Frequency domain fractional subspace identification of PEMFC model

被引：0
|
作者：
Ye W.-Q. [1 ]
Qi Z.-D. [1 ]
Tian J.-X. [1 ]
Sun C.-S. [1 ]
机构：
[1] College of Automation, Nanjing University of Science and Technology, Jiangsu, Nanjing
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2022年 / 39卷 / 07期
基金：
中国国家自然科学基金;
关键词：
fractional order; frequency domain analysis; GA–PSO algorithm; PEMFC; subspace identification;
D O I：
10.7641/CTA.2021.10371
中图分类号：
学科分类号：
摘要：
In this paper, a frequency domain fractional subspace identification method is proposed to establish PEMFC’s fractional order state space (FOSS) model for the fractional order characteristics of proton exchange membrane fuel cell (PEMFC) system in power generation. Considering the computational complexity of fractional order differential in time domain, the fractional order differential is transformed into product form in frequency domain. Firstly, the random multi-frequency sinusoidal excitation signal is adopted to obtain the input and output frequency response data. Secondly, the frequency response data is employed to construct real and imaginary part matrix. Then, RQ decomposition, SVD decomposition and least square method are used to calculate system coefficient matrix A, B, C, D. Because the parameters of the same element fractional order α, auxiliary order q and frequency domain sampling points M are unknown, a GA–PSO algorithm is employed to optimize them, in which the selection, crossover and mutation operations of GA is added to PSO process to further improve the self-adaptive search direction of individuals and enhance the ability of global optimization. The simulation results verified the effectiveness of the algorithm. The output of frequency-domain fractional subspace identification can follow the measured data more closely, and the optimized identification results have smaller error and higher accuracy, which can more accurately describe the electrical characteristics of PEMFC. © 2022 South China University of Technology. All rights reserved.
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页码：1194 / 1202
页数：8
相关论文
共 18 条
  • [1] KURNIA J C, SASMITO A P., Energy Efficiency in Mobility Systems, (2020)
  • [2] CAO H, DENG Z, XI L, Et al., Dynamic modeling of electrical characteristics of solid oxide fuel cells using fractional derivatives, International Journal of Hydrogen Energy, 35, 4, pp. 1749-1758, (2010)
  • [3] MIASSA A, OLIVIER B, EMMANUEL G., Identification of a PEMFC fractional order model, International Journal of Hydrogen Energy, 42, 2, pp. 1499-1509, (2016)
  • [4] OVERSCHEE P V, MOOR B D., Subspace Identification for Linear Systems, (1996)
  • [5] SAMI S, NASRI S, ZAFAR B, Et al., Multi-input single-output state space for hybrid power system approach using PEMFC: Fuel cell and applications, International Journal of Energy Optimization and Engineering, 6, 4, pp. 35-50, (2017)
  • [6] XU Xiayin, Temperature subspace identification model of proton exchange membrane fuel cell, Industrial Control Computer, 28, 9, pp. 77-78, (2015)
  • [7] LENG Boyang, Research on fractional state space modeling and piddmc control of PEMFC, (2016)
  • [8] TALEB M A, BTHOUX O, GODOY E., Identification of a PEMFC fractional order model, International Journal of Hydrogen Energy, 42, 2, pp. 1499-1509, (2017)
  • [9] QI Z, XU S, SHAN L, Et al., Dynamic thermal modeling of PEMFC based on fractional order theory, The 27th Chinese Control and Decision Conference (CCDC), pp. 4069-4072, (2015)
  • [10] LENG B, QI Z, XU S, Et al., Research on electrical characteristics of state space modeling and parameter identifying of PEMFC, The 34th Chinese Control Conference (CCC), pp. 2039-2044, (2015)
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