Optimal proton exchange membrane fuel cell modelling based on hybrid Teaching Learning Based Optimization – Differential Evolution algorithm

Simulation proton exchange membrane fuel cell (PEMFC) performance accurately is a challenging process. Many mathematical models have been existed, yet due to lack of accurate parameter estimations, considerable errors might occur. Nowadays, meta-heuristic optimization algorithms have been successful...

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Veröffentlicht in:Ain Shams Engineering Journal Jg. 7; H. 1; S. 347 - 360
Hauptverfasser: Turgut, Oguz Emrah, Coban, Mustafa Turhan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.03.2016
Schlagworte:
Differential Evolution
Parameter identification
Polarization curve
Proton exchange membrane fuel cell
Teaching Learning Based Optimization
Proton exchange membrane fuel cell
Parameter identification
Differential Evolution
Teaching Learning Based Optimization
Polarization curve
ISSN:2090-4479
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Zusammenfassung:Simulation proton exchange membrane fuel cell (PEMFC) performance accurately is a challenging process. Many mathematical models have been existed, yet due to lack of accurate parameter estimations, considerable errors might occur. Nowadays, meta-heuristic optimization algorithms have been successfully applied for parameter identification of PEMFC models. In this study, Teaching Learning Based Optimization method (TLBO) is hybridized with Differential Evolution (DE) algorithm for successful estimation of unknown PEMFC model parameters. Efficiency of the proposed algorithm is tested with several benchmark problems. A case study taken from the literature has been performed by hybrid TLBO–DE algorithm and other optimization methods such as Melody Search (MS), Backtracking Search (BS), Artificial Cooperative Search (ACS), Quantum behaved Particle Swarm Optimization (QPSO), Bat algorithm (BAT), Intelligent Tuned Harmony Search (ITHS) and Cuckoo Search (CS). TLBO–DE algorithm surpasses all these optimizers in terms of solution quality and accuracy.
ISSN:2090-4479
DOI:10.1016/j.asej.2015.05.003