Energy storage container ambient temperature intelligent adjustment method and system

Abstract

The application discloses an energy storage container environment temperature intelligent adjustment method and system, and relates to the technical field of energy storage container thermal management. The method comprises the following steps: collecting environment parameters and energy storage container internal state parameters; judging whether the ventilation safety condition is met according to the environment parameters; if yes, comparing the environment temperature with the seasonal threshold value to determine the target air inlet area; comparing the box temperature, the battery module temperature and the temperature control threshold value to determine the target air inlet amount and control the opening and closing angle of the electric louver; and controlling the operation power of the air suction fan according to the target air inlet amount to introduce external air for temperature adjustment. The application realizes the collaborative control of ventilation safety judgment, seasonal adaptation air inlet and precise matching of battery heat demand, and reduces the thermal management energy consumption. The container and the environment temperature difference are the core temperature control logic of the scheme, and the season is only an application description of the scene. If the temperature difference meets the preset condition, the ventilation openings on the side and the bottom can be opened at the same time.

Description

Technical Field

[0001] This invention relates to the field of thermal management technology for energy storage containers, specifically to a method and system for intelligent adjustment of ambient temperature in energy storage containers. Background Technology

[0002] Energy storage containers are core equipment for mitigating fluctuations in renewable energy generation and improving grid stability. Lithium iron phosphate (LFP) batteries, with their long cycle life, high safety, and significant cost advantages, have become the mainstream battery choice for energy storage containers. However, LFP batteries have significant thermal drawbacks: usable capacity drops sharply at low temperatures and lithium dendrites easily form during charging; increased internal resistance at low charge levels leads to localized overheating; high temperatures inside the container accelerate electrolyte decomposition in summer; and ventilation and heat dissipation exacerbate low-temperature capacity decay in winter. The performance of the thermal management system directly determines battery safety, lifespan, and the economics of the energy storage system.

[0003] Existing thermal management technologies for energy storage containers still have many shortcomings. In terms of monitoring dimensions, current technologies lack monitoring of environmental safety parameters such as dust concentration and rainfall, and only focus on the average temperature inside the container without considering the actual operating temperature of the batteries. This leads to indiscriminate ventilation activation during dusty or rainy weather, causing equipment damage. Furthermore, the ventilation temperature control is disconnected from the battery's thermal requirements, exacerbating the uniform degradation of lithium iron phosphate batteries. Regarding ventilation structure, traditional layouts are simplistic, with no seasonal adaptability to the air intake area. In summer, excessively high intake temperatures result in low cooling efficiency, while in winter, excessively low bottom intake temperatures exacerbate low-temperature capacity degradation of the batteries. Therefore, there is an urgent need for an intelligent environmental temperature adjustment method for energy storage containers that integrates comprehensive monitoring dimensions, combines environmental safety parameters with the actual battery temperature, and features a seasonally adaptable ventilation structure. This method would maximize the utilization efficiency of natural ventilation and reduce thermal management energy consumption while ensuring safe battery operation. Summary of the Invention

[0004] This invention addresses the technical problems in existing technologies, such as insufficient monitoring dimensions, lack of environmental safety parameter monitoring, failure to control ventilation based on actual battery temperature, and a single ventilation structure layout with no seasonal adaptability of the air intake area. It provides a method and system for intelligent adjustment of the ambient temperature of an energy storage container.

[0005] The technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0006] In a first aspect, the present invention provides a method for intelligent adjustment of ambient temperature in an energy storage container, comprising:

[0007] Collect environmental parameters and internal state parameters of the energy storage container. The environmental parameters include at least ambient temperature, ambient humidity, and dust concentration. The internal state parameters include at least the internal temperature of the container and the battery module temperature.

[0008] The dust concentration in the environmental parameters is compared with a preset safety threshold to determine whether the ventilation safety conditions are met.

[0009] If the ventilation safety conditions are met, the target air intake area of ​​the energy storage container is determined by comparing the ambient temperature with the preset seasonal threshold. The target air intake area is either the bottom air intake area or the side wall air intake area.

[0010] The target air intake volume is determined by comparing the internal temperature of the box, the battery module temperature, and the preset temperature control threshold, and the opening and closing angle of the electric louvers corresponding to the target air intake area is controlled according to the target air intake volume.

[0011] The operating power of the suction fan is controlled according to the target air intake volume to introduce ambient air into the energy storage container for temperature adjustment.

[0012] Secondly, the present invention provides an intelligent temperature adjustment system for an energy storage container, comprising:

[0013] The parameter acquisition module is used to collect environmental parameters and internal state parameters of the energy storage container. The environmental parameters include at least ambient temperature, ambient humidity, and dust concentration, and the internal state parameters include at least the internal temperature and battery module temperature.

[0014] The ventilation safety judgment module is used to compare the dust concentration in the environmental parameters with a preset safety threshold to determine whether the ventilation safety conditions are met.

[0015] The air intake area determination module is used to determine the target air intake area of ​​the energy storage container by comparing the ambient temperature with a preset seasonal threshold if ventilation safety conditions are met. The target air intake area is either the bottom air intake area or the side wall air intake area.

[0016] The air intake and louver control module is used to compare the internal temperature of the box, the battery module temperature and the preset temperature control threshold to determine the target air intake, and control the opening and closing angle of the electric louvers corresponding to the target air intake area according to the target air intake.

[0017] The fan control module is used to control the operating power of the suction fan according to the target air intake volume, so as to introduce external ambient air into the energy storage container for temperature adjustment.

[0018] The beneficial effects of this invention are:

[0019] Compared to existing technologies, this invention first avoids equipment damage caused by blindly activating ventilation during dusty or rainy weather by collecting dust concentration data and comparing it with safety thresholds. Secondly, it adaptively selects bottom or side wall air intake areas based on a comparison of ambient temperature and seasonal thresholds, utilizing the lower temperature air at the bottom in summer to improve cooling efficiency and reducing heat loss in winter. Thirdly, it determines the target air intake volume and controls the opening angle of the electric louvers and fan power by comparing the internal temperature and battery module temperature with temperature control thresholds, ensuring precise matching between ventilation and temperature control and the actual thermal needs of the battery, suppressing localized overheating and uniform battery degradation. This invention solves the problems of insufficient monitoring dimensions, lack of environmental safety parameter monitoring, failure to control ventilation based on actual battery temperature, and the single ventilation structure layout and lack of seasonal adaptability of air intake areas in existing technologies, reducing thermal management energy consumption while ensuring safe battery operation. Attached Figure Description

[0020] Figure 1 A flowchart illustrating an intelligent adjustment method for ambient temperature of an energy storage container provided by the present invention;

[0021] Figure 2 This is a schematic diagram of the structure of an intelligent ambient temperature adjustment system for an energy storage container provided by the present invention.

[0022] In the attached diagram, the components represented by each number are as follows:

[0023] Parameter acquisition module 11, ventilation safety judgment module 12, air intake area determination module 13, air intake volume and louver control module 14, fan control module 15. Detailed Implementation

[0024] Example 1, as Figure 1 As shown, this embodiment of the invention provides a method for intelligent adjustment of ambient temperature in an energy storage container, including:

[0025] S10: Collect environmental parameters and internal state parameters of the energy storage container, wherein the environmental parameters include at least ambient temperature, ambient humidity, and dust concentration, and the internal state parameters include at least the internal temperature of the container and the battery module temperature;

[0026] First, environmental parameters and internal state parameters of the energy storage container are collected. Energy storage containers are typically deployed outdoors, facing complex climatic environments such as high temperatures, high humidity, dust storms, and heavy rain. The internal battery systems generate a significant amount of heat during charging and discharging. Improper ventilation and temperature control can lead to increased thermal management energy consumption, or even battery performance degradation and safety accidents. Therefore, it is necessary to simultaneously sense both external environmental conditions and the internal battery operating status to provide a comprehensive basis for ventilation control decisions.

[0027] Specifically, environmental parameters include at least ambient temperature, ambient humidity, and dust concentration. Ambient temperature is used to determine whether the outside air has cooling or heat-preserving potential, serving as the basis for deciding whether to activate ventilation and selecting air intake areas. Ambient humidity is used to assess the risk of condensation in high-humidity environments, triggering dehumidification equipment when necessary. Dust concentration serves as a core threshold for ventilation safety; when dust levels exceed the limit, ventilation is forcibly shut off to prevent dust from entering the container and adhering to the surfaces of battery modules and electrical equipment, causing reduced heat dissipation efficiency or electrical short circuits. Internal status parameters include at least the container's internal temperature and the battery module temperature. The container's internal temperature reflects the overall ambient temperature level inside the container, while the battery module temperature reflects the actual operating temperature of the batteries; both together constitute the core control targets for ventilation and temperature control.

[0028] Specifically, the starting point of this step is to break through the limitation of traditional solutions that only monitor the temperature inside the chamber. By synchronously collecting multiple parameters from both the environmental and internal perspectives, it provides complete data support for subsequent ventilation safety assessments, selection of air intake areas, and adjustment of air intake volume.

[0029] Specifically, the execution steps of S10 include collecting environmental parameters and internal state parameters of the energy storage container, including:

[0030] By deploying temperature and humidity sensors, dust concentration sensors, and water immersion sensors on the outside of the energy storage container, ambient temperature, ambient humidity, dust concentration, and rainfall conditions are collected in real time.

[0031] Temperature and humidity sensors are installed inside the energy storage container to collect the temperature and humidity inside the container in real time.

[0032] Battery module temperatures are collected by reusing the battery management system inside the energy storage container.

[0033] First, ambient temperature, humidity, dust concentration, and rainfall are collected in real time using temperature and humidity sensors, dust concentration sensors, and water immersion sensors deployed on the exterior of the energy storage container. The exterior of the energy storage container is typically located in an open area, directly exposed to the natural environment. The external temperature and humidity sensors detect the ambient air temperature and humidity to determine if the outside air has cooling or heat preservation potential. The dust concentration sensors monitor the concentration of suspended particulate matter in the air; if the dust concentration exceeds the standard, ventilation should be forcibly shut off even if the temperature and humidity meet ventilation requirements to prevent dust from entering the container and damaging the equipment. The water immersion sensors detect rainfall, promptly identifying the risk of water accumulation during heavy rain and preventing rainwater from flowing back into the container through the ventilation openings. Optionally, all of the above sensors are deployed on the windward side of the container to ensure that the collected parameters accurately reflect the external air conditions about to enter the container.

[0034] Meanwhile, temperature and humidity sensors deployed inside the energy storage container collect real-time data on the internal temperature and humidity. The interior of the energy storage container is a relatively enclosed space, and the battery system generates heat during charging and discharging, leading to uneven temperature distribution. Optionally, internal temperature and humidity sensors are deployed in key locations such as the upper and lower parts of the container and around the battery clusters to sense the overall temperature and humidity levels inside the container, reflecting the actual control effect of the ventilation system on the internal environment. The internal temperature is compared with a preset temperature control threshold to determine whether the current ventilation and cooling effect meets the battery's operational requirements. It also works in conjunction with the battery module temperature to calculate the air intake, ensuring that the ventilation and temperature control match the actual internal environment. Internal humidity monitoring assesses the risk of condensation. When the internal humidity is too high, dehumidification equipment is activated to prevent condensation on the battery module surface from causing short circuits.

[0035] In addition, the battery module temperature needs to be collected by reusing the battery management system (BMS) inside the energy storage container. The BMS is the core monitoring unit of the energy storage container, which collects the actual operating temperature of each battery module in real time through NTC temperature sensors distributed on the surface of each cell in the battery module. Specifically, this step directly reuses the battery module temperature data already collected in the BMS, without the need for additional sensors, which reduces hardware costs and ensures the accuracy and real-time nature of the temperature data.

[0036] The obtained battery module temperature is the core basis for ventilation and temperature control. Compared with the average temperature inside the box, the battery module temperature can more directly reflect the thermal state of the battery, avoiding the situation where the temperature inside the box meets the standard but the battery is overheated in some areas.

[0037] In summary, through the collaborative data collection of the aforementioned multi-source sensors, a three-dimensional sensing system encompassing the environment, the internal environment, and the battery has been formed, providing a comprehensive data foundation for subsequent ventilation control.

[0038] S20: Compare the dust concentration in the environmental parameters with the preset safety threshold to determine whether the ventilation safety conditions are met;

[0039] Secondly, the dust concentration in the environmental parameters is compared with the preset safety threshold to determine whether the ventilation safety conditions are met. The dust concentration in the environmental parameters is a value collected in real time by dust concentration sensors deployed on the outside of the energy storage container. It is used to characterize the content of suspended particulate matter in the outside air, and the unit is micrograms per cubic meter. If the dust concentration is too high, it means that there is a large amount of sand, smoke or pollutants in the air. At this time, opening the ventilation will bring the dust into the container and adhere to the surface of battery modules, electrical equipment and liquid cooling pipes, causing a decrease in heat dissipation efficiency, a decrease in insulation performance and even the risk of electrical short circuit. It is necessary to forcibly shut down the ventilation system and close all motorized louvers. If the dust concentration is too low, it means that the outside air is clean and meets the air quality requirements for ventilation. Ventilation can be opened normally according to temperature and humidity conditions.

[0040] The real-time dust concentration is compared with a preset safety threshold, which is a critical concentration value used to determine whether the external air quality is suitable for ventilation. It represents the maximum allowable dust concentration for ventilation; exceeding this value indicates unsafe ventilation. This safety threshold is set comprehensively based on the dustproof requirements of the equipment inside the energy storage container and the environmental characteristics of the sensor placement location. For example, it can be set to 200 micrograms per cubic meter. When the real-time dust concentration is greater than or equal to 200 micrograms per cubic meter, the ventilation safety conditions are not met, and a forced shutdown command is executed. When the dust concentration is less than 200 micrograms per cubic meter, the ventilation safety conditions are met, and further ventilation control based on temperature and humidity conditions is allowed.

[0041] By determining the above-mentioned safe dust concentration thresholds, equipment damage caused by blindly turning on ventilation in dusty weather or highly polluted environments can be effectively avoided.

[0042] S30: If the ventilation safety conditions are met, the target air intake area of ​​the energy storage container is determined by comparing the ambient temperature with the preset seasonal threshold, wherein the target air intake area is the bottom air intake area or the side wall air intake area.

[0043] If ventilation safety conditions are not met, all motorized louvers and exhaust fans will be immediately shut off, and the air conditioning, heating, or dehumidification systems will be activated to perform temperature control compensation, forming a complete intelligent control closed loop.

[0044] Specifically, if the dust concentration is below the preset safety threshold, it indicates that the external air quality is clean and meets the air quality requirements for ventilation, allowing the ventilation system to be activated. At this point, further assessment of rainfall is needed, using immersion sensors deployed on the exterior of the energy storage container to detect rainwater accumulation in real time. If rainwater is detected, the ventilation safety conditions are deemed unmet, and all motorized louvers and exhaust fans are forcibly shut down to prevent rainwater from flowing back into the container through the ventilation openings. If no rainwater is detected, the ventilation safety conditions are deemed fully met, allowing the system to proceed to the next step of seasonal threshold assessment.

[0045] Specifically, if ventilation safety conditions are met, before determining the target air intake area of ​​the energy storage container by comparing the ambient temperature with a preset seasonal threshold, the process further includes:

[0046] If the dust concentration in the environmental parameters exceeds the preset safety threshold, or if rainwater is detected in the environmental parameters, then the ventilation safety conditions are not met.

[0047] Generate and execute a forced shutdown command, which controls all motorized louvers and exhaust fans to shut down.

[0048] Specifically, if the dust concentration in the environmental parameters exceeds the preset safety threshold, or if no rain is detected in the environmental parameters, the ventilation safety conditions are deemed not met. A dust concentration exceeding the safety threshold indicates the presence of a large amount of dust or pollutants in the outside air. Enabling ventilation in this situation would bring dust into the container, where it would adhere to the battery modules and electrical equipment surfaces, causing reduced heat dissipation efficiency or a risk of electrical short circuits. A detected rain indicates rainfall outside. Enabling ventilation in this situation would cause rainwater to backflow into the container through the vents, causing the equipment to become damp or damaged. In both of these scenarios, the basic safety conditions for ventilation are not met.

[0049] In addition, the assessment of ventilation safety conditions also includes the following situations:

[0050] For example, when the ambient temperature is greater than 30 degrees Celsius and the ambient humidity is greater than 75% relative humidity, or when the ambient humidity alone is greater than 80% relative humidity, it is determined to be a high temperature and high humidity environment. At this time, opening the ventilation will cause the hot and humid air outside to enter the container, forming condensation on the surface of the battery module and electrical equipment, which may cause a short circuit risk. Therefore, it is determined that the ventilation safety conditions are not met, and all electric louvers and exhaust fans are forcibly shut down, while the air conditioning system is started simultaneously for dehumidification and cooling.

[0051] For example, when the internal temperature of the container is greater than or equal to 38 degrees Celsius, it indicates that the external ambient air temperature is high or the battery generates a lot of heat. Natural ventilation alone is not enough to meet the cooling requirements. Continuing ventilation may bring high-temperature air into the container and aggravate heat accumulation. Therefore, it is determined that the ventilation safety conditions are not met, and all electric louvers and exhaust fans are forcibly shut down, and the liquid cooling system or air conditioning system is switched to provide forced cooling.

[0052] For example, when the battery module temperature collected by the battery management system is less than or equal to 15 degrees Celsius, it indicates that the battery is in a low temperature state. Continuing ventilation will introduce cold air into the box and aggravate the low-temperature capacity decay of the battery. Therefore, it is determined that the ventilation safety conditions are not met, and all electric louvers and exhaust fans are forcibly shut down. Simultaneously, the liquid cooling heating mode or air conditioning heating mode is switched to preheat the battery to ensure that the battery operates within a suitable temperature range.

[0053] The aforementioned safety thresholds are set based on the optimal operating temperature range of lithium iron phosphate batteries and the environmental adaptability requirements of energy storage containers. When all safety conditions are met—that is, dust concentration is below the safety threshold, no rain is detected, the environment is not hot and humid, the internal temperature is below 38 degrees Celsius, and the battery module temperature is above 15 degrees Celsius—the system determines that the ventilation safety conditions are fully met, allowing the system to proceed to the next step of seasonal threshold determination and airflow adjustment.

[0054] It should be noted that the safety threshold of prohibiting ventilation when the battery module temperature is less than or equal to 15 degrees Celsius applies to ventilation control under normal operating conditions. The cooling strategy of the liquid cooling system is not subject to this restriction. The liquid cooling system is the core guarantee for heat generation and cooling of the battery throughout its entire life cycle, and the liquid cooling system can independently activate the cooling mode according to the battery temperature.

[0055] When ventilation safety conditions are not met, a forced shutdown command is generated and executed. This command controls all motorized louvers and suction fans to shut down. Specifically, the bottom and side wall motorized louvers are driven to close to a 0-degree angle via the power control line, while the suction fans stop operating. This forced shutdown operation effectively blocks the entry of outside air into the container during sandstorms or heavy rain, preventing damage to internal equipment from dust and rainwater and ensuring the operational reliability of the energy storage container in harsh environments. Once the dust concentration drops below the safety threshold and the rain subsides, the system re-enters the normal ventilation judgment process.

[0056] Furthermore, when ventilation safety conditions are fully met, the target air intake area of ​​the energy storage container is determined by comparing the ambient temperature with a preset seasonal threshold. The energy storage container is equipped with distributed motorized louvered vents at the bottom and side walls. In summer, the bottom air intake area can be cooled using the low-temperature air from the bottom, while in winter, the side wall air intake area can be insulated using the relatively low-temperature air from the side walls.

[0057] Because outdoor ambient temperature distribution varies significantly in different seasons, the air temperature at the bottom is significantly lower than that at the side walls in summer, while the air temperature at the side walls is relatively higher than that at the bottom in winter. If a single fixed air intake area is used, high-temperature air may be drawn in during summer, resulting in low cooling efficiency, while excessively low-temperature air may be drawn in during winter, exacerbating the low-temperature capacity decay of the battery. Therefore, it is necessary to adaptively switch the air intake area according to the ambient temperature to maximize the utilization efficiency of natural ventilation and ensure that the energy storage container can achieve efficient and safe temperature control under different seasonal conditions.

[0058] Specifically, the target air intake area of ​​the energy storage container is determined by comparing the ambient temperature with a preset seasonal threshold, including:

[0059] When the ambient temperature is greater than or equal to the first temperature threshold, it is determined to be summer mode, and the bottom air intake area is determined as the target air intake area.

[0060] When the ambient temperature is less than or equal to the second temperature threshold, it is determined to be winter mode, and the side wall air intake area is determined as the target air intake area.

[0061] Wherein, the first temperature threshold is greater than the second temperature threshold.

[0062] Specifically, when the ambient temperature is greater than or equal to the first temperature threshold, it is determined to be in summer mode, and the bottom air intake area is identified as the target air intake area. In high-temperature summer environments, the bottom of outdoor containers is away from direct sunlight and close to the ground, so the air temperature around it is 3 to 5 degrees Celsius lower than that of the side walls and top. Utilizing the relatively cool air at the bottom for air intake can effectively reduce the temperature of the air entering the container, improve the efficiency of natural ventilation and cooling, reduce the frequency of start-up and operating power of liquid cooling or air conditioning systems, and thus reduce thermal management energy consumption. The bottom air intake area corresponds to the motorized louvered vents located at the bottom of the container. When opened, external air enters from the bottom and flows upward along the bottom of the battery cluster, forming a "bottom in, top out" natural convection airflow path in conjunction with the top exhaust.

[0063] Furthermore, when the ambient temperature is less than or equal to the second temperature threshold, the system is designated as winter mode, and the side wall air intake area is identified as the target air intake area. In low-temperature winter environments, the bottom of the container is well-sealed but remains cold. If air enters from the bottom, the cold air directly contacts the bottom of the battery module, exacerbating the battery's low-temperature capacity decay and increasing preheating energy consumption. However, due to the heat dissipation from internal equipment, the air temperature around the container's side walls is 2 to 4 degrees Celsius higher than the bottom. Utilizing the relatively cooler but warmer air from the side walls for air intake reduces the direct impact of cold air on the battery, minimizing heat loss. The side wall air intake area corresponds to the electrically operated louvered vents located on the container's side walls. When opened, external air enters from the side walls, forming a "side-in, top-out" convection airflow path in conjunction with the top exhaust. Simultaneously, the side suction fans operate at low power as needed to assist in increasing airflow.

[0064] The first and second temperature thresholds are critical temperature values ​​used to distinguish between summer and winter modes, representing the seasonal dividing point at which the energy storage container should switch to bottom or side-wall air intake. Specifically, the first and second temperature thresholds are set comprehensively based on the climate characteristics of the energy storage container's deployment location and the optimal operating temperature range of the lithium iron phosphate battery. The first temperature threshold is higher than the second temperature threshold, and the two form a transition range.

[0065] For example, the first temperature threshold can be set to 30 degrees Celsius, and the second temperature threshold can be set to 10 degrees Celsius. When the ambient temperature is between 10 degrees Celsius and 30 degrees Celsius, it is determined to be the spring and autumn transition mode. The electric louvered ventilation openings at the bottom and side walls can be opened simultaneously. The opening angle of each area can be adjusted according to the temperature gradient inside the box to achieve mixed air intake adjustment, taking into account both natural ventilation efficiency and temperature stability.

[0066] In summary, by segmenting the seasonal thresholds mentioned above, the air intake area of ​​the energy storage container can be adaptively switched according to the ambient temperature to optimize the seasonal adaptability of natural ventilation.

[0067] S40: Based on the comparison between the internal temperature of the box, the battery module temperature and the preset temperature control threshold, determine the target air intake volume, and control the opening and closing angle of the electric louvers corresponding to the target air intake area according to the target air intake volume;

[0068] Furthermore, after determining the target air intake area, it is necessary to compare the internal temperature of the enclosure, the battery module temperature, and the preset temperature control threshold to determine the target air intake volume. The target air intake volume is the external airflow required to meet the current battery heat dissipation needs; it represents the amount of airflow the ventilation system should provide while ensuring the battery operating temperature remains within its optimal operating range. This target air intake volume is not a fixed value but a real-time demand value dynamically calculated based on the internal ambient temperature and the actual battery operating temperature.

[0069] The container interior temperature reflects the overall thermal state of the container's internal environment, while the battery module temperature directly reflects the heat generated by the battery itself. Preset temperature control thresholds include a target temperature inside the container and a target battery temperature. The former assesses whether the container's internal environment exceeds the limit, while the latter determines whether there is a risk of localized overheating of the battery. By comparing the real-time collected container interior temperature with the target temperature, and the battery module temperature with the target battery temperature, the deviation between the current temperature and the target temperature can be quantified, and the target airflow required to eliminate this deviation can be calculated comprehensively.

[0070] Specifically, the target air intake volume is determined by comparing the internal temperature of the enclosure, the battery module temperature, and a preset temperature control threshold, including:

[0071] The first temperature deviation between the internal temperature of the box and the preset target internal temperature, and the second temperature deviation between the battery module temperature and the preset target battery temperature are obtained.

[0072] The first temperature deviation and the second temperature deviation are weighted and fused to obtain the comprehensive temperature deviation, wherein the sum of the weighting coefficients of the first temperature deviation and the second temperature deviation is 1.

[0073] The comprehensive temperature deviation is input into a preset fuzzy controller, and the initial air intake volume is obtained through fuzzy inference.

[0074] Based on the temperature difference between the current ambient temperature and the temperature inside the chamber, the initial air intake volume is corrected using a feedforward compensation algorithm to obtain the target air intake volume.

[0075] First, the first temperature deviation between the container's internal temperature and the preset target internal temperature, and the second temperature deviation between the battery module temperature and the preset target battery temperature are obtained. The target internal temperature is the ideal temperature value inside the container set according to the optimal operating environment of lithium iron phosphate batteries, for example, it can be set to 25 degrees Celsius. The target battery temperature is the ideal operating temperature of the battery module itself during charging and discharging, for example, it can be set to 30 degrees Celsius. The first temperature deviation equals the internal temperature minus the target internal temperature; a positive value indicates that the internal temperature is too high and needs cooling, while a negative value indicates that the internal temperature is too low and needs insulation. The second temperature deviation equals the battery module temperature minus the target battery temperature; a positive value indicates that the battery is at risk of overheating, while a negative value indicates that the battery temperature is too low. These two deviations reflect the current temperature control requirements from the environmental and battery perspectives, respectively.

[0076] Next, the first temperature deviation and the second temperature deviation are weighted and fused to obtain the comprehensive temperature deviation. The sum of the weighting coefficients for the first and second temperature deviations is 1. The specific values ​​can be set according to the actual operating scenario of the energy storage container. For example, since the battery body temperature directly determines battery safety and lifespan, the weighting coefficient for the first temperature deviation can be set to 0.3, and the weighting coefficient for the second temperature deviation to 0.7, making the comprehensive temperature deviation more focused on the battery module temperature. Specifically, the weighted fusion calculation method is: the comprehensive temperature deviation equals the first temperature deviation multiplied by the first weighting coefficient plus the second temperature deviation multiplied by the second weighting coefficient.

[0077] For example, assuming the internal temperature is 28 degrees Celsius and the target internal temperature is 25 degrees Celsius, the first temperature deviation is 3 degrees Celsius. Assuming the battery module temperature is 35 degrees Celsius and the target battery temperature is 30 degrees Celsius, the second temperature deviation is 5 degrees Celsius. Setting the first weighting coefficient to 0.3 and the second weighting coefficient to 0.7, the overall temperature deviation equals 3 multiplied by 0.3 plus 5 multiplied by 0.7, which equals 0.9 plus 3.5, or 4.4 degrees Celsius. This overall temperature deviation reflects the combined temperature control requirements of the internal environment and the battery itself, with the battery module temperature deviation contributing a significant proportion, making subsequent airflow calculations prioritize addressing battery overheating issues.

[0078] The calculated comprehensive temperature deviation is then input into a pre-defined fuzzy controller, and the initial air intake volume is obtained through fuzzy inference. The fuzzy controller is a nonlinear controller based on fuzzy logic, which internally includes a fuzzification interface, a knowledge base, an inference engine, and a defuzzification interface. Specifically, the comprehensive temperature deviation is first quantized into several fuzzy subsets, and corresponding membership functions are designed. Then, inference is performed based on a pre-defined fuzzy rule base. Finally, the fuzzy output is converted into a precise initial air intake volume using the centroid method or area bisector method. The advantage of this fuzzy controller is that it does not require a precise system mathematical model and can adapt to the nonlinear and time-varying characteristics of energy storage container thermal systems.

[0079] For example, taking a comprehensive temperature deviation with a domain range of -10°C to 10°C as an example, the initial air intake volume has a domain range of 0 cubic meters per hour to 5000 cubic meters per hour. First, the comprehensive temperature deviation is quantified into five fuzzy subsets: negative large (NB), negative small (NS), zero (ZO), positive small (PS), and positive large (PB). The membership function for each fuzzy subset adopts a triangular function, where negative large corresponds to a deviation range of -10 to -4, with a peak at -7; negative small corresponds to a deviation range of -6 to 0, with a peak at -3; zero corresponds to a deviation range of -2 to 2, with a peak at 0; positive small corresponds to a deviation range of 0 to 6, with a peak at 3; and positive large corresponds to a deviation range of 4 to 10, with a peak at 7. The fuzzy rule base is designed as follows: if the overall temperature deviation is negative large, the initial air intake is negative large (corresponding to air intake 0); if it is negative small, the initial air intake is negative small (corresponding to air intake 1000); if it is zero, the initial air intake is zero (corresponding to air intake 2000); if it is positive small, the initial air intake is positive small (corresponding to air intake 3000); if it is positive large, the initial air intake is positive large (corresponding to air intake 5000).

[0080] In the specific reasoning process, the comprehensive temperature deviation value is input, its membership degree on each fuzzy subset is calculated, the corresponding rule is activated, and the fuzzy subsets output by each rule are obtained. Finally, the centroid method is used for defuzzification, and the fuzzy subsets output by each rule are weighted and averaged according to their membership degrees to obtain a precise value as the initial air intake. For example, when the comprehensive temperature deviation is 4 degrees Celsius, its membership degree on the smaller positive subset is 0.3, and its membership degree on the larger positive subset is 0.7. Then the initial air intake is equal to 3000 multiplied by 0.3 plus 5000 multiplied by 0.7, which is 900 plus 3500, equal to 4400 cubic meters per hour.

[0081] Through the above fuzzy reasoning process, the comprehensive temperature deviation can be mapped to the initial air intake, which can adapt to the nonlinear and time-varying characteristics of the thermal system of energy storage containers.

[0082] Furthermore, based on the temperature difference between the current ambient temperature and the internal temperature, the initial air intake volume is corrected using a feedforward compensation algorithm to obtain the target air intake volume. The temperature difference is equal to the ambient temperature minus the internal temperature, reflecting the cooling potential of the external air. When the ambient temperature is significantly lower than the internal temperature, the temperature difference is large, and even a small air intake volume can produce a significant cooling effect. In this case, feedforward compensation can appropriately reduce the air intake volume to avoid excessive cooling. When the ambient temperature is close to or higher than the internal temperature, the temperature difference is small or negative, and the cooling effect of the air intake is limited. In this case, feedforward compensation can appropriately increase the air intake volume or prompt the activation of the liquid cooling system.

[0083] Specifically, based on the temperature difference between the current ambient temperature and the internal temperature of the chamber, the initial air intake is corrected using a feedforward compensation algorithm to obtain the target air intake, including:

[0084] Obtain the current ambient temperature and the temperature inside the chamber, and calculate the temperature difference between the ambient temperature and the temperature inside the chamber;

[0085] Obtain a preset feedforward compensation coefficient, wherein the feedforward compensation coefficient is dynamically adjusted according to the rate of change of ambient temperature, and the feedforward compensation coefficient is increased when the rate of change of ambient temperature is greater than a preset rate of change threshold.

[0086] The feedforward compensation amount is calculated by multiplying the temperature difference value by the feedforward compensation coefficient.

[0087] The target air intake volume is obtained by adding the initial air intake volume to the feedforward compensation amount.

[0088] First, obtain the current ambient temperature and the container's internal temperature, and calculate the temperature difference between them. Specifically, the temperature difference equals the ambient temperature minus the container's internal temperature. When the ambient temperature is lower than the container's internal temperature, the temperature difference is negative, indicating that the outside air temperature is lower than the container's internal temperature. In this case, the incoming air has a cooling effect, and the larger the absolute value of the temperature difference, the more significant the cooling effect. When the ambient temperature is higher than the container's internal temperature, the temperature difference is positive, indicating that the outside air temperature is higher than the container's internal temperature. In this case, the incoming air will actually heat the container, and the air intake should be reduced or stopped. This temperature difference is a key indicator for measuring the cooling potential of the outside air.

[0089] Secondly, a preset feedforward compensation coefficient is obtained. This coefficient is dynamically adjusted based on the rate of change of ambient temperature. When the rate of change of ambient temperature exceeds a preset threshold, the feedforward compensation coefficient is increased. Specifically, the rate of change of ambient temperature reflects the drastic change in external temperature. For example, in the afternoon of summer, the ambient temperature may rise rapidly. If the air intake is not adjusted in time, the internal temperature may rise accordingly. The preset threshold for the rate of change can be set to 2 degrees Celsius every 10 minutes. The initial value of the feedforward compensation coefficient can be set to 10 cubic meters per hour per degree Celsius. When the rate of change of ambient temperature exceeds the threshold, it indicates that the external temperature is in a rapid change phase, requiring stronger compensation. Therefore, the feedforward compensation coefficient is increased, for example, to 20 cubic meters per hour per degree Celsius.

[0090] Then, the feedforward compensation amount is calculated by multiplying the temperature difference value by the feedforward compensation coefficient. Specifically, the feedforward compensation amount equals the temperature difference value multiplied by the feedforward compensation coefficient. When the temperature difference value is negative, the feedforward compensation amount is negative, indicating that the air intake needs to be reduced to avoid excessive cooling; when the temperature difference value is positive, the feedforward compensation amount is positive, indicating that the outside air is heating the container, and the air intake needs to be further increased to force heat dissipation or to prompt the activation of the liquid cooling system.

[0091] Finally, the initial intake air volume is added to the feedforward compensation to obtain the target intake air volume. Through the above feedforward compensation, the target intake air volume not only responds to the current temperature deviation, but also predicts the impact of external environmental changes on the ventilation effect.

[0092] For example, with an initial air intake of 3000 cubic meters per hour, a temperature difference of -5 degrees Celsius, and a feedforward compensation coefficient of 10, the feedforward compensation is -50, and the target air intake is 2950 cubic meters per hour. The air intake should be appropriately reduced to avoid excessive cooling. If the ambient temperature rises rapidly, the feedforward compensation coefficient increases to 20, and the temperature difference is +3 degrees Celsius. The feedforward compensation is then +60, and the target air intake is 3060 cubic meters per hour. The air intake should be appropriately increased to cope with the rising temperature trend. Through this feedforward compensation algorithm, the air intake adjustment has the ability to predict changes in the external environment, making ventilation and temperature control more proactive and precise.

[0093] Furthermore, the opening and closing angles of the motorized louvers corresponding to the target air intake area are controlled based on the determined target air intake volume. There is a non-linear mapping relationship between the opening and closing angle of the motorized louvers and the air intake volume; the larger the opening and closing angle, the larger the cross-sectional area of ​​the air intake channel, resulting in a larger air intake volume for the same fan power; conversely, the smaller the opening and closing angle, the smaller the air intake volume. By converting the target air intake volume into the target opening and closing angle of each motorized louver, and adjusting multiple motorized louvers corresponding to the bottom air intake area or the side wall air intake area to that angle, precise adjustment of the air intake volume can be achieved, making the actual air intake volume approach the target air intake volume, thereby accurately matching the battery's heat dissipation requirements.

[0094] Specifically, controlling the opening and closing angle of the motorized louvers corresponding to the target air intake area based on the target air intake volume includes:

[0095] Obtain the nonlinear mapping relationship between the opening and closing angles of multiple motorized louvers corresponding to the target air intake area and the air intake volume;

[0096] Using the target air intake volume as the control objective and the opening and closing angles of each motorized louver as the decision variables, an air intake volume allocation optimization model is constructed, wherein the air intake volume allocation optimization model takes minimizing the difference in the opening and closing angles of each motorized louver as the optimization objective.

[0097] The air intake distribution optimization model is solved using the Lagrange multiplier method to determine the target opening and closing angle of each electric louver.

[0098] Each motorized louver is individually controlled to adjust to its corresponding target opening angle, thereby creating distributed air intake.

[0099] First, the nonlinear mapping relationship between the opening angles of multiple motorized louvers corresponding to the target air intake area and the air intake volume is obtained. Taking the bottom air intake area as an example, this area is usually equipped with multiple motorized louvered vents, such as four motorized louvers evenly distributed at the bottom of the container. The opening angle of each motorized louver can be continuously adjusted within the range of 0 degrees to 90 degrees, with 0 degrees corresponding to complete closure and 90 degrees corresponding to complete opening. Due to the influence of factors such as the shape of the motorized louvers, their installation position, and airflow resistance, the relationship between the opening angle and the air intake volume is not a simple linear one. It usually exhibits a saturation characteristic where the larger the angle, the slower the increase in air intake volume. This nonlinear mapping relationship can be obtained through experimental calibration, for example, by measuring the air intake volume at different opening angles on a standard wind tunnel test bench and fitting the angle-airflow curve.

[0100] Secondly, an airflow allocation optimization model is constructed, using the target airflow volume as the control objective and the opening / closing angle of each motorized louver as the decision variable. The objective of this model is to ensure that the opening / closing angle of each motorized louver is as consistent as possible, while avoiding situations where some louvers are opened too large and others too small, all while satisfying the condition that the total airflow volume equals the target airflow volume. The optimization objective is to minimize the difference in the opening / closing angle of each motorized louver, which can be expressed as the sum of squared deviations between the opening / closing angle of each louver and the average opening / closing angle. Constraints include an equality constraint on the total airflow volume (the sum of the airflow volumes of all louvers equals the target airflow volume) and a range constraint on the opening / closing angle of each louver (the opening / closing angle must be between 0 and 90 degrees).

[0101] For example, firstly, the mapping relationship between the opening angle of each motorized louver and the air intake volume is established through experimental calibration, for example, by using a quadratic function model: .in, This represents the maximum air intake volume when the motorized louvers are fully open. For the first The opening angle of each motorized louver is measured in degrees. The optimization model aims to minimize the difference in opening angles between each louver, specifically by minimizing the sum of squared deviations between each louver's opening angle and the average opening angle. Constraints include: a total airflow equation constraint, i.e. ; and constraints on the opening and closing angle range of each louver, i.e. Based on this, the target opening and closing angles of each motorized louver are determined by solving the Lagrange multiplier method.

[0102] Furthermore, the Lagrange multiplier method is used to solve the air intake distribution optimization model to determine the target opening angle of each motorized louver. The Lagrange multiplier method is a mathematical method that transforms an equality-constrained optimization problem into an unconstrained optimization problem, and is suitable for solving optimization problems with equality constraints.

[0103] Specifically, the air intake distribution optimization model is solved using the Lagrange multiplier method to determine the target opening angle of each motorized louver, including:

[0104] The objective function and constraints of the air intake distribution optimization model are constructed. The objective function is to minimize the sum of squares of the deviations between the target opening angle and the average opening angle of each motorized louver. The constraints include the total air intake equalization constraint and the inequality constraint of the range of opening angles of each motorized louver.

[0105] By introducing Lagrange multipliers and combining the equality constraints with the objective function, a Lagrange function is constructed.

[0106] By introducing slack variables, the inequality constraints are transformed into equality constraints, and a barrier function term is constructed by combining a penalty factor. The barrier function term is then added to the Lagrange function to obtain the augmented Lagrange function.

[0107] By taking the partial derivatives of the opening and closing angle variables of each motorized louver in the augmented Lagrangian function and setting the partial derivatives to zero, the optimality condition equations are obtained.

[0108] The optimality condition equations are solved, and the target opening and closing angles of each electric louver are adjusted using a graded control mode.

[0109] First, the objective function and constraints of the air intake distribution optimization model are constructed. Assume there are N motorized louvers in the bottom air intake area, and the opening angle of the i-th louver is θ. i The unit is degrees. Through experimental calibration, a mapping relationship between the opening angle of each motorized louver and the air intake volume was established, using a quadratic function model: the air intake volume equals the maximum air intake volume multiplied by the opening angle divided by the square of 90, where the maximum air intake volume is the air intake volume when the louvers are fully open. The objective function is to minimize the sum of squares of the deviations between the opening angle of each motorized louver and the average opening angle, where the average opening angle is the sum of the opening angles of all louvers divided by the total number of louvers. Constraints include an equality constraint on the total air intake volume (the sum of the air intake volumes of all louvers equals the target air intake volume) and an inequality constraint on the range of the opening angles of each motorized louver (the opening angle must be between 0 and 90 degrees).

[0110] By introducing Lagrange multipliers, the equality constraints are combined with the objective function to construct the Lagrange function. Let the equality constraint be the sum of the air intake volumes of each louver minus the target air intake volume equal to zero. Introducing Lagrange multipliers, the Lagrange function is constructed as the objective function plus the Lagrange multipliers multiplied by the equality constraints.

[0111] By introducing slack variables, inequality constraints are transformed into equality constraints. A barrier function term is constructed using a penalty factor, and this barrier function term is added to the Lagrange function to obtain the augmented Lagrange function. For inequality constraints with opening / closing angles greater than or equal to zero, slack variables are introduced to transform them into equality constraints; that is, the opening / closing angle minus the square of the slack variable equals zero. For inequality constraints with opening / closing angles less than or equal to 90°, another slack variable is introduced to transform them into equality constraints; that is, the opening / closing angle plus the square of the slack variable minus 90° equals zero. A logarithmic barrier function term is introduced, which is the negative penalty factor multiplied by the sum of the natural logarithms of all slack variables. This term is added to the Lagrange function to obtain the augmented Lagrange function.

[0112] Furthermore, by taking the partial derivatives of the opening / closing angle variables of each motorized louver in the augmented Lagrange function and setting the partial derivatives to zero, we obtain the system of optimality condition equations. Specifically, we take the partial derivatives of the opening / closing angle variables of each motorized louver and set them to zero, take the partial derivatives of the Lagrange multipliers and set them to zero, and take the partial derivatives of each relaxation variable and set them to zero. The conditions that the partial derivatives are zero together constitute a set of nonlinear equations, and the solution to this set of equations is the candidate solution that satisfies the optimality conditions.

[0113] Finally, the optimality condition equations are solved to obtain the target opening angle of each motorized louver. For example, let the optimality condition equations be a vector function F(x) equal to zero, where x contains the opening angle variables of all motorized louvers, Lagrange multipliers, and relaxation variables. In the k-th iteration, the Jacobian matrix is ​​calculated, which is the matrix composed of the partial derivatives of each equation with respect to each variable. The linear equations are then solved to obtain the correction amount, and the variable values ​​are updated to the current value plus the correction amount. The iteration terminates when the norm of the vector function F(x) is less than a preset convergence threshold. This convergence threshold is set according to the control accuracy requirements; for example, it can be set so that when the norm of F(x) is less than 0.000001, the current solution is considered sufficiently accurate, and the iteration stops. At this point, the opening angle variables of each motorized louver are the target opening angles. Through the above solution process, the optimal solution that minimizes the difference in opening angles of each louver can be obtained while satisfying the total air intake constraint and the opening angle range constraint.

[0114] Finally, the segmented control mode is used to control each electric louver to adjust to the corresponding target opening angle to form distributed air intake. Specifically, since the target opening angle is a theoretical value obtained through continuous optimization calculation, and the actual actuator of the electric louver is usually driven by a stepper motor, its control accuracy is limited by the step angle of the motor. Therefore, the continuous target opening angle is discretized into actual executable angle levels.

[0115] For example, if the step angle of the stepper motor is 1.8 degrees, then the minimum adjustment unit of the electric louver is 1.8 degrees, and the target opening / closing angle is rounded to an integer multiple of 1.8 degrees. To simplify the control logic and improve the response speed, a graded control mode can be adopted, dividing the continuous range from 0 degrees to 90 degrees into several discrete grades, such as dividing it into 10 grades with 9-degree intervals, corresponding to grades 0 to 9. Grade 0 corresponds to 0 degrees, which is completely closed, and grade 9 corresponds to 90 degrees, which is completely open.

[0116] Through the above optimized allocation, while meeting the total air intake requirement, the opening angles of each motorized louver are kept consistent or minimized. This avoids problems such as uneven airflow distribution and insufficient air intake in some areas due to excessive opening of some louvers, while also reducing additional wind resistance and energy consumption caused by excessive differences in opening angles. Distributed air intake allows external air to be evenly distributed inside the container, improving overall ventilation and cooling efficiency. This step refines air intake control from traditional single total airflow adjustment to collaborative optimization control of multiple actuators, achieving an optimal balance between air intake uniformity and system energy efficiency while meeting heat dissipation requirements.

[0117] Furthermore, to address the potential for localized overheating in lithium iron phosphate batteries under low charge or high-power charging / discharging conditions, this invention supports differentiated localized ventilation control. Each motorized louvered vent and suction fan is linked to a corresponding battery cluster, and the system monitors the temperature of each battery cluster and the temperature difference between clusters in real time.

[0118] For example, when the temperature of a battery cluster exceeds a preset local temperature control threshold, the system independently adjusts the motorized louvers and suction fan at the corresponding location of that battery cluster. The local temperature control threshold can be set to three levels: when the battery cluster temperature is greater than 30 degrees Celsius, the fan speed at the corresponding location is adjusted to 30% of its rated power; when the battery cluster temperature is greater than 35 degrees Celsius, the fan speed at the corresponding location is adjusted to 50% of its rated power; and when the battery cluster temperature is greater than 40 degrees Celsius, the fan speed at the corresponding location is adjusted to 100% of its rated power. Simultaneously, when there is a temperature difference among multiple battery clusters in the same area, the largest temperature difference is used as the basis for adjusting the fan speed, ensuring that the locally overheated area receives priority heat dissipation.

[0119] For example, the inter-cluster temperature difference control logic is as follows: when the temperature difference between different cells within the same battery cluster is greater than 3 degrees Celsius, the fan at the corresponding location is activated at low power to balance the temperature; when the temperature difference is greater than 5 degrees Celsius, the fan speed is increased to medium power; when the temperature difference is greater than 8 degrees Celsius, the fan speed is increased to full power. Through the above-mentioned localized differentiated ventilation control, precise heat dissipation can be enhanced for areas where Joule heat accumulates due to low charge state or high rate charging and discharging, avoiding "energy waste caused by overall ventilation" and effectively suppressing battery uniform degradation.

[0120] It should be noted that the aforementioned local ventilation control and the aforementioned air intake allocation optimization model can work together. Under normal operating conditions, the Lagrange multiplier method is used to solve for a distributed air intake scheme that minimizes the difference in the opening angle of each louver; under local overheating conditions, priority is given to responding to the local differentiated ventilation needs, and the louvers and fans corresponding to the overheated area are independently enhanced under control, and the system is restored to the balanced air intake mode after the local temperature drops.

[0121] S50: Control the operating power of the suction fan according to the target air intake volume to introduce ambient air into the energy storage container for temperature adjustment.

[0122] Ultimately, the operating power of the suction fan is controlled based on the target air intake volume to introduce ambient air into the energy storage container for temperature regulation. The suction fan is an electrically powered, louvered, variable-frequency fan installed on the side and top of the energy storage container. It actively draws ambient air into the container, creating a forced convection airflow path in conjunction with the electrically powered louvered vents. The operating power of the suction fan directly determines the actual air intake volume; higher power means a higher fan speed and more ambient air is introduced per unit time; lower power results in a correspondingly smaller air intake volume.

[0123] After determining the target air intake volume, it needs to be converted into a power control command for the suction fan. Since suction fans typically use variable frequency drive (VFD) control, their operating power and air intake volume have an approximately linear or monotonic relationship. This mapping relationship between air intake volume and fan power can be established through experimental calibration. For example, when the target air intake volume is 3000 cubic meters per hour, the corresponding fan operating power is 1.5 kilowatts; when the target air intake volume is 5000 cubic meters per hour, the corresponding fan operating power is 2.5 kilowatts. The controller calculates the target power value based on this mapping relationship and adjusts the fan's power supply frequency through the VFD to make the actual fan operating power approximate the target power, thereby achieving precise control of the target air intake volume.

[0124] Specifically, while adjusting the opening angle of the motorized louvers can change the cross-sectional area of ​​the air intake channel, the air intake capacity relying solely on natural convection is limited without fan assistance, especially when the external wind speed is low or the temperature difference is small, making it difficult to meet the air intake volume required for battery cooling. The active suction of the exhaust fan significantly enhances the air intake capacity, allowing external air to overcome the resistance of the louvers and ductwork and smoothly enter the container. Simultaneously, the variable frequency adjustment of the fan power and the control of the motorized louver opening angle work synergistically to achieve precise matching of the air intake volume. Ultimately, ambient air enters the container through the bottom or side wall air intake areas, absorbs heat over the surface of the battery modules, and is then exhausted from the top exhaust duct, completing the temperature adjustment of the internal environment of the energy storage container.

[0125] In addition, the method also includes:

[0126] During the operation of the suction fan, the humidity level inside the energy storage container is monitored in real time.

[0127] When the humidity value exceeds the preset dehumidification threshold, the dehumidification equipment is activated to dehumidify, and the operating power of the suction fan is reduced simultaneously.

[0128] First, the humidity level inside the energy storage container is monitored in real time while controlling the operation of the suction fan. The humidity inside the container is collected in real time by temperature and humidity sensors deployed at key locations within the container. Because the container is a relatively enclosed space, moisture may be generated during battery system operation, and humid external air may also enter the container through ventilation openings, leading to increased internal humidity. When the humidity is too high, moisture in the air will condense on the surface of the battery modules and electrical equipment, forming condensation that can cause short circuits and, in severe cases, damage to the equipment.

[0129] Specifically, when the humidity level exceeds the preset dehumidification threshold, the dehumidification equipment is activated to dehumidify, and the operating power of the suction fan is simultaneously reduced. The dehumidification threshold is a critical humidity value set according to the safe operation requirements of the battery module and electrical equipment, for example, it can be set to a relative humidity of 80%. When the humidity inside the chamber exceeds this threshold, it indicates a risk of condensation, and the dehumidification equipment, such as an industrial dehumidifier or air conditioner dehumidification mode, must be activated immediately to dry the air inside the chamber and reduce the humidity to a safe range. At the same time, since external humid air is one of the important reasons for the increase in humidity inside the chamber, the operating power of the suction fan must be reduced simultaneously to reduce the amount of external humid air introduced, and to avoid the dehumidification equipment reducing its dehumidification efficiency due to the continuous introduction of humid air while dehumidifying. Once the humidity returns to a safe range, the normal operating power of the suction fan can be restored, and the dehumidification equipment can be turned off or put into standby mode.

[0130] Through the above-mentioned humidity linkage control, the energy storage container can effectively cope with high humidity environment while ventilating and cooling, avoid the risk of condensation caused by blindly introducing humid air, and ensure the safe operation of battery system and electrical equipment.

[0131] Furthermore, this method achieves deep integration of ventilation control with the liquid cooling system, air conditioning system, and fire protection system to realize synergistic optimization of the total heat management system. When ventilation safety conditions are not met, the system automatically shuts down all motorized louvers and exhaust fans, and simultaneously switches the temperature control task to the liquid cooling system or air conditioning system.

[0132] For example, the linkage logic of the liquid cooling system is as follows: When the ventilation system is forcibly shut down due to excessive dust, detection of rainwater, high temperature and humidity, or low battery temperature, the strategy automatically switches to the liquid cooling system for battery temperature regulation. The liquid cooling system executes the liquid cooling strategy logic preset by the battery management system: when the battery module temperature is greater than or equal to 35 degrees Celsius, the liquid cooling system starts the cooling mode to forcibly cool the battery; when the battery module temperature is less than or equal to 15 degrees Celsius, the liquid cooling system starts the heating mode to preheat the battery; when the battery module temperature is between 15 degrees Celsius and 35 degrees Celsius, the liquid cooling system is in self-circulation or standby mode, and does not perform active cooling or heating to reduce energy consumption.

[0133] For example, the linkage logic of the air conditioning system is as follows: When the ventilation system is forcibly shut down, the strategy automatically switches to the air conditioning system to regulate the internal ambient temperature of the container. The air conditioning system executes according to the preset air conditioning strategy logic: when the internal ambient temperature of the container is greater than or equal to 35 degrees Celsius, the air conditioning starts the cooling mode to lower the ambient temperature inside the container; when the internal ambient temperature of the container is less than or equal to 10 degrees Celsius, the air conditioning starts the heating mode to raise the ambient temperature inside the container; when the internal ambient humidity of the container is greater than or equal to 80%, the air conditioning starts the dehumidification mode to lower the humidity inside the container to a safe range; when the ambient temperature is between 10 degrees Celsius and 35 degrees Celsius and the humidity is below 80%, the air conditioning is in standby or ventilation circulation mode.

[0134] For example, the linkage logic of the fire protection system is as follows: When the fire protection system detects battery thermal runaway or a fire accident, it performs coordinated control according to the preset control logic of the fire protection system. If the fire protection system enters smoke exhaust mode, the system simultaneously activates the motorized louvers and exhaust fans in the corresponding areas to assist in smoke exhaust; if the fire protection system determines that it is necessary to close the smoke exhaust passage and spray fire-fighting materials, the system simultaneously shuts down all motorized louvers and exhaust fans to form a sealed space to cooperate with fire fighting. The control priority of the fire protection system is higher than that of conventional ventilation and temperature control, ensuring that ventilation control obeys fire protection needs in the event of a safety accident.

[0135] Through the above-mentioned multi-system linkage mechanism, this method can realize the coordinated control of ventilation, liquid cooling, air conditioning, fire protection, dehumidification and other systems. When natural ventilation can meet the temperature control requirements, ambient air is used first to reduce energy consumption. When natural ventilation cannot meet the requirements or there are safety risks, the liquid cooling or air conditioning system will fill the gap in time. In the fire emergency state, it obeys the fire control command and forms a complete closed loop of the total heat management system.

[0136] In summary, the embodiments of this application have at least the following technical effects:

[0137] This invention first determines ventilation safety conditions by collecting dust concentration data and comparing it to a safety threshold, avoiding equipment damage caused by blindly activating ventilation in dusty or rainy weather, thus improving the environmental adaptability and equipment reliability of the energy storage container. Secondly, based on a comparison of ambient temperature and seasonal thresholds, it adaptively selects either the bottom or side wall air intake area as the target air intake area, achieving seasonal adaptability of the air intake structure. In summer, the low-temperature air at the bottom enhances cooling efficiency, while in winter, the relatively low-temperature air from the side walls reduces heat loss, maximizing the efficiency of natural ventilation. Thirdly, by comparing the internal temperature and battery module temperature with temperature control thresholds, this invention determines the target air intake volume and controls the opening angle of the electric louvers and the operating power of the suction fan, ensuring precise matching of ventilation and temperature control with the actual thermal demands of the battery. This effectively suppresses localized overheating of lithium iron phosphate batteries under low charge or high-power charging / discharging conditions, slowing down battery degradation.

[0138] Finally, through the coordinated operation of the above-mentioned multi-dimensional parameter acquisition and hierarchical control mechanism, this invention reduces thermal management energy consumption and improves the economy and operational reliability of the energy storage system while ensuring the safe operation of the battery.

[0139] Example 2, as Figure 2 As shown, based on the same inventive concept as the intelligent temperature adjustment method for an energy storage container provided in Embodiment 1, this embodiment of the invention also provides an intelligent temperature adjustment system for an energy storage container, comprising:

[0140] The parameter acquisition module 11 is used to acquire environmental parameters and internal state parameters of the energy storage container. The environmental parameters include at least ambient temperature, ambient humidity, and dust concentration, and the internal state parameters include at least the internal temperature and battery module temperature.

[0141] The ventilation safety judgment module 12 is used to compare the dust concentration in the environmental parameters with a preset safety threshold to determine whether the ventilation safety conditions are met.

[0142] The air intake area determination module 13 is used to determine the target air intake area of ​​the energy storage container by comparing the ambient temperature with a preset seasonal threshold if the ventilation safety conditions are met. The target air intake area is either the bottom air intake area or the side wall air intake area.

[0143] The air intake and louver control module 14 is used to determine the target air intake by comparing the temperature inside the box, the battery module temperature and the preset temperature control threshold, and to control the opening and closing angle of the electric louvers corresponding to the target air intake area according to the target air intake.

[0144] The fan control module 15 is used to control the operating power of the suction fan according to the target air intake volume, so as to introduce external ambient air into the energy storage container for temperature adjustment.

[0145] Specifically, the parameter acquisition module 11 is used for:

[0146] Collect environmental parameters and internal state parameters of the energy storage container, including:

[0147] By deploying temperature and humidity sensors, dust concentration sensors, and water immersion sensors on the outside of the energy storage container, ambient temperature, ambient humidity, dust concentration, and rainfall conditions are collected in real time.

[0148] Temperature and humidity sensors are installed inside the energy storage container to collect the temperature and humidity inside the container in real time.

[0149] Battery module temperatures are collected by reusing the battery management system inside the energy storage container.

[0150] The ventilation safety judgment module 12 is specifically used for:

[0151] The dust concentration in the environmental parameters is compared with a preset safety threshold to determine whether the ventilation safety conditions are met.

[0152] The air intake area determination module 13 is specifically used for:

[0153] If ventilation safety conditions are met, before determining the target air intake area of ​​the energy storage container by comparing the ambient temperature with a preset seasonal threshold, the following steps are also included:

[0154] If the dust concentration in the environmental parameters exceeds the preset safety threshold, or if rainwater is detected in the environmental parameters, then the ventilation safety conditions are not met.

[0155] Generate and execute a forced shutdown command, which controls all motorized louvers and exhaust fans to shut down.

[0156] Specifically, the target air intake area of ​​the energy storage container is determined by comparing the ambient temperature with a preset seasonal threshold, including:

[0157] When the ambient temperature is greater than or equal to the first temperature threshold, it is determined to be summer mode, and the bottom air intake area is determined as the target air intake area.

[0158] When the ambient temperature is less than or equal to the second temperature threshold, it is determined to be winter mode, and the side wall air intake area is determined as the target air intake area.

[0159] Wherein, the first temperature threshold is greater than the second temperature threshold.

[0160] The air intake and louver control module 14 is specifically used for:

[0161] The target air intake volume is determined by comparing the internal temperature of the enclosure, the battery module temperature, and a preset temperature control threshold, including:

[0162] The first temperature deviation between the internal temperature of the box and the preset target internal temperature, and the second temperature deviation between the battery module temperature and the preset target battery temperature are obtained.

[0163] The first temperature deviation and the second temperature deviation are weighted and fused to obtain the comprehensive temperature deviation, wherein the sum of the weighting coefficients of the first temperature deviation and the second temperature deviation is 1.

[0164] The comprehensive temperature deviation is input into a preset fuzzy controller, and the initial air intake volume is obtained through fuzzy inference.

[0165] Based on the temperature difference between the current ambient temperature and the temperature inside the chamber, the initial air intake volume is corrected using a feedforward compensation algorithm to obtain the target air intake volume.

[0166] Specifically, based on the temperature difference between the current ambient temperature and the internal temperature of the chamber, the initial air intake is corrected using a feedforward compensation algorithm to obtain the target air intake, including:

[0167] Obtain the current ambient temperature and the temperature inside the chamber, and calculate the temperature difference between the ambient temperature and the temperature inside the chamber;

[0168] Obtain a preset feedforward compensation coefficient, wherein the feedforward compensation coefficient is dynamically adjusted according to the rate of change of ambient temperature, and the feedforward compensation coefficient is increased when the rate of change of ambient temperature is greater than a preset rate of change threshold.

[0169] The feedforward compensation amount is calculated by multiplying the temperature difference value by the feedforward compensation coefficient.

[0170] The target air intake volume is obtained by adding the initial air intake volume to the feedforward compensation amount.

[0171] Furthermore, controlling the opening and closing angle of the motorized louvers corresponding to the target air intake area based on the target air intake volume includes:

[0172] Obtain the nonlinear mapping relationship between the opening and closing angles of multiple motorized louvers corresponding to the target air intake area and the air intake volume;

[0173] Using the target air intake volume as the control objective and the opening and closing angles of each motorized louver as the decision variables, an air intake volume allocation optimization model is constructed, wherein the air intake volume allocation optimization model takes minimizing the difference in the opening and closing angles of each motorized louver as the optimization objective.

[0174] The air intake distribution optimization model is solved using the Lagrange multiplier method to determine the target opening and closing angle of each electric louver.

[0175] Each motorized louver is individually controlled to adjust to its corresponding target opening angle, thereby creating distributed air intake.

[0176] Specifically, the air intake distribution optimization model is solved using the Lagrange multiplier method to determine the target opening angle of each motorized louver, including:

[0177] The objective function and constraints of the air intake distribution optimization model are constructed. The objective function is to minimize the sum of squares of the deviations between the target opening angle and the average opening angle of each motorized louver. The constraints include the total air intake equalization constraint and the inequality constraint of the range of opening angles of each motorized louver.

[0178] By introducing Lagrange multipliers and combining the equality constraints with the objective function, a Lagrange function is constructed.

[0179] By introducing slack variables, the inequality constraints are transformed into equality constraints, and a barrier function term is constructed by combining a penalty factor. The barrier function term is then added to the Lagrange function to obtain the augmented Lagrange function.

[0180] By taking the partial derivatives of the opening and closing angle variables of each motorized louver in the augmented Lagrangian function and setting the partial derivatives to zero, the optimality condition equations are obtained.

[0181] The optimality condition equations are solved, and the target opening and closing angles of each electric louver are adjusted using a graded control mode.

[0182] The fan control module 15 is specifically used for:

[0183] The operating power of the suction fan is controlled according to the target air intake volume to introduce ambient air into the energy storage container for temperature adjustment.

[0184] In addition, the method also includes:

[0185] During the operation of the suction fan, the humidity level inside the energy storage container is monitored in real time.

[0186] When the humidity value exceeds the preset dehumidification threshold, the dehumidification equipment is activated to dehumidify, and the operating power of the suction fan is reduced simultaneously.

Claims

1. A method for intelligent adjustment of ambient temperature in an energy storage container, characterized in that, The method includes: Collect environmental parameters and internal state parameters of the energy storage container. The environmental parameters include at least ambient temperature, ambient humidity, and dust concentration. The internal state parameters include at least the internal temperature of the container and the battery module temperature. The dust concentration in the environmental parameters is compared with a preset safety threshold to determine whether the ventilation safety conditions are met. If the ventilation safety conditions are met, the target air intake area of ​​the energy storage container is determined by comparing the ambient temperature with the preset seasonal threshold. The target air intake area is either the bottom air intake area or the side wall air intake area. The target air intake volume is determined by comparing the internal temperature of the box, the battery module temperature, and the preset temperature control threshold, and the opening and closing angle of the electric louvers corresponding to the target air intake area is controlled according to the target air intake volume. The operating power of the suction fan is controlled according to the target air intake volume to introduce ambient air into the energy storage container for temperature adjustment.

2. The intelligent temperature adjustment method for energy storage container according to claim 1, characterized in that, Collect environmental parameters and internal state parameters of the energy storage container, including: By deploying temperature and humidity sensors, dust concentration sensors, and water immersion sensors on the outside of the energy storage container, ambient temperature, ambient humidity, dust concentration, and rainfall conditions are collected in real time. Temperature and humidity sensors are installed inside the energy storage container to collect the temperature and humidity inside the container in real time. Battery module temperatures are collected by reusing the battery management system inside the energy storage container.

3. The intelligent temperature adjustment method for energy storage container according to claim 1, characterized in that, The target air intake area of ​​the energy storage container is determined by comparing the ambient temperature with a preset seasonal threshold, including: When the ambient temperature is greater than or equal to the first temperature threshold, it is determined to be summer mode, and the bottom air intake area is determined as the target air intake area. When the ambient temperature is less than or equal to the second temperature threshold, it is determined to be winter mode, and the side wall air intake area is determined as the target air intake area. Wherein, the first temperature threshold is greater than the second temperature threshold.

4. The intelligent temperature adjustment method for energy storage container according to claim 1, characterized in that, The target air intake volume is determined by comparing the internal temperature of the enclosure, the battery module temperature, and a preset temperature control threshold, including: The first temperature deviation between the internal temperature of the box and the preset target internal temperature, and the second temperature deviation between the battery module temperature and the preset target battery temperature are obtained. The first temperature deviation and the second temperature deviation are weighted and fused to obtain the comprehensive temperature deviation, wherein the sum of the weighting coefficients of the first temperature deviation and the second temperature deviation is 1. The comprehensive temperature deviation is input into a preset fuzzy controller, and the initial air intake volume is obtained through fuzzy inference. Based on the temperature difference between the current ambient temperature and the temperature inside the chamber, the initial air intake volume is corrected using a feedforward compensation algorithm to obtain the target air intake volume.

5. The intelligent temperature adjustment method for energy storage container according to claim 4, characterized in that, Based on the temperature difference between the current ambient temperature and the internal temperature of the chamber, the initial air intake volume is corrected using a feedforward compensation algorithm to obtain the target air intake volume, including: Obtain the current ambient temperature and the temperature inside the chamber, and calculate the temperature difference between the ambient temperature and the temperature inside the chamber; Obtain a preset feedforward compensation coefficient, wherein the feedforward compensation coefficient is dynamically adjusted according to the rate of change of ambient temperature, and the feedforward compensation coefficient is increased when the rate of change of ambient temperature is greater than a preset rate of change threshold. The feedforward compensation amount is calculated by multiplying the temperature difference value by the feedforward compensation coefficient. The target air intake volume is obtained by adding the initial air intake volume to the feedforward compensation amount.

6. The intelligent temperature adjustment method for energy storage container according to claim 1, characterized in that, Controlling the opening and closing angle of the motorized louvers corresponding to the target air intake area based on the target air intake volume includes: Obtain the nonlinear mapping relationship between the opening and closing angles of multiple motorized louvers corresponding to the target air intake area and the air intake volume; Using the target air intake volume as the control objective and the opening and closing angles of each motorized louver as the decision variables, an air intake volume allocation optimization model is constructed, wherein the air intake volume allocation optimization model takes minimizing the difference in the opening and closing angles of each motorized louver as the optimization objective. The air intake distribution optimization model is solved using the Lagrange multiplier method to determine the target opening and closing angle of each electric louver. Each motorized louver is individually controlled to adjust to its corresponding target opening angle, thereby creating distributed air intake.

7. The intelligent temperature adjustment method for energy storage container according to claim 6, characterized in that, The airflow distribution optimization model is solved using the Lagrange multiplier method to determine the target opening angle of each motorized louver, including: The objective function and constraints of the air intake distribution optimization model are constructed. The objective function is to minimize the sum of squares of the deviations between the target opening angle and the average opening angle of each motorized louver. The constraints include the total air intake equalization constraint and the inequality constraint of the range of opening angles of each motorized louver. By introducing Lagrange multipliers and combining the equality constraints with the objective function, a Lagrange function is constructed. By introducing slack variables, the inequality constraints are transformed into equality constraints, and a barrier function term is constructed by combining a penalty factor. The barrier function term is then added to the Lagrange function to obtain the augmented Lagrange function. By taking the partial derivatives of the opening and closing angle variables of each motorized louver in the augmented Lagrangian function and setting the partial derivatives to zero, the optimality condition equations are obtained. The optimality condition equations are solved, and the target opening and closing angles of each electric louver are adjusted using a graded control mode.

8. The intelligent temperature adjustment method for energy storage container according to claim 1, characterized in that, If ventilation safety conditions are met, before determining the target air intake area of ​​the energy storage container by comparing the ambient temperature with a preset seasonal threshold, the following steps are also included: If the dust concentration in the environmental parameters exceeds the preset safety threshold, or if rainwater is detected in the environmental parameters, then the ventilation safety conditions are not met. Generate and execute a forced shutdown command, which controls all motorized louvers and exhaust fans to shut down.

9. The intelligent temperature adjustment method for energy storage container according to claim 1, characterized in that, The method further includes: During the operation of the suction fan, the humidity level inside the energy storage container is monitored in real time. When the humidity value exceeds the preset dehumidification threshold, the dehumidification equipment is activated to dehumidify, and the operating power of the suction fan is reduced simultaneously.

10. An intelligent temperature adjustment system for an energy storage container, characterized in that, A method for intelligently adjusting the ambient temperature of an energy storage container as described in any one of claims 1-9 includes: The parameter acquisition module is used to collect environmental parameters and internal state parameters of the energy storage container. The environmental parameters include at least ambient temperature, ambient humidity, and dust concentration, and the internal state parameters include at least the internal temperature and battery module temperature. The ventilation safety judgment module is used to compare the dust concentration in the environmental parameters with a preset safety threshold to determine whether the ventilation safety conditions are met. The air intake area determination module is used to determine the target air intake area of ​​the energy storage container by comparing the ambient temperature with a preset seasonal threshold if ventilation safety conditions are met. The target air intake area is either the bottom air intake area or the side wall air intake area. The air intake and louver control module is used to compare the internal temperature of the box, the battery module temperature and the preset temperature control threshold to determine the target air intake, and control the opening and closing angle of the electric louvers corresponding to the target air intake area according to the target air intake. The fan control module is used to control the operating power of the suction fan according to the target air intake volume, so as to introduce external ambient air into the energy storage container for temperature adjustment.

Images