange efficiency mismatch of the low-temperature air conditioner under the current control cycle is: the normalized value of the correlation coefficient between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle.

[0007] Preferably, the process of constructing the first adaptive compensation factor includes: Based on the difference between the instantaneous temperature and the average temperature of the low-temperature air-conditioning application area during the current control cycle, the average temperature error of the low-temperature air-conditioning under the current control cycle is determined. ; like If the value is less than or equal to 0, the first adaptive compensation factor for the current control cycle is set to 0; otherwise, it is based on the average temperature error. Based on the heat exchange efficiency mismatch, determine the first adaptive compensation factor for the current control cycle.

[0008] Preferably, the average temperature error of the low-temperature air conditioner under the current control cycle is the result of averaging the differences between the temperature of the low-temperature air conditioner application area and the average temperature at all times within the current control cycle.

[0009] Preferably, when the average temperature error When the value is greater than 0, the value of the first adaptive compensation factor under the current control cycle is... ,in, Indicates average temperature error The normalized value of , where A represents the heat exchange efficiency mismatch of the low-temperature air conditioner under the current control cycle, and min() represents the minimum value function. This indicates the preset boundary threshold.

[0010] Preferably, the process of correcting the proportional gain of the PID controller in the next control cycle includes: The proportional gain correction value of the PID controller in the next control cycle The expression is: In the formula, This indicates the preset proportional gain reference value; This represents the first adaptive compensation factor under the current control cycle.

[0011] Preferably, the second adaptive compensation factor under the current control cycle is the average of the equivalent cooling load change rate between all adjacent moments in the current control cycle.

[0012] Preferably, the process of correcting the integral gain of the PID controller in the next control cycle includes: Integral gain correction value of the PID controller in the next control cycle The expression is: In the formula, This indicates the preset integral gain reference value; This represents the second adaptive compensation factor under the current control cycle; Indicates the preset boundary factor; represents the preset integral gain attenuation factor; max() represents the maximum value function; ln() represents the logarithmic function with the natural constant as the base; norm[] represents the normalization function.

[0013] Secondly, embodiments of this application also provide an energy-saving control device for an industrial low-temperature air conditioner, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above-described energy-saving control methods for an industrial low-temperature air conditioner.

[0014] This application has at least the following beneficial effects: This application divides the control process into continuous cycles, determines the heat exchange efficiency mismatch based on the correlation between the load of the previous control cycle and the temperature response of the current control cycle, and constructs a first adaptive compensation factor by comprehensively considering the temperature error, thereby realizing the dynamic correction of the proportional gain. This method effectively solves the problem of evaporator frosting, energy efficiency imbalance and energy consumption surge caused by the traditional PID blindly pursuing rapid cooling under low temperature conditions due to fixed gain. By adaptively suppressing the response speed under large temperature differences and high frosting risk, the method avoids the vicious cycle of "high load-low heat exchange" while maintaining the basic stability of the system, thereby improving the energy-saving control effect and operational stability of industrial low temperature air conditioning. Furthermore, this application addresses the large time delay characteristics of low-temperature air conditioners by constructing a second adaptive compensation factor through analyzing the equivalent cooling load change rate at adjacent moments within the current cycle. This enables the advanced prediction and correction of the integral gain. This method can effectively predict the temperature response trend caused by load changes. When the load fluctuates drastically, it automatically weakens the integral action to suppress overshoot caused by time delay, while maintaining a strong integral action when the load is stable to quickly eliminate steady-state errors. This improves the operational stability and energy-saving control effect of the low-temperature air conditioner. Ultimately, this application constructs a PID control model based on dynamically corrected proportional gain and integral gain. By using the deviation between the regional temperature and the target temperature as input, it generates and issues low-temperature air conditioning control commands in real time to dynamically adjust the compressor operating frequency. This achieves precise adaptive adjustment of control parameters as the operating conditions change, ensuring that the low-temperature air conditioning can maintain optimal operating conditions when dealing with the risk of frosting and time delay characteristics. Thus, while meeting the precise temperature control requirements of industrial environments, it effectively reduces the energy consumption of low-temperature air conditioning and improves the energy-saving control effect and operational stability of industrial low-temperature air conditioning. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of an energy-saving control method for an industrial low-temperature air conditioner, provided as an embodiment of this application; Figure 2 A flowchart illustrating the calculation process of the first adaptive compensation factor provided in one embodiment of this application. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an energy-saving control method and apparatus for an industrial low-temperature air conditioner proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the energy-saving control method and device for an industrial low-temperature air conditioner provided in this application.

[0020] Please see Figure 1 The diagram illustrates a flowchart of an energy-saving control method for an industrial low-temperature air conditioner according to an embodiment of this application. The method includes the following steps: Step S1: Real-time acquisition of the equivalent cooling load, evaporator outlet temperature, and temperature of the low-temperature air conditioning application area in the industrial environment.

[0021] The operating parameter data of the industrial cryogenic air conditioner is obtained, including the compressor operating load, cooling fan operating load, evaporator outlet temperature, and temperature of the application area of ​​the cryogenic air conditioner. The specific acquisition process is as follows: The compressor operating load data and cooling fan operating load data are collected in real time by installing voltage and current sensors at the compressor motor and cooling fan motor, respectively, to calculate the load in real time. The load calculation process is a well-known technology and will not be described in detail here. In this embodiment, the sampling frequency of the compressor operating load and cooling fan operating load is 1Hz. In actual application, the implementer can also set the data sampling frequency according to the specific situation. This embodiment does not impose any special restrictions.

[0022] Thermocouple sensors are installed on the surface of the evaporator outlet coil to measure the temperature of the evaporator outlet side in real time. The installation position of the thermocouple sensors can be selected according to the size of the evaporator in the actual scenario of the low-temperature air conditioner. In this embodiment, the number of thermocouple sensors is set to 4. The average value of the temperature data of the 4 thermocouple sensors at the same time is taken as the evaporator outlet side temperature at the corresponding time. The sampling frequency of the four thermocouple sensors is set to 1Hz. In actual application, as other implementation methods, implementers can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0023] The temperature of the low-temperature air conditioning application area is obtained by using an industrial temperature sensor. If the low-temperature air conditioning application area is large, multiple industrial temperature sensors can be used for data collection. The average temperature data of multiple industrial temperature sensors is then taken as the temperature of the low-temperature air conditioning application area. In this embodiment, the sampling frequency of the industrial temperature sensor is set to 1Hz. In actual applications, as other implementation methods, implementers can also set their own frequencies according to specific circumstances. This embodiment does not impose any special restrictions.

[0024] Furthermore, based on the compressor operating load and cooling fan operating load collected above, the equivalent cooling load is calculated, specifically: In this embodiment, the equivalent cooling load of the low-temperature air conditioner at time t is... The expression is: In the formula, , These represent the operating load of the compressor and the operating load of the cooling fan in the low-temperature air conditioner at time t, which are collected in real time by the sensor. , These represent the preset first weight factor and the preset second weight factor, respectively. and In this embodiment The values ​​are 0.7 and 0.3 respectively. In practical applications, as other implementation methods, implementers can also set their own values ​​according to specific circumstances. This embodiment does not impose any special restrictions.

[0025] Step S2: Divide the low-temperature air conditioning control process into multiple continuous control cycles, analyze the correlation between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle, determine the heat exchange efficiency mismatch of the low-temperature air conditioning in the current control cycle, and construct a first adaptive compensation factor based on the difference between the instantaneous temperature and the average temperature of the low-temperature air conditioning application area in the current control cycle to correct the proportional gain of the PID controller in the next control cycle; within the current control cycle, analyze the difference in equivalent cooling load between all adjacent moments to construct a second adaptive compensation factor to correct the integral gain of the PID controller in the next control cycle.

[0026] In industrial applications, cryogenic air conditioning control is crucial for ensuring process quality and product storage safety. While PID controller-based control methods can quickly adjust based on the temperature difference between the zone and the target temperature, traditional PID controllers typically use fixed gain parameters and only provide feedback on the current temperature error. In actual operation, when the temperature error is large, the cryogenic air conditioner is often forced to operate at high load for extended periods in pursuit of rapid response. However, this excessively high load condition easily leads to frost formation on the evaporator surface, significantly reducing the heat exchange efficiency between the evaporator and the environment. Once frost forms, even maintaining high load operation results in a substantial decrease in actual cooling effect, leading to a sharp increase in energy consumption and hindering effective energy-saving control of the cryogenic air conditioner.

[0027] S2.1: Divide the low-temperature air conditioning control process into multiple continuous control cycles, analyze the correlation between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle, determine the heat exchange efficiency mismatch of the low-temperature air conditioning in the current control cycle, and construct the first adaptive compensation factor in combination with the difference between the instantaneous temperature and the average temperature of the low-temperature air conditioning application area in the current control cycle, so as to correct the proportional gain of the PID controller in the next control cycle.

[0028] To address the aforementioned issues, this embodiment divides the low-temperature air conditioning control process into multiple continuous control cycles. It analyzes the correlation between the equivalent cooling load in the preceding control cycle and the evaporator outlet temperature in the current control cycle to determine the heat exchange efficiency mismatch of the low-temperature air conditioning in the current control cycle. Furthermore, it constructs a first adaptive compensation factor based on the difference between the instantaneous temperature and the average temperature of the low-temperature air conditioning application area in the current control cycle, to correct the proportional gain of the PID controller in the next control cycle. Within the current control cycle, it analyzes the differences in equivalent cooling load between all adjacent moments to construct a second adaptive compensation factor, which corrects the integral gain of the PID controller in the next control cycle, thereby achieving energy-saving control of the low-temperature air conditioning.

[0029] Specifically, this embodiment describes the control of a low-temperature air conditioner in an industrial environment. The derivative term in the PID controller is highly sensitive to noise; therefore, noise in this scenario can cause significant interference with the measured data. For example, the load in industrial circuits is variable, and other electrical equipment can frequently affect the voltage and current measured in the low-temperature air conditioner circuit, leading to a large amount of interference in the calculated operating parameters. To avoid the derivative term amplifying noise and causing instability in the control system, in this embodiment, the control period for adjusting the low-temperature air conditioner is set to T seconds. The value of T can be set by the implementer based on the evaporator temperature response time of the low-temperature air conditioner. A longer response time results in a larger control period T. The evaporator temperature response time is the time it takes for the refrigerant to reach the evaporator and take effect after the compressor and cooling fan increase their load. In this embodiment, T is 30 seconds. Because the low-temperature air conditioner is relatively large, it takes a certain amount of time for the load to adjust until the evaporator begins to show a cooling response. Therefore, the load adjustment phase is from 1 to T seconds, and the evaporator temperature response phase is from (T+1) to 2T seconds. Based on data from two consecutive control cycles, the operation of the low-temperature air conditioner is controlled. The first two control cycles are the initial stage of the low-temperature air conditioner, during which no control adjustments are made. The first time the low-temperature air conditioner is controlled by a PID controller is at time 2T+1. From (2T+1) to 3T, the same parameters are used to control the low-temperature air conditioner, and this process is repeated. By analyzing the correlation between the changing trend of the equivalent cooling load in the adjacent previous control cycle and the changing trend of the evaporator outlet temperature in the current control cycle, the heat exchange efficiency mismatch of the low-temperature air conditioner in the current control cycle is determined. Combined with the difference between the instantaneous temperature and the average temperature of the low-temperature air conditioner application area in the current control cycle, a first adaptive compensation factor is constructed to correct the proportional gain of the PID controller in the next control cycle. The specific process is as follows: Traditional PID controllers primarily adjust the gain parameter based on the error between actual and target data. In low-temperature air conditioning control scenarios, this involves dynamically adjusting the operating load of the compressor and cooling fan by monitoring the deviation between the temperature of the low-temperature air conditioning application area and the target temperature in real time, thereby achieving rapid temperature regulation. To further enhance the algorithm's responsiveness to errors, adaptive PID control strategies typically increase the proportional gain appropriately when the temperature deviation is large, thereby strengthening the system's regulation and achieving rapid temperature convergence. This is the core logic of adaptive control in achieving rapid error response during regulation. In this embodiment, the target temperature is set to 5°C. In practical applications, as other implementation methods, implementers can set the target temperature according to specific circumstances. This embodiment does not impose any special restrictions.

[0030] However, in the actual operation of low-temperature air conditioners, the sudden and significant increase in the operating load of the compressor and cooling fan in pursuit of rapid cooling will cause a large amount of refrigerant to rush into the evaporator. Since the refrigerant cannot exchange heat with the surrounding environment in a short time, the evaporator temperature will drop sharply, leading to frost formation. If the operating load is not adjusted in time to alleviate the situation, the frost layer will continue to thicken, significantly weakening the heat exchange capacity of the evaporator. This results in a slow actual temperature adjustment rate of the low-temperature air conditioner under high load operation during subsequent control processes, even if the temperature error is still large, and the energy consumption will rise sharply. The resulting vicious cycle of "high load - low heat exchange - high energy consumption" has a serious negative impact on the control effect of the low-temperature air conditioner.

[0031] Therefore, based on the above analysis, this embodiment analyzes the correlation between the changing trend of the equivalent cooling load in the adjacent previous control cycle and the changing trend of the evaporator outlet temperature in the current control cycle, determines the heat exchange efficiency mismatch of the low-temperature air conditioner in the current control cycle, and combines the difference between the instantaneous temperature and the average temperature of the low-temperature air conditioner application area in the current control cycle. The specific process is as follows: The normalized value of the correlation coefficient between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle is used as the heat exchange efficiency mismatch of the low-temperature air conditioner in the current control cycle.

[0032] It should be noted that there are many commonly used methods for calculating correlation coefficients. In this embodiment, the Pearson correlation coefficient between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle is used as the correlation coefficient between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle. In practical applications, as other implementation methods, implementers may also use Spearman correlation coefficient or Kendall's rank correlation coefficient, etc., depending on the specific circumstances. This embodiment does not impose any special restrictions on the selection of correlation coefficient calculation methods.

[0033] It should be noted that there are many commonly used normalization methods. In this embodiment, the maximum-minimum normalization method is used to normalize the correlation coefficient to the range of [0,1]. In practical applications, as other implementation methods, implementers may also use other normalization methods according to specific circumstances. This embodiment does not impose any special restrictions on the selection of normalization methods.

[0034] The calculation process of the Pearson correlation coefficient and the process of normalizing the data using the maximum-minimum normalization method are well-known techniques and will not be elaborated further.

[0035] Based on the heat exchange efficiency mismatch, it can be understood that the heat exchange efficiency mismatch characterizes the correlation difference between the changing trend of the equivalent cooling load of a low-temperature air conditioner and the changing trend of the evaporator outlet temperature. In other words, it reflects whether the current heat exchange performance of the evaporator is normal or disturbed. Changes in its value directly reveal whether the low-temperature air conditioner has a risk of energy efficiency imbalance due to heat exchange obstruction, and have a decisive impact on the adjustment of the control strategy. The calculation of the heat exchange efficiency mismatch is mainly affected by the magnitude of the correlation coefficient between the fluctuation of the equivalent cooling load in the previous control cycle and the evaporator outlet temperature in the current control cycle. When the calculated correlation coefficient deviates from the preset ideal negative correlation benchmark, i.e., the correlation... The larger the normalized mismatch value, the more abnormal the correlation between the two factors is. For example, if the load increases sharply but the temperature response is sluggish or the trend is inconsistent, the larger the heat exchange efficiency mismatch value, the more likely the evaporator has shown initial signs of frost formation, leading to a disorder in the heat exchange response mechanism. This indicates that the current load regulation strategy of the system is mismatched, and if no intervention is made, it will lead to energy waste. Conversely, when the correlation coefficient meets the expected benchmark and the mismatch value is smaller, it indicates that the load change and temperature response maintain good linear synchronization. In this case, the smaller the heat exchange efficiency mismatch value, the more likely the evaporator is in good heat exchange condition and operating stably. This indicates that the current or conventional control logic can be maintained for efficient operation.

[0036] Furthermore, based on the heat exchange efficiency mismatch and the difference between the instantaneous temperature and the average temperature of the low-temperature air-conditioning application area in the current control cycle, this embodiment constructs a first adaptive compensation factor to correct the proportional gain of the PID controller in the next control cycle. Specifically: In this embodiment, the average temperature error of the low-temperature air conditioning application area under the current control cycle is determined based on the difference between the instantaneous temperature and the average temperature within the current control cycle. Specifically, the average difference between the temperature of the low-temperature air-conditioning application area at all times in the current control cycle and the average temperature of the low-temperature air-conditioning application area at all times in the previous control cycle is taken as the average temperature error of the low-temperature air-conditioning in the current control cycle.

[0037] Furthermore, if If the value is less than or equal to 0, the first adaptive compensation factor for the current control cycle is set to 0; otherwise, the value of the first adaptive compensation factor for the current control cycle is [value missing]. ,in, Indicates average temperature error The normalized value of , where A represents the heat exchange efficiency mismatch of the low-temperature air conditioner under the current control cycle, and min() represents the minimum value function. This indicates the preset boundary threshold.

[0038] Preferably, the flowchart of the first adaptive compensation factor calculation process provided in this embodiment is as follows: Figure 2 As shown.

[0039] It should be noted that the preset boundary threshold value is set manually. In this embodiment, the preset boundary threshold value is 0.9. This is to ensure the effectiveness of adaptive compensation adjustment while strictly limiting the attenuation of the proportional gain to maintain the basic stability of the system. Due to the first adaptive compensation factor... It is used for scaling gain For terms that need to be reduced, the correction formula is as follows: If allowed Infinitely close to or even equal to 1, it will lead to If the value approaches 0, the control system will lose its basic responsiveness, resulting in control failure. Therefore, by setting 0.9 as the upper limit, it means that even under extreme conditions with large temperature differences and strong frost interference, the proportional gain of the PID controller will retain at least 10% of its original value. This ensures that the low-temperature air conditioner always retains a minimum level of regulation capability, preventing it from being unable to cope with ambient temperature fluctuations due to insufficient regulation. This achieves a balance between energy saving and frost prevention and safe system operation. In practical applications, implementers can also set the value according to specific circumstances. This embodiment does not impose any special restrictions.

[0040] Based on the first adaptive compensation factor, it can be understood that this factor characterizes the degree to which the compressor response speed needs to be suppressed under the current operating conditions. It comprehensively reflects the combined correction requirements of the control parameters based on the magnitude of the temperature error and the level of frosting risk. Its value directly affects the reduction of the proportional gain in the next control cycle, thereby avoiding a surge in energy consumption and worsening of frosting caused by blindly operating at full load. The calculation of the first adaptive compensation factor is affected by the average temperature error. and heat exchange efficiency mismatch The dual impact; when The larger and A larger value indicates a larger first adaptive compensation factor (within the 0.9 limit), reflecting a large current temperature deviation and a high risk of frosting. This necessitates a significant reduction in response speed to protect the equipment and save energy. The impact is a significant reduction in proportional gain and a slower cooling rate. Conversely, when... smaller or The smaller the value, the smaller the value of the first adaptive compensation factor, which reflects that the temperature is close to the target or the heat exchange state is good, and there is no need to make large corrections to the parameters. Its effect is to maintain a large proportional gain and maintain the ability to quickly track temperature errors.

[0041] Furthermore, based on the first adaptive compensation factor, the proportional gain of the PID controller in the next control cycle is corrected, specifically as follows: In this embodiment, the proportional gain correction value of the PID controller in the next control cycle The expression is: In the formula, This indicates the preset proportional gain reference value; This represents the first adaptive compensation factor under the current control cycle.

[0042] It should be noted that the preset proportional gain reference value in this embodiment is usually between 1.0 and 10.0. In this embodiment, the preset proportional gain reference value is set to 5.0. In actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0043] Based on the proportional gain correction value, it can be understood that the proportional gain correction value is used to characterize the actual sensitivity of the low-temperature air conditioner to temperature errors in the next control cycle, reflecting the final adjustment capability after taking into account both energy-saving targets and anti-frost strategies. Its magnitude directly determines the compressor frequency's response speed and amplitude to temperature deviations, and it is a core execution parameter for achieving precise energy-saving control. The calculation of the proportional gain correction value is subject to a preset benchmark proportional gain. and the first adaptive compensation factor The direct impact; when When the value is larger, the proportional gain correction value is smaller, reflecting that the PID controller is in a strong suppression state, aiming to sacrifice some response speed in exchange for improved heat exchange efficiency and reduced energy consumption, thus avoiding frosting; conversely, when... The smaller the value, the closer the proportional gain correction is to the reference value. This reflects that the PID controller is in a normal response state, focusing on quickly eliminating temperature errors and ensuring real-time temperature control.

[0044] Thus, by dividing the control process into continuous cycles, determining the heat exchange efficiency mismatch based on the correlation between the load of the previous control cycle and the temperature response of the current control cycle, and constructing a first adaptive compensation factor by comprehensively considering the temperature error, dynamic correction of the proportional gain is achieved. This method effectively solves the problems of evaporator frosting, energy efficiency imbalance, and energy consumption surge caused by the blind pursuit of rapid cooling under low-temperature conditions by traditional PID control with fixed gain. By adaptively suppressing the response speed under large temperature differences and high frosting risk, the method avoids the vicious cycle of "high load - low heat exchange" while maintaining the basic stability of the system, thereby improving the energy-saving control effect and operational stability of industrial low-temperature air conditioning.

[0045] S2.2: Within the current control cycle, analyze the differences in equivalent cooling load between all adjacent time points to construct a second adaptive compensation factor to correct the integral gain of the PID controller in the next control cycle.

[0046] Furthermore, due to the significant time delay between load adjustment and the actual heat exchange response of the evaporator in low-temperature air conditioning, traditional PID control is prone to overshoot due to feedback lag, leading to a decrease in the temperature control stability of low-temperature air conditioning. Therefore, the load changes within the current control cycle can be used to predict the temperature response trend at the evaporator after one control cycle, thereby adjusting the integral gain for the next control cycle. This predictive parameter correction strategy, which involves proactive adjustments, avoids temperature response overshoot and parameter adjustment lag caused by time delays, effectively suppressing overshoot and ensuring stable operation of the low-temperature air conditioner. In this embodiment, by analyzing the differences in equivalent cooling load between all adjacent moments within the current control cycle, a second adaptive compensation factor is constructed to correct the integral gain of the PID controller in the next control cycle. Specifically: In this embodiment, the average of the equivalent cooling load change rate between all adjacent moments in the current control cycle is used as the second adaptive compensation factor in the current control cycle.

[0047] It should be noted that in this embodiment, the sum of the equivalent cooling load at any time point adjacent to the previous time point within the current control cycle and the preset value are calculated, and the ratio of the equivalent cooling load at any time point to the corresponding sum value is calculated as the rate of change of the equivalent cooling load at any time point and its adjacent previous time point. The preset value is a constant greater than 0. In this embodiment, the preset value is 0.01. Under the premise of ensuring that the denominator is not 0 and does not excessively affect the calculation result, the implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0048] Furthermore, the integral gain is corrected based on the second adaptive compensation factor, specifically: Integral gain correction value of the PID controller in the next control cycle The expression is: In the formula, This indicates the preset integral gain reference value; This represents the second adaptive compensation factor under the current control cycle; This represents a preset boundary factor, used to prevent the calculation of ln() from being invalid when F=0. In this embodiment, the value of the preset boundary factor is 0.01. In actual applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions. represents the preset integral gain attenuation factor; max() represents the maximum value function; ln() represents the logarithmic function with the natural constant as the base; norm[] represents the normalization function.

[0049] It should be noted that the preset integral gain reference value is usually in the range of 0.001 to 0.1. In this embodiment, the preset integral gain reference value is set to 0.1. In actual application, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0050] It should be noted that the preset integral gain attenuation factor is used in this embodiment. The value range is [2, 5]. In this embodiment, the preset integral gain attenuation factor is... The value of is 2. In practical applications, as other implementation methods, implementers can also set it according to specific circumstances. This embodiment does not impose any special restrictions.

[0051] Based on the integral gain correction value, it can be understood that the integral gain correction value characterizes the strength of the control's correction of accumulated errors after considering time delay characteristics. It reflects the degree of conservatism or aggressiveness taken to prevent overshoot when predicting future temperature response trends. Its magnitude mainly affects how smoothly the control approaches the target temperature during the steady-state phase after load changes. It is a key parameter for ensuring control stability and energy efficiency. The calculation of the integral gain correction value is subject to the preset benchmark integral gain. Second adaptive compensation factor (involving load fluctuations) The combined effects of load fluctuations; the more drastic the load fluctuations, the more... The larger the integral gain, the smaller the correction value, reflecting the prediction that drastic load changes will cause large temperature fluctuations after a time delay. Therefore, the integral action is significantly reduced to suppress overshoot and maintain system stability; conversely, the smaller the integral gain, the smaller the correction value. As the integral gain approaches zero, the closer the correction value is to the reference value. This reflects that the PID controller operates smoothly and can maintain a strong integral action to quickly and accurately eliminate steady-state errors.

[0052] Thus, this embodiment addresses the large time delay characteristic of low-temperature air conditioners by constructing a second adaptive compensation factor through analysis of the equivalent cooling load change rate at adjacent moments within the current cycle. This enables advance prediction and correction of the integral gain. This method can effectively predict the temperature response trend caused by load changes, automatically weaken the integral action to suppress overshoot caused by time delay when the load fluctuates drastically, and maintain a strong integral action to quickly eliminate steady-state errors when the load is stable. This improves the operational stability and energy-saving control effect of the low-temperature air conditioner.

[0053] Step S3: Generate control commands for the low-temperature air conditioner based on the corrected proportional gain and integral gain, so as to dynamically regulate the temperature of the low-temperature air conditioner.

[0054] Based on step S2, the proportional gain and integral gain are dynamically corrected. Furthermore, in this embodiment, the deviation between the temperature of the low-temperature air-conditioning application area and the target temperature at any time in the next control cycle is used as the input of the PID controller. The proportional gain and integral gain of the PID controller are set to the proportional gain correction value and integral gain correction value in the next control cycle, respectively, and the temperature control signal is output to regulate the temperature of the low-temperature air-conditioning application area at any time.

[0055] The process of using a PID controller to regulate the temperature of the low-temperature air conditioning application area is a well-known technology and will not be described in detail here.

[0056] Thus, this embodiment constructs a PID control model based on dynamically corrected proportional gain and integral gain. By using the deviation between the regional temperature and the target temperature as input, it generates and issues low-temperature air conditioning control commands in real time to dynamically adjust the compressor operating frequency. This achieves precise adaptive adjustment of control parameters as the operating conditions change, ensuring that the low-temperature air conditioning can maintain optimal operating conditions when dealing with the risk of frosting and time delay characteristics. In this way, while meeting the precise temperature control requirements of industrial environments, it effectively reduces the energy consumption of low-temperature air conditioning and improves the energy-saving control effect and operational stability of industrial low-temperature air conditioning.

[0057] Based on the same inventive concept as the above method, this application embodiment also provides an energy-saving control device for an industrial low-temperature air conditioner, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described energy-saving control methods for an industrial low-temperature air conditioner.

[0058] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0059] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0060] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. An energy-saving control method for industrial low-temperature air conditioning, characterized in that, The method includes the following steps: Real-time data collection of the equivalent cooling load, evaporator outlet temperature, and temperature of the low-temperature air conditioning application area in the industrial environment; The low-temperature air conditioning control process is divided into multiple continuous control cycles. The correlation between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle is analyzed to determine the heat exchange efficiency mismatch of the low-temperature air conditioning in the current control cycle. In combination with the difference between the instantaneous temperature and the average temperature of the low-temperature air conditioning application area in the current control cycle, the first adaptive compensation factor is constructed to correct the proportional gain of the PID controller in the next control cycle. Within the current control cycle, the difference in equivalent cooling load between all adjacent time points is analyzed to construct a second adaptive compensation factor, which corrects the integral gain of the PID controller in the next control cycle. Control commands for the cryogenic air conditioner are generated based on the corrected proportional gain and integral gain to dynamically regulate the temperature of the cryogenic air conditioner. The process of correcting the proportional gain of the PID controller in the next control cycle includes: The proportional gain correction value of the PID controller in the next control cycle The expression is: In the formula, This indicates the preset proportional gain reference value; This represents the first adaptive compensation factor under the current control cycle; The process of correcting the integral gain of the PID controller in the next control cycle includes: Integral gain correction value of the PID controller in the next control cycle The expression is: In the formula, This indicates the preset integral gain reference value; This represents the second adaptive compensation factor under the current control cycle; Indicates the preset boundary factor; represents the preset integral gain attenuation factor; max() represents the maximum value function; ln() represents the logarithmic function with the natural constant as the base; norm[] represents the normalization function.

2. The energy-saving control method for an industrial low-temperature air conditioner as described in claim 1, characterized in that, Equivalent cooling load of low-temperature air conditioning at time t The expression is: In the formula, , These represent the operating load of the compressor and the operating load of the cooling fan in the low-temperature air conditioner at time t, which are collected in real time by the sensor. , These represent the preset first weight factor and the preset second weight factor, respectively. and .

3. The energy-saving control method for an industrial low-temperature air conditioner as described in claim 1, characterized in that, The heat exchange efficiency mismatch of the low-temperature air conditioner under the current control cycle is: the normalized value of the correlation coefficient between the equivalent cooling load in the adjacent previous control cycle and the evaporator outlet temperature in the current control cycle.

4. The energy-saving control method for an industrial low-temperature air conditioner as described in claim 1, characterized in that, The process of constructing the first adaptive compensation factor includes: Based on the difference between the instantaneous temperature and the average temperature of the low-temperature air-conditioning application area during the current control cycle, the average temperature error of the low-temperature air-conditioning under the current control cycle is determined. ; like If the value is less than or equal to 0, the first adaptive compensation factor for the current control cycle is set to 0; otherwise, it is based on the average temperature error. Based on the heat exchange efficiency mismatch, determine the first adaptive compensation factor for the current control cycle.

5. The energy-saving control method for an industrial low-temperature air conditioner as described in claim 4, characterized in that, The average temperature error of the low-temperature air conditioner under the current control cycle is the result of averaging the differences between the temperature of the low-temperature air conditioner application area and the average temperature at all times within the current control cycle.

6. The energy-saving control method for an industrial low-temperature air conditioner as described in claim 4, characterized in that, When the average temperature error When the value is greater than 0, the value of the first adaptive compensation factor under the current control cycle is... ,in, Indicates average temperature error The normalized value of , where A represents the heat exchange efficiency mismatch of the low-temperature air conditioner under the current control cycle, and min() represents the minimum value function. This indicates the preset boundary threshold.

7. The energy-saving control method for an industrial low-temperature air conditioner as described in claim 1, characterized in that, The second adaptive compensation factor under the current control cycle is the average of the equivalent cooling load change rate between all adjacent moments in the current control cycle.

8. An energy-saving control device for an industrial low-temperature air conditioner, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the energy-saving control method for an industrial low-temperature air conditioner as described in any one of claims 1-7.

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