锂离子电池健康状态估计及寿命预测研究进展综述
Review on Health State Estimation and Life Prediction of Lithium-ion Batteries
熊庆 1邸振国 1汲胜昌1
作者信息
- 1. 西安交通大学电工材料电气绝缘全国重点实验室,西安 710049
- 折叠
摘要
随着锂离子电池的应用越来越广泛,锂电池健康状态的精确估计和剩余寿命的实时预测对于锂电池系统的安全运行和降低运维成本具有重要意义.锂电池内部复杂的物理化学反应和外部复杂工作条件,使得实现精准的健康状态估计和寿命预测具有挑战性.该文综述近年来锂电池健康状态估计和剩余使用寿命预测方法的研究现状,分析基于物理/数学模型、数据驱动、模型法和数据驱动融合,以及多种数据驱动融合的锂电池健康状态估计方法的优缺点及适用条件,并对比分析不同数据驱动类型的锂电池寿命预测方法.指出锂电池健康状态估计及寿命预测尚存在的问题,并对未来研究方向进行展望,对完善锂电池健康状态估计和寿命预测算法理论体系、指导实际应用技术具有重要意义.
Abstract
With the increasing application of the Lithium-ion batteries(LIBs),the accurate estimation of state-of-health(SOH)and real-time prediction of the remaining life of an LIB are of great significance to the safe operation of the LIB system and the reduction of the maintenance cost.The complex physical and chemical reactions inside the LIB and the outside complex operating conditions make it a challenge to achieve accurate SOH estimation and life prediction.Conse-quently,we reviewed the research status of methods for the LIB SOH estimation and the remaining useful life(RUL)prediction in recent years.We analyzed the advantages and disadvantages of the LIB SOH estimation methods and suita-ble conditions based on the physical/mathematical model,the data driven,the fusion of model and data driven,and the fusion of multiple data driven methods.We analyzed and compared the LIB life prediction methods of three different da-ta-driven types.Moerover,we pointed out the existing problems of the LIB SOH estimation and the life prediction,and put forward prospects in the future research directions.The conclusions can improve the theoretical system of the LIB SOH estimation and life prediction algorithm and have important significance for the practical application technology.
关键词
锂离子电池/状态估计/寿命预测/电化学模型/数据驱动技术Key words
lithium-ion battery/state estimation/life prediction/electrochemical model/data driven technology引用本文复制引用
基金项目
国家自然科学基金(52007149)
电工材料电气绝缘全国重点实验室项目(EIPE22123)
碑林区科技计划(GX2226)
出版年
2024
国家科技期刊平台
NSTL
万方数据