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

SHEN Jiani; HE Yijun; MA Zifeng

doi:10.11949/j.issn.0438-1157.20171097

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

更新时间：2025-12-10

- Progress of model based SOC and SOH estimation methods for lithium-ion battery
- CIESC Journal Issue 1, Pages: 309-316(2018)
- 作者机构：
  
  1. 上海交通大学化工系,上海,200240
  2. 上海电化学能源器件工程技术中心,上海,200240
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20171097
  CLC： M912
- Online First：05 January 2018，
  
  Published：05 January 2018
- 稿件说明：
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SHEN Jiani, HE Yijun, MA Zifeng. Progress of model based SOC and SOH estimation methods for lithium-ion battery[J]. CIESC Journal, 2018, (1): 309-316.
DOI：

SHEN Jiani, HE Yijun, MA Zifeng. Progress of model based SOC and SOH estimation methods for lithium-ion battery[J]. CIESC Journal, 2018, (1): 309-316. DOI： 10.11949/j.issn.0438-1157.20171097.

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。

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.

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