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This paper describes two independent studies on γ-alumina as a plasma-activated catalyst. γ-alumina (2.5 - 4.3 wt%) was coated onto the surface of mesoporous silica to determine the importance of aluminum surface coordination on NOx conversion in conjunction with nonthermal plasma. Results indicate that the presence of 5- and 6- fold aluminum coordination sites in γ-alumina could be a significant factor in the NOx reduction process. A second study examined the effect of changing the reducing agent on NOx conversion. Several hydrocarbons were examined including propene, propane, isooctane, methanol, and acetaldehyde. It is demonstrated that methanol was the most effective reducing agent of those tested for a plasma-facilitated reaction over γ-alumina.

Natural gas quality, in terms of the volume fraction of higher hydrocarbons, strongly affects the auto-ignition characteristics of the air-fuel mixture, the engine performance and its controllability. The influence of natural gas composition on engine operation has been investigated both experimentally and through chemical kinetic based cycle simulation. A range of two component gas mixtures has been tested with methane as the base fuel. The equivalence ratio (0.3), the compression ratio (19.8), and the engine speed (1000 rpm) were held constant in order to isolate the impact of fuel autoignition chemistry. For each fuel mixture, the start of combustion was phased near top dead center (TDC) and then the inlet mixture temperature was reduced. These experimental results have been utilized as a source of data for the validation of a chemical kinetic based full-cycle simulation.

This paper discusses the compression ratio influence on maximum load of a Natural Gas HCCI engine. A modified Volvo TD100 truck engine is controlled in a closed-loop fashion by enriching the Natural Gas mixture with Hydrogen. The first section of the paper illustrates and discusses the potential of using hydrogen enrichment of natural gas to control combustion timing. Cylinder pressure is used as the feedback and the 50 percent burn angle is the controlled parameter. Full-cycle simulation is compared to some of the experimental data and then used to enhance some of the experimental observations dealing with ignition timing, thermal boundary conditions, emissions and how they affect engine stability and performance. High load issues common to HCCI are discussed in light of the inherent performance and emissions tradeoff and the disappearance of feasible operating space at high engine loads.

Homogeneous Charge Compression Ignition (HCCI) has been proposed for natural gas engines in heavy duty stationary power generation applications. A number of researchers have demonstrated, through simulation and experiment, the feasibility of obtaining high gross indicated thermal efficiencies and very low NOx emissions at reasonable load levels. With a goal of eventual commercialization of these engines, this paper sets forth some of the primary challenges in obtaining high brake thermal efficiency from production feasible engines. Experimental results, in conjunction with simulation and analysis, are used to compare HCCI operation with traditional lean burn spark ignition performance. Current HCCI technology is characterized by low power density, very dilute mixtures, and low combustion efficiency. The quantitative adverse effect of each of these traits is demonstrated with respect to the brake thermal efficiency that can be expected in real world applications.

Previous research has shown that the homogeneous charge compression ignition (HCCI) combustion concept holds promise for reducing pollutants (i.e. NOx, soot) while maintaining high thermal efficiency. However, it can be difficult to control the operation of the HCCI engines even under steady state running conditions. Power density may also be limited if high inlet air temperatures are used for achieving ignition. A methodology using a small pilot quantity of diesel fuel injected during the compression stroke to improve the power density and operation control is considered in this paper. Multidimensional computations were carried out for an HCCI engine based on a CAT3401 engine. The computations show that the required initial temperature for ignition is reduced by about 70 K for the cases of the diesel pilot charge and a 25∼35% percent increase in power density was found for those cases without adversely impacting the NOx emissions.

In this paper, the conversion of a production sport utility vehicle (SUV) to a hybrid electric vehicle utilizing a through-the-road parallel hybrid configuration is presented. The uniqueness of this design comes from its ability to decouple the front and rear drivetrain to simplify the packaging of underbody components. The Hybrid Theory utilizes a 2.0L, 4-cylinder engine that supplies 101kW (135hp) to the front wheels and a DC motor that supplies an additional 53kW (70hp) to the rear wheels to achieve the competition goals of a 25% improvement in fuel economy, a reduction in Green House Gas (GHG) emissions, as well as maintaining stock performance. The effects on drivability, manufacturing, fuel economy, emissions, and performance are presented along with the design, selection, and implementation of all of the vehicle conversion components.

A slipstream of exhaust from a Caterpillar 3126B engine was diverted into a plasma-catalytic NOx control system in the space velocity range of 7,000 to 100,000 hr-1. The stream was first fed through a non-thermal plasma that was formed in a coaxial cylinder dielectric barrier discharge reactor. Plasma treated gas was then passed over a catalyst bed held at constant temperature in the range of 573 to 773 K. Catalysts examined consisted of γ-alumina, indium-doped γ-alumina, and silver-doped γ-alumina. Road and rated load conditions resulted in engine out NOx levels of 250 - 600 ppm. The effects of hydrocarbon level, catalyst temperature, and space velocity are discussed where propene and in one case ultra-low sulfur diesel fuel (late cycle injection) were the reducing agents used for NOx reduction. Results showed NOx reduction in the range of 25 - 97% depending on engine operating conditions and management of the catalyst and slipstream conditions.

Damping measurements on vehicle subsystems are rarely straightforward due to the complexity of the dynamic interaction of system joints, trim, and geometry. Various experimental techniques can be used for damping estimation, such as frequency domain modal analysis curve-fitting methods, time domain decay-rate methods, and other methods based on energy and wave propagation. Each method has its own set of advantages and drawbacks. This paper describes an analytical and an experimental comparison between two, widely used loss factor estimation techniques frequently used in Statistical Energy Analysis (SEA). The single subsystem Power Injection Method (PIM) and the Impulse Response Decay Method (IRDM) were compared using analytical models of a variety of simulated simple spring-mass-damper systems. Frequency averaged loss factor values were estimated from both methods for comparison.

Dimethyl Ether (DME) is considered a clean alternative fuel to diesel due to its soot-free combustion characteristics and its capability to be produced from renewable energy sources rather than fossil fuels such as coal or petroleum. To mitigate the effect of strong wave dynamics on fuel supply lines caused due to the high compressibility of DME and to overcome its low lubricity, a hydraulically actuated electronic unit injector (HEUI) with pressure intensification was used. The study focuses on high pressure operation, up to 2000 bar, significantly higher than pressure ranges reported previously with DME. A one-dimensional HEUI injector model is built in MATLAB/SIMULINK graphical software environment, to predict the rate of injection (ROI) profile critical to spray and combustion characterization.

Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

The increased market share of electric vehicles and renewable energy resources have raised concerns about their impact on the current electrical distribution grid. To achieve sustainable and stable power distribution, a lot of effort has been made to implement smart grids. This paper addresses Demand Response (DR) load control in a smart grid using Internet of Things (IoT) technology. A smart grid is a networked electrical grid which includes a variety of components and sub-systems, including renewable energy resources, controllable loads, smart meters, and automation devices. An IoT approach is a good fit for the control and energy management of smart grids. Although there are various commercial systems available for smart grid control, the systems based on open sources are limited. In this study, we adopt an open source development platform named Node-RED to integrate DR capabilities in a smart grid for DR load control. The DR system employs the OpenADR standard.

Vehicle-to-Grid (V2G) service has a potential to improve the reliability and stability of the electrical grid due to the ability of providing bi-directional power flow from/to the grid. However, frequent charging/discharging may impact the battery lifetime. This paper presents the analysis of battery degradation in three scenarios. In the first scenario, different battery capacities are considered. In the second scenario, the battery degradation with various depth of discharge (DOD) are studied. In the third scenario, the capacity loss due to different charging regime are compared. The charging/discharging of plug-in electric vehicles (PEVs) are simulated in a single-phase microgrid system integrated with a photovoltaics (PV) farm, an energy storage system (ESS), and ten electric vehicle service equipment (EVSE). The battery degradation model is an energy throughput model, which is developed based on the Arrhenius equation and a power law relationship between time and capacity fading.

Compared to moving coil loudspeakers, carbon nanotube (CNT) loudspeakers are extremely lightweight and are capable of creating sound over a broad frequency range (1 Hz to 100 kHz). The thermoacoustic effect that allows for this non-vibrating sound source is naturally inefficient and nonlinear. Signal processing techniques are one option that may help counteract these concerns. Previous studies have evaluated a hybrid efficiency metric, the ratio of the sound pressure level at a single point to the input electrical power. True efficiency is the ratio of output acoustic power to the input electrical power. True efficiency data are presented for two new drive signal processing techniques borrowed from the hearing aid industry. Spectral envelope decimation of an AC signal operates in the frequency domain (FCAC) and dynamic linear frequency compression of an AC signal operates in the time domain (TCAC). Each type of processing affects the true efficiency differently.

Mandated pollutant emission levels are shifting light-duty vehicles towards hybrid and electric powertrains. Heavy-duty applications, on the other hand, will continue to rely on internal combustion engines for the foreseeable future. Hence there remain clear environmental and economic reasons to further decrease IC engine emissions. Turbocharged diesels are the mainstay prime mover for heavy-duty vehicles and industrial machines, and transient performance is integral to maximizing productivity, while minimizing work cycle fuel consumption and CO2 emissions. 1D engine simulation tools are commonplace for “virtual” performance development, saving time and cost, and enabling product and emissions legislation cycles to be met. A known limitation however, is the predictive capability of the turbocharger turbine sub-model in these tools.

Diesel engine downsizing aimed at reducing fuel consumption while meeting stringent exhaust emissions regulations is currently in high demand. The boost system architecture plays an essential role in providing adequate air flow rate for diesel fuel combustion while avoiding impaired transient response of the downsized engine. Electric Turbocharger Assist (ETA) technology integrates an electric motor/generator with the turbocharger to provide electrical power to assist compressor work or to electrically recover excess turbine power. Additionally, a variable geometry turbine (VGT) is able to bring an extra degree of freedom for the boost system optimization. The electrically-assisted turbocharger, coupled with VGT, provides an illuminating opportunity to increase the diesel engine power density and enhance the downsized engine transient response. This paper assesses the potential benefits of the electrically-assisted turbocharger with VGT to enable heavy-duty diesel engine downsizing.

A high voltage battery is an essential part of hybrid electric vehicles (HEVs). It is imperative to precisely estimate the state of charge (SOC) and state of health (SOH) of battery in real time to maintain reliable vehicle operating conditions. This paper presents a method of estimating SOC and SOH through the incorporation of current integration, voltage translation, and Ah-throughput. SOC estimation utilizing current integration is inadequate due to the accumulation of errors over the period of usage. Thus voltage translation of SOC is applied to rectify current integration method which improves the accuracy of estimation. Voltage translation data is obtained by subjecting the battery to hybrid pulse power characterization (HPPC) test. The Battery State of Health was determined by semi-empirical model combined with accumulated Ah-throughput method. Battery state of charge was employed as an input to estimate damages accumulated to battery aging through a real-time model.

This paper studies the nonlinear model predictive control for a power-split Hybrid Electric Vehicle (HEV) power management system to improve the fuel economy. In this paper, a physics-based battery model is built and integrated with a base HEV model from Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model from the software has been replaced by a single particle electrochemical lithium ion battery model. A predictive model that predicts the driver’s power request, the battery state of charge (SOC) and the engine fuel consumption is studied and used for the nonlinear model predictive controller (NMPC). A dedicated NMPC algorithm and its solver are developed and validated with the integrated HEV model. The performance of the NMPC algorithm is compared with that of a rule-based controller.

Clutches are commonly utilised in passenger type and off-road heavy-duty vehicles to disconnect the engine from the driveline and other parasitic loads. In off-road heavy-duty vehicles, along with fuel efficiency start-up functionality at extended ambient conditions, such as low temperature and intake absolute pressure are crucial. Off-road vehicle manufacturers can overcome the parasitic loads in these conditions by oversizing the engine. Caterpillar Inc. as the pioneer in off-road technology has developed a novel clutch design to allow for engine downsizing while vehicle’s performance is not affected. The tribological behaviour of the clutch will be crucial to start engagement promptly and reach the maximum clutch capacity in the shortest possible time and smoothest way in terms of dynamics. A multi-body dynamics model of the clutch system is developed in MSC ADAMS. The flywheel is introducing the same speed and torque as the engine (represents the engine input to the clutch).

It is beneficial but challenging to operate spark-ignition engines under highly lean and dilute conditions. The unstable ignition behavior can result in downgraded combustion performance in engine cylinders. Numerical approach is serving as a promising tool to identify the ignition requirements by providing insight into the complex physical/chemical phenomena. An effort to simulate the early stage of flame kernel initiation in lean and dilute fuel/air mixture has been made and discussed in this paper. The simulations are set to validate against laboratory results of spark ignition behavior in a constant volume combustion vessel. In order to present a practical as well as comprehensive ignition model, the simulations are performed by taking into consideration the discharge circuit analysis, the detailed reaction mechanism, and local heat transfer between the flame kernel and spark plug.

A model process to produce dimethylether (DME) from natural gas (NG) was simulated in a one-pass mode (no material recycle), assuming steady-state and chemical and physical equilibrium. NG conversion to synthesis gas (syngas) via steam reforming resulted in stoichiometric numbers of 2.97 along with vapor mole fraction extremes for carbon dioxide, methane, and water. These concentrations formed an eight-trial simulation grid of syngas compositions. Simulation of DME production was performed in a dual reactor configuration with methanol formation as the intermediate compound. Solutions resulting from the subsequent adiabatic dehydration of the methanol-rich phase showed a consistent DME composition (88%). The resulting solutions and unreacted syngas streams from simulation were examined for applicability to a dual-fuel NG/DME CI engine.