Progress of model based SOC and SOH estimation methods for lithium-ion battery

doi:10.11949/j.issn.0438-1157.20171097

Abstract

Abstract:

Battery management system (BMS) is an important way to ensure the efficient, reliable and safety operation of lithium-ion battery system. Among the BMS functions, estimation of battery states, especially the state of charge (SOC) and state of health (SOH), is critical to the overall performance. They are not only directly related to battery safety operation during the whole life, but also sever as the urgent prerequisite for implementing other facilities. We reviewed the domestic and foreign development of model-based battery state estimation methods, including battery model and estimation methods of SOC and SOH, in the hope of providing some inspirations to the research in this field.

Key words: lithium-ion battery, battery management system, battery model, state of charge estimation, state of health estimation

摘要：

电池管理系统是保证锂离子电池高效、安全运行的重要手段。在电池管理系统功能中，电池状态估计，特别是荷电状态（state of charge，SOC）估计和健康状态（state of health，SOH）估计至关重要。SOC/SOH不仅与全生命周期内电池安全运行直接相关，也是其他功能有效实现的必要前提。本文围绕模型类电池状态估计方法，综述了国内外在锂离子电池模型构建、SOC及SOH估计方法方面的研究进展；指出了模型类状态估计方法存在的难点和局限，提出了今后研究重点。

关键词: 锂离子电池, 电池管理系统, 电池模型, 荷电状态估计, 健康状态估计

CLC Number:

TM912

SHEN Jiani, HE Yijun, MA Zifeng. Progress of model based SOC and SOH estimation methods for lithium-ion battery[J]. CIESC Journal, 2018, 69(1): 309-316.

沈佳妮, 贺益君, 马紫峰. 基于模型的锂离子电池SOC及SOH估计方法研究进展[J]. 化工学报, 2018, 69(1): 309-316.

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