A terminal device battery unusable capacity calibration method, device and terminal device

Abstract

The application belongs to the technical field of battery management, and discloses a terminal device battery unusable capacity calibration method, device and terminal device, which comprises the following steps: in a plurality of continuous judgment periods, the current voltage and average voltage of the terminal device battery are obtained; if both are less than a preset voltage threshold, a calibration process is started; the open circuit voltage of the battery is calculated according to the latest collected current voltage and real-time discharge current, and a reference power value is obtained; the difference between the remaining capacity and the reference power value is calculated, and the difference in the plurality of continuous judgment periods is filtered to obtain a smooth difference value; a weight factor is calculated based on the current voltage, a preset shutdown voltage and the preset voltage threshold; the current estimated unusable capacity is dynamically corrected according to the smooth difference value and the weight factor, and the calibrated unusable capacity is obtained; and the available power of the terminal device is calculated and output according to the calibrated unusable capacity and the remaining capacity. The application can improve the accuracy of the unusable capacity.

Description

Technical Field

[0001] This invention belongs to the field of battery management technology, and specifically relates to a method, device, and terminal device for calibrating the unusable capacity of a terminal device's battery. Background Technology

[0002] The accuracy of battery level displays is always a major concern for end users, especially mobile phone users. Inaccurate battery levels prevent users from accurately estimating how long the phone will last, causing it to run out of power and shut down unexpectedly. Inaccurate battery levels can also cause the battery's shutdown voltage to drop, potentially leading to the system operating for extended periods in unexpectedly low-performance or unsafe low-voltage ranges. Furthermore, inaccurate battery levels can cause the phone to prematurely report 0% battery and shut down, further reducing usage time. All of these issues can cause unnecessary inconvenience for users trying to use their phones normally.

[0003] One of the key existing technologies for lithium-ion battery capacity display is the coulomb meter + OCV curve-based capacity display scheme. The discharge capacity of a lithium-ion battery decreases with varying temperature and discharge rate; this lost capacity is called unusable capacity and is not a fixed value. Current methods for estimating unusable capacity rely on modeling the OCV-SOC curve and modeling or learning the internal resistance RBAT curve, combined with the current discharge temperature and discharge current. However, the unusable capacity is subject to errors due to the influence of modeled internal resistance, current, voltage, battery temperature, battery consistency, and impedance calculation models, and these errors cannot be completely eliminated. Summary of the Invention

[0004] The purpose of this invention is to provide a high-precision, high-reliability power calibration scheme with a good user experience, which effectively solves the problem of decreased accuracy caused by inaccurate estimation of unavailable capacity at the end of the discharge in existing lithium battery power estimation schemes.

[0005] In a first aspect, embodiments of the present invention provide a method for calibrating the unusable capacity of a terminal device battery, the method comprising:

[0006] Within multiple consecutive judgment cycles, obtain the current voltage and average voltage of the terminal device's battery;

[0007] If, within any judgment period, both the current voltage and the average voltage are less than a preset voltage threshold, then the unusable capacity calibration process is initiated.

[0008] In the calibration process, based on the latest collected current voltage and real-time discharge current, the open-circuit voltage of the battery is calculated based on the battery internal resistance model, and the pre-stored OCV value and the corresponding curve of the SOC value are queried to obtain the reference charge value.

[0009] The difference between the remaining capacity estimated by the battery power algorithm and the baseline power value is calculated, and the difference is filtered for multiple consecutive judgment periods to obtain a smooth difference.

[0010] Based on the current voltage, the preset shutdown voltage, and the preset voltage threshold, a weighting factor is calculated using a linear interpolation formula. The weighting factor is used to characterize the normalized relative position of the current voltage within the interval defined by the preset shutdown voltage and the preset threshold voltage. The value of the weighting factor is the proportion of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. The larger the value of the weighting factor, the lower the system's confidence in the smoothed difference. The two are inversely proportional.

[0011] Based on the smoothing difference and the weighting factor, the currently estimated unavailable capacity is dynamically corrected to obtain the calibrated unavailable capacity;

[0012] Based on the calibrated unavailable capacity and the remaining capacity, the available power of the terminal device is calculated and output.

[0013] Optionally, the values ​​of the preset voltage threshold and the preset shutdown voltage are both determined based on the real-time temperature of the battery.

[0014] The preset voltage threshold and the preset shutdown voltage are dynamically adjusted according to different battery characteristics and system design requirements, as the battery temperature changes.

[0015] Optionally, after filtering the differences across multiple consecutive judgment periods to obtain smoothed differences, the method further includes:

[0016] Determine whether the absolute value of the smoothed difference is less than a first preset threshold;

[0017] If the absolute value of the smoothed difference is less than the first preset threshold, the calibration operation is abandoned.

[0018] Optionally, after filtering the differences across multiple consecutive judgment periods to obtain smoothed differences, the method further includes:

[0019] Determine whether the rate of change of the smoothed difference in the current judgment period and the smoothed difference in the previous judgment period is subject to a preset rate of change threshold.

[0020] If the rate of change exceeds the preset rate of change threshold, the following limiting operations are performed sequentially:

[0021] The smoothed difference is subjected to a first amplitude limiting process;

[0022] The theoretical correction value for unavailable capacity is calculated based on the smoothed difference after the first clipping process;

[0023] The theoretical correction value is subjected to a second limiting process to ensure that the absolute value of the difference between the unavailable capacity after calibration and the unavailable capacity before calibration is not greater than the maximum change limit.

[0024] Optionally, the dynamic correction process is gradual;

[0025] The system maintains the cumulative value of errors to be compensated;

[0026] In each judgment period, the original difference value calculated in the current period, or the original difference value after amplitude limiting, is added to the cumulative value of the error to be compensated in the previous period, so as to update the cumulative value of the error to be compensated in the current period.

[0027] In each judgment period, a portion of the value is taken from the cumulative value of the error to be compensated according to the weighting factor to achieve the calibration of the available capacity, and the size of the taken value is limited by the maximum change limit.

[0028] Optionally, the step of calculating the weighting factor based on the current voltage, the preset shutdown voltage, and the preset voltage threshold using a linear interpolation formula includes:

[0029] The weighting factor is calculated using the following linear interpolation formula:

[0030] Weight=(VBAT_NOW–VBAT_ZP) / (VTH–VBAT_ZP);

[0031] Wherein, Weight represents the weighting factor, VBAT_NOW represents the current voltage, VBAT_ZP represents the preset shutdown voltage, and VTH represents the preset voltage threshold.

[0032] Optionally, the step of dynamically correcting the currently estimated unavailable capacity based on the smoothing difference and the weighting factor to obtain the calibrated unavailable capacity includes:

[0033] NEW_UUSOC=UUSOC+(1–Weight)*delta_soc_avg;

[0034] Where NEW_UUSOC is the calibrated unavailable capacity, UUSOC is the currently estimated unavailable capacity, and delta_soc_avg is the smoothed difference.

[0035] Secondly, embodiments of the present invention provide a terminal device battery unusable capacity calibration device, the device comprising:

[0036] The voltage acquisition module is used to acquire the current voltage and average voltage of the terminal device's battery within multiple consecutive judgment cycles.

[0037] The calibration process initiation module is used to initiate an unusable capacity calibration process if both the current voltage and the average voltage are less than a preset voltage threshold within any judgment period.

[0038] The reference charge value acquisition module is used in the calibration process to calculate the open circuit voltage of the battery based on the latest collected current voltage and real-time discharge current, and to query the pre-stored correspondence curve between OCV value and SOC to obtain the reference charge value.

[0039] The smoothing difference calculation module is used to calculate the difference between the remaining capacity estimated by the battery power algorithm and the reference power value, and to filter the difference for multiple consecutive judgment periods to obtain a smoothing difference.

[0040] The weight factor calculation module is used to calculate the weight factor based on the current voltage, the preset shutdown voltage, and the preset voltage threshold using a linear interpolation formula. The weight factor is used to characterize the normalized relative position of the current voltage within the interval defined by the preset shutdown voltage and the preset threshold voltage. The value of the weight factor is the proportion of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. The larger the value of the weight factor, the lower the system's confidence in the smoothed difference. The two are inversely proportional.

[0041] The unavailable capacity correction module is used to dynamically correct the currently estimated unavailable capacity based on the smoothing difference and the weighting factor to obtain the calibrated unavailable capacity.

[0042] The available capacity calculation module is used to calculate and output the available power of the terminal device based on the calibrated unavailable capacity and the remaining capacity.

[0043] Optionally, the values ​​of the preset voltage threshold and the preset shutdown voltage are both determined based on the real-time temperature of the battery.

[0044] The preset voltage threshold and the preset shutdown voltage are dynamically adjusted according to different battery characteristics and system design requirements, as the battery temperature changes.

[0045] Thirdly, embodiments of the present invention provide a terminal device, including:

[0046] At least one processor;

[0047] Memory for storing the at least one processor-executable instruction;

[0048] The at least one processor is configured to execute the instructions to implement the method described in the first aspect.

[0049] Fourthly, embodiments of the present invention provide a computer-readable storage medium that, when instructions in the computer-readable storage medium are executed by a processor of a terminal device, enables the terminal device to perform the method described in the first aspect.

[0050] The terminal device battery unusable capacity calibration method provided in this invention, by introducing a voltage-based dynamic feedback calibration mechanism, achieves the following significant advantages compared to existing technologies:

[0051] 1. This invention effectively improves the accuracy of battery capacity estimation in the low-charge range, especially near the critical stage of the shutdown voltage, while ensuring the smoothness of the capacity display throughout the discharge process and allowing errors to be released steadily. This invention introduces a baseline capacity value (VBAT_SOC) based on real-time voltage and current back-calculation as a calibration benchmark in the range close to the shutdown voltage, and dynamically corrects the unusable capacity (UUSOC), effectively eliminating UUSOC estimation deviations caused by model errors, temperature changes, current fluctuations, and other factors. This ensures that when the device discharges to the preset shutdown voltage, the remaining capacity (RM_SOC) is exactly equal to the unusable capacity (UUSOC), achieving precise shutdown with BATT_SOC=0, fundamentally solving the problem of "early shutdown" or "sudden shutdown" caused by inaccurate capacity estimation.

[0052] 2. Enhanced reliability and user trust in battery level display. By employing a dual-voltage condition triggering mechanism (both current and average voltages are below a threshold) combined with a multi-cycle judgment mechanism, voltage fluctuations caused by instantaneous load changes are effectively filtered out, preventing accidental triggering of the calibration process and ensuring the accuracy and reliability of the calibration operation. This makes the final displayed available battery level (BATT_SOC) more realistic and reliable, allowing users to accurately estimate device battery life and improving the user experience.

[0053] 3. A smooth and stable calibration process is achieved. By introducing a weighting factor and establishing an inverse relationship between it and the degree of trust in the smooth difference, this method achieves intelligent dynamic adjustment of the calibration intensity. In the high-voltage range, the calibration intensity is gentle, mainly relying on traditional algorithms; as the voltage decreases, the trust in the voltage feedback value is gradually increased, enhancing the calibration intensity. This calibration strategy, which smoothly transitions with voltage, avoids abrupt changes in the power display, ensuring the stability of the calibration process and a smooth visual experience.

[0054] In summary, this invention effectively solves the problem of decreased accuracy caused by inaccurate estimation of unavailable capacity at the end of discharge in existing lithium battery power estimation schemes, and provides a power calibration scheme with high accuracy, high reliability and good user experience. Attached Figure Description

[0055] Figure 1 A flowchart of a method for calibrating the unusable capacity of a terminal device battery provided in an embodiment of the present invention;

[0056] Figure 2 This diagram illustrates the problems encountered in the uncalibrated state of existing technologies.

[0057] Figure 3 To and Figure 2 The illustrated embodiment demonstrates the effect of applying the unavailable capacity calibration method provided by this invention under the same operating conditions.

[0058] Figure 4 This is a schematic diagram of the dynamic calibration process provided in an embodiment of the present invention;

[0059] Figure 5 This is a schematic diagram of a terminal device battery unusable capacity calibration device provided in an embodiment of the present invention;

[0060] Figure 6 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0061] The present invention will be described in detail below through embodiments.

[0062] The accuracy of battery level displays is always a major concern for end users, especially mobile phone users. Inaccurate battery levels prevent users from accurately estimating how long the phone will last, causing it to run out of power and shut down unexpectedly. Inaccurate battery levels can also cause the battery's shutdown voltage to drop, potentially leading to the system operating for extended periods in unexpectedly low-performance or unsafe low-voltage ranges. Furthermore, inaccurate battery levels can cause the phone to prematurely report 0% battery and shut down, further reducing usage time. All of these issues can cause unnecessary inconvenience for users trying to use their phones normally.

[0063] One of the key existing technologies for lithium battery capacity display is the coulomb meter + OCV curve-based capacity display scheme. The discharge capacity of a lithium battery is reduced with varying temperature and discharge rate; this lost capacity is called unusable capacity and is not a fixed value. Current methods for estimating unusable capacity rely on modeling the OCV-SOC curve and modeling or learning the internal resistance RBAT curve, combined with the current discharge temperature and discharge current. Influenced by the modeled internal resistance, current, voltage, battery temperature, battery consistency, and impedance calculation model, errors in unusable capacity estimation exist and cannot be completely eliminated. These errors are particularly severe in high energy density regions, low-temperature environments, and high-current discharge scenarios, leading to inaccurate capacity readings. Therefore, this invention provides a method for calibrating the unusable capacity of a terminal device battery to address the problem of large estimation errors in unusable capacity.

[0064] Taking a mobile phone with a preset shutdown voltage of 3.4V as an example, its lithium battery capacity is typically estimated using a coulomb counter combined with an open-circuit voltage (OCV) curve, and this shutdown voltage is used to estimate the baseline point of 0% capacity. However, the actual discharge capacity of the battery is significantly affected by factors such as temperature and discharge rate, causing the OCV voltage corresponding to the true 0% capacity to be not constant. Therefore, the 0% capacity position estimated based on the model will continue to fluctuate.

[0065] Due to factors such as impedance accuracy, temperature measurement errors, voltage and current sampling deviations, and modeling limitations, the 0% battery level estimated by the battery power algorithm that integrates coulomb measurement and OCV curves often deviates from the actual physical voltage. This can lead to two abnormal situations. One situation is that when the system reports 0% battery level, the actual battery voltage is much higher than 3.4V, causing the low battery display period to last too long or the device to shut down prematurely, thus shortening the user's perceived battery life. The other situation is that when the system reports 0% battery level, the actual voltage is already significantly lower than 3.4V, causing the terminal device to shut down suddenly without warning, or causing system instability due to insufficient battery voltage.

[0066] The core of this invention lies in introducing the battery terminal real-time voltage (VBAT) parameter for dynamic calibration on the basis of the traditional unusable capacity (UUSOC) estimation scheme that combines coulomb counting and OCV curve. This aims to ensure that when the battery discharges to the preset shutdown voltage, the remaining capacity (RM_SOC) calculated by the algorithm is consistent with the unusable capacity (UUSOC), thereby significantly improving the accuracy of power estimation at the end of the discharge.

[0067] The basic theories involved in the embodiments of the present invention will be introduced below.

[0068] In existing battery capacity estimation systems, the usable capacity (BATT_SOC) ultimately displayed to the user is generally calculated using the formula BATT_SOC = RM_SOC – UUSOC. Here, RM_SOC (Remaining State of Charge) represents the theoretical total remaining battery capacity estimated by methods such as coulomb counting, while UUSOC (Unusable State of Charge) represents the unusable capacity that cannot be released under specific operating conditions.

[0069] The core expectation of this theoretical model is that when the battery continues to discharge to a preset hardware shutdown voltage (e.g., 3.4V), the available capacity BATT_SOC should drop exactly to 0%, meaning that the terminal device will exhaust its last unit of available power and shut down. Substituting this expectation (BATT_SOC=0) into the above formula, it can be derived that under ideal and accurate estimation conditions, the theoretical total remaining capacity of the battery should be exactly equal to the unavailable capacity, that is, the equation RM_SOC=UUSOC must be satisfied.

[0070] However, in practical applications, the estimation of UUSOC is easily affected by factors such as temperature, current, battery aging, and model errors, making accurate calculation difficult. This often results in RM_SO not equaling UUSOC when actually discharged to the shutdown voltage, leading to problems such as premature shutdown or distorted power display. The core objective of this invention is to introduce a voltage feedback calibration mechanism to ensure that the critical condition of RM_SOC = UUSOC is met at the end of discharge, thereby fundamentally guaranteeing power accuracy.

[0071] The following will provide a detailed description of a terminal device battery unusable capacity calibration method provided by an embodiment of the present invention.

[0072] It should be noted that the terminal device battery unusable capacity calibration method provided in this embodiment of the invention can be applied to terminal devices that use lithium batteries, such as smartphones, tablets, and wearable devices.

[0073] like Figure 1 As shown in the figure, a method for calibrating the unusable capacity of a terminal device battery provided by an embodiment of the present invention may include the following steps:

[0074] S110: During multiple consecutive judgment cycles, the current voltage and average voltage of the terminal device's battery are obtained.

[0075] In this step, the system dynamically acquires the battery voltage parameters of the terminal device over multiple consecutive judgment cycles. Specifically, the power management unit acquires the current battery voltage (VBAT_NOW) in real time at a fixed sampling frequency (e.g., once per second), which represents the instantaneous terminal voltage of the battery under load. Simultaneously, the system performs arithmetic averaging or low-pass filtering on multiple recently acquired voltage values ​​to calculate the average voltage (VBAT_AVG). This average voltage is used to eliminate voltage spikes and drastic fluctuations caused by instantaneous load changes (such as starting an application processor core), thereby more stably reflecting the overall trend of battery voltage changes. The specific length of the judgment cycle and the size of the averaging algorithm window can be configured according to actual needs; for example, it can be set to 5 consecutive cycles, each cycle being 1 second. This embodiment of the invention does not impose specific limitations on this.

[0076] S120: If the current voltage and the average voltage are both less than the preset voltage threshold in any judgment period, then the unusable capacity calibration process is started.

[0077] This step is the condition determination step for starting the calibration process. Within any given determination period, the system compares the real-time acquired current voltage (VBAT_NOW) and average voltage (VBAT_AVG) with a preset voltage threshold (VTH). One of the trigger conditions is met only when both the current voltage and average voltage are less than the preset voltage threshold. To ensure the stability of the trigger signal and prevent false triggering, this condition typically needs to be met continuously for multiple determination periods (e.g., three consecutive periods). This effectively filters out brief voltage drops caused by instantaneous high current loads. Only when the above condition is met will the system initiate the subsequent Unusable Capacity (UUSOC) calibration process. The preset voltage threshold (VTH) is not a fixed value; it is preferably dynamically adjusted based on the battery temperature, which can be obtained through a pre-stored temperature-voltage lookup table.

[0078] S130, in the calibration process, calculates the battery's open-circuit voltage based on the latest collected current voltage and real-time discharge current, using the battery internal resistance model, and queries the pre-stored OCV value and the corresponding curve of the SOC value to obtain the reference capacity value.

[0079] After the calibration process is initiated, the system performs this step to obtain a reliable voltage reference charge value. First, the system synchronously acquires the latest current voltage (VBAT_NOW) and real-time discharge current (IBAT). Next, based on a pre-established and stored battery internal resistance model, compensation calculations are performed on the current voltage. Specifically, according to Ohm's law, the current open-circuit voltage (OCV) of the battery is estimated using the formula OCV = VBAT_NOW + IBAT * R, where R is the battery internal resistance determined based on the model and temperature. Finally, by querying the pre-stored open-circuit voltage-charge (OCV-SOC) correspondence curve, the reference charge value (VBAT_SOC) corresponding to the current moment can be mapped to. Because this reference charge value is directly derived from the real-time measured voltage parameters, it more accurately reflects the physical state of the battery.

[0080] S140: Calculate the difference between the remaining capacity estimated by the battery power algorithm and the baseline power value, and filter the difference over multiple consecutive judgment periods to obtain a smooth difference.

[0081] This step aims to obtain a stable and reliable error signal. First, the difference (delta_soc) between the remaining capacity (RM_SOC) estimated by the battery power algorithm (such as the coulomb counting method) and the reference capacity value (VBAT_SOC) obtained in step S130 is calculated, i.e., delta_soc = RM_SOC - VBAT_SOC. This difference initially reflects the deviation between the algorithm's estimate and the voltage reference value. Subsequently, the difference (delta_soc) calculated over multiple consecutive judgment periods (e.g., the past 10 periods) is filtered. This filtering process can employ algorithms such as moving average, weighted average, or low-pass filtering to smooth out high-frequency noise and abnormal fluctuations in the data, ultimately outputting a smoothed difference (delta_soc_avg) that represents the trend deviation.

[0082] S150 calculates the weighting factor using a linear interpolation formula based on the current voltage, the preset shutdown voltage, and the preset voltage threshold.

[0083] The weighting factor is used to characterize the normalized relative position of the current voltage within the interval defined by the preset shutdown voltage and the preset threshold voltage, and indicates the degree of confidence in the smoothed difference. The weighting factor is inversely proportional to the degree of confidence. The value of the weighting factor is the proportion of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. The larger the value of the weighting factor, the lower the degree of confidence the system has in the smoothed difference. The two are inversely proportional.

[0084] This step is crucial for achieving intelligent dynamic calibration in this invention. The weighting factor is calculated based on the current voltage (VBAT_NOW), the preset shutdown voltage (VBAT_ZP) (e.g., 3.4V), and the preset voltage threshold (VTH). It is calculated using the following linear interpolation formula:

[0085] Weight=(VBAT_NOW–VBAT_ZP) / (VTH–VBAT_ZP).

[0086] This weighting factor has clear physical and logical meanings, as follows:

[0087] 1. This weighting factor is used to characterize the relative position of the current voltage within the interval defined by the preset shutdown voltage and the preset threshold voltage. When VBAT_NOW is close to VTH, the weight value approaches 1; when VBAT_NOW is close to VBAT_ZP, the weight value approaches 0.

[0088] 2. This weighting factor indicates the degree of trust in the smoothed difference, and the value of this weighting factor is inversely proportional to the degree of trust. The larger the weight value (the higher the voltage), the more the system trusts the original algorithm model, and the lower the trust in the smoothed difference (delta_soc_avg) obtained by voltage back-calculation; conversely, the smaller the weight value (the lower the voltage, the closer to the preset shutdown voltage), the higher the system's trust in the voltage back-calculation value, and the more necessary it is to correct unavailable capacity based on this value.

[0089] S160, based on the smoothing difference and weighting factor, dynamically corrects the currently estimated unavailable capacity to obtain the calibrated unavailable capacity.

[0090] In this step, the system dynamically corrects the currently estimated unavailable capacity (UUSOC) based on the smoothing difference (delta_soc_avg) and the weighting factor (Weight) to obtain the calibrated unavailable capacity (NEW_UUSOC). The correction formula is as follows:

[0091] NEW_UUSOC=UUSOC+(1–Weight)*delta_soc_avg.

[0092] This formula embodies the concepts of dynamism and weighting: (1 – Weight) represents the confidence coefficient for the smoothed difference. The lower the voltage (the smaller the Weight), the larger the confidence coefficient, and the greater the contribution of the smoothed difference to the final correction, thus strengthening the calibration. Furthermore, to prevent abrupt changes in displayed power, it is preferable to limit the magnitude of a single correction (i.e., amplitude limiting) to ensure that the change within a single cycle does not exceed a preset maximum change threshold. For clarity, the specific implementation of dynamic correction of unavailable capacity will be described in detail in the following embodiments.

[0093] S170 calculates and outputs the available power of the terminal device based on the calibrated unavailable capacity and remaining capacity.

[0094] Specifically, the system substitutes the calibrated unavailable capacity (NEW_UUSOC) obtained in step S160 into the basic power calculation formula:

[0095] BATT_SOC = RM_SOC - NEW_UUSOC.

[0096] The calculated BATT_SOC is the high-precision available battery power after unavailable capacity calibration. This battery power value is output to the operating system and user interface (UI) for final display to the user, thereby enabling accurate prediction of the terminal device's battery life and avoiding unpleasant experiences such as premature or sudden shutdown.

[0097] The terminal device battery unusable capacity calibration method provided in this invention, by introducing a voltage-based dynamic feedback calibration mechanism, achieves the following significant advantages compared to existing technologies:

[0098] 1. This invention effectively improves the accuracy of battery capacity estimation in the low-charge range, especially near the critical stage of the shutdown voltage, while ensuring the smoothness of the capacity display throughout the discharge process and allowing errors to be released steadily. This invention introduces a baseline capacity value (VBAT_SOC) based on real-time voltage and current back-calculation as a calibration benchmark in the range close to the shutdown voltage, and dynamically corrects the unusable capacity (UUSOC), effectively eliminating UUSOC estimation deviations caused by model errors, temperature changes, current fluctuations, and other factors. This ensures that when the device discharges to the preset shutdown voltage, the remaining capacity (RM_SOC) is exactly equal to the unusable capacity (UUSOC), achieving precise shutdown with BATT_SOC=0, fundamentally solving the problem of "early shutdown" or "sudden shutdown" caused by inaccurate capacity estimation.

[0099] 2. Enhanced reliability and user trust in battery level display. By employing a dual-voltage condition triggering mechanism (both current and average voltages are below a threshold) combined with a multi-cycle judgment mechanism, voltage fluctuations caused by instantaneous load changes are effectively filtered out, preventing accidental triggering of the calibration process and ensuring the accuracy and reliability of the calibration operation. This makes the final displayed available battery level (BATT_SOC) more realistic and reliable, allowing users to accurately estimate device battery life and improving the user experience.

[0100] 3. A smooth and stable calibration process is achieved. By introducing a weighting factor and establishing an inverse relationship between it and the degree of trust in the smooth difference, this method achieves intelligent dynamic adjustment of the calibration intensity. In the high-voltage range, the calibration intensity is gentle, mainly relying on traditional algorithms; as the voltage decreases, the trust in the voltage feedback value is gradually increased, enhancing the calibration intensity. This calibration strategy, which smoothly transitions with voltage, avoids abrupt changes in the power display, ensuring the stability of the calibration process and a smooth visual experience.

[0101] In summary, this invention effectively solves the problem of decreased accuracy caused by inaccurate estimation of unavailable capacity at the end of discharge in existing lithium battery power estimation schemes, and provides a power calibration scheme with high accuracy, high reliability and good user experience.

[0102] Building upon the above embodiments, to ensure the smoothness of the calibration process and avoid user confusion caused by sudden changes in displayed battery level (UI SOC) due to abrupt shifts in unavailable capacity (UUSOC), this invention provides two preferred implementation methods for limiting the calibration range. Those skilled in the art will understand that these two methods can be implemented individually or in combination.

[0103] As one implementation of this invention, after filtering the differences of multiple consecutive judgment periods to obtain smooth differences, the method may further include the following steps:

[0104] Determine whether the rate of change of the smoothed difference in the current judgment period compared to the smoothed difference in the previous judgment period is subject to a preset rate of change threshold.

[0105] If the rate of change exceeds the preset rate of change threshold, the following limiting operations will be performed sequentially:

[0106] The smoothed difference is subjected to the first amplitude limiting process.

[0107] The theoretical correction value for unavailable capacity is calculated based on the smoothed difference after the first clipping process.

[0108] A second limiting process is applied to the theoretical correction value to ensure that the absolute value of the difference between the unavailable capacity after calibration and the unavailable capacity before calibration is not greater than the maximum variation limit.

[0109] This implementation introduces a rate-of-change limiting mechanism, the core purpose of which is to identify and suppress abnormal error signals caused by drastic load changes, ensuring that the calibration system only responds to stable, trending errors.

[0110] Specifically, the rate of change can be calculated in the following way:

[0111] Rate of change = (Smoothing error of the current period - Smoothing error of the previous period) / Duration of the judgment period

[0112] The system compares the calculated rate of change with a preset rate of change threshold. This preset rate of change threshold is usually set to a small value, for example, 0.5% per second. Its specific value can be adjusted according to the system stability and response speed requirements. This embodiment of the invention does not impose a specific limitation on the preset rate of change threshold.

[0113] When the rate of change exceeds a preset threshold, it indicates an abnormal jump in the smoothing difference, which is usually caused by a sharp voltage drop due to a sudden large current load (such as an application processor being instantly fully loaded). This type of signal is interference rather than a true trend in power estimation error. Directly applying this abnormal value for calibration will disrupt the continuity of the power display.

[0114] At this point, the system does not completely abandon calibration, but instead executes a two-stage limiting protection strategy: First, it limits the smoothed difference itself to suppress anomalous jumps; then, it calculates the theoretical correction value for unavailable capacity based on the limited smoothed difference, and again limits the magnitude of the unavailable capacity change caused by this correction value, ensuring that the absolute value of the difference between unavailable capacity before and after calibration never exceeds the set maximum change limit. In other words, it ensures that:

[0115] |NEW_UUSOC- UUSOC|≤MAX_DELTA_UUSOC

[0116] The maximum change limit (MAX_DELTA_UUSOC) is a value much smaller than the possible abnormal fluctuations, such as 0.5% of the battery level. This limiting operation can restrict unpredictable large value changes to a range that is acceptable to the system and imperceptible to the user.

[0117] The beneficial effects of this implementation method are that it effectively filters out transient interference while retaining the ability to continue tracking the true error trend. This avoids completely missing necessary calibration opportunities due to misjudgment and thoroughly prevents sudden jumps in the displayed power value, ultimately achieving high robustness in the calibration process and high smoothness in the displayed power level.

[0118] exist Figure 1 Based on the illustrated embodiment, as one implementation of the present invention, the values ​​of the preset voltage threshold and the preset shutdown voltage are both determined based on the real-time temperature of the battery.

[0119] Among them, the preset voltage threshold and preset shutdown voltage are dynamically adjusted according to the battery temperature, based on different battery characteristics and system design requirements.

[0120] As an alternative approach, a first mapping relationship between battery temperature and a preset voltage threshold, and a second mapping relationship between battery temperature and a preset shutdown voltage are predetermined. In the first mapping relationship, the preset voltage threshold decreases as the battery temperature decreases, and in the second mapping relationship, the preset shutdown voltage decreases as the battery temperature decreases.

[0121] As an important implementation of this invention, the preset voltage threshold (VTH) and preset shutdown voltage (VBAT_ZP) are not fixed values, but rather functions of battery temperature. This will be explained in the following aspects.

[0122] Firstly, the mapping relationships are established. Two mapping relationships are determined and stored beforehand through battery testing. The first mapping relationship defines the correspondence between battery temperature and a preset voltage threshold (VTH). The second mapping relationship defines the correspondence between battery temperature and a preset shutdown voltage (VBAT_ZP).

[0123] Secondly, the characteristics of the mapping relationship. The two mapping relationships described above have the following key characteristics: In the first mapping relationship, the preset voltage threshold (VTH) decreases as the battery temperature decreases. In the second mapping relationship, the preset shutdown voltage (VBAT_ZP) also decreases as the battery temperature decreases.

[0124] Thirdly, the working principle and beneficial effects. This implementation method is based on the electrochemical characteristics of lithium batteries. In low-temperature environments, the battery's internal resistance increases significantly, resulting in a more drastic drop in the battery's terminal voltage (VBAT) under the same load current.

[0125] If VTH remains constant, the voltage will drop below the threshold prematurely at low temperatures, causing the calibration process to be triggered too early, before the algorithm model has generated significant errors. By appropriately reducing VTH as the temperature decreases, the calibration triggering time can be delayed, allowing it to more accurately enter the low-power range where calibration is truly needed. This avoids unnecessary early calibration operations and improves algorithm efficiency.

[0126] Furthermore, at low temperatures, the actual usable energy of the battery decreases due to the significant internal resistance voltage drop. Maintaining a high fixed shutdown voltage (e.g., a constant 3.4V) would cause the device to shut down prematurely with a considerable amount of unused chemical energy, shortening the perceived battery life. By appropriately lowering the shutdown voltage threshold at low temperatures, the battery life of the terminal device can be extended while ensuring battery safety. This adjustment ensures that the system can accurately define the physical point of 0% charge while discharging the battery as much as possible at different temperatures.

[0127] Fourthly, in practical implementation, the above mapping relationship is stored in the device memory in the form of a lookup table. The system monitors the battery temperature in real time and uses this information to look up the corresponding VTH and VBAT_ZP values ​​at the current temperature, which are then used for subsequent trigger judgment and weight factor calculation.

[0128] As an alternative approach, a third mapping relationship between battery temperature and a preset voltage threshold, and a fourth mapping relationship between battery temperature and a preset shutdown voltage are predetermined. In the third mapping relationship, the preset voltage threshold increases as the battery temperature decreases, and in the fourth mapping relationship, the preset shutdown voltage increases as the battery temperature decreases.

[0129] When the system design prioritizes operational stability and avoids unexpected shutdowns, the preset voltage threshold (VTH) and preset shutdown voltage (VBAT_ZP) can be increased accordingly as the battery temperature decreases to cope with the possible instantaneous voltage drop under low temperature and high current load, thus reserving sufficient buffer space for the system voltage.

[0130] Those skilled in the art can determine the specific mapping function or lookup table through experiments based on the actual application scenario.

[0131] exist Figure 1 Based on the illustrated embodiment, as an implementation of this invention, after filtering the differences of multiple consecutive judgment periods to obtain smoothed differences, the method may further include the following steps:

[0132] Determine whether the absolute value of the smoothed difference is less than a first preset threshold.

[0133] If the absolute value of the smoothed difference is less than the first preset threshold, the calibration operation is abandoned.

[0134] Specifically, the system compares the absolute value of the smoothed difference (delta_soc_avg) with a first preset threshold. If the absolute value of the smoothed difference is less than the first preset threshold, it indicates that the deviation between the remaining capacity (RM_SOC) estimated by the current algorithm and the voltage reference value (VBAT_SOC) is very small and within an acceptable error range. In this case, initiating the calibration process is not very meaningful. Therefore, the system abandons this calibration operation, maintains the currently estimated unavailable capacity (UUSOC) unchanged, and exits this round of calibration process.

[0135] The first preset threshold can be configured according to the actual application scenario and accuracy requirements, and is usually set to a small value, such as 1% of the battery level.

[0136] This implementation method prevents over-calibration and noise interference. Specifically, minute deviations may originate from measurement noise, sampling errors, or minor instantaneous fluctuations, rather than actual model errors. Responding to such minute deviations could introduce unnecessary calibration operations, causing slight fluctuations in the power display and compromising stability. Ignoring minute errors ensures that calibration is only performed on significant, trend-based deviations, greatly enhancing the algorithm's robustness against interference. Furthermore, after identifying a small error, subsequent steps such as weight calculation and correction value calculation are skipped, reducing the processor's computational burden and saving system power consumption.

[0137] To more intuitively demonstrate the technical effects of this invention, the following will be described in conjunction with the accompanying drawings. Figures 2 to 4 This will be illustrated through a specific embodiment.

[0138] This embodiment compares the performance of the proposed solution (with calibration enabled) and the traditional solution (without calibration enabled) under a specific low-temperature, high-current discharge scenario. During the test, approximately 5% unusable capacity (UUSOC) estimation error was artificially introduced into the algorithm (i.e., unusable capacity was overestimated). The test also included 4% hidden capacity (HID_SOC) to simulate problems caused by model inaccuracies in real-world environments.

[0139] like Figure 2 The image shows the problem when the calibration is not performed.

[0140] Figure 2 The horizontal axis represents time, the left vertical axis represents battery charge in percentage (%), and the measurement accuracy is 0.1%; the right vertical axis represents battery voltage in volts (V). Figure 2 The test results are analyzed as follows:

[0141] 1. Premature shutdown and incorrect battery estimation. For example... Figure 2 As shown, when the battery voltage (VBAT) drops to approximately 3.70V, the system's calculated available capacity (BATT SOC) has decreased to 0%, triggering a low-battery shutdown process. However, the theoretical total remaining capacity (RM SOC) estimated internally by the algorithm at this point is far from exhausted. Figure 2 The label indicates that the RM_SOC value when the battery reports 0% charge indicates that, theoretically, there is still a considerable amount of remaining capacity inside the battery at the moment when it reports 0% charge.

[0142] 2. Actual Battery Life Loss. To verify this error, the test was not immediately terminated after the system reported 0% battery level; instead, the discharge was bypassed and continued. The results showed that the battery could still discharge 15% of its capacity after reporting 0% without calibration. This means that due to an inaccurate estimation of Unusable Usable Capacity (UUSOC) (significantly overestimated in this case), the device prematurely terminated operation while the battery still had 15% usable capacity, resulting in a significant loss of battery life and severely impacting the user experience.

[0143] 3. Disconnect between voltage and capacity. As can be seen from the curve, at the end of the discharge process, the decreasing trend of voltage (VBAT) is not synchronized with the decreasing trend of usable capacity (which can be called BATT SOC). The capacity display shows zero, but the battery voltage is still significantly higher than the final shutdown voltage threshold. This proves that traditional solutions cannot guarantee accurate zeroing of capacity at the preset physical shutdown voltage point.

[0144] This embodiment clearly reveals the core flaws of existing power estimation schemes. Since unavailable capacity (UUSOC) is a dynamic variable affected by factors such as temperature, current, and aging, estimating it using a fixed or inaccurate model will inevitably introduce significant errors under specific operating conditions. For example... Figure 2 As shown, this error directly manifests as a serious premature shutdown problem, causing the device to be unable to utilize the full energy of the battery and shortening the user's actual usage time.

[0145] This comparative example provides a clear practical basis and motivation for proposing the solution of the present invention. It is precisely to overcome the above-mentioned shortcomings that the present invention proposes a dynamic calibration scheme based on voltage feedback to ensure that, under any operating condition, when VBAT≈VBAT_ZP, the ideal condition of RM_SOC≈UUSOC can be met, thereby achieving precise shutdown and improving battery life.

[0146] To illustrate the beneficial effects of the present invention, an experimental example embodiment is provided, such as... Figure 3 As shown, this embodiment is in relation to Figure 2 The illustrated embodiment applies the unavailable capacity calibration scheme provided by this invention under the same operating conditions. Furthermore, this embodiment aims to verify the effectiveness of the present invention's scheme; the test conditions are the same as... Figure 2 The illustrated examples (comparative examples) are kept consistent to ensure comparability.

[0147] Figure 3 The horizontal axis represents time, the left vertical axis represents battery charge in percentage (%), and the measurement accuracy is 0.1%; the right vertical axis represents battery voltage, which can be in volts (V). Figure 3 The test results are analyzed as follows:

[0148] 1. Precise power estimation and synchronized shutdown: such as Figure 3 As shown, the battery voltage (VBAT) decreases smoothly throughout the discharge process. When the voltage drops precisely to approximately the preset shutdown voltage of 3.40V, the system-calculated available charge (BATTSOC) simultaneously drops to 0%. At this point, the system triggers the shutdown procedure.

[0149] 2. A perfect balance of theoretical capacity. Figure 3 It is clearly shown that at the shutdown point, the theoretical total remaining capacity (RM_SOC) estimated internally by the algorithm also drops to the same level as the unavailable capacity (UUSOC, which, although not directly shown in the figure, can be inferred from BATT_SOC=RM_SOC-UUSOC), thus satisfying the ideal condition of RM_SOC=UUSOC. This proves that the present invention, through dynamic calibration, completely eliminates the overestimation error of UUSOC present in the comparative model.

[0150] 3. Full release of battery life. This is in contrast to the system reporting that it cannot continue working after reaching 0% battery (…). Figure 2 Unlike the embodiment shown, in this experimental example, the device cannot release any additional power after automatically shutting down at the end of the discharge. This indicates that all available battery power has been completely depleted, and the user has obtained 100% battery life, eliminating the "premature shutdown" problem.

[0151] In summary, this experimental example ( Figure 3 The illustrated embodiment and the comparative example ( Figure 2 The illustrated embodiment provides a direct and compelling comparison, demonstrating that the unavailable capacity dynamic calibration scheme provided by this invention can effectively overcome the inherent defects of traditional schemes in low-temperature, medium-to-high-rate discharge scenarios.

[0152] By monitoring battery voltage and current in real time and dynamically correcting the estimated unusable capacity (UUSOC) based on this, the present invention ensures that:

[0153] (i) Extremely high accuracy in estimating end-point power consumption, achieving perfect synchronization between physical shutdown voltage and power consumption display of 0%.

[0154] (ii) The unity of battery theoretical model and physical reality, satisfying RM_SOC=UUSOC at the shutdown point;

[0155] (iii) The user's battery life experience has been significantly improved, avoiding any form of power waste and premature shutdown.

[0156] In summary, the present invention significantly improves the accuracy and reliability of battery management and solves a long-standing technical problem in this field.

[0157] The following will combine Figure 4 This invention provides a detailed explanation of how the dynamic calibration process for unusable capacity (UUSOC) is specifically implemented. Figure 4 The calibrated unusable capacity can be represented as NEW-UUSOC, and the uncalibrated unusable capacity can be represented as UUSOC. The unit for unusable capacity is percentage (%), and the measurement accuracy is 0.1%. IBATAVG represents the average battery discharge current after smoothing and filtering, in mA. Its main function is to eliminate interference from instantaneous load fluctuations and provide a stable and reliable current value for calculating the battery's open-circuit voltage (OCV), which is a crucial foundation for the robust operation of the entire calibration algorithm.

[0158] This embodiment is performed under a scenario where a battery undergoes variable load discharge to verify the real-time correction capability of the present invention for UUSOC.

[0159] 1. Test conditions and environment.

[0160] (a) The battery is a lithium-ion battery.

[0161] (ii) Discharge load. Applying a varying pulse discharge load (such as...) Figure 4 (As shown in the IBATA VG curve), to simulate the complex scenario of constantly changing load in actual user use.

[0162] (III) Initial State. The initial estimate of unavailable capacity (UUSOC) by the power algorithm has a fixed error.

[0163] 2. Calibration process and result analysis.

[0164] Test results are as follows Figure 4 As shown, it clearly demonstrates the entire process of dynamic correction of unavailable capacity:

[0165] (1) Initial error and calibration start-up:

[0166] The UUSOC curve in the figure represents the unavailable capacity value estimated using a traditional fixed model. It remains constant throughout the process and cannot respond to changes in actual operating conditions. Once the system detects that the voltage meets the trigger conditions, it immediately initiates the calibration process.

[0167] (2) Execution of dynamic calibration:

[0168] Figure 4 The NEW-UUSOC curve in the figure shows the unusable capacity value after calibration using the method of this invention. The change process is as follows:

[0169] In the initial stage of discharge, due to the high battery voltage and large weighting factor, the system has a low degree of confidence in the voltage feedback, resulting in a gentle calibration. Therefore, the NEW-UUSOC value closely follows the initial UUSOC value and changes slowly.

[0170] During the mid- and late-stages of discharge, as the depth of discharge increases, the battery voltage gradually decreases, and the weighting factor decreases accordingly, increasing the system's confidence in the voltage feedback. At this point, the NEW-UUSOC curve begins to deviate significantly and continuously from the original UUSOC dashed line. The calibration algorithm continuously corrects for unavailable capacity downwards based on the real-time calculated smooth difference (delta_soc_avg). This process is smooth and asymptotic, effectively avoiding data jumps.

[0171] (3) Adaptability to load changes:

[0172] It is worth noting that the slope of the NEW-UUSOC curve is not constant. By comparing the IBATAVG (average discharge current) curve, it can be found that the correction rate of NEW-UUSOC accelerates during the current-increasing phase (when the internal resistance voltage drop is more significant and the unusable capacity error is larger); while during the current-decreasing phase, the correction rate slows down accordingly. This demonstrates that the proposed solution can adapt to changes in load and dynamically adjust the calibration intensity, exhibiting excellent intelligence and robustness.

[0173] In summary, this embodiment achieves this through... Figure 4 This intuitively demonstrates that the unavailable capacity calibration scheme provided by this invention is not a one-time static adjustment, but a continuous, gradual, and intelligent dynamic feedback process. The system continuously generates a reference capacity value (VBAT_SOC) by monitoring battery voltage (VBAT) and current (IBAT) in real time, calculates the error between this value and the algorithm value, and finally, through weighting factor control, smoothly and effectively corrects the estimated unavailable capacity. Figure 4 As shown, the calibrated value (NEW-UUSOC) successfully converged from the initial erroneous value to a new value that is closer to the true physical state of the battery.

[0174] This dynamic calibration mechanism is the core of the invention. It ensures that the power algorithm can continuously self-correct, thereby maintaining high accuracy under various complex operating conditions and laying a solid foundation for achieving precise shutdown.

[0175] This invention also provides a terminal device battery unusable capacity calibration device 50, such as... Figure 5 As shown, the device includes:

[0176] The voltage acquisition module 510 is used to acquire the current voltage and average voltage of the terminal device battery within multiple consecutive judgment cycles.

[0177] The calibration process initiation module 520 is used to initiate an unusable capacity calibration process if both the current voltage and the average voltage are less than a preset voltage threshold within any judgment period.

[0178] The reference charge value acquisition module 530 is used in the calibration process to calculate the open circuit voltage of the battery based on the latest collected current voltage and real-time discharge current, and to query the pre-stored correspondence curve between OCV value and SOC to obtain the reference charge value.

[0179] The smoothing difference calculation module 540 is used to calculate the difference between the remaining capacity estimated by the battery power algorithm and the reference power value, and to filter the difference for multiple consecutive judgment periods to obtain a smoothing difference.

[0180] The weight factor calculation module 550 is used to calculate the weight factor based on the current voltage, the preset shutdown voltage and the preset voltage threshold using a linear interpolation formula. The weight factor is used to characterize the normalized relative position of the current voltage within the interval defined by the preset shutdown voltage and the preset threshold voltage. The value of the weight factor is the proportion of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. The larger the value of the weight factor, the lower the system's confidence in the smoothed difference. The two are inversely proportional.

[0181] The unavailable capacity correction module 560 is used to dynamically correct the currently estimated unavailable capacity based on the smoothing difference and the weighting factor to obtain the calibrated unavailable capacity.

[0182] The available capacity calculation module 570 is used to calculate and output the available power of the terminal device based on the calibrated unavailable capacity and the remaining capacity.

[0183] Optionally, the values ​​of the preset voltage threshold and the preset shutdown voltage are both determined based on the real-time temperature of the battery.

[0184] The preset voltage threshold and the preset shutdown voltage are dynamically adjusted according to different battery characteristics and system design requirements, as the battery temperature changes.

[0185] Thirdly, embodiments of the present invention provide a terminal device 600, such as... Figure 6 As shown, it includes:

[0186] At least one processor 601;

[0187] Memory 602 for storing the at least one processor-executable instruction;

[0188] The at least one processor is configured to execute the instructions to implement the method described in the first aspect.

[0189] Fourthly, embodiments of the present invention provide a computer-readable storage medium that, when instructions in the computer-readable storage medium are executed by a processor of a terminal device, enables the terminal device to perform the method described in the first aspect.

[0190] The terminal device battery unusable capacity calibration method provided in this invention, by introducing a voltage-based dynamic feedback calibration mechanism, achieves the following significant advantages compared to existing technologies:

[0191] 1. This invention effectively improves the accuracy of battery capacity estimation in the low-charge range, especially near the critical stage of the shutdown voltage, while ensuring the smoothness of the capacity display throughout the discharge process and allowing errors to be released steadily. This invention introduces a baseline capacity value (VBAT_SOC) based on real-time voltage and current back-calculation as a calibration benchmark in the range close to the shutdown voltage, and dynamically corrects the unusable capacity (UUSOC), effectively eliminating UUSOC estimation deviations caused by model errors, temperature changes, current fluctuations, and other factors. This ensures that when the device discharges to the preset shutdown voltage, the remaining capacity (RM_SOC) is exactly equal to the unusable capacity (UUSOC), achieving precise shutdown with BATT_SOC=0, fundamentally solving the problem of "early shutdown" or "sudden shutdown" caused by inaccurate capacity estimation.

[0192] 2. Enhanced reliability and user trust in battery level display. By employing a dual-voltage condition triggering mechanism (both current and average voltages are below a threshold) combined with a multi-cycle judgment mechanism, voltage fluctuations caused by instantaneous load changes are effectively filtered out, preventing accidental triggering of the calibration process and ensuring the accuracy and reliability of the calibration operation. This makes the final displayed available battery level (BATT_SOC) more realistic and reliable, allowing users to accurately estimate device battery life and improving the user experience.

[0193] 3. A smooth and stable calibration process is achieved. By introducing a weighting factor and establishing an inverse relationship between it and the degree of trust in the smooth difference, this method achieves intelligent dynamic adjustment of the calibration intensity. In the high-voltage range, the calibration intensity is gentle, mainly relying on traditional algorithms; as the voltage decreases, the trust in the voltage feedback value is gradually increased, enhancing the calibration intensity. This calibration strategy, which smoothly transitions with voltage, avoids abrupt changes in the power display, ensuring the stability of the calibration process and a smooth visual experience.

[0194] In summary, this invention effectively solves the problem of decreased accuracy caused by inaccurate estimation of unavailable capacity at the end of discharge in existing lithium battery power estimation schemes, and provides a power calibration scheme with high accuracy, high reliability and good user experience.

[0195] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A method for calibrating the unusable capacity of a terminal device battery, characterized in that, The method includes: Within multiple consecutive judgment cycles, obtain the current voltage and average voltage of the terminal device's battery; If, within any judgment period, both the current voltage and the average voltage are less than a preset voltage threshold, then the unusable capacity calibration process is initiated. In the calibration process, based on the latest collected current voltage and real-time discharge current, the open-circuit voltage of the battery is calculated based on the battery internal resistance model, and the pre-stored OCV value and the corresponding curve of the SOC value are queried to obtain the reference charge value. The difference between the remaining capacity estimated by the battery power algorithm and the baseline power value is calculated, and the difference is filtered for multiple consecutive judgment periods to obtain a smooth difference. Based on the current voltage, the preset shutdown voltage, and the preset voltage threshold, a weighting factor is calculated using a linear interpolation formula. The weighting factor is used to characterize the normalized relative position of the current voltage within the interval defined by the preset shutdown voltage and the preset threshold voltage. The value of the weighting factor is the proportion of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. The larger the value of the weighting factor, the lower the system's confidence in the smoothed difference. The two are inversely proportional. Based on the smoothing difference and the weighting factor, the currently estimated unavailable capacity is dynamically corrected to obtain the calibrated unavailable capacity; Based on the calibrated unavailable capacity and the remaining capacity, calculate and output the available power of the terminal device; The step of calculating the weighting factor based on the current voltage, the preset shutdown voltage, and the preset voltage threshold using a linear interpolation formula includes: The weighting factor is calculated using the following linear interpolation formula: Weight=(VBAT_NOW–VBAT_ZP) / (VTH–VBAT_ZP); Wherein, Weight represents the weighting factor, VBAT_NOW represents the current voltage, VBAT_ZP represents the preset shutdown voltage, and VTH represents the preset voltage threshold. The step of dynamically correcting the currently estimated unavailable capacity based on the smoothing difference and the weighting factor to obtain the calibrated unavailable capacity includes: NEW_UUSOC=UUSOC+(1–Weight)*delta_soc_avg; Where NEW_UUSOC is the calibrated unavailable capacity, UUSOC is the currently estimated unavailable capacity, and delta_soc_avg is the smoothed difference.

2. The method according to claim 1, characterized in that, The values ​​of the preset voltage threshold and the preset shutdown voltage are both determined based on the real-time temperature of the battery. The preset voltage threshold and the preset shutdown voltage are dynamically adjusted according to different battery characteristics and system design requirements, as the battery temperature changes.

3. The method according to claim 1, characterized in that, After filtering the differences across multiple consecutive judgment periods to obtain smoothed differences, the method further includes: Determine whether the absolute value of the smoothed difference is less than a first preset threshold; If the absolute value of the smoothed difference is less than the first preset threshold, the calibration operation is abandoned.

4. The method according to claim 1, characterized in that, After filtering the differences across multiple consecutive judgment periods to obtain smoothed differences, the method further includes: Determine whether the rate of change of the smoothed difference in the current judgment period and the smoothed difference in the previous judgment period exceeds a preset rate of change threshold. If the rate of change exceeds the preset rate of change threshold, the following limiting operations are performed sequentially: The smoothed difference is subjected to a first amplitude limiting process; The theoretical correction value for unavailable capacity is calculated based on the smoothed difference after the first clipping process; The theoretical correction value is subjected to a second limiting process to ensure that the absolute value of the difference between the unavailable capacity after calibration and the unavailable capacity before calibration is not greater than the maximum change limit.

5. A terminal device battery unusable capacity calibration device, characterized in that, The device includes: The voltage acquisition module is used to acquire the current voltage and average voltage of the terminal device's battery within multiple consecutive judgment cycles. The calibration process initiation module is used to initiate an unusable capacity calibration process if both the current voltage and the average voltage are less than a preset voltage threshold within any judgment period. The reference capacity value acquisition module is used in the calibration process to calculate the open circuit voltage of the battery based on the latest collected current voltage and real-time discharge current, and to query the pre-stored correspondence curve between OCV value and SOC value to obtain the reference capacity value. The smoothing difference calculation module is used to calculate the difference between the remaining capacity estimated by the battery power algorithm and the baseline power value, and to filter the difference over multiple consecutive judgment periods to obtain a smoothing difference. The weight factor calculation module is used to calculate the weight factor based on the current voltage, the preset shutdown voltage, and the preset voltage threshold using a linear interpolation formula. The weight factor is used to characterize the normalized relative position of the current voltage within the interval defined by the preset shutdown voltage and the preset threshold voltage. The value of the weight factor is the proportion of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. The larger the value of the weight factor, the lower the system's confidence in the smoothed difference. The two are inversely proportional. The unavailable capacity correction module is used to dynamically correct the currently estimated unavailable capacity based on the smoothing difference and the weighting factor to obtain the calibrated unavailable capacity. The available capacity calculation module is used to calculate and output the available power of the terminal device based on the calibrated unavailable capacity and the remaining capacity; The weight factor calculation module is specifically used for: The weighting factor is calculated using the following linear interpolation formula: Weight=(VBAT_NOW–VBAT_ZP) / (VTH–VBAT_ZP); Wherein, Weight represents the weighting factor, VBAT_NOW represents the current voltage, VBAT_ZP represents the preset shutdown voltage, and VTH represents the preset voltage threshold. The available capacity calculation module is specifically used for: NEW_UUSOC=UUSOC+(1–Weight)*delta_soc_avg; Where NEW_UUSOC is the calibrated unavailable capacity, UUSOC is the currently estimated unavailable capacity, and delta_soc_avg is the smoothed difference.

6. The apparatus according to claim 5, characterized in that, The values ​​of the preset voltage threshold and the preset shutdown voltage are both determined based on the real-time temperature of the battery. The preset voltage threshold and the preset shutdown voltage are dynamically adjusted according to different battery characteristics and system design requirements, as the battery temperature changes.

7. A terminal device, characterized in that, include: At least one processor; Memory for storing the at least one processor-executable instruction; The at least one processor is configured to execute the instructions to implement the method as described in any one of claims 1-4.

8. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the terminal device, the terminal device is able to perform the method according to any one of claims 1-4.

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