A battery charging process detection and management system and method

Abstract

The present invention discloses a detection and management system and method during the battery charging process, which relates to the technical field of battery charging detection. It includes obtaining the charging test records of the battery, obtaining the battery type differentiation data in the charging platform, and detecting the battery type of the battery; obtaining the initial charging records of the battery, and based on the type detection data, obtaining the historical comparison charging records of the reference battery from the charging platform to evaluate the approximate degree of the battery state between the battery in the current cycle and the reference battery; adjusting the charging strategy of the battery, obtaining the battery detection range of the target reference battery, and performing abnormal detection on the charging state of the battery; powering off and standing still the suspected abnormal battery, charging the suspected abnormal battery again after powering off and standing still, performing abnormal detection on the suspected abnormal battery to obtain the abnormal battery, powering off the abnormal battery, and sending an alarm prompt to the user and the staff through the charging platform.

Description

Technical Field

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

[0002] It is crucial to detect the battery type and battery state during the battery charging process, mainly for the following reasons: 1. Ensure charging safety: During the battery charging process, different batteries have different voltage and current tolerance ranges. If a mismatched voltage and current are applied to the battery during charging, it is very likely that the battery will 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 a staged manner. Appropriate voltage and current can greatly shorten the charging time and reduce energy loss; 3. Prolong the battery life. Incorrect charging methods, such as using high voltage for nickel-metal hydride batteries, will accelerate the degradation of the electrode material.

[0003] Traditional methods for detecting the type and state of batteries all have certain deficiencies. They not only cannot quickly identify the battery type, but also due to different usage conditions of the battery, the battery state will change to a certain extent. Even for the same type of battery, the most suitable charging strategy is different. Therefore, it is also impossible to accurately detect the state of the charging 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, nor can it 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 purpose of the present invention is to provide a detection and management system and method during the battery charging process to solve the problems raised in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A detection and management method during the battery charging process, the method includes:

[0006] Step S100: Obtain the charging test record of the battery, obtain the battery type discrimination data in the charging platform, detect the battery type of the battery, and obtain the type detection data of the battery;

[0007] Step S200: Obtain the initial charging record of the battery, based on the type detection data, obtain the historical comparison charging record of the reference battery from the charging platform, evaluate the degree of approximation of the battery state between the battery in the current cycle and the reference battery, and obtain the target reference battery;

[0008] Step S300: Obtain the reference charging strategy of the target reference battery, adjust the charging strategy of the battery, obtain the battery detection range of the target reference battery, perform abnormal detection on the charging state of the battery, and obtain suspected abnormal batteries;

[0009] Step S400: Power off and let the suspected abnormal batteries stand still, charge the suspected abnormal batteries again after power-off and standing still, perform abnormal re-detection on the suspected abnormal batteries, obtain abnormal batteries, power off the abnormal batteries, and send alarm prompts to users and staff through the charging platform.

[0010] Further, step S100 includes:

[0011] Step S101: When the battery is being charged in the current cycle, superimpose a high-frequency alternating current signal on the charging current of the battery, insert a current pulse with a preset duration, and at the same time pause the charging current of the battery, test and record the charging of the battery to obtain a charging test record;

[0012] Step S102: Obtain the voltage signal V´(t) and current signal I´(t) collected during the test period from the charging test record, and through Fourier transform, convert the voltage signal V´(t) and current signal I´(t) to the frequency domain respectively to obtain V´(f) and I´(f);

[0013] 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;

[0014] Calculate the impedance phase angle of the battery θ(f)=arctan(X(f) / R(f));

[0015] Step S103: Obtain the change value △V and the minimum value V of the battery charging voltage during the insertion of the current pulse from the charging test record min and obtain the current value I of the current pulse pulse and calculate the change resistance r of the battery r = △V / I pulse ;

[0016] Obtain the steady-state voltage V of the battery after the test, and fit the voltage-time change curve V(t) of the battery after the insertion of the current pulse to a first-order exponential model: V(t)=V+(V min -V)·e （-t / τ） , τ is the time constant, and based on the first-order exponential model, obtain the time constant τ of the battery;

[0017] Step S104: Detect the battery type of the battery. The specific process is as follows:

[0018] Obtain the battery type discrimination data in the charging platform. The battery type discrimination data includes the time constant, variable resistance, range of complex impedance at a preset frequency, and impedance phase angle corresponding to each battery type;

[0019] When the time constant τ, variable resistance r, complex impedance Z(f) at a preset frequency, and impedance phase angle θ(f) of the battery are all within the range corresponding to a certain battery type, take a certain battery type as the battery type of the battery, record a certain battery type as the detected battery type of the battery, and perform aggregation to obtain the type detection data of the battery;

[0020] In the above steps, the battery type is detected by testing the battery and observing the battery reaction. This method is not only fast, but also does not require complex model training, has low computing power requirements, low detection error probability, and is applicable to mainstream battery types.

[0021] Further, step S200 includes:

[0022] Step S201: Obtain the detected battery type of the battery from the type detection data, obtain the batteries of the same type as the detected battery type in the charging platform, and record them as reference batteries, and obtain the historical comparison charging records of each reference battery;

[0023] Obtain the data corresponding to the current, voltage, and temperature of the reference battery charging from the historical comparison charging records;

[0024] Step S202: Obtain the initial charging record of the battery in the current cycle, and obtain the data corresponding to the current, voltage, and temperature of the battery charging from the initial charging record;

[0025] Preprocess the data corresponding to the current, voltage, and temperature in the historical comparison charging record and the initial charging record;

[0026] Set the unit time t´, calculate the current integral of the battery in the initial charging record within the unit time, and obtain the charging capacity Q of the battery within the unit time;

[0027] Obtain the temperature change rate v of the battery in the c-th unit time in the initial charging record c =T c / t´, T c Is the change value of the temperature at the initial time point of the battery in the c-th unit time;

[0028] Taking the average voltage, temperature change rate, and charging capacity of the battery as the charging characteristic parameters of the battery, obtaining the charging characteristic parameters of the battery within several unit time periods from the initial charging record, performing normalization processing and aggregation, to obtain the charging data set P of the battery. Among them, the c-th element in the charging data set P is the value of the charging characteristic parameters of the battery within the c-th unit time period;

[0029] Step S203: Obtain the duration and charging data set of the historical comparison charging record of the reference battery. Based on the duration corresponding to the initial charging record, divide the charging data set of the historical comparison charging record to obtain several marked charging data sets. Among them, the total number of elements in different marked charging data sets is n, and n is greater than the total number of elements m in the charging data set of the battery being charged;

[0030] Step S204: Obtain a certain marked data set G in the reference battery, and calculate the i-th element g i in a certain marked data set G and the j-th element p i in the charging data set P of the battery, and calculate the characteristic distance d(g i , p j );

[0031] Based on a certain marked data set G and the charging data set P of the battery, construct a distance matrix H, initialize the distance matrix H and set boundary conditions, and calculate the element h(i, j) corresponding to the i-th row and j-th column in the distance matrix H: h(i, j) = d(g i , p j ) + min{h(i - 1, j), h(i, j - 1), h(i - 1, j - 1)};

[0032] Obtain the last element h(m, n) in the distance matrix H, and calculate the difference value γ (g,p) between a certain marked data set G and the charging data set P of the battery:

[0033] ,

[0034] Obtain the reciprocal of the minimum value of the difference values between several marked charging data sets in the reference battery and the charging data set P of the battery as the charging state approximation value between the reference battery and the battery;

[0035] Step S205: Obtain the reference battery corresponding to the maximum value of the charging state approximation values between the battery and each reference battery, and denote it as the target reference battery, and determine that the battery state of the target reference battery is similar to that of the battery.

[0036] Further, step S300 includes:

[0037] Step S301: Obtain the reference charging strategy of the target reference battery in the charging platform. The reference charging strategy includes the change curves of the voltage and current corresponding to the target reference battery during the charging process;

[0038] Step S302: Adjust the charging strategy of the battery based on the reference charging strategy. Specifically: Obtain the remaining power of the battery in the current cycle. When the power of the target reference battery is the remaining power, obtain the change curves of the voltage and current corresponding to the target reference battery from the reference charging strategy, and use the change curves as the change curves of the voltage and current during the charging of the battery in the current cycle;

[0039] Step S303: Obtain the battery detection range of the target reference battery. The battery detection range includes the characteristic ranges corresponding to the various battery detection parameters in the target reference battery, where the characteristic range is the range composed of the maximum value and the minimum value at which the battery detection parameters in the target reference battery are normal;

[0040] Use the adjusted charging strategy to adjust the voltage and current of the battery during charging, and perform abnormal detection on the charging status of the battery. The specific detection process is as follows:

[0041] When the maximum value or the minimum value of a certain battery detection parameter in the battery is detected to be outside the characteristic range of a certain battery detection parameter, it is determined that the charging status of the battery is abnormal, and it is recorded as a suspected abnormal battery.

[0042] Further, step S400 includes:

[0043] Step S401: Obtain the suspected abnormal batteries in the charging platform, cut off the power of the suspected abnormal batteries, and let them stand still for a preset characteristic unit time. Then charge the suspected abnormal batteries again, and monitor the charging of the suspected abnormal batteries to obtain the data corresponding to the various battery detection parameters in the suspected abnormal batteries;

[0044] Step S402: When it is detected again that the maximum value or the minimum value of a certain battery detection parameter in the suspected abnormal battery is outside the characteristic range of a certain battery detection parameter, it is determined that the suspected abnormal battery is abnormal and recorded as an abnormal battery. Otherwise, continue to use the adjusted charging strategy for charging;

[0045] Cut off the power of the abnormal batteries in the charging platform, and send an alarm prompt to the users and staff of the abnormal batteries through the charging platform to process the abnormal batteries.

[0046] In order to better implement the above method, a detection and management system during the battery charging process is also proposed. The system includes a battery type detection module, an approximate evaluation module, an abnormal detection module, and an abnormal alarm module;

[0047] The battery type detection module is used to detect the battery type of the battery and obtain the type detection data of the battery;

[0048] The approximate evaluation module is used to evaluate the approximate degree of the battery state between the battery in the current cycle and the reference battery, and obtain the target reference battery;

[0049] The anomaly detection module is used to detect anomalies in the charging state of the battery and obtain suspected abnormal batteries;

[0050] The anomaly alarm module is used to re-detect anomalies for the suspected abnormal batteries, obtain the abnormal batteries, cut off the power supply for the abnormal batteries, and send an alarm to the user and the staff through the charging platform to indicate that the abnormal battery is abnormal.

[0051] Furthermore, the battery type detection module includes a charging test unit and a battery type detection unit;

[0052] The charging test unit is used to test and record the charging of the battery to obtain the charging test record;

[0053] The battery type detection unit is used to detect the battery type of the battery according to the charging test record and obtain the type detection data of the battery.

[0054] Furthermore, the approximate evaluation module includes a difference analysis unit and an approximate evaluation unit;

[0055] The difference analysis unit is used to perform a difference analysis on the charging data set of the battery and each marked data set in the reference battery to obtain the difference values between the charging data set and each marked data set;

[0056] The approximate evaluation unit is used to obtain the approximate value of the charging state between the battery and the reference battery according to the difference value, analyze the approximate degree of the charging state between the battery and the reference battery, and obtain the target reference battery.

[0057] Furthermore, the anomaly detection module includes a charging strategy adjustment unit and an anomaly detection unit;

[0058] The charging strategy adjustment unit is used to obtain the reference charging strategy of the target reference battery of the battery and adjust the charging strategy of the battery;

[0059] The anomaly detection unit is used to charge the battery using the adjusted charging strategy and detect anomalies in the charging state of the battery to obtain suspected abnormal batteries.

[0060] Furthermore, the anomaly alarm module includes an anomaly alarm unit;

[0061] An abnormal alarm unit is used to cut off the power supply of the suspected abnormal battery, charge the suspected abnormal battery after power cut, detect the abnormality of the suspected abnormal battery again to obtain the abnormal battery, and give an abnormal alarm to 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 process the abnormal battery.

[0062] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention realizes intelligent detection and management during the battery charging process. First, because different battery types are different, the characteristics exhibited by the batteries will also be different. The present invention first applies a high-frequency alternating current signal and a current pulse to the charging battery to record the reaction of the battery, thereby obtaining a series of data. By the corresponding values of these data and in combination with the ranges corresponding to different types of batteries, the battery type of the battery is quickly detected. And considering the actual situation that even if the battery types are the same, the states of different batteries will also be different, analyze the approximate state between the battery state in the current cycle and different batteries in the database, so as to optimize the charging strategy of the battery, and use the battery detection range of the target reference battery of the battery as a reference to detect the abnormality of the currently charged battery. And in order to prevent misdetection, it also performs detection after power cut and static placement, making the battery abnormality detection more accurate, which 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

[0063] Figure 1 is the method flow chart of a method for detecting and managing a battery during the charging process of the present invention;

[0064] Figure 2 is the module schematic diagram of a system for detecting and managing a battery during the charging process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0066] Embodiment: As Figure 1 - Figure 2 shown, the present invention provides a technical solution, a method for detecting and managing a battery during the charging process, the method includes:

[0067] Step S100: Obtain the charging test record of the battery, obtain the battery type discrimination data in the charging platform, detect the battery type of the battery, and obtain the type detection data of the battery;

[0068] Among them, step S100 includes:

[0069] Step S101: When the battery is being charged in the current cycle, a high-frequency alternating current signal is superimposed on the charging current of the battery, a current pulse with a preset duration is inserted, and at the same time, the charging current of the battery is paused, and the charging of the battery is tested and recorded to obtain a charging test record;

[0070] For example, the specific operation of superimposing a high-frequency alternating current signal on the charging current of the battery and inserting a current pulse with a preset duration is as follows:

[0071] A small-amplitude high-frequency alternating current signal (frequency range: 1 Hz–10 kHz, amplitude: <5% of the rated current) is superimposed on the DC charging current of the battery;

[0072] A short-time current pulse is inserted during the charging process, generally the current pulse I pulse is 1A, the duration is 10 ms, and the charging current of the battery is paused;

[0073] Step S102: Obtain the voltage signal V´(t) and current signal I´(t) collected during the test period from the charging test record. Through Fourier transform, the voltage signal V´(t) and current signal I´(t) are respectively converted to the frequency domain to obtain V´(f) and I´(f);

[0074] 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;

[0075] Calculate the impedance phase angle of the battery θ(f)=arctan(X(f) / R(f));

[0076] Step S103: Obtain the change value △V and the minimum value V of the battery charging voltage during the insertion of the current pulse from the charging test record min , obtain the current value I of the current pulse pulse , calculate the change resistance of the battery r = △V / I pulse ;

[0077] Obtain the steady-state voltage V of the battery after charging the test. Fit the voltage-time curve V(t) of the battery after inserting the current pulse to a 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, obtain the time constant τ of the battery;

[0078] For example, if the steady-state voltage V is such that the change rate of the voltage after the test is less than the change rate threshold within a certain period of time, then this voltage is set as the steady-state voltage;

[0079] For example, the calculation formula for the time constant τ is as follows:

[0080] ,

[0081] where t end is the duration required for the voltage of the battery not to change after inserting a current pulse;

[0082] Step S104: Detect the battery type of the battery. The specific process is as follows:

[0083] Obtain the battery type discrimination data in the charging platform. The battery type discrimination data includes the time constant, variable resistance, complex impedance at a preset frequency, and the corresponding range of impedance phase angle in each battery type;

[0084] When the time constant τ, variable resistance r, complex impedance Z(f) at a preset frequency, and impedance phase angle θ(f) of the battery are all within the range corresponding to a certain battery type, take a certain battery type as the battery type of the battery, and record a certain battery type as the detected battery type of the battery, and collect it to obtain the type detection data of the battery;

[0085] For example, the variable resistance r of a lithium-ion battery is generally less than 50 mΩ, while the variable resistance of a lead-acid battery is generally between 100 mΩ and 500 mΩ;

[0086] Regarding the time constant τ, since the electrolyte diffusion of a lead-acid battery is slow, τ is generally greater than 50 ms, while τ of a lithium battery is generally less than 20 ms;

[0087] Step S200: Obtain the initial charging record of the battery. Based on the type detection data, obtain the historical comparison charging record of the reference battery from the charging platform, and evaluate the approximation degree of the battery state between the battery in the current cycle and the reference battery to obtain the target reference battery;

[0088] Among them, step S200 includes:

[0089] Step S201: Obtain the detected battery type of the battery from the type detection data, obtain the batteries of the same type as the detected battery type in the charging platform, and record them as reference batteries, and obtain the historical comparison charging records of each reference battery;

[0090] Obtain the data corresponding to the current, voltage, and temperature of the reference battery charging from the historical comparison charging record;

[0091] Step S202: Obtain the initial charging record of the battery in the current cycle, and obtain the data corresponding to the current, voltage, and temperature of the battery charging from the initial charging record;

[0092] Preprocess the data corresponding to the current, voltage, and temperature in the historical comparison charging record and the initial charging record;

[0093] For example, in a specific embodiment, the preprocessing process includes denoising the current, voltage, and temperature, performing time alignment, and finally performing normalization processing;

[0094] Set the unit time period \(t'\), calculate the current integral of the battery in the initial charging record within the unit time period, and obtain the charging capacity \(Q\) of the battery within the unit time period;

[0095] Obtain the temperature change rate \(v\) of the battery in the \(c\)-th unit time period in the initial charging record c =T c / t', where \(T\) c is the change value of the temperature at the initial time point of the battery in the \(c\)-th unit time period;

[0096] Take the average voltage, temperature change rate, and charging capacity of the battery as the charging characteristic parameters of the battery. Obtain the charging characteristic parameters of the battery in several unit time periods from the initial charging record, perform normalization processing and aggregation to obtain the charging data set \(P\) of the battery. Among them, the \(c\)-th element in the charging data set \(P\) is the value of the charging characteristic parameters of the battery in the \(c\)-th unit time period;

[0097] Step S203: Obtain the duration and charging data set of the historical comparison charging record of the reference battery. Based on the duration corresponding to the initial charging record, split the charging data set of the historical comparison charging record to obtain several marked charging data sets. Among them, the total number of elements in different marked charging data sets is \(n\), and \(n\) is greater than the total number of elements \(m\) in the charging data set of the battery;

[0098] Step S204: Obtain a certain marked data set \(G\) in the reference battery, and calculate the \(i\)-th element \(g\) in a certain marked data set \(G\) i , and the \(j\)-th element \(p\) in the charging data set \(P\) i The characteristic distance \(d(g\) i , \(p\) j );

[0099] In a specific embodiment, the formula for calculating the characteristic distance \(d(g\) i , \(p\) j ) is: ,

[0100] where \(g\) i (z) is the value of the \(z\)-th charging characteristic parameter in the \(i\)-th element \(g\) i ; \(p\) j (z)is the value of the z-th charging characteristic parameter for the j-th element p j 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;

[0101] Based on a certain labeled dataset G and the charging dataset P of the battery, a distance matrix H is constructed. The distance matrix H is initialized and boundary conditions are set. Calculate the element h(i, j) corresponding to the i-th row and j-th column in the distance matrix H, where h(i, j)=d(g i , p j ) + min{h(i - 1, j), h(i, j - 1), h(i - 1, j - 1)};

[0102] For example, the specific initialization and setting of boundary conditions are: set h(0, 0)=0, h(i, 0)=+∞, h(0, j)=+∞ in the distance matrix H;

[0103] Obtain the last element h(m, n) in the distance matrix H, and calculate the difference value γ between a certain labeled dataset G and the charging dataset P (g,p) :

[0104] ,

[0105] Obtain the reciprocal of the minimum value of the difference values between several labeled charging datasets in the reference battery and the charging dataset P as the approximation of the charging state between the reference battery and the battery;

[0106] Step S205: Obtain the reference battery corresponding to the maximum value of the charging state approximation between the battery and each reference battery, and denote it as the target reference battery, and determine that the battery state of the target reference battery is similar to that of the battery;

[0107] Step S300: Obtain the reference charging strategy of the target reference battery, adjust the charging strategy of the battery, obtain the battery detection range of the target reference battery, and perform abnormal detection on the charging state of the battery to obtain a suspected abnormal battery;

[0108] Among them, step S300 includes:

[0109] Step S301: Obtain the reference charging strategy of the target reference battery in the charging platform. The reference charging strategy includes the change curves of voltage and current corresponding to the target reference battery during charging;

[0110] Step S302: Adjust the charging strategy of the battery based on the reference charging strategy. Specifically, obtain the remaining power of the battery in the current cycle. When the power of the target reference battery is the remaining power, obtain the change curves of the voltage and current corresponding to the target reference battery from the reference charging strategy, and use the change curves as the change curves of the voltage and current during the charging of the battery in the current cycle;

[0111] Step S303: Obtain the battery detection range of the target reference battery. The battery detection range includes the characteristic ranges corresponding to the battery detection parameters in the target reference battery. Among them, the characteristic range is the range composed of the maximum and minimum values of the battery detection parameters that are normal in the target reference battery;

[0112] Use the adjusted charging strategy to adjust the voltage and current of the battery during charging, and perform abnormal detection on the charging status of the battery. The specific detection process is as follows:

[0113] When the maximum or minimum value of a certain battery detection parameter in the battery is detected to be outside the characteristic range of a certain battery detection parameter, it is determined that the charging status of the battery is abnormal, and it is recorded as a suspected abnormal battery;

[0114] Step S400: Power off and statically place the suspected abnormal battery, charge the suspected abnormal battery again after power-off and static placement, perform abnormal re-detection on the suspected abnormal battery, obtain the abnormal battery, power off the abnormal battery, and send an alarm prompt to the user and the staff through the charging platform;

[0115] Among them, Step S400 includes:

[0116] Step S401: Obtain the suspected abnormal battery in the charging platform, power off the suspected abnormal battery, and statically place it for a preset characteristic unit time. Charge the suspected abnormal battery again, and monitor the charging of the suspected abnormal battery to obtain the data corresponding to the battery detection parameters in the suspected abnormal battery;

[0117] Step S402: When the maximum or minimum value of a certain battery detection parameter of the suspected abnormal battery is detected again to be outside the characteristic range of a certain battery detection parameter, it is determined that the suspected abnormal battery is abnormal and recorded as an abnormal battery. Otherwise, continue to use the adjusted charging strategy for charging;

[0118] Power off the abnormal battery in the charging platform, and send an alarm prompt to the user and the staff of the abnormal battery through the charging platform, and process the abnormal battery;

[0119] In order to better implement the above method, a battery charging process detection and management system is also proposed. The system includes a battery type detection module, an approximate evaluation module, an abnormal detection module, and an abnormal alarm module;

[0120] A battery type detection module, used to detect the battery type of a battery to obtain battery type detection data of the battery;

[0121] An approximate evaluation module, used to evaluate the approximate degree of battery state between the battery in the current cycle and a reference battery to obtain a target reference battery;

[0122] An anomaly detection module, used to detect anomalies in the charging state of a battery to obtain a suspected abnormal battery;

[0123] An anomaly alarm module, used to re-detect anomalies in the suspected abnormal battery to obtain an abnormal battery, cut off the power of the abnormal battery, and send an alarm to the user and the staff through a charging platform to prompt that the abnormal battery is abnormal;

[0124] Among them, the battery type detection module includes a charging test unit and a battery type detection unit;

[0125] A charging test unit, used to test and record the charging of a battery to obtain a charging test record;

[0126] A battery type detection unit, used to detect the battery type of a battery according to the charging test record to obtain battery type detection data of the battery;

[0127] Among them, the approximate evaluation module includes a difference analysis unit and an approximate evaluation unit;

[0128] A difference analysis unit, used to perform a difference analysis on the charging data set of a battery and each marked data set in the reference battery to obtain the difference value between the charging data set and each marked data set;

[0129] An approximate evaluation unit, used to obtain the approximate value of the charging state between the battery and the reference battery according to the difference value, analyze the approximate degree of the charging state between the battery and the reference battery to obtain a target reference battery;

[0130] Among them, the anomaly detection module includes a charging strategy adjustment unit and an anomaly detection unit;

[0131] A charging strategy adjustment unit, used to obtain the reference charging strategy of the target reference battery of a battery and adjust the charging strategy of the battery;

[0132] An anomaly detection unit, used to charge the battery using the adjusted charging strategy and detect anomalies in the charging state of the battery to obtain a suspected abnormal battery;

[0133] Among them, the anomaly alarm module includes an anomaly alarm unit;

[0134] An abnormal alarm unit is used to cut off the power supply of suspected abnormal batteries, charge the suspected abnormal batteries after power cut, detect the abnormalities of the suspected abnormal batteries again to obtain abnormal batteries, give an abnormal alarm to the abnormal batteries, and send alarm prompts to the users and staff of the abnormal batteries through a charging platform to remind them to handle the abnormal batteries.

[0135] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced by the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. A method for detecting and managing during the battery charging process, characterized in that, The method includes: Step S100: Obtain the charging test record of the battery, obtain the battery type differentiation data in the charging platform, detect the battery type of the battery, and obtain the type detection data of the battery; Step S200: Obtain the initial charging record of the battery, based on the type detection data, obtain the historical comparison charging record of the reference battery from the charging platform, evaluate the degree of approximation of the battery state between the battery in the current cycle and the reference battery, and obtain the target reference battery; Step S300: Obtain the reference charging strategy of the target reference battery, adjust the charging strategy of the battery, obtain the battery detection range of the target reference battery, perform abnormal detection on the charging state of the battery, and obtain the suspected abnormal battery; Step S400: Perform power-off static placement on the suspected abnormal battery, charge the suspected abnormal battery again after power-off static placement, perform abnormal re-detection on the suspected abnormal battery, obtain the abnormal battery, cut off the power of the abnormal battery, and send an alarm prompt to the user and the staff through the charging platform; The step S100 includes: Step S101: When the battery is charged in the current cycle, superimpose a high-frequency alternating current signal on the charging current of the battery, insert a current pulse with a preset duration, and at the same time pause the charging current of the battery, test and record the charging of the battery, and obtain the charging test record; Step S102: Obtain the voltage signal V´(t) and current signal I´(t) collected during the test period from the charging test record, and through Fourier transform, convert the voltage signal V´(t) and the current signal I´(t) to the frequency domain respectively 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 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 , and obtain the current value I of the current pulse pulse , and calculate the change resistance r = ΔV / I of the battery pulse ; Obtain the steady-state voltage V of the battery after testing, and fit the voltage-time variation curve V(t) of the battery after inserting a current pulse to a first-order exponential model: V(t) = V + (V min - V)·e （-t / τ） , where τ is the time constant. Based on the first-order exponential model, obtain the time constant τ of the battery; Step S104: Detect the battery type of the battery. The specific process is as follows: Obtain the battery type differentiation data in the charging platform. The battery type differentiation data includes the time constant, variable resistance, complex impedance at a preset frequency, and the corresponding range of the impedance phase angle in each battery type; When the time constant τ, variable resistance r, complex impedance Z(f) at a preset frequency, and impedance phase angle θ(f) of the battery are all within the range corresponding to a certain battery type, use the certain battery type as the battery type of the battery, and record the certain battery type as the detected battery type of the battery, and perform aggregation to obtain the type detection data of the battery.

2. The method for detecting and managing during the battery charging process according to claim 1, wherein, The step S200 includes: Step S201: Obtain the detected battery type of the battery from the type detection data, obtain the batteries of the same type as the detected battery type in the charging platform, and record them as reference batteries, and obtain the historical comparison charging records of each reference battery; Obtain the data corresponding to the current, voltage, and temperature of the reference battery charging from the historical comparison charging records; Step S202: Obtain the initial charging record of the battery in the current cycle, and obtain the 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 comparison charging record and the initial charging record; Set the unit time period t´, calculate the current integral of the battery in the unit time period in the initial charging record, and obtain the charging capacity Q of the battery in the unit time period; Obtain the temperature change rate v of the battery in the c-th unit time period in the initial charging record c =T c / t´, where T c is the change value of the temperature of the battery at the initial time point in the c-th unit time period; Take the average voltage, temperature change rate, and charging capacity of the battery as the charging characteristic parameters of the battery. Obtain the charging characteristic parameters of the battery in several unit time periods from the initial charging record, perform normalization processing and aggregation to obtain the charging data set P of the battery. Among them, the c-th element in the charging data set P is the value of the charging characteristic parameters of the battery in the c-th unit time period; Step S203: Obtain the duration and charging data set of the historical comparison charging record of the reference battery. Based on the duration corresponding to the initial charging record, slice the charging data set of the historical comparison charging record to obtain several marked charging data sets. Among them, the total number of elements in different marked charging data sets is n, and n is greater than the total number of elements m in the charging data set of the battery; Step S204: Obtain a certain labeled dataset G in the reference battery, and calculate the i-th element g in the certain labeled dataset G i , and the j-th element p in the charging dataset P i The feature distance d(g i , p j ); Based on the certain labeled dataset G and the charging dataset P of the battery, a distance matrix H is constructed. The distance matrix H is initialized and boundary conditions are set. Calculate the element h(i, j) corresponding to the i-th row and j-th column in the distance matrix H, where h(i, j)=d(g i , p j ) + min{h(i - 1, j), h(i, j - 1), h(i - 1, j - 1)}; Obtain 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 the charging data set P (g,p) : ， Obtain the reciprocal of the minimum value of the difference between several marked charging data sets in the reference battery and the charging data set P as the charging state approximation value between the reference battery and the battery; Step S205: Obtain the reference battery corresponding to the maximum value of the charging state approximation value between the battery and each reference battery, and denote it as the target reference battery, and determine that the battery state of the target reference battery is approximately the same as that of the battery.

3. The method for detecting and managing during the battery charging process according to claim 2, wherein The step S300 includes: Step S301: Obtain the reference charging strategy of the target reference battery in the charging platform. The reference charging strategy includes the change curves corresponding to the voltage and current of the target reference battery during charging; Step S302: Adjust the charging strategy of the battery based on the reference charging strategy. Specifically: obtain the remaining power of the battery in the current cycle. When the power of the target reference battery is the remaining power, obtain the change curves corresponding to the voltage and current of the target reference battery from the reference charging strategy, and use the change curves as the change curves of the voltage and current during charging of the battery in the current cycle; Step S303: Obtain the battery detection range of the target reference battery. The battery detection range includes the characteristic ranges corresponding to the battery detection parameters in the target reference battery, where the characteristic range is the range composed of the maximum and minimum values of the battery detection parameters in the target reference battery that are normal; Using the adjusted charging strategy, adjust the voltage and current for charging the battery, and perform abnormal detection on the charging state of the battery. The specific detection process is as follows: When the maximum or minimum value of a certain battery detection parameter in the battery is detected to be outside the characteristic range of the certain battery detection parameter, it is determined that the charging state of the battery is abnormal, and it is recorded as a suspected abnormal battery.

4. A method for detecting and managing a battery during charging according to claim 3, wherein The step S400 includes: Step S401: Obtain the suspected abnormal batteries in the charging platform, cut off the power of the suspected abnormal batteries, and keep them static for a preset characteristic unit time. Then, charge the suspected abnormal batteries again, monitor the charging of the suspected abnormal batteries, and obtain the data corresponding to each battery detection parameter in the suspected abnormal batteries; Step S402: When the maximum or minimum value of a certain battery detection parameter in the suspected abnormal battery is detected again to be outside the characteristic range of the certain battery detection parameter, it is determined that the suspected abnormal battery is abnormal and recorded as an abnormal battery. Otherwise, continue to use the adjusted charging strategy for charging; Cut off the power of the abnormal batteries in the charging platform, and send an alarm prompt to the users and staff of the abnormal batteries through the charging platform to process the abnormal batteries.

5. A detection and management system during battery charging, which is used to execute a detection and management method during battery charging described in any one of claims 1-4, characterized in that, The system includes a battery type detection module, an approximate evaluation module, an abnormal detection module, and an abnormal alarm module; The battery type detection module is used to detect the battery type of the battery to obtain the type detection data of the battery; The approximate evaluation module is used to evaluate the approximate degree of the battery state between the battery in the current cycle and the reference battery to obtain the target reference battery; The abnormal detection module is used to perform abnormal detection on the charging state of the battery to obtain suspected abnormal batteries; The abnormal alarm module is used to perform abnormal re-detection on the suspected abnormal batteries to obtain abnormal batteries, cut off the power of the abnormal batteries, and send an alarm to the users and staff through the charging platform to indicate that the abnormal batteries are abnormal.

6. The battery charging process detection and management system according to claim 5, 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.

7. The battery charging process detection and management system according to claim 5, 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 the 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 between the battery and the reference battery according to the difference value, analyze the approximate degree of the charging state between the battery and the reference battery, and obtain the target reference battery.

8. A battery charging process detection and management system according to claim 5, characterized in that, The abnormal detection module includes a charging strategy adjustment unit and an abnormal detection unit; The charging strategy adjustment unit is configured to obtain the reference charging strategy of the target reference battery of the battery and adjust the charging strategy of the battery; The anomaly detection unit is configured to charge the battery using the adjusted charging strategy and perform anomaly detection on the charging state of the battery to obtain a suspected abnormal battery.

9. A battery charging process detection and management system according to claim 5, characterized in that, The anomaly alarm module includes an anomaly alarm unit; The anomaly alarm unit is configured to cut off the power of the suspected abnormal battery, charge the suspected abnormal battery after power cut-off, perform anomaly detection on the suspected abnormal battery again to obtain an abnormal battery, perform an anomaly alarm on 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 process the abnormal battery.

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