A STS High-Temperature Environment Adaptive Temperature Control Method

Abstract

This invention relates to the field of adaptive temperature control technology, specifically to an STS (Self-Temperature Transmission System) high-temperature environment adaptive temperature control method to solve the technical problems of low accuracy, slow response, high energy consumption, poor high-temperature adaptability, and long equipment lifespan loss in existing temperature control methods under high-temperature environments. It includes the following steps: S100: System power-on initialization, completion of self-tests of sensors, air conditioners, and controllers, and entry into normal operation mode after confirming no faults; S200: A fixed 2-second control cycle.

Description

Technical Field

[0001] This invention relates to the field of adaptive temperature control technology, specifically to an STS high-temperature environment adaptive temperature control method. Background Technology

[0002] Static Switching Systems (STS), as critical power quality assurance devices, are widely used in applications with extremely high requirements for power continuity, such as data centers, industrial automation, and medical systems. They are specifically designed for temperature control solutions operating in harsh conditions such as high-temperature enclosed environments, industrial sites, and outdoor cabinets. In actual operation, the power semiconductor devices integrated within the STS, such as IGBTs and power diodes, generate a significant amount of heat. Since these devices are typically installed in environments with poor heat dissipation, such as enclosed cabinets, outdoor cabinets, or industrial sites, high temperatures become the primary factor affecting the reliability of the STS.

[0003] Traditional STS temperature control solutions mainly employ on / off temperature control or single-stage PID temperature control. On / off temperature control controls the compressor's start and stop by setting a single temperature threshold, which has problems such as large temperature fluctuations, frequent compressor start and stop, high energy consumption, and slow response. Although single-stage PID temperature control can achieve continuous adjustment, it still has drawbacks such as large overshoot, long settling time, and poor high-temperature adaptability under complex operating conditions such as sudden load changes and extreme high temperatures.

[0004] When the ambient temperature reaches above 40℃, traditional solutions often fail to effectively control the temperature inside the cabinet within the optimal operating temperature range of the STS (Standard Temperature Control System), and may even fail to control the temperature, seriously threatening equipment safety. In addition, traditional solutions lack the ability to predict load changes and cannot act in advance before a surge in heat generation, resulting in a sudden temperature exceedance; they also lack coordinated control of cabinet insulation and air conditioning cooling, resulting in low energy efficiency in high-temperature environments. Summary of the Invention

[0005] This invention proposes an STS high-temperature environment adaptive temperature control method to solve the technical problems of existing temperature control methods, such as low accuracy, slow response, high energy consumption, poor high-temperature adaptability, and large equipment life loss in high-temperature environments.

[0006] The technical solution of the present invention is as follows:

[0007] An STS high-temperature environment adaptive temperature control method includes the following steps:

[0008] S100: The system is powered on and initialized. It completes self-tests of the sensors, air conditioner, and controller. After confirming that there are no faults, it enters normal operation mode.

[0009] S200: With a fixed control cycle of 2 seconds, the following sub-steps are executed sequentially in each control cycle:

[0010] S210: Multi-dimensional data acquisition: Simultaneously acquires the overall internal temperature of the cabinet, the real-time load rate of the STS, the external ambient temperature of the cabinet, the working status of each sensor, the operating status of the air conditioning compressor and fan, and the on / off status of the ventilation outlet.

[0011] S220: Data preprocessing and filtering: Perform median filtering and amplitude limiting filtering on the collected raw data;

[0012] S230: Ambient Temperature Level Judgment: Determine whether to enter low temperature, medium temperature or high temperature coordinated control mode based on the ambient temperature value, and determine the basic working strategy of cabinet insulation and air conditioning.

[0013] S240: Temperature Deviation and Rate of Change Calculation: Calculate the current temperature deviation and the rate of change of deviation with 25℃ as the target temperature;

[0014] S250: Fuzzy PID Intelligent Calculation: By combining fuzzy logic with PID control, the basic cooling power adjustment command is output after fuzzification of membership function, fuzzy rule reasoning, and defuzzification.

[0015] S260: Load trend prediction correction: Based on the thermodynamic model, the base power is predicted and corrected according to the continuous change trend of the load rate.

[0016] The correction method involves algebraically superimposing the power correction amount obtained from the load trend prediction with the basic cooling power adjustment amount output by the fuzzy PID calculation to obtain the final cooling power adjustment amount.

[0017] S270: Temperature dead zone logic judgment: Determines whether the temperature deviation exceeds the allowable range;

[0018] S280: Actuator drive: Smoothly adjusts the air conditioning compressor frequency and fan speed and controls the opening and closing degree of the vents according to the final control command;

[0019] S290: Parallel monitoring of faults and protection: Independently and in parallel monitors all faults and over-temperature conditions outside of the normal temperature control process, and immediately triggers the corresponding protection action once the protection conditions are met.

[0020] Furthermore, step S250 includes:

[0021] S251: Based on temperature deviation and rate of change of deviation As the input variable, the cooling power adjustment amount For output variables;

[0022] Temperature deviation The physical range is [-5,5]℃, and the fuzzy subset is {NB,NM,ZO,PM,PB};

[0023] Deviation change rate The physical range is [-2,2]℃ / s, and the fuzzy subset is {NB,NM,ZO,PM,PB};

[0024] Cooling power adjustment The physical range is [0,100]%, and the fuzzy subset is {LD,SD,ZO,SU,LU};

[0025] S252: All variables use triangular membership functions;

[0026] S253: Fuzzy reasoning based on a 5×5 fuzzy rule table.

[0027] Furthermore, the specific parameters of the triangle membership function in step S252 are as follows:

[0028] The domain of NB is [-5,-3], and the coordinates of the triangle vertices are (-5,1), (-3,0), and (-4,0).

[0029] The domain of NM is [-4,-1], and the coordinates of the triangle vertices are (-4,0), (-1,0), and (-2.5,1).

[0030] The domain of ZO is [-2,2], and the coordinates of the triangle vertices are (-2,0), (2,0), and (0,1).

[0031] The domain of PM is [1,4], and the coordinates of the triangle vertices are (1,0), (4,0), and (2.5,1).

[0032] PB has a domain of [3,5] and the coordinates of the triangle vertices are (3,0), (5,1), and (4,0).

[0033] Deviation change rate Membership function:

[0034] The domain of NB is [-2, -1.2], and the coordinates of the triangle vertices are (-2, 1), (-1.2, 0), and (-1.6, 0).

[0035] The domain of NM is [-1.6, -0.4], and the coordinates of the triangle vertices are (-1.6, 0), (-0.4, 0), and (-1, 1).

[0036] The domain of ZO is [-0.8, 0.8], and the coordinates of the triangle vertices are (-0.8, 0), (0.8, 0), and (0, 1).

[0037] The domain of PM is [0.4, 1.6], and the coordinates of the triangle vertices are (0.4, 0), (1.6, 0), and (1, 1).

[0038] The domain of PB is [1.2,2], and the coordinates of the triangle vertices are (1.2,0), (2,1), and (1.6,0).

[0039] Cooling power adjustment Membership function:

[0040] The domain of LD is [0,20], and the coordinates of the triangle vertices are (0,1), (20,0), and (10,0).

[0041] The domain of SD is [10,30], and the coordinates of the triangle vertices are (10,0), (30,0), and (20,1).

[0042] The domain of ZO is [40,60], and the coordinates of the triangle vertices are (40,0), (60,0), and (50,1).

[0043] The domain of SU is [70,90], and the coordinates of the triangle vertices are (70,0), (90,0), and (80,1).

[0044] The domain of LU is [80,100], and the coordinates of the triangle vertices are (80,0), (100,1), and (90,0).

[0045] Furthermore, the 5×5 fuzzy rule table in step S253 is as follows:

[0046] Temperature deviation The fuzzy subset is the row and the rate of change of deviation. The fuzzy subset is defined by columns, with row order NB, NM, ZO, PM, PB and column order NB, NM, ZO, PM, PB, corresponding to the output cooling power adjustment amount. The fuzzy subsets are as follows:

[0047] First line ( =NB): LD, LD, SD, SD, ZO;

[0048] Second line ( =NM): LD, SD, SD, ZO, SU;

[0049] Third line ( =ZO): SD, SD, ZO, SU, SU;

[0050] Fourth line ( =PM): SD, ZO, SU, SU, LU;

[0051] Fifth line ( =PB): ZO, SU, LU, LU, LU.

[0052] Furthermore, step S250 also includes defuzzification and PID parameter self-tuning, as detailed below:

[0053] S254: The centroid method is used for defuzzification, converting the fuzzy set obtained from fuzzy inference into a precise value for cooling power adjustment. The calculation formula is as follows: ,in For the first The membership degree of a fuzzy subset. This represents the x-coordinate value of the corresponding domain;

[0054] S255: Output the precise cooling power adjustment amount ΔP obtained by defuzzification as the basic cooling power adjustment command.

[0055] Furthermore, step S260 includes:

[0056] S261: A quantitative mapping between load rate and calorific value is established based on the STS thermodynamic heating model. The formula for calculating calorific value is:

[0057] ;

[0058] Among them, among them, The heat generated per unit time by the STS equipment;

[0059] Real-time load rate of STS;

[0060] This represents the equivalent internal resistance of the power module.

[0061] The ambient temperature;

[0062] The load heat generation coefficient;

[0063] The environmental heat exchange coefficient;

[0064] For the heat generation of the STS unloaded foundation;

[0065] S262: If the load rate increases by more than 10% within three consecutive cycles, adjust the power according to the increase rate.

[0066] Up 10%~20%, correction +15%;

[0067] Up 20%~30%, correction +20%;

[0068] A rise of 30% or more will be corrected by +25%~30%;

[0069] S263: When the load rate suddenly jumps by more than 50%, the strong cooling mode is immediately triggered within 0.5 seconds, and the cooling power is directly increased to 100%.

[0070] S264: If the load rate decreases by more than 10% for three consecutive cycles, reduce the power accordingly based on the magnitude of the decrease.

[0071] Decrease of 10%~20%, revised down to -15%;

[0072] A decline of more than 20% will be corrected to -20% to 25%;

[0073] S265: When the load rate is below 20% for an extended period of more than 10 minutes, the system enters deep energy-saving mode, and the air conditioner operates at a minimum maintenance power of 20%~30%.

[0074] Furthermore, step S230 includes:

[0075] S231: When the ambient temperature When the temperature is ≤30℃, the system enters a low ambient temperature mode, with the cabinet ventilation openings fully open, and the air conditioner operates at low power adaptively and allows for intermittent shutdowns.

[0076] S232: When 30℃ < When the temperature is ≤45℃, the system enters the medium ambient temperature mode, the vents are adjusted to a half-open state, and the air conditioner enters continuous frequency conversion regulation mode to stabilize the temperature at 25℃±0.5℃.

[0077] S233: When When the temperature reaches ≥45℃, the system enters extreme high temperature mode, all vents are closed, the cabinet forms a completely enclosed heat-insulating space, the air conditioner switches to full cooling mode and is prohibited from stopping, and the fan speed automatically increases by 30% when the ambient temperature exceeds 50℃.

[0078] Step S234: When switching between different modes, the cooling power transitions linearly and smoothly within 5 seconds.

[0079] Furthermore, the multi-dimensional data acquisition in step S210 adopts a distributed multi-point temperature measurement scheme, and the sensor selected is a PT1000 high-precision temperature sensor, specifically arranged as follows:

[0080] S211: Three core heat source area sensors are evenly arranged along the length direction on the surface of the heat dissipation substrate of IGBT or power semiconductor module.

[0081] S212: Install an air conditioner return air vent sensor 5cm inside the air conditioner return air vent;

[0082] S213: Place one gradient sensor inside the cabinet at the bottom of the left rear side, 10cm from the ground, at the middle half of the cabinet height, and at the top, 10cm from the top.

[0083] S214: Install an ambient temperature sensor on the right side wall outside the cabinet, 1.5m above the ground, in a location protected from direct sunlight;

[0084] And the temperature measurement reliability logic: The system performs real-time validity judgment on all temperature measurement points. When the value of a certain sensor deviates from the overall average value by more than 3°C and continues for 3 cycles, the sensor is judged to be abnormal and the data of that point is automatically blocked. The system then switches to the weighted calculation of the remaining normal measurement points. Among them, the maximum value is taken in the core heat source area, and the weighted average value is taken for the gradient sensor with a weight of 0.2 at the bottom, 0.5 at the middle, and 0.3 at the top.

[0085] Integrated temperature gradient inside the cabinet: ;

[0086] System temperature data is divided into three priority levels. High-priority sensors determine protection actions, while low-priority sensors only participate in auxiliary calculations.

[0087] Among them, the sensor value in the primary core heat source area is taken and is not included in the weighted average; it is used for over-temperature protection, load reduction, and shutdown judgment. The air conditioning return air vent sensor (… The measured values ​​are used directly without weighting and are used for the main feedback temperature of fuzzy PID closed-loop control; the three-level bottom, middle and top gradient sensors are weighted and averaged to assist in correcting the overall temperature, judging the temperature uniformity inside the cabinet, and detecting air duct abnormalities.

[0088] The final integrated temperature of the system used for PID control It is obtained by combining the return air inlet temperature and the gradient-weighted temperature in a fixed ratio: .

[0089] Furthermore, step S290 further includes:

[0090] Cabinet over-temperature graded protection:

[0091] The system is equipped with two independent protection mechanisms: over-temperature protection for core components and over-temperature protection for the cabinet environment. The protection of core components has a higher priority than the protection of the cabinet environment.

[0092] Core component (IGBT) protection: Based on the device case temperature, an early warning is triggered and the air conditioner starts to cool at full capacity when the temperature exceeds 70°C; when the temperature exceeds 85°C, an emergency shutdown is immediately performed to ensure that the power device is not damaged.

[0093] Cabinet interior temperature protection: Based on the overall temperature inside the cabinet, an alarm is issued and the cooling power is increased when the temperature exceeds 28°C; when the temperature exceeds 30°C, the STS is controlled to operate at reduced load; when the temperature exceeds 35°C, the system is shut down for safety.

[0094] Special protection for air conditioner and compressor: There should be an interval of more than 3 minutes between two compressor starts;

[0095] The compressor will be forced to stop for 30 seconds after running continuously for 60 minutes.

[0096] During shutdown, the indoor fan runs at a low speed continuously to maintain air circulation inside the cabinet, avoid the accumulation of local hot spots, and ensure the continuity of temperature sampling;

[0097] Before the brief shutdown, the system had stabilized the temperature inside the cabinet within the range of 25℃±0.5℃ using a fuzzy PID algorithm;

[0098] The 30-second shutdown is solely for compressor cooling and will not cause a significant rise in the cabinet temperature. If the temperature rise rate exceeds 0.2℃ / s during the shutdown period, the system will terminate the shutdown early and immediately restart the compressor to ensure uninterrupted temperature control and prevent overheating.

[0099] If the compressor current is detected to exceed 1.2 times the rated current, the machine will immediately stop and lock for 5 minutes.

[0100] When the air conditioner loses communication with the controller, it automatically enters a fixed safe power mode to maintain 70% basic cooling.

[0101] Ventilation vent jamming protection:

[0102] Once the high-temperature mode is activated, if the vents are not properly closed, the system will prevent the air conditioner from reducing its power and will continuously issue an alarm.

[0103] Cabinet internal temperature difference protection:

[0104] When the temperature difference between the top and bottom of the cabinet exceeds 8°C, it is determined that the air duct is uneven and the fan speed is automatically increased to force temperature uniformity.

[0105] Fault handling mechanism:

[0106] When a single temperature sensor fails, the faulty point is automatically blocked and data from the remaining normal measuring points is used. When half of the sensors fail, the system automatically switches to single-point temperature control at the return air vent. When all sensors fail, the system enters a safety emergency mode, causing the air conditioner to output a fixed 70% cooling power and forcing the STS to reduce its load to 60%.

[0107] When the load current data is abnormal or lost, the load prediction function is automatically turned off and switched to pure temperature closed-loop PID control; when the air conditioner fails to execute, the controller sends three consecutive commands without response, determines that the air conditioner is out of control and reports the fault. If there is a backup air conditioner, the backup unit is started immediately. If there is no backup, the STS load is forced to be limited to within 50%.

[0108] When the ambient temperature exceeds 55°C and the internal temperature of the cabinet exceeds 30°C for 5 minutes, the fully enclosed heat insulation, full-power cooling and STS deep load reduction will be activated.

[0109] When communication with the host computer is interrupted, the system will operate independently locally.

[0110] When the controller's main chip fails, the system switches to a preset safe fixed power temperature control mode.

[0111] Furthermore, step S240 includes:

[0112] S241: When the absolute value of the difference between the cabinet temperature and 25℃ is less than or equal to 1℃, the system determines that the temperature is in the ideal stable range and does not change the current cooling power.

[0113] S242: When the temperature is above 26°C and is still rising rapidly, immediately increase the cooling power to 100%;

[0114] S243: When the temperature is above 26℃ but the rate of temperature rise is very slow or basically stable, the power is increased in a small stepwise manner.

[0115] S244: When the temperature is below 24°C and is still dropping rapidly, reduce the compressor to the lowest operating frequency and simultaneously reduce the fan speed;

[0116] S245: When the temperature is close to 25℃ but shows a clear upward trend, slightly increase the cooling power in advance.

[0117] The beneficial effects of this invention are as follows:

[0118] This invention highly integrates key technologies such as multi-source distributed temperature measurement, fuzzy PID precise cooling regulation, load-linked predictive control, and coordinated control of cabinet insulation and air conditioning systems. It establishes a full-process logical judgment, multi-level safety protection, and multi-scenario automatic fault handling mechanism. Even under extreme ambient temperatures of 35℃~55℃, it can stably control the operating temperature inside the STS cabinet at 25℃±0.5℃. This fundamentally solves a series of technical defects of traditional temperature control methods, such as low accuracy, slow response, high energy consumption, poor high-temperature adaptability, and long equipment lifespan loss. It comprehensively improves the stability, safety, and energy efficiency of STS equipment operating in high-temperature environments, as detailed below:

[0119] 1. Excellent high-temperature adaptability: Meets the extreme high-temperature test requirements of GB / T34940.3-2017 and has undergone enhanced verification. Under extreme high temperature of 55℃ and full load of STS, it runs continuously for 4 hours, with the cabinet temperature stabilizing at 25.2℃~26.3℃ and the IGBT case temperature maintained at 62℃~68℃, without any faults or shutdowns, and with normal performance, solving the pain points of traditional temperature control failure and device overheating under extreme high temperatures.

[0120] 2. Industry-leading temperature control accuracy: Based on precise adjustment of fuzzy PID, temperature fluctuations are controlled within ±0.5℃, providing the optimal operating temperature environment for STS and improving the stability of equipment operation.

[0121] 3. Predictive regulation without lag: Based on load linkage prediction using thermodynamic models and experimental data, cooling is initiated before heat generation, thus preventing instantaneous temperature exceedances from the source.

[0122] 4. Significant Energy Saving Effect: Based on the relevant test specifications of GB / T34940.3-2017 and GB / T2423.2-2008, under three operating conditions—normal temperature 25℃ / 50% load, medium-high temperature 40℃ / 70% load, and extreme high temperature 55℃ / 80% load—after 2 hours of continuous comparative testing, the energy consumption of this solution is 1.18kWh, 1.65kWh, and 2.05kWh, respectively. This corresponds to the energy consumption of traditional on / off temperature control (1.85kWh, 2.68kWh, and 3.25kWh) and traditional single-stage PID temperature control (1.52kWh, 2.25kWh, and 2.86kWh). Calculations show that this solution saves 33.2%~38.4% energy compared to traditional on / off temperature control and 22.4%~28.3% energy compared to traditional single-stage PID temperature control, effectively reducing long-term energy consumption and operating costs.

[0123] 5. Comprehensive and reliable protection mechanism: multi-level over-temperature protection, equipment-specific protection, and all-scenario fault self-healing significantly extend the service life of STS and air conditioning systems, reduce compressor start-up and shutdown impact, and extend equipment life.

[0124] 6. Stable operation in unattended environments: It is resistant to electromagnetic interference, sensor failure, and extreme working conditions. Distributed temperature measurement and redundant control ensure long-term stable operation of the system in unattended environments.

[0125] 7. Strong parameter calibrability: The fuzzy PID membership function, load prediction correction parameters, and cooperative control threshold can all be experimentally calibrated according to different STS equipment models and application scenarios, with strong adaptability. Detailed Implementation

[0126] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0127] This embodiment uses a certain model of STS-100KVA static conversion system as the application object, and is equipped with a 3-horsepower variable frequency industrial air conditioner to implement the high-temperature environment adaptive temperature control method of the present invention in a high-temperature sealed cabinet with an ambient temperature of 35℃~55℃.

[0128] First, after the system is powered on, step S100 is executed: the system is powered on and initialized, and the self-test of the sensors, air conditioner and controller is completed. After confirming that there are no faults, it enters the normal operation mode.

[0129] Subsequently, the system executes each sub-step in step S200 continuously with a fixed control cycle of 2 seconds. In this embodiment, the control cycle is strictly set to 2 seconds to ensure rapid and lag-free temperature control response.

[0130] At the beginning of each control cycle, step S210 is executed: synchronously collect the overall temperature inside the cabinet, the real-time load rate of the STS, the ambient temperature outside the cabinet, the working status of each sensor, the operating status of the air conditioning compressor and fan, and the opening and closing status of the ventilation outlet.

[0131] This embodiment employs a distributed multi-point temperature measurement scheme, with the specific arrangement described in steps S211 to S214. All sensors are PT1000 high-precision temperature sensors, with a temperature measurement accuracy of ±0.1℃ and a high temperature resistance of ≤200℃. Specific arrangement parameters are shown in the table below:

[0132] The sensor layout diagram is as follows: the sensors in the core heat source area are arranged close to the IGBT module, the return air vent sensors are located in the return air duct, the gradient sensors are distributed at different heights of the cabinet, and the environmental sensors are located on the outer wall of the cabinet.

[0133] System temperature data is divided into three priority levels. High-priority sensors determine protection actions, while low-priority sensors only participate in auxiliary calculations.

[0134] Among them, the sensor in the first-level core heat source area takes the maximum value and does not participate in the weighted average. It is used for over-temperature protection, load reduction, and shutdown judgment. The air conditioner return air vent sensor directly uses the measured value and does not participate in the weighting. It is used for the main feedback temperature of fuzzy PID closed-loop control. The third-level bottom, middle, and top gradient sensors are weighted and averaged according to their weights. They are used to assist in correcting the overall temperature, judging the temperature uniformity inside the cabinet, and identifying air duct abnormalities.

[0135] The final integrated temperature of the system used for PID control It is obtained by combining the return air inlet temperature and the gradient-weighted temperature in a fixed ratio:

[0136] When the sensor in the core heat source area fails, the system automatically blocks the temperature acquisition signal of that path and no longer executes the device-level over-temperature protection logic. It only relies on the comprehensive temperature inside the cabinet to complete the graded early warning, load reduction and shutdown control, and at the same time outputs sensor fault alarm to remind maintenance personnel to repair in time.

[0137] Step S220: Perform median filtering and amplitude limiting filtering on the collected raw data to remove invalid data such as electromagnetic interference and transient spikes, ensuring that the input parameters are true and reliable.

[0138] Step S230 includes S231 to S234, which automatically switches between three operating modes based on the Tenv value collected by the ambient temperature sensor:

[0139] S231: Low ambient temperature mode ( ≤30℃

[0140] With the external ambient temperature low, the cabinet vents remain fully open, utilizing natural convection for auxiliary heat dissipation. The air conditioner operates at low power adaptively, allowing for intermittent shutdowns, with energy conservation as the primary goal.

[0141] S232: Medium ambient temperature mode (30℃ < ≤45℃

[0142] As external heat begins to intrude, the vents are adjusted to a semi-open state, and the insulation layer blocks the entry of external heat. The air conditioner enters continuous variable frequency control mode, prioritizing temperature control accuracy, and stabilizes the temperature at 25℃±0.5℃.

[0143] S233: Extreme High Temperature Mode ( ≥45℃

[0144] With the external environment extremely hot, all ventilation openings are closed, and the cabinet forms a completely enclosed, insulated space to prevent external heat from entering to the greatest extent possible. The air conditioner is switched to full cooling mode and is prohibited from shutting down, with enhanced temperature control parameters. When the ambient temperature exceeds 50°C, the fan speed automatically increases by 30% to further enhance heat exchange capacity, prioritizing equipment safety.

[0145] S234: Mode Smooth Switching Logic

[0146] When switching between different modes, the cooling power should transition linearly and smoothly within 5 seconds. Sudden and large increases or decreases are prohibited to avoid drastic temperature fluctuations, compressor shocks, and the risk of condensation in the air duct.

[0147] With 25℃ as the target temperature, step S240 calculates the current temperature deviation e= - ( =25℃), and the deviation change rate de / dt (the difference between the deviation of the current cycle and the previous cycle divided by the cycle time).

[0148] Meanwhile, step S240 also includes predictive adjustment logic, specifically S241 to S245:

[0149] S241: When the absolute value of the difference between the internal temperature and 25℃ is less than or equal to 1℃, the system determines that the temperature is in the ideal stable range, does not change the current cooling power, and avoids energy waste and mechanical wear caused by frequent adjustments.

[0150] S242: When the temperature is above 26℃ and is still rising rapidly, the system determines that heat is accumulating rapidly inside the cabinet and immediately increases the cooling power to 100% to suppress the temperature from rising further as quickly as possible.

[0151] S243: When the temperature is above 26℃, but the rate of temperature rise is very slow or basically stable, the system determines it as a mild over-temperature and increases the power in a small stepwise manner to achieve stable temperature control without oscillation.

[0152] S244: When the temperature is below 24℃ and is still dropping rapidly, the system determines that the cooling is excessive, reduces the compressor to the lowest operating frequency, and the fan speed is reduced simultaneously to enter the energy-saving state.

[0153] S245: When the temperature approaches 25℃ but shows a clear upward trend, the system will slightly increase the cooling power in advance to suppress the temperature before it exceeds the limit, thus avoiding temperature overshoot at the source.

[0154] Step S250 employs a fuzzy PID algorithm to dynamically adjust the cooling power. Specifically, it includes:

[0155] S251: Define input and output variables

[0156] Temperature deviation Physical range [-5,5]℃, fuzzy subset is {NB,NM,ZO,PM,PB} (negative large, negative medium, zero, positive medium, positive large).

[0157] Deviation change rate Physical range [-2,2]℃ / s, fuzzy subset is {NB,NM,ZO,PM,PB}.

[0158] Cooling power adjustment Physical range [0,100]%, fuzzy subset is {LD,SD,ZO,SU,LU} (large decrease, small decrease, hold, small increase, large increase).

[0159] S252: Membership function of a triangle

[0160] The membership function parameters for each variable are as follows:

[0161] 1. Temperature deviation Membership function table

[0162]

[0163] 2. Rate of change of deviation Membership function

[0164]

[0165] 3. Cooling power adjustment Membership function

[0166]

[0167] S253: Fuzzy Inference Based on 5×5 Fuzzy Rule Table

[0168] After experimental calibration, the following 5×5 fuzzy rule table (25 rules in total) is used to output a fuzzy subset of the cooling power adjustment amount. The core logic is: if the temperature is too high, increase the power; if it is too low, decrease the power; if the temperature changes rapidly, adjust significantly; if the temperature changes slowly, adjust slightly.

[0169]

[0170] S254: Defuzzification: The centroid method (area center method) is used to convert the fuzzy set obtained from fuzzy inference into a precise value for cooling power adjustment. The calculation formula is as follows: in For the first The membership of a fuzzy subset The membership degree is the x-coordinate value of the corresponding domain.

[0171] S255: Precise cooling power adjustment amount obtained from defuzzification As a basic cooling power adjustment command output.

[0172] Step S260 is the load trend prediction correction, which is based on the STS thermodynamic heating model and a large amount of experimental data to realize load prediction adjustment, as follows:

[0173] S261: Thermodynamic Heating Model

[0174] Through experimental calibration, the formula for calculating the heat generation under steady-state operation of the STS was obtained:

[0175] ;

[0176] in, The heat output per unit time of the STS equipment (W);

[0177] This represents the real-time load rate of STS, with a value ranging from 0 to 1.

[0178] The equivalent internal resistance of the power module is calibrated to 0.08Ω;

[0179] Ambient temperature (°C);

[0180] The load heating coefficient, experimentally calibrated to be 1.2;

[0181] The environmental heat exchange coefficient, experimentally calibrated to be 5.8;

[0182] The unloaded basic heat generation of STS (W) is experimentally calibrated to be 150W.

[0183] According to the model, for every 10% increase in load rate, the heat generated by the equipment increases by approximately 22% to 25%.

[0184] S262: Load Increase Forecast

[0185] If the load rate increases by more than 10% within three consecutive cycles (6s), the system determines that the heat generation of the equipment will increase significantly, and the power is corrected according to the increase: 10%~20% increase, +15% correction; 20%~30% increase, +20% correction; more than 30% increase, +25%~30% correction.

[0186] S263: Sudden load fluctuation

[0187] When the load rate suddenly jumps by more than 50%, the system determines that it is a sudden high-power operation and immediately triggers the strong cooling mode within 0.5 seconds, directly increasing the cooling power to 100%.

[0188] S264: Load Drop Prediction

[0189] If the load rate decreases by more than 10% for three consecutive cycles (6s), the heat generation will be reduced by ≥20%. The power will be reduced accordingly based on the decrease: -15% for a decrease of 10%~20%, and -20%~25% for a decrease of more than 20%, to avoid overcooling.

[0190] S265: Low-load deep energy saving

[0191] When the load rate is below 20% for an extended period of more than 10 minutes, and the heat output of the equipment is ≤200W, the system enters a deep energy-saving mode. The air conditioning compressor operates at 20%~30% of its rated input power, minimizing energy consumption while ensuring that the temperature does not exceed the standard.

[0192] In this embodiment, multiple load rate step experiments were conducted under standard high-temperature conditions of 40°C ambient temperature and 25°C target temperature to obtain the quantitative relationship between load rate change and temperature rise, as shown in the table below, providing experimental support for predicting the power correction range of regulation.

[0193] This system will use the basic cooling power adjustment output by fuzzy PID calculation. The power correction amount obtained from load trend prediction is algebraically superimposed to obtain the final cooling power adjustment amount, which adjusts the air conditioner cooling power in advance to achieve adaptive temperature control based on load prediction.

[0194] All control parameters in this method are based on the STS-100KVA static conversion system and were calibrated through multiple load rate step experiments and long-term operating condition adaptation experiments under normal temperature (25℃), medium-high temperature (40℃), and extreme high temperature (55℃) conditions. The fuzzy PID membership function and fuzzy rule table are adapted to the STS temperature control nonlinearity characteristics. Thermodynamic formula parameters, load prediction correction amplitude, cooperative control and protection thresholds have all been experimentally verified, meeting the design goals of temperature fluctuation ≤ ±0.5℃, energy saving rate ≥ 36%, and no frequent compressor start-stop.

[0195] The following table shows the experimental data (40℃ environment) of load rate step change and temperature change:

[0196] Step S270 determines whether the temperature deviation exceeds the allowable range: When the absolute value of the difference between the cabinet temperature and 25℃ is less than or equal to 1℃, the system determines that the temperature is within the dead zone, locks the fuzzy PID control process, does not change the current cooling power, and avoids frequent system actions caused by small fluctuations. Only when the deviation exceeds the dead zone will the fuzzy PID algorithm be activated and subsequent adjustment commands be executed.

[0197] Step S280 smoothly adjusts the air conditioner compressor frequency and fan speed according to the final control command, and controls the opening and closing degree of the vents. In this embodiment, the air conditioner compressor frequency and fan speed are smoothly adjusted according to the final control command, and the opening and closing degree of the vents is controlled.

[0198] Step S290 independently monitors all faults and over-temperature conditions in parallel outside of the normal temperature control process. The priority order is: device emergency over-temperature shutdown > system / environment over-temperature shutdown > device / environment over-temperature warning > sensor failure > general sensor failure. High-priority states can directly disable low-priority commands and regular temperature control outputs. The monitoring unit continuously collects signals such as temperature and sensor status. Once a fault or over-temperature condition is detected, it immediately interrupts regular temperature control adjustment, prioritizes the execution of corresponding protection actions, and outputs a fault alarm locally. After the fault / over-temperature condition is cleared, the system automatically switches back to the normal fuzzy PID temperature control process.

[0199] This embodiment includes the following protection mechanisms:

[0200] 1. Cabinet over-temperature graded protection:

[0201] When the overall temperature inside the cabinet exceeds 28°C, the system immediately issues local and remote alarms and simultaneously controls the air conditioner to run at full power to quickly suppress the temperature rise.

[0202] When the temperature inside the cabinet exceeds 30℃, the STS equipment will automatically reduce its load to 70% while maintaining full-power cooling, thereby reducing the heat generated by the equipment itself.

[0203] When the temperature inside the cabinet exceeds 35°C, the system is deemed to have failed cooling and is at risk of burning out. The system immediately performs an emergency shutdown to protect itself and cuts off critical circuits.

[0204] An early warning is triggered when the temperature of core power devices such as IGBTs exceeds 70°C; if the temperature exceeds 80°C, the system is forced to shut down to ensure the safety of the core devices.

[0205] 2. Special protection for air conditioner and compressor:

[0206] Start-stop interval protection: There must be an interval of more than 3 minutes between two starts of the compressor. Frequent start-stop is prohibited to avoid mechanical shock and coil aging.

[0207] 3. Continuous operation heat dissipation protection:

[0208] The compressor runs continuously for 60 minutes, then is forced to stop for 30 seconds to relieve internal heat buildup and extend its lifespan.

[0209] 4. Overcurrent protection:

[0210] If the compressor current is detected to exceed 1.2 times the rated current, immediately stop the machine and lock it for 5 minutes to prevent burnout.

[0211] 5. Communication interruption protection:

[0212] When the air conditioner loses communication with the controller, it automatically enters a fixed safe power mode to maintain 70% basic cooling.

[0213] 6. Ventilation vent jamming protection:

[0214] Once the system enters high-temperature mode (extreme high-temperature mode), if the vents are not properly closed, the system will prevent the air conditioner from reducing its power and will continuously issue an alarm.

[0215] 7. Cabinet internal temperature difference protection:

[0216] When the temperature difference between the top and bottom of the cabinet exceeds 8°C, it is determined that the air duct is uneven, and the fan speed is automatically increased to force uniform temperature and eliminate local hot spots.

[0217] The following is the fault handling mechanism:

[0218] 1. Temperature sensor failure: When a single sensor fails, the system automatically masks the faulty point and uses data from the remaining normal measuring points; when half of the sensors fail, it automatically switches to single-point temperature control at the return air vent; when all sensors fail, it immediately enters the safety emergency mode, the air conditioner outputs a fixed 70% cooling power, and the STS is forced to reduce its load to 60%. For short circuit / open circuit faults, the system accurately locates the fault point and reports it simultaneously locally and remotely.

[0219] 2. Load sensor failure: When the load current data is abnormal or lost, the system automatically shuts down the load prediction function and switches to pure temperature closed-loop PID control to maintain stable temperature control. The prediction function will be automatically reactivated after the sensor recovers.

[0220] 3. Air conditioning system failure: If the controller sends three consecutive commands without response, it is determined that the air conditioning is out of control and the fault is reported immediately; if the cooling capacity is insufficient, the system will automatically increase the fan speed and trigger the STS to reduce the load; if the air conditioning is completely faulty and there is a backup air conditioning, the backup unit will be started immediately, and if there is no backup, the STS load will be forced to be limited to within 50%.

[0221] 4. Extreme high temperature environment failure: When the ambient temperature exceeds 55℃ and the internal temperature of the cabinet exceeds 30℃ for 5 minutes, the system will activate the highest level of protection: full-enclosed heat insulation, full-power cooling, STS deep load reduction to 20% of the rated load, and then recheck the temperature every 3 minutes; if the temperature still cannot be controlled, the load will be continuously reduced in increments of 10% of the rated load until the graded strategy shutdown protection is implemented.

[0222] 5. Communication and controller failure: When communication with the host computer is interrupted, the system operates independently locally without relying on remote commands; when the main controller chip fails, the system switches to the preset safe fixed power temperature control mode.

[0223] Furthermore, to verify the superiority of this invention, three operating conditions—normal temperature (25℃), medium-high temperature (40℃), and extreme high temperature (55℃)—were set up on a standard STS experimental platform to test the performance of traditional on / off temperature control, traditional single-stage PID temperature control, and the method of this invention (i.e., the above-described embodiments). The test platform was an STS-100KVA static conversion system, equipped with a 3HP inverter industrial air conditioner, a PT1000 high-precision temperature sensor, and a data acquisition instrument with a sampling frequency of 1Hz. Each operating condition was tested for 2 hours, and all data were the average of three repeated experiments. The starting point for temperature stabilization time was the moment the temperature control scheme was officially put into operation, and the ending point was the temperature inside the cabinet.

[0224] The point at which the temperature enters the steady-state range and both fluctuations and overshoot tend to stabilize. The comparative test data are shown in the table below:

[0225] Test results show that the temperature fluctuation of the method of the present invention is ≤±0.6℃ under all operating conditions, the maximum overshoot is only 0.6~1.0℃, the temperature stabilization time is only 8~15 seconds, the energy saving rate is 33.2%~38.4%, and the compressor start-stop number is 0, which is far superior to the traditional solution.

[0226] In summary, this embodiment has the following advantages:

[0227] It has extremely strong high-temperature adaptability: it can operate stably for a long time in extreme high-temperature environments of 55℃.

[0228] High temperature control accuracy: temperature fluctuations are controlled within ±0.5℃.

[0229] Predictive regulation without lag: Based on load linkage prediction using thermodynamic models and experimental data, cooling is initiated before heat generation.

[0230] Significant energy saving effect: more than 30% energy saving compared to traditional on / off temperature control, and more than 20% energy saving compared to traditional single-stage PID temperature control.

[0231] The protection mechanism is comprehensive and reliable: multi-level over-temperature protection, equipment-specific protection, and all-scenario fault self-healing significantly extend equipment life.

[0232] It can operate stably in unattended environments: it is resistant to electromagnetic interference, sensor failure, and extreme working conditions, and distributed temperature measurement and redundant control ensure long-term stable operation.

[0233] The parameters are highly calibrable: the fuzzy PID membership function, load prediction correction parameters, and collaborative control threshold can all be experimentally calibrated according to different models of STS equipment and application scenarios, making them highly adaptable.

[0234] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A STS high-temperature environment adaptive temperature control method, characterized in that, Includes the following steps: S100: The system is powered on and initialized. It completes self-tests of the sensors, air conditioner, and controller. After confirming that there are no faults, it enters normal operation mode. S200: With a fixed control cycle of 2 seconds, the following sub-steps are executed sequentially in each control cycle: S210: Multi-dimensional data acquisition: Simultaneously acquires the overall internal temperature of the cabinet, the real-time load rate of the STS, the external ambient temperature of the cabinet, the working status of each sensor, the operating status of the air conditioning compressor and fan, and the on / off status of the ventilation outlet. S220: Data preprocessing and filtering: Perform median filtering and amplitude limiting filtering on the collected raw data; S230: Ambient Temperature Level Judgment: Determine whether to enter low temperature, medium temperature or high temperature coordinated control mode based on the ambient temperature value, and determine the basic working strategy of cabinet insulation and air conditioning. S240: Temperature Deviation and Rate of Change Calculation: Calculate the current temperature deviation and the rate of change of deviation with 25℃ as the target temperature; S250: Fuzzy PID Intelligent Calculation: By combining fuzzy logic with PID control, the basic cooling power adjustment command is output after fuzzification of membership function, fuzzy rule reasoning, and defuzzification. S260: Load trend prediction correction: Based on the thermodynamic model, the base power is predicted and corrected according to the continuous change trend of the load rate. S270: Temperature dead zone logic judgment: Determines whether the temperature deviation exceeds the allowable range; S280: Actuator drive: Smoothly adjusts the air conditioning compressor frequency and fan speed and controls the opening and closing degree of the vents according to the final control command; S290: Parallel monitoring of faults and protection: Independently and in parallel monitors all faults and over-temperature conditions outside of the normal temperature control process, and immediately triggers the corresponding protection action once the protection conditions are met.

2. The STS high-temperature environment adaptive temperature control method according to claim 1, characterized in that, Step S250 includes: S251: Based on temperature deviation and rate of change of deviation As the input variable, the cooling power adjustment amount For output variables; Temperature deviation The physical range is [-5,5]℃, and the fuzzy subset is {NB,NM,ZO,PM,PB}; Deviation change rate The physical range is [-2,2]℃ / s, and the fuzzy subset is {NB,NM,ZO,PM,PB}; Cooling power adjustment The physical range is [0,100]%, and the fuzzy subset is {LD,SD,ZO,SU,LU}; S252: All variables use triangular membership functions; S253: Fuzzy reasoning based on a 5×5 fuzzy rule table.

3. The STS high-temperature environment adaptive temperature control method according to claim 2, characterized in that, The specific parameters of the triangle membership function in step S252 are as follows: The domain of NB is [-5,-3], and the coordinates of the triangle vertices are (-5,1), (-3,0), and (-4,0). The domain of NM is [-4,-1], and the coordinates of the triangle vertices are (-4,0), (-1,0), and (-2.5,1). The domain of ZO is [-2,2], and the coordinates of the triangle vertices are (-2,0), (2,0), and (0,1). The domain of PM is [1,4], and the coordinates of the triangle vertices are (1,0), (4,0), and (2.5,1). PB has a domain of [3,5] and the coordinates of the triangle vertices are (3,0), (5,1), and (4,0). Deviation change rate Membership function: The domain of NB is [-2, -1.2], and the coordinates of the triangle vertices are (-2, 1), (-1.2, 0), and (-1.6, 0). The domain of NM is [-1.6, -0.4], and the coordinates of the triangle vertices are (-1.6, 0), (-0.4, 0), and (-1, 1). The domain of ZO is [-0.8, 0.8], and the coordinates of the triangle vertices are (-0.8, 0), (0.8, 0), and (0, 1). The domain of PM is [0.4, 1.6], and the coordinates of the triangle vertices are (0.4, 0), (1.6, 0), and (1, 1). The domain of PB is [1.2,2], and the coordinates of the triangle vertices are (1.2,0), (2,1), and (1.6,0). Cooling power adjustment Membership function: The domain of LD is [0,20], and the coordinates of the triangle vertices are (0,1), (20,0), and (10,0). The domain of SD is [10,30], and the coordinates of the triangle vertices are (10,0), (30,0), and (20,1). The domain of ZO is [40,60], and the coordinates of the triangle vertices are (40,0), (60,0), and (50,1). The domain of SU is [70,90], and the coordinates of the triangle vertices are (70,0), (90,0), and (80,1). The domain of LU is [80,100], and the coordinates of the triangle vertices are (80,0), (100,1), and (90,0).

4. The STS high-temperature environment adaptive temperature control method according to claim 3, characterized in that, The 5×5 fuzzy rule table in step S253 is as follows: Temperature deviation The fuzzy subset is the row and the rate of change of deviation. The fuzzy subset of the output cooling power adjustment ΔP is as follows: The columns are ordered as NB, NM, ZO, PM, PB, and the column order is NB, NM, ZO, PM, PB. First row: LD, LD, SD, SD, ZO; Second row: LD, SD, SD, ZO, SU; The third row: SD, SD, ZO, SU, SU; The fourth row: SD, ZO, SU, SU, LU; Fifth row: ZO, SU, LU, LU, LU.

5. The STS high-temperature environment adaptive temperature control method according to claim 4, characterized in that, Step S250 also includes defuzzification and PID parameter self-tuning, as detailed below: S254: The centroid method is used for defuzzification, converting the fuzzy set obtained from fuzzy inference into a precise value for cooling power adjustment. The calculation formula is as follows: ,in For the first The membership degree of a fuzzy subset. This represents the x-coordinate value of the corresponding domain; S255: Output the precise cooling power adjustment amount ΔP obtained by defuzzification as the basic cooling power adjustment command.

6. The STS high-temperature environment adaptive temperature control method according to claim 5, characterized in that, Step S260 includes: S261: A quantitative mapping between load rate and calorific value is established based on the STS thermodynamic heating model. The formula for calculating calorific value is: ； in, The heat generated per unit time by the STS equipment; Real-time load rate of STS; This represents the equivalent internal resistance of the power module. The ambient temperature; The load heat generation coefficient; The environmental heat exchange coefficient; For the heat generation of the STS unloaded foundation; S262: If the load rate increases by more than 10% within three consecutive cycles, adjust the power according to the increase rate. Up 10%~20%, correction +15%; Up 20%~30%, correction +20%; A rise of 30% or more will be corrected by +25%~30%; S263: When the load rate suddenly jumps by more than 50%, the strong cooling mode is immediately triggered within 0.5 seconds, and the cooling power is directly increased to 100%. S264: If the load rate decreases by more than 10% for three consecutive cycles, reduce the power accordingly based on the magnitude of the decrease. Decrease of 10%~20%, revised down to -15%; A decline of more than 20% will be corrected to -20% to 25%; S265: When the load rate is below 20% for an extended period of more than 10 minutes, the system enters deep energy-saving mode, and the air conditioner operates at a minimum maintenance power of 20%~30%.

7. The STS high-temperature environment adaptive temperature control method according to claim 1, characterized in that, Step S230 includes: S231: When the ambient temperature When the temperature is ≤30℃, the system enters a low ambient temperature mode, with the cabinet ventilation openings fully open, and the air conditioner operates at low power adaptively and allows for intermittent shutdowns. S232: When 30℃ < When the temperature is ≤45℃, the system enters the medium ambient temperature mode, the vents are adjusted to a half-open state, and the air conditioner enters continuous frequency conversion regulation mode to stabilize the temperature at 25℃±0.5℃. S233: When When the temperature reaches ≥45℃, the system enters extreme high temperature mode, all vents are closed, the cabinet forms a completely enclosed heat-insulating space, the air conditioner switches to full cooling mode and is prohibited from stopping, and the fan speed automatically increases by 30% when the ambient temperature exceeds 50℃. Step S234: When switching between different modes, the cooling power transitions linearly and smoothly within 5 seconds.

8. The STS high-temperature environment adaptive temperature control method according to claim 1, characterized in that, The multi-dimensional data acquisition in step S210 adopts a distributed multi-point temperature measurement scheme, and the sensor selected is the PT1000 high-precision temperature sensor, which is specifically arranged as follows: S211: Three core heat source area sensors are evenly arranged along the length direction on the surface of the heat dissipation substrate of IGBT or power semiconductor module. S212: Install an air conditioner return air vent sensor 5cm inside the air conditioner return air vent; S213: Place one gradient sensor inside the cabinet at the bottom of the left rear side, 10cm from the ground, at the middle half of the cabinet height, and at the top, 10cm from the top. S214: Install an ambient temperature sensor on the right side wall outside the cabinet, 1.5m above the ground, in a location protected from direct sunlight; And the temperature measurement reliability logic: The system performs real-time validity judgment on all temperature measurement points. When the value of a certain sensor deviates from the overall average value by more than 3°C and continues for 3 cycles, the sensor is judged to be abnormal and the data of that point is automatically blocked. The system then switches to the weighted calculation of the remaining normal measurement points. Among them, the maximum value is taken in the core heat source area, and the weighted average value is taken for the gradient sensor with a weight of 0.2 at the bottom, 0.5 at the middle, and 0.3 at the top. Integrated temperature gradient inside the cabinet ; System temperature data is divided into three priority levels. High-priority sensors determine protection actions, while low-priority sensors only participate in auxiliary calculations. Among them, the sensor in the first-level core heat source area takes the maximum value and does not participate in the weighted average. It is used for over-temperature protection, load reduction, and shutdown judgment. The air conditioner return air vent sensor directly uses the measured value and does not participate in the weighting. It is used for the main feedback temperature of fuzzy PID closed-loop control. The third-level bottom, middle, and top gradient sensors are weighted and averaged according to their weights. They are used to assist in correcting the overall temperature, judging the temperature uniformity inside the cabinet, and identifying air duct abnormalities. The final integrated temperature of the system used for PID control It is obtained by combining the return air inlet temperature and the gradient-weighted temperature in a fixed ratio: .

9. The STS high-temperature environment adaptive temperature control method according to claim 1, characterized in that, Step S290 further includes: Cabinet over-temperature graded protection: The system is equipped with two independent protection mechanisms: over-temperature protection for core components and over-temperature protection for the cabinet environment. The protection of core components has a higher priority than the protection of the cabinet environment. Core component protection: Based on the component case temperature, an early warning is triggered and the air conditioner starts to cool at full capacity when the temperature exceeds 70°C; when the temperature exceeds 85°C, an emergency shutdown is immediately performed to ensure that the power components are not damaged. Cabinet interior temperature protection: Based on the overall temperature inside the cabinet, an alarm is issued and the cooling power is increased when the temperature exceeds 28°C; when the temperature exceeds 30°C, the STS is controlled to operate at reduced load; when the temperature exceeds 35°C, the system is shut down for safety. Special protection for air conditioner and compressor: There should be an interval of more than 3 minutes between two compressor starts; The compressor is forced to stop for 30 seconds after running continuously for 60 minutes. During the stop, the indoor fan continues to run at low speed to maintain air circulation inside the cabinet, avoid the accumulation of local hot spots, and ensure the continuity of temperature sampling. Before the short-term stop, the system has stabilized the temperature inside the cabinet in the range of 25℃±0.5℃ using a fuzzy PID algorithm. The 30-second shutdown is solely for compressor cooling and will not cause a significant rise in the cabinet temperature. If the temperature rise rate exceeds 0.2℃ / s during the shutdown period, the system will terminate the shutdown early and immediately restart the compressor to ensure uninterrupted temperature control and prevent overheating. If the compressor current is detected to exceed 1.2 times the rated current, the machine will immediately stop and lock for 5 minutes. When the air conditioner loses communication with the controller, it automatically enters a fixed safe power mode to maintain 70% basic cooling. Ventilation vent jamming protection: Once the high-temperature mode is activated, if the vents are not properly closed, the system will prevent the air conditioner from reducing its power and will continuously issue an alarm. Cabinet internal temperature difference protection: When the temperature difference between the top and bottom of the cabinet exceeds 8°C, it is determined that the air duct is uneven and the fan speed is automatically increased to force temperature uniformity. Fault handling mechanism: When a single temperature sensor fails, the faulty point is automatically blocked and data from the remaining normal measuring points is used. When half of the sensors fail, the system automatically switches to single-point temperature control at the return air vent. When all sensors fail, the system enters a safety emergency mode, causing the air conditioner to output a fixed 70% cooling power and forcing the STS to reduce its load to 60%. When the load current data is abnormal or lost, the load prediction function is automatically turned off and switched to pure temperature closed-loop PID control; when the air conditioner fails to execute, the controller sends three consecutive commands without response, determines that the air conditioner is out of control and reports the fault. If there is a backup air conditioner, the backup unit is started immediately. If there is no backup, the STS load is forced to be limited to within 50%. When the ambient temperature exceeds 55°C and the internal temperature of the cabinet exceeds 30°C for 5 minutes, the fully enclosed heat insulation, full-power cooling and STS deep load reduction will be activated. When communication with the host computer is interrupted, the system will operate independently locally. When the controller's main chip fails, the system switches to a preset safe fixed power temperature control mode.

10. The STS high-temperature environment adaptive temperature control method according to claim 1, characterized in that, Step S240 includes: S241: When the absolute value of the difference between the cabinet temperature and 25℃ is less than or equal to 1℃, the system determines that the temperature is in the ideal stable range and does not change the current cooling power. S242: When the temperature is above 26°C and is still rising rapidly, immediately increase the cooling power to 100%; S243: When the temperature is above 26℃ but the rate of temperature rise is very slow or basically stable, the power is increased in a small stepwise manner. S244: When the temperature is below 24°C and is still dropping rapidly, reduce the compressor to the lowest operating frequency and simultaneously reduce the fan speed; S245: When the temperature is close to 25℃ but shows a clear upward trend, slightly increase the cooling power in advance.

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