锂离子电池全生命周期的动静态荷电状态估算方法

赵剑坤; 陈世龙; 杨乃兴; 魏路路; 王琼; 陈文辉

doi:10.7652/xjtuxb202410004

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锂离子电池全生命周期的动静态荷电状态估算方法

专题电动车辆先进电池管理 | 更新时间：2025-07-28

- 锂离子电池全生命周期的动静态荷电状态估算方法
- Dynamic and Static State-of-Charge Estimation Method for the Full Lifecycle of Lithium-Ion Batteries
- 西安交通大学学报 2024年58卷第10期页码：44-50
- 作者机构：
  
  1. 西安建筑科技大学机电工程学院,西安,710055
  2. 陕西省纳米材料与技术重点实验室,西安,710055
- 作者简介：
  
  : 2024-04-30。作者简介: 赵剑坤(1999—),男,硕士生
  杨乃兴(通信作者),男,副教授,硕士生导师。基金项目: 陕西省自然科学基金资助项目(2023-JC-YB-322)
- 基金信息：
  
  : 2024-04-30。作者简介: 赵剑坤(1999—),男,硕士生;杨乃兴(通信作者),男,副教授,硕士生导师。基金项目: 陕西省自然科学基金资助项目(2023-JC-YB-322);陕西省重点研发计划资助项目(2024GX-YBXM-435)。
- DOI：10.7652/xjtuxb202410004
  中图分类号： TM912
- 网络首发：2024-10-10，
  
  纸质出版：2024
- 稿件说明：
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赵剑坤, 陈世龙, 杨乃兴, 等. 锂离子电池全生命周期的动静态荷电状态估算方法[J]. 西安交通大学学报, 2024,58(10):44-50.

ZHAO Jiankun, CHEN Shilong, YANG Naixing, et al. Dynamic and Static State-of-Charge Estimation Method for the Full Lifecycle of Lithium-Ion Batteries[J]. 2024, 58(10): 44-50.
赵剑坤, 陈世龙, 杨乃兴, 等. 锂离子电池全生命周期的动静态荷电状态估算方法[J]. 西安交通大学学报, 2024,58(10):44-50. DOI： 10.7652/xjtuxb202410004.

ZHAO Jiankun, CHEN Shilong, YANG Naixing, et al. Dynamic and Static State-of-Charge Estimation Method for the Full Lifecycle of Lithium-Ion Batteries[J]. 2024, 58(10): 44-50. DOI： 10.7652/xjtuxb202410004.

摘要

针对电池荷电状态(SOC)估算方法难以在其全生命周期内保持较高精度的问题

提出一种考虑电池衰退的动静态SOC估算方法。在静态SOC估算时

通过电池健康状态(SOH)对电池有效容量进行修正

考虑电池衰退对容量的影响; 在动态SOC估算时

利用在线求解锂扩散方程

获得当前锂离子电池的可用有效容量

并同时考虑电池的容量衰退及电流和温度对放电容量的影响。通过在LabVIEW平台搭建上述动静态SOC估算方法求解程序

对电池在美国联邦城市驾驶工况下充放电循环过程中的动静态SOC进行了估算

结果表明:电池静态SOC始终高于其动态SOC

且温度越低

电流越大

动静态SOC的误差也越大; 在新电池容量由100%衰减到58%的充放电循环过程中

电池动态SOC的最大估算误差均低于2.0%

表明所提出的SOC估算方法能够实现电池全生命周期SOC的准确估算。研究结果可为车用动力电池全生命周期的高效和安全管控提供支撑。

Abstract

Maintaining accurate state-of-charge(SOC)estimation throughout the entire battery lifecycle poses a challenge. To address this challenge

a novel dynamic and static SOC estimation method is proposed

taking into account battery degradation. In static SOC estimation

the battery's effective capacity is adjusted based on its state of health(SOH)to compensate for capacity degradation. For dynamic SOC estimation

an online solution of the lithium diffusion equation is employed to determine the available effective capacity of the lithium-ion battery

considering the effects of capacity degradation

current

and temperature on discharge capacity. The proposed dynamic and static SOC estimation method is implemented as a solver on the LabVIEW platform

and dynamic and static SOC estimation is performed for battery operation under the federal urban driving schedule and charge-discharge cycling processes. The results highlight that the static SOC consistently exceeds the dynamic SOC

with estimation errors increasing under lower temperatures and higher currents. Throughout the charge-discharge cycling process

from a new battery at 100% capacity to 58% capacity

the maximum estimation error for dynamic SOC remains below 2.0%

demonstrating the accuracy of the proposed SOC estimation method across the battery's lifecycle. These findings provide valuable support for the efficient and safe management of automotive battery systems throughout their entire lifespan.

关键词

Keywords

references

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