Battery SOC balancing method for energy storage system based on EMS

Abstract

The present invention relates to the technical field of battery SOC balancing, and specifically discloses a battery SOC balancing method for an energy storage system based on an EMS. The method comprises: determining the SOC balancing influencing factor of each battery based on the EMS, analyzing the real-time use status of the SOC of each battery, obtaining the SOC balancing state characteristic value of each battery in combination with the SOC balancing influencing factor of each battery, determining the battery SOC balancing state judgment value, judging whether the battery needs to be SOC balancing and determining the SOC balancing mode, monitoring the temperature state of the battery SOC balancing process, and judging whether the battery SOC balancing process is overheated. The present invention solves the problems that the traditional balancing method has a slow response speed when dealing with scenarios with frequent load changes and high power demands, sets a fixed SOC balancing threshold, and lacks adaptability to dynamic working conditions such as load fluctuations, avoids unnecessary energy consumption, helps to improve system safety, and reduces the probability of sudden failures.

Description

Technical Field

[0001] The present invention relates to the technical field of battery SOC balancing, and in particular to an EMS-based battery SOC balancing method for an energy storage system. Background Art

[0002] At present, the power generation of renewable energy such as solar energy and wind energy is intermittent and volatile. The energy storage system can smooth these fluctuations by storing and releasing energy to ensure the stable operation of the power grid. The effective operation of the energy storage system is inseparable from the health management and SOC balancing of the battery. Due to the differences in production process, materials, temperature changes and aging process, the single cells in the battery pack are prone to differences in capacity, internal resistance and self-discharge rate. These differences will lead to inconsistent SOC and affect the overall performance of the battery pack. Inconsistent SOC of battery cells will cause some batteries to be overcharged or over-discharged, thereby reducing the utilization rate of battery capacity, increasing the battery aging rate, shortening the life of the overall system, and even causing safety problems (such as thermal runaway). EMS, as the core control platform of the energy storage system, can monitor the status information of the battery pack such as SOC, SOH (health status), temperature and load demand in real time. The balancing method based on EMS can centrally manage the SOC of each battery cell, automatically identify the unbalanced state and perform balancing control. Through the balancing method based on EMS, the battery status can be dynamically monitored and adjusted to reduce the system safety risk.

[0003] Nowadays, there are still some shortcomings in the research on battery SOC balancing of EMS-based energy storage systems. Specifically, the traditional balancing method has a slow response speed when dealing with scenarios with frequent load changes and high power demands, which can easily lead to further expansion of SOC differences within the battery pack and reduce the overall efficiency of the system. In addition, the fixed SOC balancing threshold is set, which lacks adaptability to dynamic working conditions such as load fluctuations, resulting in unsatisfactory balancing effects in complex application scenarios, shortened battery pack life, and reduced system efficiency. Under complex working conditions, the balancing effect is poor and cannot meet the dynamic balance requirements of the system. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an EMS-based energy storage system battery SOC balancing method, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an energy storage system battery SOC balancing method based on EMS, comprising the following steps: based on EMS, analyzing the basic data of each battery in the energy storage system to determine the SOC balancing influencing factor of each battery; analyzing the real-time SOC usage status of each battery, and obtaining the SOC balancing state characteristic value of each battery in combination with the SOC balancing influencing factor of each battery; determining the battery SOC balancing state judgment value based on the SOC balancing state characteristic value of each battery; analyzing the characteristics of the energy storage system, and judging whether the battery needs to be SOC balanced in combination with the battery SOC balancing state judgment value; analyzing the target characteristics of the energy storage system of the battery that needs to be SOC balanced: if the energy storage system of the battery that needs to be SOC balanced prioritizes balancing energy efficiency, active balancing is selected; if the energy storage system of the battery that needs to be SOC balanced prioritizes balancing speed, multi-phase DC-DC converter balancing is selected; monitoring the temperature state of the battery SOC balancing process to judge whether the battery SOC balancing process is overheated.

[0006] As a further method, the SOC balancing influencing factor of each battery is determined. The specific analysis process is: obtain the basic data set of each battery, and the basic data set of each battery specifically includes the battery cumulative charging capacity, battery capacity retention rate, and battery internal resistance; based on the obtained basic data set of each battery, a comprehensive analysis is performed to obtain the SOC balancing influencing factor of each battery, and the SOC balancing influencing factor of each battery is used as the analysis basis for obtaining the characteristic value of the SOC balancing state of each battery.

[0007] As a further method, the real-time SOC usage status of each battery is analyzed, and the specific analysis process is: obtaining the real-time SOC usage status data set of each battery, and each battery SOC real-time usage status data set specifically includes the battery current SOC, the battery real-time current, and the battery SOC change rate; based on the obtained real-time SOC usage status data set of each battery, a comprehensive analysis is performed to obtain the SOC balancing determination factor of each battery, and each battery SOC balancing determination factor is used as an analysis basis for obtaining the characteristic value of the SOC balancing state of each battery.

[0008] As a further method, the characteristic value of the SOC equilibrium state of each battery is obtained. The specific analysis process is: each battery SOC equilibrium influencing factor and the corresponding battery SOC equilibrium determination factor are stored as a designated label, and each designated label is compared with the battery SOC equilibrium state characteristic value corresponding to each designated label stored in the database to obtain the battery SOC equilibrium state characteristic value corresponding to each designated label.

[0009] As a further method, the battery SOC equilibrium state determination value is determined, and the specific analysis process is: the difference between the maximum battery SOC equilibrium state characteristic value and the minimum battery SOC equilibrium state characteristic value is recorded as the battery SOC equilibrium state first determination value; the standard deviation of each battery SOC equilibrium state characteristic value is calculated, and the standard deviation of each battery SOC equilibrium state characteristic value is recorded as the battery SOC equilibrium state second determination value; the battery SOC equilibrium state first determination value and the battery SOC equilibrium state second determination value are stored as designated tags, and each designated tag is respectively compared with the battery SOC equilibrium state determination value corresponding to each designated tag stored in the database to obtain the battery SOC equilibrium state determination value corresponding to the designated tag.

[0010] As a further method, it is determined whether the battery needs to be SOC balanced. The specific analysis process is as follows: obtaining a characteristic data set of an energy storage system, the characteristic data set of the energy storage system specifically includes the power factor of the energy storage system, the load power of the energy storage system, and the load fluctuation frequency of the energy storage system; based on the obtained characteristic data set of the energy storage system, a comprehensive analysis is performed to obtain a characteristic value of the energy storage system, and the characteristic value of the energy storage system is used as an analysis basis for determining the battery SOC balance state judgment range; the characteristic value of the energy storage system is stored as a designated label, and the designated label is compared with the battery SOC balance state judgment range corresponding to each designated label stored in the database to obtain the battery SOC balance state judgment range corresponding to the designated label; if the battery SOC balance state judgment value falls within the battery SOC balance state judgment range, then each battery of the energy storage system corresponding to the battery SOC balance state judgment value does not need to be SOC balanced; if the battery SOC balance state judgment value does not fall within the battery SOC balance state judgment range, then each battery of the energy storage system corresponding to the battery SOC balance state judgment value needs to be SOC balanced.

[0011] As a further method, the energy storage system characteristic value, the specific analysis process is:

[0012]

[0013] In the formula, γ is the characteristic value of the energy storage system, ys is the power factor of the energy storage system, gl is the load power of the energy storage system, bd is the load fluctuation frequency of the energy storage system, ε1 is the compensation factor of the set ys, ε2 is the compensation factor of the set gl, and ε3 is the compensation factor of the set bd.

[0014] As a further method, the target characteristics of the energy storage system of the battery that needs SOC balancing are analyzed, and the specific analysis process is: obtaining the target characteristic data set of the energy storage system, the target characteristic data set of the energy storage system specifically includes the load fluctuation frequency of the energy storage system, the charging frequency of the energy storage system, and the daily average temperature difference of the energy storage system; based on the obtained target characteristic data set of the energy storage system, a comprehensive analysis is performed to obtain the target characteristic value of the energy storage system, and the target characteristic value of the energy storage system is used as an analysis basis for judging whether the energy storage system prioritizes balancing energy efficiency or balancing speed; the target characteristic value of the energy storage system is compared with the target characteristic threshold of the energy storage system stored in the database; if the target characteristic value of the energy storage system is not lower than the target characteristic threshold of the energy storage system, then the energy storage system of the battery that needs SOC balancing corresponding to the target characteristic value of the energy storage system prioritizes balancing speed, and multi-phase DC-DC converter balancing is selected; if the target characteristic value of the energy storage system is lower than the target characteristic threshold of the energy storage system, then the energy storage system of the battery that needs SOC balancing corresponding to the target characteristic value of the energy storage system prioritizes balancing energy efficiency, and active balancing is selected.

[0015] As a further method, it is determined whether the battery SOC balancing process is overheated, and the specific analysis process is: obtain an SOC balancing process temperature data set, the SOC balancing process temperature data set specifically includes the average battery temperature of the SOC balancing process, the maximum battery temperature of the SOC balancing process, and the maximum coolant outlet temperature of the SOC balancing process; based on the obtained SOC balancing process temperature data set, a comprehensive analysis is performed to obtain an SOC balancing process temperature evaluation value, and the SOC balancing process temperature evaluation value is used as an analysis basis for determining whether the battery SOC balancing process is overheated; compare the SOC balancing process temperature evaluation value with the SOC balancing process temperature evaluation threshold stored in a database; if the SOC balancing process temperature evaluation value is not lower than the SOC balancing process temperature evaluation threshold, then the battery SOC balancing process corresponding to the SOC balancing process temperature evaluation value is overheated; if the SOC balancing process temperature evaluation value is lower than the SOC balancing process temperature evaluation threshold, then the battery SOC balancing process corresponding to the SOC balancing process temperature evaluation value is not overheated.

[0016] As a further method, the temperature evaluation value of the SOC balancing process, the specific analysis process is:

[0017]

[0018] Wherein, ω is the temperature evaluation value of the SOC balancing process, jw is the average battery temperature during the SOC balancing process, gw is the maximum battery temperature during the SOC balancing process, ck is the maximum coolant outlet temperature during the SOC balancing process, μ1 is the compensation factor of the set jw, μ2 is the compensation factor of the set gw, μ3 is the compensation factor of the set ck, and e is a natural constant.

[0019] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0020] (1) The present invention provides an EMS-based energy storage system battery SOC balancing method and analyzes the SOC balancing influencing factors of each battery. It can more comprehensively identify the reasons affecting the uneven SOC of the battery and achieve targeted balancing. Accurate SOC balancing reduces the difference between batteries and improves the consistency of the battery pack. It determines whether balancing is required based on the SOC balancing state characteristic value and balancing judgment value of each battery, so that the system only performs balancing operations when it is really needed to avoid unnecessary energy consumption. According to the specific needs of the energy storage system, if efficient energy utilization is required, active balancing is selected. If the load changes frequently and requires rapid response, multi-phase DC-DC converter balancing is used. This flexible selection can adapt to different load characteristics and application scenarios, and also helps to improve system safety and reduce the difficulty of temperature management.

[0021] (2) The present invention analyzes the real-time SOC usage status of each battery, combines the SOC balancing influencing factors of each battery, obtains the SOC balancing status characteristic value of each battery, and analyzes the real-time SOC status of each battery in combination with the SOC balancing influencing factors (such as temperature, internal resistance, health status, etc.). It can more accurately identify which batteries need to be balanced and the priority of balancing. The SOC balancing status characteristic value helps the system to better manage the power distribution in the battery pack and optimize the efficiency during the charging and discharging process, thereby extending the battery's available power and reducing the number of cycles. The real-time SOC usage status combined with the balancing influencing factors can help the system quickly obtain the balancing requirements of each battery and shorten the balancing decision time, thereby improving the response speed of SOC balancing and reducing the probability of sudden failures.

[0022] (3) The present invention determines whether the energy storage system prioritizes energy efficiency or speed in balancing. Different application scenarios have different requirements for energy storage systems. For example, microgrid frequency regulation, backup power supply and other scenarios pay more attention to energy efficiency, while electric vehicles, emergency energy storage and other scenarios require faster balancing. By clarifying the system requirements, a suitable balancing strategy can be selected to ensure that the system can adapt to various scenarios. For application scenarios with large load fluctuations, prioritizing balancing speed helps to respond quickly when power demand changes. For scenarios with stable loads, prioritizing energy efficiency can ensure long-term stable operation of the system, improve system efficiency and power supply quality, and reduce the environmental pressure of the battery system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0024] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0025] Figure 2 A flowchart of the steps for determining whether the battery needs SOC balancing. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0027] Reference Figure 1 As shown, the present invention provides an energy storage system battery SOC balancing method based on EMS, including: based on EMS (energy management system), analyzing the basic data of each battery in the energy storage system to determine the SOC (charge state) balancing influencing factor of each battery.

[0028] The specific analysis process is as follows: obtain the basic data set of each battery, which specifically includes the battery's cumulative charging capacity, battery capacity retention rate, and battery internal resistance; based on the obtained basic data set of each battery, comprehensively analyze and obtain the SOC balance influencing factor of each battery, and use the SOC balance influencing factor of each battery as the analysis basis for obtaining the characteristic value of the SOC balance state of each battery.

[0029] In a specific embodiment, each charging data is uploaded to the EMS, and the cumulative charging capacity is obtained by cumulative calculation. The rated capacity, discharge test data and current actual capacity are recorded based on the EMS database to obtain the capacity retention rate. The EMS data analysis module records and analyzes the internal resistance measurement data to track the trend of internal resistance changes. The cumulative charging capacity refers to the total amount of electricity that has been charged into the battery during its entire life cycle, usually expressed in ampere-hours (Ah) or watt-hours (Wh). The capacity retention rate refers to the percentage of the current available capacity of the battery relative to the nominal capacity of the battery when it leaves the factory, usually expressed as a percentage (%). The internal resistance of the battery refers to the resistance to the flow of current inside the battery, usually in milliohms (mΩ). The internal resistance includes the ohmic impedance, polarization impedance and other electrochemical impedances inside the battery.

[0030] The cumulative charging capacity reflects the total amount of charging the battery has experienced. The more times the battery is charged and the larger the amount of charging, the lower the battery's capacity retention rate will tend to be. As the cumulative charging capacity increases, the battery's active materials gradually wear out and the battery's capacity retention rate also decreases. The battery will produce internal chemical reactions during the charging and discharging process. These reactions will cause the aging of the battery materials and increase the polarization effect, which is manifested as a gradual increase in internal resistance. There is a certain negative correlation between the capacity retention rate and the internal resistance. As the battery's usage time increases and aging worsens, the capacity retention rate decreases, while the internal resistance increases. When the capacity retention rate decreases, the battery's available capacity becomes smaller, and the increase in internal resistance leads to lower charging and discharging efficiency.

[0031] Data such as the cumulative charging capacity, capacity retention rate, and internal resistance can reflect the actual health status and current performance differences of each battery. Based on this information, it is possible to more accurately determine which batteries need to be balanced first, avoid performing balancing operations on batteries without demand, and improve balancing accuracy. SOC balancing influencing factors help to customize balancing strategies, adjust the balancing intensity, frequency, and method according to the specific circumstances of each battery, and achieve more personalized SOC balancing management. Accurate analysis of SOC balancing influencing factors can avoid over-balancing, reduce mechanical and chemical stress on battery cells, slow down battery wear, and extend the overall service life of the battery pack. Abnormal changes in capacity retention rate and internal resistance may indicate potential performance degradation or failure risks of the battery. Faulty batteries can be identified in advance during balancing operations and isolated or adjusted to ensure system safety.

[0032] Battery SOC balancing influencing factors, the specific analysis process is:

[0033]

[0034] Wherein, α is the battery SOC balancing influencing factor, rl is the battery cumulative charging capacity, bc is the battery capacity retention rate, nz is the battery internal resistance, σ1 is the compensation factor of the set rl, σ2 is the compensation factor of the set bc, and σ3 is the compensation factor of the set nz.

[0035] It needs to be explained that the above-mentioned battery SOC balancing influencing factor is calculated through the battery's cumulative charging capacity, battery capacity retention rate, and battery internal resistance. rl, bc, and nz are normalized. The battery's cumulative charging capacity, battery capacity retention rate, and internal resistance reflect the overall health status of the battery. The SOC balancing influencing factor can more accurately reflect the actual working capacity of the battery, and help to achieve more accurate SOC balancing. By using the balancing influencing factor to determine which batteries need to be balanced first, unnecessary battery charging and discharging losses can be reduced, thereby improving the energy utilization efficiency of the system. The balancing influencing factor can reflect the battery's degradation trend, which helps the system identify batteries that may fail in advance, facilitates maintenance or replacement planning, and prevents problems from worsening. The balancing influencing factor allows the system to autonomously adjust the balancing strategy, reduce manual monitoring and intervention, and improve the degree of automation of management.

[0036] It should be explained that the compensation factors of rl, bc, nz set above are obtained from the database. According to the historical data, a mapping set of the historically measured battery cumulative charging capacity, battery capacity retention rate, battery internal resistance and the compensation factors of rl, bc, nz is established to obtain the compensation factors of rl, bc, nz corresponding to the current rl, bc, nz.

[0037] It should be noted that τ1, τ2, τ3, ε1, ε2, ε3, θ1, θ2, μ1, μ2, and μ3 mentioned below are also obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained based on the current data.

[0038] The real-time SOC usage status of each battery is analyzed, and the SOC balance state characteristic value of each battery is obtained by combining the SOC balance influencing factors of each battery.

[0039] The specific analysis process is as follows: obtaining the real-time SOC usage status data set of each battery, which specifically includes the current SOC of the battery, the real-time current of the battery, and the SOC change rate of the battery; based on the obtained real-time SOC usage status data set of each battery, a comprehensive analysis is performed to obtain the SOC balancing determination factor of each battery, and the SOC balancing determination factor of each battery is used as the analysis basis for obtaining the characteristic value of the SOC balancing state of each battery.

[0040] It should be explained that the current SOC of the above-mentioned battery is the remaining power state of the battery at a specific moment, usually expressed as a percentage (for example, 80% means that the current power is 80% of the full power). SOC reflects the proportion of available power in the battery and is a key parameter for battery management and energy storage system scheduling. SOC is usually calculated by a battery management system (BMS). The real-time current of the battery refers to the current value of the battery at a specific moment, which is used to reflect the charging or discharging intensity of the battery. Positive current represents charging, and negative current represents discharging. The current size and direction affect the battery's SOC change rate, heat generation, etc., and are important data for SOC calculation and balancing control. Based on the current sensor, the battery SOC change rate represents the change in the battery's SOC per unit time, which is used to reflect the speed at which the SOC increases or decreases. The SOC change rate is determined by the real-time current, load conditions and battery capacity. It is usually used to monitor whether the battery's charging and discharging process is stable and to evaluate the balancing needs. The BMS calculates the SOC change rate based on the real-time current data collected by the current sensor, combined with the battery capacity and time change.

[0041] The battery's SOC change rate is directly affected by the battery's real-time current. The larger the current, the faster the SOC changes. The current direction determines the direction of increase or decrease in SOC - charging current increases SOC, and discharging current decreases SOC. The battery's real-time current determines the increase or decrease in the battery's power at each moment, thereby affecting the current SOC value. SOC is the cumulative result of charging and discharging, and is dynamically adjusted with changes in current. The SOC change rate describes the speed of change of the current SOC, that is, whether the SOC increases quickly, increases slowly, decreases quickly, or decreases slowly, depending on the size and direction of the current. The greater the change rate, the faster the SOC value changes.

[0042] Real-time data such as SOC, current and SOC change rate reflect the instantaneous state and charging and discharging requirements of the battery. By analyzing these data to obtain the SOC balancing determination factor, the balancing strategy can be dynamically adjusted to make the balancing more accurate. The SOC balancing determination factor can reflect the SOC differences of different batteries in actual operation, thereby ensuring that the power of each battery remains relatively consistent during the balancing process, reducing the SOC deviation and improving the consistency of the battery pack. Through the SOC balancing determination factor, the charging and discharging of each battery in the battery pack can be arranged more reasonably, making the SOC more balanced and effectively improving the total energy utilization of the battery pack. The SOC balancing determination factor can help the system to promptly identify battery cells with large SOC deviations in the battery pack, quickly make balancing adjustments, and ensure the power supply stability of the battery pack when the load changes.

[0043] Battery SOC balancing determination factor, the specific analysis process is:

[0044]

[0045] Wherein, β is the battery SOC balancing determination factor, dq is the current SOC of the battery, dl is the real-time current of the battery, bh is the battery SOC change rate, τ1 is the compensation factor of the set dq, τ2 is the compensation factor of the set dl, and τ3 is the compensation factor of the set bh.

[0046] It needs to be explained that the above-mentioned battery SOC balancing determination factor is calculated through the current SOC of the battery, the real-time current of the battery, and the rate of change of the SOC of the battery. The dq, dl, and bh are normalized. The current SOC and the rate of change of the SOC are combined with the real-time current of the battery to accurately reflect the real-time status of the battery. Through the SOC balancing determination factor, the system can dynamically determine whether the battery needs to be balanced to avoid the lag of the static balancing strategy. The balancing determination factor can effectively identify batteries with large SOC differences, reduce the inconsistency of the battery power in the battery pack through balancing adjustment, and improve the consistency of the battery pack. The SOC change rate combined with the real-time current reflects the actual use of the battery. The determination factor can help the system prevent over-discharge or over-charging of batteries with low SOC or too high SOC change rate, thereby improving the safety of the system. The determination factor monitors the SOC status in real time, and the system can automatically adjust the balancing strategy, optimize the balancing strategy in real time, and adaptively meet the changing needs of the battery status.

[0047] Furthermore, the characteristic value of the SOC equilibrium state of each battery is obtained. The specific analysis process is: each battery SOC equilibrium influencing factor and the corresponding battery SOC equilibrium determination factor are stored as a specified label, and each specified label is compared with the battery SOC equilibrium state characteristic value corresponding to each specified label stored in the database to obtain the battery SOC equilibrium state characteristic value corresponding to each specified label.

[0048] In a specific embodiment, the SOC balancing state characteristic value can reflect the current balancing demand of the battery, so that the system can accurately determine which batteries need to be balanced, the priority and degree of balancing, avoid unnecessary operations on unnecessary battery cells, and thus optimize balancing management. After characteristic value analysis, only the battery that needs to be balanced is controlled to charge and discharge, avoiding unnecessary balancing operations and reducing energy waste. In particular, for batteries with relatively close SOCs, the system can determine through comparison not to perform balancing, thereby reducing energy consumption. The balancing state characteristic value can accurately determine the balancing demand of SOC, avoid damage to the battery due to overcharging or over-discharging, and effectively extend the battery life. The SOC balancing influencing factors and determination factors are stored and managed in the form of tags, which is convenient for rapid comparison with the standard characteristic value library, realizing an automated and intelligent balancing control process, and reducing manual intervention.

[0049] Based on the SOC balanced state characteristic value of each battery, a battery SOC balanced state determination value is determined.

[0050] The specific analysis process is as follows: the difference between the largest battery SOC equilibrium state characteristic value and the smallest battery SOC equilibrium state characteristic value is recorded as the first battery SOC equilibrium state judgment value; the standard deviation of each battery SOC equilibrium state characteristic value is calculated, and the standard deviation of each battery SOC equilibrium state characteristic value is recorded as the second battery SOC equilibrium state judgment value; the first battery SOC equilibrium state judgment value and the second battery SOC equilibrium state judgment value are stored as designated tags, and each designated tag is respectively compared with the battery SOC equilibrium state judgment value corresponding to each designated tag stored in the database to obtain the battery SOC equilibrium state judgment value corresponding to the designated tag.

[0051] The first judgment value represents the maximum deviation of the characteristic value of the battery in the battery pack, which can intuitively measure the degree of SOC imbalance inside the battery pack, and help the system prioritize balancing when the imbalance is large. The second judgment value (standard deviation) quantifies the distribution of the characteristic values ​​of the SOC balance state of all batteries, and reflects the overall situation of the SOC difference in the battery pack in more detail, which is convenient for the system to accurately judge the balancing requirements of each battery. Through the comprehensive analysis of the first and second judgment values, the system can identify whether balancing operation is indeed required. If the judgment value is low, it means that the SOC difference is within an acceptable range, and the system can choose unbalancing, thereby reducing energy waste. When the first and second judgment values ​​are high, the system can identify that there is a large SOC difference inside the battery pack, and solve the imbalance between batteries in time through balancing operation, thereby reducing the aging risk caused by overcharging or over-discharging of individual battery cells.

[0052] like Figure 2 As shown, the characteristics of the energy storage system are analyzed, and combined with the battery SOC balance state judgment value, it is determined whether the battery needs SOC balance.

[0053] The specific analysis process is as follows: obtaining a characteristic data set of an energy storage system, which specifically includes the power factor of the energy storage system, the load power of the energy storage system, and the load fluctuation frequency of the energy storage system; based on the obtained characteristic data set of the energy storage system, a comprehensive analysis is performed to obtain a characteristic value of the energy storage system, and the characteristic value of the energy storage system is used as an analysis basis for determining the battery SOC balance state judgment range; the characteristic value of the energy storage system is stored as a designated label, and the designated label is compared with the battery SOC balance state judgment range corresponding to each designated label stored in the database to obtain the battery SOC balance state judgment range corresponding to the designated label; if the battery SOC balance state judgment value falls within the battery SOC balance state judgment range, then each battery of the energy storage system corresponding to the battery SOC balance state judgment value does not need to be SOC balanced; if the battery SOC balance state judgment value does not fall within the battery SOC balance state judgment range, then each battery of the energy storage system corresponding to the battery SOC balance state judgment value needs to be SOC balanced.

[0054] It should be explained that the above power factor indicates the ratio of the active power actually consumed by the electric energy in the circuit to the apparent power, usually expressed as a decimal or percentage, reflecting the efficiency of converting electricity into actual power in the circuit. EMS collects and summarizes data from smart meters or power factor meters to monitor the power factor of the system in real time. Load power is the electric power output by the energy storage system, that is, the power provided by the battery pack or energy storage device when supplying power to the load. The power transmitter can convert current and voltage signals into power signals, which is suitable for real-time measurement of the load power of the energy storage system and transmits its data to EMS. The load fluctuation frequency indicates the frequency of changes in the load power of the energy storage system, that is, the frequency of fluctuations in the load power per unit time. EMS collects time series data of load power and monitors the load fluctuation frequency in real time by analyzing the periodicity and frequency of load power changes.

[0055] The power factor (PF) is the ratio of the active power to the apparent power of the energy storage system. If the power factor is low, the system will have a large reactive power component, which will cause the effective power (active power) actually provided to the load to decrease. Ideally, the power factor should be close to 1 to maximize the effective load power of the system. The load fluctuation frequency refers to the number of times the load power changes per unit time. If the load fluctuation frequency is high and the load power changes rapidly, the energy storage system must have the ability to respond quickly to ensure the stable output of the load power. When the load power fluctuates frequently, the energy storage system may find it difficult to maintain a high power factor continuously, because load fluctuations will affect the reactive power demand of the system. Frequent switching and changes in the load will cause the phase difference of the system to fluctuate frequently, thereby reducing the power factor.

[0056] The comparison between the characteristic value and the judgment range of the energy storage system can dynamically determine whether SOC balancing is needed, identify the balancing requirements under different working conditions, ensure that balancing is performed only when necessary, and improve the accuracy of judgment. Different energy storage system characteristics (such as load fluctuation frequency and power factor) will affect the discharge uniformity and SOC distribution of the battery. Based on these characteristics, the balancing judgment range is adaptively adjusted, so that the system can more accurately identify whether balancing is needed and avoid unnecessary balancing operations. Balancing is performed only when the battery SOC balancing state judgment value exceeds the judgment range. The system can avoid redundant balancing when the SOC consistency is high, thereby reducing energy waste and improving the overall energy efficiency of the system. The optimized balancing control reduces excessive use of batteries, extends the service life of battery packs and balancing equipment, reduces replacement and maintenance frequency, and saves the long-term operation and maintenance costs of the system. The judgment range of the SOC balancing state is adjusted according to the load power and fluctuation frequency of the energy storage system, so that the system can still respond flexibly under high load fluctuation conditions and improve its adaptability to load changes.

[0057] Furthermore, the specific analysis process of the energy storage system characteristic value is as follows:

[0058]

[0059] In the formula, γ is the characteristic value of the energy storage system, ys is the power factor of the energy storage system, gl is the load power of the energy storage system, bd is the load fluctuation frequency of the energy storage system, ε1 is the compensation factor of the set ys, ε2 is the compensation factor of the set gl, and ε3 is the compensation factor of the set bd.

[0060] It should be explained that the above-mentioned energy storage system characteristic values ​​are calculated through the power factor of the energy storage system, the load power of the energy storage system, and the load fluctuation frequency of the energy storage system. Ys, gl, and bd are normalized. The power factor, load power, and load fluctuation frequency jointly reflect the load characteristics of the system. It can be judged whether the energy storage system is in a high dynamic load (requiring fast response) or a low dynamic load (steady state), so as to more accurately judge whether the battery needs SOC balancing. In the high-fluctuation load scenario, the system characteristic value can indicate the need for speed-first balancing method, while in the stable load scenario, a more energy-saving balancing method can be selected to improve the adaptability and efficiency of the system. The balancing demand is judged by the system characteristic value. The system can automatically determine whether the battery needs SOC balancing without manual intervention, thereby realizing intelligent and automated balancing management.

[0061] Analyze the target characteristics of the energy storage system of the battery that needs SOC balancing: if the energy storage system of the battery that needs SOC balancing prioritizes balancing energy efficiency, select active balancing; if the energy storage system of the battery that needs SOC balancing prioritizes balancing speed, select multi-phase DC-DC converter balancing.

[0062] The specific analysis process is as follows: obtaining a target characteristic data set of the energy storage system, which specifically includes the energy storage system load fluctuation frequency, the energy storage system charging frequency, and the energy storage system daily average temperature difference; based on the obtained target characteristic data set of the energy storage system, a comprehensive analysis is performed to obtain a target characteristic value of the energy storage system, and the target characteristic value of the energy storage system is used as an analysis basis for judging whether the energy storage system prioritizes balanced energy efficiency or balanced speed; comparing the target characteristic value of the energy storage system with the target characteristic threshold of the energy storage system stored in the database; if the target characteristic value of the energy storage system is not lower than the target characteristic threshold of the energy storage system, the energy storage system of the battery that needs SOC balancing corresponding to the target characteristic value of the energy storage system prioritizes balanced speed, and multi-phase DC-DC converter balancing is selected; if the target characteristic value of the energy storage system is lower than the target characteristic threshold of the energy storage system, the energy storage system of the battery that needs SOC balancing corresponding to the target characteristic value of the energy storage system prioritizes balanced energy efficiency, and active balancing is selected.

[0063] In a specific embodiment, the load fluctuation frequency refers to the frequency of changes in the load power of the energy storage system, that is, the number of changes in the load power per unit time, reflecting the volatility and dynamics of the load demand. The higher the load fluctuation frequency, the more frequent the load demand changes, and the higher the requirement for the response speed of the energy storage system. The charging frequency refers to the number of times the energy storage system is charged per unit time, usually measured in days or hours. The charging frequency reflects the usage intensity of the energy storage system and the length of the charging cycle. The higher the charging frequency, the more charging and discharging cycles the system has and the heavier the battery load is. It is obtained based on the smart meter. The daily average temperature difference refers to the difference between the highest temperature and the lowest temperature in the environment where the energy storage system is located in a day. The daily average temperature difference reflects the variation range of the ambient temperature and is an important feature of the operating environment of the energy storage system. When the temperature difference is large, the temperature influence on the battery during the charging and discharging process will be more significant. It is obtained based on the temperature sensor.

[0064] The higher the load fluctuation frequency, the more frequently the load demand of the energy storage system changes, which will shorten the battery's charge and discharge cycle and increase the charging frequency. Especially in high load fluctuation scenarios, the battery needs to be frequently charged and discharged to balance the load, increasing the number of charging times for the energy storage system. In the case of frequent load fluctuations, the battery's charge and discharge rate and discharge depth at different load powers will continue to change, resulting in unstable battery heating. In particular, high load fluctuation frequencies will cause frequent changes in battery temperature, resulting in greater temperature differences. High charging frequency means that the energy storage system is frequently in a charging state, and the battery temperature fluctuates greatly during the charging and discharging process, thereby causing the average daily temperature difference to increase. Especially in summer or high temperature environments, frequent charging leads to uneven battery pack temperatures, increasing the difficulty of thermal management.

[0065] The characteristic values ​​of load fluctuation frequency, charging frequency and daily average temperature difference reflect the working environment and load characteristics of the energy storage system. They can accurately identify whether the energy storage system needs to prioritize speed with a quick response or prioritize energy with efficiency, so as to select a more appropriate balancing method. When the characteristic value is lower than the threshold and energy efficiency is prioritized, the system adopts active balancing, which can effectively reduce unnecessary energy loss, extend the charge and discharge cycle of the battery pack, and improve the overall energy efficiency of the energy storage system. In scenarios with high fluctuation frequency and high charging frequency, if the characteristic value exceeds the threshold, the multi-phase DC-DC converter balancing with speed priority is selected, which can quickly adjust the battery SOC state to meet the needs of fast balancing, improve the load response speed, accurately judge the balancing needs, and select a suitable balancing method to prevent the battery from overcharging or over-discharging during the balancing process, reducing the risk of battery abnormality and damage.

[0066] It should be explained that the specific analysis process of the above target characteristic value of the energy storage system is as follows:

[0067]

[0068] Wherein, δ is the target characteristic value of the energy storage system, bd is the load fluctuation frequency of the energy storage system, cd is the charging frequency of the energy storage system, wc is the daily average temperature difference of the energy storage system, ε3 is the compensation factor of the set bd, θ1 is the compensation factor of the set cd, θ2 is the compensation factor of the set wc, and e is a natural constant.

[0069] It should be explained that the above-mentioned target characteristic value of the energy storage system is calculated through the load fluctuation frequency of the energy storage system, the charging frequency of the energy storage system, and the daily average temperature difference of the energy storage system. BD, CD, and WC are normalized. The load fluctuation frequency, charging frequency, and daily average temperature difference jointly determine the operating conditions of the system. Under the conditions of high load fluctuation, high charging frequency, and large temperature difference, the system target characteristic value can indicate the use of a fast-response balancing strategy (such as speed priority), while under stable load conditions, the system can choose an energy-saving balancing strategy (such as energy efficiency priority). The characteristic value can identify the use of the battery under high-frequency charging or high-load fluctuation. The system will reasonably balance according to the actual needs of the battery to prevent accelerated aging caused by overheating or long-term overload. High load fluctuation frequency, high charging frequency, and large temperature difference increase the thermal load of the battery. The system identifies high temperature difference environment or high load conditions through the target characteristic value, and gives priority to speed balancing to reduce the risk of battery overheating. The system target characteristic value helps the system automatically select the balancing strategy without manual intervention, realizing intelligent management of the balancing process.

[0070] Monitor the temperature status of the battery SOC balancing process to determine whether the battery SOC balancing process is overheated.

[0071] The specific analysis process is as follows: obtaining an SOC balancing process temperature data set, which specifically includes an average battery temperature during the SOC balancing process, a maximum battery temperature during the SOC balancing process, and a maximum coolant outlet temperature during the SOC balancing process; based on the obtained SOC balancing process temperature data set, a comprehensive analysis is performed to obtain an SOC balancing process temperature evaluation value, which is used as an analysis basis for determining whether the battery SOC balancing process is overheated; comparing the SOC balancing process temperature evaluation value with the SOC balancing process temperature evaluation threshold stored in a database; if the SOC balancing process temperature evaluation value is not lower than the SOC balancing process temperature evaluation threshold, then the battery SOC balancing process corresponding to the SOC balancing process temperature evaluation value is overheated, and the SOC balancing operation needs to be immediately suspended, and the coolant flow rate needs to be increased; if the SOC balancing process temperature evaluation value is lower than the SOC balancing process temperature evaluation threshold, then the battery SOC balancing process corresponding to the SOC balancing process temperature evaluation value is not overheated.

[0072] It should be explained that the above-mentioned average battery temperature during the SOC balancing process, the maximum battery temperature during the SOC balancing process, and the maximum coolant outlet temperature during the SOC balancing process are obtained based on temperature sensors. The average battery temperature during the SOC balancing process refers to the average temperature value of the battery pack during the balancing operation, which is the average of the temperatures of each single battery cell, reflecting the overall temperature level of the battery during the balancing process. The maximum battery temperature during the SOC balancing process refers to the temperature value of the single battery cell with the highest temperature in the battery pack during the balancing period, which can reveal the temperature distribution in the battery pack and reflect the temperature difference inside the battery. The maximum coolant outlet temperature during the SOC balancing process refers to the highest temperature of the coolant discharged from the outlet after passing through the battery pack cooling system during the balancing process, reflecting the efficiency of heat transfer from the battery pack to the coolant and the working status of the cooling system.

[0073] The relationship between the maximum battery temperature and the coolant outlet temperature reflects the heat dissipation efficiency of the cooling system. The closer the coolant outlet temperature is to the maximum battery temperature, the more significant the heat dissipation effect is. If the coolant outlet temperature is significantly lower than the maximum battery temperature, it may indicate insufficient coolant circulation or insufficient heat dissipation capacity. The relationship between the average battery temperature and the maximum coolant outlet temperature can reveal the overall heat dissipation requirements of the battery pack. If the coolant outlet temperature is close to the average battery temperature, it indicates that the cooling system is more efficient and the overall temperature is effectively controlled. If the coolant outlet temperature is significantly higher than the average battery temperature, it may mean that the cooling efficiency is insufficient and the system may require a higher cooling flow rate or a stronger heat dissipation device. When the average or maximum battery temperature is too high, the coolant outlet temperature will usually increase as well. At this time, the system can determine whether it exceeds the set threshold by comparing the temperature data. If it exceeds the threshold, the cooling system adjustment is automatically triggered to prevent overheating during SOC balancing.

[0074] Batteries may experience thermal runaway at high temperatures, especially when charging and discharging continuously during the balancing process. High temperatures will increase the risk of explosion or combustion. By monitoring the temperature evaluation value, a warning will be issued when the temperature reaches the threshold, and the balancing operation can be terminated in time to ensure system safety. Batteries age faster at high temperatures, especially high temperatures during the balancing process may cause the battery capacity to drop rapidly. Through real-time monitoring of the temperature evaluation value, the system can avoid continuing to balance when the temperature is higher than the threshold, thereby extending the battery life. By evaluating the temperature data set, it is ensured that the battery is balanced within the appropriate temperature range, reducing the decrease in battery efficiency due to increased temperature, thereby keeping the energy utilization rate at a high level. Ensuring that the battery is balanced under stable temperature conditions through temperature evaluation values ​​helps to reduce temperature differences and electrochemical imbalances between batteries and improve the stability of the entire energy storage system.

[0075] Furthermore, the temperature evaluation value of the SOC balancing process, the specific analysis process is as follows:

[0076]

[0077] Wherein, ω is the temperature evaluation value of the SOC balancing process, jw is the average battery temperature during the SOC balancing process, gw is the maximum battery temperature during the SOC balancing process, ck is the maximum coolant outlet temperature during the SOC balancing process, μ1 is the compensation factor of the set jw, μ2 is the compensation factor of the set gw, μ3 is the compensation factor of the set ck, and e is a natural constant.

[0078] It should be explained that the above-mentioned temperature evaluation value of the SOC balancing process is calculated through the average battery temperature of the SOC balancing process, the maximum battery temperature of the SOC balancing process, and the maximum temperature of the coolant outlet of the SOC balancing process. jw, gw, and ck are normalized. The temperature evaluation value can help the system quickly identify overheating risks and prevent thermal runaway of the battery due to excessive temperature through comprehensive analysis of the average battery temperature, the maximum temperature and the coolant outlet temperature. The increase in temperature will cause the internal resistance of the battery to increase, affecting the charging and discharging efficiency of the battery. Through temperature evaluation value monitoring, the system can control the temperature during the balancing process to prevent the internal resistance from rising, thereby maintaining battery performance. The temperature evaluation value helps the system to reasonably judge the cooling needs by comprehensively analyzing the maximum coolant outlet temperature and the battery temperature, avoiding excessive work or insufficient cooling of the cooling system, and ensuring efficient use of energy. Based on the temperature evaluation value, the system can automatically adjust the working mode and balancing current intensity of the cooling system without human intervention, thereby realizing intelligent temperature control management.

[0079] In a specific embodiment, the compensation factor of rl is 1.1, the compensation factor of bc is 0.9, and the compensation factor of nz is 1.05. Table 1 shows the basic data of each battery, and Table 2 shows the calculation results of the SOC balancing influencing factors of each battery.

[0080] Table 1

[0081]

[0082] Table 2

[0083] Battery Pack Battery SOC balancing influencing factors Battery 1 194478.34 Battery 2 148993.16 Battery 3 246013.54 Battery 4 166461.31 Battery 5 214366.48

[0084] The compensation factor of dq is 1.2, the compensation factor of dl is 0.95, and the compensation factor of bh is 1.1. Table 3 is the real-time usage status data of the battery SOC, Table 4 is the calculation result of the battery SOC balance determination factor, and Table 5 is the battery SOC balance state characteristic value.

[0085] Table 3

[0086]

[0087] Table 4

[0088] Battery Pack Battery SOC balancing determination factor Battery 1 10.13 Battery 2 9.78 Battery 3 10.29 Battery 4 10.01 Battery 5 10.10

[0089] Table 5

[0090] Battery Pack Battery SOC equilibrium state characteristic value Battery 1 194488.47 Battery 2 149002.94 Battery 3 246023.82 Battery 4 166471.32 Battery 5 214376.58

[0091] The first determination value of the battery SOC equilibrium state is calculated to be 97020.88, the second determination value of the battery SOC equilibrium state is calculated to be 34364.11, and the determination value of the battery SOC equilibrium state is calculated to be 121.

[0092] The power factor of the energy storage system is 0.95, the load power of the energy storage system is 50 (kW), the load fluctuation frequency of the energy storage system is 0.2, the compensation factor of ys is 1.2, the compensation factor of gl is 0.9, and the compensation factor of bd is 1.1. The calculated characteristic value of the energy storage system is 4.83, and the battery SOC balance state judgment range is 10-90. The battery SOC balance state judgment value 121 does not fall within the battery SOC balance state judgment range, then each battery of the energy storage system corresponding to the battery SOC balance state judgment value needs to perform SOC balance.

[0093] The load fluctuation frequency of the energy storage system is 0.2, the charging frequency of the energy storage system is 5, the average daily temperature difference of the energy storage system is 15 degrees Celsius, the compensation factor of cd is 0.95, and the compensation factor of wc is 1.05. The target characteristic value of the energy storage system is calculated to be 3.42, and the target characteristic threshold of the energy storage system stored in the database is 3.5. 3.42 is less than 3.5, so active balancing is selected.

[0094] The average battery temperature during the SOC balancing process is 34, the maximum battery temperature during the SOC balancing process is 38, the maximum coolant outlet temperature during the SOC balancing process is 30, the compensation factor of jw is 0.9, the compensation factor of gw is 1.05, and the compensation factor of ck is 1.1. The calculated SOC balancing process temperature evaluation value is 1.498, and the SOC balancing process temperature evaluation threshold stored in the database is 1.45. The SOC balancing process temperature evaluation value 1.498 is greater than the SOC balancing process temperature evaluation threshold 1.45, and it is judged to be overheated. It is necessary to suspend balancing and increase the coolant flow rate.

[0095] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. The battery SOC balancing method of energy storage system based on EMS is characterized by: The following steps are involved: Based on EMS, analyze the basic data of each battery in the energy storage system and determine the SOC balancing influencing factors of each battery; Analyze the real-time SOC usage status of each battery, and obtain the SOC balance state characteristic value of each battery by combining the SOC balance influencing factors of each battery; Determining a battery SOC balance state determination value based on each battery SOC balance state characteristic value; Analyze the characteristics of the energy storage system and determine whether the battery needs SOC balancing based on the battery SOC balancing state judgment value; Analyze the target characteristics of the energy storage system of the battery that needs SOC balancing: Obtaining a target characteristic data set of the energy storage system, wherein the target characteristic data set of the energy storage system specifically includes the energy storage system load fluctuation frequency, the energy storage system charging frequency, and the energy storage system daily average temperature difference; Based on the acquired target characteristic data set of the energy storage system, a comprehensive analysis is performed to obtain the target characteristic value of the energy storage system, which is used as an analysis basis for judging whether the energy storage system prioritizes balanced energy efficiency or balanced speed. comparing the energy storage system target characteristic value with the energy storage system target characteristic threshold value stored in the database; If the target characteristic value of the energy storage system is not lower than the target characteristic threshold of the energy storage system, the energy storage system of the battery that needs to be SOC balanced corresponding to the target characteristic value of the energy storage system prioritizes the balancing speed and selects the multi-phase DC-DC converter for balancing; If the target characteristic value of the energy storage system is lower than the target characteristic threshold of the energy storage system, the energy storage system of the battery that needs to be SOC balanced corresponding to the target characteristic value of the energy storage system prioritizes balanced energy efficiency and selects active balancing; Monitor the temperature status of the battery SOC balancing process to determine whether the battery SOC balancing process is overheated.

2. The method for balancing the battery SOC of an energy storage system based on EMS according to claim 1, characterized in that: The specific analysis process of determining the SOC balancing influencing factors of each battery is as follows: Obtaining basic data sets of each battery, including battery cumulative charging capacity, battery capacity retention rate, and battery internal resistance; Based on the basic data sets of each battery obtained, a comprehensive analysis is performed to obtain the SOC balance influencing factors of each battery, and the SOC balance influencing factors of each battery are used as the analysis basis for obtaining the characteristic values ​​of the SOC balance state of each battery.

3. The method for balancing the battery SOC of an energy storage system based on EMS according to claim 1, characterized in that: The real-time SOC usage status of each battery is analyzed, and the specific analysis process is as follows: Obtain the real-time SOC usage status data set of each battery, which specifically includes the current SOC of the battery, the real-time current of the battery, and the SOC change rate of the battery; Based on the acquired real-time SOC usage status data set of each battery, a comprehensive analysis is performed to obtain the SOC balancing determination factor of each battery, and the SOC balancing determination factor of each battery is used as an analysis basis for obtaining the SOC balancing state characteristic value of each battery.

4. The method for balancing the battery SOC of an energy storage system based on EMS according to claim 3, characterized in that: The specific analysis process of obtaining the SOC equilibrium state characteristic value of each battery is as follows: Each battery SOC balancing influencing factor and the corresponding battery SOC balancing determination factor are stored as designated tags, and each designated tag is compared with the battery SOC balancing state characteristic value corresponding to each designated tag stored in the database to obtain the battery SOC balancing state characteristic value corresponding to each designated tag.

5. The method for balancing battery SOC of an energy storage system based on EMS according to claim 1, characterized in that: The specific analysis process of determining the battery SOC balance state judgment value is as follows: Recording the difference between the maximum battery SOC equilibrium state characteristic value and the minimum battery SOC equilibrium state characteristic value as the battery SOC equilibrium state first determination value; Calculate the standard deviation of the SOC equilibrium state characteristic value of each battery, and record the standard deviation of the SOC equilibrium state characteristic value of each battery as the second determination value of the battery SOC equilibrium state; The first battery SOC equilibrium state determination value and the second battery SOC equilibrium state determination value are stored as designated tags, and each designated tag is compared with the battery SOC equilibrium state determination value corresponding to each designated tag stored in a database to obtain the battery SOC equilibrium state determination value corresponding to the designated tag.

6. The method for balancing battery SOC of an energy storage system based on EMS according to claim 1, characterized in that: The specific analysis process of determining whether the battery needs to be SOC balanced is as follows: Acquire a characteristic data set of an energy storage system, wherein the characteristic data set of the energy storage system specifically includes a power factor of the energy storage system, a load power of the energy storage system, and a load fluctuation frequency of the energy storage system; Based on the acquired energy storage system characteristic data set, a comprehensive analysis is performed to obtain the energy storage system characteristic value, which is used as the analysis basis for determining the battery SOC equilibrium state judgment range; The energy storage system characteristic value is stored as a designated tag, and the designated tag is compared with the battery SOC equilibrium state judgment range corresponding to each designated tag stored in the database to obtain the battery SOC equilibrium state judgment range corresponding to the designated tag; If the battery SOC balance state determination value falls within the battery SOC balance state determination range, then each battery of the energy storage system corresponding to the battery SOC balance state determination value does not need to perform SOC balance; If the battery SOC balance state determination value does not fall within the battery SOC balance state determination range, each battery of the energy storage system corresponding to the battery SOC balance state determination value needs to perform SOC balance.

7. The method for balancing battery SOC of an energy storage system based on EMS according to claim 6, characterized in that: The specific analysis process of the energy storage system characteristic value is as follows: In the formula, γ is the characteristic value of the energy storage system, ys is the power factor of the energy storage system, gl is the load power of the energy storage system, bd is the load fluctuation frequency of the energy storage system, ε1 is the compensation factor of the set ys, ε2 is the compensation factor of the set gl, and ε3 is the compensation factor of the set bd.

8. The method for balancing battery SOC of an energy storage system based on EMS according to claim 1, characterized in that: The specific analysis process of judging whether the battery SOC equalization process is overheated is as follows: Obtaining a temperature data set for the SOC balancing process, wherein the temperature data set for the SOC balancing process specifically includes an average battery temperature during the SOC balancing process, a maximum battery temperature during the SOC balancing process, and a maximum coolant outlet temperature during the SOC balancing process; Based on the acquired SOC balancing process temperature data set, a comprehensive analysis is performed to obtain a SOC balancing process temperature evaluation value, which is used as an analysis basis for determining whether the battery SOC balancing process is overheated; Compare the SOC balancing process temperature evaluation value with the SOC balancing process temperature evaluation threshold stored in the database; If the SOC balancing process temperature evaluation value is not lower than the SOC balancing process temperature evaluation threshold, then the battery SOC balancing process corresponding to the SOC balancing process temperature evaluation value is overheated; If the SOC balancing process temperature evaluation value is lower than the SOC balancing process temperature evaluation threshold, then the battery SOC balancing process corresponding to the SOC balancing process temperature evaluation value does not overheat.

9. The method for balancing battery SOC of an energy storage system based on EMS according to claim 8, characterized in that: The SOC balancing process temperature evaluation value, the specific analysis process is: Wherein, ω is the temperature evaluation value of the SOC balancing process, jw is the average battery temperature during the SOC balancing process, gw is the maximum battery temperature during the SOC balancing process, ck is the maximum coolant outlet temperature during the SOC balancing process, μ1 is the compensation factor of the set jw, μ2 is the compensation factor of the set gw, μ3 is the compensation factor of the set ck, and e is a natural constant.

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