Ventilator adaptive humidification control method, apparatus, and home ventilator

Abstract

The application discloses a ventilator adaptive humidification control method and device and a household ventilator. The method comprises the following steps: acquiring pipeline pressure data, respiratory flow data and temperature data; then calculating a mask target humidity; calculating a corresponding target dew point temperature according to the mask target humidity; inputting the temperature data into a pipeline thermodynamic model to calculate a mask end airflow temperature; generating an anti-condensation control instruction according to the mask end airflow temperature, the target dew point temperature, a preset anti-condensation hard constraint and an anti-condensation strategy; in the case of meeting the anti-condensation hard constraint, calculating an optimal solution of a target humidifier heating power and a target pipeline heating power; and generating a heating control instruction according to the optimal solution. The application can realize adaptive adjustment of the humidifier heating power and the pipeline heating power, solve the contradiction between ventilator humidification and condensation, and improve user experience.

Description

Technical Field

[0001] This application relates to the field of ventilator control, and in particular to a method, device and home ventilator for adaptive humidification control of a ventilator. Background Technology

[0002] The humidification system of existing home ventilators consists of two parts: a water tank heater and a heating tube. Users manually set the humidification level (e.g., 1-5 or 1-8) and the heating tube temperature, and the device maintains a constant heating duty cycle according to the set values. Some high-end models offer an "automatic" mode, which adjusts the humidification duty cycle based on the ambient temperature and humidity sensors at the air inlet, but the adjustment logic is a simple IF-ELSE rule (the drier the environment, the more humidified; the colder the environment, the higher the tube temperature).

[0003] However, open-loop control with fixed humidification levels and tubing temperature does not respond to dynamic changes in the nighttime environment: the environment is warm and dry in the first half of the night, and cold and with high relative humidity in the second half; under a constant duty cycle, humidification may be insufficient in the first half of the night, and excessive in the second half, leading to condensation in the tubing. Existing ventilators lack an automated solution to the contradiction between humidification and condensation. Users increase the humidification level to avoid airway dryness, but condensation occurs in the tubing after the temperature drops at night; users adjust the tubing temperature to avoid condensation, but this causes the mask airflow to become too hot and uncomfortable.

[0004] In summary, the ventilator technology suffers from a contradiction between humidification and condensation, resulting in a poor user experience. Summary of the Invention

[0005] This application aims to propose an adaptive humidification control method, device, and home ventilator for ventilators, which can resolve the contradiction between humidification and condensation in ventilators and improve user experience.

[0006] In a first aspect, embodiments of this application provide a method for adaptive humidification control of a ventilator, including: Acquire pipeline pressure data, breathing flow data, and temperature data, wherein the temperature data includes at least the ambient temperature and the humidifier base plate temperature; The target humidity of the mask is calculated based on the pipeline pressure data, the breathing flow data, and the temperature data. Calculate the target dew point temperature based on the target humidity of the face mask; Input the temperature data into the pipeline thermodynamic model to calculate the airflow temperature at the mask end; Based on the airflow temperature at the mask end, the target dew point temperature, the preset anti-condensation hard constraint, and the anti-condensation strategy, an anti-condensation control command is generated. The anti-condensation control command is used to ensure that the airflow temperature at the mask end and the target dew point temperature meet the anti-condensation hard constraint. Under the condition of satisfying the aforementioned anti-condensation hard constraint, calculate the optimal solution for the target humidifier heating power and the target pipeline heating power; Heating control commands are generated based on the optimal solutions of the target humidifier heating power and the target pipeline heating power.

[0007] According to some embodiments of this application, the step of calculating the target humidity of the mask in the pipeline based on the pipeline pressure data, the breathing flow data, and the temperature data includes: The corresponding seasonal baseline humidity value is obtained based on the ambient temperature. Obtain an individual bias value, which is used to indicate the cumulative correction amount for the difference in humidification comfort for each user; Calculate minute ventilation based on the respiratory flow data; Calculate the leakage based on the respiratory flow data and the pipeline pressure data; Calculate the half-cycle imbalance index based on the leakage amount; The mouth breathing state is determined based on the half-cycle imbalance index, and the corresponding mouth breathing compensation value is obtained. The leakage compensation value is calculated based on the minute ventilation rate, the leakage rate, and the seasonal baseline humidity value. The target humidity of the mask in the pipeline is calculated based on the seasonal baseline humidity value, the personal bias value, the leakage compensation value, and the mouth breathing compensation value.

[0008] According to some embodiments of this application, after generating the heating control command based on the optimal solution of the target humidifier heating power and the target pipeline heating power, the method further includes: Re-acquire respiratory flow data at a preset cycle and calculate the change in minute ventilation. The power adjustment command is generated based on the change in minute ventilation rate. The power adjustment command is used to synchronously adjust the heating power of the humidifier and the heating power of the pipeline according to the change in minute ventilation rate.

[0009] According to some embodiments of this application, the step of inputting temperature data into the pipeline thermodynamic model and calculating the airflow temperature at the mask end includes: The actual value of the humidifier outlet temperature is calculated based on the humidifier base plate temperature and the factory calibration curve. The actual value of the humidifier outlet temperature and the ambient temperature are input into the pipeline thermodynamic model to calculate the airflow temperature at the mask end. The expression for the pipeline thermodynamic model is as follows: T_mask=T_amb+(T_hum_out1 T_amb)×exp( η); T_mask is the airflow temperature at the mask end; T_amb is the ambient temperature; T_hum_out1 is the actual value of the humidifier outlet temperature; η is the pipeline attenuation coefficient, η=(4·U·L) / (ρ·c·v·D), U is the pipeline heat transfer coefficient, L is the pipeline length, ρ is the air density, c is the specific heat of air, v is the airflow velocity in the pipeline, and D is the pipeline inner diameter.

[0010] According to some embodiments of this application, the temperature data further includes the pipe outlet temperature. After inputting the temperature data into the pipe thermodynamic model and calculating the airflow temperature at the mask end, the process further includes: The airflow temperature at the mask end is obtained based on the outlet temperature of the pipeline. The temperature deviation result is obtained by comparing the measured temperature of the airflow at the mask end with the airflow temperature at the mask end. If the temperature deviation exceeds a preset temperature deviation threshold, the heat transfer coefficient of the pipeline in the pipeline thermodynamic model is corrected to obtain a corrected pipeline thermodynamic model. The corrected pipeline thermodynamic model is used to determine the anti-condensation hard constraint and to calculate the heating power of the target pipeline.

[0011] According to some embodiments of this application, the step of calculating the target humidifier heating power and the target pipeline heating power based on the target humidity of the face mask includes: The target value of the humidifier outlet temperature is calculated based on the target humidity of the mask. The target heating power of the humidifier is calculated based on the target value of the humidifier outlet temperature, the ambient temperature, the target humidity of the mask, and the current humidity of the mask. The equivalent heat transfer coefficient of the pipeline after heating is turned on is calculated based on the anti-condensation hard constraint and the pipeline thermodynamic model. The target heating power of the pipeline is calculated based on the equivalent heat transfer coefficient. Under the hard constraint of anti-condensation, minimize the target humidifier heating power and the target pipeline heating power, and find the optimal solution for the target humidifier heating power and the target pipeline heating power.

[0012] According to some embodiments of this application, the heating control command includes a first heating command and a second heating command, and the step of generating the heating control command based on the optimal solution of the target humidifier heating power and the target pipeline heating power includes: Obtain the inspiratory phase correction factor and the expiratory phase correction factor; A first heating command is generated based on the optimal solution of the inhalation phase correction coefficient, the exhalation phase correction coefficient, and the target humidifier heating power; A second heating command is generated based on the optimal solution of the target pipeline heating power.

[0013] According to some embodiments of this application, the step of generating heating control commands based on the optimal solution of the target humidifier heating power and the target pipeline heating power further includes: The effective target humidity is obtained during each sleep process, and the effective target humidity is used as the mask target humidity during the steady state phase of each sleep process; The seasonal baseline humidity value at the current ambient temperature is updated based on the effective target humidity.

[0014] Secondly, embodiments of this application provide an electronic device, the device comprising: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the adaptive humidification control method for ventilators as described in the first aspect.

[0015] Thirdly, embodiments of this application provide a home ventilator, including a control module, which is used to run the ventilator adaptive humidification control method as described in the first aspect.

[0016] The adaptive humidification control method, device, and home ventilator of this application have at least the following beneficial effects: In this embodiment, firstly, pipeline pressure data, breathing flow data, and temperature data are acquired; then, the target humidity of the mask is calculated based on the pipeline pressure data, breathing flow data, and temperature data; the corresponding target dew point temperature is calculated based on the target humidity of the mask; the temperature data is input into the pipeline thermodynamic model to calculate the airflow temperature at the mask end; based on the airflow temperature at the mask end, the target dew point temperature, the preset anti-condensation hard constraints, and the anti-condensation strategy, an anti-condensation control command is generated; under the condition of satisfying the anti-condensation hard constraints, the optimal solution for the target humidifier heating power and the target pipeline heating power is calculated; and a heating control command is generated based on the optimal solution for the target humidifier heating power and the target pipeline heating power. This application can achieve adaptive adjustment of the humidifier heating power and the pipeline heating power, resolving the contradiction between humidification and condensation in the ventilator and improving the user experience.

[0017] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0018] The present application will be further described below with reference to the accompanying drawings and embodiments, wherein: Figure 1 A schematic flowchart illustrating an embodiment of the adaptive humidification control method for ventilators provided in this application; Figure 2 A schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0019] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0020] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0021] To address the problems of the prior art, this application provides an adaptive humidification control method, device, and home ventilator for a ventilator. The adaptive humidification control for a ventilator provided in this application will be described below.

[0022] First, it should be noted that this application is applied to the nighttime humidification therapy scenario of a ventilator: the patient wears a nasal mask or a naso-oral mask to sleep in the bedroom, and the ventilator provides humidified therapeutic airflow through the airflow channel of water tank - humidifier heating plate - heating tubing - mask. Figure 1 A flowchart illustrating the adaptive humidification control method for a ventilator provided in an embodiment of this application is shown. This method is applied to electronic devices, and includes the following steps: S101. Acquire pipeline pressure data, breathing flow data, and temperature data. The temperature data shall include at least the ambient temperature and the temperature of the humidifier base plate. S102. Calculate the target humidity of the mask based on pipeline pressure data, breathing flow data, and temperature data; S103. Calculate the corresponding target dew point temperature based on the target humidity of the face mask; S104. Input the temperature data into the pipeline thermodynamic model and calculate the airflow temperature at the mask end; S105. Based on the airflow temperature at the mask end, the target dew point temperature, the preset anti-condensation hard constraints and anti-condensation strategies, generate an anti-condensation control command. The anti-condensation control command is used to ensure that the airflow temperature at the mask end and the target dew point temperature meet the anti-condensation hard constraints. S106. Under the condition of satisfying the anti-condensation hard constraint, calculate the optimal solution of the target humidifier heating power and the target pipeline heating power; S107. Generate heating control commands based on the optimal solutions of the target humidifier heating power and the target pipeline heating power.

[0023] In this embodiment, firstly, pipeline pressure data, breathing flow data, and temperature data are acquired; then, the target humidity of the mask is calculated based on the pipeline pressure data, breathing flow data, and temperature data; the corresponding target dew point temperature is calculated based on the target humidity of the mask; the temperature data is input into the pipeline thermodynamic model to calculate the airflow temperature at the mask end; based on the airflow temperature at the mask end, the target dew point temperature, the preset anti-condensation hard constraints, and the anti-condensation strategy, an anti-condensation control command is generated; under the condition of satisfying the anti-condensation hard constraints, the optimal solution for the target humidifier heating power and the target pipeline heating power is calculated; and a heating control command is generated based on the optimal solution for the target humidifier heating power and the target pipeline heating power. This application can achieve adaptive adjustment of the humidifier heating power and the pipeline heating power, resolving the contradiction between humidification and condensation in the ventilator and improving the user experience.

[0024] In step S101 above, the pipeline pressure data, breathing flow data, and temperature data are collected through the pressure sensor, flow sensor, and temperature sensor configured on the ventilator, respectively. The temperature data includes at least the ambient temperature and the humidifier base plate temperature, meaning that at least two temperature sensors are used to collect the ambient temperature and the humidifier base plate temperature, respectively. The ambient temperature can be obtained by collecting the temperature at the humidifier air inlet.

[0025] In step S102 above, the target humidity of the mask refers to the target humidity at the mask end. Therefore, calculating the target humidity of the mask based on pipeline pressure data, breathing flow data, and temperature data means first calculating the target humidity at the mask end based on pipeline pressure data, breathing flow data, and temperature data. For example, a humidity reference table can be pre-built, a target humidity reference value can be obtained based on the ambient temperature, and then the corresponding compensation amount can be calculated based on pipeline pressure and breathing flow, such as mouth breathing compensation and leakage compensation. Then, the target humidity of the mask can be calculated by superimposing one or more compensation amounts on the target humidity reference value.

[0026] In step S103 above, the target dew point temperature corresponding to the target humidity of the mask refers to the dew point temperature T_dew of the airflow at the mask end. The target dew point temperature T_dew can be obtained by reverse calculation of the target humidity of the mask H_target using the Magnus formula.

[0027] Specifically, if the calculated H_target is in the range of 15~25 mgH2O / L, T_dew can be obtained using the following hardware-friendly approximation: T_dew ≈ 12.6 + 0.93 · (H_target 17); It should be noted that within a certain range, T_dew can be obtained quickly and accurately using a hardware-friendly approximation, with a single calculation taking approximately 5 µs, far less than the time required for the main term of the thermodynamic model. If H_target exceeds 15~25 mgH2O / L, the complete Magnus formula should be used to solve for T_dew.

[0028] In step S104 above, inputting temperature data into the pipeline thermodynamic model and calculating the airflow temperature at the mask end refers to calculating the airflow temperature T_mask at the mask end based on the ambient temperature and the humidifier base plate temperature, combined with the pre-built pipeline thermodynamic model.

[0029] It should be noted that the thermodynamic model of the pipeline can use analytical formulas or the finite difference method to calculate the airflow temperature at the mask end.

[0030] In step S105 above, the anti-condensation hard constraint means that the temperature at any point in the pipeline must be higher than the target dew point temperature T_dew + safety margin ΔT_safe (default 2°C). Since the lowest point of pipeline temperature is located at the pipeline outlet at the mask end, the constraint simplifies to: T_mask≥T_dew+ΔT_safe; In other words, the anti-condensation hard constraint in this application is that the airflow temperature at the mask end is not lower than the sum of the target dew point temperature and the safety margin.

[0031] The anti-condensation strategy mentioned above refers to the response strategy to be taken when the airflow temperature at the mask end is lower than the sum of the target dew point temperature and the safety margin. Therefore, generating an anti-condensation control command based on the mask end airflow temperature, the target dew point temperature, the preset anti-condensation hard constraint, and the anti-condensation strategy involves first determining whether the mask end airflow temperature and the target dew point temperature meet the anti-condensation hard constraint. If they do, proceed to the next step; otherwise, adjust according to the anti-condensation strategy to ensure that the mask end airflow temperature and the target dew point temperature meet the anti-condensation hard constraint, as detailed below: If the anti-condensation hard constraint is not met, first gradually increase the pipe heating power P_heat_pipe (e.g., +1W each time) to raise T_mask; if P_heat_pipe has reached the hardware limit of 25W and the constraint is still not met, then gradually decrease H_target (e.g., +1W each time). (1 mg H2O / L) until the constraint is satisfied.

[0032] In step S106 above, calculating the optimal solution for the target humidifier heating power and the target pipeline heating power under the condition of satisfying the anti-condensation hard constraint refers to calculating the target humidifier heating power P_hum and the target pipeline heating power P_heat_pipe under the anti-condensation hard constraint. Since the anti-condensation hard constraint is an inequality, there are multiple solutions. It is necessary to minimize P_hum + P_heat_pipe under the anti-condensation hard constraint, which corresponds to the lowest power consumption operating point at the hardware level. Since the thermodynamic model is analytically expressed, there is no need for iterative search, and a unique solution is determined in a single calculation.

[0033] In step S107 above, generating heating control commands based on the optimal solutions of the target humidifier heating power and the target pipeline heating power refers to controlling the humidifier heating plate and pipeline heating wires based on the target humidifier heating power and the target pipeline heating power corresponding to the lowest power consumption under the anti-condensation hard constraint.

[0034] Specifically, the humidifier heating plate and the heating wire in the tubing of the ventilator are driven by soft PWM. Therefore, the heating control command uses the target humidifier heating power and the target tubing heating power as set values ​​to adjust the heating duty cycle.

[0035] Therefore, based on the existing hardware platform of a humidifier heating plate and pipeline heating wire, this application achieves absolute humidity tracking of the target value at the mask end and prevents condensation at any point in the pipeline through a hardware-level joint control design of two soft PWM heating drive laws. This application employs a joint control law combining a pipeline thermodynamic model and anti-condensation hard constraints to couple and drive the duty cycles of the two heating circuits at the hardware level, fundamentally eliminating the contradiction between humidification and condensation.

[0036] In some implementations, calculating the target humidity of the mask in the pipeline based on pipeline pressure data, breathing flow data, and temperature data may include: The corresponding seasonal baseline humidity value is obtained based on the ambient temperature; Obtain individual bias values, which are used to indicate the cumulative correction amount for differences in humidification comfort for each user; Calculate minute ventilation based on respiratory flow data; Calculate the leakage based on respiratory flow data and pipeline pressure data; Calculate the half-cycle imbalance index based on the amount of air leakage; The mouth breathing state is determined based on the half-cycle imbalance index, and the corresponding mouth breathing compensation value is obtained. The leakage compensation value is calculated based on the minute ventilation rate, leakage rate, and seasonal baseline humidity value; The target humidity for the face mask in the pipeline is calculated based on the seasonal baseline humidity value, personal bias value, leakage compensation value, and mouth breathing compensation value.

[0037] The above-mentioned method of obtaining the corresponding seasonal baseline humidity value based on ambient temperature refers to looking up the seasonal baseline table at the current ambient temperature to obtain the seasonal baseline humidity value H_target_base corresponding to the ambient temperature in the current season. The seasonal baseline table is a pre-constructed target humidity benchmark value segmented by ambient temperature, reflecting the typical humidification demand baseline under different seasonal climatic conditions.

[0038] For example, a seasonal baseline table is shown in Table 1: Table 1. Examples of Seasonal Baselines

[0039] The aforementioned personal bias value ΔH_user refers to the accumulated personal humidity preference deviation value of the user, initially set to 0. It is gradually updated as the user manually adjusts the humidification level to compensate for differences in airway humidification comfort between individuals. Obtaining the personal bias value refers to reading it from a preset program.

[0040] Specifically, the individual bias value ΔH_user can be adaptively updated using an online individual bias identification algorithm. The update process is as follows: If the user manually fine-tunes the humidification level in automatic mode (+1 / (Level 1), the system records the current H_target and updates the personal bias ΔH_user using the following formula: ΔH_user_new=ΔH_user_old+η_learn·sign·3mgH2O / L; Where ΔH_user_new is the updated individual bias value, ΔH_user_old is the original individual bias value, η_learn is the bias update step size (default 0.3), and sign is the user adjustment flag (+1 indicates an increase). 1 indicates the user has lowered the setting, and 0 indicates no action has been taken.

[0041] The minute ventilation (MV) is calculated based on respiratory flow data. MV directly drives the convective heat dissipation term in the pipeline thermodynamic model and serves as the hardware control variable for the humidifier's heating power. Specifically, the expression for MV is: MV = RR · V_T; Where RR is the respiratory rate, obtained by counting the zero-crossing point of the respiratory flow; V_T is the tidal volume, obtained by integrating the respiratory flow during the inspiratory phase.

[0042] In this embodiment, the leakage refers to unintentional leakage. The expression for the leakage q_leak in the above calculation based on breathing flow data and pipeline pressure data is: q_leak = q_total q_patient q_vent; Where q_total is the total respiratory flow; q_patient is the patient's actual respiratory flow, which can be calculated from the minute ventilation (MV); and q_vent is the design flow rate of the mask exhaust valve under the current pressure, which corresponds to the current pressure and is obtained by looking up the table at the factory.

[0043] The above calculation of the half-cycle imbalance index (LSI) based on air leakage is used to determine mouth breathing status. The LSI is used to determine mouth breathing, and its expression is as follows: LSI = (q_in q_out) / (q_in + q_out); Where q_in is the average leakage during the inhalation phase and q_out is the average leakage during the exhalation phase.

[0044] The above method determines mouth breathing status based on the half-cycle imbalance index and obtains the corresponding mouth breathing compensation value. Specifically, when |LSI|>0.2, mouth breathing status is determined, triggering mouth breathing compensation. The mouth breathing compensation value ΔH_mouth is set as follows: +3 mgH2O / L when |LSI|>0.2, +5 mgH2O / L when |LSI|>0.4, and 0 otherwise.

[0045] The leakage compensation value is calculated based on the minute ventilation rate, leakage rate, and seasonal baseline humidity value. Specifically, the expression for the leakage compensation value ΔH_leak is as follows: ΔH_leak = α · q_leak / MV · H_target_base; Where α is the factory calibration constant, which is 0.5 by default.

[0046] The target humidity of the face mask for the pipeline is calculated based on the seasonal baseline humidity value, personal bias value, leakage compensation value, and mouth breathing compensation value. The expression for the target humidity of the face mask, H_target, is as follows: H_target = H_target_base + ΔH_user + ΔH_leak + ΔH_mouth; Where H_target_base is the seasonal baseline humidity value, ΔH_user is the personal bias value, ΔH_leak is the leakage compensation value, and ΔH_mouth is the mouth breathing compensation value.

[0047] This implementation replaces the open-loop drive with a fixed humidification level with a reverse-propagation duty cycle law based on the target humidity of the mask. Under conditions where ambient temperature and humidity, breathing parameters, and leakage all change dynamically, the actual humidity at the mask end tracks the target value. The hardware control terms are modified according to leakage compensation and mouth breathing compensation, and the humidification duty cycle is coupled with the dynamic parameters on the patient side. This avoids insufficient humidification when there is leakage in the existing scheme, and further improves the user's comfort and treatment effect.

[0048] In some implementations, after generating the heating control command based on the optimal solution of the target humidifier heating power and the target pipeline heating power, the following may also be included: Re-acquire respiratory flow data at a preset cycle and calculate the change in minute ventilation. The power adjustment command is generated based on the change in minute ventilation rate. The power adjustment command is used to synchronously adjust the heating power of the humidifier and the heating power of the pipeline according to the change in minute ventilation rate.

[0049] Specifically, after optimizing the heating power of the target humidifier and the target pipeline heating power, the minute ventilation rate (MV) is recalculated at a preset cycle, for example, every 30 seconds. The humidifier and pipeline heating power are then adjusted synchronously with the changes in MV. Typical changes in MV during different sleep states are: decreasing from 8-9 L / min to 5-7 L / min after falling asleep; and rising back to 7-9 L / min during REM sleep. This implementation directly controls the MV via power adjustment commands, increasing the humidifier and pipeline heating power synchronously when MV increases, avoiding insufficient humidification at high MV levels, and further improving user comfort and therapeutic effect.

[0050] In some implementations, inputting temperature data into a pipeline thermodynamic model to calculate the airflow temperature at the mask end may include: The actual value of the humidifier outlet temperature is calculated based on the humidifier base plate temperature and the factory calibration curve. Input the actual humidifier outlet temperature and ambient temperature into the pipeline thermodynamic model to calculate the airflow temperature at the mask end; The expression for the pipeline thermodynamic model is as follows: T_mask=T_amb+(T_hum_out1 T_amb)×exp( η); T_mask is the airflow temperature at the mask end; T_amb is the ambient temperature; T_hum_out1 is the actual value of the humidifier outlet temperature; η is the pipe attenuation coefficient, η=(4·U·L) / (ρ·c·v·D), U is the pipe heat transfer coefficient, L is the pipe length, ρ is the air density, c is the specific heat of air, v is the airflow velocity in the pipe, and D is the pipe inner diameter.

[0051] In this embodiment, the actual value of the humidifier outlet temperature is first calculated based on the humidifier base plate temperature and the factory calibration curve. Then, the actual value of the humidifier outlet temperature and the ambient temperature are input into the pipeline thermodynamic model to calculate the airflow temperature at the mask end. The airflow temperature at the mask end can be predicted quickly and accurately through the pipeline thermodynamic model.

[0052] Specifically, firstly, the actual value of the humidifier outlet temperature T_hum_out1 is calculated based on the temperature of the humidifier base plate according to the factory calibration curve; then, the actual value of the humidifier outlet temperature T_hum_out1 and the ambient temperature T_amb are substituted into the expression of the pipeline thermodynamic model to calculate the airflow temperature at the mask end.

[0053] It should be noted that the heat transfer coefficient U of the pipeline is approximately 5~10 W / (m²·K) when there is no heating pipeline. When there is a heating pipeline, it is adjusted to an equivalent negative value according to the pipeline heating power P_heat_pipe, that is, net heat compensation.

[0054] In some implementations, the temperature data also includes the pipe outlet temperature. After inputting the temperature data into the pipe thermodynamic model and calculating the airflow temperature at the mask end, it may further include: The airflow temperature at the mask end is obtained based on the outlet temperature of the pipeline. The temperature deviation result is obtained by comparing the airflow temperature measured at the mask end with the airflow temperature at the mask end. If the temperature deviation exceeds the preset temperature deviation threshold, the heat transfer coefficient of the pipeline in the pipeline thermodynamic model is corrected to obtain the corrected pipeline thermodynamic model. The corrected pipeline thermodynamic model is used to determine the anti-condensation hard constraint and to calculate the heating power of the target pipeline.

[0055] It should be noted that the heat transfer coefficient U of the pipeline, in addition to varying with the heating power of the pipeline, is also affected by factors such as ambient wind speed, the degree of aging of the pipeline, and the condition of the bedding covering it, resulting in uncertainty in actual use. Therefore, the U value in the model can be corrected to improve the accuracy of subsequent calculations.

[0056] In this embodiment, the temperature data also includes the tubing outlet temperature, which refers to adding a temperature sensor at the tubing outlet of the ventilator to sample the tubing outlet temperature.

[0057] The above comparison between the airflow measurement temperature at the mask end and the airflow temperature at the mask end refers to comparing the pipe outlet temperature as the airflow measurement temperature at the mask end T_mask1 with the airflow temperature at the mask end T_mask calculated by the pipe thermodynamic model to obtain the temperature deviation result.

[0058] If the temperature deviation exceeds the preset temperature deviation threshold, the heat transfer coefficient U in the pipeline thermodynamic model is corrected to obtain the corrected pipeline thermodynamic model. The corrected model is used for subsequent anti-condensation constraint determination and pipeline heating power back calculation.

[0059] In some implementations, calculating the target humidifier heating power and the target pipeline heating power based on the target humidity of the face mask may include: Calculate the target value of the humidifier outlet temperature based on the target humidity of the face mask; Calculate the target heating power of the humidifier based on the target outlet temperature of the humidifier, the ambient temperature, the target humidity of the mask, and the current humidity of the mask. The equivalent heat transfer coefficient of the pipeline after heating is turned on is calculated based on the anti-condensation hard constraint and the pipeline thermodynamic model. The target heating power of the pipeline is calculated based on the equivalent heat transfer coefficient. Under the hard constraint of anti-condensation, minimize the target humidifier heating power and the target pipeline heating power, and find the optimal solution for the target humidifier heating power and the target pipeline heating power.

[0060] It should be noted that the actual humidifier outlet temperature value T_hum_out1 is the current outlet temperature value of the humidifier, reflecting the current actual operating status of the humidifier, while the target humidifier outlet temperature value T_hum_out2 is the control target value.

[0061] Specifically, the calculation process for the target heating power P_hum of the humidifier is as follows: The above calculation of the humidifier outlet temperature target value based on the mask's target humidity is as follows: Assuming the air at the humidifier outlet is nearly saturated (RH ≈ 95%~100%), its absolute humidity is uniquely determined by the outlet temperature. The humidifier outlet temperature target value T_hum_out2 is then calculated from the mask's target humidity H_target using a lookup table and Newton's iteration method, as follows: Exemplarily, assume H_target = 22 mg H2O / L, and it is necessary to reverse-derive the corresponding T_hum_out2. First, look up the table: A pre-stored saturation humidity table of 256 points is used to find two adjacent items such that sat_H(T_i) ≤ 22 < sat_H(T_{i+1}). For example, sat_H(24.0 °C) = 21.8 mg / L, sat_H(24.2 °C) = 22.2 mg / L, and by linear interpolation, the initial estimate T0 ≈ 24.1 °C is obtained. Then, perform Newton iteration: Define f(T) = sat_H(T) - 22, f’(T) = d(sat_H) / dT ≈ (sat_H(T + 0.1) - sat_H(T - 0.1)) / 0.2, and calculate T1 = T0 - f(T0) / f’(T0).

[0062] The calculation of the target heating power of the humidifier according to the target value of the humidifier outlet temperature, the ambient temperature, the target humidity of the mask, and the current humidity of the mask is as follows: The specific expression is as follows: P_hum = ρ · c · MV · (T_hum_out2 - T_amb) + ΔH · MV · L_v; Where, P_hum is the target heating power of the humidifier, and ρ · c · MV · (T_hum_out2 - T_amb) represents the power required to heat the incoming air from the ambient temperature to T_hum_out2; ΔH is the humidification increment, ΔH = H_target - H_amb, H_amb is the current humidity of the mask; L_v is the latent heat of vaporization of water, and ΔH · MV · L_v represents the latent heat power required to evaporate water.

[0063] It should be noted that in addition to calculating P_hum through the target value of the humidifier outlet temperature T_hum_out2 and the ambient temperature T_amb, P_hum can also be calculated through T_hum_out2 - T_hum_out1.

[0064] Specifically, the calculation process of the target heating power P_heat_pipe of the pipeline is as follows: Substitute the anti-condensation hard constraint T_mask ≥ T_dew + ΔT_safe into the pipeline thermodynamic model to reverse-derive the required equivalent heat transfer coefficient U_eq, and then obtain P_heat_pipe from U_eq and the hardware calibration curve. Here, U_eq is the equivalent heat transfer coefficient after the pipeline heating is turned on, and its relationship with the aforementioned pipeline heat transfer coefficient U is: U_eq = U - P_heat_pipe / (π·D·L·ΔT_avg), where ΔT_avg is the average temperature difference inside and outside the pipeline.

[0065] Among them, the hardware calibration curve is the calibration data of the pipeline heating wire during mass production in the factory. Under standard environmental conditions, different powers P_heat_pipe are applied, the temperature difference between the pipeline inlet and outlet is measured, and the corresponding U_eq value is calculated to form a mapping table between P_heat_pipe and U_eq.

[0066] The above-mentioned solution for minimizing the target humidifier heating power and target pipeline heating power under the hard constraint of anti-condensation refers to minimizing P_hum + P_heat_pipe under the hard constraint of anti-condensation, which corresponds to the lowest power consumption operating point at the hardware level. Since the thermodynamic model is analytically expressed, there is no need for iterative search, and a unique solution is determined in a single calculation.

[0067] This implementation uses a humidification duty cycle law that reverses the target humidity of the face mask: by combining parameters such as H_target, MV, and T_amb to reverse the target humidifier heating power and target pipeline heating power, it achieves humidification-pipeline heating joint optimization under the hard constraint of anti-condensation, so that the absolute humidity at the face mask end tracks the target value and no condensation occurs at any point in the pipeline, further improving the user experience.

[0068] In some implementations, the heating control command includes a first heating command and a second heating command. The heating control command is generated based on the optimal solution of the target humidifier heating power and the target pipeline heating power, and may include: Obtain the inspiratory phase correction factor and the expiratory phase correction factor; The first heating command is generated based on the optimal solution of the inhalation phase correction coefficient, the exhalation phase correction coefficient, and the target humidifier heating power; The second heating command is generated based on the optimal solution of the target pipeline heating power.

[0069] In this embodiment, the inhalation phase correction coefficient and the exhalation phase correction coefficient are first obtained. Then, a first heating command is generated based on the optimal solution of the inhalation phase correction coefficient, the exhalation phase correction coefficient, and the target humidifier heating power. A second heating command is generated based on the optimal solution of the target pipeline heating power. This allows the time allocation of heating energy to match the actual airflow demand, achieving more precise humidity control and higher energy efficiency.

[0070] It should be noted that since the inhalation phase airflow carries away heat and moisture as it passes through the humidifier, if the heating power is not increased at this time, the evaporation will be insufficient, resulting in the humidity of the inhaled gas being lower than the target value. Furthermore, the exhalation phase airflow basically does not pass through the humidifier, and continuous high-power heating will cause the water temperature in the tank to be too high, generating excessive steam at the moment the next inhalation begins, causing instantaneous over-humidification and fogging of the mask. In addition, ineffective heating during the exhalation phase will also waste electrical energy.

[0071] Therefore, this application can achieve duty cycle correction of heating control during the respiratory cycle by superimposing inspiratory / exhalation phase correction coefficients c_phase1 and c_phase2 at the output of the duty cycle of heating control. For example, c_phase1=1.3 and c_phase2=0.7. That is, the duty cycle during inhalation = min(P_hum / 40,1)×1.3, and the duty cycle during exhalation = min(P_hum / 40,1)×0.7.

[0072] In some implementations, generating heating control commands based on the optimal solutions of the target humidifier heating power and the target pipeline heating power may further include: The effective target humidity is obtained during each sleep process, and the effective target humidity is used as the mask target humidity during the steady state phase of each sleep process; The seasonal baseline humidity value at the current ambient temperature is updated based on the effective target humidity. Based on the adaptive humidification control method for ventilators provided in the above embodiments, this application also provides a specific implementation of the adaptive humidification control device for ventilators.

[0073] Taking each night as an example, the effective target humidity H_target_obs during the steady-state phase of that night is assigned to the corresponding segment of the seasonal table according to the average ambient temperature of that night, and the H_target_base of that segment is updated according to the following formula: H_target_base_new=(1 β)·H_target_base_old+β·H_target_obs; Where β=0.05 (weight updated every night) is used to ensure that the seasonal table tends to converge after 20 valid nights without being disturbed by abnormalities in a single night. The effective target humidity H_target_obs refers to the H_target value that the user has not manually adjusted or that was last adjusted, which the system determines to be consistent with the user's perception.

[0074] In summary, this application achieves hardware-level coupling and driving of the duty cycles of the two heating circuits through a combined control law of pipeline thermodynamics model and anti-condensation hard constraints, fundamentally eliminating the contradiction between humidification and condensation in existing solutions. Furthermore, a reverse-engineering duty cycle law based on the target humidity of the mask replaces the open-loop drive with a fixed humidification level, ensuring that the actual humidity at the mask end tracks the target value even under dynamically changing environmental temperature, humidity, respiratory parameters, and leakage conditions. This application couples the humidification duty cycle with dynamic parameters on the patient side through three hardware control items: leakage compensation, mouth breathing compensation, and phase correction within the respiratory cycle, avoiding insufficient humidification during leakage as in existing solutions. This application also enables the hardware control parameters to converge with long-term user habits through online identification of seasonal baselines and personal biases, eliminating the need for frequent manual adjustments; this identification is a sliding window update of lookup table entries, independent of any online training.

[0075] Figure 2 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0076] The electronic device may include a processor 201 and a memory 202 storing computer program instructions.

[0077] Specifically, the processor 201 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0078] Memory 202 may include mass storage for data or instructions. For example, and not limitingly, memory 202 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 202 may include removable or non-removable (or fixed) media. Where appropriate, memory 202 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 202 is non-volatile solid-state memory.

[0079] In some embodiments, memory 202 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0080] The processor 201 reads and executes computer program instructions stored in the memory 202 to implement any of the adaptive humidification control methods for ventilators in the above embodiments.

[0081] In one example, the electronic device may also include a communication interface 203 and a bus 210. For example, Figure 2 As shown, the processor 201, memory 202, and communication interface 203 are connected through bus 210 and complete communication with each other.

[0082] The communication interface 203 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0083] Bus 210 may include hardware, software, or both. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 210 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0084] Furthermore, in conjunction with the adaptive humidification control method for ventilators in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the adaptive humidification control methods for ventilators in the above embodiments.

[0085] This application also relates to a home ventilator, including a control module for running the adaptive humidification control method for ventilators described in the above embodiments.

[0086] Specifically, the control module uses an MCU to run the ventilator's adaptive humidification control method. The core hardware of a home ventilator also includes a flow sensor, pressure sensor, temperature sensor, fan, and Flash memory.

[0087] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0088] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0089] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0090] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0091] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for adaptive humidification control of a ventilator, characterized in that, Includes the following steps: Acquire pipeline pressure data, breathing flow data, and temperature data, wherein the temperature data includes at least the ambient temperature and the humidifier base plate temperature; The target humidity of the mask is calculated based on the pipeline pressure data, the breathing flow data, and the temperature data. Calculate the target dew point temperature based on the target humidity of the face mask; Input the temperature data into the pipeline thermodynamic model to calculate the airflow temperature at the mask end; Based on the airflow temperature at the mask end, the target dew point temperature, the preset anti-condensation hard constraint, and the anti-condensation strategy, an anti-condensation control command is generated. The anti-condensation control command is used to ensure that the airflow temperature at the mask end and the target dew point temperature meet the anti-condensation hard constraint. Under the condition of satisfying the aforementioned anti-condensation hard constraint, calculate the optimal solution for the target humidifier heating power and the target pipeline heating power; Heating control commands are generated based on the optimal solutions of the target humidifier heating power and the target pipeline heating power.

2. The adaptive humidification control method for a ventilator according to claim 1, characterized in that, The step of calculating the target humidity of the mask based on the pipeline pressure data, the breathing flow data, and the temperature data includes: The corresponding seasonal baseline humidity value is obtained based on the ambient temperature. Obtain an individual bias value, which is used to indicate the cumulative correction amount for the difference in humidification comfort for each user; Calculate minute ventilation based on the respiratory flow data; Calculate the leakage based on the respiratory flow data and the pipeline pressure data; Calculate the half-cycle imbalance index based on the leakage amount; The mouth breathing state is determined based on the half-cycle imbalance index, and the corresponding mouth breathing compensation value is obtained. The leakage compensation value is calculated based on the minute ventilation rate, the leakage rate, and the seasonal baseline humidity value. The target humidity of the mask in the pipeline is calculated based on the seasonal baseline humidity value, the personal bias value, the leakage compensation value, and the mouth breathing compensation value.

3. The adaptive humidification control method for a ventilator according to claim 2, characterized in that, After generating the heating control command based on the optimal solution of the target humidifier heating power and the target pipeline heating power, the method further includes: Re-acquire respiratory flow data at a preset cycle and calculate the change in minute ventilation. The power adjustment command is generated based on the change in minute ventilation rate. The power adjustment command is used to synchronously adjust the heating power of the humidifier and the heating power of the pipeline according to the change in minute ventilation rate.

4. The adaptive humidification control method for a ventilator according to claim 1, characterized in that, The step of inputting temperature data into the pipeline thermodynamic model to calculate the airflow temperature at the mask end includes: The actual value of the humidifier outlet temperature is calculated based on the humidifier base plate temperature and the factory calibration curve. The actual value of the humidifier outlet temperature and the ambient temperature are input into the pipeline thermodynamic model to calculate the airflow temperature at the mask end. The expression for the pipeline thermodynamic model is as follows: T_mask=T_with+(T_hum_out1 T_with)×exp( η); T_mask is the airflow temperature at the mask end; T_amb is the ambient temperature; T_hum_out1 is the actual value of the humidifier outlet temperature; η is the pipeline attenuation coefficient, η=(4·U·L) / (ρ·c·v·D), U is the pipeline heat transfer coefficient, L is the pipeline length, ρ is the air density, c is the specific heat of air, v is the airflow velocity in the pipeline, and D is the pipeline inner diameter.

5. The adaptive humidification control method for a ventilator according to claim 4, characterized in that, The temperature data also includes the pipe outlet temperature. After inputting the temperature data into the pipe thermodynamic model and calculating the airflow temperature at the mask end, the process further includes: The airflow temperature at the mask end is obtained based on the outlet temperature of the pipeline. The temperature deviation result is obtained by comparing the measured temperature of the airflow at the mask end with the airflow temperature at the mask end. If the temperature deviation exceeds a preset temperature deviation threshold, the heat transfer coefficient of the pipeline in the pipeline thermodynamic model is corrected to obtain a corrected pipeline thermodynamic model. The corrected pipeline thermodynamic model is used to determine the anti-condensation hard constraint and to calculate the heating power of the target pipeline.

6. The adaptive humidification control method for a ventilator according to claim 1, characterized in that, The calculation of the target humidifier heating power and the target pipeline heating power based on the target humidity of the face mask includes: The target value of the humidifier outlet temperature is calculated based on the target humidity of the mask. The target heating power of the humidifier is calculated based on the target value of the humidifier outlet temperature, the ambient temperature, the target humidity of the mask, and the current humidity of the mask. The equivalent heat transfer coefficient of the pipeline after heating is turned on is calculated based on the anti-condensation hard constraint and the pipeline thermodynamic model. The target heating power of the pipeline is calculated based on the equivalent heat transfer coefficient. Under the hard constraint of anti-condensation, minimize the target humidifier heating power and the target pipeline heating power, and find the optimal solution for the target humidifier heating power and the target pipeline heating power.

7. The adaptive humidification control method for a ventilator according to claim 1, characterized in that, The heating control command includes a first heating command and a second heating command. Generating the heating control command based on the optimal solution of the target humidifier heating power and the target pipeline heating power includes: Obtain the inspiratory phase correction factor and the expiratory phase correction factor; A first heating command is generated based on the optimal solution of the inhalation phase correction coefficient, the exhalation phase correction coefficient, and the target humidifier heating power; A second heating command is generated based on the optimal solution of the target pipeline heating power.

8. The adaptive humidification control method for a ventilator according to claim 1, characterized in that, The step of generating heating control commands based on the optimal solution of the target humidifier heating power and the target pipeline heating power further includes: The effective target humidity is obtained during each sleep process, and the effective target humidity is used as the mask target humidity during the steady state phase of each sleep process; The seasonal baseline humidity value at the current ambient temperature is updated based on the effective target humidity.

9. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the adaptive humidification control method for ventilators as described in any one of claims 1-8.

10. A home-use ventilator, characterized in that, It includes a control module for running the adaptive humidification control method for ventilators as described in any one of claims 1-8.

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