Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and st...

Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and st...

This paper presents Neural Network (NN) model of Polymer Electrolyte Membran (PEM) Fuel Cell for electric vehicle. The NN model simplifies the conventional model that considered thermodynamics, electrochemistry, hydrodynamics and mass transfer theory. The NN has a multilayer feed forward network structure and is trained using a back propagation learning rule. The NN model is used to predict the...

The Polymer Electrolyte Membrane Fuel Cell (PEMFC), despite being regarded as an ideal replacement to the internal combustion engine, is still not an economically attractive pri-mover due to a number of key challenges that have yet to be fully resolved; some of which include degradation to cell components resulting in inadequate lifetimes, specialised and costly manufacturing processes and poor...

In recent decades, fuel cells have been widely used in energy generation. In a PEMFC, considering the specific application, two types of oxidants are used. Durability tests, which are highly costly products,  are of crucial importance in evaluating the lifetime of fuel cells. The purpose of the present paper is to investigate the performance of a fuel cell by changing the type of oxidant from a...

In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches...

The paper presents a Supervision, Control, Data Acquisition and Simulation (SCADA & Simulator) system that allows for real-time training in the actual operation of a modular PEM fuel cell system. This SCADA & Simulator system consists of a free software tool that operates in real time and simulates real situations like failures and breakdowns in the system. This developed SCADA & Simulator syst...

In this study, a novel multipurpose portable PEM fuel cell-solar-battery system was custom designed, constructed and laboratory tested, specially aims for applications in the rural areas remote from conventional electric power grid. We obtain encouraging results which show the applicability of such system for used as a multipurpose kit for portable applications. Our study shows that various pow...

In recent years, machine learning algorithms have been applied in many real-time applications. Crises the energy sector are primary challenges experienced today among all countries across globe, regardless of their economic status. There is a huge demand to acquire and produce environmentally friendly renewable distribute utilize it efficiently because its production cost. PEMFC known for effic...

Continuous developments in Proton Exchange Membrane Fuel Cells (PEMFC) make them a promising technology to achieve zero emissions multiple applications including mobility. Incremental advancements fuel cells materials and manufacture processes now suitable for commercialization. However, the complex operation of cell systems automotive has some open issues yet. This work develops compares three...