In recent years, battery accidents in electric vehicles and energy storage systems have occurred frequently. In order to solve this problem, researchers have made a lot of attempts and efforts. The main technological approaches can be divided into two routes: 1) safer batteries, such as solid-state batteries; 2) A more intelligent, advanced, and efficient battery management system. Integrating multiple sensing units into intelligent batteries will be one of the means to achieve more advanced battery management systems. By real-time monitoring of multi-dimensional parameters of batteries, combined with technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence, more accurate and efficient battery state estimation, fault diagnosis, and safety warning can be achieved, thereby achieving the goal of "fewer" or even "zero" battery accidents. The article comprehensively summarizes the research progress of various parameter monitoring methods for lithium-ion batteries, and comprehensively analyzes the sensing methods for electrical parameters (current, voltage, internal resistance) and non electrical parameters (temperature, strain, deformation, gas pressure, gas type) of the battery. This article elaborates on the measurement principles of various sensing methods, the installation position of sensors, probe size, sensitivity, resolution and other sensing performance parameters, and systematically discusses the advantages and disadvantages of various sensors, as well as their suitable application scenarios. Finally, a summary and outlook were made from two aspects: multi parameter monitoring inside the battery and the application of multi sensor data.

Source: Sensor Expert Network