An energy conditioning system that can increase system reliability

Abstract

The application discloses an energy regulating system capable of increasing system reliability and belongs to the technical field of automatic control. The energy regulating system comprises a main control module, a main refrigeration system, a hot gas bypass system, an evaporator, a test box, a temperature sensor, a humidity sensor and a man-machine interaction module. The evaporator, the temperature sensor and the humidity sensor are arranged in the test box. The main refrigeration system, the hot gas bypass system, the main control module and the man-machine interaction module are arranged outside the test box. The main refrigeration system, the hot gas bypass system, the temperature sensor, the humidity sensor and the man-machine interaction module are connected with the main control module. The main refrigeration system and the hot gas bypass system are connected with the evaporator. The application realizes on-demand refrigeration capacity supply, greatly saves energy, improves temperature control precision and speed through dynamic cold capacity field modeling and self-adaptive optimization, effectively suppresses frequent switching of electromagnetic valves, significantly prolongs equipment service life in combination with exhaust temperature safety constraints and fundamentally solves the problems of frost and condensate.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology, and more specifically to an energy regulation system that can increase system reliability. Background Technology

[0002] In the field of environmental testing equipment, the accuracy and energy efficiency of temperature and humidity control are key indicators for evaluating equipment performance. Traditional high and low temperature test chambers generally employ thermal balance temperature control technology, where the refrigeration system continuously outputs excess cooling, which is then offset by heating from the heater, achieving temperature control through a dynamic balance between cooling and heating. However, this control mode of simultaneous cooling and heating has several inherent drawbacks: on the one hand, the cooling generated by the refrigeration system and the heat generated by the heater cancel each other out, resulting in significant energy waste; on the other hand, frequent start-ups and shutdowns of the heater and prolonged high-load operation of the compressor lead to premature aging of critical components, shortening the equipment's lifespan. Furthermore, excessive cooling can easily cause problems such as evaporator frosting, condensation, and decreased temperature uniformity within the chamber, affecting the accuracy and repeatability of test results.

[0003] To address the aforementioned issues, existing technologies have introduced improved solutions such as using electronic expansion valves to regulate refrigerant flow, introducing variable frequency compressor technology, or optimizing PID control algorithms. However, most of these solutions still rely on control logic that cancels out the cooling and heating, failing to fundamentally achieve dynamic matching and precise output of cooling capacity. In the few solutions that attempt to employ cold balance technology, the control methods largely depend on traditional PID regulation, which struggles to adapt to the nonlinear and time-varying characteristics of the load, making it difficult to balance rapid cooling with high-precision stability. Furthermore, existing methods generally lack comprehensive optimization of system reliability factors such as solenoid valve lifespan and exhaust temperature safety, resulting in limited improvements in energy saving and control quality.

[0004] Therefore, developing an energy regulation technology that can achieve on-demand cooling capacity while balancing control accuracy and system reliability is an urgent technical problem to be solved in this field. Summary of the Invention

[0005] The purpose of this invention is to provide an energy regulation system that can increase system reliability, realize on-demand supply of cooling capacity, and significantly save energy; improve temperature control accuracy and speed through dynamic cooling field modeling and adaptive optimization; effectively suppress frequent switching of solenoid valves, and significantly extend equipment life by combining exhaust temperature safety constraints, fundamentally solving the problems of frosting and condensation.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: An energy regulation system that can increase system reliability includes: a main control module, a main refrigeration system, a hot gas bypass system, an evaporator, a test chamber, a temperature sensor, a humidity sensor, and a human-machine interface module. The evaporator, temperature sensor, and humidity sensor are installed inside the test chamber, and the main refrigeration system, hot gas bypass system, main control module, and human-machine interface module are installed outside the test chamber. The main refrigeration system, hot gas bypass system, temperature sensor, humidity sensor, and human-machine interface module are connected to the main control module, and the main refrigeration system and hot gas bypass system are connected to the evaporator. The main control module is configured to perform the following steps: Step 1: Construct a dynamic cooling field model; Step 2: Construct the reference trajectory and adaptive multi-objective optimization function; Step 3: Solve the adaptive multi-objective optimization function using the adaptive individual group optimization algorithm to obtain the optimal control sequence at each time point in the future control time domain; Step 4: Continuously adjust the cooling capacity of the main refrigeration system and the hot gas bypass system based on the optimal control sequence, and collect data at the next sampling time.

[0007] Furthermore, the main refrigeration system includes a first compressor, a first ball valve, a first manual expansion valve, a thermostatic expansion valve, a first oil separator, a first quick-opening solenoid valve, a first dryer filter, a first sight glass, a first solenoid valve, a second solenoid valve, a cold-end high-frequency quick-opening solenoid valve, and a first capillary tube. The input end of the first compressor is connected to the first ball valve, the first manual expansion valve, the output end of the evaporator, and the thermostatic expansion valve. The output end of the first compressor is connected to the first inlet of the water-cooled condenser and the first quick-opening solenoid valve through the first oil separator. The first quick-opening solenoid valve is connected to the first ball valve through a fourth capillary tube. The first outlet of the water-cooled condenser is sequentially connected to the first dryer filter and the first sight glass. The first sight glass is connected to the first solenoid valve, the cold-end high-frequency quick-opening solenoid valve, and the second solenoid valve. The first solenoid valve is connected to the first manual expansion valve. The cold-end high-frequency quick-opening solenoid valve is connected to the first input end of the evaporator through the first capillary tube. The second solenoid valve is connected to the input end of the thermostatic expansion valve. The output end of the thermostatic expansion valve is connected to the first input end of the plate heat exchanger. The first output end of the plate heat exchanger is connected to the input end of the first compressor.

[0008] Furthermore, the output end of the first compressor is connected to a high-pressure gauge and a high-pressure controller, the input end of the first compressor is connected to a low-pressure gauge and a needle valve, the output end of the first compressor is connected to the inlet of the first oil separator, the outlet of the first oil separator is connected to the first inlet of the water-cooled condenser, the return port of the first oil separator is connected to a second sight glass, and the second sight glass is connected to the return port of the first compressor.

[0009] Furthermore, a needle valve is connected to the first outlet of the water-cooled condenser.

[0010] Furthermore, the first output end of the evaporator is connected to the input end of the first compressor via a check valve.

[0011] Furthermore, the hot gas bypass system includes a second manual expansion valve, a second ball valve, a second capillary tube, a third capillary tube, a second oil separator, a third solenoid valve, a fourth solenoid valve, a second quick-opening solenoid valve, and a hot-end high-frequency quick-opening solenoid valve. The input end of the second compressor is connected to the second output end of the evaporator, the second manual expansion valve, the second ball valve, and the second capillary tube. The output end of the second compressor is connected to the second inlet of the water-cooled condenser through the second oil separator. The second outlet of the water-cooled condenser is connected to the third solenoid valve, the second quick-opening solenoid valve, and the second input end of the heat exchanger. The third solenoid valve is connected to a first pressure relief tank, the first pressure relief tank is connected to the second capillary tube, the second quick-opening solenoid valve is connected to the second ball valve, the second output end of the heat exchanger is connected to a second dryer filter, the second dryer filter is connected to the fourth solenoid valve and the hot-end high-frequency quick-opening solenoid valve, the fourth solenoid valve is connected to the second manual expansion valve, the hot-end high-frequency quick-opening solenoid valve is connected to the third capillary tube, and the third capillary tube is connected to the second input end of the evaporator.

[0012] Furthermore, the input end of the second compressor is connected to a low-pressure gauge and a needle valve, the output end of the second compressor is connected to a high-pressure gauge and a high-pressure controller, the output end of the second compressor is connected to the inlet of the second oil separator, the outlet of the second oil separator is connected to the second inlet of the water-cooled condenser, the return port of the second oil separator is connected to a third sight glass, and the third sight glass is connected to the return port of the second compressor.

[0013] Furthermore, a needle valve is connected to the second outlet of the water-cooled condenser.

[0014] Furthermore, in step 1, the specific discrete-time form of the dynamic cold field model is as follows: ; ; In the formula, for k+ The extended state vector at time 1, for k The extended state vector at time step 1. The temperature inside the chamber. For the rate of temperature change, The surface temperature of the evaporator. For evaporator superheat, For load disturbance observations for kThe control input vector at time t, The control duty cycle for the cold-end high-frequency fast-opening solenoid valve. The control duty cycle of the hot-end high-frequency fast-opening solenoid valve has a value range of [value missing]. And satisfy ; Let be the measurable external disturbance vector at time k. For ambient temperature, This refers to the compressor's discharge pressure. k The system output at any given time, i.e., the actual measured temperature inside the chamber; , , They are respectively k The state matrix, input matrix, and perturbation matrix at each time step; This is the output matrix; , These are process noise and measurement noise, respectively, both of which are zero-mean Gaussian white noise.

[0015] Furthermore, in step 2, the adaptive multi-objective optimization function includes temperature tracking error cost, energy consumption cost, control action smoothing cost, and exhaust temperature safety penalty term.

[0016] In summary, the present invention has at least one of the following beneficial technical effects: First, it significantly improves energy efficiency. This invention abandons the ineffective energy consumption mode of heaters offsetting cooling capacity in traditional heat balance technology. Instead, it adopts a cold balance control strategy that coordinates the regulation of cold-end and hot-end solenoid valves, so that all the cooling capacity output by the refrigeration system is used to balance the load's heat demand. Furthermore, the energy consumption cost term in the multi-objective optimization function guides the system to automatically find the lowest energy consumption operating point, thereby achieving significant energy savings.

[0017] Second, it improves the accuracy and response speed of temperature and humidity control. This invention constructs a dynamic cooling field model that includes observations of the chamber temperature, temperature change rate, evaporator superheat, and load disturbance, which can accurately predict the future state of the system. By combining the reference trajectory of the adaptive softening factor with rolling optimization solution, it achieves a balance between rapid approximation and precise stability, avoiding the a posteriori oscillation of traditional PID control, resulting in high control accuracy and fast response.

[0018] Third, it extends equipment lifespan and enhances operational reliability. This invention incorporates a smoothing cost into its optimization objectives, effectively suppressing frequent and significant switching between the cold-end and hot-end high-frequency fast-opening solenoid valves, thus reducing valve core wear. Simultaneously, by setting a safety penalty for exhaust temperature, it ensures the compressor operates within safe conditions, avoiding overheating or liquid-laden operation, thereby significantly extending the lifespan of critical components.

[0019] Fourth, it exhibits strong adaptability and robustness. The dynamic cooling field model used in this invention can update parameters online, adapting to time-varying characteristics such as changes in ambient temperature, gradual evaporator frosting, and compressor aging; the adaptive pigeon flock optimization algorithm does not require precise initial parameters, has strong global search capabilities and resistance to local optima, and can maintain good control quality under different operating conditions.

[0020] Fifth, it effectively solves the problems of frosting and condensation. By precisely controlling the surface temperature and superheat of the evaporator, the evaporator temperature is always higher than the air dew point temperature, thus avoiding frosting and condensation at the source. This eliminates the impact of frequent defrosting on the continuity of testing in traditional solutions, making it particularly suitable for testing scenarios involving humidity-sensitive electronic components and precision instruments. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the control flow of the energy regulation system of the present invention, which can increase the system reliability; Figure 2 This is a schematic diagram of the first and second refrigeration systems.

[0022] Reference numerals: 1. First compressor; 2. First ball valve; 3. First manual expansion valve; 4. Thermal expansion valve; 5. Evaporator; 6. First oil separator; 7. Water-cooled condenser; 8. First quick-opening solenoid valve; 9. Fourth capillary tube; 10. First dryer filter; 11. First sight glass; 12. First solenoid valve; 13. Cold-end high-frequency quick-opening solenoid valve; 14. Second solenoid valve; 15. First capillary tube; 16. Plate heat exchanger; 17. High-pressure gauge; 18. High-pressure controller 19. Low-pressure gauge; 20. Needle valve; 21. Second sight glass; 22. Check valve; 23. Second manual expansion valve; 24. Second ball valve; 25. Second capillary tube; 26. Second oil separator; 27. Third solenoid valve; 28. Second quick-opening solenoid valve; 29. ​​First pressure relief tank; 30. Second dryer filter; 31. Fourth solenoid valve; 32. Hot-end high-frequency quick-opening solenoid valve; 33. Third capillary tube; 34. Third sight glass; 35. Second compressor. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0024] This invention provides an energy regulation system that can increase system reliability, comprising: a main control module, a main refrigeration system, a hot gas bypass system, an evaporator 5, a test chamber, a temperature sensor, a humidity sensor, and a human-machine interaction module. The evaporator 5, temperature sensor, and humidity sensor are installed inside the test chamber, while the main refrigeration system, hot gas bypass system, main control module, and human-machine interaction module are installed outside the test chamber. The main refrigeration system, hot gas bypass system, temperature sensor, humidity sensor, and human-machine interaction module are connected to the main control module, and the main refrigeration system and hot gas bypass system are connected to the evaporator 5. like Figure 1 As shown, the main control module is configured to perform the following steps: Step 1: Construct a dynamic cooling field model; Step 2: Construct the reference trajectory and adaptive multi-objective optimization function; Step 3: Based on the adaptive group optimization algorithm, the adaptive multi-objective optimization function is solved in a rolling manner to obtain the optimal control sequence at each time step in the future control time domain; Step 4: Continuously adjust the cooling capacity of the main refrigeration system and the hot gas bypass system based on the optimal control sequence, and collect data at the next sampling time.

[0025] The main refrigeration system includes a first compressor 1, a first ball valve 2, a first manual expansion valve 3, a thermostatic expansion valve 4, a first oil separator 6, a first quick-opening solenoid valve 8, a first dryer filter 10, a first sight glass 11, a first solenoid valve 12, a second solenoid valve 14, a cold-end high-frequency quick-opening solenoid valve 13, and a first capillary tube 15. The input end of the first compressor 1 is connected to the first ball valve 2, the first manual expansion valve 3, the output end of the evaporator 5, and the thermostatic expansion valve 4. The output end of the first compressor 1 is connected to the first inlet of the water-cooled condenser 7 and the first quick-opening solenoid valve 8 through the first oil separator 6. The first quick-opening solenoid valve 8 is connected to the first capillary tube 15. Pipe 9 is connected to the first ball valve 2. The first outlet of the water-cooled condenser 7 is sequentially connected to the first dryer filter 10 and the first sight glass 11. The first sight glass 11 is connected to the first solenoid valve 12, the cold end high-frequency quick-opening solenoid valve 13 and the second solenoid valve 14. The first solenoid valve 12 is connected to the first manual expansion valve 3. The cold end high-frequency quick-opening solenoid valve 13 is connected to the first input end of the evaporator 5 through the first capillary tube 15. The second solenoid valve 14 is connected to the input end of the thermal expansion valve 4. The output end of the thermal expansion valve 4 is connected to the first input end of the plate heat exchanger 16. The first output end of the plate heat exchanger 16 is connected to the input end of the first compressor 1.

[0026] The output end of the first compressor 1 is connected to a high pressure gauge 17 and a high pressure controller 18. The input end of the first compressor 1 is connected to a low pressure gauge 19 and a needle valve 20. The output end of the first compressor 1 is connected to the inlet of the first oil separator 6. The outlet of the first oil separator 6 is connected to the first inlet of the water-cooled condenser 7. The oil return port of the first oil separator 6 is connected to a second sight glass 21. The second sight glass 21 is connected to the oil return port of the first compressor 1.

[0027] The first outlet of the water-cooled condenser 7 is connected to a needle valve 20.

[0028] The first output end of the evaporator 5 is connected to the input end of the first compressor 1 via a check valve 22.

[0029] The hot gas bypass system includes a second manual expansion valve 23, a second ball valve 24, a second capillary tube 25, a third capillary tube 33, a second oil separator 26, a third solenoid valve 27, a fourth solenoid valve 31, a second quick-opening solenoid valve 28, and a hot-end high-frequency quick-opening solenoid valve 32. The input end of the second compressor 35 is connected to the second output end of the evaporator 5, the second manual expansion valve 23, the second ball valve 24, and the second capillary tube 25. The output end of the second compressor 35 is connected to the second inlet of the water-cooled condenser 7 through the second oil separator 26. The second outlet of the water-cooled condenser 7 is connected to the third solenoid valve 27 and the second quick-opening solenoid valve 32. The second input terminal of the solenoid valve 28 and the plate heat exchanger 16 is connected to the second input terminal of the second solenoid valve 28 and the second input terminal of the plate heat exchanger 16. The third solenoid valve 27 is connected to the first pressure relief tank 29, the first pressure relief tank 29 is connected to the second capillary tube 25, the second quick-opening solenoid valve 28 is connected to the second ball valve 24, the second output terminal of the plate heat exchanger 16 is connected to the second drying filter 30, the second drying filter 30 is connected to the fourth solenoid valve 31 and the hot end high-frequency quick-opening solenoid valve 32, the fourth solenoid valve 31 is connected to the second manual expansion valve 23, the hot end high-frequency quick-opening solenoid valve 32 is connected to the third capillary tube 33, and the third capillary tube 33 is connected to the second input terminal of the evaporator 5.

[0030] The input end of the second compressor 35 is connected to a low-pressure gauge 19 and a needle valve 20. The output end of the second compressor 35 is connected to a high-pressure gauge 17 and a high-pressure controller 18. The output end of the second compressor 35 is connected to the inlet of the second oil separator 26. The outlet of the second oil separator 26 is connected to the second inlet of the water-cooled condenser 7. The return port of the second oil separator 26 is connected to a third sight glass 34. The third sight glass 34 is connected to the return port of the second compressor 35. The second outlet of the water-cooled condenser 7 is connected to a needle valve 20.

[0031] The main control module includes a PLC controller and an adaptive cooling capacity prediction optimizer. The adaptive cooling capacity prediction optimizer is used to execute the energy regulation method described above. The method will now be explained in detail with reference to specific parameter settings: Before proceeding, it should be noted that for cases involving parameter acquisition, the corresponding sensors can be added to the system. Since this is existing technology, it will not be described in detail here.

[0032] In step 1, a dynamic cooling field model is constructed, specifically as follows: After the system is powered on, the adaptive cooling capacity prediction optimizer performs initialization, reads historical operating parameters stored in the non-volatile memory of the PLC controller, and constructs a dynamic cooling capacity field state-space model based on the thermodynamic mechanism of the test chamber and data-driven approach. This model not only includes the temperature state inside the chamber, but also introduces evaporator superheat, load disturbance observations, and cooling capacity demand coefficients as extended state variables. The specific discrete-time form of the dynamic cooling capacity field model is as follows: ; ; In the formula, for k+ The extended state vector at time 1, for k The extended state vector at time step 1. The temperature inside the chamber. For the rate of temperature change, The surface temperature of the evaporator. For evaporator superheat, These are the load disturbance observations. Indicates matrix transpose; for k The control input vector at time t, The control duty cycle for the cold-end high-frequency fast-opening solenoid valve. The control duty cycle of the hot-end high-frequency fast-opening solenoid valve has a value range of [value missing]. And satisfy ; Let be the measurable external disturbance vector at time k. For ambient temperature, This refers to the compressor's discharge pressure. for k The system output at any given time, i.e., the actual measured temperature inside the chamber; , , They are respectively k The state matrix, input matrix, and perturbation matrix at each time step; This is the output matrix; , These are process noise and measurement noise, respectively, both of which are zero-mean Gaussian white noise.

[0033] In step 2, the reference trajectory and adaptive multi-objective optimization function are constructed, specifically as follows: The adaptive cooling capacity prediction optimizer sets a line that smoothly transitions from the current temperature to the set temperature. Reference trajectory The softening factor of the reference trajectory is in exponential form and is defined as follows: ; In the formula, for Time prediction Reference temperature value at any given time; The softening factor for the reference trajectory, with a value range of... In this invention It is not a fixed value, but rather depends on the current temperature deviation. Adaptive adjustment, its adaptive law is: , , This is to achieve a fast response when there is a large deviation and a smooth approximation when there is a small deviation. To predict the step size index, , For predicting the time domain, in this invention ; Set the target temperature for the test chamber.

[0034] The adaptive cooling load prediction optimizer constructs a multi-objective optimization function. This function comprises four terms: temperature tracking error cost, energy consumption cost, control action smoothing cost, and exhaust temperature safety penalty. Its specific form is as follows: ; in, For based on Time information The predicted value output at time step is obtained recursively from the model in step 1; To control the time domain, in this invention ; To predict error weights of different time lengths within the time domain, an exponential decay form is adopted. , , This gives greater weight to recent tracking errors; for The instantaneous energy consumption estimate at time t is fed back in real time by the energy consumption monitoring module, and its expression is: ,in This refers to the compressor's power coefficient per unit duty cycle. This is a correction factor for hot gas bypass energy consumption. This indicates that hot gas bypass itself has low energy consumption; Energy consumption weighting coefficient, initial value This coefficient can be adaptively adjusted according to the system operating mode: when the system is in steady state and the temperature deviation is less than 0.2℃, Gradually increase to 1.0, guiding the system to automatically find the lowest energy consumption point; during rapid rise and fall phases, Reduce to 0.1 to prioritize response speed; To control the smoothing weighting coefficient, It is used to suppress frequent and large-amplitude switching of solenoid valves and protect high-frequency fast-opening solenoid valves. The exhaust temperature safety penalty coefficient, ; The exhaust temperature safety penalty function is defined as follows: ; in This is the measured value of the exhaust temperature. As a safety threshold, This is the maximum allowable value. When hour, No penalty; once the threshold is exceeded, the penalty increases rapidly, forcing the optimizer to reduce the duty cycle of the hot-end valve. .

[0035] In step 3, the adaptive multi-objective optimization function is solved using an adaptive group optimization algorithm to obtain the optimal control sequence at each time step in the future control time domain, specifically: In each control cycle The adaptive cooling load prediction optimizer obtains the current system state vector. This includes reading from the temperature sensor inside the chamber. Obtained from the temperature change rate calculation module Read from the temperature sensor on the evaporator Obtained from the superheat calculation module and obtained from the load disturbance observer Then, solve the multi-objective optimization function described in step 2. In order to obtain the future The optimal control sequence at each time point .

[0036] This invention does not use a traditional quadratic programming solver, but instead employs an improved adaptive pigeon flock optimization algorithm. This algorithm simulates two stages of pigeon homing behavior: the map compass stage and the landmark stage, and introduces adaptive inertia weights and a mutation mechanism to improve convergence speed and avoid getting trapped in local optima. Specifically, it includes the following steps: Step 301: Pigeon Flock Initialization exist Time, randomly generated The initial position of each pigeon, and the position of each pigeon. It is A dimensional vector is represented as: ; in In this invention The initial position of each pigeon is generated near the previous optimal solution using Gaussian perturbation to utilize historical information and accelerate convergence. Simultaneously, each position vector must satisfy control constraints: for each time step... , , ,and Therefore, the actual decision variables can be simplified to: Duty cycle of each cold-end valve The duty cycle of the hot-end valve is determined by Confirmed. The pigeon's position vector is reduced to the following dimension: The range of values ​​for each component .

[0037] Step 302: Map Compass Stage This phase simulates the ability of pigeons to sense direction using the Earth's magnetic field. Each pigeon determines its optimal position based on its current location. and the global optimal position Update its speed and position. This invention improves upon the traditional pigeon flock optimization algorithm by introducing adaptive inertia weights. And Levi flight disturbances to enhance global search capabilities.

[0038] The speed update formula is as follows: ; The position update formula is as follows: ; in, The number of iterations within the pigeon flock optimization algorithm. In this invention ; For the first Only one pigeon in the 1st The velocity vector of the next iteration; For adaptive inertia weights, the expression is: , This causes the algorithm to focus on global exploration in the early stages and local development in the later stages; and As a learning factor, ; , for A random number that is uniformly distributed within an interval; This is the Lévy flight step length coefficient; To determine the random step size following a Lévy distribution, the generation formula is as follows: ,in and Follows a standard normal distribution. ; After each pigeon's location is updated, each component needs to be limited to... Find the interval and calculate the objective function value corresponding to that position. .like If the result is better than the pigeon's historical best, then update. If it is better than the global optimum, then update. After the map compass phase iterations are completed, the approximate solution of the current optimal control sequence is obtained.

[0039] Step 303: Landmark Phase This phase simulates the navigation behavior of pigeons using landmarks. The number of pigeons decreases proportionally with each generation, and the surviving pigeons move towards the population center. This invention improves upon the traditional landmark phase by using weighted centroids instead of simple averaging and introducing Gaussian variation to increase diversity.

[0040] The iterative formula for the landmark stage is as follows: ; ; ; in, For the first The number of pigeons at the next landmark iteration, initially . For the first The reciprocal of the objective function value for each pigeon, i.e., the fitness. The smaller the objective function value, the greater the fitness. This represents the position of the weighted centroid. for Uniformly distributed random numbers within an interval.

[0041] The standard deviation of Gaussian variation. These are random numbers distributed according to a standard normal distribution. Total number of iterations in the landmark stage. Second-rate.

[0042] Finally, after the landmark phase ends, the globally optimal position is determined. This is the desired optimal control sequence. .

[0043] In step 4, the cooling capacity of the main refrigeration system and the hot gas bypass system is continuously adjusted based on the optimal control sequence, and data is collected at the next sampling time. Specifically: The optimal control sequence obtained by the adaptive cooling capacity prediction optimizer is... Extract the first control vector The PLC controller converts this control quantity into a high-frequency pulse signal: for a cold-end high-frequency quick-opening solenoid valve, the pulse period is 0.2 seconds, and the high-level duration is... seconds, low level duration is Seconds; for hot-end high-frequency fast-opening solenoid valves, their pulse waveforms are complementary to those of cold-end valves, i.e., the high-level duration is seconds. Seconds. Two solenoid valves open alternately, achieving continuous adjustment of the equivalent cooling capacity.

[0044] The next sampling time after control is applied Collect new chamber temperature Evaporator temperature And energy consumption data, etc., are fed back to the adaptive cooling capacity prediction optimizer.

[0045] Depending on specific needs, the model parameters can also be updated online in each control cycle, but this invention will not elaborate on this further.

[0046] Embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0047] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0048] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0049] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0050] Contents not described in detail in this specification are prior art known to those skilled in the art. It is hereby indicated that the above description is intended to help those skilled in the art understand this invention, but does not limit the scope of protection of this invention. Any equivalent substitutions, modifications, improvements, or simplifications of the above descriptions that do not depart from the essential content of this invention fall within the scope of protection of this invention.

Claims

1. An energy regulation system that can increase system reliability, characterized in that, include: The test chamber includes a main control module, a main refrigeration system, a hot gas bypass system, an evaporator, a test chamber, a temperature sensor, a humidity sensor, and a human-machine interface module. The evaporator, temperature sensor, and humidity sensor are installed inside the test chamber, while the main refrigeration system, hot gas bypass system, main control module, and human-machine interface module are installed outside the test chamber. The main refrigeration system, hot gas bypass system, temperature sensor, humidity sensor, and human-machine interface module are connected to the main control module, and the main refrigeration system and hot gas bypass system are connected to the evaporator. The main control module is configured to perform the following steps: Step 1: Construct a dynamic cooling field model; Step 2: Construct the reference trajectory and adaptive multi-objective optimization function; Step 3: Solve the adaptive multi-objective optimization function using the adaptive individual group optimization algorithm to obtain the optimal control sequence at each time point in the future control time domain; Step 4: Continuously adjust the cooling capacity of the main refrigeration system and the hot gas bypass system based on the optimal control sequence, and collect data at the next sampling time.

2. The energy regulation system for increasing system reliability according to claim 1, characterized in that, The main refrigeration system includes a first compressor, a first ball valve, a first manual expansion valve, a thermostatic expansion valve, a first oil separator, a first quick-opening solenoid valve, a first dryer filter, a first sight glass, a first solenoid valve, a second solenoid valve, a cold-end high-frequency quick-opening solenoid valve, a first capillary tube, and a fourth capillary tube. The input end of the first compressor is connected to the first ball valve, the first manual expansion valve, the output end of the evaporator, and the thermostatic expansion valve. The output end of the first compressor is connected to the first inlet of the water-cooled condenser and the first quick-opening solenoid valve through the first oil separator. The first quick-opening solenoid valve is connected to the first ball valve through the fourth capillary tube. The first outlet of the water-cooled condenser is sequentially connected to the first dryer filter and the first sight glass. The first sight glass is connected to the first solenoid valve, the cold-end high-frequency quick-opening solenoid valve, and the second solenoid valve. The first solenoid valve is connected to the first manual expansion valve. The cold-end high-frequency quick-opening solenoid valve is connected to the first input end of the evaporator through the first capillary tube. The second solenoid valve is connected to the input end of the thermostatic expansion valve. The output end of the thermostatic expansion valve is connected to the first input end of the plate heat exchanger. The first output end of the plate heat exchanger is connected to the input end of the first compressor.

3. The energy regulation system for increasing system reliability according to claim 2, characterized in that, The output end of the first compressor is connected to a high-pressure gauge and a high-pressure controller, the input end of the first compressor is connected to a low-pressure gauge and a needle valve, the output end of the first compressor is connected to the inlet of the first oil separator, the outlet of the first oil separator is connected to the first inlet of the water-cooled condenser, the return port of the first oil separator is connected to a second sight glass, and the second sight glass is connected to the return port of the first compressor.

4. The energy regulation system for increasing system reliability according to claim 2, characterized in that, The first outlet of the water-cooled condenser is connected to a needle valve.

5. An energy regulation system that can increase system reliability according to claim 2, characterized in that, The first output terminal of the evaporator is connected to the input terminal of the first compressor via a check valve.

6. An energy regulation system for increasing system reliability according to claim 2, characterized in that, The hot gas bypass system includes a second compressor, a second manual expansion valve, a second ball valve, a second capillary tube, a third capillary tube, a second oil separator, a third solenoid valve, a fourth solenoid valve, a second quick-opening solenoid valve, and a hot-end high-frequency quick-opening solenoid valve. The input end of the second compressor is connected to the second output end of the evaporator, the second manual expansion valve, the second ball valve, and the second capillary tube. The output end of the second compressor is connected to the second inlet of the water-cooled condenser through the second oil separator. The second outlet of the water-cooled condenser is connected to the third solenoid valve, the second quick-opening solenoid valve, and the second input end of the heat exchanger. The third solenoid valve is connected to a first pressure relief tank, which is connected to the second capillary tube. The second quick-opening solenoid valve is connected to the second ball valve. The second output end of the heat exchanger is connected to a second dryer filter, which is connected to the fourth solenoid valve and the hot-end high-frequency quick-opening solenoid valve. The fourth solenoid valve is connected to the second manual expansion valve. The hot-end high-frequency quick-opening solenoid valve is connected to the third capillary tube, and the third capillary tube is connected to the second input end of the evaporator.

7. An energy regulation system for increasing system reliability according to claim 6, characterized in that, The input end of the second compressor is connected to a low-pressure gauge and a needle valve, the output end of the second compressor is connected to a high-pressure gauge and a high-pressure controller, the output end of the second compressor is connected to the inlet of the second oil separator, the outlet of the second oil separator is connected to the second inlet of the water-cooled condenser, the return port of the second oil separator is connected to a third sight glass, and the third sight glass is connected to the return port of the second compressor.

8. An energy regulation system for increasing system reliability according to claim 2, characterized in that, The second outlet of the water-cooled condenser is connected to a needle valve.

9. An energy regulation system for increasing system reliability according to claim 1, characterized in that, In step 1, the specific discrete-time form of the dynamic cold field model is as follows: ； ； In the formula, for k+ The extended state vector at time 1, for k The extended state vector at time step 1. The temperature inside the chamber. For the rate of temperature change, The surface temperature of the evaporator. For evaporator superheat, These are load disturbance observations; for k The control input vector at time t, The control duty cycle for the cold-end high-frequency fast-opening solenoid valve. The control duty cycle of the hot-end high-frequency fast-opening solenoid valve has a value range of [value missing]. And satisfy ; Let be the measurable external disturbance vector at time k. For ambient temperature, This refers to the compressor's discharge pressure. for k The system output at any given time, i.e., the actual measured temperature inside the chamber; , , They are respectively k The state matrix, input matrix, and perturbation matrix at each time step; This is the output matrix; , These are process noise and measurement noise, respectively, both of which are zero-mean Gaussian white noise.

10. An energy regulation system for increasing system reliability according to claim 1, characterized in that, In step 2, the adaptive multi-objective optimization function includes temperature tracking error cost, energy consumption cost, control action smoothing cost, and exhaust temperature safety penalty term.

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