Lithium-Ion Battery Intelligent Sensing Monitoring and Early Warning Technology
Ma Jingxuan1, Lai Yilin2, Lü Nawei1, Jiang Xin1, Jin Yang1
1. School of Electrical and Information Engineering Zhengzhou University Zhengzhou 450001 China; 2. China Electric Power Research Institute Beijing 100192 China
Abstract：Advanced battery technology is an important technical means for human beings to cope with the global climate change challenges and energy crisis, especially in recent years, the rapid development of the electric vehicle industry and large-scale energy storage has brought a huge market for the lithium-ion battery industry. However, the rapid development of lithium batteries is accompanied by many problems and challenges. The high energy density of electrode materials creates poor thermal stability, resulting in a certain probability of failure of lithium batteries during use or storage, including capacity degradation, accelerated self-discharge, shortened cycle life, thermal runaway, etc., which seriously affects the consistency, reliability, and safety of the batteries in use. In recent years, there have been a number of fire and explosion accidents in various scales of energy storage systems, such as electric vehicles and energy storage power stations at home and abroad, which indicates that the existing means of monitoring the safety status of batteries are insufficient, and there is an urgent need for intelligent sensing and early warning technologies with a wider range of monitoring dimensions and more reliable detection strength. Therefore, the use of intelligent sensing technology to identify and sense the multi-dimensional physical and chemical characteristics (electric, thermal, gas, acoustic, optical, pressure, magnetic, etc.) of the early characterisation of battery failures, online monitoring and diagnosis of the battery safety status, and early warning of battery failures can greatly reduce the rate of battery failures and the incidence of accidents. Firstly, based on the investigation of lithium-ion battery degradation and failure process, the generation and evolution mechanism of multi-dimensional characteristic signals of lithium batteries are outlined. Li-ion batteries are prone to a series of failures such as lithium precipitation, temperature rise, gas production, diaphragm puncture, short circuit, etc., and exhibit typical failure behaviours such as external battery deformation, temperature rise, gas production, liquid leakage, safety valve opening, thermal runaway and other typical failure behaviours under the abusive conditions such as overcharging, overheating, short-circuiting, and collision, which result in the uninterrupted failure of the battery's internal material structure with the continuous degradation and aging of the battery's performance. Taking the thermal runaway overcharge of commercial lithium-ion batteries as an example, the deterioration process of lithium batteries is described in four stages and the generation mechanism of multi-dimensional physical and chemical characteristic parameters, such as electrical signals, temperature signals, gas signals, sound signals, light signals, pressure signals, magnetic signals, etc., is elaborated. Based on this, multi-dimensional sensing technologies such as electrical, temperature, gas, sound, optical, pressure, electromagnetic, etc. are introduced, existing research results are comprehensively researched and reviewed, and their advantages and disadvantages in terms of lithium-ion battery fault early warning time, realisation technological difficulty, identification accuracy, monitoring range, cost, etc. are compared. From the above analysis and discussion, the main challenges facing the development of intelligent sensing monitoring and early warning technology for lithium-ion batteries are summarised, such as the difficulty of sensor implantation, the vulnerability of sensors to damage, the integration of multi-parameter sensing technology, etc. Meanwhile, it is proposed that the future development of lithium-ion batteries' intelligent sensing monitoring and early warning technology should be directed towards the development of multi-parameter integration, the development of smarter sensors, the enhancement of the implantation of sensors and the packaging of batteries, and the strengthening of the implementation of multi-parameter sensing technology. We also propose that the future development of lithium-ion battery intelligent sensing monitoring and early warning technology should be towards multi-parameter integration, develop smarter sensors, improve sensor implantation and battery packaging technology, and strengthen the implementation of multi-parameter sensing technology.
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