Scalable model generation for supercapacitors applications by using Prony's method

Shereen Hasan, Mahmoud Al Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Scalable models generation for supercapacitor is a proper way to design, analyze and show how these supercapacitors scale up for applications which based on circuits and systems. Therefore, the primary objective of this research study was to construct a scalable models generation for supercapacitor applications by using Prony's method (ARMA modeling) using electrochemical impedance spectroscopy and phase angle measurements. This research is carried out on Maxwell set of capacitors ranging from 5 to 50F. In addition, this paper includes five sections: introduction, methodology and model proposed, experimental work, results and discussions and conclusions. Finally, the error and confidence interval issues were studied and plotted to check the accuracy and validity of the system model.

Original languageEnglish
Title of host publication4th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538621066
DOIs
Publication statusPublished - Jan 31 2018
Event4th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2017 - Salmabad, Bahrain
Duration: Nov 29 2017Dec 1 2017

Publication series

Name4th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2017
Volume2018-January

Other

Other4th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2017
Country/TerritoryBahrain
CitySalmabad
Period11/29/1712/1/17

Keywords

  • Prony's method
  • Scalable model
  • Supercapacitor and Statistical analysis

ASJC Scopus subject areas

  • Education
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Electrical and Electronic Engineering
  • Mechanical Engineering

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