摘要
准确预测锂离子动力电池的剩余使用寿命(remaining useful life, RUL),确保相关行业和设施的可靠性和安全性具有重要意义。数据驱动方法仅通过实验数据总结电池性能参数变化规律从而预测电池剩余寿命,突破了传统基于模型方法精度低、难以建模、通用性差的局限。首先针对基于数据驱动的锂离子动力电池寿命预测的研究进行分析,归纳总结出锂离子动力电池寿命预测建模思路。其次,分类阐述了各种基于数据驱动的预测方法,并对其优缺点进行了分析。最后,给出了锂离子动力电池剩余寿命预测的发展趋势。
It is important to accurately predict the remaining useful life(RUL)of lithium-ion batteries to ensure the reliability and safety of related industries and facilities.The data-driven approach summarizes the changes of battery performance parameters only through experimental data so as to predict RUL,which breaks through the limitations of traditional model-based methods with low accuracy,difficult modeling and poor generality.The research on data-driven lithium-ion battery RUL prediction was analyzed,and the modeling ideas was summarized.Secondly,various data-driven prediction methods were categorized.Meanwhile,the advantages and disadvantages were analyzed.Finally,the development trend of the remaining life prediction of lithium-ion batteries was given.
作者
王志福
杨忠义
罗崴
卢彦希
WANG Zhi-fu;YANG Zhong-yi;LUO Wei;LU Yan-xi(School of Automation,Guangxi University of Science and Technology,Liuzhou 545000,China;School of Machinery and Vehicle,Beijing Institute of Technology,Beijing 100081,China;School of Mechanical and Automotive Engineering,Guangxi University of Science and Technology,Liuzhou 545000,China)
出处
《科学技术与工程》
北大核心
2023年第15期6279-6289,共11页
Science Technology and Engineering
基金
国家自然科学基金(51775042)
作者简介
第一作者:王志福(1977-),男,汉族,山东青岛人,博士,教授。研究方向:智能电动车动力学、电机驱动系统控制与测试、多域分布式驱动平台等。E-mail:wangzhifu@bit.edu.cn。
