Aluminum-Hydrogen Peroxide Fuel Cell Power System for Ocean Bottom Electrical Power

2005 ◽  
Author(s):  
R. German
Keyword(s):  
Hydrogen Peroxide ◽  
Fuel Cell ◽  
Power System ◽  
Electrical Power ◽  
Ocean Bottom

scholarly journals Kilowatt-Scale Fuel Cell Systems Powered by Recycled Aluminum

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Peter Godart ◽  
Jason Fischman ◽  
Douglas Hart
Keyword(s):  
Fuel Cell ◽  
Power System ◽  
Proton Exchange Membrane ◽  
Electrical Power ◽  
Hydrogen Gas ◽  
Proton Exchange ◽  
Hydrogen Fuel Cell ◽  
Cell Systems ◽  
Scrap Aluminum ◽  
Exchange Membrane

Abstract Presented here is a novel system that uses an aluminum-based fuel to continuously produce electrical power at the kilowatt scale via a hydrogen fuel cell. This fuel has an energy density of 23.3 kW h/L and can be produced from abundant scrap aluminum via a minimal surface treatment of gallium and indium. These additional metals, which in total comprise 2.5% of the fuel’s mass, permeate the grain boundary network of the aluminum to disrupt its oxide layer, thereby enabling the fuel to react exothermically with water to produce hydrogen gas and aluminum oxyhydroxide (AlOOH), an inert and valuable byproduct. To generate electrical power using this fuel, the aluminum–water reaction is controlled via water input to a reaction vessel in order to produce a constant flow of hydrogen, which is then consumed in a fuel cell to produce electricity. As validation of this power system architecture, we present the design and implementation of two proton-exchange membrane (PEM) fuel cell systems that successfully demonstrate this approach. The first is a 3 kW emergency power supply, and the second is a 10 kW power system integrated into a BMW i3 electric vehicle.

scholarly journals High-Power Fuel Cell Systems Fueled by Recycled Aluminum

2019 ◽  
Author(s):  
Peter Godart ◽  
Jason Fischman ◽  
Douglas Hart
Keyword(s):  
Fuel Cell ◽  
Power System ◽  
Electrical Power ◽  
Reaction Vessel ◽  
Hydrogen Gas ◽  
Constant Flow ◽  
Hydrogen Fuel Cell ◽  
Hydrogen Fuel ◽  
Emergency Power ◽  
Scrap Aluminum

Abstract Presented here is a novel system that uses an aluminum-based fuel to continuously produce electrical power at the kW scale via a hydrogen fuel cell. This fuel has an energy density of 23.3 kWh/L and can be produced from abundant scrap aluminum via a minimal surface treatment of gallium and indium. These additional metals, which in total comprise 2.5% of the fuel’s mass, permeate the grain boundary network of the aluminum and disrupt its oxide layer, thereby enabling the fuel to react exothermically with water to produce hydrogen gas and aluminum oxyhydroxide, an inert and valuable byproduct. To generate electrical power using this fuel, the aluminum-water reaction is controlled via water input to a reaction vessel in order to produce a constant flow of hydrogen, which is then consumed in a fuel cell to produce electricity. As validation of this power system architecture, we present the design and implementation of two example systems that successfully demonstrate this approach. The first is a 3 kW emergency power supply and the second is a 10 kW power system integrated into a BWM i3 electric vehicle.

Results Using Processed Acetylene Fuel Stream in Solid Oxide Fuel Cell Stack

2010 ◽  
Vol 7 (3) ◽  
Author(s):  
A. Alan Burke ◽  
Louis G. Carreiro ◽  
R. Craig Urian
Keyword(s):  
Hydrogen Peroxide ◽  
Fuel Cell ◽  
Power System ◽  
Solid Oxide Fuel Cell ◽  
High Energy ◽  
Solid Oxide ◽  
Oxide Fuel ◽  
Fuel Cell Stack ◽  
High Energy Storage ◽  
Fuel Stream

Preliminary results indicate that acetylene and hydrogen peroxide are viable reactants for a solid oxide fuel cell (SOFC) system. Acetylene was hydrogenated and reformed to a suitable feed at the anode while hydrogen peroxide was decomposed to provide oxygen to the cathode. Roughly 45% fuel and oxidant utilization were demonstrated on a SOFC stack manufactured by Delphi Corporation (Troy, MI). These reactants offer high energy storage as well as an entirely self-contained power system with no exhaust streams. Such attributes are favorable for undersea vehicles and perhaps other applications that require a self-contained or air-independent power system.

Gradient Ascent Optimization for Fault Detection in Electrical Power System Based on Wavelet Transformation

2019 ◽  
Vol 14 ◽  
Author(s):  
Iyappan Murugesan ◽  
Karpagam Sathish
Keyword(s):  
Feature Extraction ◽  
Fault Detection ◽  
Power System ◽  
Electrical Power ◽  
Daubechies Wavelet ◽  
Electrical Power System ◽  
Gradient Ascent ◽  
Neural Learning ◽  
Weight Value ◽  
Transmission And Distribution

: This paper presents electrical power system comprises many complex and interrelating elements that are susceptible to the disturbance or electrical fault. The faults in electrical power system transmission line (TL) are detected and classified. But, the existing techniques like artificial neural network (ANN) failed to improve the Fault Detection (FD) performance during transmission and distribution. In order to reduce the power loss rate (PLR), Daubechies Wavelet Transform based Gradient Ascent Deep Neural Learning (DWT-GADNL) Technique is introduced for FDin electrical power sub-station. DWT-GADNL Technique comprises three step, normalization, feature extraction and FD through optimization. Initially sample power TL signal is taken. After that in first step, min-max normalization process is carried out to estimate the various rated values of transmission lines. Then in second step, Daubechies Wavelet Transform (DWT) is employed for decomposition of normalized TLsignal to different components for feature extraction with higher accuracy. Finally in third step, Gradient Ascent Deep Neural Learning is an optimization process for detecting the local maximum (i.e., fault) from the extracted values with help of error function and weight value. When maximum error with low weight value is identified, the fault is detected with lesser time consumption. DWT-GADNL Technique is measured with PLR, feature extraction accuracy (FEA), and fault detection time (FDT). The simulation result shows that DWT-GADNL Technique is able to improve the performance of FEA and reduces FDT and PLR during the transmission and distribution when compared to state-of-the-art works.

scholarly journals Optimization of the Fuel Cell Renewable Hybrid Power System Using the Control Mode of the Required Load Power on the DC Bus

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1889 ◽  
Author(s):  
Nicu Bizon ◽  
Valentin Alexandru Stan ◽  
Angel Ciprian Cormos
Keyword(s):  
Energy Source ◽  
Fuel Cell ◽  
Power System ◽  
Control Mode ◽  
Variable Load ◽  
Hybrid Power System ◽  
Hybrid Power ◽  
Load Power ◽  
Load Demand ◽  
Dc Bus

In this paper, a systematic analysis of seven control topologies is performed, based on three possible control variables of the power generated by the Fuel Cell (FC) system: the reference input of the controller for the FC boost converter, and the two reference inputs used by the air regulator and the fuel regulator. The FC system will generate power based on the Required-Power-Following (RPF) control mode in order to ensure the load demand, operating as the main energy source in an FC hybrid power system. The FC system will operate as a backup energy source in an FC renewable Hybrid Power System (by ensuring the lack of power on the DC bus, which is given by the load power minus the renewable power). Thus, power requested from the batteries’ stack will be almost zero during operation of the FC hybrid power system based on RPF-control mode. If the FC hybrid power system operates with a variable load demand, then the lack or excess of power on the DC bus will be dynamically ensured by the hybrid battery/ultracapacitor energy storage system for a safe transition of the FC system under the RPF-control mode. The RPF-control mode will ensure a fair comparison of the seven control topologies based on the same optimization function to improve the fuel savings. The main objective of this paper is to compare the fuel economy obtained by using each strategy under different load cycles in order to identify which is the best strategy operating across entire loading or the best switching strategy using two strategies: one strategy for high load and the other on the rest of the load range. Based on the preliminary results, the fuel consumption using these best strategies can be reduced by more than 15%, compared to commercial strategies.

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