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Recent free piston engine research reported in the literature has included development efforts for single and dual cylinder devices through both simulation and prototype operation. A single cylinder, spring opposed, oscillating linear engine and alternator (OLEA) is a suitable architecture for application as a steady state generator. Such a device could be tuned and optimized for peak efficiency and nominal power at unthrottled operation. One of the significant challenges facing researchers is startup of the engine. It could be achieved by operating the alternator in a motoring mode according to the natural system resonant frequency, effectively bouncing the translator between the spring and cylinder, increasing stroke until sufficient compression is reached to allow introduction of fuel and initiation of combustion. To study the natural resonance of the OLEA, a numeric model has been built to simulate multiple cycles of operation.

Electro-Pneumatic systems exhibit highly nonlinear characteristics due to air compressibility, the presence of friction and the nonlinearities of control valves. Monitoring by acquiring the system's transfer function accurately can be difficult for nonlinear systems. This paper outlines a new idea that one can deal with the electro-pneumatic system as a black box, and using a multivariate technique called principal component analysis (PCA) and projection to latent structure discriminant analysis (PLSDA) to provide robust information about the system's condition. The monitoring system has been experimentally validated for an electro-pneumatic printing machine system using vibration, pressure and displacement sensory data integration using PCA-PLSDA algorithm. Experiments were conducted under two pressures for three artificially conditions: normal, throttled, and leaking system.

To meet the ignition system needs of large bore high pressure lean burn natural gas engines a laser diode side pumped passively Q-switched laser igniter was designed and tested. The laser was designed to produce the optical intensities needed to initiate ignition in a lean burn high brake mean effective pressure (BMEP) engine. The experimentation explored a variety of optical and electrical input parameters that when combined produced a robust spark in air. The results show peak power levels exceeding 2 MW and peak focal intensities above 400 GW/cm2. Future research avenues and current progress with the initial prototype are presented and discussed.

The downwash of the prop-rotor blades of the Bell/Boeing V-22 “Osprey” in hover mode creates an undesirable negative lift on the wing of the aircraft. This downforce can be reduced through a number of methods. Neglecting all other effects, such as power requirements, this research investigated the feasibility of using circulation control, through blowing slots on the leading and trailing edge of the airfoil to reduce the wake profile under the wing. A model was built at West Virginia University (WVU) and tested in a Closed Loop Wind Tunnel. The airfoil was placed normal to the airflow using the tunnel air to simulate the vertical component of the downwash experienced in hover mode. The standard hover mode flap angle of 67 degrees was used throughout the testing covered in this paper. All of these tests were conducted at a free stream velocity of 59 fps, and the baseline downforce on the model was measured to be 5.45 lbs.

Two and three-dimensional test cases were simulated using a detailed kinetic mechanism for di-methyl ether to represent methane combustion. A piston-bowl assembly for the compression and expansion strokes with combustion has been simulated at 1500 RPM. A fine grid was used for the 2-D simulations and a rather coarse grid was used for the 3-D calculations together with a k-ε subgrid-scale turbulence model and a partially stirred reactor model with three time scales. Ignition was simulated artificially by increasing the temperature at one point inside the cylinder. The results of these simulations were compared with experimental results. The simulation involved an engine with a homogeneous charge of methane as fuel. Results indicate that pressure fluctuations were captured some time after the ignition started, which indicates knock conditions.

In 2011-2013, regulations will be tightened for non-road vehicles, via the application of Stage III-B standards in Europe. With state-of-the-art technology (high pressure common rail, cooled EGR), non-road diesel engines will require DPFs to control PM, as 90% reduction is requested with respect to STAGE III-A standards. Additional challenges may also foresee the obtainment of STAGE III-B standards with STAGE III-A engine technology, by means of retrofit systems for PM control. In that case, retrofit systems must furthermore guarantee simple control systems, and must be robust especially in terms of limited back pressure increase during normal operation. Moreover, retrofit systems must offer flexibility from the design point of view, in order to be correctly operated with several engines of same class, possibly characterized by totally different PM flow rates, temperature, NOx and O₂ availability.

Diesel particulate filters (DPFs) are recognized as the most efficient technology for particulate matter (PM) reduction, with filtration efficiencies in excess of 90%. Design guidelines for DPFs typically are: high removal efficiency, low pressure drop, high durability and capacity to resist high temperature excursions during regeneration events. The collected mass inside the trap needs to be periodically oxidized to regenerate the DPF. Thus, an in-depth understanding of filtration and regeneration mechanisms, together with the ability of predicting actual DPF conditions, could play a key role in optimizing the duration and number of regeneration events in case of active DPFs. Thus, the correct estimation of soot loading during operation is imperative for effectively controlling the whole engine-DPF assembly and simultaneously avoidingany system failure due to a malfunctioning DPF. A viable way to solve this problem is to use DPF models.

Evermore demanding market and legislative pressures require stationary lean burn natural gas engines to operate at higher efficiencies and reduced levels of emissions. Higher in-cylinder pressures and leaner air/fuel ratios are required in order to meet these demands. The performance and durability of spark plug ignition systems suffer as a result of the increase in spark energy required to maintain suitable engine operation under these conditions. Advancing the state of the art of ignition systems for these engines is critical to meeting increased performance requirements. Laser-spark ignition has shown potential to improve engine performance and ignition system durability to levels required meet or exceed projected requirements. This paper discusses testing which extends previous efforts [1] to include constant fueling knock, misfire, thermal efficiency, and NOx emissions mapping of a single cylinder lean burn natural gas engine.

The KIVA family of codes (Amsden et al., 1989,1993,1997) are being used by many researchers for internal combustion engine simulation. For these codes to continue to be useful, improvements need to be made to make them more efficient. One of the most CPU intensive parts of these codes is the pressure solver. Improvement in the convergence of the pressure solver could have a significant effect on the performance of the overall code. This paper presents the theory behind the matrix solution procedure utilized by KIVA. A different approach to preconditioning is then presented. When implemented, it is shown that the overall CPU time required to perform a simulation is reduced by up to 20% for pressure dominated three-dimensional simulations. This is accomplished without an increase in memory allocation.

This paper explores the feasibility of using in-cylinder pressure-based variables to predict gaseous exhaust emissions levels from a Navistar T444 direct injection diesel engine through the use of neural networks. The networks were trained using in-cylinder pressure derived variables generated at steady state conditions over a wide speed and load test matrix. The networks were then validated on previously “unseen” real-time data obtained from the Federal Test Procedure cycle through the use of a high speed digital signal processor data acquisition system. Once fully trained, the DSP-based system developed in this work allows the real-time prediction of NOX and CO2 emissions from this engine on a cycle-by-cycle basis without requiring emissions measurement.