UPS lithium battery system for IDC data center

Abstract

The present invention discloses a UPS lithium battery system for an IDC data room, and relates to the field of battery monitoring technology. When the system is running, the system dynamically obtains the comprehensive impact index Timp of the microenvironment on the battery temperature, thereby solving the problems of slow response to environmental impact and inaccurate evaluation in the traditional system. The strategy optimization module combines the UPS lithium battery operation requirements, triggers the optimization logic and dynamically calculates the optimized charging power Pr, thereby effectively coping with the problems of unreasonable power allocation and insufficient battery protection in the battery charging strategy, and simultaneously monitors the difference in the actual charging power Po in real time, ensuring the accuracy of the execution result and the safety of the system operation. In addition, the evaluation feedback module monitors the operating status of the UPS lithium battery after executing the dynamic adjustment charging strategy result, and realizes closed-loop optimization control. It can adapt to the complex thermal environment of the IDC data room, reduce the risk of overheating caused by battery temperature rise, and significantly extend the battery life.

Description

Technical Field

[0001] The invention relates to the technical field of battery monitoring, in particular to a UPS lithium battery system used in an IDC data room. Background Art

[0002] Uninterruptible power supply is an important part of the power supply and energy storage field. Its core function is to provide stable power for load equipment, especially to achieve continuous power supply when power is interrupted. With the development of lithium battery technology, lithium batteries have gradually replaced lead-acid batteries and become an important energy storage component of UPS systems. In the data center IDC scenario, since the core facilities of servers and storage devices have extremely high requirements for the continuity and stability of power, the UPS lithium battery system plays a key role in ensuring data security and business continuity.

[0003] In the current IDC data center, the impact of micro-environmental changes on the performance of lithium batteries in UPS lithium battery systems has not received sufficient attention. Traditional lithium battery management systems (BMS) mostly adopt fixed charging and discharging strategies and lack dynamic adjustment mechanisms. Specifically, when the temperature in the computer room rises, the lithium battery system may still charge in the default high-power mode, causing the battery temperature to rise further, accelerating aging and even causing safety hazards. At the same time, the lack of comprehensive consideration of other environmental parameters such as humidity makes the UPS system unable to effectively adapt to the dynamic environmental changes in the computer room. In addition, the optimization strategy of traditional UPS lithium battery systems usually only focuses on a single performance indicator, such as capacity and efficiency, and fails to balance the relationship between battery life, temperature control and computer room load requirements, which limits the overall reliability and operating efficiency of the system. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a UPS lithium battery system for an IDC data room, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a UPS lithium battery system for an IDC data center includes a micro-environment parameter acquisition module, a battery status monitoring module, a thermal impact assessment module, a strategy optimization module, a decision execution module and an assessment feedback module;

[0006] The micro-environment parameter acquisition module deploys environmental sensors at different locations in the IDC data room, collects environmental information of the IDC data room through a fixed acquisition cycle, and forms an environmental characteristic vector E after processing the environmental information;

[0007] The battery status monitoring module monitors the operating status of the UPS lithium battery and collects battery charging and discharging information, battery pack temperature information and battery internal resistance information through a fixed collection cycle to form a battery status characteristic vector B;

[0008] The thermal impact assessment module obtains the comprehensive impact index Timp of the microenvironment on the battery temperature by fitting the environmental characteristic vector E and the battery state characteristic vector B;

[0009] The strategy optimization module receives the comprehensive impact index Timp and the battery state characteristic vector B, triggers the optimization logic according to the operation requirements of the UPS lithium battery, dynamically calculates the optimized charging power Pr, and obtains the result of dynamically adjusting the charging strategy;

[0010] The decision execution module uses the received charging power Pr and the result of dynamically adjusting the charging strategy as the target value of the charging power, converts the charging power Pr into a control instruction for specific execution, and monitors the difference with the actual charging power Po in real time to obtain the safety mode state trigger result;

[0011] The evaluation feedback module obtains a performance evaluation index Qp by monitoring the operating status of the UPS lithium battery after executing the dynamic adjustment charging strategy result, and compares it with a preset performance optimization evaluation threshold Qth to obtain a charging strategy optimization evaluation plan.

[0012] Preferably, the microenvironment parameter acquisition module includes an environment acquisition unit and an environment processing unit;

[0013] The environment collection unit deploys environment sensors at different locations in the IDC data room and collects the environment information of the IDC data room through a fixed collection period, including using a temperature sensor to collect environment temperature information, using a humidity sensor to collect environment humidity information, using an air flow rate sensor to collect environment flow rate information, and connecting the refrigeration equipment through the Internet of Things to obtain the refrigeration equipment power information, to form an environment collection data group;

[0014] The ambient temperature information includes the ambient temperature Te; the ambient humidity information includes the ambient humidity He; the ambient flow rate information includes the ambient flow rate Va; the refrigeration equipment power information includes the refrigeration equipment power Pc;

[0015] The environment processing unit performs preprocessing on the environment collection data group, including denoising preprocessing, data completion preprocessing and normalization preprocessing, to form a processed environment characteristic vector E={Ten, Hen, Van, Pcn}, where Ten represents the normalized environment temperature, Hen represents the normalized environment humidity, Van represents the normalized environment flow rate, and Pcn represents the normalized refrigeration equipment power;

[0016] Among them, the denoising preprocessing uses the median filtering algorithm to eliminate outliers, including abnormal data points caused by short-term sensor fluctuations; the data completion preprocessing uses the nearest neighbor interpolation method to complete the missing data in the collection; the normalization preprocessing uses the minimum-maximum normalization method to eliminate differences in different dimensions.

[0017] Preferably, the battery status monitoring module includes a battery parameter acquisition unit and a battery data processing unit;

[0018] The battery parameter acquisition unit monitors the operating status of the UPS lithium battery and collects battery charging and discharging information, battery pack temperature information and battery internal resistance information through a fixed acquisition cycle to form a battery acquisition data group, including battery remaining capacity SOC, charging power Pchg, discharging power Pd, battery pack temperature Tbat and battery internal resistance Rint;

[0019] The battery data processing unit performs data cleaning on the battery collection data group to form a processed battery state characteristic vector B={SOC, Pchg, Pd, Tbat, Rint};

[0020] The data cleaning process includes using a median filter to perform data cleaning preprocessing.

[0021] Preferably, the thermal impact assessment module includes a data fitting unit and a comprehensive analysis unit;

[0022] The data fitting unit obtains the environmental temperature influence component Tenf by associating the environmental characteristic vector E with the battery pack temperature Tbat in the battery state characteristic vector B;

[0023] The ambient temperature influence component Tenf is obtained by the following calculation formula:

[0024] ;

[0025] Wherein, t1, t2, t3, t4 and t5 represent the preset weight values ​​of the normalized ambient temperature Ten, the normalized ambient humidity Hen, the normalized ambient flow rate Van, the normalized refrigeration equipment power Pcn and the battery pack temperature Tbat, respectively, and t1+t2+t3+t4+t5=1, and the specific value is set by the user.

[0026] Preferably, the comprehensive analysis unit performs fitting calculation according to the ambient temperature influence component Tenf and the battery state characteristic vector B to obtain the comprehensive influence index Timp of the microenvironment on the battery temperature;

[0027] The comprehensive impact index Timp is obtained by the following calculation formula:

[0028] ;

[0029] In the formula, ln represents the natural logarithm function, It indicates the difference trend of the ambient temperature impact component on the battery temperature, highlighting the state of the large temperature difference on the temperature. Rint represents the battery internal resistance, which is specifically used to reflect the correlation between the battery internal resistance and temperature rise. Indicates the remaining battery level.

[0030] Preferably, the strategy optimization module includes an optimization analysis unit and an optimization calculation unit;

[0031] The optimization analysis unit analyzes the association between the battery status and the environmental requirements according to the received comprehensive impact index Timp and the battery status characteristic vector B, and according to the operation requirements of the UPS lithium battery, including battery temperature safety association analysis, battery remaining capacity SOC association analysis and temperature rise trend association analysis, and triggers the optimization logic;

[0032] The trigger optimization logic is specifically triggered in the following ways:

[0033] When the comprehensive impact index Timp>0 and the battery pack temperature Tbat>Tsafe, the overheat protection logic is triggered;

[0034] When the remaining battery SOC is less than 10%, the priority charging logic is triggered;

[0035] When the comprehensive impact index Timp < 0, the logic of lifting the limited charging power is triggered;

[0036] Among them, Tsafe represents the temperature threshold, specifically the initial preset battery temperature safety threshold.

[0037] Preferably, the optimization calculation unit dynamically calculates the optimized charging power Pr according to the battery pack temperature information, the battery internal resistance information, the operation requirements of the UPS lithium battery and the battery remaining capacity SOC, and obtains the result of the dynamic adjustment charging strategy;

[0038] The charging power Pr is obtained by the following calculation formula:

[0039] ;

[0040] In the formula, Pchgmax represents the upper limit charging power supported by the UPS lithium battery, and SOCmax represents the maximum capacity of the battery pack;

[0041] The result of dynamically adjusting the charging strategy is obtained by integrating the result of triggering the optimization logic and the charging power Pr.

[0042] Preferably, the decision execution module includes an instruction generation unit and a safety mode detection unit;

[0043] The instruction generation unit takes the received charging power Pr and the result of the dynamic adjustment of the charging strategy as the target value of the charging power, specifically sets the charging power Pr as the real-time target value of the charging power, and then converts it into a control instruction for specific execution, including adjusting the inverter of the UPS lithium battery to perform specific charging current and voltage power adjustments;

[0044] The safety mode detection unit monitors the difference between the charging power Pr and the actual charging power Po in real time, obtains the absolute difference △P, and compares it with the preset allowable deviation threshold Pthe to obtain the safety mode state trigger result;

[0045] The absolute difference △P is obtained by the calculation formula △P=|Pr-Po|;

[0046] The safety mode status trigger result is obtained by the following matching method:

[0047] When the absolute difference △P ≥ the allowable deviation threshold Pthe, the safety mode status trigger result is obtained as triggered, entering the safety mode, limiting the charging power, including limiting the charging power Pr to 0.5 times, and simultaneously monitoring the battery pack temperature Tbat status in real time. When the battery pack temperature Tbat ≥ Tsafe temperature threshold, the temperature protection is triggered, charging is stopped and an early warning prompt is issued. At the same time, the normalized refrigeration equipment power Pcn is proportionally adjusted to control the environmental status in the IDC data room.

[0048] Preferably, the evaluation feedback module includes a UPS operation status detection unit and a performance evaluation unit;

[0049] The UPS operation status detection unit monitors the operation status of the UPS lithium battery after executing the dynamic adjustment charging strategy result, including the actual charging power Po, the battery pack temperature Tbat, the battery remaining capacity SOC and the battery internal resistance Rint, and obtains the execution feedback state vector F={Po, Tbat, SOC, Rint};

[0050] The performance evaluation unit performs correlation analysis based on the obtained execution feedback state vector F and the result of the dynamic adjustment of the charging strategy, obtains the performance evaluation index Qp, and compares it with a preset performance optimization evaluation threshold Qth to obtain a charging strategy optimization evaluation scheme.

[0051] Preferably, the performance evaluation index Qp is obtained by the following calculation formula:

[0052] ;

[0053] In the formula, Pr represents the charging power, Po represents the actual charging power, Tbat represents the battery pack temperature, Tsafe represents the temperature threshold, and Rint represents the battery internal resistance. Indicates the influence coefficient, specifically the influence coefficient of the deviation between the charging power Pr and the actual charging power Po;

[0054] The charging strategy optimization evaluation scheme is obtained by the following matching method:

[0055] When the performance evaluation index Qp is less than the performance optimization evaluation threshold Qth, the optimization effect obtained satisfies the expected effect and the strategy solution is not adjusted;

[0056] When the performance evaluation index Qp ≥ the performance optimization evaluation threshold Qth, the optimization effect does not meet the expected effect and the iterative adjustment strategy is obtained, including adjusting the charging power Pr, adjusting the trigger optimization logic conditions and the weight in the calculation formula of the ambient temperature influence component Tenf.

[0057] The present invention provides a UPS lithium battery system for an IDC data center, which has the following beneficial effects:

[0058] (1) When the system is running, the micro-environment parameter acquisition module and the battery status monitoring module provide a reliable data basis for subsequent evaluation and optimization. With the help of the thermal impact assessment module fitting analysis, the system can dynamically obtain the comprehensive impact index Timp of the micro-environment on the battery temperature, solving the problems of slow response to environmental impact and inaccurate evaluation in traditional systems. The strategy optimization module combines the UPS lithium battery operation requirements, triggers the optimization logic and dynamically calculates the optimized charging power Pr, thereby effectively dealing with the problems of unreasonable power allocation and insufficient battery protection in the battery charging strategy. At the same time, the difference in actual charging power Po is monitored in real time to ensure the accuracy of the execution results and the safety of system operation. In addition, the evaluation feedback module monitors the operating status of the UPS lithium battery after executing the dynamic adjustment of the charging strategy results, quantifies the performance evaluation index Qp, and proposes an optimization evaluation plan by comparing it with the performance optimization evaluation threshold Qth, realizing closed-loop optimization control. It can adapt to the complex thermal environment of the IDC data room, reduce the risk of overheating caused by battery temperature rise, significantly extend the battery life, and at the same time ensure the continuous and stable power supply needs of the load, providing solid support for the efficient operation and maintenance of the IDC room.

[0059] (2) The comprehensive analysis unit fits and calculates the environmental temperature impact component Tenf and the battery state characteristic vector B to obtain the comprehensive impact index Timp of the microenvironment on the battery temperature, which effectively solves the problem of insufficient quantification of the coupling relationship between the environment and the battery in the traditional method. The optimization analysis unit further completes the deep correlation analysis between the environmental demand and the battery operation state, and triggers the optimization logic according to the actual operation demand of the UPS lithium battery. The trigger logic can not only identify the battery temperature rise risk in time, but also give priority to guaranteeing the power supply demand when the remaining battery is insufficient, or appropriately release the charging power limit when the temperature trend is good. Under the guidance of the trigger logic, the optimization calculation unit dynamically calculates the optimized charging power Pr, integrates the results of the trigger optimization logic, and generates the results of the dynamic adjustment charging strategy, which fully adapts to the changes in the battery state and environmental demand, and can realize the real-time adjustment of the UPS lithium battery operation strategy, effectively avoiding the overheating, low charging efficiency or excessive battery aging caused by the fixed strategy in the traditional system that cannot flexibly respond to the temperature rise trend, insufficient power or changes in temperature control conditions.

[0060] (3) The optimized charging power Pr is converted into a control command through the instruction generation unit, and the charging current and voltage of the UPS lithium battery are adjusted in real time to ensure the accurate execution of the charging strategy, dynamically optimize the environmental status of the IDC data center, and ensure the safety and environmental adaptability of the charging strategy under multi-variable interference. The evaluation feedback module collects the execution feedback state vector F in real time through the UPS operation status detection unit, and the performance evaluation unit comprehensively analyzes the feedback state vector and the dynamic adjustment charging strategy results, calculates the performance evaluation index Qp, and compares it with the performance optimization evaluation threshold Qth. The system generates an iterative adjustment strategy scheme, which covers adjusting the charging power Pr, optimizing the trigger logic conditions, and modifying the calculation weight of the ambient temperature influence component Tenf, forming an efficient closed-loop optimization mechanism, and realizing the dynamic verification and feedback adjustment of the charging strategy execution effect. Compared with the traditional scheme that only relies on fixed parameters or manual evaluation, it ensures the comprehensive improvement of charging efficiency, temperature control capability and battery health management, thereby greatly enhancing the safety, flexibility and long-term reliability of the UPS lithium battery system in the IDC room. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 The present invention is a schematic diagram of a UPS lithium battery system block diagram for an IDC data center. DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0063] Example 1

[0064] The present invention provides a UPS lithium battery system for IDC data center, please refer to Figure 1 , including micro-environment parameter acquisition module, battery status monitoring module, thermal impact assessment module, strategy optimization module, decision execution module and evaluation feedback module;

[0065] The micro-environment parameter acquisition module deploys environmental sensors at different locations in the IDC data room, collects environmental information of the IDC data room through a fixed acquisition cycle, and forms an environmental characteristic vector E after processing the environmental information;

[0066] The battery status monitoring module monitors the operating status of the UPS lithium battery and collects battery charging and discharging information, battery pack temperature information and battery internal resistance information through a fixed collection cycle to form a battery status characteristic vector B;

[0067] The thermal impact assessment module obtains the comprehensive impact index Timp of the microenvironment on the battery temperature by fitting the environmental characteristic vector E and the battery state characteristic vector B;

[0068] The strategy optimization module receives the comprehensive impact index Timp and the battery state characteristic vector B, triggers the optimization logic according to the operation requirements of the UPS lithium battery, dynamically calculates the optimized charging power Pr, and obtains the result of dynamically adjusting the charging strategy;

[0069] The decision execution module uses the received charging power Pr and the result of dynamically adjusting the charging strategy as the target value of the charging power, converts the charging power Pr into a control instruction for specific execution, and monitors the difference with the actual charging power Po in real time to obtain the safety mode state trigger result;

[0070] The evaluation feedback module obtains a performance evaluation index Qp by monitoring the operating status of the UPS lithium battery after executing the dynamic adjustment charging strategy result, and compares it with a preset performance optimization evaluation threshold Qth to obtain a charging strategy optimization evaluation plan.

[0071] In this embodiment, the micro-environment parameter acquisition module and the battery status monitoring module provide a reliable data basis for subsequent evaluation and optimization. With the help of the thermal impact assessment module fitting analysis, the system can dynamically obtain the comprehensive impact index Timp of the micro-environment on the battery temperature, solving the problems of slow response to environmental impact and inaccurate evaluation in traditional systems. The strategy optimization module combines the UPS lithium battery operation requirements, triggers the optimization logic and dynamically calculates the optimized charging power Pr, thereby effectively dealing with the problems of unreasonable power allocation and insufficient battery protection in the battery charging strategy, and at the same time monitors the difference in the actual charging power Po in real time, ensuring the accuracy of the execution results and the safety of the system operation. In addition, the evaluation feedback module monitors the operating status of the UPS lithium battery after executing the dynamic adjustment of the charging strategy results, quantifies the performance evaluation index Qp, and proposes an optimization evaluation scheme by comparing it with the performance optimization evaluation threshold Qth, realizing closed-loop optimization control, and effectively solving the problems of lack of dynamic adjustment capability of the charging strategy in the traditional system, insufficient battery temperature control mechanism, and low charging efficiency. Through precise charging strategy optimization and operating status feedback, the system can adapt to the complex thermal environment of the IDC data center, reduce the risk of overheating caused by battery temperature rise, significantly extend battery life, and at the same time ensure the continuous and stable power supply needs of the load, providing solid support for the efficient operation and maintenance of the IDC data center.

[0072] Example 2

[0073] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the micro-environment parameter acquisition module includes an environment acquisition unit and an environment processing unit;

[0074] The environment collection unit deploys environment sensors at different locations in the IDC data room and collects the environment information of the IDC data room through a fixed collection period, including using a temperature sensor to collect environment temperature information, using a humidity sensor to collect environment humidity information, using an air flow rate sensor to collect environment flow rate information, and connecting the refrigeration equipment through the Internet of Things to obtain the refrigeration equipment power information, to form an environment collection data group;

[0075] The ambient temperature information includes the ambient temperature Te; the ambient humidity information includes the ambient humidity He; the ambient flow rate information includes the ambient flow rate Va; the refrigeration equipment power information includes the refrigeration equipment power Pc;

[0076] The environment processing unit performs preprocessing on the environment collection data group, including denoising preprocessing, data completion preprocessing and normalization preprocessing, to form a processed environment characteristic vector E={Ten, Hen, Van, Pcn}, where Ten represents the normalized environment temperature, Hen represents the normalized environment humidity, Van represents the normalized environment flow rate, and Pcn represents the normalized refrigeration equipment power;

[0077] Among them, the denoising preprocessing uses the median filtering algorithm to eliminate outliers, including abnormal data points caused by short-term sensor fluctuations; the data completion preprocessing uses the nearest neighbor interpolation method to complete the missing data in the collection; the normalization preprocessing uses the minimum-maximum normalization method to eliminate differences in different dimensions.

[0078] The battery status monitoring module includes a battery parameter acquisition unit and a battery data processing unit;

[0079] The battery parameter acquisition unit monitors the operating status of the UPS lithium battery and collects battery charging and discharging information, battery pack temperature information and battery internal resistance information through a fixed acquisition cycle to form a battery acquisition data group, including battery remaining capacity SOC, charging power Pchg, discharging power Pd, battery pack temperature Tbat and battery internal resistance Rint;

[0080] The battery data processing unit performs data cleaning on the battery collection data group to form a processed battery state characteristic vector B={SOC, Pchg, Pd, Tbat, Rint};

[0081] The data cleaning process includes using a median filter to perform data cleaning preprocessing.

[0082] The thermal impact assessment module includes a data fitting unit and a comprehensive analysis unit;

[0083] The data fitting unit obtains the environmental temperature influence component Tenf by associating the environmental characteristic vector E with the battery pack temperature Tbat in the battery state characteristic vector B;

[0084] The ambient temperature influence component Tenf is obtained by the following calculation formula:

[0085] ;

[0086] Wherein, t1, t2, t3, t4 and t5 represent the preset weight values ​​of the normalized ambient temperature Ten, the normalized ambient humidity Hen, the normalized ambient flow rate Van, the normalized refrigeration equipment power Pcn and the battery pack temperature Tbat, respectively, and t1+t2+t3+t4+t5=1, and the specific value is set by the user.

[0087] In this embodiment, the unified environmental characteristic vector E and battery state characteristic vector B formed by the micro-environment parameter acquisition module and the battery state monitoring module provide accurate quantitative indicators of the environment and battery coupling relationship for the subsequent comprehensive impact analysis, and through strict data acquisition and preprocessing processes, significantly improve the data accuracy and robustness of the system in a dynamically changing environment. In particular, the extraction of the ambient temperature impact component Tenf can accurately quantify the effect of environmental factors on battery temperature changes, providing a scientific basis for the subsequent optimization of charging strategies, thereby solving the decision-making error problem caused by data noise, missing data and inconsistent dimensions in traditional systems.

[0088] Example 3

[0089] This embodiment is explained in Example 2. Please refer to Figure 1 Specifically: the comprehensive analysis unit performs fitting calculation according to the ambient temperature influence component Tenf and the battery state characteristic vector B to obtain the comprehensive influence index Timp of the microenvironment on the battery temperature;

[0090] The comprehensive impact index Timp is obtained by the following calculation formula:

[0091] ;

[0092] In the formula, ln represents the natural logarithm function, It indicates the difference trend of the ambient temperature impact component on the battery temperature, highlighting the state of the large temperature difference affecting the temperature. It is suitable for high or low temperature abnormal scenarios. Rint represents the battery internal resistance, which is specifically used to reflect the correlation between the battery internal resistance and temperature rise. The larger the internal resistance, the more heat accumulation and the higher the temperature rise risk. The internal resistance is placed in the denominator to reduce its contribution to the overall index. Indicates the remaining battery capacity. The square root of the remaining battery capacity reflects the buffering effect of the battery's available power on temperature rise.

[0093] The strategy optimization module includes an optimization analysis unit and an optimization calculation unit;

[0094] The optimization analysis unit analyzes the association between the battery status and the environmental requirements according to the received comprehensive impact index Timp and the battery status characteristic vector B, and according to the operation requirements of the UPS lithium battery, including battery temperature safety association analysis, battery remaining capacity SOC association analysis and temperature rise trend association analysis, and triggers the optimization logic;

[0095] The trigger optimization logic is specifically triggered in the following ways:

[0096] When the comprehensive impact index Timp>0 and the battery pack temperature Tbat>Tsafe, the overheat protection logic is triggered and adjustment suggestions are generated, including limiting the charging power to avoid battery overheating;

[0097] When the battery remaining SOC is less than 10%, the priority charging logic is triggered to generate adjustment suggestions, including increasing the charging power to meet the minimum power requirement;

[0098] When the comprehensive impact index Timp is less than 0, the logic of lifting the charging power limit is triggered and adjustment suggestions are generated, including allowing the charging power to be increased;

[0099] Among them, Tsafe represents the temperature threshold, specifically the initial preset battery temperature safety threshold.

[0100] The optimization calculation unit dynamically calculates the optimized charging power Pr according to the battery pack temperature information, the battery internal resistance information, the operation requirements of the UPS lithium battery and the remaining battery capacity SOC, and obtains the result of the dynamic adjustment charging strategy;

[0101] The charging power Pr is obtained by the following calculation formula:

[0102] ;

[0103] In the formula, Pchgmax represents the upper limit charging power supported by the UPS lithium battery, and SOCmax represents the maximum capacity of the battery pack;

[0104] The result of dynamically adjusting the charging strategy is obtained by integrating the result of triggering the optimization logic and the charging power Pr.

[0105] In this embodiment, the comprehensive analysis unit obtains the comprehensive influence index Timp of the microenvironment on the battery temperature by fitting and calculating the environmental temperature influence component Tenf and the battery state characteristic vector B, which effectively solves the problem of insufficient quantification of the coupling relationship between the environment and the battery in the traditional method, and further completes the deep correlation analysis of the environmental demand and the battery operation state through the optimization analysis unit, and triggers the optimization logic according to the actual operation demand of the UPS lithium battery. The trigger logic can not only identify the battery temperature rise risk in time, but also give priority to guaranteeing the power supply demand when the remaining battery is insufficient, or appropriately release the charging power limit when the temperature trend is good. Under the guidance of the trigger logic, the optimization calculation unit dynamically calculates the optimized charging power Pr, integrates the results of the trigger optimization logic, generates the dynamic adjustment charging strategy results, fully adapts to the changes in the battery state and environmental demand, and can realize the real-time adjustment of the UPS lithium battery operation strategy, effectively avoiding the overheating, low charging efficiency or excessive battery aging caused by the fixed strategy in the traditional system that cannot flexibly respond to the temperature rise trend, insufficient power or changes in temperature control conditions. This intelligent strategy adjustment mechanism not only improves the accuracy of charging strategies and system response speed, but also ensures the long-term stability of batteries and the safety of IDC room operations, laying the foundation for efficient and intelligent battery management.

[0106] Example 4

[0107] This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the decision execution module includes an instruction generation unit and a security mode detection unit;

[0108] The instruction generation unit takes the received charging power Pr and the result of the dynamic adjustment of the charging strategy as the target value of the charging power, specifically sets the charging power Pr as the real-time target value of the charging power, that is, the limit value of the new actual charging power Po, and then converts it into a control instruction for specific execution, including adjusting the inverter of the UPS lithium battery to perform specific charging current and voltage power adjustments;

[0109] The safety mode detection unit monitors the difference between the charging power Pr and the actual charging power Po in real time, obtains the absolute difference △P, and compares it with the preset allowable deviation threshold Pthe to obtain the safety mode state trigger result;

[0110] The absolute difference △P is obtained by the calculation formula △P=|Pr-Po|;

[0111] The safety mode status trigger result is obtained by the following matching method:

[0112] When the absolute difference △P ≥ the allowable deviation threshold Pthe, the safety mode status trigger result is obtained as triggered, entering the safety mode, limiting the charging power, including limiting the charging power Pr to 0.5 times, and simultaneously monitoring the battery pack temperature Tbat status in real time. When the battery pack temperature Tbat ≥ Tsafe temperature threshold, the temperature protection is triggered, charging is stopped and an early warning prompt is issued. At the same time, the normalized refrigeration equipment power Pcn is proportionally adjusted to control the environmental status in the IDC data room.

[0113] The evaluation feedback module includes a UPS operation status detection unit and a performance evaluation unit;

[0114] The UPS operation status detection unit monitors the operation status of the UPS lithium battery after executing the dynamic adjustment charging strategy result, including the actual charging power Po, the battery pack temperature Tbat, the battery remaining capacity SOC and the battery internal resistance Rint, and obtains the execution feedback state vector F={Po, Tbat, SOC, Rint};

[0115] The performance evaluation unit performs correlation analysis based on the obtained execution feedback state vector F and the result of the dynamic adjustment of the charging strategy, obtains the performance evaluation index Qp, and compares it with a preset performance optimization evaluation threshold Qth to obtain a charging strategy optimization evaluation scheme.

[0116] The performance evaluation index Qp is obtained by the following calculation formula:

[0117] ;

[0118] In the formula, Pr represents the charging power, Po represents the actual charging power, Tbat represents the battery pack temperature, Tsafe represents the temperature threshold, and Rint represents the battery internal resistance. Indicates the influence coefficient, specifically the influence coefficient of the deviation between the charging power Pr and the actual charging power Po. The smaller the deviation, the more accurate the strategy execution and the higher the charging efficiency. Indicates the absolute value of the temperature difference, which indicates the distance between the battery temperature and the safety threshold. The smaller the temperature difference, the better the temperature control effect of the strategy. It represents the square root of the battery internal resistance Rint, reflecting the inhibitory effect of the battery health status on the charging strategy. The smaller the value, the better the battery health.

[0119] The charging strategy optimization evaluation scheme is obtained by the following matching method:

[0120] When the performance evaluation index Qp is less than the performance optimization evaluation threshold Qth, the optimization effect obtained satisfies the expected effect and the strategy solution is not adjusted;

[0121] When the performance evaluation index Qp ≥ the performance optimization evaluation threshold Qth, the optimization effect does not meet the expected effect and the iterative adjustment strategy is obtained, including adjusting the charging power Pr, adjusting the trigger optimization logic conditions and the weight in the calculation formula of the ambient temperature influence component Tenf.

[0122] In this embodiment, the optimized charging power Pr is converted into a control instruction by the instruction generation unit, and the charging current and voltage of the UPS lithium battery are adjusted in real time to ensure the accurate execution of the charging strategy, dynamically optimize the environmental state of the IDC data room, and ensure the safety and environmental adaptability of the charging strategy under multi-variable interference. The evaluation feedback module collects the execution feedback state vector F in real time through the UPS operation state detection unit, and the performance evaluation unit comprehensively analyzes the feedback state vector and the dynamic adjustment charging strategy result, calculates the performance evaluation index Qp, and compares it with the performance optimization evaluation threshold Qth. The system generates an iterative adjustment strategy scheme, covering the adjustment of the charging power Pr, the optimization of the trigger logic conditions, and the modification of the calculation weight of the ambient temperature influence component Tenf, forming an efficient closed-loop optimization mechanism, and realizing the dynamic verification and feedback adjustment of the charging strategy execution effect. Compared with the traditional scheme that only relies on fixed parameters or manual evaluation, it ensures the comprehensive improvement of charging efficiency, temperature control capability and battery health management, thereby greatly enhancing the safety, flexibility and long-term reliability of the UPS lithium battery system in the IDC room.

[0123] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. UPS lithium battery system for IDC data center, characterized by: It includes micro-environment parameter acquisition module, battery status monitoring module, thermal impact assessment module, strategy optimization module, decision execution module and evaluation feedback module; The micro-environment parameter acquisition module deploys environmental sensors at different locations in the IDC data room, collects environmental information of the IDC data room through a fixed acquisition cycle, and forms an environmental characteristic vector E after processing the environmental information; The battery status monitoring module monitors the operating status of the UPS lithium battery and collects battery charging and discharging information, battery pack temperature information and battery internal resistance information through a fixed collection cycle to form a battery status characteristic vector B; The thermal impact assessment module obtains the comprehensive impact index Timp of the microenvironment on the battery temperature by fitting the environmental characteristic vector E and the battery state characteristic vector B; The thermal impact assessment module includes a data fitting unit and a comprehensive analysis unit; The data fitting unit obtains the environmental temperature influence component Tenf by associating the environmental characteristic vector E with the battery pack temperature Tbat in the battery state characteristic vector B; The ambient temperature influence component Tenf is obtained by the following calculation formula: ； Wherein, t1, t2, t3, t4 and t5 represent the preset weight values ​​of the normalized ambient temperature Ten, the normalized ambient humidity Hen, the normalized ambient flow rate Van, the normalized refrigeration equipment power Pcn and the battery pack temperature Tbat, respectively, and t1+t2+t3+t4+t5=1, and the specific value is set by the user; The comprehensive analysis unit performs fitting calculation according to the ambient temperature influence component Tenf and the battery state characteristic vector B to obtain the comprehensive influence index Timp of the microenvironment on the battery temperature; The comprehensive impact index Timp is obtained by the following calculation formula: ； In the formula, ln represents the natural logarithm function, It indicates the difference trend of the ambient temperature impact component on the battery temperature, highlighting the state of the large temperature difference on the temperature. Rint represents the battery internal resistance, which is specifically used to reflect the correlation between the battery internal resistance and temperature rise. Indicates the remaining battery capacity; The strategy optimization module receives the comprehensive impact index Timp and the battery state characteristic vector B, triggers the optimization logic according to the operation requirements of the UPS lithium battery, dynamically calculates the optimized charging power Pr, and obtains the result of dynamically adjusting the charging strategy; The decision execution module uses the received charging power Pr and the result of dynamically adjusting the charging strategy as the target value of the charging power, converts the charging power Pr into a control instruction for specific execution, and monitors the difference with the actual charging power Po in real time to obtain the safety mode state trigger result; The evaluation feedback module obtains a performance evaluation index Qp by monitoring the operating status of the UPS lithium battery after executing the dynamic adjustment charging strategy result, and compares it with a preset performance optimization evaluation threshold Qth to obtain a charging strategy optimization evaluation plan.

2. The UPS lithium battery system for IDC data room according to claim 1 is characterized in that: The micro-environment parameter acquisition module includes an environment acquisition unit and an environment processing unit; The environment collection unit deploys environment sensors at different locations in the IDC data room and collects the environment information of the IDC data room through a fixed collection period, including using a temperature sensor to collect environment temperature information, using a humidity sensor to collect environment humidity information, using an air flow rate sensor to collect environment flow rate information, and connecting the refrigeration equipment through the Internet of Things to obtain the refrigeration equipment power information, to form an environment collection data group; The ambient temperature information includes the ambient temperature Te; the ambient humidity information includes the ambient humidity He; the ambient flow rate information includes the ambient flow rate Va; the refrigeration equipment power information includes the refrigeration equipment power Pc; The environment processing unit performs preprocessing on the environment collection data group, including denoising preprocessing, data completion preprocessing and normalization preprocessing, to form a processed environment characteristic vector E={Ten, Hen, Van, Pcn}, where Ten represents the normalized environment temperature, Hen represents the normalized environment humidity, Van represents the normalized environment flow rate, and Pcn represents the normalized refrigeration equipment power; Among them, the denoising preprocessing uses the median filtering algorithm to eliminate outliers, including abnormal data points caused by short-term sensor fluctuations; the data completion preprocessing uses the nearest neighbor interpolation method to complete the missing data in the collection; the normalization preprocessing uses the minimum-maximum normalization method to eliminate differences in different dimensions.

3. The UPS lithium battery system for IDC data room according to claim 2 is characterized in that: The battery status monitoring module includes a battery parameter acquisition unit and a battery data processing unit; The battery parameter acquisition unit monitors the operating status of the UPS lithium battery and collects battery charging and discharging information, battery pack temperature information and battery internal resistance information through a fixed acquisition cycle to form a battery acquisition data group, including battery remaining capacity SOC, charging power Pchg, discharging power Pd, battery pack temperature Tbat and battery internal resistance Rint; The battery data processing unit performs data cleaning on the battery collection data group to form a processed battery state characteristic vector B={SOC, Pchg, Pd, Tbat, Rint}; The data cleaning process includes using a median filter to perform data cleaning preprocessing.

4. The UPS lithium battery system for IDC data room according to claim 1 is characterized in that: The strategy optimization module includes an optimization analysis unit and an optimization calculation unit; The optimization analysis unit analyzes the association between the battery status and the environmental requirements according to the received comprehensive impact index Timp and the battery status characteristic vector B, and according to the operation requirements of the UPS lithium battery, including battery temperature safety association analysis, battery remaining capacity SOC association analysis and temperature rise trend association analysis, and triggers the optimization logic; The trigger optimization logic is specifically triggered in the following ways: When the comprehensive impact index Timp>0 and the battery pack temperature Tbat>Tsafe, the overheat protection logic is triggered; When the remaining battery SOC is less than 10%, the priority charging logic is triggered; When the comprehensive impact index Timp < 0, the logic of lifting the limited charging power is triggered; Among them, Tsafe represents the temperature threshold, specifically the initially preset battery temperature safety threshold.

5. The UPS lithium battery system for IDC data room according to claim 4 is characterized in that: The optimization calculation unit dynamically calculates the optimized charging power Pr according to the battery pack temperature information, the battery internal resistance information, the operation requirements of the UPS lithium battery and the remaining battery capacity SOC, and obtains the result of the dynamic adjustment charging strategy; The charging power Pr is obtained by the following calculation formula: ； In the formula, Pchgmax represents the upper limit charging power supported by the UPS lithium battery, and SOCmax represents the maximum capacity of the battery pack; The result of dynamically adjusting the charging strategy is obtained by integrating the result of triggering the optimization logic and the charging power Pr.

6. The UPS lithium battery system for IDC data room according to claim 5, characterized in that: The decision execution module includes an instruction generation unit and a safety mode detection unit; The instruction generation unit takes the received charging power Pr and the result of the dynamic adjustment of the charging strategy as the target value of the charging power, specifically sets the charging power Pr as the real-time target value of the charging power, and then converts it into a control instruction for specific execution, including adjusting the inverter of the UPS lithium battery to perform specific charging current and voltage power adjustments; The safety mode detection unit monitors the difference between the charging power Pr and the actual charging power Po in real time, obtains the absolute difference △P, and compares it with the preset allowable deviation threshold Pthe to obtain the safety mode state trigger result; The absolute difference △P is obtained by the calculation formula △P=|Pr-Po|; The safety mode status trigger result is obtained by the following matching method: When the absolute difference △P ≥ the allowable deviation threshold Pthe, the safety mode status trigger result is obtained as triggered, entering the safety mode, limiting the charging power, including limiting the charging power Pr to 0.5 times, and simultaneously monitoring the battery pack temperature Tbat status in real time. When the battery pack temperature Tbat ≥ Tsafe temperature threshold, the temperature protection is triggered, charging is stopped and an early warning prompt is issued. At the same time, the normalized refrigeration equipment power Pcn is proportionally adjusted to control the environmental status in the IDC data room.

7. The UPS lithium battery system for IDC data room according to claim 6, characterized in that: The evaluation feedback module includes a UPS operation status detection unit and a performance evaluation unit; The UPS operation status detection unit monitors the operation status of the UPS lithium battery after executing the dynamic adjustment charging strategy result, including the actual charging power Po, the battery pack temperature Tbat, the battery remaining capacity SOC and the battery internal resistance Rint, and obtains the execution feedback state vector F={Po, Tbat, SOC, Rint}; The performance evaluation unit performs correlation analysis based on the obtained execution feedback state vector F and the result of the dynamic adjustment of the charging strategy, obtains the performance evaluation index Qp, and compares it with a preset performance optimization evaluation threshold Qth to obtain a charging strategy optimization evaluation scheme.

8. The UPS lithium battery system for IDC data room according to claim 7, characterized in that: The performance evaluation index Qp is obtained by the following calculation formula: ； In the formula, Pr represents the charging power, Po represents the actual charging power, Tbat represents the battery pack temperature, Tsafe represents the temperature threshold, and Rint represents the battery internal resistance. Indicates the influence coefficient, specifically the influence coefficient of the deviation between the charging power Pr and the actual charging power Po; The charging strategy optimization evaluation scheme is obtained by the following matching method: When the performance evaluation index Qp is less than the performance optimization evaluation threshold Qth, the optimization effect obtained satisfies the expected effect and the strategy solution is not adjusted; When the performance evaluation index Qp ≥ the performance optimization evaluation threshold Qth, the optimization effect does not meet the expected effect and the iterative adjustment strategy is obtained, including adjusting the charging power Pr, adjusting the trigger optimization logic conditions and the weight in the calculation formula of the ambient temperature influence component Tenf.

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