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The properties of aluminum alloys reinforced by ceramic nanoparticles (less than 100nm) would be enhanced considerably while the ductility is retained over that of the native alloy. The potential of bulk Al-based metal matrix nano-composites (Al MMNCs) cannot be fully developed for industrial applications unless complex structural Al MMNC components can be fabricated cost effectively, such as by casting. Reliable bulk Al MMNCs cannot be cast unless the nanoparticles can be dispersed and distributed uniformly in molten Al alloys. This paper investigates a high volume production method for high performance aluminum matrix nanocomposites, in particular, the application of high intensity ultrasonic cavitation in mixing and dispersing nano-sized ceramic particles in Al melts to cast bulk Al MMNCs for complex automobile structures. Nano-sized SiC particles have been dispersed in molten aluminum alloy A356 for casting.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.

For competition in the 1998 FutureCar Challenge (FCC98), the University of Wisconsin - Madison FutureCar Team has designed and built a lightweight, charge sustaining, parallel hybrid electric vehicle by modifying a 1994 Mercury Sable Aluminum Intensive Vehicle (AIV), nicknamed the Aluminum Cow. The Wisconsin team is striving for a combined, FTP cycle gasoline-equivalent fuel economy of 21.3 km/L (50 mpg) and Ultra Low Emissions Vehicle (ULEV) federal emissions levels while maintaining the full passenger/cargo room, appearance, and feel of a full-size car. To reach these goals, Wisconsin has concentrated on reducing the overall vehicle weight. In addition to customizing the drivetrain, the team has developed a vehicle control strategy that both aims to achieve these goals and also allows for the completion of a reliable hybrid in a short period of time.

Large-scale flows in internal combustion engines directly affect combustion duration and emissions production. These benefits are significant given increasingly stringent emissions and fuel economy requirements. Recent efforts by engine manufacturers to improve in-cylinder flows have focused on the design of specially shaped intake ports. Utility engine manufacturers are limited to simple intake port geometries to reduce the complexity of casting and cost of manufacturing. These constraints create unique flow physics in the engine cylinder in comparison to automotive engines. An experimental study of intake-generated flows was conducted in a four-stroke spark-ignition utility engine. Steady flow and in-cylinder flow measurements were made using three simple intake port geometries at three port orientations. Steady flow measurements were performed to characterize the swirl and tumble-generating capability of the intake ports.

The University of Wisconsin - Madison FutureCar Team has designed and built a lightweight, charge sustaining, parallel hybrid-electric vehicle for entry into the 1999 FutureCar Challenge. The base vehicle is a 1994 Mercury Sable Aluminum Intensive Vehicle (AIV), nicknamed the “Aluminum Cow,” weighing 1275 kg. The vehicle utilizes a high efficiency, Ford 1.8 liter, turbo-charged, direct-injection compression ignition engine. The goal is to achieve a combined FTP cycle fuel economy of 23.9 km/L (56 mpg) with California ULEV emissions levels while maintaining the full passenger/cargo room, appearance, and feel of a full-size car. Strategies to reduce the overall vehicle weight are discussed in detail. Dynamometer and experimental testing is used to verify performance gains.

A fuel film model has been developed and implemented into the KIVA-II code to help account for fuel distribution during combustion in diesel engines. Spray-wall interaction and spray-film interaction are also incorporated into the model. The model simulates thin fuel film flow on solid surfaces of arbitrary configuration. This is achieved by solving the continuity and momentum equations for the two dimensional film that flows over a three dimensional surface. The major physical effects considered in the model include mass and momentum contributions to the film due to spray drop impingement, splashing effects, various shear forces, piston acceleration, and dynamic pressure effects. In order to adequately represent the drop interaction process, impingement regimes and post-impingement behavior have been modeled using experimental data and mass, momentum and energy conservation constraints. The regimes modeled for spray-film interaction are stick, rebound, spread, and splash.

The fuel film thickness resulting from diesel fuel spray impingement was measured in a chamber at conditions representative of early injection timings used for low temperature diesel combustion. The adhered fuel volume and the radial distribution of the film thickness are presented. Fuel was injected normal to the impingement surface at ambient temperatures of 353 K, 426 K and 500 K, with densities of 10 kg/m3 and 25 kg/m3. Two injectors, with nozzle diameters of 100 μm and 120 μm, were investigated. The results show that the fuel film volume was strongly affected by the ambient temperature, but was minimally affected by the ambient density. The peak fuel film thickness and the film radius were found to increase with decreased temperature. The fuel film was found to be circular in shape, with an inner region of nearly constant thickness. The major difference observed with temperature was a decrease in the radial extent of the film.

Fuel film temperature and thickness were measured on the piston crown of a DISI engine under both motored and fired conditions using the fiber-based laser-induced fluorescence method wherein a single fiber delivers the excitation light and collects the fluorescence. The fibers were installed in the piston crown of a Bowditch-type optical engine and exited via the mirror passage. The fuel used for the fuel film temperature measurement was a 2×10-6 M solution of BTBP in isooctane. The ratio of the fluorescence intensity at 515 to that at 532 nm was found to be directly, but not linearly, related to temperature when excited at 488 nm. Effects related to the solvent, solution aging and bleaching were investigated. The measured fuel film temperature was found to closely follow the piston crown metal temperature, which was measured with a thermocouple.

Automatic manufacturability analysis of injection moldings, sheet metal castings, stampings, forgings, etc., using knowledge-based heuristics depends on shape features, which are abstractions of the three dimensional (3D) geometric model of the parts. Conventional CAD systems do not explicitly contain shape feature information, therefore such information needs to be extracted from them. So far, extraction of shape features has been restricted to models with simple geometric shapes such as planar, cylindrical or conical shapes. Extending shape feature extraction to non-linear geometric models will allow Design For Manufacturability (DFM) analysis of non-linear models. This paper presents an approach to extract features from non-linear geometric models. The approach is based on abstract geometric entities called C-loops. The formation of a C-loop depends on a geometric entity called a silhouette. The C-loops are derived from the silhouette boundaries of an object.

Lithium-ion and Lithium polymer batteries are fast becoming ubiquitous in high-discharge rate applications for military and non-military systems. Applications such as small aerial vehicles and energy transfer systems can often function at C-rates greater than 1. To maximize system endurance and battery health, there is a need for models capable of precisely estimating the battery state-of-charge (SoC) under all temperature and loading conditions. However, the ability to perform state estimation consistently and accurately to within 1% error has remained unsolved. Doing so can offer enhanced endurance, safety, reliability, and planning, and additionally, simplify energy management. Therefore, the work presented in this paper aims to study and develop experimentally validated mathematical models capable of high-accuracy battery SoC estimation.

An experimental study was performed to investigate the effect of fuel composition on combustion, gaseous emissions, and detailed chemical composition and size distributions of diesel particulate matter (PM) in a modern heavy-duty diesel engine with the use of the enhanced full-dilution tunnel system of the Engine Research Center (ERC) of the UW-Madison. Detailed description of this system can be found in our previous reports [1,2]. The experiments were carried out on a single-cylinder 2.3-liter D.I. diesel engine equipped with an electronically controlled unit injection system. The operating conditions of the engine followed the California Air Resources Board (CARB) 8-mode test cycle. The fuels used in the current study include baseline No. 2 diesel (Fuel A: sulfur content = 352 ppm), ultra low sulfur diesel (Fuel B: sulfur content = 14 ppm), and Fisher-Tropsch (F-T) diesel (sulfur content = 0 ppm).

Diesel exhaust particulate trap system is one of the most effective means to control diesel particulate emissions from diesel vehicles. In this paper, a recently developed diesel exhaust particulate trap system was described and experimentally studied. This system employed a wall-flow ceramic foam filter, which was made of silicon carbide or chromium oxide. And this system was equipped with a microwave heater for the purpose of filter regeneration. Engine dynamometer testing, vehicle bench testing and on-road evaluation of this system were conducted. The experiments studied on the filtration efficiency of this system, the effectiveness of filter regeneration, the power penalty of the vehicle, the ability of noise suppression of this system, and the durability of this particulate trap system. The experimental results showed that this diesel particulate trap system was effective, reliable, and durable.

Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR.

The objective of this study was to investigate the effects of fuel viscosity and the effects of nozzle inlet configuration on the characteristics of high injection pressure sprays. Three different viscosity fuels were used to reveal the effects of viscosity on the spray characteristics. The effects of nozzle inlet configuration on spray characteristics were studied using two mini-sac six-hole nozzles with different inlet configurations. A common rail injection system was used to introduce the spray at 90 MPa injection pressure into a constant volume chamber pressurized with argon gas. The information on high pressure transient sprays was captured by a high speed movie camera synchronized with a pulsed copper vapor laser. The images were analyzed to obtain the spray characteristics which include spray tip penetration, spray cone angle at two different regions, and overall spray Sauter Mean Diameter (SMD).