CO2 cold and heat combined supply energy-saving dehumidification unit for lithium battery

Abstract

The invention relates to the field of dehumidifiers, aims to solve the problems that a traditional scheme lacks dynamic perception and fault pre-judgment and is difficult to adapt to dynamic workshop load fluctuation, and particularly relates to a CO2 cold and heat combined supply energy-saving dehumidification unit for a lithium battery. Advanced perception and quantitative evaluation of production environment load change are realized, high precision and stability of temperature and humidity environment required by lithium battery production are ensured, correlation analysis is performed on dehumidification execution effect and air dynamic change, and quantitative evaluation is performed on system health state, so that positioning early warning signals are generated in a graded manner, active predictive maintenance is realized, and high-precision and high-precision evaluation of temperature and humidity environment required by lithium battery production is realized. And finally, dynamic fluctuation characteristics of workshop air are analyzed and are associated and matched with workshop production activities, and the fluctuation trend of air parameters in a specific time period in the future is predicted, so that the control system has feed-forward regulation capability.

Description

Technical Field

[0001] This invention relates to the field of dehumidifiers, specifically to an energy-saving dehumidifier unit for lithium batteries that uses CO2 combined cooling and heating. Background Technology

[0002] With the increasing precision of lithium-ion battery manufacturing processes, the production environment places extremely stringent requirements on the control of air temperature and humidity. A high-precision constant temperature and humidity environment is a necessary condition to ensure the yield rate and battery consistency of key processes such as electrode coating, drying, and electrolyte injection. Traditionally, such environmental control has mostly adopted independent air handling solutions such as refrigeration dehumidification + electric reheating or rotary dehumidification. The former requires a large amount of electrical energy to reheat to meet the air supply temperature requirements, resulting in significant heat and cold offsetting and extremely low energy efficiency. The latter, although capable of deep dehumidification, consumes a lot of energy, and the rotary equipment is bulky and complex to operate and maintain.

[0003] To improve energy efficiency, some solutions combine heat pumps with solution dehumidification or rotary dehumidification, using the condensation heat of the heat pump to provide heat for the regeneration of the desiccant. However, these systems mostly use conventional Freon refrigerants, which suffer from efficiency degradation and insufficient environmental friendliness under high-temperature regeneration conditions. In recent years, the natural working fluid CO2 has attracted attention due to its extremely low GWP value, excellent high-temperature heat pump performance, and the ability to produce high-temperature hot water in transcritical cycles. Some studies have proposed using it for the coupling of heat pumps and dehumidification.

[0004] However, conventional application solutions often remain at the level of principle or simple integration, lacking deep integration with the dynamic, changeable, and high-precision environmental requirements of lithium battery production workshops. Their control systems often adopt simple PID control based on fixed-point feedback, which cannot effectively cope with the complex load fluctuations caused by production cycle, equipment start-up and shutdown, personnel activities, and seasonal changes in the workshop, making it difficult to balance control accuracy and energy efficiency. At the same time, the system operation status lacks intelligent perception and fault prediction capabilities, and the response to problems such as decreased dehumidification efficiency and performance degradation of key components is delayed, affecting the stability of the production environment and the reliability of equipment operation.

[0005] Therefore, there is an urgent need for a high-efficiency dehumidifier that can deeply integrate advanced thermal cycle and intelligent control technologies, and has adaptive dynamic adjustment, efficient energy management and intelligent diagnostic and early warning capabilities, in order to meet the growing demand for energy saving, precision and reliability in the production environment control of the lithium battery industry. To this end, a solution is proposed. Summary of the Invention

[0006] This invention constructs a dynamic air curve in the workshop and performs dynamic tracking analysis to achieve advanced perception and quantitative assessment of changes in the production environment load, ensuring high-precision stability of the temperature and humidity environment required for lithium battery production. It then correlates the dehumidification effect with dynamic air changes to quantitatively assess the system's health status, generating tiered location warning signals for proactive predictive maintenance and improving the reliability and stability of the entire dehumidifier unit. Finally, by analyzing the fluctuation characteristics of workshop air dynamics and correlating them with workshop production activities, it predicts the air parameter fluctuation trend in specific future periods, enabling the control system to have feedforward adjustment capabilities. This addresses the problem of traditional solutions lacking dynamic perception and fault prediction, making it difficult to adapt to dynamic workshop load fluctuations. Therefore, this invention proposes an energy-saving dehumidifier unit for lithium batteries using a CO2 combined cooling and heating system.

[0007] The objective of this invention can be achieved through the following technical solution: a CO2 combined cooling and heating energy-saving dehumidifier unit for lithium batteries, comprising a dehumidifier unit body, a control center on the dehumidifier unit body, a control panel on the control center, and an air inlet and an air outlet respectively connected to the side of the dehumidifier unit body;

[0008] The control center also includes an energy-saving dehumidifier control system.

[0009] The energy-saving dehumidifier control system includes an environmental sensing module, a dynamic sensing module, a circulating dehumidification control module, a fault diagnosis and protection module, and an interactive management module.

[0010] The environmental sensing module can sense the air environment in the lithium battery workshop and obtain air parameters;

[0011] The dynamic sensing module continuously records air parameters, performs dynamic analysis based on the recorded air parameters, obtains the workshop air dynamic curve, and performs dynamic tracking analysis based on the workshop air dynamic curve to generate dynamic evaluation results.

[0012] The circulating dehumidification control module performs quantitative analysis based on air parameters, generates a dehumidification control signal based on the quantitative analysis results, and controls the dehumidification unit through the control center;

[0013] The fault diagnosis and protection module performs correlation analysis on the air dynamic evaluation results after the dehumidification control signal is executed, obtains the dehumidification implementation efficiency, performs quantitative analysis based on the dehumidification implementation efficiency, and outputs a fault diagnosis early warning signal.

[0014] The interactive management module is used to control the interactive functions of the control center.

[0015] In a preferred embodiment of the present invention, the air parameters collected by the environmental sensing module include air temperature and relative humidity at multiple preset monitoring points in the workshop.

[0016] In a preferred embodiment of the present invention, the method by which the dynamic sensing module acquires the dynamic curve of workshop air is as follows:

[0017] Air parameters are continuously recorded and a time series dataset is constructed using a preset sampling period;

[0018] Curve trend fitting is performed on the temperature and humidity data in the time series dataset to generate dynamic air curves in the workshop.

[0019] In a preferred embodiment of the present invention, the method for the dynamic sensing module to perform dynamic tracking analysis is as follows:

[0020] Mathematical calculations were performed on the dynamic air curves in the workshop to obtain the rate of change curves for temperature and humidity.

[0021] Based on the comparison between the temperature and humidity change rate curve and the preset quasi-change rate threshold library, various anomaly assessment results are generated.

[0022] In a preferred embodiment of the present invention, the quantitative analysis process of the circulating dehumidification control module is as follows:

[0023] S1: Calculate the current absolute humidity based on the temperature and humidity values ​​in the current air parameters;

[0024] S2: Compare the current absolute moisture content with the standard moisture content range required by the lithium battery production process to obtain the moisture content deviation value;

[0025] S3: Based on the moisture content deviation value, calculate the solution circulation volume adjustment command, regeneration heating power adjustment command, and compressor frequency adjustment command of the CO2 refrigeration cycle system in the dehumidifier unit.

[0026] S4: Integrate the adjustment command into a dehumidification control signal.

[0027] In a preferred embodiment of the present invention, the circulating dehumidification control module further incorporates seasonal pattern factors and CO2 concentration data when calculating adjustment instructions;

[0028] The seasonal model factor is determined based on outdoor meteorological parameters and is used to switch the operating logic that prioritizes cooling, heating, or heat recovery.

[0029] By combining CO2 concentration data to correct the system performance coefficient and optimize the compressor frequency regulation command, the system can be ensured to operate efficiently and safely under transcritical cycles.

[0030] In a preferred embodiment of the present invention, the process of correlation analysis performed by the fault diagnosis and protection module includes:

[0031] After the dehumidification control signal is executed, the dynamic curve of the workshop air for the first time period newly generated by the dynamic sensing module is obtained;

[0032] The workshop air dynamic curve of the first time period is compared and analyzed with the workshop air dynamic curve of the second time period before the dehumidification control signal is executed. The ratio of the actual decrease in moisture content per unit time to the expected decrease is calculated to obtain the dehumidification implementation efficiency.

[0033] Establish a multidimensional feature vector that includes dehumidification implementation efficiency, operating current of key components, and vibration data.

[0034] In a preferred embodiment of the present invention, the process by which the fault diagnosis and protection module performs quantitative analysis based on the dehumidification implementation efficiency and outputs a fault diagnosis early warning signal includes:

[0035] When the dehumidification efficiency remains below the first preset efficiency threshold, a primary warning signal for the deterioration of the solution dehumidification system is generated.

[0036] When the dehumidification efficiency is lower than a second preset efficiency threshold, and a specific pattern is identified by multidimensional feature vector analysis, a location warning signal for the corresponding specific faulty component is generated. The specific faulty component includes a solution pump, a regeneration heater, or a CO2 compressor.

[0037] The warning signal shall include at least the fault level, the suspected faulty component, and the recommended troubleshooting measures.

[0038] In a preferred embodiment of the present invention, the dynamic sensing module is also used to dynamically analyze the dynamic curve of the workshop air.

[0039] Extracting periodic fluctuation features from dynamic curves;

[0040] The periodic fluctuation characteristics are matched with known production activities or equipment start-ups and shutdowns within the workshop in terms of time correlation.

[0041] Based on the matching results, the fluctuation trend of air parameters in a specific future period is predicted, and the predicted trend is input into the circulating dehumidification control module in advance.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] 1. This invention collects temperature and humidity parameters from multiple points in the workshop in real time, constructs dynamic air curves in the workshop, and performs dynamic tracking analysis to achieve advanced perception and quantitative assessment of changes in the production environment load. Combined with the accurately calculated moisture content deviation value, it can dynamically generate and optimize the coordinated adjustment commands of solution circulation volume, regeneration heating power, and compressor frequency, so that the CO2 combined cooling and heating system always operates at the optimal operating point, ensuring the high-precision stability of the temperature and humidity environment required for lithium battery production. At the same time, it achieves efficient matching and internal recovery of cooling, heating, and dehumidification energy, significantly reducing the overall energy consumption of the system.

[0044] 2. This invention also correlates the execution effect of the dehumidification control signal with dynamic changes in the air. By calculating the core performance indicator of dehumidification implementation efficiency and combining it with multi-dimensional feature vectors such as the operating current and vibration of key components, it achieves a quantitative assessment of the system's health status. This allows for the generation of location warning signals ranging from system performance degradation to specific component failures, thus changing the traditional maintenance mode that relies on manual periodic inspections or alarms after a failure occurs. It enables proactive predictive maintenance, improves the reliability and stability of the entire dehumidification unit, ensures the continuous safety of the lithium battery production environment, and reduces the risk of unplanned downtime.

[0045] 3. This invention also analyzes the dynamic curve of workshop air, extracts periodic fluctuation characteristics and correlates them with workshop production activities, thereby predicting the fluctuation trend of air parameters in a specific future period, enabling the control system to have feedforward adjustment capabilities, thereby smoothing out expected load fluctuations, avoiding temperature and humidity overshoot or adjustment oscillations caused by response delays, and making environmental control more stable and accurate. Attached Figure Description

[0046] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0047] Figure 1 This is a schematic diagram of the structure of the present invention.

[0048] Figure 2 This is a system block diagram of the present invention;

[0049] Figure 3 This is a system flowchart of the present invention.

[0050] In the diagram: 1. Main body of the dehumidifier unit; 2. Air outlet; 3. Air inlet; 4. Control panel; 5. Control center. Detailed Implementation

[0051] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0052] Example 1: Please refer to Figure 1 - Figure 3 As shown, a CO2 combined cooling and heating energy-saving dehumidifier unit for lithium batteries is provided. The unit consists of a dehumidifier unit body 1, which has an air inlet 3 and an air outlet 2 on its side for processing the air flow in the workshop. The core intelligent control capability of the unit is integrated into the control center 5, which is equipped with a control panel 4 for human-machine interaction.

[0053] Example 2: Please refer to Figure 1 - Figure 3 As shown, a set of energy-saving dehumidifier control system runs in control center 5. This system is not a single control program, but an intelligent system with multiple functional modules working together. This enables the unit to not only passively respond to environmental changes, but also actively sense, predict, optimize and diagnose its own and the environment's operating status, thereby achieving precise, efficient and reliable temperature and humidity control.

[0054] The control system of the energy-saving dehumidifier unit includes the following modules: environmental sensing module, dynamic sensing module, circulating dehumidification control module, fault diagnosis and protection module, and interactive management module.

[0055] The environmental sensing module is used to construct an accurate environmental situation map and is responsible for real-time, distributed collection of raw environmental data within the lithium battery workshop. Specifically, it deploys temperature and humidity sensors at multiple pre-set key process points and spatial areas within the workshop to continuously collect air temperature and relative humidity parameters. This multi-point layout overcomes the limitations of single-point monitoring and can construct an accurate environmental situation map reflecting the overall workshop environment and local micro-environmental differences, providing a reliable data foundation for subsequent advanced control.

[0056] The dynamic perception module is responsible for deep processing and information extraction of the raw data collected by the environmental perception module, specifically including dynamic curve construction, dynamic tracking and anomaly assessment, periodic feature learning and load prediction.

[0057] Dynamic curve construction: The module continuously records air parameters at a preset sampling period (e.g., every minute) to form a time-series dataset. Subsequently, a data fitting algorithm is used to process the temperature and humidity data in this dataset to generate a dynamic air curve that can intuitively reflect the continuous change trend of temperature and humidity in the workshop.

[0058] Dynamic tracking and anomaly assessment: Mathematical calculations, such as differentiation, are performed on the dynamic curves to obtain the rate of change curves for temperature and humidity. This rate curve is then compared in real-time with a pre-set library of quasi-rate of change thresholds that include the allowable range of changes under various normal production disturbances. For example, if the rate of increase in humidity suddenly far exceeds the threshold when the equipment is normally turned on, it may be determined that the workshop access control is malfunctioning or that there is an unexpected source of moisture, thus generating an anomaly assessment result and providing a basis for early intervention in the control module.

[0059] Periodic Feature Learning and Load Forecasting: By analyzing historical dynamic curves, recurring periodic fluctuation characteristics are extracted (such as temperature rise at the start of each morning shift, or a sudden increase in humidity after each batch of specific equipment has finished operating). By associating and matching these characteristics with known production activities or equipment start-up and shutdown schedules provided by the workshop production management system, the module can establish a causal model of environmental load fluctuations. Based on this model, the air parameter fluctuation trend for a specific future period (such as the next production batch) is predicted, and this prediction information is sent in advance to the circulating dehumidification control module to achieve feedforward control.

[0060] The circulating dehumidification control module is the decision-making and command center of the system. It is used to receive real-time data from the environmental sensing module, evaluation results and predicted trends from the dynamic sensing module, and generate specific equipment control commands.

[0061] The specific process is as follows:

[0062] S1 (State Quantization): Based on the current temperature and humidity at the monitoring point, accurately calculate the current absolute humidity, which represents the total amount of moisture in the air.

[0063] S2 (Deviation Calculation): The current absolute moisture content is compared with the standard moisture content range strictly determined according to the lithium battery manufacturing process to calculate the moisture content deviation value. This deviation value accurately quantifies the difference between the current environment and the target environment.

[0064] S3 (Multivariate Collaborative Decision Making): Based on the moisture content deviation value, the module does not perform a single adjustment, but coordinates the adjustment instructions of three key actuators within the computer group:

[0065] Solution circulation rate adjustment command: Controls the flow rate of the dehumidifying solution in the solution dehumidification system;

[0066] Regeneration heating power adjustment command: controls the heat input required for solution regeneration;

[0067] CO2 compressor frequency regulation command: the core power controlling the entire CO2 refrigeration / heat pump cycle.

[0068] S4 (Command Integration and Output): Integrates the above commands into a unified dehumidification control signal, which is then sent to each actuator of the unit through the control center 5.

[0069] In addition, the circulating dehumidification control module incorporates two layers of advanced optimization logic in its basic decision-making:

[0070] Adaptive operating mode: Introducing a seasonal mode factor (determining summer, winter, or transitional season based on outdoor meteorological parameters) to dynamically switch the unit's operating logic. For example, in summer, priority is given to using the cooling capacity of the CO2 cycle for cooling and recovering its high-temperature heat emissions for solution regeneration; in winter, it switches to heat pump mode, providing both workshop heating and regeneration heat source.

[0071] Safety and energy efficiency optimization: Real-time monitoring of CO2 concentration data within the system, combined with the characteristics of transcritical cycles, corrects the system performance coefficient, thereby optimizing the compressor frequency regulation command, and pursuing optimal energy efficiency while ensuring the system operates within a safe pressure range.

[0072] The fault diagnosis and protection module assesses the health status of the unit by analyzing the actual effects of control actions, and realizes predictive maintenance. Specifically, it includes multiple steps such as performance evaluation, multi-dimensional feature analysis, and graded early warning.

[0073] Performance Evaluation: After the circulating dehumidification control module issues and executes the command, the fault diagnosis module obtains the newly generated dynamic curve for the first time period and compares it with the curve for the second time period before the command execution. By calculating the ratio of the actual decrease in moisture content per unit time to the expected decrease based on the control signal, the dehumidification implementation efficiency is obtained. This efficiency directly reflects the overall performance of the unit.

[0074] Multidimensional feature analysis: The module collects and integrates data such as operating current and vibration spectrum of key components (such as solution pump, regeneration heater, CO2 compressor) and constructs a multidimensional feature vector together with dehumidification implementation efficiency.

[0075] Tiered early warning: Primary or location-based early warnings are issued based on performance evaluation results and multidimensional feature analysis results.

[0076] Primary warning: When the dehumidification efficiency continues to be lower than the first preset efficiency threshold, it is determined that the overall system performance has declined, and a primary warning signal is generated, indicating that routine maintenance may be required, such as solution concentration check or filter cleaning.

[0077] Location-based early warning: When efficiency further decreases to a more stringent second preset threshold, and a specific fault mode is identified through multi-dimensional feature vector analysis (such as an abnormal decrease in solution pump current accompanied by specific vibration characteristics), the module can generate a location-based early warning signal, clearly indicating the suspected faulty component (e.g., possible mechanical wear of the solution pump), and providing suggested troubleshooting measures. The early warning information includes at least the fault level, the suspected faulty component, and handling suggestions.

[0078] The interactive management module is responsible for the graphical interface display of Control Panel 4, parameter settings, visualization of operating status, historical data query, and clear prompts for early warning information, enabling managers to easily monitor the unit status and receive maintenance guidance.

[0079] In summary, the deep integration of CO2 transcritical combined cooling and heating technology with an intelligent control system that integrates sensing, analysis, decision-making, and diagnosis not only provides a high-efficiency dehumidifier hardware solution but also constructs a complete intelligent environmental control solution. This system can dynamically adapt to the complex load changes in the lithium battery workshop, proactively adjust to match the production cycle, collaboratively optimize energy consumption and accuracy, and has intelligent diagnostic capabilities to ensure operational reliability, fully meeting the high standards required for the production environment in modern lithium battery manufacturing.

[0080] Thresholds, preset values, preset ranges, etc. are set for result comparison and analysis to determine whether they are good or bad. The value of these thresholds is determined by a combination of large-scale model analysis of sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influences.

[0081] Furthermore, the settings for weighting ratios, influence factors, etc., are based on the magnitude of each parameter's influence on the results. The specific values ​​are allocated to ultimately reflect the impact on the results. The settings for input and storage are also determined by a combination of large-scale model analysis of sample data and human experience. Appropriate adjustments can also be made based on seasonal or rational influence conditions.

[0082] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A lithium battery-powered CO2 combined cooling and heating energy-saving dehumidifier unit, characterized in that, It includes a dehumidifier unit body (1), a control center (5) is provided on the dehumidifier unit body (1), a control panel (4) is provided on the control center (5), and an air inlet (3) and an air outlet (2) are respectively connected to the side of the dehumidifier unit body (1). The control center (5) also includes an energy-saving dehumidifier control system; The energy-saving dehumidifier control system includes an environmental sensing module, a dynamic sensing module, a circulating dehumidification control module, a fault diagnosis and protection module, and an interactive management module. The environmental sensing module can sense the air environment in the lithium battery workshop and obtain air parameters; The dynamic sensing module continuously records air parameters, performs dynamic analysis based on the recorded air parameters, obtains the workshop air dynamic curve, and performs dynamic tracking analysis based on the workshop air dynamic curve to generate dynamic evaluation results. The circulating dehumidification control module performs quantitative analysis based on air parameters, generates a dehumidification control signal based on the quantitative analysis results, and controls the dehumidification unit through the control center (5); The fault diagnosis and protection module performs correlation analysis on the air dynamic evaluation results after the dehumidification control signal is executed, obtains the dehumidification implementation efficiency, performs quantitative analysis based on the dehumidification implementation efficiency, and outputs a fault diagnosis early warning signal. The interactive management module is used to control the interactive functions of the control center.

2. The energy-saving dehumidifier unit for lithium batteries with CO2 combined cooling and heating as described in claim 1, characterized in that, The air parameters collected by the environmental sensing module include air temperature and relative humidity at multiple preset monitoring points within the workshop.

3. The energy-saving dehumidifier unit for lithium batteries with CO2 combined cooling and heating as described in claim 1, characterized in that, The method by which the dynamic sensing module acquires the dynamic curve of workshop air is as follows: Air parameters are continuously recorded and a time series dataset is constructed using a preset sampling period; Curve trend fitting is performed on the temperature and humidity data in the time series dataset to generate dynamic air curves in the workshop.

4. The energy-saving dehumidifier unit for lithium batteries with CO2 combined cooling and heating as described in claim 1, characterized in that, The method by which the dynamic sensing module performs dynamic tracking and analysis is as follows: Mathematical calculations were performed on the dynamic air curves in the workshop to obtain the rate of change curves for temperature and humidity. Based on the comparison between the temperature and humidity change rate curve and the preset quasi-change rate threshold library, various anomaly assessment results are generated.

5. A CO2 combined cooling and heating energy-saving dehumidifier unit for lithium batteries according to claim 1, characterized in that, The quantitative analysis process performed by the circulating dehumidification control module is as follows: S1: Calculate the current absolute humidity based on the temperature and humidity values ​​in the current air parameters; S2: Compare the current absolute moisture content with the standard moisture content range required by the lithium battery production process to obtain the moisture content deviation value; S3: Based on the moisture content deviation value, calculate the solution circulation volume adjustment command, regeneration heating power adjustment command, and compressor frequency adjustment command of the CO2 refrigeration cycle system in the dehumidifier unit. S4: Integrate the adjustment command into a dehumidification control signal.

6. A lithium battery CO2 combined cooling and heating energy-saving dehumidifier unit according to claim 5, characterized in that, When calculating adjustment commands, the circulating dehumidification control module further incorporates seasonal pattern factors and CO2 concentration data. The seasonal model factor is determined based on outdoor meteorological parameters and is used to switch the operating logic that prioritizes cooling, heating, or heat recovery. By combining CO2 concentration data to correct the system performance coefficient and optimize the compressor frequency regulation command, the system can be ensured to operate efficiently and safely under transcritical cycles.

7. A lithium battery CO2 combined cooling and heating energy-saving dehumidifier unit according to claim 1, characterized in that, The process of correlation analysis performed by the fault diagnosis and protection module includes: After the dehumidification control signal is executed, the dynamic curve of the workshop air for the first time period newly generated by the dynamic sensing module is obtained; The workshop air dynamic curve of the first time period is compared and analyzed with the workshop air dynamic curve of the second time period before the dehumidification control signal is executed. The ratio of the actual decrease in moisture content per unit time to the expected decrease is calculated to obtain the dehumidification implementation efficiency. Establish a multidimensional feature vector that includes dehumidification implementation efficiency, operating current of key components, and vibration data.

8. A lithium battery CO2 combined cooling and heating energy-saving dehumidifier unit according to claim 1, characterized in that, The process by which the fault diagnosis and protection module performs quantitative analysis based on the dehumidification efficiency and outputs a fault diagnosis and early warning signal includes: When the dehumidification efficiency remains below the first preset efficiency threshold, a primary warning signal for the deterioration of the solution dehumidification system is generated. When the dehumidification efficiency is lower than a second preset efficiency threshold, and a specific pattern is identified by multidimensional feature vector analysis, a location warning signal for the corresponding specific faulty component is generated. The specific faulty component includes a solution pump, a regeneration heater, or a CO2 compressor. The warning signal shall include at least the fault level, the suspected faulty component, and the recommended troubleshooting measures.

9. A lithium battery CO2 combined cooling and heating energy-saving dehumidifier unit according to claim 1, characterized in that, The dynamic sensing module is also used for dynamic analysis of the workshop air dynamic curve; Extracting periodic fluctuation features from dynamic curves; The periodic fluctuation characteristics are matched with known production activities or equipment start-ups and shutdowns within the workshop in terms of time correlation. Based on the matching results, the fluctuation trend of air parameters in a specific future period is predicted, and the predicted trend is input into the circulating dehumidification control module in advance.

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