基于瞬态模型的超级电容状态估计
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(1.国网黑龙江省电力有限公司电力科学研究院 ,黑龙江 哈尔滨 150030; 2.哈尔滨工业大学电 气工程及自动化学院 ,黑龙江 哈尔滨 150001; 3.黑龙江工程学院电气与信息工程学院 ,黑龙江 哈尔滨 150050)

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通讯作者:

段建东(1985—),男,博士,教授,主要从事储能系统管理、储能与电力变换等研究;E-mail:duanjiandong@hit.edu.cn

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TM53

基金项目:

国家自然科学基金(52177211);黑龙江省博士后科研启动项目(LBH-Q20020)


State estimation of supercapacitor based on transient model
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(1. Electric Power Research Institute , State Grid Heilongjiang Electric Power Co ., Ltd., Harbin 150030, China; 2. School of Electrical Engineering and Automation , Harbin Institute of Technology , Harbin 150001, China; 3. College of Electrical and Information Engineering , Heilongjiang Institute of Technology , Harbin 150050, China)

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    摘要:

    超级电容多支路模型能够较准确地描述 超级电容充放电特性,但在利用其进行超级电容状态估计时,难以获取准确参数,易导致状态估计结果存在较大误差。为了提升瞬态过程中超级电容参数辨识和状态估计的准确性,提出了基于瞬态模型的扩展卡尔曼滤波 (extended Kalman filter,EKF)–自适应无迹卡尔曼滤波 (adaptive unscented kalman filter,AUKF)状态估计算法。首先,分析了快速充放电情形下的模型简化可行性,在可行性成立的情况下对多支路模型进行简化;其次,将模型参数作为扩展状态加入状态方程中,采用 EKF-AUKF 算法同时估计超级电容等效电路参数和状态;最后,通过仿真和实验验证了所提方法的准确性。实验结果表明,基于瞬态模型的EKF-AUKF 算法能够实现准确的参数辨识和状态估计。

    Abstract:

    The multi-branch model of a supercap acitor can accurately describe the charge and discharge characteristics of a supercapacitor,but it is difficult to obtain the exact parameters when it is used to estimate the state of the supercapacitor,resulting in large errors in the state estimation results.In order to improve the accuracy of supercapacitor parameter identification and state estimation in the transient process,a state estimation algorithm combining an extended Kalman filter (EKF) and an adaptive unscented Kalman filter (AUKF) based on a transient model is proposed.Firstly,the model simplification feasibility in the case of fast charge and discharge is analyzed,and the multi-branch model is simplified when the feasibility is established.Secondly,the model parameters are added into the state equation as extended states,and the EKF-AUKF algorithm is used to estimate the equivalent circuit parameters and states of the supercapacitor simultaneously.Finally,the accuracy of the EKF-AUKF algorithm is validated by simulation and experiment.The experimental results show that the EKF-AUKF algorithm based on the transient model can achieve accurate parameter identification and state estimation.

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引用本文

荣爽,陈晓光,关万琳,等.基于瞬态模型的超级电容状态估计[J].电力科学与技术学报,2026,41(1):185-193.
RONG Shuang, CHEN Xiaog uang, GUAN Wanlin, et al. State estimation of supercapacitor based on transient model[J]. Journal of Electric Power Science and Technology,2026,41(1):185-193.

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  • 收稿日期:2024-11-04
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  • 在线发布日期: 2026-02-11
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