Temperature control method and instant temperature control device

Abstract

The application belongs to the technical field of temperature control equipment, and particularly relates to a temperature control method and instant temperature control equipment. The method comprises the following steps: acquiring the flow and temperature of fluid for instant temperature control through a sensor; for a feedforward control stage, a controller of the temperature control equipment determines feedforward driving parameters for controlling a heating body based on the flow and temperature, a preset target temperature and device performance parameters read from a memory of the temperature control equipment, wherein the device performance parameters represent the heating capacity of the heating body and the heat loss of the temperature control equipment; for an incremental control stage, the controller determines a correction increment based on the temperature, the preset target temperature and incremental control parameters read from the memory of the temperature control equipment; the controller corrects the feedforward driving parameters by using the correction increment to determine target driving parameters; and the controller controls the heating body based on the target driving parameters.

Description

Technical Field

[0001] This application belongs to the field of temperature control equipment technology, and particularly relates to a temperature control method and a temperature control device for real-time temperature adjustment. Background Technology

[0002] Real-time temperature control equipment is widely used in various terminal scenarios such as smart home appliances, fluid heat exchange, and commercial temperature control. It features fast fluid flow rate, low thermal inertia, and high dynamic adjustment requirements. In actual operation, the equipment is susceptible to various nonlinear and time-varying disturbances such as fluid flow fluctuations, ambient temperature drift, component aging, and pipe fouling. As a result, existing real-time temperature control equipment generally suffers from deficiencies in temperature control accuracy, dynamic response speed, and anti-interference capability due to significant temperature control lag and numerous interference factors. Summary of the Invention

[0003] In view of this, embodiments of this application provide a temperature control method and a real-time temperature control device to solve the problems of insufficient temperature control accuracy, dynamic response speed and anti-interference ability of existing real-time temperature control devices.

[0004] A first aspect of this application provides a temperature control method applied to a temperature control device for real-time temperature adjustment of a fluid. The temperature control device includes a heating element for heating the fluid. The method includes: acquiring the flow rate and temperature of the fluid for real-time temperature adjustment via a sensor; for a feedforward control phase, the controller of the temperature control device determines feedforward driving parameters for controlling the heating element based on the flow rate and temperature, a preset target temperature, and device performance parameters read from the memory of the temperature control device, wherein the device performance parameters characterize the heating capacity of the heating element and the heat loss of the temperature control device; for an incremental control phase, the controller determines a correction increment based on the temperature, the preset target temperature, and incremental control parameters read from the memory of the temperature control device; the controller uses the correction increment to correct the feedforward driving parameters to determine target driving parameters; and the controller controls the heating element based on the target driving parameters.

[0005] According to an embodiment of this application, the controller determines a correction increment based on the temperature, the preset target temperature, and incremental control parameters read from the memory of the temperature control device. This includes the controller performing the following operations: for the current data acquisition cycle, determining the temperature control error of the current data acquisition cycle based on the temperature of the current data acquisition cycle and the target temperature; and using a proportional-integral-derivative control algorithm, determining the correction increment based on the temperature control error of the current data acquisition cycle and the incremental control parameters.

[0006] According to an embodiment of this application, the incremental control parameters include multiple error proportionality coefficients and temperature-duty cycle conversion coefficients corresponding to different error ranges; wherein, determining the correction increment based on the temperature control error of the current data acquisition cycle and the incremental control parameters includes: determining a target error proportionality coefficient corresponding to the temperature control error of the current data acquisition cycle from the multiple error proportionality coefficients; determining the duty cycle correction amount based on the target error proportionality coefficient, the temperature control error of the current data acquisition cycle, the temperature control error of historical data acquisition cycles, and the temperature-duty cycle conversion coefficient, and determining the duty cycle correction amount as the correction increment.

[0007] According to an embodiment of this application, the duty cycle correction amount is calculated using the following formula:

[0008] in, This is the duty cycle correction amount. This represents the temperature control error during the current data acquisition cycle. Temperature control error during historical data collection period. This is the temperature-duty cycle conversion factor. This is the target error proportionality coefficient.

[0009] According to an embodiment of this application, the error proportional coefficient represents the proportional element coefficient of the PID control and is related to the temperature control response speed and steady-state stability of the temperature control device. The plurality of error proportional coefficients includes a first error proportional coefficient and a second error proportional coefficient, wherein the error range corresponding to the first error proportional coefficient is smaller than the error range corresponding to the second error proportional coefficient. Determining the target error proportional coefficient for the temperature control error in the current data acquisition cycle from the plurality of error proportional coefficients includes: based on the error range of the temperature control error, determining the target error proportional coefficient corresponding to the error range of the temperature control error from the first error proportional coefficient and the second error proportional coefficient.

[0010] According to an embodiment of this application, the target error proportionality coefficient is calculated using the following formula:

[0011] in, This is the second error scaling factor. This is the first error proportionality coefficient. The selection function represents the error range of the temperature control error. When the value is greater than x, the target error scaling factor should be selected. Otherwise choose .

[0012] According to an embodiment of this application, the controller of the temperature control device determines the feedforward drive parameters for controlling the heating element based on the flow rate and temperature, the preset target temperature, and the device performance parameters read from the memory of the temperature control device. The controller performs the following operations: determining the basic temperature control power of the heating element based on the flow rate and temperature, the target temperature, and the device performance parameters; determining the feedforward drive duty cycle based on the basic temperature control power, and using the feedforward drive duty cycle as the feedforward drive parameter.

[0013] According to an embodiment of this application, the feedforward drive duty cycle Calculated using the following formula:

[0014] in, The rated power of the heating element, Based on the temperature control power.

[0015] According to embodiments of this application, the temperature of the fluid includes the fluid inflow temperature; the equipment performance parameters include the heating element efficiency coefficient and the system loss compensation coefficient. The heating element efficiency coefficient is the ratio of the effective heat output power of the heating element to the fluid flowing through it under rated operating conditions to the rated input electrical power of the heating element, used to correct the deviation in the electro-thermal conversion efficiency of the heating element itself. The system loss compensation coefficient is a correction coefficient used to compensate for the additional heat loss caused by pipeline heat dissipation, fluid mixing heat loss, pipeline thermal resistance, and temperature sensor response lag, used to correct the overall heat loss deviation of the system; the incremental control parameters and the equipment performance parameters are calibrated under decoupled conditions.

[0016] According to an embodiment of this application, determining the basic temperature control power of the heating element based on the flow rate and temperature, the target temperature and the device performance parameters includes: determining the basic temperature control power based on the flow rate and fluid inflow temperature, the heating element efficiency coefficient, the system loss compensation coefficient and the target temperature.

[0017] According to an embodiment of this application, the base temperature control power Calculated using the following formula:

[0018] in, The fluid flow rate, For isobaric specific heat capacity, For the target temperature, The fluid inflow temperature, This is the system loss compensation coefficient. This is the efficiency coefficient of the heating element.

[0019] According to an embodiment of this application, the controller controls the heating element based on the target driving parameters, including: storing the target driving parameters in the register of the controller; and transmitting the target driving parameters stored in the register to the pulse width modulation heating driving module, so that the pulse width modulation heating driving module controls the temperature adjustment power of the heating element based on the target driving parameters.

[0020] According to an embodiment of this application, the target driving parameter includes a target driving duty cycle, and the feedforward driving parameter includes a feedforward driving duty cycle. The target driving duty cycle is calculated using the following formula:

[0021] in, Driven by the target duty cycle, For feedforward drive duty cycle, This is the duty cycle correction amount, i.e., the correction increment.

[0022] According to an embodiment of this application, the temperature control method further includes: if the correction increment does not meet the limiting constraint condition of a preset range, correcting the correction increment.

[0023] According to an embodiment of this application, the temperature of the fluid includes the fluid inflow temperature and the fluid outflow temperature.

[0024] According to an embodiment of this application, the method further includes using the controller to perform the following operations: for the current data acquisition cycle, filtering the fluid inflow temperature and the fluid outflow temperature acquired in the current data acquisition cycle to obtain new fluid inflow temperature and new fluid outflow temperature, and using the new fluid inflow temperature and new fluid outflow temperature to determine feedforward drive parameters and subsequent steps; performing pulse debouncing processing on the fluid flow rate acquired in the current data acquisition cycle to obtain new fluid flow rate, and using the new fluid flow rate to determine feedforward drive parameters and subsequent steps; and / or storing the new fluid inflow temperature, the new fluid outflow temperature and the new fluid flow rate.

[0025] A second aspect of this application provides a real-time temperature control device with a temperature control method. The temperature control device includes: a heating element for adjusting the temperature of a fluid; a sensor for collecting the flow rate and temperature of the fluid; a memory for storing device performance parameters and incremental control parameters; and a controller for controlling the heating element based on the flow rate and temperature of the fluid, the device performance parameters, and the incremental control parameters.

[0026] A third aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the above-described image layout methods.

[0027] The beneficial effects of this embodiment compared to the prior art are as follows: Based on real-time fluid flow and temperature prediction of temperature control requirements, and using feedforward drive parameters as a foundation, incremental correction is performed in conjunction with real-time temperature control errors. This effectively offsets deviations caused by operating condition disturbances such as flow fluctuations and environmental interference, compensating for the shortcomings of single feedforward control without feedback correction, and significantly improving temperature control accuracy. Furthermore, this embodiment can adaptively match temperature control parameters based on flow and temperature, effectively avoiding problems such as temperature overshoot and frequent equipment start-ups and shutdowns, reducing the demand for hardware resources, and effectively improving temperature control stability and accuracy. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 A flowchart of a temperature control method according to an embodiment of this application is shown; Figure 2 A flowchart is shown showing a temperature control method applied to an instantaneous temperature control device according to an embodiment of this application; Figure 3 A flowchart illustrating the calibration of the heating element efficiency coefficient and the system loss compensation coefficient according to an embodiment of this application is shown; Figure 4 A flowchart illustrating the calibration of the temperature-duty cycle conversion factor and the scaling factor according to an embodiment of this application is shown. Figure 5 A structural block diagram of a temperature control device according to an embodiment of this application is shown. Detailed Implementation

[0030] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0032] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0033] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0034] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."

[0035] Furthermore, in the description of this application, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0036] Instant temperature control equipment is a device that regulates (e.g., heats) the temperature of fluids (such as water, coffee, and milk) in real time. Examples include instant heating devices, which can be end products such as instant water dispensers, water heaters, smart coffee machines, baby formula warmers, and commercial fluid heating equipment.

[0037] Taking instant hot water dispensers as an example, the water is heated instantly as it flows through the heating chamber, with a short system lag time, typically tens to hundreds of milliseconds. However, heating efficiency, pipe heat dissipation, and sensor response exhibit nonlinearity and time-varying characteristics. In actual operation, long-term disturbances such as heating element aging, scale buildup, and ambient temperature drift place higher demands on temperature control algorithms. Therefore, the core performance indicators of instant heating technology are the accuracy of outlet water temperature control, heating response speed, anti-interference ability under operating conditions, operational stability, and mass production adaptability.

[0038] Existing instantaneous temperature control technologies can adapt to different levels of basic application scenarios, but it is still difficult to achieve a balance between the core requirements of high-precision temperature control, low resource consumption, low hardware cost, and high operational reliability. These shortcomings have become one of the main technical bottlenecks restricting the optimization and upgrading of instantaneous heating equipment towards higher precision, lower power consumption, and lower cost, as well as further improving mass production consistency and engineering implementation efficiency.

[0039] In view of this, embodiments of this application provide a temperature control method and a real-time temperature control device to solve the problems of insufficient temperature control accuracy, dynamic response speed and anti-interference ability of existing real-time temperature control devices.

[0040] In this embodiment, temperature control requirements are predicted based on real-time fluid flow and temperature. Using feedforward drive parameters as a foundation, incremental correction is applied in conjunction with real-time temperature control errors. This effectively offsets deviations caused by operating condition disturbances such as flow fluctuations and environmental interference, compensating for the lack of feedback correction in single feedforward control and significantly improving temperature control accuracy. Furthermore, this embodiment can adaptively match temperature control parameters based on flow and temperature, effectively avoiding problems such as temperature overshoot and frequent equipment start-ups and shutdowns, reducing hardware resource requirements, and effectively improving temperature control stability and accuracy.

[0041] Figure 1 A flowchart of a temperature control method according to an embodiment of this application is shown.

[0042] Please see Figure 1 The temperature control method of a temperature control device for real-time temperature adjustment of fluid in this application embodiment may include operations S101 to S105: In operation S101, the flow rate and temperature of the fluid for real-time temperature control are obtained through sensors.

[0043] In operation S102, for the feedforward control phase, the controller of the temperature control device determines the feedforward drive parameters for controlling the heating element based on the flow rate and temperature, the preset target temperature, and the device performance parameters read from the memory of the temperature control device.

[0044] In operation S103, for the incremental control phase, the controller determines the correction increment based on the temperature, the preset target temperature, and the incremental control parameters read from the memory of the temperature control device.

[0045] In operation S104, the controller uses the correction increment to correct the feedforward drive parameters and determine the target drive parameters.

[0046] In operation S105, the controller controls the heating element based on the target drive parameters.

[0047] Sensors are a class of sensing devices that can acquire various physical parameters of the environment, fluids, or equipment during operation in real time, and convert non-electrical physical signals into recognizable and transmittable electrical signals. Examples include flow sensors and temperature sensors. This embodiment uses a flow sensor to detect flow rate and a temperature sensor to detect temperature. The controller can include, but is not limited to, microcontroller units (MCUs), microprocessor units (MPUs), and digital signal processors (DSPs). For MCUs, different processor architectures such as 16-bit, 32-bit, and 64-bit can be used. This embodiment uses a 32-bit low-power MCU as an example.

[0048] Equipment performance parameters characterize the heating capacity of the heating element and the heat loss of the temperature control equipment, such as the efficiency coefficient of the heating element, the system loss compensation coefficient, the rated power of the heating element, and the specific heat capacity of the fluid at constant pressure.

[0049] The efficiency coefficient of the heating element includes the heating element efficiency coefficient. The heating element efficiency coefficient is the ratio of the effective heat output power of the heating element to the fluid flowing through it under rated operating conditions to the rated input electrical power of the heating element. It is used to correct the deviation of the heating element's own electro-thermal conversion efficiency. This parameter is only related to the material properties and physical structure of the heating element and is a fixed scalar parameter.

[0050] System loss compensation coefficient This is a correction factor used to compensate for additional system heat loss caused by pipeline heat dissipation, fluid mixing heat loss, pipeline thermal resistance, and temperature sensor response lag. It is used to correct the overall system heat loss deviation. This parameter is only related to the pipeline structure and installation environment of the temperature control system and is a fixed scalar parameter.

[0051] Throughout the entire process of temperature control equipment initiating temperature adjustment and providing real-time temperature regulation of the fluid, the sensors on the equipment continuously collect the fluid's flow rate and temperature in real time. The sensors periodically sample according to a preset data acquisition cycle, and the acquisition frequency can be adaptively adjusted according to the equipment's temperature control conditions. The collected flow rate and temperature are real-time dynamic data, accurately reflecting the true state of the fluid at any given moment. After completing signal acquisition, the sensors transmit the flow rate and temperature to the temperature control equipment's controller in real time, providing accurate and real-time raw data support for subsequent feedforward parameter calculations and error correction control, thus avoiding temperature control runaway problems caused by data lag or data deviation.

[0052] During the feedforward control phase, after receiving the collected real-time fluid working fluid data, the controller calculates the current fluid temperature control requirements by combining it with a preset target temperature (e.g., 45℃ set by the user). Simultaneously, it matches the retrieved equipment performance parameters and, through a built-in feedforward control algorithm model, quantifies the basic operating power required by the heating element under the current conditions, ultimately calculating the feedforward drive parameters for the heating element. These feedforward drive parameters are the initial drive parameters adapted to the current real-time operating conditions.

[0053] Incremental control achieves precise fine-tuning based on feedforward control, eliminating static errors and operating condition disturbance errors. The controller first uses the calculated feedforward drive parameters and the acquired fluid temperature. Based on the temperature, the preset target temperature, and the incremental control parameters read from the temperature control device's memory, the controller performs minute incremental adjustments and deviation compensation on the feedforward drive parameters. Finally, it calculates the target drive parameters that are adapted to the current real-time operating conditions and can accurately eliminate temperature deviations.

[0054] The controller uses the final determined target driving parameters as the final control command to update and precisely regulate the working parameters of the heating element in real time. Specifically, it adjusts the core working parameters such as the working power, running time, and start-stop frequency of the heating element so that the heating output power of the heating element is fully matched with the current fluid temperature control requirements.

[0055] By continuously iterating through the closed-loop process of data acquisition, feedforward prediction, incremental correction, and parameter control, the fluid temperature is dynamically and continuously adaptively adjusted, continuously reducing the difference between the actual fluid temperature and the preset target temperature. Ultimately, the fluid temperature output by the temperature control device is stably approached and locked at the target temperature, achieving high-precision and high-stability control of the fluid in real time.

[0056] According to the embodiments of this application, temperature control requirements are predicted based on real-time fluid flow and temperature. Using feedforward drive parameters as a basis, incremental correction is performed in conjunction with real-time temperature control errors. This effectively offsets deviations caused by operating condition disturbances such as flow fluctuations and environmental interference, compensating for the shortcomings of single feedforward control without feedback correction, and significantly improving temperature control accuracy. Furthermore, this embodiment can adaptively match temperature control parameters based on flow and temperature, effectively avoiding problems such as temperature overshoot and frequent equipment start-ups and shutdowns, reducing the demand for hardware resources, and effectively improving temperature control stability and accuracy.

[0057] Figure 2 A flowchart of a temperature control method applied to an instantaneous temperature control device according to an embodiment of this application is shown.

[0058] According to an embodiment of this application, the flow rate and temperature of the fluid used for real-time temperature control are obtained by means of sensors, including: obtaining the fluid inflow temperature when the fluid flows in through a first temperature sensor; obtaining the fluid outflow temperature when the fluid flows out of the temperature control device through a second temperature sensor; and obtaining the fluid volumetric flow rate when the fluid flows in through a flow sensor.

[0059] Throughout the entire process of the temperature control equipment starting its temperature adjustment operation and regulating the fluid temperature in real time, the sensors on the equipment continuously collect the fluid flow rate and temperature in real time. This step forms the basis for the data input of the temperature control closed-loop control. All collected parameters are obtained by external sensors directly connected to the MCU pins, and the collection rules are fully matched with the hardware initialization configuration. The specific collection method is as follows: See Figure 2 The temperature control device acquires the flow rate and temperature of the fluid used for real-time temperature adjustment through a real-time operating condition data acquisition module that includes sensors. For example, it acquires the real-time fluid inflow temperature into the temperature control device through a first temperature sensor (e.g., an inlet water temperature sensor). (Unit: °C), this sensor corresponds to the ADC sampling channel of the MCU; the real-time fluid outflow temperature from the temperature control device is collected through the second temperature sensor (outflow water temperature sensor). (Unit: °C), this sensor also corresponds to the ADC sampling channel of the MCU; it collects the real-time fluid volumetric flow rate of the fluid flowing into the temperature control equipment through a flow sensor. (Unit: ml / s) This sensor corresponds to the pulse capture channel of the MCU. The fluid inflow temperature, fluid outflow temperature, fluid volumetric flow rate and other data collected above together constitute the fluid flow rate and temperature data.

[0060] In some embodiments, the sampling period of different sensors is completely synchronized with the control period of the temperature control algorithm, strictly ensuring the timing consistency of flow and temperature data acquisition and temperature control adjustment. The acquired flow and temperature data are real-time dynamic data, which can accurately reflect the true state of the fluid at the current moment. After the sensors complete the physical signal acquisition, they convert non-electrical physical parameter signals such as temperature and flow into standardized electrical signals that can be recognized by the MCU, and transmit them to the controller of the temperature control device in real time. This provides accurate and synchronous raw data support for subsequent feedforward parameter calculation and error correction control, avoiding temperature control runaway problems caused by data lag, timing misalignment, and data deviation.

[0061] According to an embodiment of this application, the controller of the temperature control device determines the feedforward drive parameters for controlling the heating element based on the flow rate and temperature, the preset target temperature, and the device performance parameters read from the memory of the temperature control device. The controller performs the following operations: determining the basic temperature control power of the heating element based on the flow rate and temperature, the target temperature, and the device performance parameters; determining the feedforward drive duty cycle based on the basic temperature control power, and using the feedforward drive duty cycle as the feedforward drive parameter.

[0062] In some embodiments, see Figure 2 The following example uses a temperature control device as an instant heating device. Based on the real-time acquired flow rate and temperature, the user-preset target temperature, and the retrieved device performance parameters, the controller calculates the basic temperature control power of the heating element, which corresponds to the feedforward basic heating power of the instant heating device.

[0063] After obtaining the accurate feedforward basic heating power, the controller further combines the rated power of the heating element in the instantaneous heating device to convert the basic temperature control power into the corresponding PWM feedforward drive duty cycle, such as... Figure 2 The feedforward duty cycle is shown. This feedforward drive duty cycle determines more than 95% of the temperature control output power of the equipment, enabling it to quickly match real-time water flow conditions to complete pre-adjustment. It only reserves a very small correction margin for subsequent incremental closed-loop fine-tuning, greatly reducing the system's dynamic lag and overshoot problems, and laying the foundation for high-precision, high-response real-time temperature control.

[0064] According to embodiments of this application, the fluid temperature includes the fluid inflow temperature and the fluid volumetric flow rate; the equipment performance parameters include the heating element efficiency coefficient and the system loss compensation coefficient. The heating element efficiency coefficient is the ratio of the effective heat output power of the heating element to the fluid flowing through it under rated operating conditions to the rated input electrical power of the heating element, used to correct the deviation in the electro-thermal conversion efficiency of the heating element itself. The system loss compensation coefficient is a correction coefficient used to compensate for the additional heat loss of the system caused by pipeline heat dissipation, fluid mixing heat loss, pipeline thermal resistance, and temperature sensor response lag, used to correct the overall heat loss deviation of the system; the incremental control parameters and the equipment performance parameters are calibrated under decoupled conditions.

[0065] According to an embodiment of this application, the basic temperature control power of the heating element is determined based on the flow rate and temperature, the target temperature and equipment performance parameters, including: determining the basic temperature control power based on the flow rate, the fluid inflow temperature, the heating element efficiency coefficient, the system loss compensation coefficient and the target temperature.

[0066] Based on the collected fluid inflow temperature and fluid volumetric flow rate (i.e., flow rate), combined with the preset target temperature, heating element efficiency coefficient, and system loss compensation coefficient, the controller calculates the basic temperature control power of the heating element in real time. Figure 2 The feedforward base heating power shown The calculation of the feedforward foundation heating power is shown in formula (1): (1) in, For isobaric specific heat capacity, The target temperature.

[0067] After accurately calculating the feedforward base heating power, the controller adjusts the base temperature control power and the rated power of the heating element in the equipment performance parameters. ,Sure Figure 2 The feedforward drive duty cycle shown As shown in formula (2): (2) According to the embodiments of this application, the operating parameters of the heating element are controlled by calculating the feedforward drive duty cycle, which effectively reduces the problems of dynamic lag and temperature overshoot in the real-time temperature control system, and lays a solid foundation for the equipment to achieve high-precision and high-response real-time temperature control.

[0068] According to an embodiment of this application, the controller determines the correction increment based on the temperature, the preset target temperature, and the incremental control parameters read from the memory of the temperature control device. The controller performs the following operations: determining the temperature control error of the current data acquisition cycle based on the temperature and the target temperature of the current data acquisition cycle; and determining the correction increment using a proportional-integral-derivative control algorithm based on the temperature control error of the current data acquisition cycle and the incremental control parameters.

[0069] After the device completes the basic adjustment of the feedforward drive duty cycle, the controller performs incremental correction calculations for the current data acquisition cycle. First, the controller obtains the fluid outflow temperature corresponding to the current data acquisition cycle. The temperature error calculation module compares the real-time outflow temperature with the system's preset target temperature. By performing interpolation calculations, the temperature control error under the current data acquisition cycle can be accurately obtained, i.e. Figure 2 The error e(k) shown directly reflects the deviation between the actual fluid temperature and the set temperature under the current temperature control condition, providing a precise error basis for closed-loop correction. This represents the temperature control error during the current data acquisition cycle. The calculation is shown in formula (3): (3) Furthermore, the controller incorporates a Proportional-Integral-Derivative (PID) control algorithm. Using the calculated real-time temperature control error as the core correction basis, and combining this with pre-stored equipment performance parameters, it dynamically calculates the real-time duty cycle correction, i.e., the correction increment. These equipment performance parameters can be matched to the heating element's operating characteristics, system heat exchange losses, and other inherent operating conditions, ensuring that the calculated correction closely matches the actual operating state of the equipment. This avoids adjustment deviations caused by single error corrections and improves the adaptability and accuracy of the correction parameters.

[0070] Finally, the controller superimposes the calculated duty cycle correction amount with the feedforward drive duty cycle of the current cycle to complete the dynamic compensation correction of the basic pre-adjustment parameters, and finally determines the target drive duty cycle that is adapted to the current real-time operating conditions.

[0071] According to the embodiments of this application, based on the feedforward prediction parameters and the real-time closed-loop error as the correction basis, a micro-precise parameter adjustment is achieved through the PID algorithm. Only the feedforward basic duty cycle is slightly modified, which not only retains the advantage of fast response of feedforward control, but also makes up for the defects of feedforward control that have no closed-loop feedback and cannot eliminate static error, effectively improving temperature control accuracy and operating stability.

[0072] According to embodiments of this application, the incremental control parameters include multiple error proportionality coefficients and temperature-duty cycle conversion coefficients corresponding to different error ranges.

[0073] According to an embodiment of this application, the controller determines the correction increment based on temperature, a preset target temperature, and incremental control parameters read from the memory of the temperature control device, including: determining a target error ratio coefficient from multiple error ratio coefficients relative to the temperature control error of the current data acquisition cycle; determining a duty cycle correction amount based on the target error ratio coefficient, the temperature control error of the current data acquisition cycle, the temperature control error of historical data acquisition cycles, and the temperature-duty cycle conversion coefficient; and determining the duty cycle correction amount as the correction increment.

[0074] Temperature-Duty Cycle Conversion Factor The unit is % / ℃, which refers to the basic adjustment of the PWM drive duty cycle corresponding to a unit temperature deviation. It is an inherent conversion scalar of the system and is only related to the rated power of the heating element and the heat capacity characteristics of the pipeline. It is the basic reference parameter for calculating the PID correction and has no cross-correlation with the heating element efficiency coefficient and system loss compensation coefficient of the feedforward link.

[0075] The error proportional gain is the proportional element coefficient of the PID control core, directly determining the response speed and steady-state stability of the closed-loop system: an excessively large coefficient can easily lead to temperature overshoot and oscillation, while an excessively small coefficient results in a lag in temperature deviation correction response. To balance fast response under large deviations and steady-state accuracy under small deviations, this embodiment decomposes the proportional amplification factor into a small error proportional gain. With large error proportionality coefficient Two independently calibrated settings, each adapted to different temperature error ranges, with a small error scaling factor. With large error proportionality coefficient That is, the first error proportionality coefficient and the second error proportionality coefficient.

[0076] The aforementioned high-precision incremental correction target-driven duty cycle determination method is completely decoupled from the feedforward basic control link. It only performs fine correction on the small temperature deviation remaining after feedforward pre-control, without interfering with the calculation process of feedforward basic power, and is suitable for high-precision real-time temperature control scenarios.

[0077] In this embodiment, the incremental control parameters pre-stored in the calibrated PID parameter storage area of ​​the temperature control device include multiple error proportional coefficients corresponding to different error ranges and temperature-duty cycle conversion coefficients. Specifically, these are fixed parameters that are solidified in the device's memory after mass production calibration, including small error proportional coefficients, large error proportional coefficients, error switching thresholds, and temperature-duty cycle conversion coefficients, which can provide standardized parameter support for the accurate calculation of duty cycle correction.

[0078] For detailed correction procedures, please refer to [link / reference]. Figure 2 The controller first calculates the real-time temperature control error Error0 (i.e., based on the fluid outflow temperature of the current data acquisition cycle and the preset target temperature) Figure 2 e(k)), and synchronously retrieve the temperature control error Error1 (i.e., the previous historical data acquisition cycle stored in the memory) Figure 2 e(k-1)) completes the periodic sampling and retention of error data. Then, the controller dynamically matches the corresponding target error ratio coefficient from the first error ratio coefficient and the second error ratio coefficient according to the current real-time temperature control error value range, and completes the coefficient adaptive switching through the error switching threshold: when the absolute value of the real-time temperature control error is greater than the set threshold, the large error ratio coefficient is selected as the current target error ratio coefficient, and vice versa, as shown in formula (4), to realize the differentiated correction and adaptation under different deviation conditions.

[0079] (4) in, This is the target error proportionality coefficient. The function is used in If the value is greater than a preset threshold x, for example, x could be 5.0, then return... Otherwise return .

[0080] See Figure 2 After determining the target error proportional coefficient, the incremental PID correction calculation module of the controller adopts a lightweight incremental PID algorithm, combining the current cycle temperature control error, historical cycle temperature control error, target error proportional coefficient, and temperature-duty cycle conversion coefficient. The duty cycle correction for the current cycle is calculated. As shown in formula (5): (5) Finally, the controller, through the total duty cycle synthesis and limiting module, superimposes the calculated duty cycle correction amount onto the feedforward drive duty cycle of the current cycle to obtain a target drive duty cycle that accurately adapts to the real-time operating conditions, i.e., the target drive parameter. This achieves refined and graded correction of temperature deviations, significantly improving temperature control stability and control accuracy under small deviation conditions. Target drive duty cycle The calculation is shown in formula (6): (6) In some embodiments, see Figure 2 The total duty cycle synthesis and limiting module can control the target drive duty cycle. Implement a hard limit constraint of 0-100% to prevent the driver output from exceeding the limit and damaging the hardware.

[0081] According to an embodiment of this application, the temperature control method further includes: if the correction increment does not meet the limiting constraint condition of the preset range, correcting the correction increment.

[0082] Based on the aforementioned incremental duty cycle correction, a duty cycle correction amount (i.e., correction increment) limiting constraint logic is added to avoid temperature control fluctuations caused by abnormal single correction amounts, further improving the stability of real-time temperature regulation of the equipment. In this embodiment, after calculating the duty cycle correction amount, the temperature control method further performs correction amount verification and constraint operations. The overall correction logic, in conjunction with the feedforward control loop and the PID incremental calculation loop, achieves ultimate optimization of closed-loop temperature control.

[0083] Specifically, the controller calculates the duty cycle correction amount for the current cycle using an incremental PID algorithm. Then, the correction amount is substituted into the preset limiting constraint for legality verification. In this embodiment, the preset limiting constraint is a duty cycle range of ±5%, that is, the maximum duty cycle correction increment allowed in a single execution is [-5%, +5%]. If it is determined that the currently calculated duty cycle correction amount is within the preset range, then the correction amount is determined to meet the limiting constraint and can be directly used to superimpose the feedforward drive duty cycle to calculate the target drive duty cycle.

[0084] If the current duty cycle correction exceeds the preset limit of ±5%, it is determined that the correction does not meet the limit constraint condition. The controller will then forcibly correct the excessive duty cycle correction, limiting the actual duty cycle correction used in the calculation to the ±5% limit threshold. This limit constraint mechanism completely eliminates the problem of excessive single duty cycle correction, effectively avoiding defects such as fluid temperature overshoot, temperature oscillation, and unstable operating conditions caused by excessive single control amplitude. While ensuring the ability to finely correct temperature control, it significantly improves the dynamic stability and anti-interference capability of the real-time temperature control system.

[0085] According to embodiments of this application, the temperature control method further includes using a controller to perform the following operations: for the current data acquisition cycle, filtering the fluid inflow temperature and fluid outflow temperature acquired in the current data acquisition cycle to obtain new fluid inflow temperature and new fluid outflow temperature, and using the new fluid inflow temperature and new fluid outflow temperature to determine feedforward drive parameters and subsequent steps; performing pulse de-jitter processing on the fluid flow rate acquired in the current data acquisition cycle to obtain new fluid flow rate, and using the new fluid flow rate to determine feedforward drive parameters and subsequent steps; and / or storing the new fluid inflow temperature, new fluid outflow temperature and new fluid flow rate.

[0086] This embodiment describes the sampling data preprocessing and caching mechanism of the temperature control method. Before performing steps such as feedforward drive duty cycle calculation, temperature control error calculation and target drive duty cycle correction, the original collected fluid flow rate and temperature are preprocessed to reduce noise, avoid data jump problems caused by hardware sampling noise and instantaneous operating condition fluctuations, and ensure the accuracy and stability of the temperature control algorithm.

[0087] Specifically, for the current data acquisition cycle, the controller can perform moving average filtering on the original fluid inflow and outflow temperatures collected by the sensor to remove high-frequency noise and instantaneous abnormal fluctuations during temperature sampling, and calculate the new, noise-reduced fluid inflow and outflow temperatures. Simultaneously, the controller performs pulse de-jitter processing on the fluid flow rate collected in the current cycle, filtering out interference noise and instantaneous false trigger signals during flow rate pulse acquisition, resulting in a stable and reliable new fluid flow rate.

[0088] In some alternative embodiments, a first-order low-pass filter can be used instead of a moving average filter, with the filter coefficient set to 0.2-0.3 or other values.

[0089] In this embodiment, the new fluid inflow temperature, new fluid outflow temperature, and new fluid flow rate after filtering and anti-shake preprocessing will be used as effective operating parameters to replace the original sampled data in all subsequent algorithm processes. These parameters will be used to perform steps such as feedforward drive duty cycle calculation, temperature control error solving, duty cycle increment correction, and target drive duty cycle determination, thereby avoiding problems such as abnormal fluctuations in temperature control power and incorrect temperature control correction caused by changes in the original data source.

[0090] Furthermore, the controller can synchronously store the pre-processed effective working fluid parameters into the MCU's RAM register. On the one hand, this provides real-time and reliable data support for the temperature control algorithm calculation in the current data acquisition cycle. On the other hand, it can retain the cycle operating data, providing a stable data foundation for historical error comparison, incremental PID calculation, and parameter iterative correction, effectively improving the anti-interference capability and operational consistency of the overall temperature control system.

[0091] According to an embodiment of this application, the controller controls the heating element based on target driving parameters, including: storing the target driving parameters in the controller's register; and transmitting the target driving parameters stored in the register to the pulse width modulation heating drive module, so that the pulse width modulation heating drive module controls the temperature adjustment power of the heating element based on the target driving parameters.

[0092] This embodiment uses a hardware-driven control method based on the target drive duty cycle (i.e., target drive parameters) to achieve precise power output of the heating element. This method is used to complete closed-loop temperature control adjustment in a single control cycle, thereby achieving stable and precise control of the heating element's operating parameters.

[0093] See Figure 2 After the controller calculates the target drive duty cycle for the current cycle, it first writes the final effective target drive duty cycle into the corresponding drive register of the MCU in real time to complete the temporary storage and locking of the control parameters, ensuring the uniqueness and stability of the drive parameters within the current control cycle, and avoiding abnormal jumps in drive parameters caused by algorithm operation fluctuations.

[0094] Subsequently, the MCU transmits the target drive duty cycle stored in the register to the device's pulse width modulation heating drive module (i.e., Figure 2 The PWM heating drive module in the middle adjusts the heating element (i.e., according to the received target drive duty cycle) based on the pulse width modulation heating drive module. Figure 2 The real-time temperature control power of the instantaneous heating element is precisely matched to the current fluid temperature control requirements, thereby completing the closed-loop temperature regulation operation of a single control cycle.

[0095] Meanwhile, this temperature control method employs a periodic cyclic execution mechanism. Within each data acquisition cycle, the device repeatedly executes the entire process of fluid flow and temperature data acquisition and preprocessing, feedforward drive duty cycle calculation, incremental error correction, target drive duty cycle update, and hardware power output. Furthermore, it utilizes calibration parameters stored in the memory throughout the algorithm calculation, eliminating the need for repeated parameter calibration. This allows for continuous dynamic adaptation to real-time changes in fluid conditions, achieving uninterrupted real-time closed-loop control of the fluid outlet temperature and effectively ensuring the stability and consistency of temperature control under all operating conditions.

[0096] In some embodiments, the temperature control device can be configured with an expandable Flash storage unit for persistent storage of fault data, operating parameters, and user-remembered data. The device can record various operating parameters and abnormal fault information during operation in real time, while retaining user-defined temperature control parameters and other memorized data. This facilitates fault tracing, operational status review, and reuse of user-remembered parameters, improving the reliability and ease of use of the device. Furthermore, the device utilizes the spare storage space of the Flash memory to temporarily store OTA upgrade packages, providing data storage support for iterative upgrades of the device's program.

[0097] The device has a dedicated serial port for OTA remote upgrades. Upgrade programs can be transmitted via the serial port through an external terminal. The upgrade package stored in Flash memory is used to complete the iterative update of the device firmware without disassembling the device to burn programs. This allows for convenient algorithm optimization, function upgrades, and vulnerability fixes, greatly improving the ease of later maintenance and function expansion of the device.

[0098] Meanwhile, this device adopts a multi-channel serial port layered communication architecture, for example, configuring 5 independent serial ports to achieve differentiated functional communication, corresponding to multiple functions such as operation panel communication, peripheral data interaction, device debugging, and OTA upgrades. Through the independent division of labor among multiple serial ports, isolated transmission of human-machine interaction data, peripheral sensor data, debugging data, and upgrade data is achieved, avoiding mutual interference between various communication data. This effectively ensures the real-time performance, stability, and security of data interaction in the temperature control equipment, further improving the overall system's operational reliability and scalability.

[0099] Figure 3 A flowchart illustrating the calibration process of the heating element efficiency coefficient and the system loss compensation coefficient according to an embodiment of this application is shown.

[0100] This embodiment specifically illustrates the factory calibration and verification method of the equipment performance parameters solidified in the temperature control equipment memory. The equipment performance parameters mainly include the heating element efficiency coefficient and the system loss compensation coefficient. Both types of parameters are independently and decoupledly calibrated and solidified in the equipment's Flash memory before the equipment leaves the factory, providing accurate and reusable basic calibration parameters for the equipment's feedforward control algorithm, ensuring the temperature control accuracy under all operating conditions from the source.

[0101] Taking an instantaneous water heating device as an example, the heating element efficiency coefficient is calibrated at the factory using an independent open-loop calibration method, avoiding system losses and PID feedback interference throughout the process, ensuring that the parameters only characterize the inherent electro-thermal conversion characteristics of the heating element itself. (See also...) Figure 3 During calibration, the system loss compensation coefficient of the temperature control equipment is set to an initial value, such as 1.0, and the PID feedback control loop is closed, retaining only the open-loop feedforward control channel; simultaneously, a fixed standard water flow rate (e.g., ), fixed inlet water temperature (e.g.) A fixed PWM drive duty cycle is applied, and the theoretical output power of the heating element is calculated using formula (7). .

[0102] (7) in, For a fixed PWM drive duty cycle, It is the rated input electrical power of the heating element.

[0103] After the outlet water temperature of the equipment reaches a steady state, the stable outlet water temperature is collected, and the effective power of the heating water on the liquid flowing through it is calculated according to the thermodynamic formula of the specific heat capacity of water at constant pressure, as shown in formula (8): (8) (9) Among them, the specific heat capacity of water at constant pressure Take a fixed constant , Used to convert volumetric flow rate units ml / s to mass flow rate units kg / s (the density of water is approximately 1 kg / L).

[0104] The calibration value of the heating element efficiency coefficient is calculated by formula (9). The initial setting value of the heating element efficiency coefficient is iteratively corrected based on the calibration value. For example, if the initial setting value is greater than the calibration calculation value, it is lowered, and if it is less than the calibration calculation value, it is raised, until the outlet water temperature under feedforward control is stable within ±1℃ of the target temperature, thus completing the independent calibration of the heating element efficiency coefficient of a single device.

[0105] In some embodiments, after the heating element efficiency coefficient is calibrated, the equipment further performs independent calibration of the system loss compensation coefficient. This calibration process is completely decoupled from the PID control loop and does not interfere with the heating element efficiency coefficient calibration. This effectively ensures the independence and accuracy of the feedforward control parameters and adapts to the high-precision temperature control requirements of instantaneous temperature control equipment under all operating conditions.

[0106] The core calibration design concept of the system loss compensation coefficient includes three points: achieving parameter decoupling, ensuring accuracy under all operating conditions, and optimizing mass production efficiency. First, it achieves complete decoupling of the two feedforward parameters. The heating element efficiency coefficient is calibrated under rated operating conditions where system heat loss is negligible, representing only the electro-thermal conversion characteristics of the heating element itself. By constructing extreme loss conditions, additional system heat losses such as pipeline heat dissipation and structural thermal resistance become the dominant influencing factors on temperature control accuracy. The influencing factors of the two types of calibration conditions do not overlap at all, completely avoiding the defects of traditional parameter calibration where parameters are mutually coupled and mutually exclusive. Second, it achieves comprehensive coverage of temperature control accuracy under all operating conditions. The proportion of heat loss in an instantaneous heating system is negatively correlated with the inlet water flow rate and positively correlated with the temperature rise. Low inlet water temperature, low flow rate, and high target temperature represent the boundary conditions with the highest proportion of overall heat loss and the greatest difficulty in feedforward compensation. Parameters calibrated based on this extreme scenario ensure that feedforward compensation accuracy meets the standard under extreme conditions, and the compensation accuracy under normal operating conditions is even higher, completely solving the problem of under-compensation for extreme temperature scenarios that exists in conventional calibration methods. Third, the mass production parameter adjustment process is simplified. The water circuit structure and insulation structure of temperature control equipment of the same model are completely fixed. The system loss characteristics are inherent properties of the whole machine and there is no need to repeat the calibration for each unit.

[0107] The specific calibration and parameter solidification process is as follows: First, after calibrating the heating element efficiency coefficient, the efficiency coefficient is fixed to the calibrated value. The PID feedback control loop is completely disabled, and only the open-loop feedforward control channel is retained to eliminate the interference of closed-loop correction on calibration accuracy. Then, an extreme calibration condition with low inlet water temperature, low flow rate, and high target temperature is constructed to maximize system heat loss and accurately highlight the impact of system losses on temperature control accuracy. After the equipment outlet water temperature reaches a stable state under this condition, the deviation between the steady-state outlet water temperature and the preset target temperature is collected, and the dimensionless system loss compensation coefficient with a value greater than 1 is gradually adjusted. Until the outlet water temperature is stably controlled within the target temperature range of ±0.5℃ in pure feedforward control mode, and at the same time, a power correction space of no more than 5% is reserved for subsequent PID feedback fine-tuning, so as to complete the independent and accurate calibration of the system loss compensation coefficient.

[0108] After calibration, the finalized system loss compensation coefficients are stored in the device's Flash memory. Based on the fixed loss characteristics of the entire machine, only a single extreme condition calibration is required during the prototype stage. All devices in the mass production batch can directly reuse these stored parameters. During mass production, only the heating element efficiency coefficient needs to be calibrated for each unit, greatly simplifying the mass production debugging process and shortening the mass production cycle. During normal operation, the controller directly reads the stored system loss compensation coefficients to participate in feedforward power calculations, eliminating the need for users or equipment to dynamically adjust calibration parameters. This steadily improves the fluid temperature control accuracy and stability under all operating conditions, especially extreme loss conditions.

[0109] Figure 4A flowchart illustrating the calibration process of the temperature-duty cycle conversion factor and the scaling factor according to an embodiment of this application is shown.

[0110] This embodiment specifically illustrates the factory-independent calibration method and dynamic application logic for the temperature-duty cycle conversion coefficient and proportional amplification coefficient (i.e., error proportional coefficient) embedded in the device memory. These two types of parameters are the core reference parameters for incremental PID closed-loop fine correction. Both are decoupled and calibrated before leaving the factory and embedded in the device's Flash memory. They are completely independent of the feedforward control loop, completely eliminating parameter coupling interference and ensuring the response speed and steady-state accuracy of closed-loop temperature control correction.

[0111] First, the temperature-duty cycle conversion coefficient... The independent calibration process is explained below. This parameter characterizes the inherent conversion relationship between temperature deviation and PWM drive duty cycle adjustment, and is the benchmark parameter for calculating incremental PID correction. Figure 4 As shown, to ensure accurate and completely decoupled calibration results, the dual feedforward core parameters, namely the heating element efficiency coefficient and system loss compensation coefficient, which have been factory-calibrated, are fixed throughout the calibration process. This ensures that the feedforward control outputs a stable basic heating power and completely shields the feedforward link from interfering with the calibration of the PID reference parameters.

[0112] During the specific calibration process, the PID feedback control of the equipment is activated, while the proportional amplification factor is fixed. To eliminate the superposition interference of proportional gain on the calibration process, ensuring that the calibration results only reflect the inherent characteristics of temperature deviation and duty cycle adjustment. After the feedforward power stabilizes and the outlet water temperature reaches a steady state, a stable temperature deviation of 2℃~3℃ is created through controllable methods such as pausing heating, adjusting the inlet water flow rate, and modifying the target temperature. The dynamic process of the system temperature returning to normal is observed and iteratively adjusted. Value: If the temperature recovery time is greater than 10 seconds, increase the value accordingly. To improve correction efficiency; if the temperature overshoot is greater than 1°C, the value should be appropriately reduced. To suppress overshoot, repeated iterative calibrations were performed until the system temperature returned to normal within 3 to 5 seconds and the temperature overshoot was ≤1℃. This process was used to accurately calibrate and store the temperature-duty cycle conversion coefficient.

[0113] After completion After calibrating the baseline parameters, the independent calibration of the dual-speed PID proportional gain (i.e., the error proportional gain) is further completed, including the small error proportional gain adapted to small error operating conditions. Large error proportional coefficient for adapting to large error operating conditions This solves the technical contradiction that a single proportional coefficient cannot simultaneously achieve rapid response to large deviations and high precision in steady-state conditions with small deviations.

[0114] For small error proportional coefficient The calibration locks onto the already calibrated unit. The parameters are set to ensure the system operates within a small error range where the absolute value of the temperature error is ≤5℃. Small temperature deviations are introduced in a controllable manner, and the system is continuously iteratively adjusted. The numerical values ​​are maintained until the system reaches a steady state, at which point the continuous fluctuation range of the outlet water temperature is ≤ ±0.3℃, meeting the requirements for small-deviation steady-state high-precision temperature control and completing the process. Calibration. For large error scaling factors. The calibration is also fixed. A baseline value is used to enable the system to operate within a large error range where the absolute value of the temperature error is greater than 5°C. A significant, controllable temperature deviation is introduced, and iterative optimization is performed. The numerical value ensures that the system can quickly bring the deviated outlet water temperature back to within ±1℃ of the target temperature within 5 seconds, meeting the requirement for rapid correction of large deviations and completing the task. calibration.

[0115] This embodiment also defines the dynamic switching logic of the dual proportional coefficients. The device presets 5℃ as the error switching threshold. The controller collects the current temperature error Error0 in real time during each control cycle and dynamically matches the current effective proportional coefficient according to the absolute value of the error. For the specific switching logic, please refer to formula (4). Calibration complete. , , All parameters are stored in the device's Flash memory. During normal operation, the device directly calls the stored parameters without the need for on-site parameter adjustment and calibration. The dual-level dynamic proportional coefficient adapts to all error conditions, ensuring both rapid response under large temperature deviations and ultra-high steady-state temperature control accuracy under small temperature deviations, significantly improving the dynamic performance and steady-state stability of the whole machine's closed-loop temperature control system.

[0116] The temperature control method provided in this application adopts a dual-stage decoupled closed-loop temperature control architecture that combines feedforward pre-control with incremental PID fine-tuning. With the help of a systematic factory parameter calibration and solidification mechanism and optimized hardware resource configuration, the overall technical solution achieves many beneficial effects that are significantly superior to the prior art.

[0117] First, this application significantly improves the temperature control accuracy of instantaneous temperature regulation. The feedforward stage relies on pre-compensation of more than 95% of the heating power based on pre-working fluid parameters such as inlet water temperature and inlet water flow rate, which can pre-control the outlet water temperature within the target value ±0.5℃ range. The subsequent PID closed-loop stage only performs fine incremental correction for residual small temperature deviations, which can control the steady-state outlet water temperature fluctuation within ±0.3℃, and the temperature overshoot during the heating process does not exceed 1℃. This effectively solves the problems of slow response, large steady-state fluctuation, and undercompensation under extreme conditions in traditional instantaneous temperature control systems, and fully meets the requirements of high-precision constant temperature control.

[0118] Secondly, it significantly improves the efficiency of mass production debugging and batch consistency of equipment. This embodiment achieves complete decoupling calibration of feedforward parameters and PID parameters. Key parameters such as system loss compensation coefficient, temperature-duty cycle conversion coefficient, and magnitude error ratio coefficient can be solidified in the equipment Flash after a single calibration of the prototype. Mass production equipment of the same model can be directly reused. During the mass production stage, only the heating element efficiency coefficient needs to be calibrated independently for each unit, which greatly shortens the mass production parameter adjustment cycle, reduces the difficulty of mass production debugging, and improves the temperature control consistency and operational stability of batch equipment.

[0119] Meanwhile, this embodiment achieves precise hardware resource adaptation and low-power, low-cost operation. According to the actual resource requirements of the algorithm, a 32-bit low-power MCU can be matched. At a main frequency of 48MHz, the time for a single complete temperature control algorithm is less than 1ms, and the CPU utilization rate is less than 1%. While ensuring high-precision and high-real-time temperature control computing capabilities, it avoids redundant waste of hardware resources and effectively reduces the power consumption and hardware cost of the device.

[0120] Finally, this embodiment possesses strong functional scalability and scenario adaptability. The device's fixed code reserves standardized parameter interfaces and hardware driver interfaces. Combined with an expandable Flash storage unit and a 5-channel independent serial port architecture, it can stably realize extended functions such as OTA remote upgrades, persistent storage of fault information, operating parameters, and user memory data, multi-peripheral data interaction, and device debugging. This facilitates subsequent algorithm iteration optimization and functional upgrades, and can flexibly adapt to different mass production application scenarios, effectively improving the intelligence level of the device and the versatility of the product.

[0121] Figure 5 A structural block diagram of a temperature control device according to an embodiment of this application is shown.

[0122] like Figure 5 As shown, the real-time temperature control device 500 with a temperature control method includes: a heating element 510 for regulating the temperature of a fluid; a sensor for collecting the flow rate and temperature of the fluid; a memory 520 for storing device performance parameters and incremental control parameters; and a controller 530 for controlling the heating element based on fluid working fluid data, device performance parameters, and incremental control parameters.

[0123] The sensors can collect the fluid inflow temperature in real time through the first temperature sensor 541, the fluid outflow temperature through the second temperature sensor 542, and the fluid flow rate through the flow sensor 543.

[0124] In some embodiments, the temperature control device 500 may also include an operation panel module 550. Users can input the desired target temperature using the key input unit on the operation panel module 550. The operation panel module 550 may also include a temperature display unit to display the water temperature in real time, and a running status indicator light to show the operating status of the temperature control device 500. Simultaneously, users can operate the start / stop control unit on the operation panel module 550 to control the operating status of the temperature control device 500. The operation panel module 550 can achieve bidirectional communication with the controller 530, such as command input or status display output.

[0125] In some embodiments, the memory 520 may use a scalable Flash memory module to store device performance parameters and logs of the temperature control device 500 during operation. The controller 530 may be a 32-bit low-power microcontroller, for example, with more than 128KB of Flash memory and more than 8KB of RAM. It may also be a microcontroller with a clock speed greater than 48MHz and five or more serial ports.

[0126] In some embodiments, the controller 530 transmits the stored target driving parameters to the pulse width modulation heating drive module 560, and the pulse width modulation heating drive module 560 controls the temperature adjustment power of the heating element 510 based on the target driving parameters to drive the heating element 510 to output power according to the set power.

[0127] According to embodiments of this application, the temperature control device predicts temperature adjustment needs based on real-time fluid flow and temperature. Using feedforward drive parameters as a foundation, it performs incremental correction based on real-time temperature control errors. This effectively offsets deviations caused by operating condition disturbances such as flow fluctuations and environmental interference, compensating for the shortcomings of single feedforward control without feedback correction, and significantly improving temperature control accuracy. Furthermore, this embodiment can adaptively match temperature adjustment parameters based on flow and temperature, effectively avoiding problems such as temperature overshoot and frequent equipment start-ups and shutdowns, reducing hardware resource requirements, and effectively improving temperature control stability and accuracy.

[0128] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0129] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0130] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0131] In the embodiments provided in this application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings or direct couplings or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0132] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0133] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0134] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0135] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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. Such 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 this application, and should all be included within the protection scope of this application.

Claims

1. A temperature control method, applied to a temperature control device for real-time temperature adjustment of a fluid, the temperature control device comprising a heating element for heating the fluid, characterized in that, include: The flow rate and temperature of the fluid used for real-time temperature control are obtained through sensors. For the feedforward control stage, the controller of the temperature control device determines the feedforward drive parameters for controlling the heating element based on the flow rate and temperature, the preset target temperature, and the device performance parameters read from the memory of the temperature control device. The device performance parameters characterize the heating capacity of the heating element and the heat loss of the temperature control device. For the incremental control phase, the controller determines the correction increment based on the temperature, the preset target temperature, and the incremental control parameters read from the memory of the temperature control device; The controller uses the correction increment to correct the feedforward drive parameters and determine the target drive parameters; The controller controls the heating element based on the target driving parameters.

2. The temperature control method according to claim 1, characterized in that, The controller determines the correction increment based on the temperature, the preset target temperature, and the incremental control parameters read from the memory of the temperature control device, including the controller performing the following operations: For the current data acquisition cycle, the temperature control error for the current data acquisition cycle is determined based on the temperature of the current data acquisition cycle and the target temperature. Using a proportional-integral-derivative control algorithm, the correction increment is determined based on the temperature control error of the current data acquisition cycle and the incremental control parameters.

3. The temperature control method according to claim 2, characterized in that, The incremental control parameters include multiple error proportional coefficients and temperature-duty cycle conversion coefficients corresponding to different error ranges; The determination of the correction increment based on the temperature control error of the current data acquisition cycle and the incremental control parameters includes: Determine the target error ratio corresponding to the temperature control error in the current data acquisition cycle from the plurality of error ratio ratios; Based on the target error ratio coefficient, the temperature control error of the current data acquisition cycle, the temperature control error of the historical data acquisition cycle, and the temperature-duty cycle conversion coefficient, the duty cycle correction amount is determined, and the duty cycle correction amount is determined as the correction increment.

4. The temperature control method according to claim 3, characterized in that, The duty cycle correction amount is calculated using the following formula: in, This is the duty cycle correction amount. This represents the temperature control error during the current data acquisition cycle. Temperature control error during historical data collection period. This is the temperature-duty cycle conversion factor. This is the target error proportionality coefficient.

5. The temperature control method according to claim 3, characterized in that, The error proportional coefficient represents the proportional element coefficient of the PID control and is related to the temperature adjustment response speed and steady-state stability of the temperature control device. The multiple error proportional coefficients include a first error proportional coefficient and a second error proportional coefficient. The error range corresponding to the first error proportional coefficient is smaller than the error range corresponding to the second error proportional coefficient. The determination of the target error ratio coefficient relative to the temperature control error of the current data acquisition cycle from the plurality of error ratio coefficients includes: Based on the error range of the temperature control error, a target error proportional coefficient corresponding to the error range of the temperature control error is determined from the first error proportional coefficient and the second error proportional coefficient.

6. The temperature control method according to claim 5, characterized in that, The target error proportionality coefficient is calculated using the following formula: in, This is the second error scaling factor. This is the first error proportionality coefficient. The selection function represents the error range of the temperature control error. When the value is greater than x, the target error scaling factor should be selected. Otherwise choose .

7. The temperature control method according to claim 1, characterized in that, The controller of the temperature control device determines the feedforward drive parameters for controlling the heating element based on the flow rate and temperature, the preset target temperature, and the device performance parameters read from the memory of the temperature control device. The controller then performs the following operations: The basic temperature control power of the heating element is determined based on the flow rate and temperature, the target temperature, and the equipment performance parameters; The feedforward drive duty cycle is determined based on the basic temperature control power, and the feedforward drive duty cycle is used as the feedforward drive parameter.

8. The temperature control method according to claim 7, characterized in that, The feedforward drive duty cycle Calculated using the following formula: in, The rated power of the heating element, Based on the temperature control power.

9. The temperature control method according to claim 7, characterized in that, The fluid temperature includes the fluid inflow temperature; the equipment performance parameters include the heating element efficiency coefficient and the system loss compensation coefficient. The heating element efficiency coefficient is the ratio of the effective heat output power of the heating element to the flowing fluid under rated operating conditions to the rated input electrical power of the heating element, used to correct the deviation in the electro-thermal conversion efficiency of the heating element itself. The system loss compensation coefficient is a correction coefficient used to compensate for the additional heat loss of the system caused by pipeline heat dissipation, fluid mixing heat loss, pipeline thermal resistance, and temperature sensor response lag, used to correct the overall heat loss deviation of the system; the incremental control parameters and the equipment performance parameters are calibrated under decoupled conditions. The determination of the basic temperature control power of the heating element based on the flow rate and temperature, the target temperature, and the equipment performance parameters includes: The base temperature control power is determined based on the flow rate and fluid inflow temperature, the heating element efficiency coefficient, the system loss compensation coefficient, and the target temperature.

10. The temperature control method according to claim 9, characterized in that, The basic temperature regulating power Calculated using the following formula: in, The fluid flow rate, For isobaric specific heat capacity, For the target temperature, The fluid inflow temperature, This is the system loss compensation coefficient. This is the efficiency coefficient of the heating element.

11. The temperature control method according to claim 1, characterized in that, The controller controls the heating element based on the target driving parameters, including: The target driving parameters are stored in the registers of the controller; The target driving parameters stored in the register are transmitted to the pulse width modulation heating driving module, so that the pulse width modulation heating driving module controls the temperature adjustment power of the heating element based on the target driving parameters.

12. The temperature control method according to claim 1 or 11, characterized in that, The target driving parameter includes the target driving duty cycle, and the feedforward driving parameter includes the feedforward driving duty cycle. The target driving duty cycle is calculated using the following formula: in, Driven by the target duty cycle, For feedforward drive duty cycle, This is the duty cycle correction amount, i.e., the correction increment.

13. The temperature control method according to claim 1, characterized in that, Also includes: If the correction increment does not meet the preset range limiting constraint, the correction increment is corrected.

14. The temperature control method according to claim 1, characterized in that, The temperature of the fluid includes the fluid inflow temperature and the fluid outflow temperature; The method further includes using the controller to perform the following operations: For the current data acquisition cycle, the fluid inflow temperature and the fluid outflow temperature acquired within the current data acquisition cycle are filtered to obtain new fluid inflow temperature and new fluid outflow temperature, and the feedforward driving parameters are determined using the new fluid inflow temperature and the new fluid outflow temperature, as well as subsequent steps. The steps of performing pulse debouncing processing on the flow rate of the fluid collected in the current data acquisition cycle to obtain a new flow rate of the fluid, and using the new flow rate of the fluid to determine the feedforward drive parameters and subsequent steps; and / or The new fluid inflow temperature, the new fluid outflow temperature, and the new fluid flow rate are stored.

15. A real-time temperature control device, employing the temperature control method according to any one of claims 1 to 14, characterized in that, The temperature control device includes: A heating element used to regulate the temperature of a fluid; Sensors are used to collect the flow rate and temperature of fluids; Memory, used to store device performance parameters and incremental control parameters; A controller is used to control the heating element based on the fluid flow rate and temperature, the device performance parameters, and the incremental control parameters.

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