Temperature control system

Abstract

The invention relates to the technical field of industrial equipment temperature control, and discloses a temperature control system, which comprises a multi-source state sensing module for acquiring a power load, temperature, humidity and feedback temperature; the feed-forward prediction and analysis module is used for generating a feed-forward signal based on the load and the temperature; the closed-loop feedback and safety guarantee module is used for calculating a feedback signal according to the temperature deviation; the cooperative control decision module combines the feed-forward signal and the feedback signal to generate a fan instruction, and generates a baffle instruction for balancing heat dissipation and regeneration according to the feed-forward signal and humidity; the self-adaptive heat dissipation execution module is used for executing a fan instruction to generate cooling airflow; and the dynamic energy regeneration module executes a baffle instruction to distribute the waste gas flow direction. According to the method, the power load is introduced to serve as a prospective index, correction is conducted in combination with the environment temperature, a predictive heat dissipation control model is constructed, the system can start heat dissipation adjustment before a large amount of heat is generated, and therefore smooth and stable control over the equipment temperature is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial equipment temperature control, in particular to a temperature control system. BACKGROUND

[0002] The continuity and stability of industrial production are highly dependent on various types of power equipment, such as air compressors. In the process of converting electrical energy into mechanical energy or potential energy, these devices inevitably generate a large amount of by-product heat. The timely and effective discharge of these heat is a prerequisite for ensuring the safe operation of the equipment under rated parameters. If the temperature control fails, heat accumulation will cause a series of problems such as lubrication failure, premature aging of components, and reduced operating efficiency, which may eventually lead to unplanned downtime and affect the entire production process. Therefore, it is of direct and important significance to equip such equipment with an efficient and reliable temperature control system to ensure the safety of industrial production.

[0003] In the prior art, closed-loop control systems based on temperature feedback have been widely used to address the heat dissipation problem of equipment. Such systems obtain real-time temperature through temperature sensors deployed at key locations of the equipment and compare it with a preset temperature target value. A controller, such as a proportional-integral-derivative (PID) controller, adjusts the speed of the heat dissipation fan based on the deviation between the two, thereby changing the intensity of the cooling airflow. This control method can continuously adjust the temperature of the equipment, and in the case of relatively stable equipment load, it can maintain the equipment temperature near the target value, achieving effective temperature management and ensuring the basic operation safety of the equipment.

[0004] However, the inherent limitations of the prior art gradually emerge when dealing with complex and variable industrial environments. First, this control mechanism that relies entirely on temperature feedback is passive in nature. The heat is generated by changes in equipment load, and the response of the control system must wait for heat conduction and ultimately reflected in the change of temperature readings. This physical process has inherent time lag, so in the case of frequent load fluctuations, the control action is always slower than the actual heat dissipation demand, resulting in significant overshoot and oscillation of the equipment temperature around the target value. Second, the design goal of existing heat dissipation systems is single, i.e., simply discharging heat as waste into the environment, causing direct energy waste. Finally, some systems that integrate heat recovery functions usually have fixed heat exchange structures. This static design cannot be adjusted according to the real-time operating state of the equipment, making it difficult to balance the two performance indicators of heat recovery efficiency and maximum heat dissipation capacity, and unable to achieve a globally optimal operating strategy. Therefore, the present application proposes a temperature control system to solve the above problems. SUMMARY

[0005] In view of the deficiencies of the prior art, the temperature control system provided by the application solves the technical problems of control response lag, waste heat of heat dissipation not being effectively utilized, and inability to dynamically balance between energy saving and extreme heat dissipation performance in the prior art.

[0006] To achieve the above object, the application is implemented by the following technical solutions:

[0007] A temperature control system, comprising:

[0008] A multi-source state perception module for acquiring power load data, environmental temperature data, environmental humidity data and feedback temperature data of a controlled device in real time;

[0009] A feedforward prediction and analysis module for receiving the power load data and the environmental temperature data, analyzing and predicting future heat dissipation requirements to generate a feedforward cooling requirement signal;

[0010] A closed-loop feedback and safety guarantee module for receiving the feedback temperature data and calculating a feedback cooling requirement signal according to the deviation of a preset target temperature;

[0011] A cooperative control decision module for determining a total cooling requirement by combining the feedforward cooling requirement signal and the feedback cooling requirement signal, and generating a fan speed instruction based on the total cooling requirement, and generating a baffle position instruction for dynamically balancing between heat dissipation efficiency and energy regeneration based on the feedforward cooling requirement signal and the environmental humidity data;

[0012] An adaptive heat dissipation execution module for receiving the fan speed instruction and adjusting the speed of the fan to generate cooling air flow;

[0013] A dynamic energy regeneration module for receiving the baffle position instruction and adjusting the position of the baffle to dynamically distribute the flow direction of high-temperature exhaust gas formed after the cooling air flow passes through the radiator.

[0014] In a specific embodiment, the multi-source state perception module acquires data by the following means:

[0015] A power sensor deployed in the power supply line of the controlled device is used to acquire the power load data;

[0016] A temperature and humidity sensor deployed in the environment where the controlled device is located is used to acquire the environmental temperature data and the environmental humidity data;

[0017] A temperature sensor deployed in the radiator area of the controlled device is used to acquire the feedback temperature data.

[0018] In one embodiment, the feedforward prediction and analysis module generates the feedforward cooling demand signal by:

[0019] First, time series analysis is performed on the received power load data to calculate its variation to determine a base cooling demand;

[0020] Second, an environmental correction factor is determined based on the difference between the received environmental temperature data and a preset reference environmental temperature;

[0021] Finally, the base cooling demand and the environmental correction factor are combined to generate the feedforward cooling demand signal.

[0022] Preferably, in the step of generating the feedforward cooling demand signal by the feedforward prediction and analysis module, the value of the environmental correction factor increases as the difference between the environmental temperature data and the reference environmental temperature increases, to pre-compensate for the decrease in heat dissipation efficiency caused by the increase in environmental temperature in the feedforward stage.

[0023] In one embodiment, the closed-loop feedback and safety assurance module operates by:

[0024] First, the error between the feedback temperature data and the preset target temperature is calculated;

[0025] Second, based on the error, the feedback cooling demand signal is generated by proportional-integral-derivative control logic;

[0026] In addition, the feedback temperature data is continuously monitored, and when the feedback temperature data reaches or exceeds a preset safety upper limit temperature, a safety override instruction with the highest priority is generated and issued to the adaptive heat dissipation execution module and the dynamic energy regeneration module.

[0027] In one embodiment, the collaborative control decision module operates by:

[0028] First, the feedforward cooling demand signal and the feedback cooling demand signal are added to determine the total cooling demand;

[0029] Second, based on the total cooling demand, the fan speed instruction is generated;

[0030] Then, the priority of energy regeneration is determined according to the environmental humidity data;

[0031] Finally, the baffle position instruction is generated according to the feedforward cooling demand signal and the priority of energy regeneration.

[0032] Preferably, the step of generating the damper position command by the synergic control decision module further comprises the following logic:

[0033] when the feedforward cooling demand signal is below a preset high load threshold, generating a damper position command for closing the bypass air passage to prioritize the efficiency of energy regeneration;

[0034] when the feedforward cooling demand signal reaches or exceeds the high load threshold, generating a damper position command for opening the bypass air passage to prioritize the ability of extreme heat dissipation.

[0035] In one specific embodiment, the adaptive heat dissipation execution module comprises:

[0036] a variable frequency driver for receiving the fan rotation speed command and generating a corresponding driving power supply;

[0037] a fan connected to the variable frequency driver for generating the cooling airflow under the driving of the driving power supply.

[0038] In one specific embodiment, the dynamic energy regeneration module comprises:

[0039] a heat exchange shroud wrapping a heat sink of the controlled device, the heat exchange shroud being provided with a heat exchange passage and a bypass air passage;

[0040] a damper provided at the intersection of the heat exchange passage and the bypass air passage;

[0041] an actuator for receiving the damper position command and driving the damper to act to adjust the flow distribution of the high-temperature exhaust gas in the two passages.

[0042] Preferably, the heat exchange shroud further comprises:

[0043] a heat exchange pipeline provided in the heat exchange passage, the heat exchange pipeline being configured to exchange heat with the heat exchange pipeline by the humid hot compressed air generated by the controlled device itself when the high-temperature exhaust gas flows through the heat exchange passage.

[0044] In summary, the present application has at least one of the following beneficial technical effects:

[0045] 1. The present application introduces power load as a forward-looking indicator and combines environmental temperature for correction, to build a predictive heat dissipation control model, so that the system can start heat dissipation adjustment before a large amount of heat is generated, thereby realizing smooth and stable control of the device temperature, compared with the reactive control mode of the prior art which only relies on temperature sensor feedback, the present application overcomes the inherent response lag defect, effectively avoids the problem of repeated large fluctuations of device temperature around the set point.

[0046] 2. The present application creatively designs an internal energy regeneration loop, which captures and guides the high-temperature gas originally discarded in the heat dissipation process for non-consumption pre-drying treatment of the humid hot compressed air generated by the device itself, organically couples the heat dissipation cooling and air drying two independent energy consumption processes, realizes the energy cascade utilization inside the system, and forms an essential difference from the existing technology of directly discharging heat dissipation waste heat, causing energy waste, solving the problem of low system energy efficiency.

[0047] 3. The present application provides a set of collaborative decision-making and dynamic balance mechanism, the system actively adjusts the flow distribution of internal high-temperature waste gas based on the prediction of future load, can preferentially guarantee energy regeneration under normal working conditions, and switches to the extreme heat dissipation mode when extreme load arrives, giving the system the ability to weigh and choose between different operation targets, compared with the fixed structure of the existing heat recovery system, solving the internal contradiction that it cannot balance regular energy saving and extreme working condition performance. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 is a system function module structure diagram of the present application;

[0049] Figure 2 is a multi-source state perception module schematic diagram of the present application;

[0050] Figure 3 is a feedforward prediction and analysis module schematic diagram of the present application;

[0051] Figure 4 is a closed-loop feedback and safety guarantee module schematic diagram of the present application;

[0052] Figure 5 is a collaborative control decision-making module schematic diagram of the present application;

[0053] Figure 6 is a self-adaptive heat dissipation execution module schematic diagram of the present application;

[0054] Figure 7 is a dynamic energy regeneration module schematic diagram of the present application.

[0055] Reference signs: 10, multi-source state perception module; 20, feedforward prediction and analysis module; 30, closed-loop feedback and safety guarantee module; 40, collaborative control decision module; 50, adaptive heat dissipation execution module; 60, dynamic energy regeneration module. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the specification of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0057] Referring to the drawings Figure 1 , Figure 1 is a functional module structure block diagram of a temperature control system according to an embodiment of the present application. The temperature control system provided by the present application can include: a multi-source state perception module 10, a feedforward prediction and analysis module 20, a closed-loop feedback and safety guarantee module 30, a collaborative control decision module 40, an adaptive heat dissipation execution module 50, and a dynamic energy regeneration module 60.

[0058] The multi-source state perception module 10 is a signal input unit of the system, and the output ends thereof are connected with the input ends of the feedforward prediction and analysis module 20 and the input ends of the closed-loop feedback and safety guarantee module 30, respectively. The multi-source state perception module 10 is used to acquire power load data, environmental temperature data, environmental humidity data, and feedback temperature data of a controlled device in real time.

[0059] The feedforward prediction and analysis module 20 is used to process part of the data from the multi-source state perception module 10. Specifically, it receives the power load data and the environmental temperature data, and generates a feedforward cooling demand signal through internal analysis and calculation. The output end of the feedforward prediction and analysis module 20 is connected with the input end of the collaborative control decision module 40, and is used to transmit the generated feedforward cooling demand signal and the original environmental humidity data.

[0060] The closed-loop feedback and safety guarantee module 30 also receives data from the multi-source state perception module 10. Specifically, it receives the feedback temperature data, and calculates a feedback cooling demand signal according to the deviation of the data from a preset target temperature. The output end of the closed-loop feedback and safety guarantee module 30 is connected with the input end of the collaborative control decision module 40, and is used to transmit the generated feedback cooling demand signal. In addition, the closed-loop feedback and safety guarantee module 30 is also provided with a safety override instruction path for direct communication with the adaptive heat dissipation execution module 50 and the dynamic energy regeneration module 60.

[0061] The collaborative control decision module 40 is the system's control command generation unit. This module receives feedforward cooling demand signals and ambient humidity data from the feedforward prediction and analysis module 20, and feedback cooling demand signals from the closed-loop feedback and safety assurance module 30.

[0062] The collaborative control decision module 40 determines a total cooling demand by combining the feedforward cooling demand signal and the feedback cooling demand signal, and generates a fan speed command based on this. Simultaneously, the collaborative control decision module 40 also generates an independent baffle position command based on the feedforward cooling demand signal and ambient humidity data. The output of the collaborative control decision module 40 is connected to the input of the adaptive heat dissipation execution module 50 and the dynamic energy regeneration module 60, respectively, for issuing the fan speed command and the baffle position command.

[0063] The adaptive heat dissipation execution module 50 is used to receive the fan speed command from the cooperative control decision module 40 and adjust the fan speed according to the command to generate a cooling airflow that matches the heat dissipation requirements.

[0064] The dynamic energy regeneration module 60 receives baffle position commands from the collaborative control decision module 40 and adjusts the position of the internal baffles according to the commands. This adjustment is used to dynamically allocate the flow direction of the high-temperature exhaust gas formed after the cooling airflow generated by the adaptive heat dissipation execution module 50 passes through the radiator of the controlled equipment.

[0065] The specific implementation methods of each module in the embodiments of the present invention will be described in detail below.

[0066] See attached document Figure 2 The multi-source state sensing module 10 provides the basic data required for operational decisions of the entire temperature control system. The reliability and accuracy of this module directly affect the overall performance of the system. In one specific embodiment, the multi-source state sensing module 10 consists of three sensors with different functions and their associated circuitry.

[0067] The multi-source state sensing module 10 includes a power sensor for acquiring power load data. In one embodiment, the power sensor may be a non-invasive Hall effect current sensor or a Rogowski coil, clamped to one or more phases of the power supply cable of the controlled device, such as the main drive motor of an air compressor. This sensor is configured to monitor the line current flowing through the motor cable in real time. Power load data It can then be calculated in the following way:

[0068] ;

[0069] in, Instantaneous active power of the motor of the controlled device; Line voltage of the power supply system, which can be regarded as a known or measurable constant value in a stable power grid; Line current value measured in real time by the power sensor; Power factor of the motor under the current load, which can be measured by a more comprehensive power quality analyzer or calibrated in advance.

[0070] In other embodiments, if the power factor of the motor and the voltage do not change much in the main operating range, the measured line current value can be directly used as raw data reflecting the trend of power load change.

[0071] The multi-source state perception module 10 further includes an environment sensor for obtaining environment temperature data and environment humidity data. In an embodiment, the environment sensor is a composite sensor integrating a capacitive humidity sensing unit and a thermistor temperature sensing unit. To ensure the representativeness of the measurement data, the sensor is installed at a position in the equipment room where the air is well ventilated but the direct impact of the equipment cooling air flow is avoided, for example, near the air inlet of the equipment room. The sensor outputs a signal representing the environment temperature and a signal representing the relative humidity of the environment.

[0072] The multi-source state perception module 10 further includes a feedback temperature sensor for obtaining feedback temperature data. In an embodiment, the feedback temperature sensor can be a K-type thermocouple or a PT100 platinum resistance temperature probe, which is selected according to the operating temperature range of the radiator of the controlled device and the required response time. The installation position of the sensor is crucial for the accuracy of the feedback control. It is directly fixed to the area with the highest heat exchange efficiency of the radiator, for example, the end of the heat air exhaust of the radiator fin group, or directly attached to the outer wall of the high-temperature fluid pipeline before entering the radiator. The choice of this position ensures that the temperature measured by the sensor can most truly reflect the thermal load state of the controlled device.

[0073] All sensors convert their physical measurement values into standard industrial electrical signals (such as 4-20mA current signals) or output digital data through bus protocols (such as Modbus-RTU) through signal conditioning circuits for subsequent modules to receive and process.

[0074] Referring to the accompanying Figure 3, the feedforward prediction and analysis module 20 can be physically implemented by a software program or firmware logic block within a main controller in the temperature control system, such as a programmable logic controller (PLC) or a microcontroller unit (MCU). The feedforward prediction and analysis module 20 receives the power load data and the ambient temperature data provided by the multi-source state perception module 10, and its core function is to transform these real-time data into control signals with predictive properties.

[0075] In a specific embodiment, the feedforward prediction and analysis module 20 generates the feedforward cooling demand signal by performing the following steps:

[0076] First, the feedforward prediction and analysis module 20 performs a time series analysis on the received power load data to calculate its variation and determine the base cooling demand. Since the original power load data may contain electrical noise or transient jitter, the feedforward prediction and analysis module 20 can first perform a low-pass filtering process on the data stream, such as a moving average filter with a window size of N, to obtain a smoothed load value . Subsequently, the feedforward prediction and analysis module 20 calculates the load variation within the time window .

[0077] ;

[0078] The load variation is used to calculate the base cooling demand in the following way:

[0079] ;

[0080] wherein, is the base cooling demand, which is a dimensionless value representing the heat dissipation demand intensity caused only by the load variation; is the calculated load variation; is a preset power-heat conversion coefficient representing the heat generation rate corresponding to a unit power variation of the controlled device, which can be determined by calibrating the thermodynamic properties of the specific device.

[0081] This step realizes the transformation of the future trend of the device load into a quantifiable heat dissipation demand.

[0082] Secondly, the feedforward prediction and analysis module 20 determines an ambient correction factor based on the difference between the received ambient temperature data and a preset reference ambient temperature . Reference ambient temperature is a reference temperature for system design, such as 25 degrees Celsius.Ambient correction factor is calculated as follows:

[0083]

[0084] wherein, is the ambient correction factor; is the real-time acquired ambient temperature data; is the preset reference ambient temperature; is a positive temperature influence coefficient, whose magnitude determines the sensitivity of the ambient temperature to the correction of the heat dissipation requirement; The function ensures that only when the ambient temperature exceeds the reference temperature, the correction factor will be greater than 1, thereby increasing the cooling requirement.

[0085] This step realizes adaptive compensation for changes in ambient temperature.

[0086] Finally, the feedforward prediction and analysis module 20 combines the basic cooling requirement with the ambient correction factor to generate the final feedforward cooling requirement signal . The specific combination operation is multiplication:

[0087]

[0088] wherein, is the final generated feedforward cooling requirement signal. This signal integrates information in two dimensions of device load change and environmental heat dissipation conditions.

[0089] After completing the calculation, the feedforward prediction and analysis module 20 outputs the value of together with the ambient humidity data received from the multi-source state perception module 10 but not processed in this module to the collaborative control decision module 40.

[0090] Referring to the accompanying drawings, Figure 4 the closed-loop feedback and safety assurance module 30 can also be physically implemented by a software program or firmware logic block within the main controller of the temperature control system. The core function of the closed-loop feedback and safety assurance module 30 is to correct the results of the feedforward control, eliminate steady-state errors, and provide decisive safety assurance for the entire system. The closed-loop feedback and safety assurance module 30 receives feedback temperature data provided by the multi-source state perception module 10.

[0091] ​In one embodiment, the closed-loop feedback and safety assurance module 30 first performs a feedback correction function. The closed-loop feedback and safety assurance module 30 is preprogrammed with a desired target temperature value , which is the stable operating temperature point that the system is expected to maintain. The closed-loop feedback and safety assurance module 30 continuously calculates the error between the feedback temperature data and the preprogrammed target temperature :

[0092] ;

[0093] wherein, is the temperature error at time ; is the preprogrammed target temperature; is the real-time feedback temperature data obtained at time .

[0094] The error is input into a proportional-integral-derivative (PID) control logic to generate a feedback cooling demand signal . In a discrete-time implementation, it is calculated as follows:

[0095] ;

[0096] wherein, is the feedback cooling demand signal generated at time ; , and are the proportional, integral, and derivative gain coefficients of the PID controller, which are tuned during system commissioning according to the thermal inertia of the controlled device; is the computation period of the controller.

[0097] This step generates a feedback control signal for accurate temperature correction by synthesizing the current error, the cumulative historical error, and the error rate of change.

[0098] After the calculation, the closed-loop feedback and safety assurance module 30 outputs the value of to the collaborative control decision module 40.

[0099] In addition, the closed-loop feedback and safety assurance module 30 also performs a key safety assurance function. The closed-loop feedback and safety assurance module 30 is preprogrammed with an absolute safety upper limit temperature , which is higher than the target temperature . The closed-loop feedback and safety assurance module 30 continuously compares the real-time feedback temperature data with the safety upper limit temperature Comparison is made.

[0100] Once the condition is met , the closed-loop feedback and safety assurance module 30 immediately triggers a safety override mechanism. Under this mechanism, the closed-loop feedback and safety assurance module 30 will generate and issue a safety override instruction with the highest system priority.

[0101] The instruction will be sent directly to the adaptive cooling execution module 50 and the dynamic energy regeneration module 60 through a dedicated instruction channel, forcing them to perform maximum cooling actions, specifically: forcing the fan in the adaptive cooling execution module 50 to reach maximum speed, while forcing the baffle in the dynamic energy regeneration module 60 to fully open the bypass air duct. This state will remain until the feedback temperature falls below a preset safety recovery temperature, after which control authority is returned to the collaborative control decision module 40.

[0102] Referring to the accompanying Figure 5 , the collaborative control decision module 40 can also be physically implemented by a software program or firmware logic block within the main controller in the temperature control system. The collaborative control decision module 40 is the instruction generation center of the entire system, responsible for integrating the analysis results of upstream modules and generating collaborative control instructions for downstream execution modules. The input signals of the collaborative control decision module 40 include: the feedforward cooling demand signal and environmental humidity data from the feedforward prediction and analysis module 20, and the feedback cooling demand signal from the closed-loop feedback and safety assurance module 30.

[0103] In a specific embodiment, the collaborative control decision module 40 generates and issues instructions by performing the following steps:

[0104] First, the collaborative control decision module 40 performs an additive operation on the received feedforward cooling demand signal and the feedback cooling demand signal to determine the total cooling demand required by the system at the moment:

[0105] ;

[0106] wherein is the total cooling demand, which is a dimensionless value that combines predictive adjustment and feedback correction.

[0107] Second, the collaborative control decision module 40 generates a fan speed instruction based on the calculated total cooling demand . In an embodiment, the instruction It is a frequency setpoint output to the variable frequency drive. This generation process uses a preset mapping function. accomplish:

[0108] ;

[0109] Mapping function dimensionless The values ​​are mapped linearly or non-linearly to the operating frequency range of the variable frequency drive (e.g., 0-50Hz) and include output limiting logic to ensure that the generated frequency commands do not exceed the rated operating range of the fan motor.

[0110] Then, the collaborative control decision module 40 determines the environmental humidity based on the received data. To determine the priority of energy regeneration In one embodiment, this priority is quantized as a value between 0 and 1, calculated as follows:

[0111] ;

[0112] in, It serves as a priority index for energy regeneration; For real-time acquisition of ambient relative humidity; and These are preset humidity thresholds, representing environmental humidity conditions that are completely unnecessary and most necessary for energy regeneration, respectively. The function limits the calculation result to the interval [0,1].

[0113] Finally, the collaborative control decision module 40 determines the cooling demand signal based on the feedforward cooling demand signal. and the calculated energy regeneration priority The baffle position command is generated through a multivariate decision logic. The decision logic has a built-in preset high load threshold. .

[0114] when The value is lower than this high load threshold At that time, the baffle position command generated by the collaborative control decision module 40 By closing the bypass ventilation duct with the drive baffle, all the high-temperature exhaust gas flows through the heat exchange channel, at which point the energy regeneration efficiency is at its highest.

[0115] when The value reaches or exceeds the high load threshold. At that time, the baffle position command generated by the collaborative control decision module 40 Fully open the drive baffle to reduce system air resistance; at this point, the system's maximum heat dissipation capacity is at its strongest.

[0116] In a preferred embodiment, when The value is close to the high load threshold. Within a transition range, the opening degree of the baffle will be simultaneously affected by... The impact. Higher. The value will make the baffle more inclined to remain in the closed bypass vent state, so as to extend the working time of energy regeneration while meeting basic heat dissipation requirements.

[0117] After completing the above calculations, the collaborative control decision module 40 will generate the fan speed command. and baffle position instructions The outputs are respectively sent to the adaptive heat dissipation execution module 50 and the dynamic energy regeneration module 60.

[0118] See attached document Figure 6 The adaptive heat dissipation execution module 50 is a physical unit that performs temperature regulation operations. Its function is to convert the electrical commands generated by the cooperative control decision module 40 into cooling airflow with a specific intensity.

[0119] In one specific embodiment, the adaptive thermal execution module 50 includes a variable frequency drive and a fan.

[0120] The variable frequency drive is used to receive fan speed commands from the collaborative control decision module 40. The instruction can be an analog signal, such as a 4-20mA current signal or a 0-10V voltage signal, or a digital setting value transmitted via an industrial bus (such as Modbus or CANopen). The microprocessor inside the frequency converter driver parses the instruction and generates a set of three-phase AC power with adjustable frequency and voltage as the drive power supply according to its preset voltage / frequency (V / f) curve.

[0121] The fan is an industrial fan matched to the radiator of the controlled equipment. In one embodiment, to overcome the air resistance generated by the radiator fins and the channels within the baffle, a centrifugal fan or a vortex fan with high air pressure characteristics can be selected. The three-phase asynchronous motor of the fan is electrically connected to the output terminals of the frequency converter driver.

[0122] The module's workflow is as follows: The frequency converter receives the instruction. Then, a drive power supply of the corresponding frequency is output to the fan motor. The fan motor speed... It is approximately proportional to the power supply frequency. According to the fan law, the air volume of the cooling airflow generated by the fan... It is directly proportional to the motor speed, while the wind pressure The cooling air flow is then proportional to the square of the motor speed. In this way, the module converts an electrical control command into a cooling air flow with a specific flow rate and pressure. The cooling air flow is directed to the heat sink of the controlled equipment, and removes heat by forced convection.

[0123] In addition, the adaptive cooling execution module 50 is also configured to receive a safety override command from the closed-loop feedback and safety assurance module 30. When receiving the command, the frequency drive will ignore the regular command from the coordinated control decision module 40, and immediately raise its output frequency to a pre-set maximum safe operating frequency, so as to drive the fan to dissipate heat at maximum capacity.

[0124] Referring to the drawings Figure 7 The dynamic energy regeneration module 60 is a physical assembly that implements the dynamic switching between energy recovery and heat dissipation modes.

[0125] In one specific embodiment, the dynamic energy regeneration module 60 includes a heat exchange shroud, a baffle, an actuator, and a heat exchange pipeline.

[0126] The heat exchange shroud is a metal or composite shell that is used to wrap the heat sink of the controlled equipment. Its inlet is connected to the air outlet of the heat sink, and is used to collect all the high-temperature exhaust gas generated by the adaptive cooling execution module 50 after passing through the heat sink. Inside the shroud, one or more partitions are provided to divide the internal cavity of the shroud into a heat exchange channel and a bypass air duct. The path of the heat exchange channel is designed to be relatively tortuous, so as to increase the residence time of the gas therein. The path of the bypass air duct is designed to be relatively straight, so as to constitute a low-flow-resistance discharge path.

[0127] The baffle is provided at the intersection of the inlet of the heat exchange channel and the bypass air duct. In one embodiment, the baffle can be a valve plate that rotates around an axis. When the baffle is rotated to a position, it can completely close the inlet of the heat exchange channel, so that all the high-temperature exhaust gas flows out from the bypass air duct. When the baffle is rotated to another position, it can completely close the inlet of the bypass air duct, so that all the high-temperature exhaust gas is introduced into the heat exchange channel.

[0128] The actuator is used to receive the baffle position command from the coordinated control decision module 40 and drive the baffle to act. In one embodiment, the actuator can be a stepper motor or a servo motor, which is connected to the rotating shaft of the baffle through a set of link mechanisms, so as to realize precise control of the opening angle of the baffle.

[0129] The heat exchange pipeline is arranged inside the heat exchange passage. The pipeline is an independent, sealed metal pipeline, and its inlet and outlet are connected with the high-pressure wet hot air pipeline of the controlled equipment (for example, an air compressor) respectively. Specifically, the heat exchange pipeline is used to preheat the high-temperature, high-humidity compressed air generated by the controlled equipment itself in the compression process by the heat carried by the high-temperature exhaust gas in the heat exchange passage.

[0130] The working process of the dynamic energy regeneration module 60 is as follows: when it receives an instruction for closing the bypass air duct, the actuator drives the baffle to close the bypass air duct inlet, and all the high-temperature exhaust gas is forced to flow into the heat exchange passage. When the exhaust gas flows through the passage, the heat carried by the exhaust gas is transferred to the wet hot compressed air flowing in the pipeline through the outer wall of the heat exchange pipeline in the form of convection and conduction, so as to preheat the compressed air and reduce the relative humidity of the compressed air. When the module receives an instruction for opening the bypass air duct, the actuator drives the baffle to open the bypass air duct inlet, and the high-temperature exhaust gas will be preferentially discharged from the low-resistance passage, thereby reducing the back pressure of the whole system, so that the adaptive heat dissipation execution module 50 can cool the radiator with the maximum air volume.

[0131] Similarly, the dynamic energy regeneration module 60 is also configured to receive a safety override instruction from the closed-loop feedback and safety guarantee module 30. When receiving the instruction, the actuator will ignore the regular instruction from the collaborative control decision module 40 and forcibly drive the baffle to the position of completely opening the bypass air duct to cooperate with the system to perform the maximum heat dissipation action.

[0132] In order to further illustrate the collaborative working process of the technical scheme of the present application, the following will be described through a specific working scene example.

[0133] The application object of the embodiment is an industrial air compressor deployed in a manufacturing workshop. The preset parameters of the temperature control system are as follows: the target temperature is 85℃, the safety upper limit temperature is 95℃, the high load threshold is set to a specific value, and the reference environment temperature is 25℃.

[0134] The system is powered on and initialized, and the air compressor is in a stable low load running state. At this time, the power load data obtained by the multi-source state perception module 10 is low and stable, the feedback temperature is stabilized at 84℃. The load change calculated by the feedforward prediction and analysis module 20 is close to zero, so the feedforward cooling demand signal output by the feedforward prediction and analysis module 20 It is also close to zero. The closed-loop feedback and safety assurance module 30 calculates a small positive error (85℃-84℃), and its PID controller outputs a small positive feedback cooling demand signal. To maintain thermal balance. The collaborative control decision module 40 will handle minute... and Adding them together, we get a lower total cooling requirement. Based on this, a low fan speed command is generated. At the same time, due to Well below the high load threshold The collaborative control decision module 40 generates a baffle position command for closing the bypass ventilation duct. The adaptive cooling module 50 operates the fan at a low speed. The baffle of the dynamic energy regeneration module 60 closes the bypass duct, and all high-temperature exhaust gas flows through the heat exchange channel to preheat the humid compressed air generated by the compressor itself.

[0135] A large pneumatic device in the workshop starts up, and the load on the air compressor increases rapidly. The power sensor of the multi-source state sensing module 10 immediately detects the power load data. The temperature increases sharply. Due to the thermal inertia of the equipment, the feedback temperature at this time... No significant changes have occurred yet. The feedforward prediction and analysis module 20 calculates a large positive load change. This generates a significant base cooling demand. Combined with the ambient temperature at the time, which was above the reference value of 25°C. This module calculates an environmental correction factor greater than 1. Ultimately, this outputs a signal indicating a significantly increased feedforward cooling demand. After receiving the signal, the collaborative control decision module 40 calculates the total cooling demand. This resulted in a significant increase, immediately generating a high fan speed command. The adaptive thermal execution module 50 rapidly increases the fan speed, providing enhanced cooling airflow before the equipment temperature begins to rise significantly.

[0136] Multiple pneumatic devices are operating simultaneously in the workshop, with air compressors reaching full load. The feedforward prediction and analysis module 20 calculates the feedforward cooling demand signal. The value exceeded the preset high load threshold. At this point, while maintaining the high fan speed command, the internal decision-making logic of the collaborative control decision module 40 is triggered. The collaborative control decision module 40 generates a new baffle position command. , which is used to fully open the bypass air passage. The actuator of the dynamic energy regeneration module 60 receives the instruction and drives the shutter to switch the high-temperature exhaust gas from the heat exchange passage to the bypass air passage with low resistance for direct discharge. In this working condition, the system temporarily stops the energy regeneration function in exchange for the lowest system air resistance, thereby ensuring that the adaptive cooling execution module 50 can output the maximum cooling airflow and ensuring the temperature safety of the equipment under extreme load.

[0137] After a maintenance failure, the air inlet of the radiator is partially blocked, resulting in a decrease in the system cooling capacity. Although the adaptive cooling execution module 50 has been running at a high speed, the feedback temperature continues to rise and eventually reaches the safety upper limit temperature of 95°C . The closed-loop feedback and safety guarantee module 30 immediately detects this condition and triggers the safety override mechanism. The closed-loop feedback and safety guarantee module 30 sends a safety override instruction with the highest priority to the adaptive cooling execution module 50 and the dynamic energy regeneration module 60 through a dedicated instruction channel. The frequency converter of the adaptive cooling execution module 50 immediately drives the fan to the highest speed at the physical limit. The actuator of the dynamic energy regeneration module 60 also forces the shutter to remain in the position of fully opening the bypass air passage. This forced maximum cooling state will continue to run until the fault is eliminated, the feedback temperature falls within the safety range.

[0138] The embodiments of the specific implementation are the preferred embodiments of the present application, and are not limited to the protection scope of the present application, wherein the same parts are denoted by the same reference numerals. Therefore: any equivalent changes made according to the structure, shape, principle of the present application should be covered within the protection scope of the present application.

Claims

1. A temperature control system, characterized by, The method comprises the following steps: a multi-source state perception module is configured to acquire power load data, ambient temperature data, ambient humidity data and feedback temperature data of a controlled device in real time; a feedforward prediction and analysis module is configured to receive the power load data and the ambient temperature data, analyze and predict future heat dissipation demand to generate a feedforward cooling demand signal; a closed-loop feedback and safety guarantee module is configured to receive the feedback temperature data and calculate a feedback cooling demand signal according to the deviation of a preset target temperature; a collaborative control decision module is configured to determine total cooling demand by combining the feedforward cooling demand signal and the feedback cooling demand signal, and generate a fan speed instruction based on the total cooling demand; and generate a baffle position instruction for dynamically balancing between heat dissipation efficiency and energy regeneration based on the feedforward cooling demand signal and the ambient humidity data; an adaptive heat dissipation execution module is configured to receive the fan speed instruction and adjust the speed of the fan to generate cooling airflow; a dynamic energy regeneration module is configured to receive the baffle position instruction and adjust the position of the baffle to dynamically allocate the flow direction of high-temperature exhaust gas formed after the cooling airflow passes through the radiator.

2. The temperature control system of claim 1, wherein, The multi-source state perception module is configured to perform the following steps: acquire the power load data through a power sensor deployed on the power supply line of the controlled device; acquire the ambient temperature data and the ambient humidity data through a temperature and humidity sensor deployed in the environment where the controlled device is located; acquire the feedback temperature data through a temperature sensor deployed in the radiator area of the controlled device.

3. The temperature control system of claim 1, wherein, The feedforward prediction and analysis module is configured to perform the following steps: perform time series analysis on the received power load data, calculate the change amount to determine the basic cooling demand; determine an environmental correction factor according to the difference between the received ambient temperature data and a preset reference ambient temperature; combine the basic cooling demand and the environmental correction factor to generate the feedforward cooling demand signal.

4. A temperature control system according to claim 3, wherein, The feedforward prediction and analysis module generates the feedforward cooling demand signal by performing the following steps: The value of the environmental correction factor increases as the difference between the ambient temperature data and the reference ambient temperature increases, to pre-compensate for the decrease in heat dissipation efficiency caused by the increase in ambient temperature in the feedforward stage.

5. The temperature control system of claim 1, wherein, The closed-loop feedback and safety guarantee module is configured to perform the following steps: calculate the error between the feedback temperature data and the preset target temperature; generate the feedback cooling demand signal through proportional-integral-derivative control logic based on the error; continuously monitor the feedback temperature data, and when the feedback temperature data reaches or exceeds a preset safety upper limit temperature, generate and issue a safety override instruction with the highest priority to the adaptive heat dissipation execution module and the dynamic energy regeneration module.

6. The temperature control system of claim 1, wherein, The collaborative control decision module is configured to perform the following steps: perform addition operation on the feedforward cooling demand signal and the feedback cooling demand signal to determine the total cooling demand; generate the fan speed instruction based on the total cooling demand; determine the priority of energy regeneration according to the ambient humidity data; The baffle position instruction is generated according to the feedforward cooling demand signal and the priority of the energy regeneration.

7. A temperature control system according to claim 6, wherein, The step of generating the baffle position instruction by the cooperative control decision module further comprises: When the feedforward cooling demand signal is lower than a preset high-load threshold, a baffle position instruction for closing the bypass air duct is generated to prioritize the efficiency of energy regeneration; When the feedforward cooling demand signal reaches or exceeds the high-load threshold, a baffle position instruction for opening the bypass air duct is generated to prioritize the ability of extreme heat dissipation.

8. The temperature control system of claim 1, wherein, The adaptive heat dissipation execution module comprises: a variable frequency driver configured to receive the fan rotating speed instruction and generate a corresponding driving power supply; a fan connected to the variable frequency driver and configured to generate the cooling airflow under the driving of the driving power supply.

9. The temperature control system of claim 1, wherein, The dynamic energy regeneration module comprises: a heat exchange fairing configured to wrap a heat sink of the controlled device, the heat exchange fairing being provided with a heat exchange passage and a bypass air duct; a baffle provided at the intersection of the heat exchange passage and the bypass air duct; an actuator configured to receive the baffle position instruction and drive the baffle to act to adjust the flow distribution of the high-temperature exhaust gas in the heat exchange passage and the bypass air duct.

10. A temperature control system according to claim 9, wherein, The heat exchange fairing further comprises: a heat exchange pipeline provided in the heat exchange passage, the heat exchange pipeline being configured to exchange heat with the heat exchange pipeline by the high-temperature exhaust gas when flowing through the heat exchange passage through the humid and hot compressed air generated by the controlled device itself.

Images