A liquid thermostatic control system for bacteriophage preparation

Abstract

This invention discloses a liquid temperature-controlled system for phage preparations, belonging to the field of biological agent storage and transportation. The liquid temperature-controlled system for phage preparations includes a housing, a temperature regulation unit, an energy storage and power supply unit, a solar power generation unit, an environmental sensing unit, an intelligent control unit, and a monitoring, control, and data acquisition unit. This invention solves the problems of existing temperature-controlled storage equipment relying on mains power, insufficient energy management efficiency, and susceptibility to failure due to energy depletion in outdoor or unstable power environments. Through solar self-powering and intelligent energy prediction management, this invention enables long-term self-sustaining operation of the system in complex environments. Furthermore, by employing a multi-mode switching and adaptive temperature control strategy based on energy prediction, it can improve the system's environmental adaptability and energy utilization efficiency while ensuring the core temperature requirement for phage preparation activity.

Description

Technical Field

[0001] This invention relates to the field of biological agent storage and transportation technology, specifically to a liquid constant temperature control system for bacteriophage preparations. Background Technology

[0002] Bacteriophage preparations, as highly specific antimicrobial agents, have shown broad application prospects in the medical, agricultural, and food industries. However, the biological activity of bacteriophage preparations is extremely sensitive to storage temperature, and they typically require transportation and storage under specific constant temperature conditions (e.g., 2-8°C) to maintain their potency. Traditional constant temperature storage boxes mostly rely on mains power, and their application scenarios are severely limited by fixed power sources, making them difficult to deploy in the field, remote areas, or environments with unstable power. Although existing technologies use battery or solar-powered refrigeration equipment, they generally suffer from insufficient energy management efficiency and poor environmental adaptability. They cannot perform intelligent dynamic control based on energy reserves, environmental conditions, and equipment status. Under harsh conditions such as continuous rain or extreme temperatures, they are prone to energy depletion leading to temperature control failure, causing the bacteriophage preparation to become inactive and unusable. Therefore, they cannot meet current needs. In view of this, this invention proposes a liquid constant temperature control system for bacteriophage preparations. Summary of the Invention

[0003] The purpose of this invention is to provide a liquid constant temperature control system for phage preparations. By integrating solar power generation, intelligent energy management, and multi-mode adaptive temperature control technology, a self-sustaining, reliable, and environmentally adaptable mobile constant temperature storage solution is constructed. This system can dynamically predict energy income and expenditure and intelligently switch working modes based on ambient light, temperature, and its own energy status. Under the premise of ensuring long-term stability of the core storage temperature of phage preparations, it maximizes energy utilization efficiency and system endurance, thus solving the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a liquid constant temperature control system for phage preparations, comprising: The interior of the box forms a sealed, temperature-controlled chamber for containing and storing bacteriophage preparations; The temperature control unit is located inside the chamber and is used to regulate and maintain the temperature inside the temperature control chamber at a preset constant temperature. The energy storage power supply unit is used to provide operating power to the temperature regulation unit; The solar power generation unit, located on the outside of the enclosure, is used to convert solar energy into electrical energy to charge the energy storage power supply module; The environmental sensing unit includes a light sensor and an ambient temperature sensor located outside the enclosure, and a formulation temperature sensor located inside the temperature control chamber, for real-time monitoring of external light intensity, ambient temperature and formulation liquid temperature. The intelligent control unit is used to control the operation of the temperature regulation unit to maintain a constant temperature, and to control the cabinet to switch between standard working mode and low power consumption constant temperature maintenance mode according to the remaining power of the energy storage power supply unit. The monitoring, control and data acquisition unit is used to remotely monitor the real-time temperature of the temperature control chamber, the remaining power and charging / discharging status of the energy storage power supply unit, the working power of the solar power generation unit, and the current working mode of the enclosure. It also collects, stores, and uploads relevant historical operating data. Furthermore, the monitoring, control and data acquisition unit sends control commands to the intelligent control module according to preset strategies or remote instructions to adjust the temperature setpoint or the working mode switching threshold.

[0005] Furthermore, the intelligent control unit includes: The data acquisition module is configured to acquire the real-time power generation of the solar power generation unit, the real-time remaining power and charging / discharging current of the energy storage power supply unit, and the real-time temperature gradient inside and outside the temperature control chamber. The energy prediction module has a pre-stored state assessment model containing time variables. It is configured to predict the net energy income and expenditure of the enclosure over a future period based on real-time data acquired by the data acquisition module. The prediction takes into account the sustainability of the current power generation, the estimated power consumption required by the temperature regulation unit to maintain the target temperature, and the current capacity of the energy storage power supply unit. The dynamic decision-making module is configured to generate mode switching instructions based on the real-time remaining power of the energy storage power supply unit and the dynamic results of the net energy income and expenditure forecast provided by the energy prediction module. The specific decision-making logic is as follows: When forecasts indicate that net energy will remain positive for some time and energy storage is sufficient, a switching command is generated to maintain or switch to the standard operating mode. When the forecast shows that the net energy will be close to balance or turn negative in the future, even if the current remaining power is higher than the first preset threshold, a switching command is generated to switch to the low power constant temperature maintenance mode. The intelligent control unit executes the control of the temperature regulation unit and switches the cabinet's working mode according to the switching instructions generated by the dynamic decision module.

[0006] Furthermore, when the dynamic decision-making module switches to the low-power isostatic maintenance mode, it executes an adaptive pulse width modulation temperature control strategy, specifically: In the initial stage of entering low power mode, the temperature regulation unit is controlled to run intermittently by high frequency and initial duty cycle, and the temperature rise rate and drop rate are recorded in real time during each running cycle. Based on the recorded data, a thermal inertia model of the temperature-controlled chamber under the current environmental conditions is dynamically established through a built-in learning algorithm. Based on the thermal inertia model, the duty cycle and period of PWM control are dynamically adjusted to minimize the effective operating time of the temperature regulation unit while ensuring that the internal temperature of the temperature control chamber does not exceed the preset safe fluctuation range. At the same time, the width of the preset safe fluctuation range is dynamically adjusted according to the remaining power level of the energy storage power supply unit. That is, the lower the power level, the wider the allowable short-term fluctuation range is.

[0007] Furthermore, when the dynamic decision-making module switches to the low-power constant temperature maintenance mode, the intelligent control unit executes an adaptive temperature control strategy, specifically: In response to the switching command issued by the dynamic decision module to switch to the low-power constant temperature maintenance mode, it takes over the control of the temperature regulation unit. It has a pre-stored initial PWM parameter library and a safety temperature fluctuation parameter library corresponding to different power levels; Based on real-time data from the environmental sensing unit, the matching initial frequency and duty cycle parameters are called from the initial PWM parameter library to start intermittent control of the temperature regulation unit. During operation, the duty cycle and period of the PWM control parameters are dynamically optimized and adjusted according to the real-time temperature change rate of the temperature control chamber to approximate the minimum required operating time of the temperature regulation unit. Meanwhile, based on the real-time remaining power level of the energy storage power supply unit fed back by the data acquisition module, the corresponding temperature fluctuation range threshold is dynamically called from the safe temperature fluctuation parameter library and set. The parameter library is preset to allow a wider short-term temperature fluctuation range threshold as the power level is lower.

[0008] Furthermore, the monitoring, control, and data acquisition unit includes: The data collection module is connected to the temperature regulation unit, energy storage power supply unit, solar power generation unit, environmental sensing unit and intelligent control unit, and is configured to collect and preprocess monitoring data from each unit in real time. The instruction forwarding module has multiple preset control strategies. The control strategies are set based on different geographical locations, seasonal modes or task priorities. It is configured to automatically match and activate the corresponding control strategies based on the real-time and historical data analysis results provided by the data collection module, or receive instructions from the remote management platform to generate specific temperature setpoints, working mode switching thresholds or system operating parameters, and forward them to the intelligent control unit. The edge computing module is configured to perform edge computing analysis on the collected historical and real-time data locally, and perform system health diagnosis. The diagnosis includes: identifying the performance degradation trend of the temperature regulation unit, assessing the capacity degradation status of the energy storage power supply unit, judging the abnormal photoelectric conversion efficiency of the solar power generation unit, and predicting the changes in the thermal insulation performance of the enclosure, and generating corresponding early warning reports. The data synchronization module is configured to upload processed data, early warning reports, system status, and analysis results from the edge computing module to a remote cloud platform or management terminal via a wireless communication network, and simultaneously receive query and control commands from the remote terminal.

[0009] Furthermore, the monitoring, control, and data acquisition unit is further configured as follows: It has a pre-built anomaly level definition library and a corresponding emergency strategy library. The anomaly level definition library divides system anomalies into multiple levels. Each level is defined based on the degree of performance degradation or anomaly information in the early warning report generated by the edge computing module. The emergency strategy library stores specific physical control strategies corresponding to each anomaly level. When the edge computing module generates an early warning report, it performs the following operations: Based on the content of the early warning report, match and determine the level of the current abnormal event from the abnormal level definition library; Based on the determined anomaly level, the corresponding emergency strategy is automatically retrieved from the emergency strategy library and immediately sent to the intelligent control unit for execution via the instruction forwarding module; The data synchronization module synchronizes the determined anomaly level, the invoked emergency strategy content, and the details of executed instructions as high-level event logs to the remote management platform.

[0010] Furthermore, based on the determined anomaly level, the corresponding emergency policy is automatically retrieved from the emergency policy library. Emergency policies include, but are not limited to: When the performance degradation of the temperature regulation unit is detected to reach a preset level, a compensatory operation command is issued to instruct the intelligent control unit to extend the single operation time of the temperature regulation unit. When the photovoltaic conversion efficiency of the solar power generation unit is abnormally high and reaches a preset level, an energy priority command is issued to force the intelligent control unit to switch the working mode of the cabinet to a low-power constant temperature maintenance mode and dynamically reduce the power consumption of other auxiliary units except for the constant temperature function. When the predicted change in the thermal insulation performance of the enclosure reaches a preset level, a thermal insulation enhancement command is issued to instruct the intelligent control unit to increase the temperature monitoring frequency and trigger the temperature adjustment action in the low-power constant temperature maintenance mode in advance to offset the increased heat loss.

[0011] Furthermore, the energy storage power supply unit includes an energy storage module with redundant configuration and a multi-channel isolated charge and discharge control circuit, specifically: The energy storage module contains multiple independent parallel energy storage battery packs, each of which is connected to an independent charging and discharging control circuit, and the circuits are electrically isolated from each other. The multi-channel isolated charge and discharge control circuit selectively enables and disconnects the charge and discharge paths of some energy storage battery packs according to the instructions of the intelligent control unit or the supervision, control and data acquisition unit, so as to realize the group maintenance, fault isolation and power output mode switching of the energy storage power supply unit.

[0012] Furthermore, when the intelligent control unit executes the adaptive pulse width modulation temperature control strategy, it is configured to perform a sensorless real-time thermal load identification step to solve the problem of thermal inertia model inaccuracy caused by the reduction of phage preparation dosage. The real-time heat load identification step specifically includes: during the operating cycle of a single cooling action performed by the temperature regulation unit, the intelligent control unit, based on the principle of energy conservation, uses a built-in dynamic heat capacity calculation formula to derive the equivalent heat load coefficient of the current temperature control chamber in real time. The formula for calculating the dynamic heat capacity is: ; in, The equivalent heat load coefficient is a numerical value that characterizes the total heat capacity of the remaining phage preparation and air in the current temperature-controlled chamber, and is expressed in joules per degree Celsius. and These are the start and end times of the temperature regulation unit in the single cooling action, respectively. and These are the real-time voltage and real-time current values ​​output by the energy storage power supply unit to the temperature regulation unit during the operating cycle, respectively. The preset electrothermal conversion efficiency constant of the temperature regulation unit; This is a definite integral operation performed over time to calculate the total input electrical energy within the operating cycle; The overall heat transfer coefficient of the vacuum insulation material of the box wall layer is preset; The effective heat dissipation surface area of ​​the enclosure; The average external ambient temperature measured by the ambient temperature sensor during the operating cycle; The average internal temperature of the temperature-controlled chamber measured by the formulation temperature sensor during the operating cycle; It is the absolute value of the temperature change inside the temperature-controlled chamber during the operating cycle; The intelligent control unit will calculate the equivalent heat load coefficient. The thermal inertia model is updated in real time as a core physical parameter.

[0013] Furthermore, the intelligent control unit is also equipped with a low-margin micro-frequency flexible protection strategy, the strategy specifically being: The intelligent control unit is preset with a standard thermal load threshold corresponding to the full-load operating condition. When the equivalent heat load coefficient calculated by the intelligent control unit When the ratio is lower than the preset proportion of the standard heat load threshold, the phage preparation in the current temperature-controlled chamber is determined to be in a low-reserve, high-risk state. At this time, the intelligent control unit automatically and forcibly locks the PWM control mode to the micro-frequency point-fire mode; In the micro-frequency spot firing mode, the intelligent control unit shortens the fundamental period of the PWM control signal to the millisecond level, and based on the equivalent thermal load coefficient... The attenuation ratio linearly reduces the upper limit of the duty cycle of a single pulse. By using a high-frequency and extremely short cold injection method, it prevents the temperature of the phage preparation from falling below the activity safety limit due to excessive cooling energy in a single pulse under low heat capacity conditions.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention achieves energy self-sufficiency and high environmental adaptability by deeply integrating solar power supply, multi-source environmental sensing, and intelligent energy prediction management on the basis of traditional constant temperature control systems. Furthermore, the system can dynamically assess future energy income and expenditure and intelligently decide on the working mode based on real-time light, temperature, and energy storage capacity, thereby avoiding the dependence of traditional equipment on fixed power sources. This enables reliable deployment in the field, remote areas, and environments with unstable power supply, solving the problem of energy depletion and temperature control failure under continuous harsh conditions due to insufficient energy management efficiency.

[0015] 2. This invention introduces an adaptive pulse width modulation temperature control strategy based on energy prediction and local edge computing functions to achieve refined constant temperature maintenance and proactive system maintenance in low-power mode. The system can dynamically optimize the operating parameters of the temperature control unit according to the thermal inertia of the environment, maximizing energy saving while ensuring safe fluctuations in the formulation temperature. At the same time, by continuously monitoring the performance degradation of key units and pre-setting emergency strategies, it can provide early warnings and automatically compensate for performance degradation or isolate faults, thereby improving the operational reliability of the system in long-term unattended scenarios and the preservation safety of phage formulations, and thus reducing the risk of formulation inactivation and scrapping due to equipment performance degradation or sudden abnormalities. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the module of the phage preparation liquid constant temperature control system of the present invention; Figure 2 This is a schematic diagram of the external appearance of the housing of the present invention; Figure 3 This is a schematic diagram of the interior of the housing of the present invention.

[0017] In the diagram: 1. Box; 2. Solar photovoltaic panel; 3. Preparation rack; 4. Temperature control component; 5. Monitoring component; 6. Energy storage component. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To address the technical problems of existing temperature-controlled storage equipment, such as reliance on mains power, insufficient energy management efficiency, and susceptibility to failure due to energy depletion in the field or in environments with unstable power supply, please refer to [link to relevant documentation]. Figures 1-3 This embodiment provides the following technical solution: A liquid temperature control system for phage preparations, comprising: The interior of the box 1 forms a sealed temperature-controlled chamber for containing and storing the bacteriophage preparation. The walls of the box 1 are filled with vacuum insulation material, and the inner walls of the temperature-controlled chamber are coated with an antibacterial coating to enhance the insulation performance and inhibit the growth of microorganisms. The temperature control unit is located inside the chamber 1 and is used to adjust and maintain the temperature in the temperature control chamber at a preset constant temperature. The energy storage power supply unit is used to provide operating power to the temperature regulation unit; A solar power generation unit, located outside the housing 1, is used to convert solar energy into electrical energy to charge the energy storage power supply module. Specifically, it includes: Solar photovoltaic panels 2 are installed on the top and sides of the exterior of the housing 1. The solar photovoltaic panels 2 are electrically connected to the energy storage components 6 and are used to convert solar energy into electrical energy and charge the energy storage components 6. The environmental sensing unit includes a light sensor and an ambient temperature sensor located outside the housing 1, and a formulation temperature sensor located inside the temperature control chamber, for real-time monitoring of external light intensity, ambient temperature and formulation liquid temperature. The intelligent control unit is used to control the operation of the temperature regulation unit to maintain a constant temperature, and to control the cabinet 1 to switch between the standard working mode and the low power consumption constant temperature maintenance mode according to the remaining power of the energy storage power supply unit. The monitoring, control and data acquisition unit is used to remotely monitor the real-time temperature of the temperature control chamber, the remaining power and charging / discharging status of the energy storage power supply unit, the working power of the solar power generation unit, and the current working mode of the enclosure 1. It also collects, stores and uploads relevant historical operating data. In addition, the monitoring, control and data acquisition unit sends control commands to the intelligent control module according to preset strategies or remote commands to adjust the temperature setpoint or the working mode switching threshold.

[0020] The technical effects of the above-mentioned solution are as follows: By filling the interior of the housing 1 with vacuum insulation material and coating it with an antibacterial coating, the insulation performance of the sealed temperature-controlled chamber is enhanced and the growth of microorganisms is inhibited. The temperature regulation unit can precisely regulate and maintain the preparation liquid at a preset constant temperature, thereby ensuring the activity and stability of the bacteriophage preparation. The energy storage and power supply unit continuously provides working power to the system, ensuring the continuity of temperature control. The solar power generation unit utilizes the solar photovoltaic panels 2 on the top and sides of the housing 1 to convert solar energy into electrical energy and charge the energy storage component 6, thereby improving the system's energy efficiency. With its self-sufficiency and field applicability, the environmental sensing unit provides accurate data support for intelligent regulation by monitoring external light, ambient temperature, and internal temperature of the formulation in real time. Based on this, the intelligent regulation unit intelligently switches between standard operating mode and low-power constant temperature maintenance mode according to the energy storage capacity, thereby optimizing energy consumption while ensuring the core constant temperature function. The monitoring and control and data acquisition unit realizes remote monitoring and data management of temperature, power, power and operating mode, and can remotely adjust system parameters according to strategies or instructions, thereby comprehensively improving the system's controllability, reliability and intelligent management level.

[0021] like Figures 2-3 As shown, it also includes: The formulation rack 3 is movably installed in the temperature-controlled chamber of the box 1. The entire formulation rack 3 can be taken out of the box 1 through the handles on both sides. It is integrated with a formulation temperature sensor to support and fix the container holding the phage formulation liquid, and to monitor the temperature of the formulation liquid in real time through the formulation temperature sensor. Temperature control component 4 is installed inside the cover of the chamber 1 to maintain the temperature inside the chamber 1 at a constant 4℃. The monitoring component 5 is located inside the cover of the enclosure 1 and integrates a temperature sensor for the enclosure 1. It is used to monitor the temperature inside the enclosure 1 in real time and constitutes the execution component of the temperature regulation unit. Its start-up, shutdown and power are controlled by the intelligent control unit. The energy storage component 6, located inside the cover of the housing 1, stores electrical energy and supplies power to the housing 1, forming the main body of the energy storage and power supply unit. It is electrically connected to the temperature control component 4 and provides it with operating power. Simultaneously, it is electrically connected to the solar photovoltaic panel 2 to receive charging. It should be noted that when the housing 1 does not store bacteriophage preparations, the charging scheme for the energy storage component 6 can be flexibly replaced, including: Wired charging interface: A standard wired charging interface (such as Type-C, DC round hole, etc.) is added to the outside of the box (or box cover) to support connection to the mains adapter, vehicle power supply or power bank for fast charging. This solution can serve as a reliable means of replenishing power in the absence of light or in emergency situations, ensuring that reliable power can be obtained to power the box 1 each time it is initially used to store phage preparations. Among them, the wall of the temperature control chamber of box 1 is embedded with ultraviolet sterilization equipment. The ultraviolet sterilization equipment realizes the automatic start and stop control of self-cleaning sterilization and disinfection in box 1 through monitoring and control and data acquisition unit.

[0022] The technical effects of the above-mentioned technical solution are as follows: The integrated formulation temperature sensor design of the formulation rack 3 enables accurate and direct monitoring of the temperature of the formulation liquid inside the container, enhancing the pertinence and reliability of constant temperature control. The cooperation between the temperature regulating component 4 and the monitoring component 5 ensures that the environment inside the chamber 1 can be accurately and stably maintained at the set constant temperature of 4℃, providing the most suitable storage conditions for phage formulations. The integration of the energy storage component 6 into the lid of the chamber 1 optimizes the space layout and improves the integration and portability of the equipment. The ultraviolet sterilization device is embedded in the wall of the temperature control chamber and automatically starts and stops through the monitoring and control unit. The internal environment can be self-cleaned and disinfected without opening the chamber, effectively preventing cross-contamination and significantly improving the aseptic safety guarantee of formulation storage and the automation level of the system.

[0023] The intelligent control unit includes: The data acquisition module is configured to acquire the real-time power generation of the solar power generation unit, the real-time remaining power and charging / discharging current of the energy storage power supply unit, and the real-time temperature gradient inside and outside the temperature control chamber. The energy prediction module has a pre-stored state assessment model containing time variables. It is configured to predict the net energy income and expenditure of the container 1 over a future period based on real-time data acquired by the data acquisition module. The prediction takes into account the sustainability of the current power generation, the estimated power consumption required by the temperature regulation unit to maintain the target temperature, and the current capacity of the energy storage power supply unit. The dynamic decision-making module is configured to generate mode switching instructions based on the real-time remaining power of the energy storage power supply unit and the dynamic results of the net energy income and expenditure forecast provided by the energy prediction module. The specific decision-making logic is as follows: When forecasts indicate that net energy will remain positive for some time and energy storage is sufficient, a switching command is generated to maintain or switch to the standard operating mode. When the forecast shows that the net energy will be close to balance or turn negative in the future, even if the current remaining power is higher than the first preset threshold, a switching command is generated to switch to the low power constant temperature maintenance mode. The intelligent control unit executes the control of the temperature regulation unit and the switching of the working mode of the cabinet 1 according to the switching instructions generated by the dynamic decision module.

[0024] The technical effects of the above-mentioned solution are as follows: The intelligent control unit comprehensively acquires real-time data on power generation, energy storage, and temperature gradient through the data acquisition module, which lays a data foundation for precise control. The energy prediction module dynamically predicts future net energy income and expenditure based on the pre-stored state assessment model, and comprehensively considers the sustainability of power generation, constant temperature power consumption, and energy storage capacity. It can realize the energy management upgrade from passive response to active prediction. The dynamic decision module executes forward-looking dynamic decision-making logic based on real-time power consumption and prediction results. It can intervene in advance when energy is close to balance or about to be in short supply, and actively switch to low power consumption mode. Thus, while ensuring the uninterrupted operation of the core constant temperature function, it improves the energy utilization efficiency and operational reliability of the system under complex or harsh lighting conditions, thereby avoiding the risk of temperature runaway due to energy storage depletion.

[0025] When the dynamic decision-making module switches to the low-power isothermal maintenance mode, it executes an adaptive pulse width modulation temperature control strategy, specifically: In the initial stage of entering low power mode, the temperature regulation unit is controlled to run intermittently by high frequency and initial duty cycle, and the temperature rise rate and drop rate are recorded in real time during each running cycle. Based on the recorded data, a thermal inertia model of the temperature-controlled chamber under the current environmental conditions (based on environmental sensing unit data) is dynamically established through a built-in learning algorithm. Based on the thermal inertia model, the duty cycle and period of PWM control are dynamically adjusted to minimize the effective operating time of the temperature regulation unit while ensuring that the internal temperature of the temperature control chamber does not exceed the preset safe fluctuation range. At the same time, the width of the preset safe fluctuation range is dynamically adjusted according to the remaining power level of the energy storage power supply unit. That is, the lower the power, the wider the allowable short-term fluctuation range is, in order to further reduce energy consumption and prioritize the core temperature zone maintenance capability.

[0026] The technical effects of the above solution are as follows: When the dynamic decision-making module switches to low-power mode, it initiates an adaptive pulse width modulation temperature control strategy. Through high-frequency intermittent operation and data recording, it can quickly learn and model the thermal inertia characteristics of the current environment, enabling control parameters to dynamically match actual heat exchange conditions. Based on the thermal inertia model, it dynamically adjusts the PWM duty cycle and period, minimizing the effective operating time of the temperature regulation unit while strictly constraining temperature fluctuations within a safe range, thus achieving refined energy-saving control. At the same time, it innovatively dynamically correlates the remaining energy storage capacity with the allowable safe temperature fluctuation range. The lower the energy storage capacity, the wider the fluctuation range is appropriately widened. In extremely low energy conditions, it prioritizes the maintenance capability of the core temperature zone by sacrificing some temperature accuracy, thereby maximizing the continuous operating time of the system under energy-constrained conditions, and thus improving the system's environmental adaptability and energy emergency guarantee capability.

[0027] When the dynamic decision-making module switches to the low-power constant temperature maintenance mode, the intelligent control unit executes an adaptive temperature control strategy, specifically: In response to the switching command issued by the dynamic decision module to switch to the low-power constant temperature maintenance mode, it takes over the control of the temperature regulation unit. It has a pre-stored initial PWM parameter library and a safety temperature fluctuation parameter library corresponding to different power levels; Based on real-time data from the environmental sensing unit, the matching initial frequency and duty cycle parameters are called from the initial PWM parameter library to start intermittent control of the temperature regulation unit. During operation, the duty cycle and period of the PWM control parameters are dynamically optimized and adjusted according to the real-time temperature change rate of the temperature control chamber to approximate the minimum required operating time of the temperature regulation unit. Meanwhile, based on the real-time remaining power level of the energy storage power supply unit fed back by the data acquisition module, the corresponding temperature fluctuation range threshold is dynamically called from the safe temperature fluctuation parameter library and set. The parameter library is preset to allow a wider short-term temperature fluctuation range threshold as the power level is lower.

[0028] The technical effects of the above solution are as follows: The intelligent control unit, through a combination of pre-stored parameter library and dynamic optimization, can quickly respond and accurately start low-power control when executing adaptive temperature control strategy. By calling the matching initial PWM parameters based on real-time environmental data, it ensures the adaptability of the control starting point to the current conditions and shortens the adjustment time. By dynamically optimizing the control parameters according to the rate of temperature change, it can autonomously learn and approach the minimum necessary operating time of the temperature regulation unit, thereby optimizing energy consumption while maintaining the preset temperature range. At the same time, it dynamically adjusts the allowable temperature fluctuation range threshold according to the remaining power level, establishing an intelligent trade-off mechanism between power consumption and temperature control accuracy. When energy is tight, it can significantly reduce power consumption by strategically relaxing short-term temperature control accuracy, thereby ensuring the system's core constant temperature maintenance capability under extreme conditions, and thus improving the system's intelligence level, environmental adaptability, and continuous operational reliability.

[0029] The monitoring, control, and data acquisition unit includes: The data collection module is communicatively connected to the temperature regulation unit, energy storage power supply unit, solar power generation unit, environmental sensing unit, and intelligent control unit. It is configured to collect and preprocess (including data cleaning, data unification, etc., since the methods and implementation processes used for preprocessing are existing technologies in the field and are not creative technical solutions of this invention, they will not be described in detail here) monitoring data from each unit in real time. The monitoring data includes, but is not limited to, real-time temperature, humidity, light intensity, multiple electrical parameters of the energy storage unit, power generation parameters of the power unit, and the operating status and internal decision parameters of the intelligent control unit. The instruction forwarding module has multiple preset control strategies. The control strategies are set based on different geographical locations, seasonal modes or task priorities. It is configured to automatically match and activate the corresponding control strategies based on the real-time and historical data analysis results provided by the data collection module, or receive instructions from the remote management platform to generate specific temperature setpoints, working mode switching thresholds or system operating parameters, and forward them to the intelligent control unit. The edge computing module is configured to perform edge computing analysis on the collected historical and real-time data locally, and perform system health diagnosis. The diagnosis includes: identifying the performance degradation trend of the temperature regulation unit, assessing the capacity degradation status of the energy storage power supply unit, judging the abnormal photoelectric conversion efficiency of the solar power generation unit, and predicting the changes in the thermal insulation performance of the enclosure 1, and generating corresponding early warning reports. The data synchronization module is configured to upload processed data, early warning reports, system status, and analysis results from the edge computing module to a remote cloud platform or management terminal via a wireless communication network, and simultaneously receive query and control commands from the remote terminal.

[0030] The technical effects of the above-mentioned technical solution are as follows: The monitoring and control and data acquisition unit, through the data aggregation module, can achieve comprehensive real-time acquisition and standardized preprocessing of multi-source heterogeneous monitoring data of the system, thereby providing a high-quality data foundation for subsequent intelligent decision-making. The command forwarding module, through pre-stored control strategies based on geographical location, season, or task priority, can automatically match or forward remote commands according to data analysis results, enabling the system to adapt to complex and ever-changing external conditions and task requirements, thereby improving the flexibility and automation level of control. The edge computing module performs data analysis and health diagnosis locally, which can promptly identify the performance degradation and abnormal trends of key components and generate early warning reports, thereby enhancing the reliability and service life of the system. The data synchronization module achieves stable data interaction and command synchronization with the remote platform through the wireless network, ensuring the feasibility of remote monitoring, centralized management, and real-time intervention.

[0031] The monitoring, control, and data acquisition unit is further configured as follows: It has a pre-built anomaly level definition library and a corresponding emergency strategy library. The anomaly level definition library divides system anomalies into multiple levels. Each level is defined based on the degree of performance degradation or anomaly information in the early warning report generated by the edge computing module. The emergency strategy library stores specific physical control strategies corresponding to each anomaly level. When the edge computing module generates an early warning report, it performs the following operations: Based on the content of the early warning report, match and determine the level of the current abnormal event from the abnormal level definition library; Based on the determined anomaly level, the corresponding emergency strategy is automatically retrieved from the emergency strategy library and immediately sent to the intelligent control unit for execution via the instruction forwarding module; The data synchronization module synchronizes and uploads the determined anomaly level, the invoked emergency response strategy, and the details of executed instructions as high-level event logs to the remote management platform. Emergency strategies include, but are not limited to: When the performance degradation of the temperature regulation unit is detected to reach a preset level, a compensatory operation command is issued to instruct the intelligent control unit to extend the single operation time of the temperature regulation unit. When the photovoltaic conversion efficiency of the solar power generation unit is abnormally high and reaches the preset level, an energy priority command is issued to force the intelligent control unit to switch the working mode of the cabinet 1 to the low power constant temperature maintenance mode and dynamically reduce the power consumption of other auxiliary units except for the constant temperature function. When the predicted change in the thermal insulation performance of the enclosure 1 reaches a preset level, a thermal insulation enhancement command is issued to instruct the intelligent control unit to increase the temperature monitoring frequency and trigger the temperature adjustment action in the low-power constant temperature maintenance mode in advance to offset the increased heat loss.

[0032] The technical effects of the above-mentioned solution are as follows: The monitoring, control, and data acquisition unit, through a pre-set anomaly level definition library and emergency strategy library, can automatically match and execute graded emergency strategies based on the severity of the warnings from the edge computing module, realizing a rapid closed loop from anomaly monitoring to intelligent handling, thereby improving the system's autonomous response capability and reliability. By calling specific physical control strategies such as compensatory operation, energy priority commands, and heat preservation enhancement commands, it can adaptively adjust operating parameters and modes when the performance of key components deteriorates or environmental conditions worsen, thus effectively maintaining the core constant temperature function in the event of sudden anomalies, ensuring the activity and safety of phage preparations. At the same time, high-level event logs are synchronized to the remote platform in real time, ensuring the transparency and traceability of abnormal situations to the management end, thereby providing key decision support for remote monitoring and manual intervention, and further enhancing the overall management efficiency and operational safety of the system.

[0033] The energy storage power supply unit includes energy storage modules with redundant configurations and multi-channel isolated charge and discharge control circuits, specifically: The energy storage module contains multiple independent parallel energy storage battery packs, each of which is connected to an independent charging and discharging control circuit, and the circuits are electrically isolated from each other. The multi-channel isolated charge and discharge control circuit selectively enables and disconnects the charge and discharge paths of some energy storage battery packs according to the instructions of the intelligent control unit or the supervision, control and data acquisition unit, so as to realize the group maintenance, fault isolation and power output mode switching of the energy storage power supply unit.

[0034] The technical effects of the above-mentioned solution are as follows: By adopting parallel redundant energy storage modules and multi-channel isolated charging and discharging control circuits, the energy storage power supply unit can improve the power supply reliability and operational flexibility of the system. The configuration of multiple independent energy storage battery packs provides hardware redundancy, thereby ensuring continuous power supply capability. The corresponding isolated charging and discharging circuit can realize the switching control of grouped battery packs according to intelligent instructions, thereby supporting online maintenance, fault unit isolation, and dynamic switching of output power mode according to load demand. This design not only optimizes the management efficiency and service life of the energy storage power supply unit, but also enhances the system's adaptability and stability in the face of different operating conditions and emergencies.

[0035] Working Principle: Based on environmental perception data and a built-in energy prediction model, the intelligent control unit dynamically predicts the system's net energy expenditure and determines the operating mode accordingly. When energy is sufficient, it maintains standard constant temperature control. When the predicted energy is close to equilibrium or about to be scarce, it proactively switches to a low-power constant temperature maintenance mode. In this low-power mode, the system uses an adaptive PWM strategy to dynamically optimize the start-stop duty cycle and cycle of the temperature control unit based on a chamber thermal inertia model established through real-time learning. When the power is reduced, the allowable temperature fluctuation range is appropriately widened, thereby minimizing energy consumption while ensuring the active temperature range of the formulation. At the same time, the monitoring, control, and data acquisition unit can realize remote monitoring, data analysis, and strategy distribution. Through edge computing, it can perform system health diagnosis and anomaly warning, thereby automatically triggering corresponding emergency control strategies according to the predefined anomaly level. This invention, through the synergy of forward-looking energy prediction management, adaptive fine-grained temperature control, and remote intelligent monitoring, can improve energy utilization efficiency and temperature control reliability in complex environments such as the field or without a stable power grid, thereby extending the continuous working time of the system under harsh conditions and ensuring the long-term activity stability of the bacteriophage formulation.

[0036] Furthermore, in the cold chain storage and end-to-end transportation of bacteriophage preparations, a key issue exists: the bacteriophage preparation (typically packaged in vials, ampoules, or specialized test tubes) dynamically decreases during medical or research use. This discrete reduction in physical mass directly leads to a non-linear and drastic decrease in the total heat capacity of the temperature-controlled chamber inside the enclosure. Existing constant temperature control systems are typically based on fixed PID parameters or fuzzy control rules, assuming that the load characteristics of the controlled object remain constant. This contradiction between the static model and the dynamic load makes the system highly susceptible to excessive cooling power when only a small amount of preparation remains (i.e., under low heat load conditions), leading to temperature overshoot and even causing the biological preparation to freeze and become inactive.

[0037] To address this issue and avoid the increased cost, space occupation, and reduced reliability (mechanical sensors are easily damaged in bumpy outdoor environments) caused by introducing weight or level sensors, this invention proposes a sensorless real-time thermal load identification mechanism based on the coupling and reverse deduction of electrical and thermodynamic parameters.

[0038] The real-time heat load identification step performed by the intelligent control unit specifically includes the following detailed processing steps: Step 1: Identify the adaptive definition and steady-state triggering of the cycle; The intelligent control unit captures the system within a specific time window of a single cooling action.

[0039] The intelligent control unit monitors the internal temperature of the control chamber in real time, based on feedback from the formulation temperature sensor (integrated into the formulation rack 3). When detected The temperature rises back to the preset cooling start-up threshold (e.g., target constant temperature value) due to environmental heat leakage. +Laptic bias = When the start time is reached, the intelligent control unit issues a control command to drive the energy storage power supply unit to output operating voltage to the temperature regulation unit (preferably a TEC semiconductor refrigeration module or a micro inverter compressor). At this time, the high-precision timer inside the intelligent control unit locks the current moment as the start time. And simultaneously record the internal temperature at this time. .

[0040] Subsequently, the system entered a continuous cooling state. When The temperature drops to a preset cooling stop threshold (e.g., target constant temperature value). -Laptic bias = When the time is reached, the intelligent control unit cuts off the output and locks the current time as the end time. And record the internal temperature at this time. .

[0041] During this process, the intelligent control unit executes an effectiveness prediction logic: if the running cycle duration is... If the time is less than the minimum time threshold (e.g., 30 seconds), it may be a misjudgment caused by temperature fluctuations or electromagnetic interference due to the lid of box 1 not being closed tightly. The system will automatically discard all data for this cycle and will not perform thermal load updates to ensure the robustness of the calculation model.

[0042] Step 2: High-frequency synchronous integration of multidimensional electrical physical quantities; After confirming entry into a valid operating cycle [ After that, the data acquisition module of the intelligent control unit starts a high-speed sampling task.

[0043] In order to accurately measure the total energy input into the thermodynamic system, the data acquisition module measures the real-time voltage at the output of the energy storage power supply unit. and the real-time current in the circuit Perform synchronous sampling. Set the sampling frequency to no less than 100Hz (i.e., sample once every 10 milliseconds) to fully capture the waveform characteristics of the PWM modulation signal or transient fluctuations in the battery voltage.

[0044] The floating-point arithmetic unit of the intelligent control unit performs definite integral operations in the discrete-time domain based on the physical definition of energy. Specifically, the system calculates each sampling point. instantaneous power The power is then accumulated over the entire cycle, calculated using the following formula: ; in, This is the sampling interval. The integral value... It precisely represents the total electrical energy (in joules) released by the energy storage power supply unit and injected into the temperature regulation unit during this cycle.

[0045] To further improve accuracy, the intelligent control unit also incorporates a line loss compensation algorithm. The system pre-stores the equivalent series resistance of PCB traces and conductors. When calculating effective power, the heat loss from the circuit will be automatically deducted. This ensures that the calculations represent the actual effective energy acting on both ends of the temperature control unit.

[0046] Step 3: Dynamic lookup and correction of electrothermal conversion efficiency; Electricity This is not equivalent to the heat removed. To obtain the actual cooling capacity, an electrothermal conversion efficiency constant is introduced. (COP).

[0047] In a preferred embodiment of the present invention It is a three-dimensional mapping table stored in non-volatile memory, and the dimensions of the table include: operating voltage. Ambient temperature difference and efficiency value .

[0048] The intelligent control unit measures the current average ambient temperature based on the environmental sensing unit (whose sensors can be located in monitoring component 5). and average internal temperature of the chamber The operating temperature difference is calculated, and combined with the average operating voltage, the accurate efficiency coefficient under the current operating condition is indexed from the three-dimensional mapping table using bilinear interpolation. .

[0049] Based on this, the system calculates the theoretical total heat transfer during that period: ; Step 4: Dynamic compensation for heat leakage based on the heat conduction model; During the cooling process, the wall layer of chamber 1 is not absolutely insulated, and external heat will continuously penetrate into the interior of the chamber through the vacuum insulation material (in... (Under operating conditions). This heat will offset the cooling effect; if it is not removed, it will lead to errors in the heat load calculation.

[0050] The intelligent control unit uses a built-in heat conduction formula to calculate the total heat leakage during the cycle. : ; In the formula: is the effective heat dissipation surface area of ​​enclosure 1, and is the preset geometric parameter.

[0051] The overall heat transfer coefficient of the wall layer of the box is 1.

[0052] This embodiment introduces The aging correction factor. The edge computing module records the cumulative service time of enclosure 1. And according to the preset material aging curve (e.g., vacuum degree decay curve), periodically check... By making minor upward adjustments (e.g., increasing by 1% annually), full lifecycle identification is achieved.

[0053] Step 5: Reverse derivation of the equivalent heat load coefficient; Based on the law of conservation of energy: the net heat removed from the system = the heat capacity of the controlled object × the temperature change.

[0054] The intelligent control unit substitutes the parameters obtained in the above steps into the core formula to deduce the current equivalent heat load coefficient. : ; This coefficient The physical unit is J / ℃, which is a polymer physical quantity. Numerically, it is equal to the sum of the heat capacity of the remaining phage preparation (located on the preparation rack 3), the heat capacity of the packaging container, the heat capacity of the inner liner of the box 1, and the air, so as to directly reflect the magnitude of the system's thermal inertia.

[0055] Step 6: Model parameter update and PID reconstruction; Calculated Then, the intelligent control unit performs first-order low-pass filtering to eliminate random errors. Subsequently, the system will apply the latest... Compare with the preset full-load heat capacity reference value.

[0056] like A significant decrease indicates that a large amount of the formulation (located on formulation rack 3) has been used. The intelligent control unit immediately performs PID parameter reconstruction: Reduce proportional gain coefficient Reduce the system's response to temperature deviations and prevent overshoot under low load.

[0057] shorten the points time : Accelerate the elimination of steady-state errors.

[0058] Update the feedforward control: recalculate the theoretical power required to maintain a constant temperature based on the new heat capacity.

[0059] Furthermore, the low-margin micro-frequency flexible protection strategy provided in this embodiment includes the following logic control stages: Phase 1: Threshold determination for low margin and high risk status; The intelligent control unit's memory contains a pre-set standard thermal load threshold corresponding to full-load conditions. During system operation, the intelligent control unit continuously monitors and updates the data in real time. .

[0060] The system is set with a risk assessment ratio coefficient. (In this embodiment, 20% is preferred).

[0061] The dynamic decision-making module executes comparison logic in real time: when the calculation yields... When this occurs, the system is determined to be in a low-margin, high-risk state.

[0062] At this point, the thermal buffering capacity of the liquid inside the tank was nearing its physical limit, and any injection of energy at a normal level could lead to temperature runaway. Therefore, the intelligent control unit immediately suspended the standard PID control program and forced the system into micro-frequency injection mode.

[0063] Second stage: Time domain reconstruction of micro-frequency spot firing mode; Once in this mode, the intelligent control unit physically reconstructs the underlying PWM drive signal, the core of which is to change the energy injection method from macroscopic pulses to microscopic particle streams.

[0064] The intelligent control unit forcibly boosts the PWM carrier frequency from the low frequency (e.g., 1Hz, period 1000ms) in the normal mode to a micro frequency band (e.g., 50Hz, period 20ms). The physical significance of this frequency boost is to divide the cooling action per unit time into smaller time slices. Although this slightly increases the losses of the switching transistors, it is crucial for ensuring the safety of biological agents.

[0065] While shortening the cycle, the system establishes a duty cycle hard-limiting model based on load attenuation rate. The intelligent control unit adjusts according to the current... The maximum allowable duty cycle for a single micropulse is calculated using the following formula. : ; in, The base duty cycle cap (e.g., 10%). Minimum bias to maintain the circuit's conduction characteristics.

[0066] For example, when the heat load is only 10% of full load, the system may strictly limit the conduction time of a single pulse to less than 1 millisecond (20ms period × 5% duty cycle). This extremely short, point-to-point power-on ensures that the cold end of the temperature control unit is quickly de-energized as soon as it generates a small amount of cooling energy. Because the power-on time is much shorter than the thermal time constant of the ceramic substrate of the cooling chip, the cooling surface does not have time to reach a deep cryogenic temperature (e.g., -10°C), but is maintained at a mild cryogenic temperature (e.g., 2°C), thus effectively eliminating the cold source conditions for icing in a physically effective manner.

[0067] Phase 3: Flexible protection and thermal relaxation control; In the micro-frequency spot firing mode, the intelligent control unit executes a cyclical control logic of spot firing, relaxation, and detection: Burst firing: When cooling is required, output a series of signals. Restricted micropulse sequences.

[0068] Relaxation: After the pulse sequence ends, the system forcibly inserts a thermal diffusion quiescent period (e.g., 500 ms). During this period, utilizing the natural convection of air within chamber 1 and the thermal conduction properties of the fluid, the cold energy just injected into the small area is evenly diffused throughout the entire formulation vial. This process prevents the cold energy from accumulating in localized areas.

[0069] Flexible feedback: The data acquisition module monitors the rate of temperature change using oversampling. If the rate of temperature drop exceeds the preset safety slope (indicating that even the micropulse energy is too high), the system will immediately trigger the fuse protection, forcibly skipping the pulse output of the next cycle and waiting for thermal equilibrium.

[0070] This embodiment also introduces abnormal operating condition handling logic: If the denominator If the temperature difference is less than the minimum effective temperature difference (e.g., 0.1℃), the system will determine that the current identification is invalid and directly use the previous cycle's data. This prevents numerical overflow caused by division by zero or extremely small values.

[0071] When the environmental sensing unit detects that the lid of box 1 has been opened (due to a sudden change in light sensitivity or activation of a magnetic switch), the system infers that the user may be adding new formulations or ice packs, at which point the thermal load state changes abruptly. The intelligent control unit will immediately exit the micro-frequency spot firing mode and reset. Set the default value to full load and run at standard power until the next stable identification cycle is completed before updating the parameters.

[0072] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply 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 process, method, article, or apparatus.

[0073] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A liquid constant temperature control system for bacteriophage preparations, characterized in that, include: The interior of the box (1) forms a closed temperature-controlled chamber for containing and storing bacteriophage preparations. The walls of the box (1) are filled with vacuum insulation material, and the inner walls of the temperature-controlled chamber are coated with an antibacterial coating to enhance the heat preservation performance and inhibit the growth of microorganisms. A temperature control unit is located inside the housing (1) and is used to adjust and maintain the temperature inside the temperature control chamber at a preset constant temperature. The energy storage power supply unit is used to provide operating power to the temperature regulation unit; A solar power generation unit is installed outside the housing (1) and is used to convert solar energy into electrical energy to charge the energy storage power supply module; The environmental sensing unit includes a light sensor and an ambient temperature sensor located outside the housing (1), and a formulation temperature sensor located inside the temperature control chamber, for real-time monitoring of external light intensity, ambient temperature and formulation liquid temperature. The intelligent control unit is used to control the operation of the temperature regulation unit to maintain a constant temperature, and to control the cabinet (1) to switch between the standard working mode and the low power consumption constant temperature maintenance mode according to the remaining power of the energy storage power supply unit. The monitoring, control and data acquisition unit is used to remotely monitor the real-time temperature of the temperature control chamber, the remaining power and charging / discharging status of the energy storage power supply unit, the working power of the solar power generation unit and the current working mode of the enclosure (1), and to collect, store and upload relevant historical operating data. In addition, the monitoring, control and data acquisition unit also sends control instructions to the intelligent control module according to preset strategies or remote instructions to adjust the temperature setpoint or working mode switching threshold.

2. The phage preparation liquid constant temperature control system according to claim 1, characterized in that, The intelligent control unit includes: The data acquisition module is configured to acquire the real-time power generation of the solar power generation unit, the real-time remaining power and charging / discharging current of the energy storage power supply unit, and the real-time temperature gradient inside and outside the temperature control chamber. The energy prediction module has a pre-stored state assessment model containing time variables. It is configured to predict the net energy income and expenditure of the box (1) in the future period based on the real-time data obtained by the data acquisition module. The prediction integrates the sustainability of the current power generation, the estimated power consumption required by the temperature regulation unit to maintain the target temperature, and the current capacity of the energy storage power supply unit. The dynamic decision-making module is configured to generate mode switching instructions based on the real-time remaining power of the energy storage power supply unit and the dynamic results of the net energy income and expenditure forecast provided by the energy prediction module. The specific decision-making logic is as follows: When forecasts indicate that net energy will remain positive for some time and energy storage is sufficient, a switching command is generated to maintain or switch to the standard operating mode. When the forecast shows that the net energy will be close to balance or turn negative in the future, even if the current remaining power is higher than the first preset threshold, a switching command is generated to switch to the low power constant temperature maintenance mode. The intelligent control unit executes the control of the temperature regulation unit and the switching of the working mode of the cabinet (1) according to the switching instructions generated by the dynamic decision module.

3. The phage preparation liquid constant temperature control system according to claim 2, characterized in that, When the dynamic decision-making module switches to the low-power isothermal maintenance mode, it executes an adaptive pulse width modulation temperature control strategy, specifically: In the initial stage of entering low power mode, the temperature regulation unit is controlled to run intermittently by high frequency and initial duty cycle, and the temperature rise rate and drop rate are recorded in real time during each running cycle. Based on the recorded data, a thermal inertia model of the temperature-controlled chamber under the current environmental conditions is dynamically established through a built-in learning algorithm. Based on the thermal inertia model, the duty cycle and period of PWM control are dynamically adjusted to minimize the effective operating time of the temperature regulation unit while ensuring that the internal temperature of the temperature control chamber does not exceed the preset safe fluctuation range. At the same time, the width of the preset safe fluctuation range is dynamically adjusted according to the remaining power level of the energy storage power supply unit. That is, the lower the power level, the wider the allowable short-term fluctuation range is.

4. The phage preparation liquid constant temperature control system according to claim 2, characterized in that, When the dynamic decision-making module switches to the low-power constant temperature maintenance mode, the intelligent control unit executes an adaptive temperature control strategy, specifically: In response to the switching command issued by the dynamic decision module to switch to the low-power constant temperature maintenance mode, it takes over the control of the temperature regulation unit. It has a pre-stored initial PWM parameter library and a safety temperature fluctuation parameter library corresponding to different power levels; Based on real-time data from the environmental sensing unit, the matching initial frequency and duty cycle parameters are called from the initial PWM parameter library to start intermittent control of the temperature regulation unit. During operation, the duty cycle and period of the PWM control parameters are dynamically optimized and adjusted according to the real-time temperature change rate of the temperature control chamber to approximate the minimum required operating time of the temperature regulation unit. Meanwhile, based on the real-time remaining power level of the energy storage power supply unit fed back by the data acquisition module, the corresponding temperature fluctuation range threshold is dynamically called from the safe temperature fluctuation parameter library and set. The parameter library is preset to allow a wider short-term temperature fluctuation range threshold as the power level is lower.

5. The phage preparation liquid constant temperature control system according to claim 1, characterized in that, The monitoring, control, and data acquisition unit includes: The data collection module is connected to the temperature regulation unit, energy storage power supply unit, solar power generation unit, environmental sensing unit and intelligent control unit, and is configured to collect and preprocess monitoring data from each unit in real time. The instruction forwarding module has multiple preset control strategies. The control strategies are set based on different geographical locations, seasonal modes or task priorities. It is configured to automatically match and activate the corresponding control strategies based on the real-time and historical data analysis results provided by the data collection module, or receive instructions from the remote management platform to generate specific temperature setpoints, working mode switching thresholds or system operating parameters, and forward them to the intelligent control unit. The edge computing module is configured to perform edge computing analysis on the collected historical and real-time data locally and perform system health diagnosis. The diagnosis includes: identifying the performance degradation trend of the temperature regulation unit, assessing the capacity degradation status of the energy storage power supply unit, judging the abnormal photoelectric conversion efficiency of the solar power generation unit, and predicting the change in the insulation performance of the box (1), and generating a corresponding early warning report. The data synchronization module is configured to upload processed data, early warning reports, system status, and analysis results from the edge computing module to a remote cloud platform or management terminal via a wireless communication network, and simultaneously receive query and control commands from the remote terminal.

6. The phage preparation liquid constant temperature control system according to claim 5, characterized in that, The monitoring, control, and data acquisition unit is further configured as follows: It has a pre-built anomaly level definition library and a corresponding emergency strategy library. The anomaly level definition library divides system anomalies into multiple levels. Each level is defined based on the degree of performance degradation or anomaly information in the early warning report generated by the edge computing module. The emergency strategy library stores specific physical control strategies corresponding to each anomaly level. When the edge computing module generates an early warning report, it performs the following operations: Based on the content of the early warning report, match and determine the level of the current abnormal event from the abnormal level definition library; Based on the determined anomaly level, the corresponding emergency strategy is automatically retrieved from the emergency strategy library and immediately sent to the intelligent control unit for execution via the instruction forwarding module; The data synchronization module synchronizes the determined anomaly level, the invoked emergency strategy content, and the details of executed instructions as high-level event logs to the remote management platform.

7. The phage preparation liquid constant temperature control system according to claim 6, characterized in that, Based on the determined anomaly level, the corresponding emergency policy is automatically retrieved from the emergency policy library. Emergency policies include, but are not limited to: When the performance degradation of the temperature regulation unit is detected to reach a preset level, a compensatory operation command is issued to instruct the intelligent control unit to extend the single operation time of the temperature regulation unit. When the photoelectric conversion efficiency of the solar power generation unit is abnormally high and reaches the preset level, an energy priority command is issued to force the intelligent control unit to switch the working mode of the box (1) to the low power constant temperature maintenance mode and dynamically reduce the power consumption of other auxiliary units except for the constant temperature function. When the predicted change in the thermal insulation performance of the enclosure (1) reaches a preset level, a thermal insulation enhancement command is issued to instruct the intelligent control unit to increase the temperature monitoring frequency and trigger the temperature adjustment action in the low-power constant temperature maintenance mode in advance to offset the increased heat loss.

8. The phage preparation liquid constant temperature control system according to claim 1, characterized in that, The energy storage power supply unit includes energy storage modules with redundant configurations and multi-channel isolated charge and discharge control circuits, specifically: The energy storage module contains multiple independent parallel energy storage battery packs, each of which is connected to an independent charging and discharging control circuit, and the circuits are electrically isolated from each other. The multi-channel isolated charge and discharge control circuit selectively enables and disconnects the charge and discharge paths of some energy storage battery packs according to the instructions of the intelligent control unit or the supervision, control and data acquisition unit, so as to realize the group maintenance, fault isolation and power output mode switching of the energy storage power supply unit.

9. A phage preparation liquid constant temperature control system according to claim 3, characterized in that, When the intelligent control unit executes the adaptive pulse width modulation temperature control strategy, it is configured to perform a sensorless real-time thermal load identification step to solve the problem of thermal inertia model inaccuracy caused by the reduction of phage preparation dosage. The real-time heat load identification step specifically includes: during the operating cycle of a single cooling action performed by the temperature regulation unit, the intelligent control unit, based on the principle of energy conservation, uses a built-in dynamic heat capacity calculation formula to derive the equivalent heat load coefficient of the current temperature control chamber in real time. The formula for calculating the dynamic heat capacity is: ； in, The equivalent heat load coefficient is a numerical value that characterizes the total heat capacity of the remaining phage preparation and air in the current temperature-controlled chamber, and is expressed in joules per degree Celsius. and These are the start and end times of the temperature regulation unit in the single cooling action, respectively. and These are the real-time voltage and real-time current values ​​output by the energy storage power supply unit to the temperature regulation unit during the operating cycle, respectively. The preset electrothermal conversion efficiency constant of the temperature regulation unit; This is a definite integral operation performed over time to calculate the total input electrical energy within the operating cycle; The overall heat transfer coefficient of the vacuum insulation material of the wall layer of the box (1) is preset; The effective heat dissipation surface area of ​​the enclosure (1); The average external ambient temperature measured by the ambient temperature sensor during the operating cycle; The average internal temperature of the temperature-controlled chamber measured by the formulation temperature sensor during the operating cycle; It is the absolute value of the temperature change inside the temperature-controlled chamber during the operating cycle; The intelligent control unit will calculate the equivalent heat load coefficient. The thermal inertia model is updated in real time as a core physical parameter.

10. A phage preparation liquid constant temperature control system according to claim 9, characterized in that, The intelligent control unit is also equipped with a low-margin micro-frequency flexible protection strategy, the strategy being as follows: The intelligent control unit is preset with a standard thermal load threshold corresponding to the full-load operating condition. When the equivalent heat load coefficient calculated by the intelligent control unit When the ratio is lower than the preset proportion of the standard heat load threshold, the phage preparation in the current temperature-controlled chamber is determined to be in a low-reserve, high-risk state. At this time, the intelligent control unit automatically and forcibly locks the PWM control mode to the micro-frequency point-fire mode; In the micro-frequency spot firing mode, the intelligent control unit shortens the fundamental period of the PWM control signal to the millisecond level, and based on the equivalent thermal load coefficient... The attenuation ratio linearly reduces the upper limit of the duty cycle of a single pulse. By using a high-frequency and extremely short cold injection method, it prevents the temperature of the phage preparation from falling below the safety limit of activity due to excessive cooling energy in a single pulse under low heat capacity conditions.

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