欢迎访问《电化学(中英文)》期刊官方网站,今天是

电化学(中英文) ›› 2020, Vol. 26 ›› Issue (3): 370-388.  doi: 10.13208/j.electrochem.190309

• 研究论文 • 上一篇    下一篇

基于伪随机二进制序列的阻抗谱快速重构及其在电化学能源领域的应用

李伟恒1,2, 黄秋安2,*(), 杨维明3, 杨昌平1, 张久俊2,*()   

  1. 1. 湖北大学物理与电子科学学院,湖北 武汉 430062
    2. 上海大学可持续能源研究院,上海 200444
    3. 湖北大学计算机与信息工程学院,湖北 武汉 430062
  • 收稿日期:2019-03-11 修回日期:2019-04-17 出版日期:2020-06-28 发布日期:2020-01-16
  • 通讯作者: 黄秋安,张久俊 E-mail:qiuan_huang@shu.edu.cn;jiujun.zhang@i.shu.edu.cn
  • 基金资助:
    基金国家自然科学基金项目(11674086)

Recent Advancement in Pseudo-Random Binary Sequence Signals-Based Fast Reconstruction of Impedance Spectrum and Its Applications in Electrochemical Energy Sources

LI Wei-heng1,2, HUANG Qiu-an2,*(), YANG Wei-ming3, YANG Chang-ping1, ZHANG Jiu-jun2,*()   

  1. 1. Faculty of Physics & Electronic Science, Hubei University, Wuhan 430062, China
    2. Institute for Sustainable Energy, Shanghai University, Shanghai 200444, China
    3. School of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China
  • Received:2019-03-11 Revised:2019-04-17 Published:2020-06-28 Online:2020-01-16
  • Contact: HUANG Qiu-an,ZHANG Jiu-jun E-mail:qiuan_huang@shu.edu.cn;jiujun.zhang@i.shu.edu.cn

摘要:

阻抗谱的应用范围越来越广,其传统测试方法耗时长的问题也日益突出. 提高阻抗谱测量速度的各种尝试中,合成宽带激励信号和设计高效率估计算法被认为是最具潜力的解决方案,由于伪随机二进制序列(pseudo-random binary sequence,PRBS)具有功率谱平坦和易生成等优点,它在阻抗谱快速测试中具有独特优势. 本文综述了快速阻抗谱测试中三个核心问题:PRBS信号类型、不同快速算法及其在电化学能源领域的典型应用. 对于PRBS信号类型,即最大长度序列信号、混合PRBS、离散区间二进制序列和正交PRBS,本文讨论了它们各自的特点和应用范围;对于不同的PRBS激励信号的快速算法,即离散傅里叶变换/快速傅里叶变换、小波变换、快速m序列变换、基于系统辨识的参数估计算法以及这些算法各自的特点和应用范围,本文进行了深入的分析;对于PRBS阻抗谱快速测量的应用,本文以铅酸电池、锂离子电池、质子交换膜燃料电池和超级电容器等电化学能源为例,验证了其应用的可行性. 为促进技术的进一步完善,本文总结和分析了PRBS阻抗谱快速测量存在的挑战,并提出了克服这些挑战所必需的未来研究方略.

关键词: 阻抗谱, 快速测量, 伪随机二进制序列, 估计算法, 电化学能源

Abstract:

With the extensive application of impedance spectroscopy, the time-consuming issue of its traditional testing methods has become more and more serious, which limits its application range. In the study of accelerating impedance measurement or reconstruction, the synthesis of wideband excitation signals and the design of high efficiency estimation algorithms have been identified as important ways. In view of the purpose of rapid impedance reconstruction, Pseudo-Random Binary Sequence (PRBS) has the advantages of flat power spectrum and easy generation, and has a good application prospect. This paper reviews three core issues in rapid reconstruction of impedance spectrum: PRBS signal types, different fast algorithms, and their typical applications in the field of electrochemical energy. For the PRBS signal types, namely, the maximum length sequence signal, the hybrid PRBS, the discrete interval binary sequence and the orthogonal PRBS, their respective characteristics and application ranges are discussed. For the fast algorithms corresponding to different PRBS excitation signals, namely, the discrete Fourier transform/Fast Fourier transform, wavelet transform, fast m-sequence transform, parameter estimation algorithm based on system identification, and their respective characteristics and application scope, this paper has carried out in-depth analysis on computation efficiency and calculation precision for fast reconstruction of impedance spectrum. For the application of rapid impedance spectrum measurement based on PRBS, the electrochemical energy sources such as lead-acid batteries, lithium-ion batteries, proton exchange membrane fuel cells and supercapacitors are taken as examples to verify the feasibility of its application. In order to promote the further improvement of technology, this paper summarizes and analyzes the challenges in rapid measurements or reconstruction of impedance spectrum based on PRBS signals, and proposes the future research strategy necessary to overcome these challenges: 1) design hardware test system according to specific application scenarios; 2) choose the optimal estimation algorithms based on the test object; 3) balance the complexity between excitation signal generation and impedance estimation algorithms.

Key words: impedance spectroscopy, fast measurement, pseudo-random binary sequence, estimation algorithm, electrochemical energy

中图分类号: