Method and device for calibrating unavailable capacity of battery of terminal equipment and terminal equipment

Abstract

The invention belongs to the technical field of battery management, and discloses a terminal equipment battery unavailable capacity calibration method and device and terminal equipment, and the method comprises the steps: obtaining the current voltage and average voltage of a terminal equipment battery in a plurality of continuous judgment periods; if the voltage values are both smaller than the preset voltage threshold value, starting a calibration process; according to the latest collected current voltage and the real-time discharge current, the open-circuit voltage of the battery is obtained through calculation, and a reference electric quantity value is obtained; calculating a difference value between the residual capacity and the reference electric quantity value, and filtering the difference values of a plurality of continuous judgment periods to obtain a smooth difference value; calculating a weight factor based on the current voltage, a preset shutdown voltage and a preset voltage threshold; dynamically correcting the currently estimated unavailable capacity according to the smooth difference value and the weight factor to obtain the calibrated unavailable capacity; and calculating and outputting available power of the terminal equipment according to the calibrated unavailable capacity and residual capacity. The accuracy of the unavailable capacity can be improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of battery management, and particularly relates to a terminal device battery unusable capacity calibration method and device and a terminal device. BACKGROUND

[0002] The precision of battery power display has always been a problem that terminal users (especially mobile phone users) are very concerned about. Inaccurate power can prevent users from correctly estimating the time the mobile phone can be normally used, resulting in the mobile phone running out of power and shutting down at an unexpected time. Inaccurate power can also cause the shutdown voltage of the battery to decrease, and the system may run in an unexpected low-performance voltage range or an unsafe low-voltage range for a long time. Inaccurate power can also cause the mobile phone to shut down prematurely at 0%, affecting the user's mobile phone usage time. These problems will cause unnecessary trouble to the user's normal use of the mobile phone.

[0003] One of the important technical routes of the existing lithium battery power is a power display scheme based on coulomb counting + OCV curve. The dischargeable capacity of a lithium battery is lost with different temperatures and discharge rates. This part of the lost power is called unusable capacity, and is not a fixed value. The existing unusable capacity estimation relies on modeling OCV-SOC curve and modeling or learning internal resistance RBAT curve, combined with the current discharge temperature and discharge current estimation. Affected by the modeled internal resistance, current, voltage, battery temperature, battery consistency and impedance calculation model, the unusable capacity has errors and cannot be completely eliminated. SUMMARY

[0004] The purpose of the present application is to provide a high-precision, high-reliability and user-friendly power calibration scheme, which effectively solves the problem of precision decline caused by inaccurate unusable capacity estimation at the end of discharge in the existing lithium battery power estimation scheme.

[0005] In a first aspect, an embodiment of the present application provides a terminal device battery unusable capacity calibration method, which comprises: In a first aspect, an embodiment of the present application provides a terminal device battery unusable capacity calibration method, which comprises: If the current voltage and the average voltage are both less than a preset voltage threshold in any judgment period, start the unusable capacity calibration process; In the calibration process, the open circuit voltage of the battery is calculated based on the battery internal resistance model according to the latest collected current voltage and real-time discharge current, and the corresponding relationship curve of the pre-stored OCV value and power SOC is queried to obtain a reference power value; Calculate the difference between the residual capacity estimated by the battery power algorithm and the reference power value, and filter the difference in the continuous multiple judgment periods to obtain a smooth difference value; Based on the current voltage, the preset shutdown voltage, and the preset voltage threshold, a weight factor is calculated 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 ratio of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. A larger value of the weight factor indicates a lower degree of trust in the smoothed difference by the system, and the two are inversely proportional. Dynamically correcting the currently estimated unavailable capacity according to the smoothed difference and the weight factor to obtain a calibrated unavailable capacity; The available power of the terminal device is calculated and outputted according to the calibrated unavailable capacity and the remaining capacity.

[0006] 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; The preset voltage threshold and the preset shutdown voltage are dynamically adjusted as the battery temperature changes according to different battery characteristics and system design requirements.

[0007] Optionally, after filtering the difference values ​​of a plurality of consecutive judgment cycles to obtain a smoothed difference value, the method further includes: Determining 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 current calibration operation is abandoned.

[0008] Optionally, after filtering the difference values ​​of a plurality of consecutive judgment cycles to obtain a smoothed difference value, the method further includes: Determine whether the change rate of the smoothed difference value of the current judgment period and the smoothed difference value of the previous judgment period exceeds a preset change rate threshold; If the change rate exceeds the preset change rate threshold, the following limiting operations are performed in sequence: performing a first amplitude limiting process on the smoothed difference; Calculating a theoretical correction value of unavailable capacity based on the smoothed difference after the first clipping process; A second limiting process is performed on the theoretical correction value to ensure that the absolute value of the difference between the unusable capacity after calibration and the unusable capacity before calibration is not greater than the maximum change limit.

[0009] Optionally, the dynamic correction process is asymptotic; The system maintains the accumulated value of errors to be compensated; In each judgment period, the original difference value obtained in the current period or the original difference value after the limiting processing is accumulated into the error accumulation value to be compensated in the last period to update the error accumulation value to be compensated in the current period; In each judgment period, a part of the error accumulation value to be compensated is taken out according to the weight factor to realize the calibration of the available capacity, and the size of the taken-out value is limited by the maximum change limit.

[0010] Optionally, the weight factor is calculated by a linear interpolation formula based on the current voltage, the preset shutdown voltage and the preset voltage threshold, and the linear interpolation formula comprises: The weight factor is calculated by the following linear interpolation formula: Weight = (VBAT NOW - VBAT ZP) / (VTH - VBAT ZP); Wherein, Weight represents the weight factor, VBAT NOW represents the current voltage, VBAT ZP represents the preset shutdown voltage, and VTH represents the preset voltage threshold.

[0011] Optionally, the current estimated unavailable capacity is dynamically corrected according to the smooth difference value and the weight factor to obtain the calibrated unavailable capacity, and the linear interpolation formula comprises: NEW UUSOC = UUSOC + (1 - Weight) * delta soc avg; Wherein, NEW UUSOC is the calibrated unavailable capacity, UUSOC is the current estimated unavailable capacity, and delta soc avg is the smooth difference value.

[0012] In a second aspect, an embodiment of the present application provides a terminal device battery unavailable capacity calibration device, and the device comprises: A voltage acquisition module is configured to acquire the current voltage and the average voltage of the terminal device battery in a plurality of continuous judgment periods. A calibration process starting module is configured to start the unavailable capacity calibration process if the current voltage and the average voltage are both less than a preset voltage threshold in any judgment period. A reference power value acquisition module is configured to calculate the open circuit voltage of the battery based on a battery internal resistance model according to the latest acquired current voltage and real-time discharge current in the calibration process, and acquire a reference power value by querying a pre-stored OCV value and power SOC corresponding relationship curve. A smooth difference value calculation module is configured to calculate the difference value between the remaining capacity estimated by the battery power algorithm and the reference power value, and filter the difference values in a plurality of continuous judgment periods to obtain a smooth difference value. a weight factor calculation module, configured to calculate a weight factor based on the current voltage, the preset shutdown voltage and the preset voltage threshold value, the weight factor being used to represent a normalized relative position of the current voltage in an interval defined by the preset shutdown voltage and the preset threshold voltage, the value of the weight factor being a proportion of a difference between the current voltage and the preset shutdown voltage to a length of the interval, the greater the value of the weight factor, the lower the degree of trust of the system in the smoothed difference value, and the two being in an inverse relationship; a non-usable capacity correction module, configured to dynamically correct a current estimated non-usable capacity according to the smoothed difference value and the weight factor, to obtain a calibrated non-usable capacity; a usable capacity calculation module, configured to calculate and output a usable power of the terminal device according to the calibrated non-usable capacity and the residual capacity.

[0013] Optionally, the preset voltage threshold value and the preset shutdown voltage are both determined based on a real-time temperature of the battery. The preset voltage threshold value and the preset shutdown voltage are dynamically adjusted according to different battery characteristics and system design requirements and changes in the battery temperature.

[0014] In a third aspect, an embodiment of the present application provides a terminal device, comprising: at least one processor; a memory for storing instructions executable by the at least one processor; The at least one processor is configured to execute the instructions to implement the method of the first aspect.

[0015] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, when instructions in the computer readable storage medium are executed by a processor of a terminal device, the terminal device is enabled to execute the method of the first aspect.

[0016] The terminal device battery non-usable capacity calibration method provided by the embodiment of the present application introduces a dynamic feedback calibration mechanism based on voltage, compared with the prior art, the following significant beneficial effects can be achieved: 1、The application effectively improves the accuracy of battery power estimation in the low power interval, especially near the critical stage of the shutdown voltage, while ensuring the smoothness of the power display during the entire discharge process, and allowing the error to be released smoothly. The application introduces a reference power value (VBAT SOC) based on real-time voltage and current back-propagation as a calibration reference in the interval close to the shutdown voltage, and dynamically corrects the unusable capacity (UUSOC), which can effectively eliminate the UUSOC estimation deviation caused by model error, temperature change, current fluctuation and other factors. This ensures that the remaining capacity (RM SOC) is exactly equal to the unusable capacity (UUSOC) when the terminal is discharged to the preset shutdown voltage, i.e. accurate shutdown of BATT SOC=0, which fundamentally solves the problem of "premature shutdown" or "sudden shutdown" caused by inaccurate power estimation.

[0017] 2、Enhanced reliability and user trust of power display. Through the double voltage condition trigger (current voltage and average voltage are lower than threshold) and combined with the judgment mechanism of continuous multiple periods, the voltage fluctuation interference caused by instantaneous load change is effectively filtered, preventing false triggering of the calibration process, ensuring the accuracy and reliability of the calibration operation. This makes the available power (BATT SOC) displayed to the user more real and reliable, and the user can accurately estimate the device battery life, improving the user experience.

[0018] 3、Smooth and stable calibration process is achieved. By introducing a weight factor (Weight) and establishing its inverse relationship with the degree of trust in the smoothing difference value, this method realizes intelligent dynamic adjustment of the calibration strength. In the high voltage interval, the calibration strength is soft, mainly relying on traditional algorithms; as the voltage decreases, the trust in the voltage feedback value is gradually increased, and the calibration strength is enhanced. This smooth transition calibration strategy avoids the jump of power display, ensuring the stability and smoothness of the calibration process.

[0019] In summary, the application effectively solves the problem of precision decline caused by inaccurate estimation of unusable capacity at the end of discharge in the existing lithium battery power estimation scheme, and provides a high-precision, high-reliability and user-friendly power calibration scheme. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 A flowchart of a terminal device battery unusable capacity calibration method provided by the embodiment of the application; Figure 2 A problem display effect diagram in the prior art without calibration; Figure 3 An effect display diagram of the embodiment shown in Figure 2 application of the unusable capacity calibration method provided by the application under the same working conditions; Figure 4 A dynamic calibration process schematic diagram provided for an embodiment of the present application; Figure 5 A terminal device battery unusable capacity calibration device structure schematic diagram provided for an embodiment of the present application; Figure 6 A terminal device structure schematic diagram provided for an embodiment of the present application. DETAILED DESCRIPTION

[0021] The present application will be described in detail below through embodiments.

[0022] The accuracy of battery power display has always been a very concerned issue for terminal users, especially mobile phone users. Inaccurate power will make users unable to correctly estimate the time the mobile phone can be normally used, resulting in the mobile phone running out of power at an unexpected time point. Inaccurate power may also cause the shutdown voltage of the battery to decrease, and the system may run in an unexpected low performance voltage interval or an unsafe low voltage interval for a long time. Inaccurate power may also cause the mobile phone to shut down prematurely at 0%, affecting the user's mobile phone use time. These problems will cause unnecessary trouble to the normal use of the mobile phone by the user.

[0023] One of the important technical routes of the existing lithium battery power is a power display scheme based on coulomb counter + OCV curve. The dischargeable capacity of a lithium battery is lost with different temperatures and discharge rates. This part of the lost power is called unusable capacity, and is not a fixed value. The existing estimation of unusable capacity relies on modeling OCV-SOC curve and modeling or learning internal resistance RBAT curve, combined with the current discharge temperature and discharge current estimation. Affected by the modeled internal resistance, current, voltage, battery temperature, battery consistency and impedance calculation model, the unusable capacity has errors and cannot be completely eliminated. The error is particularly serious in the problem of inaccurate power caused by high energy density, low temperature and large current discharge scenarios. Therefore, an embodiment of the present application provides a terminal device battery unusable capacity calibration method to solve the problem of large unusable capacity estimation error.

[0024] Taking a mobile phone with a preset 3.4V shutdown voltage as an example, its lithium battery power estimation usually adopts a scheme of coulomb counter combined with open circuit voltage (OCV) curve, and the shutdown voltage is used as the reference point of 0% power. However, the actual dischargeable capacity of the battery is significantly affected by factors such as temperature and discharge rate, resulting in the OCV voltage corresponding to the true 0% power not being fixed. Therefore, the position of 0% power estimated based on the model will continue to fluctuate.

[0025] Due to the influence of factors such as impedance accuracy, temperature measurement error, voltage and current sampling deviation, and model modeling limitations, the 0% electric quantity estimated by the electric quantity algorithm of the fusion of coulomb counter and OCV curve often deviates from the actual physical voltage. This may lead to the following two abnormal situations. One situation is that when the system reports 0% electric quantity, the actual battery voltage is much higher than 3.4V, causing the low electric quantity display segment to last too long or the device to shut down in advance, thereby shortening the user's perceived endurance time; the other situation is that when the system reports 0% electric quantity, the actual voltage has been significantly lower than 3.4V, causing the terminal device to suddenly shut down without warning, or causing the system to run unstable due to insufficient battery voltage.

[0026] The core of the present application is to introduce the real-time battery terminal voltage (VBAT) parameter for dynamic calibration on the basis of the traditional coulomb counter and OCV curve combined unusable capacity (UUSOC) estimation scheme, aiming to ensure that when the battery is discharged to the preset shutdown voltage, the remaining capacity (RM_SOC) and the unusable capacity (UUSOC) calculated by the algorithm are consistent, thereby significantly improving the electric quantity estimation accuracy at the end of discharge.

[0027] The basic theory related to the embodiments of the present application is introduced below.

[0028] In the existing battery electric quantity estimation system, the available electric quantity (BATT_SOC) finally displayed to the user is generally calculated by the formula BATT_SOC=RM_SOC–UUSOC. Among them, RM_SOC (Remaining State of Charge) represents the theoretical total remaining capacity of the battery estimated by coulomb counting and other methods, and UUSOC (Unusable State of Charge) represents the unusable capacity that cannot be released under certain working conditions.

[0029] The core expectation of this theoretical model is that when the battery is continuously discharged to the preset hardware shutdown voltage (such as 3.4V), the available electric quantity BATT_SOC should be exactly 0%, which means that the terminal device will consume the last unit of available electric energy and perform shutdown. By substituting this expectation (BATT_SOC=0) into the above formula, it can be deduced that under the ideal precise estimation state, the theoretical total remaining capacity of the battery should be exactly equal to the unusable capacity, that is, it should satisfy the equation relationship RM_SOC=UUSOC.

[0030] However, in practical applications, accurate calculation of UUSOC is difficult because the estimation is easily affected by factors such as temperature, current, battery aging, and model errors. As a result, RM_SO often does not equal UUSOC when the battery is actually discharged to the shutdown voltage, causing problems such as premature shutdown or distorted battery display. The core purpose of this invention is to ensure that the key condition of RM_SOC = UUSOC is met at the end of discharge by introducing a voltage feedback calibration mechanism, thereby fundamentally ensuring battery accuracy.

[0031] The following is a detailed description of a method for calibrating the unavailable capacity of a battery in a terminal device provided by an embodiment of the present invention.

[0032] It should be noted that the terminal device battery unavailable capacity calibration method provided by the embodiment of the present invention can be applied to terminal devices using lithium batteries such as smart phones, tablet computers, and wearable devices.

[0033] like Figure 1 As shown, a method for calibrating the unavailable capacity of a battery of a terminal device provided by an embodiment of the present invention may include the following steps: S110, obtaining the current voltage and average voltage of the battery of the terminal device within a plurality of consecutive determination cycles.

[0034] In this step, the system dynamically acquires the terminal device's battery voltage parameters over multiple consecutive judgment cycles. Specifically, the power management unit collects the battery's current voltage (VBAT_NOW) in real time at a fixed sampling frequency (e.g., once per second). This value represents the instantaneous terminal voltage of the battery under load. Simultaneously, the system performs arithmetic averaging or low-pass filtering on the multiple recently collected voltage values ​​to calculate an average voltage (VBAT_AVG). This average voltage is used to eliminate voltage spikes and sharp fluctuations caused by transient load changes (such as starting the application processor core), thereby more stably reflecting the overall battery voltage trend. The specific length of the judgment cycle and the window size of the averaging algorithm can be configured according to actual needs. For example, it can be set to five consecutive cycles, each lasting one second. This embodiment of the present invention does not impose specific limitations on this.

[0035] S120: If, in any judgment cycle, the current voltage and the average voltage are both lower than the preset voltage threshold, the unavailable capacity calibration process is started.

[0036] The present step is a start condition judgment step of the calibration process. In any judgment period, the system compares the current voltage (VBAT NOW) and the average voltage (VBAT AVG) obtained in real time with the preset voltage threshold (VTH). Only when both the current voltage and the average voltage are less than the preset voltage threshold, one of the trigger conditions is met. To ensure the stability of the trigger signal and prevent false triggering, this condition usually needs to be continuously met for a plurality of judgment periods (for example, 3 consecutive periods). This can effectively filter out the voltage drop caused by the instantaneous large current load. Only when the above condition is met, the system will start the subsequent unusable capacity (UUSOC) calibration process. The preset voltage threshold (VTH) is not a fixed value, which is preferably dynamically adjusted according to the battery temperature, and can be obtained by a pre-stored temperature-voltage lookup table.

[0037] S130, in the calibration process, the open circuit voltage of the battery is calculated based on the latest collected current voltage and real-time discharge current, and the corresponding relationship curve between the OCV value and the SOC is queried to obtain a reference power value.

[0038] After the calibration process is started, the system performs the present step to obtain a reliable voltage reference power value. First, the system synchronously collects the current voltage (VBAT NOW) and the real-time discharge current (IBAT). Then, based on the pre-established and stored battery internal resistance model, the current voltage is compensated and calculated. Specifically, according to Ohm's law, the current open circuit voltage (OCV) of the battery is estimated by the formula OCV = VBAT NOW + IBAT * R, wherein R is the battery internal resistance determined based on the model and the temperature. Finally, the pre-stored open circuit voltage-power (OCV-SOC) corresponding relationship curve is queried, and the reference power value (VBAT SOC) corresponding to the current time is mapped. The reference power value can more truly reflect the physical state of the battery because it is directly derived from the real-time measured voltage parameter.

[0039] S140, the difference between the remaining capacity estimated by the battery power calculation algorithm and the reference power value is calculated, and the difference values of a plurality of consecutive judgment periods are filtered to obtain a smooth difference value.

[0040] The 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 capacity 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. The difference preliminarily reflects the deviation between the algorithm estimated value and the voltage reference value. Subsequently, the difference values (delta soc) calculated in a plurality of consecutive judgment periods (for example, the past 10 periods) are filtered. The filtering process can use moving average, weighted average or low-pass filtering algorithm, the purpose is to smooth out the high-frequency noise and abnormal fluctuations in the data, and finally output a smoothed difference value (delta soc avg) that can represent the trend deviation.

[0041] In S150, a weight factor is calculated based on the current voltage, the preset shutdown voltage and the preset voltage threshold value by a linear interpolation formula.

[0042] The weight factor is used to represent the normalized relative position of the current voltage in the interval defined by the preset shutdown voltage and the preset threshold voltage, and indicates the degree of trust in the smoothed difference value. The weight factor and the degree of trust are inversely proportional, the value of the weight factor is the proportion of the difference of the current voltage relative to the preset shutdown voltage in the length of the entire interval, the greater the value of the weight factor, the lower the degree of trust of the system in the smoothed difference value, and the two are inversely proportional.

[0043] This step is the key to realize intelligent dynamic calibration of the application. The calculation of the weight factor (Weight) is based on the current voltage (VBAT NOW), the preset shutdown voltage (VBAT ZP) (such as 3.4V) and the preset voltage threshold value (VTH). The calculation is performed by the following linear interpolation formula: Weight = (VBAT NOW-VBAT ZP) / (VTH-VBAT ZP).

[0044] The weight factor has a clear physical and logical meaning, which is as follows: 1. The weight factor is used to represent the relative position of the current voltage in the interval defined by the preset shutdown voltage and the preset threshold voltage. When VBAT NOW approaches VTH, the value of Weight approaches 1; when VBAT NOW approaches VBAT ZP, the value of Weight approaches 0.

[0045] 2、The weight factor indicates the degree of trust in the smoothed difference value, and the value of the weight factor is inversely proportional to the degree of trust. The greater the Weight value (the higher the voltage), the more the system trusts the original algorithm model, and the lower the trust degree of the smoothed difference value (delta_soc_avg) obtained by voltage back calculation; on the contrary, the smaller the Weight value (the lower the voltage, the closer to the preset shutdown voltage), the higher the trust degree of the voltage back calculation value, and the more the system needs to correct the unavailable capacity according to the value.

[0046] S160, according to the smoothed difference value and the weight factor, dynamically correcting the current estimated unavailable capacity to obtain the calibrated unavailable capacity.

[0047] In this step, the system dynamically corrects the current estimated unavailable capacity (UUSOC) according to the smoothed difference value (delta_soc_avg) and the weight factor (Weight) to obtain the calibrated unavailable capacity (NEW_UUSOC), and the correction formula is: NEW_UUSOC = UUSOC + (1-Weight) * delta_soc_avg.

[0048] The formula embodies the dynamic and weighted idea: (1-Weight) is the trust coefficient of the smoothed difference value. The lower the voltage (the smaller the Weight), the greater the trust coefficient, the greater the contribution of the smoothed difference value to the final correction amount, and the calibration intensity is also enhanced. In addition, in order to prevent the display of the electric quantity from jumping, the amplitude of single correction is preferably limited (i.e. amplitude limiting processing) to ensure that the change amount in a single period does not exceed a preset maximum change threshold. In order to clearly describe the scheme, the specific implementation of dynamically correcting the unavailable capacity will be described in detail in the following embodiments.

[0049] S170, according to the calibrated unavailable capacity and the remaining capacity, calculating and outputting the available electric quantity of the terminal device.

[0050] Specifically, the system substitutes the calibrated unavailable capacity (NEW_UUSOC) obtained in step S160 into the basic electric quantity calculation formula: BATT_SOC = RM_SOC - NEW_UUSOC.

[0051] The calculated BATT_SOC is the available electric quantity with high precision after unavailable capacity calibration. The electric quantity value is output to the operating system and the user interface (UI) for final display to the user, thereby realizing accurate prediction of the endurance time of the terminal device and avoiding early shutdown or sudden shutdown and other bad experiences.

[0052] The terminal device battery unusable capacity calibration method provided by the embodiment of the present application introduces a dynamic feedback calibration mechanism based on voltage, and compared with the prior art, the following significant beneficial effects can be achieved: 1. The present application effectively improves the accuracy of battery power estimation in the low power interval, especially near the critical stage of the shutdown voltage, while ensuring the smoothness of the power display during the entire discharge process and allowing the error to be released smoothly. By introducing a reference power value (VBAT_SOC) based on real-time voltage and current back-propagation as a calibration reference in the interval close to the shutdown voltage, and dynamically correcting the unusable capacity (UUSOC), the present application can effectively eliminate the UUSOC estimation deviation caused by factors such as model error, temperature change, and current fluctuation. This ensures that the remaining capacity (RM_SOC) is exactly equal to the unusable capacity (UUSOC) when the terminal is discharged to the preset shutdown voltage, i.e. achieving precise shutdown of BATT_SOC=0, and fundamentally solving the problem of "premature shutdown" or "sudden shutdown" caused by inaccurate power estimation.

[0053] 2. The reliability and user trust of the power display are enhanced. By triggering under the condition of double voltage (the current voltage and the average voltage are both lower than the threshold value) and combining the judgment mechanism of multiple consecutive periods, the voltage fluctuation interference caused by instantaneous load change is effectively filtered, the calibration process is prevented from being triggered by mistake, and the accuracy and reliability of the calibration operation are ensured. This makes the available power (BATT_SOC) displayed to the user more real and reliable, and the user can accurately estimate the device's battery life, improving the user experience.

[0054] 3. A smooth and stable calibration process is achieved. By introducing a weight factor (Weight) and establishing its inverse relationship with the degree of trust in the smoothing difference value, the method realizes intelligent dynamic adjustment of the calibration strength. In the high voltage interval, the calibration strength is soft, mainly relying on the traditional algorithm; as the voltage decreases, the trust in the voltage feedback value is gradually increased, and the calibration strength is enhanced. This calibration strategy with smooth transition with voltage avoids the jump of power display, ensuring the stability and smoothness of the calibration process.

[0055] In summary, the present application effectively solves the problem of precision decline caused by inaccurate estimation of unusable capacity at the end of discharge in the existing lithium battery power estimation scheme, and provides a power calibration scheme with high precision, high reliability, and good user experience.

[0056] On the basis of the above embodiment, in order to ensure the stability of the calibration process and avoid the jump of the display power (UI SOC) caused by the mutation of the unusable capacity (UUSOC) and cause user confusion, the present application provides two preferred implementation methods for limiting the calibration amplitude. Those skilled in the art can understand that the two methods can be implemented separately or in combination.

[0057] As an implementation manner of the embodiment of the present application, after filtering the difference values of the continuous multiple judgment periods to obtain the smooth difference values, the method can further include the following steps: judging whether the change rate of the smooth difference value of the current judgment period and the smooth difference value of the previous judgment period is a preset change rate threshold.

[0058] If the change rate exceeds the preset change rate threshold, the following limiting operations are sequentially performed: performing first limiting processing on the smooth difference value.

[0059] calculating the theoretical correction value of the unusable capacity based on the smooth difference value after the first limiting processing.

[0060] performing second limiting processing on the theoretical correction value to ensure that the absolute value of the difference between the calibrated unusable capacity and the unusable capacity before calibration is not greater than a maximum change limit value.

[0061] The change rate limiting mechanism introduced in the implementation manner aims to identify and suppress abnormal error signals caused by severe transient load, and ensure that the calibration system only responds to stable and trend error.

[0062] Specifically, the change rate can be calculated in the following manner: change rate = (smooth error of the current period - smooth error of the previous period) / judgment period length The system compares the calculated change rate with a preset change rate threshold. The preset change rate threshold is usually set to a small value, for example, 0.5% per second, and the specific value can be adjusted according to the system stability and response speed requirements. The embodiment of the present application does not make specific limitations on the preset change rate threshold.

[0063] When the change rate exceeds the preset change rate threshold, it indicates that the smooth difference value has an abnormal jump, which is usually caused by a sharp drop in voltage due to a transient large current load (for example, an application processor is instantaneously fully loaded). Such signals belong to interference rather than real power estimation error trend. If the abnormal value is directly applied for calibration, it will destroy the continuity of power display.

[0064] At this time, the system does not completely give up calibration, but sequentially performs two-stage limiting guarantee strategies: first, limiting processing is performed on the smooth difference value itself to suppress the abnormal jump; then, the theoretical correction value of the unusable capacity is calculated based on the smooth difference value after limiting, and the change amplitude of the unusable capacity caused by the correction value is limited again to ensure that the absolute value of the difference between the unusable capacity before and after calibration does not exceed the set maximum change limit value. That is, to ensure that: | NEW_UUSOC - UUSOC | < MAX_DELTA_UUSOC Where MAX_DELTA_UUSOC is a quantity much smaller than the abnormal jump value that can occur, for example, an electrical quantity value of 0.5%. Through this limiting operation, unforeseeable large value changes can be limited to a range that is acceptable by the system and imperceptible to the user.

[0065] The present implementation has the advantage that it effectively filters transient interference while retaining the ability to continue tracking the true error trend. It avoids both completely missing the necessary calibration opportunity due to misjudgment and completely preventing sudden jumps in the displayed electrical quantity value, ultimately achieving high robustness of the calibration process and high smoothness of the displayed electrical quantity.

[0066] On the basis of the embodiment shown, as an implementation of an embodiment of the present application, the values of the preset voltage threshold and the preset shutdown voltage are both determined based on the real-time temperature of the battery. Figure 1 Where 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.

[0067] As an optional way, a first mapping relationship between the battery temperature and the preset voltage threshold, and a second mapping relationship between the battery temperature and the preset shutdown voltage are determined in advance. 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.

[0068] As an important implementation of an embodiment of the present application, the preset voltage threshold (VTH) and the preset shutdown voltage (VBAT_ZP) are not fixed values, but functions of the battery temperature. The following will be described from the following aspects.

[0069] First, the establishment of the mapping relationship. The two mapping relationships are determined and stored in advance through battery testing. Among them, the first mapping relationship defines the corresponding relationship between the battery temperature and the preset voltage threshold (VTH). The second mapping relationship defines the corresponding relationship between the battery temperature and the preset shutdown voltage (VBAT_ZP).

[0070] Second, the characteristics of the mapping relationship. The above two mapping relationships 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.

[0071]

[0072] ​The third aspect is the working principle and beneficial effects. This implementation is based on the electrochemical characteristics of lithium batteries. In a low-temperature environment, the internal resistance of the battery increases significantly, causing the terminal voltage (VBAT) of the battery to drop more sharply under the same load current.

[0073] If VTH remains fixed, the voltage will drop below the threshold too early in a low-temperature environment, causing the calibration process to be triggered prematurely, while the algorithm model may not have produced significant errors at this time. By appropriately lowering VTH as the temperature decreases, the calibration trigger timing can be delayed, allowing it to more accurately enter the low-power interval that actually requires calibration, avoiding unnecessary early calibration operations and improving algorithm efficiency.

[0074] And in a low-temperature environment, due to the large internal resistance voltage drop, the actual available energy of the battery will decrease. If a higher fixed shutdown voltage is maintained (such as always 3.4V), it will cause a considerable part of the chemical energy in the device to be unused before it is shut down, shortening the user's perceived battery life. By appropriately lowering the shutdown voltage threshold in a low-temperature environment, the terminal device's battery life can be extended while ensuring battery safety. This adjustment ensures that the system can accurately define the physical point of 0% power while emptying the battery as much as possible at different temperatures.

[0075] In the fourth aspect, in specific implementation, the mapping relationship is stored in the device memory in the form of a query table. The system monitors the battery temperature in real time and obtains the corresponding VTH and VBAT_ZP values at the current temperature by looking up the table, which are used for subsequent trigger judgment and weight factor calculation.

[0076] As another optional way, a third mapping relationship between the battery temperature and the preset voltage threshold, and a fourth mapping relationship between the battery temperature and the preset shutdown voltage are predetermined, in which the preset voltage threshold increases as the battery temperature decreases in the third mapping relationship, and the preset shutdown voltage increases as the battery temperature decreases in the fourth mapping relationship.

[0077] When the system design prioritizes operational stability and avoids unexpected shutdowns, the preset voltage threshold (VTH) and the preset shutdown voltage (VBAT_ZP) can be increased accordingly as the battery temperature decreases to cope with the possible voltage instantaneous drop under low-temperature large-current load, reserving sufficient buffer space for the system voltage.

[0078] The skilled person can determine the specific mapping relationship function or query table through experiments according to the actual application scenario.

[0079] In the Figure 1 Based on the embodiment shown in the figure, as an implementation of the embodiment of the present application, after filtering the difference of the continuous multiple judgment periods to obtain a smoothed difference, the method can further include the following steps: determine whether the absolute value of the smoothed difference value is less than a first preset threshold value.

[0080] If the absolute value of the smoothed difference value is less than the first preset threshold value, the current calibration operation is abandoned.

[0081] Specifically, the system compares the absolute value of the smoothed difference value (delta_soc_avg) with the first preset threshold value. If the absolute value of the smoothed difference value is less than the first preset threshold value, 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, within an acceptable error range. At this time, it is not meaningful to start the calibration process. Therefore, the system abandons the current calibration operation, maintains the current estimated unusable capacity (UUSOC) unchanged, and exits the current round of calibration process.

[0082] The first preset threshold value can be configured according to the actual application scenario and the accuracy requirement, and is usually set to a small value, for example, 1% of the power value.

[0083] Through this embodiment, excessive calibration and noise interference can be prevented. Specifically, a small deviation may be caused by measurement noise, sampling error or small transient fluctuations, rather than real model error. If a response is made to such small deviations, unnecessary calibration operations may be introduced, causing slight fluctuations in power display and destroying stability. Ignoring small errors ensures that calibration actions are only performed for significant, trend-oriented deviations, greatly enhancing the anti-interference ability of the algorithm. Moreover, after determining that the error is small, the subsequent weight calculation, correction value calculation and other steps are skipped, reducing the computational burden of the processor and helping to save system power consumption.

[0084] To more directly reflect the technical effects of the present application, the following will be described in conjunction with the accompanying drawings Figures 2 to 4 , through a specific embodiment.

[0085] This embodiment compares the effects of the present application scheme (calibration enabled) and the traditional scheme (calibration not enabled) in a specific low-temperature, high-current discharge scenario. In the test, an estimated error of about 5% of the unusable capacity (UUSOC) is artificially introduced into the algorithm (i.e., the unusable capacity is overestimated), and 4% of the hidden capacity (HID_SOC) is included in the test to simulate the problem caused by inaccurate models in the real environment.

[0086] As shown in FIG. 8, the problem under the uncalibrated condition is shown. Figure 2

[0087] Figure 2 The horizontal axis in the graph is time, the left vertical axis is power, with a unit of percentage (%), and the measurement accuracy is 0.1%; the right vertical axis is the battery voltage, which can be in V.​Figure 2 The test results are analyzed as follows: 1. Premature shutdown and incorrect power estimation. Figure 2 As shown in the figure, when the battery voltage (VBAT) drops to about 3.70V, the available power (BATT SOC) calculated by the system has dropped to 0%, and the system triggers the low-battery shutdown process. However, the theoretical total remaining capacity (RM SOC) estimated by the algorithm is far from exhausted. Figure 2 The uncalibrated RM_SOC value when reporting 0 indicates that when reporting 0% power, there is still considerable remaining capacity in the battery in theory.

[0088] 2. Actual range loss. To verify this discrepancy, the test did not terminate immediately after the system reported 0% charge, but instead continued discharging, bypassing the shutdown protection. The results showed that even after the uncalibrated battery reported 0%, it could still discharge 15%. This means that due to an inaccurate estimate of the unusable capacity (UUSOC) (in this case, a significant overestimation), the device terminated prematurely even though the battery still had 15% usable charge, resulting in a significant loss of range and severely impacting the user experience.

[0089] 3. The relationship between voltage and charge is disconnected. As shown in the curve, at the end of discharge, the decreasing trend of voltage (VBAT) is out of sync with the decreasing trend of available capacity (which can be called BATT SOC). Even though the charge level has returned to zero, the battery voltage remains significantly above the final shutdown voltage threshold. This demonstrates that traditional solutions cannot guarantee a precise return to zero charge at the preset physical shutdown voltage.

[0090] This example clearly reveals the core flaw of existing power estimation solutions. Since unavailable capacity (UUSOC) is a dynamic variable affected by factors such as temperature, current, and aging, using a fixed or inaccurate model for estimation will inevitably introduce huge errors under specific operating conditions. Figure 2 As shown, this error directly manifests as a serious premature shutdown problem, which causes the device to be unable to utilize the full energy of the battery and shortens the user's actual usage time.

[0091] This comparative example provides a clear practical basis and motivation for the proposal of the present invention. To overcome the aforementioned drawbacks, the present invention proposes a dynamic calibration scheme based on voltage feedback to ensure that under all operating conditions, when VBAT ≈ VBAT_ZP, the ideal condition of RM_SOC ≈ UUSOC is met, thereby achieving precise shutdown and improving the battery life experience.

[0092] In order to illustrate the beneficial effects of the present invention, an experimental example is provided. Figure 3 As shown, this embodiment isFigure 2 The embodiments shown in the same working conditions, the application of the present application provides a non-available capacity calibration scheme. And, the embodiment is designed to verify the effect of the present application scheme, test conditions and Figure 2 The embodiments shown (comparative example) to ensure consistency for comparison.

[0093] Figure 3 The horizontal axis in the figure is time, the left vertical axis is the amount of electricity, the unit is percent (%), the measurement accuracy is 0.1%; the right vertical axis is the battery voltage, which can be V. Figure 3 The test results are analyzed as follows: 1. Accurate estimation of the amount of electricity and synchronous shutdown: as Figure 3 As shown in the whole discharge process, the battery voltage (VBAT) decreases smoothly. When the voltage accurately decreases to the preset shutdown voltage of about 3.40V, the available amount of electricity (BATTSOC) calculated by the system is synchronously reduced to 0%. At this time, the system triggers the shutdown process.

[0094] 2. Perfect balance of theoretical capacity. Figure 3 It is clearly shown that at the shutdown point, the theoretically estimated total remaining capacity (RM SOC) inside the algorithm also decreases to the same level as the unusable capacity (UUSOC, although not directly plotted in the figure, but it can be inferred from BATT SOC=RM_SOC-UUSOC), that is, it meets the ideal condition of RM_SOC=UUSOC. This proves that the present application eliminates the overestimation error of UUSOC in the comparative example through dynamic calibration.

[0095] 3. Complete release of endurance. Unlike the comparative example (the embodiment shown in Figure 2 The device in this experimental example cannot release additional electricity after automatically shutting down at the end of discharge. This indicates that all available capacity of the battery has been completely consumed, and the user obtains 100% of the endurance time, eliminating the problem of "premature shutdown".

[0096] In summary, the experimental example (the embodiment shown in Figure 3 ) and the comparative example (the embodiment shown in Figure 2 ) form a direct and powerful contrast. It is proved that the dynamic calibration scheme of the present application for non-available capacity can effectively overcome the inherent defects of the traditional scheme in the low temperature and high rate discharge scenarios.

[0097] By monitoring the battery voltage and current in real time, and dynamically correcting the estimated value of the non-available capacity (UUSOC), the present application ensures: (1) High accuracy of the end amount of electricity, achieving perfect synchronization of the physical shutdown voltage and the amount of electricity display 0%.

[0098] (II) The unification of the battery theoretical model and the physical reality, which satisfies RM_SOC=UUSOC at the shutdown point; (III) The significant improvement of the user's endurance experience, which avoids any form of power waste and early shutdown.

[0099] In summary, the scheme of the present application significantly improves the accuracy and reliability of battery management, and solves the long-standing technical problems in the field.

[0100] The following will be combined Figure 4 to specifically explain how the dynamic calibration process of the unusable capacity (UUSOC) in the present application is implemented. Figure 4 The calibrated unusable capacity can be represented as NEW-UUSOC, and the uncalibrated unusable capacity can be represented as UUSOC, wherein the unit of the unusable capacity is percentage (%), and the measurement accuracy is 0.1%; IBATAVG represents the smoothed battery average discharge current, and the unit is mA. Its main function is to eliminate the interference caused by transient load fluctuations and provide a stable and reliable current value for calculating the open circuit voltage (OCV) of the battery, which is an important basis for the stable operation of the entire calibration algorithm.

[0101] The present embodiment is executed in a scenario where a battery experiences variable load discharge to verify the real-time correction capability of the present application scheme for UUSOC.

[0102] 1. Test conditions and environment.

[0103] (I) The battery is a lithium ion battery.

[0104] (II) Discharge load. Apply a variable pulse discharge load (such as Figure 4 shown in the IBATAVG curve), to simulate the complex scenario of changing load in actual user use.

[0105] (III) Initial state. The initial estimation of the unusable capacity (UUSOC) by the power algorithm has a fixed error.

[0106] 2. Calibration process and result analysis.

[0107] The test results are shown in Figure 4 , which clearly shows the whole process of dynamic correction of the unusable capacity: (1) Initial error and calibration start: The UUSOC curve in the figure represents the unusable capacity value estimated according to the traditional fixed model, which remains constant throughout the process and cannot respond to changes in actual working conditions. The system starts the calibration process immediately after monitoring that the voltage meets the trigger condition.

[0108] (2) The execution of dynamic calibration: Figure 4 The NEW-UUSOC curve shows the value of unusable capacity after calibration by the method of the present application. The change process is as follows: In the initial stage of discharge, because the battery voltage is high, the weight factor (Weight) is large, and the system has low confidence in the voltage feedback, so the calibration is gentle. Therefore, the NEW-UUSOC value closely follows the initial UUSOC value and changes slowly.

[0109] In the middle and late stages of discharge, as the depth of discharge increases, the battery voltage gradually decreases, and the weight factor (Weight) decreases accordingly, and the system has increased confidence in the voltage feedback. At this time, the NEW-UUSOC curve deviates from the original UUSOC dashed line obviously and continuously. The calibration algorithm continuously corrects the unusable capacity downward according to the real-time calculated smoothed difference (delta_soc_avg). This process is smooth and asymptotic, effectively avoiding data jumps.

[0110] (3) Adaptability to load changes: It is worth noting that the slope of the NEW-UUSOC curve is not constant. By comparing the IBAT AVG (average discharge current) curve, it can be found that in the stage of increasing current (internal resistance pressure drop is more significant, and the error of unusable capacity is larger), the correction rate of NEW-UUSOC is accelerated; in the stage of decreasing current, the correction rate is slowed down accordingly. This proves that the method of the present application can adapt to the changes of the load, dynamically adjust the calibration strength, and embodies excellent intelligence and robustness.

[0111] In summary, the present embodiment proves by Figure 4 directly that the unusable capacity calibration method provided by the present application is not a one-time static adjustment, but a continuous, asymptotic, and intelligent dynamic feedback process. The system continuously generates a reference power value (VBAT_SOC) by real-time monitoring of the battery voltage (VBAT) and current (IBAT), calculates the error with the algorithm value, and finally corrects the estimated value of the unusable capacity by the weight factor control. As Figure 4 shown, the calibrated value (NEW-UUSOC) successfully converges from the initial error value to a new value closer to the real physical state of the battery.

[0112] This dynamic calibration mechanism is the core of the present application, which ensures that the power algorithm can continuously correct itself, thereby maintaining high accuracy under various complex working conditions and laying a solid foundation for the final realization of precise shutdown.

[0113] The present application also provides a terminal device battery unusable capacity calibration device 50, asFigure 5 As shown in the figure, the device comprises: The voltage acquisition module 510 is configured to acquire the current voltage and the average voltage of the terminal device battery in a plurality of consecutive judgment periods. The calibration procedure starting module 520 is configured to start the unusable capacity calibration procedure if the current voltage and the average voltage are both less than the preset voltage threshold in any judgment period. The reference power value acquisition module 530 is configured to, in the calibration procedure, calculate the open circuit voltage of the battery based on the battery internal resistance model according to the latest acquired current voltage and real-time discharge current, and query the pre-stored corresponding relationship curve of the OCV value and the power SOC to obtain the reference power value. The smooth difference calculation module 540 is configured to calculate the difference between the remaining capacity estimated by the battery power algorithm and the reference power value, and filter the difference in the plurality of consecutive judgment periods to obtain a smooth difference. The weight factor calculation module 550 is configured to calculate a weight factor based on the current voltage, the preset shutdown voltage and the preset voltage threshold through a linear interpolation formula, wherein the weight factor is used to represent the normalized relative position of the current voltage in the interval defined by the preset shutdown voltage and the preset threshold voltage, and 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 greater the value of the weight factor, the lower the degree of trust of the system to the smooth difference, and the two are inversely proportional. The unusable capacity correction module 560 is configured to dynamically correct the currently estimated unusable capacity according to the smooth difference and the weight factor to obtain the calibrated unusable capacity. The available capacity calculation module 570 is configured to calculate and output the available power of the terminal device according to the calibrated unusable capacity and the remaining capacity.

[0114] Optionally, the values of the preset voltage threshold and the preset shutdown voltage are 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.

[0115] In a third aspect, an embodiment of the present application provides a terminal device 600, as shown in the figure, comprising: Figure 6 As shown in the figure, the device comprises: At least one processor 601; The memory 602 is configured to store the executable instructions of the at least one processor. The at least one processor is configured to execute the instructions to implement the method of the first aspect.

[0116] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, when instructions in the computer readable storage medium are executed by a processor of a terminal device, the terminal device is enabled to perform the method of the first aspect.

[0117] The terminal device battery unusable capacity calibration method provided by the embodiments of the present application introduces a dynamic feedback calibration mechanism based on voltage, compared with the prior art, the following significant beneficial effects can be achieved: 1、The present application effectively improves the accuracy of battery power estimation in the low power interval, especially near the critical stage of the shutdown voltage, while ensuring the smoothness of the power display during the entire discharge process and allowing the error to be released smoothly. By introducing a reference power value (VBAT_SOC) based on real-time voltage and current back-propagation as a calibration reference in the interval close to the shutdown voltage, and dynamically correcting the unusable capacity (UUSOC), the present application can effectively eliminate the UUSOC estimation deviation caused by model error, temperature change, current fluctuation and other factors. This ensures that the remaining capacity (RM_SOC) is exactly equal to the unusable capacity (UUSOC) when the terminal device is discharged to the preset shutdown voltage, i.e. precise shutdown is achieved when BATT_SOC=0, fundamentally solving the problem of "premature shutdown" or "sudden shutdown" caused by inaccurate power estimation.

[0118] 2、Enhances the reliability and user trust of the power display. By triggering the double voltage condition (both the current voltage and the average voltage are lower than the threshold value) and combining the judgment mechanism of multiple consecutive periods, the voltage fluctuation interference caused by instantaneous load change is effectively filtered, preventing false triggering of the calibration process and ensuring the accuracy and reliability of the calibration operation. This makes the available power (BATT_SOC) displayed to the user more real and reliable, and the user can accurately estimate the device's battery life, improving the user experience.

[0119] 3、Achieves a smooth and stable calibration process. By introducing a weight factor (Weight) and establishing an inverse relationship between the weight factor and the degree of trust in the smoothing difference value, the method realizes intelligent dynamic adjustment of the calibration strength. In the high voltage interval, the calibration strength is soft, mainly relying on traditional algorithms; as the voltage decreases, the trust in the voltage feedback value is gradually increased, and the calibration strength is enhanced. This voltage-smoothed calibration strategy avoids the jump of the power display, ensuring the stability and smoothness of the calibration process.

[0120] In summary, the present application effectively solves the problem of accuracy decline caused by inaccurate estimation of unusable capacity at the end of discharge in the existing lithium battery power estimation scheme, and provides a high-precision, high-reliability and user-friendly power calibration scheme.

[0121] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and are not to be construed as limiting the present application, and that changes, modifications, substitutions and variations can be made by those skilled in the art without departing from the spirit and scope of the present application.

Claims

1. A method for calibrating the unavailable capacity of a terminal device battery, characterized in that: The method comprises: Obtain the current voltage and average voltage of the terminal device battery within multiple consecutive judgment cycles; If, within any judgment period, both the current voltage and the average voltage are less than the preset voltage threshold, the unavailable capacity calibration process is initiated; In the calibration process, the open circuit voltage of the battery is calculated based on the latest collected current voltage and real-time discharge current based on the battery internal resistance model, and the pre-stored correspondence curve between the OCV value and the state of charge (SOC) is queried to obtain the reference power value; Calculating the difference between the remaining capacity estimated by the battery power algorithm and the reference power value, and filtering the difference over multiple consecutive judgment cycles to obtain a smoothed difference; Based on the current voltage, the preset shutdown voltage, and the preset voltage threshold, a weight factor is calculated 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 ratio of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. A larger value of the weight factor indicates a lower degree of trust in the smoothed difference by the system, and the two are inversely proportional. Dynamically correcting the currently estimated unavailable capacity according to the smoothed difference and the weight factor to obtain a calibrated unavailable capacity; The available power of the terminal device is calculated and outputted according to the calibrated unavailable capacity and the remaining capacity.

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 as the battery temperature changes according to different battery characteristics and system design requirements.

3. The method according to claim 1, characterized in that After filtering the difference values ​​of a plurality of consecutive judgment cycles to obtain a smoothed difference value, the method further includes: Determining 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 current calibration operation is abandoned.

4. The method according to claim 1, wherein After filtering the difference values ​​of a plurality of consecutive judgment cycles to obtain a smoothed difference value, the method further includes: Determine whether the change rate of the smoothed difference value of the current judgment period and the smoothed difference value of the previous judgment period exceeds a preset change rate threshold; If the change rate exceeds the preset change rate threshold, the following limiting operations are performed in sequence: performing a first amplitude limiting process on the smoothed difference; Calculating a theoretical correction value of unavailable capacity based on the smoothed difference after the first clipping process; A second limiting process is performed on the theoretical correction value to ensure that the absolute value of the difference between the unusable capacity after calibration and the unusable capacity before calibration is not greater than the maximum change limit.

5. The method according to any one of claims 1 to 4, characterized in that The weight factor is calculated based on the current voltage, the preset shutdown voltage, and the preset voltage threshold by a linear interpolation formula, including: The weight factor is calculated using the following linear interpolation formula: Weight=(VBAT_NOW–VBAT_ZP) / (VTH–VBAT_ZP); Wherein, Weight represents a weight factor, VBAT_NOW represents a current voltage, the VBAT_ZP represents a preset shutdown voltage, and VTH represents the preset voltage threshold.

6. The method according to claim 5, characterized in that The dynamically correcting the currently estimated unavailable capacity according to the smoothed difference and the weight factor to obtain a calibrated unavailable capacity includes: NEW_UUSOC=UUSOC+(1–Weight)*delta_soc_avg; Among them, NEW_UUSOC is the calibrated unavailable capacity, UUSOC is the currently estimated unavailable capacity, and delta_soc_avg is the smoothed difference.

7. A terminal device battery unavailable capacity calibration device, characterized in that: The device comprises: The voltage acquisition module is used to obtain the current voltage and average voltage of the terminal device battery within multiple consecutive judgment cycles; a calibration process starting module, configured to start an unavailable capacity calibration process if both the current voltage and the average voltage are less than a preset voltage threshold within any judgment period; A reference power value acquisition module is used to calculate the open circuit voltage of the battery based on the battery internal resistance model according to the latest collected current voltage and real-time discharge current during the calibration process, and query a pre-stored corresponding relationship curve between the OCV value and the state of charge (SOC) to obtain a reference power value; a smoothed difference calculation module, configured to calculate the difference between the remaining capacity estimated by the battery power algorithm and the reference power value, and to filter the difference over a plurality of consecutive judgment cycles to obtain a smoothed difference; a weight factor calculation module, configured to calculate a weight factor based on the current voltage, the preset shutdown voltage, and the preset voltage threshold using a linear interpolation formula, wherein 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 ratio of the difference between the current voltage and the preset shutdown voltage to the length of the entire interval. A larger value of the weight factor indicates a lower degree of trust in the smoothed difference by the indicator system, and the two are inversely proportional. an unavailable capacity correction module, configured to dynamically correct the currently estimated unavailable capacity based on the smoothed difference and the weight factor to obtain a 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.

8. The device according to claim 7, 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 as the battery temperature changes according to different battery characteristics and system design requirements.

9. A terminal device, characterized in that: include: at least one processor; a 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 according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor of a terminal device, the terminal device is enabled to execute the method according to any one of claims 1 to 6.

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