Detection management system and method in battery charging process

Abstract

The invention discloses a detection management system and method in a battery charging process, and relates to the technical field of battery charging detection, and the method comprises the steps: obtaining a charging test record of a battery, obtaining battery type distinguishing data in a charging platform, and detecting the battery type of the battery; acquiring an initial charging record of the battery, acquiring a historical contrast charging record of a reference battery from the charging platform based on the type detection data, and evaluating the battery state approximation degree between the battery and the reference battery in the current period; the charging strategy of the battery is adjusted, the battery detection range of the target reference battery is obtained, and abnormity detection is carried out on the charging state of the battery; the suspected abnormal battery is subjected to power-off standing, the suspected abnormal battery after power-off standing is charged again, the suspected abnormal battery is subjected to anomaly detection, an abnormal battery is obtained, the abnormal battery is subjected to power-off, and an alarm prompt is sent to a user and a worker through a charging platform.

Description

Technical Field

[0001] The present invention relates to the technical field of battery charging detection, and in particular to a detection management system and method during battery charging. Background Art

[0002] It is very important to detect the battery type and battery status during the battery charging process. The main reasons are as follows: 1. Ensure charging safety: During the battery charging process, different batteries have different voltage and current tolerance ranges. Once the battery is charged with mismatched voltage and current during the charging process, it is very likely to cause the battery to release harmful gases or even explode; 2. Optimize the charging strategy. Different types of batteries require specific charging curves for charging. For example, lithium-ion batteries need to be charged with constant voltage and constant current, while lead-acid batteries need to be charged in stages. The appropriate voltage and current can greatly shorten the charging time and reduce energy loss; 3. Extend battery life. Wrong charging methods, such as using high voltage for nickel-hydrogen batteries, will accelerate the degradation of electrode materials.

[0003] Traditional methods for detecting the type and status of batteries have certain shortcomings. Not only are they unable to quickly identify the type of battery, but the battery status will also change due to different battery usage conditions. Even for batteries of the same type, the most suitable charging strategies are different. Therefore, it is impossible to accurately detect the status of the charged battery, and thus it is impossible to adjust and optimize the battery charging strategy according to the actual situation of the battery during the battery charging process, and it is also impossible to accurately detect battery faults, which not only leads to a decrease in battery charging efficiency, but may even cause safety accidents. Summary of the invention

[0004] The object of the present invention is to provide a detection management system and method for a battery charging process to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: a detection and management method during battery charging, the method comprising: Step S100: obtaining a charging test record of the battery, obtaining battery type differentiation data in the charging platform, detecting the battery type of the battery, and obtaining battery type detection data; Step S200: obtaining an initial charging record of the battery, obtaining a historical comparison charging record of a reference battery from a charging platform based on the type detection data, evaluating the degree of similarity between the battery state in the current cycle and the reference battery, and obtaining a target reference battery; Step S300: obtaining a reference charging strategy of a target reference battery, adjusting the charging strategy of the battery, obtaining a battery detection range of the target reference battery, performing abnormality detection on the charging state of the battery, and obtaining a suspected abnormal battery; Step S400: power off the suspected abnormal battery and let it stand, recharge the suspected abnormal battery after power off and standing, re-detect the suspected abnormal battery for abnormality, obtain the abnormal battery, power off the abnormal battery, and send an alarm to users and staff through the charging platform.

[0006] Furthermore, step S100 includes: Step S101: when the battery is charged in the current cycle, a high-frequency AC signal is superimposed on the battery charging current, and a current pulse of a preset duration is inserted, and the battery charging current is paused at the same time, and the battery charging is tested and recorded to obtain a charging test record; Step S102: obtaining the voltage signal V´(t) and the current signal I´(t) collected during the test period from the charging test record, and converting the voltage signal V´(t) and the current signal I´(t) into the frequency domain by Fourier transform to obtain V´(f) and I´(f); Calculate the complex impedance of the battery: Z(f)=V´(f) / I´(f)=R(f)+jX(f), where R(f) is the real part of the complex impedance Z(f) and X(f) is the imaginary part of the complex impedance. Calculate the impedance phase angle of the battery at θ(f)=arctan(X(f) / R(f)); Step S103: Obtain the change value △V and the minimum value V of the battery charging voltage during the insertion current pulse from the charging test record min , get the current value I of the current pulse pulse , calculate the changing resistance of the battery r=△V / I pulse ; Obtain the steady-state voltage V of the battery after the test, and fit the voltage-time curve V(t) of the battery after the current pulse is inserted into the first-order exponential model: V(t)=V+(V min -V)·e （-t / τ） , τ is the time constant, based on the first-order exponential model, the time constant τ of the battery is obtained; Step S104: Detect the battery type of the battery. The specific process is as follows: Obtaining battery type differentiation data in the charging platform, the battery type differentiation data including the time constant, variable resistance, complex impedance at a preset frequency, and impedance phase angle range of each battery type; When the time constant τ, the variable resistance r, the complex impedance Z(f) and the impedance phase angle θ(f) of the battery are all within the range corresponding to a certain battery type, the certain battery type is taken as the battery type of the battery, and the certain battery type is recorded as the detected battery type of the battery, and the battery type is collected to obtain the battery type detection data; In the above steps, the battery type is detected by testing the battery and observing the battery reaction. This method is not only rapid, but also does not require complex model training, has low computing power requirements, has a low probability of detection errors, and is applicable to mainstream battery types.

[0007] Further, step S200 includes: Step S201: obtaining a detected battery type of a battery from type detection data, obtaining batteries of the same type as the detected battery type in a charging platform and recording them as reference batteries, and obtaining historical comparison charging records of each reference battery; Obtain data corresponding to the current, voltage, and temperature of the reference battery charging from the historical reference charging records; Step S202: obtaining the initial charging record of the battery in the current cycle, and obtaining data corresponding to the current, voltage, and temperature of the battery charging from the initial charging record; Preprocess the data corresponding to the current, voltage and temperature in the historical control charging records and the initial charging records; Set the unit time t´, calculate and integrate the battery current in the initial charging record within the unit time, and obtain the battery charging capacity Q within the unit time; Get the temperature change rate of the battery in the initial charging record within the cth unit time v c =T c / t´,T c is the change in temperature of the battery at the initial time point within the cth unit time; The average voltage value, temperature change rate and charging capacity of the battery are used as the charging characteristic parameters of the battery. The various charging characteristic parameters of the battery within a number of unit time lengths are obtained from the initial charging records, normalized and collected to obtain the charging data set P of the battery, wherein the cth element in the charging data set P is the value of the various charging characteristic parameters of the battery within the cth unit time length; Step S203: obtaining the duration and charging data set of the historical control charging record of the reference battery, and dividing the charging data set of the historical control charging record based on the duration corresponding to the initial charging record to obtain a plurality of marked charging data sets, wherein the total number of elements in different marked charging data sets is n, and n is greater than the total number of elements in the charging data set m; Step S204: Obtain a certain labeled data set G in the reference battery, and calculate the i-th element in the certain labeled data set G g i , and the jth element p in the charging data set P j The characteristic distance d(g i , p j ); Based on a certain labeled data set G and a battery charging data set P, a distance matrix H is constructed, the distance matrix H is initialized and boundary conditions are set, and the element h(i,j)=d(g i , p j )+min{h(i-1,j), h(i,j-1), h(i-1,j-1)}; Get the last element h(m,n) in the distance matrix H and calculate the difference value γ between a certain labeled data set G and a charging data set P (g,p) : , Obtaining the reciprocal of the minimum value of the difference between a plurality of marked charging data sets in the reference battery and the charging data set P as an approximate value of the state of charge between the reference battery and the battery; Step S205: obtaining a reference battery corresponding to the maximum value of the approximate state of charge between the battery and each reference battery, and recording it as a target reference battery, and determining whether the battery states of the target reference battery and the battery are similar.

[0008] Furthermore, step S300 includes: Step S301: obtaining a reference charging strategy of a target reference battery in a charging platform, wherein the reference charging strategy includes a change curve of voltage and current corresponding to the target reference battery during charging; Step S302: adjusting the charging strategy of the battery based on the reference charging strategy, specifically: obtaining the remaining power of the battery in the current cycle, obtaining the voltage and current corresponding change curves after the power of the target reference battery is the remaining power from the reference charging strategy, and using them as the voltage and current change curves when the battery is charged in the current cycle; Step S303: obtaining a battery detection range of the target reference battery, where the battery detection range includes a characteristic range corresponding to each battery detection parameter in the target reference battery, wherein the characteristic range is a range consisting of normal maximum and minimum values ​​of the battery detection parameters in the target reference battery; The adjusted charging strategy is used to adjust the voltage and current of the battery charging, and the abnormality detection of the battery charging state is performed. The specific detection process is as follows: When the maximum value or minimum value of a battery detection parameter in the battery is detected to be not within the characteristic range of the battery detection parameter, the battery charging state is determined to be abnormal and is recorded as a suspected abnormal battery.

[0009] Furthermore, step S400 includes: Step S401: obtaining a suspected abnormal battery in the charging platform, powering off the suspected abnormal battery, and keeping it idle for a preset characteristic unit time, charging the suspected abnormal battery again, and monitoring the charging of the suspected abnormal battery to obtain data corresponding to various battery detection parameters of the suspected abnormal battery; Step S402: When the maximum value or minimum value of a battery detection parameter of the suspected abnormal battery is detected again and is not within the characteristic range of the battery detection parameter, the suspected abnormal battery is determined to be abnormal and recorded as an abnormal battery. Otherwise, the adjusted charging strategy is continued to be used for charging; The abnormal battery in the charging platform is powered off, and an alarm is sent to the user and staff of the abnormal battery through the charging platform to handle the abnormal battery.

[0010] In order to better implement the above method, a detection and management system for battery charging process is also proposed, the system includes a battery type detection module, an approximate evaluation module, an abnormality detection module and an abnormality alarm module; A battery type detection module, used to detect the battery type of the battery and obtain battery type detection data; An approximate evaluation module is used to evaluate the approximation degree of the battery state between the battery in the current cycle and the reference battery to obtain a target reference battery; An abnormality detection module is used to detect abnormalities in the charging state of the battery and obtain suspected abnormal batteries; The abnormal alarm module is used to re-detect the abnormality of the suspected abnormal battery, obtain the abnormal battery, cut off the power of the abnormal battery, and send an alarm to the user and staff through the charging platform to prompt the abnormal battery to be abnormal.

[0011] Further, the battery type detection module includes a charging test unit and a battery type detection unit; A charging test unit, used to test and record the charging of the battery to obtain a charging test record; The battery type detection unit is used to detect the battery type of the battery according to the charging test record to obtain the battery type detection data.

[0012] Further, the approximate assessment module includes a difference analysis unit and an approximate assessment unit; A difference analysis unit, used to perform difference analysis on the charging data set of the battery and each marked data set in the reference battery, and obtain a difference value between the charging data set and each marked data set; The approximate evaluation unit is used to obtain the approximate value of the charging state of the battery and the reference battery according to the difference value, analyze the degree of similarity of the charging state between the battery and the reference battery, and obtain the target reference battery.

[0013] Further, the anomaly detection module includes a charging strategy adjustment unit and an anomaly detection unit; A charging strategy adjustment unit, used to obtain a reference charging strategy of a target reference battery of the battery and adjust the charging strategy of the battery; The abnormality detection unit is used to charge the battery using the adjusted charging strategy and perform abnormality detection on the charging state of the battery to obtain a suspected abnormal battery.

[0014] Further, the abnormal alarm module includes an abnormal alarm unit; The abnormal alarm unit is used to cut off the power supply of the suspected abnormal battery, charge the suspected abnormal battery after the power is cut off, perform abnormal detection on the suspected abnormal battery again, obtain the abnormal battery, and issue an abnormal alarm for the abnormal battery. An alarm prompt is sent to the user and staff of the abnormal battery through the charging platform to remind them to deal with the abnormal battery.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention realizes intelligent detection and management of the battery charging process. Firstly, because different battery types have different characteristics, the characteristics exhibited by the batteries will also be different. The present invention first applies high-frequency AC signals and current pulses to the charged batteries to record the reactions of the batteries, thereby obtaining a series of data. The battery type of the battery is quickly detected through the values ​​corresponding to these data and in combination with the ranges corresponding to different types of batteries. In addition, considering the actual situation that even if the battery types of the batteries are the same, the states of different batteries will be different, the battery state of the battery in the current cycle and the approximate states between different batteries in the database are analyzed, thereby optimizing the battery charging strategy. The battery detection range of the target reference battery of the battery is used as a reference to perform abnormal detection on the currently charged battery. In order to prevent false detection, the battery abnormality detection is more accurate by cutting off the power and letting it stand for a while before performing the detection. This not only helps to improve the charging efficiency of the battery, but also greatly protects the charging safety of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a method flow chart of a detection management method during battery charging of the present invention; Figure 2 It is a module schematic diagram of a detection and management system during battery charging of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution, a detection and management method during battery charging, the method comprising: Step S100: obtaining a charging test record of the battery, obtaining battery type differentiation data in the charging platform, detecting the battery type of the battery, and obtaining battery type detection data; Wherein, step S100 includes: Step S101: when the battery is charged in the current cycle, a high-frequency AC signal is superimposed on the battery charging current, and a current pulse of a preset duration is inserted, and the battery charging current is paused at the same time, and the battery charging is tested and recorded to obtain a charging test record; For example, the specific operation of superimposing a high-frequency AC signal on the battery charging current and inserting a current pulse of a preset duration is as follows: A small high-frequency AC signal (frequency range: 1 Hz–10 kHz, amplitude: <5% rated current) is superimposed on the DC charging current of the battery. During the charging process, a short current pulse is inserted, usually a current pulse I pulse 1A, duration is 10ms, and the battery charging current is suspended; Step S102: obtaining the voltage signal V´(t) and the current signal I´(t) collected during the test period from the charging test record, and converting the voltage signal V´(t) and the current signal I´(t) into the frequency domain by Fourier transform to obtain V´(f) and I´(f); Calculate the complex impedance of the battery: Z(f)=V´(f) / I´(f)=R(f)+jX(f), where R(f) is the real part of the complex impedance Z(f) and X(f) is the imaginary part of the complex impedance. Calculate the impedance phase angle of the battery at θ(f)=arctan(X(f) / R(f)); Step S103: Obtain the change value △V and the minimum value V of the battery charging voltage during the insertion current pulse from the charging test record min , get the current value I of the current pulse pulse , calculate the changing resistance of the battery r=△V / Ipulse ; Obtain the steady-state voltage V of the battery after the test, and fit the voltage-time curve V(t) of the battery after the current pulse is inserted into the first-order exponential model: V(t)=V+(V min -V)·e （-t / τ） , τ is the time constant, based on the first-order exponential model, the time constant τ of the battery is obtained; For example, if the steady-state voltage V, i.e., the rate of change of the voltage after the test within a certain period of time is less than the rate of change threshold, then the voltage is set as the steady-state voltage; For example, the calculation formula for the time constant τ is: , Among them, t end The time required for the battery voltage to stop changing after a current pulse is inserted; Step S104: Detect the battery type of the battery. The specific process is as follows: Obtaining battery type differentiation data in the charging platform, the battery type differentiation data including the time constant, variable resistance, complex impedance at a preset frequency, and impedance phase angle range of each battery type; When the time constant τ, the variable resistance r, the complex impedance Z(f) and the impedance phase angle θ(f) of the battery are all within the range corresponding to a certain battery type, the certain battery type is taken as the battery type of the battery, and the certain battery type is recorded as the detected battery type of the battery, and the battery type is collected to obtain the battery type detection data; For example, the variable resistance r of a lithium-ion battery is generally less than 50 mΩ, while the variable resistance r of a lead-acid battery is generally between 100 mΩ and 500 mΩ; For the time constant τ, due to the slow diffusion of the electrolyte in lead-acid batteries, τ is generally greater than 50ms, while for lithium batteries, τ is generally less than 20ms; Step S200: obtaining an initial charging record of the battery, obtaining a historical comparison charging record of a reference battery from a charging platform based on the type detection data, evaluating the degree of similarity between the battery state in the current cycle and the reference battery, and obtaining a target reference battery; Wherein, step S200 includes: Step S201: obtaining a detected battery type of a battery from type detection data, obtaining batteries of the same type as the detected battery type in a charging platform and recording them as reference batteries, and obtaining historical comparison charging records of each reference battery; Obtain data corresponding to the current, voltage, and temperature of the reference battery charging from the historical reference charging records; Step S202: obtaining the initial charging record of the battery in the current cycle, and obtaining data corresponding to the current, voltage, and temperature of the battery charging from the initial charging record; Preprocess the data corresponding to the current, voltage and temperature in the historical control charging records and the initial charging records; For example, in a specific embodiment, the preprocessing process includes performing noise reduction on the current, voltage, and temperature, performing time alignment, and finally performing normalization processing; Set the unit time t´, calculate and integrate the battery current in the initial charging record within the unit time, and obtain the battery charging capacity Q within the unit time; Get the temperature change rate of the battery in the initial charging record within the cth unit time v c =T c / t´,T c is the change in temperature of the battery at the initial time point within the cth unit time; The average voltage value, temperature change rate and charging capacity of the battery are used as the charging characteristic parameters of the battery. The various charging characteristic parameters of the battery within a number of unit time lengths are obtained from the initial charging records, normalized and collected to obtain the charging data set P of the battery, wherein the cth element in the charging data set P is the value of the various charging characteristic parameters of the battery within the cth unit time length; Step S203: obtaining the duration and charging data set of the historical control charging record of the reference battery, and dividing the charging data set of the historical control charging record based on the duration corresponding to the initial charging record to obtain a plurality of marked charging data sets, wherein the total number of elements in different marked charging data sets is n, and n is greater than the total number of elements in the charging data set m; Step S204: Obtain a certain labeled data set G in the reference battery, and calculate the i-th element in the certain labeled data set G g i , and the jth element p in the charging data set P j The characteristic distance d(g i , p j ); In a specific embodiment, the characteristic distance d(g i , p j ) is calculated as: , Among them, g i (z) is the i-th element g i The value of the zth charging characteristic parameter in p j (z)is the jth element p j The value of the zth charging characteristic parameter in; k=3; w z is the characteristic weight of the z-th charging characteristic parameter, which can be obtained by the entropy weight method; Based on a certain labeled data set G and a battery charging data set P, a distance matrix H is constructed, the distance matrix H is initialized and boundary conditions are set, and the element h(i,j)=d(g i , p j )+min{h(i-1,j), h(i,j-1), h(i-1,j-1)}; For example, the specific initialization and boundary conditions are as follows: h(0,0)=0, h(i,0)=+∞, h(0,j)=+∞ in the distance matrix H; Get the last element h(m,n) in the distance matrix H and calculate the difference value γ between a certain labeled data set G and a charging data set P (g,p) : , Obtaining the reciprocal of the minimum value of the difference between a plurality of marked charging data sets in the reference battery and the charging data set P as an approximate value of the state of charge between the reference battery and the battery; Step S205: obtaining a reference battery corresponding to the maximum value of the approximate state of charge between the battery and each reference battery, and recording it as a target reference battery, and determining that the battery state of the target reference battery is similar to that of the battery; Step S300: obtaining a reference charging strategy of a target reference battery, adjusting the charging strategy of the battery, obtaining a battery detection range of the target reference battery, performing abnormality detection on the charging state of the battery, and obtaining a suspected abnormal battery; Wherein, step S300 includes: Step S301: obtaining a reference charging strategy of a target reference battery in a charging platform, wherein the reference charging strategy includes a change curve of voltage and current corresponding to the target reference battery during charging; Step S302: adjusting the charging strategy of the battery based on the reference charging strategy, specifically: obtaining the remaining power of the battery in the current cycle, obtaining the voltage and current corresponding change curves after the power of the target reference battery is the remaining power from the reference charging strategy, and using them as the voltage and current change curves when the battery is charged in the current cycle; Step S303: obtaining a battery detection range of the target reference battery, where the battery detection range includes a characteristic range corresponding to each battery detection parameter in the target reference battery, wherein the characteristic range is a range consisting of normal maximum and minimum values ​​of the battery detection parameters in the target reference battery; The adjusted charging strategy is used to adjust the voltage and current of the battery charging, and the abnormality detection of the battery charging state is performed. The specific detection process is as follows: When the maximum value or minimum value of a battery detection parameter in the battery is detected to be out of the characteristic range of a battery detection parameter, the battery charging state is determined to be abnormal and is recorded as a suspected abnormal battery; Step S400: power off the suspected abnormal battery and let it stand, recharge the suspected abnormal battery after power off and standing, re-detect the suspected abnormal battery for abnormality, obtain the abnormal battery, power off the abnormal battery, and send an alarm prompt to the user and staff through the charging platform; Wherein, step S400 includes: Step S401: obtaining a suspected abnormal battery in the charging platform, powering off the suspected abnormal battery, and keeping it idle for a preset characteristic unit time, charging the suspected abnormal battery again, and monitoring the charging of the suspected abnormal battery to obtain data corresponding to various battery detection parameters of the suspected abnormal battery; Step S402: When the maximum value or minimum value of a battery detection parameter of the suspected abnormal battery is detected again and is not within the characteristic range of the battery detection parameter, the suspected abnormal battery is determined to be abnormal and recorded as an abnormal battery. Otherwise, the adjusted charging strategy is continued to be used for charging; The abnormal battery in the charging platform is powered off, and an alarm is sent to the user and staff of the abnormal battery through the charging platform to handle the abnormal battery; In order to better implement the above method, a detection and management system for battery charging process is also proposed, the system includes a battery type detection module, an approximate evaluation module, an abnormality detection module and an abnormality alarm module; A battery type detection module, used to detect the battery type of the battery and obtain battery type detection data; An approximate evaluation module is used to evaluate the approximation degree of the battery state between the battery in the current cycle and the reference battery to obtain a target reference battery; An abnormality detection module is used to detect abnormalities in the charging state of the battery and obtain suspected abnormal batteries; The abnormal alarm module is used to re-detect the abnormality of the suspected abnormal battery, obtain the abnormal battery, cut off the power of the abnormal battery, and send an alarm to the user and staff through the charging platform to indicate the abnormal battery is abnormal; Wherein, the battery type detection module includes a charging test unit and a battery type detection unit; A charging test unit, used to test and record the charging of the battery to obtain a charging test record; A battery type detection unit, used to detect the battery type of the battery according to the charging test record to obtain battery type detection data; Wherein, the approximate evaluation module includes a difference analysis unit and an approximate evaluation unit; A difference analysis unit, used to perform difference analysis on the charging data set of the battery and each marked data set in the reference battery, and obtain a difference value between the charging data set and each marked data set; An approximate evaluation unit, used to obtain an approximate value of the state of charge of the battery and the reference battery according to the difference value, analyze the degree of approximation of the state of charge between the battery and the reference battery, and obtain a target reference battery; Among them, the abnormality detection module includes a charging strategy adjustment unit and an abnormality detection unit; A charging strategy adjustment unit, used to obtain a reference charging strategy of a target reference battery of the battery and adjust the charging strategy of the battery; An abnormality detection unit is used to charge the battery using the adjusted charging strategy, and to perform abnormality detection on the charging state of the battery to obtain a suspected abnormal battery; Wherein, the abnormal alarm module includes an abnormal alarm unit; The abnormal alarm unit is used to cut off the power supply of the suspected abnormal battery, charge the suspected abnormal battery after the power is cut off, perform abnormal detection on the suspected abnormal battery again, obtain the abnormal battery, and issue an abnormal alarm for the abnormal battery. An alarm prompt is sent to the user and staff of the abnormal battery through the charging platform to remind them to deal with the abnormal battery.

[0019] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A detection and management method during battery charging, characterized in that: The method comprises: Step S100: obtaining a charging test record of a battery, obtaining battery type differentiation data in a charging platform, detecting the battery type of the battery, and obtaining type detection data of the battery; Step S200: obtaining an initial charging record of the battery, obtaining a historical comparison charging record of a reference battery from the charging platform based on the type detection data, evaluating the degree of similarity between the battery state of the battery in the current cycle and the reference battery, and obtaining a target reference battery; Step S300: obtaining a reference charging strategy of the target reference battery, adjusting the charging strategy of the battery, obtaining a battery detection range of the target reference battery, performing an abnormality detection on the charging state of the battery, and obtaining a suspected abnormal battery; Step S400: power off the suspected abnormal battery and let it stand, recharge the suspected abnormal battery after power off and standing, re-detect the suspected abnormal battery for abnormality, obtain the abnormal battery, power off the abnormal battery, and send an alarm to users and staff through the charging platform.

2. A battery charging process detection and management method according to claim 1, characterized in that: The step S100 includes: Step S101: when the battery is charged in the current cycle, a high-frequency AC signal is superimposed on the charging current of the battery, and a current pulse of a preset duration is inserted, and the charging current of the battery is paused, and the charging of the battery is tested and recorded to obtain a charging test record; Step S102: obtaining a voltage signal V´(t) and a current signal I´(t) collected during the test period from the charging test record, and converting the voltage signal V´(t) and the current signal I´(t) into the frequency domain by Fourier transform to obtain V´(f) and I´(f); Calculate the complex impedance of the battery Z(f)=V´(f) / I´(f)=R(f)+jX(f), where R(f) is the real part of the complex impedance Z(f), and X(f) is the imaginary part of the complex impedance; Calculate the impedance phase angle of the battery at θ(f)=arctan(X(f) / R(f)); Step S103: Obtain the change value ΔV and the minimum value V of the battery charging voltage during the insertion current pulse from the charging test record min , obtain the current value I of the current pulse pulse , calculate the changing resistance of the battery r = △V / I pulse ; Obtain the steady-state voltage V of the battery after the test, and fit the voltage-time curve V(t) of the battery after the current pulse is inserted into the first-order exponential model: V(t)=V+(V min -V)·e （-t / τ） , τ is a time constant, and based on the first-order exponential model, the time constant τ of the battery is obtained; Step S104: Detect the battery type of the battery. The specific process is as follows: Obtaining battery type differentiation data in the charging platform, the battery type differentiation data including a time constant, a variable resistance, a complex impedance at a preset frequency, and a range corresponding to an impedance phase angle in each battery type; When the time constant τ, variable resistance r, complex impedance Z(f) and impedance phase angle θ(f) of the battery are all within the range corresponding to a certain battery type, the certain battery type is used as the battery type of the battery, and the certain battery type is recorded as the detected battery type of the battery, and the data are collected to obtain the type detection data of the battery.

3. A battery charging process detection and management method according to claim 2, characterized in that: The step S200 includes: Step S201: obtaining the detected battery type of the battery from the type detection data, obtaining batteries of the same type as the detected battery type in the charging platform and recording them as reference batteries, and obtaining historical comparison charging records of each reference battery; Obtain data corresponding to the current, voltage, and temperature of the reference battery charging from the historical reference charging records; Step S202: obtaining an initial charging record of the battery in the current cycle, and obtaining data corresponding to the charging current, voltage, and temperature of the battery from the initial charging record; Preprocessing the data corresponding to the current, voltage and temperature in the historical control charging record and the initial charging record; Set a unit time t´, calculate and integrate the current of the battery in the unit time in the initial charging record, and obtain the charging capacity Q of the battery in the unit time; Obtain the temperature change rate of the battery in the cth unit time in the initial charging record v c =T c / t´,T c is the change in temperature of the battery at the initial time point within the c-th unit time; The average voltage value, temperature change rate and charging capacity of the battery are used as charging characteristic parameters of the battery, and various charging characteristic parameters of the battery within a plurality of unit time lengths are obtained from the initial charging record, normalized and collected to obtain a charging data set P of the battery, wherein the cth element in the charging data set P is the value of various charging characteristic parameters of the battery within the cth unit time length; Step S203: obtaining the duration and charging data set of the historical control charging record of the reference battery, and dividing the charging data set of the historical control charging record based on the duration corresponding to the initial charging record to obtain a plurality of marked charging data sets, wherein the total number of elements in different marked charging data sets is n, and n is greater than the total number of elements in the charging data set m; Step S204: Obtain a certain labeled data set G in the reference battery, and calculate the i-th element in the certain labeled data set G g i , with the jth element p in the charging data set P j The characteristic distance d(g i , p j ); Based on the certain labeled data set G and the charging data set P of the battery, a distance matrix H is constructed, the distance matrix H is initialized and boundary conditions are set, and the element h(i,j)=d(g i , p j )+min{h(i-1,j), h(i,j-1), h(i-1,j-1)}; Get the last element h(m,n) in the distance matrix H, and calculate the difference value γ between the certain marked data set G and the charging data set P (g,p) : ， Obtaining the reciprocal of the minimum value of the difference between a plurality of marked charging data sets in the reference battery and the charging data set P as an approximate value of the state of charge between the reference battery and the battery; Step S205: obtaining a reference battery corresponding to the maximum value of the approximate state of charge between the battery and each reference battery, and recording it as a target reference battery, and determining that the battery state of the target reference battery is similar to that of the battery.

4. A battery charging process detection management method according to claim 3, characterized in that: The step S300 includes: Step S301: obtaining a reference charging strategy of the target reference battery in the charging platform, wherein the reference charging strategy includes a change curve of the voltage and current of the target reference battery during the charging process; Step S302: adjusting the charging strategy of the battery based on the reference charging strategy, specifically: obtaining the remaining power of the battery in the current cycle, obtaining the change curve of the voltage and current corresponding to the remaining power of the target reference battery from the reference charging strategy, and using the change curve of the voltage and current when the battery is charged in the current cycle; Step S303: Acquire a battery detection range of the target reference battery, wherein the battery detection range includes a characteristic range corresponding to each battery detection parameter in the target reference battery, wherein the characteristic range is a range consisting of normal maximum and minimum values ​​of the battery detection parameters in the target reference battery; The adjusted charging strategy is used to adjust the voltage and current of the battery charging, and the abnormality detection is performed on the charging state of the battery. The specific detection process is as follows: When the maximum value or the minimum value of a certain battery detection parameter of the battery is detected to be not within the characteristic range of the certain battery detection parameter, the charging state of the battery is determined to be abnormal and the battery is recorded as a suspected abnormal battery.

5. A method for detecting and managing battery charging according to claim 4, characterized in that: The step S400 includes: Step S401: obtaining a suspected abnormal battery in the charging platform, powering off the suspected abnormal battery, and keeping it idle for a preset characteristic unit time, charging the suspected abnormal battery again, and monitoring the charging of the suspected abnormal battery to obtain data corresponding to various battery detection parameters of the suspected abnormal battery; Step S402: When the maximum value or minimum value of a battery detection parameter of the suspected abnormal battery is detected again and is not within the characteristic range of the battery detection parameter, the suspected abnormal battery is determined to be abnormal and recorded as an abnormal battery. Otherwise, the adjusted charging strategy is continued to be used for charging; The abnormal battery in the charging platform is powered off, and an alarm is sent to the user and staff of the abnormal battery through the charging platform to process the abnormal battery.

6. A battery charging process detection management system, used to execute a battery charging process detection management method as claimed in any one of claims 1 to 5, characterized in that: The system includes a battery type detection module, a proximity assessment module, an anomaly detection module, and an anomaly alarm module; The battery type detection module is used to detect the battery type of the battery and obtain the type detection data of the battery; The approximate evaluation module is used to evaluate the degree of similarity between the battery state of the battery in the current cycle and the reference battery to obtain a target reference battery; The abnormality detection module is used to detect abnormalities in the charging state of the battery and obtain suspected abnormal batteries; The abnormal alarm module is used to re-detect the abnormality of the suspected abnormal battery, obtain the abnormal battery, cut off the power of the abnormal battery, and send an alarm to the user and staff through the charging platform to prompt the abnormal battery to be abnormal.

7. A battery charging process detection and management system according to claim 6, characterized in that: The battery type detection module includes a charging test unit and a battery type detection unit; The charging test unit is used to test and record the charging of the battery to obtain a charging test record; The battery type detection unit is used to detect the battery type of the battery according to the charging test record to obtain the type detection data of the battery.

8. A battery charging process detection and management system according to claim 6, characterized in that: The approximate evaluation module includes a difference analysis unit and an approximate evaluation unit; The difference analysis unit is used to perform difference analysis on the charging data set of the battery and each marked data set in the reference battery to obtain a difference value between the charging data set and each marked data set; The approximate evaluation unit is used to obtain the approximate value of the state of charge of the battery and the reference battery according to the difference value, analyze the degree of similarity of the state of charge between the battery and the reference battery, and obtain a target reference battery.

9. A battery charging process detection and management system according to claim 6, characterized in that: The abnormality detection module includes a charging strategy adjustment unit and an abnormality detection unit; The charging strategy adjustment unit is used to obtain a reference charging strategy of a target reference battery of the battery and adjust the charging strategy of the battery; The abnormality detection unit is used to charge the battery using the adjusted charging strategy, and perform abnormality detection on the charging state of the battery to obtain a suspected abnormal battery.

10. A battery charging process detection and management system according to claim 6, characterized in that: The abnormal alarm module includes an abnormal alarm unit; The abnormal alarm unit is used to cut off the power supply of the suspected abnormal battery, charge the suspected abnormal battery after the power supply is cut off, perform abnormal detection on the suspected abnormal battery again to obtain an abnormal battery, and issue an abnormal alarm for the abnormal battery, and send an alarm prompt to the user and staff of the abnormal battery through the charging platform to remind them to deal with the abnormal battery.

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