A heat dissipation control method, system and electronic device

Abstract

The application discloses a heat dissipation control method, system and electronic device, relates to the technical field of device heat dissipation, and comprises the following steps: detecting actual temperature values of multiple heat generation areas, quantitatively processing heat distribution to obtain temperature state parameters, matching the temperature state parameters between areas with preset conditions of working conditions, and constructing multiple levels of working conditions containing entering and exiting double condition constraints, so as to guarantee the quick response of the system to the gradual deterioration of the heat state, effectively avoid the frequent oscillation of the working condition caused by the slight temperature fluctuation, and balance the heat dissipation performance, energy consumption and noise of the system. Further decoupling and fine control of the wind speed and the wind direction are performed, so that the technical problem that the fan control is extensive and it is difficult to balance the heat dissipation performance, energy consumption and noise can be solved, and the technical effect that a balance is achieved among the heat dissipation performance, energy consumption and noise is achieved.

Description

Technical Field

[0001] This application relates to the field of equipment heat dissipation technology, and in particular to a heat dissipation control method, system and electronic device. Background Technology

[0002] In the cooling of electronic devices such as servers and personal computers, the temperature of a single hotspot area is typically compared with a fixed threshold to determine the operating condition, and then the fan speed is adjusted accordingly. However, considering the uneven distribution of heat load across different heat-generating areas, resulting in significant temperature differences, the ability to sense and quantify this unevenness is poor. This leads to a large amount of cool air being blown indiscriminately towards areas with lower temperatures or no heat generation, resulting in a serious waste of airflow resources and increased overall power consumption and noise. Furthermore, when the temperature of a hotspot exceeds the threshold, it often approaches or exceeds the device's frequency reduction or protection threshold. The lag and coarseness of the overall fan speed control result in poor timeliness of hotspot cooling, easily inducing the processor to be forced to reduce its frequency due to overheating, leading to performance degradation. Therefore, how to achieve precise fan control to balance cooling performance, power consumption, and noise has become a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0003] This application provides a heat dissipation control method, system, and electronic device to at least solve the problems of crude fan control and difficulty in achieving a balance between heat dissipation performance, energy consumption, and noise in related technologies.

[0004] This application provides a heat dissipation control method, including: Obtain the actual temperature values ​​of multiple heating areas within the target device during the actual cycle, and determine the temperature state parameters between the areas based on the actual temperature values. The corresponding target heat dissipation condition is determined based on the relationship between the temperature state parameters and the preset operating conditions; wherein, the preset operating conditions include the operating condition entry conditions and the exit conditions corresponding to the actual operating conditions; the heat dissipation conditions include at least the over-temperature condition, the guided heat dissipation condition, the balanced condition, and the silent condition. Based on the deviation between the target temperature value and the actual temperature value of the area under the target heat dissipation condition, fuzzy control processing is performed to obtain the wind speed control quantity and / or the wind direction control quantity corresponding to multiple heat-generating areas, so as to control the fan to dissipate heat from the heat-generating areas.

[0005] This application also provides a heat dissipation control system, including multiple temperature sensors, a fan module, and a controller; the multiple temperature sensors are located in the heat-generating area corresponding to the fan module and are connected to the controller; the fan module is connected to the controller; The controller is used to execute the steps of the heat dissipation control method described above, so as to control the fan module to dissipate heat from the heat-generating area.

[0006] This application also provides an electronic device, including: A memory is used to store computer programs; a processor is used to implement the steps of any of the above-mentioned heat dissipation control methods when executing computer programs.

[0007] This application achieves several key improvements. First, by determining the temperature state parameters between multiple heat-generating areas based on their actual temperature values, the system can quantify the unevenness of heat distribution between these areas, distinguishing between true hot spots and low-temperature zones. This provides a precise basis for accurate heat distribution identification and on-demand air supply. Second, by matching the temperature state parameters between areas with preset operating conditions, a multi-level operating condition system is constructed, incorporating both entry and exit constraints. This includes an over-temperature condition for heat dissipation, ensuring the system's heat dissipation safety. A guided heat dissipation condition addresses the issue of uneven heat distribution. A balanced condition ensures even airflow distribution. A quiet condition optimizes energy consumption and noise. This system ensures a rapid response to gradually deteriorating thermal conditions while effectively avoiding frequent oscillations caused by minor temperature fluctuations, achieving a balance between heat dissipation performance, energy consumption, and noise. Finally, by decoupling wind speed and direction settings, fine-grained adjustments to the spatial allocation of wind speed and direction control values ​​are achieved. The fan speed control dynamically adjusts the overall cooling capacity based on the overall heat load, while multiple airflow direction control variables independently adjust the airflow distribution ratio according to the actual heat dissipation needs of each heat-generating area. This ensures that cool air is precisely delivered to the most needed hot spots, effectively avoiding energy waste caused by ineffective airflow. Furthermore, because the total airflow is supplied on demand rather than continuously operating at full speed, overall energy consumption and operating noise are reduced. In addition, by acquiring actual temperature values ​​over a specific period to form a closed-loop feedback system, the effectiveness of each control measure can be verified by temperature data collected in the next period. This avoids the lag and frequency reduction issues caused by open-loop control in conventional solutions, improving the timeliness of heat dissipation control.

[0008] Because this application detects the actual temperature values ​​of multiple heat-generating areas, and then quantifies the heat distribution to obtain temperature state parameters, and performs graded processing of operating conditions based on the temperature state parameters, it can then perform decoupled and refined control of wind speed and wind direction. Therefore, it can solve the technical problem of coarse fan control and difficulty in achieving a balance between heat dissipation performance, energy consumption and noise, and achieve a coordinated balance among heat dissipation performance, energy consumption and noise. Attached Figure Description

[0009] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A schematic flowchart illustrating a heat dissipation control method provided in an embodiment of this application; Figure 2 A schematic diagram illustrating the process of determining a target heat dissipation condition as provided in an embodiment of this application; Figure 3 A schematic diagram of the architecture of a heat dissipation control system provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a fan module provided in an embodiment of this application; Figure 5 This is a schematic diagram of a heat dissipation control device provided in an embodiment of this application. Detailed Implementation

[0011] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0012] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0013] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0014] Conventional electronic device cooling solutions distribute airflow evenly throughout the entire internal space, regardless of which area is experiencing severe heat generation. However, the heat load varies significantly across different areas. For instance, a central processing unit (CPU) operating at full load can reach temperatures exceeding 85°C, while memory might only reach 50°C. This uniform airflow wastes a large amount of cool air in lower-temperature areas, while the hottest areas don't receive sufficient airflow. To address these hot spots, engineers often increase the speed of all fans, leading to increased noise and energy consumption. Further improvements include adding fixed air ducts to the fan outlets to direct airflow to specific areas. However, these mechanically fixed ducts cannot dynamically adjust to changes in load. Other solutions use individual temperature sensors to detect temperatures and increase fan speed when a threshold is exceeded, but this method is slow and only adjusts the overall airflow, not the direction. The cooling control method provided in this application solves these technical problems.

[0015] The specific application environment architecture or specific hardware architecture on which the execution of the heat dissipation control method depends is described here.

[0016] For large data centers housing electronic equipment, multiple servers are deployed within a single rack, each with significantly different loads and heat outputs. By installing multi-zone fan modules at the rear of the rack, with each zone corresponding to a server slot, and dynamically adjusting fan speeds and deflector openings based on the temperature difference between the inlet and outlet airflow of each server, cool air is prioritized for high-load servers. This reduces ineffective airflow in the cold aisle, lowering the data center's Power Usage Effectiveness (PUE) by 0.1 to 0.2. The fan modules employ a multi-outlet distribution structure, with each outlet equipped with an independently adjustable deflector, and the overall fan speed is controllable.

[0017] The embodiments of this application provide a heat dissipation control method, and the method is described in detail below in conjunction with the execution flow of the heat dissipation control method.

[0018] Figure 1 This is a flowchart illustrating a heat dissipation control method provided in an embodiment of this application, as shown below. Figure 1 As shown, the method includes: S11: Obtain the actual temperature values ​​of multiple heating areas within the target equipment during the actual cycle, and determine the temperature status parameters between areas based on the actual temperature values; S12: Determine the corresponding target heat dissipation condition based on the relationship between temperature state parameters and preset operating conditions; Among them, the preset operating conditions include the conditions for entering the operating condition and the conditions for exiting the actual operating condition; the heat dissipation conditions include at least the over-temperature condition, the guided heat dissipation condition, the balanced condition, and the silent condition; S13: Based on the deviation between the target temperature value and the actual temperature value of the target heat dissipation condition, fuzzy control processing is performed to obtain the wind speed control quantity and / or the wind direction control quantity corresponding to multiple heat-generating areas, so as to control the fan to dissipate heat from the heat-generating areas.

[0019] Specifically, the target device can be an electronic device such as a server, personal computer, or network device. The target device contains multiple heat-generating areas, such as the CPU area, memory area, and motherboard area. Each heat-generating area is equipped with at least one temperature sensor to collect the real-time temperature of that area. A heat-generating area refers to the physical area or component area inside an electronic device that generates heat during operation. For example, the CPU area is the location of the central processing unit and its surrounding area; the memory area is the location of the memory modules and its surrounding area; and the motherboard area is the location of the motherboard and its surrounding area.

[0020] Temperature state parameters between regions are comprehensive indicators used to characterize the temperature distribution among various heat-generating areas within the entire target device. Temperature state parameters can include one or more of the following: the maximum temperature value in each heat-generating area, the average temperature value across all heat-generating areas, the maximum temperature difference between regions, and the rate of temperature change of the maximum temperature value. These parameters reflect the overall thermal state of the system from different dimensions. For example, the maximum temperature value reflects the urgency of heat dissipation in the hottest area, the average temperature value reflects the overall heat load level of the system, and the maximum temperature difference between regions reflects the degree of uneven heat distribution.

[0021] By acquiring the actual temperature values ​​of multiple heating zones and calculating the temperature state parameters between zones, the system can comprehensively perceive the thermal state of each zone, effectively avoiding the reduced accuracy caused by relying on a single temperature sensor and resulting in limited data. Simultaneously, by abstracting multiple discrete temperature values ​​into comprehensive state parameters reflecting the degree of uneven heat distribution, the system possesses the ability to proactively identify whether heat distribution is balanced, providing a data foundation for subsequent refined control.

[0022] The heat dissipation condition in step S12 refers to a heat dissipation operation mode selected by the system based on the current thermal state. Different heat dissipation conditions correspond to different control strategies and target parameters.

[0023] This application includes at least the following four heat dissipation conditions: Over-temperature condition: This condition is used to perform full-speed heat dissipation when the hot spot temperature exceeds the safety threshold or the heating rate is too fast. It is the highest priority condition and mainly ensures the heat dissipation safety of the system.

[0024] Directional heat dissipation mode: Used when there is a large temperature difference between areas and the temperature of hot spots is high, the airflow is concentrated and directed to the hot spot area, mainly to solve the problem of uneven heat distribution.

[0025] Balanced operating mode: Used when the overall heat load of the system is high but the heat distribution is relatively uniform, to evenly distribute the airflow and appropriately increase the total air volume.

[0026] Silent mode: Used to reduce fan speed and reduce the opening of various adjustment plates in other states, mainly to optimize energy consumption and noise performance.

[0027] Preset operating conditions refer to the pre-defined rules used to determine which cooling mode the system should enter or exit from the current operating mode. There are two types of preset operating conditions: Entry conditions are the conditions required to switch from the current operating mode to a target operating mode. For example, entering a guided cooling mode requires a critical temperature difference greater than the third temperature threshold and a first critical temperature greater than the fourth temperature threshold. Exit conditions corresponding to the actual operating mode are the conditions under which the system exits a particular operating mode if certain conditions are met during continuous operation. Setting exit conditions prevents the system from remaining in that operating mode even when its requirements are not met, thus avoiding energy waste or control malfunctions. There are non-overlapping differences between the thresholds corresponding to the entry and exit conditions for each operating mode, giving the operating mode switching a hysteresis characteristic and avoiding frequent oscillations in operating mode caused by small temperature fluctuations.

[0028] The preset operating conditions are set according to the principle of prioritizing heat dissipation safety, heat dissipation performance, energy consumption, and noise from high to low. Specifically, the over-temperature condition is the highest priority to ensure heat dissipation safety, followed by the guided heat dissipation condition to eliminate hot spots, then the balanced condition to take into account overall heat dissipation, and the silent condition is the default condition to optimize energy consumption and noise.

[0029] Regarding the settings for entering and exiting operating conditions, the temperature parameters involved in the preset conditions are the same for each heat dissipation operating condition, but the temperature parameters involved in the preset conditions between each heat dissipation operating condition may be inconsistent.

[0030] Based on the relationship between temperature status parameters and operating condition entry conditions, the actual target heat dissipation operating conditions that can be divided are determined, and the temperature status parameters are continuously monitored. If the temperature status parameters after entering the actual target heat dissipation operating condition meet the corresponding exit conditions, the actual target heat dissipation operating condition is exited.

[0031] The fuzzy control processing in step 13 refers to the process of obtaining wind speed control and / or wind direction control quantities by taking the precise temperature deviation and its rate of change as input, based on fuzzy mathematics theory, through membership function fuzzification, fuzzy inference, and defuzzification. This embodiment employs a fuzzy proportional-integral-derivative (PID) algorithm. The input parameters are mapped to a preset fuzzy universe of discourse (e.g., [-6, +6]), defining five fuzzy subsets: negative big (NB), negative small (NS), near-zero (Zero, ZO), positive small (PS), and positive big (PB) (all triangular membership functions). Fuzzy output quantities are obtained through inference using a preset fuzzy rule base, and the actual control quantity is obtained by defuzzification using the centroid method. Fuzzy control processing can handle the nonlinear mapping relationship between temperature deviation and control quantity, exhibiting better robustness and adaptability compared to traditional PID, and maintaining stable control performance under various operating conditions.

[0032] The basic process of fuzzy control processing includes: first, calculating the input variables, such as temperature deviation and its rate of change; then, mapping these precise values ​​to the fuzzy universe of discourse through a membership function, transforming them into fuzzy subsets to achieve fuzzification; next, inference is performed based on a preset fuzzy rule base to obtain the fuzzy output; finally, the fuzzy output is defuzzified, for example, using the centroid method, to obtain the precise control quantity.

[0033] The target temperature value for a region refers to the desired temperature value set for each heat-generating region under different heat dissipation conditions. The target temperature value is a crucial input parameter for fuzzy control processing, used to calculate the deviation between the actual temperature and the target temperature. Under different heat dissipation conditions, the target temperature value can be set differently or uniformly.

[0034] In the guided heat dissipation mode, the target temperature of the hot spot area, i.e., the heat-generating area where the first critical temperature value T_max is located, is set lower than the target temperature of the non-hot spot area. For example, the target temperature of the hot spot area is set to 65℃, and the target temperature of the non-hot spot area is set to 75℃. In this way, the deviation between the actual temperature and the target temperature of the hot spot area (e=T_current-T_set) is much larger than that of the non-hot spot area, resulting in a greater wind direction control value for the hot spot area than for the non-hot spot area, thereby achieving concentrated airflow guidance towards the hot spot area.

[0035] The fan speed control signal is used to adjust the total fan speed. Based on the overall system heat load, the fan speed control dynamically adjusts the total cooling capacity, determined by the deviation between the system's overall target temperature and its maximum temperature. The fan speed control signal is typically output in the form of a pulse width modulation (PWM) duty cycle, continuously adjustable from 0% to 100%. The fan motor is driven by a metal-oxide-semiconductor field-effect transistor (MOSFET) H-bridge or a dedicated drive circuit, thereby adjusting the total fan airflow. By dynamically adjusting the overall cooling capacity based on the overall heat load, the fan speed control achieves on-demand airflow supply rather than continuous full-speed operation, effectively reducing overall energy consumption and operating noise.

[0036] The airflow control signal is used to adjust the opening of the regulating plates at each air outlet. Each heat-generating area corresponds to one airflow control signal, and each airflow control signal independently adjusts the airflow distribution ratio of the corresponding heat-generating area. The airflow control signal is usually output in the form of an angle value, corresponding to the opening angle of the regulating plate. In this embodiment, each heat-generating area corresponds to one airflow control signal u_n∈[0,1]. After linear mapping, the opening angle of the regulating plate is obtained as u_n×90°. The first and second guide vanes are driven to rotate by a micro servo motor, thereby adjusting the airflow direction and airflow distribution ratio of the corresponding air duct. Multiple airflow control signals independently adjust the airflow distribution ratio according to the actual heat dissipation needs of each heat-generating area, so that the cool air is accurately delivered to the hottest areas that need it most, effectively avoiding energy waste caused by ineffective air supply.

[0037] Through the embodiments of this application, firstly, the temperature state parameters between multiple heat-generating areas are determined by their actual temperature values. This allows the system to quantify the unevenness of heat distribution between areas, distinguishing between true hot spots and low-temperature zones, achieving accurate heat distribution identification, and providing a quantitative basis for on-demand air supply. Secondly, the temperature state parameters between areas are matched with preset operating conditions to construct multi-level operating conditions including entry and exit constraints, over-temperature conditions for heat dissipation, ensuring the system's heat dissipation safety. Guided heat dissipation conditions address the problem of uneven heat distribution. Balanced operating conditions evenly distribute airflow. Quiet operating conditions optimize energy consumption and noise. This ensures the system's rapid response to gradually deteriorating thermal conditions while effectively avoiding frequent oscillations in operating conditions caused by small temperature fluctuations, achieving a balance between heat dissipation performance, energy consumption, and noise. Finally, through decoupling settings for wind speed and direction, fine-grained adjustment of the spatial allocation of wind speed and direction control values ​​is achieved. The fan speed control dynamically adjusts the overall cooling capacity based on the overall heat load, while multiple airflow direction control variables independently adjust the airflow distribution ratio according to the actual heat dissipation needs of each heat-generating area. This ensures that cool air is precisely delivered to the most needed hot spots, effectively avoiding energy waste caused by ineffective airflow. Furthermore, because the total airflow is supplied on demand rather than continuously operating at full speed, overall energy consumption and operating noise are reduced. In addition, by acquiring actual temperature values ​​over a specific period to form a closed-loop feedback system, the effectiveness of each control measure can be verified by temperature data collected in the next period. This avoids the lag and frequency reduction issues caused by open-loop control in conventional solutions, improving the timeliness of heat dissipation control.

[0038] Because this application detects the actual temperature values ​​of multiple heat-generating areas, and then quantifies the heat distribution to obtain temperature state parameters, and performs graded processing of operating conditions based on the temperature state parameters, it can then perform decoupled and refined control of wind speed and wind direction. Therefore, it can solve the technical problem of coarse fan control and difficulty in achieving a balance between heat dissipation performance, energy consumption and noise, and achieve a coordinated balance among heat dissipation performance, energy consumption and noise.

[0039] In some embodiments, obtaining the actual temperature values ​​of each of the multiple heat-generating areas within the target device during the actual cycle includes: Acquire the first temperature values ​​collected by multiple sensors in each heating area; Each initial temperature value is processed to obtain the actual temperature value of the heating zone.

[0040] Specifically, considering that one or more temperature sensors can be installed in each heating area, installing multiple sensors means collecting multiple temperature values ​​for a single heating area, i.e., multiple first temperature values. These multiple first temperature values ​​are then processed, such as by averaging, variance processing, weighted averaging, median filtering, or outlier removal, with the aim of corresponding to a single actual temperature value within a heating area.

[0041] There are no restrictions on the installation location of multiple temperature sensors in a heat-generating area; they can be set according to the actual situation.

[0042] This embodiment integrates multiple first temperature values ​​to eliminate measurement biases, individual differences, or local hot / cold spot interference that may exist with a single sensor. Through multi-sensor fusion processing, the obtained actual temperature value is closer to the true average temperature or characteristic temperature of the heating area, providing accurate data for subsequent temperature state parameter calculations and modeling.

[0043] In some embodiments, the temperature state parameters include at least a first critical temperature value between regions, an average temperature value, a critical temperature difference between regions, and a temperature change rate over a periodic interval; the process of determining the temperature state parameters includes: The maximum and minimum values ​​are selected from the actual temperature values ​​of each heating zone and used as the first and second critical temperature values, respectively. The average temperature value is obtained by averaging the actual temperature values ​​of each heating zone. The critical temperature difference value is determined based on the first critical temperature value and the second critical temperature value. Obtain the historical first critical temperature value corresponding to the previous actual cycle, the interval between the previous actual cycle and the actual cycle; and determine the temperature change rate based on the historical first critical temperature value, the first critical temperature value and the interval.

[0044] Specifically, the maximum and minimum values ​​are selected from the actual temperature values ​​of each heat-generating region, corresponding to the first critical temperature value (T_max) and the second critical temperature value (T_min). The first critical temperature value represents the temperature of the hottest region in the system and is an important basis for judging the urgency of heat dissipation. The second critical temperature value represents the temperature of the lowest-temperature region in the system. If there are three heat-generating regions, the maximum temperature value T_max = max(T1, T2, T3).

[0045] The actual temperature values ​​of each heat-generating area are averaged to obtain the average temperature value T_avg = (T1 + T2 + ... + Tn) / n, where n represents the n heat-generating areas, and the average temperature value characterizes the overall heat load level of the system.

[0046] The critical temperature difference ΔT = T_max - T_min is determined based on the first and second critical temperature values. The critical temperature difference is the maximum temperature difference between regions and is used to quantify the degree of unevenness in heat distribution.

[0047] Obtain the historical first critical temperature value T_max(k-1) corresponding to the previous actual cycle, the interval time Δt between the previous actual cycle and the actual cycle, and determine the temperature change rate dT_max / dt=(T_max(k)-T_max(k-1)) / Δt based on the historical first critical temperature value, the first critical temperature value and the interval time. The temperature change rate characterizes the rate of temperature change in the hottest region.

[0048] For example, if at a certain sampling moment, T1=85.0℃ (CPU), T2=65.0℃ (memory), and T3=60.0℃ (motherboard assembly) are read, then T_max=85.0℃, T_min=60.0℃, T_avg=70.0℃, and ΔT=25.0℃. If the previous cycle T_max(k-1)=80.0℃ and the interval time Δt=0.1 seconds, then dT_max / dt=(85.0-80.0) / 0.1=50.0℃ / s.

[0049] The temperature status parameters provided in this embodiment comprehensively characterize the current thermal state from multiple dimensions. The maximum temperature value reflects the urgency of heat dissipation in the hottest area, the average temperature value reflects the overall heat load level of the system, the critical temperature difference value reflects the unevenness of heat distribution, and the temperature change rate reflects the temperature change trend. These four parameters complement each other, providing complete and accurate input information for subsequent operating condition judgment, effectively avoiding decision-making biases caused by relying on only a single temperature parameter.

[0050] In some embodiments, determining the corresponding target heat dissipation condition based on the relationship between temperature state parameters and preset operating conditions includes: The actual target heat dissipation condition is determined based on the relationship between temperature state parameters and the conditions for entering each heat dissipation condition. After entering the actual target heat dissipation condition, the temperature status parameters are continuously monitored; If the temperature status parameters after entering the actual target heat dissipation condition are detected to meet the corresponding exit conditions, then exit the actual target heat dissipation condition and return to the step of determining the actual target heat dissipation condition based on the relationship between the temperature status parameters and the entry conditions of each heat dissipation condition. If the temperature status parameters after entering the actual target heat dissipation condition are not met, the actual target heat dissipation condition will be maintained and used as the final target heat dissipation condition.

[0051] Specifically, the controller determines the actual target heat dissipation condition based on the relationship between the temperature status parameters obtained in the current actual cycle, such as T_max, T_avg, ΔT, and dT_max / dt, and the condition entry conditions for each heat dissipation condition. The condition entry conditions for each heat dissipation condition are determined sequentially according to a preset priority order, from highest to lowest priority: over-temperature condition, guided heat dissipation condition, equalization condition, and silent condition. If the temperature status parameters meet the condition entry conditions of a high-priority condition, the actual target heat dissipation condition is directly determined as that high-priority condition, and the determination of low-priority conditions is skipped.

[0052] After entering the actual target heat dissipation condition, the controller continuously monitors the temperature status parameters and compares the monitored temperature status parameters with the exit conditions corresponding to the actual target heat dissipation condition in each actual cycle.

[0053] If the temperature status parameters after entering the actual target heat dissipation condition meet the corresponding exit conditions, the controller exits the actual target heat dissipation condition and returns to the step of determining the actual target heat dissipation condition based on the relationship between the temperature status parameters obtained in the current actual cycle and the entry conditions of each heat dissipation condition. The actual target heat dissipation condition is then determined again based on the relationship between the temperature status parameters and the entry conditions of each heat dissipation condition. In other words, each matching process starts from the entry conditions of the highest priority over-temperature condition and re-determines each level step by step, ensuring that the system can promptly switch back to a lower priority condition after the thermal condition improves, or immediately upgrade to a higher priority condition when the thermal condition deteriorates.

[0054] If the temperature status parameters after entering the actual target heat dissipation condition are not met, the controller maintains the actual target heat dissipation condition and uses it as the final target heat dissipation condition.

[0055] For example, if the current operating condition is guided cooling (T_set_sys=75℃, hot spot area T_set=65℃, non-hot spot area T_set=75℃), the controller continuously monitors temperature status parameters such as T_max and ΔT. When ΔT < the fifth temperature threshold (e.g., 10℃) or T_max < the sixth temperature threshold (e.g., 70℃) is detected, the exit condition for guided cooling is met. The controller exits guided cooling and returns to the step of determining the actual target cooling condition based on the relationship between the temperature status parameters obtained in the current actual cycle and the entry conditions of each cooling condition. If ΔT=8℃ and T_max=68℃ are detected, the exit condition is met. After rematching, the condition T_max>75℃ is not met, but T_avg=68℃ is less than 70℃ and ΔT≤10℃, so it can still enter the balanced operating condition or the silent operating condition. If ΔT=12℃ and T_max=72℃ are detected, the exit condition is not met. The controller will maintain the directional heat dissipation condition and continue to control the wind speed and direction according to the current T_set configuration.

[0056] The system provided in this embodiment first determines which operating condition to enter, and then continuously monitors whether the exit conditions are met. Once the exit conditions are met, the determination process restarts. By using threshold differences between the entry and exit conditions for each operating condition, frequent oscillations in operating conditions caused by minor temperature fluctuations are effectively avoided, ensuring stable system operation.

[0057] In some embodiments, determining the actual target heat dissipation condition based on the relationship between temperature state parameters and the condition entry conditions for each heat dissipation condition includes: Prioritize each heat dissipation condition so that the priority of the conditions for entering the over-temperature condition, the guided heat dissipation condition, the balanced condition, and the silent condition gradually decreases. If the temperature state parameters meet the conditions for entering the first priority over-temperature condition, then the actual target heat dissipation condition is determined to be an over-temperature condition. If the temperature status parameters do not meet the conditions for entering the first priority over-temperature condition, but meet the conditions for entering the second priority guided heat dissipation condition, then the actual target heat dissipation condition is determined to be the guided heat dissipation condition. If the temperature state parameters do not meet the conditions for entering the second priority guided heat dissipation condition, but meet the conditions for entering the third priority balanced condition, then the actual target heat dissipation condition is determined to be the balanced condition. If the temperature status parameters do not meet the conditions for entering the third priority balanced operating condition, then the actual target heat dissipation operating condition is determined to be the silent operating condition.

[0058] Specifically, the controller prioritizes each heat dissipation condition, such that the priority of the entry conditions for the over-temperature condition, guided heat dissipation condition, balanced condition, and silent condition decreases in descending order. That is, the over-temperature condition has the first priority, the guided heat dissipation condition has the second priority, the balanced condition has the third priority, and the silent condition has the fourth priority.

[0059] If the temperature status parameters meet the entry conditions for the first priority over-temperature condition (T_max > 85℃ or dT_max / dt > 30℃ / s), the controller determines the actual target heat dissipation condition as the over-temperature condition and skips the determination of the entry conditions for the guided heat dissipation condition, the balanced condition, and the silent condition. If the temperature status parameters do not meet the entry conditions for the over-temperature condition but meet the entry conditions for the second priority guided heat dissipation condition (ΔT > 15℃ and T_max > 75℃), the controller determines the actual target heat dissipation condition as the guided heat dissipation condition and skips the determination of the entry conditions for the balanced condition and the silent condition. If the temperature status parameters do not meet the entry conditions for the guided heat dissipation mode, but meet the entry conditions for the third priority balanced mode (i.e., T_avg is greater than the sixth temperature threshold, e.g., 70℃, and ΔT is less than or equal to the fifth temperature threshold, e.g., 10℃), the controller determines the actual target heat dissipation mode as the balanced mode. If the temperature status parameters do not meet the entry conditions for the balanced mode, and the entry conditions for the guided heat dissipation mode are also not met, the controller determines the actual target heat dissipation mode as the silent mode, i.e., the default mode.

[0060] Figure 2 This is a schematic diagram illustrating a process for determining a target heat dissipation condition, as provided in an embodiment of this application. Figure 2 As shown, this step includes: S21: Obtain temperature status parameters; S22: Determine whether the temperature status parameters meet the conditions for entering the first priority over-temperature condition. If yes, proceed to step S23; otherwise, proceed to step S24. S23: Determined to be an over-temperature condition; S24: Determine whether the temperature status parameters meet the conditions for entering the second priority guided heat dissipation condition. If yes, proceed to step S25; otherwise, proceed to step S26. S25: Determined to be a guided heat dissipation condition; S26: Determine whether the temperature state parameters meet the conditions for entering the third priority equilibrium working condition. If yes, proceed to step S27; otherwise, proceed to step S28. S27: Determined to be a balanced operating condition; S28: Determined to be in silent operating condition; S29: Output operating mode and target temperature value.

[0061] It should be noted that the judgments in the above four steps are executed sequentially, not in parallel. For example, in a certain actual cycle with T_max=88℃, ΔT=20℃, and T_avg=72℃, although the guided heat dissipation condition (ΔT>15℃ and T_max>75℃) and the equilibrium condition (T_avg>70℃ and the equilibrium condition of ΔT≤10℃ is not met) may be triggered at the same time, the controller directly determines the actual target heat dissipation condition as the over-temperature condition because the condition entry condition of the first priority over-temperature condition (T_max>85℃) is met first, skipping the judgment of other conditions. For example, when T_max=80℃, ΔT=20℃, and T_avg=68℃, the conditions for entering the over-temperature condition are not met (T_max<85℃ and dT_max / dt<30℃ / s), but the conditions for entering the guided heat dissipation condition (ΔT>15℃ and T_max>75℃) are met. The controller directly determines the actual target heat dissipation condition as the guided heat dissipation condition.

[0062] The hierarchical priority matching setting for heat dissipation conditions provided in this embodiment places heat dissipation safety and overheat prevention as the highest priority, followed by heat dissipation performance and hot spot elimination, and energy consumption and noise optimization as the default lowest priority. This ensures that the system can output the control mode that best matches the current thermal state under different load conditions.

[0063] In some embodiments, the condition for entering the over-temperature condition is that the first critical temperature value is greater than the first temperature threshold or the temperature change rate is greater than the first threshold change rate; the condition for exiting the over-temperature condition is that the first critical temperature value is less than the second temperature threshold and the temperature change rate is less than the second threshold change rate; wherein, the first temperature threshold is greater than the second temperature threshold and the first threshold change rate is greater than the second threshold change rate. The condition for entering the guided heat dissipation mode is that the critical temperature difference is greater than the third temperature threshold and the first critical temperature is greater than the fourth temperature threshold; the condition for exiting the guided heat dissipation mode is that the critical temperature difference is less than the fifth temperature threshold, or the first critical temperature is less than the sixth temperature threshold; wherein, the third temperature threshold is greater than the fifth temperature threshold and less than the sixth temperature threshold; the fourth temperature threshold is greater than the sixth temperature threshold and less than the second temperature threshold. The condition for entering the equilibrium operating condition is that the average temperature value is greater than the sixth temperature threshold and the critical temperature difference value is less than or equal to the fifth temperature threshold; the condition for exiting the equilibrium operating condition is that the average temperature value is less than the seventh temperature threshold; wherein, the seventh temperature threshold is less than the sixth temperature threshold. The conditions for entering the silent operating mode are that the average temperature value is less than or equal to the sixth temperature threshold, or the critical temperature difference value is greater than the fifth temperature threshold.

[0064] Specifically, Table 1 shows the preset conditions for each heat dissipation mode. As shown in Table 1, the system maintains the current mode `mode_current` and the counter (initially 0). During each outer loop cycle (500ms), the following logic is executed: calculate the desired mode `mode_desired`; if `mode_desired == mode_current`, clear the counter; if `mode_desired != mode_current`, increment the counter by 1. When the counter reaches the mode entry delay threshold, switch `mode_current`; otherwise, maintain the current mode.

[0065] Table 1. Preset Conditions for Each Heat Dissipation Operation

[0066] The entry condition for over-temperature operation is as follows: the first critical temperature value T_max is greater than the first temperature threshold (e.g., 85℃), or the temperature change rate dT_max / dt is greater than the first threshold change rate (e.g., 30℃ / s). The exit condition for over-temperature operation is as follows: the first critical temperature value T_max is less than the second temperature threshold (e.g., 80℃) and the temperature change rate dT_max / dt is less than the second threshold change rate (e.g., 20℃ / s). Here, the first temperature threshold is greater than the second temperature threshold, and the first threshold change rate is greater than the second threshold change rate. This design, with the entry threshold higher than the exit threshold, gives the over-temperature operation a delayed switching characteristic. The system will not immediately exit the over-temperature operation as soon as T_max drops below 80℃, but will only exit if T_max remains below 80℃ and the temperature change rate remains below 20℃ / s, avoiding frequent switching of operating conditions caused by temperature fluctuations near the threshold.

[0067] The entry condition for guided heat dissipation mode is: the critical temperature difference ΔT is greater than the third temperature threshold (e.g., 15℃) and the first critical temperature value T_max is greater than the fourth temperature threshold (e.g., 75℃). The exit condition for guided heat dissipation mode is: the critical temperature difference ΔT is less than the fifth temperature threshold (e.g., 10℃), or the first critical temperature value T_max is less than the sixth temperature threshold (e.g., 70℃). Specifically, the third temperature threshold is greater than the fifth temperature threshold and less than the sixth temperature threshold; the fourth temperature threshold is greater than the sixth temperature threshold and less than the second temperature threshold. This exit condition is set as an OR relationship; as long as ΔT or T_max drops sufficiently, the guided heat dissipation mode can be exited, ensuring that the system can promptly exit the high-power mode after the hotspot is eliminated.

[0068] The conditions for entering the equilibrium operating condition are: the average temperature value T_avg is greater than the sixth temperature threshold, such as 70℃, and the critical temperature difference value ΔT is less than or equal to the fifth temperature threshold, such as 10℃. The conditions for exiting the equilibrium operating condition are: the average temperature value T_avg is less than the seventh temperature threshold, such as 65℃. The seventh temperature threshold is less than the sixth temperature threshold.

[0069] The conditions for entering silent operation mode are: the average temperature value T_avg is less than or equal to the sixth temperature threshold, such as 70℃, or the critical temperature difference value ΔT is greater than the fifth temperature threshold, such as 10℃. Silent operation mode is the default operation mode and will automatically take effect when the conditions for entering all high-priority operation modes are not met.

[0070] The aforementioned relationship between threshold values ​​ensures a hysteresis difference between the entry and exit thresholds for each operating condition, preventing repeated switching of operating conditions when the temperature fluctuates slightly around the threshold. For example, the entry condition for the guided heat dissipation condition is ΔT > 15℃ and T_max > 75℃, while the exit condition is ΔT < 10℃ or T_max < 70℃. The hysteresis differences are 5℃ in the ΔT direction and 5℃ in the T_max direction, respectively. This ensures that even if ΔT oscillates slightly between 10℃ and 15℃, or T_max oscillates slightly between 70℃ and 75℃, the system will not repeatedly switch between the guided heat dissipation condition and other operating conditions. The defined hysteresis relationship between various temperature thresholds provided in this embodiment ensures that operating condition switching has a defined hysteresis range, effectively avoiding frequent oscillations of operating conditions caused by slight temperature fluctuations. Furthermore, the entry and exit thresholds for each operating condition cover the complete thermal state range from over-temperature protection to energy-saving and silent operation, enabling the system to output differentiated control strategies for different load levels, balancing optimization in terms of heat dissipation performance, energy consumption, and noise.

[0071] In some embodiments, fuzzy control processing is performed based on the deviation between the target temperature value and the actual temperature value of the target heat dissipation condition to obtain wind speed control quantity and / or wind direction control quantity corresponding to multiple heat-generating areas, including: Obtain the deviation between the target temperature value and the actual temperature value in the area, and the rate of change of the deviation over the interval period; The deviation and the rate of change of deviation are used as input parameters for fuzzy control processing, respectively mapped to a preset fuzzy universe, and fuzzy subsets are obtained by fuzzification processing through membership functions. The fuzzy output is obtained by reasoning about the fuzzy subset based on the preset fuzzy rule base; The fuzzy output is defuzzified to obtain the wind speed control quantity and / or wind direction control quantity.

[0072] Specifically, the controller acquires the deviation between the target temperature value and the actual temperature value of the area, as well as the rate of change of the deviation between the current actual cycle and the previous actual cycle. For wind speed control, the first temperature deviation e_speed between T_max and T_set_sys and the difference between the current e_speed and the previous cycle e_speed(k-1) are acquired as the deviation rate of change ec_speed. For wind direction control in each heat-generating area n, the second temperature deviation e_n between T_n and T_set_n and the difference between the current e_n and the previous cycle e_n(k-1) are acquired as the deviation rate of change ec_n.

[0073] The controller uses the deviation and the rate of change of deviation as input parameters for fuzzy control processing, mapping them to a preset fuzzy universe of discourse, such as [-6, +6], and then performs fuzzification processing using a triangular membership function to obtain fuzzy subsets. Five fuzzy subsets are defined on the preset fuzzy universe of discourse: NB (negative large), NS (negative small), ZO (zero), PS (positive small), and PB (positive large).

[0074] NB and PB are right-angled triangles, achieving full membership at their left and right boundaries, respectively. NS, ZO, and PS are symmetrical isosceles triangles, with adjacent subsets having a membership of 0.5 at their intersection points, ensuring smoothness and continuity of control. The actual universe of discourse for each input parameter is mapped to the fuzzy universe of discourse through a quantization factor. For example, the actual universe of discourse for e_speed [-20, +20]℃ corresponds to a quantization factor Ke=0.3, and the actual universe of discourse for ec_speed [-10, +10]℃ / period corresponds to a quantization factor Kec=0.6.

[0075] The controller infers the fuzzy output from the fuzzy subset based on a preset fuzzy rule base. The preset fuzzy rule base contains ΔKp, ΔKi, and ΔKd, which are the adjustment values ​​for the proportional, integral, and derivative actions, respectively. For example, when e is NB and ec is NB, ΔKp is set to NB (strong proportional suppression), ΔKi is set to NB (suppressing integral to prevent saturation when the deviation is large), and ΔKd is set to PB (enhancing derivative to suppress overshoot). When e is ZO and ec is ZO, ΔKp, ΔKi, and ΔKd are all set to ZO (maintaining the original parameters). When e is PB and ec is PB, ΔKp is set to PB for a strong proportional response, ΔKi is set to PB to enhance integral to eliminate steady-state error when approaching the target, and ΔKd is set to NB to weaken derivative to reduce jitter.

[0076] The controller defuzzifies the fuzzy output to obtain the wind speed control quantity and / or wind direction control quantity. This embodiment uses the centroid method for defuzzification: ΔKp = Σ(μ_i·y_i) / Σ(μ_i), where μ_i is the membership degree of the i-th rule, and y_i is the universe of discourse value (vertex coordinates) of the fuzzy set output by that rule; ΔKi and ΔKd are defuzzified similarly. After defuzzification, the actual universe of discourse is mapped back using a scaling factor, and the PID parameters are updated according to Kp_new = Kp0 + ΔKp·Gp, Ki_new = Ki0 + ΔKi·Gi, and Kd_new = Kd0 + ΔKd·Gd, with initial parameters such as Kp0 = 2.0, Ki0 = 0.5, and Kd0 = 0.1. The final control quantity u = Kp_new·e + Ki_new·Σe + Kd_new·ec is limited to [0, 1] and used as the wind speed control quantity u_fan or the wind direction control quantity u_n.

[0077] Table 2 shows the target output values ​​and operating condition descriptions for each heat dissipation condition. As shown in Table 2, Mode_id is the heat dissipation condition identifier, T_set_1, T_set_2, and T_set_3 are the regional target temperature values ​​for each heat dissipation area, and T_set_sys is the total target temperature value. The regional target temperature value is given to the corresponding air direction controller, and the total target temperature value is given to the air speed controller.

[0078] Table 2 Target Output Values ​​and Operating Condition Descriptions for Each Heat Dissipation Condition

[0079] This embodiment provides a method to obtain wind speed control quantities and multiple wind direction control quantities by fuzzifying, inferring, and defuzzifying the precise temperature deviation and its rate of change. This allows the controller to establish a nonlinear mapping relationship between the temperature deviation and the control quantities, resulting in stronger robustness and adaptability compared to traditional linear PID control, and maintaining stable control performance under various operating conditions. A pre-set fuzzy rule base embeds expert experience into the controller in an interpretable form, facilitating rule expansion. By outputting the wind speed control quantities and wind direction control quantities from their respective fuzzy controllers, the two control loops are decoupled, allowing total airflow regulation and airflow direction regulation to be executed independently and in parallel, further improving the system's refined control level.

[0080] In some embodiments, the process of determining the input parameters for fuzzy control processing during the determination of the wind speed control quantity includes: Obtain the total target temperature value; The first temperature deviation is determined based on the first critical temperature value and the total target temperature value; Obtain the historical first temperature deviation of the previous actual cycle and the interval between the previous actual cycle and the actual cycle; The rate of change of deviation is determined based on the historical first temperature deviation, the first temperature deviation, and the interval time. Use the first temperature deviation and the rate of change of deviation as input parameters.

[0081] Specifically, the controller acquires the total target temperature value T_set_sys. The total target temperature value is determined by the central management strategy based on the current target heat dissipation conditions, such as T_set_sys=75℃ under over-temperature conditions, T_set_sys=75℃ under guided heat dissipation conditions, T_set_sys=75℃ under balanced conditions, and T_set_sys=85℃ under silent conditions.

[0082] The controller determines the first temperature deviation e_speed = T_max - T_set_sys based on the first critical temperature value T_max and the total target temperature value T_set_sys. A positive deviation indicates over-temperature, requiring an increase in fan speed. For example, when T_max = 85℃ and T_set_sys = 75℃, e_speed = +10℃.

[0083] The controller obtains the historical first temperature deviation e_speed(k-1) corresponding to the previous actual cycle and determines the interval Δt between the previous actual cycle and the current actual cycle based on the set actual cycle. The controller determines the deviation change rate ec_speed based on the historical first temperature deviation e_speed(k-1), the first temperature deviation e_speed, and the interval Δt. In this embodiment, ec_speed = e_speed(k) - e_speed(k-1). For example, when e_speed(k) = +10℃ and e_speed(k-1) = +5℃, ec_speed = +5℃ / cycle; if normalization to a change rate is required, ec_speed can also be = (e_speed(k) - e_speed(k-1)) / Δt.

[0084] The controller takes the first temperature deviation e_speed and the deviation change rate ec_speed as input parameters of the wind speed fuzzy PID controller. After fuzzification, fuzzy inference and defuzzification processing as described in Example 6, the wind speed control quantity u_fan∈[0,1] is obtained, and then linearly mapped to a PWM duty cycle of 0~100% to drive the fan speed.

[0085] For example, the function is to calculate the fan speed (PWM duty cycle) based on T_set_sys and the current T_max, and execute it every 100ms.

[0086] Input: T_set_sys (from the central management policy, such as 75°C), T_max (from the state calculation layer, such as 85°C).

[0087] Step 1: Calculate the deviation e_speed; using the engineering control standard: e_speed = T_max - T_set_sys (a positive deviation indicates overheating, requiring an increase in speed). Example: e_speed = 85 - 75 = +10℃; Step 2: Calculate the rate of change of deviation ec_speed; ec_speed = e_speed(k) - e_speed(k-1); Example: In the previous cycle, e_speed(k-1) = +5℃, then ec_speed = +5℃ / cycle; Step 3: Fuzzification; Universe of discourse and membership function (triangle): e_speed actual universe of discourse [-20, +20]℃, fuzzy universe of discourse [-6, +6], quantization factor Ke=0.3. ec_speed actual universe of discourse [-10, +10]℃ / cycle, fuzzy universe of discourse [-6, +6], quantization factor Kec=0.6. Output adjustment ΔKp actual universe of discourse [-1, +1], ΔKi actual universe of discourse [-0.2, +0.2], ΔKd actual universe of discourse [-0.1, +0.1]; fuzzy universes are all set to [-6, +6].

[0088] The domain of the variables is quantized to the interval [-6, 6], and five fuzzy subsets are defined: NB (negative large), NS (negative small), ZO (zero), PS (positive small), and PB (positive large). Each subset adopts a triangular membership function, where NB and PB are right triangles, achieving full membership at their left and right boundaries, respectively; NS, ZO, and PS are symmetrical isosceles triangles, with adjacent subsets having a membership of 0.5 at their intersection, ensuring the smoothness and continuity of the control.

[0089] Fuzzy subset: {NB, NS, ZO, PS, PB} triangle vertex coordinates (fuzzy universe of discourse). The subset corresponding to vertex 1 is {-6, -6, -3, 0, 3}, the subset corresponding to vertex 2 is {-6, -3, 0, 3, 6}, and the subset corresponding to vertex 3 is {-3, 0, 3, 6, 6}.

[0090] Step 4: Fuzzy reasoning (complete rule table); ΔKp rule table (proportional effect): e\ec NB NS ZO PS PB; NB NB NB NS NS ZO; NS NB NS NS ZO PS; ZO NS NS ZO PS PS; PS NS ZO PS PS PB; PB ZO PS PS PB PB.

[0091] ΔKi rule table (integral action, following the principle of suppressing integration to prevent saturation when the deviation is large, and strengthening integration to eliminate steady-state error when approaching the target): e\ec NB NS ZO PS PB; NB NB NB NS ZO ZO; NS NB NS NS ZO PS; ZO NS NS ZO PS PS; PS NS ZO PS PS PB; PB ZO ZO PS PB PB.

[0092] ΔKd rule table (differential action, suppressing overshoot): e\ec NB NS ZO PS PB; NB PB PB PS ZO ZO; NS PB PS PS ZO NS; ZO PS PS ZO NS NS; PS PS ZO NS NS NB; PB ZO ZO NS NB NB.

[0093] Step 5: Defuzzify; use the centroid method: ΔKp = Σ(μ_i·y_i) / Σ(μ_i), where μ_i is the membership degree of the i-th rule, and y_i is the universe of discourse (vertex coordinates) of the output fuzzy set of that rule. ΔKi and ΔKd are similar.

[0094] Step 6: Update PID parameters; Kp_new=Kp0+ΔKp·Gp, where Gp=1 / 6≈0.166; Ki_new=Ki0+ΔKi·Gi, where Gi=0.2 / 6≈0.0333; Kd_new=Kd0+ΔKd·Gd, where Gd=0.1 / 6≈0.0167.

[0095] Initial parameters: Kp0=2.0, Ki0=0.5, Kd0=0.1.

[0096] Step 7: PID calculation output; u_fan(k) = Kp_new·e_speed(k) + Ki_new·Σe_speed(k) + Kd_new·ec_speed(k); Limiting to [0, 1], mapping to PWM duty cycle 0~100%. Example: If Kp_new=2.5, Ki_new=0.6, Kd_new=0.08, e_speed=10, Σe_speed=150, ec_speed=5, then u_fan=2.5·10+0.6·150+0.08·5=115.4, limiting to 1.0 (100%). Output: u_fan∈[0, 1].

[0097] This embodiment uses the deviation between the system's maximum temperature value T_max and the total target temperature value T_set_sys as the core input for fan speed control. This allows the total fan airflow to adaptively adjust according to the overall system heat load level, effectively avoiding the coarse control of conventional solutions where fans can only maintain a constant speed or switch speeds. By introducing the deviation change rate as a second input, the controller can predict temperature change trends, increasing fan speed in advance when the temperature rises rapidly and decreasing fan speed in advance when the temperature drops rapidly. This effectively suppresses temperature overshoot and oscillation, improving the timeliness and stability of control.

[0098] In some embodiments, the process of determining the input parameters for fuzzy control processing during the determination of wind direction control parameters includes: Obtain the regional target temperature value of each target heating area; The second temperature deviation for each target heating zone is determined based on the actual temperature value of each zone and the target temperature value of the zone. Obtain the historical second temperature deviation of the previous actual cycle; The third temperature deviation is determined based on the historical second temperature deviation and the second temperature deviation. The second and third temperature deviations are used as input parameters for each target heating region.

[0099] Specifically, the controller acquires the target temperature value T_set_n for each target heat-generating area. The target temperature value for each area is determined by the central management strategy based on the current target heat dissipation conditions. For example, under directional heat dissipation conditions, T_set_1 = 65℃ for hot spots and T_set_2 = T_set_3 = 75℃ for non-hot spots; under silent conditions, T_set_n = 85℃ for all areas; and under over-temperature and balanced conditions, T_set_n = 75℃ for all areas.

[0100] The controller determines the corresponding second temperature deviation e_n = T_n - T_set_n based on the actual temperature value T_n of each target heating area and the corresponding target temperature value T_set_n. A positive deviation indicates that the actual temperature of the area is higher than the target temperature, and the corresponding regulating plate needs to be opened wider to allocate more airflow. For example, when T_1 = 85℃ and T_set_1 = 65℃, e_1 = +20℃; when T_2 = 65℃ and T_set_2 = 75℃, e_2 = -10℃; when T_3 = 60℃ and T_set_3 = 75℃, e_3 = -15℃.

[0101] The controller obtains the historical second temperature deviation e_n(k-1) corresponding to the previous actual cycle. Based on the historical second temperature deviation e_n(k-1) and the current second temperature deviation e_n, the controller determines the third temperature deviation ec_n = e_n(k) - e_n(k-1). For example, when e_1(k) = +20℃ and e_1(k-1) = +16℃, ec_1 = +4℃ / cycle; when e_2(k) = -10℃ and e_2(k-1) = -8℃, ec_2 = -2℃ / cycle.

[0102] The controller takes the second temperature deviation e_n and the third temperature deviation ec_n as input parameters corresponding to each target heating area, and sends them to the wind direction fuzzy PID controller corresponding to each area. After fuzzification, fuzzy inference and defuzzification processing, the wind direction control quantity u_n∈[0,1] of each area is obtained, and then mapped to the opening angle of the corresponding regulating plate = u_n×90°. The regulating plate drive group drives the first guide vane and the second guide vane to rotate, so as to realize the continuous adjustment of the air outlet direction and airflow distribution ratio of the area.

[0103] For example, the function is as follows: Each controller independently manages one air outlet. Based on the deviation between the independent target temperature and the actual temperature of the area, it calculates the opening degree of the regulating plate, and executes in parallel every 100ms. Input (taking the first controller as an example): T_set_1 (from the central management strategy), T_1 (from the perception layer). The processing logic is basically the same as that of the wind speed controller, but the deviation is defined as follows (also using measured value - set value): e_n = T_n - T_set_n, a positive deviation indicates that it is too hot and the regulating plate needs to be opened larger. ec_n = e_n(k) - e_n(k-1).

[0104] In this embodiment, the fuzzy rule base is used in the wind direction controller, which employs the same fuzzy rule table as the wind speed controller (ΔKp, ΔKi, and ΔKd rule tables are reused). The reason is that both are based on temperature deviation and its rate of change to nonlinearly adjust the actuators (fan speed / regulator opening), resulting in a consistent control law structure; only the domain of discourse and proportional factor need to be adjusted according to different physical dimensions, and this reuse does not affect implementation. Output: u_n∈[0,1], obtained through linear mapping as the regulator opening angle = u_n×90°.

[0105] This embodiment provides a method by independently setting a fuzzy PID controller for each heat-generating area and using the deviation between the actual temperature value and the target temperature value of each area as input. This allows the opening of the regulating plate in each area to be independently adjusted according to the current heat dissipation demand of that area, achieving continuous and adjustable distribution of airflow among multiple air outlets. By introducing a third temperature deviation as a second input, each airflow controller can predict the temperature change trend of each area, further improving the foresight and stability of the opening adjustment of the regulating plate in each area.

[0106] In some embodiments, the target temperature value of the area under each heat dissipation condition is different from the target opening degree of the airflow adjustment mechanism corresponding to each heat-generating area; wherein, under the guided heat dissipation condition, the target temperature value of each hot spot area is less than the target temperature value of the non-hot spot area, so that the second temperature deviation of the hot spot area is greater than the second temperature deviation of the non-hot spot area; wherein, the hot spot area is the heat-generating area where the first critical temperature value is located.

[0107] Specifically, under over-temperature conditions, T_set_sys = 75℃, and T_set_n = 75℃ for all heat-generating areas. The temperature deviation e_n = T_n - 75 for all areas is positive and may be large. The target opening of all adjustment plates is increased, for example, the opening of all corresponding adjustment plates is close to 90°. The fan speed control requires the fan to run at high speed to achieve full-speed overall heat dissipation.

[0108] In the guided heat dissipation mode, T_set_sys = 75℃, T_set_hot = 65℃ in the hot spot area (the heat-generating area where T_max is located), and T_set_other = 75℃ in the non-hot spot area. The actual temperature of the hot spot area is usually much higher than T_set_hot, making the second temperature deviation e_hot = T_hot - 65 in the hot spot area much larger than e_other = T_other - 75 in the non-hot spot area (the latter is negative or slightly positive). As a result, the opening of the regulating plate corresponding to the hot spot area is much larger than the opening of the regulating plate corresponding to the non-hot spot area (the former opening is close to 90°, while the latter opening is smaller), so that the airflow is concentrated and guided to the hot spot area.

[0109] Under balanced operating conditions, T_set_sys = 75℃, and T_set_n = 75℃ for all heat-generating areas. The temperature deviation e_n of each area is similar, corresponding to similar openings of the regulating plates (the openings of each regulating plate are roughly the same). The airflow is evenly distributed among multiple air outlets, and the overall heat dissipation capacity is improved by controlling the fan speed.

[0110] In silent operation, T_set_sys = 85℃, and T_set_n = 85℃ for all heat-generating areas. The actual current temperature is usually below 85℃, so e_n is negative or slightly positive, all adjustment plates are open only slightly, and the fan speed is low, achieving energy-saving and low-noise operation.

[0111] As can be seen from the above differentiated settings, the target temperature value of the area under each heat dissipation condition in this embodiment is different from the target opening degree of the airflow adjustment mechanism corresponding to each heat-generating area. Among them, the target temperature value of the hot spot area under the guided heat dissipation condition is lower than the target temperature value of the non-hot spot area, so that the second temperature deviation of the hot spot area is greater than the second temperature deviation of the non-hot spot area. Consequently, the target opening degree of the adjustment plate corresponding to the hot spot area is greater than the target opening degree of the adjustment plate corresponding to the non-hot spot area, thereby concentrating the airflow to the hot spot area.

[0112] This embodiment provides a method for setting a target temperature value for hot spots that is significantly lower than that for non-hot spots under guided heat dissipation conditions. Utilizing the deviation-driven mechanism of a fuzzy PID controller, the opening of the regulating plate corresponding to the hot spot area is naturally greater than that corresponding to the non-hot spot area, thus precisely directing most of the cool air to the hot spot area. This indirect method of driving airflow distribution through target temperature differences eliminates the need for direct multivariate coupling solutions to the regulating plate opening. The control law structure is simple, parameter tuning is convenient, and it is easily extended to more heat-generating areas. Furthermore, the differentiated settings under various operating conditions allow the same fuzzy PID controller to adapt to differentiated heat dissipation needs under different thermal states, demonstrating excellent versatility.

[0113] In some embodiments, the temperature state parameter further includes the rate of change of temperature difference; the rate of change of temperature difference is determined by the historical critical temperature difference value and the critical temperature difference value corresponding to the previous actual cycle. Correspondingly, the method also includes: If the rate of change of temperature difference is greater than the first threshold, and the critical temperature difference value has not reached the third temperature threshold, and the difference between the third temperature threshold and the second threshold is less than the second threshold, then the guided heat dissipation mode will be entered ahead of the first preset time. And / or, if the rate of change of temperature difference is less than the second threshold and the device is in the guided heat dissipation condition, the device exits the guided heat dissipation condition ahead of schedule by a second preset time; wherein the first threshold is greater than the second threshold.

[0114] Specifically, the controller additionally calculates the temperature difference change rate dΔT / dt = (ΔT(k) - ΔT(k-1)) / Δt at the state calculation layer, where ΔT(k) is the critical temperature difference value of the current actual cycle, ΔT(k-1) is the critical temperature difference value of the previous actual cycle, and Δt is the actual cycle. This temperature difference change rate is included in the temperature state parameter set as part of the temperature state parameter set.

[0115] When the rate of change of temperature difference dΔT / dt is greater than the first threshold, for example, 3℃ / s, and the critical temperature difference ΔT has not reached the third temperature threshold, for example, 15℃, but the difference between the critical temperature difference and the third temperature threshold is less than the second threshold, for example, 2℃, the controller determines that the current thermal state has a tendency to deteriorate rapidly and enters the guided heat dissipation mode ahead of a first preset time, for example, 0.5 seconds. That is, when ΔT has not yet reached the condition for entering the guided heat dissipation mode but is close and the rate of deterioration is relatively fast, the system switches to the guided heat dissipation mode in advance to complete the airflow guidance and suppress the peak temperature of the hot spot.

[0116] When the rate of change of temperature difference dΔT / dt is less than the third threshold, such as -2℃ / s, and the system is already in the guided heat dissipation mode, the controller determines that the current thermal state has improved rapidly and exits the guided heat dissipation mode ahead of the second preset time, such as 1 second. That is, when ΔT has not yet decreased to the exit condition but the rate of decrease is relatively fast, the system exits the guided heat dissipation mode in advance to avoid over-adjustment and reduce unnecessary airflow consumption.

[0117] The first threshold is greater than the third threshold. For example, the absolute value of the first threshold 3℃ / s is greater than the absolute value of the third threshold -2℃ / s, which ensures that the judgment directions of entering early when deterioration is rapid and exiting early when improvement is rapid are opposite and do not conflict.

[0118] This embodiment introduces the rate of change of temperature difference as an advance characteristic quantity, enabling the system to switch to directional heat dissipation mode in advance when the critical temperature difference value has not yet exceeded the entry condition but has already shown a rapid deterioration trend, thereby reducing the peak temperature of the hot spot. At the same time, it exits the directional heat dissipation mode in advance when the critical temperature difference value has already decreased rapidly, avoiding over-adjustment and energy waste caused by maintaining high airflow directional air supply when the thermal condition has been significantly improved.

[0119] In some embodiments, the target threshold under the preset conditions of each heat dissipation condition is obtained by adjusting the online learning algorithm; wherein, the online learning algorithm records the actual temperature value of the temperature change curve during the switching of each condition and counts the frequency of entering the heat dissipation condition. If the frequency exceeds the preset number, the parameter to be adjusted is determined according to the actual temperature value; the target threshold is adjusted according to the parameter to be adjusted to obtain the adjusted target threshold.

[0120] Specifically, the controller records the temperature change curves and actual temperature values ​​during each operating condition switch in the historical record module, and counts the frequency of entering each heat dissipation operating condition. Whenever the system switches from one operating condition to another, it records the temperature status parameters such as T_max, T_avg, ΔT, and dT_max / dt at the time of the switch, as well as the temperature change curves over several cycles after the switch, such as 10 cycles; and counts the number of times each operating condition is entered within the most recent time window, such as the most recent 24 hours or the most recent 1000 switches.

[0121] If the frequency exceeds a preset limit, the controller determines the parameters to be adjusted based on the actual temperature value. If the hotspot temperature continues to rise for more than a preset duration (e.g., 2 seconds) after entering strong directional cooling mode multiple times, the entry threshold for the current directional cooling mode is determined to be too high. For example, if the third temperature threshold of 15℃ is set too high, the system should intervene earlier to avoid excessively high hotspot peaks. Alternatively, if the actual temperature is already close to the throttling threshold before switching to balanced mode multiple times in silent mode, the threshold setting between the current silent and balanced modes is determined to be too low.

[0122] The controller adjusts the target thresholds based on the parameters to be adjusted to obtain the adjusted target thresholds. For example, the third temperature threshold for the guided heat dissipation condition is lowered from 15℃ to 13℃, and the sixth temperature threshold for the silent condition is lowered from 70℃ to 68℃. The adjusted target thresholds replace the original target thresholds for subsequent determination of entry and exit conditions.

[0123] The update strategy for online learning algorithms can employ incremental updates or sliding window statistics. For example, a threshold re-evaluation can be performed every N accumulated switches, with each adjustment limited to ±2°C to avoid frequent switching of operating conditions due to threshold jumps. Regarding the online learning algorithm, backpropagation learning or reinforcement learning algorithms can be used; no specific limitation is made here, and the appropriate algorithm can be selected based on the actual situation.

[0124] The embodiment provides an online learning algorithm that dynamically optimizes target thresholds for various operating conditions based on actual system operating data. This enables the system to adapt to different hardware configurations, such as CPUs with different power consumption, heat sinks with different performance, and different environmental conditions, such as different altitudes and different intake air temperatures. This eliminates the need for manual on-site calibration, reducing deployment costs and maintenance difficulty, and making the system more versatile.

[0125] In some embodiments, after determining the target heat dissipation condition, the process enters the target heat dissipation condition through an actual control cycle; wherein the actual control cycle is longer than the actual cycle.

[0126] Specifically, the controller collects the actual temperature values ​​of each heating zone at a real-time interval, such as 100ms, and determines the temperature state parameters between zones, such as T_max, T_avg, ΔT, dT_max / dt, etc. This real-time interval corresponds to the operating rhythm of the sensing layer and the state calculation layer, ensuring the real-time performance of temperature acquisition and state calculation.

[0127] The controller determines whether to enter the target heat dissipation condition based on the actual control cycle, such as 500ms. Specifically, if the actual control cycle is longer than the actual cycle, for example, 5 times the actual cycle, the central management strategy in the decision-making layer determines the target heat dissipation condition only at the beginning of each actual control cycle, based on the relationship between the latest temperature status parameters obtained in the current actual cycle and the condition entry conditions of each heat dissipation condition, and uses the determined target heat dissipation condition and its corresponding regional target temperature value as the target within that actual control cycle.

[0128] Between two adjacent actual control cycles, the controller continuously runs the fuzzy control processing module according to the actual cycle, calculating the wind speed control quantity and the wind direction control quantity based on the deviation between the target temperature value of the area under the determined target heat dissipation condition and the actual temperature value collected in each actual cycle. That is, between two operating condition decisions, the target heat dissipation condition and the target temperature value of each area remain unchanged, and the fuzzy control processing module continuously updates the control quantity at a higher frequency to track the actual temperature changes.

[0129] The asynchronous multi-rate execution method provided in this embodiment operates with the inner loop (sensing layer, state calculation layer, wind speed controller, and wind direction controller) running at a higher frequency (e.g., 100ms) to ensure real-time control and rapid response to temperature changes. The outer loop's condition determination method operates at a lower frequency (e.g., 500ms) to avoid system oscillations caused by frequent switching of heat dissipation conditions. By separating high-frequency control from low-frequency decision-making, the system ensures both response speed and operational stability.

[0130] In some embodiments, the adjustment plate corresponding to each wind direction control quantity has a preset critical opening limit; when the opening angle corresponding to any wind direction control quantity is less than the critical opening limit, the critical opening limit is output.

[0131] Specifically, the adjustment plates corresponding to each airflow control value have preset critical opening degrees, i.e., minimum opening limits. These minimum opening limits are preset angle thresholds, such as 10° (corresponding to approximately 11% opening) or 15° (corresponding to approximately 17% opening). The specific value of these minimum opening limits can be determined comprehensively based on factors such as the fan's performance curve, the system's wind resistance characteristics, and the layout of the heat-generating areas, to ensure that the airflow channel always has a minimum conduction area under any operating condition.

[0132] When the opening angle corresponding to any wind direction control quantity is less than the minimum opening limit, the minimum opening limit is used for output. That is, before the controller outputs the adjustment plate drive signal at the execution layer, it first compares each wind direction control quantity (opening angle) with the preset minimum opening limit. If the opening angle corresponding to a certain wind direction control quantity is greater than or equal to the minimum opening limit, the drive signal is output according to the actual value of the wind direction control quantity; if the opening angle corresponding to a certain wind direction control quantity is less than the minimum opening limit, the wind direction control quantity is forcibly clamped to the minimum opening limit value, and then the corresponding drive signal is output.

[0133] For example, suppose the preset minimum opening limit is 10°. In silent energy-saving mode, if a heat-generating area has an actual temperature much lower than the target temperature, the fuzzy PID output of the airflow controller corresponds to an opening angle of 2°. Since 2° < 10°, the controller forcibly corrects this airflow control value to 10°, and the final opening angle of the regulating plate is 10°, not 2°. In this way, even when no additional cooling is needed in any area, each regulating plate maintains a basic opening, ensuring that the airflow generated by the fan always has a clear exit path.

[0134] For example, suppose the minimum opening limit is 15°. In the guided heat dissipation mode, the opening of the regulating plate corresponding to the non-hotspot area is calculated to be 8°, which is also less than 15°. The system automatically clamps it to 15° output to maintain the basic ventilation volume of the non-hotspot area and avoid airflow blockage caused by the regulating plate being completely closed.

[0135] The minimum opening limit mechanism provided in this embodiment ensures that the actual opening of the regulating plate will not fall below the preset minimum value under any operating condition, fundamentally preventing problems such as airflow channel blockage, abnormal increase in system back pressure, and fan deviation from normal operating point caused by the regulating plate being completely closed. Simultaneously, because the regulating plate always maintains a basic opening, a small amount of cool air continuously flows through each heat-generating area, preventing excessive temperature drops in each area due to complete lack of airflow, and effectively limiting the negative deviation between the actual temperature and the target temperature to a small range.

[0136] Furthermore, this application also provides a heat dissipation control system, including multiple temperature sensors, a fan module, and a controller; the multiple temperature sensors are located in the heat-generating area corresponding to the fan module and are connected to the controller; the fan module is connected to the controller; The controller is used to execute the steps of the above-described heat dissipation control method to control the fan module to dissipate heat from the heat-generating area.

[0137] Specifically, multiple temperature sensors are located within the corresponding heat-generating areas of the fan module, such as being mounted close to the CPU, memory, and motherboard assembly, and connected to the controller. The temperature sensors report the collected temperature values ​​to the controller in real time via digital interfaces such as the Inter-Integrated Circuit (I2C) or System Management Bus (SMBus). The fan module is connected to the controller, which drives the fan body and adjusts the fan speed via a PWM signal line.

[0138] The controller, such as a Baseboard Management Controller (BMC) or a dedicated thermal management microcontroller, internally includes a temperature acquisition module, a state calculation module, a central management strategy module, a fuzzy PID controller for wind speed, and a fuzzy PID controller group for wind direction. The temperature acquisition module reads the temperature values ​​from each temperature sensor via a digital interface on an actual cycle. The state calculation module calculates temperature state parameters such as T_max, T_avg, ΔT, and dT_max / dt based on the temperature values. The central management strategy module determines the target heat dissipation condition based on the relationship between the temperature state parameters and the preset conditions of each operating condition on an actual control cycle, and outputs the corresponding target temperature value for the area. The fuzzy PID controller for wind speed calculates the wind speed control quantity based on the deviation between T_set_sys and T_max on an actual cycle. The controllers in the fuzzy PID controller group for wind direction calculate the wind direction control quantity for each area in parallel on an actual cycle based on the deviation between T_set_n and T_n. The controller's PWM output port is connected to the fan drive circuit and the regulator board drive group, respectively. The fan drive circuit converts the PWM signal into power current to drive the fan motor; the regulator board drive group, such as a micro servo drive circuit, converts the PWM signal into current to drive the regulator board servo.

[0139] Figure 3 This is a schematic diagram of the architecture of a heat dissipation control system provided in an embodiment of this application, as shown below. Figure 3 As shown, a hierarchical, multi-closed-loop feedback control architecture is adopted, separating data perception, state calculation, pattern decision-making, low-level control, and physical execution. The entire system is divided into five layers according to signal flow and decision-making hierarchy: physical layer, perception layer, state calculation layer, decision-making layer, and execution layer.

[0140] The physical layer is the controlled object, including heat-generating areas (CPU, memory, motherboard assembly) and fans and airflow distribution components. Specifically, the fans and airflow distribution components consist of the fan body, the airflow distribution components, and the regulating plates. Fan speed and regulating plate opening jointly determine the airflow in each area, thus affecting temperature. The physical layer's inputs are the fan's PWM drive signal (determining speed) and the opening angle signals of each regulating plate; its output is the temperature change of each heat-generating area (detected by sensors).

[0141] The sensing layer is used to collect the temperature of each heat-generating area in real time and convert the physical quantity into a digital quantity. The sensing layer includes a temperature sensor group and a signal conversion module. Multiple digital temperature sensors are installed close to each heat-generating area, and a digital interface (such as an I2C bus) is used to read the sensor data. The read sensor data is sent to the signal conversion module through sampling. That is, after the system powers on, the I2C interface and timer are initialized, and the sampling period is set to 100ms. In each sampling period, a read command is sent to each sensor sequentially, the temperature data is received, and the temperature value is stored in a variable.

[0142] The state calculation module in the state calculation layer calculates a comprehensive index reflecting the overall thermal state of the system based on various temperature values, serving as input for the central management strategy. It executes once per cycle (100ms). The decision layer contains the central management strategy (mode decision unit), a wind speed controller, and multiple wind direction controllers. The execution layer converts the digital control signals output from the decision layer into physical actions, including fan drive circuits and regulating plate motor drive circuits. Temperature changes in each heat-generating area within the physical layer are fed back to the sensing layer through airflow distribution, forming a closed loop.

[0143] For a description of the heat dissipation control system provided in this application, please refer to the above method embodiments. This application will not repeat the description here, as it has the same beneficial effects as the above heat dissipation control method.

[0144] In some embodiments, the fan module includes an elongated split housing, and the interior of the split housing is divided by a partition to form a plurality of parallel air ducts; a fan body is installed in each air duct. An adjustment plate assembly is provided at the air outlet of each air duct. The adjustment plate assembly includes a horizontally arranged first air guide blade and a vertically arranged second air guide blade to rotate according to the wind speed control amount and / or multiple wind direction control amounts.

[0145] Specifically, Figure 4 This is a schematic diagram of the structure of a fan module provided in an embodiment of this application, as shown below. Figure 4 As shown, the fan module includes a long, narrow splitter housing. Inside the splitter housing, multiple parallel air ducts are formed by partitions. The number of air ducts corresponds one-to-one with the number of heat-generating areas; for example, three heat-generating areas correspond to three parallel air ducts. Each air duct houses a fan body, and the fan speed can be controlled by an independent PWM signal.

[0146] Each air duct's outlet end is equipped with an adjusting plate assembly, which includes a horizontally arranged first guide vane 1 and a vertically arranged second guide vane 2. The module is also equipped with an actuator, which is respectively connected to the first guide vane 1 and the second guide vane 2 in a transmission connection. It should be noted that... Figure 4The middle section, specifically the first guide vane 1, is not fully detailed to ensure a clear view of the fan blades' installation position. For example, the middle section is located on one side of the adjustment plate assembly. During operation, the control system acquires ambient temperature difference data, calculates the optimal airflow direction and volume, and then instructs the actuator to drive the adjustment plate to deflect. For instance, when air needs to be directed downwards and to the left, the first guide vane 1 deflects to the left, and the second guide vane 2 deflects downwards, achieving precise, targeted heat dissipation. The first guide vane 1 rotates around a vertical axis to adjust the horizontal airflow distribution; the second guide vane 2 rotates around a horizontal axis to adjust the vertical airflow distribution. Both the first guide vane 1 and the second guide vane 2 are driven by micro-servos, enabling continuous rotation based on wind speed control and / or multiple wind direction control values, thus achieving continuous adjustment of the airflow direction and distribution ratio.

[0147] For example, the maximum opening of the first guide vane 1 and the second guide vane 2 is 90°. The rotation angle is controlled by the PWM duty cycle signal of the micro servo motor, for example, the high-level time = 0.5ms + u_n × 2.0ms (when u_n = 0.5, the high-level time of 1.5ms corresponds to 45°). The opening limit of the regulating plate assembly is guaranteed by the internal control algorithm of the controller. For example, the regulating plate corresponding to each wind direction control quantity has a preset minimum opening limit. When the opening angle corresponding to any wind direction control quantity is less than the minimum opening limit, the minimum opening limit is output to avoid the regulating plate being completely closed, which would cause the corresponding area to not receive any airflow and thus cause local overheating.

[0148] In a server scenario, within a 2U server, temperature sensors are installed on the CPU, memory, and motherboard assembly. When the CPU is operating at full load, T... CPU The temperature rises to 85℃, while the memory temperature (T_max) is 55℃, resulting in a ΔT of 30℃. The expert system detects that ΔT > 15℃ and T_max > 75℃, automatically entering guided cooling mode: the fan speed increases to 80%, the CPU's corresponding exhaust vent opening widens to 90%, and the memory and motherboard exhaust vents decrease to 30%. As a result, over 85% of the cool air is directed towards the CPU, causing its temperature to drop to 75℃ within 3 seconds, preventing throttling. Meanwhile, the memory and motherboard, with their lower heat output, can maintain normal temperatures with a 30% opening.

[0149] In addition, it can also be applied to multi-zone air supply scenarios in smart home air conditioning, addressing the common problem of cold living rooms and hot bedrooms in residential central air conditioning or floor-standing air conditioners. The air outlets are divided into multiple independent zones (corresponding to sofa areas, dining areas, bed areas, etc.), and infrared or temperature sensors are installed to detect the temperature of each zone. By calculating the temperature difference between zones, the expert system automatically switches the air supply mode (such as a concentrated airflow mode that directs airflow to the hottest area, and a balanced airflow mode), achieving a smart and comfortable experience with airflow following the user and automatic temperature control, while reducing compressor energy consumption.

[0150] It can also be applied to scenarios involving the elimination of localized hotspots in industrial equipment. In industrial equipment such as laser cutting machines, high-power power cabinets, and injection molding machines, certain components (such as Insulated Gate Bipolar Transistor (IGBT) modules, laser generators, and motor drivers) experience severe instantaneous heat generation, while the overall ambient temperature remains low. Traditional overall air cooling consumes a lot of power and generates a lot of noise. This solution can be configured as a point-to-point heat dissipation module: multiple miniature fan outlets are arranged inside the equipment, each outlet corresponding to a hotspot component. Through temperature difference recognition, the outlet's regulating plate is opened and the fan speed is increased only when the hotspot overheats, while non-hotspot areas maintain low airflow or are even shut off. This can significantly reduce the heat dissipation energy consumption and dust intake of industrial equipment.

[0151] This embodiment provides an adjustable plate assembly containing horizontal and vertical guide vanes, which divides the split housing into multiple parallel air ducts. Each air duct's outlet end is equipped with an independent air duct and adjustable plate, allowing for precise airflow distribution to each area. The continuously rotatable guide vanes enable continuous adjustment of the airflow distribution ratio, overcoming the limitation of conventional solutions where baffles can only open and close. By decoupling the fan body from the adjustable plate assembly, decoupled and coordinated control of wind speed and direction is achieved.

[0152] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0153] Embodiments of this application also provide a heat dissipation control device. Figure 5 This is a schematic diagram of a heat dissipation control device provided in an embodiment of this application, as shown below. Figure 5 As shown, the device includes: The first determining module 11 is used to obtain the actual temperature values ​​of each of the multiple heating areas in the target device during the actual cycle, and to determine the temperature state parameters between the areas based on the actual temperature values. The second determining module 12 is used to determine the corresponding target heat dissipation condition based on the relationship between the temperature state parameters and the preset conditions of the operating condition; wherein, the preset conditions of the operating condition include the conditions for entering the operating condition and the conditions for exiting the actual operating condition; the heat dissipation conditions include at least the over-temperature condition, the guided heat dissipation condition, the balanced condition and the silent condition. Control module 13 is used to perform fuzzy control processing based on the deviation between the target temperature value and the actual temperature value of the target heat dissipation condition to obtain the wind speed control quantity and / or the wind direction control quantity corresponding to multiple heat-generating areas, so as to control the fan to dissipate heat from the heat-generating areas.

[0154] For a description of the features in the corresponding embodiment of the device, please refer to the relevant description of the corresponding embodiment of the heat dissipation control method, which will not be repeated here.

[0155] Embodiments of this application also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above embodiments of the heat dissipation control method.

[0156] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above-described embodiments of the heat dissipation control method when it is run.

[0157] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0158] Embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above-described heat dissipation control method embodiments.

[0159] Embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the above-described heat dissipation control method embodiments.

[0160] Any of the components, modules, units, parts, methods, and operations described herein can be implemented using software, firmware, hardware (e.g., fixed logic circuitry), manual processing, or any combination thereof. Alternatively or additionally, any functionality described herein can be executed at least in part by one or more hardware logic components, such as, but not limited to, CPUs, Field-Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application-Specific Standard Products (ASSPs), Systems on Chips (SoCs), Complex Programmable Logic Devices (CPLDs), Microcontroller Units (MCUs), etc. The terms "system," "computing device," or "apparatus" as used herein encompass various means, devices, and machines for processing data, including, for example, one or more programmable processors, computers, SoCs, or combinations thereof. The apparatus may also include code that creates an execution environment for the computer program in question, such as code constituting processor firmware, protocol stacks, database management systems, operating systems, cross-platform runtime environments, virtual machines, or combinations thereof. The aforementioned computer program (also known as a program, software, software application, application (App), script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and can be deployed in any form, including as a standalone program or as a module, component, subroutine, object, or other unit suitable for a computing environment.

[0161] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0162] The above provides a detailed description of a heat dissipation control method, system, and electronic device provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of this application.

Claims

1. A heat dissipation control method, characterized in that, include: Obtain the actual temperature values ​​of multiple heating areas within the target device during the actual cycle, and determine the temperature state parameters between the areas based on the actual temperature values. The corresponding target heat dissipation condition is determined based on the relationship between the temperature state parameters and the preset operating conditions; wherein, the preset operating conditions include the operating condition entry conditions and the exit conditions corresponding to the actual operating conditions; the heat dissipation conditions include at least the over-temperature condition, the guided heat dissipation condition, the balanced condition, and the silent condition. Based on the deviation between the target temperature value and the actual temperature value of the area under the target heat dissipation condition, fuzzy control processing is performed to obtain the wind speed control quantity and / or the wind direction control quantity corresponding to multiple heat-generating areas, so as to control the fan to dissipate heat from the heat-generating areas.

2. The heat dissipation control method according to claim 1, characterized in that, The temperature state parameters include at least the first critical temperature value between regions, the average temperature value, the critical temperature difference value between regions, and the temperature change rate at intervals. The process of determining the temperature state parameters includes: The maximum and minimum values ​​are selected from the actual temperature values ​​of each heating zone and used as the first and second critical temperature values, respectively. The average temperature value is obtained by averaging the actual temperature values ​​of each heating zone. The critical temperature difference value is determined based on the first critical temperature value and the second critical temperature value; Obtain the historical first critical temperature value corresponding to the previous actual cycle, the interval between the previous actual cycle and the actual cycle; and determine the temperature change rate based on the historical first critical temperature value, the first critical temperature value and the interval.

3. The heat dissipation control method according to claim 2, characterized in that, The target heat dissipation condition is determined based on the relationship between the temperature state parameters and the preset operating conditions, including: The actual target heat dissipation condition is determined based on the relationship between the temperature state parameters and the conditions for entering each heat dissipation condition. After entering the actual target heat dissipation condition, the temperature status parameters are continuously monitored; If the temperature status parameters after entering the actual target heat dissipation condition are detected to meet the corresponding exit conditions, then the actual target heat dissipation condition is exited, and the process returns to the step of determining the actual target heat dissipation condition based on the relationship between the temperature status parameters and the condition entry conditions of each heat dissipation condition. If the temperature status parameters after entering the actual target heat dissipation condition are not detected to meet the corresponding exit conditions, the actual target heat dissipation condition is maintained and used as the final target heat dissipation condition.

4. The heat dissipation control method according to claim 3, characterized in that, The actual target heat dissipation conditions are determined based on the relationship between the temperature state parameters and the conditions for entering each heat dissipation condition, including: Prioritize each heat dissipation condition so that the priority of the entry conditions for the over-temperature condition, the guided heat dissipation condition, the balanced condition, and the silent condition gradually decreases. If the temperature state parameters meet the conditions for entering the over-temperature condition with the first priority, then the actual target heat dissipation condition is determined to be the over-temperature condition. If the temperature state parameters do not meet the conditions for entering the first priority over-temperature condition, but meet the conditions for entering the second priority guided heat dissipation condition, then the actual target heat dissipation condition is determined to be the guided heat dissipation condition. If the temperature state parameters do not meet the conditions for entering the second priority guided heat dissipation condition, but meet the conditions for entering the third priority balanced condition, then the actual target heat dissipation condition is determined to be the balanced condition. If the temperature state parameters do not meet the conditions for entering the third priority balanced operating condition, then the actual target heat dissipation operating condition is determined to be the silent operating condition.

5. The heat dissipation control method according to claim 3 or 4, characterized in that, The condition for entering the over-temperature condition is that the first critical temperature value is greater than the first temperature threshold or the temperature change rate is greater than the first threshold change rate; the condition for exiting the over-temperature condition is that the first critical temperature value is less than the second temperature threshold and the temperature change rate is less than the second threshold change rate; wherein, the first temperature threshold is greater than the second temperature threshold, and the first threshold change rate is greater than the second threshold change rate. The condition for entering the guided heat dissipation mode is that the critical temperature difference is greater than the third temperature threshold and the first critical temperature value is greater than the fourth temperature threshold; the condition for exiting the guided heat dissipation mode is that the critical temperature difference is less than the fifth temperature threshold, or the first critical temperature value is less than the sixth temperature threshold; wherein, the third temperature threshold is greater than the fifth temperature threshold and less than the sixth temperature threshold; the fourth temperature threshold is greater than the sixth temperature threshold and less than the second temperature threshold. The condition for entering the equilibrium operating condition is that the average temperature value is greater than the sixth temperature threshold, and the critical temperature difference value is less than or equal to the fifth temperature threshold; the condition for exiting the equilibrium operating condition is that the average temperature value is less than the seventh temperature threshold; wherein, the seventh temperature threshold is less than the sixth temperature threshold. The condition for entering the silent operating mode is that the average temperature value is less than or equal to the sixth temperature threshold, or the critical temperature difference value is greater than the fifth temperature threshold.

6. The heat dissipation control method according to any one of claims 2 to 4, characterized in that, Based on the deviation between the target temperature value and the actual temperature value of the area under the target heat dissipation condition, fuzzy control processing is performed to obtain wind speed control quantities and / or wind direction control quantities corresponding to multiple heat-generating areas, including: Obtain the deviation between the target temperature value and the actual temperature value in the region, and the rate of change of the deviation over the interval period; The deviation and the rate of change of the deviation are used as input parameters for fuzzy control processing, respectively mapped to a preset fuzzy universe, and fuzzy subsets are obtained by fuzzification processing through a membership function. The fuzzy output quantity is obtained by reasoning on the fuzzy subset according to the preset fuzzy rule base; The fuzzy output is defuzzified to obtain the wind speed control quantity and / or the wind direction control quantity.

7. The heat dissipation control method according to claim 6, characterized in that, In the process of determining the wind speed control quantity, the process of determining the input parameters for the fuzzy control processing includes: Obtain the total target temperature value; A first temperature deviation is determined based on the first critical temperature value and the total target temperature value; Obtain the historical first temperature deviation of the previous actual cycle and the interval between the previous actual cycle and the actual cycle; The deviation change rate is determined based on the historical first temperature deviation, the first temperature deviation, and the interval time. The first temperature deviation and the rate of change of the deviation are used as input parameters.

8. The heat dissipation control method according to claim 6, characterized in that, In the process of determining the wind direction control quantity, the process of determining the input parameters of the fuzzy control processing includes: Obtain the regional target temperature value of each target heating area; The second temperature deviation corresponding to each target heating area is determined based on the actual temperature value of each target heating area and the target temperature value of the area; Obtain the historical second temperature deviation of the previous actual cycle; The third temperature deviation is determined based on the historical second temperature deviation and the second temperature deviation. The second temperature deviation and the third temperature deviation are used as input parameters for each target heating area.

9. The heat dissipation control method according to claim 8, characterized in that, The target temperature value of each area under each heat dissipation condition is different from the target opening degree of the airflow adjustment mechanism corresponding to each heat-generating area; wherein, under the guided heat dissipation condition, the target temperature value of each hot spot area is less than the target temperature value of the non-hot spot area, so that the second temperature deviation of the hot spot area is greater than the second temperature deviation of the non-hot spot area; wherein, the hot spot area is the heat-generating area where the first critical temperature value is located.

10. The heat dissipation control method according to claim 5, characterized in that, The temperature state parameter also includes the temperature difference change rate; the temperature difference change rate is determined by the historical critical temperature difference value corresponding to the previous actual cycle and the critical temperature difference value. Correspondingly, the method further includes: If the rate of change of temperature difference is greater than the first threshold, and the critical temperature difference value has not reached the third temperature threshold, and the difference between the critical temperature difference value and the third temperature threshold is less than the second threshold, then the guided heat dissipation condition is entered ahead of schedule by a first preset time. And / or, if the rate of change of temperature difference is less than the second threshold and the guided heat dissipation condition is in effect, then the guided heat dissipation condition is exited before the second preset time; wherein, the first threshold is greater than the second threshold.

11. The heat dissipation control method according to claim 10, characterized in that, The target thresholds for each heat dissipation condition are obtained by adjusting the preset thresholds under the operating conditions through an online learning algorithm. The online learning algorithm records the actual temperature values ​​of the temperature change curves during each switching of operating conditions and counts the frequency of entering the heat dissipation condition. If the frequency exceeds the preset number, the parameter to be adjusted is determined based on the actual temperature value. The target threshold is then adjusted based on the parameter to be adjusted to obtain the adjusted target threshold.

12. The heat dissipation control method according to claim 1, characterized in that, After determining the target heat dissipation condition, the system enters the target heat dissipation condition through an actual control cycle; wherein the actual control cycle is longer than the actual cycle.

13. A heat dissipation control system, characterized in that, It includes multiple temperature sensors, a fan module, and a controller; the multiple temperature sensors are located in the heat-generating area corresponding to the fan module and are connected to the controller; the fan module is connected to the controller. The controller is used to execute the steps of the heat dissipation control method according to any one of claims 1 to 12, so as to control the fan module to dissipate heat from the heat-generating area.

14. The heat dissipation control system according to claim 13, characterized in that, The fan module includes a long strip-shaped splitter housing, and the interior of the splitter housing is divided into multiple parallel air ducts by partition plates; a fan body is installed in each air duct. An adjustment plate assembly is provided at the air outlet of each air duct. The adjustment plate assembly includes a horizontally arranged first air guide blade and a vertically arranged second air guide blade to rotate according to the wind speed control amount and / or multiple wind direction control amounts.

15. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the steps of the heat dissipation control method as described in any one of claims 1 to 12.

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