Research And Implementation Of A Thermal Runawayalarm System For Lithium Batteries Based On Thermal Imaging

With the continuous development of new energy,the value of lithium batteries is constantly increasing,while lithium batteries are widely used,their safety also needs to be taken seriously.As an energy source that provides power for equipment,Lithium batteries often encounter safety issues.The thermal runaway of lithium batteries can cause immeasurable losses.Therefore,monitoring the thermal runaway of lithium batteries is a very important research direction.The traditional monitoring method for thermal runaway of lithium batteries is to establish a thermal runaway model based on the behavior of heat diffusion during operation,or to use sensors to monitor the process of heat diffusion in the battery.In recent years,with the continuous development of infrared thermal imaging technology,infrared thermal imaging has become one of the important ways to monitor the thermal runaway of lithium batteries.Infrared thermal imaging can safely measure the temperature of extremely hot objects and collect real-time temperature change data of objects.This article establishes a lithium battery thermal runaway alarm system through infrared thermal imaging,analyzes the thermal runaway process of lithium batteries,and designs a lithium battery thermal runaway alarm system in Pycharm using Python language.The system consists of three modules: image acquisition module,image processing module,and thermal runaway alarm module.In the image acquisition module,infrared thermal imaging is used to capture the process of heat diffusion on the battery surface,recording the entire process from heat generation to thermal runaway of the lithium battery.In the image processing module,an improved grey wolf two-dimensional inter class variance(OTSU)image segmentation algorithm is first proposed.After improving the initialization population strategy and group position update strategy of the Grey Wolf algorithm,the improved Grey Wolf algorithm is used to optimize the threshold of two-dimensional OTSU and find the optimal threshold of image segmentation.Using the improved Grey Wolf twodimensional OTSU algorithm for image segmentation of lithium battery thermal imaging,then the battery shell area and high temperature area on the battery surface are segmented,and the location features of the high temperature area are extracted.In the thermal runaway alarm module,a lithium battery thermal runaway alarm mechanism has been designed.First,determine the location of the high-temperature area on the surface of the lithium battery thermal imaging after segmentation using the improved Grey Wolf two-dimensional OTSU algorithm,and determine whether the battery is in a state of overcharge,external short circuit,or internal diaphragm thermal puncture.After determining the state of the battery,analyze the area change and area change rate of the high-temperature area on the battery surface during its heat propagation process,and set the corresponding area size threshold and area change rate threshold.When the size and rate of change of the hightemperature area during the heat transfer process of the battery exceed the thermal runaway threshold,a thermal runaway alarm will be triggered and the alarm information will be displayed on the system interface.This study shows that the system has a high accuracy in detecting the thermal runaway state of lithium batteries,and can achieve real-time monitoring of batteries and thermal runaway alarms.