CN117452220A - Energy storage battery thermal runaway rapid response system and method - Google Patents
Energy storage battery thermal runaway rapid response system and method Download PDFInfo
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Abstract
The invention discloses a rapid response system and a rapid response method for thermal runaway of an energy storage battery, which relate to the technical field of energy storage battery testing and comprise the following steps: the device comprises a battery compartment, an image processing module, a temperature comparison module and a runaway early warning module. Through the linkage between each module, the comprehensive real-time supervision battery cluster operating condition of full period to carry out real-time processing through Harris angular point algorithm based on grey intensity detection to the image, confirm the angular point and then confirm risk electric core coordinate position, power off immediately to trouble battery package, detect risk electric core and temperature rise around through the temperature sensing detector, compare with the target threshold value, confirm that the risk level adopts corresponding hierarchical early warning mechanism, promote early warning mechanism's timeliness, hierarchical response, the effect is accurate.
Description
Technical Field
The invention relates to the technical field of energy storage battery testing of electrochemical energy storage, in particular to a rapid response system and a rapid response method for thermal runaway of an energy storage battery.
Background
With the application of large-scale energy storage systems, thermal runaway of energy storage batteries is an important safety issue for energy storage systems. Because of the inconsistency of the battery cells, thermal runaway of the local battery cells is unavoidable, the thermal runaway risk can be generated under the accident conditions of overcharging, short circuit and the like of the energy storage lithium ion battery, in the prior art, when the energy storage lithium ion battery happens, whether the thermal runaway risk exists or not is determined by adopting a smoke detector to detect whether gas-liquid escaping substances are sprayed out of a safety valve or not, and then a system reaction is made, the smoke detector can acquire the sprayed gas-liquid escaping substances only after a long time, the response time of a response system is slow, and the position of the battery cells with the thermal runaway cannot be accurately given out.
Therefore, how to overcome the above-mentioned problems is one of the technical problems to be solved in the present stage.
Disclosure of Invention
In view of the above, the present invention provides a system and a method for fast responding to thermal runaway of an energy storage battery, which make a system response to give a judgment by spraying a gas-liquid escaping material at a safety valve at a first time, and accurately give a position of the battery where thermal runaway occurs, so as to solve the problems of low thermal runaway response efficiency of the energy storage battery, etc.
In a first aspect, the present application provides a thermal runaway fast response system for an energy storage battery, comprising: the device comprises a battery compartment, an image acquisition module, an image processing module, a temperature comparison module and a runaway early warning module;
the battery compartment comprises a plurality of battery clusters, the battery clusters comprise a plurality of battery packs, and the battery clusters are arranged in an array by the plurality of battery packs;
the image acquisition module is used for continuously acquiring the gas-liquid escaped object images at the safety valve of the battery cluster in real time;
the image processing module is used for determining a coordinate position of the risk battery cell;
the out-of-control early warning module sends out an instruction for disconnecting the fault battery pack;
the temperature comparison module is used for comparing the sizes of the risk cells and surrounding cells Wen Sheng T with a target threshold T;
the out-of-control early warning module is also used for determining the system risk level according to the magnitude relation between the risk battery cell and surrounding telecom Wen Sheng T and the target threshold T, judging the fault diffusion condition, and determining the next operation of the whole energy storage system according to the judging result.
Optionally, wherein: the image acquisition module comprises an AI camera, wherein the AI camera is fixed at the center position of the top of the battery compartment and is positioned right above the center position of the battery cluster.
Optionally, wherein: the image processing module comprises an image sensor and a computer, wherein the image sensor is electrically connected with the AI camera and the computer and is used for transmitting real-time images acquired by the AI camera to the computer.
Optionally, wherein: the computer uses a Harris angular point algorithm based on gray intensity detection, compares the change degree of pixel gray values in windows before and after sliding by using a fixed window to slide on an image, and determines the gas-liquid overflow coordinate position of the risk cell through the characteristic value.
Optionally, wherein: the temperature comparison module further comprises a temperature sensing detector, wherein the temperature sensing detector is used for detecting the temperature rise of the gas-liquid overflow coordinate position.
In a second aspect, the present application provides a method for thermal runaway fast response of an energy storage battery, comprising:
s1: acquiring a real-time image of a battery cell in a battery compartment;
s2: establishing a battery pack thermal runaway image analysis based on a Harris corner algorithm;
s3: according to the coordinate position determined in the step S2, rapidly powering off a single fault battery pack, and observing the temperature change of the risk battery cell and surrounding battery cells in the next step;
s4: acquiring target positions and surrounding cell temperatures, and comparing the target positions with a target threshold value;
s5: and establishing a thermal runaway grading early warning mechanism of the energy storage battery.
Optionally, wherein: the S1 specifically comprises the following steps: an AI camera is arranged at the center position of the top in the battery compartment, and all the battery cell images in the battery compartment are acquired in real time by using the full time interval and the full space of the AI camera.
Optionally, wherein: the step S2 specifically comprises the following steps:
s21: the coordinates of the target pixel point are (x, y), the moving distance of the fixed window in the x direction is u, the moving distance in the y direction is v, and the gray scale variation in the window is expressed as: e (E) x，y ＝∑ω u，v (I x+u，y+v -I x，y ) 2 Wherein ω is u，v As a Gaussian window function, I x+u，y+v For the gradient of the target pixel point in the target coordinate position, I x，y Gradient of the target pixel point in the initial coordinate position;
s22: smoothing the target image by Gaussian filtering to obtain a new autocorrelation matrix Wherein (1)>For the gradient product of the target pixel in the X direction,/->Is the gradient product of the target pixel point in the Y direction, I x I y The gradient product of the target pixel point in the X direction and the Y direction is obtained;
s23: calculating the response value of the feature point through a corner response function R=detM-k (traceM) and comparing the response value with a set threshold value; if the response value is larger than the threshold value, the corresponding pixel point is marked as a corner point, wherein k is a Harris operator parameter, detM is a determinant of a matrix M, and traceM is a trace of the matrix M;
s24: and setting the local extremum which does not meet the given threshold condition to zero through non-maximum suppression, thereby determining the final characteristics extracted by the Harris corner algorithm.
Optionally, wherein: the step S4 specifically comprises the following steps: the target threshold T comprises two-level thresholds T1 and T2, wherein T1 is 1 ℃/10s, and T2 is 1.5 ℃/10s;
and C, carrying out temperature rise acquisition on the risk battery cells and surrounding battery cells of which the coordinates are determined in the step S2 through the temperature sensing probe, comparing the acquired temperature change value delta T with a set target threshold value T, and judging the range of the target threshold value T where the delta T is located.
Optionally, wherein: the step S5 specifically comprises the following steps:
when delta T is less than T1, starting the fire-fighting equipment of the single fault battery pack in the step S2 for primary risk early warning, and observing the temperature change of the next step;
when T1 is less than delta T and less than T2, stopping all actions of the current battery cluster for secondary risk early warning, starting the liquid cooling equipment and starting the fire fighting equipment;
when DeltaT is more than T2, the whole system is powered down in an emergency mode for three-level risk early warning, and an emergency plan is started.
Compared with the prior art, the energy storage battery thermal runaway rapid response system and the method provided by the invention have the advantages that at least the following beneficial effects are realized:
1. the high-definition camera is used for acquiring the image of the current core in real time, so that the specific condition of the risk battery core can be visualized;
2. and detecting image characteristic points by using a Harris corner detection algorithm to analyze whether gas-liquid escaping substances are sprayed at the safety valve, so that high-precision image processing can be realized, the specific coordinate position of the risk cell can be rapidly positioned, the fault cell pack is immediately powered off, and the first-step rapid response is completed.
3. Through real-time monitoring and real-time image processing, whether gas-liquid overflows are sprayed out of the safety valve or not is accurately judged, and accordingly corresponding response measures are adopted.
4. Aiming at the early warning grades of different levels, the method corresponds to different response strategies, and realizes accurate early warning and accurate prevention and control.
Of course, it is not necessary for any one product to practice the invention to achieve all of the technical effects described above at the same time.
Other features of the present invention and its advantages will become apparent from the following detailed description of exemplary embodiments of the invention, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic diagram illustrating a connection of a module of a thermal runaway rapid response system of an energy storage battery according to an embodiment of the present invention;
fig. 2 is a schematic diagram showing an internal structure of a battery compartment of a rapid thermal runaway response system for an energy storage battery according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of a thermal runaway rapid response method of an energy storage battery according to an embodiment of the invention.
Detailed Description
Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of exemplary embodiments may have different values.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Accordingly, it is intended that the present invention covers the modifications and variations of this invention provided they come within the scope of the appended claims (the claims) and their equivalents. The embodiments provided by the embodiments of the present invention may be combined with each other without contradiction.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Fig. 1 is a schematic connection diagram of a module of an energy storage battery thermal runaway rapid response system according to an embodiment of the present invention, fig. 2 is a schematic internal structure diagram of a battery compartment of the energy storage battery thermal runaway rapid response system according to an embodiment of the present invention, please refer to fig. 1 and fig. 2, and the energy storage battery thermal runaway rapid response system according to an embodiment of the present invention includes: the device comprises a battery compartment 5, an image acquisition module 1, an image processing module 2, a temperature comparison module 3 and a runaway early warning module 4;
the battery compartment 5 comprises a plurality of battery clusters 51, the battery clusters 51 comprise a plurality of battery packs 52, and the battery clusters 51 are arranged in an array by the plurality of battery packs 52;
the image acquisition module 1 is used for continuously acquiring the gas-liquid escaping object images at the safety valve of the battery cluster 51 in real time;
the image processing module 2 is used for determining the coordinate position of the risk cell;
the out-of-control early warning module 4 sends out an instruction for disconnecting the fault battery pack;
the temperature comparison module 3 is used for comparing the sizes of the risk cells and surrounding cells Wen Sheng T with a target threshold T;
the out-of-control early warning module 4 is further configured to determine a risk level according to a magnitude relation between the risk cells and surrounding cells Wen Sheng T and a target threshold T, determine a fault diffusion condition, and determine a next operation on the whole energy storage system according to a determination result.
Specifically, the battery cluster 51 is formed by arranging a plurality of battery packs 52 in an array manner, wherein the array manner can be single-layer single-column arrangement, single-layer multi-column arrangement, multi-layer single-column arrangement, or multi-layer multi-column arrangement, and the arrangement manner of the battery packs 52 in the specific battery cluster 51 can be set according to actual needs, and only single-layer multi-column arrangement is illustrated in the figure; the battery cluster 51 is located at the center position in the battery compartment 5, and only the square compartment body is shown in the figure, the invention is not limited to this, and the specific shape structure of the battery compartment 5 includes, but is not limited to, square, cylindrical, hemispherical, conical, cylindrical+conical, etc.; an image acquisition module 1 is also fixed on one surface of the top of the battery bin 5 facing the battery cluster 51 and is used for acquiring images of the whole appearance of the battery cluster 51, so that the coordinate position of the risk battery cell can be acquired clearly and accurately; the rapid thermal runaway response system of the energy storage battery further comprises a temperature comparison module 3 and a runaway early warning module 4, the image processing module 2 determines specific coordinate positions of risk cells, the runaway early warning module 4 sends out instructions for disconnecting a fault battery pack, the fault battery pack is powered off, the temperature rise delta T of the collected risk cells and surrounding cells is compared with a set target threshold T by combining the temperature comparison module 3, the risk level of the system is determined according to the comparison result, the diffusion condition of the faults is judged, and corresponding early warning measures are adopted for the energy storage system according to the judgment result, so that real-time monitoring and real-time image processing are carried out through linkage among the image acquisition module 1, the image processing module 2, the temperature comparison module 3 and the runaway early warning module 4 in the battery compartment 5, whether gas-liquid overflows are sprayed out at a safety valve or not is accurately judged, and the specific coordinate positions of the risk cells can be timely and effectively acquired, and corresponding response measures are adopted.
In the energy storage battery thermal runaway rapid response system provided by the embodiment of the invention, the image acquisition module 1 comprises the AI camera 11, and the AI camera 11 is fixed at the center position of the top of the battery compartment 5 and is positioned right above the center position of the battery cluster 51. Specifically, the image acquisition module 1 includes the AI camera 11, and AI camera 11 is located the one side towards battery cluster 51 in battery compartment 5 storehouse top to fix at battery compartment 5 top central point put, and AI camera 11 is located battery cluster 51 central point put directly over, so, through setting up AI camera 11 directly over the inside battery cluster 51 central point put of battery compartment 5, can make the concrete condition of risk electric core visual, can gather the high definition image data of battery cluster 51 in real time.
The image processing module 2 comprises an image sensor 21 and a computer 22, wherein the image sensor 21 is electrically connected with the AI camera 11 and the computer 22, and is used for transmitting real-time images acquired by the AI camera 11 to the computer 22. Specifically, the image processing module 2 includes an image sensor 21 and a computer 22, the image sensor 21 is connected with the AI camera 11 and is used for receiving images of the battery cluster 51 collected in real time, the image sensor 21 is also connected with the computer 22 and is used for transmitting the images of the battery cluster 51 collected in real time by the image collecting module 1 to the computer 22, image processing software and standard pictures of the battery cluster 51 in a normal working state without risk are stored in the computer 22, the high-definition pictures of the battery cluster 51 collected in real time are compared with the standard pictures of the battery cluster 51 in the normal working state without risk by the image processing software, whether the battery pack 52 in the battery cluster 51 in the working state has a runaway risk is confirmed, so, by arranging the image sensor 21 and the computer 22, the high-definition images of the battery cluster 51 collected by the image collecting module 1 can be transmitted to the computer 22 in real time, whether thermal runaway occurs is judged by comparing with the standard pictures of the battery cluster 51 in a specific battery pack, and after the battery pack is positioned, the power of the fault battery pack is cut off, so that the first step of quick response is completed.
It should be noted that, in the embodiment of the present invention, the computer 22 is a PC with image processing software installed therein, and will not be described in detail.
In the rapid response system for thermal runaway of the energy storage battery provided by the embodiment of the invention, the computer 22 uses a Harris corner algorithm based on gray intensity detection, and the degree of change of pixel gray values in a window before and after sliding is compared by sliding the fixed window on an image, and the gas-liquid overflow coordinate position of a risk battery cell is determined by the characteristic value. Specifically, the image processing software in the computer 22 uses a Harris angular point algorithm based on gray intensity detection, the software firstly compares a high-definition image of the battery cluster 51 acquired in real time with a standard image of the battery cluster 51 in a normal working state without risk, if the acquired image is not different from the standard image, the next image is continuously compared, if the acquired image is different from the standard image, the pixel gray value of a difference position on the image is calculated through the Harris angular point algorithm, the Harris angular point algorithm slides on the image acquired in real time with the difference through a fixed small window, the change degree of the pixel gray value in the small window before and after sliding is compared, and then the coordinate position of the gas-liquid overflow of the risk battery core is determined through the calculated characteristic value, so that the change degree of the gray value in the high-definition image before and after sliding of the window is compared by using the Harris compared in the computer 22, and the positioning tracking of the risk battery core is realized.
The embodiment of the invention provides a rapid response system for thermal runaway of an energy storage battery, wherein a temperature comparison module 3 further comprises a temperature sensing detector 31, and the temperature sensing detector 31 is used for detecting temperature rise of a coordinate position of gas-liquid overflow. Specifically, the temperature comparison module 3 further includes a temperature sensing detector 31, and a plurality of temperature sensing detectors 31 can be set in the battery compartment 5 according to the specific arrangement of the battery packs 52 in the actual battery cluster 51, after the computer 22 calculates the coordinate position of the gas-liquid overflow of the risk battery core through the Harris corner algorithm, the temperature increasing value of the risk battery core which sprays the corresponding coordinate position of the gas-liquid overflow in a certain time is detected through the temperature sensing detector 31, so that the temperature of the coordinate position of the risk battery core can be detected through the temperature sensing detector 31, the temperature rise and the degree of runaway of the risk battery core can be further determined under the condition that the risk battery core is confirmed to be out of control, and preparation is made for taking corresponding response measures for the next step.
Based on the same inventive concept, the embodiment of the invention further provides a thermal runaway rapid response method of an energy storage battery, please refer to fig. 3, fig. 3 is a flow chart of the thermal runaway rapid response method of the energy storage battery, which includes:
s1: acquiring a real-time image of the battery cell in the battery compartment 5;
s2: establishing a battery pack thermal runaway image analysis based on a Harris corner algorithm;
s3: according to the coordinate position determined in the step S2, rapidly powering off a single fault battery pack, and observing the temperature change of the risk battery cell and surrounding battery cells in the next step;
s4: acquiring target positions and surrounding cell temperatures, and comparing the target positions with a target threshold value;
s5: and establishing a thermal runaway grading early warning mechanism of the energy storage battery.
Specifically, through the arrangement of each module and component in the energy storage battery thermal runaway quick response system, the energy storage battery thermal runaway quick response method can be operated, and comprises the following four steps of S1: the image acquisition module 1 is used for carrying out full-time all-dimensional high-definition image acquisition on the real-time working state of the battery cluster 51 in the battery compartment 5, and S2: the image sensor 21 in the image processing module 2 transmits the real-time high-definition battery cluster 51 image acquired by the AI camera 11 to the computer 22, the image processing software in the computer 22 firstly compares the acquired real-time high-definition battery cluster 51 image with a standard image in a normal working state without risk of the battery cluster 51, if no difference exists, the next high-definition battery cluster 51 image is continuously compared with the standard image, if the difference exists, the image processing software based on the Harris corner algorithm carries out the change analysis of pixel gray values on the high-definition battery cluster 51 image with the difference, the characteristic value is confirmed, and then the coordinate position of a risk cell is determined, and S3: according to the risk battery cell coordinate position confirmed by the image processing module 2 in the step S2, the risk early warning module 4 sends out a command for powering off a fault battery pack on the risk battery cell coordinate position, the fault battery pack is powered off, the temperature change of the risk battery cell and surrounding battery cells in the next step is observed, and the step S4: the temperature sensor in the temperature comparison module 3 is used for collecting the temperatures of the target-position risk battery cell and surrounding battery cells, comparing the collected temperature rise data in a certain time with a target threshold value, judging fault diffusion conditions, and dividing the risk level of the system according to the temperature rise data, and S5: and (3) establishing a thermal runaway grading early warning mechanism of the energy storage battery, and taking corresponding prevention and control measures according to the judging result of the system risk grade in the step (S4), so that the coordinate position of the risk battery cell can be confirmed at the first time through the general cooperation among the steps, then the risk grade is determined according to the comparison of the temperature rise of the target position risk battery cell and the target threshold value, and further the corresponding grading early warning mechanism is adopted, thereby realizing the rapid positioning and rapid response of the uncontrolled battery cell and improving the timeliness of the early warning mechanism.
In the method for rapidly responding to thermal runaway of the energy storage battery provided by the embodiment of the invention, S1 specifically comprises the following steps: an AI camera 11 is arranged at the center position of the top in the battery compartment 5, and all battery cell images in the battery compartment 5 are acquired in real time by using the AI camera 11 in a full-time-interval full-space mode. Specifically, in step S1, the image acquisition module 1 performs full-time full-scale high-definition image acquisition on the real-time working state of the battery cluster 51 in the battery compartment 5, and the image acquisition module 1 includes the AI camera 11, the AI camera 11 is fixed on one surface of the top of the battery compartment 5 facing the battery cluster 51, and the AI camera 11 is located right above the center position of the battery cluster 51, that is, the shooting view angle of the AI camera 11 can fully cover the battery cluster 51 in the battery compartment 5, so that the AI camera 11 can realize full-time full-scale image acquisition on the full-scale high-definition image in the working process of the battery cluster 51.
The step S2 specifically comprises the following steps of:
s21: the coordinates of the target pixel point are (x, y), the moving distance of the fixed window in the x direction is u, the moving distance in the y direction is v, and the gray scale variation in the window is expressed as:
E x，y ＝∑ω u，v (I x+u，y+v -I x，y ) 2 wherein ω is u，v As a Gaussian window function, I x+u，y+v For the gradient of the target pixel point in the target coordinate position, I x，y Gradient of the target pixel point in the initial coordinate position;
s22: smoothing the target image by Gaussian filtering to obtain a new autocorrelation matrix Wherein (1)>For the gradient product of the target pixel in the X direction,/->Is the gradient product of the target pixel point in the Y direction, I x I y The gradient product of the target pixel point in the X direction and the Y direction is obtained;
s23: calculating the response value of the feature point through a corner response function R=detM-k (traceM) and comparing the response value with a set threshold value; if the response value is larger than the threshold value, the corresponding pixel point is marked as a corner point, wherein k is a Harris operator parameter, detM is a determinant of a matrix M, and traceM is a trace of the matrix M;
s24: and setting the local extremum which does not meet the given threshold condition to zero through non-maximum suppression, thereby determining the final characteristics extracted by the Harris corner algorithm.
Specifically, in step S2, a thermal runaway image analysis of the battery pack based on Harris corner algorithm is established, the Harris algorithm detects each frame of image one by one, and finds out the corner point of the target in the image, and the method can be specifically subdivided into 4 steps of S21, S22, S23 and S24, in step S21, the target pixel point of the risk cell is assumed to be (x, y), the small window slides on the target image along any direction, the moving distance in the x direction is assumed to be u, the moving distance in the y direction is assumed to be v, and the gradient I of the (x, y) in the X, Y directions is calculated x ，I y Then the gradient coordinates of each pixel point can be expressed as (I x ，I y ) Calculating the gradient product of the corresponding pixel point through the gradient coordinates, namelyThe amount of gray scale change within the window can be expressed as:
from the taylor formula, f (x+u, y+v) =f (x, y) +uf x (x，y)+vf y (x，y)
The amount of gray scale change within the window can be reduced to:
can obtain matrix
In step S22, the target image is smoothed by Gaussian filtering, and the matrix M is Gaussian weighted to obtain an autocorrelation matrix
In step S23, matrix M 1 Feature decomposition into M 1 ＝A T The form of PA, A is the orthogonal matrix, P is the diagonal matrix, the main diagonal element is the eigenvalue, the above-mentioned simplification is:calculating a characteristic point response function R=detM-k (traceM), wherein k is a Harris operator parameter, detM is a determinant of a matrix M, traceM is a trace of the matrix M, lambda 1 And lambda (lambda) 2 Is the eigenvalue of matrix M, and detM 1 ＝λ 1 *λ 2 ，trace(M 1 )＝λ 1 +λ 2 . Substituting the characteristic value into the Harris response value R of each pixel point can be calculated.
In step S24, a minimum threshold is set, non-maximum suppression is performed in a certain range of the field, a local extremum which does not meet the given threshold condition is set to zero, if the response value R is greater than the threshold, the local maximum point is the corner point in the image, so as to determine the final corner point extracted by the Harris corner point algorithm and determine the coordinate position of the risk cell corresponding to the target pixel, thus, the corner point in the image can be determined by the image processing module 2 based on the Harris corner point algorithm, the pseudo corner point lower than the minimum threshold is set to zero by the non-maximum suppression, the maximum point is reserved as the corner point, and then the coordinate position of the risk cell of the sprayed gas-liquid overflow is determined by the coordinates of the corner point and the offset of the corner point in the x and y directions.
The embodiment of the invention provides a rapid response method for thermal runaway of an energy storage battery, wherein S4 specifically comprises the following steps: the target threshold T comprises two-level thresholds T1 and T2, wherein T1 is 1 ℃/10s, and T2 is 1.5 ℃/10s; and C, carrying out temperature rise acquisition on the risk battery cells and surrounding battery cells of which the coordinates are determined in the step S2 through the temperature sensing probe, comparing the acquired temperature change value delta T with a set target threshold value T, and judging the range of the target threshold value T where the delta T is located.
Specifically, after the coordinate position of the risk battery cell is determined through the step S2, the temperature sensing probe in the temperature comparison module 3 is required to collect temperature rise of the risk battery cell and surrounding temperature, and the collected temperature rise data is compared with a preset temperature target threshold T, wherein the target threshold comprises a T1 second-level threshold and a T2 second-level threshold, and similarly, the temperature rise of the risk battery cell corresponds to three temperature ranges, namely less than 1 ℃/10S,1 ℃/10S-1.5 ℃/10S and more than 2 ℃/10S, so that the temperature rise data of the risk battery cell and surrounding temperature rise data can be collected through the temperature sensing probe, and the risk level of the risk battery cell is judged by combining the preset target threshold.
The embodiment of the invention provides a rapid response method for thermal runaway of an energy storage battery, wherein S5 specifically comprises the following steps:
when delta T is less than T1, starting the fire-fighting equipment of the single fault battery pack in the step S2 for primary risk early warning, and observing the temperature change of the next step;
when T1 is less than delta T2, stopping all actions of the current battery cluster 51 for secondary risk early warning, starting the liquid cooling equipment and starting the fire fighting equipment;
when delta T is larger than T2, the whole system is powered down in an emergency mode for three-level risk early warning, and an emergency plan is started.
Specifically, through the temperature target threshold range where the risk battery cell is located in the temperature comparison module 3, the risk level of the system is determined, when the risk battery cell is confirmed to be the primary risk early warning through temperature comparison, on the basis of rapidly powering off a single fault battery pack in the step S2, the fire-fighting equipment of the fault battery pack is further started, and the temperature change in the next step is observed; if the risk battery cell temperature does not have the continuous rising trend, continuing liquid cooling until the temperature is reduced to the normal temperature, if the risk battery cell temperature is continuously increased to the range of the secondary risk early warning interval, stopping all actions of the current battery cluster 51, starting liquid cooling equipment, and starting fire fighting equipment; if the risk cell temperature does not have a continuous rising trend afterwards, all actions of the current battery cluster 51 are continuously stopped, liquid cooling is continuously carried out until the normal temperature is reduced, if the risk cell temperature is continuously increased to a three-level risk early warning interval, the whole system is powered down in an emergency mode, an emergency plan is started, and therefore different emergency plans are adopted for different risk levels through a multi-level risk early warning mechanism, and the effects are accurate.
According to the embodiment, the energy storage battery thermal runaway rapid response system and the method provided by the invention have the following beneficial effects: the method comprises the steps of carrying out real-time monitoring and real-time image processing through linkage among an image acquisition module, an image processing module, a temperature comparison module and an out-of-control early warning module in a battery compartment, accurately judging whether gas-liquid overflows are sprayed out at a safety valve, timely and effectively acquiring specific coordinate positions of risk battery cells, and adopting corresponding response measures; the AI camera is arranged right above the center position of the battery cluster in the battery bin, so that full-time full-space and full-direction image acquisition in the working process of the battery cluster is realized; the image sensor and the computer are arranged, the high-definition image of the battery cluster acquired by the image acquisition module is transmitted to the computer in real time for processing, and whether thermal runaway occurs is judged; comparing the change degree of gray values in high-definition images before and after window sliding based on a Harris corner algorithm for gray intensity detection, determining coordinate positions of risk cells, and cutting off a power supply of a fault battery pack after a specific battery pack is positioned, so that the first step of quick response is completed; the temperature of the target position of the risk battery cell and the temperature of surrounding battery cells are detected by the temperature sensing detector, the temperature rise and the out-of-control degree of the risk battery cell are further determined, the risk level of the system is determined according to the comparison between the temperature rise of the target position and the target threshold value, a corresponding grading early warning mechanism is adopted, the out-of-control battery cell is rapidly positioned and rapidly responded, and the timeliness of the early warning mechanism is improved; the multi-level risk early warning mechanism adopts different emergency schemes aiming at different risk levels, responds in a grading manner and has accurate effect.
While certain specific embodiments of the invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the invention. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the invention. The scope of the invention is defined by the appended claims.
Claims (10)
1. A fast thermal runaway response system for an energy storage battery, comprising: the device comprises a battery compartment, an image acquisition module, an image processing module, a temperature comparison module and a runaway early warning module;
the battery compartment comprises a plurality of battery clusters, the battery clusters comprise a plurality of battery packs, and the battery clusters are arranged in an array by the plurality of battery packs;
the image acquisition module is used for continuously acquiring the gas-liquid escaped object images at the safety valve of the battery cluster in real time;
the image processing module is used for determining a coordinate position of the risk battery cell;
the out-of-control early warning module sends out an instruction for disconnecting the fault battery pack; the temperature comparison module is used for comparing the sizes of the risk cells and surrounding cells Wen Sheng T with a target threshold T;
the out-of-control early warning module is also used for determining the system risk level according to the magnitude relation between the risk cells and surrounding cells Wen Sheng T and the target threshold T, judging the fault diffusion condition, and determining the next operation of the whole energy storage system according to the judging result.
2. The energy storage battery thermal runaway rapid response system of claim 1, wherein said image acquisition module comprises an AI camera, said AI camera being secured to a top center position of the battery compartment and positioned directly above said center position of the battery cluster.
3. The rapid thermal runaway response system of claim 2, wherein the image processing module comprises an image sensor and a computer, the image sensor being electrically connected to the AI camera and the computer for transmitting real-time images acquired by the AI camera to the computer.
4. A rapid thermal runaway response system for an energy storage battery as defined in claim 3, wherein said computer uses Harris corner algorithm based on gray level intensity detection to determine the gas-liquid overflow coordinates of the risk cell by comparing the degree of change of gray level of pixels in windows before and after sliding by sliding a fixed window over the image.
5. The energy storage cell thermal runaway rapid response system of claim 1, wherein said temperature comparison module further comprises a temperature sensing detector for detecting a temperature rise of said gas-liquid overflow coordinates.
6. A method of rapid thermal runaway response of an energy storage battery, comprising:
s1: acquiring a real-time image of a battery cell in a battery compartment;
s2: establishing a battery pack thermal runaway image analysis based on a Harris corner algorithm;
s3: according to the coordinate position determined in the step S2, rapidly powering off a single fault battery pack, and observing the temperature change of the risk battery cell and surrounding battery cells in the next step;
s4: acquiring target positions and surrounding cell temperatures, and comparing the target positions with a target threshold value;
s5: and establishing a thermal runaway grading early warning mechanism of the energy storage battery.
7. The method for thermal runaway rapid response of an energy storage battery according to claim 6, wherein S1 is specifically:
an AI camera is arranged at the center position of the top in the battery compartment, and all the battery cell images in the battery compartment are acquired in real time by using the full time interval and the full space of the AI camera.
8. The method for thermal runaway rapid response of an energy storage battery according to claim 6, wherein S2 comprises the steps of:
s21: the coordinates of the target pixel point are (x, y), the moving distance of the fixed window in the x direction is u, the moving distance in the y direction is v, and the gray scale variation in the window is expressed as: e (E) x,y ＝∑ω u,v (I x+u,y+v -I x,y ) 2 Wherein ω is u,v As a Gaussian window function, I x+u,y+v For the gradient of the target pixel point in the target coordinate position, I x,y Gradient of the target pixel point in the initial coordinate position;
s22: smoothing the target image by Gaussian filtering to obtain a new autocorrelation matrix Wherein,for the gradient product of the target pixel in the X direction,/->Is the gradient product of the target pixel point in the Y direction, I x I y The gradient product of the target pixel point in the X direction and the Y direction is obtained;
s23: calculating the response value of the feature point through a corner response function R=detM-k (traceM) and comparing the response value with a set threshold value; if the response value is larger than the threshold value, the corresponding pixel point is marked as a corner point, wherein k is a Harris operator parameter, detM is a determinant of a matrix M, and traceM is a trace of the matrix M;
s24: and setting the local extremum which does not meet the given threshold condition to zero through non-maximum suppression, thereby determining the final characteristics extracted by the Harris corner algorithm.
9. The method for thermal runaway rapid response of an energy storage battery according to claim 8, wherein S4 is specifically:
the target threshold T comprises two-level thresholds T1 and T2, wherein T1 is 1 ℃/10s, and T2 is 1.5 ℃/10s;
and C, carrying out temperature rise acquisition on the risk battery cells and surrounding battery cells of which the coordinates are determined in the step S2 through the temperature sensing probe, comparing the acquired temperature change value delta T with a set target threshold value T, and judging the range of the target threshold value T where the delta T is located.
10. The method for thermal runaway rapid response of an energy storage battery according to claim 6, wherein S5 is specifically:
when delta T is less than T1, starting the fire-fighting equipment of the single fault battery pack in the step S2 for primary risk early warning, and observing the temperature change of the next step;
when T1 is less than delta T2, stopping all actions of the current battery cluster for secondary risk early warning, starting the liquid cooling equipment and starting the fire fighting equipment;
when delta T is larger than T2, the whole system is powered down in an emergency mode for three-level risk early warning, and an emergency plan is started.
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| CN117691227B (en) * | 2024-02-04 | 2024-04-26 | 江苏林洋亿纬储能科技有限公司 | Method and system for safety pre-warning of battery energy storage system and computing device |
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