Temperature control method and control device based on self-learning duty cycle

Abstract

This invention discloses a temperature control method and device based on self-learning duty cycle. The method is applied to a heating device and includes: acquiring a preset duty cycle fitting coefficient and a preset correction coefficient for the heating device; selectively acquiring a first correction coefficient for the heating device when it is stable at a first target temperature based on a first target temperature; obtaining a second correction coefficient based on the first correction coefficient and the preset correction coefficient; obtaining an initial duty cycle of the heating device at a second target set temperature based on the second correction coefficient, the second target temperature, and the preset duty cycle fitting coefficient; and adjusting the current temperature of the heating device based on the initial duty cycle and using a proportional-integral-differential algorithm to bring the current temperature to the second target set temperature.

Description

Technical Field

[0001] This invention relates to the field of temperature control, and specifically provides a temperature control method and control device based on self-learning duty cycle. Background Technology

[0002] With the increasing demand for modern cooking, steam ovens are becoming more and more widely used. However, as users use heating devices like steam ovens, the changing food and operating conditions alter the working environment, causing the temperature control parameters to become inaccurate and unable to meet the needs of precise cooking.

[0003] Accordingly, a new temperature control scheme is needed in this field to solve the above problems. Summary of the Invention

[0004] In order to overcome the above-mentioned defects, the present invention is proposed to provide a solution or at least a partial solution to the technical problem that the prior art cannot meet the user's requirements for fine cooking during use.

[0005] In a first aspect, the present invention provides a temperature control method for duty cycle based on self-learning, the method comprising: applying to a heating device, including: acquiring a preset duty cycle fitting coefficient and a preset correction coefficient of the heating device; selectively acquiring a first correction coefficient of the heating device when it is stable at the first target temperature based on a first target temperature; obtaining a second correction coefficient based on the first correction coefficient and the preset correction coefficient; obtaining an initial duty cycle of the heating device at the second target temperature based on the second correction coefficient, the second target temperature, and the preset duty cycle fitting coefficient; and adjusting the current temperature of the heating device based on the initial duty cycle and using a proportional-integral-differential algorithm to make the current temperature reach the second target temperature.

[0006] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, obtaining the first correction coefficient when the heating device is stable at the first target temperature includes: in response to a control command to heat to the first target temperature, obtaining the stable duty cycle when the heating device is stable at the first target temperature, wherein the first target set temperature is the target expected temperature reached by the heating device after heating in response to user operation; and obtaining the first correction coefficient based on the stable duty cycle.

[0007] As an alternative or supplement to the above solution, in a method according to an embodiment of the present invention, obtaining the first correction coefficient based on the stable duty cycle includes: obtaining the first correction coefficient based on the stable duty cycle, the first target temperature, and the preset duty cycle fitting coefficient.

[0008] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, selectively obtaining a first correction coefficient when the heating device is stable at the first target temperature based on a first target temperature includes: determining whether the first target temperature is greater than a preset threshold temperature; if the first target temperature is greater than the preset threshold temperature, then performing "obtaining the first correction coefficient based on the stable duty cycle and the correlation between the preset initial duty cycle of the reference device and the target temperature".

[0009] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, updating a preset first correction coefficient based on the stable duty cycle and a preset preset duty cycle fitting coefficient to obtain a second correction coefficient includes: obtaining a second correction coefficient based on the stable duty cycle, the preset preset duty cycle fitting coefficient and the preset first correction coefficient.

[0010] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, obtaining the second correction coefficient based on the first correction coefficient and the preset correction coefficient includes: obtaining the second correction coefficient based on the first correction coefficient and the preset correction coefficient and using a first-order hysteresis filter.

[0011] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, obtaining a second correction coefficient based on a first correction coefficient and a preset correction coefficient using a first-order hysteresis filter includes: obtaining the second correction coefficient based on the first correction coefficient, the preset correction coefficient, and the following formula:

[0012] α2 = α1 × k2 + α0 × k1, where α2 is the second correction coefficient, α1 is the first correction coefficient, α0 is the preset correction coefficient, k1 is a constant, and k2 is a constant.

[0013] As an alternative or supplement to the above scheme, in the method according to an embodiment of the present invention, the proportional-integral-differential algorithm in "adjusting the current temperature of the heating device by using a proportional-integral-differential algorithm" is determined based on the following: the algorithm coefficients in the proportional-integral-differential algorithm of the heating device at the second target temperature are determined based on the initial duty cycle and the second correction coefficient.

[0014] As an alternative or supplement to the above solution, in a method according to an embodiment of the present invention, before "adjusting the current temperature of the heating device based on the initial duty cycle and using a proportional-integral-differential algorithm to make the current temperature reach the second target temperature", the method further includes: responding to a control command to heat to the second target temperature, performing heating at full load power; determining whether the absolute value of the difference between the current temperature and the second target temperature is less than or equal to a first preset threshold; if the absolute value of the difference between the current temperature and the target temperature is less than or equal to the first preset threshold, then performing "adjusting the current temperature of the heating device based on the initial duty cycle and using a proportional-integral-differential algorithm to make the current temperature reach the second target temperature" is executed. The temperature is controlled by a proportional-integral-derivative (PID) algorithm based on the initial duty cycle to achieve the second target temperature. The method further includes: determining whether the absolute value of the difference between the current temperature and the second target temperature is less than or equal to a second preset threshold within a preset time period; if so, determining that a stable phase has been entered; when entering the temperature stable phase, temperature control is performed using a different combination of PID parameters than the control phase of "controlling the current temperature of the heating device based on the initial duty cycle and using a PID algorithm," wherein at least one parameter in the PID parameter combination has a value less than the corresponding parameter value in the control phase.

[0015] As an alternative or supplement to the above solutions, in a method according to an embodiment of the present invention, the step of using a proportional-integral-derivative (PID) parameter combination for temperature control, which is different from the control phase of "adjusting the current temperature of the heating device based on the initial duty cycle and using a proportional-integral-derivative (PID) algorithm," includes: when the absolute value of the difference between the current temperature and the second target temperature is less than or equal to a second preset threshold, using a first PID parameter combination for temperature control; when the absolute value of the difference between the current temperature and the second target temperature is greater than the second preset threshold and less than or equal to a third preset threshold, using a second PID parameter combination for temperature control, wherein at least one parameter in the second PID parameter combination has a value greater than the value of the corresponding parameter in the second PID parameter combination.

[0016] In a second aspect, a control device is provided, comprising a processor and a storage device, the storage device being adapted to store a plurality of computer programs, the computer programs being adapted to be loaded and run by the processor to execute the self-learning duty cycle-based temperature control method described in any of the above-described technical solutions.

[0017] In a third aspect, a computer-readable storage medium is provided, wherein a plurality of computer programs are stored therein, the computer programs being adapted to be loaded and run by a processor to perform the self-learning duty cycle-based temperature control method described in any of the above-described technical solutions.

[0018] In a fourth aspect, a heating device is provided, including a control device that operates the self-learning duty cycle-based temperature control method described in any of the above-mentioned technical solutions of the self-learning duty cycle-based temperature control method.

[0019] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects:

[0020] In implementing the technical solution of this invention, by obtaining the preset duty cycle fitting coefficient and preset correction coefficient of the heating device, a first correction coefficient is selectively obtained, and a second correction coefficient is obtained by combining the preset correction coefficient, thereby obtaining the initial duty cycle at the second target temperature. In this way, based on the initial duty cycle and the proportional-integral-differential algorithm, the current temperature of the heating device can be precisely controlled to reach the second target temperature. This processing method can dynamically adapt to changes in the working environment of the heating device, reducing the burden on users to manually adjust parameters and decreasing reliance on experimentation. More importantly, this technology can improve the temperature control accuracy of the heating device, effectively solving the problem of inaccurate temperature control parameters caused by changes in food placement and device operation, improving cooking results, and thus enhancing the user's cooking experience. Attached Figure Description

[0021] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. Furthermore, similar numbers in the drawings are used to denote similar components, wherein:

[0022] Figure 1 This is a schematic flowchart of the main steps of a temperature control method based on self-learning duty cycle according to an embodiment of the present invention.

[0023] Figure 2 This is a flowchart illustrating the minor steps of a temperature control method based on self-learning duty cycle according to an embodiment of the present invention. Detailed Implementation

[0024] Some embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0025] In the description of this invention, "module" and "processor" can include hardware, software, or a combination of both. A module can include hardware circuitry, various suitable sensors, communication ports, memory, and may also include software components, such as computer programs, or a combination of software and hardware. A processor can be a central processing unit, microprocessor, image processor, digital signal processor, or any other suitable processor. The processor has data and / or signal processing capabilities. The processor can be implemented in software, in hardware, or a combination of both. Non-transitory computer-readable storage media includes any suitable medium capable of storing computer programs, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The terms "at least one A or B" or "at least one of A and B" have a similar meaning to "A and / or B" and can include only A, only B, or A and B. The singular terms "a" or "this" can also include plural forms.

[0026] See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a temperature control method based on self-learning duty cycle according to an embodiment of the present invention. Figure 1 As shown, the temperature control method based on self-learning duty cycle in this embodiment of the invention mainly includes the following steps S10-S40.

[0027] Step S10: Obtain the preset duty cycle fitting coefficient and preset correction coefficient of the heating equipment.

[0028] In this embodiment, the preset duty cycle fitting coefficient of the heating device is a parameter preset in the heating device's memory, used to calculate the preset duty cycle. The preset correction coefficient is set at the factory and updated during each iteration of temperature control.

[0029] In one implementation, the preset duty cycle fitting coefficients are a and b. In this implementation, the preset duty cycle fitting coefficients a and b constitute a fitting formula for calculating the preset duty cycle, which is the basis of the pulse width modulation (PWM) control signal. In this formula, the set temperature Tset is the target temperature that the user wants the heating device to reach, and the preset duty cycle is the PWM duty cycle that the heating device should use when the set temperature Tset is reached. The preset duty cycle can be obtained by substituting the set temperature Tset into the preset duty cycle fitting formula.

[0030] Step S20: Selectively obtain a first correction coefficient when the heating device is stable at the first target temperature based on the first target temperature.

[0031] In this embodiment, the first target temperature is the target temperature set by the user, which is the second target temperature in the previous update cycle.

[0032] In one implementation, the first correction coefficient is obtained through steps S201-202, as follows:

[0033] Step S201: In response to the control command to heat to the first target temperature, obtain the stable duty cycle of the heating device when it is stable at the first target temperature.

[0034] In this embodiment, the first target temperature is the desired temperature reached by the heating device after heating in response to user operation.

[0035] In one implementation, the user issues a cooking command through the device's user interface or other interface, setting a first target temperature. This temperature is the temperature the user expects the heating device to stably reach after the heating process. The heating device then responds to this command and begins heating to the set first target temperature.

[0036] After the heating device heats the equipment to the first target temperature and reaches a stable state, the equipment control system acquires the duty cycle at this time, i.e., the stable duty cycle. Preferably, in this embodiment, the stable duty cycle can be obtained by reading the PWM output signal of the equipment control system.

[0037] In this embodiment, obtaining a stable duty cycle is done to prepare for the subsequent calculation of the first correction factor. The duty cycle reflects, to some extent, the heating capacity and current operating state of the heating equipment, and is therefore an important parameter for calculating the correction factor.

[0038] Step S202: Obtain the first correction coefficient based on the stable duty cycle.

[0039] In one implementation, the control system calculates a first correction factor using the newly acquired stable duty cycle and the set first target temperature. This correction factor is a value reflecting the difference between the heating device's actual operation and the preset parameters, and it is used in subsequent temperature control processes to improve the device's control accuracy towards the target temperature.

[0040] Step S202-1: Obtain the first correction coefficient based on the stable duty cycle, the first target temperature, and the preset duty cycle fitting coefficient.

[0041] In one embodiment, specifically in this embodiment, the first correction coefficient α1 is calculated based on the following formula:

[0042] α1 = PWMstable / (a ​​×Tset1 + b)

[0043] Where α1 is the first correction coefficient, PWMstable is the obtained stable duty cycle, Tset1 is the set first target temperature, and a and b are preset duty cycle fitting coefficients. This formula is used to revise the correction coefficient.

[0044] In this embodiment, the first correction coefficient for obtaining the heating device when it is stable at the first target temperature based on the first target temperature further includes steps S203-204, as follows:

[0045] Step S203: Determine whether the first target temperature is greater than the preset threshold temperature.

[0046] In this embodiment, the preset threshold temperature is a predetermined temperature limit.

[0047] In one embodiment, preferably, the threshold temperature is set to 150°C. This threshold temperature helps the system determine whether it is in a suitable state for learning the correction coefficient. For heating equipment, generally speaking, when the operating temperature is high, the heating efficiency and temperature control performance of the equipment are relatively stable. In this case, the preset correction coefficient is more accurate and better reflects the actual operating performance of the equipment. Conversely, at lower temperatures, such as below 150°C, the performance of the equipment may be affected by many factors, such as ambient temperature and the degree of equipment preheating. The obtained correction coefficient may not be accurate in this case, leading to deviations in the subsequent temperature control process.

[0048] Therefore, the process of determining whether the first target temperature is greater than the preset threshold temperature in step S203 is actually a safeguard mechanism to ensure that the correction coefficient is obtained when the equipment is operating stably on the fitted curve. Only when the first target temperature is greater than the preset threshold temperature will the next step, calculating and obtaining the correction coefficient, be executed. This improves the temperature control accuracy of the entire system, ensuring that the expected temperature control effect can be achieved under various conditions.

[0049] Step S204: If the first target temperature is greater than the preset threshold temperature, then execute "obtain the first correction coefficient based on the stable duty cycle and the correlation between the initial duty cycle of the preset reference device and the target temperature".

[0050] In this embodiment, when the first target temperature is greater than the preset threshold temperature, the first correction parameter is obtained.

[0051] Step S30: Obtain the second correction coefficient based on the first correction coefficient and the preset correction coefficient.

[0052] In this embodiment, specifically, the first correction factor is obtained in the preceding steps based on actual operating conditions. The preset correction factor, on the other hand, is pre-set during system design based on experiments or experience, and it reflects the operating characteristics of the heating equipment under normal circumstances.

[0053] By combining these two correction factors, a new, more accurate second correction factor can be obtained. This correction factor integrates the actual operating conditions and general operating characteristics of the heating equipment, thus more accurately reflecting the actual operating situation of the heating equipment and providing more accurate corrections in subsequent temperature control.

[0054] In this embodiment, preferably, the second correction coefficient is obtained through step S301.

[0055] Step S301: Based on the first correction coefficient and the preset correction coefficient, and using first-order hysteresis filtering, obtain the second correction coefficient.

[0056] In this embodiment, first-order hysteresis filtering is a filtering technique used in control systems and signal processing. It can effectively smooth signals, reduce noise interference, and preserve the basic characteristics of the signal.

[0057] In one implementation, the first correction coefficient and the preset correction coefficient are considered as input signals. Through first-order hysteresis filtering, a smooth and stable correction coefficient, namely the second correction coefficient, can be obtained. This correction coefficient considers both the first and preset correction coefficients, and the filtering process ensures its stability and accuracy. This calculation process enables dynamic adjustment of the correction coefficient, allowing the device's operating state to be reflected more accurately in each iteration.

[0058] The advantage of using a first-order hysteresis filter is that it can effectively consider and handle dynamic changes in the operating state of the equipment. By iteratively updating the correction coefficients, the operating parameters of the equipment can be dynamically adjusted according to the actual operating state, thereby achieving more precise temperature control.

[0059] Taking a steam oven as an example, each cooking process has its specific temperature requirements, and even for the same food, different users may have different cooking preferences. This requires the steam oven to be able to learn and fine-tune itself based on actual conditions to meet the personalized needs of users.

[0060] The second correction coefficient, derived from the first and preset correction coefficients, incorporates both the current and previous operating states of the equipment, providing a better reflection of the oven's actual operating status. Furthermore, this coefficient is dynamically adjusted to adapt to various changing conditions. For example, if a user prefers steaming and baking cakes, these foods will cause temperature fluctuations within the oven, affecting its operating status and temperature control accuracy. By dynamically adjusting the second correction coefficient, these changes can be reflected promptly and accurately, thus achieving precise temperature control.

[0061] In actual cooking, this means that whether baking bread, cakes, or meat, users can get satisfactory results. The food's interior and exterior can reach the expected temperature evenly and accurately, which not only ensures the food's taste and nutrition but also improves cooking efficiency and saves users time.

[0062] In this embodiment, the second correction factor is obtained based on the first correction factor, the preset correction factor, and the following formula:

[0063] α2 = α1 × k2 + α0 × k1,

[0064] Where α2 is the second correction coefficient, α1 is the first correction coefficient, α0 is the preset correction coefficient, k1 is a constant, and k2 is a constant.

[0065] Step S40: Based on the second correction coefficient, the second target temperature, and the preset duty cycle fitting coefficient, obtain the initial duty cycle of the heating device at the second target temperature.

[0066] In this embodiment, the initial duty cycle is the duty cycle of the heating device calculated at the second target temperature, which is used for subsequent control.

[0067] In one implementation, the initial duty cycle is calculated using the formula Y = α2 × (a × Tset2 + b). Here, Y is the initial duty cycle, α2 is the second correction coefficient, Tset2 is the set second target temperature, and a and b are preset duty cycle fitting coefficients.

[0068] Step S50: Based on the initial duty cycle, the current temperature of the heating device is adjusted using a proportional-integral-differential algorithm to bring the current temperature to the second target temperature.

[0069] In this embodiment, the current temperature is the actual temperature of the oven read by a temperature sensor inside the heating device. In this embodiment, based on the obtained initial duty cycle, the current temperature of the heating device is precisely controlled in real time using a proportional-integral-differential algorithm.

[0070] In one implementation, the current temperature of the heating device is continuously and in real-time adjusted to ensure that it ultimately reaches the set target temperature precisely. This allows the user to set the device temperature as needed, and the device can automatically adjust the temperature to meet the user's requirements.

[0071] In this embodiment, step S50 further includes step S501 to determine the algorithm coefficients in the proportional-integral-differential algorithm.

[0072] Step S501: Determine the algorithm coefficients in the proportional-integral-differential algorithm of the heating device at the second target temperature based on the initial duty cycle, the second correction coefficient, and the preset duty cycle fitting coefficient.

[0073] In this embodiment, the algorithm coefficients include at least one of a first proportional coefficient, a first integral coefficient, and a first differential coefficient.

[0074] In one embodiment, the second correction coefficient α2 and the preset duty cycle fitting coefficient a are combined to obtain α2×a. This coefficient is referred to as the control sensitivity coefficient for ease of description. In this embodiment, the control sensitivity coefficient is denoted by Sen.

[0075] In this embodiment, when the initial duty cycle is greater than a preset first duty cycle threshold and less than a preset second duty cycle threshold, the first proportional coefficient satisfies:

[0076] Kp = k1 × Sen + k2 × Y,

[0077] Where k1 and k2 are constants, Kp is the first proportional coefficient, Sen is the control sensitivity coefficient, and Y is the initial duty cycle. Both the first and second duty cycle thresholds are determined based on the control sensitivity coefficient. In this embodiment, the duty cycle threshold is determined using a second correction coefficient and a preset duty cycle fitting coefficient.

[0078] Approximately, when the initial duty cycle is greater than a preset first duty cycle threshold and less than a preset second duty cycle threshold, the first differential coefficient satisfies:

[0079] Kd = (k4 / Sen) × Y + k5,

[0080] Where k4 is a constant term, Kd is the first proportional coefficient, and Y is the initial duty cycle.

[0081] The first integral coefficient satisfies:

[0082] Ki = Kp / k3,

[0083] Where k3 is a constant term, Ki is the first proportionality coefficient, and Kp is the first proportionality coefficient.

[0084] When the initial duty cycle is less than or equal to the preset first duty cycle threshold or greater than or equal to the second duty cycle threshold, the calculation formulas for the first proportional coefficient and the first differential coefficient will change.

[0085] Specifically, the first proportionality coefficient satisfies:

[0086] Kp = k6 × Sen,

[0087] Where k6 is the first preset constant term, Kp is the first proportional coefficient, and Sen is the control sensitivity coefficient. Moreover, when the initial duty cycle is less than or equal to the first duty cycle threshold, the value of k6 is less than the value of k6 when the initial duty cycle is greater than or equal to the second duty cycle threshold.

[0088] Similarly, when the initial duty cycle is less than or equal to a preset first duty cycle threshold or greater than or equal to a second duty cycle threshold, the first differential coefficient satisfies:

[0089] Kd = k7,

[0090] Where k7 is the second preset constant term, and Kd is the first differential coefficient. When the initial duty cycle is less than or equal to the first duty cycle threshold, the value of k7 is less than the value of k7 when the initial duty cycle is greater than or equal to the second duty cycle threshold.

[0091] In this embodiment, based on the three initial duty cycle determination scenarios, the control sensitivity coefficient and the initial duty cycle or the control sensitivity coefficient alone are used to input into different mathematical models to obtain the proportional coefficient of the heating device under different initial duty cycle working environments. This makes the obtained coefficient more accurate and solves the problem of time-consuming and costly trial-and-error methods for finding the proportional coefficient in the prior art.

[0092] In this embodiment, the current temperature is controlled based on the initial duty cycle and using a proportional-integral-differential algorithm. Through meticulous adjustments, the internal temperature of the heating device can accurately reach the target temperature set by the user and remain stable at this temperature.

[0093] At the beginning of the adjustment phase, a preset initial integral value is given to the PID controller, which is the initial cumulative deviation value, or the initial duty cycle. This initial duty cycle is predicted and calculated based on the stable initial duty cycle of the heating equipment at the target temperature.

[0094] The adjustment phase can be divided into one or more stages. It should be noted that in actual operation, the temperature control process may be affected by many factors, such as the dynamic characteristics of the system, changes in ambient temperature, and user operation.

[0095] In this embodiment, to address different influences, the control system preferably divides the adjustment phase into multiple sub-phases, each with its own objectives and strategies. For example, in this embodiment, the adjustment phase has three sub-phases: a "rapid adjustment" phase, a "fine-tuning" phase, and a "maintaining stability" phase.

[0096] First, the system enters a "rapid adjustment" phase, where the controller parameters are set to relatively large values ​​to quickly reduce the difference between the actual and target temperatures. After certain conditions are met, the system enters a "fine-tuning" phase, where the controller parameters are set to smaller values ​​to reduce over-adjustment and oscillations in temperature. Finally, the system enters a "maintaining stability" phase, where the controller parameters are set to moderate values ​​to maintain temperature stability.

[0097] In this embodiment, specifically, the initial duty cycle is introduced into the control through steps S601-602.

[0098] Step S601: Determine the initial value of the cumulative deviation in the proportional-integral-derivative algorithm based on the ratio of the initial duty cycle to the preset integral parameter.

[0099] In this embodiment, the cumulative deviation, also known as the integral term, represents the accumulation of all past deviation values.

[0100] In one implementation, the initial duty cycle of the device is multiplied by a preset integral parameter, and the result is the initial value of the cumulative deviation. This calculation process can be expressed as: Initial value of cumulative deviation = Initial duty cycle × Preset integral parameter.

[0101] Step S602: Based on the initial value of the cumulative deviation, the current temperature is controlled using a proportional-integral-differential algorithm.

[0102] In one implementation, the purpose of using an initial cumulative deviation value to regulate the current temperature is to prevent a large temperature rebound in the system when it first enters this stage, which would affect the steaming and baking effect.

[0103] Step S701: Determine whether the absolute value of the difference between the current temperature and the target temperature is less than or equal to the second preset threshold within a preset time period.

[0104] In this embodiment, both the preset duration and the second preset threshold can be flexibly set according to requirements.

[0105] Step S702: If yes, confirm that you have entered the stable phase.

[0106] When the temperature reaches a stable state, a different combination of proportional-integral-derivative (PID) parameters is used for temperature control compared to the control stage where the current temperature is controlled based on the proportional-integral-derivative (PID) algorithm. In this combination, at least one parameter has a value less than the corresponding parameter value in the control stage.

[0107] Similar to the adjustment phase, the stabilization phase can also have one or more sub-phases. Preferably, in this embodiment, the stabilization phase is divided into two smaller phases. Specifically, when the absolute value of the difference between the current temperature and the target temperature is less than or equal to a second preset threshold, temperature control is performed using a first proportional-integral-derivative parameter combination. In this phase, the proportional coefficient (P), integral coefficient (I), and derivative coefficient (D) are set to be smaller, mainly to minimize small temperature fluctuations, and the integral rate (EskAs) may be set to be smaller to reduce fluctuations.

[0108] When the absolute value of the difference between the current temperature and the target temperature is greater than a second preset threshold and less than or equal to a third preset threshold, temperature control is performed using a second proportional-integral-derivative (PID) parameter combination. In this combination, at least one parameter has a value greater than the corresponding parameter in the second PID parameter combination. During this stage, one or more of the proportional coefficient (P), integral coefficient (I), or derivative coefficient (D) will be appropriately increased to enable faster response and adjustment to temperature deviations. Simultaneously, the integral speed (EskAs) may be set relatively high for rapid regulation.

[0109] The stable phase is the final stage in the entire temperature control process. It's designed to maintain the oven temperature at the preset target temperature and prevent large temperature fluctuations. During this phase, the adjustment function of the PID controller is gradually weakened, especially the proportional (P) and derivative (D) controls, to avoid temperature oscillations caused by excessively rapid responses.

[0110] Here's an example. In the stabilization phase, assume the steam oven has reached the set temperature of 200°C and has already undergone precise temperature adjustments during the adjustment phase. The main goal of this stabilization phase is to ensure stable oven temperature and minimize temperature fluctuations.

[0111] The stable phase is divided into two sub-phases: Phase 1 and Phase 2.

[0112] Phase 1: Phase 1 begins when the actual temperature inside the oven deviates from the target temperature within a certain range, such as ±2°C. In this phase, the primary goal is to minimize small temperature fluctuations; therefore, the proportional (P), integral (I), and derivative (D) coefficients of the PID controller may be set relatively small. For example, P could be set to 0.5, I to 1, and D to 0. Simultaneously, to eliminate small steady-state temperature differences, the integral rate (EskAs) may be set relatively small, such as 0.1.

[0113] Phase 2: If the actual temperature inside the oven deviates from the target temperature by more than ±2°C but less than ±10°C, Phase 2 will be initiated. In this phase, a faster response and adjustment to the temperature deviation is required. Therefore, the proportional gain (P) and derivative gain (D) may be moderately increased, for example, P is set to 1, I to 1, and D to 0. Simultaneously, the integral gain (I) is set relatively large, such as 0.4.

[0114] These two stages will automatically switch based on the deviation between the actual temperature inside the oven and the target temperature, ensuring that the steam oven maintains a stable temperature throughout the cooking process.

[0115] This sophisticated control strategy enables the steam oven to maintain high precision and stable temperature control under various cooking conditions, thereby ensuring consistent cooking quality and food taste.

[0116] In this embodiment, before adjusting the current temperature based on the initial duty cycle and using the proportional-integral-differential algorithm, steps S801-802 are included, which are the heating stage of the heating device.

[0117] It should be noted that when the absolute value of the difference between the current temperature and the target temperature is greater than the third preset threshold, the system will return to the adjustment state.

[0118] Step S801: In response to the control command to heat to the target temperature, perform heating at full load power.

[0119] In one implementation, the main task of the system at this stage is to bring the heating device to the set temperature as quickly as possible. To achieve this goal, the heating element assembly used at this stage will operate at full power or maintain a high power to raise the temperature of the heating device to the target temperature as quickly as possible.

[0120] In this step, the system does not use a PID algorithm for control because speed is the most critical factor at this stage. This design aims to ensure the steam oven reaches the target temperature as quickly as possible. Therefore, the selected heating element combination will be activated and operate at maximum power to rapidly increase the internal temperature of the steam oven.

[0121] However, the specific strategy for fully opening the heating elements is controlled by the oven's "rapid heating" switch. If the "rapid heating" switch is on, the system will use the maximum power combination of heating elements to raise the temperature. If the "rapid heating" switch is off, the system will use the normal combination of heating elements to raise the temperature. But in either case, the goal at this stage is to raise the temperature as quickly as possible.

[0122] It should be noted that the heating phase ends when the current temperature of the heating device reaches the preset full-opening stop point. At this time, the current temperature will continue to rise due to inertia and then fall back. When the temperature condition meets the requirements of step S602, step S50 will be executed. The temperature setting of the full-opening stop point is positively correlated with the target temperature. In this embodiment, the relationship between the full-opening stop point and the target temperature is obtained in advance by fitting experimental data, and then the corresponding full-opening stop point is calculated based on the target temperature.

[0123] Step S802: Determine whether the absolute value of the difference between the current temperature and the target temperature is less than or equal to the first preset threshold.

[0124] In one implementation, this step is a condition for activating PID control, namely, the absolute value of the difference between the current temperature and the target temperature is less than or equal to a first preset threshold, indicating that the device temperature is approximately close to the target temperature. In this case, the system will proceed to the next step, which is to adjust the temperature based on the initial duty cycle and using a proportional-integral-derivative (PID) algorithm.

[0125] If the absolute value of the difference between the current temperature and the target temperature is less than or equal to the first preset threshold, then proceed to step S50.

[0126] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effects of the present invention, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the scope of protection of the present invention.

[0127] Those skilled in the art will understand that all or part of the processes in the method of the above-described embodiment of the present invention 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 a computer program, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium can include any entity or device capable of carrying the computer program, a medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, 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.

[0128] Furthermore, the present invention also provides a control device. In one embodiment of the control device according to the present invention, the control device includes a processor and a storage device. The storage device can be configured to store a program for executing the temperature control method based on self-learning duty cycle of the above-described method embodiments. The processor can be configured to execute the program in the storage device, which includes, but is not limited to, the program for executing the temperature control method based on self-learning duty cycle of the above-described method embodiments. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. This control device can be a control device device comprising various electronic devices.

[0129] Furthermore, the present invention also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to the present invention, the computer-readable storage medium can be configured to store a program that executes the temperature control method based on self-learning duty cycle of the above-described method embodiments. This program can be loaded and run by a processor to implement the temperature control method based on self-learning duty cycle. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. The computer-readable storage medium can be a storage device device comprising various electronic devices. Optionally, in the embodiments of the present invention, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0130] Furthermore, the present invention also provides a heating device, including a control device, wherein the control device operates the temperature control method based on self-learning duty cycle as described in any of the above-mentioned technical solutions of the temperature control method based on self-learning duty cycle.

[0131] Furthermore, it should be understood that since the various modules are only provided to illustrate the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor itself, or a part of the processor's software, hardware, or a combination of software and hardware. Therefore, the number of modules shown in the figures is merely illustrative.

[0132] Those skilled in the art will understand that the various modules in the device can be adaptively split or combined. Such splitting or combining of specific modules will not cause the technical solution to deviate from the principles of the present invention; therefore, the technical solutions after splitting or combining will fall within the protection scope of the present invention.

[0133] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A temperature control method based on self-learning duty cycle, characterized in that, Acting on heating equipment, including: Obtain the preset duty cycle fitting coefficient and preset correction coefficient of the heating device; The first correction coefficient is obtained based on the selective acquisition of the heating device when it is stable at the first target temperature; The second correction factor is obtained based on the first correction factor and the preset correction factor; According to the formula: Y = α² × (a × Test² + b) The initial duty cycle Y of the heating device at the second target set temperature is obtained, where α2 is the second correction coefficient, Test2 is the second target temperature, and a and b are preset duty cycle fitting coefficients; Based on the initial duty cycle, the current temperature of the heating device is adjusted using a proportional-integral-differential algorithm to bring the current temperature to the second target temperature. The first correction factor for obtaining the heating device when it stabilizes at the first target temperature includes: In response to a control command to heat to a first target temperature, the stable duty cycle of the heating device when it stabilizes at the first target temperature is obtained, wherein the first target temperature is the target desired temperature reached by the heating device after heating in response to a user operation; According to the formula: α1 = PWMstable / (a ​​× Test1 + b), The first correction coefficient α1 is obtained, where PWMstable is the stable duty cycle, Tset1 is the first target temperature, and a and b are the duty cycle fitting coefficients.

2. The temperature control method based on self-learning duty cycle according to claim 1, wherein the first correction coefficient is selectively obtained based on the first target temperature when the heating device is stable at the first target temperature, includes: Determine whether the first target temperature is greater than a preset threshold temperature; If the first target temperature is greater than the preset threshold temperature, then the first correction coefficient is obtained.

3. The temperature control method based on self-learning duty cycle according to claim 1, characterized in that, The process of obtaining the second correction coefficient based on the first correction coefficient and the preset correction coefficient includes: The second correction coefficient is obtained based on the first correction coefficient and the preset correction coefficient, using a first-order hysteresis filter.

4. The temperature control method based on self-learning duty cycle according to claim 2, characterized in that, Based on the first correction coefficient and a preset correction coefficient, and using first-order hysteresis filtering, the second correction coefficient is obtained as follows: The second correction factor is obtained based on the first correction factor, the preset correction factor, and the following formula: α2 = α1 × k2 + α0 × k1, Where α2 is the second correction coefficient, α1 is the first correction coefficient, α0 is the preset correction coefficient, k1 is a constant, and k2 is a constant.

5. The temperature control method based on self-learning duty cycle according to claim 1, characterized in that, The proportional-integral-differential algorithm used in "regulating the current temperature of the heating equipment using a proportional-integral-differential algorithm" is based on the following: The algorithm coefficients in the proportional-integral-differential algorithm of the heating device at the second target temperature are determined based on the initial duty cycle, the second correction coefficient, and the preset duty cycle fitting coefficient. The algorithm coefficients include at least one of a first proportional coefficient, a first integral coefficient, and a first differential coefficient; When the initial duty cycle is greater than a preset first duty cycle threshold and less than a preset second duty cycle threshold, the first proportional coefficient satisfies: Kp = k1 × Sen + k2 × Y, Wherein, k1 and k2 are constant terms, Kp is the first proportional coefficient, Sen is the control sensitivity coefficient, and Y is the initial duty cycle; the control sensitivity coefficient Sen = α2 × a, where α2 is the second correction coefficient and a is the preset duty cycle fitting coefficient; The first differential coefficient satisfies: Kd=(k4 / Sen)×Y+k5, Where k4 and k5 are constant terms, Kd is the first differential coefficient, Y is the initial duty cycle, and Sen is the control sensitivity coefficient; The first integral coefficient satisfies: Ki = Kp / k3, Where k3 is a constant term, Ki is the first integral coefficient, and Kp is the first proportional coefficient.

6. A control device comprising a processor and a storage device, said storage device being adapted to store a plurality of computer programs, characterized in that, The computer program is adapted to be loaded and run by the processor to perform the self-learning duty cycle-based temperature control method according to any one of claims 1 to 5.

7. A computer-readable storage medium storing a plurality of computer programs, characterized in that, The computer program is adapted to be loaded and run by a processor to perform the self-learning duty cycle-based temperature control method according to any one of claims 1 to 5.

8. A heating device, comprising a control device, characterized in that, The control device operates to perform the self-learning duty cycle-based temperature control method according to any one of claims 1 to 5.

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