Parameter Identification of Flexible Supercapacitors with Fractional Cuckoo Search

被引：0
|
作者：
AbdelAty, A. M. [1 ]
Fouda, M. E. [2 ,3 ]
Elbarawy, M. T. M. M. [1 ]
Attia, H. A. [1 ]
Radwan, A. G. [2 ,4 ]
机构：
[1] Fayoum Univ, Fac Engn, Engn Math & Phys Dept, Faiyum, Egypt
[2] Cairo Univ, Fac Engn, Engn Math & Phys Dept, Cairo, Egypt
[3] Univ Calif Irvine, Elect Engn & Comp Sci Dept, Irvine, CA USA
[4] Nile Univ, Sch Engn & Appl Sci, Giza, Egypt
来源：
2020 32ND INTERNATIONAL CONFERENCE ON MICROELECTRONICS (ICM) | 2020年
关键词：
Flexible SuperCapacitor; R-s-CPE model; R-p-R-s-CPE model; R-s-C-CPE model; Cuckoo search; ENERGY-STORAGE;
D O I：
10.1109/ICM50269.2020.9331777
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we identify the model parameters of flexible supercapacitors from time-domain data using fractional cuckoo search. The time-domain data are five galvanostatic charging/discharging (GCD) curves of reduced graphene oxidebased flexible supercapacitor at different exfoliated-graphene-mediated graphene oxide (EGM-rGO) relative content. These time-domain curves are used the parameters of three wellknown supercapacitor models: R-s-CPE, R-p-R-s-CPE, and RsC-CPE. The extracted parameters are summarized, and the effect of EGM-rGO relative content is discussed. Based on these discussions, one model is recommended for each EGM-rGO relative content.
引用
收藏
页码：238 / 241
页数：4
相关论文
共 50 条
  • [21] The Parameter Identification of PMSM Based on Improved Cuckoo Algorithm
    Wu, Zhongqiang
    Du, Chunqi
    NEURAL PROCESSING LETTERS, 2019, 50 (03) : 2701 - 2715
  • [22] Parameter Control Based Cuckoo Search Algorithm for Numerical Optimization
    Cheng, Jiatang
    Xiong, Yan
    NEURAL PROCESSING LETTERS, 2022, 54 (04) : 3173 - 3200
  • [23] Modified cuckoo search algorithm with self adaptive parameter method
    Li, Xiangtao
    Yin, Minghao
    INFORMATION SCIENCES, 2015, 298 : 80 - 97
  • [24] The Parameter Identification of PMSM Based on Improved Cuckoo Algorithm
    Zhongqiang Wu
    Chunqi Du
    Neural Processing Letters, 2019, 50 : 2701 - 2715
  • [25] Multi-Population Genetic Algorithm and Cuckoo Search Hybrid Technique for Parameter Identification of Fermentation Process Models
    Angelova, Maria
    Roeva, Olympia
    Vassilev, Peter
    Pencheva, Tania
    PROCESSES, 2023, 11 (02)
  • [26] Parameter Identification Method for Collaborative Robot Joint Using a Cuckoo Search-BP Neural Network Approach
    Xiong, Liangping
    Hu, Huifeng
    An, Kang
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2024, 38 (07)
  • [27] Parameter Identification for Area-Specific Resistance of Direct Methanol Fuel Cell Using Cuckoo Search Algorithm
    Ding, Jiajun
    He, Xiongxiong
    Jiang, Bo
    Wu, Yiming
    BIO-INSPIRED COMPUTING - THEORIES AND APPLICATIONS, BIC-TA 2015, 2015, 562 : 107 - 112
  • [28] Structural damage identification based on cuckoo search algorithm
    Xu, H. J.
    Liu, J. K.
    Lu, Z. R.
    ADVANCES IN STRUCTURAL ENGINEERING, 2016, 19 (05) : 849 - 859
  • [29] Parameter extraction of photovoltaic cell using an improved cuckoo search optimization
    Gude, Srihari
    Jana, Kartick Chandra
    SOLAR ENERGY, 2020, 204 : 280 - 293
  • [30] Parameter Estimation of Weibull Mixtures Based on Improved Cuckoo Search Algorithm
    Chi, Kuo
    Kang, Jian-She
    Wang, Guang-yan
    Yang, Rui-feng
    2016 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-CHENGDU), 2016,
12345