Visual detection method, system and equipment for battery state and medium

Abstract

The invention provides a battery state visual detection method, system and device and a medium. The method comprises the following steps: marking a plurality of discharge voltage inflection points of a secondary battery in a current working state; determining an abnormal operation index of the secondary battery in the current working state based on the average battery temperature in the battery temperature information corresponding to the discharge voltage inflection point in combination with the capacity loss characteristic of the battery capacity on the discharge voltage inflection point; the charge change trend of the secondary battery working under the discharge working condition is determined, and the heat balance temperature of heating detection of the secondary battery under the discharge working condition is determined through the charge change trend and the voltage characteristic data of the secondary battery; and according to the heat balance temperature and the inflection point voltage of the secondary battery, the discharge health state visually displayed in the discharge process of the secondary battery is judged. Based on the scheme, the battery state can be comprehensively detected under the multi-parameter interaction effect of the secondary battery, so that the prediction capability of battery health state evaluation can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of battery status detection, and more specifically, to a method, system, device and medium for visually detecting battery status. Background Art

[0002] Battery status detection refers to the real-time monitoring and evaluation of various performance parameters of secondary batteries during use, such as voltage, temperature, state of charge, health status, etc., through a series of physical and electrochemical means, in order to accurately understand the operating status and remaining life of the secondary battery. This process usually combines sensors, data acquisition modules and intelligent algorithms to determine whether the battery is in normal working condition through a comprehensive analysis of the internal and external characteristics of the battery.

[0003] However, in the existing battery status visualization detection methods, health status assessment usually relies on simple single parameters such as voltage and temperature. There is a lack of comprehensive analysis of multi-dimensional factors such as electric field characteristics and capacity decay in the complex discharge process of the battery. As a result, the existing technology cannot accurately capture the subtle changes in battery performance degradation, resulting in the inability to effectively predict the potential failures and degradation trends of secondary batteries during the discharge process, thereby affecting the accuracy of battery management. Therefore, how to comprehensively detect the battery status under the interaction of multiple parameters of secondary batteries to improve the predictive ability of battery health status assessment is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a method, system, device and medium for visually detecting battery status, which can realize comprehensive detection of battery status under the interaction of multiple parameters of secondary batteries, thereby improving the predictive ability of battery health status assessment.

[0005] In a first aspect, the present application provides a method for visually detecting a battery status, comprising: Visually monitor the state of charge of the secondary battery, and mark multiple discharge voltage inflection points of the secondary battery in the current working state according to the monitoring results and the electric field characteristics of the secondary battery in low-voltage and overvoltage states, and collect the battery temperature information of the secondary battery at each discharge voltage inflection point in a discharge cycle; Determine a capacity loss characteristic of the secondary battery when state detection is performed at each discharge voltage inflection point, and determine an abnormal operation index of the secondary battery in a current working state based on the capacity loss characteristic combined with an average battery temperature in the battery temperature information; Determine the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery; The discharge health state of the secondary battery visually displayed during the discharge process is determined according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0006] In some embodiments, determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss feature and the average battery temperature in the battery temperature information specifically includes: determining the battery temperature of the secondary battery in a discharge cycle according to the battery temperature information; Determine the average battery temperature at each discharge voltage inflection point through the battery temperature in one cycle; Determining a capacity attenuation deviation of the secondary battery under a current working state according to the capacity loss characteristic; An abnormal operation index of the secondary battery in the current working state is determined according to the average battery temperature and the capacity decay deviation.

[0007] In some embodiments, determining the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition specifically includes: Determining operating voltage information of the secondary battery operating under a discharge condition according to the abnormal operating indicator; Determining the state of charge value of the secondary battery under discharge conditions; Determining a charge fluctuation deviation of the secondary battery operating under a discharge condition according to the state of charge value; The charge variation trend of the secondary battery operating under the discharge condition is determined by the operating voltage information and the charge fluctuation deviation.

[0008] In some embodiments, determining the thermal equilibrium temperature of the secondary battery under the discharge condition by using the charge variation trend and the voltage characteristic data of the secondary battery specifically includes: Determining a state of charge amplitude at which the secondary battery generates heat under a discharge condition according to the charge variation trend; Collecting voltage characteristic data of the secondary battery; Determining the temperature convergence entropy of heat generated by the secondary battery under discharge conditions according to the voltage characteristic data; The thermal equilibrium temperature of the secondary battery detected during heat generation under a discharge condition is determined by the state of charge amplitude and the temperature convergence entropy.

[0009] In some embodiments, determining the discharge health state of the secondary battery displayed visually during the discharge process according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery specifically includes: Determining the steady-state operating characteristics of the battery when it is working according to the thermal equilibrium temperature; Determining the knee voltage of the secondary battery; Determining a health index of the secondary battery according to the steady-state operation characteristics and the inflection point voltage; The discharge health state of the secondary battery visually displayed during the discharge process is determined according to the health index.

[0010] In some embodiments, marking multiple discharge voltage inflection points of the secondary battery in the current working state according to the monitoring results and the electric field characteristics of the secondary battery in the low voltage and overvoltage states specifically includes: Extracting the battery discharge time of the secondary battery from the monitoring result after the state of charge of the secondary battery is detected; Determine the low voltage electric field characteristics of secondary batteries under low voltage conditions; Determine the overvoltage electric field characteristics of the secondary battery under overvoltage state; Determining the electric field characteristics of the secondary battery under low voltage and over voltage states through the low voltage electric field characteristics and the over voltage electric field characteristics; A plurality of discharge voltage inflection points of the secondary battery in a current working state are determined according to the battery discharge time and the electric field characteristics.

[0011] In some embodiments, a temperature sensor is used to collect battery temperature information at each discharge voltage inflection point of the secondary battery during a discharge cycle.

[0012] In a second aspect, the present application provides a visual detection system for battery status, comprising: The monitoring module is used to visually monitor the state of charge of the secondary battery, and mark multiple discharge voltage inflection points of the secondary battery in the current working state according to the monitoring results and the electric field characteristics of the secondary battery in the low-voltage and overvoltage states, and collect the battery temperature information of the secondary battery at each discharge voltage inflection point in a discharge cycle; a processing module, configured to determine a capacity loss characteristic of the secondary battery when state detection is performed at each discharge voltage inflection point, and determine an abnormal operation index of the secondary battery in a current working state based on the capacity loss characteristic combined with an average battery temperature in the battery temperature information; The processing module is further used to determine the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery; The execution module is used to determine the discharge health state of the secondary battery displayed visually during the discharge process according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0013] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned visual detection method of the battery status.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions or codes, and when the instructions or codes are executed on a computer, the computer implements the above-mentioned visual detection method of the battery status when executing.

[0015] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: In a method, system, device and medium for visually detecting the state of a battery provided by the present application, the state of charge of a secondary battery is visually monitored, and multiple discharge voltage inflection points of the secondary battery in a current working state are marked according to the monitoring results and the electric field characteristics of the secondary battery in low-voltage and overvoltage states, and the battery temperature information of the secondary battery at each discharge voltage inflection point in a discharge cycle is collected; the capacity loss characteristics of the secondary battery when the state is detected at each discharge voltage inflection point are determined, and the abnormal operation index of the secondary battery in the current working state is determined based on the capacity loss characteristics combined with the average battery temperature in the battery temperature information; the charge change trend of the secondary battery working under the discharge condition is determined according to the abnormal operation index and the state of charge value of the secondary battery under the discharge condition, and the thermal equilibrium temperature of the secondary battery for heat detection under the discharge condition is determined through the charge change trend and the voltage characteristic data of the secondary battery; the discharge health state of the secondary battery visually displayed during the discharge process is determined according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0016] It can be seen that in this application, the discharge health state of the secondary battery displayed visually during the discharge process is determined according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery; wherein, by comprehensively analyzing the state of charge, electric field characteristics and voltage changes, the key time nodes of the secondary battery during the discharge process can be accurately marked, the accuracy of the discharge cycle prediction is improved, and the risk of battery performance degradation is discovered in advance; by combining the battery temperature information with the capacity loss, an in-depth analysis of the battery operation status is provided. Combining the indicators of temperature change and capacity decay can accurately evaluate the discharge health state of the secondary battery displayed visually during the discharge process, timely identify the abnormal operation of the secondary battery, and reduce the probability of failure; through the analysis of the charge change trend and voltage characteristic data, the thermal equilibrium temperature of the secondary battery can be accurately predicted to avoid safety problems caused by overheating; combining the thermal equilibrium temperature and the inflection point voltage to determine the discharge health state of the secondary battery displayed visually during the discharge process can more comprehensively and accurately evaluate the overall operation of the secondary battery. Through visual display, users can understand the battery health status in real time, intuitively identify potential faults, and take corresponding maintenance measures in time to extend the service life of secondary batteries and improve users' battery management efficiency; in summary, based on the above scheme, it is possible to carry out comprehensive detection of battery status under the multi-parameter interaction of secondary batteries, thereby improving the predictive ability of battery health status assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0018] Figure 1 is an exemplary flow chart of a method for visually detecting a battery status according to some embodiments of the present application; Figure 2 It is a pulse discharge battery terminal voltage waveform diagram shown in some embodiments of the present application; Figure 3 is a schematic diagram of a process for determining a thermal equilibrium temperature according to some embodiments of the present application; Figure 4 is a schematic structural diagram of a battery status visualization detection system according to some embodiments of the present application; Figure 5 It is a structural schematic diagram of a computer device for implementing a method for visually detecting battery status according to some embodiments of the present application. DETAILED DESCRIPTION

[0019] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0020] refer to Figure 1 , which is an exemplary flow chart of a method for visually detecting a battery status according to some embodiments of the present application, and the method for visually detecting a battery status mainly includes the following steps: In step 101, the state of charge of the secondary battery is visually monitored, and multiple discharge voltage inflection points of the secondary battery in the current working state are marked according to the monitoring results and the electric field characteristics of the secondary battery in low-voltage and overvoltage states, and the battery temperature information of the secondary battery at each discharge voltage inflection point in a discharge cycle is collected.

[0021] It should be noted that in the present application, the state of charge of the secondary battery is visually detected; in the specific implementation, first, the current sensor and voltage sensor are used to continuously record the current, voltage, working time and other data of the secondary battery to ensure that the sampling frequency is high enough to capture dynamic changes; then, the remaining power of the secondary battery is estimated by the coulomb counting method (based on current-time integration), and at the same time, combined with the open circuit voltage (OCV) characteristics of the battery, the initial value of the state of charge (SOC) is calibrated through the experimental calibration curve to reduce the error; to improve the accuracy, the extended Kalman filter (EKF) algorithm can be used to fuse the sensor data with the electrochemical model, dynamically correct the SOC value, and overcome the interference of noise and nonlinear factors.

[0022] In some embodiments, marking multiple discharge voltage inflection points of the secondary battery in the current working state according to the monitoring results and the electric field characteristics of the secondary battery in the low voltage and overvoltage states can be achieved by the following steps: Extracting the battery discharge time of the secondary battery from the monitoring result after the state of charge of the secondary battery is detected; Determine the low voltage electric field characteristics of secondary batteries under low voltage conditions; Determine the overvoltage electric field characteristics of the secondary battery under overvoltage state; Determining the electric field characteristics of the secondary battery under low voltage and over voltage states through the low voltage electric field characteristics and the over voltage electric field characteristics; A plurality of discharge voltage inflection points of the secondary battery in a current working state are determined according to the battery discharge time and the electric field characteristics.

[0023] In the specific implementation, firstly, based on the monitoring result of the state of charge (SOC), the time interval of the battery discharge process is determined, wherein the discharge time extraction can be determined by the following formula, namely, discharge time = the time point when the SOC reaches the discharge termination condition (such as lower than the set threshold) - the time point when the discharge starts, and the time range of the discharge termination condition (such as lower than the set threshold) - the time point when the discharge starts can be used as the battery discharge time of the secondary battery; secondly, within the time range of the battery discharge time, data points whose voltage is lower than the low-voltage threshold (such as 2.8V) are screened out, and then the finite element analysis tool is used to simulate the electric field under the low-voltage state, and the set of the field intensity mean and the field intensity gradient in the electric field is collected as the low-voltage electric field characteristics of the secondary battery under the low-voltage state; then, the data points whose voltage is higher than the overvoltage threshold (such as 4.2V) are screened out from the pre-collected discharge data. V), and then use the finite element analysis tool to construct the electric field model of the battery under the overvoltage state, and output the overvoltage electric field characteristics of the secondary battery under the overvoltage state through the electric field model of the battery under the overvoltage state; then, integrate the low-voltage and overvoltage electric field characteristic data to construct a state characteristic curve, which can be modeled by parameters, and is expressed as: state characteristic curve = f (low-voltage characteristic value, high-voltage characteristic value), and then analyze the relationship between the electric field characteristics and the SOC, determine the critical area (such as the SOC range where the electric field strength exceeds a specific value), and use the critical area as the electric field characteristics of the secondary battery under low-voltage and overvoltage states; finally, combine the battery discharge time interval and the electric field characteristic curve to analyze the critical time points of the secondary battery in voltage change, use the timing analysis algorithm to mark the alternation and superposition moments of the low-voltage characteristics and the overvoltage characteristics, determine the key time nodes, and use the key time nodes as multiple discharge voltage inflection points of the secondary battery in the current working state. For example, when the voltage is close to the critical value, the corresponding time is recorded as the discharge voltage inflection point.

[0024] It should be noted that, in the present application, the discharge voltage inflection point refers to the time point when the electric field characteristics reach a specific threshold during the battery discharge process; the battery discharge time refers to the time from the start of discharge to the stop of discharge; the low-voltage electric field characteristics refer to the distribution characteristics of the internal electric field when the battery is in a low-voltage state; the overvoltage electric field characteristics refer to the distribution characteristics of the internal electric field when the battery is in an overvoltage state; the electric field characteristics refer to the working characteristics of the battery electric field under low-voltage and overvoltage conditions.

[0025] In some embodiments, reference Figure 2As described, the figure is a flow chart of the pulse discharge battery terminal voltage waveform diagram shown in some embodiments of the present application, the terminal voltage curve of the battery's single pulse discharge, the current pulse starts at point A, and the current pulse ends at point C; it can be seen from the figure that the voltages of segments AB and CD drop and rise instantly; at the moment the current pulse of the secondary battery ends, the ohmic polarization effect disappears, therefore, in the voltage response curve, the instantaneous change in the battery terminal voltage at the moment the current pulse starts and ends is caused by the ohmic internal resistance; the two voltage differences ΔU1 and ΔU2 measured in the experiment are not consistent, therefore, when identifying the ohmic internal resistance, the average value of the two voltage differences is taken for calculation to reduce the error.

[0026] It should be noted that, in the present application, battery temperature information refers to the temperature values ​​at different positions of the secondary battery during operation and its status data changing over time; the battery temperature information is used to describe the thermal distribution characteristics of the secondary battery under different operating conditions.

[0027] In specific implementation, the battery temperature information of the secondary battery at each discharge voltage inflection point during a discharge cycle can be collected in the following manner, namely: first, multiple temperature sensors are installed on the surface and inside of the battery. These sensors capture temperature changes in milliseconds through high-speed sampling to ensure the real-time and accuracy of the temperature data; then, based on the battery discharge voltage inflection point, the sampled data is mapped to the corresponding time point, and the temperature information corresponding to the node is extracted. The interpolation algorithm can then be used to supplement the missing data, and the temperature distribution under complex working conditions can also be predicted through a time series model (such as LSTM). At the same time, data storage and processing can be carried out with the help of a cloud system to compare real-time temperature information with historical data to identify abnormal temperature rise trends. The battery temperature information corresponding to the discharge voltage inflection point can be obtained by reading the cloud system, which will not be repeated here.

[0028] In step 102, the capacity loss characteristics of the secondary battery when performing state detection at each discharge voltage inflection point are determined, and the abnormal operation index of the secondary battery in the current working state is determined based on the capacity loss characteristics combined with the average battery temperature in the battery temperature information.

[0029] In some embodiments, determining the capacity loss characteristics of a secondary battery when performing status detection at each discharge voltage inflection point can be achieved in the following manner, namely: the capacity loss of the secondary battery can be calculated by the coulomb counting method, namely: capacity loss characteristic = battery rated capacity - residual capacity at the discharge voltage inflection point. In order to improve the accuracy of the capacity loss characteristic, historical data can be reused in other embodiments and the influence of factors such as ambient temperature and charge and discharge rate can be always considered to correct the capacity loss characteristic, which is not limited here.

[0030] In some embodiments, determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss feature combined with the average battery temperature in the battery temperature information can be implemented by the following steps: determining the battery temperature of the secondary battery in a discharge cycle according to the battery temperature information; Determine the average battery temperature at each discharge voltage inflection point through the battery temperature in one cycle; Determining a capacity attenuation deviation of the secondary battery under a current working state according to the capacity loss characteristic; An abnormal operation index of the secondary battery in the current working state is determined according to the average battery temperature and the capacity decay deviation.

[0031] It should be noted that, in the present application, the abnormal operation index is an indicator that quantifies the degree of abnormality of the battery operation state. The higher the abnormal operation index, the lower the health of the secondary battery. The battery temperature of the secondary battery in a discharge cycle represents the set of temperature values ​​at different time points during the period from when the secondary battery is fully charged to when it reaches the discharge cut-off condition. The average battery temperature is used to reflect the thermal characteristics of the secondary battery in a discharge cycle. The capacity loss characteristic represents the capacity reduction caused by chemical reaction decay and cycle loss during the operation of the secondary battery. The capacity decay deviation is a quantitative value used to evaluate the degree of abnormal capacity decay.

[0032] In the specific implementation, first, use the temperature sensor to record the temperature change during the discharge cycle, and the sampling frequency should meet the dynamic response requirements (such as above 1Hz), where the discharge cycle is defined by the battery SOC (state of charge) or voltage threshold (such as SOC from 100% to 20% or voltage is lower than the set value), and then process the temperature data to remove noise (such as using a sliding average filter) to obtain the battery temperature data during the discharge cycle; then, divide the discharge cycle into multiple time nodes, each time node corresponds to a time window (such as 1 minute), and calculate the mean of the temperature data in each time node, that is, calculate the sum of the single temperature sampling values ​​in the time node and the quotient of the sampling number of the node, and sum the single temperature sampling values ​​in the time node The quotient of the sampling number of the node is taken as the average battery temperature of each discharge voltage inflection point; then, the actual capacity loss characteristics are compared with the theoretical capacity loss characteristics to determine the capacity attenuation deviation, that is, capacity attenuation deviation = capacity loss characteristics - theoretical capacity loss characteristics, where = the absolute value of the difference between the capacity loss characteristics and the theoretical capacity loss characteristics, and the theoretical capacity loss characteristics can be obtained through model calculation of parameters such as discharge rate, temperature, and number of cycles; finally, a multivariate regression model is constructed to combine the average battery temperature and capacity attenuation deviation to calculate the abnormal operation index, that is, abnormal operation index = a*average battery temperature+b*capacity attenuation deviation+c, where a, b, c are parameters of the multivariate regression model, which are trained by historical operation data.

[0033] In step 103, the charge variation trend of the secondary battery under the discharge condition is determined according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition, and the thermal equilibrium temperature of the secondary battery for heat detection under the discharge condition is determined by the charge variation trend and the voltage characteristic data of the secondary battery.

[0034] In some embodiments, determining the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition can be achieved by the following steps: Determining operating voltage information of the secondary battery operating under a discharge condition according to the abnormal operating indicator; Determining the state of charge value of the secondary battery under discharge conditions; Determining a charge fluctuation deviation of the secondary battery operating under a discharge condition according to the state of charge value; The charge variation trend of the secondary battery operating under the discharge condition is determined by the operating voltage information and the charge fluctuation deviation.

[0035] It should be noted that, in the present application, the operating voltage information represents the real-time voltage data of the secondary battery operating under discharge conditions; the state of charge value is a quantitative value reflecting the current available energy level of the battery; the charge fluctuation deviation is a quantitative value used to measure the deviation of abnormal changes in the state of charge; the charge change trend represents the dynamic change law of the state of charge of the secondary battery over time under operating conditions.

[0036] In the specific implementation, first, the voltage data of a specific time period during the discharge process is screened according to the abnormal operation index, such as the voltage change interval caused by temperature abnormality or capacity attenuation deviation, and then the voltage sensor is used to record the voltage change sequence over time during the discharge period, and the fluctuation characteristics are identified through data analysis, such as the extreme points or rapid change areas of the operating voltage, reflecting the voltage characteristics under abnormal operating conditions, that is, the operating voltage information of the secondary battery working under discharge conditions is obtained; then, the coulomb counting method can be used to calculate the state of charge at each moment, that is, the state of charge value can be the initial state of charge and the differential of the instantaneous discharge current over the discharge time and the nominal capacity of the battery. The difference is taken as the state of charge value of the secondary battery under the discharge condition; then, the charge fluctuation deviation of the secondary battery working under the discharge condition can be calculated in the following way, that is, charge fluctuation deviation = actual state of charge value under the discharge condition - theoretical state of charge value calculated based on the standard discharge curve; finally, the operating voltage information and the charge fluctuation deviation are correlated and analyzed, and the relationship between the two is extracted by constructing a multivariate model (such as linear regression or support vector machine), and then the charge change trend is extracted by using time series analysis (such as sliding window method), and a trend curve is generated, that is, the charge change trend of the secondary battery working under the discharge condition is obtained.

[0037] In some embodiments, the thermal equilibrium temperature of the secondary battery under discharge conditions is determined by the charge change trend and the voltage characteristic data of the secondary battery, referring to Figure 3 As shown in FIG. 1 , this figure is a schematic diagram of a process for determining the thermal equilibrium temperature in some embodiments of the present application. In this embodiment, the thermal equilibrium temperature can be determined by the following steps: In step 1031, a charge state amplitude at which the secondary battery generates heat under a discharge condition is determined according to the charge change trend; In step 1032, voltage characteristic data of the secondary battery is collected; In step 1033, the temperature convergence entropy of heat generated by the secondary battery under the discharge condition is determined according to the voltage characteristic data; In step 1034, a thermal equilibrium temperature of the secondary battery detected during heat generation under a discharge condition is determined by using the state of charge amplitude and the temperature convergence entropy.

[0038] It should be noted that, in the present application, the thermal equilibrium temperature refers to the stable temperature when the heat generation and heat dissipation of the secondary battery are in dynamic equilibrium; the state of charge amplitude refers to the dynamic range of battery charge change; the voltage characteristic data refers to the characteristic set of the voltage change of the secondary battery with time and frequency during operation; the temperature convergence entropy is an indicator to measure the degree of battery heat generation and the concentration of thermal effects.

[0039] In the specific implementation, firstly, the charge change trend data is used to extract the amplitude fluctuation range of the charge state. If the charge change trend is time series data, the time domain analysis technology (such as FFT) is used to extract the main frequency and amplitude of the signal, quantify the energy fluctuation caused by the charge change during the discharge process of the secondary battery, and improve the reliability of the amplitude calculation through smoothing or denoising, and eliminate the influence of short-term spikes, that is, the charge state amplitude of the secondary battery under the discharge condition is obtained; secondly, a high-precision voltage sensor is used to record the voltage data during the discharge process in real time to form a characteristic time series, and the frequency domain characteristics (such as main frequency and harmonics) of the voltage signal are extracted through Fourier transform (FFT), the voltage fluctuation mode is analyzed, and then combined with the abnormal operation indicators, the specific period of time is analyzed. The voltage characteristics (such as overshoot and drop points) are marked, and the marked voltage characteristics are used as voltage characteristic data; then, the voltage characteristic data is used to calculate the temperature convergence entropy related to the thermal effect, and the conditional entropy is constructed through the joint distribution of the temperature data and the voltage characteristic data. The conditional probability distribution of the temperature under a given voltage value can be used as the conditional entropy, and then the temperature convergence entropy of the secondary battery under discharge conditions is calculated through the conditional entropy, that is, the temperature convergence entropy = the entropy value of the temperature - the conditional entropy, where the difference between the entropy value of the temperature and the conditional entropy is taken as the absolute value; finally, an association model is constructed, the state of charge amplitude and the temperature convergence entropy are used as input variables, and the model parameters are fitted using regression analysis (such as multivariate linear regression or neural network) to predict the thermal equilibrium temperature, which is K 1 * SOC amplitude + K 2 * Temperature Convergence Entropy + K 3 , where K 1 , K 2 , K 3 It is a correlation model determined by fitting historical experimental data.

[0040] In step 104, a discharge health state of the secondary battery visually displayed during the discharge process is determined according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0041] In some embodiments, determining the discharge health state of the secondary battery displayed visually during the discharge process according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery can be achieved by using the following steps: Determining the steady-state operating characteristics of the battery when it is working according to the thermal equilibrium temperature; Determining the knee voltage of the secondary battery; Determining a health index of the secondary battery according to the steady-state operation characteristics and the inflection point voltage; The discharge health state of the secondary battery visually displayed during the discharge process is determined according to the health index.

[0042] It should be noted that, in the present application, the steady-state operating characteristics refer to the thermal characteristics of the secondary battery when the temperature and heat flow reach equilibrium after a long period of operation, which is used to evaluate the battery thermal management capability; the inflection point voltage refers to the point at which the voltage curve of the secondary battery changes significantly during the discharge process, which usually occurs when the battery is about to reach the discharge cut-off voltage; the inflection point voltage reflects the change in battery performance, indicating the attenuation or damage of the battery capacity; the health index represents a quantitative parameter of the overall health status of the secondary battery; the discharge health status represents the overall operating status of the secondary battery during the discharge process.

[0043] In the specific implementation, first, the thermal behavior of the secondary battery in steady state is analyzed through the thermal equilibrium temperature, combined with the working environment and discharge conditions of the secondary battery. The steady-state operation characteristics involve the temperature stability and thermal diffusion characteristics of the secondary battery after long-term discharge. Based on the thermal equilibrium temperature, the heat flow and heat capacity of the secondary battery in steady state are inferred using thermodynamic models (such as the one-dimensional heat conduction equation). Then, by comparing with the battery design parameters (such as material properties, dimensions, etc.), the thermal diffusion rate and thermal uniformity of the secondary battery are evaluated, and the thermal diffusion rate and thermal uniformity of the secondary battery are used as the steady-state operation characteristics of the battery when working; secondly, by analyzing the relationship between the battery voltage and the discharge capacity, the inflection point of the voltage curve can be found using the second-order derivative method. The inflection point usually corresponds to a significant change in the battery capacity attenuation or an increase in the internal impedance of the battery. The voltage value corresponding to the inflection point of the voltage curve is used as the inflection point voltage; then, combining the steady-state operation characteristics (such as temperature stability) and the inflection point voltage, a health index model is constructed. The health index model includes historical data fitting to determine the model parameters, the inflection point voltage, and the inflection point voltage. point voltage and a reference voltage value, wherein the reference voltage value can be determined by historical voltage data, which will not be repeated here; further, determining the discharge health state of the secondary battery visually displayed during the discharge process according to the health index can be achieved in the following manner, namely: by comparing the health index with a preset health state standard, determining the discharge health state of the secondary battery visually displayed during the discharge process, wherein the discharge health state standard includes: high health index (health index>0.8): the battery is in good health and suitable for continued use; medium health index (0.5<health index≤0.8): the battery has a certain decline and needs to be inspected or restricted in use; low health index (health index≤0.5): the battery is in poor health and it is recommended to replace or repair it; a machine learning model (such as a classification algorithm) can be used to further optimize the determination of the health state to adapt to different types of batteries and working environments.

[0044] In addition, in another aspect of the present application, in some embodiments, the present application provides a visual detection system for battery status, referring to Figure 4 , which is a schematic diagram of the structure of a visual detection system for battery status according to some embodiments of the present application, and the visual detection system for battery status includes: a monitoring module 201, a processing module 202 and an execution module 203, which are respectively described as follows: Monitoring module 201, in the present application, the monitoring module 201 is mainly used to visually monitor the state of charge of the secondary battery, and mark multiple discharge voltage inflection points of the secondary battery in the current working state according to the monitoring results and the electric field characteristics of the secondary battery in the low voltage and overvoltage states, and collect the battery temperature information of the secondary battery at each discharge voltage inflection point in a discharge cycle; The processing module 202 in the present application is mainly used to determine the capacity loss characteristics of the secondary battery when the state is detected at each discharge voltage inflection point, and determine the abnormal operation index of the secondary battery in the current working state based on the capacity loss characteristics combined with the average battery temperature in the battery temperature information; The processing module 202 is further used to determine the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery; The execution module 203 in the present application is mainly used to determine the discharge health state of the secondary battery displayed visually during the discharge process according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0045] The above describes in detail the examples of the visual detection method, system, device and medium of the battery status provided by the embodiments of the present application. It can be understood that the corresponding device includes a hardware structure and / or software module corresponding to each function in order to realize the above functions. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present application.

[0046] In some embodiments, the present application also provides a computer device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned visual detection method of the battery status.

[0047] In some embodiments, reference Figure 5 , the dotted line in the figure indicates that the unit or the module is optional, and the figure is a schematic diagram of the structure of a computer device for implementing a visual detection method of battery status according to an embodiment of the present application. The visual detection method of battery status described in the above embodiment can be Figure 5 The computer device shown in the figure is implemented, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device can be a terminal device, a server or a chip.

[0048] The processor 301 may be a general-purpose processor or a special-purpose processor. For example, the processor 301 may be a central processing unit (CPU), which may be used to control the computer device, execute software programs, and process data of the software programs. The computer device may also include a communication unit 305 to implement signal input (reception) and output (transmission).

[0049] For example, the computer device may be a chip, the communication unit 305 may be an input and / or output circuit of the chip, or the communication unit 305 may be a communication interface of the chip, and the chip may be a component of a terminal device, a network device, or other devices.

[0050] For another example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0051] The computer device may include one or more memories 302, on which a program 304 is stored. The program 304 can be executed by the processor 301 to generate instructions 303, so that the processor 301 performs the method described in the above method embodiment according to the instructions 303. Optionally, data (such as a target audit model) can also be stored in the memory 302. Optionally, the processor 301 can also read the data stored in the memory 302, and the data can be stored at the same storage address as the program 304, or the data can be stored at a different storage address from the program 304.

[0052] The processor 301 and the memory 302 may be provided separately or integrated together, for example, integrated on a system-on-chip of a terminal device.

[0053] It should be understood that each step of the above method embodiment can be completed by a hardware-based logic circuit or software-based instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0054] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0055] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer implements the above-mentioned visual detection method of the battery status when executing.

[0056] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0057] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A visual detection method for battery status, characterized in that: The steps include: Visually monitor the state of charge of the secondary battery, and mark multiple discharge voltage inflection points of the secondary battery in the current working state according to the monitoring results and the electric field characteristics of the secondary battery in low-voltage and overvoltage states, and collect the battery temperature information of the secondary battery at each discharge voltage inflection point in a discharge cycle; Determine a capacity loss characteristic of the secondary battery when state detection is performed at each discharge voltage inflection point, and determine an abnormal operation index of the secondary battery in a current working state based on the capacity loss characteristic combined with an average battery temperature in the battery temperature information; Determine the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery; The discharge health state of the secondary battery visually displayed during the discharge process is determined according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

2. The method according to claim 1, characterized in that Determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss feature and the average battery temperature in the battery temperature information specifically includes: determining a battery temperature of the secondary battery in a discharge cycle according to the battery temperature information; Determine the average battery temperature at each discharge voltage inflection point through the battery temperature in one cycle; Determining a capacity attenuation deviation of the secondary battery under a current working state according to the capacity loss characteristic; An abnormal operation index of the secondary battery in the current working state is determined according to the average battery temperature and the capacity decay deviation.

3. The method according to claim 1, characterized in that Determining the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition specifically includes: Determining operating voltage information of the secondary battery operating under a discharge condition according to the abnormal operating indicator; Determining the state of charge value of the secondary battery under discharge conditions; Determining a charge fluctuation deviation of the secondary battery operating under a discharge condition according to the state of charge value; The charge variation trend of the secondary battery operating under the discharge condition is determined by the operating voltage information and the charge fluctuation deviation.

4. The method according to claim 1, characterized in that Determining the thermal equilibrium temperature of the secondary battery under the discharge condition by using the charge variation trend and the voltage characteristic data of the secondary battery specifically includes: Determining a state of charge amplitude at which the secondary battery generates heat under a discharge condition according to the charge variation trend; Collecting voltage characteristic data of the secondary battery; Determining the temperature convergence entropy of heat generated by the secondary battery under discharge conditions according to the voltage characteristic data; The thermal equilibrium temperature of the secondary battery detected during heat generation under a discharge condition is determined by the state of charge amplitude and the temperature convergence entropy.

5. The method according to claim 1, characterized in that Determining the discharge health state of the secondary battery visually displayed during the discharge process according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery specifically includes: Determining steady-state operating characteristics of the battery when it is operating according to the thermal equilibrium temperature; Determining the knee voltage of the secondary battery; Determining a health index of the secondary battery according to the steady-state operation characteristics and the inflection point voltage; The discharge health state of the secondary battery visually displayed during the discharge process is determined according to the health index.

6. The method according to claim 1, characterized in that According to the monitoring results and the electric field characteristics of the secondary battery under low voltage and overvoltage conditions, multiple discharge voltage inflection points of the secondary battery under the current working state are marked, including: Extracting the battery discharge time of the secondary battery from the monitoring result after the state of charge of the secondary battery is detected; Determine the low voltage electric field characteristics of secondary batteries under low voltage conditions; Determine the overvoltage electric field characteristics of the secondary battery under overvoltage state; Determining the electric field characteristics of the secondary battery under low voltage and over voltage states through the low voltage electric field characteristics and the over voltage electric field characteristics; A plurality of discharge voltage inflection points of the secondary battery in a current working state are determined according to the battery discharge time and the electric field characteristics.

7. The method according to claim 1, characterized in that A temperature sensor is used to collect battery temperature information at each discharge voltage inflection point of the secondary battery during a discharge cycle.

8. A visual detection system for battery status, characterized in that: include: The monitoring module is used to visually monitor the state of charge of the secondary battery, and mark multiple discharge voltage inflection points of the secondary battery in the current working state according to the monitoring results and the electric field characteristics of the secondary battery in the low-voltage and overvoltage states, and collect the battery temperature information of the secondary battery at each discharge voltage inflection point in a discharge cycle; a processing module, configured to determine a capacity loss characteristic of the secondary battery when state detection is performed at each discharge voltage inflection point, and determine an abnormal operation index of the secondary battery in a current working state based on the capacity loss characteristic combined with an average battery temperature in the battery temperature information; The processing module is further used to determine the charge change trend of the secondary battery under the discharge condition according to the abnormal operation index and the charge state value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery; The execution module is used to determine the discharge health state of the secondary battery displayed visually during the discharge process according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

9. A computer device, characterized in that: The computer device comprises a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the visual detection method of the battery status according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions or codes, and when the instructions or codes are executed on a computer, the computer implements the visual detection method for the battery status as described in any one of claims 1 to 7.

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