An automatic cut-off system and method for overcharge monitoring of lithium batteries for communication equipment

Abstract

The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring automatic cut-off system and method, it is related to lithium battery monitoring technical field.The application discloses a kind of communication equipment lithium battery overcharge monitoring

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of lithium battery monitoring, in particular to a communication equipment lithium battery overcharge monitoring automatic cut-off system and method. BACKGROUND

[0002] A lithium battery is an energy storage device with lithium metal or lithium alloy as a positive electrode material and a non-aqueous electrolyte. Its core is composed of a positive electrode, a negative electrode, an electrolyte and a separator. With the advantages of high energy density, long cycle life and low self-discharge rate, lithium batteries have been widely used in consumer electronics, new energy vehicles, energy storage systems and other fields, and have become one of the core devices for energy storage and supply in modern society. Among them, the stability of the positive electrode material directly affects the safety performance of the lithium battery. In the charging and discharging process, the stability of the positive electrode crystal structure determines the efficiency of lithium ion deintercalation, and is closely related to whether the battery will have a thermal runaway and other safety accidents.

[0003] Overcharge is one of the most common safety hazards in the use of lithium batteries. When a lithium battery is continuously charged above the rated voltage, the positive electrode material will collapse due to excessive lithium ion deintercalation, and lattice oxygen will escape. The escaped oxygen reacts with the electrolyte to release a large amount of heat and gas, and if the heat accumulates and cannot be dissipated, it may cause the battery to swell, catch fire or even explode. Therefore, overcharge monitoring is a key link to ensure the safe operation of lithium batteries, and its core is to capture the characteristic signals (such as voltage change, temperature rise, oxygen escape rate, etc.) in the overcharge process in real time, judge the battery state in time and trigger protective measures.

[0004] The existing overcharge monitoring technology relies on indirect indicators such as voltage and temperature, which has obvious limitations: first, the response is lagging, the significant change in voltage and temperature often occurs after the irreversible damage to the positive electrode material, making it difficult to achieve early warning; second, the precision is insufficient, the temperature fluctuations and charging rate changes are not considered to interfere with the monitoring signals, and the drift error of the sensor after long-term use is ignored, resulting in a large deviation between the monitoring value and the actual state; third, it lacks foresight, only based on the current state to judge the risk, and cannot predict the overcharge trend in the future, which may cause safety accidents due to delayed protective action. These defects make it difficult for existing technology to meet the precision and advance requirements of lithium battery overcharge monitoring in high safety scenarios, so a communication equipment lithium battery overcharge monitoring automatic cut-off system and method is proposed to solve such problems. SUMMARY

[0005] Technical problems solved

[0006] In view of the deficiencies of the prior art, the application provides a communication equipment lithium battery overcharge monitoring automatic cut-off system and method, which solves the problems raised in the background art.

[0007] Technical scheme

[0008] To achieve the above object, the present application is implemented by the following technical solutions: a communication equipment lithium battery overcharge monitoring automatic cut-off system, comprising:

[0009] The data acquisition module is used for collecting overcharge associated data sets in the lithium battery charging process and pre-processing the overcharge associated data sets; the overcharge associated data sets include original collection data of the positive lattice oxygen escape rate;

[0010] The data analysis module is used for performing feature extraction analysis on the pre-processed overcharge associated data sets to obtain overcharge associated characteristic values; and based on the overcharge associated characteristic values, the original collection values of the positive lattice oxygen escape rate are corrected in accuracy to obtain accurate positive lattice oxygen escape rate;

[0011] The overcharge prediction module is used for taking the charging voltage change rate as an overcharge driving variable, performing trend analysis on the accurate positive lattice oxygen escape rate and the overcharge driving variable to obtain the positive lattice oxygen escape rate prediction value in the future preset time;

[0012] The overcharge judgment module is used for comparing the accurate positive lattice oxygen escape rate and the positive lattice oxygen escape rate prediction value with corresponding preset threshold values respectively to judge the current and future overcharge risk states;

[0013] The overcharge cut-off module is used for performing charging loop conduction or cut-off operation according to the overcharge risk state judgment result.

[0014] Preferably, the overcharge associated data sets further include battery temperature data, charging rate data, sensor drift calibration data, and charging voltage change rate data.

[0015] Preferably, the pre-processing step of the overcharge associated data sets is as follows:

[0016] For the collected overcharge associated data sets, the effective value range corresponding to each data type is preset based on the physical characteristics of the lithium battery, and abnormal data exceeding the effective range is removed;

[0017] The data processed by the above method is subjected to noise reduction processing by using the sliding average filtering method to eliminate high-frequency electromagnetic interference signals;

[0018] The data processed by the above method is converted into dimensionless values based on the initial state of the new battery as a reference to complete the pre-processing.

[0019] Preferably, the step of performing feature extraction analysis based on the pre-processed overcharge associated data sets is as follows:

[0020] From the battery temperature data, the real-time value and the change rate in the preset time are extracted as temperature influence features;

[0021] From the charging rate data, the current value and the ratio to the rated rate are extracted as the rate influence feature;

[0022] From the sensor drift calibration data, the cumulative drift and single sampling drift value are extracted as the sensor drift influence feature;

[0023] From the original collection data of the positive electrode lattice oxygen release rate, the instantaneous value and the average value within a preset time are extracted as the oxygen release rate original feature;

[0024] From the charging voltage change rate data, the real-time value and the change trend of continuous multiple sampling are extracted as the voltage change rate feature;

[0025] The temperature influence feature, the rate influence feature, the sensor drift influence feature, the oxygen release rate original feature and the voltage change rate feature are integrated to form the overcharge correlation feature value.

[0026] Preferably, the step of correcting the original collection value of the positive electrode lattice oxygen release rate in accuracy is as follows:

[0027] Based on the temperature influence feature in the overcharge correlation feature value, a temperature influence coefficient is calculated;

[0028] Based on the rate influence feature in the overcharge correlation feature value, a rate influence coefficient is calculated;

[0029] Based on the sensor drift influence feature in the overcharge correlation feature value, a sensor drift influence coefficient is calculated;

[0030] The temperature influence coefficient, the rate influence coefficient, the sensor drift influence coefficient and the original collection value of the positive electrode lattice oxygen release rate are coupled and operated to correct the accurate positive electrode lattice oxygen release rate.

[0031] Preferably, the specific steps of the trend analysis of the accurate positive electrode lattice oxygen release rate and the overcharge driving variable are as follows:

[0032] Combined with the current change slope of the accurate positive electrode lattice oxygen release rate, the positive electrode lattice oxygen release rate prediction value within a preset time in the future is derived by linear extrapolation method.

[0033] Preferably, the step of judging the current and future overcharge risk state is as follows:

[0034] The current overcharge critical threshold based on the overcharge destructive test calibration and the future overcharge warning threshold based on the oxygen release rate growth rate are preset;

[0035] If the accurate positive electrode lattice oxygen release rate is greater than or equal to the current overcharge critical threshold, it is determined that the current overcharge risk exists;

[0036] If the positive electrode lattice oxygen escape rate prediction value is greater than or equal to the future overcharge warning threshold, it is determined that there is a future overcharge risk;

[0037] If neither of the above conditions is met, it is determined that there is no overcharge risk.

[0038] Preferably, the logic of performing the charging circuit conduction or cut-off operation according to the overcharge risk state determination result is as follows:

[0039] If it is determined that there is a current overcharge risk or a future overcharge risk, the main circuit switch and the redundant magnetic holding relay are controlled to be turned off synchronously, and the charging circuit cut-off operation is performed.

[0040] If it is determined that there is no overcharge risk, the main circuit switch and the redundant magnetic holding relay are maintained in the conduction state, and normal charging is maintained.

[0041] A method for automatically cutting off overcharge of a lithium battery of a communication device, comprising the following steps:

[0042] Step 1: Collecting an overcharge associated data set during the charging process of the lithium battery, and preprocessing the overcharge associated data set; the overcharge associated data set includes original collected data of the positive electrode lattice oxygen escape rate;

[0043] Step 2: Feature extraction analysis is performed on the preprocessed overcharge associated data set to obtain overcharge associated feature values; and based on the overcharge associated feature values, the original collected values of the positive electrode lattice oxygen escape rate are corrected in accuracy to obtain accurate positive electrode lattice oxygen escape rate.

[0044] Step 3: Taking the charging voltage change rate as an overcharge driving variable, trend analysis is performed on the accurate positive electrode lattice oxygen escape rate and the overcharge driving variable to obtain a positive electrode lattice oxygen escape rate prediction value in a future preset time;

[0045] Step 4: Comparing the accurate positive electrode lattice oxygen escape rate and the positive electrode lattice oxygen escape rate prediction value with corresponding preset thresholds respectively to determine the current and future overcharge risk states.

[0046] Step 5: Performing the charging circuit conduction or cut-off operation according to the overcharge risk state determination result.

[0047] Advantages

[0048] The present application has the following advantages:

[0049] (1) The overcharge monitoring automatic cut-off system and method for the lithium battery of the communication equipment can accurately eliminate the interference of temperature fluctuation, charging rate change and sensor aging on the monitoring data by the systematic coupling correction of the temperature influence coefficient, the rate influence coefficient and the sensor drift influence coefficient of the original collection value of the oxygen release rate of the positive lattice, in combination with real-time accurate oxygen release rate monitoring, so that the oxygen release rate monitoring value is closer to the real state, early accurate identification of overcharge risk is realized, misjudgment or omission is avoided due to data deviation, and the accuracy and reliability of the overcharge monitoring of the lithium battery are improved from the source.

[0050] (2) The overcharge monitoring automatic cut-off system and method for the lithium battery of the communication equipment can obtain the future prediction value by calculating the current oxygen release rate change slope and linear extrapolation, in combination with the double judgment logic of the current overcharge critical threshold and the future overcharge early warning threshold, so that the development trend of the overcharge risk can be captured in advance, the current overcharge risk that has occurred is responded in time, the future overcharge risk that is about to occur is prewarned, the time redundancy of overcharge protection is greatly improved, irreversible damage of the battery caused by monitoring lag is effectively avoided, and the forward-looking and safety of the overcharge protection of the lithium battery are significantly enhanced.

[0051] Of course, it is not necessary for any product implementing the present application to achieve all the advantages described above. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 FIG. 1 is a structural diagram of the overcharge monitoring automatic cut-off system for the lithium battery of the communication equipment according to the present application;

[0053] Figure 2 FIG. 2 is a flowchart of the overcharge monitoring automatic cut-off method for the lithium battery of the communication equipment according to the present application. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0055] The embodiments of the present application provide a technical solution: an overcharge monitoring automatic cut-off system for the lithium battery of the communication equipment, as shown in FIG. 1, comprising: Figure 1

[0056] The data collection module is used for collecting the overcharge associated data set in the charging process of the lithium battery and pre-processing the overcharge associated data set; the overcharge associated data set includes the original collection data of the oxygen release rate of the positive lattice.

[0057] ​The data analysis module is configured to perform feature extraction analysis on the preprocessed overcharge correlation data set to obtain overcharge correlation feature values; and perform precision correction on the original collection value of the positive electrode lattice oxygen escape rate based on the overcharge correlation feature values to obtain a precise positive electrode lattice oxygen escape rate.

[0058] The overcharge prediction module is configured to take the charging voltage change rate as an overcharge driving variable, perform trend analysis on the precise positive electrode lattice oxygen escape rate and the overcharge driving variable, and obtain a positive electrode lattice oxygen escape rate prediction value in a future preset time.

[0059] The overcharge judgment module is configured to compare the precise positive electrode lattice oxygen escape rate and the positive electrode lattice oxygen escape rate prediction value with corresponding preset threshold values, respectively, to determine current and future overcharge risk states.

[0060] The overcharge cut-off module is configured to perform a charging loop conduction or cut-off operation according to the overcharge risk state determination result.

[0061] Specifically, the overcharge correlation data set further includes battery temperature data, charging rate data, sensor drift calibration data, and charging voltage change rate data.

[0062] The battery temperature data is collected by a certain brand NTC temperature sensor pasted on the positive electrode tab of the lithium battery, the sensor sampling interval is set to 50 milliseconds, the analog temperature signal output by the sensor is transmitted to a certain brand 16-bit analog-to-digital conversion chip, and after the chip converts the analog signal into a digital signal, the battery temperature data in ℃ is obtained.

[0063] The charging rate data is collected by a certain brand Hall current sensor connected in series in the charging loop, and is specifically obtained by ratio calculation of the real-time charging current value and the rated capacity labeled when the lithium battery is shipped.

[0064] The sensor drift calibration data is collected by a calibration module of a certain brand micro in-situ mass spectrometer for collecting the original data of the positive electrode lattice oxygen escape rate. The module automatically starts calibration after completing 100 samplings, compares the detection value of this sampling with the standard oxygen concentration signal value built-in the module, calculates the difference between the detection value and the standard oxygen concentration signal value as the cumulative drift, and records the difference between the sampling drift value and the last calibration drift value as the single sampling drift value.

[0065] The charging voltage change rate data is collected by a certain brand voltage sensor connected in parallel across the positive and negative electrodes of the lithium battery to collect the real-time charging voltage value, the sampling interval is 50 milliseconds, the difference between the voltage value of the current sampling period and the voltage value of the last sampling period is calculated, and then the difference is divided by the sampling interval 0.05 seconds to obtain the charging voltage change rate data in V / s, i.e. the charging voltage change rate.

[0066] The above-mentioned manner is adopted to collect various data, so as to comprehensively obtain key environmental and equipment parameters affecting the collection accuracy of the positive electrode lattice oxygen escape rate: the battery temperature directly affects the sensor sensitivity, the charging rate is related to the internal airflow disturbance of the battery, the sensor drift reflects the aging error of the equipment, and the charging voltage change rate reflects the advancement speed of the overcharging process. The complete collection of the four types of data provides comprehensive and reliable data support for subsequent preprocessing, feature extraction and accuracy correction, and ensures that the subsequent analysis can cover the main interference factors.

[0067] Specifically, the preprocessing steps of the overcharge associated data set are as follows:

[0068] For the collected overcharge associated data set, based on the physical property manual of the positive electrode material (such as NCM, LCO) of the lithium battery and 100 groups of standard charging experiment data, the effective value range corresponding to each data type is preset: the effective range of the positive electrode lattice oxygen escape rate original value is 0 to 5 ppm / s, the effective range of the battery temperature is -10℃ to 60℃, the effective range of the charging rate is 0.1C to 3C, the effective range of the sensor cumulative drift is -0.1 ppm / s to 0.1 ppm / s, and the effective range of the charging voltage change rate is -0.5V / s to 1V / s. The data exceeding the above preset range is determined as abnormal data and is removed;

[0069] For the data after the above abnormal data removal processing, a sliding average filtering method with a window size of 5 is used for noise reduction processing, that is, for each data point, 5 data including itself and the two adjacent data points before and after it are taken, the arithmetic mean of the 5 data is calculated, and the mean value is taken as the filtered effective data.

[0070] The data after the above filtering processing is taken as the initial value of each data collected when the new battery is charged for the first time as the reference value, and the ratio of each filtered data to the corresponding reference value is calculated to obtain the dimensionless overcharge associated data set, and the preprocessing is completed.

[0071] The above-mentioned preprocessing steps can gradually improve the data quality: the preset effective range can remove abnormal data caused by sudden factors such as sensor failure and electromagnetic interference, and avoid the interference of abnormal data on subsequent analysis; the sliding average filtering method can effectively suppress the signal fluctuation caused by high-frequency electromagnetic interference in the charging process, and improve the data smoothness; the dimensionless processing can eliminate the influence of the dimensional difference between different data types, so that the data of different dimensions such as temperature and rate have comparability, and lay a unified dimension foundation for subsequent feature extraction and coefficient calculation.

[0072] Specifically, based on the preprocessed overcharge associated data set, the steps of feature extraction analysis are as follows:

[0073] From the pre-processed battery temperature data, the dimensionless data at the current time is directly read as the temperature real-time value, and all temperature data collected in the last 1 second is selected. The difference between the last data value and the first data value in this time period is calculated and divided by 1 second to obtain the temperature change rate. The temperature real-time value and the temperature change rate are used as temperature influence characteristics together;

[0074] From the pre-processed charging rate data, the dimensionless data at the current time is directly read as the charging rate current value, and the ratio of the current value to the dimensionless reference value (the value is 1.0) corresponding to the rated rate is calculated. The charging rate current value and the ratio are used as the rate influence characteristics together;

[0075] From the pre-processed sensor drift calibration data, the dimensionless cumulative drift and single sampling drift value are directly read. The cumulative drift and single sampling drift value are used as the sensor drift influence characteristics together;

[0076] From the pre-processed positive electrode lattice oxygen evolution rate original collection data, the dimensionless data at the current time is directly read as the oxygen evolution rate instantaneous value. The arithmetic mean of all original data collected in the last 0.5 second is calculated. The oxygen evolution rate instantaneous value and the arithmetic mean are used as the oxygen evolution rate original characteristics together;

[0077] From the pre-processed charging voltage change rate data, the dimensionless data at the current time is directly read as the voltage change rate real-time value. The voltage change rate data of the last 3 consecutive samplings are selected. By comparing the size relationship between the last data and the previous data, the trend of the voltage change rate is determined. Specifically, data increase is an upward trend, data decrease is a downward trend, and data unchanged is a stable trend. The voltage change rate real-time value and the trend are used as the voltage change rate characteristics together;

[0078] The temperature influence characteristics, the rate influence characteristics, the sensor drift influence characteristics, the oxygen evolution rate original characteristics, and the voltage change rate characteristics are classified and summarized according to the data type to form the overcharge correlation characteristic value.

[0079] Specifically, the steps of precision correction of the original collection value of the positive electrode lattice oxygen evolution rate are as follows:

[0080] Based on the temperature influence characteristics in the overcharge correlation characteristic value, the temperature influence characteristics include the temperature real-time value and the temperature change rate. The actual temperature corresponding to the temperature real-time value is first back calculated, and then the actual temperature and the temperature change rate are substituted into the formula to calculate the temperature influence coefficient;

[0081] The temperature influence coefficient is obtained as follows:

[0082]

[0083] In the formula, represents the temperature influence coefficient, which is a dimensionless coefficient, reflecting the influence degree of temperature on the collection accuracy of the oxygen evolution rate of the positive electrode lattice oxygen. The greater the temperature factor, the greater the oxygen evolution rate collection error caused by the temperature factor; The smaller the temperature factor, the smaller the interference of the temperature on the collection accuracy; represents the actual temperature corresponding to the real-time temperature value, which is ℃, obtained by multiplying the real-time temperature value in the temperature influence characteristic by 25, representing the current actual temperature of the battery. The greater the deviation from 25℃, the greater the influence on The greater the deviation from 25℃, the greater the influence on When the temperature is higher than 25℃, the will increase, and when the temperature is lower than 25℃, the will decrease; 0.003 and 0.001 are fixed coefficients, which are obtained by linear fitting of experimental data through 50 sets of comparison experiments in the temperature range of-10℃ to 60℃, and are dimensionless coefficients; represents the temperature change rate in the temperature influence characteristic, which is ℃ / s, representing the speed of temperature change, The greater the temperature change rate, the faster the temperature rises or falls, The greater the temperature change rate, the more obvious the interference of the temperature on the oxygen evolution rate collection;

[0084] Based on the rate influence characteristic in the overcharge correlation characteristic value, the rate influence characteristic includes the current value of the charging rate and the charging rate ratio, and the charging rate ratio is selected to be substituted into the formula to calculate the rate influence coefficient;

[0085] The rate influence coefficient is obtained as follows:

[0086]

[0087] In the formula, represents the rate influence coefficient, which is a dimensionless coefficient, reflecting the influence degree of the charging rate on the collection accuracy of the oxygen evolution rate of the positive electrode lattice oxygen. The greater the rate influence coefficient, the smaller the interference of the charging rate on the collection accuracy; The smaller the rate influence coefficient, the greater the collection error at high rate; 0.08 is a fixed coefficient, which is obtained by nonlinear fitting of experimental data through 30 sets of comparison experiments in the charging rate range of 0.1C to 3C, and is a dimensionless coefficient; represents the charging rate ratio in the rate influence characteristic, which is a dimensionless coefficient, and is specifically obtained by dividing the current value of the charging rate by the rated reference value 1.0, representing the proportion of the current charging rate relative to the rated rate. The greater the charging rate ratio, The smaller the charging rate ratio, the more significant the interference of the rate on the oxygen evolution rate collection;

[0088] Based on the sensor drift influence feature in the overcharge correlation characteristic value, the sensor drift influence feature includes the cumulative drift amount and the single sampling drift value, the two values are substituted into the formula, and the sensor drift influence coefficient is calculated;

[0089] The sensor drift influence coefficient is obtained in the following way:

[0090]

[0091] In the formula, The sensor drift influence coefficient is a dimensionless coefficient, which reflects the influence degree of the sensor drift on the collection accuracy of the positive electrode lattice oxygen evolution rate. The greater the sensor drift, the smaller the interference with the collection accuracy; The smaller the drift, the greater the collection error caused by the drift; 0.05, 0.02 are fixed coefficients, which are obtained by statistical correlation between the drift and the detection error through 1000 times of cyclic calibration experiments of the sensor, and are dimensionless coefficients; The cumulative drift amount in the sensor drift influence feature is represented by ppm / s, which represents the total drift degree of the sensor after long-term use. The greater the cumulative drift amount, The smaller the cumulative drift amount, the more obvious the interference of the sensor aging with the oxygen evolution rate collection; The single sampling drift value in the sensor drift influence feature is represented by ppm / s, which represents the drift change of the sensor at each sampling, The greater the single sampling drift value, The smaller the single sampling drift value, the more significant the interference of the single sampling drift with the collection accuracy;

[0092] Based on the temperature influence coefficient, the rate influence coefficient, and the sensor drift influence coefficient calculated above, and combined with the oxygen evolution rate original feature in the overcharge correlation characteristic value, including the oxygen evolution rate original collection value, the four values are substituted into the coupling formula, and the accurate positive electrode lattice oxygen evolution rate is corrected.

[0093] The accurate positive electrode lattice oxygen evolution rate is obtained in the following way:

[0094]

[0095] In the formula, The accurate positive electrode lattice oxygen evolution rate represents the corrected oxygen evolution rate true value, which directly reflects the intensity of the battery positive electrode lattice oxygen evolution. The greater the accurate positive electrode lattice oxygen evolution rate, the higher the overcharge risk; The smaller the accurate positive electrode lattice oxygen evolution rate, the lower the overcharge risk, which is ppm / s; represents the original collection value in the original characteristic of oxygen evolution rate, with unit of ppm / s, specifically represents the uncorrected oxygen evolution rate data, which is the basis for subsequent precision correction. The size reflects the original collection of oxygen evolution rate; represents the temperature influence coefficient, which is a dimensionless coefficient; represents the rate influence coefficient, which is a dimensionless coefficient; represents the sensor drift influence coefficient, which is a dimensionless coefficient, the temperature influence coefficient, the rate influence coefficient, and the sensor drift influence coefficient function to correct the interference of the corresponding factors to closer to the true value.

[0096] The precision correction adopts the above steps, which can systematically offset the errors caused by various interference factors: the calculation of the temperature influence coefficient, the rate influence coefficient, and the sensor drift influence coefficient is based on the fixed coefficients obtained by fitting a large amount of comparative experimental data, which ensures that the coefficients can truly and accurately reflect the influence of various interference factors on the oxygen evolution rate collection value; the coupling operation adopts a multiplication model, which conforms to the superimposed influence law of temperature, rate, drift, and other interference factors on the oxygen evolution rate collection value, the calculation logic is simple and clear, the operation speed is fast, and it is suitable for the low-power operation requirements of communication equipment; the accurate positive lattice oxygen evolution rate obtained by correction effectively improves the accuracy of the core monitoring data, and provides a high-quality data basis for subsequent overcharge prediction and risk judgment.

[0097] Specifically, the specific steps of trend analysis on the accurate positive lattice oxygen evolution rate and overcharge driving variable are as follows:

[0098] The overcharge driving variable is determined as the charging voltage change rate, which is obtained after preprocessing the collected charging voltage data, including abnormal data elimination, sliding average filtering, and dimensionless, with unit of V / s;

[0099] The accurate positive lattice oxygen evolution rate data collected in the last 5 sampling periods are obtained, with a sampling interval of 100 milliseconds, and the current change slope is calculated by linear regression method;

[0100] The current change slope is obtained as follows:

[0101]

[0102] In the formula, in the formula, represents the current change slope, with unit of ppm / s², reflecting the change trend of the accurate positive lattice oxygen evolution rate of the last 5 samples. is positive and the larger it is, the faster the oxygen evolution rate rises, and the more rapidly the overcharge risk grows; is negative, the oxygen evolution rate shows a downward trend, and the overcharge risk decreases;​ represents the accurate positive electrode lattice oxygen release rate of the i-th sampling, with unit of ppm / s, which is the true value of the corrected oxygen release rate of each of the last 5 samplings; i is the sampling serial number (1 to 5), which is a dimensionless number; the summation operation in the numerator and denominator is used to fit the slope by linear regression, reflecting the trend of the oxygen release rate.

[0103] The future preset time is set to 1 second, and the positive electrode lattice oxygen release rate prediction value in the future preset time is derived by linear extrapolation based on the calculated current change slope and the accurate positive electrode lattice oxygen release rate of the last sampling;

[0104] The future positive electrode lattice oxygen release rate prediction value is obtained in the following manner:

[0105]

[0106] In the formula, represents the future positive electrode lattice oxygen release rate prediction value, with unit of ppm / s, which is the estimation of the oxygen release rate in the future 1 second, used to judge the overcharge risk in advance. The larger N is, the higher the estimated future overcharge risk is; the smaller N is, the lower the estimated future overcharge risk is; represents the accurate positive electrode lattice oxygen release rate of the 5th, i.e. the last sampling, with unit of ppm / s; represents the current change slope, with unit of ppm / s2; represents the future preset time, which is 1 second, with unit of s.

[0107] Specifically, the steps of judging the current and future overcharge risk state are as follows:

[0108] A preset current overcharge critical threshold is calibrated by an overcharge destructive test: 20 battery samples of the same model and specification as the target lithium battery are selected, and overcharged at 0.5C rate continuously in a 25℃ normal temperature environment. The positive electrode lattice oxygen release rate when the electrolyte of each sample is decomposed obviously (gas production rate > 1 mL / min) is monitored, and the arithmetic mean of the rate data of the 20 samples is calculated as the current overcharge critical threshold;

[0109] A preset future overcharge warning threshold is set based on the current overcharge critical threshold, combined with the calculated oxygen release rate growth rate, i.e. the current change slope, and the warning advance coefficient is set to 0.8 seconds, and the future overcharge warning threshold is derived by formula;

[0110] The current and future overcharge risk state is judged: if the accurate positive electrode lattice oxygen release rate is greater than or equal to the current overcharge critical threshold, it is determined that the current overcharge risk exists; if the future positive electrode lattice oxygen release rate prediction value is greater than or equal to the future overcharge warning threshold, it is determined that the future overcharge risk exists; if neither of the above conditions is met, it is determined that no overcharge risk exists.

[0111] Specifically, according to the overcharge risk state judgment result, the logic of executing the charging loop conduction or cut-off operation is as follows:

[0112] If it is determined that there is a current overcharge risk or a future overcharge risk, the overcharge judgment module outputs a high-level cut-off signal to the overcharge cut-off module, the overcharge cut-off module controls a certain brand of MOSFET drive chip to output a 1.5 ampere drive current, which is synchronously transmitted to the control end of the main loop switch and the redundant magnetic latching relay, the main loop switch is turned off within 50 nanoseconds, the redundant magnetic latching relay loses power to open the contact, and the charging main loop is cut off together. The state detection unit collects on-off feedback signals, and outputs a cut-off completion signal when both are disconnected.

[0113] If it is determined that there is no overcharge risk, the overcharge judgment module outputs a low-level conduction signal to the overcharge cut-off module, the overcharge cut-off module controls the MOSFET drive chip to output a 0.5 ampere maintenance current, the main loop switch remains on, and the redundant magnetic latching relay continues to be powered to maintain the contact on, thereby maintaining the normal conduction of the charging loop together. The state detection unit collects the conduction feedback signal to ensure the stability of the loop.

[0114] An overcharge monitoring and automatic cut-off method for a communication equipment lithium battery, as shown in Figure 2 , comprising the following steps:

[0115] Step 1: Collect the overcharge associated data set during the charging process of the lithium battery, and pre-process the overcharge associated data set;

[0116] Step 2: Perform feature extraction analysis on the pre-processed overcharge associated data set to obtain overcharge associated feature values; and based on the overcharge associated feature values, perform precision correction on the original collected value of the positive lattice oxygen escape rate to obtain a precise positive lattice oxygen escape rate;

[0117] Step 3: Taking the charging voltage change rate as the overcharge driving variable, perform trend analysis on the precise positive lattice oxygen escape rate and the overcharge driving variable to obtain a positive lattice oxygen escape rate prediction value within a preset future time;

[0118] Step 4: Compare the precise positive lattice oxygen escape rate and the positive lattice oxygen escape rate prediction value with the corresponding preset threshold values, respectively, to determine the current and future overcharge risk states;

[0119] Step 5: According to the overcharge risk state judgment result, execute the charging loop conduction or cut-off operation.

[0120] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting; it is not intended to exclude myriad other embodiments of the present application that other presenters can develop. It is also possible, however, that only a single element can be present. It is further noted that such a term as "comprising" is intended to mean that the embodiments include the recited elements, but not excluding other elements. "Consisting essentially of when used herein in relation to a composition, means that the composition includes the recited elements, and can include additional elements, so long as the additional elements do not materially alter the basic and novel characteristics of the claimed composition. "Consisting of" when used herein in relation to a composition, means that the composition includes the recited elements, and no additional elements.

[0121] The preferred embodiments of the application disclosed above are only to help explain the principles of the present application. The preferred embodiments do not describe all the details of the present application, nor limit the present application to only the specific embodiments described. It is apparent that many modifications and variations can be made to the present application based on the content of the present disclosure. The present disclosure selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. An automatic overcharge monitoring and disconnection system for lithium batteries in communication equipment, characterized in that, include: Data acquisition module: used to collect overcharge-related datasets during the lithium battery charging process and to preprocess the overcharge-related datasets; The overcharge correlation dataset includes raw data on the oxygen escape rate from the positive electrode lattice; Data analysis module: used to perform feature extraction and analysis on the preprocessed overfilling association dataset to obtain overfilling association feature values; Based on the overcharge correlation feature value, the original collected value of the positive electrode lattice oxygen escape rate is then corrected to obtain the accurate positive electrode lattice oxygen escape rate. Overcharge prediction module: Used to perform trend analysis on the precise positive electrode lattice oxygen escape rate and the overcharge driving variable with the charging voltage change rate as the overcharge driving variable, and obtain the predicted value of the positive electrode lattice oxygen escape rate within a preset time period in the future. Overcharge detection module: used to compare the accurate positive lattice oxygen escape rate and the predicted positive lattice oxygen escape rate with the corresponding preset thresholds to determine the current and future overcharge risk status; Overcharge cut-off module: Used to perform charging circuit connection or disconnection operation based on the overcharge risk status judgment result.

2. The automatic overcharge monitoring and disconnection system for lithium batteries in communication equipment according to claim 1, characterized in that: The overcharge correlation dataset also includes: battery temperature data, charging rate data, sensor drift calibration data, and charging voltage change rate data.

3. The automatic overcharge monitoring and disconnection system for lithium batteries in communication equipment according to claim 1, characterized in that: The preprocessing steps for the overcharged associated dataset are as follows: Step 1: For the collected overcharge-related dataset, based on the physical characteristics of lithium batteries, preset the valid value range for each data type and remove abnormal data that exceeds the valid range. Step 2: For the data processed in Step 1 above, noise reduction is performed using the moving average filtering method to eliminate high-frequency electromagnetic interference signals. Step 3: Convert the data processed in Step 2 into dimensionless values ​​based on the initial state of the new battery to complete the preprocessing.

4. The automatic overcharge monitoring and disconnection system for lithium batteries in communication equipment according to claim 1, characterized in that: The steps for feature extraction and analysis of the preprocessed over-aggregated dataset are as follows: Extract real-time values ​​and the rate of change within a preset time period from battery temperature data as temperature influence characteristics; Extract the current value and its ratio to the rated rate from the charging rate data as the rate-affected feature; From the sensor drift calibration data, the cumulative drift amount and the drift value of a single sampling are extracted as sensor drift influence characteristics; From the raw data of oxygen escape rate in the positive electrode lattice, the instantaneous value and the average value within a preset time period are extracted as the raw features of oxygen escape rate. From the charging voltage change rate data, extract the real-time value and the change trend of multiple consecutive samplings as voltage change rate features; By integrating the characteristics of temperature influence, rate influence, sensor drift influence, original oxygen escape rate, and voltage change rate, an overcharge-related characteristic value is formed.

5. The automatic overcharge monitoring and disconnection system for lithium batteries in communication equipment according to claim 1, characterized in that: The steps for refining the accuracy of the original collected values ​​of oxygen escape rate from the positive electrode lattice are as follows: Calculate the temperature influence coefficient based on the temperature influence characteristics in the overcharge correlation eigenvalues; Calculate the ratio influence coefficient based on the ratio influence feature in the overcharge correlation feature value; Based on the sensor drift influence characteristics in the overcharge correlation feature value, the sensor drift influence coefficient is calculated; The temperature influence coefficient, rate influence coefficient, and sensor drift influence coefficient are coupled with the original collected value of the positive electrode lattice oxygen escape rate to obtain the accurate positive electrode lattice oxygen escape rate.

6. The automatic overcharge monitoring and disconnection system for a communication device lithium battery according to claim 1, characterized in that: The specific steps for trend analysis of the oxygen escape rate and overcharge driving variable in the precise cathode lattice are as follows: By combining the current slope of the precise change in the oxygen escape rate of the cathode lattice, the predicted value of the oxygen escape rate of the cathode lattice within a preset time period is derived by linear extrapolation.

7. The automatic overcharge monitoring and disconnection system for lithium batteries in communication equipment according to claim 1, characterized in that: The steps for determining the current and future overcharging risk status are as follows: The current overcharge critical threshold is preset based on the overcharge destructive test calibration, and the future overcharge warning threshold is derived based on the oxygen escape rate growth rate. If the precise measurement of the oxygen escape rate from the positive electrode lattice is greater than or equal to the current overcharge critical threshold, it is determined to be an overcharge risk. If the predicted oxygen escape rate of the positive electrode lattice is greater than or equal to the future overcharge warning threshold, it is determined to be a future overcharge risk. If neither of these conditions is met, it is determined that there is no risk of overcharging.

8. The automatic overcharge monitoring and disconnection system for lithium batteries in communication equipment according to claim 1, characterized in that: The logic for performing the charging circuit on or off operation based on the overcharge risk status judgment result is as follows: If a current or future overcharge risk is identified, the main circuit switch and redundant magnetic latching relay are simultaneously disconnected to execute a charging circuit cutoff operation. If it is determined that there is no risk of overcharging, maintain the main circuit switch and redundant magnetic latching relay in the conducting state to maintain normal charging.

9. A method for automatic overcharge monitoring and disconnection of lithium batteries in communication devices, used to implement the automatic overcharge monitoring and disconnection system for lithium batteries in communication devices as described in any one of claims 1-8, characterized in that: Includes the following steps: Step 1: Collect overcharge correlation dataset during the lithium battery charging process and preprocess the overcharge correlation dataset; the overcharge correlation dataset includes the raw collected data of the oxygen escape rate of the positive electrode lattice; Step 2: Perform feature extraction analysis on the preprocessed overcharge correlation dataset to obtain overcharge correlation feature values; then, based on the overcharge correlation feature values, perform precision correction on the original collected values ​​of positive electrode lattice oxygen escape rate to obtain the accurate positive electrode lattice oxygen escape rate. Step 3: Using the charging voltage change rate as the overcharge driving variable, perform trend analysis on the precise positive electrode lattice oxygen escape rate and the overcharge driving variable to obtain the predicted value of the positive electrode lattice oxygen escape rate within a preset time period. Step 4: Compare the precise positive lattice oxygen escape rate and the predicted positive lattice oxygen escape rate with the corresponding preset thresholds to determine the current and future overcharge risk status. Step 5: Based on the overcharge risk assessment result, perform the charging circuit connection or disconnection operation.

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