Soc value dynamic updating method, safety monitoring method and device, and energy storage equipment

Abstract

The embodiment of the application discloses a SOC value dynamic updating method, a safety monitoring method and device, and an energy storage equipment. The method comprises the following steps: determining the sleep time of the energy storage equipment based on the battery state of the energy storage equipment, determining the sleep power consumption based on the sleep time and the sleep current, determining the wake-up power consumption based on the wake-up time and the wake-up current, and dynamically correcting the SOC value at the end of the sleep mode in the current time based on the sleep power consumption and the wake-up power consumption. The embodiment of the application adaptively adjusts the sleep time based on the battery state of the energy storage equipment in the sleep mode, so that the sleep time changes along with the change of the battery state, and is no longer a fixed value. The embodiment of the application improves the situation of invalid wake-up and the situation of easy to miss, and also calculates the sleep power consumption and the wake-up power consumption. The sleep power consumption and the wake-up power consumption are included in the correction process of the SOC value, the power consumption deviation accumulated in the sleep mode is compensated, and therefore, a more accurate SOC value is obtained, and the updating accuracy of the SOC value is improved.

Description

Technical Field

[0001] This application relates to the field of energy storage equipment technology, and in particular to a method for dynamically updating SOC value, a safety monitoring method, a device, and an energy storage equipment. Background Technology

[0002] When energy storage devices enter hibernation mode, they need to perform self-tests at a fixed frequency to obtain information such as battery status and system status. This prevents malfunctions during hibernation and ensures the safety of the energy storage device. Therefore, the energy storage device consumes a certain amount of power in hibernation mode to support the completion of the self-test. Related technologies primarily update the SOC (State of Charge) value based on the energy storage device's power consumption in normal operating mode, ignoring the power consumption during hibernation. This causes a discrepancy between the calculated SOC value and the actual SOC value. Since the energy storage device needs to perform related business operations based on the SOC value, when the SOC value deviates, the energy storage device is prone to misjudgment and enter an abnormal state. Summary of the Invention

[0003] One objective of this application is to provide a method for dynamically updating SOC values, a safety monitoring method, an apparatus, and an energy storage device to improve the situation where SOC value updates are inaccurate in related technologies.

[0004] In a first aspect, embodiments of this application provide a method for dynamically updating the SOC value, comprising: determining the next sleep time of an energy storage device based on the battery state of the energy storage device in the previous wake-up state, wherein the energy storage device includes a sleep mode that alternates between the sleep state and the wake-up state; determining the sleep power consumption in the sleep mode based on each sleep time in the sleep mode and the sleep current in the sleep state; determining the wake-up power consumption in the sleep mode based on the wake-up time corresponding to each wake-up state and the wake-up current in the wake-up state; and dynamically correcting the SOC value at the end of the current sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode.

[0005] Optionally, determining the next sleep time of the energy storage device based on the battery state of the energy storage device in the previous wake-up state includes: acquiring state description data in the previous wake-up state, wherein the state description data is used to describe the multi-dimensional state of the battery of the energy storage device in the previous wake-up state; acquiring a baseline sleep time; and determining the next sleep time of the energy storage device based on the state description data and the baseline sleep time.

[0006] Optionally, obtaining the reference sleep time includes: determining the reference sleep time based on the rated total capacity of the battery and the sleep current.

[0007] Optionally, determining the next sleep time of the energy storage device based on the state description data and the reference sleep time includes: determining a battery parameter set in the current wake-up state based on the state description data in the previous wake-up state, wherein the battery parameter set includes multiple target adjustment coefficients representing multiple performance parameters of the battery for adjusting the sleep time; and adjusting the reference sleep time through the battery parameter set to obtain the next sleep time of the energy storage device.

[0008] Optionally, the step of adjusting the reference sleep time through the battery parameter set to obtain the next sleep time of the energy storage device includes: multiple target adjustment coefficients and the reference sleep time are all positively correlated with the next sleep time.

[0009] Optionally, determining the battery parameter set for the current wake-up state based on the state description data from the previous wake-up state includes: determining a first target adjustment coefficient related to the remaining capacity of the battery in the previous wake-up state; determining a second target adjustment coefficient related to the voltage of the battery in the previous wake-up state; and determining a third target adjustment coefficient related to the battery temperature based on the battery temperature in the previous wake-up state.

[0010] Optionally, the step of dynamically correcting the SOC value at the end of the current sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode includes: determining the total power consumption of the energy storage device in the sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode; determining the depleted capacity value in the current sleep mode based on the total power consumption in the current sleep mode and the rated total capacity of the battery; and determining the remaining capacity value of the battery at the end of the current sleep mode based on the remaining capacity value of the battery at the time of entering the current sleep mode and the depleted capacity value in the current sleep mode.

[0011] In a second aspect, embodiments of this application provide a safety monitoring method for an energy storage device, comprising: obtaining the remaining capacity value of the battery at the end of the current hibernation mode obtained by the above-described dynamic update method of SOC value, and performing a safety monitoring operation based on the remaining capacity value of the battery at the end of the current hibernation mode.

[0012] Optionally, the safety monitoring operation based on the remaining battery capacity at the end of the current sleep mode includes: reducing the baseline sleep time in response to the remaining battery capacity being less than a first warning value; and controlling the energy storage device to enter a shutdown state and / or sending low battery information to the server in response to the remaining battery capacity being less than a second warning value, wherein the second warning value is less than the first warning value.

[0013] In a third aspect, embodiments of this application provide a dynamic SOC value update device, comprising: a sleep time update module, configured to determine the next sleep time of the energy storage device based on the battery state of the energy storage device in the previous wake-up state, wherein the energy storage device includes a sleep mode that alternates between the sleep state and the wake-up state; a sleep power consumption determination module, configured to determine the sleep power consumption in the sleep mode based on each sleep time in the sleep mode and the sleep current in the sleep state; a wake-up power consumption determination module, configured to determine the wake-up power consumption in the sleep mode based on the wake-up time corresponding to each wake-up state and the wake-up current in the wake-up state; and a dynamic SOC correction module, configured to dynamically correct the SOC value at the end of the current sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode.

[0014] In a fourth aspect, embodiments of this application provide an energy storage device, including a memory and a processor. The memory is connected to the processor, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, it causes the energy storage device to implement the above-described dynamic SOC value update method or the above-described safety monitoring method for the energy storage device.

[0015] In a fifth aspect, embodiments of this application provide a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the aforementioned dynamic SOC value update method or the aforementioned safety monitoring method for energy storage devices.

[0016] The embodiments of this application can achieve the following technical effects: The embodiments of this application can adaptively adjust the sleep time based on the battery state of the energy storage device in sleep mode, so that the sleep time changes with the changes in battery state and is no longer a fixed value, improving the situation of invalid wake-up and easy missed detection. In addition, the sleep power consumption and wake-up power consumption can be calculated and incorporated into the correction process of SOC value in sleep mode to compensate for the power consumption deviation accumulated in sleep mode, thereby obtaining a more accurate SOC value and improving the accuracy of SOC value update. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the 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.

[0018] Figure 1 This is a schematic diagram of the circuit structure of an energy storage device provided in an embodiment of this application;

[0019] Figure 2 This is a schematic diagram of the communication architecture between the energy storage device and the cloud server provided in an embodiment of this application;

[0020] Figure 3 A schematic diagram of the communication architecture between the energy storage device, cloud server, and terminal device provided in the embodiments of this application;

[0021] Figure 4 A circuit structure diagram of an energy storage device is provided for another embodiment of this application;

[0022] Figure 5 A schematic diagram illustrating a process for dynamically updating the SOC value, provided in an embodiment of this application;

[0023] Figure 6a A first schematic diagram illustrating how an energy storage device adaptively adjusts its sleep duration in sleep mode, as provided in an embodiment of this application.

[0024] Figure 6b A second schematic diagram illustrating how an energy storage device adaptively adjusts its sleep duration in sleep mode, as provided in this application embodiment;

[0025] Figure 7 A schematic diagram of the structure of a time estimation model provided in an embodiment of this application;

[0026] Figure 8 A flowchart illustrating a safety monitoring method for an energy storage device provided in an embodiment of this application;

[0027] Figure 9 This is a schematic diagram of the structure of a dynamic SOC value update device provided in an embodiment of this application;

[0028] Figure 10 This is a schematic diagram of the structure of a safety monitoring device for an energy storage device provided in an embodiment of this application;

[0029] Figure 11 This is a schematic diagram of the structure of a BMS controller provided in an embodiment of this application. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0031] It should be noted that, unless there is a conflict, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than the module division in the device or the order in the flowchart. Moreover, the terms "first," "second," and "third" used in this application do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.

[0032] To monitor the battery or system status of energy storage devices in hibernation mode, existing technologies require waking the device at regular intervals to allow it to perform self-tests. If the device is not triggered to enter normal operation during this wake-up period, it re-enters hibernation. The inventors discovered that this hibernation period is a fixed value, for example, 6 hours. After entering hibernation mode, the energy storage device needs to wake up every 6 hours to perform self-tests.

[0033] When the sleep time is a fixed, small value, the energy storage device enters the wake-up state more frequently. The power consumption required for the energy storage device to perform self-test operations in the wake-up state is not low. In the sleep mode, the energy storage device needs to consume a lot of power to complete the self-test operations.

[0034] When the hibernation period is a fixed, large value, although the energy storage device does not need to frequently enter and exit the wake-up state, it is difficult for the device to detect abnormal factors in hibernation mode, resulting in the inability to take timely safety measures. For example, if the hibernation period is 48 hours, the energy storage device needs to wait 48 hours before entering the wake-up state to perform self-test operations. However, if the energy storage device's power is completely exhausted within this 48-hour period, causing it to completely shut down, it will be unable to be remotely woken up later. Alternatively, if the temperature of the energy storage device rises during this 48-hour period, but the device is not woken up and cannot report the high-temperature information to the cloud, it may be damaged by the high temperature.

[0035] The inventors also discovered that in order to ensure that the remote wake-up and self-test functions of the energy storage device can be executed normally in the sleep mode, the battery of the energy storage device needs to provide power to the remote wake-up and self-test circuits in the sleep mode, thereby increasing the power consumption of the energy storage device in the sleep mode and causing the battery of the energy storage device to be over-discharged.

[0036] Energy storage devices primarily use the Coulomb integral method to update the State of Charge (SOC) value. The Coulomb integral formula is: Q represents the amount of electricity that the battery of the energy storage device outputs to the load. This refers to the current flowing through the battery of the energy storage device. The output current of the energy storage device in sleep mode is usually in the microamp level, which is easily ignored. This causes a deviation between the SOC value calculated by the energy storage device and the actual SOC value, which in turn makes it impossible for the energy storage device to derive accurate charging or discharging time based on the distorted SOC value.

[0037] The inventors also discovered that after an energy storage device enters an abnormal state, it is usually forced to shut down directly. Users do not receive any warning information in advance that the energy storage device is about to enter an abnormal state, which leads to a decrease in the availability of the energy storage device.

[0038] Therefore, the embodiments of this application can adaptively adjust the sleep time based on the battery state of the energy storage device in sleep mode, so that the sleep time changes with the battery state and is no longer a fixed value. This improves the situation of invalid wake-ups and easy missed detections. Furthermore, it can calculate sleep power consumption and wake-up power consumption, incorporating these into the SOC value correction process to compensate for the power consumption deviation accumulated in sleep mode, thereby obtaining a more accurate SOC value and improving the accuracy of SOC value updates. In addition, the embodiments of this application can also implement a layered early warning method, avoiding the poor system availability problem caused by a "one-size-fits-all" monitoring method and improving the intelligence of safety early warning.

[0039] The following embodiments of this application provide an energy storage device, which can be a portable independent power supply device or a stationary power supply device. Please refer to... Figure 1 The energy storage device 100 includes a battery 11, a BMS (Battery Management System) controller 12, an auxiliary power supply circuit 13, an independent power supply circuit 14, a communication circuit 15, a voltage acquisition circuit 16, and a temperature acquisition circuit 17.

[0040] Battery 11 is used to provide power, wherein battery 11 includes multiple individual cells connected in series, the number of individual cells being customized by the designer according to business needs.

[0041] The BMS controller 12 is electrically connected to the battery 11 and is used to manage and analyze various tasks of the energy storage device 100, and can control the energy storage device 100 to enter a sleep mode. In some embodiments, when the BMS controller 12 receives a remote sleep command, the BMS controller 12 controls the energy storage device 100 to enter a sleep mode. In some embodiments, when the BMS controller 12 receives a local sleep command, the BMS controller 12 controls the energy storage device 100 to enter a sleep mode. The local sleep command includes a command generated when the sleep button of the energy storage device is pressed or a sleep command sent from a local host computer to the BMS controller 12. In some embodiments, when the BMS controller 12 detects that a target task has been completed, the BMS controller 12 controls the energy storage device 100 to enter a sleep mode. The target task includes a charging task, a discharging task, or an equalization task. In some embodiments, when the BMS controller 12 detects that the SOC value of the battery 11 is less than a preset sleep threshold, the BMS controller 12 controls the energy storage device 100 to enter a sleep mode.

[0042] The auxiliary power supply circuit 13 is electrically connected to the battery 11 and the BMS controller 12 respectively. Under the control of the BMS controller 12, it converts the power provided by the battery 11 into the corresponding voltage and then transmits the voltage to the external device 18 to drive the external device 18 to work. The external device 18 includes a solar charger or inverter, etc.

[0043] The independent power supply circuit 14 is electrically connected to the battery 11 and the BMS controller 12 respectively, and is used to output power in sleep mode under the control of the BMS controller 12.

[0044] The communication circuit 15 is electrically connected to both the independent power supply circuit 14 and the BMS controller 12, and operates based on the power supplied by the independent power supply circuit 14. The communication circuit 15 includes a fiber optic communication module, a WIFI module, a Bluetooth module, a 6G communication module, a 5G communication module, a 4G communication module, or a 3G communication module, etc.

[0045] Please see Figure 2 The energy storage device 100 is connected to the cloud server 200 via the communication circuit 15.

[0046] When the communication circuit 15 receives a remote sleep command from the cloud server 200, it forwards the command to the BMS controller 12. The BMS controller 12 then controls the energy storage device 100 to enter sleep mode and stops the auxiliary power supply circuit 13 from supplying power to the external device 18. Simultaneously, the BMS controller 12 controls the independent power supply circuit 14 to continue operating, providing current to the communication circuit 15 to ensure it continues to function in sleep mode and supports remote wake-up. The current supplied by the independent power supply circuit 14 to the communication circuit 15 is at the microampere level, meaning it maintains low-power operation of the communication circuit 15.

[0047] Please see Figure 3 The energy storage device 100 is connected to the terminal device 300 via the communication circuit 15. The terminal device 300 includes mobile phones, desktop computers, tablets, smartwatches, etc.

[0048] The terminal device 300 supports the installation of various applications (APPs), including an energy storage APP for controlling the energy storage device 100. Users register as members in the energy storage APP and bind the energy storage device 100 to the APP. Users can open the energy storage APP on the terminal device 300, and the energy storage APP controls the terminal device 300 to establish a communication connection with the energy storage device 100, which may include Bluetooth or WIFI connection.

[0049] After the terminal device 300 establishes a communication connection with the energy storage device 100, the user can perform various operations on the energy storage APP, including power-off, power-on, hibernation, and query operations. The terminal device 300 responds to the user's input hibernation operation through the energy storage APP, generates a hibernation command, and sends the hibernation command to the energy storage device 100, causing the energy storage device 100 to enter hibernation mode based on the hibernation command.

[0050] The voltage acquisition circuit 16 is electrically connected to the battery 11 and the BMS controller 12, respectively, and is used to acquire the voltage of each individual cell in the battery 11 and the current flowing through the battery 11. The voltage acquisition circuit 16 includes an AFE chip (Analog Front End) or a circuit composed of various discrete components with voltage acquisition and current acquisition functions.

[0051] Please see Figure 4The voltage acquisition circuit 16 is an AFE chip, which is electrically connected to each individual battery cell and is used to acquire the voltage of each individual battery cell and the current flowing through the battery 11. The AFE chip is the analog signal acquisition center of the energy storage device, which can convert various analog physical quantities (such as voltage and current) into digital signals.

[0052] Temperature acquisition circuit 17 is located adjacent to battery 11 and electrically connected to BMS controller 12, and is used to acquire the battery temperature of battery 11. Temperature acquisition circuit includes negative temperature coefficient thermistors or positive temperature coefficient thermistors, etc.

[0053] The working principle of energy storage device 100 is as follows:

[0054] When the BMS controller 12 receives a local or remote sleep command, it controls the energy storage device 100 to enter sleep mode. Specifically, the BMS controller 12 controls the auxiliary power supply circuit 13, voltage acquisition circuit 16, and temperature acquisition circuit 17 to stop working, reducing the system power consumption of the energy storage device 100 from the watt level to the milliwatt level, while keeping the independent power supply circuit 14 and communication circuit 15 working so that the communication circuit 15 can support the remote wake-up function.

[0055] In sleep mode, the BMS controller 12 needs to periodically perform safety monitoring operations and SOC value update operations. For example, the BMS controller 12 needs to wake up the AFE chip and temperature acquisition circuit 17 at dynamically adjusted sleep times to re-enter the working state, so that the AFE chip can collect the voltage and temperature of each individual cell and the acquisition circuit 17 can collect the battery temperature of the battery 11. The BMS controller 12 performs safety monitoring operations based on the voltage and temperature of each individual cell. At the same time, the BMS controller 12 also updates the SOC value of the energy storage device 100 in real time.

[0056] When the BMS controller 12 receives a local wake-up command or a remote wake-up command sent by the cloud server 200 or terminal device 300 via the communication circuit 15, the BMS controller 12 controls the energy storage device 100 to enter the normal power-on mode. Specifically, the BMS controller 12 controls the auxiliary power supply circuit 13, voltage acquisition circuit 16, and temperature acquisition circuit 17 to enter the working state, and controls the independent power supply circuit 14 and communication circuit 15 to remain operational.

[0057] In summary, in the energy storage device 100 provided in this application embodiment, each circuit has a clearly defined function. The BMS controller 12 serves as the decision-making core, coordinating the execution of hibernation management, SOC calculation, and safety logic. The auxiliary power supply circuit 13 controls the power supply to the external device 18. The independent power supply circuit 14 and the communication circuit 15 maintain a low-power remote communication link. The energy storage device 100 minimizes standby power consumption and improves the long-term reliability of the battery 11 while ensuring uninterrupted safety monitoring.

[0058] The following embodiments of this application provide a detailed description of the dynamic updating of the SOC value and the safety monitoring of energy storage devices. For specific details, please refer to... Figure 5 The embodiments of this application implement a method for dynamically updating the SOC value through steps S51 to S54, as detailed below:

[0059] Step S51: Based on the battery state of the energy storage device in the previous wake-up state, determine the next sleep time of the energy storage device. The energy storage device includes a sleep mode that alternates between sleep and wake-up states.

[0060] The status modes of energy storage devices include normal operation mode, shutdown mode, and hibernation mode.

[0061] The normal operating mode is the mode in which the energy storage device can function normally. The energy storage device enters the normal operating mode when it receives a local power-on command or a remote power-on command sent by a cloud server or terminal device via a communication circuit. For example, when the energy storage device enters the normal operating mode, it supplies power to the solar charger or inverter through an auxiliary power circuit. Therefore, the energy consumption of the energy storage device is relatively high in the normal operating mode.

[0062] The shutdown mode is a mode in which the energy storage device is completely shut down. The energy storage device enters shutdown mode when it receives a local shutdown command or a remote shutdown command sent by a cloud server or terminal device via the communication circuit. For example, when the energy storage device enters shutdown mode, the BMS controller, auxiliary power supply circuit, independent power supply circuit, communication circuit, voltage acquisition circuit, and temperature acquisition circuit all cease operation.

[0063] Hibernation mode is the standby state of an energy storage device. The device enters hibernation mode when it receives a local hibernation command or a remote hibernation command from a cloud server or terminal device via communication circuitry. In hibernation mode, essential circuits maintain normal operation to enable remote control and safety monitoring functions, while unnecessary circuits cease operation to avoid wasting power. Essential circuits include the BMS controller, independent power supply circuit, and communication circuit; unnecessary circuits include auxiliary power supply circuit, voltage acquisition circuit, and temperature acquisition circuit.

[0064] In order to enable the energy storage device to perform self-testing in hibernation mode, the embodiments of this application can configure the energy storage device to enter a short-term wake-up state in hibernation mode. Therefore, the hibernation mode includes alternating hibernation and wake-up states. The hibernation time of each hibernation state of the energy storage device in hibernation mode can be dynamically adjusted, and the wake-up time of each wake-up state in hibernation mode is a fixed value or a dynamically adjusted value.

[0065] Please see Figure 6a The energy storage device operates in hibernation mode, alternating between hibernation and wake-up states. The time spent in the hibernation state and the time spent in the wake-up state constitute one alternation cycle. The energy storage device includes N alternation cycles in hibernation mode, where the hibernation time in the first alternation cycle is... The hibernation time of the first alternation cycle is The hibernation time in the second alternation cycle is... The wake-up time for the second alternating wake-up cycle is Among them, hibernation time Less than the hibernation time .

[0066] like Figure 6a As shown, the self-check operations performed by the energy storage device in the wake-up state of hibernation mode are all the same. Therefore, the wake-up time corresponding to all alternating wake-up states is a fixed value. The battery status of the energy storage device exhibits different characteristics at different stages of hibernation mode. In some hibernation scenarios, the overall performance is that the hibernation time corresponding to different alternating hibernation states decreases sequentially to expedite the execution of self-check operations, promptly detect anomalies, and prevent risks. For example, as... Figure 6a As shown, sleep time Less than the hibernation time hibernation time Less than the hibernation time And so on.

[0067] In other hibernation scenarios, the overall performance is characterized by irregular variations in hibernation time corresponding to different alternating hibernation states. For examples, please refer to [link to relevant documentation]. Figure 6b hibernation time Less than the hibernation time hibernation time Less than the hibernation time However, after the battery experiences the third alternating wake-up cycle, its battery condition tends to improve, and the sleep time decreases. Greater than the hibernation time hibernation time Greater than the hibernation time hibernation time Greater than the hibernation time .

[0068] The previous wake-up state is the wake-up state most recent to the current time point, which is the time point when the energy storage device is about to enter the sleep state after leaving the wake-up state. For example, the current time point is the critical time point between the wake-up state and the sleep state in the first alternation cycle, and the previous wake-up state is the wake-up state in the first alternation cycle. Alternatively, the current time point is the critical time point between the wake-up state and the sleep state in the second alternation cycle, and the previous wake-up state is the wake-up state in the second alternation cycle. It can be understood that the previous wake-up state can also be the state before the energy storage device enters the sleep mode (i.e., the normal working state). That is, before the energy storage device enters the sleep mode, the energy storage device calculates the next sleep time based on the battery state and sets the sleep time for the sleep state in the first alternation cycle after the energy storage device enters the sleep mode.

[0069] The next sleep time is the time of the next sleep state, which is the sleep state that follows and is adjacent to the previous wake-up state. For example, please refer to... Figure 6a The previous wake-up state is the wake-up state of the first alternation cycle, and the next sleep state is the sleep state of the second alternation cycle. The wake-up state of the first alternation cycle and the sleep state of the second alternation cycle are adjacent. As another example, the previous wake-up state is the wake-up state of the second alternation cycle, and the next sleep state is the sleep state of the third alternation cycle. The wake-up state of the second alternation cycle and the sleep state of the third alternation cycle are adjacent. And so on, without further elaboration.

[0070] Battery status is used to reflect the operating condition of the battery in an energy storage device. Embodiments of this application may describe the battery status in one or more ways. For example, embodiments of this application may describe the battery status using the remaining battery capacity, the voltage of a single cell in the battery, the battery temperature, or a combination of the remaining battery capacity, the voltage of a single cell, and the battery temperature, thereby reflecting the operating condition of the battery in the energy storage device.

[0071] It is understood that the battery state changes over time. When the embodiments of this application are based on the battery state of the energy storage device in the previous wake-up state, the next sleep time determined by the embodiments of this application also changes. Therefore, the next sleep time adapts to the battery state of the energy storage device in the previous wake-up state and is no longer a fixed value. This improves the situation of invalid wake-up and missed detection caused by using a fixed sleep time, which is conducive to reducing power consumption and improving the ability of the energy storage device to prevent abnormal situations in sleep mode.

[0072] Step S52: Determine the sleep power consumption in sleep mode based on the sleep time and sleep current in each sleep mode.

[0073] The quiescent current is the current output by the battery of an energy storage device in its quiescent state. The value of the quiescent current is known in advance and remains constant. In an energy storage device, the circuits that can remain operational in the quiescent state can be known in advance, and the quiescent current controlling these circuits can also be calculated in advance. For example, the current supplied by the battery to the BMS controller, independent power supply circuit, and communication circuit can be calculated in advance. The total current consumed by the BMS controller, independent power supply circuit, and communication circuit in the quiescent state is the quiescent current.

[0074] Sleep power consumption is the total amount of electricity consumed by an energy storage device in sleep mode. Determining sleep power consumption in sleep mode based on the sleep time and sleep current during each sleep period includes the following steps: summing up the sleep times in each sleep period to obtain the total sleep time; multiplying the total sleep time by the sleep current to obtain the sleep power consumption in sleep mode.

[0075] For example, in this application embodiment, the total sleep time is calculated according to Formula 1, as shown below:

[0076] Formula 1

[0077] Where N represents the total number of times the energy storage device goes through a wake-up state or a sleep state before leaving the sleep mode. Total sleep time Let be the sleep time for the i-th sleep state.

[0078] The embodiments of this application calculate the sleep power consumption in sleep mode according to formula two, as shown below:

[0079] Formula 2

[0080] in, For sleep mode power consumption, This is the dormant current.

[0081] Step S53: Determine the wake-up power consumption in sleep mode based on the wake-up time and wake-up current in each wake-up state.

[0082] After each sleep cycle in hibernation mode, the energy storage device automatically enters the wake-up state. Specifically, when the energy storage device enters the hibernation state of the i-th alternation cycle, the timer of the BMS controller starts to execute timing operations. When the BMS controller detects that the timer's timing duration equals the sleep time of the i-th alternation cycle, the BMS controller enters the wake-up state, controlling the voltage acquisition circuit to collect the voltage of the individual battery cells and controlling the temperature acquisition circuit to collect the battery temperature.

[0083] The wake-up time is the time it takes for an energy storage device to wake up from its hibernation mode. In some embodiments, the wake-up time is a fixed value that can be customized by the designer based on the specific features of the energy storage device. In other embodiments, the wake-up time is a dynamically adjustable value. The energy storage device can dynamically adjust its wake-up time based on its wake-up update information. For example, the wake-up update information may include the device's usage time or aging level. The longer the usage time or the higher the aging level, the longer the wake-up time. During this longer wake-up time, the energy storage device performs multiple self-check operations, thereby timely and reliably monitoring whether aging energy storage devices experience abnormalities in hibernation mode. Conversely, the shorter the usage time or the lower the aging level, the shorter the wake-up time, allowing the energy storage device to quickly complete its self-check operations within a shorter wake-up time.

[0084] The wake-up power consumption in sleep mode is determined based on the wake-up time and wake-up current in each wake-up state, including the following steps: obtain the total wake-up time, multiply the total wake-up time by the wake-up current, and obtain the wake-up power consumption in sleep mode.

[0085] Obtaining the total wake-up time includes the following steps: determining the total number of times the energy storage device experiences a wake-up state before leaving the hibernation mode, multiplying the total number of times by the preset wake-up time to obtain the total wake-up time.

[0086] For example, in this embodiment of the application, the total wake-up time is calculated according to Formula 3, as shown below:

[0087] Formula 3

[0088] in, Total wake-up time, To wake up time.

[0089] This application embodiment calculates the wake-up power consumption in sleep mode according to formula four, as shown below:

[0090] Formula 4

[0091] in, To reduce power consumption during wake-up, To wake up the current.

[0092] Step S54: Based on the sleep power consumption and wake-up power consumption in the current sleep mode, dynamically correct the SOC value at the end of the current sleep mode.

[0093] Although the power consumption during sleep and wake-up is relatively small, it can accumulate into a large total power consumption over a long period. This application incorporates the sleep and wake-up power consumption of the current sleep mode into the SOC value correction process, compensating for the accumulated power consumption deviation during sleep mode. This ensures that the corrected SOC value accurately reflects the energy storage device's power status, improving the accuracy of SOC value updates.

[0094] In this embodiment of the application, step S54: dynamically correcting the SOC value at the end of the current sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode, is specifically implemented by the following steps S541 to S543.

[0095] Step S541: Based on the sleep power consumption and wake-up power consumption in the current sleep mode, determine the total power consumption of the energy storage device in sleep mode.

[0096] In this embodiment, the sleep power consumption and wake-up power consumption in the current sleep mode are added together to obtain the total power consumption of the energy storage device in sleep mode, as shown in Equation 5:

[0097] Formula 5

[0098] in, This represents the total power consumption of the energy storage device in sleep mode.

[0099] Step S542: Based on the total power consumption and the rated total capacity of the battery in the current sleep mode, determine the power consumption value in the current sleep mode.

[0100] In this embodiment of the application, the rated total capacity of the battery is obtained, and the total power consumption is divided by the rated total capacity to obtain the first SOC value, as shown in Equation 6:

[0101] Formula Six

[0102] in, This represents the capacity consumption value during the current sleep mode. This refers to the rated total capacity of the energy storage equipment.

[0103] Step S543: Based on the remaining capacity value of the battery at the moment of entering the current sleep mode and the depleted capacity value in the current sleep mode, determine the remaining capacity value of the battery at the end of the current sleep mode.

[0104] In this embodiment, the remaining capacity value updated in real time is stored locally on the energy storage device. When the energy storage device enters the current sleep mode, this embodiment retrieves the remaining battery capacity value at the current sleep mode time from the local storage device.

[0105] In this embodiment, the remaining battery capacity at the current sleep mode time is subtracted from the capacity loss during the current sleep mode to obtain the remaining battery capacity at the end of the current sleep mode, as shown in Equation 7:

[0106] Formula 7

[0107] in, This represents the remaining battery capacity at the end of the current sleep mode. This represents the remaining battery capacity at the current time of the hibernation mode.

[0108] To illustrate the SOC dynamic correction process in the embodiments of this application in detail, the embodiments of this application are described in detail with reference to the following examples, as follows:

[0109] Rated total capacity of energy storage devices It has a capacity of 10000mAh. This is the capacity of the energy storage device when it enters hibernation mode. It is 50%. Dormant current. The current is 500uA (i.e., 0.0005A). The total number of cycles N is 120, and the total sleep time is... 2400h. Wake-up current. It is 20mA. The wake-up time is 2 seconds.

[0110] Based on equation two, we have: sleep power consumption =0.0005A×2400h=1.2Ah (i.e. 1200mAh).

[0111] Based on equation four, we have: wake-up power consumption =0.02A×2 / 3600h * 120= 0.000667Ah (i.e. 0.667mAh).

[0112] Based on equation six, we have: the power consumption value in the current sleep mode. .

[0113] The remaining battery capacity at the moment of the last sleep mode. Based on Equation 7, we have: the remaining battery capacity at the end of the current sleep mode. .

[0114] The embodiments of this application adopt the above method to effectively compensate for the SOC drift caused by the self-discharge of the energy storage device in the dormant mode, correct the SOC estimation error after long-term dormancy, and significantly improve the prediction accuracy of the SOC value.

[0115] As mentioned above, the sleep time of each sleep state in the energy storage device under sleep mode can adaptively change according to the battery state. The embodiments of this application can dynamically determine the sleep time of each sleep state. Specifically, step S51 of the aforementioned embodiments of this application: determining the next sleep time of the energy storage device based on the battery state of the energy storage device in the previous wake-up state, is achieved through the following steps S511 to S513.

[0116] Step S511: Obtain the state description data of the previous wake-up state. The state description data is used to describe the multi-dimensional state of the battery of the energy storage device in the previous wake-up state.

[0117] In some embodiments, the state description data is a parameter describing the battery state of the energy storage device in the previous wake-up state from one dimension. The state description data is a type of state description parameter, which is a parameter describing the battery state of the energy storage device in the previous wake-up state from one dimension. For example, the state description parameter is any parameter among the SOC value of the previous wake-up state, the minimum single-cell voltage of the previous wake-up state, and the battery temperature of the previous wake-up state.

[0118] In some embodiments, the state description data consists of parameters that describe the battery state of the energy storage device in the previous wake-up state from multiple dimensions. The state description data includes multiple types of state description parameters, which are any two or three of the SOC value of the previous wake-up state, the minimum single cell voltage of the previous wake-up state, and the battery temperature of the previous wake-up state.

[0119] When the status description data includes the SOC value of the previous wake-up state, obtaining the status description data of the previous wake-up state includes the following steps: obtaining the log file of the previous wake-up state, the log file including the latest SOC value of the energy storage device, parsing the latest SOC value from the log file, and setting the latest SOC value as the SOC value of the previous wake-up state.

[0120] When the status description data includes the minimum single-cell voltage of the previous wake-up state, obtaining the status description data of the previous wake-up state includes the following steps: obtaining the log file of the previous wake-up state, the log file includes the single-cell voltage of each single cell in the energy storage device in the previous wake-up state, parsing the single-cell voltage of each single cell in the previous wake-up state from the log file, and finding the minimum single-cell voltage from the single-cell voltage of each single cell in the previous wake-up state.

[0121] When the status description data includes the battery temperature of the previous wake-up state, obtaining the status description data of the previous wake-up state includes the following steps: obtaining the log file of the previous wake-up state, the log file including the latest battery temperature of the energy storage device, parsing the latest battery temperature from the log file, and setting the latest battery temperature as the battery temperature of the previous wake-up state.

[0122] Based on state description data, this application embodiment can determine the next hibernation time of an energy storage device using various methods. This application embodiment can utilize deep modeling or functional methods to determine the next hibernation time of an energy storage device.

[0123] ①Depth model approach.

[0124] The energy storage device is equipped with a pre-trained time prediction model. The state description data includes multiple state description parameters. In this embodiment, the multiple state description parameters are input into the time prediction model so that the time prediction model outputs the next sleep time.

[0125] Inputting multiple state description parameters into the time prediction model includes the following steps: normalizing each type of state description parameter to obtain normalized state description parameters; determining state description features based on the normalized state description parameters; concatenating the state description features corresponding to each type of state description parameter to obtain concatenated features; and inputting the concatenated features into the time prediction model to obtain the next sleep time.

[0126] This application embodiment can collect various types of training sample data regarding hibernation mode and use a neural network algorithm to train a time prediction model. Please refer to... Figure 7The time prediction model 70 includes an input layer 71, a processing layer 72, and an output layer 73. The input layer 71 receives state description features corresponding to various state description parameters and concatenates these features to obtain concatenated features. The processing layer 72 can be a fully connected layer used to process and analyze the concatenated features. The output layer 73 outputs the next sleep time.

[0127] ② Function method.

[0128] The status description data is a status description parameter. Determining the next hibernation time of the energy storage device based on the status description data includes the following steps: inputting the status description parameter into a preset time prediction function to obtain the next hibernation time of the energy storage device.

[0129] The time prediction function is defined by the designer based on engineering experience. This function can be linear, nonlinear, exponential, or stepwise, etc. For example, a linear function can be defined as follows: In this context, k and b are determined in advance by the designer, and the independent variable x is a state description parameter.

[0130] In some embodiments, the time prediction function includes a first prediction function, which is a function of the SOC value of the previous wake-up state as the independent variable and the next sleep time as the dependent variable. Inputting the state description parameters into the preset time prediction function to obtain the next sleep time of the energy storage device includes the following steps: substituting the SOC value of the previous wake-up state into the first prediction function to obtain the next sleep time of the energy storage device.

[0131] For example, the expression for the first prediction function is: ,in, and Determined in advance by the designer, independent variables The SOC value of the previous wake-up state is the dependent variable. This is the time for the next hibernation period.

[0132] In some embodiments, the time prediction function includes a second prediction function, which is a function of the minimum cell voltage of the previous wake-up state as the independent variable and the next sleep time as the dependent variable. Inputting the state description parameters into the preset time prediction function to obtain the next sleep time of the energy storage device includes the following steps: substituting the SOC value of the previous wake-up state into the second prediction function to obtain the next sleep time of the energy storage device.

[0133] For example, the expression for the second prediction function is: ,in, and Determined in advance by the designer, independent variables The minimum single-cell voltage of the previous wake-up state, the dependent variable. This is the time for the next hibernation period.

[0134] In some embodiments, the time prediction function includes a third prediction function, which is a function of the battery temperature of the previous wake-up state as the independent variable and the next sleep time as the dependent variable. Inputting the state description parameters into the preset time prediction function to obtain the next sleep time of the energy storage device includes the following steps: substituting the SOC value of the previous wake-up state into the third prediction function to obtain the next sleep time of the energy storage device.

[0135] For example, the expression for the third prediction function is: ,in, and Determined in advance by the designer, independent variables The battery temperature during the previous wake-up state is the dependent variable. This is the time for the next hibernation period.

[0136] Step S512: Obtain the baseline sleep time.

[0137] The reference sleep time serves as a benchmark for determining the next sleep time. In this application embodiment, the next sleep time is obtained by fusing state description data based on the reference sleep time. In some embodiments, the reference sleep time is customized by the designer based on engineering experience. For example, the reference sleep time may be 20 hours or 18 hours. In other embodiments, the reference sleep time can be determined by following the rated total capacity and sleep current of the energy storage device's battery. Specifically, this application embodiment determines the reference sleep time based on the rated total capacity and sleep current of the battery. For example, this application embodiment divides the rated total capacity by the sleep current to obtain the reference sleep time.

[0138] Step S513: Determine the next sleep time of the energy storage device based on the status description data and the baseline sleep time.

[0139] The status description data includes multiple types of status description parameters. In some embodiments, determining the next sleep time of the energy storage device based on the status description data and the baseline sleep time includes the following steps: weighting the baseline sleep time based on multiple types of status description parameters to obtain the next sleep time of the energy storage device.

[0140] Status description data can reflect the battery status of energy storage devices from one or more dimensions. By adjusting the baseline sleep time using status description data, the obtained next sleep time can comprehensively reflect the battery status of the energy storage device in each dimension. This allows the next sleep time to more accurately adapt to changes in battery status, avoiding excessive power consumption due to too short a sleep time or missed detection due to too long a sleep time. This balances power consumption and missed detection in the sleep mode of the energy storage device, improving its low power consumption capability and risk prevention capability in sleep mode.

[0141] In other embodiments, determining the next sleep time of the energy storage device based on state description data and a reference sleep time includes the following steps: determining a set of battery parameters in the current wake-up state based on state description data from the previous wake-up state, the set of battery parameters including multiple target adjustment coefficients representing multiple performance parameters of the battery for adjusting the sleep time, and adjusting the reference sleep time through the set of battery parameters to obtain the next sleep time of the energy storage device.

[0142] This application embodiment converts multi-dimensional state description data into a set of battery parameters with the same dimension that can be quantified and engineered. By using the multi-dimensional set of battery parameters to jointly adjust the baseline sleep time, the obtained next sleep time can comprehensively reflect the battery status of the energy storage device in each dimension, so that the next sleep time closely follows the battery status and adapts more accurately.

[0143] Determining the battery parameter set for the current wake-up state based on the state description data from the previous wake-up state includes the following steps: determining the adjustment coefficient corresponding to the state description parameter as the target adjustment coefficient, the target adjustment coefficient being positively correlated with the sleep time, and combining the target adjustment coefficients corresponding to all state description parameters to obtain the battery parameter set.

[0144] The state description data includes the battery's remaining capacity, voltage, and temperature in the previous wake-up state. The battery parameter set includes a first target adjustment coefficient, a second target adjustment coefficient, and a third target adjustment coefficient. Determining the adjustment coefficient corresponding to the state description parameters as the target adjustment coefficient includes the following steps: determining the first target adjustment coefficient related to capacity based on the battery's remaining capacity in the previous wake-up state; determining the second target adjustment coefficient related to voltage based on the battery's voltage in the previous wake-up state; and determining the third target adjustment coefficient related to battery temperature based on the battery temperature in the previous wake-up state.

[0145] In this application embodiment, a clear mapping rule is configured for each state description parameter. The corresponding target adjustment coefficient can be determined through both the state description parameter and the mapping rule. The multi-dimensional state description data is fully quantified and standardized to obtain a clearer and more accurate set of battery parameters, which is beneficial for obtaining an accurate and reliable next sleep time.

[0146] Determining the adjustment coefficient corresponding to the state description parameter as the target adjustment coefficient includes the following steps: obtaining a target adjustment coefficient table, which includes multiple parameter ranges and the adjustment coefficient corresponding to each parameter range; traversing the target adjustment coefficient table to find the parameter range corresponding to the state description parameter, wherein the parameter range corresponding to the state description parameter is the target parameter range; and determining the adjustment coefficient corresponding to the target parameter range as the target adjustment coefficient.

[0147] In some embodiments, the target adjustment coefficient table is a table that records multiple parameter ranges and the adjustment coefficients corresponding to each parameter range. For example, the target adjustment coefficient table is shown in Table 1:

[0148] Table 1

[0149]

[0150] As shown in Table 1, this embodiment retrieves the target adjustment coefficient table locally from the energy storage device, and iterates through the target adjustment coefficient table to find the target parameter range corresponding to the state description parameters and the target adjustment coefficient corresponding to the target parameter range. For example, if the battery's remaining capacity (i.e., SOC value) in the previous wake-up state was 90%, the target adjustment coefficient was 2.0. Another example: if the battery's voltage (i.e., minimum single-cell voltage) in the previous wake-up state was 3.3V, the target adjustment coefficient was 1.0. Yet another example: if the battery temperature in the previous wake-up state was 40℃, the target adjustment coefficient was 1.5.

[0151] As shown in Table 1, within the parameter range and adjustment coefficient corresponding to the SOC value, the parameter range and adjustment coefficient are directly proportional; that is, the larger the parameter range, the larger the adjustment coefficient. When the SOC value is within the parameter range (80%, 1), it indicates that the energy storage device has sufficient power and does not need to be frequently woken up to perform self-test operations. Therefore, in this case, the sleep time needs to be extended, and the target adjustment coefficient should be set to 2.0.

[0152] When the SOC value is within the parameter range [20%, 80%], it indicates that the energy storage device has sufficient power. It does not need to wake up frequently but maintain a moderate level of wake-up. This avoids missed detections due to excessively long sleep periods, and also avoids power waste caused by frequent self-test operations due to excessively short sleep periods. Therefore, compared to the first scenario, this scenario can moderately extend the sleep time and set the target adjustment coefficient to 1.0.

[0153] When the SOC value is in the parameter range [0, 20%), it indicates that the energy storage device has low power and the battery is close to the end of discharge. The battery voltage will drop sharply. In order to prevent the battery from over-discharging, it is necessary to shorten the sleep time to increase the number of times the energy storage device is woken up, increase the execution frequency of self-test operation, and improve the risk prevention capability. Compared with the second case, this case can shorten the sleep time and set the target adjustment coefficient to 0.1.

[0154] As shown in Table 1, the parameter range and adjustment coefficient are directly proportional within the parameter range corresponding to the minimum single-cell voltage. When the minimum single-cell voltage is >3.5V, it indicates that the energy storage device has sufficient power and does not need to be frequently woken up to perform self-test operations. Therefore, in this case, the sleep time needs to be extended, and the target adjustment coefficient should be set to 1.5.

[0155] When the minimum single-cell voltage is within the parameter range [3.2V, 3.5V], it indicates that the energy storage device has sufficient power. There is no need for frequent but moderate wake-up. This avoids missed detections due to excessively long sleep periods, and also avoids power waste caused by frequent self-test operations due to excessively short sleep periods. Therefore, compared to the first scenario, this scenario can moderately extend the sleep time and set the target adjustment coefficient to 1.0.

[0156] When the minimum single-cell voltage is within the parameter range [0, 3.2), it indicates that the energy storage device has low power and the battery is close to the end of discharge. The battery voltage will drop sharply. In order to prevent the battery from over-discharging, it is necessary to shorten the sleep time to increase the number of times the energy storage device is woken up, increase the execution frequency of self-test operation, and improve the risk prevention capability. Compared with the second case, this case can shorten the sleep time and set the target adjustment coefficient to 0.2.

[0157] As shown in Table 1, among the parameter ranges and adjustment coefficients corresponding to battery temperature, when the battery temperature is within the parameter range [20℃, 30℃], [20℃, 30℃] is a suitable temperature range for battery storage, and it does not need to be frequently woken up to perform self-test operations. Therefore, in this case, it is necessary to extend the sleep time and set the target adjustment coefficient to 1.5.

[0158] When the battery temperature is within the parameter range (30℃, 50℃) or [0, 20℃), although the battery is not within the optimal temperature range, the temperature range of [0, 20℃) or (30℃, 50℃) does not cause excessive damage to the battery. Frequent but moderate wake-up is unnecessary. This avoids missed detections due to excessively long sleep periods, and also avoids power waste caused by frequent self-test operations due to excessively short sleep periods. Therefore, compared to the first scenario, this scenario can moderately extend the sleep time, and the target adjustment coefficient can be set to 1.0.

[0159] When the battery temperature is >50℃ or <0℃, the battery of the energy storage device is in a high-temperature or low-temperature state, which is therefore a relatively dangerous situation. In order to prevent abnormalities, this embodiment of the application needs to shorten the sleep time to increase the number of times the energy storage device is woken up, increase the execution frequency of self-test operations, and improve the risk prevention capability. Compared with the second case, this case can shorten the sleep time and set the target adjustment coefficient to 0.5.

[0160] As shown in Table 1, when the SOC value is in the parameter range [0, 20%), the minimum single-cell voltage is in the parameter range [0, 3.2), and the battery temperature is in the parameter range (30℃, 50℃), then the battery parameter set is (0.1, 0.2, 1.0). Similarly, when the SOC value is in the parameter range [20%, 80%], the minimum single-cell voltage is in the parameter range [3.2V, 3.5V], and the battery temperature is in the parameter range (30℃, 50℃), then the battery parameter set is (1.0, 1.0, 1.0).

[0161] In other embodiments, the target adjustment coefficient table includes three different types of tables recording multiple parameter ranges and the corresponding adjustment coefficients for each parameter range. Specifically, the target adjustment coefficient table includes a first coefficient table, a second coefficient table, and a third coefficient table. The first coefficient table records the parameter ranges corresponding to the SOC value and the corresponding adjustment coefficients for each parameter range. The second coefficient table records the parameter ranges corresponding to the minimum cell voltage and the corresponding adjustment coefficients for each parameter range. The third coefficient table records the parameter ranges corresponding to the battery temperature and the corresponding adjustment coefficients for each parameter range.

[0162] In some embodiments, traversing the target adjustment coefficient table to find the parameter range corresponding to the state description parameter includes the following steps: in response to the state description parameter being the SOC value of the previous wake-up state, obtaining a first coefficient table, and traversing the first coefficient table to find the parameter range corresponding to the SOC value of the previous wake-up state.

[0163] For example, the first coefficient table is shown in Table 2:

[0164] Table 2

[0165]

[0166] As shown in Table 2, when the SOC value of the current wake-up state is 10%, the target adjustment coefficient is 0.1.

[0167] In some embodiments, traversing the parameter range corresponding to the state description parameter in the target adjustment coefficient table includes the following steps: in response to the state description parameter being the minimum single-cell voltage of the previous wake-up state, obtaining a second coefficient table, and traversing the parameter range corresponding to the minimum single-cell voltage of the previous wake-up state in the second coefficient table.

[0168] For example, the second coefficient table is shown in Table 3:

[0169] Table 3

[0170]

[0171] As shown in Table 3, when the minimum single-cell voltage is 3.3V, the target regulation coefficient is 1.0.

[0172] In some embodiments, traversing the target adjustment coefficient table to find the parameter range corresponding to the state description parameter includes the following steps: in response to the state description parameter being the battery temperature of the previous wake-up state, obtaining a third coefficient table, and traversing the third coefficient table to find the parameter range corresponding to the battery temperature of the previous wake-up state.

[0173] For example, the third coefficient table is shown in Table 4:

[0174] Table 4

[0175]

[0176] As shown in Table 4, when the battery temperature is 40℃, the target adjustment coefficient is 1.0.

[0177] The battery parameter set includes multiple target adjustment coefficients. By adjusting the baseline sleep time using the battery parameter set, the next sleep time of the energy storage device can be obtained. This includes the fact that multiple target adjustment coefficients and the baseline sleep time are all positively correlated with the next sleep time.

[0178] This application embodiment multiplies multiple target adjustment coefficients by a baseline sleep time to obtain the next sleep time of the energy storage device. Specifically, this application embodiment calculates the next sleep time of the energy storage device according to formula eight, as shown below:

[0179] Formula 8

[0180] in, Let be the sleep time of the sleep state in the i-th alternation cycle. Based on the base sleep time, The first target adjustment coefficient is the SOC value corresponding to the wake-up state of the (i-1)th alternation cycle (i.e., the previous wake-up state, or the sleep state that will enter the i-th alternation cycle). The second target adjustment coefficient is the minimum single-unit voltage corresponding to the wake-up state in the (i-1)th alternation cycle. The third target adjustment coefficient is the battery temperature corresponding to the wake-up state in the (i-1)th alternation cycle.

[0181] For example, when the baseline sleep time is 20 hours, the remaining capacity of the battery in the previous wake-up state is 85%, the minimum single-cell voltage is 3.6V, the battery temperature is 30℃, and i=12, that is, the battery parameter set is (2.0, 1.5, 1.0), then: the sleep time of the 12th alternation cycle for:

[0182] Hour.

[0183] For another example, when the baseline sleep time is 12 hours, the remaining capacity of the battery in the previous wake-up state is 85%, the minimum single-cell voltage is 3.6V, the battery temperature is 30°C, and i=12, the sleep time of the 12th alternation cycle is... for:

[0184] Hour.

[0185] It is understood that the embodiments of this application adjust the reference sleep time by combining the first target adjustment coefficient corresponding to the SOC value of the previous wake-up state, the second target adjustment coefficient corresponding to the minimum single cell voltage of the previous wake-up state, and the third target adjustment coefficient corresponding to the battery temperature of the previous wake-up state. The obtained next sleep time is comprehensively and adaptively changed according to the power status, minimum single cell voltage status, and battery temperature status of the energy storage device. This avoids the energy storage device from frequently waking up for self-testing, which wastes power consumption. It also avoids the risk caused by missing the check of abnormal conditions due to excessively long sleep time, thereby improving the risk resistance and endurance of the energy storage device in sleep mode.

[0186] This application embodiment obtains the remaining capacity value of the battery at the end of the current hibernation mode, and can perform safety monitoring operations based on the remaining capacity value of the battery at the end of the current hibernation mode, so that the energy storage device can eliminate risks or abnormal situations in a timely manner, and improve the risk resistance and endurance of the energy storage device in hibernation mode.

[0187] In some embodiments, performing a safety monitoring operation based on the remaining battery capacity at the end of the current sleep mode includes the following steps: in response to the remaining battery capacity being less than a first warning value, reducing the baseline sleep time; in response to the remaining battery capacity being less than a second warning value, controlling the energy storage device to enter a shutdown state and / or sending a low battery information to the server, wherein the second warning value is less than the first warning value.

[0188] The first warning value is customized by the designer based on the product situation. For example, the first warning value is the sum of the preset safe SOC value and the target margin. With a target margin of 5% and a first warning value of 10%, the first warning value is 15%.

[0189] The second warning value is customized by the designer based on the product situation. For example, the second warning value is a preset safety SOC value, such as the preset safety SOC value. The first warning value is 10%, and the second warning value is 10%.

[0190] Reducing the baseline sleep time involves the following steps: obtaining a correction factor, which is in the range of values ​​greater than 0 and less than 1; multiplying the correction factor by the baseline sleep time to obtain the corrected baseline sleep time.

[0191] The correction factor is customized by the designer based on engineering experience; for example, the correction factor is 30%. If the baseline sleep time is 20 hours, the corrected baseline sleep time is 20 * 30% = 6 hours. If the quasi-sleep time is 10 hours, the corrected baseline sleep time is 10 * 30% = 3 hours.

[0192] In some embodiments, when the remaining battery capacity at the end of the current sleep mode is less than the first warning value, this application embodiment generates a first warning code (e.g., 0x01), sends the first warning code to a cloud server or terminal device or displays it locally, and reduces the original baseline sleep time. On the one hand, the first warning code alerts the user to the risk that the energy storage device is about to be in an abnormal situation. On the other hand, reducing the original baseline sleep time shortens the sleep time, increases the number of self-checks, and enhances the risk resistance and perception capabilities.

[0193] In some embodiments, when the remaining battery capacity at the end of the current sleep mode is less than the second warning value, this application embodiment generates a second warning code (e.g., 0xFF) and controls the energy storage device to enter a shutdown state, thereby preventing the energy storage device from falling into a more dangerous situation. Alternatively, it controls the energy storage device to send a low battery information to the server to alert the user about the risk that the energy storage device is about to be in an abnormal situation.

[0194] In some embodiments, this application obtains the individual cell voltage difference, which is the voltage difference between any two cells in the energy storage device. In response to the individual cell voltage difference being greater than a preset voltage difference, a battery abnormality information is sent to the server, and / or, in response to the battery temperature being greater than a first temperature threshold, a high temperature alarm information is sent to the server, in response to the battery temperature being less than a second temperature threshold, a low temperature alarm information is sent to the server, and / or, in response to the minimum individual cell voltage being less than a preset voltage threshold, a low power information is sent to the server.

[0195] Please refer to Table 5:

[0196] Table 5

[0197]

[0198] As shown in Table 5 V_Mincell is the minimum single-cell voltage, which is the preset safe SOC value.

[0199] The preset voltage difference, first temperature threshold, second temperature threshold, and preset voltage threshold are customized by the designer based on engineering experience. For example, as shown in Table 5, the preset voltage difference is 50mV, the first temperature threshold is 45℃, the second temperature threshold is -10℃, and the preset voltage threshold is 2.8V.

[0200] When the voltage difference between individual cells is greater than 50mV, this embodiment of the application generates a third warning code (0x02) and controls the energy storage device to send battery abnormal information to the server to indicate that the energy storage device is in an abnormal state.

[0201] When the battery temperature is >45℃ or the battery temperature In this embodiment, a fourth warning code (0x03) is generated, and the energy storage device is controlled to send a high temperature alarm or a low temperature alarm to the server to indicate that the energy storage device is in a high temperature state or a low temperature state.

[0202] When the minimum single-cell voltage is less than 2.8V, this embodiment generates a second warning code (e.g., 0xFF) and controls the energy storage device to enter a shutdown state.

[0203] This application embodiment employs a layered early warning system. When an energy storage device is about to experience an anomaly, it can promptly send warning information to the cloud server or terminal device, allowing users to monitor the energy storage device and take timely countermeasures. When the energy storage device's power level falls below a preset voltage threshold, this application embodiment controls the energy storage device to enter a shutdown state to prevent it from further deteriorating into a serious anomaly.

[0204] In summary, the embodiments of this application realize closed-loop management of "on-demand wake-up, precise monitoring, and proactive protection", which not only significantly reduces standby power consumption, but also ensures that the battery status is always under control, and significantly improves the security and prediction accuracy of long-term system storage.

[0205] As another aspect of this application, this application provides a method for safety monitoring of energy storage devices. Please refer to... Figure 8 The safety monitoring method for energy storage devices includes the following steps:

[0206] Step S51: Based on the battery state of the energy storage device in the previous wake-up state, determine the next sleep time of the energy storage device. The energy storage device includes a sleep mode that alternates between sleep and wake-up states.

[0207] Step S52: Determine the sleep power consumption in sleep mode based on the sleep time and sleep current in each sleep mode.

[0208] Step S53: Determine the wake-up power consumption in sleep mode based on the wake-up time and wake-up current in each wake-up state.

[0209] Step S54: Based on the sleep power consumption and wake-up power consumption in the current sleep mode, dynamically correct the SOC value at the end of the current sleep mode.

[0210] Step S55: Obtain the remaining battery capacity at the end of the current sleep mode.

[0211] Step S56: Perform a safety monitoring operation based on the remaining battery capacity at the end of the current sleep mode.

[0212] This application embodiment can adaptively adjust the sleep time based on the battery state of the energy storage device during sleep mode. This allows the sleep time to change with the battery state, rather than remaining a fixed value, improving the handling of invalid wake-ups and potential missed detections. Furthermore, it can calculate sleep power consumption and wake-up power consumption, incorporating these into the SOC value correction process to compensate for accumulated power consumption deviations during sleep mode, thereby obtaining a more accurate SOC value and improving the accuracy of SOC value updates. In addition, this application embodiment can implement a tiered early warning system, avoiding the poor system availability caused by a "one-size-fits-all" monitoring approach and improving the intelligence of safety early warnings.

[0213] In some embodiments, performing a safety monitoring operation based on the remaining battery capacity at the end of the current sleep mode includes the following steps: in response to the remaining battery capacity being less than a first warning value, reducing the baseline sleep time; in response to the remaining battery capacity being less than a second warning value, controlling the energy storage device to enter a shutdown state and / or sending a low battery information to the server, wherein the second warning value is less than the first warning value.

[0214] It should be noted that in the above embodiments, there is no necessarily a certain order between the steps. Those skilled in the art can understand from the description of the embodiments of this application that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in turn, etc.

[0215] As another aspect of the embodiments of this application, this application provides a device for dynamically updating the SOC value. The device for dynamically updating the SOC value can be a software module, which includes several instructions stored in a memory. A processor can access the memory, call the instructions, and execute them to complete the method for dynamically updating the SOC value described in the various embodiments above.

[0216] In some implementations, the SOC dynamic update device can also be constructed from hardware devices. For example, the SOC dynamic update device can be constructed from one or more chips, which can work together to complete the SOC dynamic update method described in the various implementations above. As another example, the SOC dynamic update device can also be constructed from various logic devices, such as general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), microcontrollers, ARM (Acorn RISC Machine) or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination of these components.

[0217] Please see Figure 9 The SOC value dynamic update device 900 includes a sleep time update module 91, a sleep power consumption determination module 92, a wake-up power consumption determination module 93, and an SOC dynamic correction module 94.

[0218] The sleep time update module 91 is used to determine the next sleep time of the energy storage device based on the battery state of the energy storage device in the previous wake-up state. The energy storage device includes a sleep mode that alternates between a sleep state and the wake-up state. The sleep power consumption determination module 92 is used to determine the sleep power consumption in the sleep mode based on the sleep time in each sleep mode and the sleep current in the sleep state. The wake-up power consumption determination module 93 is used to determine the wake-up power consumption in the sleep mode based on the wake-up time corresponding to each wake-up state and the wake-up current in the wake-up state. The SOC dynamic correction module 94 is used to dynamically correct the SOC value at the end of the current sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode.

[0219] In some embodiments, the sleep time update module 91 is specifically used to: obtain state description data of the previous wake-up state, wherein the state description data is used to describe the multi-dimensional state of the battery of the energy storage device in the previous wake-up state; and determine the next sleep time of the energy storage device based on the state description data and the baseline sleep time.

[0220] In some embodiments, the sleep time update module 91 is further configured to: determine a reference sleep time based on the rated total capacity of the battery and the sleep current.

[0221] In some embodiments, the sleep time update module 91 is further configured to: determine a battery parameter set in the current wake-up state based on the state description data in the previous wake-up state, the battery parameter set including multiple target adjustment coefficients for adjusting the sleep time, representing multiple performance parameters of the battery; and adjust the reference sleep time through the battery parameter set to obtain the next sleep time of the energy storage device.

[0222] In some embodiments, the sleep time update module 91 is further configured to: all of the target adjustment coefficients and the baseline sleep time are positively correlated with the next sleep time.

[0223] In some embodiments, the sleep time update module 91 is further configured to: determine a first target adjustment coefficient related to the capacity based on the remaining capacity value of the battery in the previous wake-up state; determine a second target adjustment coefficient related to the voltage based on the voltage of the battery in the previous wake-up state; and determine a third target adjustment coefficient related to the battery temperature based on the battery temperature in the previous wake-up state.

[0224] In some embodiments, the SOC dynamic correction module 94 is specifically configured to: determine the total power consumption of the energy storage device in the current sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode; determine the depleted capacity value in the current sleep mode based on the total power consumption in the current sleep mode and the rated total capacity of the battery; and determine the remaining capacity value of the battery at the end of the current sleep mode based on the remaining capacity value of the battery at the time of entering the current sleep mode and the depleted capacity value in the current sleep mode.

[0225] As another aspect of this application, this application provides a safety monitoring device for energy storage equipment. Please refer to... Figure 10 The safety monitoring device 97 for energy storage equipment includes a SOC acquisition module 95 and a safety monitoring module 96. The SOC acquisition module 95 is used to acquire the remaining battery capacity value at the end of the current sleep mode obtained by the aforementioned SOC value dynamic update device. The safety monitoring module 96 is used to perform safety monitoring operations based on the remaining battery capacity value at the end of the current sleep mode.

[0226] In some embodiments, the safety monitoring module 96 is specifically configured to: reduce the baseline sleep time in response to the remaining battery capacity value at the end of the current sleep mode being less than a first warning value; control the energy storage device to enter a shutdown state and / or send low battery information to the server in response to the remaining battery capacity value at the end of the current sleep mode being less than a second warning value; wherein the second warning value is less than the first warning value.

[0227] It should be noted that the aforementioned SOC value dynamic update device or energy storage device safety monitoring device can execute the SOC value dynamic update method or energy storage device safety monitoring method provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the embodiments of the SOC value dynamic update device or energy storage device safety monitoring device can be found in the SOC value dynamic update method or energy storage device safety monitoring method provided in the embodiments of this application.

[0228] See Figure 11 , Figure 11 This is a schematic diagram of a BMS controller provided in an embodiment of this application. The BMS controller 12 includes one or more processors 121 and a memory 122. The memory 122 is connected to one or more processors 121, for example, via a bus.

[0229] Processor 121 is configured to support the BMS controller in performing the corresponding functions in the methods described in the above method embodiments. The processor may be a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof. The aforementioned hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0230] Memory 122 is used to store program code, etc. Memory may include volatile memory (VM), such as random access memory (RAM); memory may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); memory may also include combinations of the above types of memory.

[0231] The memory 122 can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the SOC value dynamic update method or the energy storage device safety monitoring method in the embodiments of this application. The processor executes the various functional applications and data processing of the SOC value dynamic update device or the energy storage device safety monitoring device by running the non-volatile software programs, instructions, and modules stored in the memory, thereby realizing the functions of the SOC value dynamic update method or the energy storage device safety monitoring method and the various modules or units of the SOC value dynamic update device or the energy storage device safety monitoring device provided in the above method embodiments.

[0232] The memory 122 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function. The data storage area may store data created by the use of the SOC value dynamic update device or the safety monitoring device of the energy storage device. In some embodiments, the memory may optionally include memory remotely configured relative to the processor, which can be connected to the SOC value dynamic update device or the safety monitoring device of the energy storage device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0233] The one or more modules are stored in the memory. When executed by the one or more processors, they perform the SOC value dynamic update method or the energy storage device safety monitoring method in any of the above method embodiments. For example, they perform the method steps described in the above method embodiments to realize the functions of the modules described in the above device embodiments.

[0234] This application also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a BMS controller, cause the BMS controller to perform the method described in the foregoing embodiments.

[0235] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0236] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A method for dynamically updating SOC values, characterized in that, include: Based on the battery state of the energy storage device in the previous wake-up state, the next sleep time of the energy storage device is determined, and the energy storage device includes a sleep mode that alternates between the sleep state and the wake-up state; Based on the sleep time in the sleep mode and the sleep current in the sleep state, the sleep power consumption in the sleep mode is determined; Based on the wake-up time corresponding to each wake-up state and the wake-up current in each wake-up state, the wake-up power consumption in the sleep mode is determined; Based on the sleep power consumption and wake-up power consumption in the current sleep mode, the SOC value at the end of the current sleep mode is dynamically corrected; The determination of the next sleep time for the energy storage device, based on the battery state of the energy storage device in the previous wake-up state, includes: Obtain the state description data of the previous wake-up state, which is used to describe the multi-dimensional state of the battery of the energy storage device in the previous wake-up state; A reference sleep time is determined based on the battery's rated total capacity and the sleep current; The battery parameter set for the current wake-up state is determined based on the state description data of the previous wake-up state. The battery parameter set includes multiple target adjustment coefficients for adjusting the sleep time, which represent multiple performance parameters of the battery. The next sleep time of the energy storage device is obtained by adjusting the reference sleep time using the battery parameter set.

2. The method according to claim 1, characterized in that, The step of adjusting the reference sleep time using the battery parameter set to obtain the next sleep time of the energy storage device includes: The target adjustment coefficients and the baseline sleep time are all positively correlated with the next sleep time.

3. The method according to claim 1, characterized in that, The step of determining the battery parameter set for the current wake-up state based on the state description data from the previous wake-up state includes: Based on the remaining capacity value of the battery in the previous wake-up state, a first target adjustment coefficient related to the capacity is determined; Based on the battery voltage in the previous wake-up state, a second target adjustment coefficient related to the voltage is determined; Based on the battery temperature of the battery in the previous wake-up state, a third target adjustment coefficient related to the battery temperature is determined.

4. The method according to any one of claims 1 to 3, characterized in that, The dynamic correction of the SOC value at the end of the current sleep mode based on the sleep power consumption and wake-up power consumption in the current sleep mode includes: Based on the sleep power consumption and wake-up power consumption in the current sleep mode, determine the total power consumption of the energy storage device in the sleep mode; Based on the total power consumption and the rated total capacity of the battery in the current sleep mode, determine the capacity loss value in the current sleep mode; Based on the remaining capacity of the battery at the moment of entering the current sleep mode and the depleted capacity during the current sleep mode, the remaining capacity of the battery at the end of the current sleep mode is determined.

5. A safety monitoring method for an energy storage device, characterized in that, include: Obtain the remaining battery capacity value at the end of the current sleep mode, obtained by the SOC value dynamic update method according to any one of claims 1 to 4. A safety monitoring operation is performed based on the remaining battery capacity at the end of the current hibernation mode.

6. The security monitoring method according to claim 5, characterized in that, The safety monitoring operation based on the remaining battery capacity at the end of the current sleep mode includes: In response to the remaining battery capacity being less than a first warning value at the end of the current sleep mode, the baseline sleep time is reduced; In response to the battery's remaining capacity being less than a second warning value at the end of the current sleep mode, the energy storage device is controlled to enter a shutdown state and / or a low battery information is sent to the server, wherein the second warning value is less than the first warning value.

7. A device for dynamically updating SOC values, characterized in that, include: A sleep time update module is used to determine the next sleep time of an energy storage device based on the battery state of the energy storage device in the previous wake-up state. The energy storage device includes a sleep mode that alternates between a sleep state and the wake-up state. Determining the next sleep time based on the battery state of the energy storage device in the previous wake-up state includes: acquiring state description data from the previous wake-up state, the state description data describing the multi-dimensional state of the battery in the previous wake-up state; determining a baseline sleep time based on the battery's rated total capacity and sleep current; determining a battery parameter set for the current wake-up state based on the state description data from the previous wake-up state, the battery parameter set including multiple target adjustment coefficients representing multiple performance parameters of the battery for adjusting the sleep time; and adjusting the baseline sleep time using the battery parameter set to obtain the next sleep time of the energy storage device. A sleep power consumption determination module is used to determine the sleep power consumption in the sleep mode based on the sleep time in the sleep mode and the sleep current in the sleep state; A wake-up power consumption determination module is used to determine the wake-up power consumption in the sleep mode based on the wake-up time corresponding to each wake-up state and the wake-up current in the wake-up state. The SOC dynamic correction module is used to dynamically correct the SOC value at the end of the current sleep mode based on the sleep power consumption and the wake-up power consumption in the current sleep mode.

8. An energy storage device, characterized in that, The device includes a memory and a processor, the memory being connected to the processor, the processor being configured to execute one or more computer programs stored in the memory, and the processor, when executing the one or more computer programs, causing the energy storage device to implement the SOC value dynamic update method as described in any one of claims 1-4 or the energy storage device safety monitoring method as described in claim 5 or 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the SOC value dynamic update method as described in any one of claims 1-4 or the energy storage device safety monitoring method as described in claim 5 or 6.

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