Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review

Md Ohirul Qays; Yonis Buswig; Md Liton Hossain; Ahmed Abu-Siada

doi:10.17775/CSEEJPES.2019.03060

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review

Regular Papers | 更新时间：2026-10-15

- Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review
- Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review
- 中国电机工程学会电力与能源系统学报(英文) 2022年8卷第1期页码：105-114
- 作者机构：
  
  1. Faculty of Engineering, Universiti Malaysia Sarawak, Kota Samarahan,Malaysia
  2. Department of Electrical and Computer Engineering, Curtin University,WA,Perth,Australia
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2019.03060
  中图分类号：
- 纸质出版：2022-01-01
- 稿件说明：
移动端阅览
Md Ohirul Qays, Yonis Buswig, Md Liton Hossain, 等. Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(1):105-114.

Md Ohirul Qays, Yonis Buswig, Md Liton Hossain, et al. Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review[J]. CSEE Journal of Power and Energy Systems, 2022, 8(1): 105-114.
Md Ohirul Qays, Yonis Buswig, Md Liton Hossain, 等. Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(1):105-114. DOI： 10.17775/CSEEJPES.2019.03060.

Md Ohirul Qays, Yonis Buswig, Md Liton Hossain, et al. Recent progress and future trends on the state of charge estimation methods to improve battery-storage efficiency: A review[J]. CSEE Journal of Power and Energy Systems, 2022, 8(1): 105-114. DOI： 10.17775/CSEEJPES.2019.03060.

摘要

Abstract

Battery storage systems are subject to frequent charging/discharging cycles

which reduce the operational life of the battery and reduce system reliability in the long run. As such

several Battery Management Systems (BMS) have been developed to maintain system reliability and extend the battery's operative life. Accurate estimation of the battery's State of Charge (SOC) is a key challenge in the BMS due to its non-linear characteristics. This paper presents a comprehensive review on the most recent classifications and mathematical models for SOC estimation. Future trends for SOC estimation methods are also presented.

关键词

Keywords

references

浏览量

106

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

Online identification of power battery parameters for electric vehicles using a decoupling multiple forgetting factors recursive least squares method

Neural Network Model with Cascaded Structure for State-of-Charge Estimation in Lithium-Ion Batteries

Distributed Unknown Input and State Estimation for Nonlinear Multi-Agent Systems with Applications to Battery Management

Capacity Configuration of Energy Storage Systems for Echelon Utilization Based on Accelerated Life Test in Microgrids

Adjustable Robust Sizing and Operation Co-Optimization for Grid-Connected LVDC Systems with Photovoltaic and Battery