Battery capacity calculation method and energy storage device

Abstract

This application discloses a battery capacity calculation method and an energy storage device. The battery capacity calculation method is applied to an energy storage device, which includes a battery module and a functional module connected to the battery module. The battery capacity calculation method includes: sampling first current data flowing through the battery module at a first frequency; sampling second current data flowing through the functional module at a second frequency, where the second frequency is greater than the first frequency; obtaining the output state of the battery module; and calculating the battery capacity change value of the battery module within the sampling time based on the first current data, the second current data, and the output state. This application can improve the accuracy of the calculated battery capacity change value, reduce the deviation between the calculated value and the actual value of the remaining battery capacity or state of charge, thereby improving the accuracy of the battery capacity display of the energy storage device and improving the user experience.

Description

Technical Field

[0001] This application relates to the field of energy storage technology, specifically to a battery capacity calculation method and an energy storage device. Background Technology

[0002] In related technologies, energy storage devices calculate battery capacity through a battery management system (BMS). The BMS collects the output or input current values ​​from the battery and then uses an ampere-hour integral algorithm to calculate the change in battery capacity. Based on this change, the latest remaining usable energy or state of charge can be obtained. However, the output current of an energy storage device varies under different operating conditions, and at times it may exhibit a pulse wave pattern. In such cases, calculating the battery capacity change using the current values ​​sampled by the BMS will result in low accuracy, leading to a significant deviation between the calculated remaining usable energy or state of charge and the actual value. Summary of the Invention

[0003] In view of this, this application provides a battery capacity calculation method and an energy storage device to reduce the deviation between the calculated current remaining usable power or state of charge and the actual power value. The technical solution of this application is as follows:

[0004] In a first aspect, this application provides a battery capacity calculation method applied to an energy storage device, the energy storage device including a battery module and a functional module connected to the battery module. The battery capacity calculation method includes: sampling first current data flowing through the battery module at a first frequency, sampling second current data flowing through the functional module at a second frequency greater than the first frequency, obtaining the output state of the battery module, and calculating the change in battery capacity of the battery module within the sampling period based on the first current data, the second current data, and the output state.

[0005] In one embodiment of this application, calculating the battery capacity change value of an energy storage device within a sampling period based on first current data, second current data, and output status includes: calculating the first capacity change value of a battery module within a sampling period based on the first current data; calculating the second capacity change value of each functional module within a sampling period based on each second current data; obtaining the first reliability coefficient of the first current data based on the output status; obtaining the second reliability coefficient of the second current data; and calculating the battery capacity change value within a sampling period based on the first capacity change value, each second capacity change value, the first reliability coefficient, and the second reliability coefficient.

[0006] In one embodiment of this application, the sum of the first reliability coefficient and the second reliability coefficient is 1.

[0007] In one embodiment of this application, the output state of the energy storage device includes an unloaded state and a loaded state. If the output state is an unloaded state, the first confidence coefficient is less than the second confidence coefficient. If the output state is a loaded state, the first confidence coefficient is greater than or equal to the second confidence coefficient.

[0008] In one embodiment of this application, the load state includes a low-power output state and a high-power output state. If the load state is a low-power output state, the first confidence coefficient is equal to the second confidence coefficient. If the load state is a high-power output state, the first confidence coefficient is greater than the second confidence coefficient.

[0009] In one embodiment of this application, the output state of the energy storage device includes an unloaded state and a loaded state. Obtaining the output state of the energy storage device includes: if the first current data is less than or equal to the first preset current, then the battery module is determined to be in an unloaded state; if the first current data is greater than the first preset current, then the battery module is determined to be in a loaded state.

[0010] In one embodiment of this application, the load state includes a low-power output state and a high-power output state. If the first current data is greater than the first preset current, the battery module is determined to be in the load state, including: if the first current data is greater than the first preset current and less than the second preset current, the battery module is determined to be in the low-power output state; if the first current data is greater than or equal to the second preset current, the battery module is determined to be in the high-power output state.

[0011] In one embodiment of this application, the battery capacity calculation method further includes: obtaining the state of charge of the battery module; and updating the state of charge based on the battery capacity change value.

[0012] Secondly, this application provides an energy storage device, including a processing module, a battery module, and functional modules connected to the battery module. The battery module includes a cell module and a battery management unit connected to the cell module. The battery management unit is connected to each functional module, and a processing module is connected to both the functional modules and the battery management unit. The battery management unit is used to sample first current data flowing through the battery module at a first frequency. The functional modules are used to sample second current data flowing through the functional modules at a second frequency, where the second frequency is greater than the first frequency. The processing module is used to obtain the output state of the battery module and calculate the change in battery capacity of the battery module during the sampling period based on the first current data, the second current data, and the output state.

[0013] In one embodiment of this application, the processing module is further configured to: calculate a first capacity change value of the battery module within the sampling time based on the first current data, calculate a second capacity change value of each functional module within the sampling time based on each second current data; obtain a first reliability coefficient of the first current data based on the output state, obtain a second reliability coefficient of the second current data, and calculate the battery capacity change value within the sampling time based on the first capacity change value, each second capacity change value, the first reliability coefficient, and the second reliability coefficient.

[0014] This application samples the first current data flowing through the battery module at a first frequency, and simultaneously samples the second current data flowing through the functional module at a second frequency. Since the sampling frequency of the second current data is greater than that of the first current data, the battery module of the energy storage device can increase the sampling points of the current data during the pulse current period. This makes the battery capacity change value calculated based on the current data closer to the actual capacity change value, thereby reducing the deviation between the calculated value of the remaining battery capacity or state of charge and the actual value, and thus improving the accuracy of the battery capacity displayed by the energy storage device and improving the user experience. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the structure of an energy storage device provided in an embodiment of this application.

[0016] Figure 2 This is a flowchart illustrating a battery capacity calculation method provided in an embodiment of this application.

[0017] Figure 3 This is a flowchart illustrating a method for calculating battery capacity change provided in an embodiment of this application.

[0018] Figure 4 This is a flowchart illustrating a method for identifying the output status of an energy storage device according to an embodiment of this application.

[0019] Figure 5 This is a flowchart illustrating a method for identifying the load status of an energy storage device according to an embodiment of this application.

[0020] Figure 6 This is a flowchart illustrating another battery capacity calculation method provided in an embodiment of this application.

[0021] Figure 7 This is a schematic diagram of the structure of an energy storage device provided in an embodiment of this application.

[0022] Figure 8 This is a circuit diagram of an energy storage device provided in an embodiment of this application. Detailed Implementation

[0023] It should be noted that in the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone, where A and B can be singular or plural. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and drawings of this application are used to distinguish similar objects, not to describe a specific order or sequence.

[0024] It should also be noted that the methods disclosed in the embodiments of this application or the methods shown in the flowcharts include one or more steps for implementing the method. Without departing from the scope of the claims, the execution order of multiple steps can be interchanged, and some steps can also be deleted.

[0025] Many energy storage devices currently have battery capacity display functions. The calculation of battery capacity is mainly achieved through the battery management system in the energy storage device. The battery management system includes a battery management chip, which collects the input or output current value of the battery side of the energy storage device. Then, it calculates the change value of battery capacity through the ampere-hour integration algorithm, so as to obtain the remaining battery capacity or state of charge based on the change value of battery capacity.

[0026] The formula for the above-mentioned ampere-hour integration algorithm includes:

[0027]

[0028] In the formula, ΔF is the change in battery capacity, t1 is the sampling time of the battery management chip, and I1 is the sampled current value.

[0029] The sampling period for the current value collected by the aforementioned battery management chip is fixed, for example, it can sample the current value once every 250ms or once every 100ms. When the functional module of the energy storage device is unloaded, the current output from the battery side to the functional module is a pulse current, which can be a pulse current with a fixed period or a random pulse current. The functional module is connected to the battery side and includes circuits or components that implement a certain function; this is not limited here. For example, the functional modules in the energy storage device can include inverter modules, rectifier modules, and auxiliary power supply modules. The energy storage device can be a device with pure energy storage function, or it can be other devices with energy storage function, such as refrigerators, air conditioners, and self-moving devices with battery modules.

[0030] Therefore, as mentioned above, when the functional modules of the energy storage device enter the idle period, the battery management chip samples the current value of the battery side through a fixed sampling period. The low frequency of the sampling period results in a large gap between sampling points. Some sampling points may be able to collect pulse current, while others may miss the pulse current, resulting in a current value of zero. This leads to a calculated change in battery capacity of zero, which is inconsistent with the actual value. As time accumulates, this situation will occur more and more frequently, resulting in a larger and larger deviation between the calculated value of the remaining battery capacity or state of charge and the actual value.

[0031] This application provides a battery capacity calculation method to reduce the deviation between the calculated current remaining available power or state of charge and the actual power value.

[0032] Please refer to Figure 1 This is a schematic diagram of the structure of an energy storage device provided in an embodiment of this application. The energy storage device 100 includes a battery module 110 and multiple functional modules 120 connected to the battery module 110. Each functional module 120 receives the current output from the battery module 110 to perform its corresponding function. Furthermore, each functional module 120 is equipped with a current sampling chip to sample the current flowing through it.

[0033] Next, in conjunction with the above Figure 1 This application introduces a battery capacity calculation method provided by an embodiment. Please refer to... Figure 2 This is a flowchart illustrating a battery capacity calculation method provided in an embodiment of this application, specifically including the following steps:

[0034] Step S21: Sample the first current data flowing through the battery module at a first frequency.

[0035] In this embodiment, the current flowing through the battery module can be divided into input current and output current. Input current and output current refer to the direction of the current relative to the direction of the battery module. It can be set so that if the input current is in the first direction, the output current is in the second direction. Therefore, when taking values, if the input current is positive, then the output current is negative, or vice versa. The battery management system can sample the current flowing through the battery module, that is, sample the charging current or discharging current of the battery module, thereby obtaining the first current data.

[0036] That is, the first frequency can be the sampling frequency of the battery management system. The first current data obtained from the sampling can be transmitted to the processing module of the energy storage device, which can be used to calculate the battery capacity.

[0037] Step S22: Sample the second current data flowing through the functional module at a second frequency, which is greater than the first frequency.

[0038] It is understood that steps S22 and S21 are performed simultaneously. That is, in this embodiment, the sampling duration of the second current data is the same as the sampling duration of the first current data, i.e., while sampling the first current data flowing through the battery module, the second current data flowing through the functional module is also sampled. Similarly, for each functional module, the current flowing into or out of the functional module will also be included, i.e., the second current data can be current data with positive and negative values.

[0039] The functional module may include a current sampling chip, such as an integrated circuit (IC). The second frequency is the sampling frequency of the current flowing through the sampling chip in the functional module. This chip samples the second current data at the second frequency. The sampled second current data can be transmitted to the processing module of the energy storage device. Alternatively, the functional module may also include a corresponding current sampling circuit to sample the second current data. This current sampling circuit can also be set up independently of the functional module.

[0040] In this embodiment, the second frequency is greater than the first frequency, meaning the sampling period of the current sampling chip in this functional module is less than the sampling period of the battery management chip. For example, if the sampling period of the battery management chip is 250ms, the sampling period of the current sampling chip can be 50ms. Therefore, the battery management chip and the current sampling chip can be configured for the energy storage device according to the above conditions, without limitation.

[0041] Step S23: Obtain the output status of the battery module.

[0042] Similarly, steps S23, S22, and S21 can also be executed simultaneously. The output state of the battery module can be obtained from the states stored in the energy storage device. In this case, the energy storage device needs to update the output state promptly after a change in the output state. In one embodiment, the output state of the battery module can be determined based on the first current data of the battery module, for example, by determining whether it is currently in a charging or discharging state based on the sign of the first current data. During discharging, the magnitude of the first current data can be used to determine whether it is currently under heavy load, light load, or no load.

[0043] Step S24: Calculate the battery capacity change value of the battery module during the sampling period based on the first current data, the second current data, and the output status.

[0044] In this embodiment, the sampling duration can be the battery capacity update time of the energy storage device. For example, the energy storage device can update the battery capacity every second. After acquiring the first current data, the second current data, and the corresponding output status within the same sampling duration, the processing module can calculate the battery capacity change value within that sampling duration. Then, by subtracting the battery capacity change value from the remaining battery capacity calculated after the previous sampling duration, the remaining battery capacity after the current sampling duration can be obtained. Alternatively, the state of charge change value can be calculated based on the battery capacity change value, thereby updating the displayed state of charge.

[0045] Specifically, the first current data flowing through the battery module is sampled at a first frequency, while the second current data flowing through the functional module is sampled at a second frequency. Since the sampling frequency of the second current data is greater than that of the first current data, the battery module of the energy storage device can increase the sampling points of the current data during the pulse current period. This makes the battery capacity change value calculated based on the current data closer to the actual capacity change value, thereby reducing the deviation between the calculated value of the remaining battery capacity or state of charge and the actual value, and thus improving the accuracy of the battery capacity display of the energy storage device and improving the user experience.

[0046] Please refer to Figure 3 This is a flowchart illustrating a method for calculating battery capacity change values ​​provided in an embodiment of this application. This method is one implementation of step S24 described above and specifically includes the following steps:

[0047] Step S31: Calculate the first capacity change value of the battery module within the sampling time based on the first current data.

[0048] In this embodiment, the first current data includes multiple current sample values. These multiple sample values ​​can be current data collected from multiple sampling points within one sampling period, or current data collected within multiple sampling periods, specifically determined based on the battery capacity update time setting. Therefore, the capacity change within each sampling time can be calculated using the sample values ​​through ampere-hour integration, and finally, the sum of all capacity changes is calculated, which is the first capacity change value within that sampling time.

[0049] The specific formula for calculating the first capacity change value can be:

[0050]

[0051] In the above formula, ΔF a I is the first capacity change value. a For the first current data, t i t represents the starting point of the sampling duration. j This represents the end point of the sampling duration, i.e., t.i To t j This indicates the sampling duration mentioned above. The processing module can be configured with a corresponding calculation program for this formula. After acquiring the first current data, inputting it into this calculation program will yield the corresponding first capacity change value.

[0052] Step S32: Calculate the second capacity change value of each functional module within the sampling time based on the second current data.

[0053] Similarly, the second current data also includes multiple current sample values. Since the second frequency is greater than the first frequency, the sampling period between each sample value in the second current data is relatively small, and the number of sample values ​​in the second current data is large within the same sampling duration.

[0054] The specific formula for calculating the second capacity change value can be:

[0055]

[0056] In the above formula, ΔF b For the second capacity change value, I b For functional modules in t i To t j The second current data is the sampling duration.

[0057] Step S33: Obtain the first confidence coefficient of the first current data and the second confidence coefficient of the second current data based on the output status.

[0058] In this embodiment, the first confidence coefficient represents the reliability of the first current data, that is, it represents the proportion of the first capacity change value when calculating the total battery capacity change value. Similarly, the second confidence coefficient represents the reliability of the second current data, that is, it represents the proportion of the second capacity change value when calculating the total battery capacity change value.

[0059] The first and second reliability coefficients are pre-stored in the processing module and can be adjusted by the user. Furthermore, the sum of the first and second reliability coefficients is 1. For example, when the battery module outputs a pulse current, to reduce the impact of missing pulse current sampling values, the reliability of the second current data is higher, and in this case, the second reliability coefficient can be greater than the first reliability coefficient.

[0060] In one embodiment, the operating state of the battery module can be determined by the magnitudes of the first and second current data. The first and second reliability coefficients can then be calculated and adjusted based on the operating state of the battery module. This reduces the deviation between the calculated and actual values ​​of the remaining battery capacity or state of charge, thereby improving the accuracy of the battery capacity display in the energy storage device and enhancing the user experience. Step S34: Calculate the battery capacity change value within the sampling period based on the first capacity change value, each second capacity change value, the first reliability coefficient, and the second reliability coefficient.

[0061] In this embodiment of the application, since the first confidence coefficient can be the proportion of the first capacity change value in the battery capacity change value, and the second confidence coefficient can be the proportion of the second capacity change value in the battery capacity change value, the formula for the battery capacity change value can be:

[0062] ΔF=K1ΔF a +K2ΔF b ;

[0063] In the above formula, K1 is the first confidence coefficient, K2 is the second confidence coefficient, and ΔF is the change in battery capacity.

[0064] Since the first and second confidence coefficients obtained from the battery module output status represent the reliability of the first and second current data respectively, especially when the battery module is in an unloaded state, the battery module outputs pulse current. By setting the second frequency to be greater than the first frequency, a higher second confidence coefficient is set to increase the proportion of the second current data with a larger sampling frequency in the calculation. This can reduce the impact of missing the sampling value of the pulse current and further reduce the deviation between the calculated value and the actual value of the battery capacity change.

[0065] In this embodiment, the output state of the energy storage device includes an unloaded state and a loaded state. The unloaded state means that the energy storage device is not connected to a load, or the energy storage device is connected to a load but the load is not working. In the unloaded state, the battery module of the energy storage device outputs pulse current to the functional module, including pulse current with a fixed period and random pulse current. The loaded state means that the energy storage device is connected to a load and the load starts to work.

[0066] If the output state is an unloaded state, the first confidence coefficient obtained based on the unloaded state is less than the second confidence coefficient. That is, the proportion of the second capacity change value when calculating the battery capacity change value is greater than the proportion of the first capacity change value, thereby reducing the impact of missing the sampling value of the pulse current and reducing the deviation between the calculated value and the actual value of the battery capacity change value under the unloaded state.

[0067] If the output state is under load, then the first confidence coefficient is greater than or equal to the second confidence coefficient. The first current data can be collected by the battery management system in the energy storage device, while the second current data can be collected by the functional modules in the energy storage device.

[0068] While the first sampling frequency of the battery management system is lower than the second sampling frequency of the functional modules, the sampling accuracy of the battery management system is higher. When the energy storage device is under load, the output current of the battery modules is relatively stable. Therefore, using the more accurate first current data from the battery management module to calculate the first capacity change value will more closely approximate the actual battery capacity change value. Thus, under load conditions, using a first confidence coefficient greater than or equal to the second confidence coefficient can effectively improve the accuracy of the calculated battery capacity change value.

[0069] Please refer to Figure 4 , Figure 4 A flowchart illustrating a method for identifying the output status of an energy storage device, provided in this application embodiment, includes the following steps:

[0070] Step S41: Compare the first current data with the first preset current.

[0071] Step S42: If the first current data is less than or equal to the first preset current, then the battery module is determined to be in an unloaded state.

[0072] Step S43: If the first current data is greater than the first preset current, then it is determined that the battery module is under load.

[0073] In this embodiment, the first preset current can be the effective current value output from the battery side to the functional module of the energy storage device under no-load conditions, or it can be the average current value output from the battery side to the functional module of the energy storage device under no-load conditions.

[0074] In this embodiment, the load-bearing state may further include a low-power output state and a high-power output state. The low-power output state includes the energy storage device connecting to a low-power load, such as a computer, mobile phone, or television, and outputting electrical energy to that load at a low power level; or some functional modules within the energy storage module operating, consuming the battery module's electrical energy at a low power level. The high-power output state includes the energy storage device connecting to a high-power load, such as an air conditioner, refrigerator, or car, and outputting electrical energy to that load at a high power level.

[0075] In obtaining the first and second confidence coefficients, if the load condition is low-power output, the first confidence coefficient is equal to the second confidence coefficient. If the load condition is high-power output, the first confidence coefficient is greater than the second confidence coefficient. That is, in the low-power output state, the current output by the battery module may be unstable. Therefore, by applying equal confidence coefficients to the first and second current data, both acquisition accuracy and the number of acquisition points can be balanced, thereby reducing calculation errors caused by unstable current output. In the high-power output state, the current output by the battery module is relatively stable. Given the higher accuracy of the first current data acquired by the battery management system, selecting a first confidence coefficient greater than the second confidence coefficient can improve calculation accuracy.

[0076] Please refer to Figure 5 , Figure 5 A flowchart illustrating a method for identifying the load state of an energy storage device, provided in this application embodiment, includes the following steps:

[0077] Step S51: Compare the first current data with the second preset current.

[0078] Step S52: If the first current data is greater than the first preset current and less than the second preset current, then the battery module is determined to be in a low-power output state.

[0079] Step S53: If the first current data is greater than or equal to the second preset current, then the battery module is determined to be in a high-power output state.

[0080] In this embodiment, the second preset current can be defined by the user's actual distinction between low-power and high-power loads. For example, the second preset current can be obtained by actually testing the current of low-power and high-power loads and preset in the processing module of the energy storage device. For example, during the test, the energy storage device can be connected to the high-power load and provide current to the high-power load to record the first current value output to the high-power load. Then, the energy storage device can be connected to the low-power load and provide current to the low-power load to record the second current output to the low-power load. The current value between the first current and the second current is selected as the aforementioned second preset current value.

[0081] Please refer to Figure 6 , Figure 6 This is a flowchart illustrating another battery capacity calculation method provided in an embodiment of this application, wherein... Figure 6 The battery capacity calculation method shown includes steps S61 to S66, and steps S61 to S64 and Figure 2 The steps S21 to S24 of the battery capacity calculation method shown are the same or similar, and therefore will not be repeated. Figure 2Compared to the battery capacity calculation method shown, the difference lies in that... Figure 6 The battery capacity calculation method shown also includes:

[0082] Step S65: Obtain the state of charge of the battery module.

[0083] Step S66: Update the state of charge based on the change in battery capacity.

[0084] In this embodiment, the state of charge (SOC) is the ratio of the remaining charge of the energy storage device to the charge at full charge. Therefore, when updating the SOC, the processing module can obtain the SOC of the battery module after the previous sampling period, which is the current SOC to be updated, and update the SOC using this battery capacity change value. For example, the formula for calculating and updating the SOC includes:

[0085]

[0086] In the above formula, SOC is the updated state of charge, and SOC1 is the state of charge to be updated.

[0087] Please refer to Figure 7 , Figure 7 This is a schematic diagram of an energy storage device provided in an embodiment of this application. The energy storage device 700 includes a processing module 710, a battery module 720, and functional modules 730 connected to the battery module 720. The battery module includes a cell assembly 721 and a battery management unit 722 connected to the cell assembly 721. The battery management unit 722 is connected to each of the functional modules 730.

[0088] The battery management unit 722 is used to sample first current data flowing through the battery module 720 at a first frequency. The functional module 730 is used to sample second current data flowing through the functional module 730 at a second frequency; the second frequency is greater than the first frequency. The processing module 710 is used to obtain the output state of the battery module 720, and to calculate the change in battery capacity of the battery module 720 during the sampling period based on the first current data, the second current data, and the output state.

[0089] In this embodiment of the application, the processing module 710 is further configured to: calculate the first capacity change value of the battery module 720 within the sampling time based on the first current data, and calculate the second capacity change value of each functional module 730 within the sampling time based on each second current data; obtain the first reliability coefficient of the first current data based on the output state, and obtain the second reliability coefficient of the second current data; and calculate the battery capacity change value within the sampling time based on the first capacity change value, each second capacity change value, the first reliability coefficient, and the second reliability coefficient.

[0090] In this embodiment of the application, more detailed functional descriptions of the above modules can be found in the corresponding content of the foregoing section, and will not be repeated here.

[0091] Please refer to Figure 8 , Figure 8 This is a circuit diagram of an energy storage device provided in an embodiment of this application. The energy storage device 800 includes a processing module 810, a battery module 820, and a first functional module 830 and a second functional module 840 connected to the battery module 820. The battery module includes a cell assembly 821 and a battery management unit 822 connected to the cell assembly 821. The battery management unit 822 is connected to the first functional module 830 and the second functional module 840.

[0092] Specifically, the battery management unit 822 includes a current sampling chip AFE, a capacitor C1, resistors R1, R2, and R5. The first end of resistor R5 is connected to the cell assembly 821, and the second end of resistor R5 is connected to the first functional module 830 and the second functional module 840. It can be understood that resistor R5 is connected in series in the aforementioned load circuit. Capacitor C1 is connected in parallel with resistor R5. The first end of resistor R1 is connected to the first end of resistor R5, and the second end of resistor R1 is connected to the first end of capacitor C1 and the current sampling chip AFE. The first end of resistor R2 is connected to the second end of resistor R5, and the second end of resistor R2 is connected to the second end of capacitor C2 and the current sampling chip AFE. The current sampling chip AFE is used to connect to the processing module 810. Resistors R1, R2, and C1 constitute a differential filter circuit to filter the differentially sampled first current data, and resistor R5 is the sampling resistor.

[0093] The first functional module 830 includes a control chip IC1, a capacitor C2, resistors R3, R4, and R6. Resistor R6 is connected in series with the load circuit. Capacitor C2 is connected in parallel with resistor R6. The first terminal of resistor R3 is connected to the first terminal of resistor R6, and the second terminal of resistor R3 is connected to the first terminal of capacitor C2 and the control chip IC1 of the first functional module 830. The first terminal of resistor R4 is connected to the second terminal of resistor R6, and the second terminal of resistor R4 is connected to the second terminal of capacitor C2 and the control chip IC1 of the first functional module 830. The control chip IC1 is used to connect to the processing module 810. Resistors R3, R4, and C2 constitute a differential filter circuit to filter the differentially sampled second current data; resistor R6 is the sampling resistor.

[0094] The second functional module 840 includes a control chip IC2, a capacitor C3, resistors R7, R8, and R9. Resistor R9 is connected in series with the load circuit. Capacitor C3 is connected in parallel with resistor R9. The first terminal of resistor R7 is connected to the first terminal of resistor R7, and the second terminal of resistor R7 is connected to the first terminal of capacitor C3 and the control chip IC2. The first terminal of resistor R8 is connected to the second terminal of resistor R9, and the second terminal of resistor R8 is connected to the second terminal of capacitor C3 and the control chip IC2. The control chip IC2 is used to connect to the processing module 810. Resistors R7, R8, and C3 constitute a differential filter circuit to filter the differentially sampled second current data; resistor R9 is the sampling resistor.

[0095] In this embodiment, the output current of the battery module 820 exhibits a pulse wave form when unloaded, meaning a pulse current is transmitted in the load circuit of the battery module 820. The current sampling period of the current sampling chip AFE for the load circuit is fixed, for example, once every 250ms or once every 100ms. The sampling periods of the current sampling chips IC1 and IC2 are much smaller than the sampling period of the current sampling chip AFE; for example, the current sampling of the load circuit can be performed once every 1ms or once every 10ms.

[0096] The formula for calculating the change in battery capacity of battery module 820 during one sampling period includes:

[0097] ΔF=K1ΔF a +K2ΔF b1 +K3ΔF b2 ;

[0098]

[0099]

[0100]

[0101] In the above formula, t i To t j Where ΔF is the sampling duration, K1 is the reliability coefficient of battery management unit 822, K2 is the reliability coefficient of first functional module 830, and K3 is the reliability coefficient of second functional module 840. a The first capacity change value of the battery management unit 822 during the sampling period, ΔF b1 The second capacity change value of the first functional module 830 during the sampling time is ΔF. b2 This represents the third capacity change value of the second functional module 840 during the sampling period. aFor the first current data of the battery management unit 822 during the sampling period, I b1 For the second current data of the first functional module 830 during the sampling period, I b2 The second functional module 840 receives the second current data during the sampling period.

[0102] Where K1+K2+K3=1, the logic for obtaining K1, K2, and K3 includes:

[0103] (1) When the energy storage device 800 is connected to a load, K1 = 1, K2 = 0, K3 = 0; when the energy storage device 800 is unloaded, K1 = 0, K2 + K3 = 1.

[0104] (2) When I < I1 in the output current of the battery module 820, K1 = 0, K2 + K3 = 1, I1 is the first preset current value, used to distinguish whether the battery module 820 is under no-load or under load. I can be the current value sampled by the battery management unit 822. I < I1 indicates no-load.

[0105] When I1 < I < I2 in the output current of the battery module 820, K1 = 0.5, K2 + K3 = 0.5, and I2 is the second preset current value, which is used to distinguish between low-power load and high-power load under the load of the battery module 820. I1 < I < I2 indicates low-power load.

[0106] In the output current of the battery module 820 mentioned above, I2 > I, K1 = 1, K2 = 0, K3 = 0, and I2 > I indicates high power load.

[0107] In this embodiment of the application, the first functional module 830 and the second functional module 840 listed are only two of the functional modules of the energy storage device 800. The energy storage device 800 may also include three or more functional modules.

[0108] When the energy storage device 800 includes three or more functional modules, the formula for calculating the change in battery capacity may also include:

[0109] ΔF=K1ΔF a +K2ΔF b1 +K3ΔF b2 +…+K n ΔF bn-1 ;

[0110] K1+K2+K3+…+K n =1;

[0111] In the above formula, K n Let ΔF be the reliability coefficient of the (n-1)th functional module. bn-1This represents the capacity change value of the (n-1)th functional module during the sampling period. It's understandable that the more functional modules participate in current sampling, the more accurate the calculated battery capacity change value will be, thus making the calculated battery capacity change value closer to the actual value.

[0112] This application also provides a computer storage medium storing a computer program that, when executed by a processor, causes the processor to perform the battery capacity calculation method described above.

[0113] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer storage medium or transmitted through the computer storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital versatile discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0114] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks. Unless otherwise specified, the technical features of this embodiment and its implementation can be combined arbitrarily.

[0115] The embodiments described above are merely preferred embodiments of this application and are not intended to limit the scope of this application. Any modifications and improvements made by those skilled in the art to the technical solutions of this application without departing from the spirit of this application should fall within the protection scope defined by the claims of this application.

Claims

1. A method for calculating battery capacity, characterized in that, The method is applied to an energy storage device, the energy storage device including a battery module and multiple functional modules connected to the battery module; the method includes: The first current data flowing through the battery module is sampled at a first frequency; The second current data flowing through the functional module is sampled at a second frequency; the second frequency is greater than the first frequency. Obtain the output state of the battery module; Based on the first current data, the second current data, and the output status, calculate the change in battery capacity of the battery module during the sampling period; The step of calculating the battery capacity change of the battery module within the sampling time based on the first current data, the second current data, and the output state includes: Calculate the first capacity change value of the battery module during the sampling period based on the first current data; Calculate the second capacity change value of each functional module within the sampling time based on each of the second current data; Based on the output state, obtain the first confidence coefficient of the first current data and obtain the second confidence coefficients corresponding to each of the second current data. The battery capacity change value within the sampling period is calculated based on the first capacity change value, each of the second capacity change values, the first confidence coefficient, and each of the second confidence coefficients.

2. The battery capacity calculation method as described in claim 1, characterized in that, The sum of the first reliability coefficient and the second reliability coefficient is 1.

3. The battery capacity calculation method according to claim 2, characterized in that, The output states of the battery module include no-load state and loaded state; If the output state is an unloaded state, then the first confidence coefficient is less than the second confidence coefficient; If the output state is a loaded state, then the first confidence coefficient is greater than or equal to the second confidence coefficient.

4. The battery capacity calculation method according to claim 3, characterized in that, The load conditions include low-power output state and high-power output state; If the load state is a low-power output state, then the first confidence coefficient is equal to the second confidence coefficient; If the load state is a high-power output state, then the first confidence coefficient is greater than the second confidence coefficient.

5. The battery capacity calculation method as described in claim 1, characterized in that, The output state of the battery module includes an unloaded state and a loaded state. Obtaining the output state of the battery module includes: If the first current data is less than or equal to the first preset current, then the battery module is determined to be in an unloaded state. If the first current data is greater than the first preset current, then the battery module is determined to be under load.

6. The battery capacity calculation method according to claim 5, characterized in that, The load state includes a low-power output state and a high-power output state. The step of determining that the battery module is in a load state if the first current data is greater than the first preset current includes: If the first current data is greater than the first preset current and less than the second preset current, then the battery module is determined to be in a low-power output state. If the first current data is greater than or equal to the second preset current, then the battery module is determined to be in a high-power output state.

7. The battery capacity calculation method according to claim 1, characterized in that, Also includes: Obtain the state of charge of the battery module; The state of charge is updated based on the change in battery capacity.

8. An energy storage device, characterized in that, It includes a processing module, a battery module, and multiple functional modules connected to the battery module; the battery module includes a cell module and a battery management unit connected to the cell module; the battery management unit is connected to each functional module; the processing module is connected to both the functional modules and the battery management unit. The battery management unit is used to sample first current data flowing through the battery module at a first frequency; The functional module is used to sample second current data flowing through the functional module at a second frequency; The second frequency is greater than the first frequency; The processing module is used to obtain the output state of the battery module, and to calculate the battery capacity change value of the battery module within the sampling time based on the first current data, the second current data and the output state. The processing module is also used for: Calculate the first capacity change value of the battery module during the sampling period based on the first current data; Calculate the second capacity change value of each functional module within the sampling time based on each of the second current data; Based on the output state, obtain the first confidence coefficient of the first current data and obtain the second confidence coefficients corresponding to each of the second current data. as well as The battery capacity change value within the sampling period is calculated based on the first capacity change value, each of the second capacity change values, the first confidence coefficient, and each of the second confidence coefficients.

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