Intelligent UPS and storage battery comprehensive monitoring method

Abstract

The present application relates to the field of data processing, and particularly relates to a kind of intelligent UPS and battery comprehensive monitoring method. Including: obtaining operating load, residual power and the voltage data of each battery cell in battery pack;Calculate the degree of unhealthiness of the battery pack;For each battery pack, calculate and distribute initial discharge ratio;Get the scheduling load intensity of each battery pack, calculate the un-degradation degree of each battery pack, and calculate the voltage difference index between battery cells;Evaluate the actual available proportion of the residual power shown by each battery pack;With the initial discharge ratio of each battery pack as a reference, adjust it based on the actual available proportion, generate discharge control instructions for inter-battery pack power balance collaborative control;According to the discharge control instruction, control each battery pack to discharge, and evaluate the health status of the standby power supply system. The present application can realize intelligent load distribution and collaborative control among battery packs, optimize the operating state and service life of battery pack.

Description

Technical Field

[0001] This invention relates to the field of data processing, and specifically to an intelligent integrated monitoring method for UPS and batteries. Background Technology

[0002] With the rapid development of information technology and critical infrastructure, uninterruptible power supply (UPS) systems, as the core of backup power protection, are of paramount importance in terms of reliability. Battery banks are a key component of UPS systems, and their performance directly determines the availability of the entire power system.

[0003] Currently, advanced intelligent UPS systems in the industry can continuously monitor key operating parameters of batteries, such as voltage, current, temperature, internal resistance, and inter-cell voltage difference. Based on this data, the system can estimate the battery's state of health (SOH) and remaining charge (SOC), thereby providing a certain degree of proactive early warning and predictive maintenance. These systems aim to extend the overall battery life by optimizing charging and discharging strategies to avoid battery overload and deep discharge, ultimately improving power supply reliability and reducing long-term operation and maintenance costs.

[0004] However, the industry still faces a significant challenge in capacity calibration, a core component of battery condition assessment. Traditional calibration methods rely on a Battery Management System (BMS) to measure the battery's actual capacity by performing a complete 100% discharge-charge cycle. This method is inherently destructive: it not only accelerates battery aging and shortens their lifespan, but more importantly, it requires isolating the battery pack from the system during calibration, leading to power outages and reduced system availability. Furthermore, the process is time-consuming (typically several hours to tens of hours) and requires specialized personnel, resulting in high labor and time costs. Summary of the Invention

[0005] This invention provides an intelligent integrated monitoring method for UPS and batteries to solve existing problems.

[0006] The intelligent UPS and battery integrated monitoring method of the present invention adopts the following technical solution:

[0007] One embodiment of the present invention provides an intelligent UPS and battery integrated monitoring method, the method comprising the following steps:

[0008] Acquire the operating load, remaining capacity, and voltage data of each battery cell in the backup power system;

[0009] For each battery pack, the degree of unhealth of the battery pack is calculated based on the change in its remaining charge under operating load during the continuous monitoring period;

[0010] Based on the health status and current remaining power of each battery pack, the initial discharge ratio is calculated and allocated for each battery pack.

[0011] The scheduling load intensity of each battery pack is obtained, and the non-degradation degree of each battery pack is calculated based on the historical change data of the scheduling load intensity and unhealthiness of each battery pack. The voltage difference index between cells is calculated based on the voltage data of each cell.

[0012] Based on the inter-cell voltage difference index and the degree of non-degradation of each battery pack, assess the actual usable proportion of the remaining capacity displayed by each battery pack;

[0013] Based on the initial discharge ratio of each battery pack, the discharge control command is adjusted according to the actual available ratio to generate discharge control commands for the coordinated control of power balance among battery packs.

[0014] The system controls the discharge of each battery pack according to the discharge control command, monitors the status changes of the backup power system, and assesses the health status of the backup power system.

[0015] Optionally, for each battery pack, the health status of the battery pack is calculated based on the change in its remaining charge under operating load during a continuous monitoring period, specifically including:

[0016] For any given battery pack, the battery pack is continuously monitored for a preset duration, and the battery pack is controlled to be in a non-charging discharge state during the same duration.

[0017] Obtain the operating load of the battery pack during the continuous duration, as well as the remaining charge of the battery pack at the start and end times of the continuous duration;

[0018] Calculate the difference between the remaining power at the start time and the remaining power at the end time to obtain the change in remaining power over the continuous time period;

[0019] Take the reciprocal of the running load to obtain the load factor;

[0020] Obtain the historical maximum battery capacity decay value, which is the maximum battery capacity reduction value of each battery pack under the same time period obtained from historical monitoring data.

[0021] The ratio of the change in remaining power to the historical maximum power decay value is determined as the relative decay ratio;

[0022] Multiplying the load factor and the relative degradation ratio yields the degree of unhealthiness of the battery pack.

[0023] Optionally, based on the health status and current remaining charge of each battery pack, an initial discharge ratio is calculated and allocated for each battery pack, specifically including:

[0024] For the backup power system at the current moment, obtain the health status and current remaining power of each battery pack;

[0025] Determine the maximum unhealthy level across all battery packs, and the maximum current remaining charge level.

[0026] For any given battery pack, the health degradation coefficient is obtained by comparing the unhealth level of the battery pack with the maximum value of the unhealth level.

[0027] Calculate the difference between the maximum current remaining power and the current remaining power of the battery pack to obtain the power gap value;

[0028] The ratio of the power shortage value to the maximum current remaining power value is determined as the relative power shortage coefficient;

[0029] Multiplying the health degradation coefficient by the relative power deficiency coefficient yields the discharge ratio penalty factor for the battery pack. The value of the discharge ratio penalty factor is negatively correlated with the value of the initial discharge ratio.

[0030] The discharge ratio penalty factor for each battery pack is normalized, and the proportion of the normalized value of each battery pack to the sum of the values ​​of all battery packs is determined as the initial discharge ratio of each battery pack.

[0031] Optionally, the scheduling load intensity of each battery pack is obtained, and the non-degradation degree of each battery pack is calculated based on the historical changes in the scheduling load intensity and unhealthiness of each battery pack, specifically including:

[0032] Obtain the initial discharge ratio allocated to each battery pack in each cycle within a preset historical period;

[0033] Calculate the sum of the initial discharge ratios of each battery pack in all cycles of the preset historical period to obtain the historical cumulative scheduling value;

[0034] Obtain the rated capacity of each battery pack;

[0035] The ratio of the historical cumulative scheduling value to the rated capacity of each battery pack is determined as the scheduling load intensity, which characterizes the strength of the scheduling task undertaken per unit capacity.

[0036] The degradation inhibition coefficient of each battery pack is calculated based on historical data on the changes in the unhealth status of each battery pack.

[0037] The product of the scheduling load intensity and the degradation suppression coefficient of each battery pack is determined as the degree of non-degradation of that battery pack.

[0038] Optionally, the degradation suppression coefficient of each battery pack is calculated based on historical data on the changes in the unhealth status of each battery pack, specifically including:

[0039] For the current moment, obtain the health status record of each battery pack within a preset historical period;

[0040] For any given battery pack, based on the unhealthy status records, calculate the change in the unhealthy status of the battery pack over adjacent recording periods;

[0041] The maximum value among all the changes is determined as the maximum single degradation, and the average value of all the changes is calculated to obtain the average degradation.

[0042] The degradation suppression coefficient, which characterizes the rate of decline in the health status of the battery pack, is obtained by adding the maximum single degradation amount and the average degradation amount and taking the reciprocal.

[0043] Optionally, the voltage difference index between cells is calculated based on the voltage data of each cell, specifically including:

[0044] For any given battery pack, obtain the current voltage data of all cells within it;

[0045] Calculate the difference between the current voltage data of each cell in the battery pack and the current voltage data of any other cell;

[0046] For each cell, the maximum value among all calculated voltage differences is determined as the individual maximum voltage difference of that cell;

[0047] The arithmetic mean of the maximum individual voltage difference of all cells is determined as the average cell voltage difference of the battery pack.

[0048] The maximum value among the maximum individual voltage differences of all cells is determined as the maximum cell voltage difference of the battery pack.

[0049] The average cell voltage difference and the maximum cell voltage difference are defined as the inter-cell voltage difference indicators.

[0050] Optionally, based on the inter-cell voltage difference index and the degree of non-degradation of each battery pack, the actual usable proportion of the remaining capacity displayed by each battery pack is evaluated, specifically including:

[0051] For any battery pack at the current moment, obtain its degree of non-degradation and inter-cell voltage difference indicators;

[0052] Multiply the non-degradation degree, the reciprocal of the average cell voltage difference, and the reciprocal of the maximum cell voltage difference to obtain an intermediate evaluation value characterizing the actual usability of the battery pack's capacity.

[0053] The intermediate evaluation values ​​of all battery packs are normalized to obtain the actual usable percentage of remaining power displayed for each battery pack.

[0054] Optionally, based on the initial discharge ratio of each battery pack, adjustments are made according to the actual available ratio to generate discharge control commands for coordinated control of power balance among battery packs, specifically including:

[0055] Compare the actual usable percentage of each battery pack with the preset usable percentage threshold;

[0056] Battery packs whose actual usable ratio is lower than the preset usable ratio threshold are marked as battery packs to be compensated.

[0057] For each battery pack to be compensated, the amount of discharge difference that needs to be compensated is calculated based on the degree to which its actual usable ratio is lower than the preset usable ratio threshold.

[0058] All battery packs whose actual usable percentage is higher than the preset usable percentage threshold are marked as candidate compensation battery packs.

[0059] Based on the actual available ratio and remaining power status of each candidate compensation battery pack, the discharge difference that needs to be compensated is allocated to at least one candidate compensation battery pack.

[0060] For each battery pack to be compensated, the compensation ratio is calculated based on the difference in discharge amount that needs to be compensated, and the compensation ratio is subtracted from the initial discharge ratio to obtain the final discharge ratio of each battery pack to be compensated.

[0061] For each candidate compensation battery pack with allocated discharge difference, the final discharge ratio of each candidate compensation battery pack with allocated discharge difference is obtained by adding the initial discharge ratio to the compensation ratio.

[0062] The final discharge ratios of all battery packs are adjusted and integrated to generate discharge control commands for controlling the specific discharge current of each battery pack.

[0063] Optionally, monitor changes in the status of the backup power system and assess its health status, specifically including:

[0064] Start the monitoring and evaluation period;

[0065] During the monitoring and evaluation period, the actual usable ratio of each battery pack is continuously calculated according to the preset time cycle.

[0066] Calculate the reduction in the actual usable percentage between two consecutive monitoring and evaluation periods;

[0067] The maximum value of all reductions is determined as the maximum decay rate;

[0068] The difference between the actual usable proportion at the start and end of the monitoring period is calculated as the total attenuation.

[0069] Obtain the actual available percentage of each battery pack at the end of the monitoring period;

[0070] The first evaluation factor is obtained by taking the reciprocal of the total attenuation.

[0071] The ratio of the actual usable percentage of each battery pack to the maximum decay rate at the end of the monitoring period is used as the second evaluation factor.

[0072] Multiplying the first evaluation factor by the second evaluation factor yields the health status performance value of the backup power system.

[0073] This invention proposes an intelligent UPS and battery integrated monitoring system, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of an intelligent UPS and battery integrated monitoring method.

[0074] The beneficial effects of the technical solution of the present invention are:

[0075] In this embodiment of the invention, the health and degradation trend of the battery pack are dynamically assessed by analyzing its power loss performance under real load, and the actual usable power is accurately calculated by combining the cell voltage difference. Based on this, the system can automatically optimize the discharge ratio of each battery pack, dynamically transferring the load from weakened battery packs to healthy battery packs, thereby achieving power balance and synergistic life extension among battery packs. This method completely avoids the damage to batteries and the risk of service interruption caused by traditional full discharge calibration, realizing a shift from "passive replacement" to "proactive prediction and optimization" operation and maintenance mode, significantly improving the reliability of the power supply system and reducing the total life cycle cost. Attached Figure Description

[0076] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0077] Figure 1 A flowchart illustrating an intelligent UPS and battery integrated monitoring method provided in one embodiment of the present invention;

[0078] Figure 2 This is a structural diagram of an intelligent UPS and battery integrated monitoring system provided in one embodiment of the present invention. Detailed Implementation

[0079] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent UPS and battery integrated monitoring method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0080] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0081] The following description, in conjunction with the accompanying drawings, details a specific scheme for an intelligent UPS and battery integrated monitoring method provided by the present invention.

[0082] This invention provides an intelligent integrated monitoring method for UPS and batteries. Please refer to [link / reference]. Figure 1 The diagram illustrates a flowchart of an intelligent UPS and battery integrated monitoring method according to an embodiment of the present invention, which includes the following steps:

[0083] S101. Obtain the operating load, remaining power, and voltage data of each battery cell in the backup power system.

[0084] For example, this step is implemented through a three-tier architecture of an intelligent UPS system:

[0085] Bottom layer (physical acquisition layer): Hall current sensors installed on the battery output circuit directly measure the real-time current, and calculate the real-time output power and operating load rate by combining the total battery pack voltage. The battery pack terminal voltage, individual cell voltage, and temperature are directly acquired by the voltage sampling circuit and temperature sensor built into the BMS (Battery Management System).

[0086] Middle layer (control processing layer): The system's main controller receives raw data from the sensors, filters and calculates it, and converts it into an intuitive list of remaining battery percentage, operating load percentage, and individual cell voltages.

[0087] Upper layer (data application layer): The processed parameters are uploaded to the monitoring platform in real time through communication interfaces (such as SNMP, CAN or Modbus protocol) to provide a data foundation for subsequent analysis.

[0088] Among them, the acquisition of runtime load:

[0089] First, the Hall current sensor senses the battery pack's output current in real time and converts it into a standard electrical signal. Simultaneously, the battery management system accurately measures the battery pack's total output voltage at the current moment. Upon receiving these current and voltage signals, the main controller calculates the battery pack's instantaneous output power by multiplying them. Finally, the main controller compares this instantaneous output power with the system's preset rated output power and calculates a percentage value. This percentage value is defined as the battery pack's "operating load," which directly reflects how much of its maximum capacity the battery pack's current output power represents.

[0090] How to get the remaining battery power:

[0091] The battery management system continuously and accurately tracks every current flowing into and out of the battery pack, and continuously accumulates these currents (i.e., "capacity integration"). Simultaneously, the system combines pre-calibrated battery characteristic curves (such as voltage performance at different capacities) and real-time monitored temperature data to dynamically correct and calibrate the accumulated value of the aforementioned capacity integration, eliminating the influence of measurement drift and environmental factors. After correction, the battery management system calculates and outputs a value from 0% to 100%, which represents the percentage of the battery pack's estimated usable capacity in its current state relative to its total capacity in its new state; this is referred to as the "current remaining capacity."

[0092] Obtaining cell voltage data:

[0093] The battery management system (BMS) utilizes its internal, sophisticated multi-channel voltage detection capabilities to simultaneously and independently measure the voltage across each cell in a series-connected battery pack. To ensure data consistency over time, the system employs synchronous sampling technology, guaranteeing the capture of voltage values ​​from all cells at nearly the same moment, thus preventing data misalignment caused by instantaneous load fluctuations. After measurement, the BMS compiles all cell voltage values, along with their corresponding cell identifiers, into a single, complete data packet.

[0094] S102. For each battery pack, calculate the degree of unhealthiness of the battery pack based on the change in remaining charge under operating load during the continuous monitoring period.

[0095] In this embodiment, for each battery pack, the degree of unhealthiness of the battery pack is calculated based on the change in its remaining charge under operating load during a continuous monitoring period, specifically including:

[0096] For any given battery pack, the battery pack is continuously monitored for a preset duration, and the battery pack is controlled to be in a non-charging discharge state during the same duration.

[0097] Obtain the operating load of the battery pack during the continuous duration, as well as the remaining charge of the battery pack at the start and end times of the continuous duration;

[0098] Calculate the difference between the remaining power at the start time and the remaining power at the end time to obtain the change in remaining power over the continuous time period;

[0099] Take the reciprocal of the running load to obtain the load factor;

[0100] Obtain the historical maximum battery capacity decay value, which is the maximum battery capacity reduction value of each battery pack under the same time period obtained from historical monitoring data.

[0101] The ratio of the change in remaining power to the historical maximum power decay value is determined as the relative decay ratio;

[0102] Multiplying the load factor and the relative degradation ratio yields the degree of unhealthiness of the battery pack.

[0103] For example, when quantifying the health status of a single battery pack (labeled a), a standardized data acquisition process is first performed. Specifically, the battery pack is kept in a discharged state for a continuous three-hour period, during which charging is prohibited. Using the aforementioned data acquisition method, the average operating load of the battery pack during this monitoring period is acquired and recorded, denoted as . .

[0104] At the same time, the remaining power at the start of the monitoring period is accurately recorded. Remaining battery power at the end The difference between the two This allows us to obtain the change in remaining electricity during the monitoring period.

[0105] The computational logic aims to capture abnormal performance degradation of the battery under light load. Its core relationship can be expressed as: average operating load during the monitoring period. The smaller the value, the more the remaining power changes. Compared to a historical reference value—that is, the maximum capacity degradation value obtained from historical data of all battery packs under the same three-hour monitoring duration. The higher the ratio, the more unhealthy the battery pack is.

[0106] Optionally, maximum power decay value The method for obtaining this value can be as follows: Extract the maximum reduction in remaining charge of each battery pack under discharge conditions from the historical monitoring data of all battery packs in the system within the same monitoring duration (e.g., three consecutive hours). This value can be dynamically updated based on full lifecycle data, or obtained statistically using a sliding window mechanism (e.g., data from the most recent year) to ensure that it reflects the maximum attenuation benchmark of the current operating stage of the system.

[0107] Based on this, the battery pack's health status is... The calculation formula can be:

[0108] ;

[0109] in, This can be considered a load influence factor determined by the operating load, and It reflects the relative decay rate of the current remaining power compared to historical extreme cases.

[0110] By using the above method, synchronous calculations can be performed on each battery pack in the system to obtain a set of indicators reflecting the current performance status of each battery pack and its degree of unhealthiness.

[0111] S103. Calculate and allocate the initial discharge ratio for each battery pack based on the unhealth status and current remaining charge of each battery pack.

[0112] In this embodiment, based on the unhealth status and current remaining power of each battery pack, an initial discharge ratio is calculated and allocated for each battery pack, specifically including:

[0113] For the backup power system at the current moment, obtain the health status and current remaining power of each battery pack;

[0114] Determine the maximum unhealthy level across all battery packs, and the maximum current remaining charge level.

[0115] For any given battery pack, the health degradation coefficient is obtained by comparing the unhealth level of the battery pack with the maximum value of the unhealth level.

[0116] Calculate the difference between the maximum current remaining power and the current remaining power of the battery pack to obtain the power gap value;

[0117] The ratio of the power shortage value to the maximum current remaining power value is determined as the relative power shortage coefficient;

[0118] Multiplying the health degradation coefficient by the relative power deficiency coefficient yields the discharge ratio penalty factor for the battery pack. The value of the discharge ratio penalty factor is negatively correlated with the value of the initial discharge ratio.

[0119] The discharge ratio penalty factor for each battery pack is normalized, and the proportion of the normalized value of each battery pack to the sum of the values ​​of all battery packs is determined as the initial discharge ratio of each battery pack.

[0120] For example, in the operation and management of battery packs, it is necessary to periodically allocate initial discharge ratios. This allocation process is typically performed on a 24-hour cycle. The allocation decision is mainly based on two dynamic indicators: one is the degree of unhealthiness of each battery pack calculated in the most recent analysis cycle. Secondly, the remaining power of each battery pack is displayed in real time at the time of allocation. .

[0121] The core principle of allocation is to protect battery packs in poor condition and prevent them from over-discharging. Specifically, for any battery pack at analysis time t... If its level of unhealthiness The maximum level of unhealthiness relative to all current battery packs ratio The larger the value, the higher its current remaining battery power. With the maximum remaining capacity of all battery packs The difference The larger the value, the worse the battery pack's health and the lower its real-time charge. Therefore, a smaller initial discharge ratio should be assigned to it to prevent this "weak" pack from falling into deep discharge, which would accelerate its aging.

[0122] To quantify the extent to which the discharge ratio should be reduced, an intermediate parameter is introduced, called the discharge ratio penalty factor. Its calculation formula can be:

[0123] ;

[0124] In the formula, the first term This can be considered a health degradation coefficient, reflecting the relative health disadvantage of the battery pack; the second item This can be considered a relative charge deficiency coefficient, reflecting the relative degree of charge depletion in the battery pack. Discharge ratio penalty factor. The higher the value, the stronger the discharge limit should be imposed on the battery pack.

[0125] Next, the discharge ratio penalty factor was calculated for all battery packs. Processing is then performed. First, calculations are performed for each battery pack. Then, the min-max normalization method is used on these... Perform normalization to make the results The numerical value falls between 0 and 1. Finally, each battery pack... Value divided by all battery packs The sum of these values ​​yields the final initial discharge ratio of the battery pack. After obtaining the initial discharge ratio of each battery pack, the battery management system calculates the target discharge current for each battery pack based on the total load demand of the UPS system. The power control unit adjusts the duty cycle of the DC / DC converter in the corresponding power circuit according to this current command, thereby precisely controlling the current drawn from each battery pack and achieving proportional discharge.

[0126] S104. Obtain the scheduling load intensity of each battery pack, calculate the non-degradation degree of each battery pack based on the historical change data of the scheduling load intensity and unhealthiness of each battery pack, and calculate the inter-cell voltage difference index based on the voltage data of each cell.

[0127] In this embodiment, the scheduling load intensity of each battery pack is obtained, and the non-degradation degree of each battery pack is calculated based on the historical change data of the scheduling load intensity and unhealthiness of each battery pack. Specifically, this includes:

[0128] Obtain the initial discharge ratio allocated to each battery pack in each cycle within a preset historical period;

[0129] Calculate the sum of the initial discharge ratios of each battery pack in all cycles of the preset historical period to obtain the historical cumulative scheduling value;

[0130] Obtain the rated capacity of each battery pack;

[0131] The ratio of the historical cumulative scheduling value to the rated capacity of each battery pack is determined as the scheduling load intensity, which characterizes the strength of the scheduling task undertaken per unit capacity.

[0132] The degradation inhibition coefficient of each battery pack is calculated based on historical data on the changes in the unhealth status of each battery pack.

[0133] The product of the scheduling load intensity and the degradation suppression coefficient of each battery pack is determined as the degree of non-degradation of that battery pack.

[0134] The degradation suppression coefficient of each battery pack is calculated based on historical data on the changes in the unhealth status of each battery pack, specifically including:

[0135] For the current moment, obtain the health status record of each battery pack within a preset historical period;

[0136] For any given battery pack, based on the unhealthy status records, calculate the change in the unhealthy status of the battery pack over adjacent recording periods;

[0137] The maximum value among all the changes is determined as the maximum single degradation, and the average value of all the changes is calculated to obtain the average degradation.

[0138] The degradation suppression coefficient, which characterizes the rate of decline in the health status of the battery pack, is obtained by adding the maximum single degradation amount and the average degradation amount and taking the reciprocal.

[0139] The voltage difference index between cells is calculated based on the voltage data of each cell, specifically including:

[0140] For any given battery pack, obtain the current voltage data of all cells within it;

[0141] Calculate the difference between the current voltage data of each cell in the battery pack and the current voltage data of any other cell;

[0142] For each cell, the maximum value among all calculated voltage differences is determined as the individual maximum voltage difference of that cell;

[0143] The arithmetic mean of the maximum individual voltage difference of all cells is determined as the average cell voltage difference of the battery pack.

[0144] The maximum value among the maximum individual voltage differences of all cells is determined as the maximum cell voltage difference of the battery pack.

[0145] The average cell voltage difference and the maximum cell voltage difference are defined as the inter-cell voltage difference indicators.

[0146] For example, to assess the long-term performance degradation trend of a battery pack, it is necessary to calculate a non-degradation index. This index aims to quantify the battery pack's ability to resist aging; a higher value indicates a more stable health condition.

[0147] Calculate the battery pack at the current moment. This requires extracting historical data. First, obtain the most recent calculated health status of the battery pack. This includes the results of N consecutive historical analyses prior to this. Based on this time-series data, the difference in the degree of unhealthiness between two adjacent analyses is calculated and denoted as... .

[0148] Non-degradation It integrates the following four key factors:

[0149] Historical Dispatch Load: Statistics on the initial discharge ratio allocated to this battery pack over the most recent N cycles. The cumulative value, also known as the historical cumulative scheduling value, is denoted as... This value reflects the system's dependence on the battery pack's discharge capacity over a past period.

[0150] Optionally, historical cumulative scheduling value In the calculation, the initial discharge ratio This is a normalized ratio value, reflecting the relative discharge intensity of each battery pack in each scheduling cycle. To further approximate the actual physical load, the initial discharge ratio can be adjusted before accumulation. Multiplying this by the total discharge (or total load power) of the system during the cycle yields the actual discharge contribution of the battery pack within that cycle, which is then accumulated to obtain... This allows for a more accurate reflection of the historical scheduling load.

[0151] Intrinsic capacity benchmark: Obtain the factory rated capacity of the battery pack. This serves as a benchmark for measuring its inherent performance potential.

[0152] Health fluctuation range: from all adjacent differences calculated above Find the maximum value among them, and denote it as . This value reflects the worst transition in unhealthiness within a single cycle.

[0153] Average trend of health status: Calculate all differences The arithmetic mean, denoted as This value reflects the average rate at which the degree of unhealthiness deteriorates over time.

[0154] Based on the above parameters, the battery pack non-degeneracy at time t The calculation formula can be:

[0155] ;

[0156] In the formula, the first term It can be defined as the scheduling load intensity, which characterizes the intensity of historical scheduling tasks undertaken per unit of rated capacity. (Second item) It can be defined as the degradation inhibition coefficient, which reflects the stability of health status over time; the more drastic the fluctuation and the faster the increase in the degree of ill health, the smaller the coefficient.

[0157] Therefore, the degree of non-degradation is obtained by multiplying the dispatch load intensity by the degradation suppression coefficient. Its physical meaning is: if a battery pack can historically withstand a relatively high discharge load (high dispatch load intensity) while its health indicators remain stable and deteriorate slowly (high degradation suppression coefficient), then its degree of non-degradation is... A higher value indicates a lower degree of aging and more reliable performance.

[0158] Furthermore, regarding the inter-cell voltage difference index, it is necessary to first analyze the voltage balance within the battery pack. This requires obtaining cell voltage data over a continuous 10 hours preceding time t.

[0159] For each cell in this battery pack Calculate the absolute value of the difference between its voltage and the voltage of each other cell in the group within the aforementioned time window, and find the maximum value, which is recorded as the maximum voltage difference of the individual cell. .

[0160] Calculate the maximum individual voltage difference for all cells in the battery pack. The arithmetic mean of the values ​​is used to obtain the average cell voltage difference. .

[0161] From the maximum individual voltage difference of all cells In the process, find the global maximum value and record it as the maximum cell voltage difference. .

[0162] And the average cell voltage difference and maximum cell voltage difference It was determined to be the voltage difference index between battery cells.

[0163] Average cell voltage difference reflects the overall voltage balance of the battery pack; the worse the balance, the lower the actual usable capacity. Maximum cell voltage difference reflects the deviation of the worst cell within the pack; extreme imbalance will significantly limit the usable capacity of the entire pack. Together, they can provide a more comprehensive assessment of the 'phantom charge' phenomenon caused by cell inconsistency.

[0164] S105. Based on the inter-cell voltage difference index and the degree of non-degradation of each battery pack, evaluate the actual usable proportion of the remaining power displayed by each battery pack.

[0165] In this embodiment, based on the inter-cell voltage difference index and the degree of non-degradation of each battery pack, the actual usable proportion of the remaining capacity displayed by each battery pack is evaluated, specifically including:

[0166] For any battery pack at the current moment, obtain its degree of non-degradation and inter-cell voltage difference indicators;

[0167] Multiply the non-degradation degree, the reciprocal of the average cell voltage difference, and the reciprocal of the maximum cell voltage difference to obtain an intermediate evaluation value characterizing the actual usability of the battery pack's capacity.

[0168] The intermediate evaluation values ​​of all battery packs are normalized to obtain the actual usable percentage of remaining power displayed for each battery pack.

[0169] For example, when assessing the true usable energy of a battery pack, it is necessary to calculate a key metric: actual usable capacity. This metric aims to correct the remaining capacity displayed by the system to reflect the "virtual capacity" portion that cannot be effectively used due to cell imbalances and battery pack aging.

[0170] For the battery pack at the current time t Its actual usable power The calculation formula can be:

[0171] ;

[0172] in, This represents the degree of non-degradation of the battery pack at the current moment. The physical meaning of the formula is: degree of non-degradation. A higher average cell voltage difference indicates a better overall battery pack health; and maximum cell voltage difference The smaller the value, the better the voltage consistency of the cells within the battery pack. These three factors work together to determine the usability value.

[0173] Calculated for all battery packs The value is processed using the min-max normalization method, mapping it to the [0,1] interval to obtain the normalized actual usable proportion. Battery pack The system displays the current remaining battery power. Ratio of actual availability Multiplying these two values ​​gives the estimated actual remaining usable power of the battery pack at time t.

[0174] Calculate the difference between the actual remaining usable power of each battery pack and the power displayed by the system. This difference is the estimated amount of "phantom power" caused by cell imbalance and aging.

[0175] When power balancing and coordinated control are required, battery packs with significant "phantom power" (i.e., low availability) are identified as targets for compensation. The system will select the battery pack with the most suitable power from those not currently scheduled for primary discharge tasks and with sufficient remaining available power as a supplementary battery pack. During subsequent discharge processes, the supplementary battery pack will dynamically share part of the load to optimize the overall depth of discharge and extend the battery system life.

[0176] This method dynamically assesses and corrects the available capacity of the battery pack by integrating the non-degradation degree and the voltage difference between cells, providing a direct basis for implementing precise power balance and coordinated control.

[0177] S106. Based on the initial discharge ratio of each battery pack, adjust it according to the actual available ratio to generate discharge control commands for coordinated control of power balance among battery packs.

[0178] In this embodiment, the initial discharge ratio of each battery pack is used as a benchmark, and adjustments are made based on the actual available ratio to generate discharge control commands for coordinated control of power balance among battery packs. Specifically, these commands include:

[0179] Compare the actual usable percentage of each battery pack with the preset usable percentage threshold;

[0180] Battery packs whose actual usable ratio is lower than the preset usable ratio threshold are marked as battery packs to be compensated.

[0181] For each battery pack to be compensated, the amount of discharge difference that needs to be compensated is calculated based on the degree to which its actual usable ratio is lower than the preset usable ratio threshold.

[0182] All battery packs whose actual usable percentage is higher than the preset usable percentage threshold are marked as candidate compensation battery packs.

[0183] Based on the actual available ratio and remaining power status of each candidate compensation battery pack, the discharge difference that needs to be compensated is allocated to at least one candidate compensation battery pack.

[0184] For each battery pack to be compensated, the compensation ratio is calculated based on the difference in discharge amount that needs to be compensated, and the compensation ratio is subtracted from the initial discharge ratio to obtain the final discharge ratio of each battery pack to be compensated.

[0185] For each candidate compensation battery pack with allocated discharge difference, the final discharge ratio of each candidate compensation battery pack with allocated discharge difference is obtained by adding the initial discharge ratio to the compensation ratio.

[0186] The final discharge ratios of all battery packs are adjusted and integrated to generate discharge control commands for controlling the specific discharge current of each battery pack.

[0187] For example, this step aims to execute the core decision of power balance coordinated control. Its inputs are the pre-calculated initial discharge ratio and actual available ratio of each battery pack, and its output is a discharge control command that can directly drive the power unit. The specific implementation process is as follows:

[0188] Set a preset usable percentage threshold (e.g., 0.7). This will determine the actual usable percentage for each battery pack. Compare with this threshold.

[0189] Battery packs with an actual usable percentage below the threshold are marked as battery packs requiring compensation. These battery packs have significantly lower usable capacity than displayed due to internal imbalances or aging. If discharged as planned, they are likely to reach the cutoff voltage prematurely, triggering system protection and locking up the remaining capacity.

[0190] For each battery pack to be compensated, based on the specific extent to which its actual usable percentage is lower than the threshold, and in conjunction with its current remaining capacity and total load prediction, the amount of discharge difference that needs to be compensated in subsequent discharge cycles is calculated. This difference represents the additional discharge task that other battery packs need to undertake to protect this battery pack.

[0191] All battery packs with an actual usable percentage higher than the threshold are marked as candidate compensation battery packs. These battery packs are in good condition and have the potential to provide additional discharge capacity.

[0192] Based on the actual available percentage and current remaining capacity of each candidate compensation battery pack, the calculated total discharge difference requiring compensation is reasonably allocated to one or more candidate compensation battery packs. The allocation principle is usually to prioritize battery packs with high available percentages and sufficient remaining capacity.

[0193] For each battery pack to be compensated, a compensation ratio is calculated based on the compensation amount allocated to it. This compensation ratio is then subtracted from its initial discharge ratio to obtain the adjusted final discharge ratio for that battery pack.

[0194] For each candidate battery pack assigned a compensation task, a gain ratio is calculated based on its allocated compensation amount. This gain ratio is then added to its initial discharge ratio to obtain its adjusted final discharge ratio. The gain ratio and the compensation ratio are inverses of each other.

[0195] For battery packs that are neither subject to compensation nor to compensation, their final discharge ratio remains consistent with the initial discharge ratio.

[0196] For each battery pack to be compensated The difference in discharge amount that needs to be compensated .in, This indicates the preset available percentage threshold. This indicates the actual usable percentage of the battery pack; This indicates the current remaining charge of the battery pack; This represents the system's predicted total load demand (normalized ratio) for the next scheduling cycle.

[0197] Compensation ratio It can be calculated as follows:

[0198] ;

[0199] This represents the current remaining power of the k-th candidate battery pack. Candidate battery packs are sorted by weighted ratio of actual usable capacity to remaining power, and are given priority in undertaking compensation tasks.

[0200] The final discharge ratios of all battery packs calculated above are integrated and combined with the total load requirements of the system to convert them into a series of specific discharge current setpoints. These setpoints are encapsulated as discharge control commands and sent to the power control units (such as the controllers of bidirectional DC / DC converters) corresponding to each battery pack.

[0201] S107. Control the discharge of each battery pack according to the discharge control command, monitor the status changes of the backup power system, and assess the health status of the backup power system.

[0202] In this embodiment, monitoring the state changes of the backup power system and assessing the health status of the backup power system specifically includes:

[0203] Start the monitoring and evaluation period;

[0204] During the monitoring and evaluation period, the actual usable ratio of each battery pack is continuously calculated according to the preset time cycle.

[0205] Calculate the reduction in the actual usable percentage between two consecutive monitoring and evaluation periods;

[0206] The maximum value of all reductions is determined as the maximum decay rate;

[0207] The difference between the actual usable proportion at the start and end of the monitoring period is calculated as the total attenuation.

[0208] Obtain the actual available percentage of each battery pack at the end of the monitoring period;

[0209] The first evaluation factor is obtained by taking the reciprocal of the total attenuation.

[0210] The ratio of the actual usable percentage of each battery pack to the maximum decay rate at the end of the monitoring period is used as the second evaluation factor.

[0211] Multiplying the first evaluation factor by the second evaluation factor yields the health status performance value of the backup power system.

[0212] For example, after performing a complete power balancing coordinated control operation, the system enters the effect monitoring and evaluation phase. This phase aims to quantitatively evaluate the effectiveness of the coordinated control strategy and dynamically score the overall health status of the battery system.

[0213] After completing a discharge ratio adjustment (i.e., executing a discharge control command), a fixed monitoring window of 12 hours is opened. During this window, the system calculates the actual usable ratio of all battery packs every 3 hours. Since a new balancing decision is triggered every 12 hours, four consecutive sequences of actual usable proportion data can be accumulated within a balancing cycle.

[0214] Based on the monitoring data after the p-th equilibration, the following calculations are performed:

[0215] Calculate the difference between the actual usable proportion obtained from two consecutive monitoring sessions (e.g., the (m-1)th and the mth session), and denote it as . This value reflects the rate of fluctuation or decline in the actual available proportion over a short period of time.

[0216] Calculate the difference between the actual usable proportion measured at the first (immediately after balancing) and the last (12-hour) measurement within this monitoring period, and record it as . This value reflects the total decrease in the actual available percentage over the entire monitoring period.

[0217] Attenuation at all calculated adjacent points Find its maximum value in the middle, and denote it as . This value indicates the most dramatic single decay of the actual available percentage within the period.

[0218] Based on the above indicators, during the monitoring period after the p-th balancing, the battery pack State performance The calculation formula can be:

[0219] ;

[0220] in, This represents the actual usable percentage of the battery pack as measured at the end of this monitoring cycle.

[0221] The physical meaning of the formula is: This represents the overall attenuation suppression factor. Total attenuation. The smaller the value, the more stable the available proportion of the battery pack remains after balancing; the larger the factor value, the better.

[0222] This is the final value volatility ratio. It comprehensively considers the absolute available level at the end of the cycle (which can be used as...). (represented) and the maximum decaying fluctuation within the period (can be expressed as) (This is indicated by the formula). The higher the final value and the smaller the fluctuation, the larger the ratio of this item.

[0223] Therefore, state performance The higher the value, the more stable the available power of the battery pack is after the last balancing adjustment, the slower the degradation, and the better the final state.

[0224] Calculate the status performance of all battery packs during the current monitoring period. The arithmetic mean of the values ​​is then calculated. This mean is subjected to min-max normalization to map it to a standard scoring range (e.g., 0 to 100). The normalized score serves as the overall health status value of the battery system after the p-th charge balance.

[0225] By continuously implementing the above methods, the effectiveness of the power balance coordinated control implemented at different cycles can be tracked and evaluated. The system records and analyzes the overall battery status acquired under different monitoring cycles and displays it intuitively through a visualization interface, forming a historical health trend curve to provide a basis for predictive maintenance.

[0226] The execution process of the control commands is as follows:

[0227] The battery management system in an intelligent UPS system accurately calculates the target discharge current value required for each battery pack based on the real-time total load demand and the final discharge ratio of each battery pack calculated in the preceding steps. Subsequently, the BMS sends a digital signal containing this current command to the independent power controller of each battery branch.

[0228] Each branch's power controller drives its corresponding bidirectional DC / DC converter to execute commands. The converter uses high-frequency pulse width modulation technology to precisely control the on and off times of its internal power switching devices (such as MOSFETs or IGBTs), thereby dynamically and in real time adjusting the current drawn from its respective battery pack to ensure that the current value is consistent with the target discharge current value, that is, to discharge strictly according to the final discharge ratio.

[0229] The regulated current from all battery branches flows to a common DC bus, forming a stable and controlled total DC power supply, which is then converted into AC power by an inverter to supply power to the load.

[0230] In summary, in this embodiment of the invention, key state indicators such as unhealthy status, initial discharge ratio, non-degradation degree, and actual usable ratio are calculated sequentially through real-time monitoring and data analysis. Based on these indicators, the discharge task is dynamically adjusted to achieve balanced and coordinated control of the power among battery packs. This effectively optimizes the operating status and lifespan of the battery packs and ultimately completes a closed-loop management process from state perception to intelligent maintenance.

[0231] This invention also proposes an intelligent UPS and battery integrated monitoring system; please refer to [link / reference]. Figure 2 The diagram shows a structural diagram of an intelligent UPS and battery integrated monitoring system provided in an embodiment of the present invention. The system includes: a data acquisition module 101, a data processing module 102, and a health assessment module 103.

[0232] The data acquisition module 101 is used to acquire the operating load, remaining power, and voltage data of each battery cell in the backup power system.

[0233] Data processing module 102 is used to calculate the health status of each battery pack based on the change in its remaining charge under operating load during a continuous monitoring period.

[0234] Based on the health status and current remaining power of each battery pack, the initial discharge ratio is calculated and allocated for each battery pack.

[0235] The scheduling load intensity of each battery pack is obtained, and the non-degradation degree of each battery pack is calculated based on the historical change data of the scheduling load intensity and unhealthiness of each battery pack. The voltage difference index between cells is calculated based on the voltage data of each cell.

[0236] Based on the inter-cell voltage difference index and the degree of non-degradation of each battery pack, assess the actual usable proportion of the remaining capacity displayed by each battery pack;

[0237] Based on the initial discharge ratio of each battery pack, the discharge control command is adjusted according to the actual available ratio to generate discharge control commands for the coordinated control of power balance among battery packs.

[0238] The health assessment module 103 is used to control the discharge of each battery pack according to the discharge control command, monitor the status changes of the backup power system, assess the health status of the backup power system, and display the results visually.

[0239] It should be noted that the system provided in the above embodiments is only an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer equipment can be divided into different functional modules to complete all or part of the functions described above. In addition, the intelligent UPS and battery integrated monitoring system and the intelligent UPS and battery integrated monitoring method embodiment provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiment, which will not be repeated here.

[0240] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0241] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0242] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent integrated monitoring method for UPS and battery, characterized in that, include: Acquire the operating load, remaining capacity, and voltage data of each battery cell in the backup power system; For each battery pack, the degree of unhealth of the battery pack is calculated based on the change in its remaining charge under operating load during the continuous monitoring period; Based on the health status and current remaining power of each battery pack, the initial discharge ratio is calculated and allocated for each battery pack. Obtain the scheduling load intensity of each battery pack, and calculate the non-degradation degree of each battery pack based on the historical changes in the scheduling load intensity and unhealthiness of each battery pack, specifically including: Obtain the initial discharge ratio allocated to each battery pack in each cycle within a preset historical period; Calculate the sum of the initial discharge ratios of each battery pack in all cycles of the preset historical period to obtain the historical cumulative scheduling value; Obtain the rated capacity of each battery pack; The ratio of the historical cumulative scheduling value to the rated capacity of each battery pack is determined as the scheduling load intensity, which characterizes the strength of the scheduling task undertaken per unit capacity. The degradation inhibition coefficient of each battery pack is calculated based on historical data on the changes in the unhealth status of each battery pack. The product of the scheduling load intensity and the degradation suppression coefficient of each battery pack is determined as the degree of non-degradation of that battery pack. The voltage difference index between cells is calculated based on the voltage data of each cell; Based on the inter-cell voltage difference index and the degree of non-degradation of each battery pack, the actual usable proportion of the remaining capacity displayed by each battery pack is evaluated, specifically including: For any battery pack at the current moment, obtain its degree of non-degradation and inter-cell voltage difference indicators; Multiply the non-degradation degree, the reciprocal of the average cell voltage difference, and the reciprocal of the maximum cell voltage difference to obtain an intermediate evaluation value characterizing the actual usability of the battery pack's capacity. The intermediate evaluation values ​​of all battery packs are normalized to obtain the actual usable percentage of remaining power displayed for each battery pack. Based on the initial discharge ratio of each battery pack, the discharge control command is adjusted according to the actual available ratio to generate discharge control commands for the coordinated control of power balance among battery packs. The system controls the discharge of each battery pack according to the discharge control command, monitors the status changes of the backup power system, and assesses the health status of the backup power system.

2. The intelligent UPS and battery integrated monitoring method according to claim 1, characterized in that, For each battery pack, the degree of unhealthiness of the battery pack is calculated based on the change in its remaining charge under operating load during a continuous monitoring period, specifically including: For any given battery pack, the battery pack is continuously monitored for a preset duration, and the battery pack is controlled to be in a non-charging discharge state during the same duration. Obtain the operating load of the battery pack during the continuous duration, as well as the remaining charge of the battery pack at the start and end times of the continuous duration; Calculate the difference between the remaining power at the start time and the remaining power at the end time to obtain the change in remaining power over the continuous time period; Take the reciprocal of the running load to obtain the load factor; Obtain the historical maximum battery capacity decay value, which is the maximum battery capacity reduction value of each battery pack under the same time period obtained from historical monitoring data. The ratio of the change in remaining power to the historical maximum power decay value is determined as the relative decay ratio; Multiplying the load factor and the relative degradation ratio yields the degree of unhealthiness of the battery pack.

3. The intelligent UPS and battery integrated monitoring method according to claim 1, characterized in that, The process of calculating and allocating an initial discharge ratio for each battery pack based on its health status and current remaining charge includes: For the backup power system at the current moment, obtain the health status and current remaining power of each battery pack; Determine the maximum unhealthy level across all battery packs, and the maximum current remaining charge level. For any given battery pack, the health degradation coefficient is obtained by comparing the unhealth level of the battery pack with the maximum value of the unhealth level. Calculate the difference between the maximum current remaining power and the current remaining power of the battery pack to obtain the power gap value; The ratio of the power shortage value to the maximum current remaining power value is determined as the relative power shortage coefficient; Multiplying the health degradation coefficient by the relative power deficiency coefficient yields the discharge ratio penalty factor for the battery pack. The value of the discharge ratio penalty factor is negatively correlated with the value of the initial discharge ratio. The discharge ratio penalty factor for each battery pack is normalized, and the proportion of the normalized value of each battery pack to the sum of the values ​​of all battery packs is determined as the initial discharge ratio of each battery pack.

4. The intelligent UPS and battery integrated monitoring method according to claim 1, characterized in that, The calculation of the degradation suppression coefficient for each battery pack based on historical data on the unhealth status of each battery pack specifically includes: For the current moment, obtain the health status record of each battery pack within a preset historical period; For any given battery pack, based on the unhealthy status records, calculate the change in the unhealthy status of the battery pack over adjacent recording periods; The maximum value among all the changes is determined as the maximum single degradation, and the average value of all the changes is calculated to obtain the average degradation. The degradation suppression coefficient, which characterizes the rate of decline in the health status of the battery pack, is obtained by adding the maximum single degradation amount and the average degradation amount and taking the reciprocal.

5. The intelligent UPS and battery integrated monitoring method according to claim 1, characterized in that, The calculation of the inter-cell voltage difference index based on the voltage data of each cell specifically includes: For any given battery pack, obtain the current voltage data of all cells within it; Calculate the difference between the current voltage data of each cell in the battery pack and the current voltage data of any other cell; For each cell, the maximum value among all calculated voltage differences is determined as the individual maximum voltage difference of that cell; The arithmetic mean of the maximum individual voltage difference of all cells is determined as the average cell voltage difference of the battery pack. The maximum value among the maximum individual voltage differences of all cells is determined as the maximum cell voltage difference of the battery pack. The average cell voltage difference and the maximum cell voltage difference are defined as the inter-cell voltage difference indicators.

6. The intelligent UPS and battery integrated monitoring method according to claim 1, characterized in that, The process involves using the initial discharge ratio of each battery pack as a benchmark, adjusting it based on the actual available ratio, and generating discharge control commands for coordinated power balance control among battery packs. Specifically, this includes: Compare the actual usable percentage of each battery pack with the preset usable percentage threshold; Battery packs whose actual usable ratio is lower than the preset usable ratio threshold are marked as battery packs to be compensated. For each battery pack to be compensated, the amount of discharge difference that needs to be compensated is calculated based on the degree to which its actual usable ratio is lower than the preset usable ratio threshold. All battery packs whose actual usable percentage is higher than the preset usable percentage threshold are marked as candidate compensation battery packs. Based on the actual available ratio and remaining power status of each candidate compensation battery pack, the discharge difference that needs to be compensated is allocated to at least one candidate compensation battery pack. For each battery pack to be compensated, the compensation ratio is calculated based on the difference in discharge amount that needs to be compensated, and the compensation ratio is subtracted from the initial discharge ratio to obtain the final discharge ratio of each battery pack to be compensated. For each candidate compensation battery pack with allocated discharge difference, the final discharge ratio of each candidate compensation battery pack with allocated discharge difference is obtained by adding the initial discharge ratio to the compensation ratio. The final discharge ratios of all battery packs are adjusted and integrated to generate discharge control commands for controlling the specific discharge current of each battery pack.

7. The intelligent UPS and battery integrated monitoring method according to claim 1, characterized in that, The monitoring of status changes in the backup power system and the assessment of the health status of the backup power system specifically include: Start the monitoring and evaluation period; During the monitoring and evaluation period, the actual usable ratio of each battery pack is continuously calculated according to the preset time cycle. Calculate the reduction in the actual usable percentage between two consecutive monitoring and evaluation periods; The maximum value of all reductions is determined as the maximum decay rate; The difference between the actual usable proportion at the start and end of the monitoring period is calculated as the total attenuation. Obtain the actual available percentage of each battery pack at the end of the monitoring period; The first evaluation factor is obtained by taking the reciprocal of the total attenuation. The ratio of the actual usable percentage of each battery pack to the maximum decay rate at the end of the monitoring period is used as the second evaluation factor. Multiplying the first evaluation factor by the second evaluation factor yields the health status performance value of the backup power system.

8. An intelligent UPS and battery integrated monitoring system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent UPS and battery integrated monitoring method as described in any one of claims 1-7.

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