A Visual Detection Method, System, Device and Medium for Battery State

Abstract

The present application provides a method, system, device and medium for visual detection of battery state, which marks multiple discharge voltage inflection points of a secondary battery in the current working state; determines 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 and the capacity loss characteristics of the battery capacity at the discharge voltage inflection point; then determines the charge change trend of the secondary battery during discharge operation, and determines the thermal equilibrium temperature for heat detection of the secondary battery during discharge operation through the charge change trend and the voltage characteristic data of the secondary battery; and determines the discharge health state visually displayed by the secondary battery during discharge based on the thermal equilibrium temperature and the inflection point voltage of the secondary battery. Based on the above solution, a comprehensive detection of the battery state can be realized under the interaction of multiple parameters of the secondary battery, thereby improving the prediction ability of battery health state assessment.

Description

Technical Field

[0001] This application relates to the technical field of battery state detection. More specifically, this application relates to a method, system, device, and medium for visual detection of battery state. Background Art

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

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

[0004] This application provides a method, system, device, and medium for visual detection of battery state, which can comprehensively detect the battery state under the interaction of multiple parameters of secondary batteries, thereby improving the prediction ability of battery state of health assessment.

[0005] In a first aspect, this application provides a method for visual detection of battery state, including:

[0006] 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 over-voltage states, and collect the battery temperature information at each discharge voltage inflection point within one discharge cycle of the secondary battery.

[0007] Determine the capacity loss characteristics of the secondary battery when performing state detection 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 and the average battery temperature in the battery temperature information.

[0008] Determine the charge change trend of the secondary battery during discharge based on the abnormal operation index and the state of charge value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature for heat detection of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery;

[0009] Judge the discharge health state visually displayed by the secondary battery during discharge according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0010] In some embodiments, determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss characteristic and the average battery temperature in the battery temperature information specifically includes:

[0011] Determine the battery temperature of the secondary battery within one discharge cycle according to the battery temperature information;

[0012] Determine the average battery temperature of each discharge voltage inflection point through the battery temperature within one cycle;

[0013] Determine the capacity attenuation deviation of the secondary battery in the current working state according to the capacity loss characteristic;

[0014] Determine the abnormal operation index of the secondary battery in the current working state according to the average battery temperature and the capacity attenuation deviation.

[0015] In some embodiments, determining the charge change trend of the secondary battery during discharge based on the abnormal operation index and the state of charge value of the secondary battery under the discharge condition specifically includes:

[0016] Determine the operating voltage information of the secondary battery during discharge according to the abnormal operation index;

[0017] Determine the state of charge value of the secondary battery under the discharge condition;

[0018] Determine the charge fluctuation deviation of the secondary battery during discharge according to the state of charge value;

[0019] Determine the charge change trend of the secondary battery during discharge through the operating voltage information and the charge fluctuation deviation.

[0020] In some embodiments, determining the thermal equilibrium temperature for heat detection of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery specifically includes:

[0021] Determine the charge state amplitude of the secondary battery during discharge heat generation according to the charge change trend;

[0022] Collect the voltage characteristic data of the secondary battery;

[0023] Determine the temperature convergence entropy of the secondary battery generating heat under the discharge condition according to the voltage characteristic data;

[0024] Determine the thermal equilibrium temperature of the secondary battery for heat generation detection under the discharge condition through the state-of-charge amplitude and the temperature convergence entropy.

[0025] In some embodiments, determining the discharge health state visually displayed during the discharge process of the secondary battery according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery specifically includes:

[0026] Determine the steady-state operation characteristics when the battery is working according to the thermal equilibrium temperature;

[0027] Determine the inflection point voltage of the secondary battery;

[0028] Determine the health index of the secondary battery according to the steady-state operation characteristics and the inflection point voltage;

[0029] Determine the discharge health state visually displayed during the discharge process of the secondary battery according to the health index.

[0030] 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 over-voltage states specifically includes:

[0031] Extract the battery discharge time of the secondary battery from the monitoring results after detecting the state of charge of the secondary battery;

[0032] Determine the low-voltage electric field characteristics of the secondary battery in the low-voltage state;

[0033] Determine the over-voltage electric field characteristics of the secondary battery in the over-voltage state;

[0034] Determine the electric field characteristics of the secondary battery in the low-voltage and over-voltage states through the low-voltage electric field characteristics and the over-voltage electric field characteristics;

[0035] Determine multiple discharge voltage inflection points of the secondary battery in the current working state according to the battery discharge time and the electric field characteristics.

[0036] In some embodiments, use a temperature sensor to collect the battery temperature information at each discharge voltage inflection point of the secondary battery during a discharge cycle.

[0037] In a second aspect, the present application provides a visual detection system for battery state, including:

[0038] A monitoring module for visually monitoring the state of charge of a secondary battery, 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 over-voltage states, and collecting the battery temperature information at each discharge voltage inflection point within one discharge cycle of the secondary battery;

[0039] A processing module for determining the capacity loss characteristics when the secondary battery performs state detection at each discharge voltage inflection point, and determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss characteristics and the average battery temperature in the battery temperature information;

[0040] The processing module is further configured to determine the charge change trend of the secondary battery during the discharge operation according to the abnormal operation index and the state of charge value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature of the secondary battery for heat detection during the discharge operation through the charge change trend and the voltage characteristic data of the secondary battery;

[0041] An execution module for determining the visually displayed discharge health state of the secondary battery during the discharge process according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0042] In a third aspect, the present application provides a computer device, which includes 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 above-mentioned visual detection method for the battery state.

[0043] In a fourth aspect, the present application 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 is enabled to execute the above-mentioned visual detection method for the battery state.

[0044] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects:

[0045] In a method, system, device, and medium for visual detection of battery status provided by this application, the state of charge of a secondary battery is visually monitored, and based on the monitoring results and the electric field characteristics of the secondary battery in the low-voltage and over-voltage states, multiple discharge voltage inflection points of the secondary battery in the current working state are marked. The battery temperature information at each discharge voltage inflection point within one discharge cycle of the secondary battery is collected; the capacity loss characteristics of the secondary battery when performing state detection at each discharge voltage inflection point are determined, and based on the capacity loss characteristics and the average battery temperature in the battery temperature information, the abnormal operation index of the secondary battery in the current working state is determined; according to the abnormal operation index and the state of charge value of the secondary battery under the discharge condition, the charge change trend of the secondary battery when working under the discharge condition is determined, and through the charge change trend and the voltage characteristic data of the secondary battery, the thermal equilibrium temperature for heat detection of the secondary battery under the discharge condition is determined; according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery, the discharge health state visually displayed by the secondary battery during the discharge process is determined.

[0046] It can be seen that in this application, according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery, the discharge health state visually displayed by the secondary battery during the discharge process is determined; among them, 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, improving the accuracy of discharge cycle prediction and detecting the risk of battery performance degradation in advance; by combining the battery temperature information with the capacity loss, in-depth analysis of the battery operating state is provided. The index combining temperature change and capacity decay can accurately evaluate the discharge health state visually displayed by the secondary battery during the discharge process, timely identify the abnormal operation of the secondary battery, and reduce the probability of failure occurrence; through the analysis of the charge change trend and voltage characteristic data, the thermal equilibrium temperature of the secondary battery can be accurately predicted, avoiding safety problems caused by overheating; by combining the thermal equilibrium temperature and the inflection point voltage to determine the discharge health state visually displayed by the secondary battery during the discharge process, the overall operation of the secondary battery can be evaluated more comprehensively and accurately. Through visual display, users can grasp the battery health status in real time, intuitively identify potential faults, take corresponding maintenance measures in a timely manner, extend the service life of the secondary battery, and improve the battery management efficiency of users; in summary, based on the above solution, comprehensive detection of the battery status can be realized under the interaction of multiple parameters of the secondary battery, thereby improving the prediction ability of battery health state assessment. Brief Description of the Drawings

[0047] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0048] Figure 1 is an exemplary flowchart of a method for visual inspection of battery state according to some embodiments of the present application;

[0049] Figure 2 is a waveform diagram of the terminal voltage of a pulsed discharge battery according to some embodiments of the present application;

[0050] Figure 3 is a schematic flowchart for determining the thermal equilibrium temperature according to some embodiments of the present application;

[0051] Figure 4 is a schematic structural diagram of a system for visual inspection of battery state according to some embodiments of the present application;

[0052] Figure 5 is a schematic structural diagram of a computer device for implementing a method for visual inspection of battery state according to some embodiments of the present application. Detailed Embodiments

[0053] To better understand the technical solutions of the present application, the following will detail the technical solutions of the present application in combination with the accompanying drawings of the specification and specific embodiments.

[0054] Refer to Figure 1 , which is an exemplary flowchart of a method for visual inspection of a battery state according to some embodiments of the present application. The method for visual inspection of the battery state mainly includes the following steps:

[0055] In step 101, 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 over-voltage states, and collect the battery temperature information at each discharge voltage inflection point within one discharge cycle of the secondary battery.

[0056] It should be noted that in this application, the state of charge of the secondary battery is visually detected. Specifically, in implementation, first, a current sensor and a voltage sensor are used to continuously record data such as the current, voltage, and working time of the secondary battery, ensuring that the sampling frequency is high enough to capture dynamic changes. Then, the remaining power of the secondary battery is estimated by Coulomb counting (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 an experimental calibration curve to reduce errors. To improve the accuracy, the extended Kalman filter (EKF) algorithm can be used to fuse the sensor data with the electrochemical model and dynamically correct the SOC value to overcome the interference of noise and non-linear factors.

[0057] 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 over-voltage states can be achieved by the following steps:

[0058] Extract the battery discharge time of the secondary battery from the monitoring results after detecting the state of charge of the secondary battery;

[0059] Determine the low-voltage electric field characteristics of the secondary battery in the low-voltage state;

[0060] Determine the over-voltage electric field characteristics of the secondary battery in the over-voltage state;

[0061] Determine the electric field characteristics of the secondary battery in the low-voltage and over-voltage states through the low-voltage electric field characteristics and the over-voltage electric field characteristics;

[0062] Determine multiple discharge voltage inflection points of the secondary battery in the current working state according to the battery discharge time and the electric field characteristics.

[0063] In specific implementation, first, based on the monitoring results of the state of charge (SOC), determine the time interval of the battery discharge process. Among them, the discharge time extraction can be determined by the following formula, that is, the discharge time = the time point when the SOC reaches the discharge termination condition (such as below the set threshold) - the time point when the discharge starts. The time range of the discharge termination condition (such as below 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, screen out the data points with voltages lower than the low voltage threshold (such as 2.8 V), and then use the finite element analysis tool to simulate the electric field under the low voltage state, and collect the set of the average field strength and the field strength gradient in this electric field as the low voltage electric field characteristics of the secondary battery under the low voltage state. Then, screen out the time period with a voltage higher than the overvoltage threshold (such as 4.2 V) from the pre-collected discharge data, and then use the finite element analysis tool to construct an 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. Furthermore, integrate the low voltage and overvoltage electric field characteristic data to construct a state characteristic curve. This state characteristic curve can be parametrically modeled and is expressed as: state characteristic curve = f (low voltage characteristic value, high voltage characteristic value). Then, analyze the relationship between the electric field characteristics and the SOC, determine the critical region (such as the SOC range where the electric field strength exceeds a specific value), and use this critical region as the electric field characteristics of the secondary battery under the low voltage and overvoltage states. Finally, combine the battery discharge time interval and the electric field characteristic curve, analyze the critical time point of the secondary battery during the voltage change, adopt the time series analysis algorithm, mark the alternating and superimposing moments of the low voltage characteristics and the overvoltage characteristics, determine the key time nodes, and use this key time node as the multiple discharge voltage inflection points of the secondary battery under the current working state. For example, when the voltage approaches the critical value, record the corresponding time as the discharge voltage inflection point.

[0064] It should be noted that in this 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 elapsed from the start of the battery discharge to the stop of the discharge; the low voltage electric field characteristic refers to the distribution characteristic of the internal electric field when the battery is in the low voltage state; the overvoltage electric field characteristic refers to the distribution characteristic of the internal electric field when the battery is in the overvoltage state; the electric field characteristic refers to the working characteristic of the battery electric field under the low voltage and overvoltage conditions.

[0065] In some embodiments, refer to Figure 2As described above, the figure is a flow chart of the pulse discharge battery terminal voltage waveform shown in some embodiments of the present application. The terminal voltage curve of a single pulse discharge of the battery starts at point A and ends at point C. It can be seen from the figure that the voltages of segments AB and CD drop and rise instantaneously. At the moment the current pulse ends, the ohmic polarization effect of the secondary battery 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.

[0066] It should be noted that, in this application, battery temperature information refers to the temperature values at different locations 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.

[0067] 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 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, or the temperature distribution under complex working conditions can 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.

[0068] 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 and the average battery temperature in the battery temperature information.

[0069] In some embodiments, determining the capacity loss characteristics of a secondary battery during 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 characteristics = battery rated capacity - residual capacity at the discharge voltage inflection point. In order to improve the accuracy of the capacity loss characteristics, in other embodiments, historical data can be reused and the influence of factors such as ambient temperature and charge and discharge rate can be always considered to correct the capacity loss characteristics. This is not limited here.

[0070] In some embodiments, determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss characteristic and combining the average battery temperature in the battery temperature information can be implemented by the following steps:

[0071] Determine the battery temperature of the secondary battery within a discharge cycle according to the battery temperature information;

[0072] Determine the average battery temperature of each discharge voltage inflection point through the battery temperature within one cycle;

[0073] Determine the capacity attenuation deviation of the secondary battery in the current working state according to the capacity loss characteristic;

[0074] Determine the abnormal operation index of the secondary battery in the current working state according to the average battery temperature and the capacity attenuation deviation.

[0075] It should be noted that in this application, the abnormal operation index is an index that quantifies the degree of abnormality of the battery operation state. The higher the abnormal operation index, the lower the health degree of the secondary battery; the battery temperature of the secondary battery within a discharge cycle represents the set of temperature values at different time points during the period when the secondary battery is fully charged to the discharge cut-off condition, and the average battery temperature is used to reflect the thermal characteristics of the secondary battery within one discharge cycle; the capacity loss characteristic represents the amount of capacity reduction of the secondary battery during operation due to chemical reaction decline and cycle loss; the capacity attenuation deviation is a quantitative value used to evaluate the degree of abnormal capacity attenuation.

[0076] In specific implementation, first, a temperature sensor is used to record the temperature change during the discharge cycle. The sampling frequency should meet the dynamic response requirements (such as above 1 Hz). Among them, the discharge cycle is defined by the battery SOC (state of charge) or voltage threshold (such as SOC from 100% to 20% or the voltage is lower than the set value). Then, the temperature data is processed to remove noise (such as using moving average filtering) to obtain the battery temperature data during the discharge cycle. Then, the discharge cycle is divided into multiple time nodes, each time node corresponds to a time window (such as 1 minute), and the average value of the temperature data within each time node is calculated, that is, the quotient of the sum of the single temperature sampling values within the time node and the number of samplings at this node. The quotient of the sum of the single temperature sampling values within the time node and the number of samplings at this node is used as the average battery temperature at each discharge voltage inflection point. Furthermore, the actual capacity loss characteristic is compared with the theoretical capacity loss characteristic to determine the capacity attenuation deviation, that is, capacity attenuation deviation = capacity loss characteristic - theoretical capacity loss characteristic, where, = the absolute value of the difference between the capacity loss characteristic and the theoretical capacity loss characteristic. The theoretical capacity loss characteristic can be obtained through model calculation of parameters such as discharge rate, temperature, and number of cycles. Finally, a multivariable regression model is constructed to combine the average battery temperature and the 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, and c are the parameters of the multivariable regression model and are obtained by training with historical operation data.

[0077] In step 103, according to the abnormal operation index and the state of charge value of the secondary battery under the discharge condition, the charge change trend of the secondary battery working under the discharge condition is determined, and the thermal equilibrium temperature for heat generation detection of the secondary battery under the discharge condition is determined through the charge change trend and the voltage characteristic data of the secondary battery.

[0078] In some embodiments, the charge change trend of the secondary battery working under the discharge condition determined according to the abnormal operation index and the state of charge value of the secondary battery under the discharge condition can be implemented by the following steps:

[0079] Determine the operating voltage information of the secondary battery working under the discharge condition according to the abnormal operation index;

[0080] Determine the state of charge value of the secondary battery under the discharge condition;

[0081] Determine the charge fluctuation deviation of the secondary battery working under the discharge condition according to the state of charge value;

[0082] Determine the charge change trend of the secondary battery working under the discharge condition through the operating voltage information and the charge fluctuation deviation.

[0083] It should be noted that in this application, the operating voltage information represents the real-time voltage data of the secondary battery operating under the discharge condition; the state of charge value is a quantitative value reflecting the current available energy level of the battery; the charge fluctuation deviation is a deviation quantitative value used to measure 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 the operating condition.

[0084] In specific implementation, first, according to the abnormal operation indicators, screen the voltage data during a specific period in the discharge process, such as the voltage change interval caused by abnormal temperature or capacity attenuation deviation. Then, use the voltage sensor to record the voltage change sequence over time during discharge, and identify the fluctuation characteristics through data analysis, such as the extreme points or rapid change areas of the operating voltage, to reflect the voltage characteristics under abnormal operating conditions, that is, obtain the operating voltage information of the secondary battery operating under the discharge condition. Next, 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 obtained by subtracting the ratio of the differential of the initial state of charge and the instantaneous discharge current over the discharge time to the nominal capacity of the battery from 1. Then, the charge fluctuation deviation of the secondary battery operating 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, perform a correlation analysis on the operating voltage information and the charge fluctuation deviation, extract the relationship between the two by constructing a multi-variable model (such as linear regression or support vector machine), and then use time series analysis (such as the sliding window method) to extract the charge change trend and generate a trend curve, that is, obtain the charge change trend of the secondary battery operating under the discharge condition.

[0085] In some embodiments, determine the thermal equilibrium temperature for heat detection of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery. Refer to Figure 3 As shown, this figure is a schematic flowchart for determining the thermal equilibrium temperature in some embodiments of this application. In this embodiment, the thermal equilibrium temperature can be determined by the following steps:

[0086] In step 1031, determine the state of charge amplitude of the secondary battery generating heat under the discharge condition according to the charge change trend.

[0087] In step 1032, collect the voltage characteristic data of the secondary battery.

[0088] In step 1033, determine the temperature convergence entropy of the secondary battery generating heat under the discharge condition according to the voltage characteristic data.

[0089] In step 1034, determine the thermal equilibrium temperature for heat detection of the secondary battery under the discharge condition through the state of charge amplitude and the temperature convergence entropy.

[0090] It should be noted that in this application, the thermal equilibrium temperature represents the stable temperature at which the heat generation and heat dissipation of the secondary battery are in dynamic equilibrium; the state-of-charge amplitude represents the dynamic range of the battery state-of-charge change; the voltage characteristic data represents the set of characteristics of the voltage of the secondary battery changing with time and frequency during operation; the temperature convergence entropy is an index for measuring the degree of battery heat generation and the concentration of thermal effects.

[0091] In specific implementation, first, the amplitude fluctuation range of the state of charge is extracted by using the state-of-charge change trend data. If the state-of-charge change trend is time-series data, time-domain analysis techniques (such as FFT) are used to extract the main frequency and amplitude of the signal, quantify the energy fluctuation caused by the state-of-charge change during the discharge process of the secondary battery, and improve the reliability of the amplitude calculation through smoothing or denoising processing to exclude the influence of short-term spikes, that is, the state-of-charge amplitude of the secondary battery generating heat under the discharge condition is obtained; second, 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, the frequency-domain characteristics (such as the main frequency, harmonics) of the voltage signal are extracted through Fourier transform (FFT), the voltage fluctuation mode is analyzed, and then combined with the abnormal operation index, the voltage characteristics (such as overshoot, drop point) in a specific period are marked, and the marked voltage characteristics are used as the voltage characteristic data; then, the temperature convergence entropy related to the thermal effect is calculated by using the voltage characteristic data. 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 generating heat under the discharge condition is calculated through the conditional entropy, that is, temperature convergence entropy = entropy value of temperature - conditional entropy, where the absolute value of the difference between the entropy value of temperature and the conditional entropy is taken; finally, an association model is constructed, the state-of-charge amplitude and the temperature convergence entropy are used as input variables, and regression analysis (such as multiple linear regression or neural network) is used to fit the model parameters to predict the thermal equilibrium temperature, and the thermal equilibrium temperature = K1 * state-of-charge amplitude + K2 * temperature convergence entropy + K3, where K1, K2, and K3 are association models determined by fitting through historical experimental data.

[0092] In step 104, the discharge health state visually displayed during the discharge process of the secondary battery is determined according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0093] In some embodiments, the discharge health state visually displayed during the discharge process of the secondary battery determined according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery can be implemented by the following steps:

[0094] Determine the steady-state operation characteristics when the battery is working according to the thermal equilibrium temperature;

[0095] Determine the inflection point voltage of the secondary battery;

[0096] Determine the health index of the secondary battery based on the steady-state operation characteristics and the inflection point voltage;

[0097] Determine the discharge health state visually displayed during the discharge process of the secondary battery according to the health index.

[0098] It should be noted that in this application, the steady-state operation characteristics represent the thermal characteristics of the secondary battery when the temperature and heat flux reach equilibrium after long-term operation, and are used to evaluate the battery thermal management ability; the inflection point voltage represents the point where the voltage curve of the secondary battery changes significantly during the discharge process, usually occurring when the battery is about to reach the discharge cut-off voltage; the inflection point voltage reflects the change in battery performance and indicates 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 state represents the overall operating state of the secondary battery during the discharge process.

[0099] In specific implementation, first, analyze the thermal behavior of the secondary battery under steady state 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 heat diffusion characteristics of the secondary battery after long-term discharge. Based on the thermal equilibrium temperature, the heat flux and heat capacity of the secondary battery under steady state are deduced using a thermodynamic model (such as a one-dimensional heat conduction equation), and then, by comparing with the battery design parameters (such as material characteristics, dimensions, etc.), the heat diffusion speed and heat uniformity of the secondary battery are evaluated, and the heat diffusion speed and heat uniformity of the secondary battery are used as the steady-state operation characteristics during battery operation; second, the inflection point of the voltage curve can be found by analyzing the relationship between the battery voltage and the discharge capacity using the second derivative method. The inflection point usually corresponds to a significant change in battery capacity attenuation or the moment when the internal impedance of the battery increases, and the voltage value corresponding to the inflection point of the voltage curve is used as the inflection point voltage; then, combined with 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 model parameters determined by fitting historical data, the inflection point voltage, and a reference voltage value. Among them, the reference voltage value can be determined through historical voltage data, which will not be elaborated here; furthermore, the discharge health state visually displayed during the discharge process of the secondary battery can be determined according to the health index in the following way, that is: by comparing the health index with a preset health state standard, the discharge health state visually displayed during the discharge process of the secondary battery is determined. Among them, the discharge health state standards include: high health index (health index > 0.8): the battery is in good health and is suitable for continued use; medium health index (0.5 < health index ≤ 0.8): the battery shows 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.

[0100] In addition, on the other hand of the present application, in some embodiments, the present application provides a visual detection system for battery state, with reference to Figure 4 , this figure is a schematic structural diagram of a visual detection system for battery state shown in some embodiments of the present application. The visual detection system for battery state includes: a monitoring module 201, a processing module 202, and an execution module 203, which are described as follows:

[0101] Monitoring module 201, in the present application, the monitoring module 201 is mainly used for visually monitoring the state of charge of a secondary battery, 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 under low-voltage and over-voltage states, and collecting the battery temperature information at each discharge voltage inflection point within one discharge cycle of the secondary battery;

[0102] Processing module 202, in the present application, the processing module 202 is mainly used to determine the capacity loss characteristics when the secondary battery performs state detection 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;

[0103] The processing module 202 is further used to determine the charge change trend of the secondary battery when operating under a discharge condition based on the abnormal operation index and the state of charge value of the secondary battery under the discharge condition, and determine the thermal equilibrium temperature for heat detection of the secondary battery under the discharge condition through the charge change trend and the voltage characteristic data of the secondary battery;

[0104] Execution module 203, in the present application, the execution module 203 is mainly used to determine the visually displayed discharge health state of the secondary battery during the discharge process based on the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

[0105] The above text details the examples of the visual detection method, system, device, and medium for battery state provided in the embodiments of the present application. It can be understood that, in order to implement the above functions, the corresponding device includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraint conditions of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0106] In some embodiments, the present application further provides a computer device, which includes 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 above-mentioned visual detection method for battery state.

[0107] In some embodiments, referring to Figure 5 , the dashed lines in this figure indicate that the unit or module is optional. This figure is a schematic structural diagram of a computer device for implementing the visual detection method for battery state according to an embodiment of the present application. The above-mentioned visual detection method for battery state can be implemented by Figure 5 the computer device shown. 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.

[0108] The processor 301 can be a general-purpose processor or a special-purpose processor. For example, the processor 301 can be a central processing unit (CPU). The CPU can be used to control the computer device, execute software programs, and process data of software programs. The computer device can also include a communication unit 305 for realizing signal input (reception) and output (transmission).

[0109] For example, the computer device can be a chip, and the communication unit 305 can be the input and / or output circuit of the chip, or the communication unit 305 can be the communication interface of the chip. The chip can be a component of a terminal device, a network device, or other devices.

[0110] Again, for example, the computer device can be a terminal device or a server, and the communication unit 305 can be the transceiver of the terminal device or the server, or the communication unit 305 can be the transceiver circuit of the terminal device or the server.

[0111] The computer device may include one or more memories 302, on which there is a program 304. The program 304 can be run by the processor 301 to generate instructions 303, so that the processor 301 executes the method described in the above method embodiments 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. 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.

[0112] The processor 301 and the memory 302 can be set separately or integrated together. For example, they can be integrated on the system-on-chip of a terminal device.

[0113] It should be understood that each step of the above method embodiments can be completed by a logic circuit in the form of hardware or instructions in the form of software 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. For example, discrete gates, transistor logic devices, or discrete hardware components.

[0114] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take 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 code.

[0115] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or code are stored. When the instructions or code run on a computer, the computer is caused to implement the above-mentioned visual detection method of the battery state.

[0116] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0117] 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 equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A visual detection method for battery status, characterized in that, The steps include the following: Visually monitor the state of charge of the secondary battery, 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 over-voltage states, and collect the battery temperature information at each discharge voltage inflection point within one discharge cycle of the secondary battery; Determine the capacity loss characteristics of the secondary battery when performing state detection 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 in combination with the average battery temperature in the battery temperature information; Determine the charge change trend of the secondary battery during discharge operation according to the abnormal operation index and the state of charge value of the secondary battery under discharge conditions, and determine the thermal equilibrium temperature for heat generation detection of the secondary battery under discharge conditions through the charge change trend and the voltage characteristic data of the secondary battery; Determine the discharge health state visually displayed by the secondary battery during discharge according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery.

2. The method according to claim 1, wherein Determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss characteristics in combination with the average battery temperature in the battery temperature information specifically includes: Determine the battery temperature of the secondary battery within one discharge cycle according to the battery temperature information; Determine the average battery temperature at each discharge voltage inflection point through the battery temperature within one cycle; Determine the capacity attenuation deviation of the secondary battery in the current working state according to the capacity loss characteristics; Determine the abnormal operation index of the secondary battery in the current working state according to the average battery temperature and the capacity attenuation deviation.

3. The method according to claim 1, wherein Determining the charge change trend of the secondary battery during discharge operation according to the abnormal operation index and the state of charge value of the secondary battery under discharge conditions specifically includes: Determine the operating voltage information of the secondary battery during discharge operation according to the abnormal operation index; Determine the state of charge value of the secondary battery under discharge conditions; Determine the charge fluctuation deviation of the secondary battery during discharge operation according to the state of charge value; Determine the charge change trend of the secondary battery during discharge operation through the operating voltage information and the charge fluctuation deviation.

4. The method according to claim 1, characterized in that Determining the thermal equilibrium temperature for heat generation detection of the secondary battery under discharge conditions through the charge change trend and the voltage characteristic data of the secondary battery specifically includes: Determine the state of charge amplitude for heat generation of the secondary battery under discharge conditions according to the charge change trend; Collect the voltage characteristic data of the secondary battery; Determine the temperature convergence entropy for heat generation of the secondary battery under discharge conditions according to the voltage characteristic data; Determine the thermal equilibrium temperature for heat generation detection of the secondary battery under discharge conditions through the state of charge amplitude and the temperature convergence entropy.

5. The method according to claim 1, wherein Determining the discharge health state visually displayed by the secondary battery during discharge according to the thermal equilibrium temperature and the inflection point voltage of the secondary battery specifically includes: Determine the steady-state operation characteristics when the battery is working according to the thermal equilibrium temperature; Determine the inflection point voltage of the secondary battery; Determine the health index of the secondary battery according to the steady-state operation characteristics and the inflection point voltage. Determine the discharge health state visually displayed during the discharge process of the secondary battery according to the health index.

6. The method according to claim 1, wherein 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 over-voltage states, specifically including: Extract the battery discharge time of the secondary battery from the monitoring results after detecting the state of charge of the secondary battery; Determine the low-voltage electric field characteristics of the secondary battery in the low-voltage state; Determine the over-voltage electric field characteristics of the secondary battery in the over-voltage state; Determine the electric field characteristics of the secondary battery in the low-voltage and over-voltage states through the low-voltage electric field characteristics and the over-voltage electric field characteristics; Determine multiple discharge voltage inflection points of the secondary battery in the current working state according to the battery discharge time and the electric field characteristics; 7. The method according to claim 1, wherein Use a temperature sensor to collect the battery temperature information at each discharge voltage inflection point during a discharge cycle of the secondary battery.

8. A visual detection system for battery status, characterized in that Include: A monitoring module for visually monitoring the state of charge of the secondary battery, 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 over-voltage states, and collecting the battery temperature information at each discharge voltage inflection point during a discharge cycle of the secondary battery; A processing module for determining the capacity loss characteristics when the secondary battery performs state detection at each discharge voltage inflection point, and determining the abnormal operation index of the secondary battery in the current working state based on the capacity loss characteristics and the average battery temperature in the battery temperature information; The processing module is further configured to determine the charge change trend of the secondary battery during the discharge operation according to the abnormal operation index and the state of charge value of the secondary battery during the discharge operation, and determine the thermal equilibrium temperature of the secondary battery during the heat generation detection during the discharge operation through the charge change trend and the voltage characteristic data of the secondary battery; An execution module for determining the discharge health state visually displayed during the discharge process of the secondary battery 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 includes 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 state according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Instructions or codes are stored in the computer-readable storage medium, and when the instructions or codes run on a computer, the computer is caused to execute the visual detection method of the battery state according to any one of claims 1 to 7.

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