A method and system for fast charging and discharging control of a mobile power bank

Abstract

This invention discloses a fast charging and discharging control method and system for a mobile power bank, relating to the field of power bank charging and discharging control technology. It constructs a load decline trend index Ldt by real-time acquisition of feature set Bea, and calculates the trend deviation value Dis by comparing the difference between the trend feature set Beb and the template set Tpl. This allows for accurate determination of whether the current trend has deviated from a stable state before a significant current drop occurs under actual load. An early current reduction trigger set Tri is generated after the trend deviation value Dis exceeds the deviation threshold Dst, enabling the mobile power bank to adjust its output behavior in advance before rapid changes in load-side current, avoiding current surges or protocol renegotiations caused by delayed response in traditional fast charging methods. By adjusting the command Cmd to execute smooth current reduction control in advance, the output current transitions gradually, reducing the impact of current jumps on the device's power management chip.

Description

Technical Field

[0001] This invention relates to the field of power supply charging and discharging control technology, specifically to a fast charging and discharging control method and system for a mobile power supply. Background Technology

[0002] As the reliance on various electronic devices in daily life and mobile work continues to increase, power banks that can charge quickly or discharge stably under high load are gradually becoming key devices for users. Simultaneously, power banks are evolving to precisely respond to load changes, power demand rhythms, and dynamic behavior during charging and discharging. Against this technological backdrop, the control strategies of power banks no longer focus solely on basic power supply capabilities.

[0003] In existing power bank products, control systems generally tend to handle load changes in real-time, especially when current drops occur during discharging or charging. Most systems only trigger current reduction after detecting a significant drop in the instantaneous current. While this delayed response method is simple in structure, it has significant shortcomings in practical applications: when the device's load enters a decreasing phase, its power management module often enters a transition state prematurely. If the power bank cannot keep up with this trend, a mismatch between output power and device demand will occur for a short period. As user devices become increasingly sensitive to performance changes, this lag can lead to decreased charging stability, frequent protocol skipping, and even triggering abnormal protection mechanisms. Therefore, there is an urgent need for an improved solution that can identify load decreasing trends earlier and smoothly adjust the load before the actual change occurs. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a fast charging and discharging control method and system for mobile power supplies, solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a fast charging and discharging control method for a mobile power bank, comprising the following steps:

[0006] S1. Collect instantaneous current data, instantaneous voltage data, and current change rate data during the charging and discharging process of the mobile power supply, which are defined as current data Cur, voltage data Vol, and change rate Rat, respectively, and combined to form a real-time acquisition feature set Bea.

[0007] S2. Based on the real-time acquired feature set Bea, perform multi-cycle analysis of current changes, construct a load decline trend index, defined as the load decline trend index Ldt, and integrate to generate a trend feature set Beb.

[0008] S3. Compare the trend feature set Beb with the preset template set Tpl to obtain the trend deviation value, which is defined as the trend deviation value Dis. Then compare it with the preset deviation threshold Dst to generate the early current reduction trigger set Tri.

[0009] S4. Match the early current reduction trigger set Tri with the power regulation strategy set Pol inside the power bank to generate an early current reduction regulation instruction Cmd to control the output current of the power bank to decrease in advance.

[0010] Preferably, S1 includes S11;

[0011] S11. During the charging and discharging process of the power bank, the current and voltage at the output terminal are periodically sampled, with the period length being the default sampling period. Within each sampling period, the power bank sampling command is called to read the transient signal of the sampling node in the output circuit and obtain the instantaneous output current value corresponding to the sampling period, which is defined as current data Cur. At the same time, the instantaneous voltage value at the output terminal is synchronously obtained within the same sampling period and defined as voltage data Vol.

[0012] Preferably, S1 further includes S12;

[0013] S12. Based on the acquired current data Cur, calculate the difference between the current value in the current sampling period and the previous sampling period to obtain the current change; then divide the current change by the sampling period length to obtain the rate of change of the current, which is defined as the rate of change Rat.

[0014] The acquired current data Cur, voltage data Vol, and rate of change Rat are combined to construct a real-time feature set Bea that reflects the current output status of the power bank.

[0015] Preferably, S2 includes S12;

[0016] S12. Based on the continuous multi-sampling period data from the real-time acquisition feature set Bea, the current data Cur and the rate of change Rat of each sampling period are sorted by time series to form a multi-cycle current change sequence.

[0017] Periodic difference analysis is performed on the multi-cycle current change sequence. The change rate Rat of each sampling cycle is compared with the change trend of the adjacent cycles to construct the trend change rate within each sampling cycle interval. Then, the trend change rate is used to normalize the multi-cycle trend to obtain the trend base quantity representing the direction of load change, which is defined as the trend base quantity Tba.

[0018] Preferably, S2 further includes S22;

[0019] S22. Based on the acquired trend baseline quantity Tba, and combined with the rate of change Rat within the same sampling period, perform trend recursion calculation.

[0020] The trend recursion calculation uses the trend base quantity Tba as the basis for reflecting the historical trend direction and change magnitude within multiple sampling periods, and the change rate Rat of the same sampling period as the instantaneous quantity reflecting the dynamic change of the current sampling period. According to the preset trend accumulation rules, the weighted superposition and direction correction processing are performed to obtain the trend increment of the current sampling period, which is defined as the trend increment Tic.

[0021] The trend increment Tic from multiple consecutive sampling periods is compressed in amplitude and enhanced in direction to form a trend index for representing the overall load decline trend, which is defined as the load decline trend index Ldt.

[0022] Then, using the load decline trend index Ldt as the foundation, the trend base quantity Tba and trend increment Tic from the construction process are integrated to generate the trend feature set Beb.

[0023] Preferably, S3 includes S31;

[0024] S31. Based on the trend feature set Beb, extract the load decline trend index Ldt and the trend increment Tic corresponding to multiple consecutive sampling periods. Then, call the stable trend model formed by statistically processing the trend data in multiple sampling periods under normal and stable operating conditions of the power bank. Define the stable trend model as a template set Tpl, where the template set Tpl includes the stable trend index reference value and the stable trend increment reference range.

[0025] The load decline trend index Ldt in the trend feature set Beb and the stable trend index reference value in the template set Tpl are used to calculate the magnitude deviation and obtain the trend index deviation Dia; the trend increment Tic of multiple consecutive sampling periods and the stable trend increment reference interval in the template set Tpl are used to calculate the deviation period by period and obtain the deviation; the deviations are then accumulated to obtain the trend increment deviation, which is defined as the trend increment deviation Dia.

[0026] Then, the trend index deviation Dia and the trend increment deviation Dic are numerically superimposed to form the trend deviation value Dis, which represents the overall deviation of the current power bank trend.

[0027] Preferably, S3 further includes S32;

[0028] S32. Based on the generated trend deviation value Dis, compare it with a preset deviation limit value used to distinguish between a stable trend and a downward trend, wherein the deviation limit value is defined as the deviation threshold Dst;

[0029] When the trend deviation value Dis > the deviation threshold Dst, it is determined that the degree of trend deviation has reached the condition for early flow reduction. The control system generates a set of trigger information to trigger the early flow reduction decision based on the determination result, and defines the set of trigger information as the early flow reduction trigger set Tri.

[0030] When the trend deviation value Dis ≤ deviation threshold Dst, it is determined that the early flow reduction trigger set Tri will not be generated, and the current running state will remain unchanged.

[0031] Preferably, S4 includes S41;

[0032] S41. Based on the generated early current reduction trigger set Tri, read the trend deviation value Dis and time stamp information corresponding to the current sampling period, and use the trend deviation value Dis as the input parameter for determining the current reduction intensity; call the strategy set for executing early current reduction control from the preset power regulation strategy set for adjusting the output current, generate the strategy set Pol, and match and filter the current reduction amplitude and response speed corresponding to each regulation strategy in the strategy set Pol according to the trend deviation value Dis recorded in the early current reduction trigger set Tri, select a set of candidate regulation strategies that match the current trend deviation value Dis, and define the candidate regulation strategies as the candidate strategy set Poc.

[0033] Preferably, S4 further includes S42;

[0034] S42. Analyze the current reduction amplitude parameter, current reduction change rate parameter and execution mode parameter contained in each adjustment strategy in the candidate strategy set Poc, organize the adjustment parameters in a structured manner, and use them to generate control execution instructions by the mobile power supply execution module. Define the control execution instructions as adjustment instructions Cmd.

[0035] The adjustment command Cmd is used to control the output current of the power bank to decrease in advance.

[0036] A fast charging and discharging control system for a mobile power bank includes a power data acquisition module, a data cycle analysis module, a trend judgment and trigger generation module, and an adjustment command generation module.

[0037] The power data acquisition module collects instantaneous current data, instantaneous voltage data, and current change rate data during the charging and discharging process of the mobile power supply. These are defined as current data Cur, voltage data Vol, and change rate Rat, respectively, and are combined to form a real-time acquisition feature set Bea.

[0038] The data cycle analysis module performs multi-cycle analysis of current changes based on the real-time acquired feature set Bea, constructs a load decline trend index, defined as the load decline trend index Ldt, and integrates it to generate a trend feature set Beb.

[0039] The trend judgment and trigger generation module compares the trend feature set Beb with the preset template set Tpl to obtain the trend deviation value, which is defined as the trend deviation value Dis. Then, it compares it with the preset deviation threshold Dst to generate the early flow reduction trigger set Tri.

[0040] The adjustment command generation module matches the early current reduction trigger set Tri with the power regulation strategy set Pol inside the power bank to generate an early current reduction adjustment command Cmd, which controls the output current of the power bank to decrease in advance.

[0041] This invention provides a fast charging and discharging control method and system for a mobile power bank, which has the following beneficial effects:

[0042] (1) By acquiring real-time operating data from the feature set Bea, a load decline trend index Ldt is constructed, and the trend deviation value Dis is calculated by comparing the difference between the trend feature set Beb and the template set Tpl. This allows for accurate determination of whether the current trend has deviated from a stable state before the actual load generates a significant current drop. The pre-current reduction trigger set Tri is generated after the trend deviation value Dis exceeds the deviation threshold Dst, enabling the power bank to adjust its output behavior in advance before the load-side current changes rapidly, thus avoiding current surges or protocol renegotiations caused by the delayed response of traditional fast charging methods. By adjusting the instruction Cmd, the current smooth decline control is executed in advance, allowing the output current to transition gradually, reducing the impact of current jumps on the device's power management chip.

[0043] (2) By performing normalized differential analysis on continuous multi-period data from the real-time collected feature set Bea, a trend base quantity Tba that reflects the true load trend direction is obtained. Then, combined with the change rate Rat of the same period, a trend increment Tic is formed through weighted superposition and direction correction. This allows the finally generated load decline trend index Ldt to accurately represent the overall trend over multiple sampling periods without being disturbed by occasional fluctuations in a single period. The direction coefficient Dir can strengthen the trend increment under a continuous decline trend, suppress trend reversal when short-term reverse fluctuations occur, and converge the trend during high-frequency oscillations. This enables the trend feature set Beb to maintain a stable ability to identify the true change direction, thereby ensuring that subsequent trend determination steps are based on stable trend indicators, significantly improving the reliability and stability of load trend judgment.

[0044] (3) By comparing the load decline trend index Ldt in the trend feature set Beb with the trend increment Tic corresponding to the continuous sampling period with the stable trend reference value and stable trend increment reference interval of the template set Tpl, a trend deviation value Dis is formed to measure the overall deviation of the trend. This enables the system to identify early trends that are declining but have not yet formed obvious current changes. By combining the trend index deviation Dia and the trend increment deviation Dic, this gradual trend can be continuously quantified. In the early stage when the trend deviation value Dis exceeds the deviation threshold Dst, an early current reduction trigger set Tri is immediately generated to achieve accurate identification of the critical trend state. This avoids the common problems of blurred trend boundaries and difficulty in capturing low-amplitude declines in traditional schemes, so that subsequent control steps can obtain accurate trend deviation input at an earlier time. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the steps of a fast charging and discharging control method for a mobile power supply according to the present invention.

[0046] Figure 2 This is a schematic block diagram of a fast charging and discharging control system for a mobile power supply according to the present invention. Detailed Implementation

[0047] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0048] Example 1: This invention provides a fast charging and discharging control method for a mobile power bank. Please refer to [link / reference]. Figure 1 This includes the following steps:

[0049] S1. Collect instantaneous current data, instantaneous voltage data, and current change rate data during the charging and discharging process of the mobile power supply, which are defined as current data Cur, voltage data Vol, and change rate Rat, respectively, and combined to form a real-time acquisition feature set Bea.

[0050] S2. Based on the real-time acquired feature set Bea, perform multi-cycle analysis of current changes, construct a load decline trend index, defined as the load decline trend index Ldt, and integrate to generate a trend feature set Beb.

[0051] S3. Compare the trend feature set Beb with the preset template set Tpl to obtain the trend deviation value, which is defined as the trend deviation value Dis. Then compare it with the preset deviation threshold Dst to generate the early current reduction trigger set Tri.

[0052] S4. Match the early current reduction trigger set Tri with the power regulation strategy set Pol inside the power bank to generate an early current reduction regulation instruction Cmd to control the output current of the power bank to decrease in advance.

[0053] In this embodiment, a load decline trend index Ldt is constructed by acquiring real-time operating data from the feature set Bea, and a trend deviation value Dis is calculated by comparing the difference between the trend feature set Beb and the template set Tpl. This allows for accurate determination of whether the current trend has deviated from a stable state before the actual load generates a significant current drop. The early current reduction trigger set Tri is generated after the trend deviation value Dis exceeds the deviation threshold Dst, enabling the power bank to adjust its output behavior in advance before the current on the load side changes rapidly, thus avoiding current surges or protocol renegotiation caused by the delayed response of traditional fast charging methods. For example, in practical use, when a mobile phone suddenly ends its task after performing high-power calculations in the background, its load may drop rapidly within 20 to 40 milliseconds. Traditional fast charging solutions often only react after the current has already dropped sharply, which can easily lead to output current overshoot and overcompensation. This method adjusts the Cmd command to execute current smoothing control in advance, so that the output current transitions gradually, reducing the impact of current jumps on the device's power management chip. This improves the protocol stability and compatibility of most smartphones, tablets, and wearable devices under fast charging conditions, thereby significantly improving the user's stable experience during fast charging.

[0054] Example 2: Specifically: S1 includes S11;

[0055] S11. During the charging and discharging process of the power bank, the current and voltage at the output terminal are periodically sampled, with the period length being the default sampling period. Within each sampling period, the power bank sampling command is invoked to read the transient signal at the sampling node of the output circuit and obtain the instantaneous output current value corresponding to the sampling period, which is defined as the current data Cur. At the same time, the instantaneous voltage value at the output terminal is synchronously obtained within the same sampling period and defined as the voltage data Vol.

[0056] It should be noted that:

[0057] Current data Cur: obtained through instantaneous current acquisition at the output sampling node, used to represent the true load state at that moment, and is the basis for subsequent trend analysis;

[0058] Voltage data Vol: Synchronously acquired at the output terminal and used in conjunction with current data Cur to ensure consistency in trend analysis, step judgment, and stability judgment.

[0059] S1 further includes S12;

[0060] S12. Based on the acquired current data Cur, calculate the difference between the current value in the current sampling period and the previous sampling period to obtain the current change; then divide the current change by the sampling period length to obtain the rate of change of the current, which is defined as the rate of change Rat.

[0061] The acquired current data Cur, voltage data Vol, and rate of change Rat are combined to construct a real-time feature set Bea that reflects the current output status of the power bank.

[0062] It should be noted that:

[0063] Rate of change Rat: Obtained by dividing the difference between the current data Cur value of the current period and the previous period by the sampling period, it is used to reflect the instantaneous trend of current change within the current period.

[0064] In this embodiment, through the implementation of the above-mentioned data acquisition actions, during the rapid charging and discharging process of the power bank, a real-time acquisition feature set Bea, composed of current data Cur, voltage data Vol, and rate of change Rat, can be acquired and constructed in real time. This allows the control system to grasp the dynamic changes at the output end with unprecedented resolution. Since the current data Cur and voltage data Vol are acquired synchronously within the same sampling period, the sampled data not only reflects the actual load state but also ensures the temporal consistency between current and voltage, thereby significantly reducing data mismatch problems in trend analysis. Furthermore, by calculating the rate of change Rat based on the difference between adjacent sampling periods, the system can accurately identify the current change rate during rapid instantaneous phases, which is particularly important in practical application scenarios. For example, when a user switches applications on a smartphone, or when a background task suddenly starts or closes, the load may change abruptly within 5 to 10 milliseconds. Traditional methods often fail to capture these subtle changes due to sampling lag or insufficient sampling granularity. The real-time acquisition feature set Bea constructed by the above steps in this method can completely record the entire process of such sudden load changes, making subsequent trend analysis more accurate. This lays a reliable data foundation for the power bank to implement a more stable control strategy in the later stages.

[0065] Example 3: Specifically: S2 includes S12;

[0066] S12. Based on the continuous multi-sampling period data from the real-time acquisition feature set Bea, the current data Cur and the rate of change Rat of each sampling period are sorted by time series to form a multi-cycle current change sequence.

[0067] Periodic difference analysis is performed on the multi-cycle current change sequence. The change rate Rat of each sampling cycle is compared with the change trend of the adjacent cycle to construct the trend change rate within each sampling cycle interval. Then, the trend change rate is used to normalize the multi-cycle trend to obtain the trend base quantity representing the direction of load change, which is defined as the trend base quantity Tba.

[0068] It should be noted that:

[0069] Trend base quantity Tba: obtained through differential analysis of multi-period current change sequences, it reflects the directionality of the current change trend in the time dimension. It is a trend feature extracted from multi-period data and is used to support the first-level trend judgment in index construction.

[0070] The purpose of multi-period analysis is to ensure that trend judgment is not affected by accidental fluctuations in a single period, and to ensure that the construction of subsequent trends has a continuous foundation.

[0071] The purpose of normalization is to make the trend scale comparable to different current amplitude conditions, and to avoid misjudgment of the trend due to differences in absolute current range.

[0072] S2 further includes S22;

[0073] S22. Based on the acquired trend baseline quantity Tba, and combined with the rate of change Rat within the same sampling period, perform trend recursion calculation.

[0074] The trend recursion calculation uses the trend base quantity Tba as the basis for reflecting the historical trend direction and change magnitude within multiple sampling periods, and the change rate Rat of the same sampling period as the instantaneous quantity reflecting the dynamic change of the current sampling period. According to the preset trend accumulation rules, the weighted superposition and direction correction processing are performed to obtain the trend increment of the current sampling period, which is defined as the trend increment Tic.

[0075] The trend increment Tic from multiple consecutive sampling periods is compressed in amplitude and enhanced in direction to form a trend index for representing the overall load decline trend, which is defined as the load decline trend index Ldt.

[0076] Then, using the load decline trend index Ldt as the foundation, the trend base quantity Tba and trend increment Tic from the construction process are integrated to generate the trend feature set Beb;

[0077] It should be noted that:

[0078] Weighted superposition: In each sampling period, the control method assigns different weight coefficients to the trend base quantity Tba and the rate of change Rat according to the preset weight configuration. The weight memory factor corresponding to the historical trend is defined as the weight coefficient Whm, and the weight factor corresponding to the current change is defined as the weight coefficient Whc.

[0079] During the trend recursion process, by applying weighting coefficients Whm and Whc to the trend base quantity Tba and the rate of change Rat respectively, and then weighting and superimposing the two, the trend base quantity Tba is fully preserved through the larger weighting coefficient Whm when the load change direction remains consistent for a long time, thus ensuring the continuity of the trend.

[0080] When the current sampling period changes significantly, the rate of change Rat reflects this rapid change in the trend in a timely manner through an appropriate weighting coefficient Whc, so as to avoid the trend response being too slow.

[0081] Direction correction processing: In order to maintain both the continuous perception of historical trends and sensitivity to changes in direction in trend recursion, the control method uses a direction correction factor to determine the direction of the weighted results. The direction correction factor is defined as the direction coefficient Dir.

[0082] When the trend base quantity Tba and the rate of change Rat are in the same direction, that is, when the change direction of both indicates that the load is in a downward trend, the direction coefficient Dir is set to the enhancement mode, so that the calculated trend increment Tic is appropriately amplified in value to enhance the identification of the continuous downward trend.

[0083] When the trend base quantity Tba and the rate of change Rat are not in the same direction, for example, when the trend base quantity Tba shows a previous downward trend, while the current rate of change Rat shows that the current is rising or fluctuating, the direction coefficient Dir is set to the suppression mode. By reducing the effective contribution of the superposition result of the trend base quantity Tba and the rate of change Rat in terms of value, the trend increment Tic is compressed in terms of value, thereby avoiding the rapid reversal of the trend direction due to short-term reverse fluctuations.

[0084] When the trend base quantity Tba and the rate of change Rat exhibit repeated changes, i.e., the direction frequently switches across multiple sampling periods, the effective value of the direction coefficient Dir is further reduced to make the cumulative result of the trend increment Tic in multiple sampling periods tend to be smoother, so as to prevent the generation of erroneous obvious downward trend judgments in volatile scenarios.

[0085] In this embodiment, normalized differential analysis is performed on continuous multi-period data from the real-time acquired feature set Bea to obtain the trend base quantity Tba, which reflects the true load trend direction. This is then combined with the rate of change Rat in the same period, and weighted superposition and direction correction are used to form the trend increment Tic. This ensures that the final generated load decline trend index Ldt accurately represents the overall trend over multiple sampling periods, unaffected by occasional fluctuations in a single period. For example, when a smartphone enters high refresh rate mode or the screen brightness automatically adjusts, the load may experience slight and repeated rises and falls over multiple periods. Traditional methods are often frequently misjudged due to short-term fluctuations, leading to jitter in subsequent control actions. However, the direction coefficient Dir in this method strengthens the trend increment under a continuous decline trend, suppresses trend reversal during short-term reverse fluctuations, and converges the trend during high-frequency oscillations. This allows the trend feature set Beb to maintain a stable ability to identify the true direction of change, ensuring that subsequent trend determination steps are based on stable trend indicators, significantly improving the reliability and stability of load trend judgment.

[0086] Example 4: Specifically: S3 includes S31;

[0087] S31. Based on the trend feature set Beb, extract the load decline trend index Ldt and the trend increment Tic corresponding to multiple consecutive sampling periods. The load decline trend index Ldt is used to represent the overall decline intensity of the trend, while the trend increment Tic is used to represent the cumulative trend change in each sampling period. Then, under normal and stable operating conditions, the stable trend model formed by statistically processing the trend data in multiple sampling periods is called. The stable trend model is defined as a template set Tpl, where the template set Tpl includes a stable trend index reference value and a stable trend increment reference range.

[0088] The load decline trend index Ldt in the trend feature set Beb and the stable trend index reference value in the template set Tpl are used to calculate the magnitude deviation and obtain the trend index deviation Dia; the trend increment Tic of multiple consecutive sampling periods and the stable trend increment reference interval in the template set Tpl are used to calculate the deviation period by period and obtain the deviation; the deviations are then accumulated to obtain the trend increment deviation, which is defined as the trend increment deviation Dia.

[0089] Then, the trend index deviation Dia and the trend increment deviation Dic are numerically superimposed to form the trend deviation value Dis, which represents the overall deviation of the current power bank trend.

[0090] It should be noted that:

[0091] The trend index deviation Dia is derived from the load decline trend index Ldt and the trend index reference value in the template set Tpl; the trend index reference value in the template represents the typical range of Ldt for multiple sampling periods during stable operation when the load is not in a decline trend.

[0092] The trend index deviation Dia is calculated as: the difference in magnitude between the load decline trend index Ldt and the reference value of the stable trend index (the absolute difference can be taken directly without introducing additional rules).

[0093] The meaning of the trend index deviation Dia is: to indicate how much the current overall trend strength deviates from the trend strength of the stable state;

[0094] The trend increment deviation Dic is derived from the trend increment Tic comparison template interval for each sampling period; the template interval represents the normal upward and downward fluctuation range of the trend increment for each period under stable operating conditions.

[0095] The trend increment deviation Dic is calculated as follows: for each period, it is determined whether the TrendTic exceeds the template range. If it does, the excess amount is accumulated.

[0096] The significance of the trend increment deviation Dic is: it indicates whether the trend shows continuous deviation over multiple periods rather than occasional deviation in a single period;

[0097] Trend deviation value Dis = Trend index deviation Dia + Trend increment deviation Dic.

[0098] S3 further includes S32;

[0099] S32. Based on the generated trend deviation value Dis, compare it with a preset deviation limit value used to distinguish between a stable trend and a downward trend, wherein the deviation limit value is defined as the deviation threshold Dst;

[0100] When the trend deviation value Dis > the deviation threshold Dst, it is determined that the degree of trend deviation has reached the condition for early flow reduction. The control system generates a set of trigger information to trigger the early flow reduction decision based on the determination result, and defines the set of trigger information as the early flow reduction trigger set Tri.

[0101] When the trend deviation value Dis ≤ the deviation threshold Dst, it is determined that the early flow reduction trigger set Tri will not be generated, and the current running state will remain unchanged.

[0102] It should be noted that:

[0103] The deviation threshold Dst is a limit quantity derived by statistically analyzing the trend deviation behavior of the power bank during stable operation: under stable operating conditions, the trend deviation values ​​Dis of multiple sampling periods are statistically analyzed; the maximum deviation value that can represent the normal deviation range is extracted as a reference; then, the deviation amount under the downward trend trigger condition is combined for differentiation; finally, it is determined as the threshold that can distinguish between stable trends and obvious downward trends.

[0104] The early current reduction trigger set Tri provides three inputs: the current determination result of when current reduction needs to be initiated, the current trend deviation degree (from the trend deviation value Dis), and the time base of the current sampling period.

[0105] In this embodiment, the load decline trend index Ldt in the trend feature set Beb and the trend increment Tic corresponding to the continuous sampling period are compared with the stable trend reference value and stable trend increment reference range in the template set Tpl to form a trend deviation value Dis, which measures the overall deviation of the trend. This allows the system to identify early trends that are declining but have not yet formed obvious current changes. For example, when a tablet computer is running a high frame rate graphics application and enters automatic power saving mode, its load will show a gradual change of "slow decline → steady → further decline" in a short period of time. Traditional judgment methods often cannot distinguish between "normal fluctuations" and "precursors of decline" due to the lack of trend boundaries, resulting in a delay in the initiation of subsequent control actions. However, by combining the trend index deviation Dia and the trend increment deviation Dic, this method can continuously quantify this gradual trend and immediately generate an early current reduction trigger set Tri in the early stage when the trend deviation value Dis exceeds the deviation threshold Dst. This achieves accurate identification of the critical trend state and avoids the common problems of blurred trend boundaries and difficulty in capturing low-amplitude declines in traditional solutions. This allows subsequent control steps to obtain accurate trend deviation input at an earlier time.

[0106] Example 5: Specifically: S4 includes S41;

[0107] S41. Based on the generated early current reduction trigger set Tri, read the trend deviation value Dis and time stamp information corresponding to the current sampling period, and use the trend deviation value Dis as the input parameter for determining the current reduction intensity; call the strategy set for executing early current reduction control from the preset power regulation strategy set for adjusting the output current, generate the strategy set Pol, and match and filter the current reduction amplitude and response speed corresponding to each regulation strategy in the strategy set Pol according to the trend deviation value Dis recorded in the early current reduction trigger set Tri, select a set of candidate regulation strategies that match the current trend deviation value Dis, and define the candidate regulation strategies as the candidate strategy set Poc.

[0108] S4 also includes S42;

[0109] S42. Analyze the current reduction amplitude parameter, current reduction change rate parameter and execution mode parameter contained in each adjustment strategy in the candidate strategy set Poc, organize the adjustment parameters in a structured manner, and use them to generate control execution instructions by the mobile power supply execution module. Define the control execution instructions as adjustment instructions Cmd.

[0110] The adjustment command Cmd is used to control the output current of the power bank to decrease in advance.

[0111] In this embodiment, after determining that there is a need for early current reduction, different adjustment strategies are intelligently matched based on the trend deviation value Dis in the early current reduction trigger set Tri, enabling the power bank to have a graded response capability when performing early current reduction control. Since this method includes multiple adjustment strategies with different current reduction amplitudes and response speeds in the strategy set Pol, and uses the trend deviation value Dis as a parameter to filter out a candidate strategy set Poc corresponding to the current deviation level, the control system can automatically select different intensity reduction methods according to different deviation levels. For example, in a mobile office scenario using a laptop, when a user suddenly switches from low-load document editing to light graphics processing, the load does not change drastically, but may be in a slight early current reduction phase. If a fixed current reduction scheme is used, unnecessary current fluctuations are likely to occur. This method automatically selects a slight early current reduction strategy based on the trend deviation value Dis, achieving finer-grained control, while in scenarios with more obvious trend deviations, a rapid current reduction strategy is selected through the candidate strategy set Poc. Subsequently, this method will parse the selected strategy to generate adjustment instructions Cmd that can be directly called by the executable module, so that the current reduction action can accurately correspond to the current trend deviation in terms of amplitude, speed and execution mode, thereby ensuring that the early current reduction process is neither excessive nor lagging, and that the output behavior is highly consistent with the real trend.

[0112] Example 6: A fast charging and discharging control system for a mobile power bank, please refer to... Figure 2 Specifically, it includes a power data acquisition module, a data cycle analysis module, a trend judgment and trigger generation module, and an adjustment command generation module;

[0113] The power data acquisition module collects instantaneous current data, instantaneous voltage data, and current change rate data during the charging and discharging process of the mobile power supply. These are defined as current data Cur, voltage data Vol, and change rate Rat, respectively, and are combined to form a real-time acquisition feature set Bea.

[0114] The data cycle analysis module performs multi-cycle analysis of current changes based on the real-time acquired feature set Bea, constructs a load decline trend index, defined as the load decline trend index Ldt, and integrates it to generate a trend feature set Beb.

[0115] The trend judgment and trigger generation module compares the trend feature set Beb with the preset template set Tpl to obtain the trend deviation value, which is defined as the trend deviation value Dis. Then, it compares it with the preset deviation threshold Dst to generate the early flow reduction trigger set Tri.

[0116] The adjustment command generation module matches the early current reduction trigger set Tri with the power regulation strategy set Pol inside the power bank to generate an early current reduction adjustment command Cmd, which controls the output current of the power bank to decrease in advance.

[0117] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for controlling the rapid charging and discharging of a mobile power bank, characterized in that: Includes the following steps: S1. Collect instantaneous current data, instantaneous voltage data, and current change rate data during the charging and discharging process of the mobile power supply, which are defined as current data Cur, voltage data Vol, and change rate Rat, respectively, and combined to form a real-time acquisition feature set Bea. S2. Based on the real-time acquired feature set Bea, perform multi-cycle analysis of current changes, construct a load decline trend index, defined as the load decline trend index Ldt, and integrate to generate a trend feature set Beb. S3. Compare the trend feature set Beb with the preset template set Tpl to obtain the trend deviation value, which is defined as the trend deviation value Dis. Then compare it with the preset deviation threshold Dst to generate the early current reduction trigger set Tri. S4. Match the early current reduction trigger set Tri with the power regulation strategy set Pol inside the power bank to generate an early current reduction regulation instruction Cmd to control the output current of the power bank to decrease in advance. S2 includes S21; S21. Based on the continuous multi-sampling period data from the real-time acquisition feature set Bea, the current data Cur and the rate of change Rat of each sampling period are sorted by time series to form a multi-cycle current change sequence. Periodic difference analysis is performed on the multi-cycle current change sequence. The change rate Rat of each sampling cycle is compared with the change trend of the adjacent cycle to construct the trend change rate within each sampling cycle interval. Then, the trend change rate is used to normalize the multi-cycle trend to obtain the trend base quantity representing the direction of load change, which is defined as the trend base quantity Tba. S2 further includes S22; S22. Based on the acquired trend baseline quantity Tba, and combined with the rate of change Rat within the same sampling period, perform trend recursion calculation. The trend recursion calculation uses the trend base quantity Tba as the basis for reflecting the historical trend direction and change magnitude within multiple sampling periods, and the change rate Rat of the same sampling period as the instantaneous quantity reflecting the dynamic change of the current sampling period. According to the preset trend accumulation rules, the weighted superposition and direction correction processing are performed to obtain the trend increment of the current sampling period, which is defined as the trend increment Tic. The trend increment Tic from multiple consecutive sampling periods is compressed in amplitude and enhanced in direction to form a trend index for representing the overall load decline trend, which is defined as the load decline trend index Ldt. Then, using the load decline trend index Ldt as the foundation, the trend base quantity Tba and trend increment Tic from the construction process are integrated to generate the trend feature set Beb.

2. The fast charging and discharging control method for a mobile power supply according to claim 1, characterized in that: S1 includes S11; S11. During the charging and discharging process of the power bank, the current and voltage at the output terminal are periodically sampled, with the period length being the default sampling period. Within each sampling period, the power bank sampling command is called to read the transient signal of the sampling node in the output circuit and obtain the instantaneous output current value corresponding to the sampling period, which is defined as current data Cur. At the same time, the instantaneous voltage value at the output terminal is synchronously obtained within the same sampling period and defined as voltage data Vol.

3. The fast charging and discharging control method for a mobile power supply according to claim 2, characterized in that: S1 further includes S12; S12. Based on the acquired current data Cur, calculate the difference between the current value in the current sampling period and the previous sampling period to obtain the change in current. Divide the change in current by the sampling period length to obtain the rate of change of current, which is defined as the rate of change Rat. The acquired current data Cur, voltage data Vol, and rate of change Rat are combined to construct a real-time feature set Bea that reflects the current output status of the power bank.

4. The fast charging and discharging control method for a mobile power supply according to claim 1, characterized in that: S3 includes S31, S31. Based on the trend feature set Beb, extract the load decline trend index Ldt and the trend increment Tic corresponding to multiple consecutive sampling periods. Then, call the stable trend model formed by statistically processing the trend data in multiple sampling periods under normal and stable operating conditions of the power bank. Define the stable trend model as a template set Tpl, where the template set Tpl includes the stable trend index reference value and the stable trend increment reference range. The load decline trend index Ldt in the trend feature set Beb and the stable trend index reference value in the template set Tpl are used to calculate the magnitude deviation and obtain the trend index deviation Dia. The deviation between the trend increment Tic of multiple consecutive sampling periods and the stable trend increment reference interval in the template set Tpl is calculated periodically to obtain the deviation amount; then the deviation amounts are accumulated to obtain the trend increment deviation amount, which is defined as the trend increment deviation amount Dic. Then, the trend index deviation Dia and the trend increment deviation Dic are numerically superimposed to form the trend deviation value Dis, which represents the overall deviation of the current power bank trend.

5. The fast charging and discharging control method for a mobile power supply according to claim 4, characterized in that: S3 further includes S32; S32. Based on the generated trend deviation value Dis, compare it with a preset deviation limit value used to distinguish between a stable trend and a downward trend, wherein the deviation limit value is defined as the deviation threshold Dst; When the trend deviation value Dis > the deviation threshold Dst, it is determined that the degree of trend deviation has reached the condition for early flow reduction. The control system generates a set of trigger information to trigger the early flow reduction decision based on the determination result, and defines the set of trigger information as the early flow reduction trigger set Tri. When the trend deviation value Dis ≤ deviation threshold Dst, it is determined that the early flow reduction trigger set Tri will not be generated, and the current running state will remain unchanged.

6. The fast charging and discharging control method for a mobile power supply according to claim 5, characterized in that: S4 includes S41; S41. Based on the generated early descent trigger set Tri, read the trend deviation value Dis and time stamp information corresponding to the current sampling period, and use the trend deviation value Dis as the input parameter for determining the descent intensity. The strategy set Pol is generated by calling the strategy set for early current reduction control from the preset power regulation strategy set for adjusting the output current. Based on the trend deviation value Dis recorded in the early current reduction trigger set Tri, the current reduction amplitude and response speed corresponding to each regulation strategy in the strategy set Pol are matched and filtered. A set of candidate regulation strategies that match the current trend deviation value Dis is selected and the candidate regulation strategies are defined as the candidate strategy set Poc.

7. The fast charging and discharging control method for a mobile power supply according to claim 6, characterized in that: S4 also includes S42; S42. Analyze the current reduction amplitude parameter, current reduction change rate parameter and execution mode parameter contained in each adjustment strategy in the candidate strategy set Poc, organize the adjustment parameters in a structured manner, and use them to generate control execution instructions by the mobile power supply execution module. Define the control execution instructions as adjustment instructions Cmd. The adjustment command Cmd is used to control the output current of the power bank to decrease in advance.

8. A fast charging and discharging control system for a mobile power bank, applied to the fast charging and discharging control method for a mobile power bank as described in any one of claims 1 to 7, characterized in that: It includes a power data acquisition module, a data cycle analysis module, a trend judgment and trigger generation module, and an adjustment command generation module; The power data acquisition module collects instantaneous current data, instantaneous voltage data, and current change rate data during the charging and discharging process of the mobile power supply. These are defined as current data Cur, voltage data Vol, and change rate Rat, respectively, and are combined to form a real-time acquisition feature set Bea. The data cycle analysis module performs multi-cycle analysis of current changes based on the real-time acquired feature set Bea, constructs a load decline trend index, defined as the load decline trend index Ldt, and integrates it to generate a trend feature set Beb. The trend judgment and trigger generation module compares the trend feature set Beb with the preset template set Tpl to obtain the trend deviation value, which is defined as the trend deviation value Dis. Then, it compares it with the preset deviation threshold Dst to generate the early flow reduction trigger set Tri. The adjustment command generation module matches the early current reduction trigger set Tri with the power regulation strategy set Pol inside the power bank to generate an early current reduction adjustment command Cmd, which controls the output current of the power bank to decrease in advance.

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