Temperature control method and system for variable frequency compressor

Abstract

This invention relates to the field of data processing technology, and in particular to a temperature control method and system for a variable frequency compressor. The method includes the following steps: collecting multiple temperature data points at different locations within the variable frequency compressor's wine cabinet, the actual power of the variable frequency compressor, and the actual power of the circulating fan; constructing a temperature field non-uniformity index and a system dynamic response index; obtaining an adaptive smoothing coefficient for the current moment based on the temperature field non-uniformity index and the system dynamic response index; substituting the adaptive smoothing coefficient into an exponential smoothing method to obtain the average temperature prediction value for the current moment; obtaining the control error for the current moment based on a weighted combination of the deviation between the temperature field non-uniformity index, the average temperature prediction value, and the target temperature; and calculating and outputting the actuator adjustment amount based on the control error. This invention improves the accuracy of temperature prediction and the control capability of temperature field uniformity, thereby enhancing the accuracy of temperature control.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a temperature control method and system for a variable frequency compressor. Background Technology

[0002] With increasingly stringent requirements for storage environments of high-value products such as food, wine, and tea, high-precision storage equipment such as variable frequency compressor wine cabinets and tea cabinets are widely used in supermarkets, hotels, and homes. The temperature within these high-precision storage devices directly determines the quality, shelf life, and safety of the stored products. Precise temperature control prevents spoilage, preserves flavor, and avoids microbial growth, while also improving energy efficiency, extending equipment lifespan, and ensuring that high-value products remain in optimal conditions throughout their storage cycle. Traditional temperature control systems typically employ proportional-integral-derivative (PID) control algorithms to regulate the speed or power of the variable frequency compressor. These systems adjust the output in real time by calculating the deviation between the actual temperature and the set temperature. To improve response speed and predictive capability, time series prediction techniques, such as exponential smoothing, are introduced before temperature control. This method smooths the time-series data collected by multiple temperature sensors within the cabinet and predicts future temperature trends, enabling the system to make early warning adjustments to reduce overshoot or undershoot of the set temperature, thereby achieving more precise temperature control and energy savings.

[0003] However, the smoothing coefficient in existing exponential smoothing methods is based on a fixed value preset by experience. The variable frequency compressor system is a highly dynamic nonlinear system. Its temperature change characteristics change drastically with the adjustment of external heat load (such as ambient temperature, user door opening) and internal actuators (such as compressor power, fan speed). Therefore, a fixed smoothing coefficient cannot adapt to the dynamic changes in system operating conditions. For example, when the compressor starts at high power, the temperature changes rapidly. At this time, a larger smoothing coefficient is needed to capture the trend in time. If the preset smoothing coefficient is small, it will cause a significant lag in prediction. When the temperature is stable, a smaller smoothing coefficient is needed to avoid over-adjustment due to small fluctuations. If the preset smoothing coefficient is large, the system will be too sensitive to noise.

[0004] In addition, due to the presence of stacked goods, uneven air circulation, and local heat sources (such as LED lights) in the cabinet, there is often significant temperature non-uniformity in the cabinet. Traditional PID control algorithms often only control based on the average temperature and lack the ability to directly feedback and suppress temperature non-uniformity. Summary of the Invention

[0005] To address the technical problems of fixed smoothing coefficients and lack of adaptability in traditional exponential smoothing methods, and the lack of direct feedback and suppression capabilities for temperature field non-uniformity in traditional PID control algorithms which only rely on average temperature, this invention provides a temperature control method and system for a variable frequency compressor.

[0006] In a first aspect, the present invention provides a temperature control method for a variable frequency compressor, employing the following technical solution:

[0007] A method for temperature control of a variable frequency compressor, comprising the following steps:

[0008] Multiple temperature data points at different locations inside the variable frequency compressor wine cabinet, as well as drive signals from the variable frequency compressor and the circulating fan, are collected to obtain several temperature data points and actuator status at the current moment. The variable frequency compressor wine cabinet is a complete unit, including a variable frequency compressor, a circulating fan, and actuators. The variable frequency compressor is the core refrigeration component, the circulating fan is the auxiliary temperature control component, and the actuator is the control execution carrier, which is the hardware unit that drives the variable frequency compressor and the circulating fan to start, stop, or adjust their speed.

[0009] Based on several temperature data points and actuator status at the current moment, the temperature field non-uniformity index and system dynamic response index are obtained. The temperature field non-uniformity index is a weighted combination of the average sum of temperature differences and the rate of change of temperature differences; the system dynamic response index is the product of the actuator's potential capability and the average rate of change of temperature.

[0010] Based on the temperature field non-uniformity index and the system dynamic response index, the adaptive smoothing coefficient at the current moment is obtained; the adaptive smoothing coefficient at the current moment is substituted into the exponential smoothing method to obtain the average temperature prediction value at the current moment; the deviation between the temperature field non-uniformity index and the average temperature prediction value and the target temperature is weighted and combined to obtain the control error at the current moment.

[0011] The actuator adjustment amount is calculated and output based on the control error.

[0012] The innovation of this invention lies in obtaining the adaptive smoothing coefficient at the current moment based on the system dynamic response index and the temperature field non-uniformity index, which significantly improves the temperature prediction accuracy and adaptability, solves the prediction lag problem caused by the fixed smoothing coefficient, and obtains the control error at the current moment based on the weighted combination of the temperature field non-uniformity index and the deviation between the average temperature prediction value and the target temperature, thereby realizing the coordinated control of the average temperature and temperature field uniformity and improving the accuracy of temperature control.

[0013] Preferably, obtaining the temperature field non-uniformity index at the current moment includes:

[0014] , The index representing the temperature field non-uniformity at the current moment; This represents the average temperature data collected by all sensors at the current moment. This represents the temperature data collected by the i-th temperature sensor at the current moment. This represents the number of temperature sensors arranged in the variable frequency compressor wine cabinet. This represents the average of the total temperature differences at the current moment; This represents the difference between the average total temperature difference at the current moment and the average total temperature difference at the previous moment; || represents the sampling period; || represents the absolute value sign. The weighting coefficient represents the rate of change of temperature difference; This represents the rate of change of temperature difference.

[0015] By combining the sum and mean of temperature differences with the trend of temperature difference changes, the temperature field non-uniformity index obtained at the current moment is more accurate.

[0016] Preferably, the acquisition of the system dynamic response index includes:

[0017] , The system dynamic response index represents the current moment. This represents the actual power of the variable frequency compressor at the current moment. This represents the actual power of the circulating fan at the current moment; This represents the rated maximum power of the variable frequency compressor; This represents the rated maximum power of the circulating fan; This represents the difference between the mean of all temperature data collected by all sensors at the current moment and the mean of all temperature data collected by all sensors at the previous moment. The value represents the sampling period; exp() represents an exponential function with the natural constant as the base.

[0018] Preferably, obtaining the adaptive smoothing coefficient at the current moment includes:

[0019] , The adaptive smoothing coefficient represents the current moment; Represents the preset minimum boundary; Represents the preset maximum boundary; The index representing the temperature field non-uniformity at the current moment; The system dynamic response exponent represents the current moment; exp() represents an exponential function with the natural constant as the base. Represents the preset sensitivity coefficient; This represents the preset translation coefficient.

[0020] It achieves dynamic and adaptive adjustment of the exponential smoothing coefficient, solving the problem that traditional fixed coefficients cannot adapt to drastic changes in system operating conditions.

[0021] Preferably, obtaining the predicted average temperature at the current moment includes:

[0022] The average temperature data collected by all sensors at the current moment is used to form a sequence of historical average temperature data. The adaptive smoothing coefficient at the current moment is then substituted into the exponential smoothing formula to process the historical average temperature sequence, thus obtaining the predicted average temperature value at the current moment.

[0023] Preferably, obtaining the control error at the current moment includes:

[0024] , This represents the control error at the current moment; This represents the target temperature in the variable frequency compressor wine cabinet. The average predicted temperature at the current moment; The index representing the temperature field non-uniformity at the current moment; This represents the preset non-uniformity penalty weight.

[0025] This achieves dual-objective coordinated control of average temperature and temperature field uniformity, forcing the PID control algorithm to prioritize solving the problem of temperature non-uniformity within the cabinet, thereby improving the accuracy of temperature control.

[0026] Preferably, the step of calculating and outputting the actuator adjustment amount based on the control error includes:

[0027] The control error at the current moment is input into the PID control algorithm to obtain the power adjustment of the variable frequency compressor and the power adjustment of the circulating fan. The power adjustment of the variable frequency compressor and the power adjustment of the circulating fan are then sent to the drivers of the variable frequency compressor and the circulating fan to change their power.

[0028] The obtained variable frequency compressor power adjustment and circulating fan power adjustment values ​​are more accurate.

[0029] Preferably, obtaining several temperature data points at the current moment includes:

[0030] Preset sampling period A temperature sensor is placed at the top, middle, bottom, and air outlet of the variable frequency compressor wine cabinet to collect several temperature data points at each moment in real time.

[0031] Preferably, obtaining the actuator state includes:

[0032] The drive signals of the variable frequency compressor and the circulating fan are read to obtain the actuator status at each moment. The actuator status includes the actual power of the variable frequency compressor and the actual power of the circulating fan.

[0033] Secondly, the present invention provides a temperature control system for a variable frequency compressor, which adopts the following technical solution:

[0034] A temperature control system for a variable frequency compressor includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the aforementioned temperature control method for a variable frequency compressor is implemented.

[0035] By adopting the above technical solution, a computer program is generated from the temperature control method of the variable frequency compressor and stored in the memory so that it can be loaded and executed by the processor. A terminal device can then be made based on the memory and the processor for convenient use.

[0036] The present invention has the following technical effects: The adaptive exponential smoothing coefficient adjustment method based on the system dynamic response index and the temperature field non-uniformity index solves the problem that the exponential smoothing algorithm with a fixed smoothing coefficient cannot adapt to the dynamic changes in the system operating conditions, and significantly improves the temperature prediction accuracy and adaptability. Then, the temperature field non-uniformity index is introduced as a high-weight term into the control error, realizing the dual-objective coordinated control of average temperature and temperature field uniformity, forcing the PID control algorithm to prioritize solving the temperature non-uniformity problem in the cabinet, thereby improving the accuracy of temperature control. Attached Figure Description

[0037] Figure 1 This is a flowchart of a temperature control method for a variable frequency compressor according to an embodiment of the present invention;

[0038] Figure 2 This is a comparison chart of the effects of suppressing temperature field non-uniformity. Detailed Implementation

[0039] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0040] This invention discloses a temperature control method for a variable frequency compressor, referring to... Figure 1 This includes steps S1-S4:

[0041] S1: Collect multiple temperature data, actual power of the variable frequency compressor, and actual power of the circulating fan at different locations inside the wine cabinet containing the variable frequency compressor.

[0042] In this embodiment of the invention, a preset sampling period is used. =10 seconds / time, a temperature sensor is arranged at the top, middle, bottom and air outlet of the variable frequency compressor wine cabinet to collect several temperature data at each moment in real time, and simultaneously read the drive signal of the variable frequency compressor and the drive signal of the circulating fan (such as the PWM signal of the variable frequency compressor and the circulating fan) to obtain the actuator status at each moment. The actuator status includes the actual power of the variable frequency compressor and the actual power of the circulating fan. The variable frequency compressor wine cabinet is a complete machine, including a variable frequency compressor, a circulating fan and actuators. The variable frequency compressor is the core refrigeration component, the circulating fan is the auxiliary temperature control component, and the actuator is the control execution carrier, which is the hardware unit that drives the variable frequency compressor and the circulating fan to start, stop and speed adjust.

[0043] For example, if the PWM signal of the variable frequency compressor is 50%, the actual power of the variable frequency compressor is 50% of the rated maximum power of the variable frequency compressor; if the PWM signal of the circulating fan is 80%, the actual power of the circulating fan is 80% of the rated maximum power of the circulating fan.

[0044] Thus, by collecting temperature data from multiple points and actuator status, multi-dimensional data reflecting the internal temperature distribution and the degree of external intervention can be obtained, laying the foundation for subsequent refined control.

[0045] S2: Obtain the temperature field non-uniformity index at the current moment based on the difference between each temperature data point and the mean of all temperature data points at the current moment; obtain the system dynamic response index at the current moment based on the actual power of the circulating fan and the variable frequency compressor at the current moment and the changes in temperature data at the current moment.

[0046] It should be noted that, in order to characterize the temperature non-uniformity index of the variable frequency compressor wine cabinet at the current moment, the average of the sum of the differences between each temperature data point and the mean of all temperature data points at the current moment can be used to obtain the average of the total temperature difference at the current moment. The larger the average of the total temperature difference, the larger the temperature field non-uniformity index at the current moment. However, the average of the total temperature difference only reflects the instantaneous state. In order to assess the urgency of temperature control, the temperature field non-uniformity index must include the evolution trend of the temperature difference. If the average of the total temperature difference is accelerating, it means that the temperature control is facing deterioration. At this time, the temperature field non-uniformity index at the current moment must be amplified.

[0047] In this embodiment of the invention, the temperature field non-uniformity index at the current moment is obtained:

[0048] ;

[0049] In the formula, The index representing the temperature field non-uniformity at the current moment; This represents the average temperature data collected by all sensors at the current moment. This represents the temperature data collected by the i-th temperature sensor at the current moment. This represents the number of temperature sensors arranged in the variable frequency compressor wine cabinet. This represents the average of the total temperature differences at the current moment; This represents the difference between the average total temperature difference at the current moment and the average total temperature difference at the previous moment; || represents the sampling period; || represents the absolute value sign. The weighting coefficient representing the rate of change of temperature difference is preset in this embodiment of the invention. The implementers can pre-set the implementation based on the specific implementation situation. The value; It reflects the rate of temperature change; the larger the value, the faster the temperature instability in the wine cabinet with the variable frequency compressor is deteriorating.

[0050] The larger the average value of the sum of temperature differences at the current moment, and the more rapidly the temperature instability in the variable frequency compressor wine cabinet is deteriorating, that is... When it is a positive number, The larger the value, the more unstable the temperature in the wine cabinet of the variable frequency compressor at the current moment, indicating a higher urgency for temperature control.

[0051] It should be noted that the adaptive adjustment of the smoothing factor needs to assess whether the system dynamic response is stronger at the current moment. However, when the actual power of the circulating fan and the variable frequency compressor is higher and the temperature changes drastically in a short period of time, the system dynamic response index at the current moment will be greater.

[0052] In this embodiment of the invention, the system dynamic response index at the current moment is obtained:

[0053] ;

[0054] In the formula, The system dynamic response index represents the current moment. This represents the actual power of the variable frequency compressor at the current moment. This represents the actual power of the circulating fan at the current moment; This represents the rated maximum power of the variable frequency compressor; This represents the rated maximum power of the circulating fan; This represents the difference between the mean of all temperature data collected by all sensors at the current moment and the mean of all temperature data collected by all sensors at the previous moment. The value represents the sampling period; exp() represents an exponential function with the natural constant as the base.

[0055] When the total output of the actuator is higher, and the temperature changes drastically in a short period of time (e.g.) A negative number indicates that the variable frequency compressor in the wine cooler is cooling down rapidly. The larger the value, the more... A significant increase indicates a stronger dynamic response of the system.

[0056] S3: Based on the temperature field non-uniformity index and the system dynamic response index, obtain the adaptive smoothing coefficient at the current moment, substitute the adaptive smoothing coefficient at the current moment into the exponential smoothing method to obtain the average temperature prediction value at the current moment; based on the weighted combination of the temperature field non-uniformity index and the deviation between the average temperature prediction value and the target temperature, obtain the control error at the current moment.

[0057] It should be noted that the larger the sum of the temperature field non-uniformity index and the system dynamic response index at the current moment, the more drastic the temperature change at the current moment is caused by external disturbances (such as users opening doors or compressors starting at high power). In this case, the prediction model needs to assign a larger smoothing coefficient to the temperature data at the current moment to facilitate the immediate capture of temperature change trends and thus respond quickly. Conversely, the smaller the sum of the temperature field non-uniformity index and the system dynamic response index at the current moment, the smaller the smoothing coefficient needs to be assigned to the temperature data at the current moment for stable smoothing, effectively filtering out random noise and maintaining stability.

[0058] In this embodiment of the invention, the adaptive smoothing coefficient at the current moment is obtained:

[0059] ;

[0060] In the formula, The adaptive smoothing coefficient represents the current moment; Represents the preset minimum boundary; Representing a preset maximum boundary, in this embodiment of the invention, the preset... , In other embodiments, implementers may pre-set according to specific implementation conditions. as well as The value; The index representing the temperature field non-uniformity at the current moment; The system dynamic response exponent represents the current moment; exp() represents an exponential function with the natural constant as the base. Representing a preset sensitivity coefficient, in this embodiment of the invention, the preset... In order to right The changes are very sensitive. The value will increase slightly Pull towards the upper limit; Representing a preset translation coefficient, in this embodiment of the invention, the preset... , making When the value is approximately between 0.3 and 0.5, Significantly improves performance and allows for earlier response to potentially strenuous exercise;

[0061] The larger the value, the more severe the external disturbance to the system (such as the instant a user opens a door). In this case, the prediction model needs to assign a higher weight to the current temperature data to quickly capture the temperature change trend and suppress further temperature increases in uneven areas. Used to The value of is non-linearly mapped to the range of 0 to 1, therefore The closer the value is to 1, the closer the adaptive smoothing coefficient at the current moment is to the preset maximum boundary;

[0062] The smaller the value, the more stable the temperature in the wine cabinet of the variable frequency compressor at the current moment. The adaptive smoothing coefficient at the current moment is closer to the preset minimum boundary, which enables the prediction model to perform stable smoothing, effectively filter out random noise, and maintain stability.

[0063] It should be noted that the average temperature at the current moment is predicted based on the adaptive smoothing coefficient at the current moment.

[0064] Specifically, the average value of temperature data collected by all sensors at the current moment is used as the historical average temperature sequence. The adaptive smoothing coefficient at the current moment is substituted into the exponential smoothing formula to process the historical average temperature sequence, and the predicted average temperature value at the current moment is obtained.

[0065] It should be noted that due to the presence of stacked goods, uneven air circulation, and localized heat sources (such as LED lights) within the cabinet, there is often significant temperature field non-uniformity within the system. Traditional control methods often rely solely on PID control algorithms based on the average temperature, lacking direct feedback and suppression capabilities for temperature field non-uniformity. Therefore, this invention combines the current temperature field non-uniformity index to correct the error between the average temperature and the target temperature. If the error between the average temperature and the target temperature is smaller, but the temperature field non-uniformity index is larger, then the error between the average temperature and the target temperature is increased based on the temperature field non-uniformity index. This facilitates the subsequent PID control algorithm to prioritize adjusting the actual power of the variable frequency compressor and the circulating fan to eliminate the temperature difference.

[0066] In this embodiment of the invention, the control error at the current moment is obtained:

[0067] ;

[0068] In the formula, This represents the control error at the current moment; This represents the target temperature in the variable frequency compressor wine cabinet. The average predicted temperature at the current moment; The index representing the temperature field non-uniformity at the current moment; The preset non-uniformity penalty weight is used to quantify the direct impact of the temperature field non-uniformity index on control. In this embodiment of the invention, the preset weight is... In other embodiments, implementers may pre-determine specific implementation methods. The value;

[0069] An increase in the value indicates a greater temperature field non-uniformity index at the current moment. In this case, even if the predicted average temperature at the current moment is close to the target temperature in the variable frequency compressor wine cabinet, The value will also make The value of increases significantly, which makes the subsequent PID control algorithm prioritize adjusting the actual power of the variable frequency compressor and the circulating fan to eliminate the temperature difference, thus avoiding the defect of traditional control algorithms that only focus on the average temperature and ignore local hot spots.

[0070] S4: Calculate and output the actuator adjustment amount based on the control error.

[0071] In this embodiment of the invention, the control error at the current moment is input into the PID control algorithm to obtain the power adjustment amount of the variable frequency compressor and the power adjustment amount of the circulating fan. The power adjustment amount of the variable frequency compressor and the power adjustment amount of the circulating fan are sent to the drivers of the variable frequency compressor and the circulating fan to change the power of the variable frequency compressor and the circulating fan.

[0072] like Figure 2 The figure shows a comparison of the temperature field non-uniformity suppression effect provided by the embodiments of the present invention. The figure compares the dynamic changes of the temperature field non-uniformity index of the present invention (adaptive smoothing coefficient) and the prior art (fixed smoothing coefficient 0.25) under the same operating condition disturbance. It can be seen that when large external disturbances and local hot spots occur, the peak value of the curve of the present invention is significantly lower than that of the curve of the prior art. This indicates that the present invention (adaptive smoothing coefficient) can immediately increase the response speed when disturbances and local hot spots occur, and use the latest temperature to directly participate in the control, so that the system can quickly suppress the growth of temperature field non-uniformity. Therefore, by substituting the adaptive smoothing coefficient into the prediction and combining it with the temperature field non-uniformity index to calculate the control error, the coordinated control of average temperature control and temperature field uniformity control can be achieved, which greatly improves the stability of the system and its resistance to external shocks.

[0073] This invention also discloses a temperature control system for a variable frequency compressor, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a temperature control method for a variable frequency compressor provided by this invention.

[0074] The system also includes other components well-known to those skilled in the art, such as communication buses and communication interfaces, the setup and functions of which are known in the art and will not be described in detail here. In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0075] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A temperature control method for a variable frequency compressor, characterized in that, include: Multiple temperature data points at different locations inside the variable frequency compressor wine cabinet, as well as drive signals from the variable frequency compressor and the circulating fan, are collected to obtain several temperature data points and actuator status at the current moment. The variable frequency compressor wine cabinet is a complete unit, including a variable frequency compressor, a circulating fan, and actuators. The variable frequency compressor is the core refrigeration component, the circulating fan is the auxiliary temperature control component, and the actuator is the control execution carrier, which is the hardware unit that drives the variable frequency compressor and the circulating fan to start, stop, or adjust their speed. Based on several temperature data points and actuator status at the current moment, the temperature field non-uniformity index and system dynamic response index are obtained. The temperature field non-uniformity index is a weighted combination of the average sum of temperature differences and the rate of change of temperature differences; the system dynamic response index is the product of the actuator's potential capability and the average rate of change of temperature. Based on the temperature field non-uniformity index and the system dynamic response index, the adaptive smoothing coefficient at the current moment is obtained; the adaptive smoothing coefficient at the current moment is substituted into the exponential smoothing method to obtain the average temperature prediction value at the current moment. The control error at the current moment is obtained by weighting and combining the temperature field non-uniformity index with the deviation between the average temperature prediction value and the target temperature. The actuator adjustment amount is calculated and output based on the control error.

2. The temperature control method for a variable frequency compressor according to claim 1, characterized in that, The process of obtaining the temperature field non-uniformity index at the current moment includes: , The index representing the temperature field non-uniformity at the current moment; This represents the average temperature data collected by all sensors at the current moment. This represents the temperature data collected by the i-th temperature sensor at the current moment. This represents the number of temperature sensors arranged in the variable frequency compressor wine cabinet. This represents the average of the total temperature differences at the current moment; This represents the difference between the average total temperature difference at the current moment and the average total temperature difference at the previous moment; || represents the sampling period; || represents the absolute value sign. The weighting coefficient represents the rate of change of temperature difference; This represents the rate of change of temperature difference.

3. The temperature control method for a variable frequency compressor according to claim 2, characterized in that, The acquisition of the system dynamic response index includes: , The system dynamic response index represents the current moment. This represents the actual power of the variable frequency compressor at the current moment. This represents the actual power of the circulating fan at the current moment; This represents the rated maximum power of the variable frequency compressor; This represents the rated maximum power of the circulating fan; This represents the difference between the mean of all temperature data collected by all sensors at the current moment and the mean of all temperature data collected by all sensors at the previous moment. The value represents the sampling period; exp() represents an exponential function with the natural constant as the base.

4. The temperature control method for a variable frequency compressor according to claim 3, characterized in that, The process of obtaining the adaptive smoothing coefficient at the current moment includes: , The adaptive smoothing coefficient represents the current moment; Represents the preset minimum boundary; Represents the preset maximum boundary; The index representing the temperature field non-uniformity at the current moment; The system dynamic response exponent represents the current moment; exp() represents an exponential function with the natural constant as the base. This represents the preset sensitivity coefficient; This represents the preset translation coefficient.

5. The temperature control method for a variable frequency compressor according to claim 1, characterized in that, The step of obtaining the predicted average temperature at the current moment includes: The average temperature data collected by all sensors at the current moment is used to form a sequence of historical average temperature data. The adaptive smoothing coefficient at the current moment is then substituted into the exponential smoothing formula to process the historical average temperature sequence, thus obtaining the predicted average temperature value at the current moment.

6. The temperature control method for a variable frequency compressor according to claim 2, characterized in that, The process of obtaining the control error at the current moment includes: , This represents the control error at the current moment; This represents the target temperature in the variable frequency compressor wine cabinet. The average predicted temperature at the current moment; The index representing the temperature field non-uniformity at the current moment; This represents the preset non-uniformity penalty weight.

7. The temperature control method for a variable frequency compressor according to claim 1, characterized in that, The step of calculating and outputting the actuator adjustment amount based on the control error includes: The control error at the current moment is input into the PID control algorithm to obtain the power adjustment of the variable frequency compressor and the power adjustment of the circulating fan. The power adjustment of the variable frequency compressor and the power adjustment of the circulating fan are then sent to the drivers of the variable frequency compressor and the circulating fan to change their power.

8. The temperature control method for a variable frequency compressor according to claim 1, characterized in that, The acquisition of several temperature data points at the current moment includes: Preset sampling period A temperature sensor is placed at the top, middle, bottom, and air outlet of the variable frequency compressor wine cabinet to collect several temperature data points at each moment in real time.

9. The temperature control method for a variable frequency compressor according to claim 1, characterized in that, The acquisition of the actuator state includes: The drive signals of the variable frequency compressor and the circulating fan are read to obtain the actuator status at each moment. The actuator status includes the actual power of the variable frequency compressor and the actual power of the circulating fan.

10. A temperature control system for a variable frequency compressor, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement a temperature control method for a variable frequency compressor according to any one of claims 1-9.

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