Cell culture intelligent temperature control method and system based on historical database comparison

Abstract

The application discloses a kind of cell culture intelligent temperature control method and system based on historical database comparison, it is related to cell culture technical field, the system includes perception layer, control layer, execution layer, circulation layer, power-down safety protection layer.This cell culture intelligent temperature control method and system based on historical database comparison, through historical database dynamic comparison and composite control, the accurate stable regulation and control of temperature in cell culture process is realized, effectively solve the problem of traditional temperature control strategy rigidity, hot field uneven, reheat delay, simultaneously through power-down safety protection mechanism, the continuity and safety of cell culture are guaranteed, combined with cell state linkage control and data iteration optimization, the intelligent level and batch consistency of culture process are improved, without manual intervention throughout, adapt to the core demand of clinical grade cell scale preparation.

Description

Technical Field

[0001] This invention relates to the field of cell culture technology, specifically to an intelligent temperature control method and system for cell culture based on historical database comparison. Background Technology

[0002] Cell culture technology is the core foundation for clinical cell preparation and biomedical research. As a key component of cell culture equipment, the performance of the temperature control system directly determines cell viability, culture efficiency, and batch stability. Currently, traditional temperature control uses a fixed-parameter PID scheme, which cannot dynamically adjust according to changes in ambient temperature. This results in defects such as large temperature overshoot and long recovery time after the door is opened or closed. At the same time, semiconductor contact heat conduction is prone to large local temperature differences, leading to reduced cell viability or cell rupture, and also has low heat conduction efficiency and high energy consumption. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a method and system for intelligent temperature control of cell culture based on historical database comparison, which solves the problems mentioned in the background.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a smart temperature control method for cell culture based on historical database comparison, comprising the following steps:

[0005] S1: Construct a historical temperature control database containing ambient temperature, temperature control parameters, rewarming parameters, and cell safety thresholds;

[0006] S2: After the system is powered on, it collects the real-time ambient temperature and retrieves the optimal initial temperature control parameters from the database; it performs feedforward regulation based on the ambient temperature difference compensation algorithm and combines PID closed-loop control to achieve precise temperature control of the cavity temperature within ±0.1℃.

[0007] S3: When the hatch is opened and closed midway, the emergency mode is triggered to quickly restore the target temperature; the temperature control parameters are adaptively adjusted in conjunction with cell status data.

[0008] S4: When a power outage is detected, the system performs real-time backup and cyclic overwrite of the cavity temperature, ambient temperature, temperature control parameters, thermal resistance, and heat capacity parameters to reduce storage requirements, retaining the complete parameter set one second before the power outage; it calculates the cabin thermal time constant, instantaneous cooling rate, and temperature-time drop curve based on Newton's law of cooling, thereby obtaining the time threshold for the temperature to drop to the safe threshold; under power outage conditions, based on the predicted trend, it starts the output power of the emergency low-power heating component before the temperature drops to the safe threshold, achieving stable cabin temperature and long-term heat preservation; after power is restored, it reads the memory parameters, first maintains the current output power of the emergency heating component, and then dynamically adjusts the output power of the main heating component and the emergency heating component through a linear gradual algorithm, gradually transferring the heating load from the emergency heating component to the main heating component while maintaining temperature stability, and finally shuts down the emergency heating component; it retrieves the rapid rewarming parameters from the database to rapidly rewarm at a safe rate, and smoothly switches to regular temperature control after the temperature reaches the target.

[0009] Furthermore, the ambient temperature difference compensation algorithm is specifically as follows:

[0010] Calculate the ambient temperature deviation:

[0011]

[0012] The compensation coefficient is calculated using linear interpolation.

[0013]

[0014] Dynamically adjust heating and cooling power:

[0015]

[0016]

[0017] Final output total control quantity ;

[0018] in, This represents the ambient temperature deviation value. Real-time ambient temperature; Match the baseline ambient temperature to the database; This is the real-time temperature compensation coefficient; , For adjacent ambient temperature points in the database; , This refers to the compensation coefficient for adjacent temperature points; , To compensate for the real-time heating and cooling power; , The reference heating and cooling power; This is the total output control quantity; This is the feedforward compensation control quantity; This is the PID closed-loop control quantity; the above algorithm is suitable for a wide ambient temperature range of 10℃ to 40℃.

[0019] Furthermore, the specific formula for calculating the temperature drop trend after a power outage is as follows:

[0020] Calculation of thermal time constant:

[0021] in, The measured total thermal resistance of the cabin; Measured total heat capacity of the cabin; The thermal time constant of the cabin;

[0022] Instantaneous cooling rate calculation:

[0023]

[0024] in, After power outage Instantaneous cooling rate; After power outage The cavity temperature is constant; the ambient temperature remains approximately constant for a short period after power failure. ;

[0025] The temperature-time decrease curve satisfies Newton's law of cooling:

[0026]

[0027] in, The temperature inside the cabin at the moment of power failure.

[0028] Furthermore, the cell state linkage regulation is as follows: receiving cell density and culture medium metabolism data, comparing them with historical databases, dynamically adjusting temperature control parameters, using biosensors to collect cell state data in real time, and triggering temperature control and culture medium replacement when metabolic abnormalities are detected.

[0029] Furthermore, the parameters stored after power failure include: real-time chamber temperature, target culture temperature, temperature control parameters before power failure, culture process nodes, and current ambient temperature. The culture process nodes include, but are not limited to, preset temperature adjustment times and medium change times.

[0030] Furthermore, during a power outage and passive temperature lock-in, the emergency low-power heating component has a power of ≤5W, the emergency backup power supply lasts for ≥2 hours, and the cabin temperature is stably maintained at 36℃±0.5℃.

[0031] Furthermore, the reheating rate is ≤2℃ / min, the reheating completion time is ≤3 minutes, and the temperature stabilizes at the target value ±0.1℃ after reheating; the reheating rate is controlled by the following algorithm:

[0032]

[0033] in, This refers to the reheating rate; This is the retemperature coefficient; The target incubation temperature; This represents the real-time temperature of the cavity when power is restored.

[0034] A cell culture intelligent temperature control system based on historical database comparison applies the aforementioned cell culture intelligent temperature control method based on historical database comparison. The system includes a sensing layer, a control layer, an execution layer, a loop layer, and a power failure safety protection layer.

[0035] Furthermore, the sensing layer includes a cavity temperature sensor, a heat source temperature sensor, an ambient temperature sensor, a door switch sensor, and a power failure detection unit.

[0036] The control layer includes a main control module, a historical temperature control database, a PID temperature control module, a PWM speed control module, and a non-volatile power-down memory storage module.

[0037] The execution layer includes a semiconductor cooling chip, a thermally conductive aluminum busbar, and an emergency low-power heating component;

[0038] The circulation layer includes a water circulation cooling system, an internal global airflow circulation system, and an equipment shell with a local insulation layer;

[0039] The power failure safety protection layer includes an emergency backup power supply, an electric thermal insulation and sealing lock, a 36℃ phase change thermal insulation layer, and a cell safety temperature threshold module.

[0040] This invention provides a method and system for intelligent temperature control of cell culture based on historical database comparison, which has the following beneficial effects:

[0041] 1. This intelligent temperature control method and system for cell culture based on historical database comparison achieves precise and stable temperature regulation during cell culture through dynamic comparison and composite control of historical databases. It effectively solves the problems of rigidity, uneven thermal field, and slow rewarming of traditional temperature control strategies. At the same time, the continuity and safety of cell culture are ensured through a power failure safety protection mechanism. Combined with cell state linkage regulation and data iterative optimization, it improves the intelligence level and batch consistency of the culture process. No manual intervention is required throughout the process, which meets the core needs of large-scale clinical cell preparation.

[0042] 2. This intelligent temperature control method and system for cell culture based on historical database comparison employs a real-time cyclical backup mechanism for power failure parameters and a mechanism for retaining key parameters from the previous second. While reducing storage load, it accurately quantifies the cooling trend after a power outage based on Newton's law of cooling, breaking through the limitations of traditional passive insulation. It achieves proactive, predictive emergency heating before temperature drops, and the power restoration process uses a linear gradual power switching algorithm to maintain constant total power and achieve coordinated power adjustment between the two components, enabling seamless transition from emergency heating to main heating. This maintains stable temperature at all times, fundamentally preventing mass cell inactivation caused by power outages, significantly improving the power outage protection capability and long-term insulation reliability of cell culture equipment. It exhibits outstanding non-obviousness and significant technological advancements. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the steps of a cell culture intelligent temperature control method and system based on historical database comparison according to the present invention. Detailed Implementation

[0044] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0045] like Figure 1 As shown, the present invention provides a technical solution: a method and system for intelligent temperature control of cell culture based on historical database comparison. The system hardware consists of a sensing layer, a control layer, an execution layer, a loop layer, and a power-off safety protection layer. The specific steps are as follows:

[0046] Step 1: Building a Historical Temperature Control Database

[0047] The main control module pre-builds a dedicated historical temperature control database for cell culture: by deploying multiple temperature acquisition probes, it collects operating condition data for a continuous gradient ambient temperature of 10℃~40℃, a cell culture temperature of 37℃, and a culture medium storage temperature of 2℃~8℃; it records the optimal PID parameters, heating and cooling power, PWM airflow speed control parameters, emergency door rewarming parameters, power failure memory backup parameters, chamber thermal resistance and heat capacity parameters, temperature drop trend prediction model parameters, emergency low-power heating matching parameters, and cell safety temperature thresholds under each operating condition; it stores these parameters as key-value pairs of ambient temperature-temperature control parameters-rewarming parameters-memory backup parameters-thermal property parameters-safety thresholds, providing data support for dynamic control and power failure protection;

[0048] Step 2: System power-on initialization and optimal parameter retrieval

[0049] The cell culture process is started, and the temperature control system completes power-on self-test; the ambient temperature sensor in the sensing layer collects the current ambient temperature in real time and transmits it to the main control module; the main control module matches and retrieves the real-time ambient temperature with the historical database, and directly calls up the optimal initial temperature control parameters for the corresponding working condition, without needing to debug the PID from scratch; the main control module synchronously drives the semiconductor cooling chip, water circulation cooling system and internal airflow circulation system to start according to the parameters, and enters the normal temperature control preparation state.

[0050] Step 3: Dynamic difference compensation and control of ambient temperature

[0051] The main control module executes an ambient temperature difference compensation algorithm to counteract ambient temperature fluctuations. The specific formula and parameters are explained below:

[0052] Calculate the ambient temperature deviation:

[0053]

[0054] In the formula, This is the ambient temperature deviation value, which is the difference between the real-time ambient temperature and the database reference temperature. A positive value indicates an increase in ambient temperature, and a negative value indicates a decrease in ambient temperature. This refers to the real-time ambient temperature, i.e., the value collected and output by the ambient temperature sensor in real time. Match the baseline ambient temperature to the database, which is the pre-stored temperature value in the historical database that is closest to the real-time ambient temperature;

[0055] The compensation coefficient is calculated using linear interpolation.

[0056]

[0057] In the formula, This is a real-time temperature compensation coefficient used to dynamically correct heating and cooling output power. , For adjacent ambient temperature points in the database, That is, the smallest and closest in the historical database The pre-stored temperature, That is, the greatest and closest in the historical database The pre-stored temperature; , These are the compensation coefficients for adjacent temperature points, and both are parameters pre-stored in the historical database;

[0058] Dynamically adjust heating and cooling power:

[0059]

[0060]

[0061] in, , To compensate for the real-time heating and cooling power, that is, the power value finally output to the heating and cooling actuators; , Based on the heating and cooling power, For historical database The corresponding initial heating power, For historical database The corresponding initial cooling power;

[0062] Final output total control quantity ;

[0063] in, This is the total output control quantity, i.e., the final control signal driving the execution layer; It is the feedforward compensation control quantity, that is, the predictive control signal output by the difference compensation algorithm; The PID closed-loop control quantity is the feedback control signal of the PID module based on the actual temperature of the cavity. Through the above algorithm, stable temperature control is achieved in a wide ambient temperature range of 10℃ to 40℃, thus offsetting the interference of ambient temperature fluctuations in advance.

[0064] Step 4: Multi-sensor fusion for precise temperature control

[0065] The cavity temperature sensor and heat source temperature sensor collect the real-time cavity temperature at a high frequency of 10 times / second and transmit it to the main control module. The main control module transmits the total control quantity to the execution layer and the circulation layer. The semiconductor cooling chip transfers heat evenly through the heat-conducting aluminum busbar, and the internal airflow circulation system purifies the entire area to eliminate local temperature differences. Combined with PID closed-loop real-time power calibration, the cavity temperature is stably controlled within ±0.1℃ of the target value, and the heat conduction efficiency is improved by 30% compared with the traditional solution.

[0066] Step 5: Emergency rapid temperature recovery after hatch opening and closing

[0067] When the hatch switch sensor detects a hatch opening or closing action midway and the cavity temperature deviates from the target value by ≥0.5℃, the main control module automatically triggers the hatch emergency rewarming mode. The main control module retrieves the hatch-specific emergency PID parameters from the database, driving the semiconductor cooling chip to full power output, the airflow circulation system to run at 100% PWM duty cycle, and the water circulation system to work at full load. Multiple sensors perform real-time closed-loop calibration to quickly restore the temperature to the target value ±0.1℃, without overshoot or local temperature difference.

[0068] Step 6: Cell state-linked temperature control adaptive regulation

[0069] The main control module communicates with the centrifugation module to receive cell density data collected by the microscope camera and culture medium metabolism data collected by the color camera; it compares the real-time data with cell growth-temperature control correlation data in the historical database and dynamically fine-tunes the temperature control parameters based on cell metabolism rate and culture medium pH changes; when the culture medium metabolism is abnormal, it links with the temperature control system to maintain temperature stability and triggers a culture medium replacement command.

[0070] Step 7: Power-down transient detection and key parameter memorization

[0071] The process involves real-time backup and cyclic overwriting of required memory parameters, reducing storage capacity while retaining critical parameters up to one second before power failure. The main control module writes the memory parameters backed up one second before power failure—real-time chamber temperature, target culture temperature, temperature control parameters before power failure, culture process nodes, and current ambient temperature—into a non-volatile power-loss memory storage module. Simultaneously, it cuts off power to high-power components (semiconductor cooling chip, water circulation system, main fan), retaining only emergency power to the power-loss memory module, temperature sensor, electric insulation sealing lock, and emergency low-power heating component control unit.

[0072] Step 8: Temperature trend prediction and emergency heating temperature control during power outage

[0073] Based on the core parameters stored one second before the power failure, the main control module calculates the rate of temperature decrease in the cavity after the power failure and the time threshold for the temperature to drop to the safe threshold according to Newton's law of cooling. The specific calculation process and formula are as follows:

[0074] Thermal time constant calculation: The thermal time constant of the chamber is the product of thermal resistance and heat capacity, characterizing the rate at which the chamber cools down.

[0075]

[0076] in, Measured total thermal resistance of the cabin (sum of thermal resistance of shell, insulation and sealing); Measured total heat capacity of the chamber (sum of heat capacity of chamber, culture medium, and consumables); The thermal time constant of the cabin;

[0077] Instantaneous cooling rate calculation: Based on Newton's law of cooling, the heat dissipation rate of the cavity after power failure is directly proportional to the temperature difference. The formula for the instantaneous cooling rate is:

[0078]

[0079] in, After power outage Instantaneous cooling rate; After power outage The cavity temperature is measured at a specific moment; the application of Newton's law of cooling is based on a reasonable approximation: the power outage occurs within a short time window, and the ambient temperature changes slowly, therefore the ambient temperature measured one second before the power outage is used. This is considered a constant ambient temperature, thus meeting the applicable condition of Newton's law of cooling, "the ambient temperature is constant," at which point the cabin temperature... From the initial temperature (Indoor temperature at the moment of power failure) to ambient temperature Exponential decay;

[0080] The negative sign indicates that the temperature decreases over time; the larger the absolute value of the rate, the faster the temperature drops.

[0081] The temperature-time decrease curve satisfies Newton's law of cooling: Integrating the formula for the instantaneous cooling rate, we obtain the complete curve of the cavity temperature changing with time after power failure.

[0082]

[0083] in, The cabin temperature at the moment of power failure;

[0084] This curve is an exponential decay curve, which accurately describes the temperature change trend throughout the entire period after a power outage;

[0085] Calculation of the time threshold for falling to the safety threshold: Let Substituting into the temperature-time curve formula, the critical time for the temperature to drop to the safe threshold is derived:

[0086]

[0087] in, Cellular safety temperature threshold;

[0088] The main control module compares the current time in real time. With the time threshold to drop to the safety threshold ,when ( To anticipate potential temperature drops below the safety threshold (as determined by pre-stored data in the database), the emergency low-power heating components are immediately activated. The output power is matched to the cooling rate curve to actively replenish the heat lost from the cavity. The electric insulation and sealing lock automatically closes to block convective heat dissipation. The active heating and passive temperature locking work together to complete heat compensation before the temperature falls below the safety threshold, ensuring a stable cabin temperature over a long period. The emergency backup power supply only drives the heating components at the predicted point, significantly reducing energy consumption and extending the insulation time.

[0089] The electric thermal insulation and sealing lock automatically closes after receiving a power failure signal, sealing the gaps in the cabin door to block convective heat dissipation. In conjunction with the active output of the emergency low-power heating component, heat is replenished in time before the temperature drops to the safe threshold, so that the cabin temperature is stably maintained within the cell safety range. At the same time, the energy consumption of emergency power supply is greatly reduced, and the insulation time is extended.

[0090] Step 9: Rapid temperature recovery based on database after power restoration

[0091] Upon detecting the restoration of main power, the power failure detection unit immediately sends a power restoration signal to the main control module. The main control module reads all parameters from the power failure memory module before the power failure, retrieves the rapid temperature recovery parameters matching the current temperature, ambient temperature, and target temperature from the historical database, and executes the temperature recovery algorithm. The formula and parameter descriptions are as follows:

[0092]

[0093] in, This refers to the rewarming rate, i.e., the safe rewarming rate for cells, with an upper limit of ≤2℃ / min; This is the retemperature coefficient, which is pre-stored in the historical database and ranges from 0.6 to 0.9. The target culture temperature is the preset standard temperature for cell culture, such as 37°C. Real-time temperature of the cavity upon power restoration, i.e., the cavity temperature collected by the temperature sensor at the instant of power restoration;

[0094] Once the target temperature is ±0.1℃, the power gradual switching mechanism is activated to switch from the emergency low-power heating component to the main heating component while maintaining temperature stability. To ensure temperature stability, the total heating power remains constant during the gradual switching process, equal to either the initial emergency heating power or the target main heating power (whichever is greater). The specific formula is as follows:

[0095]

[0096] The power of the main heating element increases linearly:

[0097] (when hour)

[0098] (when hour)

[0099] The main control module calculates the real-time power at a frequency of 100ms / time, driving the main heating component power to increase linearly from 0 to... The power of the emergency heating component is from The change linearly decreases to 0; during the gradual change, fine-tuning is achieved through a closed-loop PID controller. (Fluctuation range ≤ ±5%), ensuring the cavity temperature remains stable within the target value ±0.1℃; when When the emergency heating component power drops to 0 and shuts off, the main heating component power stabilizes at [value missing]. Switching complete;

[0100] The main control module calculates the real-time power according to the above formula, drives the main heating component (semiconductor cooling chip heating mode) to output power gradually from 80% to 100% of the rated power, and the power of the emergency low-power heating component is gradually reduced; the airflow circulation system maintains a 70% PWM duty cycle, and multiple temperature sensors collect data at a high frequency of 10 times / second to correct the power output in real time and prevent temperature overshoot.

[0101] Step 10: Smooth transition from temperature target achievement to conventional temperature control

[0102] When the temperature at all temperature measuring points in the cavity rises back to the target value ±0.1℃, the main control module determines that the rewarming is complete; the system smoothly switches from the rapid rewarming mode to the conventional intelligent steady-state temperature control mode, restoring the normal control path of steps 3-6; thus automatically restoring the culture process nodes before the power outage, without manual intervention or process interruption throughout the entire process;

[0103] Step 11: Anomaly Warning and Database Iterative Optimization

[0104] When the system experiences temperature exceeding the limit, sensor failure, power failure, or abnormal rewarming during operation, the main control module triggers an audible and visual alarm, locks the equipment status, and records the abnormal information. After a single batch of culture is completed, all data on temperature control, power failure, rewarming, and cell status are archived to the historical database. The main control module analyzes the new data, iteratively optimizes the temperature control and rewarming parameters, and improves the temperature control accuracy and safety of subsequent batches.

[0105] Based on the above description, this invention achieves precise and stable temperature control during cell culture through dynamic comparison and composite control of historical databases, effectively solving the problems of rigidity, uneven thermal field, and slow rewarming of traditional temperature control strategies. At the same time, the continuity and safety of cell culture are ensured through a power failure safety protection mechanism. Combined with cell state linkage control and data iteration optimization, the level of intelligence and batch consistency of the culture process are improved. No manual intervention is required throughout the process, which meets the core needs of large-scale clinical cell preparation.

[0106] Employing a real-time cyclic backup mechanism for power failure parameters and a retention mechanism for key parameters from the previous second, this system reduces storage load while accurately quantifying the cooling trend after a power outage based on Newton's law of cooling. This overcomes the limitations of traditional passive insulation, enabling proactive, predictive emergency heating before temperature drops. Furthermore, the power restoration process utilizes a linear, gradual power switching algorithm to maintain constant total power and achieve coordinated power adjustment between the two components, ensuring a seamless transition from emergency heating to main heating. This maintains stable temperature at all times, fundamentally preventing mass cell inactivation due to power outages. It significantly enhances the power outage protection capabilities and long-term insulation reliability of cell culture equipment, demonstrating remarkable non-obviousness and significant technological advancements.

[0107] The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the forms disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A method for intelligent temperature control of cell culture based on historical database comparison, characterized in that: Includes the following steps: S1: Construct a historical temperature control database containing ambient temperature, temperature control parameters, rewarming parameters, and cell safety thresholds; S2: After the system is powered on, it collects the real-time ambient temperature and retrieves the optimal initial temperature control parameters from the database; it performs feedforward regulation based on the ambient temperature difference compensation algorithm and combines PID closed-loop control to achieve precise temperature control of the cavity temperature within ±0.1℃. S3: When the hatch is opened and closed midway, the emergency mode is triggered to quickly restore the target temperature; the temperature control parameters are adaptively adjusted in conjunction with cell status data. S4: When a power outage is detected, the system performs real-time backup and cyclic overwrite of the cavity temperature, ambient temperature, temperature control parameters, thermal resistance, and heat capacity parameters to reduce storage requirements, retaining the complete parameter set one second before the power outage; it calculates the cabin thermal time constant, instantaneous cooling rate, and temperature-time drop curve based on Newton's law of cooling, thereby obtaining the time threshold for the temperature to drop to the safe threshold; under power outage conditions, based on the predicted trend, it starts the output power of the emergency low-power heating component before the temperature drops to the safe threshold, achieving stable cabin temperature and long-term heat preservation; after power is restored, it reads the memory parameters, first maintains the current output power of the emergency heating component, and then dynamically adjusts the output power of the main heating component and the emergency heating component through a linear gradual algorithm, gradually transferring the heating load from the emergency heating component to the main heating component while maintaining temperature stability, and finally shuts down the emergency heating component; it retrieves the rapid rewarming parameters from the database to rapidly rewarm at a safe rate, and smoothly switches to regular temperature control after the temperature reaches the target.

2. The intelligent temperature control method for cell culture based on historical database comparison according to claim 1, characterized in that: The specific algorithm for compensating for the difference in ambient temperature is as follows: Calculate the ambient temperature deviation: The compensation coefficient is calculated using linear interpolation. Dynamically adjust heating and cooling power: Final output total control quantity ; in, This represents the ambient temperature deviation value. Real-time ambient temperature; Match the baseline ambient temperature to the database; This is the real-time temperature compensation coefficient; , For adjacent ambient temperature points in the database; , This refers to the compensation coefficient for adjacent temperature points; , To compensate for the real-time heating and cooling power; , The reference heating and cooling power; This is the total output control quantity; This is the feedforward compensation control quantity; This is the PID closed-loop control quantity; the above algorithm is suitable for a wide ambient temperature range of 10℃ to 40℃.

3. A method of intelligent temperature control for cell culture based on historical database comparison as claimed in claim 1, wherein: The specific formula for calculating the temperature drop trend after a power outage is as follows: Thermal time constant calculation: wherein, measured total thermal resistance of the tank body; measured total heat capacity of the tank body; thermal time constant of the tank body; Instantaneous cooling rate calculation: wherein, after power-off time instant cooling rate; after power-off time instant chamber temperature; the ambient temperature is approximately constant for a short time after power-off ; The temperature-time decrease curve satisfies Newton's law of cooling: wherein, Tc is the cabin temperature at the instant of power-off.

4. The method of claim 1, wherein: Cell state linkage regulation is as follows: receiving cell density and culture medium metabolism data, comparing them with historical databases, dynamically adjusting temperature control parameters, using biosensors to collect cell state data in real time, and triggering temperature control and culture medium replacement when metabolic abnormalities are detected.

5. The method of claim 1, wherein: The parameters that are stored after power failure include: real-time chamber temperature, target culture temperature, temperature control parameters before power failure, culture process nodes, and current ambient temperature. Culture process nodes include, but are not limited to, preset temperature adjustment times and medium change times.

6. The intelligent temperature control method for cell culture based on historical database comparison according to claim 1, characterized in that: When the power is cut off and the temperature is passively locked, the emergency low-power heating component has a power of ≤5W, the emergency backup power supply lasts for ≥2 hours, and the cabin temperature is stably maintained at 36℃±0.5℃.

7. The intelligent temperature control method for cell culture based on historical database comparison according to claim 1, characterized in that: The reheating rate is ≤2℃ / min, the reheating completion time is ≤3 minutes, and the temperature stabilizes at the target value ±0.1℃ after reheating. The reheating rate is controlled by the following algorithm: wherein, is the rewarming rate; is the rewarming coefficient; is the target incubation temperature; is the real-time temperature of the chamber at the time of rewiring.

8. A cell culture intelligent temperature control system based on historical database comparison, which applies the cell culture intelligent temperature control method based on historical database comparison in any one of claims 1-7. The system includes a perception layer, a control layer, an execution layer, a loop layer, and a power failure safety protection layer.

9. A cell culture intelligent temperature control system based on historical database comparison according to claim 8, characterized in that: The sensing layer includes a cavity temperature sensor, a heat source temperature sensor, an ambient temperature sensor, a door switch sensor, and a power failure detection unit. The control layer includes a main control module, a historical temperature control database, a PID temperature control module, a PWM speed control module, and a non-volatile power-down memory storage module. The execution layer includes a semiconductor cooling chip, a thermally conductive aluminum busbar, and an emergency low-power heating component; The circulation layer includes a water circulation cooling system, an internal global airflow circulation system, and an equipment shell with a local insulation layer; The power failure safety protection layer includes an emergency backup power supply, an electric thermal insulation and sealing lock, a 36℃ phase change thermal insulation layer, and a cell safety temperature threshold module.

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