恒流
常量(计算机编程)
健康状况
锂(药物)
电压
电池(电)
电流(流体)
离子
荷电状态
国家(计算机科学)
材料科学
计算机科学
电气工程
工程类
化学
功率(物理)
物理
算法
热力学
医学
内分泌学
有机化学
程序设计语言
作者
Nicholas Williard,Wei He,Michael Osterman,Michael Pecht
标识
DOI:10.36001/ijphm.2013.v4i1.1437
摘要
Traditionally, capacity and resistance have been used as the features to determine the state of health of lithium-ion batteries. In the present study, two additional features, the length of time of the constant current and the constant voltage phases of charging were used as additional indicators of state of health. To compare the appropriateness of each state of health feature, batteries were subjected to different discharge profiles and tested to failure. For each cycle, capacity, resistance, length of the constant current charge time and length of the constant voltage charge time were measured and compared based on their usefulness to estimate the state of health. Lastly, all the features were combined to give a fusion result for state of health estimation.
科研通智能强力驱动
Strongly Powered by AbleSci AI