A battery charging control method and device under low power condition, electronic equipment and storage medium

Abstract

The application provides a battery charging control method and device under low power condition, electronic equipment and storage medium, the method comprises the following steps: when detecting that the low power input source is in the effective power supply state, acquiring the reference voltage of the battery and starting the monitoring timing; collecting the real-time voltage and real-time current of the battery, and determining the dynamic shutdown threshold according to the real-time voltage; extracting the current integral feature based on the real-time current, and extracting the voltage trend feature based on the real-time voltage; the current integral feature and the voltage trend feature are fused and judged to obtain a charging state decision result; according to the charging state decision result, the monitoring timing is reset, or the shutdown operation is triggered when the cumulative length of the monitoring timing reaches the dynamic shutdown threshold, which effectively avoids the irreversible over-discharge loss of the battery caused by long time in the micro power consumption working condition, prolongs the service life of the battery.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, and in particular to a battery charging control method, apparatus, device, and storage medium under low power conditions. Background Technology

[0002] With the development of new energy storage technology, green energy sources such as photovoltaics and wind power have been widely used in portable energy storage and off-grid power supply systems. In these application scenarios, due to the uncontrollability of the external environment (such as light intensity and wind speed), the system often faces "low power" conditions with extremely low input power (such as early morning, dusk, cloudy or rainy days, or weak wind environments).

[0003] Currently, in battery charging control strategies, a hard-based judgment method based on a fixed threshold is typically used to prevent over-discharge of the battery. Specifically, the charging control device monitors the input voltage or charging current of the external power source in real time. When the input voltage or current is detected to be lower than a preset fixed threshold, it determines that the battery is in an ineffective charging state and cuts off the charging circuit or enters a sleep mode.

[0004] However, the fixed threshold method is too rigid. If the input voltage fluctuates around the threshold, it can cause the control device to frequently switch between "wake-up" and "shutdown" states, increasing unnecessary system power consumption and affecting the lifespan of electronic components. Furthermore, in low-power environments, the external input source may maintain a certain open-circuit voltage level, causing the charging control system to be continuously woken up or kept on. However, the input power is extremely weak at this time, and the actual charging current flowing into the battery may even be less than the static operating current (i.e., self-discharge) required for the control circuit to maintain its own operation. In this situation, the system appears to be in a "charging state," but essentially the battery is discharging into the control circuit. Prolonged operation in this condition not only fails to replenish energy but also accelerates the depletion of the battery, leading to irreversible over-discharge damage to the battery cells.

[0005] To address the low-power detection problem, additional hardware is typically added. This could include a separate light intensity sensor at the photovoltaic access point to predict charging feasibility, or a high-precision bidirectional power detection circuit to compare the power difference between internal and external circuits. However, these solutions significantly increase costs, circuit board footprint, and hardware complexity, making them difficult to implement in low-cost or miniaturized portable devices. Summary of the Invention

[0006] The purpose of this invention is to provide a battery charging control method, device, electronic device, and storage medium under low power conditions, so as to solve the problems of false charging and battery over-discharge caused by its own static power consumption under low power conditions.

[0007] According to a first aspect of the present invention, a battery charging control method under low power conditions is provided, comprising: when a low power input source is detected to be in an effective power supply state, acquiring a reference voltage of the battery and starting a monitoring timer; Collect the real-time voltage and real-time current of the battery, and determine the dynamic shutdown threshold based on the real-time voltage; Based on the real-time current, current integral features are extracted, and based on the real-time voltage, voltage trend features are extracted. The current integral feature and the voltage trend feature are fused together to determine the charging state decision result; Based on the charging status decision result, control the monitoring timer to reset, or trigger a shutdown operation when the cumulative duration of the monitoring timer reaches the dynamic shutdown threshold.

[0008] In some possible implementations, current integral features are extracted based on the real-time current, including: Obtain the preset loss compensation current and sampling time interval; The sampling is performed continuously multiple times according to the sampling time interval, and the preset loss compensation current is subtracted from the real-time current collected each time to obtain the single net current; The net current for each sampling is multiplied by the sampling time interval to obtain the corresponding net charge for each sampling. The cumulative net charge is obtained by summing up the net charge values ​​obtained from multiple consecutive samplings. The current integral characteristic is determined based on the comparison between the cumulative net charge and the preset charge determination threshold.

[0009] In some possible implementations, the preset charge determination threshold includes a positive determination threshold and a negative determination threshold; Based on the comparison between the cumulative net charge and the preset charge determination threshold, the current integral characteristics are determined, including: If the cumulative net charge is greater than the positive determination threshold, then the current integral feature is determined to represent the charging direction. If the cumulative net charge is less than the negative determination threshold, then the current integral characteristic is determined to represent the discharge direction. If the cumulative net charge is between the negative determination threshold and the positive determination threshold, then the current integral characteristic is determined to be in a balanced state.

[0010] In some possible implementations, voltage trend features are extracted based on the real-time voltage, including: Multiple sets of real-time voltages are continuously acquired within multiple preset sliding time windows, and the trend slope of the multiple sets of real-time voltages within the multiple sliding time windows is determined respectively. The trend score is obtained by weighted summation of the trend slopes corresponding to each sliding time window. The voltage trend characteristics are determined based on the comparison between the trend score and the preset trend threshold.

[0011] In some possible implementations, the plurality of sliding time windows include short-term time windows, medium-term time windows, and long-term time windows; The short-term time window is used to capture instantaneous voltage changes, the medium-term time window is used to filter out voltage noise and short-term fluctuation interference, and the long-term time window is used to extract the steady-state voltage changes of the battery. Furthermore, the weight coefficient corresponding to the long-term time window is greater than the weight coefficient corresponding to the medium-term time window, and the weight coefficient corresponding to the medium-term time window is greater than the weight coefficient corresponding to the short-term time window; the sum of all weight coefficients is 1.

[0012] In some possible implementations, the preset trend threshold includes a charging trend threshold and a discharging trend threshold; Based on the comparison between the trend score and the preset trend threshold, voltage trend characteristics are determined, including: If the trend score is greater than the charging trend threshold, then the voltage trend feature is characterized as a charging trend. If the trend score is less than the discharge trend threshold, then the voltage trend feature is characterized as a discharge trend. If the trend score is between the charging trend threshold and the discharging trend threshold, then the voltage trend characteristic represents a balanced state.

[0013] In some possible implementations, determining the trend slope of multiple sets of real-time voltages within multiple sliding time windows includes: Obtain the latest voltage sample value in each set of real-time voltages, as well as the initial voltage sample value when the sliding time window is established; The difference between the latest voltage sample value and the initial voltage sample value is calculated, and the result is divided by the duration of the sliding time window to obtain the trend slope corresponding to the sliding time window.

[0014] In some possible implementations, the current integral feature and the voltage trend feature are fused to determine the charging state decision result, including: A first evaluation weight and a second evaluation weight are respectively assigned to the current integral feature and the voltage trend feature, wherein the second evaluation weight is greater than the first evaluation weight; According to the first evaluation weight and the second evaluation weight, the current integral feature and the voltage trend feature are weighted and summed to obtain the fusion decision score; The charging state decision result is determined based on the fusion decision score.

[0015] In some possible implementations, determining the state of charge decision result based on the fusion decision score includes: If the fusion decision score is greater than the zero value of the evaluation benchmark, the charging state decision result is determined to be effective charging; If the fusion decision score is not greater than the zero value of the evaluation benchmark, then the charging state decision result is determined to be ineffective charging.

[0016] In some possible implementations, determining the dynamic shutdown threshold based on the real-time voltage includes: A mapping table containing multiple stepped voltage ranges is provided, and each stepped voltage range is assigned a tolerance waiting time. The real-time voltage is matched with the mapping table, and the tolerable waiting time corresponding to the matched stepped voltage range is used as the dynamic shutdown threshold. The lower the step voltage range in which the real-time voltage is located, the shorter the corresponding tolerance waiting time.

[0017] In some possible implementations, after the monitoring timing is started, the method further includes: The lowest single-cell voltage of a single battery cell in the battery is obtained in real time; Determine the difference between the reference voltage and the preset offset voltage; When the minimum single-cell voltage is less than the difference between the reference voltage and the preset offset voltage, a shutdown operation is triggered.

[0018] According to a second aspect of the present invention, a battery charging control device under low power conditions is provided, comprising: The status response module is used to obtain the battery's reference voltage and start the monitoring timing when it detects that the low-power input source is in an effective power supply state; The threshold setting module is used to collect the real-time voltage and real-time current of the battery, and determine the dynamic shutdown threshold based on the real-time voltage. The feature extraction module extracts current integral features based on the real-time current and voltage trend features based on the real-time voltage. The fusion decision module is used to fuse the current integral feature and the voltage trend feature to obtain the charging state decision result; The execution control module is used to control the monitoring timer to reset based on the charging status decision result, or to trigger a shutdown operation when the cumulative duration of the monitoring timer reaches the dynamic shutdown threshold.

[0019] According to a third aspect of the present invention, an electronic device is provided, comprising: an input unit, a memory, at least one processor, and an output interface, wherein the memory stores program instructions executable on the processor, and the processor can execute a battery charging control method under low power conditions by calling the program instructions.

[0020] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements a battery charging control method under low power conditions.

[0021] According to the present invention, by introducing a dual-modal feature extraction and fusion determination mechanism combining current integral characteristics and voltage trend characteristics when a low-power input source is detected to be in an effective power supply state, the problem of frequent system start-stop oscillations caused by the traditional fixed threshold judgment method under critical input power is solved, and the hidden danger of invalid charging misjudgment caused by the static power consumption of the system is effectively eliminated. Furthermore, by combining the current physical characteristics characterizing the energy surplus / deficit of the circuit with the voltage time-domain characteristics characterizing the electrochemical response of the battery cell, the accuracy of energy flow determination under weak current conditions is improved through cross-validation. Simultaneously, in conjunction with a mechanism based on real-time voltage dynamic adjustment of the shutdown threshold, the control system can achieve a dynamic balance between maintaining weak energy absorption and preventing deep battery discharge, thereby effectively avoiding irreversible over-discharge losses caused by the battery being in a low-power-consumption condition for a long time, and extending the battery's service life.

[0022] By introducing a preset loss compensation current in the current feature extraction, the static power consumption of the control circuit itself and the cumulative error caused by sensor zero-point drift are effectively offset. In the voltage feature extraction, a multi-scale sliding time window mechanism is introduced and differentiated weights are configured, which takes into account the system's response sensitivity to short-term effective charging signals and its ability to smooth and filter long-term polarization rebound and high-frequency noise, which is in line with the slow voltage change characteristics of the battery under low charge state. By configuring the evaluation weight of voltage trend to be greater than the evaluation weight of current integral, the decision deviation caused by long-term drift of coulomb measurement under low current conditions is suppressed. In addition, at the control execution end, the tolerance waiting time is dynamically reduced in the low charge state through the mapping table mechanism, and a multi-level closed-loop protection strategy is constructed based on the safety judgment of the lowest single-cell voltage, the reference voltage, and the preset offset voltage. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating the steps of a battery charging control method under low power conditions according to an embodiment of the present invention. Figure 2 This is a schematic flowchart illustrating the steps of the protection process after the monitoring timer is activated, according to an embodiment of the present invention. Figure 3 This is a flowchart illustrating the steps of determining the dynamic shutdown threshold based on real-time voltage according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the steps for extracting current integral features based on real-time current according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the steps for extracting voltage trend features based on real-time voltage according to an embodiment of the present invention; Figure 6 A flowchart illustrating the steps for determining the trend slope of multiple sets of real-time voltages within multiple sliding time windows according to an embodiment of the present invention; Figure 7 This is a flowchart illustrating the steps of fusing current integral features and voltage trend features to obtain a charging state decision result according to an embodiment of the present invention. Figure 8 This is a detailed execution flow diagram of a battery charging control method under low power conditions according to an embodiment of the present invention; Figure 9 This is a schematic diagram of a battery charging control device under low power conditions according to an embodiment of the present invention; Figure 10 This is a block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0026] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0027] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0028] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0029] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0030] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0031] The optional embodiments of this application are described in detail below with reference to the accompanying drawings.

[0032] Figure 1 A battery charging control method under low power conditions is shown, including the following steps S10 to S50.

[0033] Step S10: When the low power input source is detected to be in an effective power supply state, the reference voltage of the battery is obtained and the monitoring timing is started; A low-power input source refers to an external power supply whose output power is extremely low or unstable due to external environmental factors. Examples include photovoltaic panels in low-light conditions such as early morning, dusk, or cloudy / rainy days, or miniature wind turbines in low-wind conditions. An effective power supply state means that the output parameters (such as open-circuit voltage) of the low-power input source have reached the preset minimum hardware threshold for waking up the charging control device or connecting the charging circuit. It is important to note that under low-power conditions, reaching an effective power supply state only means that the external power source has successfully activated the system; it does not mean that the input power at this time is sufficient to overcome the system's own static power consumption (i.e., self-discharge) and to substantially charge the battery.

[0034] The reference voltage refers to the battery terminal voltage measured directly at the initial moment when the system is first woken up by an external input source and monitoring timing begins. This reference voltage will serve as a starting point for subsequent evaluation of the battery's true state of energy (i.e., net charge or net consumption).

[0035] Specifically, due to the extremely weak input energy under low-power conditions, it is prone to falling into a "false charging" state. This means that while the power supply appears to be on, the weak current flowing into the battery is actually offset by the self-discharge of the control circuit, resulting in the battery being in a discharging state. To accurately identify and eliminate this interference, the current battery reference voltage is recorded the instant a low-power input source meets the activation conditions (e.g., the input voltage is greater than the preset wake-up voltage), and a monitoring timer independent of the normal operating logic is simultaneously activated. By activating the monitoring timer, a clear and continuous observation timeline is provided for subsequent voltage trend calculations and current integral feature extraction.

[0036] After monitoring and timing are enabled, a hardware-level protection process is also included, such as... Figure 2 As shown, it includes the following steps: S101, real-time acquisition of the lowest single-cell voltage of a single battery cell; The lowest single-cell voltage refers to the real-time voltage of the cell with the lowest current voltage sample value among multiple series-connected cells in the battery pack.

[0037] S102, determine the difference between the reference voltage and the preset offset voltage; The preset offset voltage is a threshold set based on the battery safety boundary and self-discharge tolerance.

[0038] S103, when the lowest single-cell voltage is less than the difference between the reference voltage and the preset offset voltage, a shutdown operation is triggered; In this embodiment, the preset offset voltage is specifically set to 30mV. It should be noted that the preset offset voltage is an empirical value determined in this embodiment based on a specific battery chemistry system (such as the smooth voltage plateau characteristics of lithium iron phosphate batteries) and the noise floor level of the system's ADC sampling circuit. In practical applications, this value can also be flexibly set to other reasonable values ​​according to different battery types, capacities, and hardware sampling accuracy.

[0039] Specifically, introducing a preset offset voltage can create an immediate safety barrier during the observation period of low-power charging. In practical applications, although an external low-power input source is activated, if the input energy cannot cover the static power consumption of the control circuit, the battery pack will experience a slow voltage drop due to power supply to the outside. Due to the differences in the electrochemical characteristics of the individual cells within the battery, this voltage drop is often uneven.

[0040] To prevent irreversible physical damage to short-circuit cells, the lowest single-cell voltage is continuously and dynamically monitored after obtaining the reference voltage. The determination logic is as follows: the real-time collected lowest single-cell voltage is compared with (reference voltage V). Ref A high-frequency comparison is performed at -30mV. Once the lowest single-cell voltage drops below this calculated value, it is determined that the current operating condition poses an over-discharge threat to the weakest cell. At this point, the remaining monitoring time is ignored, and a forced shutdown command is triggered to cut off the charging and discharging circuit.

[0041] Step S20: Collect the real-time voltage and real-time current of the battery, and determine the dynamic shutdown threshold based on the real-time voltage. Real-time voltage refers to the overall battery terminal voltage or individual cell voltage acquired within the current sampling period; real-time current refers to the physical current flowing through the battery charging / discharging circuit. For broad compatibility with different hardware architectures, real-time current can be acquired through a current sampling resistor (shunt) connected in series in the charging / discharging circuit, or through a Hall effect current sensor for non-contact acquisition. Real-time voltage can be acquired through voltage division sampling via the ADC (analog-to-digital converter) pin built into the main control chip (MCU), or through an external dedicated voltage monitoring chip; specific limitations are not specified here.

[0042] Dynamic shutdown threshold refers to the maximum allowed duration of standby observation. Traditional control strategies typically employ a fixed shutdown delay (e.g., shutting down after a fixed 3-minute wait if no effective charging occurs). However, fixed delays have inherent drawbacks under low-power conditions: when the battery is extremely low (on the verge of over-discharge), a long fixed delay can cause the system to self-discharge and drain the battery; while when the battery is fully charged, a short delay can cause the system to frequently restart during low-power fluctuations.

[0043] By introducing a dynamic shutdown threshold mechanism adapted to the battery's current state of energy (i.e., real-time voltage), different time lengths for the dynamic shutdown threshold can be dynamically assigned based on the acquired real-time voltage through methods such as table lookup, piecewise mapping, or function calculation. Typically, the dynamic shutdown threshold and the real-time voltage exhibit a positive correlation or a stepwise positive correlation. The process of determining the dynamic shutdown threshold based on the real-time voltage is as follows: Figure 3 As shown, it includes the following steps: S201 provides a mapping table including multiple stepped voltage ranges, and each stepped voltage range has a corresponding tolerance waiting time. The stepped voltage range refers to several consecutive and non - overlapping numerical ranges into which the voltage range that the battery may be in is divided. The mapping relation table refers to a logical structure that is pre - stored in the memory of the control device and is used to record the corresponding relationship between the voltage range and the time parameter. This table can exist in the form of an array, a structure, or a database. The tolerable waiting duration refers to the longest time that the device is allowed to remain in the on - state without detecting an effective charging current at the current voltage level.

[0044] In a specific example, the mapping relation table between the stepped voltage range where the real - time voltage V is located and the tolerable waiting duration can be expressed as follows: V ≤ 2600mV: Enter the "2 - minute monitoring state" (the lowest voltage, the most frequent monitoring); 2600mV < V ≤ 2750mV: Enter the "5 - minute monitoring state"; 2750mV < V ≤ 2850mV: Enter the "10 - minute monitoring state; V > 2850mV: Enter the "1 - hour monitoring state" (higher voltage, longer monitoring interval).

[0045] S202: Match the real - time voltage with the mapping relation table, and use the tolerable waiting duration corresponding to the stepped voltage range that is matched and hit as the dynamic shutdown threshold; Among them, the lower the stepped voltage range where the real - time voltage is located, the shorter the corresponding tolerable waiting duration.

[0046] Specifically, using a stepped mapping relation table to determine the dynamic shutdown threshold can achieve refined hierarchical management of the battery safety state with extremely low computational overhead. Since the sensitivity of the battery to self - power consumption is different under different states of charge (SOC), by dividing the voltage into multiple steps, a set of observation period rules can be set for each state of charge.

[0047] During the execution process, the control device uses the collected real - time voltage as an index key to perform range matching in the mapping relation table. For example, when the real - time voltage is in a higher stepped range (corresponding to a high state of charge), the system allocates a longer tolerable waiting duration because high - state - of - charge batteries have a higher tolerance for micro - current consumption. Extending the observation time helps to capture the weak power input that may recover and reduces unnecessary frequent shutdowns.

[0048] Conversely, when the real-time voltage drops to a lower step range (corresponding to low charge or over-discharge edge), the system automatically matches and switches to an extremely short tolerance waiting time. The motivation behind this step-by-step reduction design is that, in the event of a critical battery charge, every second of system self-discharge could cause the battery to enter a deep over-discharge state. By shortening the tolerance period, the system can be forced to quickly enter deep sleep mode after determining that the charging is ineffective, thereby protecting the remaining battery charge under extremely low power conditions.

[0049] Step S30: Extract current integral features based on real-time current and extract voltage trend features based on real-time voltage; Current integral characteristics refer to quantitative indicators reflecting the true physical energy surplus / deficit direction of the battery after accumulating the net input current over a time span. Voltage trend characteristics refer to the slope or rate of change of the battery terminal voltage over a set observation period, reflecting the dynamic response of the battery's internal electrochemical state to weak energy input. The process of extracting current integral characteristics based on real-time current is as follows: Figure 4 As shown, it includes the following steps: S301, obtain the preset loss compensation current and sampling time interval; The preset loss compensation current refers to the reference current required for the control device or circuit board to maintain its normal operation in the current operating mode, i.e., the system's self-consumption power. The sampling time interval refers to the time step between two adjacent current data acquisitions.

[0050] S302, perform multiple consecutive samplings according to the sampling time interval, and subtract the preset loss compensation current from the real-time current collected each time to obtain the single net current; The single net current characterizes the effective current value that actually flows into or out of the battery at a single sampling point after the system's self-dissipation interference has been removed.

[0051] S303, multiply the single net current corresponding to each sampling by the sampling time interval to obtain the corresponding single net charge; S304, sum up the net charge values ​​obtained from multiple consecutive samplings to obtain the cumulative net charge value; The cumulative net charge is the total physical amount of electricity actually charged (or discharged) into the battery during this continuous sampling period.

[0052] Cumulative net charge Q integral It can be represented as: Q integral =Σ((I sample [i]-I offset )×Δt); Among them, I sample [i] represents the i-th current sample value, Δt represents the sampling time interval, and Ioffset This is the preset loss compensation current.

[0053] Under low-power conditions, the total charging current measured externally often includes the power consumption used to keep the system running. If charging is determined solely by the measured current being greater than zero, the system may remain powered on continuously, eventually draining the underlying battery cells. To obtain the true change in power consumption, a preset loss compensation current is subtracted from the collected real-time current during each sampling.

[0054] S305, Based on the comparison between the cumulative net charge and the preset charge judgment threshold, determine the current integral characteristic; The preset charge judgment threshold is a benchmark value used to measure whether the energy inflow or outflow of the battery during the observation period reaches the judgment critical point. By introducing the preset charge judgment threshold, a physically meaningful judgment buffer can be constructed, which can effectively filter out non-substantial energy fluctuations, thereby achieving robust extraction of the true energy profit and loss trend. The preset charge judgment threshold includes a positive judgment threshold and a negative judgment threshold, specifically based on the comparison result of the cumulative net charge and the preset charge judgment threshold: If the cumulative net charge is greater than the positive determination threshold, then the current integral characteristic is determined as the charging direction; The positive decision threshold is the minimum amount of charge accumulated required to determine effective charging. When the accumulated net charge is greater than the positive decision threshold, it is expressed as: When Q integral Q threshold At that time, it is determined to be a charging trend, C Result It equals 1; Among them, Q integral Q represents the cumulative net charge. threshold C is the positive decision threshold. Result This is a current integral characteristic.

[0055] If the cumulative net charge is less than the negative determination threshold, then the current integral characteristic is determined as the discharge direction; When the cumulative net charge is less than the negative determination threshold, it is expressed as: When Q integral <-Q threshold At that time, the discharge direction is determined, C Result Equals -1; Among them, Q integral For the cumulative net charge, -Q threshold C is the negative decision threshold. Result This is a current integral characteristic.

[0056] If the cumulative net charge is between the negative and positive decision thresholds, then the current integral characteristic is determined to be in equilibrium. The cumulative net charge, falling between the negative and positive decision thresholds, is expressed as: -Q threshold ≤Q integral ≤Q threshold The state is determined to be in equilibrium, C. Result Equals 0; Among them, Q integral Q represents the cumulative net charge. threshold -Q is the positive decision threshold. threshold C is the negative decision threshold. Result This is a current integral characteristic.

[0057] In a specific example: Sampling time interval Δt: 1 second (sampling once per second); Sampling duration: 10s; Sampling current I sample [i]: 0.08A; Preset loss compensation current I offset 0.02A (fixed power consumption of the system); Positive decision threshold Q threshold : 0.1As (A valid trend is determined only if the cumulative net charge reaches the target). Where Q is taken threshold =0.1As is because the error is compensated by filtering sampling noise and system self-consumption, to avoid misjudgment caused by random fluctuations; Therefore Q integral =Σ((I sample [i]-I offset )×Δt)=0.06As; Trend Judgment: Q threshold =0.1As, at this time Q integral (0.6As) > Q threshold If (0.1As), it is determined to be a charging trend, C Result =1.

[0058] The process of extracting voltage trend features based on real-time voltage is as follows: Figure 5 As shown, it includes the following steps: S306, continuously acquire multiple sets of real-time voltages within multiple preset sliding time windows, and determine the trend slope of the multiple sets of real-time voltages within the multiple sliding time windows respectively. A sliding time window is a pre-defined observation window on the time axis used to capture voltage sequences of a specific duration. The trend slope refers to the linear rate of change of voltage over time within this window, characterizing the speed of voltage rise or fall. The process of determining the trend slope of multiple sets of real-time voltages within multiple sliding time windows is as follows: Figure 6 As shown, it includes the following steps: S3061, obtain the latest voltage sample value in each set of real-time voltages, as well as the initial voltage sample value when the sliding time window is established; The latest voltage sample value refers to the real-time voltage data acquired at the battery end within the current execution cycle, representing the end point of the voltage sequence on the time axis. The starting voltage sample value refers to the voltage data at the very beginning of the time axis within the truncation range of the sliding time window.

[0059] It should be noted that the selection of the initial voltage sampling value has a dynamic sliding characteristic. In the initial stage when the monitoring time is just started, this initial voltage sampling value is the recorded reference voltage. As the monitoring process continues, once the sliding time window has been fully established and begins to slide forward, the initial voltage sampling value will be continuously updated according to the first-in-first-out principle, always anchored at the sampling point at the beginning of the current window time.

[0060] S3062 calculates the difference between the latest voltage sample value and the initial voltage sample value, and divides the result by the duration of the sliding time window to obtain the trend slope corresponding to the sliding time window.

[0061] The net voltage change within the window is obtained by subtracting the initial voltage sample value from the current latest voltage sample value. This net voltage change is then divided by the corresponding sliding time window duration (e.g., 10 seconds, 2 minutes, or 10 minutes), thereby normalizing the change to a linear rate of change per unit time, i.e., the trend slope. In this way, observation windows of different scales (short, medium, and long) can be unified to the same dimension, thus providing standardized data input for subsequent weighted score calculations and eigenvalue determination.

[0062] S307, the trend score is obtained by weighted summation of the trend slopes corresponding to each sliding time window; Multiple sliding time windows include short-term time windows, medium-term time windows, and long-term time windows; The short-term time window is used to capture instantaneous voltage changes, the medium-term time window is used to filter out voltage noise and short-term fluctuation interference, and the long-term time window is used to extract the steady-state voltage change of the battery. The weighting coefficient corresponding to the long-term time window is greater than that corresponding to the medium-term time window, and the weighting coefficient corresponding to the medium-term time window is greater than that corresponding to the short-term time window.

[0063] The trend score is a quantitative assessment of the overall voltage change trend, derived by integrating observations from multiple different scales. It can be expressed as: V delta =α×S slope +β×M slope +γ×L slope ; Among them, V delta S scores the trend. slope M represents the slope of the short-term trend. slope L represents the slope of the medium-term trend. slope Let α be the slope of the long-term trend, β be the weighting coefficients, and γ be the weighting coefficients. α + β + γ = 1, and α < β < γ.

[0064] S308, determine the voltage trend characteristics based on the comparison result between the trend score and the preset trend threshold; The preset trend threshold value refers to the benchmark value used to quantify and judge the strength of voltage change trend. It reflects the minimum change boundary of voltage rise or fall. The preset trend threshold value includes the charging trend threshold value and the discharging trend threshold value. The process of determining the voltage trend characteristics based on the comparison result of the trend score and the preset trend threshold value includes: If the trend score is greater than the charging trend threshold, then the voltage trend characteristic is represented as the charging trend: Voltage trend characteristics are characterized by charging trend as follows: V delta >T charge This is determined to be a charging trend, V Result It equals 1; Among them, V delta To score the trend, T charge V is the critical value for charging trend. Result This represents voltage trend characteristics.

[0065] If the trend score is less than the discharge trend threshold, the voltage trend characteristic is characterized as a discharge trend. Voltage trend characteristics are characterized by discharge trend as follows: V delta <T discharge This is determined to be a discharge trend, V Result Equals -1; Among them, V delta To score the trend, T discharge V is the critical value for discharge trend. Result This represents voltage trend characteristics.

[0066] If the trend score is between the charging trend threshold and the discharging trend threshold, the voltage trend characteristic is characterized as a balanced state. Voltage trend characteristics are characterized by an equilibrium state, represented as follows: T discharge ≤V delta ≤T charge It is determined to be in equilibrium, V Result It equals 0.

[0067] In a specific example: Sampling interval: 2s; Short-term time window duration: 10s, 5 sampling points; Medium-term time window duration: 2min; Long-term time window duration: 10min; Charging trend critical value T charge 0.3V / min, discharge trend critical value T discharge -0.3 / min; The real-time voltages collected at the sampling points were 2.80V, 2.81V, 2.81V, 2.82V, and 2.82V, respectively. The short-term trend slope S corresponding to the short-term time window slope The value is: (final sampling voltage - initial sampling voltage) / window duration, i.e. (2.82V - 2.80V) / (10 / 60min) = 0.02V / (1 / 6min) = 0.12V / min; According to the above calculation method, the medium-term trend slope M can be obtained. slope (2-minute window): 0.04V / min; long-term trend slope L slope (10-minute window): 0.05V / min; Short-term trend slope S slope The weight α = 0.2, and the intermediate trend slope M slope The weight β=0.3, and the long-term trend slope L slope The weight γ is 0.5.

[0068] Trend Score V delta =α×S slope +β×M slope +γ×L slope =0.2×0.12+0.3×0.04+0.5×0.05=0.061; At this time V delta (0.061V / min)>T charge (0.03V / min), determined by the rules to be a charging trend, V Result =1.

[0069] It should be noted that the charging trend critical value T is taken. charge =0.03V / min, discharge trend critical value T discharge =-0.03V / min is because: 1. Minimal voltage fluctuation: When SOC=0, the battery voltage is at the lower limit of the plateau region. When charging with a small current, the voltage rises very slowly (at a normal small current charging rate, the voltage rises by only 0.02~0.04V / min per minute). When not charging and resting, the voltage fluctuation is also controlled within ±0.02V / min, with no obvious continuous rise / fall.

[0070] 2. High noise interference resistance requirements: When the portable power supply has SOC=0, the BMS circuit, display module, standby load, etc. will bring small sampling noise, causing the voltage to fluctuate instantaneously by about ±0.01V / min. If the threshold is set too low, the noise will be misjudged as a charging and discharging trend; if it is too high, the real small current charging signal will not be recognized.

[0071] Step S40: The current integral feature and voltage trend feature are fused together to determine the charging state decision result. Fusion determination refers to the process of jointly deducing and cross-validating current-dimensional features (such as charging direction, discharging direction, or equilibrium state) with voltage-dimensional features (such as upward trend, downward trend, or stable trend).

[0072] Under low-power charging conditions, single-dimensional monitoring often has inherent physical limitations and blind spots: limited by the physical precision of the hardware circuit, the slight drift or high-frequency noise of the current sensor near zero can easily accumulate into false net charge or net outflow over long-term integration calculations. Furthermore, when a large external load is immediately disconnected or a transient fluctuation occurs in the input source, the battery cell, based on its own chemical polarization elimination effect, will produce a natural voltage rebound, which can easily be misjudged as a valid charging temperature rise by a single voltage monitoring logic. The charging state decision result obtained from this multi-dimensional cross-validation (e.g., determining a high-confidence true charging state, a true discharging state, or an invalid interference fluctuation state) directly reflects the battery's current true energy surplus / deficit threshold.

[0073] The process of fusing current integral characteristics and voltage trend characteristics to obtain the charging state decision result is as follows: Figure 7 As shown, it includes the following steps: S401, configure a first evaluation weight and a second evaluation weight for the current integral characteristic and the voltage trend characteristic respectively, wherein the second evaluation weight is greater than the first evaluation weight; The first evaluation weight and the second evaluation weight are used to quantify the contribution ratio of current dimension features and voltage dimension features in the final charging state decision, respectively.

[0074] In a specific example, the first evaluation weight W1 = 0.4 and the second evaluation weight W2 = 0.6. A weighted fusion strategy is adopted, with voltage trend as the primary factor and current integral as the secondary factor. Voltage trend has strong stability and excellent anti-interference ability, serving as the primary judgment criterion; current integral has fast response and can be cross-validated, serving as the auxiliary factor. This weight configuration can achieve the most reliable charging and discharging state identification under harsh operating conditions such as low SOC, low current, and standby.

[0075] S402, according to the first evaluation weight and the second evaluation weight, the current integral feature and the voltage trend feature are weighted and summed to obtain the fusion decision score; The fusion decision score is represented as: F Result =W1×C Result +W2×V Result ; Among them, F Result To integrate the decision scores, W1 is the first evaluation weight, and C Result For the current integral characteristic, W2 is the second evaluation weight, and V Result This represents voltage trend characteristics.

[0076] S403, determine the charging state decision result based on the fusion decision score; The state of charge (SOC) decision result is used to characterize the battery's true energy balance (e.g., confirming charging or confirming discharging), serving as the closed-loop basis for triggering the main control circuit to maintain operation or execute forced shutdown and hibernation protection. The process of determining the SOC decision result based on the fused decision score includes: If the fusion decision score is greater than the zero value of the evaluation benchmark, the charging status decision result is determined to be effective charging; The zero-value evaluation baseline represents the critical point for determining energy surplus or deficit. When the fusion decision score is greater than this zero value, it means that after eliminating the combined interference from transient noise, polarization artifacts, and sensor zero drift, it is confirmed that the current external input source is providing a substantial positive energy gain to the battery. At this point, the decision result for effective charging is output.

[0077] If the fusion decision score is not greater than the zero value of the evaluation benchmark, the charging status decision result is determined to be ineffective charging.

[0078] When the calculated fusion decision score is less than or equal to the zero value of the evaluation benchmark, it means that under the cross-validation of multi-scale time domain and current integral, the current state of the battery shows a net discharge trend or a disturbance fluctuation that does not produce substantial energy gain. Based on this, an ineffective charging decision result is output.

[0079] Step S50: Based on the charging status decision result, control the monitoring timer to reset, or trigger the shutdown operation when the cumulative duration of the monitoring timer reaches the dynamic shutdown threshold; If the charging status decision result output by the previous step is valid charging, it is determined that the current state is a safe and beneficial energy replenishment state. At this time, a reset command is issued to clear the background sleep countdown timer and restart it.

[0080] Conversely, if the charging state decision result remains ineffective charging (such as pure discharge, polarization rebound, or simple noise interference), the sleep countdown timer will not be reset, and its accumulated duration will continue to increase over time. Once this accumulated duration reaches the dynamic shutdown threshold, it is logically determined that external energy input has been cut off or cannot compensate for the system's basic self-consumption over a long period of time. To prevent the battery from being excessively consumed, a shutdown operation is triggered.

[0081] The decision-making process can be represented as: If F Result If the count is greater than 0, the count will be reset and the operation will continue.

[0082] If F Result If the count value is ≤0, the count value will continue to accumulate. When the count value reaches the shutdown threshold, the system will be shut down.

[0083] The above solution will be described in detail below with reference to a specific embodiment: (1) Example of current integral mode: Parameter settings: Sampling interval Δt: 1 second; Preset loss compensation current I offset 0.02A; Positive decision threshold Q threshold 0.1As; Negative decision threshold -Q threshold -0.1As; process: Ten consecutive samples were taken to obtain a current value sequence (unit: A): I sample =[0.08,0.08,0.08,0.08,0.08,0.08,0.08,0.08,0.08,0.08]; Calculate the cumulative charge Q integral : Q integral =Σ(I sample [i]-I offset )×Δt; Q integral =((0.08-0.02)×1s+(0.08-0.02)×1s+(0.08-0.02)×1s+(0.08-0.02)×1s+(0.08-0.02)×1s+(0.08-0.02)×1s+(0.08-0.02)×1s+(0.08-0.02)×1s+(0.08-0.02))×1s; Q integral =0.6As; Judgment: Since Qintegral(0.6As) > Qthreshold (0.1As); Output: C Result =1 (determined as charging direction); (2) Example of voltage trend mode: Parameter settings: Weighting coefficients (summing up to 1): α=0.2; β=0.3; γ=0.5; Trend slope: S slope (Short-term: 10 seconds): 0.07V / min; M slope (Mid-term: 2 minutes): 0.02V / min; L slope (Long-term: 10 minutes): 0.05V / min; Charging trend threshold T charge =0.03V / min, discharge trend critical value T discharge =-0.03V / min; process: Calculate the trend score: V delta =α×S slope +β×M slope +γ×L slope ; V delta =0.2×(0.07)+0.3×(0.02)+0.5×(0.05); V delta =0.014+0.006+0.025; V delta =0.045V / min; Judgment: Since the trend score (0.051) > T charge (0.03), Output: V Result =1 (indicated as a charging trend); (3) Example of fusion decision algorithm: Parameter settings: The total weights (set according to the current signal quality) are 1: W1=0.4, W2=0.6.

[0084] process: Obtaining the current integral characteristic C Result and voltage trend characteristics V Result ; Calculate the final score of the fusion: F Result =W1×C Result +W2×VResult ; F Result =0.4×1+0.6×1=1.0; Decision execution: Judgment: F Result (1.0)>0; Final decision: Perform a count clearing to maintain system operation.

[0085] Figure 8 A flowchart illustrating another battery charging control method under low power conditions is shown, and its specific process is as follows: A1: If the activation condition is met when a low-power input source is detected, execute A2; otherwise, maintain the power-off state. A2: Obtain the current battery terminal voltage as the reference voltage V Ref And start monitoring timing, execute A3; A3: Continuously collect the real-time voltage and real-time current I of the battery. sample [i], and the lowest single-cell voltage of a single cell in the battery, and execute A4; A4: Determine if the lowest single-cell voltage is less than the reference voltage V. Ref If the voltage is -30mV, the shutdown operation will be triggered directly, and this process will end; otherwise, A5 will be executed.

[0086] A5: Based on the determined tolerable waiting time of multiple stepped voltage ranges, obtain the current dynamic shutdown threshold T, and then execute A6a and A6b synchronously and in parallel. A6a: Obtain the preset loss compensation current I offset And the sampling time interval Δt, calculate the single net current (I) sample [i]-I offset )×Δt, and execute A7a; A7a: Calculate the cumulative net charge Q integral =Σ((I sample [i]-I offset )×Δt), and execute A8a; A8a: Set the positive decision threshold Q threshold and negative decision threshold -Q threshold Calculate the current integral characteristic C Result If Q integral Q threshold Then C Result =1, if Q integral <-Q threshold Then C Result =-1, if -Q threshold ≤Q integral ≤Q threshold Then CResult =0, execute A9; A6b: Set short-term, medium-term, and long-term sliding time windows, and calculate the short-term trend slope S for each. slope Medium-term trend slope M slope and long-term trend slope L slope Execute A7b; A7b: Set the weighting coefficients α, β, and γ, and calculate the trend score V. delta =α×S slope +β×M slope +γ×L slope ; A8b: Set the charging trend threshold T charge and the critical value of discharge trend T discharge Calculate the voltage trend characteristics V Result If V delta >T charge Then V Result =1, if V delta <T discharge Then V Result =-1, if T discharge ≤V delta ≤T charge Then V Result =0, execute A9; A9: Set the first evaluation weight W1 and the second evaluation weight W2, and calculate the fusion decision score F. Result =W1×C Result +W2×V Result And execute A10; A10: Judgment, F Result Is it greater than 0? If F Result If the value is greater than 0, execute A11; otherwise, execute A12. A11: Reset the counter to maintain operation; A12: Maintain the count value accumulation and perform shutdown when the count value reaches the shutdown threshold.

[0087] like Figure 9 As shown, one embodiment of the present invention provides a battery charging control device under low power conditions, which includes: The status response module 61 is used to acquire the battery reference voltage and start the monitoring timing when it detects that the low power input source is in an effective power supply state; The threshold setting module 62 is used to collect the real-time voltage and real-time current of the battery, and determine the dynamic shutdown threshold based on the real-time voltage. The feature extraction module 63 extracts current integral features based on real-time current and voltage trend features based on real-time voltage. The fusion decision module 64 is used to fuse the current integral characteristics and voltage trend characteristics to obtain the charging state decision result; The execution control module 65 is used to control the monitoring timer to reset based on the charging status decision result, or to trigger a shutdown operation when the cumulative duration of the monitoring timer reaches the dynamic shutdown threshold.

[0088] Each module in the above-mentioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0089] like Figure 10 As shown, one embodiment of the present invention provides an electronic device 700. The electronic device 700 includes a memory 701, a processor 702, and an input / output (I / O) interface 703. The memory 701 is used to store instructions. The processor 702 is used to execute the battery charging control method under low power conditions according to embodiments of the present application by calling the instructions stored in the memory 701. The processor 702 is connected to both the memory 701 and the I / O interface 703, for example, via a bus system and / or other forms of connection mechanisms (not shown). The memory 701 can be used to store programs and data, including the program for the battery charging control method under low power conditions according to embodiments of the present application. The processor 702 executes various functional applications and data processing of the electronic device 700 by running the program stored in the memory 701.

[0090] In this embodiment, the processor 702 can be implemented in at least one of the following hardware forms: digital signal processor (DSP), field programmable gate array (FPGA), and programmable logic array (PLA). The processor 702 can be one or a combination of several of the following: central processing unit (CPU) or other processing units with data processing capability and / or instruction execution capability.

[0091] The memory 701 in this embodiment may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0092] In this embodiment, the I / O interface 703 can be used to receive input instructions (such as numeric or character information, and to generate key signal inputs related to user settings and function control of the electronic device 700), and can also output various information (such as images or sounds) to the outside. In this embodiment, the I / O interface 703 may include one or more of the following: a physical keyboard, function keys (such as volume control keys, power buttons, etc.), a mouse, a joystick, a trackball, a microphone, a speaker, and a touch panel.

[0093] In some embodiments, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method embodiments.

[0094] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; however, as long as the combinations of these technical features are not contradictory, they should be considered within the scope of this specification.

[0095] In some embodiments, this application provides a computer program product comprising a computer program that, when executed by a processor, performs any of the methods described above.

[0096] Although the operations are described in a specific order in the accompanying drawings, this should not be construed as requiring these operations to be performed in the specific order or serial order shown, or requiring all of the operations shown to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0097] The methods, apparatus, devices, and storage media of this application can be implemented using standard programming techniques, and various method steps can be implemented using rule-based logic or other logic. It should also be noted that the terms "apparatus" and "module" as used herein and in the claims are intended to include implementations using one or more lines of software code and / or hardware implementations and / or devices for receiving input.

[0098] Any step, operation, or procedure described herein may be performed or implemented using one or more hardware or software modules, either alone or in combination with other devices. In one embodiment, the software module is implemented using a computer program product comprising a computer-readable medium containing computer program code, which is executable by a computer processor to perform any or all of the described steps, operations, or procedures.

[0099] The foregoing description of implementations of this application has been provided for illustrative and descriptive purposes. The foregoing description is not exhaustive and is not intended to limit this application to the exact forms disclosed. Various modifications and variations may exist in accordance with the foregoing teachings, or may arise from practice of this application. These embodiments were chosen and described to illustrate the principles of this application and its practical application, enabling those skilled in the art to utilize this application in various implementations and modifications to suit the specific purpose of the concept.

[0100] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0101] It can be further understood that, unless otherwise specified, "connection" includes both direct connections where no other components exist between the two parties and indirect connections where other components exist between them.

[0102] It is further understood that although the operations are described in a specific order in the accompanying drawings in the embodiments of this application, this should not be construed as requiring these operations to be performed in the specific order or serial order shown, or requiring all the operations shown to be performed to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0103] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the field of this application that are not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0104] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

[0105] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A battery charging control method under low power conditions, characterized in that, include: When a low-power input source is detected to be in an effective power supply state, the reference voltage of the battery is acquired and the monitoring timing is started; Collect the real-time voltage and real-time current of the battery, and determine the dynamic shutdown threshold based on the real-time voltage; Based on the real-time current, current integral features are extracted, and based on the real-time voltage, voltage trend features are extracted. The current integral feature and the voltage trend feature are fused together to determine the charging state decision result; Based on the charging status decision result, control the monitoring timer to reset, or trigger a shutdown operation when the cumulative duration of the monitoring timer reaches the dynamic shutdown threshold.

2. The battery charging control method under low power conditions as described in claim 1, characterized in that, Based on the real-time current, current integral features are extracted, including: Obtain the preset loss compensation current and sampling time interval; The sampling is performed continuously multiple times according to the sampling time interval, and the preset loss compensation current is subtracted from the real-time current collected each time to obtain the single net current; The net current for each sampling is multiplied by the sampling time interval to obtain the corresponding net charge for each sampling. The cumulative net charge is obtained by summing up the net charge values ​​obtained from multiple consecutive samplings. The current integral characteristic is determined based on the comparison between the cumulative net charge and the preset charge determination threshold.

3. The battery charging control method under low power conditions as described in claim 2, characterized in that, The preset charge determination threshold includes a positive determination threshold and a negative determination threshold; Based on the comparison between the cumulative net charge and the preset charge determination threshold, the current integral characteristics are determined, including: If the cumulative net charge is greater than the positive determination threshold, then the current integral feature is determined to represent the charging direction. If the cumulative net charge is less than the negative determination threshold, then the current integral characteristic is determined to represent the discharge direction. If the cumulative net charge is between the negative determination threshold and the positive determination threshold, then the current integral characteristic is determined to be in a balanced state.

4. The battery charging control method under low power conditions as described in claim 1, characterized in that, Based on the real-time voltage, voltage trend features are extracted, including: Multiple sets of real-time voltages are continuously acquired within multiple preset sliding time windows, and the trend slope of the multiple sets of real-time voltages within the multiple sliding time windows is determined respectively. The trend score is obtained by weighted summation of the trend slopes corresponding to each sliding time window. The voltage trend characteristics are determined based on the comparison between the trend score and the preset trend threshold.

5. A battery charging control method under low power conditions as described in claim 4, characterized in that: The multiple sliding time windows include short-term time windows, medium-term time windows, and long-term time windows; The short-term time window is used to capture instantaneous voltage changes, the medium-term time window is used to filter out voltage noise and short-term fluctuation interference, and the long-term time window is used to extract the steady-state voltage changes of the battery. Furthermore, the weight coefficient corresponding to the long-term time window is greater than the weight coefficient corresponding to the medium-term time window, and the weight coefficient corresponding to the medium-term time window is greater than the weight coefficient corresponding to the short-term time window; the sum of all weight coefficients is 1.

6. The battery charging control method under low power conditions as described in claim 4, characterized in that: The preset trend thresholds include charging trend thresholds and discharging trend thresholds; Based on the comparison between the trend score and the preset trend threshold, voltage trend characteristics are determined, including: If the trend score is greater than the charging trend threshold, then the voltage trend feature is characterized as a charging trend. If the trend score is less than the discharge trend threshold, then the voltage trend feature is characterized as a discharge trend. If the trend score is between the charging trend threshold and the discharging trend threshold, then the voltage trend characteristic represents a balanced state.

7. A battery charging control method under low power conditions as described in claim 4, characterized in that, Determine the trend slope of multiple sets of real-time voltages within multiple sliding time windows, including: Obtain the latest voltage sample value in each set of real-time voltages, as well as the initial voltage sample value when the sliding time window is established; The difference between the latest voltage sample value and the initial voltage sample value is calculated, and the result is divided by the duration of the sliding time window to obtain the trend slope corresponding to the sliding time window.

8. A battery charging control method under low power conditions as described in claim 1, characterized in that, The current integral feature and the voltage trend feature are fused together to determine the charging state decision result, including: A first evaluation weight and a second evaluation weight are respectively assigned to the current integral feature and the voltage trend feature, wherein the second evaluation weight is greater than the first evaluation weight; According to the first evaluation weight and the second evaluation weight, the current integral feature and the voltage trend feature are weighted and summed to obtain the fusion decision score; The charging state decision result is determined based on the fusion decision score.

9. A battery charging control method under low power conditions as described in claim 8, characterized in that, Determining the charging state decision result based on the fusion decision score includes: If the fusion decision score is greater than the zero value of the evaluation benchmark, the charging state decision result is determined to be effective charging; If the fusion decision score is not greater than the zero value of the evaluation benchmark, then the charging state decision result is determined to be ineffective charging.

10. A battery charging control method under low power conditions as described in claim 1, characterized in that, Determining the dynamic shutdown threshold based on the real-time voltage includes: A mapping table containing multiple stepped voltage ranges is provided, and each stepped voltage range is assigned a tolerance waiting time. The real-time voltage is matched with the mapping table, and the tolerable waiting time corresponding to the matched stepped voltage range is used as the dynamic shutdown threshold. The lower the step voltage range in which the real-time voltage is located, the shorter the corresponding tolerance waiting time.

11. A battery charging control method under low power conditions as described in any one of claims 1-10, characterized in that, After starting the monitoring timer, the method further includes: The lowest single-cell voltage of a single battery cell in the battery is obtained in real time; Determine the difference between the reference voltage and the preset offset voltage; When the minimum single-cell voltage is less than the difference between the reference voltage and the preset offset voltage, a shutdown operation is triggered.

12. A battery charging control device under low power conditions, characterized in that, include: The status response module is used to obtain the battery's reference voltage and start the monitoring timing when it detects that the low-power input source is in an effective power supply state; The threshold setting module is used to collect the real-time voltage and real-time current of the battery, and determine the dynamic shutdown threshold based on the real-time voltage. The feature extraction module extracts current integral features based on the real-time current and voltage trend features based on the real-time voltage. The fusion decision module is used to fuse the current integral feature and the voltage trend feature to obtain the charging state decision result; The execution control module is used to control the monitoring timer to reset based on the charging status decision result, or to trigger a shutdown operation when the cumulative duration of the monitoring timer reaches the dynamic shutdown threshold.

13. An electronic device, characterized in that, include: The device includes an input unit, a memory, at least one processor, and an output interface. The memory stores program instructions that can be executed on the processor, which can invoke the program instructions to perform a battery charging control method under low power conditions as described in any one of claims 1 to 11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the battery charging control method under low power conditions as described in any one of claims 1 to 11.

Images