基于非线性观测器的超级电容器荷电状态在线估计

doi:10.16183/j.cnki.jsjtu.2021.210

上海交通大学学报 ›› 2022, Vol. 56 ›› Issue (12): 1630-1637.doi: 10.16183/j.cnki.jsjtu.2021.210

所属专题：《上海交通大学学报》2022年“电子信息与电气工程”专题

基于非线性观测器的超级电容器荷电状态在线估计

杜宇石¹^,², 琚长江¹^,²(), 杨根科¹^,²

1.上海交通大学宁波人工智能研究院, 浙江宁波 315000
2.上海交通大学自动化系, 上海 200240

收稿日期:2021-06-15 出版日期:2022-12-28 发布日期:2023-01-05
通讯作者: 琚长江 E-mail:juchangjiang@sjtu.edu.cn.
作者简介:杜宇石(1997-), 男, 甘肃省庆阳市人, 硕士生, 从事电池能量控制管理系统研究.
基金资助:
国家重点研发计划(2020YFB1711200)

Online Estimation of Supercapacitor State of Charge Based on Nonlinear Observer

DU Yushi¹^,², JU Changjiang¹^,²(), YANG Genke¹^,²

1. Ningbo Artificial Intelligence Institute, Shanghai Jiao Tong University, Ningbo 315000, Zhejiang,China
2. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China

Received:2021-06-15 Online:2022-12-28 Published:2023-01-05
Contact: JU Changjiang E-mail:juchangjiang@sjtu.edu.cn.

摘要/Abstract

摘要：

超级电容器具有快速充放、高功率密度和长寿命等优点, 被广泛用于新能源汽车的储能系统. 系统可靠运行需获取其剩余电量, 即对其荷电状态(SOC)进行估算. 依托超级电容单体的等效模拟电路模型, 建立了以模型中多电容端电压为状态, 电容器输入电流为控制输入, 电容器输出电压为观测输出的电容器二阶非线性系统的状态空间模型, 包含了自放电现象产生的泄漏电流的因素. 为提高模拟精度, 辨识不同的模型参数,分别刻画充电和放电工况. 采用非线性观测器算法来获取模型内部状态从而实现对SOC的估计. 充放电实验的结果表明, 考虑泄漏因素和建立不同参数下的充放电模型, 能够更好地模拟超级电容器的动态特性, 同时验证了非线性观测器算法具有稳定的跟踪能力.

关键词: 超级电容器, 荷电状态估计, 非线性观测器, 泄漏电流

Abstract:

Supercapacitors have the advantages of fast charging and discharging, high power density, and long life, which are widely used in energy storage systems for new energy vehicles. Reliable operation of the system requires the acquisition of its remaining electricity, which is to estimate its state of charge (SOC). Relying on the equivalent analog circuit model of a single supercapacitor, this paper establishes a state-space model of the capacitor second-order nonlinear system with the multi-capacitor terminal voltage in the model as the state, the capacitor input current as the control input, and the capacitor output voltage as the observation output, and contains the leakage current caused by the self-discharge phenomenon. In order to improve the simulation accuracy, different model parameters were identified to characterize the charging and discharging conditions. In this paper, a nonlinear observer algorithm is used to obtain the internal state of the model to realize the estimation of SOC. The results of the charging and discharging experiment show that considering the leakage factor and establishing the charging and discharging model with different parameters, the dynamic characteristics of the supercapacitor can be better simulated, and the nonlinear observer algorithm has a stable tracking ability.

Key words: supercapacitor, state of charge (SOC) estimation, nonlinear observer, leakage current

中图分类号:

TP13
TK 01+8

杜宇石, 琚长江, 杨根科. 基于非线性观测器的超级电容器荷电状态在线估计[J]. 上海交通大学学报, 2022, 56(12): 1630-1637.

DU Yushi, JU Changjiang, YANG Genke. Online Estimation of Supercapacitor State of Charge Based on Nonlinear Observer[J]. Journal of Shanghai Jiao Tong University, 2022, 56(12): 1630-1637.

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参考文献 16

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模型类别	R₀/Ω	R₂/Ω	R_l/Ω	C₀/F	k/ (F·V^-1)	C₂/F
单一模型	0.000 63	0.5	3 000	28 000	350	500
充电模型	0.001 5	0.000 05	3 000	28 000	440	2 000
放电模型	0.000 53	0.8	3 000	28 000	400	0.1

模型类别	ME	MAE	RMSE
单一模型	2.493	0.748	1.065
充电模型	0.184	0.107	0.122

模型类别	ME	MAE	RMSE
不考虑泄漏	7.776	3.653	4.290
考虑泄漏	0.184	0.108	0.123

模型类别	ME	MAE	RMSE
单一模型	2.087	0.731	0.962
放电模型	0.303	0.190	0.214

模型类别	ME	MAE	RMSE
不考虑泄漏	3.744	2.097	2.365
考虑泄漏	0.303	0.195	0.217

基于非线性观测器的超级电容器荷电状态在线估计

Online Estimation of Supercapacitor State of Charge Based on Nonlinear Observer

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