A THERMAL EMIGRATION DETECTION SYSTEM

Abstract

This invention relates to a system (1) that enables the detection of thermal diffusion to ensure the thermal safety of batteries used in energy storage systems.

Description

1 TARIFF A THERMAL EMIGRATION DETECTION SYSTEM Technical Area 5 This invention improves the thermal safety of batteries used in energy storage systems. It relates to a system that enables the detection of thermal radiation in order to provide this. Previous Tech 10 Lithium-ion batteries are preferred because of their high energy density and long lifespan. It is widely used in energy storage systems. Batteries pose a serious safety risk, especially in the event of thermal runaway. They carry risks. Thermal propagation, 15 in a cell This occurs when the thermal escape that begins spreads rapidly to other cells, and The consequences include fire, explosion, or system failure. Thermal radiation is detected late in the solutions currently in use. Temperature sensors are used in current systems. However, Temperature increase occurs after physical or chemical signs of thermal diffusion appear 20 On the other hand, the sound that occurs in the initial stages of thermal escape, No signs such as smoke or gas emissions are being detected. Furthermore... Today, false positives occur due to detection being done with only one type of sensor. and negative rates are high. This situation leads to unnecessary interventions or spread. This causes it to be overlooked. Only 25 of the solutions used today... Obtaining data from the thermal sensor reveals low data diversity, which means... This makes it difficult to detect early signs of the spread. Finally, the current situation... Because the methods focus on intervention after the spread has begun, they are proactive. The system does not exist. Therefore, these problems are not addressed today. 30 that will overcome and enable early detection of thermal emission. Solutions are needed. 2 Chinese patent CN118418734A, which is included in the prior art. The document states that the vehicle provides an early warning of thermal runaway in a battery. The method and system are discussed. The invention involves multi-source sensors and a An early warning method for thermal runaway in a battery detected by the vehicle and It provides the system. The method includes the following steps: multi-source sensors 5 Generating data on the battery's operating status, which will be determined through this method, Filtering the data, storing the filtered operational status data in a battery. The battery will be detected and identified through the detection model. Capturing the change signal. Battery detection model, to be detected. 10 based on the battery's behavior modes in different operating states It is created through learning and training. Thermal properties in the battery to be identified. Whether a leak has occurred is determined based on the change signal, and When thermal runaway occurs, a predetermined multi-level early warning system is activated. Thermal runaway early warning at different early warning levels according to the warning mechanism. The warning is being implemented. According to this method, machine learning or artificial intelligence 15 Multi-source sensing data is processed and detected using an intelligence algorithm. highly intelligent anomaly detection and failure prediction in the battery to be produced. This is possible. The early warning logic can be dynamically adjusted, thermally. The risk of leakage can be identified earlier and more accurately. The accuracy of the warning is increased by the timing. 20 Brief Description of the Invention The aim of this invention is to address thermal processes, particularly those occurring in lithium-ion batteries. The goal is to create a system that enables early detection of the spread. 25 Detailed Description of the Invention The "Thermal Emission Detection" experiment was conducted to achieve the purpose of this invention. The "System" is shown in the attached figure; this figure is 30 3 Figure 1. Schematic view of a system that is the subject of the invention. The parts shown in the figure are individually numbered, and these numbers correspond to... The equivalents are given below: 1. System 2. Sound sensor 3. Visual sensor 4. Support sensor 5. Processing unit 10 The physical and / or chemical effects of thermal dissipation occurring in battery modules. an invention detection system that enables the detection of symptoms (1), - designed to detect acoustic signals generated in thermal radiation. a small sound sensor (2), 15 - configured to detect visual changes occurring on the battery surface at least one visual sensor (3), -structured to monitor the chemical and physical effects of thermal radiation, at least one of the following: gas sensor, pressure sensor or vibration sensor. a support sensor (4) and 20 - Communicating with sensors (2,3,4) and exchanging data through the established communication. to perform, sound, visual and environmental data with machine learning algorithms to analyze data between sensors (2,3,4) in real time to identify correlations and predict thermal emission risks at an early stage at least one processing unit configured to act and generate alerts (5) 25 It includes. In the system subject to the invention, the sound sensor (2) in (1) the first thermal emission Gas leakage occurring during these stages is due to cell cracking or mechanical deformation. 30 to detect acoustic signals and share them with the processing unit (5) It is configured. Sound sensor (2) a wide range including ultrasonic frequencies 4 It is configured to operate within a frequency range. Sound sensor (2) They are preferably high-precision piezoelectric materials. The system in question (1) includes visual sensors (3) high-speed cameras and At least one of the thermal cameras can detect smoke or light that may form on the battery surface. 5 to detect surface changes in the form of emissions or temperature increases It is structured. Data obtained by the visual sensor (3) are processed in the processing unit (5) It is analyzed with artificial intelligence algorithms. Visual sensor (3) is preferred. Another application is low light detection sensors. The system in question (1) includes the support sensor (4), gas sensor, and pressure sensor. or the chemical and physical effects of thermal radiation, such as in vibration sensors to follow up as a complement and share data with the processing unit (5) It is structured. Data obtained with support sensors (4) are audio and visual. It is used to complete the data obtained by the sensor (2,3). 15 The processing unit (5) in the system that is the subject of the invention (1) collects with sensors (2,3,4) to process audio, visual and supporting data in real time using artificial intelligence and thermal diffusion by detecting data correlations between sensors (2,3,4) It is structured to identify risks at an early stage. Processing unit (5) 20 machine learning algorithms optimized for detecting anomalies to use and estimate the risk level by performing time series analysis It is structuring. Process unit (5) thermal radiation risks and the measures to be taken Keeping a record of proactive intervention methods related to the identified risk. 25 and is configured to stop thermal radiation. The process unit (5) reducing charge level, discharging energy, cooling systems actions such as activating and isolating at-risk cells by enabling it to stop thermal dissipation in the battery module It is structured. The processing unit (5) performs multimodal data analysis and 30 errors. It is configured to significantly reduce alarms. Processing unit (5) to record data from sensors (2,3,4) and for future improvements It is structured to enable analysis for this purpose. The operating unit (5) preferably reports the identified risks and the current status of the battery. a mobile application or interface to present to the user in real time 5 It is configured to include the processing unit (5) so that the battery status along with risk analysis and recommended actions with users or operators. They can share battery modules. This allows users and operators to share information about the battery modules. being informed of the situation immediately and manual intervention when necessary. It can do. The processing unit (5) also adjusts the sensitivity of the sensors (2,3,4) to temperature, 10 Dynamically adjusting according to environmental conditions, which can include humidity and pressure. and by ensuring that accurate data is obtained under all circumstances, the efficiency of the detection process. It is structured to increase. The invention system (1) produces acoustic waves, smoke and light emission and gas and 15 By detecting and analyzing data such as pressure, the battery module... The first signs of thermal diffusion are detected and noticed before thermal escape begins. is done. From the multimodal sensors (2,3,4) used in the system (1). Detection is achieved by combining data and analyzing it with artificial intelligence. Accuracy is being increased and data diversity enhances the security of the system. The same 20 At the time of detection of thermal emission, the system (1) automatically by taking precautions to prevent the risk of thermal radiation from increasing It prevents the physical signs of thermal radiation early on. In this way, the system (1) detects the physical signs of thermal radiation early on. by identifying serious safety risks such as fire, explosion and system failure. It minimizes it. On the other hand, early detection and preventive actions save battery life. It extends battery life by minimizing its negative effects. Thanks to the system (1) that is the subject of the invention, thermal emission can be detected quickly. Actions are taken. In addition, early thermal diffusion in the system (1) detection, reduction of false positives and proactive intervention 30 This eliminates the shortcomings of the previous technique. In this way... 6 system (1) increasing the safety of batteries prevents fire, explosion and other serious It prevents the results. Based on these fundamental concepts, the invention is titled "A Thermal Emission Detection System". It is possible to develop a wide variety of applications related to (1)”, and the invention here is 5 It cannot be limited to the examples given; it is essentially as stated in the claims.

Claims

7 REQUESTS 1. Physical and / or thermal dissipation occurring in battery modules. enabling the detection of chemical signals - Designed to detect acoustic signals generated during thermal radiation, EN 5 a small sound sensor (2), - configured to detect visual changes occurring on the battery surface at least one visual sensor (3), -structured to monitor the chemical and physical effects of thermal radiation, at least 10 which can be gas sensors, pressure sensors or vibration sensors. a support sensor (4) and - Communicating with sensors (2,3,4) and exchanging data through the established communication. to perform, sound, visual and environmental data with machine learning algorithms to analyze data between sensors (2,3,4) in real time To identify correlations and predict thermal emission risks at an early stage. 15 with at least one processing unit (5) configured to act and generate alerts a characterized system (1).

2. Gas release, cell rupture, or other events that occur during the initial stages of thermal diffusion. to detect acoustic signals due to mechanical deformation and with the processing unit (5) 20 The request is characterized by the voice sensor (2) configured to share the voice. A system like the one in 1 (1).

3. Across a wide frequency range, including ultrasonic frequencies. Claim 1 or 25 characterized by the sound sensor (2) configured to work. A system like the one in 2 (1).

4. Sound sensor (2) with high precision piezoelectric materials a system like any of the above characterized demands (1).

5. At least one of the following: high-speed cameras and thermal cameras, with a battery. 8 in the form of smoke, light emission or temperature increase that may occur on its surface with visual sensor (3) configured to detect surface changes a system like any of the above characterized demands (1).

6. Characterized by visual sensors (3) with low light detection sensors 5 a system like any of the above-mentioned requests (1).

7. Thermal radiation from devices such as gas sensors, pressure sensors, or vibration detectors. to complementarily monitor chemical and physical effects and process the data 10 characterized by support sensor (4) configured to share with unit (5) a system like any of the above-mentioned requests (1).

8. Sound, visual and support data collected by sensors (2,3,4) are real. to process data between sensors (2,3,4) with artificial intelligence in real time Identifying thermal emission risks at an early stage by determining their correlations 15 The above is characterized by the processing unit (5) which is structured in accordance with the above. a system like any of the requests (1).

9. Machine learning optimized for detecting anomalies. using algorithms and time series analysis to estimate the risk level 20 The above is characterized by the processing unit (5) which is structured to do so. a system like any of the requests (1).

10. Proactive measures to be taken regarding the risks of thermal radiation. keeping records of the methods, battery module 25 in relation to the identified risk. the necessary proactive intervention to be carried out and thermal emission characterized by the processing unit (5) configured to ensure its stopping. a system like any of the above-mentioned requests (1).

11. Reducing the charge level, discharging energy, activating cooling systems 30 actions such as monitoring and isolating at-risk cells 9 configured to stop thermal dissipation in the battery module by providing any of the above requests characterized by the processing unit (5) such a system (1).

12. To record the data from the sensors (2,3,4) and for the next 5 a processing unit configured to enable analysis for improvements (5) like any of the above-mentioned claims characterized by system (1).

13. The identified risks and the current condition of the battery are reported to the user in real terms. to include a mobile application or interface to deliver in a timely manner from the above requests characterized by the configured processing unit (5) a system like any other (1).

14. The sensitivity of the sensors (2,3,4) can be in the form of temperature, humidity and pressure. 15 Dynamically adjusting according to environmental conditions and providing accurate data in all conditions. structured to increase the efficiency of the detection process by enabling its collection any of the above requests characterized by the processing unit (5) such a system (1).

Images