The purpose of a battery thermal management system (BTMS) is to maintain the battery safety and efficient use as well as ensure the battery temperature is within the safe operating range. The traditional air-cooling-based BTMS not only needs extra power, but it could also not meet the demand of new lithium-ion battery (LIB) packs with high energy density, while liquid cooling BTMS requires complex devices to ensure the effect. Therefore, phase change materials (PCMs)-based BTMS is becoming the trend. By using PCMs to absorb heat, the temperature of a battery pack could be kept within the normal operating range for a long time without using any external power. PCMs could greatly improve the heat dissipation efficiency of BTMS by combining with fillers such as expanded graphite (EG) and metal foam for their high thermal conductivity or coordinating with fins. In addition, PCMs could also be applied in construction materials, solar thermal recovery, textiles and other fields. Herein, a comprehensive review of the PCMs applied in thermal storage devices, especially in BTMS, is provided. In this work, the literature concerning current issues have been reviewed and summarized, while the key challenges of PCM application have been pointed out. This review may bring new insights to the PCM application.

The purpose of this study is to establish a life prediction model of lithium-thiocarbonyl chloride batteries by semi-empirical method. In the experiment, accelerated life tests on several groups of batteries at different temperatures were conducted. After a period of operation in the range from 25 °C to 74 °C, it was found that the higher the temperature, the less the remaining capacity of the batteries. According to the study of the battery aging mechanism, the characteristic parameter impedance of an aging battery would change exponentially with the increase of storage time and environmental temperature. The established life prediction model showed that the change in battery impedance spectrum had a good law, which made it possible to predict the state of charge (SOC) of the battery according to the local change characteristics of the electrochemical impedance spectroscopy (EIS) spectrum. The experimental data were compared with the fitted prediction curve, and the maximum deviation of the prediction was only 4.1036%, which indicated that the constructed model had high accuracy.