A method and system for managing energy in a UPS multi-cell cluster

Abstract

This application proposes a UPS multi-battery cluster energy management method and system, relating to the field of energy management technology. The method includes: simultaneously acquiring the internal true terminal voltage, external voltage, and charging / discharging current of the battery cluster; calculating the voltage difference between the internal true terminal voltage and the external voltage; when the absolute value of the charging / discharging current is greater than a preset current threshold, estimating the equivalent contact resistance of the connection point between the battery cluster and the main bus based on the voltage difference and the charging / discharging current; smoothing the equivalent contact resistance to obtain a smoothed estimated resistance; generating a compensation voltage based on the external voltage, the charging / discharging current, and the smoothed estimated resistance; and making scheduling decisions based on the compensation voltage. This application can improve the power supply stability and continuity of the UPS system under high power output demands.

Description

Technical Field

[0001] This application relates to the field of energy management technology, and in particular to a UPS multi-battery cluster energy management method and system. Background Technology

[0002] In related technologies, in uninterruptible power supply (UPS) multi-battery cluster systems, sophisticated energy management methods are typically employed to ensure continuous power supply and long-term stable operation of the battery system. However, during long-term system operation, the power cable terminals connecting the battery clusters to the main bus may slowly deteriorate, leading to a gradual increase in contact resistance. This slight increase in resistance generates an additional voltage drop in current transmission, causing a difference between the external voltage of the battery clusters measured by the system's main control unit and the actual internal voltage measured by the battery management unit. Since energy management strategies often rely on external voltage data for judgment, this discrepancy can lead to incorrect assessments of the battery cluster status, resulting in unreasonable charging and discharging scheduling, exacerbating operational imbalances between battery clusters, and ultimately affecting the overall power supply stability and continuity of the UPS system under high power output demands. Summary of the Invention

[0003] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a UPS multi-battery cluster energy management method and system, which aims to improve the power supply stability and continuity of the UPS system under high power output demand.

[0004] In a first aspect, embodiments of this application provide a UPS multi-battery cluster energy management method, including:

[0005] Simultaneously acquire the actual internal terminal voltage, external voltage, and charging / discharging current of the battery cluster;

[0006] Calculate the voltage difference between the internal true terminal voltage and the external voltage;

[0007] When the absolute value of the charging and discharging current is greater than a preset current threshold, the equivalent contact resistance of the connection point between the battery cluster and the main busbar is estimated based on the voltage difference and the charging and discharging current.

[0008] The equivalent contact resistance is smoothed to obtain a smoothed estimated resistance;

[0009] A compensation voltage is generated based on the external voltage, the charging / discharging current, and the smoothed estimation resistance.

[0010] Scheduling decisions are made based on the compensation voltage.

[0011] According to some embodiments of this application, the step of smoothing the equivalent contact resistance to obtain a smoothed estimated resistance includes:

[0012] Monitor the difference between the instantaneous rate of change of the equivalent contact resistance and the historical average rate of change;

[0013] When the instantaneous rate of change continues to exceed the preset rate of change threshold, the parameters of the smoothing method are adjusted;

[0014] Based on the parameters of the adjusted smoothing method, the equivalent contact resistance is smoothed to obtain a smoothed estimated resistance.

[0015] According to some embodiments of this application, the step of making scheduling decisions based on the compensation voltage further includes:

[0016] Real-time acquisition of the internal temperature and state of charge of the battery cluster;

[0017] Based on the compensation voltage and the nominal maximum discharge power, the instantaneous maximum discharge capacity is preliminarily estimated;

[0018] Calculate the temperature correction factor and the state of charge correction factor based on the internal temperature and the state of charge.

[0019] The corrected instantaneous maximum discharge capacity is obtained by multiplying the initially estimated instantaneous maximum discharge capacity by the temperature correction factor and the state of charge correction factor.

[0020] The system monitors the rate of change of the total system load. When the rate of change of the total system load exceeds the preset load threshold, the system adjusts the discharge priority and current distribution of the battery cluster based on the compensation voltage and the corrected instantaneous maximum discharge capacity.

[0021] According to some embodiments of this application, the step of making scheduling decisions based on the compensation voltage further includes:

[0022] Short-duration pulse discharge tests are periodically performed on each battery cluster;

[0023] Measure the voltage recovery characteristics before and after the pulsed discharge;

[0024] Based on the compensation voltage charge / discharge depth and equalization strategy and the voltage recovery characteristics, evaluate the equivalent internal resistance and actual usable capacity of the battery cluster.

[0025] The depth of charge / discharge and equalization strategy are adjusted based on the difference between the equivalent internal resistance and the actual usable capacity.

[0026] According to some embodiments of this application, the step of periodically performing a short-time pulse discharge test on each battery cluster includes:

[0027] The state of charge, internal temperature, and health status of the battery cluster can be acquired in real time.

[0028] Real-time acquisition of the operating mode of the UPS system;

[0029] The pulse current amplitude, pulse duration, and pulse interval are calculated based on the state of charge of the battery cluster, the internal temperature, the health status, and the operating mode of the UPS system.

[0030] Based on the calculated pulse current amplitude, pulse duration, and pulse interval, a short-time pulse discharge test is periodically performed on each battery cluster.

[0031] According to some embodiments of this application, the step of evaluating the equivalent internal resistance and actual usable capacity of the battery cluster based on the compensation voltage and the voltage recovery characteristics before and after the pulse discharge includes:

[0032] The voltage recovery curve of the battery cluster is measured in segments to obtain the voltage change rate in the initial fast recovery stage, the voltage plateau characteristics in the intermediate slow recovery stage, and the final steady-state recovery voltage.

[0033] The ohmic internal resistance of the battery cluster is evaluated based on the voltage change rate and the compensation voltage.

[0034] Based on the voltage plateau characteristics, the internal temperature of the battery cluster, and the state of charge, the electrochemical polarization resistance and the degree of degradation of the active material of the battery cluster are evaluated.

[0035] Based on the final steady-state recovery voltage, the discharge depth history, and the health status of the battery cluster, the estimated usable capacity of the battery cluster is obtained;

[0036] By combining the ohmic internal resistance, the electrochemical polarization internal resistance, and the degree of degradation of the active material, the equivalent internal resistance of the battery cluster is obtained.

[0037] The actual usable capacity of the battery cluster is evaluated by combining the assessed usable capacity and the equivalent internal resistance.

[0038] According to some embodiments of this application, when there is a significant difference in the equivalent internal resistance or actual usable capacity among the battery clusters, the step of adjusting the charge / discharge depth and balancing strategy based on the difference in the equivalent internal resistance and actual usable capacity includes:

[0039] The charge / discharge weights of each battery cluster are calculated based on the difference between the equivalent internal resistance and the actual usable capacity.

[0040] The upper limit of the charge / discharge depth of each battery cluster is adjusted according to the charge / discharge weight of each battery cluster.

[0041] The balanced current distribution of each battery cluster is adjusted according to the charge and discharge weight of each battery cluster.

[0042] The charge / discharge depth and balancing strategy are adjusted based on the adjusted upper limit of charge / discharge depth for each battery cluster and the adjusted balanced current distribution for each battery cluster.

[0043] According to some embodiments of this application, the step of adjusting the upper limit of charge / discharge depth of each battery cluster based on the charge / discharge weight of each battery cluster includes:

[0044] Obtain the cumulative number of cycles and the cumulative discharge amount of the battery cluster;

[0045] The long-term health degradation factor of the battery cluster is calculated based on the cumulative number of cycles and the cumulative discharge amount.

[0046] The upper limit of the charge / discharge depth of the battery cluster is adjusted based on the charge / discharge weight of each battery cluster and the long-term health degradation factor.

[0047] According to some embodiments of this application, after correcting the upper limit of charge / discharge depth of the battery cluster based on the charge / discharge weights of each battery cluster and the long-term health degradation factor, the method further includes:

[0048] When there is a continuous deviation between the actual charge / discharge depth and the upper limit of the charge / discharge depth, and the voltage fluctuation is abnormal...

[0049] The first fine-tuning amplitude is calculated based on the duration and degree of deviation between the actual depth of charge and discharge and the upper limit of the depth of charge and discharge, the current state of charge of the battery cluster, and the internal temperature.

[0050] The second fine-tuning amplitude is calculated based on the frequency and amplitude of the voltage fluctuation, the equivalent internal resistance of the battery cluster, and the actual usable capacity.

[0051] The first fine-tuning magnitude and the second fine-tuning magnitude are weighted and fused to obtain the final fine-tuning magnitude;

[0052] The upper limit of the charge / discharge depth of the modified battery cluster is adjusted according to the final fine-tuning range.

[0053] Secondly, embodiments of this application provide a UPS multi-battery cluster energy management system, including:

[0054] The data acquisition module is used to synchronously acquire the internal actual terminal voltage, external voltage, and charging / discharging current of the battery cluster;

[0055] The voltage difference calculation module is used to calculate the voltage difference between the internal real terminal voltage and the external voltage;

[0056] The resistance estimation module is used to estimate the equivalent contact resistance of the connection point between the battery cluster and the main busbar based on the voltage difference and the charging and discharging current when the absolute value of the charging and discharging current is greater than a preset current threshold.

[0057] A smoothing module is used to smooth the equivalent contact resistance to obtain a smoothed estimated resistance.

[0058] The compensation voltage generation module is used to generate a compensation voltage based on the external voltage, the charging and discharging current, and the smoothing estimation resistance.

[0059] The scheduling decision module is used to make scheduling decisions based on the compensation voltage.

[0060] The technical solution according to the embodiments of this application has at least the following beneficial effects: The UPS multi-battery cluster energy management method disclosed in this application synchronously acquires the internal true terminal voltage, external voltage, and charging / discharging current of the battery cluster, and calculates the voltage difference between the two. When the absolute value of the charging / discharging current is greater than a preset current threshold, the equivalent contact resistance of the connection point between the battery cluster and the main busbar can be accurately estimated based on the voltage difference and the charging / discharging current. Subsequently, the estimated equivalent contact resistance is smoothed to obtain a smoothed estimated resistance, effectively filtering out measurement noise and instantaneous fluctuations. On this basis, a compensation voltage is generated according to the external voltage, charging / discharging current, and smoothed estimated resistance. This compensation voltage can accurately reflect the additional voltage drop caused by the contact resistance. Finally, the system makes scheduling decisions based on the compensation voltage, thereby correcting the problem of misjudgment of battery status caused by increased external connection resistance in traditional energy management strategies. This application introduces an estimation and compensation mechanism for equivalent contact resistance, enabling the energy management system to obtain voltage data that is closer to the actual state of the battery cluster, thereby making more accurate scheduling decisions, avoiding long-term misjudgments of "hidden" physical defects, significantly improving the power supply stability and continuity of the UPS system under high power output demand, and effectively extending the overall service life of the battery cluster.

[0061] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0062] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0063] Figure 1 A flowchart illustrating a UPS multi-battery cluster energy management method provided in one embodiment of this application;

[0064] Figure 2 This is a schematic diagram of a UPS multi-battery cluster energy management system provided in one embodiment of this application. Detailed Implementation

[0065] To make the objectives, technical methods, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0066] It should be noted that the meaning of "multiple" (or "more than") in the description of the embodiments of this application refers to two or more, and "greater than," "less than," "exceeding," etc. are understood to exclude the number itself, while "above," "below," "within," etc. are understood to include the number itself. If "first," "second," etc. are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0067] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: the existence of a alone, the existence of b alone, the existence of c alone, the simultaneous existence of a and b, the simultaneous existence of a and c, the simultaneous existence of b and c, or the simultaneous existence of a, b, and c, where a, b, and c can be single or multiple.

[0068] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0069] Based on the above, this application proposes a UPS multi-battery cluster energy management method and system, aiming to improve the power supply stability and continuity of the UPS system under high power output demand.

[0070] The UPS multi-battery cluster energy management method provided in this application can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms; the software can be an application that implements the UPS multi-battery cluster energy management method, but is not limited to the above forms.

[0071] This application can be applied to numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via communication networks. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices. It should be noted that in various specific embodiments of this invention, when processing is required based on data related to the characteristics of an object (e.g., user attributes or sets of attribute information), permission or consent from the corresponding object is obtained first, and the collection, use, and processing of this data comply with relevant laws and standards. Furthermore, when the embodiments of the present invention need to obtain the attribute information of an object, they will obtain the separate permission or separate consent of the corresponding object through pop-up windows or redirection to a confirmation page. After obtaining the separate permission or separate consent of the corresponding object, they will then obtain the relevant data of the object necessary for the embodiments of the present invention to operate normally.

[0072] See Figure 1 , Figure 1This is a flowchart illustrating a UPS multi-battery cluster energy management method according to an embodiment of this application. The UPS multi-battery cluster energy management method provided in this embodiment includes, but is not limited to, steps S110 to S160, which are described in detail below.

[0073] Step S110: Simultaneously acquire the actual internal terminal voltage, external voltage, and charging / discharging current of the battery cluster;

[0074] Step S120: Calculate the voltage difference between the internal actual terminal voltage and the external voltage;

[0075] Step S130: When the absolute value of the charging and discharging current is greater than the preset current threshold, estimate the equivalent contact resistance of the connection point between the battery cluster and the main busbar based on the voltage difference and the charging and discharging current.

[0076] Step S140: Smooth the equivalent contact resistance to obtain a smoothed estimated resistance;

[0077] Step S150: Generate a compensation voltage based on the external voltage, charging / discharging current, and smoothed estimated resistance;

[0078] Step S160: Make scheduling decisions based on the compensation voltage.

[0079] It should be noted that "internal true terminal voltage" refers to the voltage value measured directly inside the battery cluster by the Battery Management Unit (BMS), reflecting the true electrochemical state of the battery cluster; "external voltage" refers to the battery cluster voltage measured by the UPS main control unit on the main bus side, which includes the voltage drop across the connecting cables and terminals; "charge and discharge current" refers to the current flowing through the battery cluster, the direction and magnitude of which indicate the energy exchange state of the battery cluster; "preset current threshold" is an empirical value or a lower limit of current set according to system characteristics, used to ensure that resistance estimation is performed when the current is sufficiently large, thereby improving estimation accuracy; "equivalent contact resistance" refers to the additional resistance caused by physical degradation at the connection point between the battery cluster and the main bus; "smoothed estimated resistance" is the result of filtering the estimated equivalent contact resistance, used to eliminate instantaneous noise and fluctuations; "compensation voltage" is calculated based on the external voltage, charge and discharge current, and smoothed estimated resistance, used to correct the deviation of the external voltage, making it closer to the internal true terminal voltage; "scheduling decision" refers to the allocation and control of the charging and discharging behavior of each battery cluster by the UPS energy management system according to the operating status of the battery cluster and system requirements.

[0080] In one embodiment, during the data acquisition phase, the system simultaneously acquires the internal true terminal voltage, external voltage, and charging / discharging current of the battery cluster. For example, the internal true terminal voltage can be directly measured by a voltage sensor inside the Battery Management Unit (BMS), the external voltage can be acquired by a voltage sensor on the main bus side of the UPS main control unit, and the charging / discharging current can be monitored in real time by current sensors such as Hall effect sensors. These data can be sampled periodically at a fixed frequency, such as once every 100 milliseconds, to ensure the real-time nature and synchronization of the data. Subsequently, the system calculates the voltage difference between the internal true terminal voltage and the external voltage. This voltage difference is caused by factors such as the contact resistance at the connection point and the cable resistance. For example, the external voltage can be directly subtracted from the internal true terminal voltage to obtain a voltage difference. Ideally, this difference should be close to zero, but in actual operation, due to various losses, there will be a certain non-zero value. When the absolute value of the charging / discharging current is greater than a preset current threshold, the system estimates the equivalent contact resistance of the connection point between the battery cluster and the main bus based on the voltage difference and the charging / discharging current. For example, when the absolute value of the charging / discharging current exceeds 10 amperes, the current can be considered large enough to produce a measurable voltage drop. In this case, the equivalent contact resistance can be initially estimated by dividing the voltage difference by the charging / discharging current. This estimation method is simple and direct, but may be affected by instantaneous current fluctuations and measurement noise. To improve the accuracy and stability of the estimated resistance, the system smooths the equivalent contact resistance to obtain a smoothed estimated resistance. For example, a moving average filter can be used to process the estimated equivalent contact resistance, averaging the most recent N estimates to eliminate instantaneous noise. Another approach is to use an exponentially weighted moving average (EWMA) filter, assigning different weights to historical data so that the most recent data has a greater impact on the smoothing result. Next, a compensation voltage is generated based on the external voltage, charging / discharging current, and smoothed estimated resistance. For example, the compensation voltage can be calculated by adding the product of the charging / discharging current and the smoothed estimated resistance to the external voltage. This compensation voltage aims to offset the voltage drop caused by the equivalent contact resistance, making the compensated voltage closer to the true internal terminal voltage of the battery cluster. Finally, the system makes scheduling decisions based on the compensation voltage. For example, the scheduling decision module can receive compensation voltage as input and combine it with other parameters such as the state of charge (SOC) and state of health (SOH) of the battery clusters to determine the charging and discharging priority and charging and discharging current allocation of each battery cluster. By using compensation voltage, the scheduling decision can more accurately reflect the actual operating status of the battery clusters, thereby avoiding misjudgments caused by the deterioration of external connection resistance.

[0081] It should be noted that the difference between the instantaneous rate of change and the historical average rate of change of the equivalent contact resistance refers to the system acquiring the current value of the equivalent contact resistance in real time and calculating its change relative to the previous moment or several previous moments, i.e., the instantaneous rate of change. Simultaneously, the system maintains a historical average rate of change of the equivalent contact resistance. This historical average can be obtained through methods such as moving average or exponentially weighted average to reflect the typical trend of the equivalent contact resistance over a period of time. By comparing the instantaneous rate of change with the historical average rate of change, it can be determined whether the current change in the equivalent contact resistance deviates from the normal pattern, such as whether there is an abnormally rapid rise or fall. Furthermore, when the instantaneous rate of change continuously exceeds a preset rate of change threshold, the parameters of the smoothing method are adjusted. The preset rate of change threshold is a pre-set value used to define the normal range of the rate of change of the equivalent contact resistance. When the instantaneous rate of change exceeds this threshold for multiple consecutive sampling periods or within a specific time window, it indicates that the equivalent contact resistance may have undergone a real, non-random, significant change. At this time, the system will adjust the parameters of the smoothing method used according to the actual situation. For example, if exponential smoothing is used, the smoothing coefficient can be adjusted; if moving average is used, the size of the moving average window can be adjusted. The purpose of this adjustment is to make the smoothing method better adapt to the dynamic characteristics of the current equivalent contact resistance, such as improving response speed during rapid changes and enhancing noise suppression when stable. Therefore, based on the adjusted parameters of the smoothing method, the equivalent contact resistance is smoothed to obtain a smoothed estimated resistance. This means that after parameter adjustment, the smoothing algorithm will use the new parameters to process the real-time acquired equivalent contact resistance, thereby generating a more accurate and real-time smoothed estimated resistance.

[0082] In one embodiment, it is assumed that during normal operation of the UPS system, the equivalent contact resistance of the connection point between the battery cluster and the main bus remains relatively stable for most of the time. In this case, the smoothing method can use a large smoothing coefficient to effectively filter out measurement noise. However, when a connection point of a battery cluster experiences poor contact due to long-term use or changes in the external environment, causing a sudden and continuous increase in the equivalent contact resistance, the system will detect that the instantaneous rate of change of the equivalent contact resistance significantly and continuously exceeds a preset rate of change threshold. At this time, the smoothing module will automatically adjust the parameters of the smoothing method, for example, by reducing the alpha value of exponential smoothing or shortening the moving average window, so that the smoothed estimated resistance can more quickly track and reflect this true resistance increase trend. Conversely, if the voltage or current fluctuation is only caused by instantaneous noise, its instantaneous rate of change may briefly exceed the threshold but will not persist. In this case, the smoothing parameters will not be adjusted, thus avoiding over-response to noise. Through this adaptive adjustment mechanism, the accuracy and response speed of the smoothed estimated resistance are optimized under different operating conditions, providing high-quality input for subsequent compensation voltage generation and scheduling decisions.

[0083] It should be noted that real-time acquisition of the internal temperature and state of charge (SOC) of the battery cluster refers to the continuous monitoring and acquisition of the real-time internal temperature and SOC of each battery cluster through the temperature sensors and SOC estimation module built into the Battery Management System (BMS). The internal temperature reflects the thermal management status and potential thermal degradation risk of the battery cluster, while the SOC indicates the current available energy of the battery cluster. These parameters are key indicators for evaluating the instantaneous performance and health status of the battery cluster. Based on the compensation voltage and nominal maximum discharge power, the instantaneous maximum discharge capacity is initially estimated. The compensation voltage reflects the voltage drop caused by the equivalent contact resistance at the connection point between the battery cluster and the main busbar, indirectly reflecting the connection quality and actual output power. The nominal maximum discharge power is the design discharge capacity benchmark of the battery cluster under ideal conditions. By combining these two, a preliminary assessment of the theoretical maximum discharge capacity of the battery cluster under the current connection state can be made. Based on the internal temperature and SOC, temperature correction factors and SOC correction factors are calculated. The discharge capacity of a battery is significantly affected by temperature and SOC. For example, in low-temperature environments, the battery's internal resistance increases, reducing its discharge capacity; similarly, the battery's discharge capacity is limited when the state of charge (SOC) is low. Temperature correction factors and SOC correction factors can be calculated using preset lookup tables, empirical formulas, or battery models to quantify the actual impact of these factors on battery discharge capacity. Therefore, by multiplying the initially estimated instantaneous maximum discharge capacity by the temperature and SOC correction factors, the corrected instantaneous maximum discharge capacity is obtained. This corrected instantaneous maximum discharge capacity provides a more accurate assessment of the actual output power of the battery cluster, taking into account the battery cluster's connection status, internal thermal state, and current available energy. The system monitors the rate of change of the total load; when the rate of change exceeds a preset load threshold, the discharge priority and current distribution of the battery clusters are adjusted based on the compensation voltage and the corrected instantaneous maximum discharge capacity. The rate of change of the total system load reflects the dynamic nature of the load on the UPS system.

[0084] In one embodiment, a UPS system providing backup power to a data center is assumed to comprise multiple battery clusters. During normal operation, the system continuously acquires the internal terminal voltage, external voltage, and charging / discharging current of each battery cluster, and estimates the equivalent contact resistance to generate a compensation voltage. When the data center suddenly experiences a large instantaneous load surge, causing the rate of change of the total system load to exceed a preset load threshold, the solution of this application is activated. At this time, the system immediately acquires the internal temperature and state of charge (SOC) of each battery cluster in real time. For example, one battery cluster may have a lower internal temperature and a higher SOC, while another may have a higher internal temperature and a lower SOC. Based on this real-time data, the system calculates the respective temperature correction factor and SOC correction factor, and, combined with the compensation voltage and nominal maximum discharge power, calculates the corrected instantaneous maximum discharge capacity of each battery cluster. Based on these corrected capacities and their respective compensation voltages, the system dynamically adjusts the discharge priority of each battery cluster to be higher than that of the battery clusters themselves, and allocates a larger discharge current to each battery cluster to prioritize meeting sudden load demands while avoiding excessive stress on the battery clusters. This dynamic and precise scheduling decision ensures stable power supply to the data center and optimizes the collaborative operation and long-term health of each battery cluster.

[0085] It should be noted that periodically performing short-time pulse discharge tests on each battery cluster refers to applying a short-time discharge pulse of preset amplitude and duration to each battery cluster at specific points in system operation or when specific conditions are met. This pulse discharge test aims to excite the internal electrochemical response of the battery cluster in a non-invasive or low-invasive manner, so as to subsequently observe its voltage recovery behavior. "Short-time" means that the pulse duration is short to avoid significantly affecting the normal operation of the battery cluster or causing over-discharge. "Periodic" ensures continuous monitoring and updating of the battery cluster's health status. Measuring the voltage recovery characteristics before and after the pulse discharge refers to monitoring and recording the change curve of the battery cluster's terminal voltage over time after the short-time pulse discharge ends. Voltage recovery characteristics typically include parameters such as the voltage change rate during the initial rapid recovery phase, the voltage plateau characteristics during the intermediate slow recovery phase, and the final steady-state recovery voltage. These parameters reflect the internal characteristics of the battery cluster, such as ohmic internal resistance, electrochemical polarization internal resistance, and active material decay. Evaluating the equivalent internal resistance and actual usable capacity of a battery cluster based on the compensation voltage, depth of charge / discharge, equalization strategy, and voltage recovery characteristics involves comprehensively considering the currently generated compensation voltage, the historical depth of charge / discharge of the battery cluster, the current equalization strategy, and the voltage recovery characteristics obtained through pulse discharge testing to quantitatively assess the equivalent internal resistance and actual usable capacity of each battery cluster. Equivalent internal resistance is a comprehensive indicator measuring the internal impedance of a battery cluster, while actual usable capacity reflects the energy that the battery cluster can actually provide under its current health condition. Adjusting the depth of charge / discharge and equalization strategy based on differences in equivalent internal resistance and actual usable capacity means that after evaluating the equivalent internal resistance and actual usable capacity of each battery cluster, if significant differences are found between different battery clusters, the upper limit of the depth of charge / discharge and the equalization current allocation for each battery cluster are dynamically adjusted based on these differences.

[0086] In one embodiment, a UPS system is assumed to contain three battery clusters: cluster A, cluster B, and cluster C. During normal system operation, the management system periodically performs short-duration pulse discharge tests on these three battery clusters. For example, every 24 hours, during specific periods of low load, the system sequentially applies a discharge pulse of 10 amps with a duration of 50 milliseconds to each battery cluster. After the pulse discharge ends, the system immediately begins measuring the voltage recovery curve of each battery cluster, recording its voltage change over the next 5 seconds. By analyzing these voltage recovery characteristics, combined with the compensation voltage, historical charge / discharge depth, and balancing strategy acquired in real time, the system assesses that: the equivalent internal resistance of battery cluster A is 5 milliohms, and its actual usable capacity is 95%; the equivalent internal resistance of battery cluster B is 8 milliohms, and its actual usable capacity is 80%; and the equivalent internal resistance of battery cluster C is 6 milliohms, and its actual usable capacity is 90%. Since the equivalent internal resistance of battery cluster B is significantly higher than that of the other battery clusters, and its actual usable capacity is lower, it indicates that its health condition is relatively poor. Therefore, the management system adjusts the charge / discharge depth and balancing strategy based on these differences. Specifically, the maximum charge / discharge depth of battery cluster B may be adjusted to 80% (lower than the 90% of other battery clusters) to reduce its load stress and slow down degradation. Simultaneously, the balancing strategy will favor battery cluster B, allocating more balancing current to help it maintain voltage consistency with other battery clusters. The maximum charge / discharge depth and balancing strategies for battery clusters A and C will be fine-tuned based on their relatively good health condition to maximize their performance. In this way, each battery cluster receives personalized management tailored to its health condition, thereby optimizing the performance and lifespan of the entire battery cluster group.

[0087] It should be noted that real-time acquisition of the battery cluster's state of charge (SOC), internal temperature, and health status refers to continuously monitoring and acquiring the current SOC, internal temperature, and state of health (SOH) of the battery cluster through the Battery Management System (BMS) or other sensors. The SOC reflects the remaining capacity of the battery cluster, the internal temperature reflects its thermal state, and the health status characterizes the overall performance and degradation of the battery cluster. Real-time acquisition of the UPS system's operating mode refers to acquiring the current operating condition of the UPS system, such as online mode, bypass mode, battery-powered mode, or maintenance mode. These parameters are crucial for dynamically adjusting the pulse discharge test parameters, aiming to ensure the safety and effectiveness of the testing process. Specifically, calculating the pulse current amplitude, pulse duration, and pulse interval based on the battery cluster's SOC, internal temperature, health status, and the UPS system's operating mode can be understood as using a preset algorithm or model to dynamically determine the most suitable pulse discharge test parameters for the current battery cluster and system state, taking into account all the parameters acquired in real time. For example, when the battery cluster has a low state of charge or a high internal temperature, the calculated pulse current amplitude may be appropriately reduced, and the pulse duration may be shortened to avoid overburdening the battery cluster. When the UPS system is in a critical operating mode (such as battery-powered mode), pulse testing may be postponed or more lenient parameters may be used to ensure the continuity and stability of the system power supply.

[0088] In one embodiment, a UPS system is assumed to contain multiple battery clusters. During periodic short-time pulse discharge tests, the system first acquires the state of charge (SOC), internal temperature, and health status of each battery cluster in real time. For example, battery cluster A has an SOC of 80%, an internal temperature of 25°C, and a health status of 95%; battery cluster B has an SOC of 60%, an internal temperature of 35°C, and a health status of 80%. Simultaneously, the system detects that the UPS is currently in online mode. Based on this data, the system performs calculations using a built-in algorithm. For battery cluster A, given its good condition, the system calculates a pulse current amplitude of 1C (where C is the battery's rated capacity), a pulse duration of 100ms, and a pulse interval of 10 minutes. For battery cluster B, due to its lower SOC, higher internal temperature, and relatively poorer health status, the system might calculate a pulse current amplitude of 0.5C, a pulse duration of 50ms, and a pulse interval of 15 minutes. Subsequently, the system performs short-time pulse discharge tests on each battery cluster based on these calculated personalized parameters. This dynamic adjustment ensures that the test can effectively acquire data, protect the battery cluster to the greatest extent, and adapt to the operating requirements of the UPS system.

[0089] It should be noted that calculating the charge / discharge weight of each battery cluster refers to determining the relative importance or load proportion of each battery cluster during the charge / discharge process based on the deviation between the equivalent internal resistance and actual usable capacity of each battery cluster and the average or benchmark value of all battery clusters, using a preset algorithm (e.g., weighted average method, fuzzy logic algorithm, or machine learning model). The purpose is to quantify the health status and performance differences of each battery cluster, providing a basis for subsequent refined management. Adjusting the upper limit of the charge / discharge depth for each battery cluster involves dynamically adjusting the maximum allowable depth of discharge and minimum depth of charge for each battery cluster based on the calculated charge / discharge weight. For example, for battery clusters with poor performance (higher equivalent internal resistance or lower actual usable capacity), their upper limit of charge / discharge depth will be appropriately lowered to avoid overcharging and discharging and extend their lifespan; while for battery clusters with better performance (lower equivalent internal resistance or higher actual usable capacity), their upper limit of charge / discharge depth can be appropriately increased to fully utilize their energy reserves. The aim is to protect weaker battery clusters while maximizing the performance of stronger battery clusters. Adjusting the equalization current allocation for each battery cluster involves dynamically allocating the equalization current based on the charge / discharge weights of each cluster. For example, a battery cluster with poor performance may be allocated more equalization current to accelerate its state of charge recovery or balance its voltage; or, under certain strategies, the equalization current may be preferentially allocated to battery clusters whose state of charge deviates significantly from the overall system's state of charge.

[0090] In one embodiment, a UPS system is assumed to contain three battery clusters: cluster A, cluster B, and cluster C. Evaluation reveals that cluster A has a relatively high equivalent internal resistance (EMR) and low usable capacity; cluster B has moderate performance; and cluster C has a low EMR and high usable capacity. First, the system calculates the charge / discharge weights for each cluster based on the differences in EMR and usable capacity. For example, cluster A might be assigned a low weight (e.g., 0.8), cluster B a medium weight (e.g., 1.0), and cluster C a high weight (e.g., 1.2). Second, based on these charge / discharge weights, the system adjusts the upper limit of the depth of charge / discharge for each cluster. Specifically, the upper limit of the depth of discharge for cluster A might be adjusted from the nominal 80% to 70%, and the lower limit of the depth of charge might be adjusted from 20% to 30% to reduce its load and protect its health. The upper limit of the depth of charge / discharge for cluster B might remain unchanged. The upper limit of the depth of discharge for cluster C might be adjusted from 80% to 85% to fully utilize its superior performance. Secondly, the system adjusts the equalization current allocation for each battery cluster based on charge / discharge weights. For example, if the state of charge (SOC) of battery cluster A is lower than that of other battery clusters, the system will allocate relatively more equalization current to it to accelerate its SOC recovery. Conversely, if the SOC of battery cluster C is too high, the system may temporarily reduce its charging current or increase its discharge equalization current.

[0091] It's important to note that obtaining the cumulative cycle count and cumulative discharge capacity of a battery cluster refers to continuously recording and accumulating the number of complete charge-discharge cycles and the total discharge capacity of each battery cluster since it was put into use, through a Battery Management System (BMS) or Energy Management System (EMS). These data are key indicators for assessing the long-term health of the battery cluster. For example, the cumulative cycle count can be defined as the number of complete cycles the battery cluster completes from full charge to a certain depth of discharge and then full charge, while the cumulative discharge capacity is the total amount of electricity output by the battery cluster during all discharge processes. Calculating the long-term health degradation factor of the battery cluster based on the cumulative cycle count and cumulative discharge capacity involves using a pre-defined battery aging model or empirical curve, taking the obtained cumulative cycle count and cumulative discharge capacity as input, to calculate a degradation factor reflecting the long-term health of the battery cluster. This degradation factor can be a value between 0 and 1, where 1 indicates the battery cluster is in a brand-new state, while a value close to 0 indicates the battery cluster is severely aged. For example, a two-dimensional lookup table based on the cycle count and discharge capacity can be established, or polynomial fitting can be used to dynamically update the degradation factor based on actual operating data. The purpose is to quantify the degree of performance degradation caused by long-term use of the battery cluster. Adjusting the upper limit of charge / discharge depth for each battery cluster, based on its charge / discharge weights and long-term health degradation factor, involves comprehensively considering the long-term health degradation factor calculated using the aforementioned methods, along with the charge / discharge weights calculated based on the differences in equivalent internal resistance and actual usable capacity. This allows for a more precise adjustment of the upper limit of charge / discharge depth for each battery cluster. For example, multiplication factors, weighted averages, or other fusion algorithms can be used to incorporate the long-term health degradation factor into the calculation of the upper limit of charge / discharge depth. If a battery cluster has a low long-term health degradation factor, even if its instantaneous performance is not significantly different, its upper limit of charge / discharge depth may be appropriately lowered to extend its lifespan and prevent premature failure. The aim is to achieve refined and personalized management of the upper limit of charge / discharge depth for battery clusters, taking into account both the instantaneous performance and long-term health status of the battery clusters.

[0092] It should be noted that when there is a persistent deviation between the actual depth of charge / discharge and the upper limit of the depth of charge / discharge, and abnormal voltage fluctuations occur, the system will trigger a further fine-tuning mechanism. "Persistent deviation" refers to the difference between the actual depth of charge / discharge and the set upper limit existing over a certain period, rather than a momentary fluctuation; "abnormal voltage fluctuations" refers to the battery cluster's terminal voltage exhibiting frequency or amplitude changes exceeding the normal range, which is usually a signal of internal battery instability. The first fine-tuning magnitude will be calculated based on the duration and degree of the deviation between the actual depth of charge / discharge and the upper limit of the depth of charge / discharge, the current state of charge of the battery cluster, and its internal temperature. A longer duration and greater degree of deviation usually indicate a significant difference between the battery cluster's operating state and expectations, requiring more significant adjustments. The current state of charge and internal temperature are key parameters affecting battery performance and safety; they are used to assess the battery cluster's adaptability to the current depth of charge / discharge, thereby more accurately determining the first fine-tuning magnitude. The second fine-tuning magnitude will be calculated based on the frequency and amplitude of voltage fluctuations, the battery cluster's equivalent internal resistance, and its actual usable capacity. The frequency and amplitude of voltage fluctuations directly reflect the battery cluster's transient response characteristics and internal stability. Equivalent internal resistance is a key indicator for measuring the internal impedance of a battery cluster, and its changes are closely related to the battery's health status. Actual usable capacity reflects the actual energy storage capacity of the battery cluster. A comprehensive consideration of these parameters helps assess the dynamic performance and health status of the battery cluster under current operating conditions, thereby calculating a second fine-tuning amplitude reflecting voltage stability requirements. The first and second fine-tuning amplitudes are weighted and fused to obtain the final fine-tuning amplitude. The purpose of weighted fusion is to comprehensively consider the different dimensions of battery cluster operation reflected by charge / discharge depth deviation and voltage fluctuation anomalies. By assigning appropriate weights to different fine-tuning amplitudes, it ensures that the final adjustment scheme can address both depth deviation issues and voltage stability, achieving a more comprehensive and balanced optimization. The upper limit of charge / discharge depth for the battery cluster is adjusted based on the final fine-tuning amplitude. This adjustment is dynamic and fine-grained, aiming to ensure that the upper limit of charge / discharge depth for the battery cluster more accurately reflects its current actual operating status and health level, thereby avoiding overcharging or over-discharging caused by inaccurate depth limit settings, and further improving the operating efficiency and safety of the battery cluster.

[0093] In one embodiment, it is assumed that the upper limit of the charge / discharge depth of a battery cluster is set to 85% after correction based on a long-term health degradation factor. However, in actual operation, the system monitors that the actual charge / discharge depth of the battery cluster is consistently maintained at around 87% for a duration exceeding a preset threshold, while its terminal voltage exhibits abnormal fluctuations with a frequency of 100Hz and an amplitude of 50mV. At this time, the fine-tuning mechanism of this application will be triggered. First, a first fine-tuning amplitude, such as -1%, is calculated based on the deviation between the actual charge / discharge depth and the upper limit (2%), the duration (e.g., 30 minutes), the current state of charge (e.g., 70%), and the internal temperature (e.g., 35°C). Then, a second fine-tuning amplitude, such as -0.5%, is calculated based on the frequency (100Hz), amplitude (50mV), equivalent internal resistance of the battery cluster (e.g., 20mΩ), and actual usable capacity (e.g., 90%). Subsequently, the two fine-tuning magnitudes are weighted and fused, for example, assigning a weight of 0.6 to the first fine-tuning magnitude and a weight of 0.4 to the second fine-tuning magnitude, resulting in a final fine-tuning magnitude of (-1% * 0.6 ) + ( -0.5% * 0.4 ) = -0.6% - 0.2% = -0.8%. Ultimately, the corrected upper limit of charge / discharge depth is adjusted from 85% to 85% - 0.8% = 84.2%. This dynamic fine-tuning allows for more precise control of the battery cluster's operation, ensuring it operates within a safer and more efficient range.

[0094] See Figure 2 , Figure 2 This is a schematic diagram of a UPS multi-battery cluster energy management system provided in one embodiment of this application. The UPS multi-battery cluster energy management system 200 includes:

[0095] Data acquisition module 210 is used to synchronously acquire the internal real terminal voltage, external voltage and charging / discharging current of the battery cluster;

[0096] Voltage difference calculation module 220 is used to calculate the voltage difference between the internal real terminal voltage and the external voltage;

[0097] The resistance estimation module 230 is used to estimate the equivalent contact resistance of the connection point between the battery cluster and the main busbar based on the voltage difference and the charging and discharging current when the absolute value of the charging and discharging current is greater than a preset current threshold.

[0098] The smoothing module 240 is used to smooth the equivalent contact resistance to obtain a smoothed estimated resistance.

[0099] The compensation voltage generation module 250 is used to generate a compensation voltage based on the external voltage, charging and discharging current, and smoothed estimated resistance.

[0100] The scheduling decision module 260 is used to make scheduling decisions based on the compensation voltage.

[0101] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0102] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0103] The foregoing has provided a detailed description of the preferred embodiments of this application. However, this application is not limited to the above-described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined in this application.

Claims

1. A UPS multi-battery cluster energy management method, characterized in that, include: Simultaneously acquire the actual internal terminal voltage, external voltage, and charging / discharging current of the battery cluster; Calculate the voltage difference between the internal true terminal voltage and the external voltage; When the absolute value of the charging and discharging current is greater than a preset current threshold, the equivalent contact resistance of the connection point between the battery cluster and the main busbar is estimated based on the voltage difference and the charging and discharging current. The equivalent contact resistance is smoothed to obtain a smoothed estimated resistance; A compensation voltage is generated based on the external voltage, the charging / discharging current, and the smoothed estimation resistance. Scheduling decisions are made based on the compensation voltage; The step of making scheduling decisions based on the compensation voltage further includes: Short-duration pulse discharge tests are periodically performed on each battery cluster; Measure the voltage recovery characteristics before and after pulse discharge; Based on the compensation voltage, depth of charge / discharge, equalization strategy, and voltage recovery characteristics, the equivalent internal resistance and actual usable capacity of the battery cluster are evaluated. Specifically, the steps are as follows: The voltage recovery curve of the battery cluster is measured segmentally to obtain the voltage change rate during the initial rapid recovery phase, the voltage plateau characteristics during the intermediate slow recovery phase, and the final steady-state recovery voltage; the ohmic internal resistance of the battery cluster is evaluated based on the voltage change rate and the compensation voltage; the electrochemical polarization internal resistance and the degree of active material degradation of the battery cluster are evaluated based on the voltage plateau characteristics, the internal temperature of the battery cluster, and the state of charge of the battery cluster; the appraised usable capacity of the battery cluster is obtained based on the final steady-state recovery voltage, the historical depth of discharge, and the health status of the battery cluster; the equivalent internal resistance of the battery cluster is obtained by combining the ohmic internal resistance, the electrochemical polarization internal resistance, and the degree of active material degradation; and the actual usable capacity of the battery cluster is evaluated by combining the appraised usable capacity and the equivalent internal resistance. The depth of charge / discharge and equalization strategy are adjusted based on the difference between the equivalent internal resistance and the actual usable capacity.

2. The method according to claim 1, characterized in that, The step of smoothing the equivalent contact resistance to obtain a smoothed estimated resistance includes: Monitor the difference between the instantaneous rate of change of the equivalent contact resistance and the historical average rate of change; When the instantaneous rate of change continues to exceed the preset rate of change threshold, the parameters of the smoothing method are adjusted; Based on the parameters of the adjusted smoothing method, the equivalent contact resistance is smoothed to obtain a smoothed estimated resistance.

3. The method according to claim 1, characterized in that, The step of making scheduling decisions based on the compensation voltage further includes: Real-time acquisition of the internal temperature and state of charge of the battery cluster; Based on the compensation voltage and the nominal maximum discharge power, the instantaneous maximum discharge capacity is preliminarily estimated; Calculate the temperature correction factor and the state of charge correction factor based on the internal temperature and the state of charge. The corrected instantaneous maximum discharge capacity is obtained by multiplying the initially estimated instantaneous maximum discharge capacity by the temperature correction factor and the state of charge correction factor. The system monitors the rate of change of the total load. When the rate of change of the total load exceeds a preset load threshold, the system adjusts the discharge priority and current distribution of the battery cluster based on the compensation voltage and the corrected instantaneous maximum discharge capacity.

4. The method according to claim 1, characterized in that, The step of periodically performing short-time pulse discharge tests on each battery cluster includes: The state of charge, internal temperature, and health status of the battery cluster can be acquired in real time. Real-time acquisition of UPS system operating mode; The pulse current amplitude, pulse duration, and pulse interval are calculated based on the state of charge of the battery cluster, the internal temperature, the health status, and the operating mode of the UPS system. Based on the calculated pulse current amplitude, pulse duration, and pulse interval, a short-time pulse discharge test is periodically performed on each battery cluster.

5. The method according to claim 1, characterized in that, When there is a significant difference in the equivalent internal resistance or actual usable capacity between the battery clusters, the step of adjusting the depth of charge / discharge and the balancing strategy based on the difference in the equivalent internal resistance and the actual usable capacity includes: The charge / discharge weights of each battery cluster are calculated based on the difference between the equivalent internal resistance and the actual usable capacity. The upper limit of the charge / discharge depth of each battery cluster is adjusted according to the charge / discharge weight of each battery cluster. The balanced current distribution of each battery cluster is adjusted according to the charge and discharge weight of each battery cluster. The charge / discharge depth and balancing strategy are adjusted based on the adjusted upper limit of charge / discharge depth for each battery cluster and the adjusted balanced current distribution for each battery cluster.

6. The method according to claim 5, characterized in that, The step of adjusting the upper limit of charge / discharge depth for each battery cluster based on the charge / discharge weight of each battery cluster includes: Obtain the cumulative number of cycles and the cumulative discharge amount of the battery cluster; The long-term health degradation factor of the battery cluster is calculated based on the cumulative number of cycles and the cumulative discharge amount. The upper limit of the charge / discharge depth of the battery cluster is adjusted based on the charge / discharge weight of each battery cluster and the long-term health degradation factor.

7. The method according to claim 6, characterized in that, After correcting the upper limit of charge / discharge depth of the battery cluster based on the charge / discharge weight of each battery cluster and the long-term health degradation factor, the method further includes: When there is a continuous deviation between the actual depth of charge and discharge and the upper limit of the depth of charge and discharge and the voltage fluctuation is abnormal, the first fine adjustment amplitude is calculated based on the duration and degree of the deviation between the actual depth of charge and discharge and the upper limit of the depth of charge and discharge, the current state of charge of the battery cluster and the internal temperature of the battery cluster. The second fine-tuning amplitude is calculated based on the frequency and amplitude of the voltage fluctuation, the equivalent internal resistance of the battery cluster, and the actual usable capacity. The first fine-tuning magnitude and the second fine-tuning magnitude are weighted and fused to obtain the final fine-tuning magnitude; The upper limit of the charge / discharge depth of the battery cluster is adjusted based on the final fine-tuning amplitude.

8. A UPS multi-battery cluster energy management system, characterized in that, The system includes: The data acquisition module is used to synchronously acquire the internal actual terminal voltage, external voltage, and charging / discharging current of the battery cluster; The voltage difference calculation module is used to calculate the voltage difference between the internal real terminal voltage and the external voltage; The resistance estimation module is used to estimate the equivalent contact resistance of the connection point between the battery cluster and the main busbar based on the voltage difference and the charging and discharging current when the absolute value of the charging and discharging current is greater than a preset current threshold. A smoothing module is used to smooth the equivalent contact resistance to obtain a smoothed estimated resistance. The compensation voltage generation module is used to generate a compensation voltage based on the external voltage, the charging and discharging current, and the smoothing estimation resistance. The scheduling decision module is used to make scheduling decisions based on the compensation voltage; The scheduling decision module is also used for: Short-duration pulse discharge tests are periodically performed on each battery cluster; Measure the voltage recovery characteristics before and after pulse discharge; Based on the compensation voltage, depth of charge / discharge, equalization strategy, and voltage recovery characteristics, the equivalent internal resistance and actual usable capacity of the battery cluster are evaluated. Specifically, the voltage recovery curve of the battery cluster is measured in segments to obtain the voltage change rate during the initial rapid recovery phase, the voltage plateau characteristics during the intermediate slow recovery phase, and the final steady-state recovery voltage. The ohmic internal resistance of the battery cluster is evaluated based on the voltage change rate and the compensation voltage. The electrochemical polarization internal resistance and the degree of active material degradation of the battery cluster are evaluated based on the voltage plateau characteristics, the internal temperature of the battery cluster, and the state of charge of the battery cluster. The appraised usable capacity of the battery cluster is obtained based on the final steady-state recovery voltage, the historical depth of discharge, and the health status of the battery cluster. The equivalent internal resistance of the battery cluster is obtained by combining the ohmic internal resistance, the electrochemical polarization internal resistance, and the degree of active material degradation. The actual usable capacity of the battery cluster is evaluated by combining the appraised usable capacity and the equivalent internal resistance. The depth of charge / discharge and equalization strategy are adjusted based on the difference between the equivalent internal resistance and the actual usable capacity.

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