Review of RUL Prediction Method for Lithium-ion Batteries

doi:10.19678/j.issn.1000-3428.0055169

Abstract

Abstract: With the rapid growth and popularization of electronic devices and electric vehicles,how to guarantee the safety and stability of lithium-ion batteries becomes an important topic of relevant research,in which the Remaining Useful Life(RUL) of batteries becomes one of the most critical means to monitor the state of batteries.During the charge-discharge cycles,lithium-ion batteries undergo an irreversible process that can cause continuous degradation on battery capacity and end up in battery malfunction.In order to perform reasonable charge-discharge management that can meet the high reliability requirements in actual applications,this paper conducts a research on the RUL prediction in the using process of lithium-ion batteries.Four RUL prediction methods are expounded herein, which are based on mechanism model,data driven,mechanism and data driven fusion and data driven model fusion respectively,and the advantages and disadvantages of RUL prediction methods based on data driven are discussed.Moreover,the future research direction and trends are also summarized and predicted herein.

Key words: electric vehicles, lithium-ion batteries, Remaining Useful Life(RUL), data driven, model fusion method

摘要： 随着电子设备的增长和电动车辆的普及，保障锂离子电池的安全和稳定成为研究人员的重要课题，其中电池的剩余使用寿命（RUL）为监测电池的手段之一。锂离子电池在其充放电循环期间会经历不可逆过程，可使电池容量持续衰减，最终导致电池故障，为进行合理的充放电管理，满足实际应用中的高可靠性要求，对使用过程中的RUL预测进行研究，介绍对锂电池RUL预测的基于机理模型、基于数据驱动、基于机理模型与数据驱动融合和基于数据驱动的模型融合等4种方法，并讨论基于数据驱动的各RUL预测方法的优缺点，总结并展望未来研究方向和发展趋势。

关键词: 电动汽车, 锂离子电池, 剩余使用寿命, 数据驱动, 模型融合方法

CLC Number:

TP391

LIU Yuefeng, ZHANG Gong, ZHANG Chenrong, ZHANG Lina, YANG Yuhui. Review of RUL Prediction Method for Lithium-ion Batteries[J]. Computer Engineering, 2020, 46(4): 11-18.

刘月峰, 张公, 张晨荣, 张丽娜, 杨宇慧. 锂离子电池RUL预测方法综述[J]. 计算机工程, 2020, 46(4): 11-18.

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