Electronic atomizer intelligent control system based on airflow induction

Abstract

The invention relates to the technical field of electronic atomizer control, in particular to an electronic atomizer intelligent control system based on airflow induction, which comprises a data acquisition synchronization module, an inspiration behavior analysis module, a power and smoke regulation module, an atomizer adaptation control module and an atomizer energy consumption management module. According to the invention, through synchronous acquisition of airflow and environmental data, the response capability of the device to the inhalation behavior of the user is improved, and through analysis of the inhalation mode prediction data of the user, the power output of the electronic atomizer is automatically adjusted, so that the smoke yield is consistent with the real-time demand of the user; meanwhile, the smoke density and quality are dynamically adjusted according to environmental factors, optimization of smoke output is ensured, the ideal state of smoke can be maintained no matter how environmental conditions change, energy consumption is effectively reduced through fine power control, the service life of a battery is prolonged, the overall energy efficiency of the electronic atomizer is improved, and meanwhile user experience is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic atomizer control, and in particular to an intelligent control system of an electronic atomizer based on airflow sensing. Background Art

[0002] Electronic atomizer control involves a combination of multiple technologies to regulate and optimize e-cigarette performance and user experience, mainly including power management, airflow detection, temperature control, and intelligent design of the user interface. By optimizing the internal electronic control system of the electronic atomizer, precise control of smoke output, heat distribution, and battery life can be achieved. With the advancement of technology, more and more intelligent functions, such as data recording via Bluetooth connection to smart devices, are also integrated into the control system of the electronic atomizer.

[0003] Among them, the airflow-sensing electronic atomizer intelligent control system is a technology that uses an airflow sensor to automatically adjust the power and smoke output of the electronic atomizer. The core is to detect the airflow changes caused by the inhalation action. The system can adjust the working state of the heating element in real time, thereby controlling the amount and concentration of smoke to meet the user's smoking needs. It not only improves the energy efficiency of the electronic atomizer, but also enhances the user experience, making the use process smoother and more satisfying.

[0004] The existing technology ignores the importance of airflow sensing and fails to achieve accurate monitoring and real-time response to the user's inhalation action, resulting in the inability to make immediate adjustments when the user's inhalation intensity changes, thereby affecting the quality and quantity of smoke output. The lack of effective airflow monitoring also means that the device cannot automatically adjust the smoke characteristics according to different environmental conditions, resulting in the evaporation and diffusion of the smoke being affected, further reducing the user experience, affecting not only the performance of the device, but also leading to low energy efficiency and shortened battery life, causing the control system to be unable to finely control the smoke output and making it difficult to meet the needs of different users. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose an intelligent control system for an electronic atomizer based on airflow sensing.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: an intelligent control system for an electronic atomizer based on airflow sensing, the system comprising:

[0007] The data acquisition and synchronization module is based on the airflow sensor to collect the inhalation speed and frequency data, monitor the stability of the electronic atomizer inhalation data in real time, and record the ambient temperature and humidity through the environmental sensor, and synchronize the data time to establish the airflow behavior data set;

[0008] The inhalation behavior analysis module continuously monitors the change of gas flow rate in the airflow channel of the electronic atomizer based on the airflow behavior data set, calculates the dynamic trend of the current inhalation rate, evaluates the stability of the inhalation rhythm, and determines the user's inhalation intensity based on the evaluation results to obtain inhalation pattern prediction data;

[0009] The power and smoke adjustment module calls the predicted inhalation mode data, analyzes the difference between the current inhalation speed and the predicted inhalation intensity, identifies the power amount to be adjusted, adjusts the power output of the electronic atomizer, analyzes the effect of the power adjustment on the smoke amount, and generates a dynamic smoke output amount;

[0010] The atomizer adaptive control module calls the dynamic smoke output, analyzes the influence of environmental factors on the evaporation rate and suspension time of smoke particles, determines the diffusion stability of smoke under different environments, adjusts the power compensation amount of the electronic atomizer, and obtains the smoke control index.

[0011] The improvements of the present invention are that the airflow behavior data set includes an inhalation speed index, an inhalation frequency index, and an ambient temperature and humidity index; the inhalation mode prediction data includes an inhalation rate trend, an inhalation rhythm stability, and an inhalation intensity index; the dynamic smoke output includes smoke volume change information and the degree of power adjustment influence; and the smoke control index includes an evaporation rate index and a suspension time index.

[0012] The present invention is improved in that the data acquisition synchronization module comprises:

[0013] The airflow data acquisition submodule is based on the airflow sensor, which monitors the airflow data during the inhalation process of the electronic atomizer, records the inhalation speed and frequency in real time, calculates the average value of the data in each time window, removes abnormal values, and obtains a valid airflow data set;

[0014] The environmental data recording submodule records the temperature and humidity data through the environmental sensor based on the effective airflow data set, monitors the changes of the environmental data at different time points, calculates the average value and fluctuation range of the environmental temperature and humidity during the inhalation process, and obtains the environmental matching data set;

[0015] The data screening synchronization submodule synchronizes the inhalation data and the environmental data based on the environmental matching data set, and calculates the time error between the data points using the formula:

[0016] ;

[0017] Get data synchronization accuracy , establish an airflow behavior data set, where, Represents the timestamp of the inhalation data, that is, the specific recording time corresponding to each data point, Represents the matching environmental data timestamp, that is, the environmental data recording time corresponding to the inhalation data timestamp, Represents the total number of data points.

[0018] The present invention is improved in that the inhalation behavior analysis module comprises:

[0019] The airflow rate monitoring submodule monitors the gas flow rate in the airflow channel of the electronic atomizer in real time based on the airflow behavior data set, continuously records the inhalation speed data, compares it with the historical inhalation speed data, analyzes the dynamic changes of the current inhalation speed, identifies the abnormal interval of the inhalation speed, and generates an inhalation speed monitoring record;

[0020] The inspiratory rhythm comparison submodule analyzes the dynamic trend of abnormal inspiratory rate based on the inspiratory speed monitoring record, calculates the rate deviation at each time point, compares and analyzes it with the user's historical breathing rhythm pattern, evaluates the consistency and variation of the inspiratory rhythm, and obtains the inspiratory rhythm stability analysis result;

[0021] The inspiratory pattern prediction submodule calls the inspiratory rhythm stability analysis result, using the formula:

[0022] ;

[0023] Calculate the predicted inspiratory pattern , get the inhalation mode prediction data, where, Representative The average inspiratory speed in the time window, Representative The inspiratory duration of the time window, Representative The inspiratory rhythm stability parameter of the time window, Representative The deviation coefficient of the time window is Represents the number of time windows for analysis.

[0024] The present invention is improved in that the power and smoke adjustment module comprises:

[0025] The inhalation mode difference calculation submodule calls the inhalation mode prediction data, analyzes the current real-time inhalation speed and the predicted inhalation intensity data, calculates the difference between the two data, and obtains the inhalation intensity deviation value;

[0026] The power adjustment amount identification submodule performs correlation analysis based on the inhalation intensity deviation value and the current power output value, using the formula:

[0027] ;

[0028] Calculate the required power adjustment , and then update the power output value according to the adjustment amount to obtain the adjusted power output value, where, represents the predicted inspiratory speed, Represents the real-time inhalation speed, Represents the current power output value, is the suction speed compensation coefficient, Adjust the base factor for power;

[0029] The dynamic smoke output calculation submodule calls the adjusted power output value, combines the real-time inhalation data, analyzes the output change trend of the smoke volume, analyzes the influence of the power adjustment on the smoke volume, and obtains the dynamic smoke output.

[0030] The present invention is improved in that the atomizer adaptation control module comprises:

[0031] The smoke evaporation rate calculation submodule calls the dynamic smoke output and uses the formula according to the ambient temperature and humidity factors:

[0032] ;

[0033] Calculating the evaporation rate of smoke particles ,in, represents the concentration of smoke particles, represents the ambient temperature, Represents the ambient humidity, represents the air flow velocity, and They are the temperature and humidity influence coefficient and the airflow influence coefficient respectively;

[0034] The diffusion stability judgment submodule calls the evaporation rate of the smoke particles, calculates the suspension time of the smoke under different environmental conditions, judges the diffusion stability by the diameter change trend of the smoke particles, and obtains the smoke diffusion result;

[0035] The power compensation amount adjustment submodule calls the smoke diffusion result, adjusts the power compensation amount of the electronic atomizer, optimizes the smoke density, and obtains the smoke control index.

[0036] The present invention is improved in that the system further comprises:

[0037] The atomizer energy consumption management module analyzes the variation range of the current power output according to the smoke control index, identifies the power fluctuation range that meets the optimization conditions, determines the optimal time interval by comparing the power regulation efficiency benchmark value, and updates the power regulation frequency of the electronic atomizer to obtain the atomizer optimization result;

[0038] The atomizer optimization result includes a power fluctuation range identification result, power regulation efficiency information, and regulation frequency update information.

[0039] The present invention is improved in that the atomizer energy consumption management module comprises:

[0040] The power fluctuation analysis submodule monitors the current power output data according to the smoke control index, calculates the power change at each sampling point, and identifies the power fluctuation range that meets the optimization conditions;

[0041] The efficiency benchmark comparison submodule evaluates the power regulation frequency within the power fluctuation interval and compares it with the power regulation efficiency benchmark value to determine the optimal power regulation time interval;

[0042] The power optimization regulation submodule uses the formula based on the optimal power regulation time interval:

[0043] ;

[0044] Update the power adjustment frequency of the electronic atomizer , and the optimization results of the atomizer are obtained, where represents the optimization rate obtained from the optimal power regulation time interval, Representing time point The power value, Represents the maximum power value in the time interval, Represents the total number of data points in the time interval.

[0045] Compared with the prior art, the advantages and positive effects of the present invention are:

[0046] In the present invention, the synchronous collection of airflow and environmental data improves the responsiveness of the device to the user's inhalation behavior. By analyzing the user's inhalation pattern prediction data, the power output of the electronic atomizer is automatically adjusted to keep the smoke output consistent with the user's real-time needs. At the same time, the smoke density and quality are dynamically adjusted according to environmental factors to ensure the optimization of smoke output. Regardless of how the environmental conditions change, the ideal state of the smoke can be maintained. Through fine power control, energy consumption is effectively reduced, battery life is extended, and the overall energy efficiency of the electronic atomizer is improved. At the same time, the user experience is enhanced to ensure the smoothness and satisfaction of the use process. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a system flow chart of the present invention;

[0048] Figure 2 This is a flow chart of the data acquisition synchronization module in the present invention;

[0049] Figure 3 is a flow chart of the inhalation behavior analysis module in the present invention;

[0050] Figure 4It is a flow chart of the power and smoke adjustment module in the present invention;

[0051] Figure 5 It is a flow chart of the atomizer adaptation control module in the present invention;

[0052] Figure 6 This is a flow chart of the atomizer energy consumption management module in the present invention. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0054] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0055] Example

[0056] See also Figure 1 The present invention provides a technical solution: an intelligent control system for an electronic atomizer based on airflow sensing includes:

[0057] The data acquisition and synchronization module is based on the airflow sensor to collect the inhalation speed and frequency data, monitor the stability of the electronic atomizer inhalation data in real time, screen the data that meets the effective measurement standards, and record the ambient temperature and humidity through the environmental sensor, and synchronize the data time to establish the airflow behavior data set;

[0058] The inhalation behavior analysis module analyzes the historical inhalation speed data based on the airflow behavior data set, continuously monitors the changes in the gas flow rate in the airflow channel of the electronic atomizer, calculates the dynamic trend of the current inhalation rate, compares it with the user's breathing rhythm pattern, evaluates the stability of the inhalation rhythm, and judges the user's inhalation intensity based on the evaluation results to obtain the inhalation pattern prediction data;

[0059] The power and smoke adjustment module calls the predicted data of the inhalation mode, analyzes the difference between the current inhalation speed and the predicted inhalation intensity, identifies the amount of power that needs to be adjusted, and then adjusts the power output of the electronic atomizer according to the real-time inhalation data, analyzes the impact of the power adjustment on the smoke volume, and generates dynamic smoke output;

[0060] The atomizer adaptive control module calls the dynamic smoke output, analyzes the impact of environmental factors on the evaporation rate and suspension time of smoke particles, determines the diffusion stability of smoke in different environments, adjusts the power compensation of the electronic atomizer, optimizes the smoke density, and obtains the smoke control index;

[0061] The atomizer energy consumption management module analyzes the change range of the current power output according to the smoke control index, identifies the power fluctuation range that meets the optimization conditions, determines the optimal time interval by comparing the power regulation efficiency benchmark value, and updates the electronic atomizer power regulation frequency to obtain the atomizer optimization result.

[0062] The airflow behavior data set includes inhalation speed index, inhalation frequency index, and ambient temperature and humidity index. The inhalation mode prediction data includes inhalation rate trend, inhalation rhythm stability, and inhalation intensity index. The dynamic smoke output includes smoke volume change information and power adjustment impact. The smoke control indicators include evaporation rate index and suspension time index. The atomizer optimization results include power fluctuation range identification results, power regulation efficiency information, and regulation frequency update information.

[0063] See also Figure 2 , the data acquisition synchronization module includes:

[0064] The airflow data acquisition submodule is based on the airflow sensor, which monitors the airflow data during the inhalation process of the electronic atomizer, records the inhalation speed and frequency in real time, calculates the average value of the data in each time window, removes abnormal values, and obtains a valid airflow data set;

[0065] Based on the airflow sensor, the airflow data of the electronic atomizer during the inhalation process is monitored. The sensor records the airflow changes in each inhalation cycle to obtain the inhalation speed and frequency. The inhalation speed can be calculated by the flow rate detection module, and the inhalation frequency is statistically analyzed based on the periodic changes of the airflow fluctuations in the time series data. In each time window, the mean inhalation speed and frequency in the time window are calculated, and the speed change threshold is set to judge the data fluctuation. Stable airflow data points are extracted based on the time series data, and mutation data points are eliminated. If the change amplitude of the inhalation speed or inhalation frequency in a certain time window exceeds the set speed change threshold, the window data is marked as invalid data and eliminated, and finally a valid airflow data set is obtained. The speed change threshold is set based on the normal fluctuation range of the electronic atomizer's inhalation speed. This value requires comprehensive statistics of a large amount of normal inhalation behavior data to obtain the mean of the inhalation speed. and standard deviation , by setting times the standard deviation range as the threshold, that is, the speed change threshold ,in, Usually 2 or 3 are used to ensure that more than 95% of normal data points are covered. For example, if the mean inhalation speed of the electronic atomizer is 12 cm / s and the standard deviation is 1.5 cm / s, then when setting When , the speed change threshold is obtained: ,If the inhalation speed exceeds 15 cm / s in a certain time window, the data point will be eliminated to ensure the rationality of the data.

[0066] The environmental data recording submodule records the temperature and humidity data through environmental sensors based on the effective airflow data set, monitors the changes of environmental data at different time points, calculates the average value and fluctuation range of environmental temperature and humidity during the inhalation process, and obtains the environmental matching data set;

[0067] Temperature and humidity data are recorded by environmental sensors. The sensors obtain environmental data at different time points and form a time series data set. The mean temperature and humidity during the inhalation process are calculated by taking the arithmetic mean of all environmental data points in a certain inhalation cycle and calculating the change amplitude of temperature and humidity in the cycle. If the change amplitude exceeds the set environmental fluctuation threshold, the environmental data in the cycle will be eliminated. The timestamp information in the effective airflow data set is called, and the environmental data timestamp is compared to filter the data with a higher matching degree to ensure that the environmental data corresponds to the inhalation data and obtain the environmental matching data set. The setting of the environmental fluctuation threshold is based on the stability requirements of the environmental data. This value can be used to obtain the mean temperature change through historical sampling data. and its standard deviation , mean humidity change and its standard deviation , the threshold is set as follows: and ,in, and As an adjustment factor, it is usually set to 2 to cover more than 95% of normal data. For example, if the mean value of the ambient temperature is 25°C and the standard deviation is 1.2°C, the temperature fluctuation threshold is calculated as follows: ,If the temperature in a time window exceeds 27.4℃, the data in this window will be eliminated. Similarly, the humidity threshold can be calculated using the same method.

[0068] The data screening and synchronization submodule synchronizes the inhalation data and the environmental data based on the environmental matching data set, and calculates the time error between the data points using the formula:

[0069] ;

[0070] Get data synchronization accuracy , establish an airflow behavior data set, which is a data set formed after the airflow data and environmental data are subjected to outlier removal, time matching and synchronization accuracy inspection, among which, Represents the timestamp of the inhalation data, that is, the specific recording time corresponding to each data point, Represents the matching environmental data timestamp, that is, the environmental data recording time corresponding to the inhalation data timestamp, represents the total number of data points;

[0071] The timestamp of the data collected by the sensor is in milliseconds (ms). Assume that the timestamp of the collected inhalation data is , and , the corresponding environment data timestamp is , and , the total number of data points , substitute the data into the formula to calculate:

[0072] ;

[0073] ;

[0074] The result shows that the data synchronization error is 6.16ms. When compared with a threshold value (e.g., 10ms), if the synchronization error is lower than the threshold value, the data meets the synchronization standard and an airflow behavior dataset can be established.

[0075] See also Figure 3 , the inhalation behavior analysis module includes:

[0076] The airflow rate monitoring submodule monitors the gas flow rate in the airflow channel of the electronic atomizer in real time based on the airflow behavior data set, continuously records the inhalation speed data, compares it with the historical inhalation speed data, analyzes the dynamic changes of the current inhalation speed, identifies the abnormal interval of the inhalation speed, and generates the inhalation speed monitoring record;

[0077] First, the gas flow rate detection cycle is set and the sampling frequency is determined. A flow rate sensor is arranged in the air flow channel of the electronic atomizer to measure the air flow rate in real time. The instantaneous speed data detected by the air flow sensor is used to calculate the average inhalation speed in a continuous time period using the sliding average method. At the same time, the data is denoised to remove the sudden changes and noise points caused by sensor errors. For example, if the detection cycle is set to 50ms and the flow rate read by the air flow sensor at a certain moment is , the sliding average is calculated as follows: ,in, is the sliding window size. If it is set to 5, then the current moment The average inhalation speed is the arithmetic mean of the data of the previous 5 moments. After calculating the inhalation speed of the continuous time window, historical data comparison is performed, the inhalation speed data sequence in the past period of time is called, and the historical data in the same time period is selected to calculate the deviation. The calculation formula is as follows: ,in, is the average air intake speed at the same time in history. For example, if the historical data is 0.8m / s and the current air intake speed is 1.2m / s, then the deviation , set the deviation threshold , such as 0.3m / s, if This moment is marked as an abnormal interval, the abnormal interval is recorded, and an inhalation speed monitoring record is generated.

[0078] The inspiratory rhythm comparison submodule analyzes the dynamic trend of abnormal inspiratory rate based on the inspiratory speed monitoring record, calculates the rate deviation at each time point, compares and analyzes it with the user's historical breathing rhythm pattern, evaluates the consistency and variation of the inspiratory rhythm, and obtains the inspiratory rhythm stability analysis results;

[0079] Compare the rate deviations at multiple consecutive time points and set the time window (e.g. 500ms), calculate the deviation mean of all time points in the window, and determine whether there is a sharp fluctuation in the inhalation rate, such as setting a fluctuation threshold When the mean deviation in the window is greater than the threshold, the window is marked as an unstable rhythm interval, and the rhythm stability is evaluated. The current user's inhalation rhythm curve is compared with its historical inhalation rhythm curve by dynamic time regularization, the rhythm consistency deviation is calculated, and the consistency benchmark threshold is set. (such as 0.15m / s). If the current rhythm deviation is greater than the reference threshold, the rhythm change amplitude is marked as abnormal. For example, if the inhalation rhythm data of a user in the past 5 times is [0.9, 1.0, 0.95, 1.05, 1.0]m / s, and the current detection rhythm is [1.2, 1.3, 1.15, 1.25, 1.3]m / s, the root mean square error (RMSE) between the two sets of data is calculated: , if calculated Greater than the set , then the inspiratory rhythm is judged to be abnormal, and the inspiratory rhythm stability analysis result is obtained.

[0080] The inspiratory pattern prediction submodule calls the inspiratory rhythm stability analysis results using the formula:

[0081] ;

[0082] Calculate the predicted inspiratory pattern , get the inhalation mode prediction data, where, Representative The average inspiratory speed in the time window, Representative The inspiratory duration of the time window, Representative The inspiratory rhythm stability parameter of the time window, Representative The deviation coefficient of the time window is Represents the number of time windows analyzed;

[0083] The test data of an electronic atomizer is as follows:

[0084] 3 time windows ( ), the suction speeds are , and ;

[0085] The inspiratory duration is , and ;

[0086] The parameters of inspiratory rhythm stability are , and ;

[0087] The coefficients of deviation are , , ;

[0088] Substitute into the formula to calculate:

[0089] ;

[0090] ;

[0091] The result shows that the predicted value of the current inhalation mode is 1.05, which is close to the set benchmark value of 1.0, indicating that the current user's inhalation mode is basically stable without obvious abnormal fluctuations.

[0092] See also Figure 4 , the power and smoke regulation module includes:

[0093] The inhalation mode difference calculation submodule calls the inhalation mode prediction data, analyzes the current real-time inhalation speed and the predicted inhalation intensity data, calculates the difference between the two data, and obtains the inhalation intensity deviation value;

[0094] The real-time inhalation speed refers to the air flow rate each time the user inhales when actually using the electronic atomizer. The flow rate can be detected by a flow sensor and converted into numerical data. The predicted inhalation intensity data is calculated based on the user's historical usage data, current environmental variables (such as temperature and humidity), and the usage mode set inside the device. In order to calculate the difference between the two, the real-time inhalation speed needs to be sampled first, and the data is stored in the cache for calculation. The time interval for each sampling is set to a fixed period so that the acquired data is continuous and comparable. For example, if a user inhales frequently in a short period of time, the system should be able to update and adjust its predicted value in time. When calculating the inhalation intensity deviation value, it is necessary to calculate the difference between the real-time inhalation speed data and the predicted inhalation intensity data, and use absolute value calculation to avoid positive and negative value offset errors. For example, if the real-time inhalation speed is 2.5L / min, and the predicted inhalation intensity data is 3.0L / min, the calculated difference is , and this result is the inhalation intensity deviation value.

[0095] The power adjustment amount identification submodule performs correlation analysis based on the inhalation intensity deviation value and the current power output value using the formula:

[0096] ;

[0097] Calculate the required power adjustment , and then update the power output value according to the adjustment amount to obtain the adjusted power output value, where, represents the predicted inspiratory speed, Represents the real-time inhalation speed, Represents the current power output value, is the suction speed compensation coefficient, Adjust the base factor for power;

[0098] Based on the inhalation intensity deviation value, the correlation analysis is performed with the current power output value. The current power output value refers to the instantaneous power provided by the device when the user inhales. This value is affected by the battery voltage, the resistance of the heating wire, and the power curve set inside the device. When calculating the power adjustment amount, the inhalation intensity deviation value must be called first, and then combined with the current power output value, the formula is used to calculate. If the current power output value , predicted inspiratory velocity , real-time suction speed , suction speed compensation coefficient , power adjustment basic coefficient , then substitute into the calculation:

[0099] ;

[0100] ;

[0101] The calculated power adjustment amount is 0.1136 W, and the power output value is finally updated to obtain the adjusted power output value.

[0102] The dynamic smoke output calculation submodule calls the adjusted power output value, combines the real-time inhalation data, analyzes the output change trend of the smoke volume, analyzes the impact of power adjustment on the smoke volume, and obtains the dynamic smoke output;

[0103] The adjusted power output value is called, and the output change trend of the smoke volume is analyzed in combination with the real-time inhalation data. The generation of smoke volume is mainly affected by the power output and is also related to the air flow. During the user's inhalation, the airflow carries the atomized liquid particles through the heating cavity. When the adjusted power output value changes, the atomization efficiency will change, thereby affecting the smoke volume. In order to calculate the smoke output change trend, the smoke generation per unit time must first be measured, and the smoke particle concentration data is obtained using optical detection or mass sensors. The density of smoke particles per unit volume is calculated in combination with the current inhalation flow. For example, if the inhalation flow measured in a certain period of time is 2.5L / min, and the smoke generation mass per unit time is 0.8g / min, then the smoke concentration is , combined with the output change trend after power adjustment, the smoke change trend in the future can be further predicted to obtain the dynamic smoke output.

[0104] See also Figure 5 , the atomizer adaptation control module includes:

[0105] The smoke evaporation rate calculation submodule calls the dynamic smoke output and uses the formula based on the ambient temperature and humidity factors:

[0106] ;

[0107] Calculating the evaporation rate of smoke particles ,in, represents the concentration of smoke particles, represents the ambient temperature, Represents the ambient humidity, represents the air flow velocity, and They are the temperature and humidity influence coefficient and the airflow influence coefficient respectively;

[0108] Get the temperature and humidity parameters of the current environment, and use the temperature sensor and humidity sensor to measure the ambient temperature respectively and ambient humidity , and use wind speed sensor to measure air flow speed , the data is used to calculate the evaporation rate of smoke particles, smoke particle concentration It is measured by the optical particle detection module, which uses the principle of light scattering to estimate the concentration of smoke particles per unit volume. In actual use, if the user is in a high humidity environment, such as indoor humidity If the evaporation rate of smoke particles is greater than a certain threshold, it will be inhibited, while in a dry environment, the evaporation rate will increase. Based on this, the following calculation formula is used: , in the calculation process, it is assumed , , , , and set , , substituting into the formula:

[0109] ;

[0110] The calculated smoke evaporation rate is .

[0111] The diffusion stability judgment submodule calls the evaporation rate of smoke particles, calculates the suspension time of smoke under different environmental conditions, judges the diffusion stability through the diameter change trend of smoke particles, and obtains the smoke diffusion result;

[0112] Call the smoke evaporation rate and calculate the suspension time of smoke under different environmental conditions. First, measure the initial diameter of the smoke particles and record the size change of the particles per unit time. If the particle diameter decrease rate is higher than the set threshold, it is judged that the smoke diffusion stability is poor. Assuming that the air flow rate is Under the environment, the particle diameter changes from the initial Down to The time is , then the diffusion stability index is calculated as: ,in, is the initial particle diameter, is the particle diameter, substitute into the calculation: The smoke diffusion results obtained reflect the stable diffusion ability of smoke in a specific environment.

[0113] The power compensation adjustment submodule calls the smoke diffusion result, adjusts the power compensation of the electronic atomizer, optimizes the smoke density, and obtains the smoke control index;

[0114] By adjusting the power compensation of the electronic atomizer to optimize the smoke density, first classify the current smoke diffusion situation. If the diffusion index If it is higher than the set standard, it means that the smoke dissipates quickly and the power compensation needs to be increased appropriately. To increase the smoke concentration, if Lower, reduce To avoid excessive accumulation of smoke, in order to ensure that the calculated power output is in line with the normal power range of the e-cigarette (usually between The adjustment formula is as follows: ,in, is the current set power, is the standard diffusion index, is the upper limit of the diffusion index, assuming , , , , substitute into the calculation: , the adjusted power output is , and obtain the smoke control index.

[0115] See also Figure 6 , the atomizer energy consumption management module includes:

[0116] The power fluctuation analysis submodule monitors the current power output data according to the smoke control index, calculates the power change at each sampling point, and identifies the power fluctuation range that meets the optimization conditions;

[0117] Monitor the current power output data, collect the original data points of power change, and perform time series processing to calculate the power change at each sampling point. The calculation of power change requires calling continuous time points and Power and Calculate the difference, that is , and combined with the time interval Calculate the instantaneous power rate of change For points with a large power change rate in a short period of time, it is necessary to further check whether they meet the optimization conditions. The judgment of the optimization conditions is based on statistical analysis and calculating the standard deviation of power fluctuations over a period of time. , and set the threshold As a basis for judgment, if at a certain time point , then the point is considered to be in the power fluctuation range. The identification of the power fluctuation range not only needs to consider the mutation value of a single point, but also needs to be screened in combination with the change trend of multiple points. For example, during the operation of the electronic atomizer, if the power fluctuation range exceeds 10% in a certain period of time, it needs to be included in the optimization range. For example, when operating at 100W, if the power at a certain point in time suddenly changes to 120W or decreases to 80W, it needs to be included in the fluctuation range. After calculating the power change trend in different power fluctuation ranges, the power fluctuation range that meets the optimization conditions is finally screened out to obtain the optimized power fluctuation range.

[0118] The efficiency benchmark comparison submodule evaluates the power regulation frequency within the power fluctuation range and compares it with the power regulation efficiency benchmark value to determine the optimal power regulation time range;

[0119] Get the power regulation frequency within the interval. The calculation of the power regulation frequency needs to be combined with time series data and set the time window. Calculate the number of power changes per unit time ,by Indicates the power regulation frequency. For the selected optimized power fluctuation range, its power regulation efficiency and power regulation efficiency benchmark value need to be calculated. The setting of needs to be combined with the energy consumption optimization target of the atomizer. For example, among the different power fluctuation ranges measured in the experiment, if the power regulation efficiency of a certain range is higher than 85%, then this range is considered to be better. The power regulation efficiency of the optimized range can be calculated using If a certain interval , it is considered to be the optimal time interval. In this way, comparison is made among multiple power fluctuation intervals, and the optimal power adjustment time interval is finally determined to obtain the optimal power adjustment time interval.

[0120] The power optimization regulation submodule is based on the optimal power regulation time interval and uses the formula:

[0121] ;

[0122] Update the power adjustment frequency of the electronic atomizer , and the optimization results of the atomizer are obtained, where represents the optimization rate obtained from the optimal power regulation time interval, Representing time point The power value, Represents the maximum power value in the time interval, Represents the total number of data points in the time interval;

[0123] Set the optimal adjustment optimization rate , the maximum power in the optimization interval , the number of data points in the optimization interval , the measured power value If they are 100W, 110W, 95W, 105W and 115W respectively, then calculate:

[0124] ;

[0125] ;

[0126] This result shows that the calculated It means that the power regulation frequency of the current electronic atomizer is adjusted to 0.21 times the optimization rate. Compared with the original power regulation frequency, the atomizer power regulation mode can be further optimized.

[0127] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An intelligent control system for electronic atomizer based on airflow sensing, characterized in that: The system comprises: The data acquisition and synchronization module is based on the airflow sensor to collect the inhalation speed and frequency data, monitor the stability of the electronic atomizer inhalation data in real time, and record the ambient temperature and humidity through the environmental sensor, and synchronize the data time to establish the airflow behavior data set; The inhalation behavior analysis module continuously monitors the change of gas flow rate in the airflow channel of the electronic atomizer based on the airflow behavior data set, calculates the dynamic trend of the current inhalation rate, evaluates the stability of the inhalation rhythm, and determines the user's inhalation intensity based on the evaluation results to obtain inhalation pattern prediction data; The power and smoke adjustment module calls the predicted inhalation mode data, analyzes the difference between the current inhalation speed and the predicted inhalation intensity, identifies the power amount to be adjusted, adjusts the power output of the electronic atomizer, analyzes the effect of the power adjustment on the smoke amount, and generates a dynamic smoke output amount; The atomizer adaptive control module calls the dynamic smoke output, analyzes the influence of environmental factors on the evaporation rate and suspension time of smoke particles, determines the diffusion stability of smoke under different environments, adjusts the power compensation amount of the electronic atomizer, and obtains the smoke control index.

2. The electronic atomizer intelligent control system based on airflow sensing according to claim 1 is characterized in that: The airflow behavior data set includes an inhalation speed index, an inhalation frequency index, and an ambient temperature and humidity index; the inhalation mode prediction data includes an inhalation rate trend, an inhalation rhythm stability, and an inhalation intensity index; the dynamic smoke output includes smoke volume change information and the degree of power adjustment impact; and the smoke control index includes an evaporation rate index and a suspension time index.

3. The intelligent control system for electronic atomizer based on airflow sensing according to claim 1, characterized in that: The data acquisition synchronization module comprises: The airflow data acquisition submodule is based on the airflow sensor, which monitors the airflow data during the inhalation process of the electronic atomizer, records the inhalation speed and frequency in real time, calculates the average value of the data in each time window, removes abnormal values, and obtains a valid airflow data set; The environmental data recording submodule records the temperature and humidity data through the environmental sensor based on the effective airflow data set, monitors the changes of the environmental data at different time points, calculates the average value and fluctuation range of the environmental temperature and humidity during the inhalation process, and obtains the environmental matching data set; The data screening synchronization submodule synchronizes the inhalation data and the environmental data based on the environmental matching data set, and calculates the time error between the data points using the formula: ； Get data synchronization accuracy , establish an airflow behavior data set, where, Represents the timestamp of the inhalation data, that is, the specific recording time corresponding to each data point, Represents the matching environmental data timestamp, that is, the environmental data recording time corresponding to the inhalation data timestamp, Represents the total number of data points.

4. The electronic atomizer intelligent control system based on airflow sensing according to claim 1, characterized in that: The inhalation behavior analysis module comprises: The airflow rate monitoring submodule monitors the gas flow rate in the airflow channel of the electronic atomizer in real time based on the airflow behavior data set, continuously records the inhalation speed data, compares it with the historical inhalation speed data, analyzes the dynamic changes of the current inhalation speed, identifies the abnormal interval of the inhalation speed, and generates an inhalation speed monitoring record; The inspiratory rhythm comparison submodule analyzes the dynamic trend of abnormal inspiratory rate based on the inspiratory speed monitoring record, calculates the rate deviation at each time point, compares and analyzes it with the user's historical breathing rhythm pattern, evaluates the consistency and variation of the inspiratory rhythm, and obtains the inspiratory rhythm stability analysis result; The inspiratory pattern prediction submodule calls the inspiratory rhythm stability analysis result, using the formula: ； Calculate the predicted inspiratory pattern , get the inhalation mode prediction data, where, Representative The average inspiratory speed in the time window, Representative The inspiratory duration of the time window, Representative The inspiratory rhythm stability parameter of the time window, Representative The deviation coefficient of the time window is Represents the number of time windows for analysis.

5. The electronic atomizer intelligent control system based on airflow sensing according to claim 1, characterized in that: The power and smoke adjustment module includes: The inhalation mode difference calculation submodule calls the inhalation mode prediction data, analyzes the current real-time inhalation speed and the predicted inhalation intensity data, calculates the difference between the two data, and obtains the inhalation intensity deviation value; The power adjustment amount identification submodule performs correlation analysis based on the inhalation intensity deviation value and the current power output value, using the formula: ； Calculate the required power adjustment , and then update the power output value according to the adjustment amount to obtain the adjusted power output value, where, represents the predicted inspiratory speed, Represents the real-time inhalation speed, Represents the current power output value, is the suction speed compensation coefficient, Adjust the base factor for power; The dynamic smoke output calculation submodule calls the adjusted power output value, combines the real-time inhalation data, analyzes the output change trend of the smoke volume, analyzes the influence of the power adjustment on the smoke volume, and obtains the dynamic smoke output.

6. The electronic atomizer intelligent control system based on airflow sensing according to claim 1, characterized in that: The atomizer adaptation control module comprises: The smoke evaporation rate calculation submodule calls the dynamic smoke output and uses the formula according to the ambient temperature and humidity factors: ； Calculating the evaporation rate of smoke particles ,in, represents the concentration of smoke particles, represents the ambient temperature, Represents the ambient humidity, represents the air flow velocity, and They are the temperature and humidity influence coefficient and the airflow influence coefficient respectively; The diffusion stability judgment submodule calls the evaporation rate of the smoke particles, calculates the suspension time of the smoke under different environmental conditions, judges the diffusion stability by the diameter change trend of the smoke particles, and obtains the smoke diffusion result; The power compensation amount adjustment submodule calls the smoke diffusion result, adjusts the power compensation amount of the electronic atomizer, optimizes the smoke density, and obtains the smoke control index.

7. The electronic atomizer intelligent control system based on airflow sensing according to claim 1, characterized in that: The system further comprises: The atomizer energy consumption management module analyzes the variation range of the current power output according to the smoke control index, identifies the power fluctuation range that meets the optimization conditions, determines the optimal time interval by comparing the power regulation efficiency benchmark value, and updates the power regulation frequency of the electronic atomizer to obtain the atomizer optimization result; The atomizer optimization result includes a power fluctuation range identification result, power regulation efficiency information, and regulation frequency update information.

8. The electronic atomizer intelligent control system based on airflow sensing according to claim 7, characterized in that: The atomizer energy consumption management module comprises: The power fluctuation analysis submodule monitors the current power output data according to the smoke control index, calculates the power change at each sampling point, and identifies the power fluctuation range that meets the optimization conditions; The efficiency benchmark comparison submodule evaluates the power regulation frequency within the power fluctuation interval and compares it with the power regulation efficiency benchmark value to determine the optimal power regulation time interval; The power optimization regulation submodule uses the formula based on the optimal power regulation time interval: ； Update the power adjustment frequency of the electronic atomizer , and get the optimization result of the atomizer, where represents the optimization rate obtained from the optimal power regulation time interval, Representing time point The power value, Represents the maximum power value in the time interval, Represents the total number of data points in the time interval.

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