Foaming reaction kettle carbon dioxide circulation temperature control system

Abstract

The application provides a foaming reaction kettle carbon dioxide circulation temperature control system, and relates to the technical field of equipment temperature control. The system comprises an acquisition module, a first calculation module, a second calculation module, a third calculation module, an establishment module, a fourth calculation module, a fifth calculation module and an adjustment module. The acquisition module is used for acquiring temperature data of the foaming reaction kettle and transmitting the temperature data to a temperature controller. The first calculation module is used for calculating an error of the temperature in the kettle and an environmental disturbance. The second calculation module is used for calculating a time integral of the error of the temperature in the kettle within a first preset time length. The third calculation module is used for calculating a Lagrange function, a Rayleigh dissipation function and a non-conservative generalized force of the foaming reaction kettle. The establishment module is used for combining the Lagrange function, the Rayleigh dissipation function and the non-conservative generalized force to establish a closed-loop error dynamics equation of the foaming reaction kettle. The fourth calculation module is used for calculating a temperature expected change rate of the foaming reaction kettle according to the closed-loop error dynamics equation. The fifth calculation module is used for calculating an optimized heating power of the foaming reaction kettle. The adjustment module is used for adjusting the foaming reaction kettle according to the optimized heating power.

Description

Technical Field

[0001] This invention relates to the field of equipment temperature control technology, and in particular to a carbon dioxide circulation temperature control system for a foaming reactor. Background Technology

[0002] A foaming reactor is a specialized piece of equipment used in the production of foamed materials, widely applied in industries such as polyurethane, resins, foamed plastics, and new insulation materials. Its main function is to complete processes such as material mixing, chemical reaction, foaming, heating, and stirring in a closed environment. Reactors typically possess functions such as pressure resistance, corrosion resistance, temperature control, and automatic stirring to ensure uniform and stable foaming reactions, improving product quality and production efficiency. Carbon dioxide circulation temperature control in foaming reactors is a temperature control method used to regulate the internal temperature of the reactor. By controlling the heating, cooling, and maintaining a constant temperature during the foaming process, the stable foaming reaction is ensured, avoiding product defects caused by temperature fluctuations.

[0003] Foaming reactions are typically extremely sensitive to temperature changes. Excessive heat can lead to material decomposition, uneven bubble formation, or product deformation, while insufficient heat can negatively impact reaction speed and foaming effectiveness. Circulating temperature control not only enables rapid and precise temperature regulation but also offers advantages such as high heat transfer efficiency, energy saving, environmental friendliness, and stable operation. This effectively improves product quality consistency, reduces energy consumption and production risks, extends equipment lifespan, and enhances overall production automation and safety.

[0004] However, most existing foaming reaction equipment relies on fixed parameter adjustment for circulating temperature control. In actual operation, when the material reaction is highly exothermic or the external environment changes, the system can only make lagging corrections based on the current temperature deviation. It is difficult to reflect the temperature change trend and heat accumulation effect in a timely manner, which can easily lead to problems such as slow temperature control response, large temperature fluctuations and local overheating. This results in decreased foaming uniformity and insufficient product stability. At the same time, under complex working conditions, it can also easily cause low energy utilization efficiency and poor equipment operation stability. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a carbon dioxide circulating temperature control system for a foaming reactor. This system can solve the problem that the circulating temperature control methods of foaming reaction equipment in the prior art mostly rely on fixed parameter adjustment. In actual operation, when the material reaction is highly exothermic or the external environment changes, the system can often only make lagging corrections based on the current temperature deviation, making it difficult to reflect the temperature change trend and heat accumulation effect in a timely manner. This can easily lead to problems such as slow temperature control response, large temperature fluctuations, and local overheating, which in turn leads to decreased foaming uniformity and insufficient product stability. At the same time, under complex working conditions, it can also easily cause low energy utilization efficiency and poor equipment operation stability.

[0006] This invention provides a carbon dioxide circulating temperature control system for a foaming reactor, applied to a foaming reactor connected to a temperature controller; the system includes: The acquisition module is used to acquire temperature data from the foaming reactor and transmit the temperature data to the temperature controller. The first calculation module is used to calculate the internal temperature error and environmental disturbance based on the temperature data. The second calculation module is used to calculate the time integral of the temperature error inside the vessel over a first preset time period; The third calculation module is used to treat the disturbed foaming reactor as a disturbed damped co-oscillator, and use the integral result as a generalized coordinate and the temperature error as a generalized velocity to calculate the Lagrangian function, Rayleigh dissipation function and nonconservative generalized force of the foaming reactor. A module is established to combine the Lagrangian function, Rayleigh dissipation function, and nonconservative generalized force to establish the closed-loop error kinetic equation of the foaming reactor; The fourth calculation module is used to calculate the expected rate of temperature change in the foaming reactor based on the closed-loop error kinetic equation. The fifth calculation module is used to calculate the optimal heating power of the foaming reactor based on the expected rate of temperature change. An adjustment module is used to adjust the foaming reactor according to the optimized heating power.

[0007] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: In this embodiment of the invention, by real-time acquisition of temperature changes during the foaming reaction and combined analysis with thermal disturbances caused by the external environment, the system can not only sense the current temperature state but also identify the development trend of temperature changes and the heat accumulation process. Based on this, the foaming reaction process is abstracted as a dynamic motion system with energy transfer and dissipation characteristics. Temperature changes are no longer considered simply as deviations but as a continuously evolving dynamic behavior, thus more accurately reflecting the coupling relationship between heat generation, transfer, and attenuation during the foaming reaction. Subsequently, by constructing a closed-loop error kinetic equation reflecting the dynamic equilibrium relationship of the system, the direction and rate of temperature change are predicted, and the heating output is dynamically corrected accordingly. This allows the heating process to adapt to the intensity of exothermic reaction and environmental changes in advance, rather than compensating for adjustments after significant temperature deviations. This effectively reduces temperature fluctuations and adjustment lag, avoids overheating caused by localized heat accumulation, improves the uniformity of the thermal field and reaction stability during the foaming process, and results in a more uniform cell structure and higher product consistency. Meanwhile, since the heating output can be dynamically optimized according to actual heat demand, it can also reduce ineffective energy consumption, improve overall energy utilization efficiency, and enhance the equipment's ability to operate continuously and stably under complex working conditions. Attached Figure Description

[0008] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0009] Figure 1 This is a schematic diagram of a carbon dioxide circulation temperature control system for a foaming reactor provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of another carbon dioxide circulation temperature control system for a foaming reactor provided in an embodiment of the present invention. Detailed Implementation

[0010] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0011] The carbon dioxide circulating temperature control system for the foaming reactor provided in this invention will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0012] Reference manual attached Figure 1 The diagram shows a schematic of a carbon dioxide circulating temperature control system for a foaming reactor provided in an embodiment of the present invention.

[0013] Reference manual attached Figure 2 The diagram shows a structural schematic of another carbon dioxide circulating temperature control system for a foaming reactor provided in an embodiment of the present invention.

[0014] This invention provides a carbon dioxide circulation temperature control system for a foaming reactor, which is applied to a foaming reactor connected to a temperature controller; Understandably, establishing a communication connection with the temperature controller allows the temperature controller to receive real-time temperature information inside the reactor and automatically adjust the heating, cooling, or circulation processes according to temperature changes, thereby ensuring that the foaming reaction process is in a suitable and stable temperature environment.

[0015] The system includes: Module 1 is used to acquire temperature data of the foaming reactor and transmit the temperature data to the temperature controller. In one possible implementation, the temperature data includes the target vessel internal temperature, the real-time vessel internal temperature, the real-time ambient temperature, the nominal ambient temperature, and the maximum permissible deviation of the vessel internal temperature.

[0016] The nominal ambient temperature refers to the standard value of the external ambient temperature that the system presets or defaults to under the design operating conditions of the foaming reactor. It serves as a benchmark for judging whether the external environment has changed significantly. The maximum permissible deviation of the reactor internal temperature refers to the maximum allowable deviation of the actual temperature inside the foaming reactor from the target temperature. It is used to limit the safe and stable operation boundary of the temperature control system. When the actual temperature deviation exceeds this permissible range, it indicates that the current thermal state may affect the stability of the foaming reaction, the uniformity of the cell structure, or the safe operation of the equipment. Therefore, the system needs to make timely adjustments or issue an early warning. By setting the maximum permissible deviation of the reactor internal temperature, it is possible to avoid excessively high temperatures leading to localized overheating, deterioration of material properties, or reaction instability. At the same time, it is also possible to prevent excessively low temperatures leading to incomplete reaction and unstable foaming effect, thereby ensuring that the foaming process is always in a suitable and controllable thermal environment.

[0017] In one possible implementation, the internal temperature error is specifically the quotient of the internal temperature deviation and the maximum permissible internal temperature deviation, wherein the internal temperature deviation is specifically the difference between the target internal temperature and the real-time internal temperature.

[0018] In one possible implementation, the environmental disturbance is specifically the difference between the real-time ambient temperature and the nominal ambient temperature.

[0019] It should be noted that by using the difference between the target internal temperature and the real-time internal temperature as the internal temperature deviation, the degree to which the current thermal state deviates from the ideal temperature state can be directly reflected. Furthermore, by comparing the internal temperature deviation with the maximum permissible internal temperature deviation, an internal temperature error with a unified reference standard can be obtained, thus facilitating the system to more accurately determine whether the current temperature deviation is close to the safe or stable operating boundary. Simultaneously, by calculating the difference between the real-time ambient temperature and the nominal ambient temperature, the environmental disturbance can be obtained, reflecting the degree of impact of external environmental changes on the heat balance of the foaming reaction. Because this method considers both internal temperature deviation and external environmental changes, it enables the system to more comprehensively identify the sources of thermal state changes, thereby improving the accuracy, stability, and timeliness of subsequent temperature regulation.

[0020] The first calculation module 2 is used to calculate the internal temperature error and environmental disturbance based on the temperature data. The internal temperature error refers to the difference between the actual detected temperature inside the foaming reactor and the preset target temperature. This difference reflects the degree to which the current foaming reaction process deviates from the ideal thermal state. If the actual temperature is higher than the target temperature, it indicates that the reaction system is overheating; if the actual temperature is lower than the target temperature, it indicates that the reaction system is underheating. Therefore, the internal temperature error can directly characterize whether the current temperature control state is stable. Environmental disturbance refers to the degree of influence of external environmental factors on the internal thermal state of the foaming reactor. For example, changes in ambient temperature, equipment heat dissipation, raw material state fluctuations, and changes in circulating medium flow rate can all cause changes in the internal thermal balance of the reactor. Environmental disturbance is used to characterize the strength of these external factors' interference with the temperature system, enabling the system to identify temperature changes not caused by the reaction itself.

[0021] By analyzing the collected temperature data, the system can simultaneously determine the degree to which the current temperature deviates from the target state and the impact of external factors on the thermal state. This allows the system to not only understand whether the current temperature is stable but also identify the causes of temperature changes. Since heat is continuously generated during the foaming reaction, and the external environment constantly affects the heat exchange process, adjusting solely based on the current temperature can easily lead to response lag. However, by simultaneously introducing environmental disturbance analysis, the system can anticipate trends in thermal state changes, making subsequent adjustments more targeted and predictive. This not only improves the accuracy of temperature control but also reduces temperature fluctuations and localized overheating, thereby enhancing the stability of the foaming process and the consistency of product quality.

[0022] The second calculation module 3 is used to calculate the time integral of the temperature error inside the vessel over a first preset time period; Specifically, by accumulating the temperature error within the reactor over a period of time, the system can reflect not only the current temperature deviation but also the cumulative degree of temperature deviation over a continuous period. Time integration refers to accumulating the continuous change in temperature error over time to obtain the long-term trend of thermal changes. The first preset duration refers to the time range used to observe the temperature change process, reflecting the overall characteristics of temperature fluctuations during a continuous operation. Because the foaming reaction involves continuous heat release and slow heat accumulation, relying solely on instantaneous temperature changes can easily overlook the impact of long-term heat accumulation. However, by performing time-cumulative analysis of temperature errors, the system can identify the trend of continuous temperature deviation in advance, making subsequent adjustments more stable and precise. Therefore, this method effectively reduces control lag, minimizes repeated temperature fluctuations, and improves the thermal balance stability and product quality consistency during the foaming reaction.

[0023] It should be noted that those skilled in the art can set the size of the first preset duration according to actual needs, and this invention does not limit this. Optionally, a time interval of 30 seconds or 60 seconds from the current time can be set. The time integration formula is as follows: , Represents the integral variable. This represents the temperature error at the point of integration. Indicates the initial time of integration. Indicates the current moment. - Indicates the duration of integration.

[0024] The third calculation module 4 is used to treat the disturbed foaming reactor as a disturbed damped co-oscillator, and use the integral result as a generalized coordinate and the temperature error as a generalized velocity to calculate the Lagrangian function, Rayleigh dissipation function and nonconservative generalized force of the foaming reactor. Among them, the disturbed damped co-oscillator refers to a model subjected to the combined effects of external disturbances, internal energy loss, and coupled vibrations. It is used to describe the dynamic fluctuation characteristics exhibited by the internal temperature of the foaming reactor as it changes over time. The generalized coordinate is a parameter used to describe the overall state change of the system. The generalized velocity is the rate of change of the generalized coordinate with time, used to characterize the speed of the system's state change. The Lagrangian function is a function used to describe the energy distribution relationship of the system, essentially reflecting the relationship between the system's internal energy storage state and its dynamic change state. In the foaming reaction process, it can reflect the dynamic balance between heat accumulation and thermal change. The Rayleigh dissipation function is a function used to describe the internal energy loss process of the system. In the foaming reactor, heat is continuously lost due to heat transfer, heat dissipation, and material exchange; therefore, the Rayleigh dissipation function can reflect the impact of the thermal decay process on the dynamic changes of the system. Non-conservative generalized force refers to the force formed by the continuous input or consumption of energy from the outside, corresponding to external forces that cannot be fully recovered through the system's internal energy storage. In this scheme, it is used to represent the continuous impact of factors such as changes in ambient temperature, external thermal disturbances, and heating input on the foaming reaction system.

[0025] It should be noted that the third calculation module equates the foaming reaction process to a system with the combined effects of energy transfer, energy loss, and external disturbances, enabling a unified dynamic description of temperature changes. Here, generalized coordinates reflect the long-term heat accumulation state, generalized velocity reflects the current thermal trend, and the Lagrangian function, Rayleigh dissipation function, and non-conservative generalized force correspond to the internal energy distribution, energy decay, and external energy interaction processes, respectively. By jointly calculating these dynamic relationships, the system can not only analyze the current temperature state but also identify the energy evolution patterns behind temperature changes, thus more accurately predicting the thermal trend. This allows subsequent temperature control adjustments to adapt to changes in foaming heat release and the environment in advance, reducing control lag, minimizing temperature fluctuations and localized overheating, and improving the uniformity of the thermal field, operational stability, and product quality consistency during the foaming reaction process.

[0026] In one possible implementation, the third computing module 4 is specifically used for: S401: Construct the Lagrangian function by combining generalized coordinates and generalized velocity; The formula for the Lagrange function is as follows: ; in, Represents the value of the Lagrange function. Indicates virtual inertia, Indicates virtual stiffness, Indicates the result of integration; Virtual inertia refers to an equivalent parameter used to characterize the sustained influence of temperature changes on the system state, similar to the inertial characteristics of a moving system. A larger virtual inertia indicates that the system's temperature change is less likely to suddenly accelerate or decelerate, meaning the thermal state change has stronger continuity. It can be estimated based on the response rate of temperature changes during the heating process of a foaming reactor, and the corresponding parameter is obtained by analyzing the relationship between the rate of temperature change per unit time and the heat input.

[0027] Virtual stiffness is an equivalent parameter used to characterize a system's ability to automatically recover to a steady state after deviating from a target temperature. It reflects the strength of the influence of temperature deviation on the system's recovery trend. The larger the virtual stiffness, the more quickly the system tends to return to the target thermal equilibrium state. It can be set based on the system's natural recovery ability after a temperature deviation occurs, for example, by empirically estimating it based on the rate at which the temperature returns to the target temperature after a deviation.

[0028] S402: Construct a Rayleigh dissipation function to describe the dissipation effect of the disturbed foaming reactor, wherein the Rayleigh dissipation function is used to introduce damping to suppress temperature oscillations in the foaming reactor; The Rayleigh dissipation function is as follows: ; in, Indicates virtual damping, This represents the Rayleigh dissipation function value; Virtual damping refers to an equivalent parameter used to characterize a system's ability to suppress temperature oscillations and reduce thermal fluctuations. Its main function is to reduce repeated temperature fluctuations during the adjustment process. The larger the virtual damping, the smoother the system's temperature change. It can be obtained by analyzing the temperature fluctuation decay process, for example, by estimating based on the rate at which temperature fluctuations gradually decrease during continuous adjustment.

[0029] S403: Construct a non-conservative generalized force by combining environmental disturbances to introduce environmental temperature fluctuations.

[0030] The specific formula for calculating non-conservative generalized forces is as follows: ; in, Denotes the non-conservative generalized force, and denotes the perturbation coupling gain. express t The amount of environmental disturbance at any given moment.

[0031] The disturbance coupling gain is a factor that amplifies or reduces the impact of environmental disturbances on the internal thermal state of the foaming reactor, describing the strength of the coupling between changes in the external environment and changes in the internal temperature. A larger disturbance coupling gain indicates a more significant impact of environmental changes on the system's thermal state. It can be empirically calibrated by comparing the correspondence between changes in ambient temperature and changes in the reactor's internal temperature; for example, the corresponding parameters can be obtained by statistically analyzing the magnitude of temperature changes within the reactor after changes in ambient temperature.

[0032] Specifically, by introducing dynamic characteristic parameters such as virtual inertia, virtual stiffness, and virtual damping, the foaming reaction process can be described as a dynamic thermal system with energy accumulation, recovery, and smooth decay capabilities. Virtual inertia reflects the persistence of thermal state changes, virtual stiffness reflects the system's ability to recover to a stable thermal equilibrium, virtual damping mitigates fluctuations during temperature regulation, and disturbance coupling gain describes the degree of influence of external environmental changes on the system's thermal state. By sharing these dynamic characteristics uniformly, not only can the current temperature state be analyzed, but the coupling relationship between heat accumulation, heat dissipation, and environmental disturbances can also be accurately reflected, thus making temperature change trend predictions more accurate. Because the system can identify the temperature development direction in advance and dynamically correct the heat input, it can effectively reduce temperature oscillations and regulation lag, avoid local overheating problems, improve thermal field uniformity, foaming stability, and product quality consistency, while enhancing continuous stable operation under complex conditions.

[0033] Module 5 is established to combine the Lagrangian function, Rayleigh dissipation function and nonconservative generalized force to establish the closed-loop error kinetic equation of the foaming reactor; The closed-loop error kinetic equation is a mathematical model describing the dynamic change of temperature error in a foaming reactor over time under feedback regulation. By combining the internal energy changes, heat loss processes, and external environmental factors, a closed-loop error kinetic equation is established to reflect the dynamic evolution of temperature error, allowing the system to simultaneously consider the coupled effects of heat accumulation, heat decay, and external disturbances. Because temperature changes during the foaming reaction are continuous and dynamic, simple temperature feedback alone is insufficient to accurately reflect the trend of thermal changes. By establishing the closed-loop error kinetic equation, the system can dynamically analyze and predict the development direction and trend of temperature deviation, making subsequent regulation more timely and accurate. This not only reduces temperature control lag but also minimizes temperature fluctuations and local overheating, improving thermal field stability, reaction uniformity, and product quality consistency during the foaming process.

[0034] In one possible implementation, module 5 is specifically used for: S501: By combining the Lagrange function and the Rayleigh dissipation function, we can establish the Euler-Lagrange equations that include non-conservative generalized forces. The specific formula for the Euler-Lagrange equations is as follows: ; S502: Derive the closed-loop error dynamics equation from the Euler-Lagrange equations.

[0035] The specific formula for the closed-loop error dynamics equation is as follows: .

[0036] It should be noted that, firstly, the energy relationship between heat accumulation and thermal state changes within the foaming reactor is described using the Lagrangian function. Then, the Rayleigh dissipation function is used to describe the energy loss generated during heat transfer and dissipation. Simultaneously, the influence of non-conservative generalized forces on external environmental disturbances and external heat inputs is characterized, thus establishing an Euler-Lagrangian equation that reflects the overall dynamic thermal behavior of the system. The Euler-Lagrangian equation is an energy balance model used to describe the time-varying state of a dynamic system, and it can uniformly express the coupling relationship between internal energy storage changes, energy dissipation, and external influences. Based on this, a closed-loop error dynamic equation is further derived, establishing a dynamic feedback correlation between temperature error, heat accumulation state, and environmental disturbances. Because this approach not only considers the current temperature deviation but also analyzes the comprehensive impact of long-term heat accumulation, heat decay, and external environmental changes on the thermal state, the system can more accurately identify temperature change trends and predict the direction of thermal state development in advance. This enables more timely and stable subsequent temperature control adjustments, thereby effectively reducing temperature oscillations, adjustment lag, and local overheating, improving the uniformity of the thermal field, reaction stability, and product quality consistency during the foaming reaction process, while enhancing the continuous and stable control capability under complex operating conditions.

[0037] The fourth calculation module 6 is used to calculate the expected rate of temperature change of the foaming reactor based on the closed-loop error kinetic equation. The expected rate of temperature change refers to the ideal temperature change rate calculated by the system based on the current temperature state, temperature change trend, and dynamic thermal balance relationship. It indicates the rate at which the internal temperature of the foaming reactor should approach the target temperature state. By dynamically analyzing the closed-loop error kinetic equation, a more reasonable temperature change trend under the current thermal state can be obtained, enabling the system not only to know the degree of current temperature deviation but also to determine the appropriate rate of temperature change for adjustment.

[0038] In one possible implementation, the fourth computing module 6 is specifically used for: S601: Calculate the rate of change of temperature error inside the vessel based on the closed-loop error kinetic equation; ; S602: Calculate the derivative of the internal temperature error with respect to time; ; in, Indicates the temperature error inside the vessel. and These represent the target temperature inside the vessel and the real-time temperature inside the vessel, respectively. This indicates the maximum permissible deviation of the temperature inside the vessel. Indicates real-time temperature inside the vessel The derivative with respect to time; S603: Combining the rate of change of temperature error inside the vessel with the derivative results, the expected rate of change of temperature is obtained.

[0039] The specific formula for calculating the expected rate of change of temperature is as follows:

[0040] in, This represents the expected rate of change of temperature.

[0041] It should be noted that this process first calculates the rate of change of temperature error inside the reactor based on the closed-loop error dynamics equation, thereby obtaining the trend of temperature deviation over time under the current thermal state. The rate of change of temperature error inside the reactor reflects how quickly the actual temperature deviates from the target temperature state, while the derivative of the temperature error inside the reactor with respect to time describes the correspondence between the real-time temperature change rate and the error change. By correlating the dynamic change relationship of temperature error with the real-time temperature change process, the system can further obtain the expected rate of change of temperature, i.e., the ideal trend of temperature change that the internal temperature of the foaming reactor should reach under the current operating conditions. In this process, environmental disturbances characterize the impact of external environmental changes on the thermal state, integral results reflect the long-term heat accumulation, damping suppresses temperature fluctuations, and recovery promotes the system to stably approach the target thermal equilibrium state. Therefore, this method can not only analyze the current temperature deviation but also comprehensively consider the combined effects of heat accumulation, heat decay, and environmental changes on the thermal state evolution process, enabling the system to predict the temperature development direction in advance and dynamically adjust the rate of temperature change. This effectively reduces temperature control lag and overshoot, minimizes local overheating and temperature oscillation, improves thermal uniformity, operational stability, and product quality consistency during the foaming reaction process, and enhances continuous and stable control capabilities under complex operating conditions.

[0042] The fifth calculation module 7 is used to calculate the optimal heating power of the foaming reactor based on the expected rate of temperature change. Optimized heating power refers to the more reasonable heating output intensity calculated by the system based on the current thermal state, temperature change trend, and ideal temperature regulation requirements. This ensures that the internal temperature of the foaming reactor changes towards the target state in a stable and suitable manner. By combining the expected rate of temperature change with the current thermal state, the system dynamically calculates the heat input required during the foaming reaction, enabling it to adjust the heating output intensity in real time according to the temperature change trend. Since the foaming reaction continuously generates exothermic phenomena and is also affected by environmental heat dissipation and changes in material state, a fixed heating method can easily lead to insufficient or excessive heat supply. However, by calculating and optimizing the heating power, the system can dynamically match the heat input with the actual heat demand, resulting in more stable and controllable temperature changes. Therefore, this method effectively reduces temperature fluctuations and localized overheating, improves the uniformity of the thermal field and reaction stability during the foaming process, reduces ineffective energy consumption, and improves energy utilization efficiency and product quality consistency.

[0043] In one possible implementation, the fifth computing module 7 is specifically used for: S701: Obtain the pre-calibrated equivalent heat capacity and pre-calibrated bias power of the foaming reactor; Among them, the pre-calibrated equivalent heat capacity is the additional heating power required to generate a unit rate temperature rise from the pre-calibrated vessel temperature. The pre-calibrated bias power is the heating power required to maintain a stable pre-calibrated vessel temperature.

[0044] S702: Optimized heating power is obtained by combining pre-calibrated equivalent heat capacity, pre-calibrated bias power, and expected rate of temperature change.

[0045] In one possible implementation, optimizing the heating power is specifically the sum of an additional adjustment power term and a pre-calibrated bias power, wherein the additional adjustment power term is specifically the product of the pre-calibrated equivalent heat capacity and the expected rate of temperature change.

[0046] Specifically, the process first obtains the pre-calibrated equivalent heat capacity and pre-calibrated bias power. The pre-calibrated equivalent heat capacity characterizes the heat energy demand per unit temperature rise during temperature changes in the foaming reactor, reflecting the overall heat capacity characteristics of the system. The pre-calibrated bias power characterizes the basic heat input required to maintain the current temperature in a stable thermal equilibrium state, essentially corresponding to the basic energy compensation required for the system to maintain thermal stability. Subsequently, the system dynamically analyzes the additional heat demand based on the expected rate of temperature change. By combining the pre-calibrated equivalent heat capacity with the expected rate of temperature change, an additional adjustment power term is obtained, reflecting the increase or decrease in heat input intensity required during the current thermal state change. This term, along with the pre-calibrated bias power, forms the optimized heating power. Because this method simultaneously considers the basic heat input required to maintain a stable thermal state and the dynamic heat input required to achieve the target temperature change trend, the heating output can better match the current actual heat demand. This not only avoids the problems of insufficient or excessive heat supply that occur under fixed heating methods, but also makes temperature changes more stable and continuous, thereby effectively reducing temperature fluctuations, regulating overshoot and local overheating, improving the uniformity of the thermal field, reaction stability and product quality consistency during the foaming process, while reducing ineffective energy consumption and improving overall energy utilization efficiency.

[0047] Adjustment module 8 is used to adjust the foaming reactor according to the optimized heating power.

[0048] In one possible implementation, it also includes: Update module 9 is used to update the precalibrated equivalent heat capacity and precalibrated bias power at second preset intervals.

[0049] It should be noted that those skilled in the art can set the second preset duration according to actual needs, and this invention does not limit this. By setting an update module to periodically update the pre-calibrated equivalent heat capacity and pre-calibrated bias power, the system can dynamically correct the thermal characteristic parameters according to the current operating status of the foaming reactor, changes in material properties, and changes in environmental conditions.

[0050] In practical applications, this carbon dioxide circulation temperature control system for the foaming reactor continuously collects temperature data, including the target internal temperature, real-time internal temperature, and ambient temperature, through an acquisition module. This data is then transmitted to the temperature controller for analysis and processing, enabling the system to monitor real-time changes in the thermal state. Based on this, the first calculation module calculates the internal temperature error and environmental disturbances, reflecting both the degree of deviation of the actual temperature from the target temperature and identifying the impact of external environmental changes on the thermal balance. This allows the system to not only perceive the temperature change but also identify its source. Subsequently, the second calculation module integrates the internal temperature error over time to obtain the long-term heat accumulation trend, enabling the system to analyze the cumulative effect of temperature deviation during continuous changes, thus avoiding delayed adjustments based solely on instantaneous temperature. Furthermore, the third calculation module equates the foaming reaction process to a dynamic thermal system with the combined effects of energy accumulation, energy dissipation, and environmental disturbances. It combines generalized coordinates, generalized velocities, Lagrangian functions, Rayleigh dissipation functions, and non-conservative generalized forces to provide a unified description of the coupling relationships between heat generation, heat transfer, heat decay, and external disturbances, thereby establishing a dynamic thermal behavior model that better reflects actual operating conditions. The module further constructs a closed-loop error dynamic equation based on the Euler-Lagrange equations, creating a dynamic feedback correlation between temperature error, heat accumulation state, and environmental disturbances, thus enabling predictive analysis of temperature change trends and directions. Subsequently, the fourth calculation module calculates the expected rate of temperature change based on the closed-loop error dynamic equations, allowing the system to clearly define the ideal temperature change rate under the current thermal state. This enables temperature regulation to not only focus on current deviations but also adapt to the evolving thermal state trend in advance. The fifth calculation module combines pre-calibrated equivalent heat capacity, pre-calibrated bias power, and expected temperature change rate to dynamically calculate heating requirements, obtaining an optimized heating power that better matches actual heat demands. The adjustment module then adjusts the foaming reactor in real time based on this optimized heating power. Simultaneously, the update module periodically updates thermal characteristic parameters, enabling the system to continuously adapt to changes in material state, environment, and heat exchange conditions. This solution transforms temperature control from traditional passive compensation regulation to proactive dynamic regulation with trend prediction capabilities. It effectively reduces temperature fluctuations, control lag, and localized overheating, while also improving thermal uniformity, foaming stability, and product quality consistency. Furthermore, it reduces ineffective energy consumption, improves overall energy efficiency, and enhances the equipment's continuous and stable operation under complex conditions.

[0051] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: In this embodiment of the invention, by real-time acquisition of temperature changes during the foaming reaction and combined analysis with thermal disturbances caused by the external environment, the system can not only sense the current temperature state but also identify the development trend of temperature changes and the heat accumulation process. Based on this, the foaming reaction process is abstracted as a dynamic motion system with energy transfer and dissipation characteristics. Temperature changes are no longer considered simply as deviations but as a continuously evolving dynamic behavior, thus more accurately reflecting the coupling relationship between heat generation, transfer, and attenuation during the foaming reaction. Subsequently, by constructing a closed-loop error kinetic equation reflecting the dynamic equilibrium relationship of the system, the direction and rate of temperature change are predicted, and the heating output is dynamically corrected accordingly. This allows the heating process to adapt to the intensity of exothermic reaction and environmental changes in advance, rather than compensating for adjustments after significant temperature deviations. This effectively reduces temperature fluctuations and adjustment lag, avoids overheating caused by localized heat accumulation, improves the uniformity of the thermal field and reaction stability during the foaming process, and results in a more uniform cell structure and higher product consistency. Meanwhile, since the heating output can be dynamically optimized according to actual heat demand, it can also reduce ineffective energy consumption, improve overall energy utilization efficiency, and enhance the equipment's ability to operate continuously and stably under complex working conditions.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A carbon dioxide circulating temperature control system for a foaming reactor, characterized in that, Applied to and The temperature controller is connected to the foaming reactor; the system includes: The acquisition module is used to acquire the temperature data of the foaming reactor and transmit the temperature data to the temperature controller; The first calculation module is used to calculate the internal temperature error and environmental disturbance based on the temperature data. The second calculation module is used to calculate the time integral of the temperature error inside the vessel over a first preset time period; The third calculation module is used to treat the disturbed foaming reactor as an equivalent disturbed damped co-oscillator, and use the integral result as a generalized coordinate, the temperature error as a generalized velocity, to calculate the Lagrangian function, Rayleigh dissipation function and nonconservative generalized force of the foaming reactor. A module is established to combine the Lagrange function, the Rayleigh dissipation function, and the non-conservative generalized force to establish the closed-loop error kinetic equation of the foaming reactor; The fourth calculation module is used to calculate the expected rate of temperature change of the foaming reactor based on the closed-loop error kinetic equation. The fifth calculation module is used to calculate the optimal heating power of the foaming reactor based on the expected rate of temperature change. An adjustment module is used to adjust the foaming reactor according to the optimized heating power.

2. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 1, characterized in that, The temperature data includes the target vessel internal temperature, real-time vessel internal temperature, real-time ambient temperature, nominal ambient temperature, and the maximum permissible deviation of the vessel internal temperature.

3. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 2, characterized in that, The internal temperature error is specifically the quotient of the internal temperature deviation and the maximum permissible internal temperature deviation, wherein the internal temperature deviation is specifically the difference between the target internal temperature and the real-time internal temperature.

4. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 2, characterized in that, The environmental disturbance is specifically the difference between the real-time ambient temperature and the nominal ambient temperature.

5. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 1, characterized in that, The third calculation module is specifically used for: S401: Construct the Lagrange function by combining the generalized coordinates and the generalized velocity; S402: Construct a Rayleigh dissipation function to describe the dissipation effect of the disturbed foaming reactor, wherein the Rayleigh dissipation function is used to introduce damping to suppress temperature oscillations in the foaming reactor; S403: Construct the non-conservative generalized force by incorporating environmental disturbances to introduce environmental temperature fluctuations.

6. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 1, characterized in that, The establishment module is specifically used for: S501: Combining the Lagrange function and the Rayleigh dissipation function, establish an Euler-Lagrange equation that includes the non-conservative generalized force; S502: Derive the closed-loop error dynamics equation from the Euler-Lagrange equation.

7. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 1, characterized in that, The fourth calculation module is specifically used for: S601: Calculate the rate of change of temperature error inside the vessel based on the closed-loop error dynamics equation; S602: Calculate the derivative of the internal temperature error with respect to time; S603: Combining the rate of change of temperature error inside the vessel with the derivative result, the expected rate of change of temperature is obtained.

8. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 1, characterized in that, The fifth calculation module is specifically used for: S701: Obtain the pre-calibrated equivalent heat capacity and pre-calibrated bias power of the foaming reactor; S702: The optimized heating power is obtained by combining the pre-calibrated equivalent heat capacity, the pre-calibrated bias power, and the expected rate of temperature change.

9. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 8, characterized in that, The optimized heating power is specifically the sum of the additional adjustment power term and the pre-calibrated bias power, wherein the additional adjustment power term is specifically the product of the pre-calibrated equivalent heat capacity and the expected rate of temperature change.

10. The carbon dioxide circulating temperature control system for the foaming reactor according to claim 8, characterized in that, Also includes: The update module is used to update the pre-calibrated equivalent heat capacity and the pre-calibrated bias power at second preset intervals.

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