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The widespread adoption of boosted, downsized SI engines has brought pre-ignition phenomena into greater focus, as the knock events resulting from pre-ignitions can cause significant hardware damage. Much attention has been given to understanding the causes of pre-ignition and identify lubricant or fuel properties and engine design and calibration considerations that impact its frequency. This helps to shift the pre-ignition limit to higher specific loads and allow further downsizing but does not fundamentally eliminate the problem. Real-time detection and mitigation of pre-ignition would thus be desirable to allow safe engine operation in pre-ignition-prone conditions. This study focuses on advancing the time of detection of pre-ignition in an engine cycle where it occurs.

In an earlier paper, the authors described how Model-Based System Engineering could be utilized to provide a virtual Hardware-in-the-Loop simulation capability, which creates a framework for the development of virtual ECU software by providing a platform upon which embedded control algorithms may be developed, tested, updated, and validated. The development of virtual ECU software is increasingly valuable in automotive control system engineering because vehicle systems are becoming more complex and tightly integrated, which requires that interactions between subsystems be evaluated during the design process. Variational analysis and robustness studies are also important and become more difficult to perform with real hardware as system complexity increases. The methodology described in this paper permits algorithm development to be performed prior to the availability of vehicle and control system hardware by providing what is essentially a virtual integration vehicle.

The low temperature conditions that occur during high efficiency clean combustion (HECC) often lead to the formation of partially oxidized HC species such as aldehydes, ketones and carboxylic acids. Using the diesel fuels specified by the Fuels for Advanced Combustion Engines (FACE) working group, carbonyl species were collected from the exhaust of a light duty diesel engine operating under HECC conditions. High pressure liquid chromatography - mass spectrometry (LC-MS) was used to speciate carbonyls as large as C 9 . A relationship between carbonyl species formed in the exhaust and fuel composition and properties was determined. Data were collected at the optimum fuel efficiency point for a typical road load condition. Results of the carbonyl analysis showed changes in formaldehyde and acetaldehyde formation, formation of higher molecular weight carbonyls and the formation of aromatic carbonyls.

Lean NOx Trap (LNT) catalysts can effectively reduce NOx from lean engine exhaust. Significant research for LNTs in diesel engine applications has been performed and has led to commercialization of the technology. For lean gasoline engine applications, advanced direct injection engines have led to a renewed interest in the potential for lean gasoline vehicles and, thereby, a renewed demand for lean NOx control. To understand the gasoline-based reductant chemistry during regeneration, a BMW lean gasoline vehicle has been studied on a chassis dynamometer. Exhaust samples were collected and analyzed for key reductant species such as H₂, CO, NH₃, and hydrocarbons during transient drive cycles. The relation of the reductant species to LNT performance will be discussed. Furthermore, the challenges of NOx storage in the lean gasoline application are reviewed.

Advanced combustion regimes such as homogeneous charge compression ignition (HCCI) and premixed charge compression ignition (PCCI) offer benefits of reduced nitrogen oxides (NOX) and particulate matter (PM) emissions. However, these combustion strategies often generate higher carbon monoxide (CO) and hydrocarbon (HC) emissions. In addition, aldehydes and ketone emissions can increase in these modes. In this study, the engine-out emissions of a compression-ignition engine operating in a fuel reactivity-controlled PCCI combustion mode using in-cylinder blending of gasoline and diesel fuel have been characterized. The work was performed on a 1.9-liter, 4-cylinder diesel engine outfitted with a port fuel injection system to deliver gasoline to the engine. The engine was operated at 2300 rpm and 4.2 bar brake mean effective pressure (BMEP) with the ratio of gasoline-to-diesel fuel that gave the highest engine efficiency and lowest emissions.

For a series plug-in hybrid electric vehicle (PHEV), it is critical that batteries be sized to maximize vehicle performance variables, such as fuel efficiency, gasoline savings, and zero emission capability. The wide range of design choices and the cost of prototype vehicles calls for a development process to quickly and systematically determine the design characteristics of the battery pack, including its size, and vehicle-level control parameters that maximize the net present value (NPV) of a vehicle during the planning stage. Argonne National Laboratory has developed Autonomie, a modeling and simulation framework. With support from The MathWorks, Argonne has integrated an optimization algorithm and parallel computing tools to enable the aforementioned development process. This paper presents a study that utilized the development process, where the NPV is the present value of all the future expenses and savings associated with the vehicle.

Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.

The addition of metal nanoparticles to standard coolant fluids dramatically increases the thermal conductivity of the liquid. The properties of the prepared nanofluids will allow for lighter, smaller, and higher efficiency spacecraft thermal control systems to be developed. Nanofluids with spherical or rod-shaped metal nanoparticles were investigated. At a volume concentration of 0.5%, the room temperature thermal conductivity of a 2 nm spherical gold nanoparticle-water solution was increased by more than 10% over water alone. Silver nanorods increased the thermal conductivity of ethylene glycol by 53% and water by 26%.

An experimental campaign is presented aiming at the characterization of thermal dissipation of batteries to be used on board of small satellites. A suitably designed device allows to manage automatically the orbital cycling simulation between battery cell charge and discharge. The cell thermal performance is characterized in various combinations of temperature, discharge current and Depth of Discharge. The gathered data are used for providing guidelines in the design of a family of Italian Small Satellites.