Mist temperature control method and system based on electronic cigarette atomizer

Abstract

The invention relates to the field of electronic cigarettes, and discloses a mist temperature control method and system based on an electronic cigarette atomizer, and the method comprises the following steps: (a) collecting the current temperature of the atomizer, the environment temperature and the smoking behavior data of a user through a sensor; (b) establishing a thermodynamic model for describing the temperature change in the atomizer; (c) constructing a multi-objective optimization control strategy; (d) determining the optimal heat supply power of the atomizer heating unit at the current moment; (e) controlling the power of the atomizer to adjust the mist temperature to enable the mist temperature of the atomizer to be within the target temperature range; and (f) comparing the real-time temperature data of the atomizer with the target temperature deviation, and feeding back and adjusting the heat supply power. The temperature of the atomizer, the environment temperature and the user smoking behavior are monitored in real time, the thermodynamic model and the optimization control strategy are combined, the power of the heating unit is regulated and controlled, the atomization temperature is stabilized within the target range, smoke quality fluctuation caused by overheating or supercooling is avoided, and the user taste and the smoking experience are improved.

Description

Technical Field

[0001] The present invention relates to the field of electronic cigarettes, and in particular to a mist temperature control method and system based on an electronic cigarette atomizer. Background Art

[0002] Electronic cigarettes are a new type of tobacco substitute product that produces aerosol by heating the e-liquid for users to inhale. Unlike traditional cigarettes, electronic cigarettes use an atomizer to convert the e-liquid into smoke. Its core component is the heating unit, which is responsible for heating the e-liquid to a suitable temperature so that it can be fully atomized, thereby providing a sensory experience similar to smoking. The performance of the atomizer has a direct impact on the quality of the smoke and the user experience, so accurate temperature control is crucial to the function of the atomizer.

[0003] In the prior art, most atomizers use constant power or simple controlled heating methods, which cannot dynamically adjust the atomization temperature according to the external environment temperature and the user's smoking behavior. When the temperature is low or high, the atomizer cannot respond in time, which leads to the atomization temperature being too high or too low, and the smoke quality and user experience are significantly affected. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a mist temperature control method and system based on an electronic cigarette atomizer, which solves the problem in the prior art that the atomizer cannot respond in time, resulting in the atomization temperature being too high or too low, and the smoke quality and user experience being significantly affected.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A mist temperature control method based on an electronic cigarette atomizer comprises the following steps: (a) collecting the current temperature of the atomizer, the ambient temperature and the user's puffing behavior data through sensors; (b) Based on the data collected by the sensor, a thermodynamic model describing the temperature change inside the atomizer is established; (c) construct a multi-objective optimization control strategy based on the deviation between the current temperature of the atomizer and the target temperature; (d) determining the optimal heating power of the atomizer heating unit at the current moment based on the thermodynamic model and multi-objective optimization control strategy; (e) according to the optimal heating power, adjusting the power supply voltage of the heating unit in real time, controlling the atomizer power to adjust the mist temperature, so that the atomizer mist temperature is within the target temperature range; (f) Compare the real-time temperature data of the atomizer with the target temperature deviation, and use feedback to adjust the heating power.

[0006] Preferably, in step (a), the sensor comprises: Temperature sensor, used to collect the current temperature inside the atomizer; An ambient temperature sensor, used to detect the ambient temperature outside the atomizer; Suction sensor, used to monitor the user's suction intensity and frequency.

[0007] Preferably, the thermodynamic model in step (b) comprises: The heat diffusion term is used to describe the spatial transfer of heat inside the atomizer; The heating power term is used to describe the contribution of the heat provided by the heating unit to the temperature change; The heat exchange term is used to describe the heat exchange process between the internal temperature of the atomizer and the external environment temperature.

[0008] Preferably, the thermal conductivity of the heat diffusion inside the atomizer is determined according to the material properties of the atomizer core; The heat transfer coefficient between the external environment and the atomizer is dynamically adjusted according to the ambient temperature; The response time of the heating unit power to the atomizer temperature is obtained by fitting the system parameters.

[0009] Preferably, the multi-objective optimization control strategy in step (c) includes: Minimize the deviation between the current temperature of the atomizer and the target temperature; Minimize the energy consumption of heating units for heating power.

[0010] Preferably, the multi-objective optimization control strategy in step (c) includes: The square value of temperature deviation is taken as the primary optimization target, and the square value of heating power is taken as the secondary optimization target; The weighting coefficient of the target is dynamically adjusted according to user needs, giving priority to either temperature control accuracy or energy consumption optimization.

[0011] Preferably, determining the optimal heating power in step (d) comprises: Construct an optimization objective function, and perform a weighted sum of the square value of the temperature deviation and the square value of the heating power; Based on the optimization objective function and the dynamic thermodynamic model, the optimal heating power at the current moment is calculated through the optimal control method.

[0012] Preferably, the temperature adjustment in step (e) comprises: According to the optimal heating power, the target supply voltage of the heating unit is calculated in real time; Adjust the power supply voltage of the heating unit to make the mist temperature of the atomizer dynamically approach the target temperature range; The supply voltage is dynamically corrected through feedback control based on the real-time temperature prediction and the target temperature deviation.

[0013] Preferably, the feedback control in step (f) comprises: Inputting the real-time collected atomizer temperature data into the dynamic thermodynamic model; Compare the prediction results of the dynamic thermodynamic model with the real-time temperature data to calculate the temperature deviation; The supply voltage of the heating unit is dynamically adjusted according to the temperature deviation to optimize the heating power.

[0014] The mist temperature control system based on the electronic cigarette atomizer includes: Data acquisition module: used to collect the current temperature of the atomizer, the ambient temperature and the user's puffing behavior data in real time, and transmit the collected data to the control module; Control module: connected to the data acquisition module, used to receive real-time data and calculate the optimal heating power of the heating unit according to the dynamic thermodynamic model; Heating module: connected to the control module, used to receive the heating power instruction output by the control module, adjust the power supply voltage, and heat the inside of the atomizer; Power supply module: connected to the heating module and the control module, used to dynamically adjust the power supply voltage of the heating module according to the heating power instruction of the control module; Feedback module: connected with the data acquisition module, control module and heating module, used to compare the deviation between the current temperature of the atomizer and the target temperature in real time, and transmit the comparison result to the control module to dynamically correct the heating power.

[0015] The present invention provides a mist temperature control method and system based on an electronic cigarette atomizer, which has the following beneficial effects: 1. The present invention can accurately regulate the power of the heating unit of the atomizer by real-time monitoring of the current temperature of the atomizer, the ambient temperature and the user's puffing behavior, combined with thermodynamic models and multi-objective optimization control strategies, so that the atomization temperature is always within the target range, thereby effectively avoiding fluctuations in smoke quality caused by overheating or overcooling, providing users with a more stable taste and consistent puffing experience, and significantly improving the user experience.

[0016] 2. Through the combination of real-time feedback control and dynamic thermodynamic model, the present invention can dynamically adjust the heating power and supply voltage according to the changes in ambient temperature and the differences in user's puffing behaviors, such as suction strength and frequency, so that the working state of the atomizer can automatically adapt to changes in external conditions, further optimize the user's personalized usage experience, and avoid lag or excessive heating.

[0017] 3. The present invention adopts a multi-objective optimization control strategy with the goal of minimizing temperature deviation and heating power consumption. By reasonably allocating weighted coefficients, it can not only meet the requirements of temperature control accuracy, but also effectively reduce unnecessary heating power loss, improve system energy efficiency, and at the same time reduce the risk of overheating of the heating unit and extend the service life of the equipment.

[0018] 4. The present invention can avoid excessive decomposition of the heating material due to excessive temperature through precise temperature control, thereby reducing the release of harmful substances and significantly reducing health risks during smoking. At the same time, after the temperature stability is improved, the heating unit and the atomization core material can be better protected, further ensuring the safety of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the method flow of the present invention; Figure 2 Schematic diagram of the system architecture of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] In order to better understand the present invention, the above contents are described in detail below in conjunction with specific embodiments.

[0022] Please refer to the attached Figure 1 The embodiment of the present invention provides a mist temperature control method based on an electronic cigarette atomizer, characterized in that it includes the following steps: (a) collecting the current temperature of the atomizer, the ambient temperature and the user's puffing behavior data through sensors; (b) Based on the data collected by the sensor, a thermodynamic model describing the temperature change inside the atomizer is established; (c) construct a multi-objective optimization control strategy based on the deviation between the current temperature of the atomizer and the target temperature; (d) determining the optimal heating power of the atomizer heating unit at the current moment based on the thermodynamic model and multi-objective optimization control strategy; (e) according to the optimal heating power, adjusting the power supply voltage of the heating unit in real time, controlling the atomizer power to adjust the mist temperature, so that the atomizer mist temperature is within the target temperature range; (f) Compare the real-time temperature data of the atomizer with the target temperature deviation, and use feedback to adjust the heating power.

[0023] In this embodiment: the temperature of the atomizer, the external environment temperature and the user's puffing behavior data are collected in real time through the temperature sensor, the ambient temperature sensor and the suction force sensor; a thermodynamic model including heat diffusion, heating power and heat exchange terms is established based on the collected data; a multi-objective optimization control strategy is constructed with the goal of minimizing temperature deviation and energy consumption; the optimal heating power is calculated using the thermodynamic model and the control strategy; the atomizer temperature is controlled to be stable within the target range by adjusting the power supply voltage of the heating unit; and the temperature deviation is compared in real time through the feedback mechanism, and the heating power is dynamically adjusted to adapt to changes in the environment and user behavior; And by dynamically adjusting the heating power, the mist temperature of the atomizer can be controlled to always be within the optimal working temperature range, avoiding the impact of overheating or overcooling on the quality of the smoke, so that users can obtain a stable taste and consistent smoking experience. By controlling the temperature within a reasonable range, the heating unit can be prevented from overheating or overloading, extending the service life of the equipment, while avoiding excessive heating of the material due to excessive temperature, thereby reducing the risk of releasing harmful substances and protecting the health of users. By detecting the user's puffing behavior (such as suction strength and frequency), the heating power can be dynamically adjusted, and the working state of the atomizer can be adjusted in real time during the user's puffing process to avoid lag or excessive heating, so that the smoke volume and temperature match the user's needs, providing a more comfortable and personalized use experience.

[0024] In step (a), the sensor includes: Temperature sensor, used to collect the current temperature inside the atomizer; An ambient temperature sensor, used to detect the ambient temperature outside the atomizer; Suction sensor, used to monitor the user's suction intensity and frequency.

[0025] In this embodiment, the temperature sensor is installed near the heating unit inside the atomizer to measure the actual temperature of the heating unit in real time. In general, the response time of the temperature sensor should be less than 1 second to ensure the timeliness and accuracy of temperature acquisition. As an option, the temperature sensor can be a thermocouple or thermistor sensor, and its measurement range should cover 0°C to 300°C to meet the temperature monitoring requirements under different usage environments and atomizer power ranges. Specifically, the data of the temperature sensor will be directly input into the thermodynamic model to describe the thermal diffusion behavior and the effect of heating power on temperature changes.

[0026] The ambient temperature sensor is used to measure the temperature of the external environment where the atomizer is located to obtain the impact of the environment on the heat exchange behavior of the atomizer. As a possible implementation method, the ambient temperature sensor can use a digital temperature sensor (such as DS18B20), and its accuracy should be within ±0.5℃ to ensure the accuracy of the heat exchange term in the thermodynamic model. Generally, the sensor is installed on the outer shell of the atomizer or close to the user's breathing position to avoid interference from internal heat.

[0027] The suction sensor is used to monitor the user's puffing behavior, including the puffing intensity and frequency. In one possible implementation, the suction sensor can use a differential pressure sensor, whose sensitivity should be sufficient to detect the pressure difference range of 1Pa to 1000Pa to capture the user's puffing changes. Specifically, the frequency and intensity of each puff of the user will be collected by the suction sensor and converted into an electrical signal and input into the control module. These data are not only used to adjust the heating power in real time, but also can be used to predict the user's next operation behavior, thereby further optimizing the mist temperature control strategy.

[0028] In some embodiments, to improve the accuracy of data collection, multiple temperature sensors can be distributed in different areas of the atomizer, such as near the center and edge of the heating unit. The distributed measurement method can more comprehensively reflect the temperature distribution inside the atomizer and avoid the error that may be caused by single-point measurement of the temperature sensor.

[0029] As an extended option, the data collected by the sensor module can be transmitted to the control module via wireless communication technology (such as Bluetooth or WiFi), thereby supporting remote control and data analysis. For example, users can view real-time temperature, environmental conditions and suction behavior data through a mobile terminal, thereby gaining a comprehensive understanding of the device's operating status.

[0030] The thermodynamic model in step (b) describes the change in atomizer temperature by: The heat diffusion term is used to describe the spatial transfer of heat inside the atomizer; The heating power term is used to describe the contribution of the heat provided by the heating unit to the temperature change; The heat exchange term is used to describe the heat exchange process between the internal temperature of the atomizer and the external environment temperature.

[0031] The thermal conductivity of heat diffusion inside the atomizer is determined according to the characteristics of the atomizer core material; The heat transfer coefficient between the external environment and the atomizer is dynamically adjusted according to the ambient temperature; The response time of the heating unit power to the atomizer temperature is obtained by fitting the system parameters.

[0032] In this embodiment, the thermodynamic model provides accurate input for the subsequent multi-objective optimization control strategy by establishing a physical description of the internal temperature change and combining it with the real-time data collected by the sensor. It also describes the temperature change mechanism inside the atomizer and can dynamically adapt to external conditions such as different ambient temperatures and user puffing behaviors. In order to further improve the accuracy of the model, the thermal conductivity of the internal heat diffusion of the atomizer, the external heat transfer coefficient, and the power response time of the heating unit are all parameterized and fitted according to the actual working conditions, so that the model has a high degree of dynamic adaptability and accuracy.

[0033] The thermodynamic model consists of three main parts: heat diffusion term, heating power term and heat exchange term, which are used to fully reflect the temperature change law inside and outside the atomizer.

[0034] Among them, data collection and input processing: The real-time data collected by the temperature sensor, ambient temperature sensor and suction sensor are used as the core input of the model. Specifically: The current temperature of the atomizer provided by the temperature sensor describes the instantaneous temperature of the heating unit; describes the external conditions; The suction intensity and frequency of the suction sensor are used to quantify the user's operating behavior.

[0035] These data are fed into a thermodynamic model in real time, which formulates three main processes that affect the temperature inside the atomizer: heat diffusion, heating power and heat exchange.

[0036] Thermal balance formula of thermodynamic model: Through the principle of thermodynamic balance, the model is established based on the following formula: Among them, q in is the input heat provided by the heating power; q out is the heat lost through thermal diffusion and heat exchange; ρ is the density of the atomizer core material; c is the specific heat capacity of the atomizer core material; V is the effective volume of the atomizer core; is the rate of change of atomizer temperature over time.

[0037] Calculation of heat dissipation, heating power and heat exchange from sensor data: Heat diffusion term: Thermal diffusion diff It describes the process of the internal temperature of the atomizer core being transferred in space through heat conduction. The calculation formula is: Among them, k is the thermal conductivity, which is determined by the characteristics of the atomizer core material; is the temperature gradient, calculated from the temperature sensor data.

[0038] Temperature gradient It can be approximately expressed as: Among them, T s (t) is the outer temperature of the atomizer provided by the temperature sensor in real time; T center is the estimated temperature of the center of the atomizer core; L is the characteristic length of the atomizer core.

[0039] Heating power term q power : Heating power term q power Describes the heat provided by the heating unit to the inside of the atomizer, the formula is: Among them, V is the power supply voltage of the heating unit, which is dynamically adjusted by the control module according to the sensor data; R is the resistance of the heating unit, which is a fixed parameter; η is the heating efficiency, which is obtained by experimental fitting and is usually between 0.8-0.95.

[0040] In step (a), the real-time control of the heating power depends on the user's suction intensity provided by the suction sensor. When the user's suction intensity increases, the control module increases the supply voltage V, thereby dynamically increasing q power .

[0041] Heat exchange term q exchange :Heat exchange describes the heat transfer between the internal temperature of the atomizer and the environment, and its formula is: q exchange =h·A·(T s (t)-T a (t)) Where h is the heat transfer coefficient, which is dynamically determined by the ambient temperature and humidity; A is the effective heat exchange area of ​​the atomizer surface; T s (t) is the current temperature of the atomizer, provided by the temperature sensor; T a (t) is the external ambient temperature, provided by the ambient temperature sensor.

[0042] In practical applications, the heat transfer coefficient h is fitted by the following formula: h=h0·(1+α·T a (t)) Where h0 is the reference heat transfer coefficient; α is the influence factor of temperature on the heat transfer coefficient. For example, when the ambient temperature T a When (t) increases, the heat exchange efficiency decreases, and the system needs to dynamically adjust the heating power according to h to maintain the target temperature.

[0043] In actual use, the thermodynamic model dynamically adjusts parameters through real-time updated sensor data. The details are as follows: The thermal diffusion coefficient k is dynamically corrected according to the atomizer core material and temperature gradient; The heat transfer coefficient h is dynamically optimized in combination with ambient temperature sensor data; The heating efficiency η is corrected according to the supply voltage V and the actual temperature rise.

[0044] Therefore, through the data collected by the sensor, the thermodynamic model uses three modules: heat diffusion, heating power and heat exchange to comprehensively describe the temperature changes inside the atomizer. Combined with the dynamic parameters updated in real time, the model provides a basis for subsequent optimization control strategies and power calculations, enabling the system to accurately adapt to complex environments and changes in user behavior.

[0045] The multi-objective optimization control strategy in step (c) includes: Minimize the deviation between the current temperature of the atomizer and the target temperature; Minimize the energy consumption of heating units for heating power.

[0046] The multi-objective optimization control strategy in step (c) adopts the following mathematical model: The square value of temperature deviation is taken as the primary optimization target, and the square value of heating power is taken as the secondary optimization target; The weighting coefficient of the target is dynamically adjusted according to user needs, giving priority to either temperature control accuracy or energy consumption optimization.

[0047] In this embodiment, step (c) dynamically coordinates the balance between the temperature control accuracy and energy consumption of the atomizer through a multi-objective optimization control strategy. The main goal is to minimize the deviation between the current temperature and the target temperature, and the secondary goal is to minimize the energy consumption of the heating unit heating power. Through mathematical modeling, the two goals are combined into an optimization objective function, and the weighted coefficients of the goals are dynamically adjusted to flexibly adapt to user needs and different usage scenarios.

[0048] In this embodiment, the multi-objective optimization control strategy realizes the dynamic adjustment of the heating power of the heating unit by constructing the optimization objective function, ensuring that the atomizer temperature is stable within the target range while reducing energy consumption. The optimization control strategy is based on the following two objectives: First, minimize the current temperature T s (t) and target temperature T target By adjusting the heating power in real time to avoid deviations between the two, the user can have a consistent smoking experience under different environmental conditions.

[0049] Second, minimize the energy consumption of the heating unit q powert , by reducing unnecessary heating power consumption, improving the energy efficiency of the system and extending the life of the equipment.

[0050] Generally, there is a certain contradiction between the above two objectives. For example, giving priority to temperature control accuracy may lead to increased power consumption. Therefore, the weighted summation method of optimizing the objective function is used to unify the two objectives and dynamically adjust the weighting coefficient according to user needs.

[0051] Mathematical modeling of optimization objective function: The expression of the optimization objective function is as follows: Where J is the total value of the optimization objective function; w1 and w2 are the weighting coefficients of the temperature deviation term and the power consumption term, respectively, which are used to adjust the weights of the two in the optimization; T s (t) is the current temperature of the atomizer measured in real time; T target is the target temperature; q powert is the heating power, calculated from the input voltage and resistance of the heating unit.

[0052] In one possible implementation, the weighting coefficients w1 and w2 can be dynamically adjusted by user selection. For example, when the user prioritizes the stability of the atomization temperature, the weight of w1 is increased to strengthen temperature control; and in low power consumption mode, the weight of w2 is increased to reduce energy consumption.

[0053] The optimal heating power in step (d) is determined by: Construct an optimization objective function, and perform a weighted sum of the square value of the temperature deviation and the square value of the heating power; Based on the optimization objective function and the dynamic thermodynamic model, the optimal heating power at the current moment is calculated through the optimal control method.

[0054] In an embodiment, step (d) calculates the optimal heating power at the current moment by an optimal control method based on the optimization objective function and the dynamic thermodynamic model. The temperature deviation and power consumption data are acquired in real time, and the weighted sum of the two is used to form an optimization objective function, and the optimal heating power under the current conditions is dynamically calculated in combination with the thermodynamic model.

[0055] According to the optimization objective function in step (c), the effect of heating power on atomizer temperature can be described by a dynamic thermodynamic model: in, is the temperature change rate, ρ is the density of the atomizer core material; c is the specific heat capacity of the atomizer core material; V is the effective volume of the atomizer core; In order to solve the optimal heating power q power , this embodiment uses the gradient descent method to iteratively solve the optimization objective function J. Its update formula is: in, represents the heating power value calculated after the n+1th iteration, It represents the heating power value calculated after the nth iteration, and α is the step size factor, which is used to control the optimization convergence speed; It represents the partial derivative of the objective function with respect to the heating power, which can be decomposed into: in, Represents the rate at which heating power affects temperature, which can be approximated by the thermodynamic model: Through iterative updates, the optimization algorithm gradually adjusts the heating power q power Finally, the minimum value of the optimization target J is reached.

[0056] Therefore, the weighting coefficients w1 and w2 can be dynamically adjusted according to user needs or system mode. For example, in the high-performance mode that prioritizes temperature control accuracy, w1 = 0.8 and w2 = 0.2 can be set to increase the weight of the temperature deviation item. In the energy-saving mode, w1 = 0.5 and w2 = 0.5 can be set to achieve a balance between temperature control and power consumption.

[0057] The temperature adjustment in step (e) comprises: According to the optimal heating power, the target supply voltage of the heating unit is calculated in real time; Adjust the power supply voltage of the heating unit to make the mist temperature of the atomizer dynamically approach the target temperature range; The feedback control in step (f) includes: Inputting the real-time collected atomizer temperature data into the dynamic thermodynamic model; Compare the prediction results of the dynamic thermodynamic model with the real-time temperature data to calculate the temperature deviation; The supply voltage of the heating unit is dynamically adjusted according to the temperature deviation to optimize the heating power.

[0058] The supply voltage is dynamically corrected through feedback control based on the real-time temperature prediction and the target temperature deviation.

[0059] In this embodiment, the temperature adjustment module in step (e) is directly related to the optimization of the heating power in the previous step. Based on the optimal heating power value calculated by the previous module, the temperature output of the system is dynamically adjusted by controlling the power supply voltage of the heating unit, so that the actual temperature of the atomizer is always close to the target temperature range. The control effect is further optimized through real-time feedback and predictive correction to ensure the stability and responsiveness of the system operation.

[0060] In step (e), the optimal heating power is first obtained through the optimization algorithm. In order to achieve the effective output of this power, it is necessary to convert it into the target power supply voltage V through the voltage calculation formula. target , the calculation formula is: in, The optimal heating power is determined by the optimization algorithm; R represents the resistance value of the heating unit, which can be given by experimental calibration or known design parameters.

[0061] In general, the above formula can be directly used to calculate the target voltage. In some implementations, the calculation accuracy of the target voltage can be improved by measuring the change in the resistance value R in real time and taking into account the nonlinear resistance characteristics caused by the temperature change of the heating element. For example, when the resistance increases linearly with temperature, it can be corrected to: R=R0·(1+β·(T s -T0)) Where R0 is the resistance value at reference temperature T0, β is the resistance temperature coefficient, T s is the current atomizer temperature.

[0062] Specifically, the technical contents of adjusting the supply voltage to achieve dynamic temperature control are as follows: After determining the target supply voltage V target After that, the actual supply voltage V is adjusted by controlling the hardware actual (t), so that the atomizer temperature T s Dynamically approaching the target temperature V target The actual supply voltage regulation process adopts a closed-loop control scheme, and the control formula is as follows: V actual (t) = V target +ΔV The temperature feedback correction value ΔV can be determined by the proportional-integral-differential (PID) control method, and its expression is: Among them, K p , K i , K d are proportional, integral and differential control coefficients respectively; T target is the target temperature value, T s (τ) is the actual temperature of the atomizer at the current moment collected by the temperature sensor, is the integral value of temperature deviation, To indicate the speed of change of temperature deviation over time, it is used to describe the trend of current temperature deviation change. τ is the time integral variable, t represents the current time point in the temperature control system, and related variables are calculated based on this moment.

[0063] In order to achieve optimal adjustment of heating power, a feedback control method based on a dynamic thermodynamic model is adopted. Specifically, the temperature data of the atomizer is collected in real time and input into the dynamic thermodynamic model for prediction and analysis. The model is expressed as follows: Among them, T s (t+Δt) is the predicted atomizer temperature at the next moment; τ represents the thermal inertia time constant, reflecting the system response speed; is the actual heating power, and the actual supply voltage V actual (t) related; h is the heat transfer coefficient; T env is the ambient temperature, which serves as an external interference factor.

[0064] The above model can predict the temperature change trend in real time and compare it with the real-time collected temperature data to calculate the temperature deviation ΔT: ΔT=T target -T s (t+Δt) In general, the temperature deviation ΔT will directly participate in the dynamic adjustment of the supply voltage. As an option, the voltage adjustment ΔV can be calculated by an incremental method to reduce the impact of transient errors. The incremental calculation formula is: ΔV=K Δ ΔT Among them, K Δ is the incremental control coefficient, obtained through experimental calibration.

[0065] In one possible implementation, the feedback control and temperature regulation are connected in the following manner: Temperature regulation provides the target supply voltage V target It is the basic input of feedback control, and feedback control further corrects the actual supply voltage V according to the prediction deviation of the dynamic thermodynamic model. actual (t). The two work together to achieve precise control of the heating unit.

[0066] Specifically, the calculated results of temperature regulation are used as the initial settings of the system, providing rapid adjustment capabilities when there is a large temperature deviation. The feedback control module obtains data in real time through the temperature sensor, and dynamically corrects the supply voltage in combination with model prediction, so that the system can maintain stable regulation within a small range.

[0067] In some embodiments, the complexity of the thermodynamic model can be further optimized, for example, by introducing nonlinear terms or compensation terms to more accurately describe the impact of environmental factors on temperature, thereby improving the robustness and adaptability of the overall control.

[0068] Generally speaking, feedback control plays a key role in optimizing system performance. In some specific scenarios, it is also possible to collect multi-point temperature data through a distributed sensor network and combine it with an improved dynamic model to achieve a more accurate control effect.

[0069] Please refer to the attached Figure 2 The present invention provides a system for implementing the above control method, comprising: Data acquisition module: used to collect the current temperature of the atomizer, the ambient temperature and the user's puffing behavior data in real time, and transmit the collected data to the control module; Control module: connected to the data acquisition module, used to receive real-time data and calculate the optimal heating power of the heating unit according to the dynamic thermodynamic model; Heating module: connected to the control module, used to receive the heating power instruction output by the control module, adjust the power supply voltage, and heat the inside of the atomizer; Power supply module: connected to the heating module and the control module, used to dynamically adjust the power supply voltage of the heating module according to the heating power instruction of the control module; Feedback module: connected with the data acquisition module, control module and heating module, used to compare the deviation between the current temperature of the atomizer and the target temperature in real time, and transmit the comparison result to the control module to dynamically correct the heating power.

[0070] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A mist temperature control method based on an electronic cigarette atomizer, characterized in that: The following steps are involved: (a) Collecting the current temperature of the atomizer, the ambient temperature and the user's puffing behavior data through sensors; (b) Based on the data collected by the sensor, a thermodynamic model is established to describe the temperature changes inside the atomizer; (c) Construct a multi-objective optimization control strategy based on the deviation between the current temperature of the atomizer and the target temperature; (d) Determine the optimal heating power of the atomizer heating unit at the current moment based on the thermodynamic model and multi-objective optimization control strategy; (e) adjusting the power supply voltage of the heating unit in real time according to the optimal heating power, controlling the atomizer power to adjust the mist temperature, so that the atomizer mist temperature is within the target temperature range; (f) Compare the real-time temperature data of the atomizer with the target temperature deviation, and use feedback to adjust the heating power.

2. The mist temperature control method based on the electronic cigarette atomizer according to claim 1 is characterized in that: In step (a), the sensor includes: Temperature sensor, used to collect the current temperature inside the atomizer; An ambient temperature sensor, used to detect the ambient temperature outside the atomizer; Suction sensor, used to monitor the user's suction intensity and frequency.

3. The mist temperature control method based on the electronic cigarette atomizer according to claim 1, characterized in that: The thermodynamic model in step (b) includes: The heat diffusion term is used to describe the spatial transfer of heat inside the atomizer; The heating power term is used to describe the contribution of the heat provided by the heating unit to the temperature change; The heat exchange term is used to describe the heat exchange process between the internal temperature of the atomizer and the external environment temperature.

4. The mist temperature control method based on the electronic cigarette atomizer according to claim 3 is characterized in that: The thermal conductivity of heat diffusion inside the atomizer is determined according to the characteristics of the atomizer core material; The heat transfer coefficient between the external environment and the atomizer is dynamically adjusted according to the ambient temperature; The response time of the heating unit power to the atomizer temperature is obtained by fitting the system parameters.

5. The mist temperature control method based on the electronic cigarette atomizer according to claim 1, characterized in that: The multi-objective optimization control strategy in step (c) includes: Minimize the deviation between the current temperature of the atomizer and the target temperature; Minimize the energy consumption of heating units for heating power.

6. The mist temperature control method based on the electronic cigarette atomizer according to claim 5, characterized in that: The multi-objective optimization control strategy in step (c) includes: The square value of temperature deviation is taken as the primary optimization target, and the square value of heating power is taken as the secondary optimization target; The weighting coefficient of the target is dynamically adjusted according to user needs, giving priority to either temperature control accuracy or energy consumption optimization.

7. The mist temperature control method based on the electronic cigarette atomizer according to claim 1, characterized in that: Determining the optimal heating power in step (d) includes: Construct an optimization objective function, and perform a weighted sum of the square value of the temperature deviation and the square value of the heating power; Based on the optimization objective function and the dynamic thermodynamic model, the optimal heating power at the current moment is calculated through the optimal control method.

8. The mist temperature control method based on the electronic cigarette atomizer according to claim 1, characterized in that: The temperature adjustment in step (e) comprises: According to the optimal heating power, the target supply voltage of the heating unit is calculated in real time; Adjust the power supply voltage of the heating unit to make the mist temperature of the atomizer dynamically approach the target temperature range; The supply voltage is dynamically corrected through feedback control based on the real-time temperature prediction and the target temperature deviation.

9. The mist temperature control method based on the electronic cigarette atomizer according to claim 1, characterized in that: The feedback control in step (f) includes: Inputting the real-time collected atomizer temperature data into the dynamic thermodynamic model; Compare the prediction results of the dynamic thermodynamic model with the real-time temperature data to calculate the temperature deviation; The supply voltage of the heating unit is dynamically adjusted according to the temperature deviation to optimize the heating power.

10. A mist temperature control system based on an electronic cigarette atomizer, based on the mist temperature control method based on an electronic cigarette atomizer according to any one of claims 1 to 9, characterized in that: include: Data acquisition module: used to collect the current temperature of the atomizer, the ambient temperature and the user's puffing behavior data in real time, and transmit the collected data to the control module; Control module: connected to the data acquisition module, used to receive real-time data and calculate the optimal heating power of the heating unit according to the dynamic thermodynamic model; Heating module: connected to the control module, used to receive the heating power instruction output by the control module, adjust the power supply voltage, and heat the inside of the atomizer; Power supply module: connected to the heating module and the control module, used to dynamically adjust the power supply voltage of the heating module according to the heating power instruction of the control module; Feedback module: connected with the data acquisition module, control module and heating module, used to compare the deviation between the current temperature of the atomizer and the target temperature in real time, and transmit the comparison result to the control module to dynamically correct the heating power.

Images