A prediction control method for a regenerative heat source supply for spray drying

Abstract

This invention discloses a predictive control method for heat storage heat source supply in spray coating drying, belonging to the field of heat source control technology in spray coating drying. The method includes heat storage control and heat release control steps: during heat storage control, future production demand information is acquired to predict the required heat storage capacity, and the start-up time for heat storage is determined based on the prediction results; during heat release control, the output parameters of the heat release medium are dynamically adjusted according to actual heat demand, and the stored heat is delivered to the end-user equipment as needed; the heat storage decision can integrate time-of-use electricity prices, renewable energy status, and the characteristic curve of the heat storage body; the heat release control uses adaptive PID or intelligent control algorithms to adjust the fan or valve, and has stepless power adjustment and heat replenishment functions as well as two-stage independent regulation functions; this invention achieves forward-looking planning, adaptive adjustment, and economical operation of heat source supply, and is suitable for high-quality spray coating drying production lines such as powder coating and electrophoretic coating.

Description

Technical Field

[0001] This invention belongs to the technical field of regenerative hot air systems in spray drying, specifically relating to a pure hot air heating control method based on magnesium brick heat storage. Background Technology

[0002] In the drying and curing process of industrial spraying, the control strategy of the heat source supply system is the core factor that determines the coating quality, energy efficiency and production cost.

[0003] As coating production lines evolve towards high speed, continuous operation, and automation, the drying process places higher demands on the dynamic response capability, anti-interference robustness, and economic scheduling level of the heat source control system. Ideal heat source control not only needs to maintain high-precision stability of curing temperature, but also needs to have the intelligent decision-making capability to predict heat load based on production plan, dynamically coordinate heat storage and release rhythm, and combine external economic signals such as time-of-use electricity pricing to achieve low-cost operation.

[0004] However, the current spray drying field generally adopts a real-time heating and feedback regulation control architecture. This type of system mainly relies on temperature sensors in the curing chamber to collect real-time data, calculates the deviation through a PID controller with fixed parameters, and drives the heating device to achieve closed-loop regulation. Although some systems have introduced frequency conversion control for fans, their control logic is limited to eliminating the temperature deviation at the current moment and cannot make forward-looking plans for future heat demand.

[0005] In actual production, the aforementioned traditional control methods have revealed the following technical bottlenecks:

[0006] 1. Traditional control is a deviation-driven mechanism, which only starts adjustment after the temperature deviates from the set value. When faced with frequent disturbances such as workpiece entry and exit, and hatch opening and closing, the system cannot detect and respond in advance.

[0007] 2. Existing PID parameters are usually fixed for a long time after being tuned once on site. However, the operating conditions of the production line change dynamically with batches, seasons and equipment aging. Fixed parameters are difficult to adapt to the full range of operating conditions and are prone to overshoot, oscillation or slow response. Moreover, retuning requires manual debugging.

[0008] 3. Existing control strategies only focus on process constraints and ignore future heat demand and energy price fluctuations, which often forces heating devices to operate at high power during peak electricity periods and leave them idle during off-peak electricity periods, making it impossible to use low-priced electricity for heat storage and resulting in high energy costs.

[0009] 4. The system relies on a single temperature signal and fails to effectively integrate multi-source information such as production scheduling and heat storage status. It lacks predictive scheduling capabilities, resulting in a waste of information resources and an inability to achieve pre-regulation to smooth temperature fluctuations.

[0010] In summary, existing technologies have significant shortcomings in terms of response foresight, parameter adaptability, and energy economy, and there is an urgent need for an intelligent heat source control method that can achieve predictive heat storage, adaptive regulation, and multi-source information fusion. Summary of the Invention

[0011] To address the technical problems of existing heat source supply control systems for spray drying, such as lag in dynamic response, poor parameter adaptability, lack of economic operation, and weak information fusion capability, this invention provides a predictive control method for the supply of a regenerative heat source for spray drying.

[0012] This method aims to replace the traditional ex-post control mode by introducing a heat storage regulation mechanism based on production demand forecasting, an adaptive / intelligent heat release regulation strategy, and multi-source information fusion decision-making, thereby achieving forward-looking planning, adaptive adjustment, and low-cost operation of heat source supply.

[0013] To achieve the above objectives, the present invention adopts the following technical solution:

[0014] A predictive control method for the supply of a regenerative heat source for spray drying;

[0015] The method first performs a thermal storage control step: obtaining future production demand information, predicting the required heat storage based on the production demand information, and controlling the thermal storage device to store energy within the determined time period according to the prediction results;

[0016] The heat release control step is then executed: During the heat release stage, the output parameters of the heat release medium are dynamically adjusted according to the actual heat demand, and the stored heat is delivered to the end heat-using equipment as needed.

[0017] Through the synergistic control of heat storage and heat release described above, the present invention can achieve predictive storage and precise release of thermal energy.

[0018] Furthermore, the above-mentioned heat storage control steps specifically include: obtaining the start time, target temperature and expected duration of the next production task, and obtaining the remaining energy of the current heat storage body;

[0019] Then calculate the energy gap required to complete the next production task;

[0020] When the energy gap is greater than zero, the system automatically decides the start time and / or heating power of the heat storage, so that the heat storage body reaches the preset energy storage state before the start of the production task.

[0021] This mechanism gives the system the ability to predict future heat loads, fundamentally overcoming the response lag problem caused by "deviation-driven" control in traditional systems.

[0022] In the above-mentioned thermal storage decision-making process, the basis for automatically deciding the thermal storage start-up time and / or heating power may include at least one of the following: time-of-use electricity price schedule, renewable energy availability status, or thermal storage heating characteristic curve.

[0023] By integrating electricity price signals and new energy information, the system can prioritize the use of off-peak electricity periods or clean energy for energy storage, thereby significantly reducing operating costs and improving the economic efficiency of energy utilization.

[0024] In terms of heat release control, the present invention uses an adaptive control algorithm or an intelligent control algorithm to dynamically adjust the output parameters of the heat release medium. The intelligent control algorithm includes at least one of fuzzy control algorithm, model predictive control algorithm, or neural network control algorithm.

[0025] By introducing the above algorithm, the controller can optimize control parameters in real time according to changes in operating conditions, effectively cope with complex operating conditions such as batch switching, ambient temperature fluctuations and equipment aging, and overcome the technical defects of poor adaptability of fixed PID parameters.

[0026] As a preferred embodiment, the heat release control step further includes: collecting the real-time temperature of the terminal heating equipment, inputting the deviation between the real-time temperature and the set temperature into an adaptive PID controller, and having the adaptive PID controller output a control signal to adjust the fan speed or the opening of the damper.

[0027] This closed-loop regulation method enables precise control of the heat release flow rate, ensuring that the terminal temperature remains stable within the process requirements range.

[0028] To prevent insufficient heat storage energy from affecting the continuity of drying during the heat release process, the present invention also provides a supplementary heating strategy: during the heat release stage, when the current energy of the heat storage body is lower than the preset minimum required energy threshold, the supplementary heating mode is activated, and the stepless power adjustment device is used to calculate the optimal supplementary heating power to supplement the heat storage body and maintain its energy above the minimum required energy threshold.

[0029] This strategy utilizes stepless power regulation devices such as thyristor power regulators to achieve smooth heating, avoiding the temperature shocks and additional energy consumption caused by traditional on / off heating.

[0030] For applications using air as the heat release medium, this invention further specifies that the heat release control steps adopt a two-stage circulation method: the first-stage circulation transfers the heat released by the heat storage body to the heat exchanger, and the second-stage circulation transfers the heat in the heat exchanger to the terminal heat-using equipment, and the air volume of the two-stage circulation is independently adjustable.

[0031] This design ensures that the primary heat transfer and secondary utilization do not interfere with each other, guaranteeing efficient heat exchange on the heat storage side while meeting the differentiated air volume and temperature requirements on the heat use side.

[0032] To facilitate intelligent remote control, the method of the present invention further includes: interacting with a remote terminal through a communication module to receive production plan instructions from a mobile terminal or computer, and / or sending system operation status data to the remote terminal.

[0033] Operators can remotely issue production tasks, modify settings, and monitor the system's operating status in real time via a mobile app or computer, thereby improving the automation and informatization level of the production line.

[0034] In a specific application of the present invention, the heat storage device is preferably a magnesium brick heat storage wall, which has a hollow air duct inside, and an electric heating wire is installed in the hollow air duct as a heating element.

[0035] Magnesia bricks have high specific heat capacity and good thermal conductivity. The heating wire is matched with the bending direction of the air duct, which can convert electrical energy into heat energy and store it efficiently during off-peak hours. When releasing heat, the air flowing through the hollow air duct fully exchanges heat with the magnesium bricks, and outputs pure hot air without any combustion products. It is especially suitable for powder coating and electrophoretic coating processes that are sensitive to moisture and impurities.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] 1. This invention adopts a heat storage control strategy based on future production demand forecasting, which transforms the heat source supply system from "post-event response" to "pre-event planning", significantly shortens the recovery time after temperature disturbance, eliminates long-term temperature fluctuations caused by response lag in traditional control, and improves the consistency of coating curing.

[0038] 2. This invention introduces advanced algorithms such as adaptive PID, fuzzy control, model predictive control, or neural networks into the heat release control, enabling the controller to autonomously optimize control parameters according to changes in operating conditions. This avoids the overshoot, oscillation, or slow response problems of fixed parameter controllers, reduces manual debugging and maintenance costs, and achieves strong robustness adaptation to complex operating conditions.

[0039] 3. This invention fully integrates time-of-use electricity pricing and renewable energy information, intelligently decides the timing of thermal storage activation and energy source, prioritizes the use of off-peak electricity or clean energy for energy storage, effectively avoids high-cost operation during peak electricity periods, and, combined with closed-loop insulation and stepless power regulation and heat compensation strategies, significantly reduces the energy consumption and operating cost per unit product.

[0040] 4. This invention achieves efficient, clean, and intelligent operation of the heat source supply system through independent control of two-stage circulating air volume, remote terminal interaction, and pure hot air output from the magnesium brick thermal storage wall. It is especially suitable for high-quality spraying and drying production lines, which can effectively improve product yield and meet the environmental protection requirements under the dual-carbon policy.

[0041] In summary, this invention effectively overcomes the shortcomings of existing spray drying heat source control technologies, such as slow response, fixed parameters, poor economy, and insufficient information fusion. It provides an intelligent heat source control method with predictive, adaptive, and economical scheduling capabilities, demonstrating significant technological advancements. Attached Figure Description

[0042] Figure 1 This is an overall flowchart of the predictive control method for the supply of a regenerative heat source for spray drying according to the present invention.

[0043] Figure 2 This is a flowchart illustrating the decision-making process for predictive thermal storage startup in this invention.

[0044] Figure 3 This is a functional block diagram of the control system of the present invention. Detailed Implementation

[0045] To enhance understanding of the present invention, the invention will be further described in detail below with reference to embodiments and accompanying drawings. These embodiments are only for explaining the invention and do not constitute a limitation on the scope of protection of the invention.

[0046] like Figure 1 , Figure 2 and Figure 3 As shown, the present invention provides a predictive control method for the supply of a regenerative heat source for spray drying, which can run on a control system including a controller, a memory, a communication module and a human-machine interface. The control system is electrically connected to the heat storage device (e.g., magnesia brick heat storage wall), heat exchanger, fan and various sensors, and can interact with a mobile app or computer via wireless or wired network.

[0047] First, the overall control flow of this invention will be explained:

[0048] After the system starts up, it first performs an initialization operation and reads the user-preset production requirement parameters, including but not limited to the target curing temperature of the workpiece to be dried, the heat preservation time, and the planned start time of the next production task. At the same time, the system obtains the current actual temperature and remaining energy value of the heat storage body through the signal acquisition module.

[0049] Based on this, the core control module determines whether heat storage needs to be activated by comparing the production demand with the current heat storage status. If heat storage is required, it enters the heat storage control step; if heat storage is not required or heat storage has been completed, it enters the heat release control step standby state.

[0050] Specifically, the execution process of the heat storage control steps is as follows:

[0051] The system obtains the start time, target temperature, and estimated duration of the next production task, and also obtains the remaining energy value of the current heat storage body.

[0052] Based on the above information, the core control module calculates the energy gap required to complete the production task, which is the difference between the theoretically required heat and the current remaining energy.

[0053] When the energy gap is greater than zero, the system automatically decides the start-up time and heating power of the thermal storage. This decision-making process can take into account a variety of factors, including but not limited to the local time-of-use electricity price schedule, the real-time availability of renewable energy sources (such as solar and wind power), and the heating and temperature rise characteristic curve of the thermal storage body itself.

[0054] Based on the above factors, the system calculates an optimal start-up time for thermal storage, ensuring that the thermal storage body can be heated to the preset target energy storage temperature before the production task begins.

[0055] Meanwhile, the system can also prioritize heating and energy storage during off-peak hours based on peak and off-peak electricity price fluctuations, thereby significantly reducing electricity procurement costs.

[0056] During the heat storage execution phase, the control system connects the power supply to the heating element through the drive execution module, and heats the heat storage body according to the determined heating power.

[0057] When the temperature of the heat storage body reaches the preset upper limit, the system automatically stops heating and enters the heat preservation state. During the heat preservation period, the insulation layer of the outer wall of the heat storage body and the air duct can effectively reduce heat loss, so that the heat can be preserved for a long time for production use.

[0058] During the heat release control phase, the system dynamically adjusts the output parameters of the heat release medium according to the actual heat demand of the end heat-using equipment (i.e., the curing chamber). When the real-time temperature of the curing chamber is lower than the set temperature, the control system starts the heat release process.

[0059] This invention employs an adaptive control algorithm or an intelligent control algorithm to achieve fine-grained regulation of the heat release process. Specifically, the system may use one or more combinations of an adaptive PID controller, a fuzzy logic controller, a model predictive controller, or a neural network controller.

[0060] Taking the adaptive PID controller as an example, the system collects the actual temperature in the curing chamber in real time, calculates the deviation value between it and the set temperature, and sends the deviation value as an input signal to the adaptive PID controller.

[0061] The controller dynamically adjusts the proportional, integral, and derivative parameters according to the preset self-tuning rules, and outputs corresponding control commands to the drive execution module, thereby adjusting the speed of the first and second fans, or adjusting the opening of the electric valves on the duct.

[0062] Through the above closed-loop regulation, the temperature of the curing chamber can be stabilized within the target range required by the process, avoiding the overshoot and oscillation phenomena commonly found in traditional fixed-parameter PID control.

[0063] To prevent the heat storage body from being over-consumed during long-term heat release, thus causing an interruption in heat supply, the present invention also designs a heat replenishment strategy.

[0064] During the heat release phase, the control system continuously monitors the current energy value of the heat storage medium. When the energy value is lower than the preset minimum required energy threshold, the system automatically starts the heat replenishment mode.

[0065] In the supplemental heating mode, the control system uses a stepless power adjustment device (such as a thyristor power regulator) to calculate the optimal supplemental heating power required at present, and then supplements the heat storage body in a continuous and smooth manner to keep its energy above the minimum required energy threshold.

[0066] This heating method avoids the temperature shock and additional switching losses caused by traditional on / off heating (such as relay on / off control), achieving dual optimization of energy saving and temperature control.

[0067] For typical application scenarios where air is used as the heat release medium, this invention further provides a two-stage circulation control method.

[0068] Specifically, the first-stage circulation is responsible for drawing the high-temperature heat energy released by the heat storage body from the heat outlet of the heat storage chamber and transporting it to the hot side inlet of the heat exchanger via the heating pipeline.

[0069] Inside the heat exchanger, high-temperature air exchanges heat with circulating air from the curing chamber. After its temperature drops, it returns to the heat storage chamber via the reheat pipe to be reheated.

[0070] The second-stage circulation is responsible for drawing the heated pure hot air from the cold side outlet of the heat exchanger, and delivering it to the air inlet of the curing chamber via the hot air duct and the first fan. After the hot air dries the workpiece in the chamber, the exhaust gas with the reduced temperature is drawn back to the heat exchanger via the air outlet, return air duct, and the second fan, completing a complete closed-loop cycle.

[0071] In this two-stage circulation architecture, the air volume of the first-stage circulation and the air volume of the second-stage circulation can be adjusted independently without interfering with each other. For example, when rapid heating is required, the speed of the two-stage fans can be increased at the same time; while after entering the heat preservation stage, the speed of the second-stage fan can be appropriately reduced to save energy, while maintaining the first-stage circulation at a small flow rate to keep the thermal channel between the heat storage body and the heat exchanger unobstructed.

[0072] To enhance the system's intelligence and ease of operation, the method of this invention also includes a remote interaction function.

[0073] The control system establishes a connection with the remote terminal through a communication module (such as a Wi-Fi module, 4G / 5G module or industrial Ethernet interface). Operators can use a mobile app or computer software to remotely send production plan instructions to the control system (such as setting the start time and curing temperature for the next morning).

[0074] After receiving these instructions, the control system stores them in the memory and automatically calculates the heat storage start-up time according to the above heat storage control steps. At the same time, the control system can also package and send the real-time operating status data of the system (such as the temperature of the heat storage body, the temperature of the curing chamber, the fan speed, the current power consumption, etc.) to the remote terminal for operators to monitor and diagnose remotely.

[0075] In a preferred application of the present invention, the above-mentioned heat storage device adopts a magnesium brick heat storage wall structure, which is composed of multiple sets of hollow magnesium bricks. Each magnesium brick has a hollow air duct inside, and the heating wire is inserted into the hollow air duct and arranged along the bend of the air duct.

[0076] When the heating wire is energized, the heat it generates is absorbed and stored by the magnesium brick. Magnesium brick material has a high specific heat capacity and good thermal conductivity, which enables it to efficiently convert electrical energy into heat energy during off-peak hours and maintain it for a long time.

[0077] When releasing heat, the air flows through the hollow air duct and exchanges heat fully with the high-temperature magnesia bricks, thus outputting pure hot air that does not contain water vapor, smoke or any combustion products.

[0078] This pure hot air is particularly suitable for powder coating and electrophoretic coating processes that require extremely high purity of the drying medium, and can effectively avoid quality defects such as bubbles, whitening or pinholes on the coating surface.

[0079] Implementation Example

[0080] An automotive parts manufacturing company has a powder coating production line. The original curing and drying system uses natural gas combustion for heating, and a fixed-parameter PID controller is used for temperature regulation. In actual production, the system has problems such as slow heating rate, large temperature fluctuation (±8℃), and high energy consumption. In addition, because the flue gas produced by natural gas combustion contains water vapor, it occasionally causes pinholes and shrinkage cavities on the coating surface, and the product rework rate has been maintained between 8% and 10% for a long time.

[0081] To improve the above situation, the company adopted the predictive control method for the supply of regenerative heat source for spray drying described in this invention to technically upgrade the original system.

[0082] In practice, the company installed a new type of heat source supply device in the workshop, consisting of a magnesium brick thermal storage wall, electric heating wire, heat exchanger, two-stage fan and control system.

[0083] The control system is connected to the mobile app of enterprise managers via a 4G network. Before leaving get off work each day, operators enter the production plan for the next day through the mobile app: production will start at 8:00 am the next day, the curing chamber needs to be heated to 185°C and kept warm, and the production time is expected to be 6 hours.

[0084] After receiving the instruction, the control system automatically reads the remaining energy of the thermal storage body (at 23:00 at night, the temperature of the thermal storage body is 120℃) and calculates that the energy gap required to complete the production task of the next day is about 180kWh.

[0085] The system further queried the local time-of-use electricity price list and confirmed that the off-peak electricity period is from 23:00 to 7:00 the next day, and the electricity price is only one-third of that during the peak electricity period.

[0086] Based on the heating characteristic curve of the magnesia brick thermal storage wall (heating at 30kW, it can raise the temperature by about 80℃ per hour), the system automatically decides to start the thermal storage heating at 1:00 AM and continue heating at 30kW until 6:30 AM. At this time, the temperature of the thermal storage body reaches the preset 750℃, and the energy is sufficient.

[0087] The next morning, after production started, the control system entered the heat release control mode.

[0088] Temperature sensors installed in the curing chamber transmit real-time temperature data to an adaptive PID controller, which dynamically adjusts the speed of the two-stage fans based on the deviation between the current temperature and the set value of 185℃.

[0089] Actual measurement data shows that when the workpiece frequently enters and exits the chamber, the chamber temperature remains stable between 184.5℃ and 185.5℃, with a fluctuation range significantly smaller than ±8℃ of the original system.

[0090] Throughout the production process, the control system continuously monitors the energy of the heat storage body. When the energy drops to the preset threshold, the thyristor power regulator automatically provides smooth heat replenishment at a power of 15kW, without any interruption in heat supply.

[0091] After three consecutive months of operation and statistics, the unit product energy consumption of the production line was reduced by about 42% and the electricity cost was reduced by about 55% after adopting the control method of this invention (thanks to the strategy of storing heat during off-peak hours and releasing heat during peak hours).

[0092] Meanwhile, since the output hot air is pure hot air without water vapor, the surface quality of the coating is significantly improved, pinholes and shrinkage cavities are basically eliminated, and the first-pass yield of the product increases from 91% before the modification to over 98%.

[0093] This implementation example fully demonstrates that the predictive control method provided by the present invention can effectively overcome the defects of the prior art, such as response lag, poor parameter adaptability, lack of economic operation, and hot air carrying water, and has significant technical progress.

[0094] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A prediction control method for a spray drying regenerative heat source supply, characterized by, Includes the following steps: Thermal storage control steps: Obtain future production demand information, predict the required heat storage based on the production demand information, and control the thermal storage device to store energy within the determined time period according to the prediction results; Heat release control steps: During the heat release stage, the output parameters of the heat release medium are dynamically adjusted according to the actual heat demand, and the stored heat is delivered to the end heat-using equipment as needed.

2. The prediction control method of the regenerative heat source supply for spray drying according to claim 1, characterized by, The heat storage control step further includes: Obtain the start time, target temperature, and estimated duration of the next production task, and obtain the remaining energy of the current heat storage body; Calculate the energy gap required to complete the next production task; When the energy gap is greater than zero, the system automatically determines the start-up time and / or heating power of the heat storage, so that the heat storage body reaches the preset energy storage state before the start of the production task.

3. The predictive control method of a regenerative heat source supply for spray drying according to claim 2, characterized by, The basis for automatically deciding the start-up time and / or heating power of thermal storage includes at least one of the following: time-of-use electricity price schedule, renewable energy availability status, or thermal storage heating characteristic curve.

4. The prediction control method of the regenerative heat source supply for spray drying according to claim 1, characterized by, In the heat release control step, an adaptive control algorithm or an intelligent control algorithm is used to dynamically adjust the output parameters of the heat release medium. The intelligent control algorithm includes at least one of fuzzy control algorithm, model predictive control algorithm, or neural network control algorithm.

5. The prediction control method of the regenerative heat source supply for spray drying according to claim 4, characterized by, The heat release control step further includes: collecting the real-time temperature of the terminal heating equipment, inputting the deviation value between the real-time temperature and the set temperature into an adaptive PID controller, and having the adaptive PID controller output a control signal to adjust the fan speed or the opening of the damper.

6. The predictive control method of the regenerative heat source supply for spray drying according to claim 1, characterized by, During the heat release phase, when the current energy of the heat storage body is lower than the preset minimum required energy threshold, the heat replenishment mode is activated: the stepless power adjustment device calculates the optimal heat replenishment power and supplements the heat storage body to maintain its energy above the minimum required energy threshold.

7. The predictive control method of the regenerative heat source supply for spray drying according to claim 1, characterized by, The heat release medium is air, and the heat release control step adopts a two-stage circulation method: the first stage circulation transfers the heat released by the heat storage body to the heat exchanger, and the second stage circulation transfers the heat in the heat exchanger to the terminal heat-using equipment, and the air volume of the two stages circulation is independently adjustable.

8. The predictive control method of the regenerative heat source supply for spray drying according to claim 1, characterized by, The method further includes: interacting with a remote terminal through a communication module to receive production plan instructions from a mobile terminal or computer, and / or sending system operation status data to the remote terminal.

9. The predictive control method of a regenerative heat source supply for spray drying according to any one of claims 1 to 8, characterized by, The heat storage device is a magnesium brick heat storage wall, and the inside of the magnesium brick heat storage wall is provided with a hollow air duct, and an electric heating wire is installed in the hollow air duct as a heating element.

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