Fuel Cell System

Gao, Fei; Kabalo, Mohammad; Rylko, Marek S.; Blunier, Benjamin; Miraoui, Abdellatif

doi:10.1007/978-1-4471-5104-3_6

Cited by 6 publications

(3 citation statements)

References 27 publications

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“…The classical structure of stand-alone power systems based on renewable energy sources is presented in Figure 1 [52,53]. This structure is composed by an energy generator, e.g., a fuel cell or PV generator, connected to a DC/DC converter controlled by a MPPT algorithm to optimize the operation of the power source.…”

Section: Dc-bus Voltage Regulatormentioning

confidence: 99%

“…The equations for imposing a critically damped behavior to the DC-bus voltage are given in Equations (42) and (38). Such expressions, normalized in terms of the duty cycle, are given in Equations (52) and (53). Moreover, it must be verified that the time t delta taken by the bus voltage for reaching the safe band is lower or equal that the time t sa f e required for a normal operation of the load.…”

Section: Critically-damped Behavior Equationsmentioning

confidence: 99%

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Sliding-Mode Control of a Charger/Discharger DC/DC Converter for DC-Bus Regulation in Renewable Power Systems

2016

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Stand-alone power systems based on renewable energy sources are used to replace generators based on fossil fuels. Those renewable power systems also require Energy Storage Devices (ESD) interfaced by a charger/discharger power converter, which consist of a bidirectional DC/DC converter, and a DC bus. This paper proposes a single sliding-mode controller (SMC) for the charger/discharger DC/DC converter to provide a stable DC bus voltage in any operation condition: charging or discharging the ESD, or even without any power exchange between the ESD and the DC bus. Due to the non-linear nature of the power converter, the SMC parameters are adapted on-line to ensure global stability in any operation condition. Such stability of the adaptive SMC is mathematically demonstrated using analytical expressions for the transversality, reachability and equivalent control conditions. Moreover, a design procedure for the adaptive SMC parameters is provided in order to ensure the dynamic response required for the correct operation of the load. Finally, simulations and experimental tests validate the proposed controller and design procedure.

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Section: Dc-bus Voltage Regulatormentioning

confidence: 99%

Section: Critically-damped Behavior Equationsmentioning

confidence: 99%

Sliding-Mode Control of a Charger/Discharger DC/DC Converter for DC-Bus Regulation in Renewable Power Systems

2016

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“…From the position of model-based methodologies, the problem of water management has been diagnosed considering models that involve multi-scale methods solved by electric circuits, numerical simulations [7][8][9], use of VOF in CFD, method of Lattice-Boltzmann, Eulerian-Lagrangian method (Eulerian for air and Lagrangian for water), neutron imaging technique, magnetic resonance imaging technique, and Kalman filter. Water management has been modelled in a stationary, dynamic, isobaric, and non-isobaric way [10][11][12][13], developing experimental techniques to predict its parameters and determine the distributions of water, gas, and of temperature in the PEMFC. The materials to build the membrane, the transient response produced by the dehydration of the membrane, the flooding of the gas diffusing layers and the dilution of the reagents in the flow channels have been analyzed [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Model to Manage Water in Polymer Electrolyte Membrane Fuel Cells

Rubio

Agila

2021

Processes

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In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response, and, consequently, its autonomous operation. By applying load, current, and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits.

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