Detection device and detection method based on energy storage battery production

Abstract

The invention relates to the technical field of energy storage battery detection equipment, in particular to a detection device and a detection method based on energy storage battery production. According to the technical scheme, the system comprises an energy storage battery module for storing electric energy; a plurality of groups of pits for positioning, placing and detecting the energy storage battery module are arranged in the detection machine table; a data acquisition module used for acquiring data of the energy storage battery module is arranged in the detection machine table, and the data acquisition module is arranged at the top of the detection machine table in a rotating and lifting manner; and a data processing and analyzing module for processing various data acquired by the data acquisition module is also arranged on the side wall of the front surface. The detection device and the detection method are convenient to use, suitable for efficient energy storage battery performance acquisition operation, accurate in judgment, capable of judging the stability of the battery in advance, capable of further improving the delivery quality of the energy storage battery and avoiding danger, and suitable for popularization and application.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage battery detection equipment, and in particular to a detection device and a detection method based on energy storage battery production. Background Art

[0002] At present, when energy storage battery technology is widely used, the thermal runaway problem seriously threatens the safety and reliability of energy storage systems. Under complex working conditions such as charge-discharge cycles, overcharge, over-discharge, external short circuit, and high-temperature environments of energy storage batteries, the internal electrochemical reactions may get out of control, leading to thermal runaway. Once thermal runaway occurs, it will not only cause a sharp decline in battery performance and shorten its service life, but also may cause catastrophic consequences such as electrolyte leakage, fire, and even explosion due to the sharp rise in the internal temperature and pressure of the battery, posing great harm to the safety of personnel's lives and property and the surrounding environment.

[0003] Existing thermal runaway detection means for energy storage batteries have obvious deficiencies. Some traditional detection methods only focus on the monitoring of a single physical quantity, such as simply relying on temperature sensors to monitor the temperature change on the battery surface. However, the thermal runaway reaction inside the battery is a complex phenomenon involving the mutual coupling of multiple physical and chemical processes. Single temperature monitoring is difficult to comprehensively and accurately reflect the true process of thermal runaway. At this time, the method based on single temperature monitoring will have missed detections and cannot timely warn of the thermal runaway risk. In addition, some detection methods have defects in detection accuracy and response speed. As a result, in the early stage of thermal runaway, it is impossible to timely and accurately judge whether thermal runaway is about to occur, thus missing the best intervention opportunity and worsening the thermal runaway accident. Moreover, existing detection devices often lack the ability to deeply analyze and comprehensively judge the variation laws of multiple parameters during thermal runaway.

[0004] In summary, traditional detection methods are difficult to effectively integrate and analyze the coordinated changes of various internal parameters of energy storage batteries, cannot establish a comprehensive and accurate thermal runaway performance evaluation model, and are difficult to meet the requirements for accurately detecting and deeply studying the thermal runaway performance of energy storage batteries. For these reasons, the present application proposes a detection device and a detection method with high integration of various data such as temperature, pressure, gas concentration, and pressure for the interior of energy storage batteries after production. Summary of the Invention

[0005] The object of the present invention is to address the problems in the background art and propose a detection device and a detection method with high integration of various data such as temperature, pressure, gas concentration, and pressure for the interior of energy storage batteries after production.

[0006] The technical solution of the present invention: A detection device based on energy storage battery production, including an energy storage battery module for electrical energy storage;

[0007] A detection machine, with multiple pits for positioning and detecting energy storage battery modules arranged inside it;

[0008] Inside it, a data acquisition module for collecting data of energy storage battery modules is arranged. The data acquisition module is rotationally and vertically arranged on the top of the detection machine;

[0009] On its front side wall, a data processing and analysis module for processing various data collected by the data acquisition module is also arranged. The data processing and analysis module relies on a server with powerful computing capabilities and a cloud computing platform as the hardware support for data processing and analysis, and has a multi-core processor, a large-capacity memory, and a high-speed storage device;

[0010] It also includes a warning module arranged on the upper surface of the detection machine for warning and positioning the energy storage battery to be tested.

[0011] Optionally, positioning grids corresponding to the positions of the energy storage battery modules are arranged in an array at the edges of the pits, and labels with row and column marking numbers are pasted at the positioning grids;

[0012] An adjustment cavity for storing each structure in the data acquisition module is opened inside the detection machine.

[0013] Optionally, the data acquisition module includes a pressing cover plate located outside the adjustment cavity and above the energy storage battery module. The two sides of the pressing cover plate are chamfered plates;

[0014] Soft strip pads are bonded to the inner walls of the two chamfered plates on both sides. The soft strip pads include a contact area and a squeezing area;

[0015] The contact area is an inclined edge, and the diameter gradually increases from the bottom upwards; the squeezing area is a vertical surface, which is the maximum diameter thickness of the soft strip pad.

[0016] Optionally, data acquisition contacts are arranged at the middle position of the bottom of each group of pits, and sensor components are arranged in an array at the position of the bottom surface of the pressing cover plate corresponding to the pits;

[0017] The data acquisition module also includes a driving and operating component installed in the adjustment cavity. The driving and operating component includes a rotating motor installed and connected to the inner wall of the bottom of the adjustment cavity. A lifting column for adjusting the height of the pressing cover plate is slidably sleeved and installed on the top of the rotating motor. The top of the lifting column is connected with a horizontally arranged lifting limit plate. The length of the lifting limit plate is greater than the top through hole of the adjustment cavity. The top of the lifting limit plate is fixedly connected with a support frame, and the other end of the support frame is fixedly connected with the top of the pressing cover plate.

[0018] Optionally, a rectangular cavity is opened in the inner wall of the lifting column, and a rectangular plate is fixedly connected to the top output end of the rotating motor. The rectangular plate is slidably arranged on the inner wall of the rectangular cavity.

[0019] Optionally, a plurality of groups of teeth are arranged on one side of the outer ring of the lifting column, and gears meshing with the teeth are arranged on the side surfaces thereof. The inner ring of the gear is penetrated by a group of rotating shafts rotatably connected to the inner wall of one side of the adjustment chamber, and the other end of the rotating shaft penetrates the side wall of the detection machine and is connected to a micro drive motor. The micro drive motor is assembled and connected to the side wall of the detection machine via a mounting seat.

[0020] The present invention also proposes a detection method for energy storage battery production using the above detection device:

[0021] The steps are as follows:

[0022] The step 1: placing and installing multiple groups of energy storage battery modules in the synchronous detection machine one by one, ensuring that each energy storage battery module is located at the center of a single pit and contacts the data collection contact;

[0023] Step 2: pre-set the operation rules of each driving device in the data acquisition module, and gradually start and operate each driving device until the lower cover plate lightly presses and contacts the upper surface of the corresponding energy storage battery module;

[0024] Step 3: Combine the data acquisition contacts and sensor components to collect and convert the voltage, gas component concentration, temperature and pressure data of multiple energy storage battery modules in real time, and combine the wireless transmission module to encrypt and transmit the data to the data processing and analysis module;

[0025] Step 4:

[0026] Step 4.1: Preliminarily combine the data processing and analysis module with a large amount of thermal runaway experimental data and actual operation data of energy storage batteries, and use machine learning algorithms to build a thermal runaway warning model;

[0027] Step 4.2: Combine the data collected by the data acquisition module with the data processing and analysis module to input the monitoring data into the early warning model, which can accurately determine whether the battery has a thermal runaway risk and issue a warning signal in the early stage of thermal runaway;

[0028] Step 4.3: Establish a mathematical model of the thermal runaway process, dynamically simulate and analyze the internal reaction process of the battery during the thermal runaway process, and deeply understand the occurrence mechanism and development process of thermal runaway by comparing and verifying the actual monitoring data with the simulation results;

[0029] Step 5: Combined with the early warning module, various monitoring parameters of the energy storage battery, thermal runaway warning information and thermal runaway simulation analysis results are displayed in real time. When the thermal runaway detection algorithm determines that the battery has a thermal runaway risk or thermal runaway has occurred, the sound and light alarm is immediately activated.

[0030] Optionally, it includes a temperature sensor module, a pressure sensor module, a gas sensor module, and a voltage and current sensor module;

[0031] Among them, the temperature sensor module uses a thermocouple sensor array, and a plurality of temperature measurement points are evenly distributed on the surface and data acquisition contact positions of each energy storage battery module. The measurement accuracy of the surface temperature sensor is ±0.3°C, and the accuracy of the internal temperature sensor is ±0.1°C, ensuring that the temperature distribution information of a single energy storage battery module at different positions can be accurately obtained in real time, constructing a three-dimensional temperature monitoring network, and comprehensively capturing the subtle changes and gradient distribution of temperature during the thermal runaway process;

[0032] The measurement range of the pressure sensor module is 0 - 22 MPa, and the accuracy is ±0.005 MPa. It is installed in the internal space of the energy storage battery module to monitor the internal pressure change caused by gas generation and expansion during the thermal runaway of the battery in real time, and the response time is less than 1 ms;

[0033] The gas sensor module selects a high-sensitivity gas sensor array to detect multiple characteristic gases simultaneously, and the detection sensitivity reaches the ppb level. The gas sensor is installed in the gas sampling channel of the energy storage battery module and is connected to the battery interior through the gas sampling system, providing important data support for analyzing the chemical reaction process of thermal runaway;

[0034] In the voltage and current sensor module, the measurement accuracy of the voltage sensor is ±0.0005 V, and the measurement accuracy of the current sensor is ±0.05 A.

[0035] Optionally, in step 3, the wireless transmission module adopts any one of Wi-Fi6 or 5G modules;

[0036] The transmission rate is greater than 100 Mbps, which is used to transmit the collected data to the remote data processing and analysis module in time;

[0037] The wireless transmission module adopts the AES encryption algorithm to ensure the security and confidentiality of data during transmission, preventing data from being stolen or tampered with;

[0038] In step 4.1, the machine learning algorithm is implemented using random forest and support vector machine to extract and analyze the features of the multi-dimensional data collected in step 3, mine the change rules and correlation features of temperature, pressure, gas component concentration, voltage, and current parameters during the thermal runaway process, and establish a thermal runaway warning index system with multi-parameter fusion;

[0039] Step 4.2 combines the real-time collected data to judge whether there is a thermal runaway risk and gives an early warning, and the warning accuracy rate is greater than 95%.

[0040] Optionally, the warning module is specifically composed of a display screen main body and an audible and visual alarm. The warning module is communicatively connected to the output end of the data processing and analysis module. Through the setting of the display screen main body, the monitoring parameters of the energy storage battery module are displayed in real time, specifically including: temperature distribution cloud map, pressure change curve, gas composition concentration histogram, voltage and current waveform diagram, thermal runaway warning information, and thermal runaway simulation analysis results.

[0041] Compared with the prior art, the present invention has the following beneficial technical effects:

[0042] The detection device of the present invention integrates the detection structure, detection module, and operation algorithms such as model establishment used in the detection method, and is used for centralized electrical acquisition of the energy storage battery, thereby improving the integration of the device, simplifying the detection device of the energy storage battery, reducing costs, and at the same time, the various structures assist each other to realize the performance acquisition and determination of the energy storage battery;

[0043] The present invention synchronously monitors the key parameters during the thermal runaway process through a multi-dimensional and high-precision sensor array, and combines advanced data processing algorithms and intelligent analysis models to realize comprehensive, accurate detection and in-depth analysis of the thermal runaway performance of the energy storage battery, effectively improving the safety and reliability of the energy storage system;

[0044] The present invention also compares and analyzes the historical data and current data of parameters such as the temperature, voltage, gas concentration, and pressure of the energy storage battery, calculates the change rate, change trend of each parameter, and their correlation, and combines the monitoring and comparison of real-time data to realize the timely warning of abnormal energy storage modules at the initial stage of changes in the energy storage battery, obtain the best intervention time, and collect multiple data to avoid the one-sidedness of relying only on a single data in a complex application environment;

[0045] The present invention also realizes the automatic alignment, automatic steering, and lifting of multiple energy storage battery modules through the composition setting of the data acquisition module, thereby improving the automation degree of the device;

[0046] In summary, the detection device and detection method of the present invention are easy to use, adapt to the efficient performance acquisition operation of the energy storage battery, have accurate judgment, can pre-judge the stability of the battery, further improve the factory quality of the energy storage battery, avoid danger, and are suitable for popularization and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The front view schematic diagram of the detection device and the energy storage battery proposed by the present invention is given;

[0048] Figure 2 For Figure 1 the structural schematic diagram of the detection machine in

[0049] Figure 3 Provide a structural schematic diagram of the data acquisition module in the present invention;

[0050] Figure 4 Provide a partial structural sectional view schematic diagram of the present invention.

[0051] Reference numerals:

[0052] 1. Energy storage battery module;

[0053] 2. Detection machine platform; 21. Pit; 22. Positioning grid; 23. Adjustment cavity;

[0054] 3. Data acquisition module; 30. Press-down cover plate; 31. Sensor assembly; 32. Driving operation assembly; 320. Micro driving motor; 321. Rotating motor; 322. Rectangular plate; 323. Lifting column; 324. Rectangular cavity; 325. Teeth; 326. Gear; 33. Lifting limit plate; 34. Support frame; 35. Data acquisition contact; 36. Soft strip pad;

[0055] 4. Data processing and analysis module;

[0056] 5. Early warning module; 51. Display screen main body; 52. Acousto-optic alarm. Detailed implementation manners

[0057] Next, the technical solutions of the present disclosure will be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all the embodiments.

[0058] Generally, the components of the embodiments of the present disclosure described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the accompanying drawings is not intended to limit the scope of the present disclosure to be protected, but only represents the selected embodiments of the present disclosure.

[0059] Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present disclosure.

[0060] In the description of the present disclosure, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present disclosure.

[0061] In the description of the present disclosure, it should be noted that unless otherwise clearly specified and limited, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present disclosure can be understood according to specific situations.

[0062] Embodiment

[0063] As Figures 1-4 As shown, a detection device based on the production of energy storage batteries proposed by the present invention includes an energy storage battery module 1 for electrical energy storage. Among them, there are multiple groups of energy storage battery modules 1 arranged in the pit 21, which are used to synchronously detect the performance of multiple energy storage batteries and improve the detection efficiency after the production of energy storage batteries.

[0064] A detection machine table 2, inside which there are multiple groups of pits 21 for positioning and placing the energy storage battery module 1 for detection; the pit 21 is a rectangular frame that conforms to the size of the bottom contact surface of the energy storage battery module 1, which is used to position and place the energy storage battery module 1 to realize the orderly placement of the energy storage battery module 1. At the border of the pit 21, there are positioning grids 22 arranged in an array corresponding to the position of the energy storage battery module 1. At the positioning grid 22, there are sticky notes with row and column marking numbers pasted, and the digital sticky notes match the row and column numbers displayed on the display screen main body 51, which are used to accurately locate the abnormal energy storage batteries.

[0065] An adjustment cavity 23 for storing each structure in the data acquisition module 3 is opened inside the detection machine table 2; a through hole penetrating the detection machine table 2 is opened at the top of the adjustment cavity 23, and among them, the lifting column 323 penetrates the through hole for height adjustment.

[0066] A data acquisition module 3 for data acquisition of the energy storage battery module 1 is arranged inside the adjustment chamber 23, and the data acquisition module 3 is rotatably and lifted on the top of the detection machine 2; the data acquisition module 3 includes a lower pressure cover plate 30 located outside the adjustment chamber 23 and above the energy storage battery module 1, and the two sides of the lower pressure cover plate 30 are chamfered plates; the inner walls of the chamfered plates on both sides are bonded with soft strip pads 36, and the soft strip pads 36 include a contact area and an extrusion area; the contact area is an inclined edge, and the diameter gradually increases from the bottom to the top; the extrusion area is a vertical surface, which is the maximum diameter thickness of the soft strip pad 36; wherein the soft strip pad 36 is arranged to contact and abut against the side of the energy storage battery module 1 at the edge, thereby stabilizing the spacing between each energy storage battery, avoiding displacement or tilting, and realizing accurate alignment and acquisition of data; the data acquisition module 3 also includes a drive operation component 32 installed in the adjustment chamber 23, and the drive operation component 32 includes a contact area with the inner wall of the bottom of the adjustment chamber 23 The rotating motor 321 is installed and connected, and the top sliding sleeve of the rotating motor 321 is installed with a lifting column 323 for adjusting the height of the pressing cover plate 30. The inner wall of the lifting column 323 is provided with a rectangular cavity 324. The top output end of the rotating motor 321 is fixedly connected with a rectangular plate 322, and the rectangular plate 322 is located at the inner wall of the rectangular cavity 324 and is slidably arranged. The rectangular arrangement of the rectangular plate 322 and the rectangular cavity 324 is used to determine that when the output end of the rotating motor 321 drives the lifting column 323 to rotate synchronously under the limiting action of the rectangular cavity 324, the position of the pressing cover plate 30 is adjusted, which is used for placing or taking the energy storage battery module 1; the top of the lifting column 323 is connected with a transversely arranged lifting limit plate 33, the length of the lifting limit plate 33 is greater than the top through hole of the adjustment cavity 23, and the top of the lifting limit plate 33 is fixedly connected with a support frame 34, and the other end of the support frame 34 is fixedly connected to the top of the pressing cover plate 30;On one side of the outer ring of the lifting column 323, multiple groups of teeth 325 are arranged. On the side of the multiple groups of teeth 325, gears 326 meshing and driving therewith are correspondingly arranged. A rotating shaft rotatably connected to the inner wall of one side of the adjustment cavity 23 penetrates through the inner ring of the gear 326. The other end of the rotating shaft penetrates through the side wall of the detection machine table 2 and is connected to a micro drive motor 320. The micro drive motor 320 and the side wall of the detection machine table 2 are assembled and connected through a mounting seat. In combination with the settings of the micro drive motor 320 and the gear 326, when the micro drive motor 320 is started, the gear 326 is rotated, and then the teeth 325 are meshed, so that the height of the teeth 325 is adjusted in the through hole, and further the height of the pressing cover plate 30 is adjusted. Specifically, after the teeth 325 are meshed to a suitable height by the gear 326, the rotating motor 321 is slightly adjusted to rotate, so that the pressing cover plate 30 corresponds to the position of the energy storage battery module 1. During the slight rotation of the output end of the rotating motor 321, the meshing between the teeth 325 and the gear 326 does not disengage. After the position correspondence between the energy storage battery module 1 and the pressing cover plate 30 is completed, the gear 326 is reversely driven to mesh with the teeth 325, and then the height of the lifting column 323 is reduced, so that the sensor assembly 31 contacts the upper surface of the energy storage battery module 1;

[0067] On the front side wall of the detection machine table 2, a data processing and analysis module 4 for processing various data collected by the data collection module 3 is also provided. The data processing and analysis module 4 relies on a server with powerful computing power and a cloud computing platform as the hardware support for data processing and analysis, and has a multi-core processor, a large-capacity memory, and a high-speed storage device;

[0068] It also includes a warning module 5 arranged on the upper surface of the detection machine table 2 for warning and positioning the energy storage battery to be tested.

[0069] In this embodiment, a method for detecting the performance of an energy storage battery in combination with the above detection device is also proposed, including the following operation steps:

[0070] Step 1: Place and install multiple groups of energy storage battery modules 1 one by one in the detection machine table 2 synchronously, ensuring that each energy storage battery module 1 is located at the center of a single pit 21 and contacts the data collection contact 35. Multiple temperature sensors for internal temperature perception and sensors for detecting the gas component concentration for connecting to the gas channel are also arranged at the corresponding positions inside the energy storage battery module 1, so as to perform comprehensive data monitoring on the energy storage battery module 1 and achieve accurate data collection;

[0071] Step 2: Preset the operation rules of each driving device in the data acquisition module 3. The specific setting algorithm can adopt the existing controller control calculation algorithm, and will not be elaborated in this embodiment. Then gradually start and run each driving device until the lower pressing cover 30 gently presses and contacts the upper surface of the energy storage battery module 1, so as to realize the contact of the sensor assembly 31 with the outer surface of the energy storage battery module 1. At the same time, combined with the setting of the data acquisition contact 35, the purpose of connecting the positive and negative poles of the energy storage battery module 1 is realized. In this embodiment, the connection relationship between the sensor and other positions of the energy storage battery module 1 is also involved, which will not be described here, and general connection means can be adopted;

[0072] Step 3: Combine the data acquisition contact 35 and the sensor assembly 31 to collect and convert the voltage, gas component concentration, temperature and pressure data of multiple groups of energy storage battery modules 1 in real time, and transmit the encrypted data to the data processing and analysis module 4 through the wireless transmission module. Specifically, a 5G module is adopted, and the transmission rate is greater than 100 Mbps, which is used to transmit the collected data to the remote data processing and analysis module 4 in time; The wireless transmission module adopts the AES encryption algorithm to ensure the security and confidentiality of the data during transmission and prevent the data from being stolen or tampered with;

[0073] Among them, the sensor assembly 31 is a multi-dimensional sensor array, including a temperature sensor module, a pressure sensor module, a gas sensor module, and a voltage and current sensor module;

[0074] Among them, the temperature sensor module adopts a thermocouple sensor array. A plurality of temperature measurement points are evenly distributed on the surface of each energy storage battery module 1 and at the position of the data acquisition contact 35. A plurality of temperature monitoring points are arranged near the electrodes and in the center area of the electrolyte. For example: in a typical lithium-ion energy storage battery, temperature sensors can be arranged at the four corners and the center position of the battery surface and at two positions near the positive and negative electrodes inside to form a three-dimensional temperature monitoring network. The measurement accuracy of the surface temperature sensor is ±0.3 °C, and the accuracy of the internal temperature sensor is ±0.1 °C, ensuring that the temperature distribution information of a single energy storage battery module 1 at different positions can be accurately obtained in real time, constructing a three-dimensional temperature monitoring network, and comprehensively capturing the subtle changes and gradient distribution of temperature during the thermal runaway process;

[0075] Among them, the temperature change calculation formula is: Where ΔT is the temperature change amount, T1 and T2 are the starting temperature and the ending temperature respectively; Δt is the time change amount, and t1 and t2 are the starting time and the ending time respectively. This formula is used to calculate the rise or fall of the battery temperature per unit time. If the temperature change rate increases abnormally, it may indicate a thermal runaway risk;

[0076] The measurement range of the pressure sensor module is 0 - 22 MPa, and the accuracy is ±0.005 MPa. It is installed in the internal space of the energy storage battery module 1. A high-precision pressure sensor is used to monitor in real time the internal pressure change caused by gas generation and expansion during the thermal runaway of the battery. The response time is less than 1 ms. Due to the pressure change caused by the decomposition and gasification of the electrolyte, the sudden increase in pressure is often one of the important signals indicating that thermal runaway is about to occur or has already occurred.

[0077] Among them, the ideal gas state equation: P v = nRT, where P is the pressure, V is the volume, n is the amount of substance, T is the temperature, and R is the universal gas constant. In the monitoring of battery thermal runaway, if the amount of substance, temperature, and the volume of the container where the gas inside the battery are known, the pressure change can be calculated according to this formula to help judge the severity of the internal reaction of the battery.

[0078] Rate of pressure change: Among them, P1 and P2 are the initial pressure and the final pressure respectively, and t1 and t2 are the initial time and the final time respectively. By calculating the rate of change of pressure with time, the growth trend of the internal pressure of the battery can be monitored, and the signs of thermal runaway can be detected in time.

[0079] The gas sensor module selects a high-sensitivity gas sensor array to detect multiple characteristic gases simultaneously. The characteristic gases include hydrogen, carbon monoxide, carbon dioxide, etc. The detection sensitivity reaches the ppb level. The gas sensor is installed in the gas sampling channel of the energy storage battery module 1 and is connected to the inside of the battery through the gas sampling system, providing important data support for analyzing the chemical reaction process of thermal runaway. For example, a metal oxide semiconductor gas sensor has a high-sensitivity response to hydrogen, while an electrochemical sensor is used to accurately detect carbon monoxide and carbon dioxide, and the change information of the gas composition and concentration inside the battery is collected in real time.

[0080] Among them, the amount-of-substance concentration of gas: Among them, c is the amount-of-substance concentration, n is the amount of solute, and V is the volume of the solution. For the gas generated by battery thermal runaway, its amount of substance or volume can be measured by the corresponding gas sensor, and then the concentration can be calculated in combination with the volume of the space where it is located.

[0081] Mass concentration of gas: Among them, ρ is the mass concentration, m is the mass of the solute, and V is the volume of the solution. The mass of the gas and the volume of the space where it is located can be measured first, and then the mass concentration can be obtained to monitor the change in the concentration of the gas generated by thermal runaway.

[0082] In the voltage-current sensor module, the measurement accuracy of the voltage sensor is ±0.0005V. A high-precision differential voltage sensor is selected to directly measure the voltage of each battery cell, enabling timely detection of abnormal conditions such as overcharging, over-discharging, and internal short circuits of the battery, as these abnormalities often accompany significant voltage fluctuations; the measurement accuracy of the current sensor is ±0.05A;

[0083] Among them, the current change rate: Among them, I1 and I2 are the starting current and the ending current respectively. When the battery undergoes thermal runaway, the internal chemical reaction may intensify, resulting in abnormal current changes. By calculating the current change rate, monitoring can be carried out.

[0084] Voltage change rate: Among them, U1 and U2 are the starting voltage and the ending voltage respectively. During the thermal runaway process of the battery, the voltage may fluctuate or decrease. Calculating the voltage change rate helps to capture these abnormalities in a timely manner.

[0085] Step 4:

[0086] Step 4.1: Pre-combine the data processing and analysis module 4 to utilize a large amount of experimental data and actual operation data of energy storage battery thermal runaway, and adopt machine learning algorithms to construct a thermal runaway early warning model; the machine learning algorithms are implemented using random forest and support vector machine, extract and analyze the features of the multi-dimensional data collected in step 3, mine the change laws and correlation features of temperature, pressure, gas component concentration, voltage, and current parameters during the thermal runaway process, and establish a multi-parameter fusion thermal runaway early warning index system;

[0087] Step 4.2: Combine the data acquisition module 3 to input the monitoring data into the data processing and analysis module 4 and input it into the early warning model, which can accurately judge whether the battery has a thermal runaway risk and issue an early warning signal in the early stage of thermal runaway; combine the real-time collected data to judge whether there is a thermal runaway risk and give an early warning, and the early warning accuracy rate is greater than 95%; the algorithm comprehensively considers the change trends, change rates, and the mutual relationships of multiple parameters such as temperature, voltage, gas concentration, and pressure, and can accurately identify the early features of thermal runaway. For example, when the temperature rise rate exceeds a certain threshold and is accompanied by abnormal voltage fluctuations, a rapid increase in the concentration of specific gases, and an increase in pressure, the algorithm determines that the battery may undergo thermal runaway and issues an early warning signal;

[0088] Step 4.3: Establish a mathematical model of the thermal runaway process, dynamically simulate and analyze the internal reaction process of the battery during the thermal runaway process, and through comparing and verifying the actual monitoring data with the simulation results, deeply understand the occurrence mechanism and development process of thermal runaway;

[0089] Step 5: Combine the warning module 5 to display the monitoring parameters, thermal runaway warning information, and thermal runaway simulation analysis results of the energy storage battery in real time. When the thermal runaway detection algorithm determines that the battery has a thermal runaway risk or thermal runaway has occurred, the audible and visual alarm 52 is immediately activated, and the sound intensity of the audible and visual alarm 52 is greater than 80 decibels; the warning module 5 is specifically composed of a display main body 51 and an audible and visual alarm 52, wherein the warning module 5 is communicatively connected to the output end of the data processing and analysis module 4, and the monitoring parameters of the energy storage battery module 1 are displayed in real time through the setting of the display main body 51, specifically including: temperature distribution cloud map, pressure change curve, gas component concentration histogram, voltage and current waveform diagram, thermal runaway warning information, and thermal runaway simulation analysis results. Among them, a positioning system is also embedded in each pit 21. In this embodiment, a conventional GPS positioning system can be used to accurately obtain the coordinate position information of the battery with thermal runaway and send it out together with the warning information, so as to facilitate the maintenance personnel to quickly find the faulty battery, isolate and process it, and minimize the impact of thermal runaway on the entire energy storage system.

[0090] The above specific embodiments are only an optional embodiment of the present invention. Based on the technical solution of the present invention and the relevant revelations of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

Claims

1. A detection device based on energy storage battery production, characterized in that: It comprises an energy storage battery module (1) for storing electric energy; A testing machine (2) is provided with a plurality of pits (21) for positioning and testing the energy storage battery module (1); A data acquisition module (3) for acquiring data of the energy storage battery module (1) is arranged inside the detection machine (2); the data acquisition module (3) is rotatably and liftably arranged on the top of the detection machine (2); The front side wall is also provided with a data processing and analysis module (4) for processing the various data collected by the data collection module (3); the data processing and analysis module (4) relies on a server with powerful computing capabilities and a cloud computing platform as hardware support for data processing and analysis, and is equipped with a multi-core processor, a large-capacity memory and a high-speed storage device; It also includes an early warning module (5) arranged on the upper surface of the detection machine (2) and used for warning and locating the energy storage battery to be tested.

2. A detection device based on energy storage battery production according to claim 1, characterized in that: Positioning grids (22) corresponding to the positions of the energy storage battery modules (1) are arranged in an array at the borders of the pits (21), and sticky notes with row and column marking numbers are pasted on the positioning grids (22); An adjustment chamber (23) for storing various structures in the data acquisition module (3) is provided in the detection machine (2).

3. A detection device based on energy storage battery production according to claim 2, characterized in that: The data acquisition module (3) comprises a lower pressing cover plate (30) located outside the adjustment cavity (23) and above the energy storage battery module (1), and both sides of the lower pressing cover plate (30) are chamfered plates; Soft strip pads (36) are bonded to the inner walls of the chamfered plates on both sides, and the soft strip pads (36) include a contact area and an extrusion area; The contact area is an inclined edge, and the diameter gradually increases from the bottom to the top; the extrusion area is a vertical surface, which is the maximum diameter thickness of the soft strip pad (36).

4. A detection device based on energy storage battery production according to claim 3, characterized in that: A data acquisition contact (35) is arranged at the middle position of the bottom of each group of the pit positions (21), and a sensor assembly (31) is arranged in an array at the position corresponding to the pit position (21) on the bottom surface of the lower pressing cover plate (30); The data acquisition module (3) also includes a driving operation component (32) installed in the adjustment cavity (23), the driving operation component (32) includes a rotating motor (321) installed and connected to the inner wall of the bottom of the adjustment cavity (23), the top sliding sleeve of the rotating motor (321) is installed with a lifting column (323) for adjusting the height of the lower pressure cover plate (30), the top of the lifting column (323) is connected to a transversely arranged lifting limit plate (33), the length of the lifting limit plate (33) is greater than the top through hole of the adjustment cavity (23), the top of the lifting limit plate (33) is fixedly connected to a support frame (34), and the other end of the support frame (34) is fixedly connected to the top of the lower pressure cover plate (30).

5. A detection device based on energy storage battery production according to claim 4, characterized in that: The inner wall of the lifting column (323) is provided with a rectangular cavity (324), the top output end of the rotating motor (321) is fixedly connected with a rectangular plate (322), and the rectangular plate (322) is slidably arranged on the inner wall of the rectangular cavity (324).

6. A detection device based on energy storage battery production according to claim 5, characterized in that: A plurality of groups of teeth (325) are arranged on one side of the outer ring of the lifting column (323), and gears (326) meshing with the teeth (325) are arranged on the side surfaces thereof. The inner ring of the gear (326) is penetrated by a group of rotating shafts rotatably connected to the inner wall of one side of the adjustment chamber (23), and the other end of the rotating shaft penetrates the side wall of the detection machine (2) and is connected to a micro drive motor (320). The micro drive motor (320) is assembled and connected to the side wall of the detection machine (2) via a mounting seat.

7. A detection method using the detection device based on energy storage battery production according to any one of claims 1 to 6, characterized in that: The steps are as follows: Step 1: placing and installing multiple groups of energy storage battery modules (1) in the synchronous detection machine (2) one by one, ensuring that each energy storage battery module (1) is located at the center of a single pit (21) and contacts the data collection contact (35); Step 2: presetting the operation rules of each driving device in the data acquisition module (3), and gradually starting and operating each driving device until the lower pressing cover plate (30) lightly presses and contacts the upper surface of the corresponding energy storage battery module (1); Step 3: In combination with the data acquisition contacts (35) and the sensor assembly (31), the voltage, gas component concentration, temperature and pressure data of the multiple energy storage battery modules (1) are collected and converted in real time, and the wireless transmission module is combined to encrypt the data and transmit it to the data processing and analysis module (4); Step 4: Step 4.1: Preliminarily combine the data processing and analysis module (4) with a large amount of thermal runaway experimental data and actual operation data of energy storage batteries, and use a machine learning algorithm to build a thermal runaway warning model; Step 4.2: The monitoring data is input into the data processing and analysis module (4) in combination with the data acquisition module (3) and input into the early warning model, which can accurately determine whether the battery has a thermal runaway risk and issue a warning signal in the early stage of thermal runaway; Step 4.3: Establish a mathematical model of the thermal runaway process, dynamically simulate and analyze the internal reaction process of the battery during the thermal runaway process, and deeply understand the occurrence mechanism and development process of thermal runaway by comparing and verifying the actual monitoring data with the simulation results; Step 5: In combination with the early warning module (5), various monitoring parameters of the energy storage battery, thermal runaway early warning information and thermal runaway simulation analysis results are displayed in real time. When the thermal runaway detection algorithm determines that the battery has a thermal runaway risk or thermal runaway has occurred, the sound and light alarm (52) is immediately activated.

8. The detection method according to claim 7, characterized in that: The sensor assembly (31) is a multi-dimensional sensor array, which includes a temperature sensor module, a pressure sensor module, a gas sensor module, and a voltage and current sensor module; The temperature sensor module adopts a thermocouple sensor array, and a plurality of temperature measurement points are evenly distributed on the surface of each energy storage battery module (1) and at the position of the data acquisition contact (35). The measurement accuracy of the surface temperature sensor is ±0.3°C, and the accuracy of the internal temperature sensor is ±0.1°C, so as to ensure that the temperature distribution information of a single energy storage battery module (1) at different positions is accurately obtained in real time, and a three-dimensional temperature monitoring network is constructed to comprehensively capture the subtle changes and gradient distribution of temperature during the thermal runaway process. The pressure sensor module has a measurement range of 0-22 MPa and an accuracy of ±0.005 MPa. It is installed in the internal space of the energy storage battery module (1) and is used to monitor in real time the internal pressure changes caused by gas generation and expansion during thermal runaway of the battery. The response time is less than 1 ms. The gas sensor module uses a high-sensitivity gas sensor array to detect multiple characteristic gases simultaneously, with a detection sensitivity reaching the ppb level. The gas sensor is installed in the gas sampling channel of the energy storage battery module (1) and is connected to the inside of the battery through a gas sampling system, providing important data support for analyzing the chemical reaction process of thermal runaway; The measurement accuracy of the voltage sensor in the voltage and current sensor module is ±0.0005V, and the measurement accuracy of the current sensor is ±0.05A.

9. The detection method according to claim 7, characterized in that: In step 3, the wireless transmission module adopts either Wi-Fi 6 or 5G module; The transmission rate is greater than 100 Mbps, and is used to transmit the collected data to the remote data processing and analysis module (4) in a timely manner; The wireless transmission module uses AES encryption algorithm to ensure the security and confidentiality of data during transmission and prevent data from being stolen or tampered with; The machine learning algorithm in step 4.1 is implemented using random forest and support vector machine, and features of the multi-dimensional data collected in step 3 are extracted and analyzed to explore the changing rules and correlation features of temperature, pressure, gas component concentration, voltage, and current parameters during the thermal runaway process, and establish a thermal runaway early warning indicator system integrating multiple parameters; Step 4.2 combines the real-time collected data to determine whether there is a risk of thermal runaway and issue an early warning, with an early warning accuracy rate greater than 95%.

10. The detection method according to claim 9, characterized in that: The early warning module (5) is specifically composed of a display screen body (51) and an audible and visual alarm (52), wherein the early warning module (5) is communicatively connected to the output end of the data processing and analysis module (4), and the display screen body (51) is set to display the monitoring parameters of the energy storage battery module (1) in real time, specifically including: temperature distribution cloud map, pressure change curve, gas component concentration bar graph, voltage and current waveform graph, thermal runaway warning information and thermal runaway simulation analysis results.

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