Auto-cascade cycle control system for ultralow environment temperature

Abstract

The invention belongs to the technical field of heat exchangers, and discloses an auto-cascade cycle control system for ultralow ambient temperature, comprising a temperature acquisition module for acquiring ambient temperature according to a preset frequency and forming a temperature sequence; the environment state analysis module calculates a corrected environment index according to the temperature sequence and further determines an environment state; the regulation and control target determination module determines a regulation and control target based on the environment state; the control parameter acquisition module determines a control item according to the regulation and control target, and acquires a control parameter by using a corresponding optimization method; the control execution module executes control according to the control parameters; the operation mode is dynamically adjusted through an intelligent control strategy, a differential control algorithm is adopted for different operation states, and efficient and stable operation under various environmental conditions is achieved. The system can intelligently adapt to various environmental conditions, and an optimal control strategy is adopted under different working conditions, so that efficient and stable operation is realized under an ultra-low environment temperature condition.

Description

Technical Field

[0001] The present invention relates to the technical field of heat exchangers, and more specifically, to a self-cascading cycle control system for ultra-low ambient temperature. Background Art

[0002] At present, in the field of ultra-low temperature heating, the main technologies used include single-stage compression, quasi-two-stage compression, two-stage compression and multi-stage cascade cycle. However, these technologies have certain limitations in practical applications. Single-stage compression and quasi-two-stage compression systems are difficult to meet heating needs under a large cycle temperature span, which may cause the compressor to shut down. Although two-stage compression and multi-stage cascade cycle can solve some problems, they are costly and complex in structure, which is not conducive to large-scale application.

[0003] In recent years, the cascade system has gradually attracted attention due to its unique advantages. The system uses only one compressor, and through the reasonable combination of high and low boiling point mixed refrigerants, it achieves structural simplification and cost reduction. However, in deep cold and low temperature environments, the cascade system still faces many challenges. These mainly include how to improve the product performance of the unit and ensure the economic operation under harsh working conditions with a large cycle temperature span; how to effectively reduce the exhaust temperature of the unit and extend the service life of the compressor; how to maximize the operating temperature range of the unit and ensure that the suction pressure of the unit is higher than the low-pressure shutdown pressure under ultra-low ambient temperatures; and how to expand the use area and applicable scenarios of the unit. Therefore, it is difficult for conventional cascade cycles to ensure energy efficiency in large temperature spans, and may even cause problems such as low-pressure shutdown and high exhaust temperature alarms. Summary of the invention

[0004] In order to overcome the problems that the prior art is difficult to ensure energy efficiency over a large temperature span, and may even cause low-pressure shutdown, high exhaust temperature alarm and other problems, the present invention proposes a self-cascading cycle control system for ultra-low ambient temperature to solve the above problems.

[0005] The present invention provides the following technical solutions:

[0006] A self-cascade cycle control system for ultra-low ambient temperature, comprising:

[0007] The temperature acquisition module is used to collect the ambient temperature at a preset frequency and sort the collected ambient temperature data in chronological order to obtain an ambient temperature sequence;

[0008] An environmental state analysis module is used to obtain a basic environmental index and an environmental correction parameter according to an environmental temperature sequence, use the environmental correction parameter to correct the basic environmental index to obtain a corrected environmental index, and determine the environmental state according to the corrected environmental index;

[0009] A control target determination module is used to determine the control target according to preset control target rules and environmental conditions;

[0010] A control parameter acquisition module, configured to determine control items according to a preset control item rule and a regulation target, and acquire control parameters by using corresponding optimization methods according to the control items;

[0011] A control execution module, configured to execute control according to the acquired control parameters.

[0012] Preferably, the basic environment index is the latest acquired environmental temperature value in the environmental temperature sequence; the environmental correction parameters include a fluctuation parameter and a trend parameter; the environmental states include a normal state, a low temperature state, and an ultra-low temperature state.

[0013] Preferably, the corrected environmental index is calculated by the following formula:

[0014] XZ = DZ + tanh(qs) × ln(1 + bd),

[0015] wherein, XZ represents the corrected environmental index, DZ represents the basic environmental index, qs represents the trend parameter, and bd represents the fluctuation parameter.

[0016] Preferably, the steps for acquiring the environmental correction parameters include:

[0017] Acquire an environmental temperature sequence, remove outliers and perform smoothing processing to obtain a smoothed environmental temperature sequence;

[0018] Acquire the standard deviation of the smoothed environmental temperature sequence as the fluctuation parameter;

[0019] Extract the latest n data from the smoothed environmental temperature sequence at a preset interval to form an analysis sequence, where n ≥ 10;

[0020] Set a sliding window with a size of m on the analysis sequence, where 1 < m < n, and extract content through the sliding window to obtain n - m + 1 subsequences with a size of m;

[0021] Perform linear regression on each subsequence, and record the slope of the subsequence as k i ; wherein, i represents the index, i = 1, 2,..., n - m + 1, k i represents the slope of the i-th subsequence;

[0022] Calculate the trend parameter by using the following formula:

[0023]

[0024] wherein, ω i represents the weight of the i-th subsequence, and the calculation formula of ω i is:

[0025]

[0026] The environmental correction parameters are composed using volatility parameters and trend parameters.

[0027] Preferably, the step of determining the environmental state according to the modified environmental index comprises:

[0028] Setting an index threshold, wherein the index threshold includes a low temperature index and an ultra-low temperature index, wherein the low temperature index is greater than the ultra-low temperature index;

[0029] Initialize a state record array Q of length l and the current state record Q_c;

[0030] Compare the modified environment index with the index threshold and update the current state record Q_c:

[0031] When the corrected environmental index is greater than the low temperature index, Q_c is set to normal state;

[0032] When the corrected environmental index is less than or equal to the low temperature index and greater than the ultra-low temperature index, Q_c is set to a low temperature state;

[0033] When the corrected environmental index is less than or equal to the ultra-low temperature index, Q_c is set to an ultra-low temperature state;

[0034] Add Q_c to the end of the state record array Q, and remove the earliest state record in the state record array Q, keeping the array length l;

[0035] Statistics state record array Q state distribution:

[0036] If all elements in Q are in the same state, then that state is determined as the current environment state;

[0037] If there are different states in Q, the environment state remains unchanged.

[0038] Preferably, the control target includes maintaining the operation of the main circulation path, starting the air supply path and starting the hot gas bypass path; the preset control target rules include:

[0039] When the environmental status is normal, the control target is determined to maintain the operation of the main circulation road;

[0040] When the environment is in a low temperature state, the control target is determined to start the air supply circuit;

[0041] When the environmental state is an ultra-low temperature state, the control target is determined to start the hot gas bypass path.

[0042] Preferably, the preset control item rules include:

[0043] When the control target is to maintain the operation of the main circulation road, the control item is determined to be the opening of the main circulation road;

[0044] When the control target is to start the air supply circuit, the control items are determined as the main circulation circuit opening and the air supply circuit opening;

[0045] When the control target is to start the hot gas bypass, the control items are determined as the main circulation opening, the air supply opening and the hot gas bypass opening.

[0046] Preferably, the step of obtaining control parameters using corresponding optimization methods according to control items includes:

[0047] When the control item is the main circulation road opening, the main circulation road opening adjustment amount is calculated using the PID control algorithm, and the main circulation road opening adjustment amount is used as the control parameter;

[0048] When the control items are the main circulation opening and the supplementary air circuit opening, the main circulation opening is set to the maximum value, the supplementary air circuit opening is calculated according to the ambient temperature and the system pressure ratio using the fuzzy control algorithm, and the main circulation opening and the supplementary air circuit opening are used as control parameters;

[0049] When the control items are the main circulation opening, the supplementary air circuit opening and the hot gas bypass opening, the main circulation opening and the supplementary air circuit opening are set to the maximum value, the hot gas bypass opening is calculated using an adaptive control algorithm, and the main circulation opening, the supplementary air circuit opening and the hot gas bypass opening are used as control parameters.

[0050] Preferably, the calculation of the main circulation opening by using the PID control algorithm includes: setting a target intake temperature; monitoring the actual intake temperature in real time; calculating the deviation between the target temperature and the actual temperature, and calculating the cumulative value and the rate of change of the temperature deviation over time; calculating the main circulation opening adjustment amount according to preset proportional, integral and differential parameters, combined with the temperature deviation, the cumulative value of the deviation and the rate of change of the deviation;

[0051] The method of using a fuzzy control algorithm to calculate the opening of the air supply circuit according to the ambient temperature and the system pressure ratio includes: dividing the ambient temperature and the system pressure ratio into three levels: low, medium, high and small, medium, and large; establishing a fuzzy rule base to define the adjustment strategy of the opening of the air supply circuit under different combinations of ambient temperature and system pressure ratio; determining the membership degree of the current ambient temperature and system pressure ratio in their respective levels; deriving the fuzzy output of the opening of the air supply circuit based on the fuzzy rule base and the membership degree; defuzzifying the fuzzy output and converting it into a specific value of the opening of the air supply circuit;

[0052] The use of an adaptive control algorithm to calculate the opening of the hot gas bypass passage includes: setting upper and lower limits of a target intake pressure; monitoring the system intake pressure in real time; calculating a deviation between the actual intake pressure and a median of a target pressure range; adjusting an adaptive coefficient based on the pressure deviation and a current system state; and using the adjusted adaptive coefficient to calculate the opening of the hot gas bypass passage.

[0053] The present invention provides a self-cascading circulation control system for ultra-low ambient temperature, which has the following beneficial effects:

[0054] First of all, the system adopts an intelligent control strategy, which can dynamically adjust the operating mode according to the changes in ambient temperature. The system collects and analyzes the ambient temperature sequence and calculates the corrected environmental index to accurately judge the current environmental status. This method not only takes into account the instantaneous temperature, but also fully considers the temperature change trend and fluctuation, making the environmental status judgment more accurate and stable. According to the judged environmental status, the system can automatically select the most suitable operating mode, such as maintaining the operation of the main circulation line, starting the air supply line or starting the hot gas bypass line. This adaptive control method enables the system to always maintain efficient and stable operation under various environmental conditions, greatly expanding the use area and applicable scenarios of the unit.

[0055] Secondly, the system adopts differentiated control algorithms for different operating states to achieve more precise and efficient control. The PID control algorithm is used in normal environmental conditions, the fuzzy control algorithm is used in low temperature conditions, and the adaptive control algorithm is used in ultra-low temperature conditions. This diversified control strategy fully considers the characteristics and requirements of the system under different working conditions, ensuring that the system can achieve optimal performance and efficiency under various environmental conditions, greatly improving the adaptability and reliability of the system.

[0056] In summary, the system of the present invention can intelligently adapt to various environmental conditions and adopt the optimal control strategy under different working conditions, thereby achieving efficient and stable operation under ultra-low ambient temperature conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 The module schematic diagram of a self-cascading cycle control system for ultra-low ambient temperature of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.

[0059] Example 1

[0060] See also Figure 1 In this embodiment, a self-cascade cycle control system for ultra-low ambient temperature includes:

[0061] The temperature acquisition module is used to acquire the ambient temperature at a preset frequency, and sort the acquired ambient temperature data in chronological order to obtain an ambient temperature sequence;

[0062] In this embodiment, the ambient temperature is acquired by a temperature sensor at a preset frequency (such as every 5 minutes). These temperature data are sorted in the order of acquisition time to form an ambient temperature sequence. This sequence contains the changes in the ambient temperature over a period of time and provides basic data for subsequent analysis.

[0063] The environmental state analysis module is used to obtain a basic environmental index and an environmental correction parameter according to the ambient temperature sequence, use the environmental correction parameter to correct the basic environmental index to obtain a corrected environmental index, and determine the environmental state according to the corrected environmental index;

[0064] The basic environmental index is the latest acquired ambient temperature value in the ambient temperature sequence; the environmental correction parameters include a fluctuation parameter and a trend parameter; the environmental states include a normal state, a low temperature state, and an ultra-low temperature state.

[0065] The corrected environmental index is calculated by the following formula:

[0066] XZ = DZ + tanh(qs) × ln(1 + bd),

[0067] In the formula, XZ represents the corrected environmental index, DZ represents the basic environmental index, qs represents the trend parameter, and bd represents the fluctuation parameter.

[0068] The steps for obtaining the environmental correction parameters include:

[0069] Obtain the ambient temperature sequence, remove outliers and perform smoothing processing to obtain a smoothed ambient temperature sequence;

[0070] Obtain the standard deviation of the smoothed ambient temperature sequence as the fluctuation parameter;

[0071] Extract the latest n data from the smoothed ambient temperature sequence at a preset interval to form an analysis sequence, where n ≥ 10;

[0072] Set a sliding window of size m on the analysis sequence, where 1 < m < n, and extract the content through the sliding window to obtain n - m + 1 subsequences of size m;

[0073] Perform linear regression on each subsequence to obtain the slope of the subsequence denoted as k i ; where, i represents the index, i = 1, 2,..., n - m + 1, k i represents the slope of the i-th subsequence;

[0074] Use the following formula to calculate the trend parameter:

[0075]

[0076] In the formula, ω i represents the weight of the i-th subsequence, ω i The calculation formula is:

[0077]

[0078] The environmental correction parameters are composed using volatility parameters and trend parameters.

[0079] The step of determining the environmental state according to the modified environmental index comprises:

[0080] Setting an index threshold, wherein the index threshold includes a low temperature index and an ultra-low temperature index, wherein the low temperature index is greater than the ultra-low temperature index;

[0081] Initialize a state record array Q of length l and the current state record Q_c;

[0082] Compare the modified environment index with the index threshold and update the current state record Q_c:

[0083] When the corrected environmental index is greater than the low temperature index, Q_c is set to normal state;

[0084] When the corrected environmental index is less than or equal to the low temperature index and greater than the ultra-low temperature index, Q_c is set to a low temperature state;

[0085] When the corrected environmental index is less than or equal to the ultra-low temperature index, Q_c is set to an ultra-low temperature state;

[0086] Add Q_c to the end of the state record array Q, and remove the earliest state record in the state record array Q, keeping the array length l;

[0087] Statistics state record array Q state distribution:

[0088] If all elements in Q are in the same state, then that state is determined as the current environment state;

[0089] If there are different states in Q, the environment state remains unchanged.

[0090] In this embodiment, the latest temperature value collected in the ambient temperature sequence is first taken as the basic environmental index. This index reflects the current instantaneous temperature conditions. Next, the environmental correction parameters are calculated. This process includes the following steps:

[0091] First, the ambient temperature sequence is subjected to outlier removal and smoothing. Outlier removal can be performed using methods such as median filtering, while smoothing can be performed using the moving average method. The temperature sequence processed in this way can better reflect the true trend of temperature changes and reduce the influence of accidental factors. Then, the standard deviation of the smoothed sequence is calculated and used as the fluctuation parameter. This parameter reflects the severity of temperature changes. Next, a certain number of recent data are extracted from the smoothed temperature sequence at preset intervals (such as 1 data every 5, a total of 20 data) to form an analysis sequence. On this analysis sequence, a sliding window is set, and multiple subsequences are extracted through this window. For each subsequence, a linear regression analysis is performed to obtain the slope of each subsequence. These slopes reflect the trend of temperature changes in different time periods. Using a predefined weight formula, a comprehensive trend parameter is calculated in combination with these slopes. With the basic environmental index, fluctuation parameter and trend parameter, the modified environmental index can be calculated. The calculation of the modified environmental index takes into account the current temperature, temperature change trend and temperature change amplitude, so it can more comprehensively reflect the environmental status.

[0092] Finally, the modified environmental index is compared with the preset threshold to determine the current environmental state. In order to avoid frequent changes in environmental state, a fixed-length array of state records is maintained. Each time a new state is determined, it is added to the end of the array and the oldest record is removed. The environmental state is updated only when all state records in the array are consistent; otherwise, the environmental state remains unchanged.

[0093] This method can comprehensively consider the instantaneous value, change trend and fluctuation of temperature and accurately judge the current environmental status, which provides a reliable basis for subsequent control strategy adjustment.

[0094] A control target determination module is used to determine the control target according to preset control target rules and environmental conditions;

[0095] The control objectives include maintaining the operation of the main circulation path, starting the air supply path and starting the hot gas bypass path; the preset control objective rules include:

[0096] When the environmental status is normal, the control target is determined to maintain the operation of the main circulation road;

[0097] When the environment is in a low temperature state, the control target is determined to start the air supply circuit;

[0098] When the environmental state is an ultra-low temperature state, the control target is determined to start the hot gas bypass path.

[0099] In this embodiment, the control target determination module determines the control target according to the preset control target rules and environmental conditions. There are three types of control targets: maintaining the operation of the main circulation road, starting the air supply road, and starting the hot gas bypass road. The process of determining the control target is as follows: First, check the current environmental conditions. If the environmental conditions are normal, the control target will be set to maintain the operation of the main circulation road. In this case, the heating demand can be met only by the main circulation road, and there is no need to start an additional auxiliary circuit. If the environmental conditions are low temperature, the control target will be set to start the air supply road. At this time, the main circulation road and the air supply road are running at the same time to cope with the lower ambient temperature. The start of the air supply road can significantly improve the heating capacity and energy efficiency ratio in a low temperature environment. When the environmental conditions are determined to be an ultra-low temperature state, the control target will be set to start the hot gas bypass road. In this extreme case, the main circulation road, the air supply road, and the hot gas bypass road are running at the same time to ensure that they can continue to work normally in an ultra-low temperature environment to prevent shutdown due to low pressure.

[0100] Through this mechanism of determining the control target based on the environmental state, the operation mode can be flexibly adjusted according to different ambient temperature conditions, which not only ensures the heating effect, but also improves adaptability and reliability. This method enables the self-cascade cycle to operate efficiently and stably in a wider temperature range, and is particularly suitable for use in areas with large ambient temperature changes and severe winters.

[0101] It should be noted that the main circulation path is the basic operation path of the self-cascade cycle and is usually used at normal ambient temperature. It includes basic components such as compressor, condenser, expansion valve and evaporator, which can meet the heating needs under normal working conditions. When the environmental state is judged to be normal, the control target will be set to maintain the operation of the main circulation path to maintain the basic heating function. The air supply path is an auxiliary circuit added on the basis of the main circulation path, which is usually enabled when the ambient temperature is low. Its main function is to increase the heating amount and efficiency by injecting gaseous refrigerant into the intermediate stage of the compressor. When the environmental state is judged to be a low temperature state, the control target will be set to start the air supply path. This can improve the heating performance in a low temperature environment, while reducing the exhaust temperature of the compressor and extending the life of the equipment. The hot gas bypass path is a protective measure taken in an extremely low temperature environment. It increases the temperature and pressure of the evaporator by directly introducing part of the high temperature and high pressure refrigerant into the evaporator. When the environmental state is judged to be an ultra-low temperature state, the control target will be set to start the hot gas bypass path. This operation can prevent shutdown due to low evaporation pressure at extremely low temperatures, thereby expanding the operating temperature range of the equipment.

[0102] A control parameter acquisition module is used to determine the control item according to the preset control item rules and the regulation target, and obtain the control parameter according to the control item using the corresponding optimization method;

[0103] The preset control item rules include:

[0104] When the control target is to maintain the operation of the main circulation road, the control item is determined to be the opening of the main circulation road;

[0105] When the control target is to start the air supply circuit, the control items are determined as the main circulation circuit opening and the air supply circuit opening;

[0106] When the control target is to start the hot gas bypass, the control items are determined as the main circulation opening, the air supply opening and the hot gas bypass opening.

[0107] The step of obtaining control parameters using corresponding optimization methods according to control items includes:

[0108] When the control item is the main circulation road opening, the PID control algorithm is used to calculate the main circulation road opening adjustment amount, and the main circulation road opening adjustment amount is used as the control parameter;

[0109] When the control items are the main circulation opening and the supplementary air circuit opening, the main circulation opening is set to the maximum value, the supplementary air circuit opening is calculated according to the ambient temperature and the system pressure ratio using the fuzzy control algorithm, and the main circulation opening and the supplementary air circuit opening are used as control parameters;

[0110] When the control items are the main circulation opening, the supplementary air circuit opening and the hot gas bypass opening, the main circulation opening and the supplementary air circuit opening are set to the maximum value, the hot gas bypass opening is calculated using an adaptive control algorithm, and the main circulation opening, the supplementary air circuit opening and the hot gas bypass opening are used as control parameters.

[0111] The method of using the PID control algorithm to calculate the main circulation opening includes: setting a target intake temperature; monitoring the actual intake temperature in real time; calculating the deviation between the target temperature and the actual temperature, and calculating the cumulative value and the rate of change of the temperature deviation over time; calculating the main circulation opening adjustment amount according to preset proportional, integral and differential parameters, combined with the temperature deviation, the cumulative value of the deviation and the rate of change of the deviation;

[0112] The method of using a fuzzy control algorithm to calculate the opening of the air supply circuit according to the ambient temperature and the system pressure ratio includes: dividing the ambient temperature and the system pressure ratio into three levels: low, medium, high and small, medium, and large; establishing a fuzzy rule base to define the adjustment strategy of the opening of the air supply circuit under different combinations of ambient temperature and system pressure ratio; determining the membership degree of the current ambient temperature and system pressure ratio in their respective levels; deriving the fuzzy output of the opening of the air supply circuit based on the fuzzy rule base and the membership degree; defuzzifying the fuzzy output and converting it into a specific value of the opening of the air supply circuit;

[0113] The use of an adaptive control algorithm to calculate the opening of the hot gas bypass passage includes: setting upper and lower limits of a target intake pressure; monitoring the system intake pressure in real time; calculating a deviation between the actual intake pressure and a median of a target pressure range; adjusting an adaptive coefficient based on the pressure deviation and a current system state; and using the adjusted adaptive coefficient to calculate the opening of the hot gas bypass passage.

[0114] In this embodiment, the control parameter acquisition module selects the control item according to the preset control item rules and the determined control target, and uses the corresponding optimization method to obtain the control parameter. It should be noted that the PID control algorithm, the fuzzy control algorithm and the adaptive control algorithm are all existing mature technologies and have been widely used in the field of industrial control. In this embodiment, different control algorithms are selected for different operating states. This process is divided into three cases according to the operating state:

[0115] When the control target is to maintain the operation of the main circulation road, only the main circulation road opening needs to be controlled. At this time, the PID control algorithm is used to calculate the adjustment amount of the main circulation road opening. The PID control algorithm is selected because the main circulation road is the basic operation path, and its control target is relatively simple and clear, mainly to maintain a stable suction temperature. The PID control algorithm has the characteristics of simple structure, high reliability, and strong adaptability, and can effectively handle linear control problems. For example, in actual operation, a target suction temperature is first set, such as 5°C. Then, the actual suction temperature is monitored in real time through a temperature sensor. The deviation between the target temperature and the actual temperature is calculated, and the cumulative value and change rate of this deviation over time are calculated. Assuming that at a certain moment, the actual suction temperature is 3°C, then the temperature deviation is 2°C. The adjustment amount of the main circulation road opening will be calculated based on the preset proportional, integral and differential parameters, combined with the current temperature deviation, cumulative deviation value and deviation change rate. For example, if the calculated adjustment amount is +5%, it means that the main circulation road opening needs to be increased by 5%.

[0116] When the control target is to start the air supply circuit, it is necessary to control the main circulation circuit opening and the air supply circuit opening at the same time. In this case, the main circulation circuit opening is set to the maximum value to ensure the heating capacity of the main circulation. For the control of the air supply circuit opening, a fuzzy control algorithm is used. The fuzzy control algorithm is selected because the control of the air supply circuit involves multiple input variables (such as ambient temperature and pressure ratio), and the relationship between these variables and the optimal air supply volume is relatively complex and difficult to describe with an accurate mathematical model. The fuzzy control algorithm can handle this multi-input, nonlinear control problem well. For example, in practical applications, the ambient temperature and pressure ratio are first divided into three levels: low, medium, high and small, medium, and large. For example, the ambient temperature may be divided into: low temperature (less than -10℃), medium temperature (-10℃ to 0℃), high temperature (greater than 0℃); the pressure ratio may be divided into: small (less than 2.5), medium (2.5 to 3.5), and large (greater than 3.5). Then, a fuzzy rule base is established to define the adjustment strategy of the air supply circuit opening under different combinations of ambient temperature and pressure ratio. For example, when the ambient temperature is low and the pressure ratio is large, a larger air supply circuit opening may be required. According to the current ambient temperature and pressure ratio, their membership levels in their respective levels are determined. Based on the fuzzy rule base and these membership levels, the fuzzy output of the air supply circuit opening is derived. Finally, this fuzzy output is defuzzified and converted into a specific air supply circuit opening value, such as 30%.

[0117] When the control target is to start the hot gas bypass, it is necessary to control the opening of the main circulation, the opening of the supplementary air circuit, and the opening of the hot gas bypass. In this case, the opening of the main circulation and the supplementary air circuit are set to the maximum value to provide the maximum heating capacity. For the control of the opening of the hot gas bypass, an adaptive control algorithm is used. The adaptive control algorithm is selected because the hot gas bypass is mainly used in an extremely low temperature environment, in which the operating characteristics may change significantly, and these changes are difficult to accurately model in advance. The adaptive control algorithm can automatically adjust the control parameters according to the actual operating status, which makes it particularly suitable for handling situations with large changes in characteristics or high uncertainty. For example, in the actual control process, the upper and lower limits of the target suction pressure are first set, such as 0.3MPa to 0.4MPa. Then, the suction pressure is monitored in real time by a pressure sensor. The deviation between the actual suction pressure and the median of the target pressure range is calculated. For example, if the actual suction pressure is 0.25MPa and the median of the target pressure range is 0.35MPa, the pressure deviation is 0.1MPa. According to this pressure deviation and the current state, the adaptive coefficient is adjusted. Finally, the opening degree of the hot gas bypass passage is calculated using the adjusted adaptive coefficient, such as 15%.

[0118] In this way, the opening of each circuit can be flexibly adjusted according to different operating conditions and environmental conditions to achieve the best heating effect and efficiency. This control strategy enables the self-cascading cycle to maintain stable and efficient operation at various ambient temperatures, especially to ensure reliable heating performance under ultra-low ambient temperature conditions. By selecting different control algorithms in a targeted manner, this embodiment achieves precise control of the self-cascading cycle under different operating conditions, significantly improving the adaptability and reliability.

[0119] The control execution module is used to execute control according to the acquired control parameters.

[0120] In this embodiment, the control execution module is responsible for executing the actual system control according to the control parameters calculated by the control parameter acquisition module. The system is precisely controlled by adjusting the corresponding valves on each loop. The control execution module converts the calculated opening value into a corresponding control signal, such as a voltage or current signal, and sends it to the driving devices of these valves, thereby realizing precise adjustment of the valve opening.

[0121] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0122] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0123] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A self-cascade cycle control system for ultra-low ambient temperature, characterized in that: Including: A temperature acquisition module, which is used to acquire the ambient temperature at a preset frequency, sort the acquired ambient temperature data in chronological order to obtain an ambient temperature sequence; An environmental state analysis module, which is used to obtain a basic environmental index and an environmental correction parameter according to the ambient temperature sequence, use the environmental correction parameter to correct the basic environmental index to obtain a corrected environmental index, and determine the environmental state according to the corrected environmental index; A regulation target determination module, which is used to determine a regulation target according to a preset regulation target rule and the environmental state; A control parameter acquisition module, which is used to determine a control item according to a preset control item rule and the regulation target, and acquire control parameters according to the control item using a corresponding optimization method; A control execution module, which is used to execute control according to the acquired control parameters.

2. The self-cascade cycle control system for ultra-low ambient temperature according to claim 1, characterized in that: The basic environmental index is the latest acquired ambient temperature value in the ambient temperature sequence; the environmental correction parameter includes a fluctuation parameter and a trend parameter; the environmental state includes a normal state, a low temperature state, and an ultra-low temperature state.

3. The self-cascade cycle control system for ultra-low ambient temperature according to claim 2, characterized in that: The corrected environmental index is calculated by the following formula: XZ = DZ + tanh(qs) × ln(1 + bd), where XZ represents the corrected environmental index, DZ represents the basic environmental index, qs represents the trend parameter, and bd represents the fluctuation parameter.

4. The self-cascade cycle control system for ultra-low ambient temperature according to claim 3, characterized in that: The steps for obtaining the environmental correction parameter include: Obtain the ambient temperature sequence, remove outliers and perform smoothing processing to obtain a smoothed ambient temperature sequence; Obtain the standard deviation of the smoothed ambient temperature sequence as the fluctuation parameter; Extract the latest n data from the smoothed ambient temperature sequence at a preset interval to form an analysis sequence, where n ≥ 10; Set a sliding window of size m on the analysis sequence, where 1 < m < n, extract the content through the sliding window to obtain n - m + 1 subsequences of size m; Perform linear regression on each subsequence and record the slope of the subsequence as k i ; where i represents the index, i=1,2,...,n-m+1, k i represents the slope of the i-th subsequence; Calculate the trend parameter using the following formula: In the formula, ω i represents the weight of the i-th subsequence, ω i The calculation formula is: Use the fluctuation parameter and the trend parameter to form the environmental correction parameter.

5. The self-cascade cycle control system for ultra-low ambient temperature according to claim 4, characterized in that: The steps for determining the environmental state according to the corrected environmental index include: Set an index threshold, the index threshold includes a low temperature index and an ultra-low temperature index, where the low temperature index is greater than the ultra-low temperature index; Initialize a state record array Q of length l and a current state record Q_c; Compare the corrected environmental index with the index threshold and update the current state record Q_c: When the corrected environmental index is greater than the low temperature index, set Q_c to the normal state; When the corrected environmental index is less than or equal to the low temperature index and greater than the ultra-low temperature index, set Q_c to the low temperature state; When the corrected environmental index is less than or equal to the ultra-low temperature index, set Q_c to the ultra-low temperature state; Add Q_c to the end of the state record array Q, and at the same time remove the earliest state record in the state record array Q to keep the array length as l; Statistically analyze the state distribution in the state record array Q: If all elements in Q are in the same state, then determine this state as the current environmental state; If there are different states in Q, then keep the environmental state unchanged.

6. The self-cascade cycle control system for ultra-low ambient temperature according to claim 2, characterized in that: The regulation targets include maintaining the operation of the main circulation path, starting the air supplement path, and starting the hot gas bypass path; The preset regulation target rules include: When the environmental state is the normal state, determine the regulation target as maintaining the operation of the main circulation path; When the environment is in a low temperature state, the control target is determined to start the air supply circuit; When the environmental state is an ultra-low temperature state, the control target is determined to start the hot gas bypass path.

7. The self-cascade cycle control system for ultra-low ambient temperature according to claim 6, characterized in that: The preset control item rules include: When the control target is to maintain the operation of the main circulation road, the control item is determined to be the opening of the main circulation road; When the control target is to start the air supply circuit, the control items are determined as the main circulation circuit opening and the air supply circuit opening; When the control target is to start the hot gas bypass, the control items are determined as the main circulation opening, the air supply opening and the hot gas bypass opening.

8. The self-cascade cycle control system for ultra-low ambient temperature according to claim 7, characterized in that: The step of obtaining control parameters using corresponding optimization methods according to control items includes: When the control item is the main circulation road opening, the main circulation road opening adjustment amount is calculated using the PID control algorithm, and the main circulation road opening adjustment amount is used as the control parameter; When the control items are the main circulation opening and the supplementary air circuit opening, the main circulation opening is set to the maximum value, the supplementary air circuit opening is calculated according to the ambient temperature and the system pressure ratio using the fuzzy control algorithm, and the main circulation opening and the supplementary air circuit opening are used as control parameters; When the control items are the main circulation opening, the supplementary air circuit opening and the hot gas bypass opening, the main circulation opening and the supplementary air circuit opening are set to the maximum value, the hot gas bypass opening is calculated using an adaptive control algorithm, and the main circulation opening, the supplementary air circuit opening and the hot gas bypass opening are used as control parameters.

9. The self-cascade cycle control system for ultra-low ambient temperature according to claim 8, characterized in that: The method of using the PID control algorithm to calculate the main circulation opening comprises: setting a target intake temperature; monitoring the actual intake temperature in real time; calculating the deviation between the target temperature and the actual temperature, and calculating the cumulative value and the rate of change of the temperature deviation over time; calculating the main circulation opening adjustment amount according to preset proportional, integral and differential parameters, combined with the temperature deviation, the cumulative value of the deviation and the rate of change of the deviation; The method of using a fuzzy control algorithm to calculate the opening of the air supply circuit according to the ambient temperature and the system pressure ratio includes: dividing the ambient temperature and the system pressure ratio into three levels: low, medium, high and small, medium, and large; establishing a fuzzy rule base to define the adjustment strategy of the opening of the air supply circuit under different combinations of ambient temperature and system pressure ratio; determining the membership degree of the current ambient temperature and system pressure ratio in their respective levels; deriving the fuzzy output of the opening of the air supply circuit based on the fuzzy rule base and the membership degree; defuzzifying the fuzzy output and converting it into a specific value of the opening of the air supply circuit; The use of an adaptive control algorithm to calculate the opening of the hot gas bypass passage includes: setting upper and lower limits of a target intake pressure; monitoring the system intake pressure in real time; calculating a deviation between the actual intake pressure and a median of a target pressure range; adjusting an adaptive coefficient based on the pressure deviation and a current system state; and using the adjusted adaptive coefficient to calculate the opening of the hot gas bypass passage.

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