A lithium battery overheat protection system and method

Abstract

This invention discloses a lithium battery overheat protection system and method. By loading the acquired lithium battery image into an image processing module, thermal imaging of the battery is processed to analyze and extract the location features of the high-temperature region. The changes in the area of ​​the high-temperature region are calculated to determine the battery's abnormal condition. Based on the determined battery state, the system enters a thermal runaway alarm detection module. If the size and rate of change of the high-temperature region on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm is triggered, and the battery abnormality is displayed. The high-temperature location features of the lithium battery determine its state. After identifying overcharging, external short circuit, and internal separator thermal puncture, the system detects the rate of change of the high-temperature region and triggers a thermal runaway alarm. This system achieves high accuracy in detecting lithium battery thermal runaway, enabling real-time monitoring and thermal runaway alarms, thus improving the accuracy of thermal runaway detection and overheat protection.

Description

Technical Field

[0001] This invention belongs to the field of battery management technology, and particularly relates to a lithium battery overheat protection system and method. Background Technology

[0002] As the cost of lithium batteries decreases and the demand for longer driving range in electric bicycles and tricycles increases, lead-acid batteries are gradually being replaced by lithium batteries in these vehicles. Lithium batteries have a high energy density. However, during the development of lithium-ion batteries, overcharging, over-discharging, and other issues can cause them to deviate from their inherent electrical characteristics, leading to battery abuse. When the lithium battery becomes too hot due to external heating or internal electrochemical reactions, it can cause thermal abuse. Continuous exothermic reactions occur inside the lithium battery, generating considerable heat and creating a cycle from exothermic reactions to a rise in battery temperature, ultimately leading to thermal runaway. Electric bicycles and tricycles frequently experience serious safety accidents due to battery spontaneous combustion. Therefore, thermal management of lithium batteries in electric bicycles and tricycles is equally important. However, most lithium battery monitoring systems mainly rely on battery internal resistance, temperature, and voltage data to dynamically judge the state of lithium batteries according to manually set thresholds. This means that alarms can only be triggered after a lithium battery failure occurs, rather than being able to proactively detect and warn in advance. It is evident that traditional lithium battery management systems rely on one or more thresholds to judge alarms, resulting in low accuracy in lithium battery detection and thus reducing the safety of lithium battery use. Summary of the Invention

[0003] In view of this, the present invention provides a lithium battery overheat protection system and method that can detect battery performance, has high accuracy in detecting lithium battery thermal runaway state, and provides real-time monitoring and thermal runaway alarm for the battery, in order to solve the above-mentioned technical problems. Specifically, the following technical solutions are adopted to achieve this.

[0004] In a first aspect, the present invention provides a lithium battery overheat protection system, comprising:

[0005] The image acquisition module is used to load the acquired lithium battery images into the image processing module. The lithium battery imaging includes image grayscale conversion, image erosion and dilation.

[0006] The image processing module is used to process images of battery thermal imaging, and to analyze and extract the location features of high-temperature areas of the battery.

[0007] The battery status detection module is used to calculate the battery abnormality by analyzing the changes in the area of ​​high-temperature regions. First, it determines whether a high-temperature region appears in the image. If a high-temperature region appears on the battery surface and is located at the battery electrode, the battery is determined to be in an external short-circuit state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area does not exceed a preset pixel value, the battery is determined to be in an internal separator thermal puncture state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area exceeds a preset pixel value, the battery is determined to be in an overcharge state.

[0008] The thermal runaway alarm module is used to determine the state of the battery and then enter the thermal runaway alarm detection module. If the size and rate of change of the high-temperature area on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm will be triggered and the abnormal battery condition will be displayed.

[0009] As a further preferred embodiment of the above technical solution, abnormal battery conditions are obtained by calculating the area change of the high-temperature region of the battery, including:

[0010] The multi-scale, multi-dimensional, and multi-physics algorithm (MSMD) is used to establish three independent solution domains for the lithium battery model: the particle domain, the electrode domain, and the battery cell domain. Each domain has its own independent coordinate system for calculating the solution variables. This method, which features short computation time, incorporates the NTGK model of the MSMD algorithm with a thermal abuse model. The thermal conductivity differential equation of the battery is then given by ρc. p = Where ρ represents the battery density, K represents the battery thermal conductivity, T represents the temperature, and Q represents the battery temperature. t c represents the heat source in the electrochemical student thermal model. p The expression for the heat source, representing the specific heat capacity of air, is Q. t =Q r +Q s +Q j +Q p Q r The expression for the heat generated by the electrochemical reaction of the battery is as follows: V represents the battery voltage, U represents the intercept obtained from the fitted voltage-current density curve, and J represents the battery voltage. r The expression for the volume current transport rate generated by an electrochemical reaction is: Y represents the reciprocal of the slope obtained from fitting the voltage-current density curve, H n Indicates the battery's rated capacity, H r The U and Y parameters are obtained during battery charging and discharging, and Vo represents the volume of a single active area of ​​the battery.

[0011] The expression for current density in area form is J = Y(VP -V N -U), where J represents the battery area current transfer rate, V P V represents the positive electrode potential. N Representing the negative electrode potential, both Y and U are related to the depth of discharge and need to be inversely synthesized as functions of the depth of discharge. The relationship between the depth of discharge and the equation is: Y and U are functions of depth of discharge (DOD), and their corresponding expressions are: Let U0 and Y0 be the values ​​inside the curly braces in the above equation, i.e., U0 is... Y0 is U0 and Y0 are both values ​​at 25℃, and T represents the Kelvin temperature of the environment. r For 25℃, C1 and C2 represent constants that determine the temperature dependence of U and Y, i.e., temperature correction coefficients;

[0012] Q j The expression for the Joule heat during battery charging and discharging is Q. j =I 2 R j Q p This refers to the polarization heat of a battery. When current flows through a battery, it causes the potential to deviate from the equilibrium potential, generating polarization resistance. The heat generated by this polarization resistance is the polarization heat. s This refers to the heat of side reactions in a battery, including the decomposition of the electrolyte, the denaturation of the positive and negative electrodes, and the formation and decomposition of the SEI film.

[0013] As a further preferred embodiment of the above technical solution, the decomposition reaction of the SEI film occurs at the electrode, and the reaction temperature is in the range of 90–120°C. The corresponding equation is: S SEI =H SEI W c R SEI and Among them, H SEI W represents the amount of heat released per unit of reaction. c R represents the carbon content. SEI A represents the reaction rate. SEI E represents the frequency factor of the reaction. a，SEI The value represents the activation energy of the reaction, R represents the universal gas constant, and m represents the activation energy of the reaction. SEI C represents the reaction order. SEI This indicates the proportion of unstable lithium in the SEI.

[0014] As a further preferred embodiment of the above technical solution, image processing is performed on the battery thermal imaging to analyze and extract the location features of the high-temperature region of the battery, including:

[0015] Different temperatures in battery thermal imaging correspond to different colors. The thermal images of batteries under external short circuit, internal separator thermal puncture, and overcharge are converted to grayscale. The grayscale level G of the image has a value range of 0≤G≤255, and different grayscale levels correspond to different colors in the thermal image.

[0016] As a further optimization of the above technical solution, the area change of the high-temperature region on the surface during the surface acoustic texture process was collected under three conditions: battery overcharging, external short circuit, and internal diaphragm thermal puncture. Gaussian approximation model, polynomial model, and sine model were used to fit the area change. The expression of the Gaussian approximation model is as follows: Where the parameter to be estimated a1 represents the peak value of the Gaussian curve, b1 represents the coordinate position corresponding to the peak value, and c1 represents the standard deviation;

[0017] The expression for the polynomial fitting model is y = P0x. n +P1x n-1 +P2x n-2 +P3x n-3 +...+P n Among them, P0, P1...P n Let represent the polynomial coefficients. The expression for sine fitting is y′=a1*sinb1x+c1, where a1, b1, and c1 represent the sine coefficients. The expression for R, which represents the square of the coefficients separating the measured and inferred data, is as follows: The closer the R value is to 1, the more successful the data fit.

[0018] SSR represents the sum of squares of the differences between the predicted data and the mean of the original data. The expression for SSR is: Where w i Represents the coefficient. This represents the predicted data. SST represents the mean of the original data; the expression for SST, which represents the sum of squares of the differences between the original data and the mean, is: Among them, w i Represents the coefficient, y i Represents the original data. The mean of the original data is represented by SSE; SSE represents the sum of squares of the errors between corresponding points in the fitted data and the original data. The closer the sum and variance are to 0, the more successful the data fit. The expression for SSE is: Where w i Represents the coefficient, y i Represents the original data. The expression for the predicted data, denoted as RMSE, is as follows: The smaller the root mean square error value, the more successful the data fitting.

[0019] As a further preferred embodiment of the above technical solution, the thermal runaway alarm module includes a battery temperature model construction unit, which establishes a battery temperature change model and uses parameter α to represent the natural cooling state of the battery temperature, i.e., the expression for the natural temperature change per minute is ΔT. n =α(T0-T c ), where T0 represents the ambient temperature, T c This represents the battery temperature; the temperature change per minute due to battery self-heating is ΔT. c =βL, where β represents the parameter coefficient and L represents the battery operating current, yielding the temperature change curve T. c =∫(α(T0-T) c )+βL)dt;

[0020] The expression for the energy required for battery heating is determined by combining the established temperature curve model with the external heating module and the specific heat capacity formula: Q = k0ΔT.

[0021] Combining energy conversion efficiency and heating power, the corresponding expression for the battery thermal energy increment is Q′=ηPt. The expression for the temperature change caused by external heating is ΔT=kPt, where k represents a parameter obtained by combining battery mass, specific heat capacity, and energy conversion efficiency, t represents heating time, P represents heating power, Q represents energy consumption, and ΔT represents the temperature change caused by heating. Finally, the expression for the battery temperature curve model is T′. c =∫(α(T0-T) c )+βL+kP)dt.

[0022] As a further preferred embodiment of the above technical solution, the thermal runaway alarm module also includes a battery power estimation unit. The battery state of charge (SOC) is used to characterize the remaining usable capacity of the battery, i.e., its capacity under a fixed discharge current. The expression for the ratio of the current remaining dischargeable capacity to the total rechargeable capacity of the battery is as follows: Where Q1 represents the remaining battery charge at the time of calculation, and Q0 represents the total battery capacity;

[0023] The SOC is estimated using the ampere-hour integration method. The initial SOC of the battery is preset to SOC0, then the current SOC1 is... Where c t η represents the rated capacity of the battery, η represents the influencing factor related to battery temperature and discharge rate, and I represents the charging and discharging current of the battery.

[0024] As a further preferred embodiment of the above technical solution, the acquired lithium battery image is loaded into the image processing module. The lithium battery imaging includes image grayscale conversion, image erosion and dilation, including:

[0025] The R, G, and B components of each pixel in the color image are statistically analyzed, and the three components with the largest brightness in two categories are taken as the gray value of the image. The brightness values ​​of the three components are averaged, and the average value is taken as the gray value of the image.

[0026] Let A be the original image, a be an element in image A, B be the structuring element, and b be the origin of the structuring element. Then the expressions for image erosion and dilation are respectively... Expansion and The result of A being translated by b is represented as A b ={a+b|a∈A}.

[0027] As a further optimization of the above technical solution, establishing a battery thermal model requires thermal equilibrium inside and outside the battery. Where ρ represents the battery density, C p Q represents the average thermal capacity, T represents the battery temperature, and Q represents the average thermal capacity. AH Q represents the heat accumulation per unit volume. gen Q represents the heat generated during battery operation. dis This indicates heat loss;

[0028] If the battery temperature is preset to be constant, then the expression for the heat generation rate is: Where i represents the current per unit volume, iV represents the electrical power, and U j，avg This represents the open-circuit potential of reaction j under average composition.

[0029] Secondly, the present invention also provides a method for overheat protection of a lithium battery, comprising the following steps:

[0030] The acquired lithium battery images are loaded into the image processing module, where lithium battery imaging includes image grayscale conversion, image erosion and dilation.

[0031] Image processing is performed on battery thermal imaging to analyze and extract the location features of high-temperature areas in the battery;

[0032] The abnormal battery conditions are determined by calculating the changes in the area of ​​the high-temperature region. First, it is determined whether a high-temperature region appears in the image. If a high-temperature region appears on the battery surface and is located at the battery electrode, the battery is determined to be in an external short circuit state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area does not exceed a preset pixel point, the battery is determined to be in an internal separator thermal puncture state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area exceeds a preset pixel point, the battery is determined to be in an overcharge state.

[0033] After determining the battery's current state, the system enters the thermal runaway alarm detection module. If the size and rate of change of the high-temperature area on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm will be triggered and the abnormal battery condition will be displayed.

[0034] This invention provides a lithium battery overheat protection system and method. By loading the acquired lithium battery image into an image processing module, thermal imaging of the battery is processed to analyze and extract the location features of high-temperature regions. The changes in the area of ​​these high-temperature regions are calculated to determine battery anomalies. Based on the determined battery state, the system proceeds to a thermal runaway alarm detection module. If the size and rate of change of the high-temperature region on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm is triggered, and the battery anomaly is displayed. The system determines the lithium battery's state by analyzing its high-temperature location features, identifying overcharging, external short circuits, and internal separator thermal puncture. It then detects the rate of change of the high-temperature region area and triggers a thermal runaway alarm. This system achieves high accuracy in detecting lithium battery thermal runaway, enabling real-time monitoring and alarm functions. It improves the accuracy of thermal imaging detection for thermal runaway, effectively protecting lithium batteries from overheating. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a structural block diagram of the lithium battery overheat protection system provided by the present invention;

[0037] Figure 2 The flowchart shows the lithium battery overheat protection method provided by the present invention. Detailed Implementation

[0038] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0039] See Figure 1 This invention provides a lithium battery overheat protection system, comprising:

[0040] The image acquisition module is used to load the acquired lithium battery images into the image processing module. The lithium battery imaging includes image grayscale conversion, image erosion and dilation.

[0041] The image processing module is used to process images of battery thermal imaging, and to analyze and extract the location features of high-temperature areas of the battery.

[0042] The battery status detection module is used to calculate the battery abnormality by analyzing the changes in the area of ​​high-temperature regions. First, it determines whether a high-temperature region appears in the image. If a high-temperature region appears on the battery surface and is located at the battery electrode, the battery is determined to be in an external short-circuit state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area does not exceed a preset pixel value, the battery is determined to be in an internal separator thermal puncture state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area exceeds a preset pixel value, the battery is determined to be in an overcharge state.

[0043] The thermal runaway alarm module is used to determine the state of the battery and then enter the thermal runaway alarm detection module. If the size and rate of change of the high-temperature area on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm will be triggered and the abnormal battery condition will be displayed.

[0044] In this embodiment, the abnormal battery conditions are obtained by calculating the area change of the high-temperature region of the battery. This includes: using the multi-scale multi-dimensional multi-physics algorithm (MSMD) to establish three independent solution domains for the lithium battery model: the particle domain, the electrode domain, and the battery cell domain. Each domain has an independent coordinate system for calculating the solution variables within that domain. The NTGK model of the MSMD algorithm, which has a short computation time, is integrated with the thermal abuse model. The thermal conductivity differential equation of the battery is then ρc. p = Where ρ represents the battery density, K represents the battery thermal conductivity, T represents the temperature, and Q represents the battery temperature. t c represents the heat source in the electrochemical student thermal model. p The expression for the heat source, representing the specific heat capacity of air, is Q. t =Q r +Q s +Q j +Q p Q r The expression for the heat generated by the electrochemical reaction of the battery is as follows: V represents the battery voltage, U represents the intercept obtained from the fitted voltage-current density curve, and J represents the battery voltage. r The expression for the volume current transport rate generated by an electrochemical reaction is: Y represents the reciprocal of the slope obtained from fitting the voltage-current density curve, H nIndicates the battery's rated capacity, H r The battery capacity, represented by parameters U and Y obtained during charging and discharging, is given by J = Y(Vo). Vo represents the volume of a single active region within the battery. The current density, expressed as an area, is given by J = Y(Vo). P -V N -U), where J represents the battery area current transfer rate, V P V represents the positive electrode potential. N Representing the negative electrode potential, both Y and U are related to the depth of discharge and need to be inversely synthesized as functions of the depth of discharge. The relationship between the depth of discharge and the equation is: Y and U are functions of depth of discharge (DOD), and their corresponding expressions are: Let U0 and Y0 be the values ​​inside the curly braces in the above equation, i.e., U0 is... Y0 is U0 and Y0 are both values ​​at 25℃, and T represents the Kelvin temperature of the environment. r For 25℃, C1 and C2 represent constants that determine the temperature dependence of U and Y, i.e., temperature correction coefficients; Q j The expression for the Joule heat during battery charging and discharging is Q. j =I 2 R j Q p This refers to the polarization heat of a battery. When current flows through a battery, it causes the potential to deviate from the equilibrium potential, generating polarization resistance. The heat generated by this polarization resistance is the polarization heat. s This refers to the heat of side reactions in a battery, including the decomposition of the electrolyte, the denaturation of the positive and negative electrodes, and the formation and decomposition of the SEI film.

[0045] It should be noted that the decomposition reaction of the SEI film occurs at the electrode, and the reaction temperature is in the range of 90–120℃. The corresponding equation is: S SEI =H SEI W c R SEI and Among them, H SEI W represents the amount of heat released per unit of reaction. c R represents the carbon content. SEI A represents the reaction rate. SEI E represents the frequency factor of the reaction. a，SEI The value represents the activation energy of the reaction, R represents the universal gas constant, and m represents the activation energy of the reaction. SEI C represents the reaction order. SEIThis indicates the proportion of unstable lithium in the SEI. During the overheating reaction stage of the battery, the electrode temperature is relatively high, with the positive electrode temperature being higher than the negative electrode temperature, and the temperature gradually decreasing from top to bottom. This may be due to the high current density at the electrode tabs, resulting in higher heat generation and thus higher temperatures in the surrounding area. Furthermore, the positive electrode material, nickel-cobalt-manganese, has poorer stability compared to the negative electrode material.

[0046] It should be understood that the grayscale distribution of an infrared image of a lithium battery actually corresponds to the temperature distribution on the battery surface. During the heating process, the surface temperature of the battery gradually increases, and the energy radiation generated by this temperature rise is captured by infrared thermal imaging. Through pseudo-color transformation, the temperature is converted into a color distribution on the battery surface. After grayscale conversion, the battery thermal image will display different grayscale distributions, separating the grayscale representing the background from the grayscale representing the target high-temperature area, thus determining the location of the high-temperature area on the battery surface. An external short circuit is a rapid discharge process. When an external conductor short-circuits, causing direct contact between the positive and negative electrodes of the lithium battery, an external short circuit is formed. When an external short circuit occurs, the battery generates a large current, and the internal electrolyte undergoes a series of chemical reactions. The generated gas causes the battery casing to expand. Overcharging, external short circuits, and thermal puncture of the internal separator can all trigger thermal runaway to varying degrees. However, the location of the high temperature varies depending on the factors, and the location of the temperature rise has a significant impact on the battery's heat dissipation. High accuracy in detecting the thermal runaway state of lithium batteries enables real-time monitoring and thermal runaway alarms. This improves the accuracy of lithium battery thermal imaging in detecting thermal runaway, thereby effectively protecting lithium batteries from overheating.

[0047] Optionally, image processing is performed on the battery thermal imaging to analyze and extract the location features of the high-temperature region of the battery, including:

[0048] Different temperatures in battery thermal imaging correspond to different colors. The thermal images of batteries under external short circuit, internal separator thermal puncture, and overcharge are converted to grayscale. The grayscale level G of the image has a value range of 0≤G≤255, and different grayscale levels correspond to different colors in the thermal image.

[0049] In this embodiment, the area change of the high-temperature region on the surface during the surface acoustic texture process is collected under three conditions: battery overcharging, external short circuit, and internal separator thermal puncture. Gaussian approximation model, polynomial model, and sine model are used to fit the area change. The expression of the Gaussian approximation model is as follows: Where the parameters to be estimated are a1 representing the peak value of the Gaussian curve, b1 representing the coordinate position corresponding to the peak value, and c1 representing the standard deviation; the expression for the polynomial fitting model is y = P0x n +P1x n-1 +P2x n-2 +P3xn-3 +...+P n Among them, P0, P1...P n Let represent the polynomial coefficients. The expression for sine fitting is y′=a1*sinb1x+c1, where a1, b1, and c1 represent the sine coefficients. The expression for R, which represents the square of the coefficients separating the measured and inferred data, is as follows: The closer the R-value is to 1, the more successful the data fit; SSR represents the sum of squares of the differences between the mean of the predicted data and the original data, and the expression for SSR is: Where w i Represents the coefficient. This represents the predicted data. SST represents the mean of the original data; the expression for SST, which represents the sum of squares of the differences between the original data and the mean, is: Among them, w i Represents the coefficient, y i Represents the original data. The mean of the original data is represented by SSE; SSE represents the sum of squares of the errors between corresponding points in the fitted data and the original data. The closer the sum and variance are to 0, the more successful the data fit. The expression for SSE is: Where w i Represents the coefficient, y i Represents the original data. The expression for the predicted data, denoted as RMSE, is as follows: The smaller the root mean square error value, the more successful the data fitting.

[0050] It should be noted that the thermal runaway alarm module includes a battery temperature model construction unit, which establishes a battery temperature change model and uses the parameter α to represent the natural cooling state of the battery temperature, i.e., the expression for the natural temperature change per minute is ΔT. n =α(T0-T c ), where T0 represents the ambient temperature, T c This represents the battery temperature; the temperature change per minute due to battery self-heating is ΔT. c =βL, where β represents the parameter coefficient and L represents the battery operating current, yielding the temperature change curve T. c =∫(α(T0-T) cThe expression for the energy required for battery temperature rise, determined by the established temperature curve model and the external heating module based on the specific heat capacity formula, is Q = k0ΔT. Combining energy conversion efficiency and heating power, the corresponding expression for battery thermal energy increment is Q′ = ηPt. The expression for the temperature change caused by external heating is ΔT = kPt, where k represents parameters obtained by combining battery mass, specific heat capacity, and energy conversion efficiency, t represents heating time, P represents heating power, Q represents energy consumption, and ΔT represents the temperature change caused by heating. Finally, the expression for the battery temperature curve model is T′. c =∫(α(T0-T) c This improves the accuracy of lithium battery overheat detection by )+βL+kP)dt.

[0051] Optionally, the thermal runaway alarm module also includes a battery capacity estimation unit. The battery state of charge (SOC) characterizes the remaining usable capacity of the battery, i.e., its capacity under a fixed discharge current. The expression for the ratio of the current remaining dischargeable capacity to the total rechargeable capacity is as follows: Where Q1 represents the remaining battery charge at the time of calculation, and Q0 represents the total battery capacity;

[0052] The SOC is estimated using the ampere-hour integration method. The initial SOC of the battery is preset to SOC0, then the current SOC1 is... Where c t η represents the rated capacity of the battery, η represents the influencing factor related to battery temperature and discharge rate, and I represents the charging and discharging current of the battery.

[0053] In this embodiment, the acquired lithium battery image is loaded into the image processing module. The lithium battery imaging includes image grayscale conversion, image erosion, and dilation. This includes: statistically analyzing the R, G, and B components of each pixel in the color image, taking the three components with the highest brightness in each of the two categories as the image's grayscale value, averaging the brightness values ​​of the three components, and using the average value as the image's grayscale value. Given that A is the original image, a is an element in image A, B is a structuring element, and b is the origin of the structuring element, the expressions for image erosion and dilation are as follows: Expansion and The result of A being translated by b is represented as A b ={a+b|a∈A}.

[0054] It should be noted that establishing a battery thermal model requires thermal equilibrium inside and outside the battery. Where ρ represents the battery density, C p Q represents the average thermal capacity, T represents the battery temperature, and Q represents the average thermal capacity. AH Q represents the heat accumulation per unit volume. genQ represents the heat generated during battery operation. dis This represents heat loss; if the battery temperature is preset to be constant, then the expression for the heat generation rate is: Where i represents the current per unit volume, iV represents the electrical power, and U j，avg This represents the open-circuit potential of reaction j under average composition, which improves the system's operational stability.

[0055] See Figure 2 The present invention also provides a method for overheat protection of lithium batteries, comprising the following steps:

[0056] S1: The acquired lithium battery images are loaded into the image processing module, where lithium battery imaging includes image grayscale conversion, image erosion and dilation;

[0057] S2: Perform image processing on battery thermal imaging to analyze and extract the location features of high-temperature areas in the battery;

[0058] S3: Calculate the battery abnormality by analyzing the changes in the area of ​​the high-temperature region. First, determine if a high-temperature region appears in the image. If a high-temperature region appears on the battery surface and is located at the battery electrode, the battery is determined to be in an external short-circuit state. If a high-temperature region appears on the battery surface, is located at the battery casing, and its area does not exceed a preset pixel point, the battery is determined to be in an internal separator thermal puncture state. If a high-temperature region appears on the battery surface, is located at the battery casing, and its area exceeds a preset pixel point, the battery is determined to be in an overcharge state.

[0059] S4: After determining the battery's current state, the system enters the thermal runaway alarm detection module. If the size and rate of change of the high-temperature area on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm will be triggered and the abnormal battery condition will be displayed.

[0060] In this embodiment, if there are obvious local brightness changes in the image, these change features can be used to perform edge detection and segment the image. Since the gray values ​​at the boundaries of adjacent gray-scale regions in the image are discontinuous, differential operators can be used for edge detection. Battery overcharging, external short circuits, and internal separator thermal puncture are also potential issues. Overcharging refers to the charging voltage exceeding the set voltage. An external short circuit occurs when the positive and negative terminals of the battery are in direct contact, causing a short circuit in the battery circuit. Internal separator thermal puncture occurs when the battery is subjected to a sharp object or other external force, causing a sudden short circuit in a certain area of ​​the battery. Overcharging is particularly dangerous due to its rapid temperature rise. Timely intervention in external short circuits can suppress thermal runaway. Internal separator thermal puncture occurs at a relatively uniform temperature rise rate, and intervention within a reasonable timeframe can also effectively suppress thermal runaway. The high accuracy of lithium battery thermal runaway detection enables real-time monitoring and thermal runaway alarms. This improves the accuracy of lithium battery thermal imaging in detecting thermal runaway, thereby effectively protecting lithium batteries from overheating.

[0061] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not as limitations; therefore, other examples of exemplary embodiments may have different values.

[0062] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0063] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A lithium battery overheat protection system, characterized in that, include: The image acquisition module is used to load the acquired lithium battery images into the image processing module. The lithium battery imaging includes image grayscale conversion, image erosion and dilation. The image processing module is used to process images of battery thermal imaging, and to analyze and extract the location features of high-temperature areas of the battery. The battery status detection module is used to calculate the battery abnormality by analyzing the changes in the area of ​​high-temperature regions. First, it determines whether a high-temperature region appears in the image. If a high-temperature region appears on the battery surface and is located at the battery electrode, the battery is determined to be in an external short-circuit state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area does not exceed a preset pixel value, the battery is determined to be in an internal separator thermal puncture state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area exceeds a preset pixel value, the battery is determined to be in an overcharge state. The thermal runaway alarm module is used to determine the state of the battery and then enter the thermal runaway alarm detection module. If the size and rate of change of the high-temperature area on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm will be triggered and the abnormal battery condition will be displayed. Calculations of changes in the area of ​​the high-temperature region of the battery reveal abnormal battery conditions, including: The multi-scale, multi-dimensional, and multi-physics algorithm (MSMD) is used to establish three independent solution domains for the lithium battery model: the particle domain, the electrode domain, and the battery cell domain. Each domain has an independent coordinate system for calculating the solution variables. This method, which features short computation time, incorporates the NTGK model of the MSMD algorithm with a thermal abuse model. The thermal conductivity differential equation of the battery is then: ,in K represents battery density, K represents battery thermal conductivity, and T represents temperature. This represents the heat source in the electrochemical student thermal model. The expression for the specific heat capacity of air and the heat source is: , The expression for the heat generated by the electrochemical reaction of the battery is as follows: V represents the battery voltage, and U represents the intercept obtained from the fitted voltage-current density curve. The expression for the volume current transport rate generated by an electrochemical reaction is: Y represents the reciprocal of the slope obtained from fitting the voltage-current density curve. Indicates the battery's rated capacity. This indicates the battery capacity obtained by acquiring U and Y parameters during battery charging and discharging. This indicates the volume of a single active region in a battery. The expression for current density in area form is: Where J represents the battery area current transfer rate, Indicates the positive electrode potential. Representing the negative electrode potential, both Y and U are related to the depth of discharge and need to be inversely synthesized as functions of the depth of discharge. The relationship between the depth of discharge and the equation is: Y and U are functions of depth of discharge (DOD), and their corresponding expressions are: In the above formula, let the curly braces contain: and ,Right now for , for , and All values ​​are at 25℃, where T represents the Kelvin temperature of the environment. It is 25℃. and This represents a constant that determines the temperature dependence of U and Y, i.e., a temperature correction factor; The expression for Joule heat during battery charging and discharging is: ; This refers to the polarization heat of a battery. When current flows through a battery, it causes the potential to deviate from the equilibrium potential, generating polarization internal resistance. The heat generated by this polarization internal resistance is called polarization heat. This refers to the heat of side reactions in a battery, including the decomposition of the electrolyte, the denaturation of the positive and negative electrodes, and the formation and decomposition of the SEI film.

2. The lithium battery overheat protection system according to claim 1, characterized in that, The decomposition reaction of the SEI film occurs at the electrode, and the reaction temperature is... The range, and the corresponding equation is , and ,in, This represents the amount of heat released per unit of reaction. Indicates the carbon content. Indicates the reaction rate. The frequency factor representing the reaction, R represents the activation energy of the reaction, and R represents the universal gas constant. Indicates the reaction order. This indicates the proportion of unstable lithium in the SEI.

3. The lithium battery overheat protection system according to claim 1, characterized in that, Image processing is performed on battery thermal imaging to analyze and extract the location features of high-temperature regions of the battery, including: Different temperatures in battery thermal imaging correspond to different colors. Thermal images of batteries under conditions of external short circuit, internal separator thermal puncture, and overcharge are converted to grayscale. The range of grayscale level G in the image is as follows: Different gray levels correspond to different colors in thermal imaging.

4. The lithium battery overheat protection system according to claim 3, characterized in that, The surface high-temperature region area change during the surface acoustic texture process was collected under three conditions: battery overcharging, external short circuit, and internal separator thermal puncture. Gaussian approximation model, polynomial model, and sine model were used to fit the area change. The expression for the Gaussian approximation model is as follows: Among them, the parameters to be estimated This represents the peak value of the Gaussian curve. This indicates the coordinate position corresponding to the peak value. Indicates standard deviation; The expression for the polynomial fitting model is: ,in, , ... Representing the polynomial coefficients, the expression for sine fitting is: ,in, , and The expression for R, representing the square of the coefficient separating the measured and inferred data, is as follows: The closer the R value is to 1, the more successful the data fit. SSR represents the sum of squares of the differences between the predicted data and the mean of the original data. The expression for SSR is: ,in Represents the coefficient. This represents the predicted data. SST represents the mean of the original data; the expression for SST, which represents the sum of squares of the differences between the original data and the mean, is: ,in, Represents the coefficient. Represents the original data. The mean of the original data is represented by SSE; SSE represents the sum of squares of the errors between corresponding points in the fitted data and the original data. The closer the sum and variance are to 0, the more successful the data fit. The expression for SSE is: ,in Represents the coefficient. Represents the original data. The expression for the predicted data, denoted as RMSE, is as follows: The smaller the root mean square error value, the more successful the data fitting.

5. The lithium battery overheat protection system according to claim 1, characterized in that, The thermal runaway alarm module includes a battery temperature model building unit, which establishes a battery temperature change model and uses parameters. The expression to represent the natural cooling state of the battery, i.e., the natural temperature change per minute, is as follows: ,in Indicates ambient temperature. This indicates the battery temperature; the temperature change per minute due to the battery's self-heating is... ,in The parameter coefficient is represented by L, which represents the battery operating current, and the temperature change curve is obtained. ; By combining the established temperature curve model with the external heating module, the expression for the energy required for battery heating is determined based on the specific heat capacity formula. ; Combining energy conversion efficiency and heating power, the corresponding expression for the increase in battery thermal energy is: The expression for the temperature change of the battery caused by external heating is: Where k represents a parameter obtained by combining battery mass, specific heat capacity, and energy conversion efficiency, t represents heating time, P represents heating power, and Q represents energy consumption. The expression for the battery temperature curve model is derived from the temperature change caused by heating. .

6. The lithium battery overheat protection system according to claim 5, characterized in that, The thermal runaway alarm module also includes a battery capacity estimation unit. The battery state of charge (SOC) characterizes the remaining usable capacity of the battery, i.e., its capacity under a fixed discharge current. The expression for the ratio of the current remaining dischargeable capacity to the total rechargeable capacity is as follows: ,in This indicates the remaining battery power at the time of calculation. Indicates the total capacity of the battery; The SOC is estimated using the ampere-hour integration method, with the initial SOC value of the battery preset to be [value missing]. Then the current Value ,in Indicates the battery's rated capacity. This represents the influencing factors related to battery temperature and discharge rate, where I represents the battery's charge and discharge current.

7. The lithium battery overheat protection system according to claim 1, characterized in that, The acquired lithium battery images are loaded into the image processing module. The lithium battery imaging process includes image grayscale conversion, image erosion, and dilation, including: The R, G, and B components of each pixel in the color image are statistically analyzed, and the three components with the largest brightness in two categories are taken as the gray value of the image. The brightness values ​​of the three components are averaged, and the average value is taken as the gray value of the image. Let A be the original image, a be an element in image A, B be the structuring element, and b be the origin of the structuring element. Then the expressions for image erosion and dilation are respectively... expansion and The result of A being translated by b is expressed as .

8. The lithium battery overheat protection system according to claim 1, characterized in that, Establishing a battery thermal model requires thermal equilibrium inside and outside the battery. ,in Indicates battery density, The average heat capacity is represented by T, and the battery temperature is represented by T. This represents the heat accumulation per unit volume. This indicates the amount of heat generated during battery operation. This indicates heat loss; If the battery temperature is preset to be constant, then the expression for the heat generation rate is: Where i represents the current per unit volume, Indicates electrical power. This represents the open-circuit potential of reaction j under average composition.

9. A method for overheat protection of a lithium battery according to any one of claims 1-8, characterized in that, Includes the following steps: The acquired lithium battery images are loaded into the image processing module, where lithium battery imaging includes image grayscale conversion, image erosion and dilation. Image processing is performed on battery thermal imaging to analyze and extract the location features of high-temperature areas in the battery; The abnormal battery conditions are determined by calculating the changes in the area of ​​the high-temperature region. First, it is determined whether a high-temperature region appears in the image. If a high-temperature region appears on the battery surface and is located at the battery electrode, the battery is determined to be in an external short circuit state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area does not exceed a preset pixel point, the battery is determined to be in an internal separator thermal puncture state. If a high-temperature region appears on the battery surface, is located on the battery casing, and its area exceeds a preset pixel point, the battery is determined to be in an overcharge state. After determining the battery's current state, the system enters the thermal runaway alarm detection module. If the size and rate of change of the high-temperature area on the battery surface reach the thermal runaway alarm threshold, a thermal runaway alarm will be triggered and the abnormal battery condition will be displayed.

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