Magnetic suspension centrifugal compressor electromagnetic valve control method and system and medium

Abstract

The invention discloses a magnetic suspension centrifugal compressor solenoid valve control method and system and a medium, and relates to the technical field of compressor thermal management, and the method comprises the steps: collecting the real-time temperature of a motor stator and a driving board, the real-time load rate of a motor, and the data of the environment temperature; calculating the temperature rise rate and the environment temperature difference of the motor stator and the driving board based on the collected data, and carrying out normalization processing; calculating a heat accumulation index based on the real-time load rate of the motor and the normalized temperature rise rate and environment temperature difference; calculating predicted temperatures of the motor stator and the drive board based on the real-time temperatures and the temperature rise rates of the motor stator and the drive board; and according to the predicted temperature, the real-time temperature, the heat accumulation index and the preset threshold value of the motor stator and the drive board, executing a hierarchical cooling control decision. Through multi-dimensional data fusion, prospective prediction and intelligent decision making, the accuracy, efficiency and reliability of thermal management of the magnetic suspension centrifugal compressor are systematically improved.

Description

Technical Field

[0001] This invention relates to the field of compressor thermal management technology, and in particular to a method, system and medium for controlling a solenoid valve of a magnetic levitation centrifugal compressor. Background Technology

[0002] Magnetic levitation centrifugal compressors are widely used in HVAC systems in large commercial buildings and data centers due to their high efficiency, oil-free operation, and low noise. Their high-speed motors and drive controllers generate a significant amount of heat during operation. To ensure safe and stable equipment operation, a refrigerant bypass circulation system is required for cooling; the opening and closing of this circulation path is precisely controlled by a solenoid valve.

[0003] Currently, the mainstream solenoid valve control strategies in the industry include: 1. Single temperature threshold control: When the temperature of a critical component (such as the motor stator) exceeds a preset upper limit, the solenoid valve opens; when it falls below the lower limit, it closes. This method is simple and direct, but it is prone to "jittering" near the temperature critical point, causing the solenoid valve to open and close frequently, severely shortening its mechanical and electrical lifespan.

[0004] 2. Hysteresis Comparison Control: To solve the jitter problem, a hysteresis or hysteresis range is introduced, that is, different upper limits for the start-up temperature and lower limits for the stop-down temperature are set. Although the number of switching is reduced to a certain extent, it is still a passive response mechanism in essence. For operating conditions such as a sharp increase in load, the response is delayed, which may lead to instantaneous local overheating.

[0005] 3. Timing control or PID control (proportional-integral-derivative control): Timing control cannot adapt to changing operating conditions and is prone to causing overcooling or insufficient heat dissipation. Although PID control can achieve smoother adjustment, its parameter tuning is complex and it mainly focuses on the current error, lacking the ability to predict future temperature change trends caused by external factors such as load rate and ambient temperature.

[0006] In summary, existing technologies generally lack the ability to comprehensively assess and proactively predict the thermal state of compressor systems. This results in control strategies that are either overly simplistic and crude, or overly complex and poorly adaptable, making it difficult to achieve the optimal balance between heat dissipation, equipment lifespan, and system energy efficiency. Therefore, there is an urgent need to develop a solenoid valve control method that can integrate multi-source information, predict temperature trends, and make intelligent decisions. Summary of the Invention

[0007] In order to overcome the above-mentioned shortcomings of the prior art, the present invention provides a method, system and medium for controlling the solenoid valve of a magnetic levitation centrifugal compressor, aiming to solve the problems of frequent switching, control lag and poor adaptability of the solenoid valve control strategy in the prior art.

[0008] The technical solution adopted by this invention to solve its technical problem is: a control method for a solenoid valve of a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction, comprising: Collect real-time temperature data of the motor stator and drive board, real-time motor load rate, and ambient temperature. The temperature rise rate of the motor stator and drive board and the ambient temperature difference are calculated based on the collected data and then normalized. The heat accumulation index is calculated based on the real-time load rate of the motor, the normalized temperature rise rate, and the ambient temperature difference. Based on the real-time temperature and temperature rise rate of the motor stator and drive board, the predicted temperature of the motor stator and drive board is calculated. Based on the predicted temperature, real-time temperature, heat accumulation index, and preset threshold of the motor stator and drive board, a graded cooling control decision is executed.

[0009] As a further improvement of the present invention: the temperature rise rate of the motor stator is: ; The temperature rise rate of the drive board is: ; Among them, T m (t) represents the real-time temperature of the motor stator at time t, T m (t-Δt) represents the real-time temperature of the motor stator at time t-Δt, where Δt is the time window, and T d (t) represents the real-time temperature of the driver board at time t, where T is the temperature of the driver board at time t. d (t-Δt) represents the real-time temperature of the drive board at time t-Δt.

[0010] As a further improvement of the present invention: the formula for calculating the heat accumulation index is as follows: ; Wherein, HCI is the heat accumulation index. This is the normalized stator temperature rise rate of the motor. L(t) represents the normalized temperature rise rate of the drive board, and L(t) represents the real-time load rate of the motor. T represents the normalized ambient temperature difference. a (t) represents the ambient temperature, T ref The reference temperature is used, and α, β, γ, and δ are weighting coefficients, with α+β+γ+δ=1.

[0011] As a further improvement of the present invention: the method for calculating the predicted temperature is as follows: Predicting future time window Δt using linear extrapolation pred The predicted temperature of the motor stator and the predicted temperature of the drive board; ; ; Among them, T m,pred For predicting the temperature of the motor stator, T m (t) represents the real-time temperature of the motor stator at time t. Δt is the rate of temperature rise of the motor stator. pred For future time windows; T d,pred To predict the temperature of the driver board, T d (t) represents the real-time temperature of the driver board at time t. This represents the temperature rise rate of the driver board.

[0012] As a further improvement of the present invention: the graded cooling control decision includes switching between emergency cooling mode, standby mode and maintenance cooling mode to control the on / off state of the solenoid valve; When the predicted temperature exceeds the upper temperature limit, the heat accumulation index exceeds the opening threshold, or the real-time temperature reaches the upper temperature limit, the emergency cooling mode is triggered and the solenoid valve is opened. When the heat accumulation index is lower than the shutdown threshold and the real-time temperature is lower than the lower limit of the temperature, the standby mode is triggered and the solenoid valve is closed. In emergency cooling mode, when the real-time temperature and heat accumulation index have both left the emergency zone, but the shutdown conditions for standby mode have not yet been met, the maintenance cooling mode is triggered. The solenoid valve is controlled by a pulse switch, and the duty cycle is dynamically adjusted according to the heat accumulation index.

[0013] As a further improvement of the present invention: the preset thresholds include the upper and lower temperature limits of the motor stator, the upper and lower temperature limits of the drive board, the opening and closing thresholds of the heat accumulation index, and the minimum switching interval; The tiered cooling control decision includes: A. Emergency Cooling Mode: When the solenoid valve is closed and the time interval between its closure and the last closure is greater than or equal to the minimum switching interval, the solenoid valve will immediately open if any of the following conditions are met: a) Predicted temperature exceeds limit: T m,pred ≥T max,motor or T d,pred ≥T max,driver ; b) Heat accumulation index exceeds the limit: HCI ≥ HCI on ; c) The real-time temperature has reached the emergency limit: T m (t)≥T max,motor or T d (t)≥T max,driver ; B. Standby Mode: When the solenoid valve is open and the time interval between its opening and the last opening is greater than or equal to the minimum switching interval, the solenoid valve will close if the following conditions are met simultaneously: a) Extremely low heat accumulation index: HCI ≤ HCI off ; b) Real-time temperature drops to the lower limit of the temperature: T m (t)≤T min,motor And T d (t)≤T min,driver ; C. Maintain Cooling Mode: In emergency cooling mode, if the real-time temperature and heat accumulation index are out of the emergency zone but the shutdown conditions of standby mode are not yet met, the system can switch to maintain cooling mode; the controller controls the solenoid valve to perform pulse switching at a certain duty cycle with a large cycle. The duty cycle can be dynamically adjusted according to the current heat accumulation index value. The higher the heat accumulation index value, the larger the duty cycle. Among them, T m,pred T is the predicted temperature of the motor stator. max,motor T is the upper limit of the temperature of the motor stator. d,pred T is the predicted temperature of the driver board. max,driver The upper temperature limit of the driver board; HCI is the thermal accumulation index. on HCI is the threshold for the thermal accumulation index. off The threshold for the thermal accumulation index; T m (t) represents the real-time temperature of the motor stator at time t, T d (t) represents the real-time temperature of the drive board at time t; T min,motor T is the lower limit of the temperature of the motor stator. min,driver This is the lower limit of the temperature of the driver board.

[0014] As a further improvement to the present invention, it also includes: The time interval between two actions of the solenoid valve must be greater than the minimum switching interval, and the motor load rate should be actively reduced when emergency cooling conditions are met but the solenoid valve cannot be opened immediately.

[0015] This invention provides a solenoid valve control system for a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction, comprising: Motor stator temperature sensor, used to detect the temperature of the motor stator; Driver board temperature sensor, used to detect driver board temperature; An ambient temperature sensor is used to detect the ambient temperature of the compressor. The load detection module is used to detect the real-time load rate of the motor. Solenoid valve, located in the refrigerant bypass circulation path; The core controller is electrically connected to the motor stator temperature sensor, drive board temperature sensor, ambient temperature sensor, load detection module, and solenoid valve. It is used to perform data acquisition, processing, heat accumulation index calculation, temperature prediction, and control decision-making, and output control signals to drive the solenoid valve.

[0016] As a further improvement of the present invention: the controller includes a data acquisition module, a data processing module, a heat accumulation index calculation module, a temperature prediction module and a control decision module, and stores preset thresholds, weighting coefficients and minimum switching intervals; The data acquisition module is used to collect real-time temperature data of the motor stator and drive board, real-time motor load rate, and ambient temperature. The data processing module is used to calculate the temperature rise rate of the motor stator and drive board and the ambient temperature difference based on the collected data, and to perform normalization processing. The heat accumulation index calculation module is used to calculate the heat accumulation index based on the real-time load rate of the motor, the normalized temperature rise rate, and the ambient temperature difference. The temperature prediction module is used to calculate the predicted temperature of the motor stator and drive board based on the real-time temperature and temperature rise rate of the motor stator and drive board. The control decision module is used to perform graded cooling control decisions based on the predicted temperature, real-time temperature, heat accumulation index and preset threshold of the motor stator and drive board.

[0017] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction.

[0018] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention collects multi-source parameters such as the real-time temperature of the motor stator and drive board, the real-time load rate of the motor, and the ambient temperature, and performs normalized fusion calculations. This enables the system to perform multi-dimensional and comprehensive quantitative assessment of the thermal state, overcoming the one-sidedness of traditional single-temperature threshold control. It significantly improves the comprehensiveness and accuracy of state judgment, laying a reliable data foundation for intelligent control. By calculating the temperature rise rate in real time and using it to predict the temperature in the short term, the control system possesses a proactive intervention capability. This method transforms the control logic from a passive "over-temperature response" to an active "pre-limit intervention," effectively preventing temperature overshoot and improving the system's safety margin and operational stability.

[0019] 2. This invention integrates the real-time motor load rate, the normalized temperature rise rate, and the thermal accumulation index of the ambient temperature difference for control execution. This enables the system to keenly sense and respond to dynamic changes in operating conditions, achieving a strong correlation between the control strategy and the actual thermal load of the system. This enhances the system's adaptability to different load conditions and ambient temperatures, thus maintaining excellent heat dissipation and energy efficiency balance under various operating scenarios. Furthermore, by making hierarchical cooling control decisions based on multiple conditions—predicted temperature, real-time temperature, and thermal accumulation index—the control actions of the solenoid valves become more refined and rational.

[0020] 3. This invention advances thermal management control from simple response to intelligent predictive decision-making, optimizing overall system energy efficiency and the lifespan of key components while ensuring the safe operation of the compressor's core components. Through multi-dimensional data fusion, forward-looking prediction, and intelligent decision-making, it systematically improves the accuracy, efficiency, and reliability of thermal management in magnetic levitation centrifugal compressors. Attached Figure Description

[0021] Figure 1 This is a flowchart of a method for controlling the solenoid valve of a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction, according to the present invention.

[0022] Figure 2 This is a structural block diagram of a solenoid valve control system for a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction, according to the present invention. Detailed Implementation

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0024] Implementation Case 1: Please see Figure 1 A method for controlling the solenoid valve of a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction includes the following steps: S1: Collects real-time temperature data of the motor stator and drive board, real-time motor load rate, and ambient temperature; collects real-time temperature data of the motor stator and drive board, real-time motor load rate, and ambient temperature at a preset sampling period (e.g., 1 second) through sensors and communication interfaces; the real-time motor load rate is the ratio of the motor's real-time input power to its rated power. S2: Calculate the temperature rise rate and ambient temperature difference of the motor stator and drive board based on the collected data, and perform normalization processing; through normalization processing, the temperature rise rate and ambient temperature difference are mapped to the [0, 1] interval to eliminate the influence of different physical dimensions. S3: Calculate the heat accumulation index (HCI) based on the real-time load rate of the motor, the normalized temperature rise rate, and the ambient temperature difference; the heat accumulation index (HCI) is used to quantify the current and future thermal risks of the system. S4: Calculate the predicted temperature of the motor stator and drive board based on the real-time temperature and temperature rise rate of the motor stator and drive board; S5: Based on the predicted temperature, real-time temperature, heat accumulation index (HCI), and preset threshold of the motor stator and drive board, execute a graded cooling control decision.

[0025] By collecting multi-source parameters such as the real-time temperature of the motor stator and drive board, the real-time load rate of the motor, and the ambient temperature, and performing normalized fusion calculations, the system can perform multi-dimensional and comprehensive quantitative evaluation of the thermal state. This overcomes the one-sidedness of traditional single temperature threshold control, significantly improves the comprehensiveness and accuracy of state judgment, and lays a reliable data foundation for intelligent control.

[0026] By calculating the temperature rise rate in real time and using it to predict the temperature in the near future, the control system has the ability to intervene proactively. This method transforms the control logic from a passive "response after over-temperature" to an active "intervention before the limit is reached", which can effectively prevent temperature overshoot and improve the safety margin and operational stability of the system.

[0027] By integrating the real-time load rate of the motor, the normalized temperature rise rate, and the thermal accumulation index of the ambient temperature difference for control execution, the system can keenly perceive and respond to dynamic changes in operating conditions. This achieves a strong correlation between the control strategy and the actual thermal load of the system, enhancing the system's adaptability to different load conditions and ambient temperatures. As a result, the system can maintain excellent heat dissipation and energy efficiency balance under various operating scenarios.

[0028] By making hierarchical cooling control decisions based on multiple conditions such as predicted temperature, real-time temperature, and heat accumulation index, the control actions of the solenoid valves are made more precise and rational.

[0029] By organically combining the above technologies, thermal management control has advanced from simple response to intelligent predictive decision-making, optimizing overall system energy efficiency and the service life of key components while ensuring the safe operation of the compressor's core components. Through multi-dimensional data fusion, forward-looking prediction, and intelligent decision-making, the accuracy, efficiency, and reliability of thermal management in magnetic levitation centrifugal compressors have been systematically improved.

[0030] In some implementations, the tiered cooling control decision includes switching between emergency cooling mode, standby mode, and sustained cooling mode to control the on / off state of the solenoid valve.

[0031] By making hierarchical cooling control decisions based on multiple conditions such as predicted temperature, real-time temperature and heat accumulation index, it is possible to effectively distinguish different thermal states such as emergency cooling mode, standby mode and maintenance cooling mode, significantly reduce the ineffective and frequent operation of solenoid valves, which is conducive to extending their service life and reducing system energy consumption, making the control action of solenoid valves more precise and rational.

[0032] In some embodiments, the temperature rise rate of the motor stator is: ; The temperature rise rate of the drive board is: ; Among them, T m (t) represents the real-time temperature of the motor stator at time t, T m (t-Δt) represents the real-time temperature of the motor stator at time t-Δt, where Δt is the time window, and T d (t) represents the real-time temperature of the driver board at time t, where T is the temperature of the driver board at time t. d (t-Δt) represents the real-time temperature of the drive board at time t-Δt.

[0033] By calculating the temperature rise rate of the motor stator and drive board in real time, the system can accurately capture the dynamic temperature change trend of key components.

[0034] In some embodiments, the heat accumulation index (HCI) is calculated using the following formula: ; Wherein, HCI is the heat accumulation index. This is the normalized stator temperature rise rate of the motor. L(t) represents the normalized temperature rise rate of the drive board, and L(t) represents the real-time load rate of the motor. T represents the normalized ambient temperature difference. a (t) represents the ambient temperature, T ref The reference temperature is 25°C, and α, β, γ, and δ are weighting coefficients, with α+β+γ+δ=1.

[0035] The weighting coefficients α, β, γ, and δ can be obtained by performing multiple linear regression analysis on a large amount of historical operating data or by training and calibrating through machine learning algorithms, in order to reflect the contribution of different factors to the total heat load of the system.

[0036] By weighting and fusing the real-time motor load rate, the normalized temperature rise rate, and the ambient temperature difference, a single, quantitative heat accumulation index (HCI) is calculated. This enables the system to perform a unified and comprehensive scientific assessment of multi-source, heterogeneous thermal state information. This index not only reflects the current balance between heat generation and dissipation in the system, but also, through the flexible configuration of weighting coefficients α, β, γ, and δ, can accurately adapt to the thermodynamic characteristics of different systems.

[0037] In some implementations, the predicted temperature is calculated as follows: Predicting future time window Δt using linear extrapolation pred The predicted temperature of the motor stator and the predicted temperature of the drive board; ; ; Among them, T m,pred For predicting the temperature of the motor stator, T m (t) represents the real-time temperature of the motor stator at time t. Δt is the rate of temperature rise of the motor stator. pred For future time windows; T d,pred To predict the temperature of the driver board, T d (t) represents the real-time temperature of the driver board at time t. This represents the temperature rise rate of the driver board.

[0038] The algorithm calculates and predicts temperatures using a linear extrapolation method based on real-time temperature and temperature rise rate. It does not rely on complex historical models or large amounts of data for training, and the algorithm is simple to implement and responds quickly.

[0039] In some implementations, the tiered cooling control decision includes: When the predicted temperature exceeds the upper temperature limit, the heat accumulation index (HCI) exceeds the opening threshold, or the real-time temperature reaches the upper temperature limit, the emergency cooling mode is triggered and the solenoid valve is opened. When the heat accumulation index (HCI) is lower than the shutdown threshold and the real-time temperature is lower than the lower limit of the temperature, the standby mode is triggered and the solenoid valve is shut off. In emergency cooling mode, when the real-time temperature and heat accumulation index (HCI) have both left the emergency zone, but the shutdown conditions for standby mode have not yet been met, the sustained cooling mode is triggered. The solenoid valve is controlled by a pulse switch, and the duty cycle is dynamically adjusted according to the heat accumulation index (HCI).

[0040] By employing a tiered decision-making approach based on a combination of multiple conditions—predicted temperature, real-time temperature, and heat accumulation index—the control system can accurately distinguish and respond to different levels of thermal risk. A multi-condition triggered emergency cooling mode enables rapid intervention and safety redundancy in critical thermal states. By requiring both heat accumulation index and temperature conditions to be met before entering standby mode, premature closure and frequent restarts of solenoid valves due to load fluctuations or residual heat are avoided. Furthermore, a pulse-based sustained cooling mode with dynamically adjusted duty cycle based on the heat accumulation index is introduced in intermediate states, achieving precise thermal balance regulation with low energy consumption and mechanical losses. Overall, this tiered strategy significantly improves the precision and rationality of control, effectively reducing ineffective solenoid valve actions while ensuring heat dissipation, thus extending lifespan and optimizing system energy efficiency.

[0041] In some implementations, the preset threshold includes an upper temperature limit T of the motor stator. max,motor The upper temperature limit T of the driver board max,driver The lower limit of the temperature T of the motor stator min,motor The lower limit T of the driver board min,driver The threshold for the heat accumulation index (HCI) on The HCI (Heat Accumulation Index) cutoff threshold off and the minimum switching gap minSwitchGap, where HCI off <HCI on ; The tiered cooling control decision includes: A. Emergency Cooling Mode: When the solenoid valve is closed and the time interval between its closure and the last closure is ≥ minimum switching interval minSwitchGap, the solenoid valve will be opened immediately if any of the following conditions are met: a) Predicted temperature exceeds limit: T m,pred ≥T max,motor or T d,pred ≥T max,driver ; Among them, T m,pred T is the predicted temperature of the motor stator. max,motor T is the upper limit of the temperature of the motor stator. d,pred T is the predicted temperature of the driver board. max,driver This is the upper temperature limit of the driver board; b) Heat accumulation index exceeds the limit: HCI≥HCI on ; Wherein, HCI is the heat accumulation index, HCI on The threshold for the heating accumulation index (HCI) is set to 1. c) The real-time temperature has reached the emergency limit (as a safety redundancy): Tm (t)≥T max,motor or T d (t)≥T max,driver ; Among them, T m (t) represents the real-time temperature of the motor stator at time t, T max,motor T is the upper limit of the temperature of the motor stator. d (t) represents the real-time temperature of the driver board at time t, where T is the temperature of the driver board at time t. max,driver This is the upper temperature limit of the driver board; B. Standby Mode: When the solenoid valve is open and the time interval between its opening and the last opening is greater than or equal to the minimum switching interval minSwitchGap, the solenoid valve will be closed if the following conditions are met simultaneously: a) Extremely low heat accumulation index: HCI≤HCI off ; Wherein, HCI is the heat accumulation index, HCI off The cutoff threshold for the Heat Accumulation Index (HCI); b) The real-time temperature has dropped below the lower limit of the temperature: T m (t)≤T min,motor And T d (t)≤T min,driver ; Among them, T m (t) represents the real-time temperature of the motor stator at time t, T min,motor T is the lower limit of the temperature of the motor stator. d (t) represents the real-time temperature of the driver board at time t, where T is the temperature of the driver board at time t. min,driver This is the lower limit of the temperature of the driver board; C. Maintain Cooling Mode: In emergency cooling mode, if the real-time temperature and heat accumulation index (HCI) are out of the emergency zone but the shutdown conditions for standby mode are not yet met, the system can switch to maintain cooling mode. The controller controls the solenoid valve to perform pulse switching at a certain duty cycle with a large cycle (e.g., 5 minutes). The duty cycle can be dynamically adjusted according to the current heat accumulation index (HCI) value. The higher the heat accumulation index (HCI) value, the larger the duty cycle. Thus, the system thermal balance can be precisely maintained with lower energy consumption and solenoid valve wear.

[0042] By constructing a complete, sophisticated, and logically rigorous hierarchical cooling control decision-making mechanism, intelligent management of solenoid valve actions is achieved, which has advantages such as foresight, accuracy, and reliability.

[0043] By setting multiple, redundant conditions, including predicted temperature, heat accumulation index, and real-time temperature, as the triggering criteria for emergency cooling mode, the system can achieve a fundamental shift from "post-event remediation" to "pre-event prevention." In particular, using predicted temperature and heat accumulation index for over-limit judgment can activate cooling in advance before the physical temperature reaches the dangerous value, effectively preventing temperature overshoot and significantly improving the operational safety of core components and system reliability. The real-time temperature upper limit condition serves as a critical safety redundancy guarantee.

[0044] Secondly, the standby mode must be triggered by simultaneously meeting two set conditions: "extremely low heat accumulation index" and "real-time temperature has dropped below the lower limit of the temperature". This enables the system to intelligently identify the true and sustainable low temperature and low load state, effectively avoiding premature closure of the solenoid valve when the load has temporarily decreased but residual heat still exists or the thermal risk is still high. This fundamentally eliminates the phenomenon of frequent short-cycle start and stop of the solenoid valve caused by this, which is crucial for extending the mechanical and electrical life of the solenoid valve.

[0045] Furthermore, by introducing a sustained cooling mode between emergency cooling and standby modes, and employing a pulse control strategy that dynamically adjusts the duty cycle based on real-time heat accumulation index values, the system can achieve stepless and precise adjustment of its heat dissipation capacity after the high-crisis period ends and before complete standby. The sustained cooling mode precisely matches the system's current actual heat dissipation needs with lower energy consumption and valve actuation frequency, smoothly maintaining thermal balance, optimizing the energy efficiency of the cooling process, and further reducing unnecessary valve wear.

[0046] Finally, by forcibly executing the precondition of "minSwitchGap" throughout the mode switching logic, the system mechanically limits the maximum number of actions of the solenoid valve per unit time, providing the most direct and effective mechanical and electrical life protection for the solenoid valve. This makes the entire intelligent control strategy not only improve performance but also have extremely high engineering practicality and reliability.

[0047] Therefore, through the above-mentioned multi-dimensional and conditional design, this hierarchical decision-making scheme achieves an optimal balance between heat dissipation performance, system safety, energy efficiency, and the lifespan of key components.

[0048] In some implementations, in step S5, the time interval between two actions of the solenoid valve must be greater than the minimum switching interval, and the motor load rate is actively reduced when the emergency cooling conditions are met but the solenoid valve cannot be opened immediately.

[0049] Under all circumstances, the time interval between two consecutive actions of the solenoid valve (open → close or close → open) must be greater than the minimum switching interval minSwitchGap.

[0050] The time interval between two actions of the solenoid valve must be greater than the minimum switching interval, which directly limits its maximum operating frequency per unit time, thus providing fundamental mechanical and electrical life protection for the solenoid valve. By introducing an active load buffering strategy, when the system anticipates an emergency cooling demand but cannot immediately open the solenoid valve due to the minimum switching interval limitation, it actively reduces the motor load rate. This allows the system to intervene quickly at the heat source, gaining critical response time for the thermal management system and effectively preventing the risk of temperature overshoot that may occur within this protection interval. This achieves intelligent coordination and safety assurance between the drive system and the cooling system under extreme operating conditions.

[0051] In some implementations, if emergency cooling conditions are met but the solenoid valve cannot be opened immediately within the minimum switching interval, a derating command is sent to the compressor main control system to reduce the motor speed or output power to reduce heat generation. By reducing heat generation at the source, time is gained for the cooling system to respond, thus achieving active buffering of the heat load.

[0052] Implementation Case 2: Please see Figure 2 A control system for a magnetic levitation centrifugal compressor solenoid valve based on multi-parameter fusion prediction includes: Motor stator temperature sensor, used to detect the temperature of the motor stator; Driver board temperature sensor, used to detect driver board temperature; An ambient temperature sensor is used to detect the ambient temperature of the compressor. The load detection module is used to detect the real-time load rate of the motor. Solenoid valve, located in the refrigerant bypass circulation path; The core controller is electrically connected to the motor stator temperature sensor, drive board temperature sensor, ambient temperature sensor, load detection module, and solenoid valve. It is used to perform data acquisition, processing, heat accumulation index calculation, temperature prediction, and control decision-making, and output control signals to drive the solenoid valve.

[0053] By configuring a motor stator temperature sensor, a drive board temperature sensor, an ambient temperature sensor, and a load detection module, and directly connecting them to the core controller, the system can acquire all key raw data (temperature, load, environment) reflecting the system's thermal state in real time and synchronously. By highly integrating data acquisition, processing, heat accumulation index calculation, temperature prediction, and control decision-making functions into a single core controller, the system possesses powerful information fusion and real-time processing capabilities. This enables efficient pipelined processing from raw data to control commands, reducing the latency and complexity of communication between multiple modules and improving the system's response speed and operational reliability. The core controller directly outputs control signals to drive the solenoid valve located in the refrigerant bypass path, allowing intelligent decisions to be accurately and quickly translated into specific cooling actions, ensuring execution efficiency and offering advantages such as high integration, fast response, and strong reliability.

[0054] In some implementations, the controller includes a data acquisition module, a data processing module, a heat accumulation index calculation module, a temperature prediction module, and a control decision module, and stores preset thresholds, weighting coefficients, and minimum switching intervals. The data acquisition module is used to collect real-time temperature data of the motor stator and drive board, real-time motor load rate, and ambient temperature. The data processing module is used to calculate the temperature rise rate of the motor stator and drive board and the ambient temperature difference based on the collected data, and to perform normalization processing. The heat accumulation index calculation module is used to calculate the heat accumulation index (HCI) based on the real-time load rate of the motor, the normalized temperature rise rate, and the ambient temperature difference. The temperature prediction module is used to calculate the predicted temperature of the motor stator and drive board based on the real-time temperature and temperature rise rate of the motor stator and drive board. The control decision module is used to perform graded cooling control decisions based on the predicted temperature, real-time temperature, heat accumulation index (HCI), and preset threshold of the motor stator and drive board.

[0055] By dividing the controller's functions into five dedicated modules—data acquisition, data processing, thermal accumulation index calculation, temperature prediction, and control decision-making—a modular design decouples the continuous data processing and control decision-making processes into functionally independent modules, resulting in a clear and logically distinct system software architecture. The data acquisition module is responsible for acquiring raw signals, the data processing module for feature extraction and standardization, the thermal accumulation index calculation module for multi-parameter fusion, the temperature prediction module for trend extrapolation, and the control decision-making module for final control decisions. This allows each module's internal algorithms to be developed, tested, and optimized independently. By having each module handle specific tasks sequentially and professionally, the entire computational process is efficient and orderly, significantly reducing the instantaneous computational load on the core controller.

[0056] Secondly, by centrally storing and managing key parameters such as preset thresholds, weighting coefficients, and minimum switching intervals, and allowing each functional module to call them as needed, the configuration, adjustment, and maintenance of system parameters become centralized and convenient. This greatly facilitates the debugging, calibration, and adaptive optimization of the system under different models or operating conditions.

[0057] This modular controller design not only efficiently and reliably implements the advanced control algorithm, but its architecture also demonstrates excellent engineering capabilities, laying a solid software foundation for the long-term stable operation, convenient maintenance, and continuous improvement of the system.

[0058] Implementation Case 3: A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the described method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction.

[0059] By embedding the steps of the aforementioned method for controlling the solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction into a computer program on a storage medium, this advanced thermal management control strategy can be independent of specific hardware environments, becoming a replicable, disseminable, and reproducible technological carrier. This allows the innovative achievement to be easily deployed and applied through various means such as software updates, pre-installation on equipment, or licensing, significantly improving the feasibility and commercial value of the technical solution. Simultaneously, this computer-readable storage medium provides tangible protection for the method invention, making legal rights protection and infringement evidence collection clearer and more convenient, thereby strengthening the strength and scope of patent protection.

[0060] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this invention and the appended claims. For example, due to the nature of software, the functions described above can be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units can be integrated into a single processing unit, or each unit can exist physically separately, or two or more units can be integrated into a single unit.

[0061] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0062] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0063] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory, random access memory, portable hard drives, magnetic disks, or optical disks.

[0064] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A control method for a solenoid valve of a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction, characterized in that: include: Collect real-time temperature data of the motor stator and drive board, real-time motor load rate, and ambient temperature. The temperature rise rate of the motor stator and drive board and the ambient temperature difference are calculated based on the collected data and then normalized. The heat accumulation index is calculated based on the real-time load rate of the motor, the normalized temperature rise rate, and the ambient temperature difference. Based on the real-time temperature and temperature rise rate of the motor stator and drive board, the predicted temperature of the motor stator and drive board is calculated. Based on the predicted temperature, real-time temperature, heat accumulation index, and preset threshold of the motor stator and drive board, a graded cooling control decision is executed.

2. The method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction according to claim 1, characterized in that: The temperature rise rate of the motor stator is: ； The temperature rise rate of the drive board is: ； Among them, T m (t) represents the real-time temperature of the motor stator at time t, T m (t-Δt) represents the real-time temperature of the motor stator at time t-Δt, where Δt is the time window, and T d (t) represents the real-time temperature of the driver board at time t, where T is the temperature of the driver board at time t. d (t-Δt) represents the real-time temperature of the drive board at time t-Δt.

3. The method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction according to claim 2, characterized in that: The formula for calculating the heat accumulation index is as follows: ； Wherein, HCI is the heat accumulation index. This is the normalized stator temperature rise rate of the motor. L(t) represents the normalized temperature rise rate of the drive board, and L(t) represents the real-time load rate of the motor. T represents the normalized ambient temperature difference. a (t) represents the ambient temperature, T ref The reference temperature is used, and α, β, γ, and δ are weighting coefficients, with α+β+γ+δ=1.

4. The method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction according to claim 3, characterized in that: The predicted temperature is calculated as follows: Predicting future time window Δt using linear extrapolation pred The predicted temperature of the motor stator and the predicted temperature of the drive board; ； ； Among them, T m,pred For predicting the temperature of the motor stator, T m (t) represents the real-time temperature of the motor stator at time t. Δt is the rate of temperature rise of the motor stator. pred For future time windows; T d,pred To predict the temperature of the driver board, T d (t) represents the real-time temperature of the driver board at time t. This represents the temperature rise rate of the driver board.

5. The method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction according to claim 1, characterized in that: The tiered cooling control decision includes switching between emergency cooling mode, standby mode and sustained cooling mode to control the on / off state of the solenoid valve. When the predicted temperature exceeds the upper temperature limit, the heat accumulation index exceeds the opening threshold, or the real-time temperature reaches the upper temperature limit, the emergency cooling mode is triggered and the solenoid valve is opened. When the heat accumulation index is lower than the shutdown threshold and the real-time temperature is lower than the lower limit of the temperature, the standby mode is triggered and the solenoid valve is closed. In emergency cooling mode, when the real-time temperature and heat accumulation index have both left the emergency zone, but the shutdown conditions for standby mode have not yet been met, the maintenance cooling mode is triggered. The solenoid valve is controlled by a pulse switch, and the duty cycle is dynamically adjusted according to the heat accumulation index.

6. The method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction according to claim 4, characterized in that: The preset thresholds include the upper and lower temperature limits of the motor stator, the upper and lower temperature limits of the drive board, the opening and closing thresholds of the heat accumulation index, and the minimum switching interval. The tiered cooling control decision includes: A. Emergency Cooling Mode: When the solenoid valve is closed and the time interval between its closure and the last closure is greater than or equal to the minimum switching interval, the solenoid valve will immediately open if any of the following conditions are met: a) Predicted temperature exceeds limit: T m,pred ≥T max,motor or T d,pred ≥T max,driver ; b) Heat accumulation index exceeds the limit: HCI ≥ HCI on ; c) The real-time temperature has reached the emergency limit: T m (t)≥T max,motor or T d (t)≥T max,driver ; B. Standby Mode: When the solenoid valve is open and the time interval between its opening and the last opening is greater than or equal to the minimum switching interval, the solenoid valve will close if the following conditions are met simultaneously: a) Extremely low heat accumulation index: HCI ≤ HCI off ; b) Real-time temperature drops to the lower limit of the temperature: T m (t)≤T min,motor And T d (t)≤T min,driver ; C. Maintain Cooling Mode: In emergency cooling mode, if the real-time temperature and heat accumulation index are out of the emergency zone but the shutdown conditions of standby mode are not yet met, the system can switch to maintain cooling mode; the controller controls the solenoid valve to perform pulse switching at a certain duty cycle with a large cycle. The duty cycle can be dynamically adjusted according to the current heat accumulation index value. The higher the heat accumulation index value, the larger the duty cycle. Among them, T m,pred T is the predicted temperature of the motor stator. max,motor T is the upper limit of the temperature of the motor stator. d,pred T is the predicted temperature of the driver board. max,driver The upper temperature limit of the driver board; HCI is the thermal accumulation index. on HCI is the threshold for the thermal accumulation index. off The threshold for the thermal accumulation index; T m (t) represents the real-time temperature of the motor stator at time t, T d (t) represents the real-time temperature of the drive board at time t; T min,motor T is the lower limit of the temperature of the motor stator. min,driver This is the lower limit of the temperature of the driver board.

7. The method for controlling a solenoid valve of a magnetically levitated centrifugal compressor based on multi-parameter fusion prediction according to claim 6, characterized in that: Also includes: The time interval between two actions of the solenoid valve must be greater than the minimum switching interval, and the motor load rate should be actively reduced when emergency cooling conditions are met but the solenoid valve cannot be opened immediately.

8. A control system for a magnetic levitation centrifugal compressor solenoid valve based on multi-parameter fusion prediction, characterized in that: include: Motor stator temperature sensor, used to detect the temperature of the motor stator; Driver board temperature sensor, used to detect driver board temperature; An ambient temperature sensor is used to detect the ambient temperature of the compressor. The load detection module is used to detect the real-time load rate of the motor. Solenoid valve, located in the refrigerant bypass circulation path; The core controller is electrically connected to the motor stator temperature sensor, drive board temperature sensor, ambient temperature sensor, load detection module, and solenoid valve. It is used to perform data acquisition, processing, heat accumulation index calculation, temperature prediction, and control decision-making, and output control signals to drive the solenoid valve.

9. A solenoid valve control system for a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction according to claim 8, characterized in that: The controller includes a data acquisition module, a data processing module, a heat accumulation index calculation module, a temperature prediction module, and a control decision module, and stores preset thresholds, weighting coefficients, and minimum switching intervals. The data acquisition module is used to collect real-time temperature data of the motor stator and drive board, real-time motor load rate, and ambient temperature. The data processing module is used to calculate the temperature rise rate of the motor stator and drive board and the ambient temperature difference based on the collected data, and to perform normalization processing. The heat accumulation index calculation module is used to calculate the heat accumulation index based on the real-time load rate of the motor, the normalized temperature rise rate, and the ambient temperature difference. The temperature prediction module is used to calculate the predicted temperature of the motor stator and drive board based on the real-time temperature and temperature rise rate of the motor stator and drive board. The control decision module is used to perform graded cooling control decisions based on the predicted temperature, real-time temperature, heat accumulation index and preset threshold of the motor stator and drive board.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by the processor, it implements the steps of the electromagnetic valve control method for a magnetic levitation centrifugal compressor based on multi-parameter fusion prediction as described in any one of claims 1-7.

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