Parameter optimization of PEMFC model using backtracking search algorithm

Saad Saleem Khan; Muhammad Awais Rafiq; Hussain Shareef; Muhammad Khurram Sultan

doi:10.1109/ICREGA.2018.8337625

Parameter optimization of PEMFC model using backtracking search algorithm

Saad Saleem Khan
, Muhammad Awais Rafiq
, Hussain Shareef
, Muhammad Khurram Sultan

Department of Electrical and Communication Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Citations (Scopus)

Abstract

Proton Exchange Membrane Fuel Cell (PEMFC) is one of the promising alternative energy source that can decrease the adverse effect of greenhouse gas emissions. However, predicting the output voltage of PEMFC is difficult because of its non-linear characteristic. Thus, in this paper the modern backtracking search algorithm (BSA) is applied for modeling the PEMFC and extracting model parameters. Initially some experiments are performed on PEMFC system while changing its load linearly. The model parameters are optimized using BSA with root mean square error as an objective function. The final modeled voltage shows that the BSA provide better results than particle swarm optimization (PSO) in modelling PEMFC output voltage.

Original language	English
Title of host publication	5th International Conference on Renewable Energy
Subtitle of host publication	Generation and Application, ICREGA 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	323-326
Number of pages	4
ISBN (Electronic)	9781538622513
DOIs	https://doi.org/10.1109/ICREGA.2018.8337625
Publication status	Published - Apr 12 2018
Event	5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 - Al Ain, United Arab Emirates Duration: Feb 26 2018 → Feb 28 2018

Publication series

Name	5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018
Volume	2018-January

Other

Other	5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018
Country/Territory	United Arab Emirates
City	Al Ain
Period	2/26/18 → 2/28/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

BSA
Optimization
PEMFC
PSO

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment

Access to Document

10.1109/ICREGA.2018.8337625

Cite this

Khan, S. S., Rafiq, M. A., Shareef, H., & Sultan, M. K. (2018). Parameter optimization of PEMFC model using backtracking search algorithm. In 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018 (pp. 323-326). (5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICREGA.2018.8337625

Parameter optimization of PEMFC model using backtracking search algorithm. / Khan, Saad Saleem; Rafiq, Muhammad Awais; Shareef, Hussain et al.
5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 323-326 (5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Khan, SS, Rafiq, MA, Shareef, H & Sultan, MK 2018, Parameter optimization of PEMFC model using backtracking search algorithm. in 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018. 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 323-326, 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018, Al Ain, United Arab Emirates, 2/26/18. https://doi.org/10.1109/ICREGA.2018.8337625

Khan SS, Rafiq MA, Shareef H, Sultan MK. Parameter optimization of PEMFC model using backtracking search algorithm. In 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 323-326. (5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018). doi: 10.1109/ICREGA.2018.8337625

Khan, Saad Saleem ; Rafiq, Muhammad Awais ; Shareef, Hussain et al. / Parameter optimization of PEMFC model using backtracking search algorithm. 5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 323-326 (5th International Conference on Renewable Energy: Generation and Application, ICREGA 2018).

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abstract = "Proton Exchange Membrane Fuel Cell (PEMFC) is one of the promising alternative energy source that can decrease the adverse effect of greenhouse gas emissions. However, predicting the output voltage of PEMFC is difficult because of its non-linear characteristic. Thus, in this paper the modern backtracking search algorithm (BSA) is applied for modeling the PEMFC and extracting model parameters. Initially some experiments are performed on PEMFC system while changing its load linearly. The model parameters are optimized using BSA with root mean square error as an objective function. The final modeled voltage shows that the BSA provide better results than particle swarm optimization (PSO) in modelling PEMFC output voltage.",

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AB - Proton Exchange Membrane Fuel Cell (PEMFC) is one of the promising alternative energy source that can decrease the adverse effect of greenhouse gas emissions. However, predicting the output voltage of PEMFC is difficult because of its non-linear characteristic. Thus, in this paper the modern backtracking search algorithm (BSA) is applied for modeling the PEMFC and extracting model parameters. Initially some experiments are performed on PEMFC system while changing its load linearly. The model parameters are optimized using BSA with root mean square error as an objective function. The final modeled voltage shows that the BSA provide better results than particle swarm optimization (PSO) in modelling PEMFC output voltage.

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KW - Optimization

KW - PEMFC

KW - PSO

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Parameter optimization of PEMFC model using backtracking search algorithm

Abstract

Publication series

Other

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this