基于贝叶斯决策的电池模型参数辨识方法

doi:10.3969/j.issn.1008-0198.2024.04.003

湖南电力 ›› 2024, Vol. 44 ›› Issue (4): 20-26.doi: 10.3969/j.issn.1008-0198.2024.04.003

• 特约专栏：新能源发电与储能技术 • 上一篇下一篇

基于贝叶斯决策的电池模型参数辨识方法

张兴伟^1,2, 单周平³, 刘立洪¹, 刘璐雨⁴, 周鲲¹, 冷照进¹

1.湖南经研电力设计有限公司,湖南长沙 410007;
2.规模化电池储能应用技术湖南省工程研究中心,湖南长沙 410001;
3.国网湖南省电力有限公司经济技术研究院,湖南长沙 410007;
4.湖南大学电气工程学院,湖南长沙 410082

收稿日期:2024-04-01 修回日期:2024-05-07 出版日期:2024-08-25 发布日期:2024-09-09
作者简介:张兴伟(1988),男,工程师,从事储能、能源电力规划研究工作。
基金资助:
国网湖南省电力有限公司科技项目(5216A222000Z)

Parameter Identification Method for Battery Model Based on Bayesian Decision-Making

ZHANG Xingwei^1,2, SHAN Zhouping³, LIU Lihong², LIU Luyu⁴, ZHOU Kun¹, LENG Zhaojin¹

1. Hunan Economic Institute Electric Power Design Co.,Ltd.,Changsha 410007,China;
2. Hunan Engineering Research Center of Large-Scale Battery Energy Storage Application Technology, Changsha 410001,China;
3. State Grid Hunan Electric Power Company Limited Economic and Technological Research Institute, Changsha 410007,China;
4. School of Electrical Engineering, Hunan University, Changsha 410082, China

Received:2024-04-01 Revised:2024-05-07 Online:2024-08-25 Published:2024-09-09

摘要/Abstract

摘要： 为实现储能电池模组(battery module,BM)等效电路模型参数估计精度和复杂度的平衡,考虑BM内单体电池内阻、容量等参数的不一致,结合串/并联电路基本特性,提出一种基于贝叶斯决策理论的BM等效电路模型辨识方法,通过引入贝叶斯信息准则估计最优模型参数。采用简化建模法、整体建模法和组合建模法在MATLAB/Simulink中搭建两并联两串联的BM等效电路模型,在恒流放电和动态应力测试工况中进行仿真与验证,结果表明,基于三阶RC、多项式函数拟合项数为3的组合建模法具有较高精度,在动态应力测试工况中模型误差不超过1.97%,验证了所提BM模型参数辨识方法的有效性和准确性,为解决多类型储能高精度等效电路模型问题提供有效方法。

关键词: 电池模组, 贝叶斯信息准则, 等效模型, 参数辨识

Abstract: In order to balance the parameter estimation accuracy and computational complexity of the equivalent circuit model of battery module (BM), an identification method of BM equivalent circuit model based on Bayesian decision theory is proposed, considering the inconsistency of internal resistance, capacity and other parameters of single battery in BM, combined with the basic characteristics of series/parallel circuits. Bayesian information criterion is introduced to estimate the optimal model parameters. The simplified modeling method, the overall modeling method and the combined modeling method are used to build two parallel and two series connection of BM equivalent circuit models in MATLAB/Simulink, and the simulation and verification are carried out in the constant current discharge and dynamic stress test conditions. The results show that the combination modeling method based on third-order RC and polynomial function fitting terms of 3 has high accuracy, and the model error does not exceed 1.97% in the dynamic stress test condition, which verifies the validity and accuracy of the proposed method of identifying the model parameters of the BM model, and provides an effective method for solving the high-precision equivalent circuit model of multiple types of energy storage.

Key words: battery module, Bayesian decision theory, equivalent model, parameter identification

中图分类号:

TM910.1

张兴伟, 单周平, 刘立洪, 刘璐雨, 周鲲, 冷照进. 基于贝叶斯决策的电池模型参数辨识方法[J]. 湖南电力, 2024, 44(4): 20-26.

ZHANG Xingwei, SHAN Zhouping, LIU Lihong, LIU Luyu, ZHOU Kun, LENG Zhaojin. Parameter Identification Method for Battery Model Based on Bayesian Decision-Making[J]. Hunan Electric Power, 2024, 44(4): 20-26.

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基于贝叶斯决策的电池模型参数辨识方法

Parameter Identification Method for Battery Model Based on Bayesian Decision-Making

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