A battery soc estimation method and device in a bbu standby mode

Abstract

The application discloses a battery SOC estimation method and device under a BBU standby working condition. The method comprises the following steps: when the BMS detects that the BBU enters the standby working condition, obtaining an initial SOC value of the battery, a battery temperature value and a battery SOH value, and a battery pack rated capacity and an AFE unit average working current; calculating a battery self-discharge consumption capacity according to the initial SOC value of the battery, the battery temperature value and the battery SOH value, and by querying a pre-calibrated self-discharge characteristic data table; calculating an AFE unit consumption capacity according to the AFE unit average working current; and estimating a current SOC value of the battery under the BBU standby working condition according to the battery self-discharge consumption capacity, the AFE unit consumption capacity and the battery pack rated capacity. The technical scheme provided by the application solves the problem that a conventional SOC estimation method cannot calculate the battery SOC of the BBU under the standby working condition, and causes an error in the estimation of the residual power, and can effectively improve the estimation accuracy of the SOC.

Description

Technical Field

[0001] This application relates to the field of battery management technology, and in particular to a method and apparatus for estimating battery SOC under BBU standby conditions. Background Technology

[0002] Battery backup units (BBUs) are widely used as backup power sources for computing servers. As backup power units, BBUs remain in standby mode for extended periods. During standby, due to the charging and discharging currents, conventional methods for estimating the battery's state of charge (SOC) based on AH integration become ineffective. This makes it impossible to calculate the SOC drop caused by battery self-discharge and other energy consumption during prolonged standby, leading to errors in the estimation of remaining battery capacity. Summary of the Invention

[0003] This application provides a method and apparatus for estimating the battery SOC under BBU standby conditions, in order to solve the problem that conventional SOC estimation methods cannot calculate the battery SOC of BBU under standby conditions, resulting in errors in the estimation of remaining power.

[0004] According to one aspect of this application, a method for estimating battery SOC under BBU standby conditions is provided, wherein the BBU includes a battery pack, an AFE unit, and a BMS, and the method includes:

[0005] When the BMS detects that the BBU has entered standby mode, it acquires the initial SOC value, battery temperature value, and battery SOH value of the battery, as well as the rated capacity of the battery pack and the average operating current of the AFE unit.

[0006] The battery self-discharge capacity is calculated by querying a pre-calibrated self-discharge characteristic data table based on the battery's initial SOC value, battery temperature value, and battery SOH value; the self-discharge characteristic data table contains time-based self-discharge capacity values ​​corresponding to different battery temperature values, different initial SOC values, and different battery SOH values.

[0007] Calculate the capacity consumed by the AFE unit based on the average operating current of the AFE unit;

[0008] Based on the battery's self-discharge capacity, the AFE unit's consumption capacity, and the battery pack's rated capacity, estimate the current SOC value of the battery under BBU standby conditions.

[0009] In some embodiments, the self-discharge characteristic data table is obtained through pre-calibration of battery testing, including temperature gradients of at least 0°C, 25°C, 35°C, and 45°C, and SOH gradients of at least 100%, 95%, 90%, 85%, and 80%. The data table stores the self-discharge capacity value corresponding to each day in 24-hour units.

[0010] In some embodiments, the battery self-discharge capacity is calculated by querying a pre-calibrated self-discharge characteristic data table based on the battery's initial SOC value, battery temperature value, and battery SOH value, including:

[0011] Based on the battery's initial SOC value, battery temperature value, and battery SOH value, a pre-calibrated self-discharge characteristic data table is queried to obtain the corresponding self-discharge capacity value for each day under the corresponding operating conditions.

[0012] The battery self-discharge capacity is calculated based on the pre-collected current cumulative standby time and the corresponding self-discharge capacity value for each day under the corresponding operating conditions.

[0013] In some embodiments, the calculation of battery self-discharge consumption capacity based on the pre-collected current cumulative standby time and the corresponding self-discharge capacity value for each day under the corresponding operating conditions includes:

[0014] If the current cumulative standby time is within the 0-24 hour period, then the current cumulative standby time is divided by 24 and multiplied by the self-discharge capacity value of the corresponding period under the corresponding operating conditions to calculate the battery self-discharge consumption capacity.

[0015] If the current cumulative standby time is within the 48-72 hour period, then subtract 48 from the current cumulative standby time and divide by 24 to obtain the quotient value. Multiply the quotient value by the self-discharge capacity value of the corresponding period under the corresponding operating condition to obtain the product. Add the product to the self-discharge capacity value of the 0-24 hour period and the self-discharge capacity value of the 24-48 hour period to calculate the battery self-discharge consumption capacity.

[0016] In some embodiments, if the current cumulative standby time is within a period of 0-24 hours, the battery self-discharge capacity is calculated using the following formula:

[0017] In the formula, The battery consumes capacity due to self-discharge. This represents the current cumulative standby time. This represents the self-discharge capacity value under the corresponding operating conditions during the 0-24 hour period.

[0018] In some embodiments, if the current cumulative standby time is within a period of 48-72 hours, the battery self-discharge capacity is calculated using the following formula:

[0019] In the formula, This represents the self-discharge capacity value under the corresponding operating conditions during the 24-48 hour period. This represents the self-discharge capacity value under the corresponding operating conditions during the 48-72 hour period.

[0020] In some embodiments, calculating the AFE cell capacity consumption based on the average operating current of the AFE cell includes:

[0021] The following formula is used to calculate the capacity consumed by the AFE unit:

[0022] In the formula, Capacity consumed by the AFE unit This represents the average operating current of the AFE unit.

[0023] In some embodiments, estimating the current SOC value of the battery under BBU standby conditions based on the battery self-discharge capacity, the AFE cell consumption capacity, and the battery pack rated capacity includes:

[0024] The following formula is used to estimate the current SOC value of the battery under BBU standby conditions:

[0025] In the formula, This represents the current SOC value of the battery under BBU standby conditions. This is the initial SOC value of the battery when the BBU enters standby mode. The battery consumes capacity due to self-discharge. Capacity consumed by the AFE unit This refers to the rated capacity of the battery pack.

[0026] In some embodiments, the method further includes:

[0027] When the BMS detects that the BBU has exited standby mode and entered charging mode, it acquires the battery temperature, battery SOH value and battery SOC at the start of charging.

[0028] Based on the battery temperature and SOH value at the start of charging, the charging cutoff SOC threshold under the corresponding operating condition is determined by referring to a table.

[0029] Charging stops when the battery SOC reaches the charging cutoff SOC threshold at the charging start time.

[0030] According to another aspect of this application, a battery SOC estimation device under BBU standby conditions is provided, wherein the BBU includes a battery pack, an AFE unit, and a BMS, characterized in that the device includes:

[0031] The acquisition module is used to acquire the initial SOC value, battery temperature value, and battery SOH value of the battery, as well as the rated capacity of the battery pack and the average operating current of the AFE unit when the BMS detects that the BBU has entered the standby mode.

[0032] A battery self-discharge capacity calculation module is used to calculate the battery self-discharge capacity by querying a pre-calibrated self-discharge characteristic data table based on the battery's initial SOC value, battery temperature value, and battery SOH value; the self-discharge characteristic data table contains time-based self-discharge capacity values ​​corresponding to different battery temperature values, different initial SOC values, and different battery SOH values.

[0033] AFE unit capacity consumption calculation module, the AFE unit capacity consumption calculation module is used to calculate the AFE unit capacity consumption based on the average operating current of the AFE unit;

[0034] The SOC estimation module is used to estimate the current SOC value of the battery under BBU standby conditions based on the battery's self-discharge consumption capacity, the AFE unit's consumption capacity, and the battery pack's rated capacity.

[0035] The technical solution provided in this application, when the BMS detects that the BBU has entered standby mode, acquires the initial SOC value, battery temperature value, and battery SOH value, as well as the rated capacity of the battery pack and the average operating current of the AFE unit. Based on the initial SOC value, battery temperature value, and battery SOH value, it calculates the battery self-discharge consumption capacity by consulting a pre-calibrated self-discharge characteristic data table; it calculates the AFE unit consumption capacity based on the average operating current of the AFE unit; and it estimates the current SOC value of the battery under BBU standby mode based on the battery self-discharge consumption capacity, AFE unit consumption capacity, and battery pack rated capacity. Since the battery capacity decay under BBU standby mode only comes from battery self-discharge loss and AFE unit consumption capacity, calculating the battery self-discharge consumption capacity and AFE unit consumption capacity solves the problem that conventional SOC estimation methods cannot calculate the battery SOC of the BBU under standby mode, leading to errors in the estimation of remaining capacity. The technical solution provided in this application can effectively improve the accuracy of SOC estimation.

[0036] It should be understood that the description in this section is not intended to identify key or important features of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1A flowchart of a battery SOC estimation method under BBU standby conditions provided in this application;

[0039] Figure 2 A schematic diagram of the BBU structure provided in this application;

[0040] Figure 3 A schematic diagram of the capacity consumption source of the BBU in standby mode provided in this application;

[0041] Figure 4 A flowchart of another battery SOC estimation method under BBU standby conditions provided in this application;

[0042] Figure 5 A schematic diagram of a battery SOC estimation device under BBU standby conditions provided in this application;

[0043] Figure 6 A schematic diagram of the electronic device for estimating battery SOC under BBU standby conditions provided in this application; Detailed Implementation

[0044] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0045] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0046] Figure 1The flowchart provided in this application illustrates a method for estimating battery SOC under BBU standby conditions. This embodiment is applicable to battery SOC estimation under BBU standby conditions. The method can be executed by a battery SOC estimation device under BBU standby conditions. This device can be implemented in hardware and / or software and can be configured in any electronic device with communication functions. Figure 2 For a schematic diagram of the BBU structure provided in this application, please refer to [link / reference]. Figure 2 The BBU includes a battery pack, an Analog Front End (AFE) unit, and a Battery Management System (BMS). The AFE unit, not shown in the diagram, is integrated within the BMS and is used to collect battery cell voltage and temperature data. The battery pack serves as backup power in the BBU system, providing discharge power when the BBU power fails and charging the battery pack when mains power is restored. The BMS collects battery pack information, communicates with the monitoring module and DC-DC converter, and controls the fan for cooling. The DC-DC converter performs charging and discharging. The fan cools the DC-DC converter and battery pack. The monitoring module monitors all BBU information and performs logic processing. The BBU, as a backup power unit, uses an N+1 scheme, where N is for normal power supply and 1 is for backup. BUS+ and BUS- are power supply interfaces for server equipment. BAT+ and BAT- are power supply interfaces for the high-voltage equipment in the battery pack. Figure 3 This diagram illustrates the capacity consumption sources of the BBU under standby conditions provided in this application. On one hand, during standby, the battery constantly self-discharges, consuming its capacity. On the other hand, while the battery is in standby, the AFE (Analog and Finger Analyzer) is operational, collecting data on the battery cells' voltage and temperature; the energy consumed by the AFE comes from the battery itself. Therefore, the capacity reduction of the BBU under standby conditions primarily originates from battery self-discharge and AFE data collection. (See also...) Figure 1 The method includes:

[0047] S110. When the BMS detects that the BBU has entered standby mode, it acquires the initial SOC value, battery temperature value, and battery SOH value of the battery, as well as the rated capacity of the battery pack and the average operating current of the AFE unit.

[0048] The initial SOC value of the battery is the battery's state of charge value at the instant the BBU enters standby mode. It is estimated by the BMS before standby triggering using methods such as the ampere-hour integration method or the open-circuit voltage method under normal charging and discharging conditions. After entering standby mode, the conventional ampere-hour integration method cannot account for the capacity decay caused by micro-currents and self-discharge. Therefore, this initial SOC value needs to be latched as the starting reference for calculating the SOC decrease throughout the entire standby cycle. All capacity losses during standby are deducted based on this initial value.

[0049] The battery temperature value is the real-time temperature data of the battery pack at the start of standby, acquired by the BMS through the temperature acquisition unit inside the battery pack. Since the battery self-discharge rate is strongly correlated with ambient temperature, and the internal chemical reaction rate of the battery differs at different temperatures, resulting in significant differences in the degree of self-discharge loss, it is necessary to obtain the current battery temperature to match the self-discharge characteristic data pre-stored in the BMS, determine the self-discharge capacity parameters under the corresponding temperature conditions, and ensure that the self-discharge loss calculation closely reflects the actual operating environment.

[0050] The State of Health (SOH) value is used to characterize the current degree of battery degradation and aging. The self-discharge characteristics of a battery change with battery cycling and capacity decay. The self-discharge rate of batteries in different aging states is different. Therefore, it is necessary to obtain the current SOH value of the battery to match the self-discharge characteristic parameters under the corresponding degradation level. This allows the technical solution provided in this application to be adapted to different aging stages throughout the battery's entire life cycle, avoiding the continuous expansion of SOC estimation deviation due to battery aging.

[0051] The rated capacity of the battery pack is the nominal capacity value specified by the manufacturer. It is a fixed parameter pre-stored in the BMS and serves as the conversion benchmark between capacity loss and SOC percentage. In this application, both self-discharge and AFE operating loss are calculated using absolute capacity values. By dividing by the rated capacity of the battery pack, the absolute capacity loss can be converted into a relative change in SOC, ultimately yielding a real-time SOC value in percentage form.

[0052] The average operating current of the AFE unit is the nominal steady-state operating current of the AFE unit in standby acquisition mode. In standby mode, the AFE unit is continuously operating to collect information such as battery cell voltage and battery temperature in real time. Its operating power is entirely provided by the battery pack; therefore, this current value is a core parameter for calculating the AFE's capacity loss. This parameter can be extracted from the AFE chip's datasheet as a typical operating current value under standby conditions, or it can be obtained through current calibration tests under actual standby conditions. The total capacity consumed by the AFE during standby can then be obtained by integrating over time.

[0053] S120. Based on the battery's initial SOC value, battery temperature value, and battery SOH value, the self-discharge capacity of the battery is calculated by querying a pre-calibrated self-discharge characteristic data table. The self-discharge characteristic data table contains time-based self-discharge capacity values ​​corresponding to different battery temperature values, different initial SOC values, and different battery SOH values.

[0054] The self-discharge characteristic data table is a calibration dataset pre-calibrated through battery testing and stored in the BMS storage unit. Battery self-discharge originates from internal side reactions, and its rate of loss is not constant but influenced by multiple factors: battery temperature directly affects the internal chemical reaction rate; higher temperatures generally result in a faster self-discharge rate. Different initial state of charge (SOC) leads to differences in the internal electrochemical potential, causing corresponding changes in the self-discharge rate. The battery state of harmonic equilibrium (SOH) reflects the degree of battery aging and degradation; as the battery is cycled and its internal materials age, the self-discharge characteristics also shift. Based on these characteristics, standby self-discharge tests were conducted under multiple combinations of different battery temperatures, initial SOCs, and SOHs. Self-discharge capacity values ​​were recorded over several consecutive time periods under each condition, thus constructing a self-discharge characteristic data table covering multiple operating conditions. The data in this table is segmented according to a preset time granularity, corresponding to self-discharge capacity loss over different standby time intervals, reflecting the cumulative change in self-discharge capacity with standby time.

[0055] Specifically, during standby operation, the BMS uses the initial SOC, temperature, and SOH values ​​of the battery latched at the start of standby as query conditions to match and filter the time-segmented self-discharge capacity data corresponding to the current battery condition from a pre-stored self-discharge characteristic data table. Then, combining the cumulative standby time up to the current moment, it calculates the cumulative self-discharge consumption capacity using a combination of segmented accumulation and linear conversion based on the remaining time: for periods that have been fully elapsed within the cumulative standby time, the self-discharge capacity value of the corresponding period is directly accumulated; for the remaining time that is currently in progress and has not yet completed a full period, the self-discharge capacity corresponding to the full period is linearly converted according to the ratio of the remaining time to the full period length. The converted capacity value is then summed with the accumulated capacity value of the completed periods to obtain the cumulative self-discharge consumption capacity of the battery up to the current moment. This method requires no additional detection hardware and achieves accurate quantification of battery self-discharge loss solely through offline calibration data and online table lookup calculations.

[0056] S130. Calculate the capacity consumed by the AFE unit based on the average operating current of the AFE unit.

[0057] Specifically, the calculation of the AFE unit's capacity consumption is based on the ampere-hour integration principle, that is, the cumulative power consumption is obtained by integrating the average operating current over time. In this scheme, since the average operating current of the AFE is a constant calibrated value, the cumulative capacity consumption can be obtained by multiplying the average operating current by the cumulative standby time. During standby operation, the BMS continuously monitors the cumulative standby time and calculates the total capacity consumed by the AFE unit from the moment it enters standby mode to the current moment, using the average operating current of the AFE as a benchmark. This calculation method has low computational complexity, is compatible with the computing power of the BMS embedded processor, and can realize real-time updates of the AFE's capacity consumption during standby.

[0058] This method of calculating AFE power consumption overcomes the shortcomings of conventional ampere-hour integration methods, which are limited by current sampling accuracy and cannot identify standby micro-current losses. Without adding hardware sampling circuits, it achieves accurate quantification of AFE power consumption under standby conditions, providing a reliable basis for accurate estimation of BBU standby SOC.

[0059] S140. Estimate the current SOC value of the battery under BBU standby conditions based on the battery self-discharge capacity, AFE cell consumption capacity, and battery pack rated capacity.

[0060] Specifically, the self-discharge capacity of the battery calculated above is first summed with the capacity consumed by the AFE unit to obtain the total battery capacity loss from the moment the battery entered standby mode to the current moment. This total capacity loss is the absolute value of the usable capacity lost by the battery during standby. Then, this total capacity loss is divided by the pre-stored rated capacity of the battery pack to obtain the cumulative degradation ratio of the battery's SOC during standby. Finally, using the initial SOC value of the battery latched at the moment of entering standby mode as the calculation benchmark, the cumulative SOC degradation ratio is subtracted to obtain the real-time SOC value of the battery at the current moment.

[0061] The technical solution provided in this application, when the BMS detects that the BBU has entered standby mode, acquires the initial SOC value, battery temperature value, and battery SOH value, as well as the rated capacity of the battery pack and the average operating current of the AFE unit. Based on the initial SOC value, battery temperature value, and battery SOH value, it calculates the battery self-discharge consumption capacity by consulting a pre-calibrated self-discharge characteristic data table; it calculates the AFE unit consumption capacity based on the average operating current of the AFE unit; and it estimates the current SOC value of the battery under BBU standby mode based on the battery self-discharge consumption capacity, AFE unit consumption capacity, and battery pack rated capacity. Since the battery capacity decay under BBU standby mode only comes from battery self-discharge loss and AFE unit consumption capacity, calculating the battery self-discharge consumption capacity and AFE unit consumption capacity solves the problem that conventional SOC estimation methods cannot calculate the battery SOC of the BBU under standby mode, leading to errors in the estimation of remaining capacity. The technical solution provided in this application can effectively improve the accuracy of SOC estimation.

[0062] Optionally, the self-discharge characteristic data sheet is obtained through pre-calibration of battery testing, including temperature gradients of at least 0°C, 25°C, 35°C, and 45°C, and SOH gradients of at least 100%, 95%, 90%, 85%, and 80%. The data sheet stores the corresponding self-discharge capacity values ​​for each day in 24-hour units.

[0063] For example, see the table below:

[0064]

[0065] Figure 4 For a flowchart of another battery SOC estimation method under BBU standby conditions provided in this application, please refer to [link / reference]. Figure 4 In some embodiments, S120 specifically includes:

[0066] S1201. Based on the battery's initial SOC value, battery temperature value, and battery SOH value, query the pre-calibrated self-discharge characteristic data table to obtain the corresponding self-discharge capacity value for each day under the corresponding operating conditions.

[0067] S1202. Calculate the battery self-discharge consumption capacity based on the pre-collected current cumulative standby time and the corresponding self-discharge capacity value for each day under the corresponding operating conditions.

[0068] In some embodiments, S1202 specifically includes:

[0069] If the current cumulative standby time is within the 0-24 hour period, then divide the current cumulative standby time by 24 and multiply it by the self-discharge capacity value of the corresponding period under the corresponding operating conditions to calculate the battery self-discharge consumption capacity.

[0070] If the current cumulative standby time is within the 48-72 hour period, subtract 48 from the current cumulative standby time and divide by 24 to obtain the quotient. Multiply the quotient by the self-discharge capacity value of the corresponding period under the corresponding operating conditions to obtain the product. Add the product to the self-discharge capacity values ​​of the 0-24 hour period and the 24-48 hour period to calculate the battery self-discharge consumption capacity.

[0071] Referring to the table above, specifically, if the current cumulative standby time is within the 0-24 hour period, the battery self-discharge capacity is calculated using the following formula:

[0072] In the formula, The battery consumes capacity due to self-discharge. This represents the current cumulative standby time. This represents the self-discharge capacity value under the corresponding operating conditions during the 0-24 hour period.

[0073] If the current cumulative standby time is within 48-72 hours, the battery self-discharge capacity is calculated using the following formula:

[0074] In the formula, This represents the self-discharge capacity value under the corresponding operating conditions during the 24-48 hour period. This represents the self-discharge capacity value under the corresponding operating conditions during the 48-72 hour period.

[0075] In some embodiments, S130 specifically includes:

[0076] The following formula is used to calculate the capacity consumed by the AFE unit:

[0077] In the formula, Capacity consumed by the AFE unit This represents the average operating current of the AFE unit.

[0078] In some embodiments, S140 specifically includes:

[0079] The following formula is used to estimate the current SOC value of the battery under BBU standby conditions:

[0080] In the formula, This represents the current SOC value of the battery under BBU standby conditions. This is the initial SOC value of the battery when the BBU enters standby mode. The battery consumes capacity due to self-discharge. Capacity consumed by the AFE unit This refers to the rated capacity of the battery pack.

[0081] In some embodiments, the method further includes:

[0082] S210. When the BMS detects that the BBU has exited the standby mode and entered the charging mode, it acquires the battery temperature at the start of charging, the battery SOH value at the start of charging, and the battery SOC at the start of charging.

[0083] Among them, the SOC value at the start of charging serves as the benchmark for calculating the amount of electricity during the charging process, and is used to judge the charging progress in real time; the battery temperature at the start of charging and the SOH value at the start of charging serve as the matching basis for the SOC threshold at the end of charging.

[0084] S220. Based on the battery temperature and SOH value at the start of charging, determine the SOC threshold for the corresponding operating condition by referring to the table.

[0085] Among them, the charging cutoff SOC threshold is the optimal charging upper limit value calibrated in advance through battery charge and discharge characteristic tests. Different charging cutoff SOC thresholds correspond to different operating conditions of different temperatures and different SOH.

[0086] Specifically, the BMS uses the battery temperature and SOH value at the start of charging as query conditions to match and determine the charging cutoff SOC threshold for the corresponding operating condition from a pre-stored calibration table. The battery's charge acceptance and internal electrochemical activity are significantly affected by temperature. At low temperatures, the battery ion diffusion rate decreases, and an excessively high charging cutoff SOC can easily cause irreversible damage such as lithium plating on the negative electrode. Simultaneously, as the battery cycles and ages, the SOH decreases, and the battery's internal resistance and polarization voltage increase. A fixed charging cutoff point can lead to deviations in the actual charging capacity. Therefore, adaptively matching the charging cutoff SOC threshold based on temperature and SOH ensures that the charging endpoint closely matches the battery's current true state, balancing backup capacity requirements with battery life protection.

[0087] S230. When the battery SOC reaches the charging cutoff SOC threshold at the start of charging, charging is stopped.

[0088] Specifically, the BMS updates the battery SOC in real time. When it detects that the battery SOC has risen to the charging cutoff SOC threshold at the start of charging, it controls the BBU to disconnect the charging circuit and stop charging the battery pack. This method ensures that the battery maintains a reasonable charge level suitable for the current operating conditions after charging, guaranteeing that the BBU has sufficient backup power capacity while avoiding overcharging or undercharging issues caused by fixed charging cutoff strategies at different temperatures and aging stages. This ensures the accuracy and consistency of SOC estimation throughout the entire cycle of standby and charging operation of the BBU.

[0089] Figure 5 A schematic diagram of a battery SOC estimation device under BBU standby conditions provided in this application is shown below. Figure 5The device includes an acquisition module 310, a battery self-discharge capacity consumption calculation module 320, an AFE cell capacity consumption calculation module 330, and a SOC estimation module 340.

[0090] The acquisition module 310 is used to acquire the initial SOC value, battery temperature value, and battery SOH value of the battery, as well as the rated capacity of the battery pack and the average operating current of the AFE unit, when the BMS detects that the BBU has entered the standby mode.

[0091] The battery self-discharge capacity calculation module 320 is used to calculate the battery self-discharge capacity by querying a pre-calibrated self-discharge characteristic data table based on the battery's initial SOC value, battery temperature value, and battery SOH value. The self-discharge characteristic data table contains time-based self-discharge capacity values ​​corresponding to different battery temperature values, different initial SOC values, and different battery SOH values.

[0092] The AFE unit capacity consumption calculation module 330 is used to calculate the AFE unit capacity consumption based on the average operating current of the AFE unit.

[0093] The SOC estimation module 340 is used to estimate the current SOC value of the battery under BBU standby conditions based on the battery self-discharge capacity, AFE cell capacity consumption, and battery pack rated capacity.

[0094] The battery SOC estimation device under BBU standby mode provided in this application can execute the battery SOC estimation method under BBU standby mode provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the method execution.

[0095] Figure 6 This is a schematic diagram of an electronic device for estimating battery SOC under BBU standby conditions, as provided in this application. The electronic device is intended to represent various forms of digital computers, such as laptops, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0096] like Figure 6As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 and a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, the ROM 12, and the RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0097] Multiple components in electronic device 10 are connected to input / output I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of monitors, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0098] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a battery SOC estimation method under BBU standby conditions.

[0099] In some embodiments, a battery SOC estimation method for BBU standby mode can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via read-only memory ROM 12 and / or communication unit 19. When the computer program is loaded into random access memory RAM 13 and executed by processor 11, one or more steps of the battery SOC estimation method for BBU standby mode described above can be performed. Alternatively, in other embodiments, processor 11 can be configured in any other suitable manner to perform a battery SOC estimation method for BBU standby mode.

[0100] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0101] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0102] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0103] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to a user; and a keyboard and pointing device through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with a user; for example, feedback provided to the user can be any form of sensory feedback; and input from the user can be received in any form.

[0104] The systems and technologies described herein can be implemented in computing systems that include backend components, middleware components, or frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium. Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0105] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0106] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0107] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for estimating battery SOC under BBU standby conditions, wherein the BBU includes a battery pack, an AFE unit, and a BMS, characterized in that, The method includes: When the BMS detects that the BBU has entered standby mode, it acquires the initial SOC value, battery temperature value, and battery SOH value of the battery, as well as the rated capacity of the battery pack and the average operating current of the AFE unit. The battery self-discharge capacity is calculated by querying a pre-calibrated self-discharge characteristic data table based on the battery's initial SOC value, battery temperature value, and battery SOH value; the self-discharge characteristic data table contains time-based self-discharge capacity values ​​corresponding to different battery temperature values, different initial SOC values, and different battery SOH values. Calculate the capacity consumed by the AFE unit based on the average operating current of the AFE unit; Based on the battery's self-discharge capacity, the AFE unit's consumption capacity, and the battery pack's rated capacity, estimate the current SOC value of the battery under BBU standby conditions.

2. The method according to claim 1, characterized in that, The self-discharge characteristic data table is obtained through pre-calibration of battery testing, including temperature gradients of at least 0°C, 25°C, 35°C, and 45°C, and SOH gradients of at least 100%, 95%, 90%, 85%, and 80%. The data table stores the corresponding self-discharge capacity values ​​for each day in 24-hour units.

3. The method according to claim 1, characterized in that, Based on the battery's initial SOC value, battery temperature value, and battery SOH value, the battery's self-discharge capacity is calculated by referring to a pre-calibrated self-discharge characteristic data table, including: Based on the battery's initial SOC value, battery temperature value, and battery SOH value, a pre-calibrated self-discharge characteristic data table is queried to obtain the corresponding self-discharge capacity value for each day under the corresponding operating conditions. The battery self-discharge capacity is calculated based on the pre-collected current cumulative standby time and the corresponding self-discharge capacity value for each day under the corresponding operating conditions.

4. The method according to claim 3, characterized in that, Based on the pre-collected current cumulative standby time and the corresponding self-discharge capacity values ​​for each day under the corresponding operating conditions, the battery self-discharge consumption capacity is calculated, including: If the current cumulative standby time is within the 0-24 hour period, then the current cumulative standby time is divided by 24 and multiplied by the self-discharge capacity value of the corresponding period under the corresponding operating conditions to calculate the battery self-discharge consumption capacity. If the current cumulative standby time is within the 48-72 hour period, then subtract 48 from the current cumulative standby time and divide by 24 to obtain the quotient value. Multiply the quotient value by the self-discharge capacity value of the corresponding period under the corresponding operating condition to obtain the product. Add the product to the self-discharge capacity value of the 0-24 hour period and the self-discharge capacity value of the 24-48 hour period to calculate the battery self-discharge consumption capacity.

5. The method according to claim 4, characterized in that, If the current cumulative standby time is within the 0-24 hour period, the battery self-discharge capacity is calculated using the following formula: In the formula, The battery consumes capacity due to self-discharge. This represents the current cumulative standby time. This represents the self-discharge capacity value under the corresponding operating conditions during the 0-24 hour period.

6. The method according to claim 4, characterized in that, If the current cumulative standby time is within 48-72 hours, the battery self-discharge capacity is calculated using the following formula: In the formula, This represents the self-discharge capacity value under the corresponding operating conditions during the 24-48 hour period. This represents the self-discharge capacity value under the corresponding operating conditions during the 48-72 hour period.

7. The method according to claim 1, characterized in that, The capacity consumption of the AFE unit is calculated based on the average operating current of the AFE unit, including: The following formula is used to calculate the capacity consumed by the AFE unit: In the formula, Capacity consumed by the AFE unit This represents the average operating current of the AFE unit.

8. The method according to claim 1, characterized in that, Based on the battery self-discharge capacity, the AFE unit consumption capacity, and the battery pack rated capacity, the current SOC value of the battery under BBU standby conditions is estimated as follows: The following formula is used to estimate the current SOC value of the battery under BBU standby conditions: In the formula, This represents the current SOC value of the battery under BBU standby conditions. This is the initial SOC value of the battery when the BBU enters standby mode. The battery consumes capacity due to self-discharge. Capacity consumed by the AFE unit This refers to the rated capacity of the battery pack.

9. The method according to claim 1, characterized in that, The method further includes: When the BMS detects that the BBU has exited standby mode and entered charging mode, it acquires the battery temperature, battery SOH value and battery SOC at the start of charging. Based on the battery temperature and SOH value at the start of charging, the charging cutoff SOC threshold under the corresponding operating condition is determined by referring to a table. Charging stops when the battery SOC reaches the charging cutoff SOC threshold at the charging start time.

10. A battery SOC estimation device under BBU standby condition, wherein the BBU includes a battery pack, an AFE unit, and a BMS, characterized in that, The device includes: The acquisition module is used to acquire the initial SOC value, battery temperature value, and battery SOH value of the battery, as well as the rated capacity of the battery pack and the average operating current of the AFE unit when the BMS detects that the BBU has entered the standby mode. A battery self-discharge capacity calculation module is used to calculate the battery self-discharge capacity by querying a pre-calibrated self-discharge characteristic data table based on the battery's initial SOC value, battery temperature value, and battery SOH value; the self-discharge characteristic data table contains time-based self-discharge capacity values ​​corresponding to different battery temperature values, different initial SOC values, and different battery SOH values. AFE unit capacity consumption calculation module, the AFE unit capacity consumption calculation module is used to calculate the AFE unit capacity consumption based on the average operating current of the AFE unit; The SOC estimation module is used to estimate the current SOC value of the battery under BBU standby conditions based on the battery's self-discharge consumption capacity, the AFE unit's consumption capacity, and the battery pack's rated capacity.

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