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Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies

Javaid, Usman; Mehmood, Adeel; Iqbal, Jamshed; Uppal, Ali Arshad

Authors

Usman Javaid

Ali Arshad Uppal



Abstract

In this research work, a Neural Network (NN) and Uniform Robust Exact Differentiator (URED) observer-based Fast Terminal Integral Sliding Mode Control (FTISMC) has been proposed for Oxygen Excess Ratio (OER) regulation of a Polymer Electrolyte Membrane Fuel Cell (PEMFC) power systems for vehicular applications. The controller uses URED as an observer for supply manifold pressure estimation. NN is used to estimate the stack temperature which is unavailable. The suggested control method increased the PEMFC's effectiveness and durability while demonstrating the finite-time convergence of system trajectories. By controlling the air-delivery system in the presence of uncertain current requirements and measurement noise, the approach ensures maximum power efficiency. The Lyapunov stability theorem has been used to confirm the stability of the presented algorithm. In addition, the suggested method eliminated the chattering phenomenon and improved power efficiency. Given these noteworthy characteristics, the research has the potential to decrease sensor dependence and production costs while also improving the transient and steady-state response in vehicular applications.

Citation

Javaid, U., Mehmood, A., Iqbal, J., & Uppal, A. A. (2023). Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies. Energy, 269, Article 126717. https://doi.org/10.1016/j.energy.2023.126717

Journal Article Type Article
Acceptance Date Jan 13, 2023
Online Publication Date Jan 14, 2023
Publication Date Apr 15, 2023
Deposit Date Feb 3, 2023
Publicly Available Date Feb 6, 2023
Journal Energy
Print ISSN 0360-5442
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 269
Article Number 126717
DOI https://doi.org/10.1016/j.energy.2023.126717
Keywords Fuel cell; Neural network; Oxygen excess ratio; Uniform robust exact differentiator; Fast terminal integral sliding mode control; Vehicular technology
Public URL https://hull-repository.worktribe.com/output/4190414

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