Search Results

Performance of a natural gas two-stroke engine incorporated in a 1-kW free-piston oscillating Linear Engine Alternator (LEA) - a household electricity generator - was investigated under different resonant frequencies for pre-design phase purposes. To increase the robustness, power density, and thermal efficiencies, the crank mechanism in free-piston LEA is omitted and all moving parts of the generator operate at a fixed resonant frequency. Flexure springs are the main source of the LEA’s stiffness and the mass-spring dynamics dominates the engine’s speed. The trade-off between the engine’s performance, mass-spring system limits, and power and efficiency targets versus the LEA speed is very crucial and demands a careful investigation specifically at the concept design stages to find the optimum design parameters and operating conditions. CFD modeling was performed to analyze the effects of resonant frequency on the engine’s gas exchange behavior.

Linear engine alternator (LEA) design optimization traditionally has been difficult because each independent variable alters the motion with respect to time, and therefore alters the engine and alternator response to other governing variables. An analogy is drawn to a conventional engine with a very light flywheel, where the rotational speed effectively is not constant. However, when springs are used in conjunction with an LEA, the motion becomes more consistent and more sinusoidal with increasing spring stiffness. This avoids some attractive features, such as variable compression ratio HCCI operation, but aids in reducing cycle-to-cycle variation for conventional combustion modes. To understand the cycle-to-cycle variations, we have developed a comprehensive model of an LEA with a 1kW target power in MATLAB®/Simulink, and an LEA corresponding to that model has been operated in the laboratory.

The range-extended electric vehicle (REEV) is a complex nonlinear system powered by internal combustion engine and electricity stored in battery. This research proposed a Multiple Operation Points (MOP) control strategy of REVV based on operation features of REEV and the universal characteristic curve of the engine. The switching logic rules of MOP strategy are designed for the desired transition of the operation mode, which makes the engine running at high efficiency region. A Genetic algorithm (GA) is adapted to search the optimal solution. The fuel consumption is defined as the target cost function. The demand power of engine is defined as optimal variable. The state of charge (SOC) and vehicle speed are selected as the state variables. The dynamic performance of vehicle and cycling life of battery is set as the constraints. The optimal switching parameters are obtained based on this control strategy. Finally, a dynamic simulation model of REEV is developed in Matlab/Simulink.

The free piston engine combined with a linear electric alternator has the potential to be a highly efficient converter from fossil fuel energy to electrical power. With only a single major moving part (the translating rod), mechanical friction is reduced compared to conventional crankshaft technology. Instead of crankshaft linkages, the motion of the translator is driven by the force balance between the engine cylinder, alternator, damping losses, and springs. Focusing primarily on mechanical springs, this paper explores the use of springs to increase engine speed and reduce cyclic variability. A numeric model has been constructed in MATLAB®/Simulink to represent the various subsystems, including the engine, alternator, and springs. Within the simulation is a controller that forces the engine to operate at a constant compression ratio by affecting the alternator load.

Recent catastrophic air crashes have shown that physical redundancy is not a foolproof option for failures on Air Data Systems (ADS) on an aircraft providing airspeed measurements. Since all the redundant sensors are subjected to the same environmental conditions in flight, a failure on one sensor could occur on the other sensors under certain conditions such as extreme weather; this class of failure is known in the literature as “common mode” failure. In this paper, different approaches to the problem of detection, identification and accommodation of failures on the Air Data System (ADS) of an aircraft are evaluated. This task can be divided into component tasks of equal criticality as Sensor Failure Detection and Identification (SFDI) and Sensor Failure Accommodation (SFA). Data from flight test experiments conducted using the WVU YF-22 unmanned research aircraft are used.

Heavy duty tractor-trailers under freeway operations consume about 65% of the total engine shaft energy to overcome aerodynamic drag force. Vehicles are exposed to on-road crosswinds which cause change in pressure distribution with a relative wind speed and yaw angle. The objective of this study was to analyze the drag losses as a function of on-road wind conditions, on-road vehicle position and trajectory. Using coefficient of drag (CD) data available from a study conducted at NASA Ames, Geographical Information Systems model, time-varying weather data and road data, a generic model was built to identify the yaw angles and the relative magnitude of wind speed on a given route over a given time period. A region-based analysis was conducted for a study on interstate trucking operation by employing I-79 running through West Virginia as a case study by initiating a run starting at 12am, 03/03/2012 out to 12am, 03/05/2012.

This paper presents 3D finite element analysis performed for a composite cylindrical tank made of 6061-aluminum liner overwrapped with carbon fibers subjected to a burst internal pressure of 1610 bars. As the service pressure expected in these tanks is 700 bars, a factor of safety of 2.3 is kept the same for all designs. The optimal design configuration of such high pressure storage tanks includes an inner liner used as a gas permeation barrier, geometrically optimized domes, inlet/outlet valves with minimum stress concentrations, and directionally tailored exterior reinforcement for high strength and stiffness. Filament winding of pressure vessels made of fiber composite materials is the most efficient manufacturing method for such high pressure hydrogen storage tanks. The complexity of the filament winding process in the dome region is characterized by continually changing the fiber orientation angle and the local thickness of the wall.

The hydrogen economy envisioned in the future requires safe and efficient means of storing hydrogen fuel for either use on-board vehicles, delivery on mobile transportation systems or high-volume storage in stationary systems. The main emphasis of this work is placed on the high -pressure storing of gaseous hydrogen on-board vehicles. As a result of its very low density, hydrogen gas has to be stored under very high pressure, ranging from 350 to 700 bars for current systems, in order to achieve practical levels of energy density in terms of the amount of energy that can be stored in a tank of a given volume. This paper presents 3D finite element analysis performed for a composite cylindrical tank made of 6061-aluminum liner overwrapped with carbon fibers subjected to a burst internal pressure of 1610 bars. As the service pressure expected in these tanks is 700 bars, a factor of safety of 2.3 is kept the same for all designs.

The new General Motors 2-mode hybrid transmission for front-wheel-drive vehicles has been incorporated into a 2009 Saturn Vue by the West Virginia University EcoCAR team. The 2-mode hybrid transmission can operate in either one of two electrically variable transmission modes or four fixed gear modes although only the electrically variable modes were explored in this paper. Other major power train components include a GM 1.3L SDE turbo diesel engine fueled with B20 biodiesel and an A123 Systems 12.9 kWh lithium-ion battery system. Two additional vehicle controllers were integrated for tailpipe emission control, CAN message integration, and power train hybridization control. Control laws for producing maximum fuel efficiency were implemented and include such features as engine auto-stop, regenerative braking and optimized engine operation. The engine operating range is confined to a high efficiency area that improves the overall combined engine and electric motor efficiency.

West Virginia University (WVU) is a participant in EcoCAR - The NeXt Challenge, an Advanced Vehicle Technology Competition sponsored by the U.S. Department of Energy, and General Motors Corporation. During the first year of the competition, the goal of the WVU EcoEvolution Team was to design a novel hybrid-electric powertrain for a 2009 Saturn Vue to increase pump-to-wheels fuel economy, reduce criteria tailpipe emissions and well-to-wheels greenhouse gas emissions (GHG) while maintaining or improving performance and utility. To this end, WVU designed a 2-Mode split-parallel diesel-electric hybrid system. Key elements of the hybrid powertrain include a General Motors 1.3L SDE Turbo Diesel engine, a General Motors Corporation 2-Mode electrically variable transmission (EVT) and an A123 Systems Lithium-Ion battery system. The engine will be fueled on a blend of 20% soy-derived biodiesel and 80% petroleum-derived ultra-low sulfur diesel fuel (B20).

Fuel economy is an important issue in urban driving cycle where vehicles are required to operate most of the time at lower power than the average demand. High power fuel cells operate economically at higher loads. Hence, conventional combination of a high power fuel cell and an additional storage device such as ultracapacitor or battery units does not necessarily provide an economic configuration. This paper offers a new configuration that consists of two fuel cells combined with a battery unit to provide a fuel efficient source of power for hybrid electric fuel cell vehicles in urban driving applications. The control algorithm and power management strategy for a combination of two downsized fuel cells and a storage device is provided and its performance of operation is compared with traditional topologies.