电工技术学报  2019, Vol. 34 Issue (19): 3968-3978    DOI: 10.19595/j.cnki.1000-6753.tces.181206
电工理论与新技术 |
基于短时搁置端电压压降的快速锂离子电池健康状态预测
郭永芳1, 黄凯2, 李志刚2
1. 河北工业大学人工智能与数据科学学院 天津 300130;
2. 省部共建电工装备可靠性与智能化国家重点实验室(河北工业大学) 天津 300130
Fast State of Health Prediction of Lithium-Ion Battery Based on Terminal Voltage Drop During Rest for Short Time
Guo Yongfang1, Huang Kai2, Li Zhigang2
1. School of Artificial Intelligence Hebei University of Technology Tianjin 300130 China;
2. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300130 China