Energies2014, 7(7), 4710-4726; doi:10.3390/en7074710 (doi registration under processing) - published online 22 July 2014 Show/Hide Abstract
Abstract: An experimental study of the intrinsic instabilities of H2/CO lean (φ = 0.4 to φ = 1.0) premixed flames at different hydrogen fractions ranging from 0% to 100% at elevated pressure and room temperature was performed in a constant volume vessel using a Schlieren system. The unstretched laminar burning velocities were compared with data from the previous literature and simulated results. The results indicate that excellent agreements are obtained. The cellular instabilities of syngas-air flames were discussed and critical flame radii were measured. When hydrogen fractions are above 50%, the flame tends to be more stable as the equivalence ratio increases; however, the instability increases for flames of lower hydrogen fractions. For the premixed syngas flame with hydrogen fractions greater than 50%, the decline in cellular instabilities induced by the increase in equivalence ratio can be attributed to a reduction of diffusive-thermal instabilities rather than increased hydrodynamic instabilities. For premixed syngas flames with hydrogen fractions lower than 50%, as the equivalence ratio increases, the cellular instabilities become more evident because the enhanced hydrodynamic instabilities become the dominant effect. For premixed syngas flames, the enhancement of cellular instabilities induced by the increase in hydrogen fraction is the result of both increasing diffusive-thermal and hydrodynamic instabilities.
Energies2014, 7(7), 4694-4709; doi:10.3390/en7074694 (doi registration under processing) - published online 22 July 2014 Show/Hide Abstract
Abstract: The enzymatic biofuel cells (EBFCs) are considered as an attractive candidate for powering future implantable medical devices. In this study, a computational model of EBFCs based on three-dimensional (3-D) interdigitated microelectrode arrays was conducted. The main focus of this research is to investigate the effect of different designs and spatial distributions of the microelectrode arrays on mass transport of fuels, enzymatic reaction rate, open circuit output potential and current density. To optimize the performance of the EBFCs, numerical simulations have been performed for cylindrical electrodes with various electrode heights and well widths. Optimized cell performance was obtained when the well width is half of the height of the 3-D electrode. In addition, semi-elliptical shaped electrode is preferred based on the results from current density and resistive heating simulation.
Energies2014, 7(7), 4676-4693; doi:10.3390/en7074676 (doi registration under processing) - published online 22 July 2014 Show/Hide Abstract
Abstract: Autonomous Underwater Vehicles (AUVs) are vehicles that are primarily used to accomplish oceanographic research data collection and auxiliary offshore tasks. At the present time, they are usually powered by lithium-ion secondary batteries, which have insufficient specific energies. In order for this technology to achieve a mature state, increased endurance is required. Fuel cell power systems have been identified as an effective means to achieve this endurance but no implementation in a commercial device has yet been realized. This paper summarizes the current state of development of the technology in this field of research. First, the most adequate type of fuel cell for this application is discussed. The prototypes and design concepts of AUVs powered by fuel cells which have been developed in the last few years are described. Possible commercial and experimental fuel cell stack options are analyzed, examining solutions adopted in the analogous aerial vehicle applications, as well as the underwater ones, to see if integration in an AUV is feasible. Current solutions in oxygen and hydrogen storage systems are overviewed and energy density is objectively compared between battery power systems and fuel cell power systems for AUVs. A couple of system configuration solutions are described including the necessary lithium-ion battery hybrid system. Finally, some closing remarks on the future of this technology are given.
Energies2014, 7(7), 4648-4675; doi:10.3390/en7074648 (doi registration under processing) - published online 22 July 2014 Show/Hide Abstract
Abstract: This paper demonstrates an energy management method using traffic information for commuter hybrid electric vehicles. A control strategy based on stochastic dynamic programming (SDP) is developed, which minimizes on average the equivalent fuel consumption, while satisfying the battery charge-sustaining constraints and the overall vehicle power demand for drivability. First, according to the sample information of the traffic speed profiles, the regular route is divided into several segments and the statistic characteristics in the different segments are constructed from gathered data on the averaged vehicle speeds. And then, the energy management problem is formulated as a stochastic nonlinear and constrained optimal control problem and a modified policy iteration algorithm is utilized to generate a time-invariant state-dependent power split strategy. Finally, simulation results over some driving cycles are presented to demonstrate the effectiveness of the proposed energy management strategy.
Energies2014, 7(7), 4629-4647; doi:10.3390/en7074629 (doi registration under processing) - published online 22 July 2014 Show/Hide Abstract
Abstract: The coming interaction between a growing electrified vehicle fleet and the desired growth in renewable energy provides new insights into the economic dispatch (ED) problem. This paper presents an economic dispatch model that considers electric vehicle charging, battery exchange stations, and wind farms. This ED model is a high-dimensional, non-linear, and stochastic problem and its solution requires powerful methods. A new finite action-set learning automata (FALA)-based approach that has the ability to adapt to a stochastic environment is proposed. The feasibility of the proposed approach is demonstrated in a modified IEEE 30 bus system. It is compared with continuous action-set learning automata and particle swarm optimization-based approaches in terms of convergence characteristics, computational efficiency, and solution quality. Simulation results show that the proposed FALA-based approach was indeed capable of more efficiently obtaining the approximately optimal solution. In addition, by using an optimal dispatch schedule for the interaction between electric vehicle stations and power systems, it is possible to reduce the gap between demand and power generation at different times of the day.
Energies2014, 7(7), 4614-4628; doi:10.3390/en7074614 (doi registration under processing) - published online 22 July 2014 Show/Hide Abstract
Abstract: Vehicle active safety control is attracting ever increasing attention in the attempt to improve the stability and the maneuverability of electric vehicles. In this paper, a neural network combined inverse (NNCI) controller is proposed, incorporating the merits of left-inversion and right-inversion. As the left-inversion soft-sensor can estimate the sideslip angle, while the right-inversion is utilized to decouple control. Then, the proposed NNCI controller not only linearizes and decouples the original nonlinear system, but also directly obtains immeasurable state feedback in constructing the right-inversion. Hence, the proposed controller is very practical in engineering applications. The proposed system is co-simulated based on the vehicle simulation package CarSim in connection with Matlab/Simulink. The results verify the effectiveness of the proposed control strategy.