Compressor system control method suitable for refrigerated cabinet

Abstract

The invention belongs to the field of compressor control, relates to a data analysis technology, and aims to solve the problem that the operation stability of a compressor cannot be guaranteed due to the fact that multiple parameters of the compressor cannot be controlled and analyzed in the prior art, in particular to a compressor system control method suitable for a refrigerated cabinet. Comprising the following steps: performing control test analysis on a compressor of the refrigerated cabinet: generating a test period, acquiring an external air temperature value of the refrigerated cabinet at the starting moment of the test period, marking the external air temperature value as an external temperature value, and performing numerical value setting on control parameters of the compressor at the starting moment of the test period; the control test analysis can be performed on the compressor of the refrigerated cabinet, the control parameters of the compressor are randomly set in the test time period of the test period, then the operation coefficient of the compressor in the test time period is calculated, and the operation state of the compressor is fed back through the operation coefficient. And data support is provided for the test time period differential marking and control optimization process.

Description

Technical Field

[0001] The invention belongs to the field of compressor control and relates to data analysis technology, and specifically is a compressor system control method suitable for a refrigerated cabinet. Background Art

[0002] The compressor is a driven fluid machine that boosts low-pressure gas to high-pressure gas. It is the heart of the refrigeration system. It sucks in low-temperature, low-pressure refrigerant gas through the intake pipe, compresses it through the operation of the motor to drive the piston, and then discharges high-temperature, high-pressure refrigerant gas to the exhaust pipe.

[0003] The invention patent with announcement number CN112346333B discloses a compressor speed control method based on BP neural network regulation. This control method integrates multiple PID models to achieve faster and more stable cross-regulation on the basis of traditional independent PID control. In the airborne environmental monitoring system, the temperature, pressure, electronic expansion valve opening, compressor internal motor temperature, compressor overheat valve opening and other factors are comprehensively considered to reasonably adjust the compressor speed to avoid regulation hysteresis due to repeated oscillations. However, this control method can only perform speed control, while other operating parameters of the compressor cannot be scientifically and effectively controlled, resulting in the inability to ensure the operating stability of the compressor. In addition, this control method cannot be combined with external environmental factors for control analysis, resulting in difficulty in balancing the energy consumption and cooling capacity of the compressor.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The object of the present invention is to provide a compressor system control method applicable to a refrigerator, which is used to solve the problem that the prior art cannot control and analyze multiple parameters of the compressor, resulting in the inability to ensure the operating stability of the compressor;

[0006] The technical problem to be solved by the present invention is: how to provide a compressor system control method suitable for a refrigerated cabinet that ensures the operating stability of the compressor through multi-parameter control analysis.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A compressor system control method applicable to a refrigerated cabinet comprises the following steps:

[0009] Step 1: Perform control test analysis on the compressor of the refrigerator: generate a test cycle and divide the test cycle into several test periods, obtain the external air temperature value of the refrigerator at the beginning of the test period and mark it as the external temperature value, and set the control parameters of the compressor at the beginning of the test period;

[0010] Step 2: Monitor and analyze the operation of the refrigerator compressor: obtain the operation coefficient YX of the compressor during the test period at the end of the test period;

[0011] Step 3: Conduct performance evaluation and analysis on the refrigerator compressor: mark the test period as a normal period or an abnormal period through the operation coefficient YX;

[0012] Step 4: Conduct statistical analysis on the test data of the refrigerator compressor: obtain the external temperature values ​​of all test time periods at the end of the test cycle, and form the external temperature range with the maximum and minimum values ​​of the external temperature values. Divide the external temperature range into several external temperature intervals, and mark the test time periods in which the external temperature values ​​are within the external temperature interval as matching time periods of the external temperature interval. The maximum and minimum values ​​of the control parameter setting values ​​corresponding to all matching time periods of the external temperature interval constitute the basic range of the external temperature interval; determine whether the external temperature interval has random setting characteristics.

[0013] Step 5: Perform control optimization analysis on the refrigerator compressor and obtain an optimized data set;

[0014] Step 6: Optimize the control of the refrigerator compressor by optimizing the data set.

[0015] Furthermore, in step one, the control parameters include inlet and outlet pressures, compression ratio and gas delivery volume, and the specific process of numerical setting includes: calling the numerical range corresponding to the control parameter, randomly selecting a numerical value from the numerical range as the set value of the control parameter, and setting the numerical value of the control parameter as the set value.

[0016] Furthermore, in step two, the process of obtaining the operating coefficient YX of the compressor during the test period includes: obtaining the energy consumption data NH and the refrigeration data ZL of the compressor during the test period and performing numerical calculations to obtain the operating coefficient YX, the refrigeration data ZL is the refrigeration capacity of the compressor during the test period, and the energy consumption data NH is the energy consumption value of the compressor during the test period.

[0017] Furthermore, in step three, the specific process of marking the test period as a normal period or an abnormal period includes: comparing the operating coefficient YX of the compressor with the preset operating threshold value YXmin at the end of the test period: if the operating coefficient YX is less than the operating threshold value YXmin, it is determined that the operating state of the compressor during the test period does not meet the requirements, and the corresponding test period is marked as an abnormal period, and the set value of the control parameter set at the start of the abnormal period is marked as an abnormal set value; if the operating coefficient YX is greater than or equal to the operating threshold value YXmin, it is determined that the operating state of the compressor during the test period meets the requirements, and the corresponding test period is marked as a normal period, and the set value of the control parameter set at the start of the normal period is marked as a positive set value.

[0018] Furthermore, in step four, the specific process of determining whether the external temperature interval has a random setting feature includes: determining whether the setting value of the control parameter corresponding to the matching time period of the external temperature interval contains an abnormal setting value: if so, determining that the external temperature interval has a random setting feature, and marking the corresponding external temperature interval as a random interval; if not, determining that the external temperature interval does not have a random setting feature, and marking the corresponding external temperature interval as a shortened interval.

[0019] Furthermore, in step five, the process of obtaining the optimized data set includes: marking the basic range of the special interval as the optimized range of the control parameter, forming a setting set of the control parameter by the set values ​​of the control parameter corresponding to the special interval, performing variance calculation on all elements in the setting set and obtaining the indentation coefficient, and determining whether the indentation coefficient is less than a preset indentation threshold and whether the setting set does not contain abnormal set values: if not, eliminating the maximum element and the minimum element in the setting set, and then recalculating the indentation coefficient; if so, forming the optimized range of the control parameter by the maximum element and the minimum element in the setting set; and forming the optimized data set of the compressor by the optimized ranges of the control parameters of all external temperature intervals.

[0020] Furthermore, in step six, the specific process of optimizing the control of the compressor of the refrigerator includes: generating a continuous control cycle after the test cycle ends and dividing the control cycle into several control time periods, the duration of the control period is equal to the duration of the test period, obtaining the external air temperature value of the refrigerator at the beginning of the control period and marking it as the temperature control value, retrieving the optimization range of the control parameter corresponding to the external temperature range of the temperature control value in the optimization data set, randomly selecting a value from the optimization range and marking it as the optimal control value of the control parameter, and setting the value of the control parameter as the optimal control value.

[0021] Furthermore, in step six, at the end of the control period, the operating coefficient YX of the compressor is also calculated and the operating state is determined. At the end of the control cycle, the optimized data set of the compressor is updated, and the updated optimized data set is used to optimize the compressor in the next control cycle.

[0022] The present invention has the following beneficial effects:

[0023] 1. Conduct control test analysis on the compressor of the refrigerator, randomly set the control parameters of the compressor during the test period of the test cycle, and then calculate its operating coefficient during the test period. Feedback the operating status of the compressor through the operating coefficient, and then provide data support for the differentiated marking and control optimization process of the test period;

[0024] 2. Evaluate and analyze the performance of the refrigerator compressor, differentiate the test periods according to the operating coefficient, and then distinguish the control parameter setting values ​​of the marked test periods, differentiate the setting values ​​of normal operating status and abnormal operating status, and then determine the random setting characteristics of the external temperature range, associate the operating status of the compressor with the external environment, and improve the energy utilization rate of the optimized control;

[0025] 3. Carry out control optimization analysis on the refrigerator compressor, mark the optimization ranges of the follow-up interval and the contraction interval respectively, optimize the compressor control in combination with the optimization ranges of all external temperature intervals, and accurately control the external ambient temperature and all control parameters within the control cycle to ensure the balance between the energy consumption and cooling capacity of the compressor. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 This is a flow chart of a method according to Embodiment 1 of the present invention;

[0028] Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] Embodiment 1: Figure 1 As shown, a compressor system control method applicable to a refrigerated cabinet comprises the following steps:

[0031] Step 1: Conduct control test analysis on the refrigerator compressor: Generate a test cycle and divide the test cycle into several test periods. At the beginning of the test period, obtain the external air temperature value of the refrigerator and mark it as the external temperature value. At the beginning of the test period, set the control parameters of the compressor. The control parameters include inlet and outlet pressures, compression ratio and gas flow rate. The inlet and outlet pressures of the compressor are the main indicators of the control working capacity, and their size directly affects the pressure ratio, output power, cooling effect, etc. The pressure ratio of the compressor is the ratio of the pressure of high-pressure gas to that of low-pressure gas. For compressors of the same model, if the compression ratio is too large, it will reduce efficiency, increase energy consumption, and even cause equipment failure. The gas flow rate is the mass of gas transported from the suction end to the exhaust end per unit time. The specific process of setting the value includes: calling the value range corresponding to the control parameter, randomly selecting a value from the value range as the set value of the control parameter, and setting the value of the control parameter to the set value.

[0032] Step 2: Monitor and analyze the operation of the refrigerator compressor: At the end of the test period, obtain the energy consumption data NH and refrigeration data ZL of the compressor, where the refrigeration data ZL is the refrigeration capacity of the compressor during the test period, and the energy consumption data NH is the energy consumption value of the compressor during the test period. The operation coefficient YX of the compressor during the test period is obtained by the formula YX=(k1×ZL) / (k2×NH), where k1 and k2 are both proportional coefficients, and k1>k2>1; randomly set the control parameters of the compressor during the test period of the test cycle, and then calculate its operation coefficient during the test period, and feedback the operating status of the compressor through the operation coefficient, thereby providing data support for the differentiated marking and control optimization process of the test period;

[0033] Step 3: Perform performance evaluation and analysis on the compressor of the refrigerator: compare the operating coefficient YX of the compressor with the preset operating threshold value YXmin at the end of the test period: if the operating coefficient YX is less than the operating threshold value YXmin, it is determined that the operating state of the compressor during the test period does not meet the requirements, and the corresponding test period is marked as an abnormal period, and the set value of the control parameter set at the beginning of the abnormal period is marked as an abnormal set value; if the operating coefficient YX is greater than or equal to the operating threshold value YXmin, it is determined that the operating state of the compressor during the test period meets the requirements, and the corresponding test period is marked as a normal period, and the set value of the control parameter set at the beginning of the normal period is marked as a positive set value;

[0034] Step 4: Statistical analysis of test data of the refrigerator compressor: at the end of the test cycle, the external temperature values ​​of all test periods are obtained, and the external temperature range is composed of the maximum and minimum values ​​of the external temperature values, and the external temperature range is divided into several external temperature intervals. The test period with the external temperature value within the external temperature interval is marked as the matching period of the external temperature interval, and the maximum and minimum values ​​of the control parameter setting values ​​corresponding to all matching periods of the external temperature interval constitute the basic range of the external temperature interval; determine whether the setting value of the control parameter corresponding to the matching period of the external temperature interval contains an abnormal setting value: if so, it is determined that the external temperature interval has a random setting feature, and the corresponding external temperature interval is marked as a random interval; if not, it is determined that the external temperature interval does not have a random setting feature, and the corresponding external temperature interval is marked as a contracted interval; the test period is differentially marked according to the operating coefficient, and then the control parameter setting value of the marked test period is distinguished, and the setting value of the normal operating state and the setting value of the abnormal operating state are differentially marked, so that the random setting feature of the external temperature interval can be determined, and the operating state of the compressor can be associated with the external environment, so as to improve the energy utilization rate of the optimized control.

[0035] Step 5: Perform control optimization analysis on the compressor of the refrigerator: mark the basic range of the special interval as the optimization range of the control parameter, form a setting set of the control parameter by the setting values ​​of the control parameter corresponding to the special interval, calculate the variance of all elements in the setting set and obtain the indentation coefficient, and determine whether the indentation coefficient is less than the preset indentation threshold and whether the setting set does not contain abnormal setting values: if not, remove the maximum element and the minimum element in the setting set, and then recalculate the indentation coefficient; if so, the optimization range of the control parameter is formed by the maximum element and the minimum element in the setting set; the optimization data set of the compressor is formed by the optimization range of the control parameters of all external temperature intervals;

[0036] Step 6: Optimize the control of the refrigerator compressor: after the test cycle is completed, a continuous control cycle is generated and the control cycle is divided into several control time periods. The length of the control period is equal to the length of the test period. At the beginning of the control period, the external air temperature value of the refrigerator is obtained and marked as the temperature control value. The optimization range of the control parameter corresponding to the external temperature interval of the temperature control value in the optimization data set is retrieved, a value is randomly selected from the optimization range and marked as the optimal control value of the control parameter, and the value of the control parameter is set as the optimal control value; at the end of the control period, the operation coefficient YX of the compressor is also calculated and the operation state is determined. At the end of the control cycle, the optimization data set of the compressor is updated, and the updated optimization data set is used to optimize the compressor in the next control cycle; the optimization ranges of the special interval and the special interval are marked respectively, and the compressor is optimized and controlled in combination with the optimization ranges of all external temperature intervals. The external ambient temperature and all control parameters are accurately controlled within the control cycle to ensure the balance between the energy consumption and cooling capacity of the compressor.

[0037] Embodiment 2: Figure 2 As shown, a compressor system control platform suitable for a refrigerated cabinet includes a control test module, an operation monitoring module, a performance evaluation module, a statistical analysis module, an optimization analysis module and an optimization control module; the control test module, the operation monitoring module, the performance evaluation module, the statistical analysis module, the optimization analysis module and the optimization control module are communicatively connected in sequence.

[0038] The control test module is used to perform control test analysis on the refrigerator compressor.

[0039] The operation monitoring module is used to monitor and analyze the operation of the refrigerator compressor and obtain the operation coefficient YX of the compressor during the test period.

[0040] The performance evaluation module is used to perform performance evaluation and analysis on the compressor of the refrigerated cabinet and mark the test period as a normal period or an abnormal period.

[0041] The statistical analysis module is used to perform statistical analysis on the test data of the refrigerator compressor and to determine whether the external temperature range has random setting characteristics.

[0042] The optimization analysis module is used to perform control optimization analysis on the refrigerator compressor and obtain an optimized data set.

[0043] The optimization control module is used to optimize the control of the compressor of the refrigerated cabinet and to periodically update the optimization data set.

[0044] A compressor system control method suitable for a refrigerator generates a test cycle and divides the test cycle into several test time periods during operation. At the beginning of the test time period, the external air temperature value of the refrigerator is obtained and marked as the external temperature value. At the beginning of the test time period, the control parameter of the compressor is set numerically. At the end of the test time period, the operation coefficient YX of the compressor in the test time period is obtained. The test time period is marked as a normal time period or an abnormal time period by the operation coefficient YX. At the end of the test cycle, the external temperature values ​​of all test time periods are obtained, the maximum and minimum values ​​of the external temperature values ​​constitute an external temperature range, the external temperature range is divided into several external temperature intervals, the test time period with the external temperature value within the external temperature interval is marked as a matching time period of the external temperature interval, and the maximum and minimum values ​​of the control parameter setting values ​​corresponding to all matching time periods of the external temperature interval constitute a basic range of the external temperature interval; it is determined whether the external temperature interval has a random setting feature; and the control optimization analysis of the compressor of the refrigerator is performed to obtain an optimized data set.

[0045] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0046] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the real value. The coefficients in the formula are set by technicians in this field according to the actual situation; for example: formula YX = (k1×ZL) / (k2×NH); technicians in this field collect multiple groups of sample data and set corresponding operating coefficients for each group of sample data; substitute the set operating coefficients and the collected sample data into the formula, any two formulas constitute a set of two-variable linear equations, screen the calculated coefficients and take the average, and obtain the values ​​of k1 and k2 as 3.83 and 2.51 respectively;

[0047] The size of the coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the coefficient depends on the amount of sample data and the initial setting of the corresponding operating coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantified value, such as the operating coefficient is proportional to the value of the refrigeration data.

[0048] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0049] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A compressor system control method suitable for a refrigerator, characterized in that: The following steps are involved: Step 1: Perform control test analysis on the compressor of the refrigerator: generate a test cycle and divide the test cycle into several test periods, obtain the external air temperature value of the refrigerator at the beginning of the test period and mark it as the external temperature value, and set the control parameters of the compressor at the beginning of the test period; Step 2: Monitor and analyze the operation of the refrigerator compressor: obtain the operation coefficient YX of the compressor during the test period at the end of the test period; Step 3: Conduct performance evaluation and analysis on the refrigerator compressor: mark the test period as a normal period or an abnormal period through the operation coefficient YX; Step 4: Conduct statistical analysis on the test data of the refrigerator compressor: obtain the external temperature values ​​of all test time periods at the end of the test cycle, and form the external temperature range with the maximum and minimum values ​​of the external temperature values. Divide the external temperature range into several external temperature intervals, and mark the test time periods in which the external temperature values ​​are within the external temperature interval as matching time periods of the external temperature interval. The maximum and minimum values ​​of the control parameter setting values ​​corresponding to all matching time periods of the external temperature interval constitute the basic range of the external temperature interval; determine whether the external temperature interval has random setting characteristics. Step 5: Perform control optimization analysis on the refrigerator compressor and obtain an optimized data set; Step 6: Optimize the control of the refrigerator compressor by optimizing the data set.

2. A compressor system control method suitable for a refrigerator according to claim 1, characterized in that: In step one, the control parameters include inlet and outlet pressures, compression ratio and gas delivery volume, and the specific process of numerical setting includes: calling the numerical range corresponding to the control parameter, randomly selecting a numerical value from the numerical range as the set value of the control parameter, and setting the numerical value of the control parameter to the set value.

3. A compressor system control method suitable for a refrigerator according to claim 2, characterized in that: In step two, the process of obtaining the operating coefficient YX of the compressor during the test period includes: obtaining the energy consumption data NH and the refrigeration data ZL of the compressor during the test period and performing numerical calculations to obtain the operating coefficient YX, the refrigeration data ZL is the refrigeration capacity of the compressor during the test period, and the energy consumption data NH is the energy consumption value of the compressor during the test period.

4. A compressor system control method suitable for a refrigerator according to claim 3, characterized in that: In step three, the specific process of marking the test period as a normal period or an abnormal period includes: comparing the operating coefficient YX of the compressor with the preset operating threshold value YXmin at the end of the test period: if the operating coefficient YX is less than the operating threshold value YXmin, it is determined that the operating state of the compressor during the test period does not meet the requirements, and the corresponding test period is marked as an abnormal period, and the set value of the control parameter set at the beginning of the abnormal period is marked as an abnormal set value; if the operating coefficient YX is greater than or equal to the operating threshold value YXmin, it is determined that the operating state of the compressor during the test period meets the requirements, and the corresponding test period is marked as a normal period, and the set value of the control parameter set at the beginning of the normal period is marked as a positive set value.

5. A compressor system control method suitable for a refrigerator according to claim 4, characterized in that: In step four, the specific process of determining whether the external temperature interval has a random setting feature includes: determining whether the setting value of the control parameter corresponding to the matching time period of the external temperature interval contains an abnormal setting value: if so, it is determined that the external temperature interval has a random setting feature, and the corresponding external temperature interval is marked as a random interval; if not, it is determined that the external temperature interval does not have a random setting feature, and the corresponding external temperature interval is marked as a shortened interval.

6. A compressor system control method suitable for a refrigerator according to claim 5, characterized in that: In step five, the process of obtaining the optimized data set includes: marking the basic range of the special interval as the optimized range of the control parameter, forming a setting set of the control parameter by the set values ​​of the control parameter corresponding to the special interval, performing variance calculation on all elements in the setting set and obtaining the indentation coefficient, determining whether the indentation coefficient is less than a preset indentation threshold and whether the setting set does not contain abnormal set values: if not, eliminating the maximum element and the minimum element in the setting set, and then recalculating the indentation coefficient; if so, forming the optimized range of the control parameter by the maximum element and the minimum element in the setting set; and forming the optimized data set of the compressor by the optimized ranges of the control parameters of all external temperature intervals.

7. A compressor system control method suitable for a refrigerator according to claim 6, characterized in that: In step six, the specific process of optimizing the control of the refrigerator compressor includes: generating a continuous control cycle after the test cycle ends and dividing the control cycle into several control time periods, the duration of the control period is equal to the duration of the test period, obtaining the external air temperature value of the refrigerator at the beginning of the control period and marking it as the temperature control value, retrieving the optimization range of the control parameter corresponding to the external temperature range of the temperature control value in the optimization data set, randomly selecting a value from the optimization range and marking it as the optimal control value of the control parameter, and setting the value of the control parameter as the optimal control value.

8. A compressor system control method suitable for a refrigerator according to claim 7, characterized in that: In step six, at the end of the control period, the operating coefficient YX of the compressor is also calculated and the operating state is determined. At the end of the control period, the optimized data set of the compressor is updated, and the updated optimized data set is used to optimize the compressor in the next control period.

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