Cooling and heating air supply control method and system based on magnetic suspension air conditioning unit

Abstract

The invention discloses a cooling and heating air supply control method and system based on a magnetic suspension air conditioning unit, and relates to the technical field of cooling and heating air supply control. The method comprises the steps that according to heat load distribution data, a chaos particle swarm optimization algorithm is used for calculation, and an optimal compressor rotating speed parameter and fan static pressure parameter combination is obtained; adjusting the compressor rotating speed parameter and the fan static pressure parameter of the magnetic suspension air conditioning unit based on the optimal combination of the compressor rotating speed parameter and the fan static pressure parameter, and calculating the optimal deflection angle parameter of the deformable guide vane based on the adjusted magnetic suspension air conditioning unit in combination with the thermal load distribution data. And the optimal deflection angle parameter of the deformable guide vane is converted into a pulse width modulation signal, a micro servo motor of the deformable guide vane is driven, and air supply airflow distribution is completed. According to the air conditioner control method based on the magnetic suspension technology, the dual purposes of energy conservation and comfort are achieved, and the space temperature uniformity and the air supply efficiency are further optimized.

Description

Technical Field

[0001] This invention relates to the field of air supply control technology, and in particular to an air supply control method and system based on a magnetic levitation air conditioning unit. Background Technology

[0002] With the continuous advancement of modern building technology and people's increasing demands for indoor environmental comfort, air conditioning, as an important device for regulating indoor temperature and humidity, plays a crucial role in building design. In the past, air conditioning units relied on mechanical bearings to support the compressor. However, in recent years, the application of magnetic levitation technology has brought about revolutionary changes in this field. Replacing the traditional mechanical bearings with magnetic levitation bearings can not only significantly reduce friction loss and improve compressor efficiency, but also greatly reduce equipment maintenance needs and operating noise due to reduced direct contact. In addition, with the development of sensor technology and intelligent control algorithms, air conditioning units can make precise adjustments based on real-time monitoring of personnel distribution information and ambient temperature data, thereby achieving more efficient and energy-saving operation.

[0003] Nevertheless, there is still room for improvement in the existing air conditioning control methods based on magnetic levitation technology. Most air conditioning products on the market today fail to fully integrate real-time monitoring of personnel activity information and indoor temperature field data, resulting in insufficient responsiveness of the air conditioning unit and an inability to adjust the air supply mode in a timely manner according to actual needs. The optimization configuration of compressor speed and fan static pressure often relies on preset rules and simple feedback mechanisms, lacking the ability to explore the global optimal solution under specific operating conditions. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a cooling and heating air supply control method based on magnetic levitation air conditioning units to solve the problem that magnetic levitation air conditioning units cannot adjust the air supply mode according to demand.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a method for controlling the cooling and heating air supply of a magnetic levitation air conditioning unit, comprising,

[0008] The magnetic levitation bearing is activated, and the position of the compressor rotor is monitored in real time by a displacement sensor. The electromagnetic force is adjusted to form a stable levitation compressor rotor.

[0009] Based on a stable suspended compressor rotor, personnel distribution data is collected and combined with ambient temperature data monitored by an infrared thermal imager to construct a comprehensive temperature field and obtain heat load distribution data.

[0010] Based on the heat load distribution data, the chaotic particle swarm optimization algorithm is used to calculate and obtain the optimal combination of compressor speed parameters and fan static pressure parameters;

[0011] Based on the optimal combination of compressor speed parameters and fan static pressure parameters, adjust the compressor speed parameters and fan static pressure parameters of the magnetic levitation air conditioning unit;

[0012] Based on the adjusted magnetic levitation air conditioning unit and combined with heat load distribution data, the optimal deflection angle parameters of the deformable guide vanes are calculated.

[0013] The optimal deflection angle parameters of the deformable guide vanes are converted into pulse width modulation signals to drive the miniature servo motors of the deformable guide vanes, thereby completing the airflow distribution.

[0014] As a preferred embodiment of the cooling and heating air supply control method for a magnetic levitation air conditioning unit described in this invention, the step of activating the magnetic levitation bearing involves using a displacement sensor to monitor the compressor rotor position in real time and adjusting the electromagnetic force to form a stably levitated compressor rotor. Specifically,

[0015] The magnetic levitation bearing is activated, and a displacement sensor is used to collect the three-dimensional position coordinates of the compressor rotor, which are then transmitted to the electromagnetic force controller.

[0016] The electromagnetic force controller calculates the required current command value for the axial electromagnetic coil based on the three-dimensional position coordinates of the compressor rotor.

[0017] The power amplifier is used to adjust the excitation current of the corresponding electromagnetic coil according to the current command value of each axial electromagnetic coil to generate a three-dimensional electromagnetic force field in space.

[0018] By applying a three-dimensional electromagnetic field to the ferromagnetic components of the compressor rotor, an electromagnetic force is generated that is opposite to gravity and vibration, thus forming a stable, suspended compressor rotor.

[0019] As a preferred embodiment of the cooling and heating air supply control method based on a magnetic levitation air conditioning unit described in this invention, the method involves: collecting personnel distribution data based on a stably suspended compressor rotor, combining this data with ambient temperature data monitored by an infrared thermal imager to construct a comprehensive temperature field, and obtaining heat load distribution data. Specifically...

[0020] Based on a stable suspended compressor rotor, a millimeter-wave radar array is used to collect real-time personnel distribution data, and an infrared thermal imager is used to capture the temperature distribution of various indoor surfaces to generate an ambient temperature data matrix.

[0021] The data processing unit is used to align the personnel distribution data with the ambient temperature data matrix in time and space. After filling the monitoring blind spots with the Kriging interpolation algorithm, a comprehensive temperature field of personnel thermal radiation and building structure heat transfer is established.

[0022] Based on the comprehensive temperature field, the equivalent value of the heat load for each spatial unit is calculated to obtain heat load distribution data.

[0023] As a preferred embodiment of the cooling and heating air supply control method based on a magnetic levitation air conditioning unit described in this invention, the step of calculating and obtaining the optimal combination of compressor speed parameters and fan static pressure parameters using a chaotic particle swarm optimization algorithm based on heat load distribution data specifically involves:

[0024] The heat load distribution data is input into the chaotic particle swarm optimization algorithm, and Y groups of particles including compressor speed parameters and fan static pressure parameters are randomly generated. The particle swarm is initialized with Tent chaos using the chaotic mapping function, and the weighted evaluation value of thermal comfort index and energy consumption coefficient corresponding to each particle in the particle swarm is calculated through the fitness function.

[0025] Based on the weighted evaluation value, each particle in the particle swarm updates its individual historical best solution and the global historical best solution. After multiple rounds of iteration, the optimal combination of compressor speed parameters and fan static pressure parameters is generated.

[0026] As a preferred embodiment of the cooling and heating air supply control method based on a magnetic levitation air conditioning unit according to the present invention, wherein: adjusting the compressor speed parameters and fan static pressure parameters of the magnetic levitation air conditioning unit based on the optimal combination of compressor speed parameters and fan static pressure parameters specifically involves...

[0027] The optimal combination of compressor speed parameters and fan static pressure parameters is transmitted to the magnetic levitation air conditioning unit control unit.

[0028] The magnetic levitation air conditioning unit control unit analyzes the optimal combination of compressor speed parameters and fan static pressure parameters to generate a three-phase PWM modulation signal and an analog voltage signal;

[0029] The inverter adjusts the power supply frequency of the permanent magnet synchronous motor according to the three-phase PWM modulation signal, so that the compressor rotor accelerates to the optimal compressor speed parameters under the support of the magnetic levitation bearing;

[0030] After receiving the analog voltage signal, the fan changes the impeller speed through a stepless speed regulation device to establish a static pressure gradient in the duct that conforms to the optimal static pressure parameters of the fan.

[0031] As a preferred embodiment of the cooling and heating air supply control method based on a magnetic levitation air conditioning unit according to the present invention, wherein: based on the adjusted magnetic levitation air conditioning unit, and combined with heat load distribution data, the optimal deflection angle parameters of the deformable guide vanes are calculated, specifically as follows:

[0032] Based on the adjusted magnetic levitation air conditioning unit, combined with heat load distribution data, computational fluid dynamics is used to solve the three-dimensional airflow organization state, and the optimal deflection angle parameters of the deformable guide vanes are iteratively calculated using chaotic particle swarm optimization algorithm.

[0033] As a preferred embodiment of the cooling and heating air supply control method based on magnetic levitation air conditioning units described in this invention, the step of converting the optimal deflection angle parameters of the deformable guide vanes into pulse width modulation signals and driving the micro servo motors of the deformable guide vanes to complete the air supply air distribution specifically involves...

[0034] The optimal deflection angle parameters of the deformable guide vane are converted into three pulse width modulation signals with phase difference by a digital signal processor;

[0035] A pulse width modulation signal drives a miniature servo motor to deflect the deformable guide vanes, which then distribute the airflow according to the heat load distribution data.

[0036] Secondly, the present invention provides a cooling and heating air supply control system based on a magnetic levitation air conditioning unit, comprising,

[0037] The adjustment module activates the magnetic levitation bearing, monitors the compressor rotor position in real time through a displacement sensor, and adjusts the electromagnetic force to form a stable suspended compressor rotor.

[0038] The data acquisition module, based on a stable suspended compressor rotor, collects personnel distribution data and combines it with ambient temperature data monitored by an infrared thermal imager to construct a comprehensive temperature field and obtain heat load distribution data.

[0039] The optimization module uses a chaotic particle swarm optimization algorithm to calculate the optimal combination of compressor speed parameters and fan static pressure parameters based on heat load distribution data.

[0040] The adjustment module adjusts the compressor speed and fan static pressure parameters of the magnetic levitation air conditioning unit based on the optimal combination of compressor speed parameters and fan static pressure parameters.

[0041] The calculation module, based on the adjusted magnetic levitation air conditioning unit and combined with heat load distribution data, calculates the optimal deflection angle parameters of the deformable guide vanes;

[0042] The airflow distribution module converts the optimal deflection angle parameters of the deformable guide vanes into pulse width modulation signals, which drive the miniature servo motors of the deformable guide vanes to complete the airflow distribution.

[0043] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the cooling and heating air supply control method based on the magnetic levitation air conditioning unit as described in the first aspect of the present invention.

[0044] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in the first aspect of the present invention.

[0045] The beneficial effects of this invention are as follows: By activating the magnetic levitation bearing and using displacement sensors to monitor and adjust the electromagnetic force in real time, stable levitation of the compressor rotor is achieved, reducing friction loss and lowering noise and maintenance requirements. At the same time, based on heat load distribution data, the air conditioning system can respond sensitively to changes in the actual environment, improving comfort. The optimal combination of compressor speed parameters and fan static pressure parameters is calculated using a chaotic particle swarm optimization algorithm, improving the energy efficiency ratio and thermal comfort of the air conditioning unit, achieving the dual goals of energy saving and comfort. Finally, the magnetic levitation air conditioning unit, in conjunction with deformable guide vanes, completes airflow distribution, further optimizing the uniformity of spatial temperature and air delivery efficiency. Attached Figure Description

[0046] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are 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.

[0047] Figure 1 This is a flowchart of a cooling and heating air supply control method based on a magnetic levitation air conditioning unit.

[0048] Figure 2 A flowchart for adjusting the parameters of a magnetic levitation air conditioning unit.

[0049] Figure 3 This is a flowchart illustrating the architecture of a cooling and heating air supply control method based on a magnetic levitation air conditioning unit.

[0050] Figure 4 A flowchart for the distribution of airflow. Detailed Implementation

[0051] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0052] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0053] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0054] Reference Figures 1-4 As one embodiment of the present invention, this embodiment provides a cooling and heating air supply control method based on a magnetic levitation air conditioning unit, comprising the following steps:

[0055] S1. Start the magnetic levitation bearing, monitor the compressor rotor position in real time through the displacement sensor, and adjust the electromagnetic force to form a stable suspended compressor rotor;

[0056] The magnetic levitation bearing is activated, and a displacement sensor is used to collect the three-dimensional position coordinates of the compressor rotor, which are then transmitted to the electromagnetic force controller.

[0057] It should be noted that after the magnetic levitation bearing is powered on and started, the eddy current displacement sensor group arranged on the radial and axial sides of the compressor rotor starts to work. The X-axis displacement sensor, Y-axis displacement sensor and Z-axis displacement sensor collect the real-time position coordinates of the compressor rotor in three-dimensional space at a sampling frequency of 20kHz, and transmit them to the ADC input port of the electromagnetic force controller through shielded twisted pair cable.

[0058] The electromagnetic force controller calculates the required current command value for the axial electromagnetic coil based on the three-dimensional position coordinates of the compressor rotor.

[0059] It should be noted that the electromagnetic force controller reads the three-dimensional position coordinates (X-axis, Y-axis, and Z-axis coordinates) of the compressor rotor uploaded by the displacement sensor group, compares the three-dimensional position coordinates with the position coordinates of the suspended target, and calculates the position deviations in the X-axis, Y-axis, and Z-axis directions. The built-in PID control algorithm of the electromagnetic force controller calculates the X-axis electromagnetic coil current correction, Y-axis electromagnetic coil current correction, and Z-axis electromagnetic coil current correction based on the X-axis, Y-axis, and Z-axis position deviations, respectively. The current correction for each axis can be calculated using the following formula:

[0060]

[0061] Where I represents the axis electromagnetic coil current correction, K represents the axis proportional control coefficient, e represents the axis direction position deviation, R represents the axis integral control term, d represents the axis derivative control coefficient, s represents the change in axis position deviation, and t represents the control period.

[0062] The calculation process employs a feedforward compensation algorithm to counteract the periodic disturbances during compressor rotor rotation, and a Kalman filter to eliminate the influence of measurement noise. The final outputs are the X-axis electromagnetic coil current command values, Y-axis electromagnetic coil current command values, and Z-axis electromagnetic coil current command values.

[0063] The power amplifier is used to adjust the excitation current of the corresponding electromagnetic coil according to the current command value of each axial electromagnetic coil to generate a three-dimensional electromagnetic force field in space.

[0064] It should be noted that the power amplifier receives the X-axis, Y-axis, and Z-axis electromagnetic coil current command values ​​from the electromagnetic force controller. The power amplifier's internal digital signal processor analyzes these axial current command values ​​and generates corresponding PWM modulation signals. These PWM modulation signals drive the H-bridge power circuit, converting the DC bus voltage into the precise excitation current required by the X-axis, Y-axis, and Z-axis electromagnetic coils. Hall effect current sensors monitor the actual current values ​​of each electromagnetic coil in real time. After comparing the actual current values ​​with the current command values, the power amplifier dynamically adjusts the PWM duty cycle using a PID control algorithm. Ultimately, it establishes excitation currents matching the command values ​​in the X-axis, Y-axis, and Z-axis electromagnetic coils. The magnetic fields generated by the three sets of electromagnetic coils are vector-synthesized in space, forming a three-dimensional electromagnetic force field that meets the requirements of compressor rotor suspension control.

[0065] By applying a three-dimensional electromagnetic field to the ferromagnetic components of the compressor rotor, an electromagnetic force is generated that is opposite to gravity and vibration, thus forming a stable suspended compressor rotor.

[0066] Furthermore, when the three-dimensional electromagnetic field acts on the ferromagnetic components of the compressor rotor, the radial horizontal electromagnetic force generated by the X-axis electromagnetic coil counteracts the horizontal displacement inertial force of the compressor rotor, the radial vertical electromagnetic force generated by the Y-axis electromagnetic coil balances the gravitational load of the compressor rotor, and the axial electromagnetic force generated by the Z-axis electromagnetic coil suppresses the axial movement of the compressor rotor. The three sets of electromagnetic forces form a vector resultant force in space, and the direction of the vector resultant force is always opposite to the direction of the compressor rotor offset detected by the displacement sensor. The electromagnetic force controller dynamically adjusts the intensity of the three-dimensional electromagnetic field according to the real-time data of the displacement sensor, so that the compressor rotor is held in the radial direction, for example, with a suspension gap of 50±2μm, and in the axial direction, for example, with a suspension gap of 20±1μm. When the compressor rotor is subjected to external vibration disturbance, the electromagnetic field completes adaptive adjustment within 5ms, and suppresses the amplitude of the compressor rotor within the range of ±3μm through the electromagnetic damping effect, ultimately achieving stable suspension of the compressor rotor.

[0067] S2. Based on the stable suspension of the compressor rotor, collect personnel distribution data and combine it with the ambient temperature data monitored by the infrared thermal imager to construct a comprehensive temperature field and obtain heat load distribution data;

[0068] Based on a stable suspended compressor rotor, a millimeter-wave radar array is used to collect real-time personnel distribution data, and an infrared thermal imager is used to capture the temperature distribution of various indoor surfaces to generate an ambient temperature data matrix.

[0069] It should be noted that, with the compressor rotor stably suspended, the millimeter-wave radar array installed on the indoor ceiling emits 76-81GHz frequency-modulated continuous waves at a scanning frequency of 60Hz. After receiving the human body reflection signal, it calculates the real-time personnel distribution coordinates through beamforming algorithm and outputs personnel distribution data including personnel position, movement speed and body shape characteristics. At the same time, infrared thermal imagers deployed on the four walls synchronously scan the temperature of each surface in the room, and use the blackbody radiation law to convert the infrared radiation intensity into temperature values, generating an ambient temperature data matrix with spatial coordinate markers.

[0070] The data processing unit is used to align the personnel distribution data with the ambient temperature data matrix in time and space. After filling the monitoring blind spots with the Kriging interpolation algorithm, a comprehensive temperature field of personnel thermal radiation and building structure heat transfer is established.

[0071] It should be noted that after receiving the personnel distribution data and the ambient temperature data matrix, the data processing unit first adds a unified timestamp and spatial coordinate system identifier to both sets of data; it then uses a dynamic time warping algorithm to compensate for the sampling time difference between the millimeter-wave radar array and the infrared thermal imager, ensuring that the personnel distribution data and the ambient temperature data matrix are strictly synchronized in the time dimension; through coordinate transformation, it converts the polar coordinates of the personnel distribution data to a Cartesian coordinate system consistent with the ambient temperature data matrix, establishing a correlated dataset including personnel coordinates, movement speed, and surface temperature. Simultaneously, it uses the Kriging interpolation algorithm to calculate the predicted temperature values ​​for blind spots such as beams, columns, doors, and windows in the building structure, incorporating human metabolic heat parameters (e.g., 58 W / m²) from the personnel distribution data during the interpolation process. 2 As a correction factor, the final comprehensive temperature field is generated.

[0072] The comprehensive temperature field includes every 0.1m 3 Four-dimensional data of a spatial unit: three-dimensional coordinates (X,Y,Z), temperature value, thermal radiation intensity of people, and heat transfer coefficient of building structure.

[0073] Based on the comprehensive temperature field, the equivalent heat load value of each spatial unit is calculated to obtain heat load distribution data;

[0074] Furthermore, the comprehensive temperature field is input into the thermodynamic calculation engine, which then analyzes each 0.1m... 3 The four parameters of the spatial unit are its three-dimensional coordinates, temperature, human thermal radiation intensity, and building structure heat transfer coefficient. Simultaneously, the instantaneous heat exchange of each spatial unit is calculated using the heat flux density formula. The heat flux density formula is as follows:

[0075] M = α × G + h(θ - τ);

[0076] Where M represents instantaneous heat exchange, α represents the heat transfer coefficient of the building envelope, G represents the temperature difference between the inner and outer surfaces of the building envelope, h represents the convective heat transfer coefficient between the air and the human body surface, θ represents the body surface temperature of the personnel, and τ represents the air temperature of the space unit.

[0077] The temperature difference t between the inner and outer surfaces of the building envelope was obtained by infrared thermal imager and embedded temperature sensor. The convective heat transfer coefficient h between air and human body surface is related to airflow velocity (e.g., 4.3 at low speed of 0.15 m / s and 6.1 at high speed of 0.35 m / s). The body surface temperature of personnel was collected by millimeter-wave radar, and the air temperature τ of space unit was taken from the comprehensive temperature field.

[0078] The instantaneous heat exchange of each spatial unit is compared with the indoor comfort temperature baseline (e.g., 24±1℃), and the equivalent heat load value of each spatial unit is output. After the equivalent heat load values ​​of all spatial units are smoothed by Gaussian filtering, heat load distribution data with three-dimensional coordinate markers is generated. The heat load distribution data includes three parameters: spatial location coordinates, real-time heat load value, and historical trend slope.

[0079] S3. Based on the heat load distribution data, use the chaotic particle swarm optimization algorithm to calculate and obtain the optimal combination of compressor speed parameters and fan static pressure parameters;

[0080] The heat load distribution data is input into the chaotic particle swarm optimization algorithm, and Y groups of particles including compressor speed parameters and fan static pressure parameters are randomly generated. The particle swarm is initialized with Tent chaos using the chaotic mapping function, and the weighted evaluation value of thermal comfort index and energy consumption coefficient corresponding to each particle in the particle swarm is calculated through the fitness function.

[0081] It should be noted that after the heat load distribution data is input into the chaotic particle swarm optimization algorithm, the initialization phase of the algorithm randomly generates an initial particle swarm of Y groups of compressor speed parameters and fan static pressure parameters. The Tent chaotic mapping function performs chaotic processing on the compressor speed parameters and fan static pressure parameters of each particle in the particle swarm. That is, the chaotic mapping function receives the compressor speed parameters and fan static pressure parameters of each particle in the particle swarm as input, and generates a chaotic sequence through iteration. The chaotic sequence performs a nonlinear transformation on the compressor speed parameters and fan static pressure parameters. The nonlinearly transformed compressor speed parameters and fan static pressure parameters are redistributed in the solution space, forming parameter combinations with ergodicity and randomness, thus completing the chaotic processing of parameters in the particle swarm optimization process. The fitness function calculates the thermal comfort index (PMV-PPD value) and energy consumption coefficient (COP reciprocal) corresponding to each particle after chaotic processing based on the heat load distribution data. At the same time, it outputs a weighted evaluation value through linear weighting (e.g., the thermal comfort index weight is 0.6, and the energy consumption coefficient weight is 0.4). The formula is as follows:

[0082] F = α·(P) + β·(C);

[0083] Where F represents the weighted evaluation value, α represents the weight of the thermal comfort index, P represents the thermal comfort index, β represents the weight of the energy consumption coefficient, and C represents the energy consumption coefficient.

[0084] Based on the weighted evaluation value, each particle in the particle swarm updates its individual historical best solution and the global historical best solution. After multiple rounds of iteration, the optimal combination of compressor speed parameters and fan static pressure parameters is generated.

[0085] Furthermore, each particle compares the weighted evaluation values ​​corresponding to the current compressor speed parameters and fan static pressure parameters with the weighted evaluation values ​​stored in the particle's individual historical optimal solution. If the current weighted evaluation value is better, the individual historical optimal solution is updated using the current compressor speed parameters and fan static pressure parameters. That is, the global historical optimal solution updates by traversing the individual historical optimal solutions of all particles and selecting the combination of compressor speed parameters and fan static pressure parameters with the highest weighted evaluation value. The updated particle swarm adjusts its flight direction according to the velocity-position model, and the position update is adjusted by the chaotic perturbation term. For example, after 200 iterations, the compressor speed parameters and fan static pressure parameters recorded in the global historical optimal solution are taken as the optimal combination of compressor speed parameters and fan static pressure parameters.

[0086] S4. Based on the optimal combination of compressor speed parameters and fan static pressure parameters, adjust the compressor speed parameters and fan static pressure parameters of the magnetic levitation air conditioning unit;

[0087] The optimal combination of compressor speed parameters and fan static pressure parameters is transmitted to the magnetic levitation air conditioning unit control unit.

[0088] It should be noted that the optimal combination of compressor speed parameters and fan static pressure parameters output by the chaotic particle swarm optimization algorithm is encapsulated into a control command data packet via real-time Ethernet protocol and uploaded to the communication interface of the magnetic levitation air conditioning unit control unit.

[0089] The magnetic levitation air conditioning unit control unit analyzes the optimal combination of compressor speed parameters and fan static pressure parameters to generate a three-phase PWM modulation signal and an analog voltage signal;

[0090] It should be noted that the digital signal processor of the magnetic levitation air conditioning unit control unit automatically converts the compressor speed parameter into a three-phase PWM modulation signal; simultaneously, the fan static pressure parameter is output as an analog voltage signal through a 12-bit digital-to-analog converter. The frequency converter drive signal includes both a three-phase PWM modulation signal and an analog voltage signal.

[0091] The inverter adjusts the power supply frequency of the permanent magnet synchronous motor according to the three-phase PWM modulation signal, so that the compressor rotor accelerates to the optimal compressor speed parameters under the support of the magnetic levitation bearing.

[0092] It should be noted that after the inverter receives the three-phase PWM modulation signal generated by the magnetic levitation air conditioning unit control unit, the IPM intelligent power module converts the three-phase PWM modulation signal into a three-phase AC voltage output; the three-phase AC voltage is applied to the stator winding of the permanent magnet synchronous motor to generate a rotating magnetic field. The rotating magnetic field drives the compressor rotor to accelerate, ultimately enabling the compressor rotor to reach the target speed under the support of the magnetic levitation bearing.

[0093] After receiving the analog voltage signal, the fan changes the impeller speed through a stepless speed regulation device to establish a static pressure gradient in the duct that conforms to the optimal static pressure parameters of the fan.

[0094] It should be noted that after the fan receives the analog voltage signal output by the control unit of the magnetic levitation air conditioning unit, the voltage-frequency converter inside the stepless speed regulation device converts the analog voltage signal into a PWM waveform of the corresponding frequency. The PWM waveform drives the MOSFET power switch to adjust the input voltage of the DC motor. At the same time, the output shaft of the DC motor is connected to the main shaft of the centrifugal impeller through a flexible coupling. The centrifugal force generated by the increase in impeller speed creates a static pressure gradient between the inlet and outlet of the volute air duct.

[0095] S5. Based on the adjusted magnetic levitation air conditioning unit and combined with the heat load distribution data, calculate the optimal deflection angle parameters of the deformable guide vanes.

[0096] Based on the adjusted magnetic levitation air conditioning unit, combined with heat load distribution data, the three-dimensional airflow organization state is solved by computational fluid dynamics, and the optimal deflection angle parameters of the deformable guide vanes are iteratively calculated by chaotic particle swarm optimization algorithm.

[0097] It should be noted that, based on the adjusted magnetic levitation air conditioning unit, a three-dimensional flow field model was established using computational fluid dynamics (CFD) methods based on heat load distribution data, and the spatial airflow organization state was obtained by solving the Navier-Stokes equations. The Navier-Stokes equations are the mathematical foundation for establishing three-dimensional flow field models in computational fluid dynamics (CFD), and are a set of partial differential equations describing fluid motion (momentum conservation), mass conservation, and energy conservation. The mass conservation equation is as follows:

[0098]

[0099] Where ρ represents fluid density and t represents time. Let denote the divergence operator, and u denote the velocity vector;

[0100] The equation for the conservation of momentum is:

[0101]

[0102] Where ρ represents fluid density, t represents time, and u represents the velocity vector. Let U represent the divergence operator, U represent the aerodynamic viscosity, W represent gravity, and j represent the hydrostatic pressure.

[0103] The energy conservation equation is as follows:

[0104]

[0105] Where ρ represents fluid density, m represents specific heat capacity of air at constant pressure, Z represents temperature, k represents thermal conductivity of air, Φ represents viscous dissipation, and Q represents external heat source;

[0106] After solving the Navier-Stokes equations, CFD post-processing software is used to extract airflow vector velocity, pressure, and temperature to obtain the spatial airflow state organization.

[0107] The particle swarm optimization (PSO) algorithm initializes a set of particle positions representing the deflection angle of the deformable guide vane. It constructs an objective function based on airflow organization and heat load distribution data, considering both temperature uniformity and airflow organization efficiency. Computational fluid dynamics (CFD) methods simulate temperature standard deviation, airflow organization efficiency, and fan energy consumption data based on the particle positions. The simulated temperature standard deviation, airflow organization efficiency, and fan energy consumption data are then weighted and summed. The weighted sum is returned to the PSO algorithm as the objective function value. The PSO algorithm updates the particle velocity and position based on the objective function value, retaining historical optimal solutions during the iteration process. Upon convergence, it outputs the optimal deflection angle parameters of the deformable guide vane that minimize the objective function.

[0108] S6. Convert the optimal deflection angle parameters of the deformable guide vanes into pulse width modulation signals and drive the micro servo motor of the deformable guide vanes to complete the airflow distribution.

[0109] The optimal deflection angle parameters of the deformable guide vane are converted into three pulse width modulation signals with phase difference by a digital signal processor;

[0110] It should be noted that after the optimal deflection angle parameters of the deformable guide vanes are input into the digital signal processor, the Park-Clark transformation is used to convert the optimal deflection angle parameters into control quantities in the dq-axis rotating coordinate system. Three-phase duty cycle data is then generated using a space vector modulation algorithm. Based on the three-phase duty cycle data, the timer unit of the digital signal processor synchronously outputs three pulse width modulation signals with a phase difference of 120 degrees.

[0111] A pulse width modulation signal drives a miniature servo motor to deflect the deformable guide vane, which then distributes the airflow according to the heat load distribution data.

[0112] It should be noted that the pulse width modulation (PWM) signal drives the miniature servo motor of the deformable guide vane to rotate, causing the deformable guide vane to rotate to the target angle position. Simultaneously, the photoelectric encoder built into the miniature servo motor detects the actual deflection angle of the deformable guide vane in real time. The actual deflection angle of the deformable guide vane is compared with the optimal deflection angle parameter, and the duty cycle of the PWM signal is adjusted using a proportional-integral-derivative (PID) control algorithm to ensure the deformable guide vane completes its deflection. After deflection, the deformable guide vane changes the direction and velocity distribution of the airflow, causing the airflow (including cold airflow in cooling mode and hot airflow in heating mode) to be automatically distributed according to the heat load distribution data collected by the infrared thermal imager. For example, in high-temperature areas, the corresponding cold airflow velocity is increased to 0.25-0.35 m / s in cooling mode, and the airflow angle is controlled within the range of 15-25°. In low-temperature areas, the hot airflow angle is adjusted to 30-45° in heating mode, maintaining a low airflow speed of 0.12-0.18 m / s.

[0113] This embodiment also provides a cooling and heating air supply control system based on a magnetic levitation air conditioning unit, including:

[0114] The adjustment module activates the magnetic levitation bearing, monitors the compressor rotor position in real time through a displacement sensor, and adjusts the electromagnetic force to form a stable suspended compressor rotor.

[0115] The data acquisition module, based on a stable suspended compressor rotor, collects personnel distribution data and combines it with ambient temperature data monitored by an infrared thermal imager to construct a comprehensive temperature field and obtain heat load distribution data.

[0116] The optimization module uses a chaotic particle swarm optimization algorithm to calculate the optimal combination of compressor speed parameters and fan static pressure parameters based on heat load distribution data.

[0117] The adjustment module adjusts the compressor speed and fan static pressure parameters of the magnetic levitation air conditioning unit based on the optimal combination of compressor speed parameters and fan static pressure parameters.

[0118] The calculation module, based on the adjusted magnetic levitation air conditioning unit and combined with heat load distribution data, calculates the optimal deflection angle parameters of the deformable guide vanes;

[0119] The airflow distribution module converts the optimal deflection angle parameters of the deformable guide vanes into pulse width modulation signals, which drive the miniature servo motors of the deformable guide vanes to complete the airflow distribution.

[0120] This embodiment also provides a computer device applicable to the cooling and heating air supply control method based on a magnetic levitation air conditioning unit, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the cooling and heating air supply control method based on a magnetic levitation air conditioning unit as proposed in the above embodiment.

[0121] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0122] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements the cooling and heating air supply control method for a magnetic levitation air conditioning unit as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0123] In summary, this invention achieves stable levitation of the compressor rotor by activating the magnetic levitation bearing and using a displacement sensor to monitor and adjust the electromagnetic force in real time. This reduces frictional losses, noise, and maintenance requirements. Simultaneously, the heat load distribution data allows the air conditioning system to respond sensitively to changes in the actual environment, improving comfort. Furthermore, the use of a chaotic particle swarm optimization algorithm to calculate the optimal combination of compressor speed and fan static pressure parameters improves the energy efficiency ratio and thermal comfort of the air conditioning unit, achieving the dual goals of energy saving and comfort. Finally, the magnetic levitation air conditioning unit, in conjunction with deformable guide vanes, completes airflow distribution, further optimizing spatial temperature uniformity and air delivery efficiency.

[0124] It should be noted that 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 preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for controlling the cooling and heating air supply of a magnetic levitation air conditioning unit, characterized in that: include, The magnetic levitation bearing is activated, and the position of the compressor rotor is monitored in real time by a displacement sensor. The electromagnetic force is adjusted to form a stable levitation compressor rotor. Based on a stable suspended compressor rotor, personnel distribution data is collected and combined with ambient temperature data monitored by an infrared thermal imager to construct a comprehensive temperature field and obtain heat load distribution data. Based on the heat load distribution data, the chaotic particle swarm optimization algorithm is used to calculate and obtain the optimal combination of compressor speed parameters and fan static pressure parameters; Based on the optimal combination of compressor speed parameters and fan static pressure parameters, adjust the compressor speed parameters and fan static pressure parameters of the magnetic levitation air conditioning unit; Based on the adjusted magnetic levitation air conditioning unit and combined with heat load distribution data, the optimal deflection angle parameters of the deformable guide vanes are calculated. The optimal deflection angle parameters of the deformable guide vanes are converted into pulse width modulation signals to drive the miniature servo motors of the deformable guide vanes, thereby completing the airflow distribution.

2. The cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in claim 1, characterized in that: The aforementioned starting magnetic levitation bearing monitors the compressor rotor position in real time using a displacement sensor and adjusts the electromagnetic force to form a stably levitated compressor rotor. Specifically, The magnetic levitation bearing is activated, and a displacement sensor is used to collect the three-dimensional position coordinates of the compressor rotor, which are then transmitted to the electromagnetic force controller. The electromagnetic force controller calculates the required current command value for the axial electromagnetic coil based on the three-dimensional position coordinates of the compressor rotor. The power amplifier is used to adjust the excitation current of the corresponding electromagnetic coil according to the current command value of each axial electromagnetic coil to generate a three-dimensional electromagnetic force field in space. By applying a three-dimensional electromagnetic field to the ferromagnetic components of the compressor rotor, an electromagnetic force is generated that is opposite to gravity and vibration, thus forming a stable, suspended compressor rotor.

3. The cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in claim 2, characterized in that: The compressor rotor, based on stable suspension, collects personnel distribution data and combines it with ambient temperature data monitored by an infrared thermal imager to construct a comprehensive temperature field and obtain heat load distribution data. Specifically, Based on a stable suspended compressor rotor, a millimeter-wave radar array is used to collect real-time personnel distribution data, and an infrared thermal imager is used to capture the temperature distribution of various indoor surfaces to generate an ambient temperature data matrix. The data processing unit is used to align the personnel distribution data with the ambient temperature data matrix in time and space. After filling the monitoring blind spots with the Kriging interpolation algorithm, a comprehensive temperature field of personnel thermal radiation and building structure heat transfer is established. Based on the comprehensive temperature field, the equivalent value of the heat load for each spatial unit is calculated to obtain heat load distribution data.

4. The cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in claim 3, characterized in that: The optimal combination of compressor speed parameters and fan static pressure parameters is obtained by using a chaotic particle swarm optimization algorithm based on heat load distribution data. The heat load distribution data is input into the chaotic particle swarm optimization algorithm, and Y groups of particles including compressor speed parameters and fan static pressure parameters are randomly generated. The particle swarm is initialized with Tent chaos using the chaotic mapping function, and the weighted evaluation value of thermal comfort index and energy consumption coefficient corresponding to each particle in the particle swarm is calculated through the fitness function. Based on the weighted evaluation value, each particle in the particle swarm updates its individual historical best solution and the global historical best solution. After multiple rounds of iteration, the optimal combination of compressor speed parameters and fan static pressure parameters is generated.

5. The cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in claim 4, characterized in that: The adjustment of the compressor speed and fan static pressure parameters of the magnetic levitation air conditioning unit based on the optimal combination of compressor speed and fan static pressure parameters specifically involves... The optimal combination of compressor speed parameters and fan static pressure parameters is transmitted to the magnetic levitation air conditioning unit control unit. The magnetic levitation air conditioning unit control unit analyzes the optimal combination of compressor speed parameters and fan static pressure parameters to generate a three-phase PWM modulation signal and an analog voltage signal; The inverter adjusts the power supply frequency of the permanent magnet synchronous motor according to the three-phase PWM modulation signal, so that the compressor rotor accelerates to the optimal compressor speed parameters under the support of the magnetic levitation bearing; After receiving the analog voltage signal, the fan changes the impeller speed through a stepless speed regulation device to establish a static pressure gradient in the duct that conforms to the optimal static pressure parameters of the fan.

6. The cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in claim 5, characterized in that: Based on the adjusted magnetic levitation air conditioning unit and combined with heat load distribution data, the optimal deflection angle parameters of the deformable guide vanes are calculated, specifically as follows: Based on the adjusted magnetic levitation air conditioning unit, combined with heat load distribution data, computational fluid dynamics is used to solve the three-dimensional airflow organization state, and the optimal deflection angle parameters of the deformable guide vanes are iteratively calculated using chaotic particle swarm optimization algorithm.

7. The cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in claim 6, characterized in that: The process involves converting the optimal deflection angle parameters of the deformable guide vanes into pulse width modulation signals and driving the miniature servo motors of the deformable guide vanes to complete the airflow distribution. Specifically, The optimal deflection angle parameters of the deformable guide vane are converted into three pulse width modulation signals with phase difference by a digital signal processor; A pulse width modulation signal drives a miniature servo motor to deflect the deformable guide vanes, which then distribute the airflow according to the heat load distribution data.

8. A cooling and heating air supply control system based on a magnetic levitation air conditioning unit, based on the cooling and heating air supply control method based on a magnetic levitation air conditioning unit as described in any one of claims 1 to 7, characterized in that: include, The adjustment module activates the magnetic levitation bearing, monitors the compressor rotor position in real time through a displacement sensor, and adjusts the electromagnetic force to form a stable suspended compressor rotor. The data acquisition module, based on a stable suspended compressor rotor, collects personnel distribution data and combines it with ambient temperature data monitored by an infrared thermal imager to construct a comprehensive temperature field and obtain heat load distribution data. The optimization module uses a chaotic particle swarm optimization algorithm to calculate the optimal combination of compressor speed parameters and fan static pressure parameters based on heat load distribution data. The adjustment module adjusts the compressor speed and fan static pressure parameters of the magnetic levitation air conditioning unit based on the optimal combination of compressor speed parameters and fan static pressure parameters. The calculation module, based on the adjusted magnetic levitation air conditioning unit and combined with heat load distribution data, calculates the optimal deflection angle parameters of the deformable guide vanes; The airflow distribution module converts the optimal deflection angle parameters of the deformable guide vanes into pulse width modulation signals, which drive the miniature servo motors of the deformable guide vanes to complete the airflow distribution.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the cooling and heating air supply control method based on any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the cooling and heating air supply control method based on any one of claims 1 to 7.

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