Instant heating self-adaptive control method and system, storage medium and water purification equipment

Abstract

The invention discloses an instant heating self-adaptive control method and system, a storage medium and water purifying equipment, the system comprises a sensor layer, a controller layer and an actuator layer, the controller layer comprises a partition heat balance model module, a feedforward-feedback cooperative controller, an online parameter identification module and a safety protection module, based on self-adaptive feed-forward control and online parameter identification of the partition dynamic heat balance model, the problems that a traditional method is slow in response, poor in precision and weak in adaptability are solved by conducting partition modeling on the heating waterway and identifying model parameters in real time and combining feed-forward and closed-loop cooperative control, the response speed is high, constant-temperature precision is high, long-term stability is good, safety is high, and the method is suitable for large-scale popularization and application. The method is high in adaptability and good in universality, and can adapt to heaters of different power levels and sensors and actuators of different types based on a control algorithm realized by software, so that the product platform development cost is reduced.

Description

Technical Field

[0001] This invention relates to instant hot water purifiers, and particularly to an instant hot water adaptive control method, system, storage medium, and water purification device based on model identification. Background Technology

[0002] As people's demands for quality of life increase, instant water purifiers have become increasingly popular due to their advantages of providing hot water instantly without waiting. However, existing instant water purifiers face significant temperature control challenges in practical applications: 1. Poor temperature stability due to multiple sources of disturbance. Inlet water temperature varies greatly with the seasons (potentially exceeding 30℃ in summer and dropping as low as 5℃ in winter), user water flow rates fluctuate arbitrarily (from trickle to large flow), heaters and piping systems suffer from thermal inertia and heat loss, and temperature sensors exhibit measurement lag. These factors combined result in slow outlet water temperature response, severe overshoot, large steady-state fluctuations, and a poor user experience.

[0003] 2. Traditional single-loop control has significant limitations. Existing technologies mostly employ simple PID temperature closed-loop control, adjusting solely based on feedback from the outlet water temperature. This method has inherent drawbacks: when there are sudden changes in inlet water temperature or flow rate, the controller can only respond after the temperature deviation has already occurred, resulting in adjustment lag; simultaneously, the use of conservative parameters to avoid oscillations sacrifices response speed. Relying solely on feedback control makes it difficult to achieve a balance between rapid response and stable temperature control.

[0004] 3. Time-varying system model parameters lead to degraded control performance. The thermal characteristic parameters of the heating system (such as heating efficiency, pipeline heat dissipation coefficient, water transfer heat coefficient, etc.) will drift with the time of use, changes in water quality, changes in filter element condition, and changes in ambient temperature. Controllers with fixed parameters cannot adapt to this time-varying characteristic, resulting in a gradual degradation of control quality, and even loss of control under extreme operating conditions.

[0005] 4. Lack of identification and response mechanisms for abnormal disturbances. In actual use, abnormal operating conditions such as sudden cold water inflow, air lock in pipelines, and short-term start-stop are frequently encountered. Existing systems lack effective identification of these disturbances, and operating according to conventional strategies can easily lead to drastic temperature fluctuations, reduced energy efficiency, and even safety hazards (such as dry burning and overheating).

[0006] Therefore, there is an urgent need for a temperature control method that can proactively predict, respond quickly, adapt adaptively, and intelligently identify anomalies, so as to simultaneously achieve rapid temperature rise, precise temperature control, high energy efficiency, and high safety. Summary of the Invention

[0007] The purpose of this invention is to provide a model-based adaptive control method, system, storage medium, and water purification device for instant heating, achieving the following objectives: 1. Under conditions of influent and flow disturbance, achieve rapid attainment of the set temperature and maintain a narrow temperature range; 2. By using temperature-flow coordinated control and thermal inertia forward compensation, overshoot and oscillation are reduced, and energy efficiency is improved; 3. Supports online self-calibration and disturbance identification, improving robustness to conditions such as sudden cooling water inflow, airlock / evacuation, and short-term start-stop; 4. Provides hardware-independent software implementation, adaptable to different heating powers, valve types and sensor configurations.

[0008] The technical solution of this invention is: An adaptive control method for instant heating includes the following steps: S1. Acquire the real-time operating parameters of the system, wherein the real-time operating parameters include at least the inlet water temperature, the outlet water temperature, and the flow rate; S2. Based on the partitioned dynamic heat balance model and the currently identified model parameters, calculate the feedforward heating power according to the real-time operating parameters and the target outlet water temperature. The partitioned dynamic heat balance model divides the heating water circuit into a heating zone, a mixing zone, and a pipeline zone and establishes heat balance equations for each zone. S3. Calculate the error between the outlet water temperature and the target outlet water temperature, and process the error through the feedback controller to obtain the feedback power correction amount; S4. The feedforward heating power and the feedback power correction amount are superimposed to obtain the preliminary power command; S5. Perform power shaping and dynamic safety boundary limiting on the preliminary power command to generate the final power command and output it to the heater for execution; S6. When the preset identification conditions are met, start the online parameter identification process and update the parameters of the partition dynamic thermal balance model according to the system's input and output data.

[0009] Preferably, the establishment of the partitioned dynamic thermal balance model in step S2 includes: The heating zone is the heater body and the surrounding water, and its dynamic characteristics are determined by the heater's heat capacity, heating efficiency, and water flow velocity. The mixing zone is the pipeline between the heater outlet and the temperature sensor, and its characteristics include heat exchange and mixing delay. The pipeline area refers to the pipeline between the temperature sensor and the water outlet, and its characteristics are pure time delay and heat loss. For the three regions mentioned above, heat balance equations are established for each region to describe the temperature change over time and predict the time and power required for the system to reach the target outlet water temperature under given heating power and flow rate conditions.

[0010] Preferably, the online parameter identification process in step S6 includes: Within a time window when the system is running stably and the disturbance is less than the threshold, parameter identification is initiated by applying a small power disturbance and observing the system's temperature response. A recursive estimation algorithm is used to estimate the parameters of the partitioned dynamic thermal balance model in real time based on the input historical power and flow data and the output historical temperature response data. The identified parameters are tested for reasonableness, and the model parameters are updated smoothly after the test is passed.

[0011] Preferably, the recursive estimation algorithm is the recursive least squares method or the Kalman filter algorithm.

[0012] Preferably, the power shaping process for the preliminary power command in step S5 includes: Set limits on the rise and fall rates of power commands; Based on the current inlet water temperature, flow rate, and system status, dynamically calculate and limit the maximum allowable heating power; Set the allowable fluctuation range of the outlet water temperature as a temperature safety window, and adjust the power in advance when the temperature approaches the boundary of the safety window.

[0013] Preferably, the method also includes step S7 of anomaly identification and processing: Monitor the response characteristics of flow and temperature signals; When a pre-defined inconsistency is detected in the flow-temperature response, it is determined to be an abnormal disturbance; In response to an abnormal disturbance, the heating power is reduced to a safe value, and control is restored via a soft start after the disturbance is confirmed to have been eliminated.

[0014] An instant heating adaptive control system includes: The sensor layer includes sensors for detecting inlet water temperature, outlet water temperature, and flow rate; The controller layer includes: The partitioned thermal balance model module is used to store and calculate the partitioned dynamic thermal balance model; A feedforward-feedback co-controller is used to calculate the feedforward heating power and the feedback power correction amount; An online parameter identification module is used to perform the online parameter identification process to update the model parameters; The safety protection module is used to perform the power shaping, dynamic safety boundary limiting, and anomaly identification and handling. The actuator layer includes at least a heater controlled by the final power command.

[0015] Preferably, the functions of the controller layer are implemented by a microcontroller unit (MCU) or a digital signal processor (DSP) by executing stored program instructions.

[0016] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0017] An instant hot water purification device includes the aforementioned adaptive control system.

[0018] Compared with the prior art, the present invention has the following significant advantages: 1. Fast response speed: Through feedforward control of the partitioned thermal balance model, it can predict and actively compensate for disturbances the instant they occur, avoiding the lag problem of "deviation first, adjustment later" in traditional feedback control, significantly shortening the temperature recovery time and improving the user experience.

[0019] 2. High temperature control accuracy: Feedforward and feedback control work together. Feedforward solves most disturbances and feedback eliminates residual errors, achieving a perfect combination of fast response and precise stability. Even when the flow rate and inlet water temperature change significantly, the outlet water temperature fluctuation can be controlled within a narrow range.

[0020] 3. Good long-term stability: Online parameter identification technology enables the system to continuously adapt to changes in hardware characteristics (such as heater aging, scale accumulation, changes in pipeline heat dissipation, etc.), and maintain high control quality for a long time without manual calibration, reducing maintenance costs.

[0021] 4. Strong safety: Through multiple protection mechanisms such as dynamic power limit, power change rate limit, and temperature safety window, combined with abnormal operating condition identification, it effectively prevents safety risks such as dry burning and overheating, and improves system reliability.

[0022] 5. High adaptability: It has the ability to identify and respond to abnormal disturbances such as air lock, water interruption, and sudden cold water inflow. It can still maintain stable operation under various extreme working conditions, and its robustness is better than traditional control methods.

[0023] 6. Good versatility: The software-based control algorithm can be adapted to heaters of different power levels, different types of sensors and actuators, reducing the cost of product platform development. Attached Figure Description

[0024] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a diagram showing the overall architecture of the instant heating adaptive control system of the present invention. Figure 2 Here is the flowchart for feedforward control; Figure 3 For feedback control and collaboration flowchart; Figure 4 Flowchart for online parameter identification; Figure 5 This is a diagram of the system's state machine. Figure 6 This is a schematic diagram of a zoned thermal balance model; Figure 7 This is a flowchart for identifying and handling abnormal operating conditions. Detailed Implementation

[0025] This invention relates to adaptive feedforward control and online parameter identification based on a zoned dynamic thermal balance model. By modeling the heating water circuit into zones, identifying model parameters in real time, and combining feedforward and closed-loop coordinated control, it solves the problems of slow response, poor accuracy, and weak adaptability of traditional methods.

[0026] like Figure 1 As shown, the instant heating adaptive control system of the present invention includes three layers: a sensor layer, a controller layer, and an actuator layer, as detailed below.

[0027] The sensor layer includes sensors for detecting inlet water temperature, outlet water temperature, and flow rate; The controller layer includes: The partitioned thermal balance model module is used to store and calculate the partitioned dynamic thermal balance model; A feedforward-feedback co-controller is used to calculate the feedforward heating power and the feedback power correction amount; An online parameter identification module is used to perform the online parameter identification process to update the model parameters; The safety protection module is used to perform the power shaping, dynamic safety boundary limiting, and anomaly identification and handling. The actuator layer includes at least a heater controlled by the final power command.

[0028] The functions of the controller layer are implemented by a microcontroller unit (MCU) or a digital signal processor (DSP) by executing stored program instructions.

[0029] Reference Figure 1 The instant heating adaptive control method of the present invention includes the following steps: S1. Acquire the real-time operating parameters of the system, wherein the real-time operating parameters include at least the inlet water temperature, the outlet water temperature, and the flow rate; S2. Based on the partitioned dynamic heat balance model and the currently identified model parameters, calculate the feedforward heating power according to the real-time operating parameters and the target outlet water temperature. The partitioned dynamic heat balance model divides the heating water circuit into a heating zone, a mixing zone, and a pipeline zone and establishes heat balance equations for each zone. S3. Calculate the error between the outlet water temperature and the target outlet water temperature, and process the error through the feedback controller to obtain the feedback power correction amount; S4. The feedforward heating power and the feedback power correction amount are superimposed to obtain the preliminary power command; S5. Perform power shaping and dynamic safety boundary limiting on the preliminary power command to generate the final power command and output it to the heater for execution; S6. When the preset identification conditions are met, start the online parameter identification process and update the parameters of the partition dynamic thermal balance model according to the system's input and output data. S7. Anomaly Identification and Handling: such as Figure 7 As shown, the response characteristics of the flow and temperature signals are monitored; when a preset inconsistency is detected in the flow-temperature response, it is determined to be an abnormal disturbance; in response to the determination of an abnormal disturbance, the heating power is reduced to a safe value, and control is restored in a soft-start mode after the disturbance is confirmed to be eliminated. S8. Repeat the above steps to achieve continuous and stable control.

[0030] In the instant heating adaptive control method flow of the present invention, the system running state machine is as follows: Figure 5 As shown.

[0031] In specific implementation, the core key design of this invention is as follows.

[0032] 1. Establishment of a zoned dynamic thermal balance model.

[0033] For the heat transfer process of the instant heating system, the water outlet path is divided into three functional areas, such as... Figure 6 As shown: (1) Heating zone The heating zone is the water body located around the heater body. This area is the main point of heat injection, and its dynamic characteristics are determined by the heater's heat capacity, heating efficiency, and water flow rate. The output temperature of the heating zone is directly affected by the heating power and the inlet water flow rate.

[0034] (2) Mixed Zone The mixing zone is the pipe section located between the heater outlet and the temperature sensor. Within this zone, hot water exchanges heat with the pipe wall and the environment, and mixing delays occur due to differences in flow rates. The presence of the mixing zone causes a time lag and attenuation in the temperature sensor readings relative to the actual heater output.

[0035] (3) Pipeline area The pipeline area refers to the pipeline from the temperature sensor to the water outlet. This area mainly exhibits pure time delay and heat dissipation loss, and its characteristics are affected by pipeline length, insulation performance, and ambient temperature.

[0036] For these three regions, heat balance equations are established for each region to describe the temperature variation over time. Key parameters include the equivalent heat capacity, heat transfer coefficient, and time lag for each region. Based on these parameters, the time and power required for the system to reach the target outlet water temperature under given heating power and flow rate conditions can be predicted.

[0037] 2. Online parameter identification and model adaptation.

[0038] Parameters in a zoned thermal model (such as heat capacity and heat transfer coefficient) can drift with system aging, water quality changes, and environmental conditions. To maintain control performance, this invention employs an online parameter identification method, such as... Figure 4 As shown: (1) Identifying the timing of selection During periods of stable system operation with minimal disturbances (such as the steady-state phase of constant flow water intake), start-up parameter identification is performed. The system's temperature response is observed by applying small power disturbances within a safe range.

[0039] (2) Recursive estimation algorithm Algorithms such as recursive least squares or Kalman filtering are used to estimate model parameters in real time based on historical data of input (power, flow rate) and output (temperature response). To avoid control jitter caused by sudden parameter changes, the identification results are smoothed and updated gradually.

[0040] (3) Parameter validity verification Perform a reasonableness check on the identified parameters (such as parameter boundaries and rate of change limits). If a parameter is abnormal, maintain the original parameter and record the abnormal state to avoid erroneous parameters affecting control.

[0041] Through continuous online identification and updates, the system always maintains an accurate model of the current operating conditions, ensuring the effectiveness of the control strategy.

[0042] 3. Model-based feedforward-feedback coordinated control.

[0043] This invention employs a control strategy that combines feedforward and feedback. The feedforward control flow is as follows: Figure 2 As shown, the feedback control and coordination process is as follows: Figure 3 As shown.

[0044] (1) Feedforward controller design Based on the zoned heat balance model, the theoretical heating power required to reach the target temperature is calculated using the current inlet water temperature, the target outlet water temperature, and the real-time flow rate. Feedforward control can adjust the heating power in advance before disturbances (such as changes in flow rate or inlet water temperature) cause deviations in the outlet water temperature, thus achieving proactive compensation.

[0045] (2) Feedback controller design A temperature error closed-loop controller is employed to correct inaccurate predictions in the model. By monitoring the deviation between the actual outlet water temperature and the target temperature, a correction power increment is generated to compensate for model errors and unmodeled disturbances.

[0046] (3) Synergy between feedforward and feedback The power calculated by feedforward and the power corrected by feedback are superimposed to obtain the final heating power command. Feedforward ensures fast response, while feedback ensures accuracy and stability; together, they achieve a control effect that is both fast and accurate.

[0047] 4. Power Shaping and Dynamic Safety Boundary To avoid system overheating or other risks caused by rapid changes in power command, the power command is shaped: (1) Power change rate limit Limits are set on the rise and fall rates of power commands to avoid temperature overshoot or heater stress caused by instantaneous power jumps.

[0048] (2) Dynamic power limit Based on the current inlet water temperature, flow rate, and system status, the maximum allowable heating power is dynamically calculated to prevent overheating under low flow rate or high inlet water temperature conditions.

[0049] (3) Temperature safety window Set the allowable fluctuation range for the outlet water temperature. When the temperature approaches the upper limit, reduce the power in advance; when it approaches the lower limit, increase the power appropriately to create a soft constraint boundary and improve the smoothness and safety of control.

[0050] The following structural embodiments further illustrate the present invention. Example 1

[0051] This implementation is designed for scenarios requiring rapid heating of low inlet water temperature during winter. Operating conditions: In winter, the inlet water temperature is low (about 5-10℃), the user sets the target outlet water temperature to 40℃, and the flow rate is medium.

[0052] Control process: After the system collects the low inlet water temperature, the zoned thermal model calculates that a higher heating power is required. The feedforward controller immediately outputs a large initial power, causing the heating zone to heat up rapidly; As the outlet water temperature gradually approaches the target, the feedback controller makes fine adjustments based on the temperature error. The power shaping module limits the rate of power change to prevent overshoot; After reaching steady state, the temperature remains around the target value with slight fluctuations. The online parameter identification system runs continuously. If a change in heating efficiency is detected (such as scale buildup), the model parameters are automatically adjusted to maintain control accuracy.

[0053] Technical benefits: Compared with traditional PID control, the temperature reach time is shortened, the overshoot is reduced, and the steady-state accuracy is improved. Example 2

[0054] This implementation addresses dynamic response scenarios involving sudden changes in traffic flow. Operating condition description: The user suddenly increases the water flow rate during constant temperature water intake (e.g., from trickle to high flow rate).

[0055] Control process: The flow sensor detected an increase in flow rate; The feedforward controller recalculates the required power based on the new flow rate and immediately increases the heating power output. At this point, the outlet water temperature had not yet dropped significantly, thus achieving active compensation; The feedback controller monitors actual temperature changes and corrects for model prediction biases. The dynamic power limit adjusts the maximum allowable heating power based on flow rate changes to ensure safety. The system quickly stabilizes at the new operating point, and temperature fluctuations are controlled within a narrow range.

[0056] Technical effect: When traffic disturbance occurs, the temperature fluctuation amplitude is small and the recovery time is short, so users cannot perceive obvious temperature changes. Example 3

[0057] This implementation is designed for parameter adaptation scenarios after long-term use. Operating condition description: After the equipment has been used for a period of time, scale buildup on the heater surface leads to a decrease in heating efficiency, and aging of the pipelines leads to an increase in heat dissipation.

[0058] Control process: The initial system is controlled using initial model parameters; The online parameter identification module continuously monitors the system response characteristics during steady-state operation; A persistent deviation was detected between the actual temperature response and the model prediction; The recursive estimation algorithm identifies the changes in heat capacity and heat transfer coefficient in the heating zone; After validating the parameters, the model parameters are updated smoothly. The feedforward controller recalculates the heating power based on the new parameters, and the control performance is restored to the initial level.

[0059] Technical benefits: No manual calibration or maintenance is required; the system automatically adapts to changes in hardware characteristics and maintains high-precision control over a long period. Example 4

[0060] This implementation addresses the scenario of identifying and protecting against abnormal disturbances.

[0061] Operating condition description: Air bubbles mixed in the pipeline or a short-term water interruption occurs, resulting in abnormal flow and temperature signals.

[0062] Control process: The system detected abnormal fluctuations in the flow sensor signal, but the temperature sensor response was delayed. The anomaly detection module identifies inconsistencies in the flow-temperature response; If the problem is identified as an airlock or water supply interruption, immediately reduce the heating power to a safe level to avoid dry burning. Continuously monitor flow and temperature signals, and wait for the disturbance to subside; After confirming that the traffic has returned to normal and is stable, perform a soft start at a lower power. The system gradually returns to normal control mode, during which online parameter identification is paused.

[0063] Technical benefits: Effectively avoids safety risks under abnormal operating conditions and improves system robustness and reliability.

[0064] The present invention also protects a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described.

[0065] The present invention also protects an instant hot water purification device, including the aforementioned adaptive control system.

[0066] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All modifications made according to the spirit and essence of the main technical solution of the present invention should be covered within the scope of protection of the present invention.

Claims

1. An instant heating adaptive control method, characterized in that, Includes the following steps: S1. Acquire the real-time operating parameters of the system, wherein the real-time operating parameters include at least the inlet water temperature, the outlet water temperature, and the flow rate; S2. Based on the partitioned dynamic heat balance model and the currently identified model parameters, calculate the feedforward heating power according to the real-time operating parameters and the target outlet water temperature. The partitioned dynamic heat balance model divides the heating water circuit into a heating zone, a mixing zone, and a pipeline zone and establishes heat balance equations for each zone. S3. Calculate the error between the outlet water temperature and the target outlet water temperature, and process the error through the feedback controller to obtain the feedback power correction amount; S4. The feedforward heating power and the feedback power correction amount are superimposed to obtain the preliminary power command; S5. Perform power shaping and dynamic safety boundary limiting on the preliminary power command to generate the final power command and output it to the heater for execution; S6. When the preset identification conditions are met, start the online parameter identification process and update the parameters of the partition dynamic thermal balance model according to the system's input and output data.

2. The instant heating adaptive control method according to claim 1, characterized in that, The establishment of the partitioned dynamic thermal balance model in step S2 includes: The heating zone is the heater body and the surrounding water, and its dynamic characteristics are determined by the heater's heat capacity, heating efficiency, and water flow velocity. The mixing zone is the pipeline between the heater outlet and the temperature sensor, and its characteristics include heat exchange and mixing delay. The pipeline area refers to the pipeline between the temperature sensor and the water outlet, and its characteristics are pure time delay and heat loss. For the three regions mentioned above, heat balance equations are established for each region to describe the temperature change over time and predict the time and power required for the system to reach the target outlet water temperature under given heating power and flow rate conditions.

3. The instantaneous heating adaptive control method according to claim 1, characterized in that, The online parameter identification process described in step S6 includes: Within a time window when the system is running stably and the disturbance is less than the threshold, parameter identification is initiated by applying a small power disturbance and observing the system's temperature response. A recursive estimation algorithm is used to estimate the parameters of the partitioned dynamic thermal balance model in real time based on the input historical power and flow data and the output historical temperature response data. The identified parameters are tested for reasonableness, and the model parameters are updated smoothly after the test is passed.

4. The instantaneous heating adaptive control method according to claim 3, characterized in that, The recursive estimation algorithm is either the recursive least squares method or the Kalman filter algorithm.

5. The instantaneous heating adaptive control method according to claim 1, characterized in that, Step S5, which involves power shaping of the initial power command, includes: Set limits on the rise and fall rates of power commands; Based on the current inlet water temperature, flow rate, and system status, dynamically calculate and limit the maximum allowable heating power; Set the allowable fluctuation range of the outlet water temperature as a temperature safety window, and adjust the power in advance when the temperature approaches the boundary of the safety window.

6. The instantaneous heating adaptive control method according to claim 1, characterized in that, It also includes step S7 for anomaly identification and handling: Monitor the response characteristics of flow and temperature signals; When a pre-defined inconsistency is detected in the flow-temperature response, it is determined to be an abnormal disturbance; In response to an abnormal disturbance, the heating power is reduced to a safe value, and control is restored via a soft start after the disturbance is confirmed to have been eliminated.

7. An instant heating adaptive control system for implementing the method according to any one of claims 1 to 6, characterized in that, include: The sensor layer includes sensors for detecting inlet water temperature, outlet water temperature, and flow rate; The controller layer includes: The partitioned thermal balance model module is used to store and calculate the partitioned dynamic thermal balance model; A feedforward-feedback co-controller is used to calculate the feedforward heating power and the feedback power correction amount; An online parameter identification module is used to perform the online parameter identification process to update the model parameters; The safety protection module is used to perform the power shaping, dynamic safety boundary limiting, and anomaly identification and handling. The actuator layer includes at least a heater controlled by the final power command.

8. The system according to claim 7, characterized in that, The functions of the controller layer are implemented by a microcontroller unit (MCU) or a digital signal processor (DSP) by executing stored program instructions.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1 to 6.

10. An instant hot water purification device, characterized in that, It includes the adaptive control system as described in claim 7 or 8.

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