Temperature control system and method based on fuzzy PID composite algorithm

Abstract

The invention provides a temperature control system and method based on a fuzzy PID composite algorithm, and relates to the technical field of temperature control. According to the system, the circulation rate of a liquid-phase heat transfer medium is precisely regulated and controlled through a micropump, the gas-phase heat transfer efficiency is enhanced in combination with a fan, and real-time feedback of a temperature detection module and closed-loop cooperative adjustment of a main control module are matched; a composite control framework is constructed through a fuzzy control module and a PID control module, and wide-range, high-precision and rapid temperature control over a target object is achieved. The fuzzy control module dynamically adjusts PID parameters in real time according to the temperature deviation and the deviation change rate, the PID control module outputs accurate control signals based on the adjusted parameters, a micropump and a fan are driven to adjust the temperature of a target object, and the problems that a traditional temperature control system is slow in response, narrow in temperature control range and poor in high and low temperature scene adaptability are solved. The system is suitable for scenes such as temperature control of high-power-density assemblies and heat dissipation of electronic devices.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology, specifically to a temperature control system and method based on a fuzzy PID composite algorithm, which is particularly suitable for scenarios with high requirements for temperature control range, response speed, and accuracy, such as temperature control of high power density components and heat dissipation of electronic devices. Background Technology

[0002] As electronic devices evolve towards higher power density and miniaturization, their thermal management becomes increasingly critical. Particularly in applications such as electric vehicle power modules, data center server chips, and high-power LED lighting, the instantaneous heat flux density of core components increases dramatically, posing unprecedented challenges to the accuracy, speed, and stability of temperature control. Traditional temperature control methods, such as simple on / off control or conventional PID control, have significant shortcomings in handling such complex thermal systems. On / off control suffers from large overshoot and poor stability; while conventional PID algorithms struggle to achieve dynamic optimal adjustment of their fixed control parameters when facing system nonlinearity, time-varying conditions, and external disturbances, easily leading to slow response, insufficient steady-state accuracy, or continuous oscillations. This not only affects device performance and lifespan but may also trigger safety issues such as thermal runaway. Summary of the Invention

[0003] This invention proposes a temperature control system based on a fuzzy PID composite algorithm.

[0004] The technical solution for achieving the objective of this invention is as follows: a temperature control system based on a fuzzy PID composite algorithm, comprising a target temperature control module, a composite heat transfer loop, a micropump unit, a fan unit, a temperature detection module, a flow detection module, a pressure detection module, and a main control module; the composite heat transfer loop is connected to the target temperature control module and contains a built-in liquid-phase heat transfer medium for heat exchange between the target object and the outside environment; the micropump unit is connected in series in the composite heat transfer loop to drive the circulation of the liquid-phase heat transfer medium and regulate its flow rate; the fan unit is correspondingly located outside the heat exchange section of the composite heat transfer loop to accelerate gas-phase heat transfer in the heat exchange section and regulate the heat exchange rate. The heat exchange efficiency is assessed. The temperature detection module is located on the surface or inside the target temperature control module to collect real-time temperature data of the target object. The flow detection module is located in the composite heat transfer loop to detect the flow rate of the liquid in the loop. The pressure detection module is located in the composite heat transfer loop to detect the loop pressure. The main control module is connected to the micro-pump unit, the fan unit, and the temperature detection module respectively. It receives real-time temperature data, compares the real-time temperature data with a preset temperature threshold, and outputs a coordinated control signal to adjust the rotation speed of the micro-pump unit and the wind speed of the fan unit to precisely control the heat transfer rate and achieve stable temperature of the target object.

[0005] This invention also proposes a temperature control method based on a fuzzy PID composite algorithm, comprising the following steps:

[0006] Step 1: Obtain the real-time temperature of the target temperature-controlled object through the temperature acquisition module and transmit it to the fuzzy PID control module;

[0007] Step 2: The fuzzy PID control module calculates the deviation between the real-time temperature and the target temperature, as well as the rate of change of the deviation.

[0008] Step 3: The fuzzy control unit, based on e, e c And fuzzy rule base, inference output PID parameter correction amount ΔK p ΔK i ΔK d Update the PID parameters;

[0009] Step 4: The PID control unit performs PID calculations based on the updated parameters and outputs control signals to the actuator;

[0010] Step 5: Limit the output control signal to prevent overshoot;

[0011] Step 6: The actuator adjusts the micro-pump speed and fan speed according to the control signal to change the temperature of the target temperature-controlled object;

[0012] Step 7: Repeat steps 1-6 until the real-time temperature stabilizes within ±0.5℃ of the target temperature.

[0013] Compared with the prior art, the significant advantages of this invention are:

[0014] 1. Wide temperature control range: Through a composite mode of "micro-pump liquid speed control + fan gas assistance + semiconductor refrigeration extreme adjustment", the temperature control range covers -25℃ to 110℃, adapting to the needs of high and low temperature scenarios.

[0015] 2. High-precision temperature control: Fuzzy PID algorithm coordinates the flow rate of the micro pump and the fan speed, with a temperature control error of ≤±0.5℃, meeting the requirements of high-precision equipment;

[0016] 3. Rapid response: The adjustment response time of both the micro pump and the fan is less than 0.3s. Combined with the composite heat transfer circuit, the temperature rise and fall response time is as short as 2s, avoiding damage to the target object due to temperature fluctuations.

[0017] 4. Energy-saving and efficient: The adjustment weight is dynamically allocated according to the temperature deviation. In non-extreme scenarios, there is no need to start the auxiliary temperature control module. Compared with the traditional full-power operation system, energy consumption is reduced by 30%-50%.

[0018] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of a temperature control system based on a fuzzy PID composite algorithm.

[0020] Figure 2 This is a schematic diagram of the fuzzy PID composite algorithm.

[0021] Figure 3 This is an example diagram of a temperature control system based on a fuzzy PID composite algorithm.

[0022] Figure 4 This is a flowchart of a temperature control system based on a fuzzy PID composite algorithm. Detailed Implementation

[0023] A temperature control system based on a fuzzy PID composite algorithm is disclosed, relating to the field of temperature control technology. This system precisely regulates the circulation rate of the liquid-phase heat transfer medium through a micro-pump, enhances gas-phase heat transfer efficiency by combining it with a fan, and integrates real-time feedback from a temperature detection module with closed-loop coordinated adjustment by the main control module. A composite control architecture is constructed using a fuzzy control module and a PID control module to achieve wide-range, high-precision, and rapid temperature control of the target object. The fuzzy control module dynamically adjusts the PID parameters in real time based on temperature deviation and the rate of change of deviation. The PID control module outputs a precise control signal based on the adjusted parameters, driving the micro-pump and fan to regulate the temperature of the target object, thus solving the problems of slow response, narrow temperature control range, and poor adaptability to high and low temperature scenarios in traditional temperature control systems. This system is suitable for scenarios such as temperature control of high-power-density components and heat dissipation of electronic devices.

[0024] A temperature control system based on a fuzzy PID composite algorithm includes a target temperature control module, a composite heat transfer loop, a micropump unit, a fan unit, a temperature detection module, a flow detection module, a pressure detection module, and a main control module. The composite heat transfer loop is connected to the target temperature control module and contains a built-in liquid-phase heat transfer medium for heat exchange between the target object and the external environment. The micropump unit is connected in series in the composite heat transfer loop to drive the circulation of the liquid-phase heat transfer medium and regulate its flow rate. The fan unit is correspondingly located outside the heat exchange section of the composite heat transfer loop to accelerate gas-phase heat transfer in the heat exchange section and adjust the heat exchange efficiency. A temperature detection module is installed on the surface or inside the target temperature control module to collect real-time temperature data of the target object; a flow detection module is installed in the composite heat transfer loop to detect the flow rate of the liquid in the loop; a pressure detection module is installed in the composite heat transfer loop to detect the loop pressure; the main control module is connected to the micropump unit, the fan unit, and the temperature detection module respectively, to receive real-time temperature data, compare the real-time temperature data with a preset temperature threshold, and output a coordinated control signal to adjust the rotation speed of the micropump unit and the wind speed of the fan unit to accurately control the heat transfer rate and achieve temperature stability of the target object.

[0025] In a further embodiment, the micropump unit is a piezoelectric-driven micropump or an electromagnetic-driven micropump, and the flow rate adjustment range of the liquid phase heat transfer medium is selected according to the actual situation, with a minimum adjustment accuracy of not less than 0.05 L / min.

[0026] In a further embodiment, the fan unit is an axial flow fan, and the wind speed adjustment range is selected according to the actual situation, with a minimum adjustment accuracy of not less than 0.1m / s.

[0027] In a further embodiment, the temperature acquisition module uses a PT1000 platinum resistance sensor with a sampling frequency of 1-10Hz. The acquired analog temperature signal is converted into a digital signal by an A / D converter and then transmitted to the main control module.

[0028] In a further embodiment, the flow detection module converts the flow value into a voltage signal and sends it to the main control module.

[0029] In a further embodiment, the pressure detection module converts the pressure value into a voltage signal and sends it to the main control module.

[0030] In a further embodiment, an auxiliary temperature control module is also included. The auxiliary temperature control module is a semiconductor refrigeration chip that is attached to the heat exchange section of the composite heat transfer circuit and electrically connected to the main control module. It is used to assist in adjusting the temperature of the liquid phase heat transfer medium in extreme temperature scenarios, thereby widening the system temperature control range.

[0031] In a further embodiment, a human-computer interaction module is also included, which is used to set the target temperature, display the real-time temperature and control parameters, and supports parameter storage and retrieval.

[0032] In a further embodiment, a fuzzy PID control algorithm is embedded in the main control module. Temperature information collected in real-time by the temperature acquisition module is used as input. The main control module processes this information through the fuzzy control module and the PID control module, then outputs a control signal. This signal controls the micro-pump speed and fan speed to control the target temperature. The main control module receives temperature, flow rate, and pressure information in real-time and transmits them to the host computer via the network. When these values ​​exceed set values, an alarm light is activated, and the host computer can control the operation of the water pump and fan.

[0033] Specifically, the main control module outputs the control signal after processing by the fuzzy control unit and the PID control unit as follows:

[0034] Fuzzy control unit: preset temperature deviation e, deviation change rate e c Based on the fuzzy subsets ({negative large, negative medium, negative small, zero, positive small, positive medium, positive large}) and membership functions, a fuzzy rule base is established, and based on the input e and e cInference output PID parameter correction (ΔK) p ΔK i ΔK d );

[0035] PID control unit: Receives the actual temperature value and the set temperature value from the temperature acquisition module, and calculates e and e0. c Combined with the ΔK output by the fuzzy control unit p ΔK i ΔK d Dynamically update PID parameters, K p =K p0 +ΔK p K i =K i0 +ΔK i K d =K d0 +ΔK d K p0 K i0 K d0 The initial parameters are used to output control signals through PID calculation.

[0036] 1. Establishment of Fuzzy Rule Base: Based on the temperature control scenario, the universe of discourse for e is set to [-3℃, 3℃], the universe of discourse for ec is set to [-1℃ / s, 1℃ / s], and the universes of discourse for ΔKp, ΔKi, and ΔKd are [-1, 1], [-0.05, 0.05], and [-0.02, 0.02], respectively; using the triangular membership function, 49 fuzzy rules are established.

[0037] 2. Algorithm operation process: The STM32 executes the algorithm cycle once every 100ms. First, it reads the real-time temperature after A / D conversion and calculates e and ec. Then, it obtains ΔKp, ΔKi, and ΔKd through fuzzy inference and updates the PID parameters. Finally, it calculates the control quantity using the positional PID formula (u(t)=Kpe(t)+Ki∫e(t)dt+Kd*de(t) / dt) and converts it into a PWM signal output to the micro pump and fan.

[0038] The workflow is shown in Figure 4. Taking a high power density module (target temperature 45℃) as an example, it is explained in two scenarios:

[0039] Low-temperature start-up scenario (initial temperature 10℃):

[0040] 1. The temperature detection module collects the initial temperature of the component at 10℃ and sends it to the main control module;

[0041] 2. When the main control module determines that the temperature is 10℃ < 20℃, it controls the micro pump unit to run at a speed of 4000rpm, and at the same time controls the auxiliary temperature control module to heat the liquid phase heat transfer medium. The fan unit runs at a speed of 2000rpm (to reduce heat loss), and the alarm light is turned on.

[0042] 4. When the component temperature is ≥20℃, control the micro pump unit to run at 2500rpm, and at the same time control the auxiliary temperature control module to heat the liquid phase heat transfer medium. The fan unit runs at 2000rpm (to reduce heat loss), and the alarm light turns off.

[0043] 3. When the component temperature is ≥42℃, the main control module switches to a fuzzy PID composite algorithm to control the micro-pump flow rate and fan speed, and the alarm light turns off;

[0044] High-load heat generation scenario (module temperature rises to 60℃):

[0045] 1. When the main control module determines that the temperature is 60℃>55℃, it controls the micro pump unit to run at a speed of 4700rpm, and at the same time controls the auxiliary temperature control module to cool the liquid phase heat transfer medium. The fan unit runs at full speed (to improve the heat exchange rate), and the alarm light is turned on.

[0046] 2. When the component temperature is <55℃, the micro-pump unit is controlled to run at 2500rpm, and the auxiliary temperature control module is controlled to cool the liquid phase heat transfer medium. The fan unit runs at full speed (to improve the heat exchange rate), and the alarm light is turned off.

[0047] 3. When the component temperature is <48℃, the main control module switches to a fuzzy PID composite algorithm to control the micro-pump flow rate and fan speed, and the alarm light turns off;

[0048] During system operation, flow and pressure information are sent to the host computer via the network in real time. When the pressure is >0.3MPa, the fuzzy PID control is exited, the micropump speed is set to 500rpm, and the alarm light is turned on; when the pressure is >0.7MPa, the micropump is turned off.

[0049] As one embodiment, a temperature control system based on a fuzzy PID composite algorithm, as shown in Figure 3, includes: [1] a micro pump, [2] a fan assembly, [3] a flow sensor, [4] a pressure sensor, [5] a temperature sensor, [6] a high power density component, [7] a main controller, [8] a host computer, and [9] an alarm light.

[0050] 1. Target temperature control module: high power density component.

[0051] 2. Composite heat transfer loop: The liquid phase heat transfer section is connected to the finned heat exchange section through a connecting pipe to form a closed loop of "liquid phase heat transfer section → heat exchange section → micro pump unit → liquid phase heat transfer section".

[0052] 3. Micropump unit: An electromagnetically driven micropump is selected, with a rated flow rate of 15L / min and a minimum adjustment accuracy of 0.05L / min. The speed is adjusted by PWM signal to directly control the circulation rate of the liquid phase heat transfer medium.

[0053] 4. Fan Unit: An axial flow fan with a rated speed of 15,000 rpm is selected. The fan speed is adjusted by the PWM signal output by the main control module and blows the air onto the finned heat exchange section.

[0054] 5. Main control module: It adopts an STM32F407 microcontroller with a built-in fuzzy PID composite algorithm. The preset target operating temperature of high power density components is 45℃, and the allowable temperature deviation is ±0.5℃. When the target temperature is <20℃ or >60℃, the auxiliary temperature control module is triggered to work.

[0055] 6. Temperature acquisition module: It adopts a PT1000 platinum resistance sensor (measurement range -200℃~600℃, accuracy class A), paired with an ADS1220 A / D converter (24-bit resolution), and the sampling frequency is set to 5Hz to ensure the accuracy and real-time performance of temperature data;

[0056] 7. Flow acquisition module: Employs the SM7000 flow sensor paired with the AD7656 chip to ensure the accuracy and real-time performance of flow data;

[0057] 8. Pressure Acquisition Module: Employs a PN2094 pressure sensor paired with an AD7656 chip to ensure the accuracy and real-time performance of pressure data;

[0058] 9. Fuzzy PID Control Module: The STM32F407 embedded chip is used as the core processor. The chip has a main frequency of 168MHz, supports fast calculation, and stores the fuzzy rule base and initial PID parameters (Kp0=2.5, Ki0=0.1, Kd0=0.05, which can be adjusted through the human-machine interaction module).

[0059] 8. Human-machine interaction module: The main controller communicates with the host computer via the network, supports setting the target temperature (0℃~300℃), displaying real-time temperature / control parameters, and saving commonly used parameter groups (up to 10 groups).

[0060] This invention is applicable to scenarios requiring high temperature control accuracy and response speed, such as temperature control of high power density components and heat dissipation of electronic devices. The precise liquid flow rate adjustment capability of the micropump combined with the gas heat transfer enhancement capability of the fan can form a composite temperature control mode of "precise liquid phase heat transfer speed control + efficient gas phase heat transfer assistance".

Claims

1. A temperature control system based on fuzzy PID compound algorithm, characterized in that, The target temperature control module, the composite heat transfer circuit, the micro-pump unit, the fan unit, the temperature detection module, the flow detection module, the pressure detection module and the main control module are included. The composite heat transfer circuit is in communication with the target temperature control module, and the liquid phase heat transfer medium is built-in, which is used to realize heat exchange between the target object and the outside world. The micro-pump unit is connected in series in the composite heat transfer circuit, which is used to drive the liquid phase heat transfer medium to circulate and adjust the flow rate. The fan unit is correspondingly arranged outside the heat exchange section of the composite heat transfer circuit, which is used to accelerate the gas phase heat transfer of the heat exchange section and adjust the heat exchange efficiency. The temperature detection module is arranged on the surface or in the target temperature control module, which is used to collect real-time temperature data of the target object. The flow detection module is arranged in the composite heat transfer circuit, which is used to detect the flow of the liquid in the circuit. The pressure detection module is arranged in the composite heat transfer circuit, which is used to detect the pressure of the circuit. The main control module is connected with the micro-pump unit, the fan unit and the temperature detection module, which is used to receive real-time temperature data, compare the real-time temperature data with the preset temperature threshold, and output a cooperative control signal to adjust the rotating speed of the micro-pump unit and the wind speed of the fan unit, so as to accurately control the heat transfer rate and realize the temperature stability of the target object.

2. The temperature control system based on fuzzy PID compound algorithm according to claim 1, characterized in that, The micro-pump unit is a piezoelectric driving micro-pump or an electromagnetic driving micro-pump, and the flow rate adjustment range of the liquid phase heat transfer medium is selected according to the actual situation, and the minimum adjustment precision is not less than 0.05 L / min.

3. The temperature control system based on fuzzy PID compound algorithm according to claim 1, characterized in that, The fan unit is an axial flow fan, and the wind speed adjustment range is selected according to the actual situation, and the minimum adjustment precision is not less than 0.1 m / s.

4. The temperature control system based on fuzzy PID compound algorithm according to claim 1, characterized in that, The temperature acquisition module adopts a PT1000 platinum resistance sensor, the sampling frequency is set to 1-10 Hz, the collected temperature analog signal is converted into a digital signal by an A / D converter, and then transmitted to the main control module.

5. The temperature control system based on fuzzy PID compound algorithm according to claim 1, characterized in that, It also includes an auxiliary temperature control module, which is a semiconductor refrigeration sheet, attached to the heat exchange section of the composite heat transfer circuit, and electrically connected with the main control module, which is used to assist in adjusting the temperature of the liquid phase heat transfer medium in extreme temperature scenes, and to expand the temperature control range of the system.

6. The temperature control system based on fuzzy PID compound algorithm according to claim 1, characterized in that, It also includes a human-computer interaction module, which is used to set the target temperature, display the real-time temperature and control parameters, and support parameter storage and calling.

7. The temperature control system based on fuzzy PID compound algorithm according to claim 1, characterized in that, The main control module is built-in fuzzy PID composite algorithm, according to the deviation between real-time temperature and preset temperature, dynamically allocate the adjustment weight of micro-pump unit and fan unit: when the absolute value of deviation is greater than the set threshold, the maximum flow rate of micro-pump and the wind speed of fan are synchronized; when the absolute value of deviation is less than or equal to the set threshold, the flow rate of micro-pump and the wind speed of fan are finely adjusted to avoid temperature overshoot.

8. The temperature control system based on fuzzy PID compound algorithm according to claim 7, characterized in that, The fuzzy PID control module includes a fuzzy control unit and a PID control unit: Fuzzy control unit: preset temperature deviation e, deviation rate e c Fuzzy subset ({negative large, negative medium, negative small, zero, positive small, positive medium, positive large}) and membership function, establish fuzzy rule base, according to the input e and e c Reasoning output PID parameter correction amount (ΔK p , ΔK i , ΔK d ); PID control unit: receives the actual temperature value and the set temperature value of the temperature acquisition module, calculates e and e c , combines the output of the fuzzy control unit ΔK p , ΔK i , ΔK d , dynamically updates the PID parameters, K p =K p0 +ΔK p , K i =K i0 +ΔK i , K d =K d0 +ΔK d , wherein K p0 , K i0 , K d0 are initial parameters, and a control signal is output through PID operation.

9. The temperature control system based on fuzzy PID compound algorithm according to claim 7, characterized in that, The core algorithm of the fuzzy PID control module is realized by an embedded chip, and the algorithm period is set to 50-200 ms.

10. A temperature control method based on the fuzzy PID compound algorithm based on the system of any one of claims 1-9, characterized in that, The following steps are included: Step 1: Obtain the real-time temperature of the target temperature control object through the temperature acquisition module, and transmit it to the fuzzy PID control module; Step 2: The fuzzy PID control module calculates the deviation and the rate of change of the deviation between the real-time temperature and the target temperature; Step 3: The fuzzy control unit infers the output PID parameter correction amount ΔK c and the fuzzy rule base according to e, e p , and updates the PID parameter i , ΔK d . Step 4: The PID control unit performs PID operation based on the updated parameters, and outputs a control signal to the actuator; Step 5: Limit the output control signal to prevent overshoot; Step 6: The actuator adjusts the micro-pump speed and fan speed according to the control signal to change the temperature of the target temperature control object; Step 7: Repeat steps 1-6 until the real-time temperature stabilizes within ±0.5℃ of the target temperature.

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