搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

一种基于简化电化学模型的锂电池互联状态观测器

庞辉 张旭

引用本文:
Citation:

一种基于简化电化学模型的锂电池互联状态观测器

庞辉, 张旭

An interconnected state observer for lithium-ion battery based on reduced electrochemical model

Pang Hui, Zhang Xu
PDF
导出引用
  • 锂电池正、负极固相浓度分布以及荷电状态的精确估计对于开发锂电池工作状态的实时监控算法,进而构建高效、可靠的锂电池管理系统具有重要意义.本文基于多孔电极理论和浓度理论,提出基于扩展单粒子模型的锂电池关键内部参数识别的优化模型和方法;在该电化学模型简化的基础上,提出一种基于H∞鲁棒控制理论框架的锂电池新型双向互联观测器,可同时实现对锂电池正、负电极浓度及荷电状态的估计,并通过对比分析不同工况下的仿真结果和实验数据,对所提出的互联观测器性能进行了系统验证.结果表明:所设计的互联观测器能够准确预测锂电池的输出电压和荷电状态,有效提高了锂电池系统模型的动态性能和鲁棒稳定性,为锂电池管理系统的开发奠定了理论基础.
    The accurate estimation of the solid concentration distribution in anode and cathode, and state-of-charge (SOC) for a Li-ion battery cell is significantly important for developing the real-time monitoring algorithm of the Li-ion cell's working operation, and further establishing an efficient and reliable advanced battery management system (BMS). Firstly, according to the porous electrode theory and concentration theory, in this article we present a systematic optimized model and a method of identifying the key internal state parameters based on a Li-ion cell's enhanced single-particle-model (ESPM), in which, an appropriate parameter vector is identified in the typical hybrid-pulse-power-characterization (HPPC) operation scenario by using the parameter sensitivity analysis method, and then this parameter optimization problem is evaluated by genetic algorithm. It is verified that the maximum relative errors of the cell's output voltage for ESPM are 1.92%, 3.18% and 2.86% under HPPC, 1C-discharge and urban dynamometer driving schedule (UDDS) current profiles, respectively. Secondly, by introducing some assumptions and reduction techniques, the battery ESPM is further reduced and then a novel interconnected state observer is proposed through the combination of the reduced ESPM and H∞ robust control theory framework, which can realize the concurrent estimation of solid concentration and SOC in anode and cathode. Finally, the comparative validation and analysis study are conducted by using the experimental data acquired in HPPC and UDDS condition to demonstrate the effectiveness and feasibility of the proposed interconnected observer. The results show that the maximum relative errors of output voltage for the ESPM, the single-electrode concentration observer (Obsv-1) and the proposed interconnected observer (Obsv-2) of Li-ion cell are 2.0%, 3.8% and 2.6%, respectively, under HPPC operation at 23 ℃; under the same input current profile and operating condition, the maximum relative errors of SOC estimation are 2.4%, 4.7% and 3.4%, respectively. Moreover, the maximum relative errors of cell's output voltage for ESPM, Obsv-1 and Obsv-2 model are 1.9%, 3.2% and 2.1%, respectively, and the maximum relative errors of SOC estimation values for these three mathematical models are 2.1%, 4.4% and 3.2%, respectively. It is concluded that the proposed robust observer for a Li-ion cell can accurately predict the output voltage and SOC, and can also improve the dynamic performance and robust stability of Li-ion cell, which provides a solid theoretical foundation for developing the BMS.
      通信作者: 庞辉, huipang@163.com
    • 基金项目: 国家自然科学基金(批准号:51675423)资助的课题.
      Corresponding author: Pang Hui, huipang@163.com
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 51675423).
    [1]

    Huang L, Li J Y 2015 Acta Phys. Sin. 64 108202 (in Chinese) [黄亮, 李建元 2015 物理学报 64 108202]

    [2]

    Cheng J, Li Z, Jia M, Tang Y W, Du S L, Ai L H, Yin B H, Ai L 2015 Acta Phys. Sin. 64 210202 (in Chinese) [程昀, 李劼, 贾明, 汤依伟, 杜双龙, 艾立华, 殷宝华, 艾亮 2015 物理学报 64 210202]

    [3]

    Boovaragavan V, Harinipriya S, Subramanian V 2008 J. Power Sources 183 361

    [4]

    Feng T, Yang L, Zhao X, Zhang H, Qiang J 2015 J. Power Sources 281 192

    [5]

    Zhang X, Lu J, Yuan S, Yang J, Zhou X 2017 J. Power Sources 345 21

    [6]

    Chaoui H, Mejdoubi A E, Gualous H 2017 IEEE Trans. Veh. Technol. 66 2000

    [7]

    Di D, Stefanopoulou A, Fiengo G 2010 J. Dyn. Syst-T. ASME 132 061302

    [8]

    Bartlett A, Marcicki J, Onori S, Rizzoni G, Yang X G, Miller T 2016 IEEE Trans. Contr. Syst. Technol. 24 384

    [9]

    Tanim T R, Rahn C D, Wang C Y 2015 Energy 80 731

    [10]

    Klein R, Chaturvedi N A, Christensen J, Ahmed J, Findeisen R, Kojic A 2013 IEEE Trans. Contr. Syst. Technol. 21 289

    [11]

    Dey S, Ayalew B, Pisu P 2014 Int. Workshop Variable Struct. Syst. Nantes, France, June 29-July 2, 2014 p1

    [12]

    Allam A, Onori S 2018 IEEE Trans. Ind. Electron. 65 7311

    [13]

    Dey S, Ayalew B, Pisu P 2015 IEEE Trans. Contr. Syst. Technol. 23 1935

    [14]

    Moura S J, Chaturvedi N A, Krstic M 2014 J. Dyn. Syst-T. ASME 136 011015

    [15]

    Moura S J, Argomedo F B, Klein R, Mirtabatabaei A, Krstic M 2017 IEEE Trans. Contr. Syst. Technol. 25 453

    [16]

    Forman J C, Moura S J, Stein J L, Fathy H K 2012 J. Power Sources 210 263

    [17]

    Zhang L, Wang L, Hinds G, Chao L, Zheng J, Li J 2014 J. Power Sources 270 367

    [18]

    Li J, Zou L, Tian F, Dong X, Zou Z, Yang H 2016 J. Electrochem. Soc. 163 A1646

    [19]

    Wang Y, Fang H, Sahinoglu Z, Wada T, Hara S 2015 IEEE Trans. Contr. Syst. Technol. 23 948

    [20]

    Pang H 2018 Acta Phys. Sin. 67 058201 (in Chinese) [庞辉 2018 物理学报 67 058201]

    [21]

    Diwakar V D 2009 Ph. D. Dissertation (St. Louis: Washington University)

    [22]

    Marcicki J, Canova M, Conlisk A T, Rizzoni G 2013 J. Power Sources 237 310

    [23]

    Moura S J, Argomedo F B, Klein R, Mirtabatabaei A, Krstic M 2017 IEEE Trans. Contr. Syst. Technol. 25 453

    [24]

    Fan G, Pan K, Canova M, Marcicki J, Yang X G 2016 J. Electrochem. Soc. 163 A666

    [25]

    Smith K, Wang C Y 2006 J. Power Sources 161 628

    [26]

    Speltino C, Domenico D D, Fiengo G, Stefanopoulou A 2009 European Control Conference (ECC) Budapest, Hungary, August 23-26, 2009 p1053

    [27]

    Zhang L Q, Wang L X, Hinds G, Lyu C, Zheng J, Li J F 2014 J. Power Sources 270 367

    [28]

    Valoen L O, Reimers J N 2005 J. Electrochem. Soc. 152 A882

    [29]

    Ahmed R, El Sayed M, Arasaratnam I, Tjong J, Habibi S 2014 IEEE J. Em. Sel. Top. 2 659

    [30]

    Marcicki J, Todeschini F, Onori S, Canova M 2012 American Control Conference (ACC 2012) Montreal, Canada, June 27-29, 2012 p572

    [31]

    Forman J C, Moura S J, Stein J L, Fathy H K 2012 J. Power Sources 210 263

    [32]

    Vanantwerp J G, Braatz R D 2000 J. Process Contr. 10 363

  • [1]

    Huang L, Li J Y 2015 Acta Phys. Sin. 64 108202 (in Chinese) [黄亮, 李建元 2015 物理学报 64 108202]

    [2]

    Cheng J, Li Z, Jia M, Tang Y W, Du S L, Ai L H, Yin B H, Ai L 2015 Acta Phys. Sin. 64 210202 (in Chinese) [程昀, 李劼, 贾明, 汤依伟, 杜双龙, 艾立华, 殷宝华, 艾亮 2015 物理学报 64 210202]

    [3]

    Boovaragavan V, Harinipriya S, Subramanian V 2008 J. Power Sources 183 361

    [4]

    Feng T, Yang L, Zhao X, Zhang H, Qiang J 2015 J. Power Sources 281 192

    [5]

    Zhang X, Lu J, Yuan S, Yang J, Zhou X 2017 J. Power Sources 345 21

    [6]

    Chaoui H, Mejdoubi A E, Gualous H 2017 IEEE Trans. Veh. Technol. 66 2000

    [7]

    Di D, Stefanopoulou A, Fiengo G 2010 J. Dyn. Syst-T. ASME 132 061302

    [8]

    Bartlett A, Marcicki J, Onori S, Rizzoni G, Yang X G, Miller T 2016 IEEE Trans. Contr. Syst. Technol. 24 384

    [9]

    Tanim T R, Rahn C D, Wang C Y 2015 Energy 80 731

    [10]

    Klein R, Chaturvedi N A, Christensen J, Ahmed J, Findeisen R, Kojic A 2013 IEEE Trans. Contr. Syst. Technol. 21 289

    [11]

    Dey S, Ayalew B, Pisu P 2014 Int. Workshop Variable Struct. Syst. Nantes, France, June 29-July 2, 2014 p1

    [12]

    Allam A, Onori S 2018 IEEE Trans. Ind. Electron. 65 7311

    [13]

    Dey S, Ayalew B, Pisu P 2015 IEEE Trans. Contr. Syst. Technol. 23 1935

    [14]

    Moura S J, Chaturvedi N A, Krstic M 2014 J. Dyn. Syst-T. ASME 136 011015

    [15]

    Moura S J, Argomedo F B, Klein R, Mirtabatabaei A, Krstic M 2017 IEEE Trans. Contr. Syst. Technol. 25 453

    [16]

    Forman J C, Moura S J, Stein J L, Fathy H K 2012 J. Power Sources 210 263

    [17]

    Zhang L, Wang L, Hinds G, Chao L, Zheng J, Li J 2014 J. Power Sources 270 367

    [18]

    Li J, Zou L, Tian F, Dong X, Zou Z, Yang H 2016 J. Electrochem. Soc. 163 A1646

    [19]

    Wang Y, Fang H, Sahinoglu Z, Wada T, Hara S 2015 IEEE Trans. Contr. Syst. Technol. 23 948

    [20]

    Pang H 2018 Acta Phys. Sin. 67 058201 (in Chinese) [庞辉 2018 物理学报 67 058201]

    [21]

    Diwakar V D 2009 Ph. D. Dissertation (St. Louis: Washington University)

    [22]

    Marcicki J, Canova M, Conlisk A T, Rizzoni G 2013 J. Power Sources 237 310

    [23]

    Moura S J, Argomedo F B, Klein R, Mirtabatabaei A, Krstic M 2017 IEEE Trans. Contr. Syst. Technol. 25 453

    [24]

    Fan G, Pan K, Canova M, Marcicki J, Yang X G 2016 J. Electrochem. Soc. 163 A666

    [25]

    Smith K, Wang C Y 2006 J. Power Sources 161 628

    [26]

    Speltino C, Domenico D D, Fiengo G, Stefanopoulou A 2009 European Control Conference (ECC) Budapest, Hungary, August 23-26, 2009 p1053

    [27]

    Zhang L Q, Wang L X, Hinds G, Lyu C, Zheng J, Li J F 2014 J. Power Sources 270 367

    [28]

    Valoen L O, Reimers J N 2005 J. Electrochem. Soc. 152 A882

    [29]

    Ahmed R, El Sayed M, Arasaratnam I, Tjong J, Habibi S 2014 IEEE J. Em. Sel. Top. 2 659

    [30]

    Marcicki J, Todeschini F, Onori S, Canova M 2012 American Control Conference (ACC 2012) Montreal, Canada, June 27-29, 2012 p572

    [31]

    Forman J C, Moura S J, Stein J L, Fathy H K 2012 J. Power Sources 210 263

    [32]

    Vanantwerp J G, Braatz R D 2000 J. Process Contr. 10 363

  • [1] 王浩, 曹珊珊, 苏俊豪, 徐海涛, 王震, 郑加金, 韦玮. 基于双包层光纤布拉格光栅传感器的锂电池组温度场监控. 物理学报, 2022, 71(10): 104207. doi: 10.7498/aps.71.20212302
    [2] 李晓杰, 喻云泰, 张志文, 董小瑞. 基于电化学老化衰退模型的锂离子动力电池外特性. 物理学报, 2022, 71(3): 038803. doi: 10.7498/aps.71.20211401
    [3] 谢奕展, 程夕明. 一种求解锂离子电池单粒子模型液相扩散方程的新方法. 物理学报, 2022, 71(4): 048201. doi: 10.7498/aps.71.20211619
    [4] 柳小伟, 宋辉, 郭美卿, 王根伟, 迟青卓. 基于电化学-应力耦合模型的锂离子电池硅/碳核壳结构的模拟与优化. 物理学报, 2021, 70(17): 178201. doi: 10.7498/aps.70.20210455
    [5] 谢奕展, 程夕明. 一种求解锂离子电池单粒子模型液相扩散方程的新方法. 物理学报, 2021, (): . doi: 10.7498/aps.70.20211619
    [6] 李涛, 程夕明, 胡晨华. 锂离子电池电化学降阶模型性能对比. 物理学报, 2021, 70(13): 138801. doi: 10.7498/aps.70.20201894
    [7] 孙凤楠, 冯露, 卜家贺, 张静, 李林安, 王世斌. 应力对锂离子电池中空碳包覆硅负极电化学性能的影响. 物理学报, 2019, 68(12): 120201. doi: 10.7498/aps.68.20182279
    [8] 曾建邦, 郭雪莹, 刘立超, 沈祖英, 单丰武, 罗玉峰. 基于电化学-热耦合模型研究隔膜孔隙结构对锂离子电池性能的影响机制. 物理学报, 2019, 68(1): 018201. doi: 10.7498/aps.68.20181726
    [9] 刘征宇, 杨昆, 魏自红, 姚利阳. 包含液相扩散方程简化的锂离子电池电化学模型. 物理学报, 2019, 68(9): 098801. doi: 10.7498/aps.68.20190159
    [10] 王其钰, 王朔, 周格, 张杰男, 郑杰允, 禹习谦, 李泓. 锂电池失效分析与研究进展. 物理学报, 2018, 67(12): 128501. doi: 10.7498/aps.67.20180757
    [11] 庞辉. 基于扩展单粒子模型的锂离子电池参数识别策略. 物理学报, 2018, 67(5): 058201. doi: 10.7498/aps.67.20172171
    [12] 庞辉. 基于电化学模型的锂离子电池多尺度建模及其简化方法. 物理学报, 2017, 66(23): 238801. doi: 10.7498/aps.66.238801
    [13] 祝大伟, 涂俐兰. 随机扰动下Lorenz混沌系统的自适应同步与参数识别. 物理学报, 2013, 62(5): 050508. doi: 10.7498/aps.62.050508
    [14] 李秀春, 谷建华, 王云岚, 赵天海. 一类带有未知参数的受扰混沌系统的观测器同步. 物理学报, 2011, 60(3): 030505. doi: 10.7498/aps.60.030505
    [15] 侯贤华, 余洪文, 胡社军. 锂离子电池Sn-Al薄膜电极的制备及电化学性能研究. 物理学报, 2010, 59(11): 8226-8230. doi: 10.7498/aps.59.8226
    [16] 马军, 苏文涛, 高加振. Hindmarsh-Rose混沌神经元自适应同步和参数识别的优化研究. 物理学报, 2010, 59(3): 1554-1561. doi: 10.7498/aps.59.1554
    [17] 闫辉, 姜洪源, 刘文剑, Ulannov A. M.. 具有迟滞非线性的金属橡胶隔振器参数识别研究. 物理学报, 2009, 58(8): 5238-5243. doi: 10.7498/aps.58.5238
    [18] 王兴元, 赵 群. 一类不确定延迟神经网络的自适应投影同步. 物理学报, 2008, 57(5): 2812-2818. doi: 10.7498/aps.57.2812
    [19] 吕 翎, 郭治安, 李 岩, 夏晓岚. 不确定混沌系统的参数识别与同步控制器的backstepping设计. 物理学报, 2007, 56(1): 95-100. doi: 10.7498/aps.56.95
    [20] 李国辉, 徐得名, 周世平. 基于状态观测器的参数调制混沌数字通信. 物理学报, 2004, 53(3): 706-709. doi: 10.7498/aps.53.706
计量
  • 文章访问数:  3054
  • PDF下载量:  65
  • 被引次数: 0
出版历程
  • 收稿日期:  2018-07-26
  • 修回日期:  2018-08-26
  • 刊出日期:  2019-11-20

一种基于简化电化学模型的锂电池互联状态观测器

  • 1. 西安理工大学机械与精密仪器工程学院, 西安 710048
  • 通信作者: 庞辉, huipang@163.com
    基金项目: 国家自然科学基金(批准号:51675423)资助的课题.

摘要: 锂电池正、负极固相浓度分布以及荷电状态的精确估计对于开发锂电池工作状态的实时监控算法,进而构建高效、可靠的锂电池管理系统具有重要意义.本文基于多孔电极理论和浓度理论,提出基于扩展单粒子模型的锂电池关键内部参数识别的优化模型和方法;在该电化学模型简化的基础上,提出一种基于H∞鲁棒控制理论框架的锂电池新型双向互联观测器,可同时实现对锂电池正、负电极浓度及荷电状态的估计,并通过对比分析不同工况下的仿真结果和实验数据,对所提出的互联观测器性能进行了系统验证.结果表明:所设计的互联观测器能够准确预测锂电池的输出电压和荷电状态,有效提高了锂电池系统模型的动态性能和鲁棒稳定性,为锂电池管理系统的开发奠定了理论基础.

English Abstract

参考文献 (32)

目录

    /

    返回文章
    返回