Altitude adaptive portable oxygen generator control system and method

Abstract

The application discloses a portable oxygen generator control system and method based on altitude adaptation, relates to the technical field of program control, and obtains and corrects the altitude value of a portable oxygen generator, then predicts solar energy supply energy, VPSA oxygen production capacity and user oxygen demand and completes supply-demand matching and balance determination of three curves; energy distribution and priority scheduling are implemented according to the determination result, the decision is converted into specific compressor power, valve aperture and auxiliary load control, and finally the regulation effect representation value of the portable oxygen generator is obtained to perform closed-loop readjustment until the system returns to a safe and optimal state. Altitude is taken as baseline information throughout the prediction, matching and execution links, so that the oxygen generator can not only identify the supply-demand gap in advance and preferentially guarantee the core oxygen supply safety under different altitudes and environments, but also dynamically optimize energy utilization and auxiliary load management, thereby realizing stable oxygen supply and energy efficiency maximization under high-altitude and low-pressure conditions.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of program control, in particular to a portable oxygen generator control system and method based on altitude adaptation. BACKGROUND

[0002] The wide application of portable oxygen generators in different altitude environments such as highlands, mountainous areas and aviation will be affected by changes in environmental air pressure, temperature and air density. To ensure the safety of users in different altitudes, the oxygen concentration of the core breathing load is stably maintained at a safety threshold, thereby ensuring the reliability, energy efficiency and user safety of the portable oxygen generator in a variable environment.

[0003] For example, a small molecular sieve oxygen generator and its control system with publication number CN109375555B, the control system includes a microprocessor, a power stabilizer, an AC-DC converter, a battery, a power failure detection module, a battery switching module, a battery voltage detection module, a battery charging protection module and a two-position four-way electromagnetic valve. When the above-mentioned small molecular sieve oxygen generator executes a shutdown operation or suddenly loses power, the battery switching module connects the circuit between the battery and the power stabilizer to supply power to the small molecular sieve oxygen generator. The microprocessor sends a power failure protection control instruction to the two-position four-way electromagnetic valve according to the control phase of the current execution of the pressure swing adsorption cycle program, adjusts the opening or closing of the two-position four-way electromagnetic valve, and makes the compressor in a low pressure load state, so as to avoid the damage of the compressor body caused by mechanical impact or the impact of the compressor body on the protective shell caused by the violent vibration of the compressor body.

[0004] For example, a full-digital oxygen generator monitoring control system with publication number CN103984277B, including: a pressure detection device connected with the oxygen generator for detecting the system pressure signal of the oxygen generator; a temperature detection device with a probe extending into the interior of the oxygen generator for detecting the internal operating temperature signal of the oxygen generator; a controller connected with the pressure detection device and the temperature detection device for setting a time interrupt source and an AD interrupt source; an optical coupling isolation device connected with the controller for optically coupling and isolating the controller from the external circuit; a display device connected with the controller for displaying the pressure data, temperature data and time data after data algorithm processing; a power supply device.

[0005] However, in the process of implementing the technical scheme of the present application, the above-mentioned technology at least has the following technical problems:

[0006] The portable oxygen generator is unstable in oxygen supply and the energy efficiency of the equipment fluctuates under different altitudes due to differences in air pressure, air density and temperature. Changes in altitude will cause changes in the oxygen content of the inlet gas and the flow characteristics of the gas. If not controlled, the compressor and adsorption system may not effectively maintain a stable oxygen supply, resulting in insufficient oxygen supply for the user's breathing load or waste of energy. At the same time, the equipment may be overloaded in a low-pressure environment, affecting the service life and safety and reliability of the portable oxygen generator. SUMMARY

[0007] To solve the technical problems existing in the prior art, the embodiments of the present application provide a portable oxygen generator control system based on altitude adaptation. The technical solution is as follows: an altitude correction module is used to obtain GPS height information of the portable oxygen generator, determine GNSS positioning quality, and correct the altitude of the portable oxygen generator.

[0008] An environmental parameter acquisition and demand prediction module is used to obtain current environmental parameters, input the environmental parameters and the corrected altitude into a demand prediction neural network model, perform supply-demand curve matching and balance determination on the portable oxygen generator, and obtain a supply-demand matching and balance determination result of the portable oxygen generator.

[0009] A supply-demand adjustment and effect monitoring module is used to adjust the portable oxygen generator according to the supply-demand matching and balance determination result, monitor the adjustment effect of the portable oxygen generator, obtain an adjustment effect representation value of the portable oxygen generator, and readjust the portable oxygen generator according to the adjustment effect.

[0010] Further, the GNSS positioning quality is determined, and the altitude of the portable oxygen generator is corrected. The specific process is as follows:

[0011] The ellipsoidal height of the portable oxygen generator at the current position and the geoid undulation at the current position are read, the ellipsoidal height output by the GPS is subtracted by the geoid undulation at the current position, and the first sea level height at the current position is obtained.

[0012] The number of locked tracking satellites and the HDOP value of the portable oxygen generator at the current position are obtained, the number of locked tracking satellites and the HDOP value of the portable oxygen generator at the current position are weighted and fused to obtain a combined height reference factor of the portable oxygen generator, the combined height reference factor of the portable oxygen generator is compared with the combined height reference factor threshold of the portable oxygen generator in the database, if the combined height reference factor of the portable oxygen generator is higher than or equal to the combined height reference factor threshold of the portable oxygen generator, the first sea level height at the current position is taken as the final sea level height at the current position, and if the combined height reference factor of the portable oxygen generator is lower than the combined height reference factor threshold of the portable oxygen generator, the altitude of the portable oxygen generator is corrected.

[0013] Further, the environmental parameters and the corrected altitude are input into a demand prediction neural network model, and the specific process is: the corrected altitude is extracted, and the current environmental parameters and the user side state information are synchronously obtained, the corrected altitude, the current environmental parameters and the user side state information are jointly taken as input quantities to input into a preset demand prediction neural network model, the demand prediction neural network model establishes a corresponding relationship between the environmental state and the energy supply and demand characteristics through multi-layer nonlinear mapping, and outputs a solar cell available energy prediction curve, a VPSA oxygen production capacity prediction curve and an oxygen demand curve of a user.

[0014] Further, the portable oxygen generator is subjected to supply and demand curve matching balance determination, and the specific process is: a supply monitoring window is preset, and the solar cell available energy prediction curve, the VPSA oxygen production capacity prediction curve and the oxygen demand curve of the user are extracted in the supply monitoring window, and the solar cell available energy prediction curve, the VPSA oxygen production capacity prediction curve and the oxygen demand curve of the user are compared and analyzed.

[0015] Further, the solar cell available energy prediction curve, the VPSA oxygen production capacity prediction curve and the oxygen demand curve of the user are compared and analyzed, and the specific process is: in each time point of the supply monitoring window, the maximum compressor power supported by the solar cell available energy prediction curve is compared with the compressor power required by the VPSA oxygen production capacity prediction curve, if the compressor power required by the VPSA oxygen production capacity prediction curve at a certain time point is higher than or equal to the maximum compressor power supported by the solar cell available energy prediction curve at the time point, the compressor power required by the VPSA oxygen production capacity prediction curve at the time point is corrected, and if the compressor power required by the VPSA oxygen production capacity prediction curve at a certain time point is lower than the maximum compressor power supported by the solar cell available energy prediction curve at the time point, the oxygen production capacity prediction value at the time point does not need to be corrected, thereby obtaining a corrected VPSA oxygen production capacity prediction curve.

[0016] Further, a portable oxygen generator supply and demand matching balance determination result is obtained, and the specific process is: in each time point of the supply monitoring window, the actual oxygen production flow corresponding to the corrected VPSA oxygen production capacity prediction curve is subtracted from the predicted inhalation flow corresponding to the oxygen demand curve of the user, if the difference between the actual oxygen production flow corresponding to the VPSA oxygen production capacity prediction curve at a certain time point and the predicted inhalation flow corresponding to the oxygen demand curve of the user at the time point is greater than or equal to zero, a first result of portable oxygen generator supply and demand matching balance determination is obtained.

[0017] If the difference between the actual oxygen production flow corresponding to the oxygen production capacity prediction curve of the VPSA at a certain time point and the predicted inhalation flow corresponding to the oxygen demand curve of the user at the time point is less than zero, a second result of portable oxygen generator supply-demand matching balance determination is obtained.

[0018] Further, the portable oxygen generator is adjusted according to the portable oxygen generator supply-demand matching balance determination result, and the specific process is as follows: if the portable oxygen generator supply-demand matching balance determination result is the first result of portable oxygen generator supply-demand matching balance determination, the portable oxygen generator is subjected to secondary energy distribution and priority determination.

[0019] If the portable oxygen generator supply-demand matching balance determination result is the second result of portable oxygen generator supply-demand matching balance determination, the priority of the oxygen production flow of the portable oxygen generator is evaluated.

[0020] Further, the adjustment effect representation value of the portable oxygen generator is obtained, and the specific process is as follows: a monitoring time period is preset, and the outlet oxygen concentration, the oxygen outlet instantaneous flow, the real-time current of the compressor and the available discharge power of the energy storage unit of the portable oxygen generator are monitored in the monitoring time period.

[0021] The deviation value between the outlet oxygen concentration of the portable oxygen generator and the oxygen concentration safety threshold value set in the database, the deviation value between the predicted inhalation flow corresponding to the oxygen demand curve of the user and the oxygen outlet instantaneous flow and the predicted inhalation flow corresponding to the oxygen demand curve of the user, the deviation value between the real-time current of the compressor and the current reference value stored in the database, and the available discharge power of the energy storage unit and the standby power threshold value are respectively analyzed by proportion and introduced into a weight coefficient to obtain the adjustment effect representation value of the portable oxygen generator. The adjustment effect representation value of the portable oxygen generator is used to evaluate the oxygen supply stability and reliability of the portable oxygen generator under the current energy and load distribution strategy.

[0022] Further, the portable oxygen generator is re-adjusted according to the adjustment effect of the portable oxygen generator, and the specific process is as follows: the adjustment effect representation value of the portable oxygen generator is extracted, and is compared with the adjustment effect representation threshold value of the portable oxygen generator set in the database. If the adjustment effect representation value of the portable oxygen generator is lower than or equal to the adjustment effect representation threshold value of the portable oxygen generator, the portable oxygen generator is re-adjusted. If the adjustment effect representation value of the portable oxygen generator is higher than the adjustment effect representation threshold value of the portable oxygen generator, the portable oxygen generator does not need to be re-adjusted.

[0023] The second aspect of the present application also provides a system of portable oxygen generator control method based on altitude adaptation, comprising: obtaining the GPS height information of the portable oxygen generator, determining the GNSS positioning quality, and correcting the altitude of the portable oxygen generator.

[0024] Obtain the current environment parameter, input the environment parameter and the corrected altitude into the demand prediction neural network model, perform supply-demand curve matching balance determination on the portable oxygen generator, and obtain the portable oxygen generator supply-demand matching balance determination result.

[0025] According to the portable oxygen generator supply-demand matching balance determination result, the portable oxygen generator is adjusted, and the adjustment effect of the portable oxygen generator is monitored, the adjustment effect value of the portable oxygen generator is obtained, and the adjustment effect of the portable oxygen generator is adjusted again.

[0026] The technical scheme provided by the embodiment of the application has at least the following beneficial effects:

[0027] The application provides a portable oxygen generator control system based on altitude self-adaptation, which firstly obtains and corrects the altitude value of the portable oxygen generator, then predicts the solar energy supply energy, VPSA oxygen production capacity and user oxygen demand and completes the supply-demand matching and balance determination of three curves, then implements energy distribution and priority scheduling according to the determination result, converts the decision into specific compressor power, valve diameter and auxiliary load control, and finally obtains the adjustment effect value of the portable oxygen generator for closed-loop readjustment until the system returns to a safe and optimal state. The altitude is embedded in the prediction, matching and execution links as the baseline information throughout, so that the oxygen generator can not only identify the supply-demand gap in advance and prioritize core oxygen supply safety under different altitudes and environments, but also dynamically optimize energy utilization and auxiliary load management, thereby realizing stable oxygen supply, energy efficiency maximization under high-altitude and low-pressure conditions.

[0028] (2) The application obtains high-precision and reliable altitude data in real time by reading the GPS ellipsoid height of the current position of the portable oxygen generator, and provides an accurate height reference for subsequent environmental self-adaptive supply-demand prediction, compressor power adjustment and VPSA oxygen production optimization, so as to realize stable oxygen output, optimized energy utilization and improved robustness and safety of system operation under different altitude conditions.

[0029] (3) The application inputs the corrected altitude, current environment parameter and user side state information into the preset demand prediction neural network model, establishes the corresponding relationship between the environment state and the energy supply-demand characteristics through multi-layer nonlinear mapping, and outputs the solar cell energy supply energy prediction curve, the VPSA oxygen production capacity prediction curve and the user oxygen demand curve. Then, in the preset supply monitoring window, the three curves are compared and analyzed at each time point, so that the portable oxygen generator can match the compressor operating power and solar energy supply capacity under different altitudes and environmental conditions, realize the actual feasibility of oxygen production capacity and supply-demand balance, improve the stability of oxygen output, energy utilization efficiency and the safety and reliability of the overall system.

[0030] (4) The present application obtains the adjustment effect representation value of the portable oxygen generator, compares the adjustment effect representation value with the threshold value set in the database to trigger the readjustment of the portable oxygen generator, so as to optimize the oxygen supply capacity and power distribution, otherwise, the existing state is maintained, thereby realizing the dynamic monitoring and self-adaptive adjustment of the oxygen supply output of the portable oxygen generator, enabling the system to timely adjust the oxygen production capacity and energy distribution according to the altitude change and environmental conditions, improving the stability of oxygen supply, energy utilization efficiency and the safety and reliability of the overall system. BRIEF DESCRIPTION OF DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0032] Figure 1 is a system module schematic diagram provided by the embodiment of the present application;

[0033] Figure 2 is a whole flow chart of the portable oxygen generator control system based on altitude adaptation provided by the embodiment of the present application;

[0034] Figure 3 is a comparison diagram of each curve prediction provided by the embodiment of the present application;

[0035] Figure 4 is a user main interface diagram of the portable oxygen generator control system based on altitude adaptation provided by the embodiment of the present application;

[0036] Figure 5 is an adjustment monitoring page provided by the embodiment of the present application;

[0037] Figure 6 is a method schematic diagram provided by the embodiment of the present application. DETAILED DESCRIPTION

[0038] The technical solutions in the present application will be described below in combination with the drawings.

[0039] In the embodiments of the present application, the words such as "example", "for example" are used to represent as an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0040] In the embodiments of the present application, "image" and "picture" can be used interchangeably, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized. "Of", "corresponding" and "corresponding" can be used interchangeably, and it should be pointed out that the meanings expressed are consistent when the distinction is not emphasized.

[0041] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1, and the meanings expressed are consistent when the distinction is not emphasized.

[0042] In order to make the technical problems, technical solutions and advantages to be solved by the present application more clear, the following will be described in detail in conjunction with the drawings and specific embodiments.

[0043] As shown in Figure 1 Figure 1 The portable oxygen generator control system based on altitude adaptation comprises an altitude correction module for obtaining GPS height information of the portable oxygen generator, determining GNSS (Global Navigation Satellite System) positioning quality, and correcting the altitude of the portable oxygen generator.

[0044] An environmental parameter acquisition and demand prediction module is configured to obtain current environmental parameters, input the environmental parameters and the corrected altitude into a demand prediction neural network model, perform supply-demand curve matching and balance determination on the portable oxygen generator, and obtain a supply-demand matching and balance determination result of the portable oxygen generator.

[0045] A supply-demand adjustment and effect monitoring module is configured to adjust the portable oxygen generator according to the supply-demand matching and balance determination result, monitor the adjustment effect of the portable oxygen generator, obtain an adjustment effect representation value of the portable oxygen generator, and readjust the portable oxygen generator according to the adjustment effect.

[0046] Figure 2 As shown in the figure, the GNSS positioning quality is determined, and the altitude of the portable oxygen generator is corrected, and the specific process is as follows: the ellipsoidal height of the portable oxygen generator at the current position and the geoid undulation at the current position are read, the ellipsoidal height output by the GPS is subtracted by the geoid undulation at the current position, and the first sea level height at the current position is obtained.

[0047] ​The number of locked tracking satellites and the HDOP value (horizontal dilution of precision) of the portable oxygen generator at the current position are acquired, the number of locked tracking satellites and the HDOP value of the portable oxygen generator at the current position are weighted and fused to obtain a combined height reference factor of the portable oxygen generator, and the combined height reference factor of the portable oxygen generator is compared with a combined height reference factor threshold of the portable oxygen generator in the database. If the combined height reference factor of the portable oxygen generator is higher than or equal to the combined height reference factor threshold of the portable oxygen generator, the first sea level height at the current position is taken as the final sea level height at the current position. If the combined height reference factor of the portable oxygen generator is lower than the combined height reference factor threshold of the portable oxygen generator, the altitude of the portable oxygen generator is corrected.

[0048] It should be noted that the ellipsoidal height itself is obtained by solving GNSS satellite signals, and the accuracy is affected by satellite geometry and signal quality. When the number of satellites is small, the distribution is uneven, or the HDOP (horizontal / vertical dilution of precision) is high, the uncertainty of height solution will increase, and the ellipsoidal height may deviate from the true altitude. Therefore, by judging the GNSS positioning quality through the number of satellites and HDOP, it can be determined whether the ellipsoidal height is reliable, and if it is reliable, the altitude is directly converted, and if it is not reliable, it needs to be corrected. When the number of satellites is insufficient or the HDOP is high, it means that the uncertainty in the vertical direction increases, which may cause significant deviation in the conversion of the ellipsoidal height to the sea level height. Therefore, the weighted fusion of the number of satellites and the HDOP into the combined height reference factor and the comparison with the threshold are used to quantitatively judge whether the current GNSS height solution is reliable enough

[0049] It should be noted that the altitude of the portable oxygen generator is corrected, and the specific process is as follows: first, take the barometric height as the real-time height, continuously record the height change trend of the barometric height with time, then take the latest valid GNSS sea level height as the reference value to provide the reference of absolute height, combine the change amount of the barometric height with the reference GNSS height, continuously collect the height value measured by the barometric pressure sensor, and analyze the height difference between adjacent time points. If the latest barometric height is higher than the previous time, it means that the barometric height changes with time and shows an upward trend, and the system will increase the corresponding change amount on the reference GNSS height, and finally obtain the corrected altitude value at the current time. If the latest barometric height is lower than the previous time, it means that the barometric height changes with time and shows a downward trend, and the corresponding change amount is subtracted from the reference GNSS height, and finally the corrected altitude value at the current time is obtained. The corrected altitude value at the current time is taken as the final sea level height.

[0050] It should be noted that the air pressure height is the height value obtained by converting the air pressure value measured by the atmospheric pressure sensor installed on the portable oxygen generator in real time into atmospheric pressure-height, which is based on the current measured ambient pressure and temperature and refers to the local temperature profile to convert a standard decreasing rate into a relative height (which is measured on the device with high frequency and low delay), while the ellipsoid height given by the GNSS is an absolute geometric height obtained by satellite positioning solution, both of which have advantages and disadvantages: the air pressure height is very sensitive to short-term height changes (climbing, descending, and slight fluctuations) and has a high sampling frequency, but is affected by weather changes (regional pressure field, weather system, temperature gradient) and can produce long-term deviation; while the GNSS sea level height (obtained by deducting the geoid undulation from the ellipsoid height) can provide an absolute reference, but has large noise, slow or discontinuous updates when the satellite geometry is poor. When the system is corrected, the last GNSS sea level height determined as "valid" is used as the reference height, and then the air pressure height is continuously recorded and the difference between adjacent sampling points is calculated, i.e. the increase or decrease of the air pressure height in each sampling period, which is the "change amount", which reflects the short-term relative height change trend; when the air pressure height rises relative to the previous time, the cumulative air pressure height change amount is added to the reference GNSS height (when it decreases, the corresponding change amount is subtracted), so as to fuse the absolute scale provided by the GNSS and the high-frequency relative change provided by the air pressure into a corrected altitude that has both absolute reference and short-term dynamic, the basis of this approach is to eliminate the air pressure bias with GNSS and capture rapid height changes with air pressure, thereby balancing accuracy and responsiveness. In actual implementation, air pressure changes will also be filtered, temperature corrected and confidence weighted to suppress short-term noise and weather-induced slow drift.

[0051] As Figure 3 shown, Figure 3 The various curve prediction comparison diagrams provided by the embodiments of the present application present the trends and mutual relationships of the solar cell available energy prediction curve, the VPSA (vacuum pressure swing adsorption) oxygen production capacity prediction curve and the user's oxygen demand curve within the prediction time, wherein the solar cell available energy prediction curve, the VPSA oxygen production capacity prediction curve and the user's oxygen demand curve are obtained by inputting the environmental parameters and the corrected altitude into the demand prediction neural network model, and the specific process is as follows: the corrected altitude is extracted, and the current environmental parameters and user side state information are synchronously obtained, the corrected altitude, the current environmental parameters and the user side state information are jointly input into the preset demand prediction neural network model as input, the demand prediction neural network model establishes the corresponding relationship between the environmental state and the energy supply and demand characteristics through multi-layer nonlinear mapping, and outputs the solar cell available energy prediction curve, the VPSA oxygen production capacity prediction curve and the user's oxygen demand curve.

[0052] It should be noted that after the altitude obtained by the fusion correction of air pressure and GNSS information and the real-time collected environmental parameters (including temperature, humidity, air pressure, light intensity and time series information, etc.) and the state parameters available to the user side (such as respiratory trigger signal, blood oxygen saturation, activity intensity and historical oxygen record) are uniformly encoded and input into the preset demand prediction neural network model, the model adopts the structure combined with multilayer perceptron and time series feature extraction unit to ensure the nonlinear mapping ability of the environment state, user state and energy supply and demand relationship. The input layer of the model receives the above-mentioned multi-dimensional feature vector (a group of input features composed of the altitude obtained by the fusion correction of air pressure and GNSS in the real-time running process of the system, the collected environmental parameters and the state parameters of the user side, which form the training data together with the corresponding output target (such as user oxygen demand, system oxygen supply capacity, etc. Prediction value) in the model training stage, to establish the nonlinear mapping relationship between input and output), which is converted layer by layer through the nonlinear activation function of the hidden layer to form a feature representation that can represent the efficiency variation law of the solar cell under different temperature, irradiance and air density conditions, while capturing the adsorption-desorption performance and outlet pressure variation characteristics of the VPSA under different air pressure and temperature and humidity conditions, and learning the oxygen consumption evolution feature distribution of the user side under different altitudes and activity scenarios. The output layer of the model is designed as a multi-head structure, which generates three types of prediction results: one is the continuous curve of the available energy of the solar cell in the future short time window, one is the oxygen production capacity curve of the VPSA in the same time window, and the other is the user oxygen demand curve. It can simultaneously capture the dynamic evolution characteristics of the energy supply side, oxygen production capacity side and user demand side in a single inference process, and implicitly encode the influence of the corrected altitude on air density, temperature gradient and oxygen supply efficiency into the prediction results, thereby providing comprehensive and accurate basic data support for subsequent energy allocation, priority determination and oxygen generator power regulation.

[0053] Specifically, the portable oxygen generator is matched and balanced according to the supply and demand curve, and the specific process is as follows: a supply monitoring window is preset, and the available energy prediction curve of the solar cell, the oxygen production capacity prediction curve of the VPSA and the oxygen demand curve of the user are extracted in the supply monitoring window. The available energy prediction curve of the solar cell, the oxygen production capacity prediction curve of the VPSA and the oxygen demand curve of the user are compared and analyzed.

[0054] It needs to be explained that to compare the solar cell energy supply curve, the VPSA oxygen production capacity prediction curve and the user oxygen demand curve on the same coordinate axis, the key is to unify and equivalent convert different physical quantities. First, the solar cell energy supply curve is essentially in units of electric power (W), which describes the power that the system can provide to the compressor and related components at a certain time point. Since there is a clear energy conversion relationship between the power consumption of the compressor and the oxygen production capacity, the solar cell output power can be converted into equivalent oxygen flow rate by the compressor efficiency and oxygen production energy consumption factor, with units of L / min. Second, the VPSA oxygen production capacity prediction curve is naturally in units of oxygen flow rate (L / min), which can be directly used as a reference curve for comparison after modification. Finally, the user's oxygen demand curve is also in units of L / min, indicating the predicted oxygen demand at different time points. Therefore, by first converting the solar cell output power into equivalent oxygen flow rate, the three curves can be mapped on the same vertical coordinate. On the coordinate axis, the horizontal coordinate is unified as time (min), and the vertical coordinate is unified as oxygen flow rate (L / min). Comparing the solar cell energy supply curve, the VPSA oxygen production capacity prediction curve and the user oxygen demand curve can directly compare whether the supply upper limit (determined by solar power and compressor power), the actual oxygen production capacity of VPSA and the user demand match at different time points, and determine whether there is a supply-demand gap or redundancy, so as to realize dynamic adjustment and optimization of energy and oxygen supply strategy.

[0055] Specifically, the solar cell energy supply curve, the VPSA oxygen production capacity prediction curve and the user oxygen demand curve are compared and analyzed, and the specific process is as follows: in each time point of the supply monitoring window, the solar cell energy supply curve corresponding to the maximum compressor power supported is compared with the VPSA oxygen production capacity prediction curve corresponding to the required compressor power. If the VPSA oxygen production capacity prediction curve corresponding to the required compressor power at a certain time point is higher than or equal to the solar cell energy supply curve corresponding to the maximum compressor power supported at that time point, the VPSA oxygen production capacity prediction curve corresponding to the required compressor power at that time point is modified. If the VPSA oxygen production capacity prediction curve corresponding to the required compressor power at a certain time point is lower than the solar cell energy supply curve corresponding to the maximum compressor power supported at that time point, the oxygen production capacity prediction value at that time point does not need to be modified, thereby obtaining the modified VPSA oxygen production capacity prediction curve.

[0056] Specifically, the portable oxygen generator supply-demand matching balance determination result is obtained, and the specific process is as follows: the actual oxygen production flow corresponding to the modified VPSA oxygen production capacity prediction curve is subtracted from the predicted inhalation flow corresponding to the user's oxygen demand curve at each time point in the supply monitoring window. If the difference between the actual oxygen production flow corresponding to the VPSA oxygen production capacity prediction curve and the predicted inhalation flow corresponding to the user's oxygen demand curve at a certain time point is greater than or equal to zero, a first result of the portable oxygen generator supply-demand matching balance determination is obtained.

[0057] If the difference between the actual oxygen production flow corresponding to the VPSA oxygen production capacity prediction curve and the predicted inhalation flow corresponding to the user's oxygen demand curve at a certain time point is less than zero, a second result of the portable oxygen generator supply-demand matching balance determination is obtained.

[0058] It should be noted that, specifically, at each time point, the VPSA theoretical oxygen production capacity is the maximum oxygen output under ideal power, and the solar energy available energy determines the maximum power that the compressor can obtain at that time. If the solar energy available energy is insufficient to support the full power operation of the compressor, the VPSA oxygen production capacity must be proportionally or nonlinearly corrected according to the actual available power to obtain the actual oxygen production at that time. This value is usually lower than the theoretical oxygen production capacity, but it is not equal to the solar energy available energy itself, but is obtained by converting the power-oxygen performance relationship. When the VPSA oxygen production capacity prediction curve at this time point is corrected according to the required compressor power, first calculate the difference between the VPSA oxygen production capacity prediction curve at this time point and the required compressor power and the solar cell available energy prediction curve corresponding to the maximum compressor power supported, and input the power difference into the pre-set power-oxygen efficiency mapping table for table lookup matching. Through the mapping table, the actual oxygen flow that the VPSA can stably maintain under the current available power is obtained. Then, the difference between the VPSA oxygen production capacity prediction curve at this time point and the required compressor power and the solar cell available energy prediction curve corresponding to the maximum compressor power supported is taken as an input condition to query the pre-set power-oxygen efficiency mapping table. The mapping table will directly output a compressor power fine adjustment value and form a dynamic adjustment control instruction. Subsequently, the controller sends the fine adjustment value to the compressor drive unit and the VPSA valve control unit (combines the original planned compressor set power and the compressor power fine adjustment value to form a new target power), so that the device can smoothly reduce to the actual oxygen production capacity consistent with the energy supply under the limited power condition, avoiding the unrealistic situation that the theoretical production capacity exceeds the energy support range. The corrected VPSA oxygen production capacity not only ensures that it matches the available power on the energy side, but also helps to avoid the unrealistic situation that the theoretical oxygen production capacity is higher than the energy support level, so that the corrected curve is more consistent with the oxygen supply capacity boundary of the portable oxygen generator under real operating conditions. For example, if the VPSA theoretical oxygen production capacity is 5 liters / minute at a certain time, but the solar energy can only provide 80% of the power required for compressor driving, then the actual oxygen production capacity may be only 4 liters / minute. This 4 liters / minute is the corrected oxygen production capacity, which is used for comparison with the user demand curve.

[0059] Specifically, the portable oxygen generator is adjusted according to the portable oxygen generator supply-demand matching balance determination result, and the specific process is as follows: if the portable oxygen generator supply-demand matching balance determination result is the portable oxygen generator supply-demand matching balance determination first result, then the portable oxygen generator is subjected to secondary energy distribution and priority determination.

[0060] If the portable oxygen generator supply-demand matching balance determination result is the portable oxygen generator supply-demand matching balance determination second result, then the priority of the portable oxygen generator oxygen production flow is evaluated.

[0061] It should be noted that the specific process of secondary energy distribution and priority determination for the portable oxygen generator is as follows: the redundant energy at this moment (the actual available energy provided by the solar cell minus the energy required by the compressor and VPSA to meet the user's demand, and then the remaining part) is matched with the preset standby energy threshold in the threshold database. If the redundant energy exceeds the threshold, a standby mode enabling instruction is generated, wherein the standby mode is specifically to guide the redundant energy part into the energy storage unit. In this process, the system will collect oxygen outlet concentration sensor data in real time. When it is detected that the main oxygen supply path concentration is continuously higher than 96%, the energy management unit will call the task scheduler to issue a reduction instruction to reduce the power or suspend the operation of non-critical loads (such as fans, auxiliary displays or low-priority sensor modules), so as to achieve the goal of energy saving and standby energy storage. When the outlet oxygen concentration drops below 96%, the controller will immediately trigger an emergency priority scheduling to forcibly shut down all auxiliary loads, and redistribute all available redundant energy to the compressor and VPSA valve control unit, so as to quickly restore the oxygen production capacity by increasing the compressor speed or shortening the adsorption cycle period, so as to restore the oxygen concentration of the core breathing load to the safety threshold, until the monitoring value is stabilized above 96%, and the system will cancel the emergency scheduling and re-enter the supply-demand balance optimization state.

[0062] It should be noted that the specific process of priority evaluation of the oxygen production flow of the portable oxygen generator is as follows: the oxygen outlet concentration of the supply monitoring window is obtained, and is compared with the set oxygen concentration threshold. If the oxygen outlet concentration is higher than or equal to the oxygen concentration threshold, the energy consumption of the non-critical function of the portable oxygen generator is reduced. If the oxygen outlet concentration is lower than the oxygen concentration threshold, the core oxygen supply priority strategy of the portable oxygen generator is triggered.

[0063] It should be noted that the specific process of reducing the energy consumption of non-critical functions of the portable oxygen generator is as follows: first, input the supply-demand difference at this moment into the pre-set negative difference level-energy consumption reduction mapping table for table lookup matching, read the load reduction amount of each type of non-critical function suitable for the current gap amplitude (such as display screen backlight brightness, user interaction interface refresh rate, remote data upload frequency, log recording frequency, communication module wake-up interval, non-critical sensor sampling rate, fan speed, cooling cycle power, status indicator light brightness, auxiliary heating or humidifier power, Bluetooth / Wi-Fi broadcast frequency, etc.) from the mapping table, and form a set of dynamic energy consumption reduction control instructions with the fine tuning values output by the mapping table; then, the controller issues the fine tuning parameters to the corresponding execution units according to the instructions (for example, the display backlight brightness is reduced by the mapping value and the new target brightness is obtained by subtracting the original brightness value, the upload interval of wireless communication is enlarged by the mapping value to obtain a new upload plan, the sampling rate of non-critical sensors is reduced by the mapping value to obtain a new sampling period, and the fan speed is linearly or stepwise adjusted by the mapping value to obtain a new target speed), thereby realizing adaptive degradation of non-critical functions.

[0064] It should be noted that the trigger core oxygen supply priority strategy is as follows: the controller immediately performs energy redistribution, preferentially allocates all available power to the compressor and VPSA cycle, suspends or suspends all non-critical loads that can be deprived (such as high-brightness backlight, non-emergency communication, log-intensive upload, non-critical sensor polling, auxiliary heating / humidification, non-core fan high speed, etc.), and releases the maximum available power as a hard constraint; at the same time, the compressor drive power is increased at a controlled rate (set maximum climb rate), or a short-time pulse power supply mode is enabled on the supported design to provide instantaneous high output during the inspiration phase, to increase the VPSA inlet pressure and gas flow in the fastest way; during the whole process, the controller will limit the maximum amplitude and minimum duration of each action to avoid mechanical impact or molecular sieve damage, and monitor the outlet oxygen concentration, flow and equipment temperature at a high sampling rate during execution; if the concentration rises and stabilizes above the safety threshold within a limited time, the controller restores the suspended auxiliary load in stages according to the pre-set hysteresis strategy, gradually returns the compressor to the energy-saving operating point, while recording the whole process data and reporting warnings / events for operation and maintenance and subsequent model adjustment.

[0065] As shown in Figure 4 , the controller is configured to execute the core oxygen supply priority strategy when the oxygen concentration at the outlet of the portable oxygen generator is below the safety threshold, and the supply-demand difference is greater than the pre-set threshold. Figure 4The user main interface schematic diagram of the portable oxygen generator control system based on altitude self-adaption provided by the embodiment of the present application centrally presents six key real-time data including the current altitude, the outlet oxygen concentration, the adjustment effect, the solar power and the energy storage state, wherein the adjustment effect characteristic value of the portable oxygen generator is obtained, and the specific process is as follows: a preset monitoring time period is set, and the outlet oxygen concentration of the portable oxygen generator, the oxygen outlet instantaneous flow, the real-time current of the compressor and the available discharge power of the energy storage unit are monitored in the monitoring time period.

[0066] The deviation value between the outlet oxygen concentration of the portable oxygen generator and the oxygen concentration safety threshold value set in the database, the deviation value between the predicted inhalation flow corresponding to the user oxygen demand curve and the oxygen outlet instantaneous flow and the predicted inhalation flow corresponding to the user oxygen demand curve, the deviation value between the real-time current of the compressor and the current reference value stored in the database and the available discharge power of the energy storage unit and the standby power threshold value are respectively analyzed by percentage and introduced into the weight coefficient to obtain the adjustment effect characteristic value of the portable oxygen generator, and the adjustment effect characteristic value of the portable oxygen generator is used to evaluate the oxygen supply stability and reliability of the portable oxygen generator under the current energy and load distribution strategy.

[0067] It should be noted that the adjustment effect characteristic value of the portable oxygen generator is analyzed under the following conditions:

[0068] ;

[0069] In the formula, Q represents the adjustment effect characteristic value of the portable oxygen generator, OC1 represents the outlet oxygen concentration of the portable oxygen generator, OC represents the oxygen concentration safety threshold value, OL2 represents the oxygen outlet instantaneous flow, OL represents the predicted inhalation flow corresponding to the user oxygen demand curve, YI3 represents the real-time current of the compressor, YI represents the current reference value, IW4 represents the available discharge power of the energy storage unit, IW represents the standby power threshold value of the energy storage unit, A1 represents the weight coefficient corresponding to the outlet oxygen concentration stored in the database, A2 represents the weight coefficient corresponding to the oxygen outlet instantaneous flow stored in the database, A3 represents the weight coefficient corresponding to the real-time current of the compressor stored in the database, and A4 represents the weight coefficient corresponding to the available discharge power of the energy storage unit stored in the database.

[0070] It should be noted that the outlet oxygen concentration is compared with the oxygen concentration safety threshold value set in the database, and the purpose is to measure whether the current oxygen supply can meet the minimum safety requirement, and the oxygen concentration safety threshold value is the minimum safety line specified in the design, and the higher the oxygen concentration is not better, and excessive increase will waste energy and may cause other problems.

[0071] It should be noted that during the operation of a portable oxygen concentrator, the oxygen outlet concentration directly reflects the effective quality of oxygen inhaled by the user, and its stability is highly dependent on the matching degree of the instantaneous flow rate at the oxygen outlet. When there is a deviation in the instantaneous flow rate, the system will compensate for the oxygen production capacity by adjusting the real-time current of the compressor. The higher the current value, the higher the compressor load and gas passage pressure, which will affect the adsorption efficiency of the molecular sieve and the stability of the concentration output. At the same time, the increase in compressor current will increase the overall energy consumption and make it more dependent on the available discharge power of the energy storage unit. When the energy storage power drops to near the threshold, the system's compensation ability is limited, which leads to insufficient flow regulation and ultimately feeds back to the fluctuation of the outlet oxygen concentration. This closed-loop link, which is caused by the flow deviation, coupled through the compressor current and energy storage power, and then back to the oxygen concentration, constitutes the dynamic balance mechanism of the core performance of the portable oxygen concentrator.

[0072] It should be noted that the weighting coefficients corresponding to the outlet oxygen concentration, the instantaneous oxygen outlet flow rate, the real-time compressor current, and the available discharge power of the energy storage unit are all stored in the database, and their values ​​are typically set between 0 and 1. For example, by constructing mapping tables between the outlet oxygen concentration, the instantaneous oxygen outlet flow rate, the real-time compressor current, and the available discharge power of the energy storage unit and their corresponding weighting coefficients, the real-time detected outlet oxygen concentration, instantaneous oxygen outlet flow rate, real-time compressor current, and available discharge power of the energy storage unit are input into the corresponding mapping tables in the database, thereby quickly obtaining the weighting coefficients corresponding to the outlet oxygen concentration, the instantaneous oxygen outlet flow rate, the real-time compressor current, and the available discharge power of the energy storage unit, respectively.

[0073] It should be noted that by experimentally determining the typical correspondence between key parameters such as outlet oxygen concentration, flow rate, current, and energy storage power and weighting coefficients, an initial baseline mapping table is formed, describing the relationship between parameters and weighting coefficients under standard environment and typical load. During operation, when the system detects a change in parameters, it discretizes each key input parameter into several levels according to its value range. For each level, the initial weighting coefficient is recorded in the baseline mapping table (this table is the "baseline" at the time of equipment delivery). During operation, the system first looks up the table based on real-time parameters and performs linear or smooth interpolation on adjacent levels to obtain the mapping weight at that moment (called the mapping weight). Then, the mapping weight and the initial weight are merged according to a historical smoothing strategy (such as moving average) to obtain the final weight. This ensures that the mapping relationship has reliable experimental basis and can be automatically corrected in actual operation as conditions such as altitude, temperature, and load change, avoiding the contradiction that a single fixed relationship cannot reflect time-varying characteristics.

[0074] like Figure 5 As shown,Figure 5 The adjustment monitoring page provided for the embodiments of the present application lists in log form the various adjustments made automatically by the system over time, and readjusts according to the adjustment effect of the portable oxygen generator, the specific process being: extracting the adjustment effect representation value of the portable oxygen generator and comparing it with the adjustment effect representation threshold value of the portable oxygen generator set in the database, if the adjustment effect representation value of the portable oxygen generator is lower than or equal to the adjustment effect representation threshold value of the portable oxygen generator, readjusting the portable oxygen generator, if the adjustment effect representation value of the portable oxygen generator is higher than the adjustment effect representation threshold value of the portable oxygen generator, no readjustment is needed for the portable oxygen generator.

[0075] It should be noted that the specific process of readjusting the portable oxygen generator is: inputting the difference between the adjustment effect representation threshold value of the portable oxygen generator and the adjustment effect representation value of the portable oxygen generator into the power and flow fine-tuning mapping table, obtaining the corresponding compressor power increment and VPSA valve control adjustment amplitude by table lookup matching, and at the same time, referring to the maximum climb rate, allowable current rise rate and energy storage unit discharge power limit set by the compressor manufacturer, determining the controlled rate of this adjustment, i.e. the compressor output power allowed to be increased per second and the corresponding adsorption cycle optimization amplitude. Subsequently, the controller smoothly climbs the original set power to the incremental value recommended by the mapping table at the controlled rate, while synchronously adjusting the VPSA valve opening and cycle timing to increase oxygen output, and under the supported design, a short-time pulse power supply mode can be enabled to provide a high instantaneous flow in the inhalation phase to quickly restore oxygen concentration. Throughout the process, the system monitors the oxygen outlet concentration, instantaneous flow, compressor current and energy storage unit output power at a high frequency, and compares with the expected recovery curve for closed-loop verification, if the oxygen concentration and flow reach the safety threshold, the controller gradually retreats the compressor power and pulse power supply according to the hysteresis strategy, while restoring part of the non-critical load, achieving the balance between energy saving and stable oxygen supply; if it does not meet the standard, the incremental adjustment is executed in a loop and the energy distribution is optimized according to the energy storage state until normal recovery.

[0076] It should be noted that the power and flow fine-tuning mapping table is a stepwise power and valve control adjustment test on the compressor and VPSA system under different altitudes, temperatures, humidities and load scenarios, recording the changes in oxygen concentration, oxygen production flow and response time under each input condition; then based on these experimental data, combined with the compressor performance curve and the mechanism model of molecular sieve adsorption / desorption, a relationship model between power and flow is constructed. Then through back calculation (for example, given the target adjustment effect difference, how much power and valve control amplitude need to be increased to make up for it), a large number of "difference-action" samples are generated, and are corrected under different working conditions, and finally the mapping relationship is arranged into a table for use.

[0077] For example, Figure 6As shown, the second aspect of the present application also provides a method for controlling a portable oxygen generator based on altitude adaptation, comprising: obtaining GPS height information of the portable oxygen generator, determining GNSS positioning quality, and correcting the altitude of the portable oxygen generator.

[0078] Obtaining the current environmental parameters, inputting the environmental parameters and the corrected altitude into the demand prediction neural network model, and performing supply-demand curve matching and balance determination on the portable oxygen generator to obtain the supply-demand matching and balance determination result of the portable oxygen generator.

[0079] According to the supply-demand matching and balance determination result of the portable oxygen generator, the portable oxygen generator is adjusted, and the adjustment effect of the portable oxygen generator is monitored to obtain the adjustment effect representation value of the portable oxygen generator, and the portable oxygen generator is readjusted according to the adjustment effect of the portable oxygen generator.

[0080] It should also be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (read-only memory, ROM), a programmable read-only memory (programmable ROM, PROM), an erasable programmable read-only memory (erasable PROM, EPROM), an electrically erasable programmable read-only memory (electrically EPROM, EEPROM) or a flash memory. The volatile memory can be a random access memory (random access memory, RAM) used as an external cache. By way of example but not limitation, many forms of random access memory (random access memory, RAM) can be used, such as static random access memory (static RAM, SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (double data rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM), synchronous link dynamic random access memory (synchlink DRAM, SLDRAM) and direct memory bus random access memory (direct rambus RAM, DR RAM).

[0081] The above-described embodiments can be implemented in whole or in part by software, hardware (e.g., circuitry), firmware, or any combination thereof. When implemented in software, the above-described embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present application are entirely or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through wired (e.g., infrared, wireless, microwave, etc.) or wireless means. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center, etc. containing one or more available medium collections. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0082] It should be understood that the term "and / or" herein merely describes an association relationship of associated objects, which means that there can be three relationships, for example, A and / or B can represent three cases of A alone, A and B together, and B alone, where A and B can be singular or plural. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after it, but it can also represent an "and / or" relationship, which can be understood in the context before and after it.

[0083] In the present application, "at least one" means one or more, and "multiple" means two or more. "At least one of the following" or the like means any combination of the items, including any combination of single item or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0084] It should be understood that in various embodiments of the present application, the size of the sequence number of the above-described processes does not mean the order of execution, and the execution order of the processes should be determined by their functions and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0085] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0086] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the devices, apparatuses and units described above can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0087] In several embodiments provided by the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely schematic, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0088] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0089] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically independently, or two or more units can be integrated into one unit.

[0090] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0091] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A portable oxygen concentrator control system based on altitude adaptation, characterized in that, The system includes: The altitude correction module is used to acquire the GPS altitude information of the portable oxygen concentrator, determine the GNSS positioning quality, and correct the altitude of the portable oxygen concentrator. The environmental parameter acquisition and demand forecasting module is used to acquire current environmental parameters, input the environmental parameters and the corrected altitude into the demand forecasting neural network model, perform supply and demand curve matching balance determination on the portable oxygen concentrator, and obtain the supply and demand matching balance determination result of the portable oxygen concentrator. The supply and demand adjustment and effect monitoring module is used to adjust the portable oxygen concentrator according to the supply and demand matching balance judgment result, monitor the adjustment effect of the portable oxygen concentrator, obtain the adjustment effect characterization value of the portable oxygen concentrator, and readjust it according to the adjustment effect of the portable oxygen concentrator. The specific process for obtaining the regulation effect characterization values ​​of the portable oxygen concentrator is as follows: A preset monitoring period is set, during which the outlet oxygen concentration, instantaneous oxygen outlet flow rate, real-time current of the compressor, and available discharge power of the energy storage unit of the portable oxygen concentrator are detected. The deviations between the oxygen concentration safety threshold set in the database and the outlet oxygen concentration and oxygen concentration safety threshold of the portable oxygen concentrator, the deviations between the predicted inhalation flow rate corresponding to the user's oxygen demand curve and the instantaneous oxygen outlet flow rate and the predicted inhalation flow rate corresponding to the user's oxygen demand curve, the deviations between the current reference value stored in the database and the real-time current of the compressor and the current reference value stored in the database, and the available discharge power and standby power threshold of the energy storage unit are analyzed by proportion and weighting coefficients to obtain the regulation effect characterization value of the portable oxygen concentrator. The regulation effect characterization value of the portable oxygen concentrator is used to evaluate the oxygen supply stability and reliability of the portable oxygen concentrator under the current energy and load distribution strategy.

2. The portable oxygen concentrator control system based on altitude adaptation according to claim 1, characterized in that, The specific process for determining the GNSS positioning quality and correcting the altitude of the portable oxygen concentrator is as follows: Read the ellipsoidal height of the portable oxygen generator at the current location and the geoid undulation at the current location. Subtract the geoid undulation at the current location from the ellipsoidal height output by the GPS to obtain the first sea level height at the current location. The system obtains the number of locked-tracking satellites and HDOP value of the portable oxygen concentrator at the current location. It then performs a weighted fusion of these data to obtain the joint altitude reference factor (LIFR) for the portable oxygen concentrator. This LIFR is compared with the LIFR threshold in the database. If the LIFR is higher than or equal to the threshold, the first sea level at the current location is used as the final sea level. If the LIFR is lower than the threshold, the altitude of the portable oxygen concentrator is corrected.

3. The portable oxygen concentrator control system based on altitude adaptation according to claim 1, characterized in that, The specific process of inputting environmental parameters and the corrected altitude into the demand prediction neural network model is as follows: The corrected altitude is extracted and the current environmental parameters and user-side status information are acquired simultaneously. The corrected altitude, current environmental parameters, and user-side status information are combined as inputs into a preset demand prediction neural network model. The demand prediction neural network model establishes the correspondence between environmental status and energy supply and demand characteristics through multi-layer nonlinear mapping, and outputs the available energy prediction curve of solar cells, the oxygen production capacity prediction curve of VPSA, and the oxygen demand curve of users.

4. The portable oxygen concentrator control system based on altitude adaptation according to claim 3, characterized in that, The specific process for determining the supply and demand curve matching balance of the portable oxygen concentrator is as follows: A preset supply monitoring window is established. The available energy prediction curve of the solar cell, the oxygen production capacity prediction curve of the VPSA, and the oxygen demand curve of the user are extracted from the supply monitoring window. The available energy prediction curve of the solar cell, the oxygen production capacity prediction curve of the VPSA, and the oxygen demand curve of the user are compared and analyzed.

5. The portable oxygen concentrator control system based on altitude adaptation according to claim 4, characterized in that, The process of comparing and analyzing the energy supply prediction curve of the solar cell, the oxygen production capacity prediction curve of the VPSA, and the user's oxygen demand curve is as follows: At each time point within the supply monitoring window, the maximum compressor power supported by the solar cell's available energy prediction curve is compared with the required compressor power corresponding to the VPSA's oxygen production capacity prediction curve. If the required compressor power corresponding to the VPSA's oxygen production capacity prediction curve at a certain time point is higher than or equal to the maximum compressor power supported by the solar cell's available energy prediction curve at that time point, then the required compressor power corresponding to the VPSA's oxygen production capacity prediction curve at that time point is corrected. If the required compressor power corresponding to the VPSA's oxygen production capacity prediction curve at a certain time point is lower than the maximum compressor power supported by the solar cell's available energy prediction curve at that time point, then no correction is needed for the oxygen production capacity prediction value at that time point. This yields the corrected VPSA oxygen production capacity prediction curve.

6. The portable oxygen concentrator control system based on altitude adaptation according to claim 5, characterized in that, The specific process for obtaining the supply and demand balance determination result of the portable oxygen concentrator is as follows: At each time point in the supply monitoring window, the difference between the actual oxygen production flow rate corresponding to the oxygen production capacity prediction curve of the corrected VPSA and the predicted inhalation flow rate corresponding to the oxygen demand curve of the user is calculated. If the difference between the actual oxygen production flow rate corresponding to the oxygen production capacity prediction curve of the VPSA and the predicted inhalation flow rate corresponding to the oxygen demand curve of the user at a certain time point is greater than or equal to zero, the first result of the supply and demand matching balance judgment of the portable oxygen concentrator is obtained. If the difference between the actual oxygen production flow rate corresponding to the oxygen production capacity prediction curve of the VPSA at a certain time point and the predicted inhalation flow rate corresponding to the oxygen demand curve of the user at that time point is less than zero, then the second result of the supply and demand matching balance determination of the portable oxygen concentrator is obtained.

7. The portable oxygen concentrator control system based on altitude adaptation according to claim 6, characterized in that, The process of adjusting the portable oxygen concentrator based on the supply and demand balance determination result is as follows: If the supply and demand matching balance determination result of the portable oxygen concentrator is the first result of the supply and demand matching balance determination of the portable oxygen concentrator, then a second energy allocation and priority determination will be performed on the portable oxygen concentrator. If the supply and demand matching balance determination result of the portable oxygen concentrator is the second result of the portable oxygen concentrator supply and demand matching balance determination, then the oxygen production flow rate of the portable oxygen concentrator will be prioritized for evaluation.

8. The portable oxygen concentrator control system based on altitude adaptation according to claim 1, characterized in that, The process of readjusting based on the adjustment effect of the portable oxygen concentrator is as follows: Extract the regulation effect characterization value of the portable oxygen concentrator and compare it with the regulation effect characterization threshold set in the database. If the regulation effect characterization value of the portable oxygen concentrator is lower than or equal to the regulation effect characterization threshold, the portable oxygen concentrator is readjusted. If the regulation effect characterization value of the portable oxygen concentrator is higher than the regulation effect characterization threshold, the portable oxygen concentrator does not need to be readjusted.

9. The method for using a portable oxygen concentrator control system based on altitude adaptation as described in any one of claims 1-8, characterized in that, include: Obtain the GPS altitude information of the portable oxygen concentrator, determine the GNSS positioning quality, and correct the altitude of the portable oxygen concentrator. The current environmental parameters are obtained, and the environmental parameters and the corrected altitude are input into the demand prediction neural network model to determine the supply and demand curve matching balance of the portable oxygen concentrator and obtain the supply and demand matching balance determination result of the portable oxygen concentrator. The portable oxygen concentrator is adjusted based on the supply and demand matching balance determination results, and the adjustment effect is monitored to obtain the characteristic value of the adjustment effect. Then, the portable oxygen concentrator is readjusted based on the adjustment effect.

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