Abstract
In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking desired voltage and less energy consumption through investigating and comparing under random current variations with the minimum number of fitness evaluation less than 20 iterations.
Highlights
The motivation of this paper is to focus on the dynamic response of the PEM fuel cell stack and stabilize the power output, especially when it is used in mobile applications
numerical feedforward controller (NFFC) is assumed to calculate the inverse dynamic of proton exchange membrane fuel cells (PEMFCs) system, and so it is called inverse feedforward controller (IFC)
Because the thermodynamic potential (EN) value of the PEMFC system as in equation (6) has been improved toward increasing that led to the improved the performance of the Fuel Cell system
Summary
The electrons and protons react with oxygen from air to produce water and heat as result of reaction Benchouia, et al, 2015, Beirami, et al, 2015, and Derbeli, et al, 2017. Activation loss is the voltage drop due to the energized between the anode and cathode, Correa, et al, 2003 To determine this type of loss, Eq (7) can be used: Vact = α1 + α2 ∗ T + α3 ∗ T ∗ ln(CO2) + α4 ∗ T ∗ ln(I). There are two inputs of the PEMFC system which controlled the operation of the Fuel Cell, the first one is the hydrogen partial pressure (PH2) controlled effort and the second is the oxygen partial pressure (PO2) a constant value in this paper.
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