基于数据驱动的锂离子电池健康状态估计技术

doi:10.11930/j.issn.1004-9649.202202012

摘要/Abstract

摘要： 电池健康状态（state of health, SOH）是影响锂离子电池大规模应用的关键因素，而基于数据驱动的锂离子健康状态估计方法已经成为当前相关研究的热点课题。为了系统地剖析数据驱动下电池SOH估计方法的关键技术和难点问题，从电池数据来源、特征工程、估计模型以及验证途径4个核心环节出发，综述当前研究的进展。通过多种不同方法基本机理的分析和优缺点对比，凝炼出制约技术发展的瓶颈问题，展望未来研究的重点方向，推动基于数据驱动的锂离子电池SOH估计技术的进一步发展与应用。

关键词: 锂离子电池, 健康状态评估, 数据驱动技术, 特征工程, 回归模型

Abstract: The battery state of health (SOH) is a key factor affecting the large-scale application of lithium-ion batteries, and the data-driven lithium-ion SOH assessment method has become a hot topic in current related research. In order to systematically dissect the key technologies and difficulties of the data-driven battery SOH assessment method, this paper reviews the current research progress from four core links, namely, battery data sources, feature engineering, assessment models, and validation approaches. By analyzing the basic mechanism and comparing the advantages and disadvantages of various methods, this paper pinpoints the bottlenecks that restrict the development of technology and puts forward key directions for future research to promote the development and application of lithium-ion battery SOH assessment based on data-driven technology.

Key words: lithium-ion battery, state of health assessment, data-driven technology, feature engineering, regression model

黎冲, 王成辉, 王高, 鲁宗虎, 马成智. 基于数据驱动的锂离子电池健康状态估计技术[J]. 中国电力, 2022, 55(8): 73-86,95.

LI Chong, WANG Chenghui, WANG Gao, LU Zonghu, MA Chengzhi. Technology of Lithium-Ion Battery State-of-Health Assessment Based on Data-Driven[J]. Electric Power, 2022, 55(8): 73-86,95.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202202012

https://www.electricpower.com.cn/CN/Y2022/V55/I8/73

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